System

Abstract

A system is provided.SOLUTION: A system comprising: means for obtaining up-to-date news articles from news sources specific to the communications industry; means for summarizing the obtained news articles using a generative AI model; means for setting up virtual personas and simulating discussions using the generative AI model based on the summarized news articles; means for analyzing merits and demerits from the results of the discussion simulations; and means for delivering the summarized news articles and discussion results to user terminals.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] The communications industry is constantly changing, requiring people to learn new information quickly and effectively. However, it takes a lot of time and effort to read and analyze a huge number of news articles from multiple perspectives while also carrying out daily tasks. This makes it difficult to efficiently obtain important information and deepen one's understanding. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system that includes: means for acquiring the latest news articles from news sources specialized in the telecommunications industry; means for summarizing the acquired news articles using a generative AI model; means for setting virtual personas and simulating discussions using the generative AI model based on the summarized news articles; means for analyzing the advantages and disadvantages from the results of the discussion simulation; and means for delivering the summarized news articles and discussion results to a user's device. This invention makes it possible to efficiently summarize and analyze the latest information in the telecommunications industry and quickly compile opinions from multiple perspectives, thereby reducing learning time and improving work efficiency.

[0006] A "news article" is an article containing current information related to the communications industry.

[0007] A "generative AI model" is an artificial intelligence model that uses natural language processing technology to summarize news articles and simulate discussions.

[0008] A "summary" is a concise summary of the contents of a news article, extracting the important points and expressing them in a short form.

[0009] A "virtual persona" is a fictional character that represents a specific role or position and is used in hypothetical discussions.

[0010] "Discussion simulation" is a method of using a generative AI model to recreate an exchange of opinions about a news article between virtual personas.

[0011] "Merits" are advantages or beneficial aspects associated with a particular news article, extracted based on the results of the discussion simulation.

[0012] "Disadvantages" are shortcomings or negative aspects associated with a particular news article, extracted based on the results of the discussion simulation.

[0013] "Delivery" means sending summarized news articles and discussion results to the user's terminal. [Brief explanation of the drawings]

[0014] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0015] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0018] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0019] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0020] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0022] [First embodiment]

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0024] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0027] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0034] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0035] One embodiment of the present invention is described below. The system of the present invention efficiently summarizes and analyzes the latest news in the telecommunications industry, and by utilizing generative AI models at each step, it is possible to quickly aggregate information from multiple perspectives.

[0036] System Configuration and Operation

[0037] 1. Retrieving news articles

[0038] The server periodically retrieves the latest news articles via the API of a news site specializing in the telecommunications industry.

[0039] Specifically, the server sends a request to the news site's API endpoint and receives the latest article data related to the telecommunications industry in JSON format.

[0040] 2. News article summaries

[0041] The server inputs the retrieved news articles into a generative AI model to generate summaries.

[0042] First, the server extracts only the main text from the received article data and passes that text to a generative AI model to generate a summarized sentence.

[0043] 3. Argument Simulation

[0044] The server uses a generative AI model to set up virtual personas, each of which simulates a discussion based on a summary of a news article.

[0045] Specifically, virtual personas such as "AI specialist," "technical specialist," and "marketing specialist" are created, model inputs are prepared to generate opinions from each perspective, and the discussion is reproduced using a generative AI model.

[0046] 4. Analysis of advantages and disadvantages

[0047] Based on the results of the discussion simulation, the server extracts and lists the advantages and disadvantages related to the news article.

[0048] The server identifies advantages and disadvantages from the opinions of each generated persona and organizes them in a list format.

[0049] 5. Distribution of summaries and discussion results

[0050] The server delivers the final summarized news articles and discussion results to the user's terminal.

[0051] Specifically, by combining summaries and discussion results into a single data structure and sending it to the user's device, users can efficiently check the important points of the news and various opinions.

[0052] Specific examples

[0053] Let's say you retrieve the following article data from a news site:

[0054] json

[0055] {

[0056] "title": "Next-generation communication technology improves communication speeds",

[0057] "content": "The introduction of 5G, the next-generation communications technology, has significantly improved communication speeds. This..."

[0058] }

[0059] In response, the server does the following:

[0060] 1. Sending an API request:

[0061] The server uses the news site's API to retrieve the latest articles.

[0062] 2. Extract and summarize article text:

[0063] The server extracts the main text from the acquired article data and generates a summary using a generative AI model.

[0064] 3. Argument simulation:

[0065] The server sets up virtual personas and uses generative AI models to simulate discussions from each persona's perspective.

[0066] 4. Analysis of advantages and disadvantages:

[0067] The server extracts advantages and disadvantages based on the discussion results and compiles them into a list.

[0068] 5. Summary and discussion distribution:

[0069] The server compiles the summary and discussion results into a single data structure and sends it to the user's terminal.

[0070] In this way, the system of the present invention efficiently acquires, summarizes, analyzes, and presents the latest information in the telecommunications industry from multiple perspectives, allowing users to obtain important information in a short amount of time.

[0071] The processing flow will be explained below.

[0072] Step 1:

[0073] The server retrieves the latest news articles from the API of a news site specializing in the telecommunications industry. Specifically, the server periodically sends requests to the news site's API endpoint and receives article data for the corresponding category in JSON format. For example, the server retrieves data from "https: / / news.example.com / api / telecommunications industry" and saves the content.

[0074] Step 2:

[0075] The server extracts the text from the retrieved news articles. Specifically, it extracts the content of the article from the JSON data received by the server and saves it in text format. For example, it extracts the text as follows: articles = response.json(), and article_texts = [article['content'] for article in articles].

[0076] Step 3:

[0077] The server inputs the extracted text into a generative AI model to generate a summary. Specifically, it uses the summarization function of the generative AI model to condense long articles into a few paragraphs. For example, it generates a summary using summarizer = pipeline("summarization") and summaries = [summarizer(text, max_length=130, min_length=30, do_sample=False) for text in article_texts].

[0078] Step 4:

[0079] The server sets up virtual personas and simulates a debate for each persona based on a summary of a news article. Specifically, it sets up three personas: an "AI specialist," a "technical specialist," and a "marketing specialist," and generates debate sentences from each persona's perspective using a generative AI model. For example, input data is prepared as follows: debate_inputs = [f"{persona}: {summary}" for persona in personas for summary in summaries].

[0080] Step 5:

[0081] The server uses a generative AI model to extract and list advantages and disadvantages from the simulated debate. Specifically, it identifies the advantages and disadvantages from the opinions of each persona and organizes them in a list format. For example, the analysis is performed as follows: advantages = [result for result in debate_outputs if "advantages" in result] and disadvantages = [result for result in debate_outputs if "disadvantages" in result].

[0082] Step 6:

[0083] The server delivers summarized news articles and discussion results to the user's device. Specifically, the server combines the summaries and discussion results into a single data structure and sends it to the user's device. For example, the data is structured as summary_and_debate = {"summaries": summaries, "advantages": advantages, "disadvantages": disadvantages} and sent to the user's device as send_to_user_device(user_id, summary_and_debate). This allows the user to efficiently obtain important information and diverse opinions.

[0084] Example 1

[0085] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0086] In modern society, the telecommunications industry is changing rapidly, creating a need to quickly acquire the latest information and analyze it efficiently. However, processing huge amounts of information and analyzing it from various perspectives is not an easy task. With current methods, summarization and multifaceted analysis require time and effort, making it difficult for users to immediately grasp important information. For this reason, there is a need to develop a system that can automatically acquire, summarize, and analyze multifaceted information specific to the telecommunications industry and provide it quickly.

[0087] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0088] In this invention, the server includes means for acquiring the latest information from information sources specialized in the telecommunications industry, means for summarizing the acquired information using a generative AI model, means for setting up a virtual character and simulating a discussion using the generative AI model based on the summarized information, means for analyzing advantages and disadvantages from the results of the discussion simulation, and means for delivering the summarized information and discussion results to a user's device. This makes it possible to quickly acquire the latest information in the telecommunications industry and efficiently provide it to users through summaries and multifaceted analysis.

[0089] "Telecommunications industry" refers to industries and markets related to communications technology and services.

[0090] "Source" refers to any official or unofficial medium or platform that provides information on a particular subject.

[0091] A "generative AI model" refers to an algorithm or system that uses artificial intelligence technology to generate new information or content from data.

[0092] "Virtual character" refers to a fictional person or agent with a specific role or perspective.

[0093] "Simulating a discussion" refers to using a generative AI model to simulate a process in which virtual characters exchange opinions on a particular topic.

[0094] An "advantage" refers to an element or aspect that is beneficial in a particular situation or condition.

[0095] "Disadvantages" refer to elements or aspects that are unfavorable in a particular situation or condition.

[0096] "User Equipment" refers to any device or terminal used to receive and view information.

[0097] The present invention provides a system for efficiently acquiring, summarizing, and analyzing the latest information in the communications industry, and providing users with discussion results from multiple perspectives. Specific embodiments of the present invention will be described below.

[0098] Hardware and Software Configuration

[0099] The server is a data center server with high-performance processing power that processes API requests, analyzes data, and operates generative AI models. Specifically, it uses the following software and services:

[0100] API request processing: Web server software such as Apache or Nginx

[0101] Data format: JSON format parser

[0102] Generative AI models: OpenAI's GPT-3 and similar generative AI models

[0103] Database: A relational database such as MySQL or PostgreSQL

[0104] Program processing flow

[0105] Get news articles

[0106] The server obtains the latest information using the API of a source specialized in the telecommunications industry. The specific steps are as follows:

[0107] Sending API requests: The server periodically sends an HTTP request to the source's API endpoint to retrieve the latest information.

[0108] Receiving data: Receive data in JSON format from the API and save the data in a database on the server.

[0109] News article summaries

[0110] The server summarizes the acquired information using a generative AI model. The specific steps are as follows:

[0111] Text extraction: The server extracts the body text from the received JSON data.

[0112] Input to the generative AI model: The extracted text is passed to the generative AI model to generate a summary.

[0113] Example prompt sentence:

[0114] Summarize this article: The introduction of 5G, the next generation of communications technology, has significantly increased communication speeds. This...

[0115] Argument simulation

[0116] The server uses a generative AI model to set up virtual characters and simulate discussions based on the summarized information. The specific steps are as follows:

[0117] Setting virtual characters: The server sets up three virtual characters: "AI person," "technical person," and "marketing person."

[0118] Creating prompts for discussion generation: Generate prompts for each character and input them into the generative AI model.

[0119] Example prompt sentence:

[0120] AI Expert: Please comment on this article from an AI perspective. The introduction of 5G, the next generation communication technology, has significantly improved communication speeds.

[0121] Techie: What is the technological impact of this article? The introduction of 5G, the next generation communication technology, has significantly increased communication speeds.

[0122] Marketer: Based on this article, what marketing strategies can you think of? The introduction of 5G, the next generation communication technology, has significantly improved communication speeds.

[0123] Analysis of advantages and disadvantages

[0124] The server extracts advantages and disadvantages from the simulation results of the discussion. The specific steps are as follows:

[0125] Analysis of discussion results: The server analyzes the opinions of each generated character and identifies their advantages and disadvantages.

[0126] List creation: The extracted advantages and disadvantages are organized in a list format and saved on the server.

[0127] Summary and discussion results distribution

[0128] The server compiles the summarized information and the results of the discussion into a single data structure and delivers it to the user's terminal. The specific steps are as follows:

[0129] Data synthesis: Generate a data structure that summarizes the summary, discussion results, advantages and disadvantages.

[0130] Data transmission: Send data to the user's device via API or WebSocket, allowing the user to retrieve information efficiently.

[0131] According to the embodiment of the present invention, it is possible to quickly obtain the latest information in the communications industry and efficiently provide it to users through summaries and multifaceted analyses.

[0132] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0133] Step 1:

[0134] Get news articles

[0135] The server retrieves the latest news articles using the API of a telecommunications industry-specific information source. Specifically, the server periodically sends an HTTP request to the API endpoint and receives the latest news article data in JSON format. For example, it sends a request to the "GET / latest-news" endpoint and receives the following JSON response:

[0136] json

[0137] {

[0138] "title": "Next-generation communication technology improves communication speeds",

[0139] "content": "The introduction of 5G, the next-generation communications technology, has significantly improved communication speeds. This..."

[0140] }

[0141] Input: News site API endpoint

[0142] Output: News article data in JSON format

[0143] Step 2:

[0144] News article summaries

[0145] The server inputs the retrieved news article into a generative AI model to generate a summary. First, the server extracts the text from the received JSON data and passes that text to a generative AI model (e.g., OpenAI's GPT-3) to generate a summary. Specifically, the server inputs the following prompt sentence into the model:

[0146] prompt = "Summarize this article: The introduction of 5G, the next-generation communications technology, has dramatically increased communication speeds. This means..."

[0147] The generated summary is saved in the server for later processing.

[0148] Input: News article body text

[0149] Output: Summary text generated by the generative AI model

[0150] Step 3:

[0151] Argument simulation

[0152] The server uses a generative AI model to create virtual characters, each of which simulates a discussion based on a summary of a news article. First, the server creates virtual characters such as an "AI expert," an "engineer," and a "marketing expert." It then generates prompts for each character, such as:

[0153] AI Expert: Please comment on this article from an AI perspective. The introduction of 5G, the next generation communication technology, has significantly improved communication speeds.

[0154] Techie: What is the technological impact of this article? The introduction of 5G, the next generation communication technology, has significantly increased communication speeds.

[0155] Marketer: Based on this article, what marketing strategies can you think of? The introduction of 5G, the next generation communication technology, has significantly improved communication speeds.

[0156] The generated discussion content is stored on the server.

[0157] Input: Summary text and virtual character settings

[0158] Output: Discussion content of each character by the generative AI model

[0159] Step 4:

[0160] Analysis of advantages and disadvantages

[0161] The server extracts advantages and disadvantages based on the results of the simulated discussion. It analyzes the opinions of the generated virtual characters, identifies advantages and disadvantages from each point of view, and compiles them into a list. For example, it creates a list like this:

[0162] python

[0163] pros_and_cons = {

[0164] "Advantages": ["High speed", "New business opportunities"],

[0165] Disadvantages: High cost, infrastructure burden

[0166] }

[0167] This list is stored on the server.

[0168] Input: Discussion content of each character

[0169] Output: A list of advantages and disadvantages

[0170] Step 5:

[0171] Summary and discussion results distribution

[0172] The server compiles the summarized news articles and the results of the discussion into a single data structure and delivers it to the user's device. The data structure looks like this:

[0173] json

[0174] {

[0175] "summary": "The introduction of 5G, the next-generation communication technology, has significantly improved communication speeds.",

[0176] "pros_and_cons": {

[0177] "Advantages": ["High speed", "New business opportunities"],

[0178] Disadvantages: High cost, infrastructure burden

[0179] },

[0180] "discussion": {

[0181] "AI Personnel": "With improved communication speeds, it is highly likely that the speed at which AI analyzes data will also improve.",

[0182] "Technical Staff": "We expect new technology to improve stability.",

[0183] "Marketer": "High-speed communications will enable us to bring new services to market."

[0184] }

[0185] }

[0186] This data is sent to the user's device via API or WebSocket, allowing the user to access the information efficiently.

[0187] Input: Summary, discussion results, list of advantages and disadvantages

[0188] Output: Sending the integrated data to the user's terminal

[0189] (Application example 1)

[0190] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0191] Although systems exist that efficiently summarize the latest news in the telecommunications industry and enable discussion from multiple perspectives, there is a lack of means for users to quickly and visually understand the information. In particular, there is a need to provide visualized information using mobile information terminals and video display devices so that users can intuitively understand important information. This is expected to improve the efficiency of decision-making.

[0192] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0193] In this invention, the server includes means for acquiring the latest news articles from news sources specialized in the communications industry, means for summarizing the acquired news articles using a generative AI model, means for setting a virtual persona and simulating a discussion based on the summarized news articles using the generative AI model, means for analyzing the advantages and disadvantages from the results of the discussion simulation, means for delivering the summarized news articles and discussion results to a user's terminal, and means for visualizing the summaries and discussion results on a mobile information terminal or video display device used by the user, thereby enabling the user to quickly and intuitively understand important information.

[0194] A "news source specializing in the telecommunications industry" is an information provider that specializes in telecommunications technology, infrastructure, services, and related information.

[0195] A "breaking news story" is a story that contains timely, new information relevant to the communications industry.

[0196] A "generative AI model" is an artificial intelligence model that uses natural language processing to summarize and generate text data.

[0197] A "summary" is a shortened version of the original text that extracts the most important information.

[0198] A "virtual persona" is a character that is set up as a virtual being with a different perspective or role.

[0199] "Simulation" means recreating the process of actual discussion or exchange of opinions in a virtual environment.

[0200] "Advantages and disadvantages" refers to the advantages and disadvantages of a certain event or option.

[0201] A "mobile information terminal" refers to a portable information processing device such as a smartphone or tablet.

[0202] The term "video display device" refers to a device for displaying video, and includes, for example, a head-mounted display.

[0203] "Visualization" means representing information visually using shapes, graphs, text, etc.

[0204] "User terminal" refers to the device that the user ultimately uses to view information, and examples include smartphones and computers.

[0205] In this embodiment, technologies such as a server, a mobile information terminal, a video display device, and a generative AI model are used to realize efficient summaries of news articles specific to the telecommunications industry and discussion simulations from multiple perspectives.

[0206] System basic configuration and operation

[0207] Program Overview

[0208] The system retrieves the latest news articles from the telecommunications industry, uses a generative AI model to summarize and simulate discussions, and then provides the results to users.

[0209] Hardware and software used

[0210] Hardware: Mobile information terminals (smartphones and tablets), video display devices (head-mounted displays, etc.)

[0211] Software: Python (Flask framework), generative AI model (OpenAI GPT-4), news site API

[0212] Data processing and calculation

[0213] The server retrieves the latest news articles from the news site's API and receives the data in JSON format. Next, it uses a generative AI model to summarize the article text and simulates a discussion using virtual personas. Finally, it delivers the summary and discussion results to the user's device and visualizes them on the device.

[0214] Specific examples

[0215] For example, suppose you retrieve the following article data from a news site:

[0216] The introduction of 5G, the next-generation communications technology, has significantly improved communication speeds. This has...

[0217] In this case, the server extracts the body text from the article data and inputs the following prompt sentences into the generative AI model:

[0218] Summarize this article: The introduction of 5G, the next generation of communications technology, has significantly increased communication speeds. This...

[0219] The generative AI model generates a summary based on this prompt and then simulates the discussion from the perspective of virtual personas (e.g., "AI expert," "technical person," "marketing person"), analyzing the advantages and disadvantages of the simulated discussion and summarizing the results.

[0220] Summary and discussion visualization

[0221] The server delivers the summarized articles and discussion results to mobile information terminals and video display devices, where they are visualized, allowing users to efficiently understand the latest trends in the communications industry.

[0222] Thus, this invention provides a system that allows users to efficiently process and utilize information by acquiring data from specific news sources, summarizing using a generative AI model, simulating discussions using virtual personas, and visualizing the results.

[0223] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0224] Step 1:

[0225] The server retrieves the latest news articles from the API of a news source that specializes in the telecommunications industry. It sends a request to the news site's API endpoint and receives the latest article data in JSON format. The input is the API request from the server, and the output is the news article data in JSON format.

[0226] Step 2:

[0227] The server extracts the body text from the JSON data of the retrieved news article. Specifically, it extracts the value corresponding to the "content" key from the JSON data as text. The input is the JSON data of the news article, and the output is the text of the article body.

[0228] Step 3:

[0229] The server passes the extracted article text to a generative AI model to generate a summary. First, a prompt is created and input into the generative AI model. The generative AI model analyzes the text data and outputs a summarized sentence. The input is the article text and the prompt, and the output is the summarized article text.

[0230] Step 4:

[0231] The server uses the summarized text to simulate a discussion between virtual personas. It sets up virtual personas (e.g., "AI expert," "technical person," and "marketing person"), prepares prompts to generate discussions from each persona's perspective, and inputs these into the generative AI model. The model generates opinions from each persona's perspective. The inputs are the summary text and the prompts from the virtual personas, and the output is the discussion text generated for each persona.

[0232] Step 5:

[0233] The server extracts advantages and disadvantages from the generated argument text. It analyzes the opinions expressed in the argument and organizes the advantages and disadvantages in a list format. The input is the argument text, and the output is a list of advantages and disadvantages.

[0234] Step 6:

[0235] The server combines the summarized news article and the results of the discussion (a list of advantages and disadvantages) into a single data structure. Finally, it converts the data into a format that can be delivered to the user's device. The input is the summary text and the list of discussion results, and the output is the integrated data for the user's device.

[0236] Step 7:

[0237] The user's terminal visualizes the data received from the server. Specifically, the summary and discussion results are displayed on a mobile information terminal or video display device, and presented in a format that is intuitively easy for the user to understand. The input is the integrated data from the server, and the output is the visualized information.

[0238] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0239] The present invention is described below in detail in terms of an embodiment. The system includes an emotion engine that summarizes and analyzes news articles specific to the telecommunications industry, recognizes a user's emotions, and customizes the information accordingly. This allows users to efficiently obtain important information in a short amount of time, and the information is optimized to fit the user's emotional state.

[0240] System Configuration and Operation

[0241] 1. Retrieving news articles

[0242] The server retrieves the latest news articles from the API of a news site specializing in the telecommunications industry. Specifically, the server periodically sends requests to the news site's API endpoint and receives telecommunications industry-related article data in JSON format. For example, the server retrieves data from "https: / / news.example.com / api / telecommunications industry" and saves the content.

[0243] 2. News article summaries

[0244] The server extracts the text from the retrieved news articles. Specifically, it extracts the article content from the JSON data received by the server and saves it in text format. The extracted text is input into a generative AI model to generate a summary. The generative AI model's summarization function is used to condense long articles into a few paragraphs.

[0245] 3. Argument Simulation

[0246] The server uses a generative AI model to set up virtual personas, each of which simulates a discussion based on a summary of a news article. Specifically, the server sets up three personas: an "AI specialist," a "technical specialist," and a "marketing specialist," and uses the generative AI model to generate text for the discussion from each persona's perspective.

[0247] 4. Analysis of advantages and disadvantages

[0248] The server extracts and lists the advantages and disadvantages related to the news article based on the generated discussion results. It identifies advantages and disadvantages from the opinions of each persona and organizes them in a list format.

[0249] 5. User Emotion Recognition

[0250] The device is equipped with an emotion engine that recognizes emotions through the user's facial expressions, voice, or text input. Specifically, it uses the device's built-in camera, microphone, keyboard input, etc. to analyze the user's emotional state (e.g., joy, sadness, surprise, etc.) in real time.

[0251] 6. Emotional customization

[0252] The server customizes summarized news articles and discussion results based on the user's emotional data obtained from the emotion engine. Specifically, it provides information adapted to the user's emotional state, such as emphasizing the benefits if the user is expressing positive emotions, or explaining the disadvantages in detail if the user is expressing negative emotions.

[0253] 7. Distribution of summaries and discussion results

[0254] The server finally delivers the summarized news article and customized discussion results to the user's device. Specifically, by combining the summary and discussion results into a single data structure and sending it to the user's device, the user can efficiently obtain the key points of the news and various opinions.

[0255] Specific examples

[0256] Let's say you retrieve the following article data from a news site:

[0257] json

[0258] {

[0259] "title": "Next-generation communication technology improves communication speeds",

[0260] "content": "The introduction of 5G, the next-generation communications technology, has significantly improved communication speeds. This..."

[0261] }

[0262] In response, the server does the following:

[0263] 1. Sending an API request:

[0264] The server uses the news site's API to retrieve the latest articles.

[0265] 2. Extract and summarize article text:

[0266] The server extracts the main text from the acquired article data and generates a summary using a generative AI model.

[0267] 3. Argument simulation:

[0268] The server sets up virtual personas and uses generative AI models to simulate discussions from each persona's perspective.

[0269] 4. Analysis of advantages and disadvantages:

[0270] The server extracts advantages and disadvantages based on the discussion results and compiles them into a list.

[0271] 5. User Emotion Recognition:

[0272] The device uses the camera, microphone, and keyboard input to recognize the user's emotions.

[0273] 6. Emotional customization:

[0274] The server customizes how information is presented based on the user's emotional data.

[0275] 7. Summary and discussion distribution:

[0276] The server compiles the summaries and discussion results into a single data structure and sends it to the user's device, allowing the user to efficiently obtain important information and diverse opinions, while adapting the information to the user's emotional state.

[0277] In this way, the system of the present invention efficiently summarizes and analyzes the latest information in the telecommunications industry, and customizes it to the user's emotional state, allowing the user to obtain important information in a short amount of time.

[0278] The processing flow will be explained below.

[0279] Step 1:

[0280] The server retrieves the latest news articles from the API of a news site specializing in the telecommunications industry. Specifically, the server periodically sends requests to the news site's API endpoint and receives telecommunications industry-related article data in JSON format. For example, the server retrieves data from "https: / / news.example.com / api / telecommunications industry".

[0281] Step 2:

[0282] The server extracts the text from the retrieved news articles. Specifically, it extracts the content of the article from the JSON data received by the server and saves it in text format. For example, it extracts the text as follows: articles = response.json(), and article_texts = [article['content'] for article in articles].

[0283] Step 3:

[0284] The server inputs the extracted text into a generative AI model to generate a summary. Specifically, it uses the summarization function of the generative AI model to condense long articles into a few paragraphs. For example, it generates a summary using summarizer = pipeline("summarization") and summaries = [summarizer(text, max_length=130, min_length=30, do_sample=False) for text in article_texts].

[0285] Step 4:

[0286] The server sets up virtual personas and simulates a debate for each persona based on a summary of a news article. Specifically, it sets up three personas: an "AI specialist," a "technical specialist," and a "marketing specialist," and generates debate sentences from each persona's perspective using a generative AI model. For example, input data is prepared as follows: debate_inputs = [f"{persona}: {summary}" for persona in personas for summary in summaries].

[0287] Step 5:

[0288] The server uses a generative AI model to extract and list advantages and disadvantages from the simulated debate. Specifically, it identifies the advantages and disadvantages from the opinions of each persona and organizes them in a list format. For example, the analysis is performed as follows: advantages = [result for result in debate_outputs if "advantages" in result] and disadvantages = [result for result in debate_outputs if "disadvantages" in result].

[0289] Step 6:

[0290] The device is equipped with an emotion engine that recognizes emotions through the user's facial expressions, voice, or text input. Specifically, it analyzes the user's emotional state in real time using the device's built-in camera, microphone, keyboard input, etc. For example, it implements face recognition using a camera and voice emotion analysis using a microphone.

[0291] Step 7:

[0292] The server customizes summarized news articles and discussion results based on the user's emotional data obtained from the emotion engine. Specifically, it provides information adapted to the user's emotional state, such as emphasizing the benefits if the user is expressing positive emotions and detailing the disadvantages if the user is expressing negative emotions.

[0293] Step 8:

[0294] The server finally delivers the summarized news article and customized discussion results to the user's device. Specifically, the server combines the summary and discussion results into a single data structure and sends it to the user's device. For example, the data is structured as summary_and_debate = {"summaries": summaries, "advantages": advantages, "disadvantages": disadvantages} and sent to the user's device as send_to_user_device(user_id, summary_and_debate). As a result, the user can efficiently obtain important information and diverse opinions, and the information is adapted to the user's emotional state.

[0295] Example 2

[0296] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0297] In today's information society, it is important to efficiently obtain the latest news specific to a specific industry and summarize and analyze that information. However, it is not easy to extract the necessary information from the vast amount of information and provide it to users in an appropriate format. In addition, there is a lack of means to customize information based on user emotions, which poses a challenge in terms of how users can obtain the most appropriate information.

[0298] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring the latest information from information sources specialized in the telecommunications industry, means for summarizing the acquired information using a generative AI model, means for setting up a virtual person and simulating a discussion using the generative AI model based on the summarized information, means for analyzing the advantages and disadvantages from the results of the discussion simulation, means for recognizing the user's emotions, means for customizing the summarized information and discussion results according to the user's emotional state, and means for delivering the summarized information and discussion results to the user's terminal. This allows the user to efficiently acquire important information in a short amount of time, and the information can be optimized to suit the user's emotional state.

[0299] "Source" refers to a service or platform that provides up-to-date information or data on a particular industry or field.

[0300] A "generative AI model" refers to an artificial intelligence algorithm that uses machine learning techniques to summarize and analyze information from text and data.

[0301] "Virtual person" refers to the concept of creating a fictional character with a specific role or perspective, and generating discussions and opinions from that perspective.

[0302] "User emotion" refers to the psychological state or reaction that a user expresses through facial expression, voice, or text input.

[0303] "Customization" means the adjustment and optimization of information and service content to meet specific conditions and requirements.

[0304] "Terminal" refers to a device or hardware that allows a user to receive and view information, including, for example, a PC, smartphone, or tablet.

[0305] "API" stands for Application Programming Interface, and refers to an interface for exchanging information and functions between different software systems.

[0306] The present invention is best understood by describing an embodiment thereof as follows: The system of the present invention obtains up-to-date information from sources specialized in the telecommunications industry, efficiently summarizes and analyzes it, and provides customized information based on the user's emotional state.

[0307] Configuration and Operation

[0308] The server periodically obtains the latest information using the API of a source specialized in the telecommunications industry. Specifically, the server sends an HTTP GET request to the "information provider API" and receives data in JSON format. The received data is then analyzed using a parser and the obtained information is stored in a database.

[0309] Next, the server uses a generative AI model to summarize the information it has obtained. The server extracts the content from the JSON data and inputs the following prompt to the generative AI model:

[0310] "Summarize the following sentence: The introduction of 5G, the next generation communications technology, has significantly improved communication speeds. This has..."

[0311] The generated summary text is again stored in the database.

[0312] The server then sets up virtual people (personas) and simulates a discussion from each person's perspective using the generative AI model. The virtual people are set as "engineer," "marketer," and "AI person," and the following prompts are input to the generative AI model:

[0313] "Please comment on this summary as a technical expert."

[0314] The generated comments are stored in a database for each persona.

[0315] The server then analyzes the generated discussion results, extracting and listing the advantages and disadvantages. This not only provides a summary of the news, but also organizes opinions from multiple perspectives, making the advantages and disadvantages clear.

[0316] The device uses a camera, microphone, and keyboard input to recognize the user's emotions. Specifically, the device uses a built-in camera to recognize facial expressions, a microphone to analyze voice, and keyboard input to analyze text, thereby analyzing the user's emotional state in real time.

[0317] The server customizes the summarized information and discussion results based on the emotional data sent from the device. If the user is expressing positive emotions, the server emphasizes the benefits, and if the user is expressing negative emotions, it explains the disadvantages in detail.

[0318] Finally, the server delivers the summarized information and customized discussion results to the user's device. The summary and discussion results are combined into a single data structure and sent to the device, allowing the user to efficiently obtain important information in a short time, and the information is optimized for the user's emotional state.

[0319] Specific examples

[0320] For example, if you retrieve the following article data from the API:

[0321] "The introduction of 5G, the next generation communications technology, has significantly increased communication speeds. This has led to the telecommunications industry..."

[0322] The server summarizes this and generates the following text:

[0323] "With the introduction of 5G, communication speeds have improved."

[0324] Next, generate the following simulation prompt as the "Technician":

[0325] "Please comment on this summary as a technical expert."

[0326] The generated comment is, "The introduction of 5G technology has made high-speed communication possible and dramatically improved data transfer speeds."

[0327] As a result, the system of the present invention efficiently summarizes and analyzes the latest information in the telecommunications industry and customizes it to the user's emotional state, allowing the user to obtain important information in a short amount of time.

[0328] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0329] Step 1: Get news articles

[0330] The server retrieves the latest news articles using the API of a source specialized in the telecommunications industry. Specifically, the server periodically sends HTTP GET requests to the API of the information provider and receives data in JSON format. The input for this process is the API endpoint URL, and the output is news article data in JSON format. After receiving the data, the server parses the JSON data using a parser, extracts the required article data, and stores it in a database.

[0331] Step 2: Summarize the news article

[0332] The server extracts the main text from the saved news article data and inputs it into the generative AI model to generate a summary. Specifically, it extracts the content field from the article data and sends it to the generative AI model as a prompt. An example of a prompt is "Please summarize the following sentence: With the introduction of next-generation communication technology 5G, communication speeds have improved significantly. As a result..." The input for this process is the extracted main text, and the output is the summarized text. The generated summary is then saved back into the database.

[0333] Step 3: Simulating the discussion

[0334] The server sets up virtual characters and uses a generative AI model to simulate a discussion in which each virtual character engages in a discussion based on a summary of a news article. Specifically, it sets up three virtual characters: an "engineer," a "marketer," and an "AI technician," and generates discussions from each of their perspectives using a generative AI model. The input is the summary text and the settings of each virtual character, and the output is discussion text generated from each virtual character's perspective. As an example, it uses the prompt sentence, "Please comment on this summary as an engineer." The generated discussion text is stored in a database.

[0335] Step 4: Analyze the pros and cons

[0336] The server extracts and lists the advantages and disadvantages based on the generated discussion results. Specifically, it analyzes the discussion text using natural language processing to extract positive and negative elements. The input is the saved discussion text, and the output is a list of advantages and disadvantages. The extracted elements are saved in a database as the analysis results.

[0337] Step 5: Recognizing User Emotions

[0338] The device uses a camera, microphone, and keyboard input to recognize the user's emotions in real time. Specifically, it uses a camera to recognize facial expressions, a microphone to perform voice analysis, and analyzes text entered from the keyboard to estimate the user's emotions. The input is the user's facial expressions, voice, and text input, and the output is recognized emotion data. The emotion data is sent from the device to a server.

[0339] Step 6: Emotional customization

[0340] The server customizes summarized news articles and discussion results based on the emotion data sent from the device. Specifically, if the user expresses positive emotion, it emphasizes the benefits, and if the user expresses negative emotion, it explains the disadvantages in detail. The input for this process is the user's emotion data, summarized articles, and discussion results, and the output is customized information. The customized information is adjusted and edited according to the user's emotion.

[0341] Step 7: Summary and distribution of discussion results

[0342] The server finally delivers the customized summary and discussion results to the user's device. Specifically, it combines the summary and discussion results into a single data structure and sends it to the user's device. The input is the customized information, and the output is the information delivered to the user's device. The user receives this and can view the key points and diverse opinions of the news in a customized format.

[0343] (Application example 2)

[0344] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0345] In modern society, information in the telecommunications industry is extremely important, and it is necessary to efficiently grasp rapidly changing news. However, due to the wide variety of information, it is difficult for users to quickly obtain the information they need and accurately understand it. Furthermore, if the news content does not match the user's emotions or interests, there is a problem that the information will be less receptive, making it difficult to provide effective information.

[0346] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0347] In this invention, the server includes: means for acquiring the latest news articles from a news data source specialized for the telecommunications industry; means for summarizing the acquired news articles using a generative AI model; means for setting virtual roles and simulating a discussion based on the summarized news articles using the generative AI model; means for customizing the summarized news articles and discussion results based on the emotional state of the user using a terminal equipped with an emotion engine that recognizes the user's emotions; and means for delivering the summarized news articles and discussion results to the user's terminal. This allows users to efficiently acquire important information in a short amount of time, and the information can be provided in a form adapted to the user's emotional state.

[0348] A "server" is a computer system that provides data and functions to clients over a network.

[0349] A "news data source" is a digital source that provides up-to-date information on a particular subject.

[0350] "API" stands for Application Programming Interface, a set of rules and tools for exchanging information and functionality between different software applications.

[0351] A "generative AI model" is an algorithm that uses artificial intelligence to generate text and data, specifically a model that performs natural language processing.

[0352] A "summary" is a concise summary of original data or information.

[0353] A "virtual role" is a simulated character or persona with a particular perspective or opinion, used in simulations and discussions.

[0354] An "emotion engine" is a software module for recognizing and analyzing a user's emotional state.

[0355] "User's terminal" refers to any device used by a user, specifically a smartphone, computer, tablet, etc.

[0356] "Customization" refers to tailoring or modifying information or services to a particular user or situation.

[0357] This invention describes a system that efficiently collects and summarizes news articles specific to the telecommunications industry, and customizes them to fit the user's emotional state.

[0358] 1. System Overview

[0359] This system works in conjunction with a server and user devices. The server retrieves news specific to the telecommunications industry and summarizes it using a generative AI model. It then sets up virtual roles to simulate discussions based on news articles and analyzes the results. The user devices use an emotion engine to recognize the user's emotions, and the server uses this data to customize summaries and discussion results. The information is then delivered to the user devices.

[0360] 2. Hardware and Software Used

[0361] Hardware: Server computers, user devices (smartphones, computers, tablets, etc.), cameras, microphones

[0362] software:

[0363] Server: Node.js / Express.js, MongoDB, Axios (for API requests)

[0364] Generative AI model: OpenAI GPT-4

[0365] Emotion recognition: Affectiva SDK, Microsoft Azure Emotion API

[0366] 3. Processing Flow

[0367] News article retrieval and summarization

[0368] The server periodically retrieves the latest news articles from telecommunications industry news data sources via API, which are then summarized using OpenAI GPT-4, a generative AI model.

[0369] Virtual role setting and discussion simulation

[0370] The server creates virtual roles (e.g., technical person, marketing person) and uses a generative AI model to simulate each role discussing a news article, analyzing the resulting pros and cons.

[0371] Emotion Recognition and Customization

[0372] The user's device uses a camera and microphone to recognize the user's emotional state in real time. The emotion engine analyzes the data and sends it to the server. The server then customizes summarized news articles and discussion results based on the emotional data, providing information in a format that best suits the user's emotional state.

[0373] Summary and discussion results distribution

[0374] Finally, customized summaries and discussion results are delivered to users' devices, allowing them to obtain information efficiently and emotionally adapted.

[0375] 4. Specific Examples

[0376] Some examples of articles retrieved from news sites include:

[0377] Title: "Next-generation communication technology improves communication speeds"

[0378] Abstract: "The introduction of 5G, the next-generation communications technology, has significantly increased communication speeds. This has improved communication efficiency and led to the emergence of a variety of new services."

[0379] Prompt Sentence Examples

[0380] News article summary prompt:

[0381] Summarize this news article text:

[0382] "The introduction of 5G, the next-generation communications technology, has significantly increased communication speeds. This has improved communication efficiency and led to the emergence of a variety of new services. 5G networks are expected to be widely applicable, from homes to factories and agriculture."

[0383] Emotion customization prompt:

[0384] Emphasize positive aspects for happy emotions:

[0385] This allows the user to efficiently obtain important information in a short amount of time, and the information can be provided in a form that is adapted to the user's emotional state.

[0386] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0387] Step 1:

[0388] The server sends a request to the API endpoint of the news data source to retrieve the latest news articles specific to the telecommunications industry. The input is the API endpoint URL, and the output is the news article data (in JSON format). Specifically, the server sends an HTTP GET request to the API of the specified news data source.

[0389] Step 2:

[0390] The server extracts the text from the acquired news article data and generates a summary using a generative AI model. The input is the news article data, and the output is the summarized article text. Specifically, the server extracts the text portion of the article from the JSON of the news article data and sends it to the GPT-4 model along with a prompt to generate a summary.

[0391] Step 3:

[0392] The server sets up virtual roles and simulates discussions based on news articles using a generative AI model. The input is a summarized article text, and the output is the content of the discussions held by the virtual roles. Specifically, the server sets up multiple virtual roles (e.g., technical staff, marketing staff) and sends discussion prompts for each role to the generative AI model to generate the content of the discussions.

[0393] Step 4:

[0394] The server analyzes the generated discussion content and extracts the advantages and disadvantages. The input is the discussion content, and the output is a list of advantages and disadvantages. Specifically, the server uses the generative AI model to analyze the discussion content and organize the identified advantages and disadvantages in list form.

[0395] Step 5:

[0396] The device recognizes the user's emotional state in real time using a camera, microphone, and keyboard input. The input is the user's facial expression, voice, and text input, and the output is the user's emotional data. Specifically, the device uses an emotion engine to analyze the user's input data and identify the user's emotional state.

[0397] Step 6:

[0398] The server customizes summarized news articles and discussion results based on the user's emotional data. The input is the summarized news article, the discussion content, and the user's emotional data, and the output is customized news articles and discussion results. Specifically, the server analyzes the user's emotional state and edits the information to highlight advantages for positive emotions and to explain disadvantages in detail for negative emotions.

[0399] Step 7:

[0400] The server delivers the customized summary and discussion results to the user's device. The input is the customized news article and discussion content, and the output is the information sent to the user's device. Specifically, the server compiles the edited information into a single data structure and sends it to the user's device.

[0401] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0402] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0403] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0404] [Second embodiment]

[0405] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0406] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0407] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0408] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0409] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0410] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0411] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0412] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0413] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0414] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0415] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0416] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0417] One embodiment of the present invention is described below. The system of the present invention efficiently summarizes and analyzes the latest news in the telecommunications industry, and by utilizing generative AI models at each step, it is possible to quickly aggregate information from multiple perspectives.

[0418] System Configuration and Operation

[0419] 1. Retrieving news articles

[0420] The server periodically retrieves the latest news articles via the API of a news site specializing in the telecommunications industry.

[0421] Specifically, the server sends a request to the news site's API endpoint and receives the latest article data related to the telecommunications industry in JSON format.

[0422] 2. News article summaries

[0423] The server inputs the retrieved news articles into a generative AI model to generate summaries.

[0424] First, the server extracts only the main text from the received article data and passes that text to a generative AI model to generate a summarized sentence.

[0425] 3. Argument Simulation

[0426] The server uses a generative AI model to set up virtual personas, each of which simulates a discussion based on a summary of a news article.

[0427] Specifically, virtual personas such as "AI specialist," "technical specialist," and "marketing specialist" are created, model inputs are prepared to generate opinions from each perspective, and the discussion is reproduced using a generative AI model.

[0428] 4. Analysis of advantages and disadvantages

[0429] Based on the results of the discussion simulation, the server extracts and lists the advantages and disadvantages related to the news article.

[0430] The server identifies advantages and disadvantages from the opinions of each generated persona and organizes them in a list format.

[0431] 5. Distribution of summaries and discussion results

[0432] The server delivers the final summarized news articles and discussion results to the user's terminal.

[0433] Specifically, by combining summaries and discussion results into a single data structure and sending it to the user's device, users can efficiently check the important points of the news and various opinions.

[0434] Specific examples

[0435] Let's say you retrieve the following article data from a news site:

[0436] json

[0437] {

[0438] "title": "Next-generation communication technology improves communication speeds",

[0439] "content": "The introduction of 5G, the next-generation communications technology, has significantly improved communication speeds. This..."

[0440] }

[0441] In response, the server does the following:

[0442] 1. Sending an API request:

[0443] The server uses the news site's API to retrieve the latest articles.

[0444] 2. Extract and summarize article text:

[0445] The server extracts the main text from the acquired article data and generates a summary using a generative AI model.

[0446] 3. Argument simulation:

[0447] The server sets up virtual personas and uses generative AI models to simulate discussions from each persona's perspective.

[0448] 4. Analysis of advantages and disadvantages:

[0449] The server extracts advantages and disadvantages based on the discussion results and compiles them into a list.

[0450] 5. Summary and discussion distribution:

[0451] The server compiles the summary and discussion results into a single data structure and sends it to the user's terminal.

[0452] In this way, the system of the present invention efficiently acquires, summarizes, analyzes, and presents the latest information in the telecommunications industry from multiple perspectives, allowing users to obtain important information in a short amount of time.

[0453] The processing flow will be explained below.

[0454] Step 1:

[0455] The server retrieves the latest news articles from the API of a news site specializing in the telecommunications industry. Specifically, the server periodically sends requests to the news site's API endpoint and receives article data for the corresponding category in JSON format. For example, the server retrieves data from "https: / / news.example.com / api / telecommunications industry" and saves the content.

[0456] Step 2:

[0457] The server extracts the text from the retrieved news articles. Specifically, it extracts the content of the article from the JSON data received by the server and saves it in text format. For example, it extracts the text as follows: articles = response.json(), and article_texts = [article['content'] for article in articles].

[0458] Step 3:

[0459] The server inputs the extracted text into a generative AI model to generate a summary. Specifically, it uses the summarization function of the generative AI model to condense long articles into a few paragraphs. For example, it generates a summary using summarizer = pipeline("summarization") and summaries = [summarizer(text, max_length=130, min_length=30, do_sample=False) for text in article_texts].

[0460] Step 4:

[0461] The server sets up virtual personas and simulates a debate for each persona based on a summary of a news article. Specifically, it sets up three personas: an "AI specialist," a "technical specialist," and a "marketing specialist," and generates debate sentences from each persona's perspective using a generative AI model. For example, input data is prepared as follows: debate_inputs = [f"{persona}: {summary}" for persona in personas for summary in summaries].

[0462] Step 5:

[0463] The server uses a generative AI model to extract and list advantages and disadvantages from the simulated debate. Specifically, it identifies the advantages and disadvantages from the opinions of each persona and organizes them in a list format. For example, the analysis is performed as follows: advantages = [result for result in debate_outputs if "advantages" in result] and disadvantages = [result for result in debate_outputs if "disadvantages" in result].

[0464] Step 6:

[0465] The server delivers summarized news articles and discussion results to the user's device. Specifically, the server combines the summaries and discussion results into a single data structure and sends it to the user's device. For example, the data is structured as summary_and_debate = {"summaries": summaries, "advantages": advantages, "disadvantages": disadvantages} and sent to the user's device as send_to_user_device(user_id, summary_and_debate). This allows the user to efficiently obtain important information and diverse opinions.

[0466] Example 1

[0467] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0468] In modern society, the telecommunications industry is changing rapidly, creating a need to quickly acquire the latest information and analyze it efficiently. However, processing huge amounts of information and analyzing it from various perspectives is not an easy task. With current methods, summarization and multifaceted analysis require time and effort, making it difficult for users to immediately grasp important information. For this reason, there is a need to develop a system that can automatically acquire, summarize, and analyze multifaceted information specific to the telecommunications industry and provide it quickly.

[0469] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0470] In this invention, the server includes means for acquiring the latest information from information sources specialized in the telecommunications industry, means for summarizing the acquired information using a generative AI model, means for setting up a virtual character and simulating a discussion using the generative AI model based on the summarized information, means for analyzing advantages and disadvantages from the results of the discussion simulation, and means for delivering the summarized information and discussion results to a user's device. This makes it possible to quickly acquire the latest information in the telecommunications industry and efficiently provide it to users through summaries and multifaceted analysis.

[0471] "Telecommunications industry" refers to industries and markets related to communications technology and services.

[0472] "Source" refers to any official or unofficial medium or platform that provides information on a particular subject.

[0473] A "generative AI model" refers to an algorithm or system that uses artificial intelligence technology to generate new information or content from data.

[0474] "Virtual character" refers to a fictional person or agent with a specific role or perspective.

[0475] "Simulating a discussion" refers to using a generative AI model to simulate a process in which virtual characters exchange opinions on a particular topic.

[0476] An "advantage" refers to an element or aspect that is beneficial in a particular situation or condition.

[0477] "Disadvantages" refer to elements or aspects that are unfavorable in a particular situation or condition.

[0478] "User Equipment" refers to any device or terminal used to receive and view information.

[0479] The present invention provides a system for efficiently acquiring, summarizing, and analyzing the latest information in the communications industry, and providing users with discussion results from multiple perspectives. Specific embodiments of the present invention will be described below.

[0480] Hardware and Software Configuration

[0481] The server is a data center server with high-performance processing power that processes API requests, analyzes data, and operates generative AI models. Specifically, it uses the following software and services:

[0482] API request processing: Web server software such as Apache or Nginx

[0483] Data format: JSON format parser

[0484] Generative AI models: OpenAI's GPT-3 and similar generative AI models

[0485] Database: A relational database such as MySQL or PostgreSQL

[0486] Program processing flow

[0487] Get news articles

[0488] The server obtains the latest information using the API of a source specialized in the telecommunications industry. The specific steps are as follows:

[0489] Sending API requests: The server periodically sends an HTTP request to the source's API endpoint to retrieve the latest information.

[0490] Receiving data: Receive data in JSON format from the API and save the data in a database on the server.

[0491] News article summaries

[0492] The server summarizes the acquired information using a generative AI model. The specific steps are as follows:

[0493] Text extraction: The server extracts the body text from the received JSON data.

[0494] Input to the generative AI model: The extracted text is passed to the generative AI model to generate a summary.

[0495] Example prompt sentence:

[0496] Summarize this article: The introduction of 5G, the next generation of communications technology, has significantly increased communication speeds. This...

[0497] Argument simulation

[0498] The server uses a generative AI model to set up virtual characters and simulate discussions based on the summarized information. The specific steps are as follows:

[0499] Setting virtual characters: The server sets up three virtual characters: "AI person," "technical person," and "marketing person."

[0500] Creating prompts for discussion generation: Generate prompts for each character and input them into the generative AI model.

[0501] Example prompt sentence:

[0502] AI Expert: Please comment on this article from an AI perspective. The introduction of 5G, the next generation communication technology, has significantly improved communication speeds.

[0503] Techie: What is the technological impact of this article? The introduction of 5G, the next generation communication technology, has significantly increased communication speeds.

[0504] Marketer: Based on this article, what marketing strategies can you think of? The introduction of 5G, the next generation communication technology, has significantly improved communication speeds.

[0505] Analysis of advantages and disadvantages

[0506] The server extracts advantages and disadvantages from the simulation results of the discussion. The specific steps are as follows:

[0507] Analysis of discussion results: The server analyzes the opinions of each generated character and identifies their advantages and disadvantages.

[0508] List creation: The extracted advantages and disadvantages are organized in a list format and saved on the server.

[0509] Summary and discussion results distribution

[0510] The server compiles the summarized information and the results of the discussion into a single data structure and delivers it to the user's terminal. The specific steps are as follows:

[0511] Data synthesis: Generate a data structure that summarizes the summary, discussion results, advantages and disadvantages.

[0512] Data transmission: Send data to the user's device via API or WebSocket, allowing the user to retrieve information efficiently.

[0513] According to the embodiment of the present invention, it is possible to quickly obtain the latest information in the communications industry and efficiently provide it to users through summaries and multifaceted analyses.

[0514] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0515] Step 1:

[0516] Get news articles

[0517] The server retrieves the latest news articles using the API of a telecommunications industry-specific information source. Specifically, the server periodically sends an HTTP request to the API endpoint and receives the latest news article data in JSON format. For example, it sends a request to the "GET / latest-news" endpoint and receives the following JSON response:

[0518] json

[0519] {

[0520] "title": "Next-generation communication technology improves communication speeds",

[0521] "content": "The introduction of 5G, the next-generation communications technology, has significantly improved communication speeds. This..."

[0522] }

[0523] Input: News site API endpoint

[0524] Output: News article data in JSON format

[0525] Step 2:

[0526] News article summaries

[0527] The server inputs the retrieved news article into a generative AI model to generate a summary. First, the server extracts the text from the received JSON data and passes that text to a generative AI model (e.g., OpenAI's GPT-3) to generate a summary. Specifically, the server inputs the following prompt sentence into the model:

[0528] prompt = "Summarize this article: The introduction of 5G, the next-generation communications technology, has dramatically increased communication speeds. This means..."

[0529] The generated summary is saved in the server for later processing.

[0530] Input: News article body text

[0531] Output: Summary text generated by the generative AI model

[0532] Step 3:

[0533] Argument simulation

[0534] The server uses a generative AI model to create virtual characters, each of which simulates a discussion based on a summary of a news article. First, the server creates virtual characters such as an "AI expert," an "engineer," and a "marketing expert." It then generates prompts for each character, such as:

[0535] AI Expert: Please comment on this article from an AI perspective. The introduction of 5G, the next generation communication technology, has significantly improved communication speeds.

[0536] Techie: What is the technological impact of this article? The introduction of 5G, the next generation communication technology, has significantly increased communication speeds.

[0537] Marketer: Based on this article, what marketing strategies can you think of? The introduction of 5G, the next generation communication technology, has significantly improved communication speeds.

[0538] The generated discussion content is stored on the server.

[0539] Input: Summary text and virtual character settings

[0540] Output: Discussion content of each character by the generative AI model

[0541] Step 4:

[0542] Analysis of advantages and disadvantages

[0543] The server extracts advantages and disadvantages based on the results of the simulated discussion. It analyzes the opinions of the generated virtual characters, identifies advantages and disadvantages from each point of view, and compiles them into a list. For example, it creates a list like this:

[0544] python

[0545] pros_and_cons = {

[0546] "Advantages": ["High speed", "New business opportunities"],

[0547] Disadvantages: High cost, infrastructure burden

[0548] }

[0549] This list is stored on the server.

[0550] Input: Discussion content of each character

[0551] Output: A list of advantages and disadvantages

[0552] Step 5:

[0553] Summary and discussion results distribution

[0554] The server compiles the summarized news articles and the results of the discussion into a single data structure and delivers it to the user's device. The data structure looks like this:

[0555] json

[0556] {

[0557] "summary": "The introduction of 5G, the next-generation communication technology, has significantly improved communication speeds.",

[0558] "pros_and_cons": {

[0559] "Advantages": ["High speed", "New business opportunities"],

[0560] Disadvantages: High cost, infrastructure burden

[0561] },

[0562] "discussion": {

[0563] "AI Personnel": "With improved communication speeds, it is highly likely that the speed at which AI analyzes data will also improve.",

[0564] "Technical Staff": "We expect new technology to improve stability.",

[0565] "Marketer": "High-speed communications will enable us to bring new services to market."

[0566] }

[0567] }

[0568] This data is sent to the user's device via API or WebSocket, allowing the user to access the information efficiently.

[0569] Input: Summary, discussion results, list of advantages and disadvantages

[0570] Output: Sending the integrated data to the user's terminal

[0571] (Application example 1)

[0572] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0573] Although systems exist that efficiently summarize the latest news in the telecommunications industry and enable discussion from multiple perspectives, there is a lack of means for users to quickly and visually understand the information. In particular, there is a need to provide visualized information using mobile information terminals and video display devices so that users can intuitively understand important information. This is expected to improve the efficiency of decision-making.

[0574] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0575] In this invention, the server includes means for acquiring the latest news articles from news sources specialized in the communications industry, means for summarizing the acquired news articles using a generative AI model, means for setting a virtual persona and simulating a discussion based on the summarized news articles using the generative AI model, means for analyzing the advantages and disadvantages from the results of the discussion simulation, means for delivering the summarized news articles and discussion results to a user's terminal, and means for visualizing the summaries and discussion results on a mobile information terminal or video display device used by the user, thereby enabling the user to quickly and intuitively understand important information.

[0576] A "news source specializing in the telecommunications industry" is an information provider that specializes in telecommunications technology, infrastructure, services, and related information.

[0577] A "breaking news story" is a story that contains timely, new information relevant to the communications industry.

[0578] A "generative AI model" is an artificial intelligence model that uses natural language processing to summarize and generate text data.

[0579] A "summary" is a shortened version of the original text that extracts the most important information.

[0580] A "virtual persona" is a character that is set up as a virtual being with a different perspective or role.

[0581] "Simulation" means recreating the process of actual discussion or exchange of opinions in a virtual environment.

[0582] "Advantages and disadvantages" refers to the advantages and disadvantages of a certain event or option.

[0583] A "mobile information terminal" refers to a portable information processing device such as a smartphone or tablet.

[0584] The term "video display device" refers to a device for displaying video, and includes, for example, a head-mounted display.

[0585] "Visualization" means representing information visually using shapes, graphs, text, etc.

[0586] "User terminal" refers to the device that the user ultimately uses to view information, and examples include smartphones and computers.

[0587] In this embodiment, technologies such as a server, a mobile information terminal, a video display device, and a generative AI model are used to realize efficient summaries of news articles specific to the telecommunications industry and discussion simulations from multiple perspectives.

[0588] System basic configuration and operation

[0589] Program Overview

[0590] The system retrieves the latest news articles from the telecommunications industry, uses a generative AI model to summarize and simulate discussions, and then provides the results to users.

[0591] Hardware and software used

[0592] Hardware: Mobile information terminals (smartphones and tablets), video display devices (head-mounted displays, etc.)

[0593] Software: Python (Flask framework), generative AI model (OpenAI GPT-4), news site API

[0594] Data processing and calculation

[0595] The server retrieves the latest news articles from the news site's API and receives the data in JSON format. Next, it uses a generative AI model to summarize the article text and simulates a discussion using virtual personas. Finally, it delivers the summary and discussion results to the user's device and visualizes them on the device.

[0596] Specific examples

[0597] For example, suppose you retrieve the following article data from a news site:

[0598] The introduction of 5G, the next-generation communications technology, has significantly improved communication speeds. This has...

[0599] In this case, the server extracts the body text from the article data and inputs the following prompt sentences into the generative AI model:

[0600] Summarize this article: The introduction of 5G, the next generation of communications technology, has significantly increased communication speeds. This...

[0601] The generative AI model generates a summary based on this prompt and then simulates the discussion from the perspective of virtual personas (e.g., "AI expert," "technical person," "marketing person"), analyzing the advantages and disadvantages of the simulated discussion and summarizing the results.

[0602] Summary and discussion visualization

[0603] The server delivers the summarized articles and discussion results to mobile information terminals and video display devices, where they are visualized, allowing users to efficiently understand the latest trends in the communications industry.

[0604] Thus, this invention provides a system that allows users to efficiently process and utilize information by acquiring data from specific news sources, summarizing using a generative AI model, simulating discussions using virtual personas, and visualizing the results.

[0605] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0606] Step 1:

[0607] The server retrieves the latest news articles from the API of a news source that specializes in the telecommunications industry. It sends a request to the news site's API endpoint and receives the latest article data in JSON format. The input is the API request from the server, and the output is the news article data in JSON format.

[0608] Step 2:

[0609] The server extracts the body text from the JSON data of the retrieved news article. Specifically, it extracts the value corresponding to the "content" key from the JSON data as text. The input is the JSON data of the news article, and the output is the text of the article body.

[0610] Step 3:

[0611] The server passes the extracted article text to a generative AI model to generate a summary. First, a prompt is created and input into the generative AI model. The generative AI model analyzes the text data and outputs a summarized sentence. The input is the article text and the prompt, and the output is the summarized article text.

[0612] Step 4:

[0613] The server uses the summarized text to simulate a discussion between virtual personas. It sets up virtual personas (e.g., "AI expert," "technical person," and "marketing person"), prepares prompts to generate discussions from each persona's perspective, and inputs these into the generative AI model. The model generates opinions from each persona's perspective. The inputs are the summary text and the prompts from the virtual personas, and the output is the discussion text generated for each persona.

[0614] Step 5:

[0615] The server extracts advantages and disadvantages from the generated argument text. It analyzes the opinions expressed in the argument and organizes the advantages and disadvantages in a list format. The input is the argument text, and the output is a list of advantages and disadvantages.

[0616] Step 6:

[0617] The server combines the summarized news article and the results of the discussion (a list of advantages and disadvantages) into a single data structure. Finally, it converts the data into a format that can be delivered to the user's device. The input is the summary text and the list of discussion results, and the output is the integrated data for the user's device.

[0618] Step 7:

[0619] The user's terminal visualizes the data received from the server. Specifically, the summary and discussion results are displayed on a mobile information terminal or video display device, and presented in a format that is intuitively easy for the user to understand. The input is the integrated data from the server, and the output is the visualized information.

[0620] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0621] The present invention is described below in detail in terms of an embodiment. The system includes an emotion engine that summarizes and analyzes news articles specific to the telecommunications industry, recognizes a user's emotions, and customizes the information accordingly. This allows users to efficiently obtain important information in a short amount of time, and the information is optimized to fit the user's emotional state.

[0622] System Configuration and Operation

[0623] 1. Retrieving news articles

[0624] The server retrieves the latest news articles from the API of a news site specializing in the telecommunications industry. Specifically, the server periodically sends requests to the news site's API endpoint and receives telecommunications industry-related article data in JSON format. For example, the server retrieves data from "https: / / news.example.com / api / telecommunications industry" and saves the content.

[0625] 2. News article summaries

[0626] The server extracts the text from the retrieved news articles. Specifically, it extracts the article content from the JSON data received by the server and saves it in text format. The extracted text is input into a generative AI model to generate a summary. The generative AI model's summarization function is used to condense long articles into a few paragraphs.

[0627] 3. Argument Simulation

[0628] The server uses a generative AI model to set up virtual personas, each of which simulates a discussion based on a summary of a news article. Specifically, the server sets up three personas: an "AI specialist," a "technical specialist," and a "marketing specialist," and uses the generative AI model to generate text for the discussion from each persona's perspective.

[0629] 4. Analysis of advantages and disadvantages

[0630] The server extracts and lists the advantages and disadvantages related to the news article based on the generated discussion results. It identifies advantages and disadvantages from the opinions of each persona and organizes them in a list format.

[0631] 5. User Emotion Recognition

[0632] The device is equipped with an emotion engine that recognizes emotions through the user's facial expressions, voice, or text input. Specifically, it uses the device's built-in camera, microphone, keyboard input, etc. to analyze the user's emotional state (e.g., joy, sadness, surprise, etc.) in real time.

[0633] 6. Emotional customization

[0634] The server customizes summarized news articles and discussion results based on the user's emotional data obtained from the emotion engine. Specifically, it provides information adapted to the user's emotional state, such as emphasizing the benefits if the user is expressing positive emotions, or explaining the disadvantages in detail if the user is expressing negative emotions.

[0635] 7. Distribution of summaries and discussion results

[0636] The server finally delivers the summarized news article and customized discussion results to the user's device. Specifically, by combining the summary and discussion results into a single data structure and sending it to the user's device, the user can efficiently obtain the key points of the news and various opinions.

[0637] Specific examples

[0638] Let's say you retrieve the following article data from a news site:

[0639] json

[0640] {

[0641] "title": "Next-generation communication technology improves communication speeds",

[0642] "content": "The introduction of 5G, the next-generation communications technology, has significantly improved communication speeds. This..."

[0643] }

[0644] In response, the server does the following:

[0645] 1. Sending an API request:

[0646] The server uses the news site's API to retrieve the latest articles.

[0647] 2. Extract and summarize article text:

[0648] The server extracts the main text from the acquired article data and generates a summary using a generative AI model.

[0649] 3. Argument simulation:

[0650] The server sets up virtual personas and uses generative AI models to simulate discussions from each persona's perspective.

[0651] 4. Analysis of advantages and disadvantages:

[0652] The server extracts advantages and disadvantages based on the discussion results and compiles them into a list.

[0653] 5. User Emotion Recognition:

[0654] The device uses the camera, microphone, and keyboard input to recognize the user's emotions.

[0655] 6. Emotional customization:

[0656] The server customizes how information is presented based on the user's emotional data.

[0657] 7. Summary and discussion distribution:

[0658] The server compiles the summaries and discussion results into a single data structure and sends it to the user's device, allowing the user to efficiently obtain important information and diverse opinions, while adapting the information to the user's emotional state.

[0659] In this way, the system of the present invention efficiently summarizes and analyzes the latest information in the telecommunications industry, and customizes it to the user's emotional state, allowing the user to obtain important information in a short amount of time.

[0660] The processing flow will be explained below.

[0661] Step 1:

[0662] The server retrieves the latest news articles from the API of a news site specializing in the telecommunications industry. Specifically, the server periodically sends requests to the news site's API endpoint and receives telecommunications industry-related article data in JSON format. For example, the server retrieves data from "https: / / news.example.com / api / telecommunications industry".

[0663] Step 2:

[0664] The server extracts the text from the retrieved news articles. Specifically, it extracts the content of the article from the JSON data received by the server and saves it in text format. For example, it extracts the text as follows: articles = response.json(), and article_texts = [article['content'] for article in articles].

[0665] Step 3:

[0666] The server inputs the extracted text into a generative AI model to generate a summary. Specifically, it uses the summarization function of the generative AI model to condense long articles into a few paragraphs. For example, it generates a summary using summarizer = pipeline("summarization") and summaries = [summarizer(text, max_length=130, min_length=30, do_sample=False) for text in article_texts].

[0667] Step 4:

[0668] The server sets up virtual personas and simulates a debate for each persona based on a summary of a news article. Specifically, it sets up three personas: an "AI specialist," a "technical specialist," and a "marketing specialist," and generates debate sentences from each persona's perspective using a generative AI model. For example, input data is prepared as follows: debate_inputs = [f"{persona}: {summary}" for persona in personas for summary in summaries].

[0669] Step 5:

[0670] The server uses a generative AI model to extract and list advantages and disadvantages from the simulated debate. Specifically, it identifies the advantages and disadvantages from the opinions of each persona and organizes them in a list format. For example, the analysis is performed as follows: advantages = [result for result in debate_outputs if "advantages" in result] and disadvantages = [result for result in debate_outputs if "disadvantages" in result].

[0671] Step 6:

[0672] The device is equipped with an emotion engine that recognizes emotions through the user's facial expressions, voice, or text input. Specifically, it analyzes the user's emotional state in real time using the device's built-in camera, microphone, keyboard input, etc. For example, it implements face recognition using a camera and voice emotion analysis using a microphone.

[0673] Step 7:

[0674] The server customizes summarized news articles and discussion results based on the user's emotional data obtained from the emotion engine. Specifically, it provides information adapted to the user's emotional state, such as emphasizing the benefits if the user is expressing positive emotions and detailing the disadvantages if the user is expressing negative emotions.

[0675] Step 8:

[0676] The server finally delivers the summarized news article and customized discussion results to the user's device. Specifically, the server combines the summary and discussion results into a single data structure and sends it to the user's device. For example, the data is structured as summary_and_debate = {"summaries": summaries, "advantages": advantages, "disadvantages": disadvantages} and sent to the user's device as send_to_user_device(user_id, summary_and_debate). As a result, the user can efficiently obtain important information and diverse opinions, and the information is adapted to the user's emotional state.

[0677] Example 2

[0678] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0679] In today's information society, it is important to efficiently obtain the latest news specific to a specific industry and summarize and analyze that information. However, it is not easy to extract the necessary information from the vast amount of information and provide it to users in an appropriate format. In addition, there is a lack of means to customize information based on user emotions, which poses a challenge in terms of how users can obtain the most appropriate information.

[0680] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring the latest information from information sources specialized in the telecommunications industry, means for summarizing the acquired information using a generative AI model, means for setting up a virtual person and simulating a discussion using the generative AI model based on the summarized information, means for analyzing the advantages and disadvantages from the results of the discussion simulation, means for recognizing the user's emotions, means for customizing the summarized information and discussion results according to the user's emotional state, and means for delivering the summarized information and discussion results to the user's terminal. This allows the user to efficiently acquire important information in a short amount of time, and the information can be optimized to suit the user's emotional state.

[0681] "Source" refers to a service or platform that provides up-to-date information or data on a particular industry or field.

[0682] A "generative AI model" refers to an artificial intelligence algorithm that uses machine learning techniques to summarize and analyze information from text and data.

[0683] "Virtual person" refers to the concept of creating a fictional character with a specific role or perspective, and generating discussions and opinions from that perspective.

[0684] "User emotion" refers to the psychological state or reaction that a user expresses through facial expression, voice, or text input.

[0685] "Customization" means the adjustment and optimization of information and service content to meet specific conditions and requirements.

[0686] "Terminal" refers to a device or hardware that allows a user to receive and view information, including, for example, a PC, smartphone, or tablet.

[0687] "API" stands for Application Programming Interface, and refers to an interface for exchanging information and functions between different software systems.

[0688] The present invention is best understood by describing an embodiment thereof as follows: The system of the present invention obtains up-to-date information from sources specialized in the telecommunications industry, efficiently summarizes and analyzes it, and provides customized information based on the user's emotional state.

[0689] Configuration and Operation

[0690] The server periodically obtains the latest information using the API of a source specialized in the telecommunications industry. Specifically, the server sends an HTTP GET request to the "information provider API" and receives data in JSON format. The received data is then analyzed using a parser and the obtained information is stored in a database.

[0691] Next, the server uses a generative AI model to summarize the information it has obtained. The server extracts the content from the JSON data and inputs the following prompt to the generative AI model:

[0692] "Summarize the following sentence: The introduction of 5G, the next generation communications technology, has significantly improved communication speeds. This has..."

[0693] The generated summary text is again stored in the database.

[0694] The server then sets up virtual people (personas) and simulates a discussion from each person's perspective using the generative AI model. The virtual people are set as "engineer," "marketer," and "AI person," and the following prompts are input to the generative AI model:

[0695] "Please comment on this summary as a technical expert."

[0696] The generated comments are stored in a database for each persona.

[0697] The server then analyzes the generated discussion results, extracting and listing the advantages and disadvantages. This not only provides a summary of the news, but also organizes opinions from multiple perspectives, making the advantages and disadvantages clear.

[0698] The device uses a camera, microphone, and keyboard input to recognize the user's emotions. Specifically, the device uses a built-in camera to recognize facial expressions, a microphone to analyze voice, and keyboard input to analyze text, thereby analyzing the user's emotional state in real time.

[0699] The server customizes the summarized information and discussion results based on the emotional data sent from the device. If the user is expressing positive emotions, the server emphasizes the benefits, and if the user is expressing negative emotions, it explains the disadvantages in detail.

[0700] Finally, the server delivers the summarized information and customized discussion results to the user's device. The summary and discussion results are combined into a single data structure and sent to the device, allowing the user to efficiently obtain important information in a short time, and the information is optimized for the user's emotional state.

[0701] Specific examples

[0702] For example, if you retrieve the following article data from the API:

[0703] "The introduction of 5G, the next generation communications technology, has significantly increased communication speeds. This has led to the telecommunications industry..."

[0704] The server summarizes this and generates the following text:

[0705] "With the introduction of 5G, communication speeds have improved."

[0706] Next, generate the following simulation prompt as the "Technician":

[0707] "Please comment on this summary as a technical expert."

[0708] The generated comment is, "The introduction of 5G technology has made high-speed communication possible and dramatically improved data transfer speeds."

[0709] As a result, the system of the present invention efficiently summarizes and analyzes the latest information in the telecommunications industry and customizes it to the user's emotional state, allowing the user to obtain important information in a short amount of time.

[0710] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0711] Step 1: Get news articles

[0712] The server retrieves the latest news articles using the API of a source specialized in the telecommunications industry. Specifically, the server periodically sends HTTP GET requests to the API of the information provider and receives data in JSON format. The input for this process is the API endpoint URL, and the output is news article data in JSON format. After receiving the data, the server parses the JSON data using a parser, extracts the required article data, and stores it in a database.

[0713] Step 2: Summarize the news article

[0714] The server extracts the main text from the saved news article data and inputs it into the generative AI model to generate a summary. Specifically, it extracts the content field from the article data and sends it to the generative AI model as a prompt. An example of a prompt is "Please summarize the following sentence: With the introduction of next-generation communication technology 5G, communication speeds have improved significantly. As a result..." The input for this process is the extracted main text, and the output is the summarized text. The generated summary is then saved back into the database.

[0715] Step 3: Simulating the discussion

[0716] The server sets up virtual characters and uses a generative AI model to simulate a discussion in which each virtual character engages in a discussion based on a summary of a news article. Specifically, it sets up three virtual characters: an "engineer," a "marketer," and an "AI technician," and generates discussions from each of their perspectives using a generative AI model. The input is the summary text and the settings of each virtual character, and the output is discussion text generated from each virtual character's perspective. As an example, it uses the prompt sentence, "Please comment on this summary as an engineer." The generated discussion text is stored in a database.

[0717] Step 4: Analyze the pros and cons

[0718] The server extracts and lists the advantages and disadvantages based on the generated discussion results. Specifically, it analyzes the discussion text using natural language processing to extract positive and negative elements. The input is the saved discussion text, and the output is a list of advantages and disadvantages. The extracted elements are saved in a database as the analysis results.

[0719] Step 5: Recognizing User Emotions

[0720] The device uses a camera, microphone, and keyboard input to recognize the user's emotions in real time. Specifically, it uses a camera to recognize facial expressions, a microphone to perform voice analysis, and analyzes text entered from the keyboard to estimate the user's emotions. The input is the user's facial expressions, voice, and text input, and the output is recognized emotion data. The emotion data is sent from the device to a server.

[0721] Step 6: Emotional customization

[0722] The server customizes summarized news articles and discussion results based on the emotion data sent from the device. Specifically, if the user expresses positive emotion, it emphasizes the benefits, and if the user expresses negative emotion, it explains the disadvantages in detail. The input for this process is the user's emotion data, summarized articles, and discussion results, and the output is customized information. The customized information is adjusted and edited according to the user's emotion.

[0723] Step 7: Summary and distribution of discussion results

[0724] The server finally delivers the customized summary and discussion results to the user's device. Specifically, it combines the summary and discussion results into a single data structure and sends it to the user's device. The input is the customized information, and the output is the information delivered to the user's device. The user receives this and can view the key points and diverse opinions of the news in a customized format.

[0725] (Application example 2)

[0726] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0727] In modern society, information in the telecommunications industry is extremely important, and it is necessary to efficiently grasp rapidly changing news. However, due to the wide variety of information, it is difficult for users to quickly obtain the information they need and accurately understand it. Furthermore, if the news content does not match the user's emotions or interests, there is a problem that the information will be less receptive, making it difficult to provide effective information.

[0728] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0729] In this invention, the server includes: means for acquiring the latest news articles from a news data source specialized for the telecommunications industry; means for summarizing the acquired news articles using a generative AI model; means for setting virtual roles and simulating a discussion based on the summarized news articles using the generative AI model; means for customizing the summarized news articles and discussion results based on the emotional state of the user using a terminal equipped with an emotion engine that recognizes the user's emotions; and means for delivering the summarized news articles and discussion results to the user's terminal. This allows users to efficiently acquire important information in a short amount of time, and the information can be provided in a form adapted to the user's emotional state.

[0730] A "server" is a computer system that provides data and functions to clients over a network.

[0731] A "news data source" is a digital source that provides up-to-date information on a particular subject.

[0732] "API" stands for Application Programming Interface, a set of rules and tools for exchanging information and functionality between different software applications.

[0733] A "generative AI model" is an algorithm that uses artificial intelligence to generate text and data, specifically a model that performs natural language processing.

[0734] A "summary" is a concise summary of original data or information.

[0735] A "virtual role" is a simulated character or persona with a particular perspective or opinion, used in simulations and discussions.

[0736] An "emotion engine" is a software module for recognizing and analyzing a user's emotional state.

[0737] "User's terminal" refers to any device used by a user, specifically a smartphone, computer, tablet, etc.

[0738] "Customization" refers to tailoring or modifying information or services to a particular user or situation.

[0739] This invention describes a system that efficiently collects and summarizes news articles specific to the telecommunications industry, and customizes them to fit the user's emotional state.

[0740] 1. System Overview

[0741] This system works in conjunction with a server and user devices. The server retrieves news specific to the telecommunications industry and summarizes it using a generative AI model. It then sets up virtual roles to simulate discussions based on news articles and analyzes the results. The user devices use an emotion engine to recognize the user's emotions, and the server uses this data to customize summaries and discussion results. The information is then delivered to the user devices.

[0742] 2. Hardware and Software Used

[0743] Hardware: Server computers, user devices (smartphones, computers, tablets, etc.), cameras, microphones

[0744] software:

[0745] Server: Node.js / Express.js, MongoDB, Axios (for API requests)

[0746] Generative AI model: OpenAI GPT-4

[0747] Emotion recognition: Affectiva SDK, Microsoft Azure Emotion API

[0748] 3. Processing Flow

[0749] News article retrieval and summarization

[0750] The server periodically retrieves the latest news articles from telecommunications industry news data sources via API, which are then summarized using OpenAI GPT-4, a generative AI model.

[0751] Virtual role setting and discussion simulation

[0752] The server creates virtual roles (e.g., technical person, marketing person) and uses a generative AI model to simulate each role discussing a news article, analyzing the resulting pros and cons.

[0753] Emotion Recognition and Customization

[0754] The user's device uses a camera and microphone to recognize the user's emotional state in real time. The emotion engine analyzes the data and sends it to the server. The server then customizes summarized news articles and discussion results based on the emotional data, providing information in a format that best suits the user's emotional state.

[0755] Summary and discussion results distribution

[0756] Finally, customized summaries and discussion results are delivered to users' devices, allowing them to obtain information efficiently and emotionally adapted.

[0757] 4. Specific Examples

[0758] Some examples of articles retrieved from news sites include:

[0759] Title: "Next-generation communication technology improves communication speeds"

[0760] Abstract: "The introduction of 5G, the next-generation communications technology, has significantly increased communication speeds. This has improved communication efficiency and led to the emergence of a variety of new services."

[0761] Prompt Sentence Examples

[0762] News article summary prompt:

[0763] Summarize this news article text:

[0764] "The introduction of 5G, the next-generation communications technology, has significantly increased communication speeds. This has improved communication efficiency and led to the emergence of a variety of new services. 5G networks are expected to be widely applicable, from homes to factories and agriculture."

[0765] Emotion customization prompt:

[0766] Emphasize positive aspects for happy emotions:

[0767] This allows the user to efficiently obtain important information in a short amount of time, and the information can be provided in a form that is adapted to the user's emotional state.

[0768] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0769] Step 1:

[0770] The server sends a request to the API endpoint of the news data source to retrieve the latest news articles specific to the telecommunications industry. The input is the API endpoint URL, and the output is the news article data (in JSON format). Specifically, the server sends an HTTP GET request to the API of the specified news data source.

[0771] Step 2:

[0772] The server extracts the text from the acquired news article data and generates a summary using a generative AI model. The input is the news article data, and the output is the summarized article text. Specifically, the server extracts the text portion of the article from the JSON of the news article data and sends it to the GPT-4 model along with a prompt to generate a summary.

[0773] Step 3:

[0774] The server sets up virtual roles and simulates discussions based on news articles using a generative AI model. The input is a summarized article text, and the output is the content of the discussions held by the virtual roles. Specifically, the server sets up multiple virtual roles (e.g., technical staff, marketing staff) and sends discussion prompts for each role to the generative AI model to generate the content of the discussions.

[0775] Step 4:

[0776] The server analyzes the generated discussion content and extracts the advantages and disadvantages. The input is the discussion content, and the output is a list of advantages and disadvantages. Specifically, the server uses the generative AI model to analyze the discussion content and organize the identified advantages and disadvantages in list form.

[0777] Step 5:

[0778] The device recognizes the user's emotional state in real time using a camera, microphone, and keyboard input. The input is the user's facial expression, voice, and text input, and the output is the user's emotional data. Specifically, the device uses an emotion engine to analyze the user's input data and identify the user's emotional state.

[0779] Step 6:

[0780] The server customizes summarized news articles and discussion results based on the user's emotional data. The input is the summarized news article, the discussion content, and the user's emotional data, and the output is customized news articles and discussion results. Specifically, the server analyzes the user's emotional state and edits the information to highlight advantages for positive emotions and to explain disadvantages in detail for negative emotions.

[0781] Step 7:

[0782] The server delivers the customized summary and discussion results to the user's device. The input is the customized news article and discussion content, and the output is the information sent to the user's device. Specifically, the server compiles the edited information into a single data structure and sends it to the user's device.

[0783] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0784] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0785] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0786] [Third embodiment]

[0787] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0788] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0789] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0790] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0791] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0792] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0793] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0794] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0795] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0796] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0797] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0798] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0799] One embodiment of the present invention is described below. The system of the present invention efficiently summarizes and analyzes the latest news in the telecommunications industry, and by utilizing generative AI models at each step, it is possible to quickly aggregate information from multiple perspectives.

[0800] System Configuration and Operation

[0801] 1. Retrieving news articles

[0802] The server periodically retrieves the latest news articles via the API of a news site specializing in the telecommunications industry.

[0803] Specifically, the server sends a request to the news site's API endpoint and receives the latest article data related to the telecommunications industry in JSON format.

[0804] 2. News article summaries

[0805] The server inputs the retrieved news articles into a generative AI model to generate summaries.

[0806] First, the server extracts only the main text from the received article data and passes that text to a generative AI model to generate a summarized sentence.

[0807] 3. Argument Simulation

[0808] The server uses a generative AI model to set up virtual personas, each of which simulates a discussion based on a summary of a news article.

[0809] Specifically, virtual personas such as "AI specialist," "technical specialist," and "marketing specialist" are created, model inputs are prepared to generate opinions from each perspective, and the discussion is reproduced using a generative AI model.

[0810] 4. Analysis of advantages and disadvantages

[0811] Based on the results of the discussion simulation, the server extracts and lists the advantages and disadvantages related to the news article.

[0812] The server identifies advantages and disadvantages from the opinions of each generated persona and organizes them in a list format.

[0813] 5. Distribution of summaries and discussion results

[0814] The server delivers the final summarized news articles and discussion results to the user's terminal.

[0815] Specifically, by combining summaries and discussion results into a single data structure and sending it to the user's device, users can efficiently check the important points of the news and various opinions.

[0816] Specific examples

[0817] Let's say you retrieve the following article data from a news site:

[0818] json

[0819] {

[0820] "title": "Next-generation communication technology improves communication speeds",

[0821] "content": "The introduction of 5G, the next-generation communications technology, has significantly improved communication speeds. This..."

[0822] }

[0823] In response, the server does the following:

[0824] 1. Sending an API request:

[0825] The server uses the news site's API to retrieve the latest articles.

[0826] 2. Extract and summarize article text:

[0827] The server extracts the main text from the acquired article data and generates a summary using a generative AI model.

[0828] 3. Argument simulation:

[0829] The server sets up virtual personas and uses generative AI models to simulate discussions from each persona's perspective.

[0830] 4. Analysis of advantages and disadvantages:

[0831] The server extracts advantages and disadvantages based on the discussion results and compiles them into a list.

[0832] 5. Summary and discussion distribution:

[0833] The server compiles the summary and discussion results into a single data structure and sends it to the user's terminal.

[0834] In this way, the system of the present invention efficiently acquires, summarizes, analyzes, and presents the latest information in the telecommunications industry from multiple perspectives, allowing users to obtain important information in a short amount of time.

[0835] The processing flow will be explained below.

[0836] Step 1:

[0837] The server retrieves the latest news articles from the API of a news site specializing in the telecommunications industry. Specifically, the server periodically sends requests to the news site's API endpoint and receives article data for the corresponding category in JSON format. For example, the server retrieves data from "https: / / news.example.com / api / telecommunications industry" and saves the content.

[0838] Step 2:

[0839] The server extracts the text from the retrieved news articles. Specifically, it extracts the content of the article from the JSON data received by the server and saves it in text format. For example, it extracts the text as follows: articles = response.json(), and article_texts = [article['content'] for article in articles].

[0840] Step 3:

[0841] The server inputs the extracted text into a generative AI model to generate a summary. Specifically, it uses the summarization function of the generative AI model to condense long articles into a few paragraphs. For example, it generates a summary using summarizer = pipeline("summarization") and summaries = [summarizer(text, max_length=130, min_length=30, do_sample=False) for text in article_texts].

[0842] Step 4:

[0843] The server sets up virtual personas and simulates a debate for each persona based on a summary of a news article. Specifically, it sets up three personas: an "AI specialist," a "technical specialist," and a "marketing specialist," and generates debate sentences from each persona's perspective using a generative AI model. For example, input data is prepared as follows: debate_inputs = [f"{persona}: {summary}" for persona in personas for summary in summaries].

[0844] Step 5:

[0845] The server uses a generative AI model to extract and list advantages and disadvantages from the simulated debate. Specifically, it identifies the advantages and disadvantages from the opinions of each persona and organizes them in a list format. For example, the analysis is performed as follows: advantages = [result for result in debate_outputs if "advantages" in result] and disadvantages = [result for result in debate_outputs if "disadvantages" in result].

[0846] Step 6:

[0847] The server delivers summarized news articles and discussion results to the user's device. Specifically, the server combines the summaries and discussion results into a single data structure and sends it to the user's device. For example, the data is structured as summary_and_debate = {"summaries": summaries, "advantages": advantages, "disadvantages": disadvantages} and sent to the user's device as send_to_user_device(user_id, summary_and_debate). This allows the user to efficiently obtain important information and diverse opinions.

[0848] Example 1

[0849] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0850] In modern society, the telecommunications industry is changing rapidly, creating a need to quickly acquire the latest information and analyze it efficiently. However, processing huge amounts of information and analyzing it from various perspectives is not an easy task. With current methods, summarization and multifaceted analysis require time and effort, making it difficult for users to immediately grasp important information. For this reason, there is a need to develop a system that can automatically acquire, summarize, and analyze multifaceted information specific to the telecommunications industry and provide it quickly.

[0851] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0852] In this invention, the server includes means for acquiring the latest information from information sources specialized in the telecommunications industry, means for summarizing the acquired information using a generative AI model, means for setting up a virtual character and simulating a discussion using the generative AI model based on the summarized information, means for analyzing advantages and disadvantages from the results of the discussion simulation, and means for delivering the summarized information and discussion results to a user's device. This makes it possible to quickly acquire the latest information in the telecommunications industry and efficiently provide it to users through summaries and multifaceted analysis.

[0853] "Telecommunications industry" refers to industries and markets related to communications technology and services.

[0854] "Source" refers to any official or unofficial medium or platform that provides information on a particular subject.

[0855] A "generative AI model" refers to an algorithm or system that uses artificial intelligence technology to generate new information or content from data.

[0856] "Virtual character" refers to a fictional person or agent with a specific role or perspective.

[0857] "Simulating a discussion" refers to using a generative AI model to simulate a process in which virtual characters exchange opinions on a particular topic.

[0858] An "advantage" refers to an element or aspect that is beneficial in a particular situation or condition.

[0859] "Disadvantages" refer to elements or aspects that are unfavorable in a particular situation or condition.

[0860] "User Equipment" refers to any device or terminal used to receive and view information.

[0861] The present invention provides a system for efficiently acquiring, summarizing, and analyzing the latest information in the communications industry, and providing users with discussion results from multiple perspectives. Specific embodiments of the present invention will be described below.

[0862] Hardware and Software Configuration

[0863] The server is a data center server with high-performance processing power that processes API requests, analyzes data, and operates generative AI models. Specifically, it uses the following software and services:

[0864] API request processing: Web server software such as Apache or Nginx

[0865] Data format: JSON format parser

[0866] Generative AI models: OpenAI's GPT-3 and similar generative AI models

[0867] Database: A relational database such as MySQL or PostgreSQL

[0868] Program processing flow

[0869] Get news articles

[0870] The server obtains the latest information using the API of a source specialized in the telecommunications industry. The specific steps are as follows:

[0871] Sending API requests: The server periodically sends an HTTP request to the source's API endpoint to retrieve the latest information.

[0872] Receiving data: Receive data in JSON format from the API and save the data in a database on the server.

[0873] News article summaries

[0874] The server summarizes the acquired information using a generative AI model. The specific steps are as follows:

[0875] Text extraction: The server extracts the body text from the received JSON data.

[0876] Input to the generative AI model: The extracted text is passed to the generative AI model to generate a summary.

[0877] Example prompt sentence:

[0878] Summarize this article: The introduction of 5G, the next generation of communications technology, has significantly increased communication speeds. This...

[0879] Argument simulation

[0880] The server uses a generative AI model to set up virtual characters and simulate discussions based on the summarized information. The specific steps are as follows:

[0881] Setting virtual characters: The server sets up three virtual characters: "AI person," "technical person," and "marketing person."

[0882] Creating prompts for discussion generation: Generate prompts for each character and input them into the generative AI model.

[0883] Example prompt sentence:

[0884] AI Expert: Please comment on this article from an AI perspective. The introduction of 5G, the next generation communication technology, has significantly improved communication speeds.

[0885] Techie: What is the technological impact of this article? The introduction of 5G, the next generation communication technology, has significantly increased communication speeds.

[0886] Marketer: Based on this article, what marketing strategies can you think of? The introduction of 5G, the next generation communication technology, has significantly improved communication speeds.

[0887] Analysis of advantages and disadvantages

[0888] The server extracts advantages and disadvantages from the simulation results of the discussion. The specific steps are as follows:

[0889] Analysis of discussion results: The server analyzes the opinions of each generated character and identifies their advantages and disadvantages.

[0890] List creation: The extracted advantages and disadvantages are organized in a list format and saved on the server.

[0891] Summary and discussion results distribution

[0892] The server compiles the summarized information and the results of the discussion into a single data structure and delivers it to the user's terminal. The specific steps are as follows:

[0893] Data synthesis: Generate a data structure that summarizes the summary, discussion results, advantages and disadvantages.

[0894] Data transmission: Send data to the user's device via API or WebSocket, allowing the user to retrieve information efficiently.

[0895] According to the embodiment of the present invention, it is possible to quickly obtain the latest information in the communications industry and efficiently provide it to users through summaries and multifaceted analyses.

[0896] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0897] Step 1:

[0898] Get news articles

[0899] The server retrieves the latest news articles using the API of a telecommunications industry-specific information source. Specifically, the server periodically sends an HTTP request to the API endpoint and receives the latest news article data in JSON format. For example, it sends a request to the "GET / latest-news" endpoint and receives the following JSON response:

[0900] json

[0901] {

[0902] "title": "Next-generation communication technology improves communication speeds",

[0903] "content": "The introduction of 5G, the next-generation communications technology, has significantly improved communication speeds. This..."

[0904] }

[0905] Input: News site API endpoint

[0906] Output: News article data in JSON format

[0907] Step 2:

[0908] News article summaries

[0909] The server inputs the retrieved news article into a generative AI model to generate a summary. First, the server extracts the text from the received JSON data and passes that text to a generative AI model (e.g., OpenAI's GPT-3) to generate a summary. Specifically, the server inputs the following prompt sentence into the model:

[0910] prompt = "Summarize this article: The introduction of 5G, the next-generation communications technology, has dramatically increased communication speeds. This means..."

[0911] The generated summary is saved in the server for later processing.

[0912] Input: News article body text

[0913] Output: Summary text generated by the generative AI model

[0914] Step 3:

[0915] Argument simulation

[0916] The server uses a generative AI model to create virtual characters, each of which simulates a discussion based on a summary of a news article. First, the server creates virtual characters such as an "AI expert," an "engineer," and a "marketing expert." It then generates prompts for each character, such as:

[0917] AI Expert: Please comment on this article from an AI perspective. The introduction of 5G, the next generation communication technology, has significantly improved communication speeds.

[0918] Techie: What is the technological impact of this article? The introduction of 5G, the next generation communication technology, has significantly increased communication speeds.

[0919] Marketer: Based on this article, what marketing strategies can you think of? The introduction of 5G, the next generation communication technology, has significantly improved communication speeds.

[0920] The generated discussion content is stored on the server.

[0921] Input: Summary text and virtual character settings

[0922] Output: Discussion content of each character by the generative AI model

[0923] Step 4:

[0924] Analysis of advantages and disadvantages

[0925] The server extracts advantages and disadvantages based on the results of the simulated discussion. It analyzes the opinions of the generated virtual characters, identifies advantages and disadvantages from each point of view, and compiles them into a list. For example, it creates a list like this:

[0926] python

[0927] pros_and_cons = {

[0928] "Advantages": ["High speed", "New business opportunities"],

[0929] Disadvantages: High cost, infrastructure burden

[0930] }

[0931] This list is stored on the server.

[0932] Input: Discussion content of each character

[0933] Output: A list of advantages and disadvantages

[0934] Step 5:

[0935] Summary and discussion results distribution

[0936] The server compiles the summarized news articles and the results of the discussion into a single data structure and delivers it to the user's device. The data structure looks like this:

[0937] json

[0938] {

[0939] "summary": "The introduction of 5G, the next-generation communication technology, has significantly improved communication speeds.",

[0940] "pros_and_cons": {

[0941] "Advantages": ["High speed", "New business opportunities"],

[0942] Disadvantages: High cost, infrastructure burden

[0943] },

[0944] "discussion": {

[0945] "AI Personnel": "With improved communication speeds, it is highly likely that the speed at which AI analyzes data will also improve.",

[0946] "Technical Staff": "We expect new technology to improve stability.",

[0947] "Marketer": "High-speed communications will enable us to bring new services to market."

[0948] }

[0949] }

[0950] This data is sent to the user's device via API or WebSocket, allowing the user to access the information efficiently.

[0951] Input: Summary, discussion results, list of advantages and disadvantages

[0952] Output: Sending the integrated data to the user's terminal

[0953] (Application example 1)

[0954] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0955] Although systems exist that efficiently summarize the latest news in the telecommunications industry and enable discussion from multiple perspectives, there is a lack of means for users to quickly and visually understand the information. In particular, there is a need to provide visualized information using mobile information terminals and video display devices so that users can intuitively understand important information. This is expected to improve the efficiency of decision-making.

[0956] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0957] In this invention, the server includes means for acquiring the latest news articles from news sources specialized in the communications industry, means for summarizing the acquired news articles using a generative AI model, means for setting a virtual persona and simulating a discussion based on the summarized news articles using the generative AI model, means for analyzing the advantages and disadvantages from the results of the discussion simulation, means for delivering the summarized news articles and discussion results to a user's terminal, and means for visualizing the summaries and discussion results on a mobile information terminal or video display device used by the user, thereby enabling the user to quickly and intuitively understand important information.

[0958] A "news source specializing in the telecommunications industry" is an information provider that specializes in telecommunications technology, infrastructure, services, and related information.

[0959] A "breaking news story" is a story that contains timely, new information relevant to the communications industry.

[0960] A "generative AI model" is an artificial intelligence model that uses natural language processing to summarize and generate text data.

[0961] A "summary" is a shortened version of the original text that extracts the most important information.

[0962] A "virtual persona" is a character that is set up as a virtual being with a different perspective or role.

[0963] "Simulation" means recreating the process of actual discussion or exchange of opinions in a virtual environment.

[0964] "Advantages and disadvantages" refers to the advantages and disadvantages of a certain event or option.

[0965] A "mobile information terminal" refers to a portable information processing device such as a smartphone or tablet.

[0966] The term "video display device" refers to a device for displaying video, and includes, for example, a head-mounted display.

[0967] "Visualization" means representing information visually using shapes, graphs, text, etc.

[0968] "User terminal" refers to the device that the user ultimately uses to view information, and examples include smartphones and computers.

[0969] In this embodiment, technologies such as a server, a mobile information terminal, a video display device, and a generative AI model are used to realize efficient summaries of news articles specific to the telecommunications industry and discussion simulations from multiple perspectives.

[0970] System basic configuration and operation

[0971] Program Overview

[0972] The system retrieves the latest news articles from the telecommunications industry, uses a generative AI model to summarize and simulate discussions, and then provides the results to users.

[0973] Hardware and software used

[0974] Hardware: Mobile information terminals (smartphones and tablets), video display devices (head-mounted displays, etc.)

[0975] Software: Python (Flask framework), generative AI model (OpenAI GPT-4), news site API

[0976] Data processing and calculation

[0977] The server retrieves the latest news articles from the news site's API and receives the data in JSON format. Next, it uses a generative AI model to summarize the article text and simulates a discussion using virtual personas. Finally, it delivers the summary and discussion results to the user's device and visualizes them on the device.

[0978] Specific examples

[0979] For example, suppose you retrieve the following article data from a news site:

[0980] The introduction of 5G, the next-generation communications technology, has significantly improved communication speeds. This has...

[0981] In this case, the server extracts the body text from the article data and inputs the following prompt sentences into the generative AI model:

[0982] Summarize this article: The introduction of 5G, the next generation of communications technology, has significantly increased communication speeds. This...

[0983] The generative AI model generates a summary based on this prompt and then simulates the discussion from the perspective of virtual personas (e.g., "AI expert," "technical person," "marketing person"), analyzing the advantages and disadvantages of the simulated discussion and summarizing the results.

[0984] Summary and discussion visualization

[0985] The server delivers the summarized articles and discussion results to mobile information terminals and video display devices, where they are visualized, allowing users to efficiently understand the latest trends in the communications industry.

[0986] Thus, this invention provides a system that allows users to efficiently process and utilize information by acquiring data from specific news sources, summarizing using a generative AI model, simulating discussions using virtual personas, and visualizing the results.

[0987] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0988] Step 1:

[0989] The server retrieves the latest news articles from the API of a news source that specializes in the telecommunications industry. It sends a request to the news site's API endpoint and receives the latest article data in JSON format. The input is the API request from the server, and the output is the news article data in JSON format.

[0990] Step 2:

[0991] The server extracts the body text from the JSON data of the retrieved news article. Specifically, it extracts the value corresponding to the "content" key from the JSON data as text. The input is the JSON data of the news article, and the output is the text of the article body.

[0992] Step 3:

[0993] The server passes the extracted article text to a generative AI model to generate a summary. First, a prompt is created and input into the generative AI model. The generative AI model analyzes the text data and outputs a summarized sentence. The input is the article text and the prompt, and the output is the summarized article text.

[0994] Step 4:

[0995] The server uses the summarized text to simulate a discussion between virtual personas. It sets up virtual personas (e.g., "AI expert," "technical person," and "marketing person"), prepares prompts to generate discussions from each persona's perspective, and inputs these into the generative AI model. The model generates opinions from each persona's perspective. The inputs are the summary text and the prompts from the virtual personas, and the output is the discussion text generated for each persona.

[0996] Step 5:

[0997] The server extracts advantages and disadvantages from the generated argument text. It analyzes the opinions expressed in the argument and organizes the advantages and disadvantages in a list format. The input is the argument text, and the output is a list of advantages and disadvantages.

[0998] Step 6:

[0999] The server combines the summarized news article and the results of the discussion (a list of advantages and disadvantages) into a single data structure. Finally, it converts the data into a format that can be delivered to the user's device. The input is the summary text and the list of discussion results, and the output is the integrated data for the user's device.

[1000] Step 7:

[1001] The user's terminal visualizes the data received from the server. Specifically, the summary and discussion results are displayed on a mobile information terminal or video display device, and presented in a format that is intuitively easy for the user to understand. The input is the integrated data from the server, and the output is the visualized information.

[1002] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1003] The present invention is described below in detail in terms of an embodiment. The system includes an emotion engine that summarizes and analyzes news articles specific to the telecommunications industry, recognizes a user's emotions, and customizes the information accordingly. This allows users to efficiently obtain important information in a short amount of time, and the information is optimized to fit the user's emotional state.

[1004] System Configuration and Operation

[1005] 1. Retrieving news articles

[1006] The server retrieves the latest news articles from the API of a news site specializing in the telecommunications industry. Specifically, the server periodically sends requests to the news site's API endpoint and receives telecommunications industry-related article data in JSON format. For example, the server retrieves data from "https: / / news.example.com / api / telecommunications industry" and saves the content.

[1007] 2. News article summaries

[1008] The server extracts the text from the retrieved news articles. Specifically, it extracts the article content from the JSON data received by the server and saves it in text format. The extracted text is input into a generative AI model to generate a summary. The generative AI model's summarization function is used to condense long articles into a few paragraphs.

[1009] 3. Argument Simulation

[1010] The server uses a generative AI model to set up virtual personas, each of which simulates a discussion based on a summary of a news article. Specifically, the server sets up three personas: an "AI specialist," a "technical specialist," and a "marketing specialist," and uses the generative AI model to generate text for the discussion from each persona's perspective.

[1011] 4. Analysis of advantages and disadvantages

[1012] The server extracts and lists the advantages and disadvantages related to the news article based on the generated discussion results. It identifies advantages and disadvantages from the opinions of each persona and organizes them in a list format.

[1013] 5. User Emotion Recognition

[1014] The device is equipped with an emotion engine that recognizes emotions through the user's facial expressions, voice, or text input. Specifically, it uses the device's built-in camera, microphone, keyboard input, etc. to analyze the user's emotional state (e.g., joy, sadness, surprise, etc.) in real time.

[1015] 6. Emotional customization

[1016] The server customizes summarized news articles and discussion results based on the user's emotional data obtained from the emotion engine. Specifically, it provides information adapted to the user's emotional state, such as emphasizing the benefits if the user is expressing positive emotions, or explaining the disadvantages in detail if the user is expressing negative emotions.

[1017] 7. Distribution of summaries and discussion results

[1018] The server finally delivers the summarized news article and customized discussion results to the user's device. Specifically, by combining the summary and discussion results into a single data structure and sending it to the user's device, the user can efficiently obtain the key points of the news and various opinions.

[1019] Specific examples

[1020] Let's say you retrieve the following article data from a news site:

[1021] json

[1022] {

[1023] "title": "Next-generation communication technology improves communication speeds",

[1024] "content": "The introduction of 5G, the next-generation communications technology, has significantly improved communication speeds. This..."

[1025] }

[1026] In response, the server does the following:

[1027] 1. Sending an API request:

[1028] The server uses the news site's API to retrieve the latest articles.

[1029] 2. Extract and summarize article text:

[1030] The server extracts the main text from the acquired article data and generates a summary using a generative AI model.

[1031] 3. Argument simulation:

[1032] The server sets up virtual personas and uses generative AI models to simulate discussions from each persona's perspective.

[1033] 4. Analysis of advantages and disadvantages:

[1034] The server extracts advantages and disadvantages based on the discussion results and compiles them into a list.

[1035] 5. User Emotion Recognition:

[1036] The device uses the camera, microphone, and keyboard input to recognize the user's emotions.

[1037] 6. Emotional customization:

[1038] The server customizes how information is presented based on the user's emotional data.

[1039] 7. Summary and discussion distribution:

[1040] The server compiles the summaries and discussion results into a single data structure and sends it to the user's device, allowing the user to efficiently obtain important information and diverse opinions, while adapting the information to the user's emotional state.

[1041] In this way, the system of the present invention efficiently summarizes and analyzes the latest information in the telecommunications industry, and customizes it to the user's emotional state, allowing the user to obtain important information in a short amount of time.

[1042] The processing flow will be explained below.

[1043] Step 1:

[1044] The server retrieves the latest news articles from the API of a news site specializing in the telecommunications industry. Specifically, the server periodically sends requests to the news site's API endpoint and receives telecommunications industry-related article data in JSON format. For example, the server retrieves data from "https: / / news.example.com / api / telecommunications industry".

[1045] Step 2:

[1046] The server extracts the text from the retrieved news articles. Specifically, it extracts the content of the article from the JSON data received by the server and saves it in text format. For example, it extracts the text as follows: articles = response.json(), and article_texts = [article['content'] for article in articles].

[1047] Step 3:

[1048] The server inputs the extracted text into a generative AI model to generate a summary. Specifically, it uses the summarization function of the generative AI model to condense long articles into a few paragraphs. For example, it generates a summary using summarizer = pipeline("summarization") and summaries = [summarizer(text, max_length=130, min_length=30, do_sample=False) for text in article_texts].

[1049] Step 4:

[1050] The server sets up virtual personas and simulates a debate for each persona based on a summary of a news article. Specifically, it sets up three personas: an "AI specialist," a "technical specialist," and a "marketing specialist," and generates debate sentences from each persona's perspective using a generative AI model. For example, input data is prepared as follows: debate_inputs = [f"{persona}: {summary}" for persona in personas for summary in summaries].

[1051] Step 5:

[1052] The server uses a generative AI model to extract and list advantages and disadvantages from the simulated debate. Specifically, it identifies the advantages and disadvantages from the opinions of each persona and organizes them in a list format. For example, the analysis is performed as follows: advantages = [result for result in debate_outputs if "advantages" in result] and disadvantages = [result for result in debate_outputs if "disadvantages" in result].

[1053] Step 6:

[1054] The device is equipped with an emotion engine that recognizes emotions through the user's facial expressions, voice, or text input. Specifically, it analyzes the user's emotional state in real time using the device's built-in camera, microphone, keyboard input, etc. For example, it implements face recognition using a camera and voice emotion analysis using a microphone.

[1055] Step 7:

[1056] The server customizes summarized news articles and discussion results based on the user's emotional data obtained from the emotion engine. Specifically, it provides information adapted to the user's emotional state, such as emphasizing the benefits if the user is expressing positive emotions and detailing the disadvantages if the user is expressing negative emotions.

[1057] Step 8:

[1058] The server finally delivers the summarized news article and customized discussion results to the user's device. Specifically, the server combines the summary and discussion results into a single data structure and sends it to the user's device. For example, the data is structured as summary_and_debate = {"summaries": summaries, "advantages": advantages, "disadvantages": disadvantages} and sent to the user's device as send_to_user_device(user_id, summary_and_debate). As a result, the user can efficiently obtain important information and diverse opinions, and the information is adapted to the user's emotional state.

[1059] Example 2

[1060] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1061] In today's information society, it is important to efficiently obtain the latest news specific to a specific industry and summarize and analyze that information. However, it is not easy to extract the necessary information from the vast amount of information and provide it to users in an appropriate format. In addition, there is a lack of means to customize information based on user emotions, which poses a challenge in terms of how users can obtain the most appropriate information.

[1062] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring the latest information from information sources specialized in the telecommunications industry, means for summarizing the acquired information using a generative AI model, means for setting up a virtual person and simulating a discussion using the generative AI model based on the summarized information, means for analyzing the advantages and disadvantages from the results of the discussion simulation, means for recognizing the user's emotions, means for customizing the summarized information and discussion results according to the user's emotional state, and means for delivering the summarized information and discussion results to the user's terminal. This allows the user to efficiently acquire important information in a short amount of time, and the information can be optimized to suit the user's emotional state.

[1063] "Source" refers to a service or platform that provides up-to-date information or data on a particular industry or field.

[1064] A "generative AI model" refers to an artificial intelligence algorithm that uses machine learning techniques to summarize and analyze information from text and data.

[1065] "Virtual person" refers to the concept of creating a fictional character with a specific role or perspective, and generating discussions and opinions from that perspective.

[1066] "User emotion" refers to the psychological state or reaction that a user expresses through facial expression, voice, or text input.

[1067] "Customization" means the adjustment and optimization of information and service content to meet specific conditions and requirements.

[1068] "Terminal" refers to a device or hardware that allows a user to receive and view information, including, for example, a PC, smartphone, or tablet.

[1069] "API" stands for Application Programming Interface, and refers to an interface for exchanging information and functions between different software systems.

[1070] The present invention is best understood by describing an embodiment thereof as follows: The system of the present invention obtains up-to-date information from sources specialized in the telecommunications industry, efficiently summarizes and analyzes it, and provides customized information based on the user's emotional state.

[1071] Configuration and Operation

[1072] The server periodically obtains the latest information using the API of a source specialized in the telecommunications industry. Specifically, the server sends an HTTP GET request to the "information provider API" and receives data in JSON format. The received data is then analyzed using a parser and the obtained information is stored in a database.

[1073] Next, the server uses a generative AI model to summarize the information it has obtained. The server extracts the content from the JSON data and inputs the following prompt to the generative AI model:

[1074] "Summarize the following sentence: The introduction of 5G, the next generation communications technology, has significantly improved communication speeds. This has..."

[1075] The generated summary text is again stored in the database.

[1076] The server then sets up virtual people (personas) and simulates a discussion from each person's perspective using the generative AI model. The virtual people are set as "engineer," "marketer," and "AI person," and the following prompts are input to the generative AI model:

[1077] "Please comment on this summary as a technical expert."

[1078] The generated comments are stored in a database for each persona.

[1079] The server then analyzes the generated discussion results, extracting and listing the advantages and disadvantages. This not only provides a summary of the news, but also organizes opinions from multiple perspectives, making the advantages and disadvantages clear.

[1080] The device uses a camera, microphone, and keyboard input to recognize the user's emotions. Specifically, the device uses a built-in camera to recognize facial expressions, a microphone to analyze voice, and keyboard input to analyze text, thereby analyzing the user's emotional state in real time.

[1081] The server customizes the summarized information and discussion results based on the emotional data sent from the device. If the user is expressing positive emotions, the server emphasizes the benefits, and if the user is expressing negative emotions, it explains the disadvantages in detail.

[1082] Finally, the server delivers the summarized information and customized discussion results to the user's device. The summary and discussion results are combined into a single data structure and sent to the device, allowing the user to efficiently obtain important information in a short time, and the information is optimized for the user's emotional state.

[1083] Specific examples

[1084] For example, if you retrieve the following article data from the API:

[1085] "The introduction of 5G, the next generation communications technology, has significantly increased communication speeds. This has led to the telecommunications industry..."

[1086] The server summarizes this and generates the following text:

[1087] "With the introduction of 5G, communication speeds have improved."

[1088] Next, generate the following simulation prompt as the "Technician":

[1089] "Please comment on this summary as a technical expert."

[1090] The generated comment is, "The introduction of 5G technology has made high-speed communication possible and dramatically improved data transfer speeds."

[1091] As a result, the system of the present invention efficiently summarizes and analyzes the latest information in the telecommunications industry and customizes it to the user's emotional state, allowing the user to obtain important information in a short amount of time.

[1092] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1093] Step 1: Get news articles

[1094] The server retrieves the latest news articles using the API of a source specialized in the telecommunications industry. Specifically, the server periodically sends HTTP GET requests to the API of the information provider and receives data in JSON format. The input for this process is the API endpoint URL, and the output is news article data in JSON format. After receiving the data, the server parses the JSON data using a parser, extracts the required article data, and stores it in a database.

[1095] Step 2: Summarize the news article

[1096] The server extracts the main text from the saved news article data and inputs it into the generative AI model to generate a summary. Specifically, it extracts the content field from the article data and sends it to the generative AI model as a prompt. An example of a prompt is "Please summarize the following sentence: With the introduction of next-generation communication technology 5G, communication speeds have improved significantly. As a result..." The input for this process is the extracted main text, and the output is the summarized text. The generated summary is then saved back into the database.

[1097] Step 3: Simulating the discussion

[1098] The server sets up virtual characters and uses a generative AI model to simulate a discussion in which each virtual character engages in a discussion based on a summary of a news article. Specifically, it sets up three virtual characters: an "engineer," a "marketer," and an "AI technician," and generates discussions from each of their perspectives using a generative AI model. The input is the summary text and the settings of each virtual character, and the output is discussion text generated from each virtual character's perspective. As an example, it uses the prompt sentence, "Please comment on this summary as an engineer." The generated discussion text is stored in a database.

[1099] Step 4: Analyze the pros and cons

[1100] The server extracts and lists the advantages and disadvantages based on the generated discussion results. Specifically, it analyzes the discussion text using natural language processing to extract positive and negative elements. The input is the saved discussion text, and the output is a list of advantages and disadvantages. The extracted elements are saved in a database as the analysis results.

[1101] Step 5: Recognizing User Emotions

[1102] The device uses a camera, microphone, and keyboard input to recognize the user's emotions in real time. Specifically, it uses a camera to recognize facial expressions, a microphone to perform voice analysis, and analyzes text entered from the keyboard to estimate the user's emotions. The input is the user's facial expressions, voice, and text input, and the output is recognized emotion data. The emotion data is sent from the device to a server.

[1103] Step 6: Emotional customization

[1104] The server customizes summarized news articles and discussion results based on the emotion data sent from the device. Specifically, if the user expresses positive emotion, it emphasizes the benefits, and if the user expresses negative emotion, it explains the disadvantages in detail. The input for this process is the user's emotion data, summarized articles, and discussion results, and the output is customized information. The customized information is adjusted and edited according to the user's emotion.

[1105] Step 7: Summary and distribution of discussion results

[1106] The server finally delivers the customized summary and discussion results to the user's device. Specifically, it combines the summary and discussion results into a single data structure and sends it to the user's device. The input is the customized information, and the output is the information delivered to the user's device. The user receives this and can view the key points and diverse opinions of the news in a customized format.

[1107] (Application example 2)

[1108] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1109] In modern society, information in the telecommunications industry is extremely important, and it is necessary to efficiently grasp rapidly changing news. However, due to the wide variety of information, it is difficult for users to quickly obtain the information they need and accurately understand it. Furthermore, if the news content does not match the user's emotions or interests, there is a problem that the information will be less receptive, making it difficult to provide effective information.

[1110] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1111] In this invention, the server includes: means for acquiring the latest news articles from a news data source specialized for the telecommunications industry; means for summarizing the acquired news articles using a generative AI model; means for setting virtual roles and simulating a discussion based on the summarized news articles using the generative AI model; means for customizing the summarized news articles and discussion results based on the emotional state of the user using a terminal equipped with an emotion engine that recognizes the user's emotions; and means for delivering the summarized news articles and discussion results to the user's terminal. This allows users to efficiently acquire important information in a short amount of time, and the information can be provided in a form adapted to the user's emotional state.

[1112] A "server" is a computer system that provides data and functions to clients over a network.

[1113] A "news data source" is a digital source that provides up-to-date information on a particular subject.

[1114] "API" stands for Application Programming Interface, a set of rules and tools for exchanging information and functionality between different software applications.

[1115] A "generative AI model" is an algorithm that uses artificial intelligence to generate text and data, specifically a model that performs natural language processing.

[1116] A "summary" is a concise summary of original data or information.

[1117] A "virtual role" is a simulated character or persona with a particular perspective or opinion, used in simulations and discussions.

[1118] An "emotion engine" is a software module for recognizing and analyzing a user's emotional state.

[1119] "User's terminal" refers to any device used by a user, specifically a smartphone, computer, tablet, etc.

[1120] "Customization" refers to tailoring or modifying information or services to a particular user or situation.

[1121] This invention describes a system that efficiently collects and summarizes news articles specific to the telecommunications industry, and customizes them to fit the user's emotional state.

[1122] 1. System Overview

[1123] This system works in conjunction with a server and user devices. The server retrieves news specific to the telecommunications industry and summarizes it using a generative AI model. It then sets up virtual roles to simulate discussions based on news articles and analyzes the results. The user devices use an emotion engine to recognize the user's emotions, and the server uses this data to customize summaries and discussion results. The information is then delivered to the user devices.

[1124] 2. Hardware and Software Used

[1125] Hardware: Server computers, user devices (smartphones, computers, tablets, etc.), cameras, microphones

[1126] software:

[1127] Server: Node.js / Express.js, MongoDB, Axios (for API requests)

[1128] Generative AI model: OpenAI GPT-4

[1129] Emotion recognition: Affectiva SDK, Microsoft Azure Emotion API

[1130] 3. Processing Flow

[1131] News article retrieval and summarization

[1132] The server periodically retrieves the latest news articles from telecommunications industry news data sources via API, which are then summarized using OpenAI GPT-4, a generative AI model.

[1133] Virtual role setting and discussion simulation

[1134] The server creates virtual roles (e.g., technical person, marketing person) and uses a generative AI model to simulate each role discussing a news article, analyzing the resulting pros and cons.

[1135] Emotion Recognition and Customization

[1136] The user's device uses a camera and microphone to recognize the user's emotional state in real time. The emotion engine analyzes the data and sends it to the server. The server then customizes summarized news articles and discussion results based on the emotional data, providing information in a format that best suits the user's emotional state.

[1137] Summary and discussion results distribution

[1138] Finally, customized summaries and discussion results are delivered to users' devices, allowing them to obtain information efficiently and emotionally adapted.

[1139] 4. Specific Examples

[1140] Some examples of articles retrieved from news sites include:

[1141] Title: "Next-generation communication technology improves communication speeds"

[1142] Abstract: "The introduction of 5G, the next-generation communications technology, has significantly increased communication speeds. This has improved communication efficiency and led to the emergence of a variety of new services."

[1143] Prompt Sentence Examples

[1144] News article summary prompt:

[1145] Summarize this news article text:

[1146] "The introduction of 5G, the next-generation communications technology, has significantly increased communication speeds. This has improved communication efficiency and led to the emergence of a variety of new services. 5G networks are expected to be widely applicable, from homes to factories and agriculture."

[1147] Emotion customization prompt:

[1148] Emphasize positive aspects for happy emotions:

[1149] This allows the user to efficiently obtain important information in a short amount of time, and the information can be provided in a form that is adapted to the user's emotional state.

[1150] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1151] Step 1:

[1152] The server sends a request to the API endpoint of the news data source to retrieve the latest news articles specific to the telecommunications industry. The input is the API endpoint URL, and the output is the news article data (in JSON format). Specifically, the server sends an HTTP GET request to the API of the specified news data source.

[1153] Step 2:

[1154] The server extracts the text from the acquired news article data and generates a summary using a generative AI model. The input is the news article data, and the output is the summarized article text. Specifically, the server extracts the text portion of the article from the JSON of the news article data and sends it to the GPT-4 model along with a prompt to generate a summary.

[1155] Step 3:

[1156] The server sets up virtual roles and simulates discussions based on news articles using a generative AI model. The input is a summarized article text, and the output is the content of the discussions held by the virtual roles. Specifically, the server sets up multiple virtual roles (e.g., technical staff, marketing staff) and sends discussion prompts for each role to the generative AI model to generate the content of the discussions.

[1157] Step 4:

[1158] The server analyzes the generated discussion content and extracts the advantages and disadvantages. The input is the discussion content, and the output is a list of advantages and disadvantages. Specifically, the server uses the generative AI model to analyze the discussion content and organize the identified advantages and disadvantages in list form.

[1159] Step 5:

[1160] The device recognizes the user's emotional state in real time using a camera, microphone, and keyboard input. The input is the user's facial expression, voice, and text input, and the output is the user's emotional data. Specifically, the device uses an emotion engine to analyze the user's input data and identify the user's emotional state.

[1161] Step 6:

[1162] The server customizes summarized news articles and discussion results based on the user's emotional data. The input is the summarized news article, the discussion content, and the user's emotional data, and the output is customized news articles and discussion results. Specifically, the server analyzes the user's emotional state and edits the information to highlight advantages for positive emotions and to explain disadvantages in detail for negative emotions.

[1163] Step 7:

[1164] The server delivers the customized summary and discussion results to the user's device. The input is the customized news article and discussion content, and the output is the information sent to the user's device. Specifically, the server compiles the edited information into a single data structure and sends it to the user's device.

[1165] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1166] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1167] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1168] [Fourth embodiment]

[1169] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1170] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1171] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1172] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1173] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1174] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1175] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1176] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1177] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1178] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1179] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1180] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1181] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1182] One embodiment of the present invention is described below. The system of the present invention efficiently summarizes and analyzes the latest news in the telecommunications industry, and by utilizing generative AI models at each step, it is possible to quickly aggregate information from multiple perspectives.

[1183] System Configuration and Operation

[1184] 1. Retrieving news articles

[1185] The server periodically retrieves the latest news articles via the API of a news site specializing in the telecommunications industry.

[1186] Specifically, the server sends a request to the news site's API endpoint and receives the latest article data related to the telecommunications industry in JSON format.

[1187] 2. News article summaries

[1188] The server inputs the retrieved news articles into a generative AI model to generate summaries.

[1189] First, the server extracts only the main text from the received article data and passes that text to a generative AI model to generate a summarized sentence.

[1190] 3. Argument Simulation

[1191] The server uses a generative AI model to set up virtual personas, each of which simulates a discussion based on a summary of a news article.

[1192] Specifically, virtual personas such as "AI specialist," "technical specialist," and "marketing specialist" are created, model inputs are prepared to generate opinions from each perspective, and the discussion is reproduced using a generative AI model.

[1193] 4. Analysis of advantages and disadvantages

[1194] Based on the results of the discussion simulation, the server extracts and lists the advantages and disadvantages related to the news article.

[1195] The server identifies advantages and disadvantages from the opinions of each generated persona and organizes them in a list format.

[1196] 5. Distribution of summaries and discussion results

[1197] The server delivers the final summarized news articles and discussion results to the user's terminal.

[1198] Specifically, by combining summaries and discussion results into a single data structure and sending it to the user's device, users can efficiently check the important points of the news and various opinions.

[1199] Specific examples

[1200] Let's say you retrieve the following article data from a news site:

[1201] json

[1202] {

[1203] "title": "Next-generation communication technology improves communication speeds",

[1204] "content": "The introduction of 5G, the next-generation communications technology, has significantly improved communication speeds. This..."

[1205] }

[1206] In response, the server does the following:

[1207] 1. Sending an API request:

[1208] The server uses the news site's API to retrieve the latest articles.

[1209] 2. Extract and summarize article text:

[1210] The server extracts the main text from the acquired article data and generates a summary using a generative AI model.

[1211] 3. Argument simulation:

[1212] The server sets up virtual personas and uses generative AI models to simulate discussions from each persona's perspective.

[1213] 4. Analysis of advantages and disadvantages:

[1214] The server extracts advantages and disadvantages based on the discussion results and compiles them into a list.

[1215] 5. Summary and discussion distribution:

[1216] The server compiles the summary and discussion results into a single data structure and sends it to the user's terminal.

[1217] In this way, the system of the present invention efficiently acquires, summarizes, analyzes, and presents the latest information in the telecommunications industry from multiple perspectives, allowing users to obtain important information in a short amount of time.

[1218] The processing flow will be explained below.

[1219] Step 1:

[1220] The server retrieves the latest news articles from the API of a news site specializing in the telecommunications industry. Specifically, the server periodically sends requests to the news site's API endpoint and receives article data for the corresponding category in JSON format. For example, the server retrieves data from "https: / / news.example.com / api / telecommunications industry" and saves the content.

[1221] Step 2:

[1222] The server extracts the text from the retrieved news articles. Specifically, it extracts the content of the article from the JSON data received by the server and saves it in text format. For example, it extracts the text as follows: articles = response.json(), and article_texts = [article['content'] for article in articles].

[1223] Step 3:

[1224] The server inputs the extracted text into a generative AI model to generate a summary. Specifically, it uses the summarization function of the generative AI model to condense long articles into a few paragraphs. For example, it generates a summary using summarizer = pipeline("summarization") and summaries = [summarizer(text, max_length=130, min_length=30, do_sample=False) for text in article_texts].

[1225] Step 4:

[1226] The server sets up virtual personas and simulates a debate for each persona based on a summary of a news article. Specifically, it sets up three personas: an "AI specialist," a "technical specialist," and a "marketing specialist," and generates debate sentences from each persona's perspective using a generative AI model. For example, input data is prepared as follows: debate_inputs = [f"{persona}: {summary}" for persona in personas for summary in summaries].

[1227] Step 5:

[1228] The server uses a generative AI model to extract and list advantages and disadvantages from the simulated debate. Specifically, it identifies the advantages and disadvantages from the opinions of each persona and organizes them in a list format. For example, the analysis is performed as follows: advantages = [result for result in debate_outputs if "advantages" in result] and disadvantages = [result for result in debate_outputs if "disadvantages" in result].

[1229] Step 6:

[1230] The server delivers summarized news articles and discussion results to the user's device. Specifically, the server combines the summaries and discussion results into a single data structure and sends it to the user's device. For example, the data is structured as summary_and_debate = {"summaries": summaries, "advantages": advantages, "disadvantages": disadvantages} and sent to the user's device as send_to_user_device(user_id, summary_and_debate). This allows the user to efficiently obtain important information and diverse opinions.

[1231] Example 1

[1232] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1233] In modern society, the telecommunications industry is changing rapidly, creating a need to quickly acquire the latest information and analyze it efficiently. However, processing huge amounts of information and analyzing it from various perspectives is not an easy task. With current methods, summarization and multifaceted analysis require time and effort, making it difficult for users to immediately grasp important information. For this reason, there is a need to develop a system that can automatically acquire, summarize, and analyze multifaceted information specific to the telecommunications industry and provide it quickly.

[1234] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1235] In this invention, the server includes means for acquiring the latest information from information sources specialized in the telecommunications industry, means for summarizing the acquired information using a generative AI model, means for setting up a virtual character and simulating a discussion using the generative AI model based on the summarized information, means for analyzing advantages and disadvantages from the results of the discussion simulation, and means for delivering the summarized information and discussion results to a user's device. This makes it possible to quickly acquire the latest information in the telecommunications industry and efficiently provide it to users through summaries and multifaceted analysis.

[1236] "Telecommunications industry" refers to industries and markets related to communications technology and services.

[1237] "Source" refers to any official or unofficial medium or platform that provides information on a particular subject.

[1238] A "generative AI model" refers to an algorithm or system that uses artificial intelligence technology to generate new information or content from data.

[1239] "Virtual character" refers to a fictional person or agent with a specific role or perspective.

[1240] "Simulating a discussion" refers to using a generative AI model to simulate a process in which virtual characters exchange opinions on a particular topic.

[1241] An "advantage" refers to an element or aspect that is beneficial in a particular situation or condition.

[1242] "Disadvantages" refer to elements or aspects that are unfavorable in a particular situation or condition.

[1243] "User Equipment" refers to any device or terminal used to receive and view information.

[1244] The present invention provides a system for efficiently acquiring, summarizing, and analyzing the latest information in the communications industry, and providing users with discussion results from multiple perspectives. Specific embodiments of the present invention will be described below.

[1245] Hardware and Software Configuration

[1246] The server is a data center server with high-performance processing power that processes API requests, analyzes data, and operates generative AI models. Specifically, it uses the following software and services:

[1247] API request processing: Web server software such as Apache or Nginx

[1248] Data format: JSON format parser

[1249] Generative AI models: OpenAI's GPT-3 and similar generative AI models

[1250] Database: A relational database such as MySQL or PostgreSQL

[1251] Program processing flow

[1252] Get news articles

[1253] The server obtains the latest information using the API of a source specialized in the telecommunications industry. The specific steps are as follows:

[1254] Sending API requests: The server periodically sends an HTTP request to the source's API endpoint to retrieve the latest information.

[1255] Receiving data: Receive data in JSON format from the API and save the data in a database on the server.

[1256] News article summaries

[1257] The server summarizes the acquired information using a generative AI model. The specific steps are as follows:

[1258] Text extraction: The server extracts the body text from the received JSON data.

[1259] Input to the generative AI model: The extracted text is passed to the generative AI model to generate a summary.

[1260] Example prompt sentence:

[1261] Summarize this article: The introduction of 5G, the next generation of communications technology, has significantly increased communication speeds. This...

[1262] Argument simulation

[1263] The server uses a generative AI model to set up virtual characters and simulate discussions based on the summarized information. The specific steps are as follows:

[1264] Setting virtual characters: The server sets up three virtual characters: "AI person," "technical person," and "marketing person."

[1265] Creating prompts for discussion generation: Generate prompts for each character and input them into the generative AI model.

[1266] Example prompt sentence:

[1267] AI Expert: Please comment on this article from an AI perspective. The introduction of 5G, the next generation communication technology, has significantly improved communication speeds.

[1268] Techie: What is the technological impact of this article? The introduction of 5G, the next generation communication technology, has significantly increased communication speeds.

[1269] Marketer: Based on this article, what marketing strategies can you think of? The introduction of 5G, the next generation communication technology, has significantly improved communication speeds.

[1270] Analysis of advantages and disadvantages

[1271] The server extracts advantages and disadvantages from the simulation results of the discussion. The specific steps are as follows:

[1272] Analysis of discussion results: The server analyzes the opinions of each generated character and identifies their advantages and disadvantages.

[1273] List creation: The extracted advantages and disadvantages are organized in a list format and saved on the server.

[1274] Summary and discussion results distribution

[1275] The server compiles the summarized information and the results of the discussion into a single data structure and delivers it to the user's terminal. The specific steps are as follows:

[1276] Data synthesis: Generate a data structure that summarizes the summary, discussion results, advantages and disadvantages.

[1277] Data transmission: Send data to the user's device via API or WebSocket, allowing the user to retrieve information efficiently.

[1278] According to the embodiment of the present invention, it is possible to quickly obtain the latest information in the communications industry and efficiently provide it to users through summaries and multifaceted analyses.

[1279] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1280] Step 1:

[1281] Get news articles

[1282] The server retrieves the latest news articles using the API of a telecommunications industry-specific information source. Specifically, the server periodically sends an HTTP request to the API endpoint and receives the latest news article data in JSON format. For example, it sends a request to the "GET / latest-news" endpoint and receives the following JSON response:

[1283] json

[1284] {

[1285] "title": "Next-generation communication technology improves communication speeds",

[1286] "content": "The introduction of 5G, the next-generation communications technology, has significantly improved communication speeds. This..."

[1287] }

[1288] Input: News site API endpoint

[1289] Output: News article data in JSON format

[1290] Step 2:

[1291] News article summaries

[1292] The server inputs the retrieved news article into a generative AI model to generate a summary. First, the server extracts the text from the received JSON data and passes that text to a generative AI model (e.g., OpenAI's GPT-3) to generate a summary. Specifically, the server inputs the following prompt sentence into the model:

[1293] prompt = "Summarize this article: The introduction of 5G, the next-generation communications technology, has dramatically increased communication speeds. This means..."

[1294] The generated summary is saved in the server for later processing.

[1295] Input: News article body text

[1296] Output: Summary text generated by the generative AI model

[1297] Step 3:

[1298] Argument simulation

[1299] The server uses a generative AI model to create virtual characters, each of which simulates a discussion based on a summary of a news article. First, the server creates virtual characters such as an "AI expert," an "engineer," and a "marketing expert." It then generates prompts for each character, such as:

[1300] AI Expert: Please comment on this article from an AI perspective. The introduction of 5G, the next generation communication technology, has significantly improved communication speeds.

[1301] Techie: What is the technological impact of this article? The introduction of 5G, the next generation communication technology, has significantly increased communication speeds.

[1302] Marketer: Based on this article, what marketing strategies can you think of? The introduction of 5G, the next generation communication technology, has significantly improved communication speeds.

[1303] The generated discussion content is stored on the server.

[1304] Input: Summary text and virtual character settings

[1305] Output: Discussion content of each character by the generative AI model

[1306] Step 4:

[1307] Analysis of advantages and disadvantages

[1308] The server extracts advantages and disadvantages based on the results of the simulated discussion. It analyzes the opinions of the generated virtual characters, identifies advantages and disadvantages from each point of view, and compiles them into a list. For example, it creates a list like this:

[1309] python

[1310] pros_and_cons = {

[1311] "Advantages": ["High speed", "New business opportunities"],

[1312] Disadvantages: High cost, infrastructure burden

[1313] }

[1314] This list is stored on the server.

[1315] Input: Discussion content of each character

[1316] Output: A list of advantages and disadvantages

[1317] Step 5:

[1318] Summary and discussion results distribution

[1319] The server compiles the summarized news articles and the results of the discussion into a single data structure and delivers it to the user's device. The data structure looks like this:

[1320] json

[1321] {

[1322] "summary": "The introduction of 5G, the next-generation communication technology, has significantly improved communication speeds.",

[1323] "pros_and_cons": {

[1324] "Advantages": ["High speed", "New business opportunities"],

[1325] Disadvantages: High cost, infrastructure burden

[1326] },

[1327] "discussion": {

[1328] "AI Personnel": "With improved communication speeds, it is highly likely that the speed at which AI analyzes data will also improve.",

[1329] "Technical Staff": "We expect new technology to improve stability.",

[1330] "Marketer": "High-speed communications will enable us to bring new services to market."

[1331] }

[1332] }

[1333] This data is sent to the user's device via API or WebSocket, allowing the user to access the information efficiently.

[1334] Input: Summary, discussion results, list of advantages and disadvantages

[1335] Output: Sending the integrated data to the user's terminal

[1336] (Application example 1)

[1337] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1338] Although systems exist that efficiently summarize the latest news in the telecommunications industry and enable discussion from multiple perspectives, there is a lack of means for users to quickly and visually understand the information. In particular, there is a need to provide visualized information using mobile information terminals and video display devices so that users can intuitively understand important information. This is expected to improve the efficiency of decision-making.

[1339] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1340] In this invention, the server includes means for acquiring the latest news articles from news sources specialized in the communications industry, means for summarizing the acquired news articles using a generative AI model, means for setting a virtual persona and simulating a discussion based on the summarized news articles using the generative AI model, means for analyzing the advantages and disadvantages from the results of the discussion simulation, means for delivering the summarized news articles and discussion results to a user's terminal, and means for visualizing the summaries and discussion results on a mobile information terminal or video display device used by the user, thereby enabling the user to quickly and intuitively understand important information.

[1341] A "news source specializing in the telecommunications industry" is an information provider that specializes in telecommunications technology, infrastructure, services, and related information.

[1342] A "breaking news story" is a story that contains timely, new information relevant to the communications industry.

[1343] A "generative AI model" is an artificial intelligence model that uses natural language processing to summarize and generate text data.

[1344] A "summary" is a shortened version of the original text that extracts the most important information.

[1345] A "virtual persona" is a character that is set up as a virtual being with a different perspective or role.

[1346] "Simulation" means recreating the process of actual discussion or exchange of opinions in a virtual environment.

[1347] "Advantages and disadvantages" refers to the advantages and disadvantages of a certain event or option.

[1348] A "mobile information terminal" refers to a portable information processing device such as a smartphone or tablet.

[1349] The term "video display device" refers to a device for displaying video, and includes, for example, a head-mounted display.

[1350] "Visualization" means representing information visually using shapes, graphs, text, etc.

[1351] "User terminal" refers to the device that the user ultimately uses to view information, and examples include smartphones and computers.

[1352] In this embodiment, technologies such as a server, a mobile information terminal, a video display device, and a generative AI model are used to realize efficient summaries of news articles specific to the telecommunications industry and discussion simulations from multiple perspectives.

[1353] System basic configuration and operation

[1354] Program Overview

[1355] The system retrieves the latest news articles from the telecommunications industry, uses a generative AI model to summarize and simulate discussions, and then provides the results to users.

[1356] Hardware and software used

[1357] Hardware: Mobile information terminals (smartphones and tablets), video display devices (head-mounted displays, etc.)

[1358] Software: Python (Flask framework), generative AI model (OpenAI GPT-4), news site API

[1359] Data processing and calculation

[1360] The server retrieves the latest news articles from the news site's API and receives the data in JSON format. Next, it uses a generative AI model to summarize the article text and simulates a discussion using virtual personas. Finally, it delivers the summary and discussion results to the user's device and visualizes them on the device.

[1361] Specific examples

[1362] For example, suppose you retrieve the following article data from a news site:

[1363] The introduction of 5G, the next-generation communications technology, has significantly improved communication speeds. This has...

[1364] In this case, the server extracts the body text from the article data and inputs the following prompt sentences into the generative AI model:

[1365] Summarize this article: The introduction of 5G, the next generation of communications technology, has significantly increased communication speeds. This...

[1366] The generative AI model generates a summary based on this prompt and then simulates the discussion from the perspective of virtual personas (e.g., "AI expert," "technical person," "marketing person"), analyzing the advantages and disadvantages of the simulated discussion and summarizing the results.

[1367] Summary and discussion visualization

[1368] The server delivers the summarized articles and discussion results to mobile information terminals and video display devices, where they are visualized, allowing users to efficiently understand the latest trends in the communications industry.

[1369] Thus, this invention provides a system that allows users to efficiently process and utilize information by acquiring data from specific news sources, summarizing using a generative AI model, simulating discussions using virtual personas, and visualizing the results.

[1370] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1371] Step 1:

[1372] The server retrieves the latest news articles from the API of a news source that specializes in the telecommunications industry. It sends a request to the news site's API endpoint and receives the latest article data in JSON format. The input is the API request from the server, and the output is the news article data in JSON format.

[1373] Step 2:

[1374] The server extracts the body text from the JSON data of the retrieved news article. Specifically, it extracts the value corresponding to the "content" key from the JSON data as text. The input is the JSON data of the news article, and the output is the text of the article body.

[1375] Step 3:

[1376] The server passes the extracted article text to a generative AI model to generate a summary. First, a prompt is created and input into the generative AI model. The generative AI model analyzes the text data and outputs a summarized sentence. The input is the article text and the prompt, and the output is the summarized article text.

[1377] Step 4:

[1378] The server uses the summarized text to simulate a discussion between virtual personas. It sets up virtual personas (e.g., "AI expert," "technical person," and "marketing person"), prepares prompts to generate discussions from each persona's perspective, and inputs these into the generative AI model. The model generates opinions from each persona's perspective. The inputs are the summary text and the prompts from the virtual personas, and the output is the discussion text generated for each persona.

[1379] Step 5:

[1380] The server extracts advantages and disadvantages from the generated argument text. It analyzes the opinions expressed in the argument and organizes the advantages and disadvantages in a list format. The input is the argument text, and the output is a list of advantages and disadvantages.

[1381] Step 6:

[1382] The server combines the summarized news article and the results of the discussion (a list of advantages and disadvantages) into a single data structure. Finally, it converts the data into a format that can be delivered to the user's device. The input is the summary text and the list of discussion results, and the output is the integrated data for the user's device.

[1383] Step 7:

[1384] The user's terminal visualizes the data received from the server. Specifically, the summary and discussion results are displayed on a mobile information terminal or video display device, and presented in a format that is intuitively easy for the user to understand. The input is the integrated data from the server, and the output is the visualized information.

[1385] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1386] The present invention is described below in detail in terms of an embodiment. The system includes an emotion engine that summarizes and analyzes news articles specific to the telecommunications industry, recognizes a user's emotions, and customizes the information accordingly. This allows users to efficiently obtain important information in a short amount of time, and the information is optimized to fit the user's emotional state.

[1387] System Configuration and Operation

[1388] 1. Retrieving news articles

[1389] The server retrieves the latest news articles from the API of a news site specializing in the telecommunications industry. Specifically, the server periodically sends requests to the news site's API endpoint and receives telecommunications industry-related article data in JSON format. For example, the server retrieves data from "https: / / news.example.com / api / telecommunications industry" and saves the content.

[1390] 2. News article summaries

[1391] The server extracts the text from the retrieved news articles. Specifically, it extracts the article content from the JSON data received by the server and saves it in text format. The extracted text is input into a generative AI model to generate a summary. The generative AI model's summarization function is used to condense long articles into a few paragraphs.

[1392] 3. Argument Simulation

[1393] The server uses a generative AI model to set up virtual personas, each of which simulates a discussion based on a summary of a news article. Specifically, the server sets up three personas: an "AI specialist," a "technical specialist," and a "marketing specialist," and uses the generative AI model to generate text for the discussion from each persona's perspective.

[1394] 4. Analysis of advantages and disadvantages

[1395] The server extracts and lists the advantages and disadvantages related to the news article based on the generated discussion results. It identifies advantages and disadvantages from the opinions of each persona and organizes them in a list format.

[1396] 5. User Emotion Recognition

[1397] The device is equipped with an emotion engine that recognizes emotions through the user's facial expressions, voice, or text input. Specifically, it uses the device's built-in camera, microphone, keyboard input, etc. to analyze the user's emotional state (e.g., joy, sadness, surprise, etc.) in real time.

[1398] 6. Emotional customization

[1399] The server customizes summarized news articles and discussion results based on the user's emotional data obtained from the emotion engine. Specifically, it provides information adapted to the user's emotional state, such as emphasizing the benefits if the user is expressing positive emotions, or explaining the disadvantages in detail if the user is expressing negative emotions.

[1400] 7. Distribution of summaries and discussion results

[1401] The server finally delivers the summarized news article and customized discussion results to the user's device. Specifically, by combining the summary and discussion results into a single data structure and sending it to the user's device, the user can efficiently obtain the key points of the news and various opinions.

[1402] Specific examples

[1403] Let's say you retrieve the following article data from a news site:

[1404] json

[1405] {

[1406] "title": "Next-generation communication technology improves communication speeds",

[1407] "content": "The introduction of 5G, the next-generation communications technology, has significantly improved communication speeds. This..."

[1408] }

[1409] In response, the server does the following:

[1410] 1. Sending an API request:

[1411] The server uses the news site's API to retrieve the latest articles.

[1412] 2. Extract and summarize article text:

[1413] The server extracts the main text from the acquired article data and generates a summary using a generative AI model.

[1414] 3. Argument simulation:

[1415] The server sets up virtual personas and uses generative AI models to simulate discussions from each persona's perspective.

[1416] 4. Analysis of advantages and disadvantages:

[1417] The server extracts advantages and disadvantages based on the discussion results and compiles them into a list.

[1418] 5. User Emotion Recognition:

[1419] The device uses the camera, microphone, and keyboard input to recognize the user's emotions.

[1420] 6. Emotional customization:

[1421] The server customizes how information is presented based on the user's emotional data.

[1422] 7. Summary and discussion distribution:

[1423] The server compiles the summaries and discussion results into a single data structure and sends it to the user's device, allowing the user to efficiently obtain important information and diverse opinions, while adapting the information to the user's emotional state.

[1424] In this way, the system of the present invention efficiently summarizes and analyzes the latest information in the telecommunications industry, and customizes it to the user's emotional state, allowing the user to obtain important information in a short amount of time.

[1425] The processing flow will be explained below.

[1426] Step 1:

[1427] The server retrieves the latest news articles from the API of a news site specializing in the telecommunications industry. Specifically, the server periodically sends requests to the news site's API endpoint and receives telecommunications industry-related article data in JSON format. For example, the server retrieves data from "https: / / news.example.com / api / telecommunications industry".

[1428] Step 2:

[1429] The server extracts the text from the retrieved news articles. Specifically, it extracts the content of the article from the JSON data received by the server and saves it in text format. For example, it extracts the text as follows: articles = response.json(), and article_texts = [article['content'] for article in articles].

[1430] Step 3:

[1431] The server inputs the extracted text into a generative AI model to generate a summary. Specifically, it uses the summarization function of the generative AI model to condense long articles into a few paragraphs. For example, it generates a summary using summarizer = pipeline("summarization") and summaries = [summarizer(text, max_length=130, min_length=30, do_sample=False) for text in article_texts].

[1432] Step 4:

[1433] The server sets up virtual personas and simulates a debate for each persona based on a summary of a news article. Specifically, it sets up three personas: an "AI specialist," a "technical specialist," and a "marketing specialist," and generates debate sentences from each persona's perspective using a generative AI model. For example, input data is prepared as follows: debate_inputs = [f"{persona}: {summary}" for persona in personas for summary in summaries].

[1434] Step 5:

[1435] The server uses a generative AI model to extract and list advantages and disadvantages from the simulated debate. Specifically, it identifies the advantages and disadvantages from the opinions of each persona and organizes them in a list format. For example, the analysis is performed as follows: advantages = [result for result in debate_outputs if "advantages" in result] and disadvantages = [result for result in debate_outputs if "disadvantages" in result].

[1436] Step 6:

[1437] The device is equipped with an emotion engine that recognizes emotions through the user's facial expressions, voice, or text input. Specifically, it analyzes the user's emotional state in real time using the device's built-in camera, microphone, keyboard input, etc. For example, it implements face recognition using a camera and voice emotion analysis using a microphone.

[1438] Step 7:

[1439] The server customizes summarized news articles and discussion results based on the user's emotional data obtained from the emotion engine. Specifically, it provides information adapted to the user's emotional state, such as emphasizing the benefits if the user is expressing positive emotions and detailing the disadvantages if the user is expressing negative emotions.

[1440] Step 8:

[1441] The server finally delivers the summarized news article and customized discussion results to the user's device. Specifically, the server combines the summary and discussion results into a single data structure and sends it to the user's device. For example, the data is structured as summary_and_debate = {"summaries": summaries, "advantages": advantages, "disadvantages": disadvantages} and sent to the user's device as send_to_user_device(user_id, summary_and_debate). As a result, the user can efficiently obtain important information and diverse opinions, and the information is adapted to the user's emotional state.

[1442] Example 2

[1443] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1444] In today's information society, it is important to efficiently obtain the latest news specific to a specific industry and summarize and analyze that information. However, it is not easy to extract the necessary information from the vast amount of information and provide it to users in an appropriate format. In addition, there is a lack of means to customize information based on user emotions, which poses a challenge in terms of how users can obtain the most appropriate information.

[1445] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring the latest information from information sources specialized in the telecommunications industry, means for summarizing the acquired information using a generative AI model, means for setting up a virtual person and simulating a discussion using the generative AI model based on the summarized information, means for analyzing the advantages and disadvantages from the results of the discussion simulation, means for recognizing the user's emotions, means for customizing the summarized information and discussion results according to the user's emotional state, and means for delivering the summarized information and discussion results to the user's terminal. This allows the user to efficiently acquire important information in a short amount of time, and the information can be optimized to suit the user's emotional state.

[1446] "Source" refers to a service or platform that provides up-to-date information or data on a particular industry or field.

[1447] A "generative AI model" refers to an artificial intelligence algorithm that uses machine learning techniques to summarize and analyze information from text and data.

[1448] "Virtual person" refers to the concept of creating a fictional character with a specific role or perspective, and generating discussions and opinions from that perspective.

[1449] "User emotion" refers to the psychological state or reaction that a user expresses through facial expression, voice, or text input.

[1450] "Customization" means the adjustment and optimization of information and service content to meet specific conditions and requirements.

[1451] "Terminal" refers to a device or hardware that allows a user to receive and view information, including, for example, a PC, smartphone, or tablet.

[1452] "API" stands for Application Programming Interface, and refers to an interface for exchanging information and functions between different software systems.

[1453] The present invention is best understood by describing an embodiment thereof as follows: The system of the present invention obtains up-to-date information from sources specialized in the telecommunications industry, efficiently summarizes and analyzes it, and provides customized information based on the user's emotional state.

[1454] Configuration and Operation

[1455] The server periodically obtains the latest information using the API of a source specialized in the telecommunications industry. Specifically, the server sends an HTTP GET request to the "information provider API" and receives data in JSON format. The received data is then analyzed using a parser and the obtained information is stored in a database.

[1456] Next, the server uses a generative AI model to summarize the information it has obtained. The server extracts the content from the JSON data and inputs the following prompt to the generative AI model:

[1457] "Summarize the following sentence: The introduction of 5G, the next generation communications technology, has significantly improved communication speeds. This has..."

[1458] The generated summary text is again stored in the database.

[1459] The server then sets up virtual people (personas) and simulates a discussion from each person's perspective using the generative AI model. The virtual people are set as "engineer," "marketer," and "AI person," and the following prompts are input to the generative AI model:

[1460] "Please comment on this summary as a technical expert."

[1461] The generated comments are stored in a database for each persona.

[1462] The server then analyzes the generated discussion results, extracting and listing the advantages and disadvantages. This not only provides a summary of the news, but also organizes opinions from multiple perspectives, making the advantages and disadvantages clear.

[1463] The device uses a camera, microphone, and keyboard input to recognize the user's emotions. Specifically, the device uses a built-in camera to recognize facial expressions, a microphone to analyze voice, and keyboard input to analyze text, thereby analyzing the user's emotional state in real time.

[1464] The server customizes the summarized information and discussion results based on the emotional data sent from the device. If the user is expressing positive emotions, the server emphasizes the benefits, and if the user is expressing negative emotions, it explains the disadvantages in detail.

[1465] Finally, the server delivers the summarized information and customized discussion results to the user's device. The summary and discussion results are combined into a single data structure and sent to the device, allowing the user to efficiently obtain important information in a short time, and the information is optimized for the user's emotional state.

[1466] Specific examples

[1467] For example, if you retrieve the following article data from the API:

[1468] "The introduction of 5G, the next generation communications technology, has significantly increased communication speeds. This has led to the telecommunications industry..."

[1469] The server summarizes this and generates the following text:

[1470] "With the introduction of 5G, communication speeds have improved."

[1471] Next, generate the following simulation prompt as the "Technician":

[1472] "Please comment on this summary as a technical expert."

[1473] The generated comment is, "The introduction of 5G technology has made high-speed communication possible and dramatically improved data transfer speeds."

[1474] As a result, the system of the present invention efficiently summarizes and analyzes the latest information in the telecommunications industry and customizes it to the user's emotional state, allowing the user to obtain important information in a short amount of time.

[1475] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1476] Step 1: Get news articles

[1477] The server retrieves the latest news articles using the API of a source specialized in the telecommunications industry. Specifically, the server periodically sends HTTP GET requests to the API of the information provider and receives data in JSON format. The input for this process is the API endpoint URL, and the output is news article data in JSON format. After receiving the data, the server parses the JSON data using a parser, extracts the required article data, and stores it in a database.

[1478] Step 2: Summarize the news article

[1479] The server extracts the main text from the saved news article data and inputs it into the generative AI model to generate a summary. Specifically, it extracts the content field from the article data and sends it to the generative AI model as a prompt. An example of a prompt is "Please summarize the following sentence: With the introduction of next-generation communication technology 5G, communication speeds have improved significantly. As a result..." The input for this process is the extracted main text, and the output is the summarized text. The generated summary is then saved back into the database.

[1480] Step 3: Simulating the discussion

[1481] The server sets up virtual characters and uses a generative AI model to simulate a discussion in which each virtual character engages in a discussion based on a summary of a news article. Specifically, it sets up three virtual characters: an "engineer," a "marketer," and an "AI technician," and generates discussions from each of their perspectives using a generative AI model. The input is the summary text and the settings of each virtual character, and the output is discussion text generated from each virtual character's perspective. As an example, it uses the prompt sentence, "Please comment on this summary as an engineer." The generated discussion text is stored in a database.

[1482] Step 4: Analyze the pros and cons

[1483] The server extracts and lists the advantages and disadvantages based on the generated discussion results. Specifically, it analyzes the discussion text using natural language processing to extract positive and negative elements. The input is the saved discussion text, and the output is a list of advantages and disadvantages. The extracted elements are saved in a database as the analysis results.

[1484] Step 5: Recognizing User Emotions

[1485] The device uses a camera, microphone, and keyboard input to recognize the user's emotions in real time. Specifically, it uses a camera to recognize facial expressions, a microphone to perform voice analysis, and analyzes text entered from the keyboard to estimate the user's emotions. The input is the user's facial expressions, voice, and text input, and the output is recognized emotion data. The emotion data is sent from the device to a server.

[1486] Step 6: Emotional customization

[1487] The server customizes summarized news articles and discussion results based on the emotion data sent from the device. Specifically, if the user expresses positive emotion, it emphasizes the benefits, and if the user expresses negative emotion, it explains the disadvantages in detail. The input for this process is the user's emotion data, summarized articles, and discussion results, and the output is customized information. The customized information is adjusted and edited according to the user's emotion.

[1488] Step 7: Summary and distribution of discussion results

[1489] The server finally delivers the customized summary and discussion results to the user's device. Specifically, it combines the summary and discussion results into a single data structure and sends it to the user's device. The input is the customized information, and the output is the information delivered to the user's device. The user receives this and can view the key points and diverse opinions of the news in a customized format.

[1490] (Application example 2)

[1491] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1492] In modern society, information in the telecommunications industry is extremely important, and it is necessary to efficiently grasp rapidly changing news. However, due to the wide variety of information, it is difficult for users to quickly obtain the information they need and accurately understand it. Furthermore, if the news content does not match the user's emotions or interests, there is a problem that the information will be less receptive, making it difficult to provide effective information.

[1493] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1494] In this invention, the server includes: means for acquiring the latest news articles from a news data source specialized for the telecommunications industry; means for summarizing the acquired news articles using a generative AI model; means for setting virtual roles and simulating a discussion based on the summarized news articles using the generative AI model; means for customizing the summarized news articles and discussion results based on the emotional state of the user using a terminal equipped with an emotion engine that recognizes the user's emotions; and means for delivering the summarized news articles and discussion results to the user's terminal. This allows users to efficiently acquire important information in a short amount of time, and the information can be provided in a form adapted to the user's emotional state.

[1495] A "server" is a computer system that provides data and functions to clients over a network.

[1496] A "news data source" is a digital source that provides up-to-date information on a particular subject.

[1497] "API" stands for Application Programming Interface, a set of rules and tools for exchanging information and functionality between different software applications.

[1498] A "generative AI model" is an algorithm that uses artificial intelligence to generate text and data, specifically a model that performs natural language processing.

[1499] A "summary" is a concise summary of original data or information.

[1500] A "virtual role" is a simulated character or persona with a particular perspective or opinion, used in simulations and discussions.

[1501] An "emotion engine" is a software module for recognizing and analyzing a user's emotional state.

[1502] "User's terminal" refers to any device used by a user, specifically a smartphone, computer, tablet, etc.

[1503] "Customization" refers to tailoring or modifying information or services to a particular user or situation.

[1504] This invention describes a system that efficiently collects and summarizes news articles specific to the telecommunications industry, and customizes them to fit the user's emotional state.

[1505] 1. System Overview

[1506] This system works in conjunction with a server and user devices. The server retrieves news specific to the telecommunications industry and summarizes it using a generative AI model. It then sets up virtual roles to simulate discussions based on news articles and analyzes the results. The user devices use an emotion engine to recognize the user's emotions, and the server uses this data to customize summaries and discussion results. The information is then delivered to the user devices.

[1507] 2. Hardware and Software Used

[1508] Hardware: Server computers, user devices (smartphones, computers, tablets, etc.), cameras, microphones

[1509] software:

[1510] Server: Node.js / Express.js, MongoDB, Axios (for API requests)

[1511] Generative AI model: OpenAI GPT-4

[1512] Emotion recognition: Affectiva SDK, Microsoft Azure Emotion API

[1513] 3. Processing Flow

[1514] News article retrieval and summarization

[1515] The server periodically retrieves the latest news articles from telecommunications industry news data sources via API, which are then summarized using OpenAI GPT-4, a generative AI model.

[1516] Virtual role setting and discussion simulation

[1517] The server creates virtual roles (e.g., technical person, marketing person) and uses a generative AI model to simulate each role discussing a news article, analyzing the resulting pros and cons.

[1518] Emotion Recognition and Customization

[1519] The user's device uses a camera and microphone to recognize the user's emotional state in real time. The emotion engine analyzes the data and sends it to the server. The server then customizes summarized news articles and discussion results based on the emotional data, providing information in a format that best suits the user's emotional state.

[1520] Summary and discussion results distribution

[1521] Finally, customized summaries and discussion results are delivered to users' devices, allowing them to obtain information efficiently and emotionally adapted.

[1522] 4. Specific Examples

[1523] Some examples of articles retrieved from news sites include:

[1524] Title: "Next-generation communication technology improves communication speeds"

[1525] Abstract: "The introduction of 5G, the next-generation communications technology, has significantly increased communication speeds. This has improved communication efficiency and led to the emergence of a variety of new services."

[1526] Prompt Sentence Examples

[1527] News article summary prompt:

[1528] Summarize this news article text:

[1529] "The introduction of 5G, the next-generation communications technology, has significantly increased communication speeds. This has improved communication efficiency and led to the emergence of a variety of new services. 5G networks are expected to be widely applicable, from homes to factories and agriculture."

[1530] Emotion customization prompt:

[1531] Emphasize positive aspects for happy emotions:

[1532] This allows the user to efficiently obtain important information in a short amount of time, and the information can be provided in a form that is adapted to the user's emotional state.

[1533] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1534] Step 1:

[1535] The server sends a request to the API endpoint of the news data source to retrieve the latest news articles specific to the telecommunications industry. The input is the API endpoint URL, and the output is the news article data (in JSON format). Specifically, the server sends an HTTP GET request to the API of the specified news data source.

[1536] Step 2:

[1537] The server extracts the text from the acquired news article data and generates a summary using a generative AI model. The input is the news article data, and the output is the summarized article text. Specifically, the server extracts the text portion of the article from the JSON of the news article data and sends it to the GPT-4 model along with a prompt to generate a summary.

[1538] Step 3:

[1539] The server sets up virtual roles and simulates discussions based on news articles using a generative AI model. The input is a summarized article text, and the output is the content of the discussions held by the virtual roles. Specifically, the server sets up multiple virtual roles (e.g., technical staff, marketing staff) and sends discussion prompts for each role to the generative AI model to generate the content of the discussions.

[1540] Step 4:

[1541] The server analyzes the generated discussion content and extracts the advantages and disadvantages. The input is the discussion content, and the output is a list of advantages and disadvantages. Specifically, the server uses the generative AI model to analyze the discussion content and organize the identified advantages and disadvantages in list form.

[1542] Step 5:

[1543] The device recognizes the user's emotional state in real time using a camera, microphone, and keyboard input. The input is the user's facial expression, voice, and text input, and the output is the user's emotional data. Specifically, the device uses an emotion engine to analyze the user's input data and identify the user's emotional state.

[1544] Step 6:

[1545] The server customizes summarized news articles and discussion results based on the user's emotional data. The input is the summarized news article, the discussion content, and the user's emotional data, and the output is customized news articles and discussion results. Specifically, the server analyzes the user's emotional state and edits the information to highlight advantages for positive emotions and to explain disadvantages in detail for negative emotions.

[1546] Step 7:

[1547] The server delivers the customized summary and discussion results to the user's device. The input is the customized news article and discussion content, and the output is the information sent to the user's device. Specifically, the server compiles the edited information into a single data structure and sends it to the user's device.

[1548] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1549] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1550] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1551] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1552] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1553] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1554] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1555] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1556] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1557] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1558] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1559] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1560] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1561] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1562] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1563] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1564] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1565] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1566] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1567] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1568] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1569] The following is further disclosed regarding the above embodiment.

[1570] (Claim 1)

[1571] A means to obtain the latest news articles from news sources specializing in the telecommunications industry, and

[1572] A means for summarizing the retrieved news articles using a generative AI model; and

[1573] means for establishing a virtual persona and simulating a discussion using a generative AI model based on the summarized news article;

[1574] A means for analyzing the advantages and disadvantages from the simulation results of the above discussion;

[1575] means for delivering the summarized news articles and discussion results to a user's terminal;

[1576] A system including:

[1577] (Claim 2)

[1578] 2. The system according to claim 1, wherein the news article acquisition means acquires data via an API of a news site.

[1579] (Claim 3)

[1580] 2. The system according to claim 1, wherein the means for simulating a discussion has a plurality of virtual personas, each of which generates opinions from a different perspective.

[1581] "Example 1"

[1582] (Claim 1)

[1583] A means of obtaining up-to-date information from sources specializing in the telecommunications industry;

[1584] a means for summarizing the obtained information using a generative AI model;

[1585] means for setting up a virtual character and simulating a discussion using a generative AI model based on the summarized information;

[1586] A means for analyzing advantages and disadvantages from the simulation results of the above discussion;

[1587] means for delivering the summarized information and discussion results to a user's device;

[1588] A system including:

[1589] (Claim 2)

[1590] 2. The system according to claim 1, wherein the information acquisition means acquires data via an API of an information providing site.

[1591] (Claim 3)

[1592] 2. The system according to claim 1, wherein the means for simulating a discussion has a plurality of virtual characters, each of which generates opinions from a different viewpoint.

[1593] "Application Example 1"

[1594] (Claim 1)

[1595] A means to obtain the latest news articles from news sources specializing in the telecommunications industry, and

[1596] A means for summarizing the retrieved news articles using a generative AI model; and

[1597] means for establishing a virtual persona and simulating a discussion using a generative AI model based on the summarized news article;

[1598] A means for analyzing the advantages and disadvantages from the simulation results of the above discussion;

[1599] means for delivering the summarized news articles and discussion results to a user's terminal;

[1600] a means for visualizing the summary and discussion results on a mobile information terminal or a video display device used by a user;

[1601] A system including:

[1602] (Claim 2)

[1603] 2. The system according to claim 1, wherein the news article acquisition means acquires data via an API of a news site.

[1604] (Claim 3)

[1605] 2. The system according to claim 1, wherein the means for simulating a discussion has a plurality of virtual personas, each of which generates opinions from a different perspective.

[1606] "Example 2: Combining Emotion Engines"

[1607] (Claim 1)

[1608] A means of obtaining up-to-date information from sources specializing in the telecommunications industry;

[1609] a means for summarizing the obtained information using a generative AI model;

[1610] A means for setting up a virtual person and simulating a discussion using a generative AI model based on the summarized information;

[1611] A means for analyzing the advantages and disadvantages from the simulation results of the above discussion;

[1612] means for recognizing a user's emotion;

[1613] means for customizing summarized information and discussion results according to the emotional state of the user;

[1614] means for delivering the summarized information and discussion results to a user's terminal;

[1615] A system including:

[1616] (Claim 2)

[1617] 2. The system according to claim 1, wherein the means for acquiring the information acquires data via an API of an information providing service.

[1618] (Claim 3)

[1619] 2. The system according to claim 1, wherein the means for simulating a discussion has a plurality of virtual characters, each of which generates opinions from a different viewpoint.

[1620] "Application example 2 when combining emotion engines"

[1621] (Claim 1)

[1622] A means to retrieve the latest news articles from news data sources specialized in the telecommunications industry, and

[1623] A means for summarizing the retrieved news articles using a generative AI model; and

[1624] means for setting virtual roles and simulating a discussion using a generative AI model based on the summarized news article;

[1625] A means for analyzing the advantages and disadvantages from the simulation results of the above discussion;

[1626] means for customizing summarized news articles and discussion results based on the emotional state of the user using a terminal equipped with an emotion engine that recognizes the user's emotions;

[1627] means for delivering the summarized news articles and discussion results to a user's terminal;

[1628] A system including:

[1629] (Claim 2)

[1630] 2. The system according to claim 1, wherein the news article acquisition means acquires data via an API of a news data site.

[1631] (Claim 3)

[1632] 2. The system according to claim 1, wherein the means for simulating a discussion has a plurality of virtual roles, each of which generates opinions from a different viewpoint. [Explanation of symbols]

[1633] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means to obtain the latest news articles from news sources specializing in the telecommunications industry, and A means for summarizing the retrieved news articles using a generative AI model; and means for establishing a virtual persona and simulating a discussion using a generative AI model based on the summarized news article; A means for analyzing the advantages and disadvantages from the simulation results of the above discussion; means for delivering the summarized news articles and discussion results to a user's terminal; A system including:

2. 2. The system according to claim 1, wherein the news article acquisition means acquires data via an API of a news site.

3. 2. The system according to claim 1, wherein the means for simulating a discussion has a plurality of virtual personas, each of which generates opinions from a different viewpoint.

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