System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving a prompt from a user; means for generating a query from the prompt; means for selecting a relevant advertisement based on the query; means for displaying the advertisement on a device until a final AI for the generated query is generated; means for collecting and analyzing information from a plurality of sources; and means for displaying the final AI on the device while hiding the advertisement.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] When using chat-based search engines such as Bing, there is a problem that it takes time for search results to be displayed, causing users to wait. Conventional search-based advertising mainly consists of text ads, and lacks a mechanism for displaying highly appealing ads such as image ads or video ads. Furthermore, operating a generation AI is expensive, and how to cover this cost is an issue. Therefore, in order to cover the cost of using generation AI, a system is needed that effectively utilizes the waiting time for search results and provides users with relevant ads. [Means for solving the problem]

[0005] The present invention is a system that includes a means for receiving a prompt from a user and generating a search query from the prompt, a means for selecting relevant advertisements based on the search query, a means for displaying advertisements on a terminal until a final AI output for the generated search query is generated, a means for collecting and analyzing information from multiple data sources, and a means for displaying the final AI output on a terminal while simultaneously hiding the advertisements. This system displays relevant advertisements while users wait for search results, allowing the cost of using the AI ​​to be covered by advertising revenue. Furthermore, the selected advertisements include not only text advertisements but also image and video advertisements, increasing their appeal to users. This allows for the creation of an environment that continuously provides advanced functionality while covering token costs with advertising revenue.

[0006] A "prompt" is the text or question a user enters into a system to search or query.

[0007] A "search query" is a keyword or phrase generated based on a prompt to search for specific information.

[0008] "Advertising" refers to information that introduces products and services to users and encourages them to purchase or use them.

[0009] "Generative AI" refers to artificial intelligence systems that learn from large datasets and generate appropriate responses to user prompts.

[0010] "Token cost" refers to the cost of the computing resources and processing power required to operate the generation AI.

[0011] "Data sources" refer to resources such as websites and databases from which information is collected.

[0012] "Analysis" refers to the process of processing collected data and converting it into meaningful information.

[0013] "Final output" refers to the response or answer that the generative AI generates based on the prompts.

[0014] "Terminal" refers to the device (e.g., PC, smartphone, tablet) that a user uses to access the system. [Brief explanation of the drawings]

[0015] [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

[0016] 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.

[0017] First, the terms used in the following description will be explained.

[0018] 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).

[0019] 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.

[0020] 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.

[0021] 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.

[0022] 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."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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."

[0036] This invention is a system that generates a search query based on a prompt input by a user and displays related advertisements. The advertisements are displayed while the AI ​​is waiting to generate the final output. When the final output is displayed on the device, the advertisements are hidden.

[0037] System program and processing description

[0038] 1. Receiving a prompt

[0039] A user enters a search prompt into a device, for example, "Tell me reviews of the latest smartphones."

[0040] 2. Generating a search query

[0041] The server generates a search query based on the prompt received from the user, for example, "latest smartphone reviews."

[0042] 3. Ad selection

[0043] The server selects advertisements from the database that are relevant to the generated search query, for example, "Smartphone Ad 1," "Smartphone Ad 2," and "Smartphone Ad 3."

[0044] 4. Display of advertisements

[0045] The device will display the selected ads, either randomly or sequentially, until the AI ​​generates the search results.

[0046] 5. Data Collection and Analysis

[0047] The server collects information from multiple sources based on the search query and analyzes this data, for example, by collecting and analyzing reviews and user ratings of the latest smartphones.

[0048] 6. Generative AI Generates Output

[0049] Based on the data collected by the server, a generative AI (e.g., a large-scale language model) generates a response to the user prompt, for example, "Reviews of the latest smartphones give high marks to the new model from company A."

[0050] 7. Display AI results and hide ads

[0051] The device displays the generated final output and simultaneously hides the advertisement. For example, it displays the output "The latest smartphone reviews have given high marks to the new model from company A," and then removes the advertisement from the screen.

[0052] Specific examples

[0053] 1. A user types the search prompt "What are the latest smartphone reviews?"

[0054] 2. The server receives the prompt and translates it into the search query "latest smartphone reviews."

[0055] 3. The server selects "Smartphone Ad 1," "Smartphone Ad 2," and "Smartphone Ad 3" based on the search query.

[0056] 4. The device displays the ads and shows them to the user while the generation AI generates the final output.

[0057] 5. The server collects and analyzes data related to "Latest Smartphone Reviews."

[0058] 6. The server uses the AI ​​to generate a response such as, "Company A's new model has received high marks in reviews of the latest smartphones."

[0059] 7. The device will display the final output and hide the ads at the same time.

[0060] These steps allow users to view relevant ads during the waiting time and then receive a response from the AI. This system uses advertising revenue to cover the operating costs of the AI, ensuring sustainable service provision.

[0061] The processing flow will be explained below.

[0062] Step 1:

[0063] A user inputs a search prompt into the device, for example, "Tell me reviews of the latest smartphones." The input prompt is sent to the server.

[0064] Step 2:

[0065] The server analyzes the received prompt and generates an appropriate search query based on the prompt content. For example, the prompt "Tell me reviews of the latest smartphones" is converted into the search query "Latest smartphone reviews."

[0066] Step 3:

[0067] The server selects relevant ads based on the search query. It retrieves ads related to the search query from the database and creates an appropriate ad list. For example, "Smartphone Ad 1," "Smartphone Ad 2," and "Smartphone Ad 3" are selected.

[0068] Step 4:

[0069] While the device is waiting for the final output from the AI ​​to be generated, the selected advertisements will be displayed. The advertisements will be displayed randomly or in order. For example, "Smartphone Ad 1," "Smartphone Ad 2," and "Smartphone Ad 3" will be displayed in sequence.

[0070] Step 5:

[0071] The server collects information from multiple sources based on the search query, for example, by using web scraping techniques to gather relevant reviews and user ratings.

[0072] Step 6:

[0073] The server analyzes the collected information, extracts the most relevant information from the collected data, and organizes the analysis results.

[0074] Step 7:

[0075] The server uses generative AI to generate the final output. Based on the analysis results, it generates an appropriate answer to the user's prompt. For example, it might generate a response like, "Reviews of the latest smartphones give high marks to the new model from company A."

[0076] Step 8:

[0077] The device displays the final output of the AI ​​generation. At the same time as showing the generated response to the user, the displayed advertisement is hidden. For example, a message such as "Company A's new model has received high praise in reviews of the latest smartphones" is displayed on the screen, and the advertisement disappears.

[0078] Through these steps, users can view relevant ads during the waiting time and then receive a response from the AI. This system uses advertising revenue to cover the operating costs of the AI, ensuring sustainable service provision.

[0079] Example 1

[0080] 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."

[0081] In conventional systems, if it takes a long time to generate search results, the user experience is degraded because nothing is displayed during the waiting time.In addition, the high operating costs of the generation AI make it difficult to provide a sustainable service.

[0082] 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.

[0083] In this invention, the server includes means for receiving a prompt from a user, means for generating a search query from the prompt, means for selecting relevant content based on the search query, means for displaying advertisements on the terminal until the final output of the generation AI for the generated search query is generated, means for collecting and analyzing information from multiple data sources, and means for displaying the final output of the generation AI on the terminal while simultaneously hiding advertisements. This makes it possible to improve the user experience while using advertising revenue to cover the operating costs of the generation AI.

[0084] "User" means an individual or entity who operates a terminal to enter prompts and obtain information using the system.

[0085] A "prompt" is a question or instruction that a user enters into a system.

[0086] "Search query" refers to a sentence or phrase used in a search that is generated based on a user prompt.

[0087] "Generative AI" refers to artificial intelligence models that generate natural language responses based on input data.

[0088] "Device" refers to the device (e.g., smartphone, computer, tablet) that a user uses to enter prompts and view generated AI responses and advertisements.

[0089] "Advertisement" means any text, image or video content displayed to a User for commercial purposes.

[0090] "Data Source" refers to the website, API, database, or other source used to collect information.

[0091] "Analysis" refers to the process of processing and analyzing collected data.

[0092] "Revenue" refers to the economic benefits derived from displaying advertisements.

[0093] The system of this invention allows users to input a prompt, retrieve related information based on it, and wait for the output of the AI ​​while displaying an advertisement. Specifically, the user, terminal, and server each play their respective roles to realize the overall process.

[0094] First, the user inputs a prompt such as "Tell me a review of the latest smartphone" into the device. The device detects this input and sends the prompt to the server using a communication method, primarily an internet connection.

[0095] The server receives the prompt and generates an appropriate search query using natural language processing (NLP) techniques. Specifically, it uses text analysis libraries (e.g., SpaCy, NLTK). For example, the prompt "Tell me reviews of the latest smartphones" is converted into the search query "Latest smartphone reviews."

[0096] The server then selects relevant ads from a pre-built ad database based on the search query. Each ad is associated with a specific keyword. For example, ads related to keywords like "smartphone" and "review" are selected.

[0097] The selected ad is sent to the device, which then displays it to the user. Ads are displayed randomly or sequentially, and are realized using UI components for displaying ads. Specifically, React and Vue.js libraries are used on the front end.

[0098] Meanwhile, the server collects information from multiple data sources (websites, APIs, databases, etc.) based on the search query. The collected data is processed using analytical libraries (e.g., Pandas, NumPy). For example, reviews and user ratings of the latest smartphones are collected and analyzed.

[0099] The server uses a generative AI model (e.g., GPT-3) based on the analyzed data to generate a response to the user prompt, such as "Company A's new model has received high marks in reviews of the latest smartphones."

[0100] Finally, the generated response is sent to the device, which displays it to the user. At the same time, the displayed ad is hidden. The UI components are updated to hide the ad.

[0101] This system allows users to view relevant ads while they wait, and then receive useful responses from the AI. Advertising revenue covers the AI's operating costs, enabling the service to be provided sustainably.

[0102] As a concrete example, let's assume that you input a prompt such as "Please tell me reviews of the latest smartphones." In response to this prompt, the server generates a search query for "latest smartphone reviews," selects relevant advertisements, and finally generates a response such as "Company A's new model is highly rated in reviews of the latest smartphones."

[0103] In this way, a mechanism is realized in which users can efficiently obtain information through the system while also compensating for operational costs by viewing advertisements.

[0104] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0105] Step 1:

[0106] Receiving prompts

[0107] The user inputs a prompt sentence into the terminal, such as "Tell me a review of the latest smartphone."

[0108] The terminal captures the prompt text entered and sends it to the server in its raw form.

[0109] Input: The prompt text entered by the user (e.g., "Tell me your review of the latest smartphones")

[0110] Output: Prompt sent from terminal to server

[0111] Step 2:

[0112] Generating a search query

[0113] The server parses the received prompt and converts it into an appropriate search query using natural language processing (NLP) techniques and parsing libraries (e.g., SpaCy, NLTK).

[0114] Input: Prompt sent from the terminal

[0115] Data processing: Using natural language processing technology, we analyze prompts and generate search queries (e.g., "latest smartphone reviews")

[0116] Output: Generated search query

[0117] Step 3:

[0118] Ad selection

[0119] The server selects relevant advertisements from an advertisement database based on the generated search query, filtering advertisements that match keywords in the query.

[0120] Input: Generated search query

[0121] Data processing: Filter and select advertisements from the advertisement database using related keywords (e.g., "Smartphone Ad 1," "Smartphone Ad 2," "Smartphone Ad 3")

[0122] Output: Selected ad list

[0123] Step 4:

[0124] Displaying ads

[0125] The device receives the advertising data sent from the server and displays it to the user. Front-end UI components (e.g., React, Vue.js) are used to display the advertisements.

[0126] Input: Ad list sent from the server

[0127] Specific operation: Advertisements are displayed randomly or sequentially on the user's device screen.

[0128] Output: Ad displayed on the user's device

[0129] Step 5:

[0130] Data collection and analysis

[0131] Based on the search query, the server collects relevant information from multiple data sources, including websites, APIs, databases, etc. The collected data is processed using analytical libraries (e.g., Pandas, NumPy).

[0132] Input: Generated search query

[0133] Data processing: Collect information from multiple sources and process and analyze the data using analytics libraries (e.g., reviews and user ratings of the latest smartphones).

[0134] Output: Analyzed data

[0135] Step 6:

[0136] Generative AI generates output

[0137] The server uses a generative AI model (e.g., GPT-3) based on the analyzed data to generate a response to the prompt.

[0138] Input: Parsed data, prompts for the generative AI model

[0139] Data processing: The generative AI model generates a response based on the prompt and the analyzed data (e.g., "Company A's new model is highly rated in reviews of the latest smartphones").

[0140] Output: The generated response text

[0141] Step 7:

[0142] Display AI results and hide ads

[0143] The device receives the generated response from the server and displays it to the user, simultaneously hiding the displayed ad, updating the UI components to hide the ad area, and displaying the response text.

[0144] Input: Generated response text

[0145] Specific operation: The advertisement display area is hidden and the response text is displayed on the user's device screen.

[0146] Output: The generated AI's response text displayed on the user's device

[0147] This process allows users to view relevant advertisements while they wait, and then obtain useful information from the AI. The advertising revenue can then be used to cover the operational costs of the AI.

[0148] (Application example 1)

[0149] 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."

[0150] A means of providing useful information to users during the waiting time between when they input a prompt and when the generation AI generates the final output is required. A mechanism is also required to effectively utilize revenue from displaying advertisements to cover the operational costs of the generation AI. Furthermore, it is also necessary to provide additional information related to the generated content in a timely manner.

[0151] 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.

[0152] In this invention, the server includes means for receiving a prompt from a user, means for generating a search query from the prompt, and means for selecting a relevant advertisement based on the search query. This makes it possible to display an appropriate advertisement between the time the user inputs the prompt and the time the generation AI generates the final output, and to display related data when the advertisement ends.

[0153] A "prompt" is a question or request that a user enters into a system.

[0154] A "search query" refers to a query to a search engine or database that is generated based on a user prompt.

[0155] "Advertisement" refers to content in the form of text, images, or video that introduces products or services to users.

[0156] "Generative AI" refers to artificial intelligence that provides a final output that is analyzed and generated based on user prompts.

[0157] "Data source" refers to the source of information, such as a website or database, from which information is collected.

[0158] "Terminal" refers to the device (e.g., smartphone, computer) that a user uses to enter prompts and receive output.

[0159] "Analysis" refers to the process of analyzing collected data and extracting information that meets the user's requirements.

[0160] "Hidden" refers to removing the advertisement from the device screen so that it is no longer visually perceptible to the user.

[0161] "Revenue" refers to the economic benefits obtained from displaying advertisements.

[0162] "Token cost" refers to the costs associated with the computing resources and data processing required to operate the generating AI.

[0163] "Additional display" refers to displaying supplemental information related to the generated content to provide the user with such information.

[0164] This invention is a system that generates search queries based on prompts entered by users, displays relevant ads, and provides the final output using a generative AI. Part of the system runs on a device such as a smartphone, while the other part runs on a server.

[0165] Hardware and software used

[0166] Hardware: Smartphones, computers

[0167] Software: Python 3, ad management software, generative AI models (e.g., GPT-3)

[0168] DETAILED DESCRIPTION OF THE EMBODIMENTS

[0169] 1. Receiving a prompt

[0170] The user types a prompt into the terminal. This prompt contains the user's question or request. For example, "What are the latest movie reviews?"

[0171] 2. Generating a search query

[0172] The device sends the input prompt to the server, which analyzes the prompt and generates an appropriate search query that is optimized for the user's needs, such as "latest movie reviews."

[0173] 3. Advertisement selection and display

[0174] Based on the generated search query, the server selects relevant ads from an advertising database. These ads can be in the form of text, images, or videos. The device displays the selected ads to the user while the generation AI generates the final output.

[0175] 4. Data Collection and Analysis

[0176] The server collects and analyzes the necessary information from multiple data sources based on the search query. This analysis process uses natural language processing technology to handle large amounts of data. Specific systems retrieve information by making database queries or API calls.

[0177] 5. Generative AI Generates Output

[0178] Based on the collected data and analysis results, the server uses a generative AI model to generate the final output in response to the user's prompt. For example, if the prompt is "Tell me the latest movie reviews," the output generated will be "Movie X is highly rated in the latest movie reviews."

[0179] 6. Display generated AI output and hide ads

[0180] The device displays the final generated output to the user while hiding the ads, and adds relevant data to the generated content, ensuring fast and accurate information for the user while also ensuring revenue from the ads displayed.

[0181] Example

[0182] If a user inputs the prompt "What is the recommended drama this month?", the system generates a search query "This month's recommended drama review" and displays advertisements such as "Products related to drama B are on sale!". While the advertisement is displayed, the server collects related data, and the generation AI generates the final output "This month's recommended drama is drama Y!", which is displayed on the device while hiding the advertisement.

[0183] Example prompt statement

[0184] "Tell me the latest movie reviews"

[0185] What's your recommended drama this month?

[0186] This embodiment allows users to efficiently obtain the information they expect, and advertising revenue can be used to cover the costs of operating the system.

[0187] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0188] Step 1:

[0189] The user enters the prompt

[0190] The user inputs a prompt into the terminal. The input prompt is a sentence containing the user's question or request. For example, the user might input "Tell me the latest movie reviews."

[0191] Type: "What's the latest movie review?"

[0192] Output: The prompt is typed into the terminal.

[0193] Step 2:

[0194] The terminal sends a prompt to the server

[0195] The terminal sends the entered prompt to the server, a process that occurs over the network.

[0196] Input: The prompt entered by the user

[0197] Output: A prompt is sent to the server

[0198] Step 3:

[0199] The server generates a search query from the prompt

[0200] The server analyzes the received prompt and generates a relevant search query, for example, "What are the latest movie reviews?"

[0201] Input: The prompt sent by the user ("What's the latest movie review?")

[0202] Output: Generated search query ("latest movie reviews")

[0203] Step 4:

[0204] The server selects relevant ads based on the search query.

[0205] The server selects relevant advertisements from the advertisement database based on the generated search query. The selected advertisements are then displayed on the device, so in this step the most relevant advertisement is selected. For example, for "latest movie reviews," movie-related product advertisements are selected.

[0206] Input: Search query ("Latest movie reviews")

[0207] Output: Selected advertisement ("Movie-related product advertisement")

[0208] Step 5:

[0209] Display ads on your device

[0210] The device displays selected advertisements sent from the server, which can be in image or video format.

[0211] Input: Ad sent by server

[0212] Output: Ads are displayed on the device

[0213] Step 6:

[0214] The server collects and analyzes information from multiple data sources.

[0215] Based on the search query, the server collects and analyzes relevant information from websites and databases. The collected data is then analyzed using natural language processing techniques. For example, the server collects and analyzes the latest movie reviews from a movie review site.

[0216] Input: Search query ("Latest movie reviews")

[0217] Output: Analyzed data (latest movie reviews)

[0218] Step 7:

[0219] Generative AI generates the final output

[0220] The server uses the parsed data to run a generative AI model and generate the final output in response to a user prompt, for example, "What are the latest movie reviews?", generating a response such as "Movie X is highly rated in the latest movie reviews."

[0221] Input: Parsed data

[0222] Output: Final output ("Movie X is highly rated in the latest movie reviews")

[0223] Step 8:

[0224] Display the final output on your device while hiding ads

[0225] The device displays the final output received from the server and simultaneously hides the advertisement that was being displayed. For example, it displays the output "Movie X is highly rated in the latest movie reviews" and removes the advertisement from the screen.

[0226] Input: Final output, currently displayed ad

[0227] Output: Show final output to user, hide ads

[0228] Step 9:

[0229] Viewing Additional Information

[0230] The device will display additional information related to the generated content in a timely manner, with the additional information primarily related to the final output.

[0231] Input: Data related to the final output

[0232] Output: Display additional information

[0233] 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.

[0234] The present invention is a system that generates search queries in response to user prompts and displays relevant advertisements. The system also incorporates an emotion engine that recognizes the user's emotions. The emotion engine identifies emotions from the user's prompts and adjusts the display of advertisements and the output of the generation AI based on the emotions.

[0235] System program and processing description

[0236] 1. Receiving a prompt

[0237] A user inputs a search prompt into the device, for example, "Tell me reviews of the latest smartphones." The input prompt is sent to the server.

[0238] 2. Emotional Recognition

[0239] The server analyzes the received prompt and uses an emotion engine to recognize the user's emotion, for example, emotions such as "excited," "excited," and "frustrated" are identified.

[0240] 3. Generating search queries

[0241] The server generates a search query based on the prompt and the recognized sentiment, for example, "latest smartphone reviews."

[0242] 4. Ad selection

[0243] The server selects relevant advertisements based on the generated search query and emotion. It retrieves advertisements that match the search query and emotion from the database and creates an appropriate advertisement list. For example, for a user in an "excited" state, "new product campaign advertisements" are selected.

[0244] 5. Display of advertisements

[0245] The device displays selected ads until the final output is generated by the AI. The ads are displayed randomly or in order. The display time and content of the ads are also adjusted depending on the user's emotions. For example, a "new product campaign ad" is displayed longer to an excited user.

[0246] 6. Data Collection and Analysis

[0247] The server collects information from multiple sources based on the search query, for example, by using web scraping techniques to gather relevant reviews and user ratings.

[0248] 7. Generative AI Generates Output

[0249] The server uses generative AI to generate the final output based on the collected information and the recognized emotion. For example, it generates a response such as, "Reviews of the latest smartphones give high marks to the new model from company A." If the emotion is "unhappy," it also details specific issues and areas for improvement.

[0250] 8. Display AI results and hide ads

[0251] The device displays the final output of the AI ​​generation. At the same time as showing the generated response to the user, the displayed advertisement is hidden. For example, a message such as "Company A's new model has received high praise in reviews of the latest smartphones" is displayed on the screen, and the advertisement disappears.

[0252] Specific examples

[0253] 1. A user types the search prompt "What are the latest smartphone reviews?"

[0254] 2. The server receives the prompt and uses the emotion engine to recognize the user's emotion as "excited."

[0255] 3. The server generates the search query "latest smartphone reviews" based on the prompt and the perceived sentiment.

[0256] 4. The server selects a "new product campaign ad" based on the search query and "excitement."

[0257] 5. The device displays the advertisement and shows the "New Product Campaign Ad" to the user until the generation AI generates the final output.

[0258] 6. The server collects and analyzes data related to "Latest Smartphone Reviews."

[0259] 7. The server uses the AI ​​to generate a response such as, "Company A's new model has received high marks in reviews of the latest smartphones."

[0260] 8. The device will display the final output and hide the ads at the same time.

[0261] These steps allow users to view relevant ads while they wait, and then receive a response from the generation AI. Furthermore, the emotion engine provides ad displays and responses based on the user's emotions, creating a more personalized experience. This system uses advertising revenue to cover the operating costs of the generation AI, ensuring sustainable service provision.

[0262] The processing flow will be explained below.

[0263] Step 1:

[0264] A user inputs a search prompt into the device, for example, "Tell me reviews of the latest smartphones." The input prompt is sent to the server.

[0265] Step 2:

[0266] The server analyzes the received prompt and uses an emotion engine to recognize the user's emotion, for example, emotions such as "excited" or "frustrated" are identified from the prompt.

[0267] Step 3:

[0268] The server generates a search query based on the prompt and the recognized sentiment. For example, the prompt "Tell me reviews of the latest smartphones" is converted into the search query "Latest smartphone reviews."

[0269] Step 4:

[0270] The server selects relevant advertisements based on the search query and the recognized emotion. For example, a user in an "excited" state might be shown a "new product campaign advertisement," while a user in a "dissatisfied" state might be shown a "specific problem-solving advertisement."

[0271] Step 5:

[0272] The device will display selected ads until the final output is generated by the AI. The ads will be displayed randomly or in order. For example, a "new product campaign ad" will be displayed longer to excited users.

[0273] Step 6:

[0274] The server collects information from multiple data sources based on the search query, for example, by using web scraping techniques to gather reviews and user ratings of the latest smartphones.

[0275] Step 7:

[0276] The server analyzes the collected information, for example, by processing the collected reviews and ratings data and extracting particularly important information.

[0277] Step 8:

[0278] The server uses generative AI to generate the final output. Based on the analysis results and the recognized sentiment, it generates an appropriate response to the user's prompt. For example, the response might be, "Reviews of the latest smartphones give high marks to the new model from company A."

[0279] Step 9:

[0280] The device displays the final output of the AI ​​generation. At the same time as showing the generated response to the user, the displayed advertisement is hidden. For example, a message such as "Company A's new model has received high praise in reviews of the latest smartphones" is displayed on the screen, and the advertisement disappears.

[0281] Through these steps, users can view relevant ads while waiting and then receive a response from the AI. This system uses advertising revenue to cover the operating costs of the AI, ensuring sustainable service provision. The emotion engine provides ad display and responses based on the user's emotions, enabling a more personalized experience.

[0282] Example 2

[0283] 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."

[0284] Previous systems simply generated search queries based on user prompts and displayed relevant ads. This resulted in uniform ad display without considering user sentiment, making it difficult to achieve a personalized experience. Furthermore, effective ad display was not possible during the waiting time for the AI ​​to generate a response based on the search query, making it difficult to optimize advertising revenue.

[0285] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0286] In this invention, the server includes means for [using an emotion engine to analyze prompts and identify emotions], means for [generating search queries based on the prompts and the recognized emotions], and means for [selecting relevant advertisements based on the search queries and emotions]. This enables personalized advertisement display that takes user emotions into consideration and appropriate response generation by the generation AI.

[0287] "User" refers to an individual or entity that utilizes the System to search for information and receive responses.

[0288] A "prompt" refers to a search or question keyword or phrase that a user enters into the system.

[0289] "Server" refers to a computer within a system that processes, analyzes, and provides information.

[0290] An "emotion engine" refers to natural language processing algorithms or software that identify emotions from user prompts.

[0291] "Search query" refers to the keywords or phrases used in a search that are generated based on prompts and perceived sentiment.

[0292] "Advertising" means commercial messages or content that are selected and displayed to users based on their search queries and user sentiment.

[0293] "Generative AI" refers to artificial intelligence algorithms or software that generate appropriate responses based on collected information and user sentiment.

[0294] "Data Source" means a website, database, or other source used to provide information relevant to a Search Query.

[0295] "Final output" refers to the final response or result generated by the generative AI and provided to the user.

[0296] "Device" refers to a device, such as a computer, smartphone, or tablet, used by a user to enter prompts and display responses and advertisements.

[0297] The present invention is a system that receives user prompts, performs emotion identification, and displays relevant advertisements to generate personalized responses. To implement this system, the following processes must be performed:

[0298] First, the user inputs a search prompt into the device. For example, the user inputs a prompt such as "Tell me reviews of the latest smartphones." The input prompt is sent from the device to the server.

[0299] The server then analyzes the received prompt using an emotion engine to identify the user's emotion from the prompt. This emotion engine uses natural language processing (NLP) techniques to extract emotions such as "excitement," "interest," and "frustration."

[0300] After the emotion is identified, the server generates a search query based on the prompt and the recognized emotion, for example, "latest smartphone reviews," which is used against databases within the server and sources on the Internet.

[0301] The server then selects relevant advertisements based on the generated search query and the user's emotions. The advertisements are retrieved from a database and the one that best matches the user's emotions is selected. For example, a user in an "excited" state might be shown a "new product campaign advertisement."

[0302] The device then displays the selected advertisements until the final output is generated. The advertisements are displayed randomly or sequentially, and the display time and content of the advertisements are adjusted according to the user's emotions. For example, a "new product campaign advertisement" may be displayed longer to an excited user.

[0303] The server then processes the search query to gather the necessary information from multiple sources. For example, it uses web scraping technology to gather reviews and user ratings. The collected data is then analyzed and the generative AI generates the final output, which also takes into account user sentiment.

[0304] Finally, the device displays the final output of the generated AI to the user. For example, it displays a response such as, "Reviews of the latest smartphones have given high marks to the new model from company A," while simultaneously hiding the advertisement. This allows the user to obtain efficient and personalized information.

[0305] As a concrete example of how this system works, the following series of procedures will be explained:

[0306] 1. A user types the search prompt "What are the latest smartphone reviews?"

[0307] 2. The server receives the prompt and uses the emotion engine to recognize the user's emotion as "excited."

[0308] 3. The server generates the search query "latest smartphone reviews" based on the prompt and the perceived sentiment.

[0309] 4. The server selects a "new product campaign ad" based on the search query and "excitement."

[0310] 5. The device displays the advertisement and shows the "New Product Campaign Ad" to the user until the generation AI generates the final output.

[0311] 6. The server collects and analyzes data related to "Latest Smartphone Reviews."

[0312] 7. The server uses the AI ​​to generate a response such as, "Company A's new model has received high marks in reviews of the latest smartphones."

[0313] 8. The device will display the final output and hide the ads at the same time.

[0314] This allows users to view relevant ads while they wait, and then receive personalized responses from the AI. This system uses advertising revenue to cover the operating costs of the AI, ensuring sustainable service provision.

[0315] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0316] Step 1:

[0317] A user inputs a search prompt into a device. The input prompt, for example, "Tell me reviews of the latest smartphones," is sent from the device to a server. Specifically, the user inputs text into the search bar and clicks the "Submit" button, which sends the prompt to the server.

[0318] Input: The prompt string entered by the user

[0319] Output: Prompt data sent to the server

[0320] Step 2:

[0321] The server receives a prompt from the user. The received prompt is sent for parsing. Specifically, the server takes the prompt string and converts it into a data format to be passed to the next processing step.

[0322] Input: Prompt data submitted by the user

[0323] Output: prompt data for analysis

[0324] Step 3:

[0325] The server uses an emotion engine to identify the emotion of the prompt. The emotion engine uses natural language processing technology to identify, for example, "excitement," "interest," or "frustration." Specifically, it analyzes the prompt string and generates emotion data by adding emotion tags.

[0326] Input: Prompt data for analysis

[0327] Output: Data containing the identified emotions

[0328] Step 4:

[0329] The server generates a search query based on the prompt and the identified emotion. For example, the prompt "Tell me reviews of the latest smartphones" is tagged with the emotion "excited," generating the search query "latest smartphone reviews."

[0330] Input: prompt data and emotion data

[0331] Output: Generated search query

[0332] Step 5:

[0333] The server selects relevant advertisements based on the generated search query and the identified emotion. For example, a "new product campaign advertisement" is selected for a user who is "excited" by searching the advertisement database.

[0334] Input: Generated search queries and sentiment data

[0335] Output: Selected advertising data

[0336] Step 6:

[0337] The device displays the advertisements sent from the server. The advertisements are displayed randomly or sequentially until the generation AI generates the final output. For example, a "new product campaign advertisement" is displayed on the user's screen, and the display time is adjusted according to the user's emotions.

[0338] Input: Selected advertising data

[0339] Output: Advertisement displayed on user device

[0340] Step 7:

[0341] The server collects relevant information from multiple data sources based on the search query, using web scraping technology to collect reviews and user ratings, which are used as input data for the generation AI.

[0342] Input: Generated search query

[0343] Output: Collected data (reviews, user ratings, etc.)

[0344] Step 8:

[0345] The server generates the final output from the generative AI based on the collected information and the identified emotions, for example, generating a response such as, "Reviews of the latest smartphones give high marks to the new model from company A."

[0346] Input: Collected data and identified emotion data

[0347] Output: The final output data (response) generated

[0348] Step 9:

[0349] The device displays the final output of the generated AI and hides the advertisement. For example, it displays "Company A's new model has received high praise in reviews of the latest smartphones," and at the same time, the advertisement that was being displayed up until then disappears.

[0350] Input: The final output data generated

[0351] Output: The final response and disappearing ad displayed on the user's device

[0352] (Application example 2)

[0353] 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."

[0354] Conventional advertising display systems can only display generic ads without considering user emotions, which does not improve the user experience and limits the effectiveness of ads. Furthermore, users become frustrated with the wait time it takes for the AI ​​to generate a response. Therefore, there is a need for a system that can identify user emotions and optimize the content and display time of ads based on those emotions.

[0355] 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.

[0356] In this invention, the server includes means for receiving a prompt from a user, means for generating a search query from the prompt, means for selecting a relevant advertisement based on the search query, means for displaying an advertisement on the terminal until a final output of the AI ​​for the generated search query is generated, means for collecting and analyzing information from multiple data sources, means for displaying the final output of the generated AI on the terminal while simultaneously hiding the advertisement, means for recognizing the user's emotions and adjusting the content and display time of the advertisement based on the emotions, and means for generating a search query based on the emotions and selecting an advertisement based on the search query. This enables personalized advertisement display according to the user's emotions, improving the user experience and maximizing advertising effectiveness.

[0357] The "means for receiving prompts from a user" is a function that receives prompts such as search requests or questions entered by a user into a terminal and transmits them to a server.

[0358] "Means for generating search queries from prompts" refers to a function that generates appropriate search queries based on received prompts. These search queries form the basis for information gathering and ad selection by the generation AI.

[0359] The "means for selecting relevant advertisements based on a search query" is a function for selecting advertisements corresponding to the generated search query from a database and displaying the advertisements appropriately.

[0360] "Means for displaying advertisements on a device until the final output of the AI ​​for the generated search query is generated" refers to a function that displays selected advertisements on a user's device during the waiting time until the final output of the AI ​​based on the search query is displayed.

[0361] "Means for collecting and analyzing information from multiple data sources" refers to a function for collecting necessary information from multiple information sources based on the generated search query and analyzing it.

[0362] "Means for displaying the final output of the generated AI on the device and simultaneously hiding advertisements" refers to a function that displays the final output of the generating AI on the user's device and simultaneously hides the advertisements that were displayed.

[0363] "Means for recognizing user emotions and adjusting the content and display time of advertisements based on those emotions" refers to a function that identifies the user's emotions from prompts and optimizes the content and display time of advertisements based on those emotions.

[0364] "Means for generating search queries based on emotions and selecting advertisements based on those" refers to a function that generates search queries taking into account recognized emotions and selects advertisements based on those queries.

[0365] This invention is a system that displays relevant advertisements based on a user's search prompts and emotions, and generates optimal output using a generative AI model. The system is mainly composed of a server, a terminal, and an emotion engine.

[0366] Program Overview

[0367] 1. Receiving prompts:

[0368] A user enters a search prompt into a terminal, for example, "What's the best destination for my next trip?"

[0369] The entered prompt is sent to the server.

[0370] 2. Emotion Recognition:

[0371] The server analyzes the received prompt and uses an emotion engine to recognize the user's emotions, for example, emotions such as "excitement," "anticipation," and "anxiety."

[0372] 3. Generating a search query:

[0373] The server generates a search query based on the prompt and the recognized sentiment, for example, "next travel destination."

[0374] 4. Advertisement Selection:

[0375] The server selects relevant advertisements based on the generated search query and emotion. It retrieves advertisements that match the search query and emotion from the database and creates an appropriate advertisement list. For example, for a user in an "excited" state, "new travel campaign advertisements" are selected.

[0376] 5. Display of advertisements:

[0377] The device displays selected ads until the final output is generated by the AI. The ads are displayed randomly or sequentially. The display time and content of the ads are also adjusted depending on the user's emotions. For example, a "new travel campaign ad" is displayed longer to an excited user.

[0378] 6. Data Collection and Analysis:

[0379] The server gathers information from multiple sources based on the search query, for example, using web scraping techniques to gather related travel articles and user ratings, using Python's requests library.

[0380] 7. Generative AI Generates Output:

[0381] The server uses generative AI to generate the final output based on the collected information and the recognized emotion. For example, it generates a response such as "Hawaii is a particularly good choice for your next trip." If the emotion is "anxiety," it also details safety and the weather. Generative AI uses language models such as GPT-3.

[0382] 8. Display AI results and hide ads:

[0383] The device displays the final output of the AI ​​generation. At the same time as showing the generated response to the user, the ad that was being displayed disappears. For example, a message saying "Hawaii is a particularly good choice for your next trip" appears on the screen, and the ad disappears.

[0384] Hardware and software used

[0385] Hardware:

[0386] User's device (smartphone, tablet, PC, etc.)

[0387] Server (data processing, storage, generative AI execution)

[0388] software:

[0389] Sentiment engine (using natural language processing libraries such as the BERT model)

[0390] Advertisement selection system (machine learning model, database system)

[0391] Data collection tools (such as the Python requests library)

[0392] Generative AI (language models such as GPT-3)

[0393] User interface (React Native, Flutter, etc.)

[0394] Specific examples

[0395] A user enters a search prompt: "What is the best destination for my next trip?" The server receives the prompt and uses an emotion engine to recognize the user's emotion as "excitement." Based on the prompt and the recognized emotion, the server generates a search query: "next travel destination." The server then selects travel-related advertisements and displays "New Travel Campaign Ads."

[0396] Based on the collected information, the server uses generative AI to generate the final output. For example, it might generate a response like, "Hawaii is a great place to visit next." This output is then displayed on the device, while the ad is hidden.

[0397] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0398] Step 1:

[0399] A user inputs a search prompt into a terminal. Specifically, the user inputs the prompt "What is the best destination for my next trip?", and the prompt is sent from the terminal to a server. The input data is the user's search request, and the output data is the prompt sent to the server.

[0400] Step 2:

[0401] The server analyzes the received prompt. In this step, the server passes the prompt to the emotion engine, which uses natural language processing techniques (e.g., the BERT model) to recognize the user's emotion. The input data is the user's prompt, and the output data is the recognized user emotion (e.g., "excited").

[0402] Step 3:

[0403] The server generates a search query based on the prompt and the recognized sentiment. Specifically, the server generates a search query for "next travel destination." The input data are the prompt and sentiment, and the output data is the generated search query.

[0404] Step 4:

[0405] The server selects relevant advertisements based on the generated search query and sentiment. Here, the server searches for appropriate advertisements from the advertisement database and selects "new travel campaign advertisements" for users in the "excited" state. The input data are the search query and sentiment, and the output data is the selected advertisement list.

[0406] Step 5:

[0407] The device displays the selected ads until the final output is generated by the AI. Specifically, the ads are displayed on the screen so that the user can view them. The input data is the selected ad list, and the output data is the ads displayed on the device.

[0408] Step 6:

[0409] The server collects and analyzes information based on the search query. In this step, the server collects relevant information using web scraping or API requests, and processes the data using analysis software (e.g., Python's requests library). The input data is the search query, and the output data is the collected and analyzed information.

[0410] Step 7:

[0411] The server uses generative AI to generate the final output based on the collected information and the recognized emotions. For example, the server uses GPT-3 to generate a response such as "Hawaii is a highly recommended destination for your next trip." The input data are the collected information and emotions, and the output data is the generated final output.

[0412] Step 8:

[0413] The terminal displays the final output of the generated AI and simultaneously hides the advertisements. Here, the terminal displays the generated response message and removes the advertisements from the screen. The input data is the final output message and the advertisement list, and the output data is the final message displayed to the user and the advertisements to be hidden.

[0414] 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.

[0415] 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.

[0416] 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.

[0417] [Second embodiment]

[0418] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0419] 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.

[0420] 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).

[0421] 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.

[0422] 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.

[0423] 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).

[0424] 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.

[0425] 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.

[0426] 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.

[0427] 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.

[0428] 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.

[0429] 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."

[0430] This invention is a system that generates a search query based on a prompt input by a user and displays related advertisements. The advertisements are displayed while the AI ​​is waiting to generate the final output. When the final output is displayed on the device, the advertisements are hidden.

[0431] System program and processing description

[0432] 1. Receiving a prompt

[0433] A user enters a search prompt into a device, for example, "Tell me reviews of the latest smartphones."

[0434] 2. Generating a search query

[0435] The server generates a search query based on the prompt received from the user, for example, "latest smartphone reviews."

[0436] 3. Ad selection

[0437] The server selects advertisements from the database that are relevant to the generated search query, for example, "Smartphone Ad 1," "Smartphone Ad 2," and "Smartphone Ad 3."

[0438] 4. Display of advertisements

[0439] The device will display the selected ads, either randomly or sequentially, until the AI ​​generates the search results.

[0440] 5. Data Collection and Analysis

[0441] The server collects information from multiple sources based on the search query and analyzes this data, for example, by collecting and analyzing reviews and user ratings of the latest smartphones.

[0442] 6. Generative AI Generates Output

[0443] Based on the data collected by the server, a generative AI (e.g., a large-scale language model) generates a response to the user prompt, for example, "Reviews of the latest smartphones give high marks to the new model from company A."

[0444] 7. Display AI results and hide ads

[0445] The device displays the generated final output and simultaneously hides the advertisement. For example, it displays the output "The latest smartphone reviews have given high marks to the new model from company A," and then removes the advertisement from the screen.

[0446] Specific examples

[0447] 1. A user types the search prompt "What are the latest smartphone reviews?"

[0448] 2. The server receives the prompt and translates it into the search query "latest smartphone reviews."

[0449] 3. The server selects "Smartphone Ad 1," "Smartphone Ad 2," and "Smartphone Ad 3" based on the search query.

[0450] 4. The device displays the ads and shows them to the user while the generation AI generates the final output.

[0451] 5. The server collects and analyzes data related to "Latest Smartphone Reviews."

[0452] 6. The server uses the AI ​​to generate a response such as, "Company A's new model has received high marks in reviews of the latest smartphones."

[0453] 7. The device will display the final output and hide the ads at the same time.

[0454] These steps allow users to view relevant ads during the waiting time and then receive a response from the AI. This system uses advertising revenue to cover the operating costs of the AI, ensuring sustainable service provision.

[0455] The processing flow will be explained below.

[0456] Step 1:

[0457] A user inputs a search prompt into the device, for example, "Tell me reviews of the latest smartphones." The input prompt is sent to the server.

[0458] Step 2:

[0459] The server analyzes the received prompt and generates an appropriate search query based on the prompt content. For example, the prompt "Tell me reviews of the latest smartphones" is converted into the search query "Latest smartphone reviews."

[0460] Step 3:

[0461] The server selects relevant ads based on the search query. It retrieves ads related to the search query from the database and creates an appropriate ad list. For example, "Smartphone Ad 1," "Smartphone Ad 2," and "Smartphone Ad 3" are selected.

[0462] Step 4:

[0463] While the device is waiting for the final output from the AI ​​to be generated, the selected advertisements will be displayed. The advertisements will be displayed randomly or in order. For example, "Smartphone Ad 1," "Smartphone Ad 2," and "Smartphone Ad 3" will be displayed in sequence.

[0464] Step 5:

[0465] The server collects information from multiple sources based on the search query, for example, by using web scraping techniques to gather relevant reviews and user ratings.

[0466] Step 6:

[0467] The server analyzes the collected information, extracts the most relevant information from the collected data, and organizes the analysis results.

[0468] Step 7:

[0469] The server uses generative AI to generate the final output. Based on the analysis results, it generates an appropriate answer to the user's prompt. For example, it might generate a response like, "Reviews of the latest smartphones give high marks to the new model from company A."

[0470] Step 8:

[0471] The device displays the final output of the AI ​​generation. At the same time as showing the generated response to the user, the displayed advertisement is hidden. For example, a message such as "Company A's new model has received high praise in reviews of the latest smartphones" is displayed on the screen, and the advertisement disappears.

[0472] Through these steps, users can view relevant ads during the waiting time and then receive a response from the AI. This system uses advertising revenue to cover the operating costs of the AI, ensuring sustainable service provision.

[0473] Example 1

[0474] 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."

[0475] In conventional systems, if it takes a long time to generate search results, the user experience is degraded because nothing is displayed during the waiting time.In addition, the high operating costs of the generation AI make it difficult to provide a sustainable service.

[0476] 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.

[0477] In this invention, the server includes means for receiving a prompt from a user, means for generating a search query from the prompt, means for selecting relevant content based on the search query, means for displaying advertisements on the terminal until the final output of the generation AI for the generated search query is generated, means for collecting and analyzing information from multiple data sources, and means for displaying the final output of the generation AI on the terminal while simultaneously hiding advertisements. This makes it possible to improve the user experience while using advertising revenue to cover the operating costs of the generation AI.

[0478] "User" means an individual or entity who operates a terminal to enter prompts and obtain information using the system.

[0479] A "prompt" is a question or instruction that a user enters into a system.

[0480] "Search query" refers to a sentence or phrase used in a search that is generated based on a user prompt.

[0481] "Generative AI" refers to artificial intelligence models that generate natural language responses based on input data.

[0482] "Device" refers to the device (e.g., smartphone, computer, tablet) that a user uses to enter prompts and view generated AI responses and advertisements.

[0483] "Advertisement" means any text, image or video content displayed to a User for commercial purposes.

[0484] "Data Source" refers to the website, API, database, or other source used to collect information.

[0485] "Analysis" refers to the process of processing and analyzing collected data.

[0486] "Revenue" refers to the economic benefits derived from displaying advertisements.

[0487] The system of this invention allows users to input a prompt, retrieve related information based on it, and wait for the output of the AI ​​while displaying an advertisement. Specifically, the user, terminal, and server each play their respective roles to realize the overall process.

[0488] First, the user inputs a prompt such as "Tell me a review of the latest smartphone" into the device. The device detects this input and sends the prompt to the server using a communication method, primarily an internet connection.

[0489] The server receives the prompt and generates an appropriate search query using natural language processing (NLP) techniques. Specifically, it uses text analysis libraries (e.g., SpaCy, NLTK). For example, the prompt "Tell me reviews of the latest smartphones" is converted into the search query "Latest smartphone reviews."

[0490] The server then selects relevant ads from a pre-built ad database based on the search query. Each ad is associated with a specific keyword. For example, ads related to keywords like "smartphone" and "review" are selected.

[0491] The selected ad is sent to the device, which then displays it to the user. Ads are displayed randomly or sequentially, and are realized using UI components for displaying ads. Specifically, React and Vue.js libraries are used on the front end.

[0492] Meanwhile, the server collects information from multiple data sources (websites, APIs, databases, etc.) based on the search query. The collected data is processed using analytical libraries (e.g., Pandas, NumPy). For example, reviews and user ratings of the latest smartphones are collected and analyzed.

[0493] The server uses a generative AI model (e.g., GPT-3) based on the analyzed data to generate a response to the user prompt, such as "Company A's new model has received high marks in reviews of the latest smartphones."

[0494] Finally, the generated response is sent to the device, which displays it to the user. At the same time, the displayed ad is hidden. The UI components are updated to hide the ad.

[0495] This system allows users to view relevant ads while they wait, and then receive useful responses from the AI. Advertising revenue covers the AI's operating costs, enabling the service to be provided sustainably.

[0496] As a concrete example, let's assume that you input a prompt such as "Please tell me reviews of the latest smartphones." In response to this prompt, the server generates a search query for "latest smartphone reviews," selects relevant advertisements, and finally generates a response such as "Company A's new model is highly rated in reviews of the latest smartphones."

[0497] In this way, a mechanism is realized in which users can efficiently obtain information through the system while also compensating for operational costs by viewing advertisements.

[0498] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0499] Step 1:

[0500] Receiving prompts

[0501] The user inputs a prompt sentence into the terminal, such as "Tell me a review of the latest smartphone."

[0502] The terminal captures the prompt text entered and sends it to the server in its raw form.

[0503] Input: The prompt text entered by the user (e.g., "Tell me your review of the latest smartphones")

[0504] Output: Prompt sent from terminal to server

[0505] Step 2:

[0506] Generating a search query

[0507] The server parses the received prompt and converts it into an appropriate search query using natural language processing (NLP) techniques and parsing libraries (e.g., SpaCy, NLTK).

[0508] Input: Prompt sent from the terminal

[0509] Data processing: Using natural language processing technology, we analyze prompts and generate search queries (e.g., "latest smartphone reviews")

[0510] Output: Generated search query

[0511] Step 3:

[0512] Ad selection

[0513] The server selects relevant advertisements from an advertisement database based on the generated search query, filtering advertisements that match keywords in the query.

[0514] Input: Generated search query

[0515] Data processing: Filter and select advertisements from the advertisement database using related keywords (e.g., "Smartphone Ad 1," "Smartphone Ad 2," "Smartphone Ad 3")

[0516] Output: Selected ad list

[0517] Step 4:

[0518] Displaying ads

[0519] The device receives the advertising data sent from the server and displays it to the user. Front-end UI components (e.g., React, Vue.js) are used to display the advertisements.

[0520] Input: Ad list sent from the server

[0521] Specific operation: Advertisements are displayed randomly or sequentially on the user's device screen.

[0522] Output: Ad displayed on the user's device

[0523] Step 5:

[0524] Data collection and analysis

[0525] Based on the search query, the server collects relevant information from multiple data sources, including websites, APIs, databases, etc. The collected data is processed using analytical libraries (e.g., Pandas, NumPy).

[0526] Input: Generated search query

[0527] Data processing: Collect information from multiple sources and process and analyze the data using analytics libraries (e.g., reviews and user ratings of the latest smartphones).

[0528] Output: Analyzed data

[0529] Step 6:

[0530] Generative AI generates output

[0531] The server uses a generative AI model (e.g., GPT-3) based on the analyzed data to generate a response to the prompt.

[0532] Input: Parsed data, prompts for the generative AI model

[0533] Data processing: The generative AI model generates a response based on the prompt and the analyzed data (e.g., "Company A's new model is highly rated in reviews of the latest smartphones").

[0534] Output: The generated response text

[0535] Step 7:

[0536] Display AI results and hide ads

[0537] The device receives the generated response from the server and displays it to the user, simultaneously hiding the displayed ad, updating the UI components to hide the ad area, and displaying the response text.

[0538] Input: Generated response text

[0539] Specific operation: The advertisement display area is hidden and the response text is displayed on the user's device screen.

[0540] Output: The generated AI's response text displayed on the user's device

[0541] This process allows users to view relevant advertisements while they wait, and then obtain useful information from the AI. The advertising revenue can then be used to cover the operational costs of the AI.

[0542] (Application example 1)

[0543] 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."

[0544] A means of providing useful information to users during the waiting time between when they input a prompt and when the generation AI generates the final output is required. A mechanism is also required to effectively utilize revenue from displaying advertisements to cover the operational costs of the generation AI. Furthermore, it is also necessary to provide additional information related to the generated content in a timely manner.

[0545] 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.

[0546] In this invention, the server includes means for receiving a prompt from a user, means for generating a search query from the prompt, and means for selecting a relevant advertisement based on the search query. This makes it possible to display an appropriate advertisement between the time the user inputs the prompt and the time the generation AI generates the final output, and to display related data when the advertisement ends.

[0547] A "prompt" is a question or request that a user enters into a system.

[0548] A "search query" refers to a query to a search engine or database that is generated based on a user prompt.

[0549] "Advertisement" refers to content in the form of text, images, or video that introduces products or services to users.

[0550] "Generative AI" refers to artificial intelligence that provides a final output that is analyzed and generated based on user prompts.

[0551] "Data source" refers to the source of information, such as a website or database, from which information is collected.

[0552] "Terminal" refers to the device (e.g., smartphone, computer) that a user uses to enter prompts and receive output.

[0553] "Analysis" refers to the process of analyzing collected data and extracting information that meets the user's requirements.

[0554] "Hidden" refers to removing the advertisement from the device screen so that it is no longer visually perceptible to the user.

[0555] "Revenue" refers to the economic benefits obtained from displaying advertisements.

[0556] "Token cost" refers to the costs associated with the computing resources and data processing required to operate the generating AI.

[0557] "Additional display" refers to displaying supplemental information related to the generated content to provide the user with such information.

[0558] This invention is a system that generates search queries based on prompts entered by users, displays relevant ads, and provides the final output using a generative AI. Part of the system runs on a device such as a smartphone, while the other part runs on a server.

[0559] Hardware and software used

[0560] Hardware: Smartphones, computers

[0561] Software: Python 3, ad management software, generative AI models (e.g., GPT-3)

[0562] DETAILED DESCRIPTION OF THE EMBODIMENTS

[0563] 1. Receiving a prompt

[0564] The user types a prompt into the terminal. This prompt contains the user's question or request. For example, "What are the latest movie reviews?"

[0565] 2. Generating a search query

[0566] The device sends the input prompt to the server, which analyzes the prompt and generates an appropriate search query that is optimized for the user's needs, such as "latest movie reviews."

[0567] 3. Advertisement selection and display

[0568] Based on the generated search query, the server selects relevant ads from an advertising database. These ads can be in the form of text, images, or videos. The device displays the selected ads to the user while the generation AI generates the final output.

[0569] 4. Data Collection and Analysis

[0570] The server collects and analyzes the necessary information from multiple data sources based on the search query. This analysis process uses natural language processing technology to handle large amounts of data. Specific systems retrieve information by making database queries or API calls.

[0571] 5. Generative AI Generates Output

[0572] Based on the collected data and analysis results, the server uses a generative AI model to generate the final output in response to the user's prompt. For example, if the prompt is "Tell me the latest movie reviews," the output generated will be "Movie X is highly rated in the latest movie reviews."

[0573] 6. Display generated AI output and hide ads

[0574] The device displays the final generated output to the user while hiding the ads, and adds relevant data to the generated content, ensuring fast and accurate information for the user while also ensuring revenue from the ads displayed.

[0575] Example

[0576] If a user inputs the prompt "What is the recommended drama this month?", the system generates a search query "This month's recommended drama review" and displays advertisements such as "Products related to drama B are on sale!". While the advertisement is displayed, the server collects related data, and the generation AI generates the final output "This month's recommended drama is drama Y!", which is displayed on the device while hiding the advertisement.

[0577] Example prompt statement

[0578] "Tell me the latest movie reviews"

[0579] What's your recommended drama this month?

[0580] This embodiment allows users to efficiently obtain the information they expect, and advertising revenue can be used to cover the costs of operating the system.

[0581] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0582] Step 1:

[0583] The user enters the prompt

[0584] The user inputs a prompt into the terminal. The input prompt is a sentence containing the user's question or request. For example, the user might input "Tell me the latest movie reviews."

[0585] Type: "What's the latest movie review?"

[0586] Output: The prompt is typed into the terminal.

[0587] Step 2:

[0588] The terminal sends a prompt to the server

[0589] The terminal sends the entered prompt to the server, a process that occurs over the network.

[0590] Input: The prompt entered by the user

[0591] Output: A prompt is sent to the server

[0592] Step 3:

[0593] The server generates a search query from the prompt

[0594] The server analyzes the received prompt and generates a relevant search query, for example, "What are the latest movie reviews?"

[0595] Input: The prompt sent by the user ("What's the latest movie review?")

[0596] Output: Generated search query ("latest movie reviews")

[0597] Step 4:

[0598] The server selects relevant ads based on the search query.

[0599] The server selects relevant advertisements from the advertisement database based on the generated search query. The selected advertisements are then displayed on the device, so in this step the most relevant advertisement is selected. For example, for "latest movie reviews," movie-related product advertisements are selected.

[0600] Input: Search query ("Latest movie reviews")

[0601] Output: Selected advertisement ("Movie-related product advertisement")

[0602] Step 5:

[0603] Display ads on your device

[0604] The device displays selected advertisements sent from the server, which can be in image or video format.

[0605] Input: Ad sent by server

[0606] Output: Ads are displayed on the device

[0607] Step 6:

[0608] The server collects and analyzes information from multiple data sources.

[0609] Based on the search query, the server collects and analyzes relevant information from websites and databases. The collected data is then analyzed using natural language processing techniques. For example, the server collects and analyzes the latest movie reviews from a movie review site.

[0610] Input: Search query ("Latest movie reviews")

[0611] Output: Analyzed data (latest movie reviews)

[0612] Step 7:

[0613] Generative AI generates the final output

[0614] The server uses the parsed data to run a generative AI model and generate the final output in response to a user prompt, for example, "What are the latest movie reviews?", generating a response such as "Movie X is highly rated in the latest movie reviews."

[0615] Input: Parsed data

[0616] Output: Final output ("Movie X is highly rated in the latest movie reviews")

[0617] Step 8:

[0618] Display the final output on your device while hiding ads

[0619] The device displays the final output received from the server and simultaneously hides the advertisement that was being displayed. For example, it displays the output "Movie X is highly rated in the latest movie reviews" and removes the advertisement from the screen.

[0620] Input: Final output, currently displayed ad

[0621] Output: Show final output to user, hide ads

[0622] Step 9:

[0623] Viewing Additional Information

[0624] The device will display additional information related to the generated content in a timely manner, with the additional information primarily related to the final output.

[0625] Input: Data related to the final output

[0626] Output: Display additional information

[0627] 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.

[0628] The present invention is a system that generates search queries in response to user prompts and displays relevant advertisements. The system also incorporates an emotion engine that recognizes the user's emotions. The emotion engine identifies emotions from the user's prompts and adjusts the display of advertisements and the output of the generation AI based on the emotions.

[0629] System program and processing description

[0630] 1. Receiving a prompt

[0631] A user inputs a search prompt into the device, for example, "Tell me reviews of the latest smartphones." The input prompt is sent to the server.

[0632] 2. Emotional Recognition

[0633] The server analyzes the received prompt and uses an emotion engine to recognize the user's emotion, for example, emotions such as "excited," "excited," and "frustrated" are identified.

[0634] 3. Generating search queries

[0635] The server generates a search query based on the prompt and the recognized sentiment, for example, "latest smartphone reviews."

[0636] 4. Ad selection

[0637] The server selects relevant advertisements based on the generated search query and emotion. It retrieves advertisements that match the search query and emotion from the database and creates an appropriate advertisement list. For example, for a user in an "excited" state, "new product campaign advertisements" are selected.

[0638] 5. Display of advertisements

[0639] The device displays selected ads until the final output is generated by the AI. The ads are displayed randomly or in order. The display time and content of the ads are also adjusted depending on the user's emotions. For example, a "new product campaign ad" is displayed longer to an excited user.

[0640] 6. Data Collection and Analysis

[0641] The server collects information from multiple sources based on the search query, for example, by using web scraping techniques to gather relevant reviews and user ratings.

[0642] 7. Generative AI Generates Output

[0643] The server uses generative AI to generate the final output based on the collected information and the recognized emotion. For example, it generates a response such as, "Reviews of the latest smartphones give high marks to the new model from company A." If the emotion is "unhappy," it also details specific issues and areas for improvement.

[0644] 8. Display AI results and hide ads

[0645] The device displays the final output of the AI ​​generation. At the same time as showing the generated response to the user, the displayed advertisement is hidden. For example, a message such as "Company A's new model has received high praise in reviews of the latest smartphones" is displayed on the screen, and the advertisement disappears.

[0646] Specific examples

[0647] 1. A user types the search prompt "What are the latest smartphone reviews?"

[0648] 2. The server receives the prompt and uses the emotion engine to recognize the user's emotion as "excited."

[0649] 3. The server generates the search query "latest smartphone reviews" based on the prompt and the perceived sentiment.

[0650] 4. The server selects a "new product campaign ad" based on the search query and "excitement."

[0651] 5. The device displays the advertisement and shows the "New Product Campaign Ad" to the user until the generation AI generates the final output.

[0652] 6. The server collects and analyzes data related to "Latest Smartphone Reviews."

[0653] 7. The server uses the AI ​​to generate a response such as, "Company A's new model has received high marks in reviews of the latest smartphones."

[0654] 8. The device will display the final output and hide the ads at the same time.

[0655] These steps allow users to view relevant ads while they wait, and then receive a response from the generation AI. Furthermore, the emotion engine provides ad displays and responses based on the user's emotions, creating a more personalized experience. This system uses advertising revenue to cover the operating costs of the generation AI, ensuring sustainable service provision.

[0656] The processing flow will be explained below.

[0657] Step 1:

[0658] A user inputs a search prompt into the device, for example, "Tell me reviews of the latest smartphones." The input prompt is sent to the server.

[0659] Step 2:

[0660] The server analyzes the received prompt and uses an emotion engine to recognize the user's emotion, for example, emotions such as "excited" or "frustrated" are identified from the prompt.

[0661] Step 3:

[0662] The server generates a search query based on the prompt and the recognized sentiment. For example, the prompt "Tell me reviews of the latest smartphones" is converted into the search query "Latest smartphone reviews."

[0663] Step 4:

[0664] The server selects relevant advertisements based on the search query and the recognized emotion. For example, a user in an "excited" state might be shown a "new product campaign advertisement," while a user in a "dissatisfied" state might be shown a "specific problem-solving advertisement."

[0665] Step 5:

[0666] The device will display selected ads until the final output is generated by the AI. The ads will be displayed randomly or in order. For example, a "new product campaign ad" will be displayed longer to excited users.

[0667] Step 6:

[0668] The server collects information from multiple data sources based on the search query, for example, by using web scraping techniques to gather reviews and user ratings of the latest smartphones.

[0669] Step 7:

[0670] The server analyzes the collected information, for example, by processing the collected reviews and ratings data and extracting particularly important information.

[0671] Step 8:

[0672] The server uses generative AI to generate the final output. Based on the analysis results and the recognized sentiment, it generates an appropriate response to the user's prompt. For example, the response might be, "Reviews of the latest smartphones give high marks to the new model from company A."

[0673] Step 9:

[0674] The device displays the final output of the AI ​​generation. At the same time as showing the generated response to the user, the displayed advertisement is hidden. For example, a message such as "Company A's new model has received high praise in reviews of the latest smartphones" is displayed on the screen, and the advertisement disappears.

[0675] Through these steps, users can view relevant ads while waiting and then receive a response from the AI. This system uses advertising revenue to cover the operating costs of the AI, ensuring sustainable service provision. The emotion engine provides ad display and responses based on the user's emotions, enabling a more personalized experience.

[0676] Example 2

[0677] 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."

[0678] Previous systems simply generated search queries based on user prompts and displayed relevant ads. This resulted in uniform ad display without considering user sentiment, making it difficult to achieve a personalized experience. Furthermore, effective ad display was not possible during the waiting time for the AI ​​to generate a response based on the search query, making it difficult to optimize advertising revenue.

[0679] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0680] In this invention, the server includes means for [using an emotion engine to analyze prompts and identify emotions], means for [generating search queries based on the prompts and the recognized emotions], and means for [selecting relevant advertisements based on the search queries and emotions]. This enables personalized advertisement display that takes user emotions into consideration and appropriate response generation by the generation AI.

[0681] "User" refers to an individual or entity that utilizes the System to search for information and receive responses.

[0682] A "prompt" refers to a search or question keyword or phrase that a user enters into the system.

[0683] "Server" refers to a computer within a system that processes, analyzes, and provides information.

[0684] An "emotion engine" refers to natural language processing algorithms or software that identify emotions from user prompts.

[0685] "Search query" refers to the keywords or phrases used in a search that are generated based on prompts and perceived sentiment.

[0686] "Advertising" means commercial messages or content that are selected and displayed to users based on their search queries and user sentiment.

[0687] "Generative AI" refers to artificial intelligence algorithms or software that generate appropriate responses based on collected information and user sentiment.

[0688] "Data Source" means a website, database, or other source used to provide information relevant to a Search Query.

[0689] "Final output" refers to the final response or result generated by the generative AI and provided to the user.

[0690] "Device" refers to a device, such as a computer, smartphone, or tablet, used by a user to enter prompts and display responses and advertisements.

[0691] The present invention is a system that receives user prompts, performs emotion identification, and displays relevant advertisements to generate personalized responses. To implement this system, the following processes must be performed:

[0692] First, the user inputs a search prompt into the device. For example, the user inputs a prompt such as "Tell me reviews of the latest smartphones." The input prompt is sent from the device to the server.

[0693] The server then analyzes the received prompt using an emotion engine to identify the user's emotion from the prompt. This emotion engine uses natural language processing (NLP) techniques to extract emotions such as "excitement," "interest," and "frustration."

[0694] After the emotion is identified, the server generates a search query based on the prompt and the recognized emotion, for example, "latest smartphone reviews," which is used against databases within the server and sources on the Internet.

[0695] The server then selects relevant advertisements based on the generated search query and the user's emotions. The advertisements are retrieved from a database and the one that best matches the user's emotions is selected. For example, a user in an "excited" state might be shown a "new product campaign advertisement."

[0696] The device then displays the selected advertisements until the final output is generated. The advertisements are displayed randomly or sequentially, and the display time and content of the advertisements are adjusted according to the user's emotions. For example, a "new product campaign advertisement" may be displayed longer to an excited user.

[0697] The server then processes the search query to gather the necessary information from multiple sources. For example, it uses web scraping technology to gather reviews and user ratings. The collected data is then analyzed and the generative AI generates the final output, which also takes into account user sentiment.

[0698] Finally, the device displays the final output of the generated AI to the user. For example, it displays a response such as, "Reviews of the latest smartphones have given high marks to the new model from company A," while simultaneously hiding the advertisement. This allows the user to obtain efficient and personalized information.

[0699] As a concrete example of how this system works, the following series of procedures will be explained:

[0700] 1. A user types the search prompt "What are the latest smartphone reviews?"

[0701] 2. The server receives the prompt and uses the emotion engine to recognize the user's emotion as "excited."

[0702] 3. The server generates the search query "latest smartphone reviews" based on the prompt and the perceived sentiment.

[0703] 4. The server selects a "new product campaign ad" based on the search query and "excitement."

[0704] 5. The device displays the advertisement and shows the "New Product Campaign Ad" to the user until the generation AI generates the final output.

[0705] 6. The server collects and analyzes data related to "Latest Smartphone Reviews."

[0706] 7. The server uses the AI ​​to generate a response such as, "Company A's new model has received high marks in reviews of the latest smartphones."

[0707] 8. The device will display the final output and hide the ads at the same time.

[0708] This allows users to view relevant ads while they wait, and then receive personalized responses from the AI. This system uses advertising revenue to cover the operating costs of the AI, ensuring sustainable service provision.

[0709] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0710] Step 1:

[0711] A user inputs a search prompt into a device. The input prompt, for example, "Tell me reviews of the latest smartphones," is sent from the device to a server. Specifically, the user inputs text into the search bar and clicks the "Submit" button, which sends the prompt to the server.

[0712] Input: The prompt string entered by the user

[0713] Output: Prompt data sent to the server

[0714] Step 2:

[0715] The server receives a prompt from the user. The received prompt is sent for parsing. Specifically, the server takes the prompt string and converts it into a data format to be passed to the next processing step.

[0716] Input: Prompt data submitted by the user

[0717] Output: prompt data for analysis

[0718] Step 3:

[0719] The server uses an emotion engine to identify the emotion of the prompt. The emotion engine uses natural language processing technology to identify, for example, "excitement," "interest," or "frustration." Specifically, it analyzes the prompt string and generates emotion data by adding emotion tags.

[0720] Input: Prompt data for analysis

[0721] Output: Data containing the identified emotions

[0722] Step 4:

[0723] The server generates a search query based on the prompt and the identified emotion. For example, the prompt "Tell me reviews of the latest smartphones" is tagged with the emotion "excited," generating the search query "latest smartphone reviews."

[0724] Input: prompt data and emotion data

[0725] Output: Generated search query

[0726] Step 5:

[0727] The server selects relevant advertisements based on the generated search query and the identified emotion. For example, a "new product campaign advertisement" is selected for a user who is "excited" by searching the advertisement database.

[0728] Input: Generated search queries and sentiment data

[0729] Output: Selected advertising data

[0730] Step 6:

[0731] The device displays the advertisements sent from the server. The advertisements are displayed randomly or sequentially until the generation AI generates the final output. For example, a "new product campaign advertisement" is displayed on the user's screen, and the display time is adjusted according to the user's emotions.

[0732] Input: Selected advertising data

[0733] Output: Advertisement displayed on user device

[0734] Step 7:

[0735] The server collects relevant information from multiple data sources based on the search query, using web scraping technology to collect reviews and user ratings, which are used as input data for the generation AI.

[0736] Input: Generated search query

[0737] Output: Collected data (reviews, user ratings, etc.)

[0738] Step 8:

[0739] The server generates the final output from the generative AI based on the collected information and the identified emotions, for example, generating a response such as, "Reviews of the latest smartphones give high marks to the new model from company A."

[0740] Input: Collected data and identified emotion data

[0741] Output: The final output data (response) generated

[0742] Step 9:

[0743] The device displays the final output of the generated AI and hides the advertisement. For example, it displays "Company A's new model has received high praise in reviews of the latest smartphones," and at the same time, the advertisement that was being displayed up until then disappears.

[0744] Input: The final output data generated

[0745] Output: The final response and disappearing ad displayed on the user's device

[0746] (Application example 2)

[0747] 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."

[0748] Conventional advertising display systems can only display generic ads without considering user emotions, which does not improve the user experience and limits the effectiveness of ads. Furthermore, users become frustrated with the wait time it takes for the AI ​​to generate a response. Therefore, there is a need for a system that can identify user emotions and optimize the content and display time of ads based on those emotions.

[0749] 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.

[0750] In this invention, the server includes means for receiving a prompt from a user, means for generating a search query from the prompt, means for selecting a relevant advertisement based on the search query, means for displaying an advertisement on the terminal until a final output of the AI ​​for the generated search query is generated, means for collecting and analyzing information from multiple data sources, means for displaying the final output of the generated AI on the terminal while simultaneously hiding the advertisement, means for recognizing the user's emotions and adjusting the content and display time of the advertisement based on the emotions, and means for generating a search query based on the emotions and selecting an advertisement based on the search query. This enables personalized advertisement display according to the user's emotions, improving the user experience and maximizing advertising effectiveness.

[0751] The "means for receiving prompts from a user" is a function that receives prompts such as search requests or questions entered by a user into a terminal and transmits them to a server.

[0752] "Means for generating search queries from prompts" refers to a function that generates appropriate search queries based on received prompts. These search queries form the basis for information gathering and ad selection by the generation AI.

[0753] The "means for selecting relevant advertisements based on a search query" is a function for selecting advertisements corresponding to the generated search query from a database and displaying the advertisements appropriately.

[0754] "Means for displaying advertisements on a device until the final output of the AI ​​for the generated search query is generated" refers to a function that displays selected advertisements on a user's device during the waiting time until the final output of the AI ​​based on the search query is displayed.

[0755] "Means for collecting and analyzing information from multiple data sources" refers to a function for collecting necessary information from multiple information sources based on the generated search query and analyzing it.

[0756] "Means for displaying the final output of the generated AI on the device and simultaneously hiding advertisements" refers to a function that displays the final output of the generating AI on the user's device and simultaneously hides the advertisements that were displayed.

[0757] "Means for recognizing user emotions and adjusting the content and display time of advertisements based on those emotions" refers to a function that identifies the user's emotions from prompts and optimizes the content and display time of advertisements based on those emotions.

[0758] "Means for generating search queries based on emotions and selecting advertisements based on those" refers to a function that generates search queries taking into account recognized emotions and selects advertisements based on those queries.

[0759] This invention is a system that displays relevant advertisements based on a user's search prompts and emotions, and generates optimal output using a generative AI model. The system is mainly composed of a server, a terminal, and an emotion engine.

[0760] Program Overview

[0761] 1. Receiving prompts:

[0762] A user enters a search prompt into a terminal, for example, "What's the best destination for my next trip?"

[0763] The entered prompt is sent to the server.

[0764] 2. Emotion Recognition:

[0765] The server analyzes the received prompt and uses an emotion engine to recognize the user's emotions, for example, emotions such as "excitement," "anticipation," and "anxiety."

[0766] 3. Generating a search query:

[0767] The server generates a search query based on the prompt and the recognized sentiment, for example, "next travel destination."

[0768] 4. Advertisement Selection:

[0769] The server selects relevant advertisements based on the generated search query and emotion. It retrieves advertisements that match the search query and emotion from the database and creates an appropriate advertisement list. For example, for a user in an "excited" state, "new travel campaign advertisements" are selected.

[0770] 5. Display of advertisements:

[0771] The device displays selected ads until the final output is generated by the AI. The ads are displayed randomly or sequentially. The display time and content of the ads are also adjusted depending on the user's emotions. For example, a "new travel campaign ad" is displayed longer to an excited user.

[0772] 6. Data Collection and Analysis:

[0773] The server gathers information from multiple sources based on the search query, for example, using web scraping techniques to gather related travel articles and user ratings, using Python's requests library.

[0774] 7. Generative AI Generates Output:

[0775] The server uses generative AI to generate the final output based on the collected information and the recognized emotion. For example, it generates a response such as "Hawaii is a particularly good choice for your next trip." If the emotion is "anxiety," it also details safety and the weather. Generative AI uses language models such as GPT-3.

[0776] 8. Display AI results and hide ads:

[0777] The device displays the final output of the AI ​​generation. At the same time as showing the generated response to the user, the ad that was being displayed disappears. For example, a message saying "Hawaii is a particularly good choice for your next trip" appears on the screen, and the ad disappears.

[0778] Hardware and software used

[0779] Hardware:

[0780] User's device (smartphone, tablet, PC, etc.)

[0781] Server (data processing, storage, generative AI execution)

[0782] software:

[0783] Sentiment engine (using natural language processing libraries such as the BERT model)

[0784] Advertisement selection system (machine learning model, database system)

[0785] Data collection tools (such as the Python requests library)

[0786] Generative AI (language models such as GPT-3)

[0787] User interface (React Native, Flutter, etc.)

[0788] Specific examples

[0789] A user enters a search prompt: "What is the best destination for my next trip?" The server receives the prompt and uses an emotion engine to recognize the user's emotion as "excitement." Based on the prompt and the recognized emotion, the server generates a search query: "next travel destination." The server then selects travel-related advertisements and displays "New Travel Campaign Ads."

[0790] Based on the collected information, the server uses generative AI to generate the final output. For example, it might generate a response like, "Hawaii is a great place to visit next." This output is then displayed on the device, while the ad is hidden.

[0791] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0792] Step 1:

[0793] A user inputs a search prompt into a terminal. Specifically, the user inputs the prompt "What is the best destination for my next trip?", and the prompt is sent from the terminal to a server. The input data is the user's search request, and the output data is the prompt sent to the server.

[0794] Step 2:

[0795] The server analyzes the received prompt. In this step, the server passes the prompt to the emotion engine, which uses natural language processing techniques (e.g., the BERT model) to recognize the user's emotion. The input data is the user's prompt, and the output data is the recognized user emotion (e.g., "excited").

[0796] Step 3:

[0797] The server generates a search query based on the prompt and the recognized sentiment. Specifically, the server generates a search query for "next travel destination." The input data are the prompt and sentiment, and the output data is the generated search query.

[0798] Step 4:

[0799] The server selects relevant advertisements based on the generated search query and sentiment. Here, the server searches for appropriate advertisements from the advertisement database and selects "new travel campaign advertisements" for users in the "excited" state. The input data are the search query and sentiment, and the output data is the selected advertisement list.

[0800] Step 5:

[0801] The device displays the selected ads until the final output is generated by the AI. Specifically, the ads are displayed on the screen so that the user can view them. The input data is the selected ad list, and the output data is the ads displayed on the device.

[0802] Step 6:

[0803] The server collects and analyzes information based on the search query. In this step, the server collects relevant information using web scraping or API requests, and processes the data using analysis software (e.g., Python's requests library). The input data is the search query, and the output data is the collected and analyzed information.

[0804] Step 7:

[0805] The server uses generative AI to generate the final output based on the collected information and the recognized emotions. For example, the server uses GPT-3 to generate a response such as "Hawaii is a highly recommended destination for your next trip." The input data are the collected information and emotions, and the output data is the generated final output.

[0806] Step 8:

[0807] The terminal displays the final output of the generated AI and simultaneously hides the advertisements. Here, the terminal displays the generated response message and removes the advertisements from the screen. The input data is the final output message and the advertisement list, and the output data is the final message displayed to the user and the advertisements to be hidden.

[0808] 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.

[0809] 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.

[0810] 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.

[0811] [Third embodiment]

[0812] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0813] 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.

[0814] 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).

[0815] 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.

[0816] 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.

[0817] 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).

[0818] 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.

[0819] 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.

[0820] 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.

[0821] 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.

[0822] 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.

[0823] 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."

[0824] This invention is a system that generates a search query based on a prompt input by a user and displays related advertisements. The advertisements are displayed while the AI ​​is waiting to generate the final output. When the final output is displayed on the device, the advertisements are hidden.

[0825] System program and processing description

[0826] 1. Receiving a prompt

[0827] A user enters a search prompt into a device, for example, "Tell me reviews of the latest smartphones."

[0828] 2. Generating a search query

[0829] The server generates a search query based on the prompt received from the user, for example, "latest smartphone reviews."

[0830] 3. Ad selection

[0831] The server selects advertisements from the database that are relevant to the generated search query, for example, "Smartphone Ad 1," "Smartphone Ad 2," and "Smartphone Ad 3."

[0832] 4. Display of advertisements

[0833] The device will display the selected ads, either randomly or sequentially, until the AI ​​generates the search results.

[0834] 5. Data Collection and Analysis

[0835] The server collects information from multiple sources based on the search query and analyzes this data, for example, by collecting and analyzing reviews and user ratings of the latest smartphones.

[0836] 6. Generative AI Generates Output

[0837] Based on the data collected by the server, a generative AI (e.g., a large-scale language model) generates a response to the user prompt, for example, "Reviews of the latest smartphones give high marks to the new model from company A."

[0838] 7. Display AI results and hide ads

[0839] The device displays the generated final output and simultaneously hides the advertisement. For example, it displays the output "The latest smartphone reviews have given high marks to the new model from company A," and then removes the advertisement from the screen.

[0840] Specific examples

[0841] 1. A user types the search prompt "What are the latest smartphone reviews?"

[0842] 2. The server receives the prompt and translates it into the search query "latest smartphone reviews."

[0843] 3. The server selects "Smartphone Ad 1," "Smartphone Ad 2," and "Smartphone Ad 3" based on the search query.

[0844] 4. The device displays the ads and shows them to the user while the generation AI generates the final output.

[0845] 5. The server collects and analyzes data related to "Latest Smartphone Reviews."

[0846] 6. The server uses the AI ​​to generate a response such as, "Company A's new model has received high marks in reviews of the latest smartphones."

[0847] 7. The device will display the final output and hide the ads at the same time.

[0848] These steps allow users to view relevant ads during the waiting time and then receive a response from the AI. This system uses advertising revenue to cover the operating costs of the AI, ensuring sustainable service provision.

[0849] The processing flow will be explained below.

[0850] Step 1:

[0851] A user inputs a search prompt into the device, for example, "Tell me reviews of the latest smartphones." The input prompt is sent to the server.

[0852] Step 2:

[0853] The server analyzes the received prompt and generates an appropriate search query based on the prompt content. For example, the prompt "Tell me reviews of the latest smartphones" is converted into the search query "Latest smartphone reviews."

[0854] Step 3:

[0855] The server selects relevant ads based on the search query. It retrieves ads related to the search query from the database and creates an appropriate ad list. For example, "Smartphone Ad 1," "Smartphone Ad 2," and "Smartphone Ad 3" are selected.

[0856] Step 4:

[0857] While the device is waiting for the final output from the AI ​​to be generated, the selected advertisements will be displayed. The advertisements will be displayed randomly or in order. For example, "Smartphone Ad 1," "Smartphone Ad 2," and "Smartphone Ad 3" will be displayed in sequence.

[0858] Step 5:

[0859] The server collects information from multiple sources based on the search query, for example, by using web scraping techniques to gather relevant reviews and user ratings.

[0860] Step 6:

[0861] The server analyzes the collected information, extracts the most relevant information from the collected data, and organizes the analysis results.

[0862] Step 7:

[0863] The server uses generative AI to generate the final output. Based on the analysis results, it generates an appropriate answer to the user's prompt. For example, it might generate a response like, "Reviews of the latest smartphones give high marks to the new model from company A."

[0864] Step 8:

[0865] The device displays the final output of the AI ​​generation. At the same time as showing the generated response to the user, the displayed advertisement is hidden. For example, a message such as "Company A's new model has received high praise in reviews of the latest smartphones" is displayed on the screen, and the advertisement disappears.

[0866] Through these steps, users can view relevant ads during the waiting time and then receive a response from the AI. This system uses advertising revenue to cover the operating costs of the AI, ensuring sustainable service provision.

[0867] Example 1

[0868] 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."

[0869] In conventional systems, if it takes a long time to generate search results, the user experience is degraded because nothing is displayed during the waiting time.In addition, the high operating costs of the generation AI make it difficult to provide a sustainable service.

[0870] 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.

[0871] In this invention, the server includes means for receiving a prompt from a user, means for generating a search query from the prompt, means for selecting relevant content based on the search query, means for displaying advertisements on the terminal until the final output of the generation AI for the generated search query is generated, means for collecting and analyzing information from multiple data sources, and means for displaying the final output of the generation AI on the terminal while simultaneously hiding advertisements. This makes it possible to improve the user experience while using advertising revenue to cover the operating costs of the generation AI.

[0872] "User" means an individual or entity who operates a terminal to enter prompts and obtain information using the system.

[0873] A "prompt" is a question or instruction that a user enters into a system.

[0874] "Search query" refers to a sentence or phrase used in a search that is generated based on a user prompt.

[0875] "Generative AI" refers to artificial intelligence models that generate natural language responses based on input data.

[0876] "Device" refers to the device (e.g., smartphone, computer, tablet) that a user uses to enter prompts and view generated AI responses and advertisements.

[0877] "Advertisement" means any text, image or video content displayed to a User for commercial purposes.

[0878] "Data Source" refers to the website, API, database, or other source used to collect information.

[0879] "Analysis" refers to the process of processing and analyzing collected data.

[0880] "Revenue" refers to the economic benefits derived from displaying advertisements.

[0881] The system of this invention allows users to input a prompt, retrieve related information based on it, and wait for the output of the AI ​​while displaying an advertisement. Specifically, the user, terminal, and server each play their respective roles to realize the overall process.

[0882] First, the user inputs a prompt such as "Tell me a review of the latest smartphone" into the device. The device detects this input and sends the prompt to the server using a communication method, primarily an internet connection.

[0883] The server receives the prompt and generates an appropriate search query using natural language processing (NLP) techniques. Specifically, it uses text analysis libraries (e.g., SpaCy, NLTK). For example, the prompt "Tell me reviews of the latest smartphones" is converted into the search query "Latest smartphone reviews."

[0884] The server then selects relevant ads from a pre-built ad database based on the search query. Each ad is associated with a specific keyword. For example, ads related to keywords like "smartphone" and "review" are selected.

[0885] The selected ad is sent to the device, which then displays it to the user. Ads are displayed randomly or sequentially, and are realized using UI components for displaying ads. Specifically, React and Vue.js libraries are used on the front end.

[0886] Meanwhile, the server collects information from multiple data sources (websites, APIs, databases, etc.) based on the search query. The collected data is processed using analytical libraries (e.g., Pandas, NumPy). For example, reviews and user ratings of the latest smartphones are collected and analyzed.

[0887] The server uses a generative AI model (e.g., GPT-3) based on the analyzed data to generate a response to the user prompt, such as "Company A's new model has received high marks in reviews of the latest smartphones."

[0888] Finally, the generated response is sent to the device, which displays it to the user. At the same time, the displayed ad is hidden. The UI components are updated to hide the ad.

[0889] This system allows users to view relevant ads while they wait, and then receive useful responses from the AI. Advertising revenue covers the AI's operating costs, enabling the service to be provided sustainably.

[0890] As a concrete example, let's assume that you input a prompt such as "Please tell me reviews of the latest smartphones." In response to this prompt, the server generates a search query for "latest smartphone reviews," selects relevant advertisements, and finally generates a response such as "Company A's new model is highly rated in reviews of the latest smartphones."

[0891] In this way, a mechanism is realized in which users can efficiently obtain information through the system while also compensating for operational costs by viewing advertisements.

[0892] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0893] Step 1:

[0894] Receiving prompts

[0895] The user inputs a prompt sentence into the terminal, such as "Tell me a review of the latest smartphone."

[0896] The terminal captures the prompt text entered and sends it to the server in its raw form.

[0897] Input: The prompt text entered by the user (e.g., "Tell me your review of the latest smartphones")

[0898] Output: Prompt sent from terminal to server

[0899] Step 2:

[0900] Generating a search query

[0901] The server parses the received prompt and converts it into an appropriate search query using natural language processing (NLP) techniques and parsing libraries (e.g., SpaCy, NLTK).

[0902] Input: Prompt sent from the terminal

[0903] Data processing: Using natural language processing technology, we analyze prompts and generate search queries (e.g., "latest smartphone reviews")

[0904] Output: Generated search query

[0905] Step 3:

[0906] Ad selection

[0907] The server selects relevant advertisements from an advertisement database based on the generated search query, filtering advertisements that match keywords in the query.

[0908] Input: Generated search query

[0909] Data processing: Filter and select advertisements from the advertisement database using related keywords (e.g., "Smartphone Ad 1," "Smartphone Ad 2," "Smartphone Ad 3")

[0910] Output: Selected ad list

[0911] Step 4:

[0912] Displaying ads

[0913] The device receives the advertising data sent from the server and displays it to the user. Front-end UI components (e.g., React, Vue.js) are used to display the advertisements.

[0914] Input: Ad list sent from the server

[0915] Specific operation: Advertisements are displayed randomly or sequentially on the user's device screen.

[0916] Output: Ad displayed on the user's device

[0917] Step 5:

[0918] Data collection and analysis

[0919] Based on the search query, the server collects relevant information from multiple data sources, including websites, APIs, databases, etc. The collected data is processed using analytical libraries (e.g., Pandas, NumPy).

[0920] Input: Generated search query

[0921] Data processing: Collect information from multiple sources and process and analyze the data using analytics libraries (e.g., reviews and user ratings of the latest smartphones).

[0922] Output: Analyzed data

[0923] Step 6:

[0924] Generative AI generates output

[0925] The server uses a generative AI model (e.g., GPT-3) based on the analyzed data to generate a response to the prompt.

[0926] Input: Parsed data, prompts for the generative AI model

[0927] Data processing: The generative AI model generates a response based on the prompt and the analyzed data (e.g., "Company A's new model is highly rated in reviews of the latest smartphones").

[0928] Output: The generated response text

[0929] Step 7:

[0930] Display AI results and hide ads

[0931] The device receives the generated response from the server and displays it to the user, simultaneously hiding the displayed ad, updating the UI components to hide the ad area, and displaying the response text.

[0932] Input: Generated response text

[0933] Specific operation: The advertisement display area is hidden and the response text is displayed on the user's device screen.

[0934] Output: The generated AI's response text displayed on the user's device

[0935] This process allows users to view relevant advertisements while they wait, and then obtain useful information from the AI. The advertising revenue can then be used to cover the operational costs of the AI.

[0936] (Application example 1)

[0937] 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."

[0938] A means of providing useful information to users during the waiting time between when they input a prompt and when the generation AI generates the final output is required. A mechanism is also required to effectively utilize revenue from displaying advertisements to cover the operational costs of the generation AI. Furthermore, it is also necessary to provide additional information related to the generated content in a timely manner.

[0939] 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.

[0940] In this invention, the server includes means for receiving a prompt from a user, means for generating a search query from the prompt, and means for selecting a relevant advertisement based on the search query. This makes it possible to display an appropriate advertisement between the time the user inputs the prompt and the time the generation AI generates the final output, and to display related data when the advertisement ends.

[0941] A "prompt" is a question or request that a user enters into a system.

[0942] A "search query" refers to a query to a search engine or database that is generated based on a user prompt.

[0943] "Advertisement" refers to content in the form of text, images, or video that introduces products or services to users.

[0944] "Generative AI" refers to artificial intelligence that provides a final output that is analyzed and generated based on user prompts.

[0945] "Data source" refers to the source of information, such as a website or database, from which information is collected.

[0946] "Terminal" refers to the device (e.g., smartphone, computer) that a user uses to enter prompts and receive output.

[0947] "Analysis" refers to the process of analyzing collected data and extracting information that meets the user's requirements.

[0948] "Hidden" refers to removing the advertisement from the device screen so that it is no longer visually perceptible to the user.

[0949] "Revenue" refers to the economic benefits obtained from displaying advertisements.

[0950] "Token cost" refers to the costs associated with the computing resources and data processing required to operate the generating AI.

[0951] "Additional display" refers to displaying supplemental information related to the generated content to provide the user with such information.

[0952] This invention is a system that generates search queries based on prompts entered by users, displays relevant ads, and provides the final output using a generative AI. Part of the system runs on a device such as a smartphone, while the other part runs on a server.

[0953] Hardware and software used

[0954] Hardware: Smartphones, computers

[0955] Software: Python 3, ad management software, generative AI models (e.g., GPT-3)

[0956] DETAILED DESCRIPTION OF THE EMBODIMENTS

[0957] 1. Receiving a prompt

[0958] The user types a prompt into the terminal. This prompt contains the user's question or request. For example, "What are the latest movie reviews?"

[0959] 2. Generating a search query

[0960] The device sends the input prompt to the server, which analyzes the prompt and generates an appropriate search query that is optimized for the user's needs, such as "latest movie reviews."

[0961] 3. Advertisement selection and display

[0962] Based on the generated search query, the server selects relevant ads from an advertising database. These ads can be in the form of text, images, or videos. The device displays the selected ads to the user while the generation AI generates the final output.

[0963] 4. Data Collection and Analysis

[0964] The server collects and analyzes the necessary information from multiple data sources based on the search query. This analysis process uses natural language processing technology to handle large amounts of data. Specific systems retrieve information by making database queries or API calls.

[0965] 5. Generative AI Generates Output

[0966] Based on the collected data and analysis results, the server uses a generative AI model to generate the final output in response to the user's prompt. For example, if the prompt is "Tell me the latest movie reviews," the output generated will be "Movie X is highly rated in the latest movie reviews."

[0967] 6. Display generated AI output and hide ads

[0968] The device displays the final generated output to the user while hiding the ads, and adds relevant data to the generated content, ensuring fast and accurate information for the user while also ensuring revenue from the ads displayed.

[0969] Example

[0970] If a user inputs the prompt "What is the recommended drama this month?", the system generates a search query "This month's recommended drama review" and displays advertisements such as "Products related to drama B are on sale!". While the advertisement is displayed, the server collects related data, and the generation AI generates the final output "This month's recommended drama is drama Y!", which is displayed on the device while hiding the advertisement.

[0971] Example prompt statement

[0972] "Tell me the latest movie reviews"

[0973] What's your recommended drama this month?

[0974] This embodiment allows users to efficiently obtain the information they expect, and advertising revenue can be used to cover the costs of operating the system.

[0975] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0976] Step 1:

[0977] The user enters the prompt

[0978] The user inputs a prompt into the terminal. The input prompt is a sentence containing the user's question or request. For example, the user might input "Tell me the latest movie reviews."

[0979] Type: "What's the latest movie review?"

[0980] Output: The prompt is typed into the terminal.

[0981] Step 2:

[0982] The terminal sends a prompt to the server

[0983] The terminal sends the entered prompt to the server, a process that occurs over the network.

[0984] Input: The prompt entered by the user

[0985] Output: A prompt is sent to the server

[0986] Step 3:

[0987] The server generates a search query from the prompt

[0988] The server analyzes the received prompt and generates a relevant search query, for example, "What are the latest movie reviews?"

[0989] Input: The prompt sent by the user ("What's the latest movie review?")

[0990] Output: Generated search query ("latest movie reviews")

[0991] Step 4:

[0992] The server selects relevant ads based on the search query.

[0993] The server selects relevant advertisements from the advertisement database based on the generated search query. The selected advertisements are then displayed on the device, so in this step the most relevant advertisement is selected. For example, for "latest movie reviews," movie-related product advertisements are selected.

[0994] Input: Search query ("Latest movie reviews")

[0995] Output: Selected advertisement ("Movie-related product advertisement")

[0996] Step 5:

[0997] Display ads on your device

[0998] The device displays selected advertisements sent from the server, which can be in image or video format.

[0999] Input: Ad sent by server

[1000] Output: Ads are displayed on the device

[1001] Step 6:

[1002] The server collects and analyzes information from multiple data sources.

[1003] Based on the search query, the server collects and analyzes relevant information from websites and databases. The collected data is then analyzed using natural language processing techniques. For example, the server collects and analyzes the latest movie reviews from a movie review site.

[1004] Input: Search query ("Latest movie reviews")

[1005] Output: Analyzed data (latest movie reviews)

[1006] Step 7:

[1007] Generative AI generates the final output

[1008] The server uses the parsed data to run a generative AI model and generate the final output in response to a user prompt, for example, "What are the latest movie reviews?", generating a response such as "Movie X is highly rated in the latest movie reviews."

[1009] Input: Parsed data

[1010] Output: Final output ("Movie X is highly rated in the latest movie reviews")

[1011] Step 8:

[1012] Display the final output on your device while hiding ads

[1013] The device displays the final output received from the server and simultaneously hides the advertisement that was being displayed. For example, it displays the output "Movie X is highly rated in the latest movie reviews" and removes the advertisement from the screen.

[1014] Input: Final output, currently displayed ad

[1015] Output: Show final output to user, hide ads

[1016] Step 9:

[1017] Viewing Additional Information

[1018] The device will display additional information related to the generated content in a timely manner, with the additional information primarily related to the final output.

[1019] Input: Data related to the final output

[1020] Output: Display additional information

[1021] 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.

[1022] The present invention is a system that generates search queries in response to user prompts and displays relevant advertisements. The system also incorporates an emotion engine that recognizes the user's emotions. The emotion engine identifies emotions from the user's prompts and adjusts the display of advertisements and the output of the generation AI based on the emotions.

[1023] System program and processing description

[1024] 1. Receiving a prompt

[1025] A user inputs a search prompt into the device, for example, "Tell me reviews of the latest smartphones." The input prompt is sent to the server.

[1026] 2. Emotional Recognition

[1027] The server analyzes the received prompt and uses an emotion engine to recognize the user's emotion, for example, emotions such as "excited," "excited," and "frustrated" are identified.

[1028] 3. Generating search queries

[1029] The server generates a search query based on the prompt and the recognized sentiment, for example, "latest smartphone reviews."

[1030] 4. Ad selection

[1031] The server selects relevant advertisements based on the generated search query and emotion. It retrieves advertisements that match the search query and emotion from the database and creates an appropriate advertisement list. For example, for a user in an "excited" state, "new product campaign advertisements" are selected.

[1032] 5. Display of advertisements

[1033] The device displays selected ads until the final output is generated by the AI. The ads are displayed randomly or in order. The display time and content of the ads are also adjusted depending on the user's emotions. For example, a "new product campaign ad" is displayed longer to an excited user.

[1034] 6. Data Collection and Analysis

[1035] The server collects information from multiple sources based on the search query, for example, by using web scraping techniques to gather relevant reviews and user ratings.

[1036] 7. Generative AI Generates Output

[1037] The server uses generative AI to generate the final output based on the collected information and the recognized emotion. For example, it generates a response such as, "Reviews of the latest smartphones give high marks to the new model from company A." If the emotion is "unhappy," it also details specific issues and areas for improvement.

[1038] 8. Display AI results and hide ads

[1039] The device displays the final output of the AI ​​generation. At the same time as showing the generated response to the user, the displayed advertisement is hidden. For example, a message such as "Company A's new model has received high praise in reviews of the latest smartphones" is displayed on the screen, and the advertisement disappears.

[1040] Specific examples

[1041] 1. A user types the search prompt "What are the latest smartphone reviews?"

[1042] 2. The server receives the prompt and uses the emotion engine to recognize the user's emotion as "excited."

[1043] 3. The server generates the search query "latest smartphone reviews" based on the prompt and the perceived sentiment.

[1044] 4. The server selects a "new product campaign ad" based on the search query and "excitement."

[1045] 5. The device displays the advertisement and shows the "New Product Campaign Ad" to the user until the generation AI generates the final output.

[1046] 6. The server collects and analyzes data related to "Latest Smartphone Reviews."

[1047] 7. The server uses the AI ​​to generate a response such as, "Company A's new model has received high marks in reviews of the latest smartphones."

[1048] 8. The device will display the final output and hide the ads at the same time.

[1049] These steps allow users to view relevant ads while they wait, and then receive a response from the generation AI. Furthermore, the emotion engine provides ad displays and responses based on the user's emotions, creating a more personalized experience. This system uses advertising revenue to cover the operating costs of the generation AI, ensuring sustainable service provision.

[1050] The processing flow will be explained below.

[1051] Step 1:

[1052] A user inputs a search prompt into the device, for example, "Tell me reviews of the latest smartphones." The input prompt is sent to the server.

[1053] Step 2:

[1054] The server analyzes the received prompt and uses an emotion engine to recognize the user's emotion, for example, emotions such as "excited" or "frustrated" are identified from the prompt.

[1055] Step 3:

[1056] The server generates a search query based on the prompt and the recognized sentiment. For example, the prompt "Tell me reviews of the latest smartphones" is converted into the search query "Latest smartphone reviews."

[1057] Step 4:

[1058] The server selects relevant advertisements based on the search query and the recognized emotion. For example, a user in an "excited" state might be shown a "new product campaign advertisement," while a user in a "dissatisfied" state might be shown a "specific problem-solving advertisement."

[1059] Step 5:

[1060] The device will display selected ads until the final output is generated by the AI. The ads will be displayed randomly or in order. For example, a "new product campaign ad" will be displayed longer to excited users.

[1061] Step 6:

[1062] The server collects information from multiple data sources based on the search query, for example, by using web scraping techniques to gather reviews and user ratings of the latest smartphones.

[1063] Step 7:

[1064] The server analyzes the collected information, for example, by processing the collected reviews and ratings data and extracting particularly important information.

[1065] Step 8:

[1066] The server uses generative AI to generate the final output. Based on the analysis results and the recognized sentiment, it generates an appropriate response to the user's prompt. For example, the response might be, "Reviews of the latest smartphones give high marks to the new model from company A."

[1067] Step 9:

[1068] The device displays the final output of the AI ​​generation. At the same time as showing the generated response to the user, the displayed advertisement is hidden. For example, a message such as "Company A's new model has received high praise in reviews of the latest smartphones" is displayed on the screen, and the advertisement disappears.

[1069] Through these steps, users can view relevant ads while waiting and then receive a response from the AI. This system uses advertising revenue to cover the operating costs of the AI, ensuring sustainable service provision. The emotion engine provides ad display and responses based on the user's emotions, enabling a more personalized experience.

[1070] Example 2

[1071] 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."

[1072] Previous systems simply generated search queries based on user prompts and displayed relevant ads. This resulted in uniform ad display without considering user sentiment, making it difficult to achieve a personalized experience. Furthermore, effective ad display was not possible during the waiting time for the AI ​​to generate a response based on the search query, making it difficult to optimize advertising revenue.

[1073] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1074] In this invention, the server includes means for [using an emotion engine to analyze prompts and identify emotions], means for [generating search queries based on the prompts and the recognized emotions], and means for [selecting relevant advertisements based on the search queries and emotions]. This enables personalized advertisement display that takes user emotions into consideration and appropriate response generation by the generation AI.

[1075] "User" refers to an individual or entity that utilizes the System to search for information and receive responses.

[1076] A "prompt" refers to a search or question keyword or phrase that a user enters into the system.

[1077] "Server" refers to a computer within a system that processes, analyzes, and provides information.

[1078] An "emotion engine" refers to natural language processing algorithms or software that identify emotions from user prompts.

[1079] "Search query" refers to the keywords or phrases used in a search that are generated based on prompts and perceived sentiment.

[1080] "Advertising" means commercial messages or content that are selected and displayed to users based on their search queries and user sentiment.

[1081] "Generative AI" refers to artificial intelligence algorithms or software that generate appropriate responses based on collected information and user sentiment.

[1082] "Data Source" means a website, database, or other source used to provide information relevant to a Search Query.

[1083] "Final output" refers to the final response or result generated by the generative AI and provided to the user.

[1084] "Device" refers to a device, such as a computer, smartphone, or tablet, used by a user to enter prompts and display responses and advertisements.

[1085] The present invention is a system that receives user prompts, performs emotion identification, and displays relevant advertisements to generate personalized responses. To implement this system, the following processes must be performed:

[1086] First, the user inputs a search prompt into the device. For example, the user inputs a prompt such as "Tell me reviews of the latest smartphones." The input prompt is sent from the device to the server.

[1087] The server then analyzes the received prompt using an emotion engine to identify the user's emotion from the prompt. This emotion engine uses natural language processing (NLP) techniques to extract emotions such as "excitement," "interest," and "frustration."

[1088] After the emotion is identified, the server generates a search query based on the prompt and the recognized emotion, for example, "latest smartphone reviews," which is used against databases within the server and sources on the Internet.

[1089] The server then selects relevant advertisements based on the generated search query and the user's emotions. The advertisements are retrieved from a database and the one that best matches the user's emotions is selected. For example, a user in an "excited" state might be shown a "new product campaign advertisement."

[1090] The device then displays the selected advertisements until the final output is generated. The advertisements are displayed randomly or sequentially, and the display time and content of the advertisements are adjusted according to the user's emotions. For example, a "new product campaign advertisement" may be displayed longer to an excited user.

[1091] The server then processes the search query to gather the necessary information from multiple sources. For example, it uses web scraping technology to gather reviews and user ratings. The collected data is then analyzed and the generative AI generates the final output, which also takes into account user sentiment.

[1092] Finally, the device displays the final output of the generated AI to the user. For example, it displays a response such as, "Reviews of the latest smartphones have given high marks to the new model from company A," while simultaneously hiding the advertisement. This allows the user to obtain efficient and personalized information.

[1093] As a concrete example of how this system works, the following series of procedures will be explained:

[1094] 1. A user types the search prompt "What are the latest smartphone reviews?"

[1095] 2. The server receives the prompt and uses the emotion engine to recognize the user's emotion as "excited."

[1096] 3. The server generates the search query "latest smartphone reviews" based on the prompt and the perceived sentiment.

[1097] 4. The server selects a "new product campaign ad" based on the search query and "excitement."

[1098] 5. The device displays the advertisement and shows the "New Product Campaign Ad" to the user until the generation AI generates the final output.

[1099] 6. The server collects and analyzes data related to "Latest Smartphone Reviews."

[1100] 7. The server uses the AI ​​to generate a response such as, "Company A's new model has received high marks in reviews of the latest smartphones."

[1101] 8. The device will display the final output and hide the ads at the same time.

[1102] This allows users to view relevant ads while they wait, and then receive personalized responses from the AI. This system uses advertising revenue to cover the operating costs of the AI, ensuring sustainable service provision.

[1103] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1104] Step 1:

[1105] A user inputs a search prompt into a device. The input prompt, for example, "Tell me reviews of the latest smartphones," is sent from the device to a server. Specifically, the user inputs text into the search bar and clicks the "Submit" button, which sends the prompt to the server.

[1106] Input: The prompt string entered by the user

[1107] Output: Prompt data sent to the server

[1108] Step 2:

[1109] The server receives a prompt from the user. The received prompt is sent for parsing. Specifically, the server takes the prompt string and converts it into a data format to be passed to the next processing step.

[1110] Input: Prompt data submitted by the user

[1111] Output: prompt data for analysis

[1112] Step 3:

[1113] The server uses an emotion engine to identify the emotion of the prompt. The emotion engine uses natural language processing technology to identify, for example, "excitement," "interest," or "frustration." Specifically, it analyzes the prompt string and generates emotion data by adding emotion tags.

[1114] Input: Prompt data for analysis

[1115] Output: Data containing the identified emotions

[1116] Step 4:

[1117] The server generates a search query based on the prompt and the identified emotion. For example, the prompt "Tell me reviews of the latest smartphones" is tagged with the emotion "excited," generating the search query "latest smartphone reviews."

[1118] Input: prompt data and emotion data

[1119] Output: Generated search query

[1120] Step 5:

[1121] The server selects relevant advertisements based on the generated search query and the identified emotion. For example, a "new product campaign advertisement" is selected for a user who is "excited" by searching the advertisement database.

[1122] Input: Generated search queries and sentiment data

[1123] Output: Selected advertising data

[1124] Step 6:

[1125] The device displays the advertisements sent from the server. The advertisements are displayed randomly or sequentially until the generation AI generates the final output. For example, a "new product campaign advertisement" is displayed on the user's screen, and the display time is adjusted according to the user's emotions.

[1126] Input: Selected advertising data

[1127] Output: Advertisement displayed on user device

[1128] Step 7:

[1129] The server collects relevant information from multiple data sources based on the search query, using web scraping technology to collect reviews and user ratings, which are used as input data for the generation AI.

[1130] Input: Generated search query

[1131] Output: Collected data (reviews, user ratings, etc.)

[1132] Step 8:

[1133] The server generates the final output from the generative AI based on the collected information and the identified emotions, for example, generating a response such as, "Reviews of the latest smartphones give high marks to the new model from company A."

[1134] Input: Collected data and identified emotion data

[1135] Output: The final output data (response) generated

[1136] Step 9:

[1137] The device displays the final output of the generated AI and hides the advertisement. For example, it displays "Company A's new model has received high praise in reviews of the latest smartphones," and at the same time, the advertisement that was being displayed up until then disappears.

[1138] Input: The final output data generated

[1139] Output: The final response and disappearing ad displayed on the user's device

[1140] (Application example 2)

[1141] 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."

[1142] Conventional advertising display systems can only display generic ads without considering user emotions, which does not improve the user experience and limits the effectiveness of ads. Furthermore, users become frustrated with the wait time it takes for the AI ​​to generate a response. Therefore, there is a need for a system that can identify user emotions and optimize the content and display time of ads based on those emotions.

[1143] 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.

[1144] In this invention, the server includes means for receiving a prompt from a user, means for generating a search query from the prompt, means for selecting a relevant advertisement based on the search query, means for displaying an advertisement on the terminal until a final output of the AI ​​for the generated search query is generated, means for collecting and analyzing information from multiple data sources, means for displaying the final output of the generated AI on the terminal while simultaneously hiding the advertisement, means for recognizing the user's emotions and adjusting the content and display time of the advertisement based on the emotions, and means for generating a search query based on the emotions and selecting an advertisement based on the search query. This enables personalized advertisement display according to the user's emotions, improving the user experience and maximizing advertising effectiveness.

[1145] The "means for receiving prompts from a user" is a function that receives prompts such as search requests or questions entered by a user into a terminal and transmits them to a server.

[1146] "Means for generating search queries from prompts" refers to a function that generates appropriate search queries based on received prompts. These search queries form the basis for information gathering and ad selection by the generation AI.

[1147] The "means for selecting relevant advertisements based on a search query" is a function for selecting advertisements corresponding to the generated search query from a database and displaying the advertisements appropriately.

[1148] "Means for displaying advertisements on a device until the final output of the AI ​​for the generated search query is generated" refers to a function that displays selected advertisements on a user's device during the waiting time until the final output of the AI ​​based on the search query is displayed.

[1149] "Means for collecting and analyzing information from multiple data sources" refers to a function for collecting necessary information from multiple information sources based on the generated search query and analyzing it.

[1150] "Means for displaying the final output of the generated AI on the device and simultaneously hiding advertisements" refers to a function that displays the final output of the generating AI on the user's device and simultaneously hides the advertisements that were displayed.

[1151] "Means for recognizing user emotions and adjusting the content and display time of advertisements based on those emotions" refers to a function that identifies the user's emotions from prompts and optimizes the content and display time of advertisements based on those emotions.

[1152] "Means for generating search queries based on emotions and selecting advertisements based on those" refers to a function that generates search queries taking into account recognized emotions and selects advertisements based on those queries.

[1153] This invention is a system that displays relevant advertisements based on a user's search prompts and emotions, and generates optimal output using a generative AI model. The system is mainly composed of a server, a terminal, and an emotion engine.

[1154] Program Overview

[1155] 1. Receiving prompts:

[1156] A user enters a search prompt into a terminal, for example, "What's the best destination for my next trip?"

[1157] The entered prompt is sent to the server.

[1158] 2. Emotion Recognition:

[1159] The server analyzes the received prompt and uses an emotion engine to recognize the user's emotions, for example, emotions such as "excitement," "anticipation," and "anxiety."

[1160] 3. Generating a search query:

[1161] The server generates a search query based on the prompt and the recognized sentiment, for example, "next travel destination."

[1162] 4. Advertisement Selection:

[1163] The server selects relevant advertisements based on the generated search query and emotion. It retrieves advertisements that match the search query and emotion from the database and creates an appropriate advertisement list. For example, for a user in an "excited" state, "new travel campaign advertisements" are selected.

[1164] 5. Display of advertisements:

[1165] The device displays selected ads until the final output is generated by the AI. The ads are displayed randomly or sequentially. The display time and content of the ads are also adjusted depending on the user's emotions. For example, a "new travel campaign ad" is displayed longer to an excited user.

[1166] 6. Data Collection and Analysis:

[1167] The server gathers information from multiple sources based on the search query, for example, using web scraping techniques to gather related travel articles and user ratings, using Python's requests library.

[1168] 7. Generative AI Generates Output:

[1169] The server uses generative AI to generate the final output based on the collected information and the recognized emotion. For example, it generates a response such as "Hawaii is a particularly good choice for your next trip." If the emotion is "anxiety," it also details safety and the weather. Generative AI uses language models such as GPT-3.

[1170] 8. Display AI results and hide ads:

[1171] The device displays the final output of the AI ​​generation. At the same time as showing the generated response to the user, the ad that was being displayed disappears. For example, a message saying "Hawaii is a particularly good choice for your next trip" appears on the screen, and the ad disappears.

[1172] Hardware and software used

[1173] Hardware:

[1174] User's device (smartphone, tablet, PC, etc.)

[1175] Server (data processing, storage, generative AI execution)

[1176] software:

[1177] Sentiment engine (using natural language processing libraries such as the BERT model)

[1178] Advertisement selection system (machine learning model, database system)

[1179] Data collection tools (such as the Python requests library)

[1180] Generative AI (language models such as GPT-3)

[1181] User interface (React Native, Flutter, etc.)

[1182] Specific examples

[1183] A user enters a search prompt: "What is the best destination for my next trip?" The server receives the prompt and uses an emotion engine to recognize the user's emotion as "excitement." Based on the prompt and the recognized emotion, the server generates a search query: "next travel destination." The server then selects travel-related advertisements and displays "New Travel Campaign Ads."

[1184] Based on the collected information, the server uses generative AI to generate the final output. For example, it might generate a response like, "Hawaii is a great place to visit next." This output is then displayed on the device, while the ad is hidden.

[1185] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1186] Step 1:

[1187] A user inputs a search prompt into a terminal. Specifically, the user inputs the prompt "What is the best destination for my next trip?", and the prompt is sent from the terminal to a server. The input data is the user's search request, and the output data is the prompt sent to the server.

[1188] Step 2:

[1189] The server analyzes the received prompt. In this step, the server passes the prompt to the emotion engine, which uses natural language processing techniques (e.g., the BERT model) to recognize the user's emotion. The input data is the user's prompt, and the output data is the recognized user emotion (e.g., "excited").

[1190] Step 3:

[1191] The server generates a search query based on the prompt and the recognized sentiment. Specifically, the server generates a search query for "next travel destination." The input data are the prompt and sentiment, and the output data is the generated search query.

[1192] Step 4:

[1193] The server selects relevant advertisements based on the generated search query and sentiment. Here, the server searches for appropriate advertisements from the advertisement database and selects "new travel campaign advertisements" for users in the "excited" state. The input data are the search query and sentiment, and the output data is the selected advertisement list.

[1194] Step 5:

[1195] The device displays the selected ads until the final output is generated by the AI. Specifically, the ads are displayed on the screen so that the user can view them. The input data is the selected ad list, and the output data is the ads displayed on the device.

[1196] Step 6:

[1197] The server collects and analyzes information based on the search query. In this step, the server collects relevant information using web scraping or API requests, and processes the data using analysis software (e.g., Python's requests library). The input data is the search query, and the output data is the collected and analyzed information.

[1198] Step 7:

[1199] The server uses generative AI to generate the final output based on the collected information and the recognized emotions. For example, the server uses GPT-3 to generate a response such as "Hawaii is a highly recommended destination for your next trip." The input data are the collected information and emotions, and the output data is the generated final output.

[1200] Step 8:

[1201] The terminal displays the final output of the generated AI and simultaneously hides the advertisements. Here, the terminal displays the generated response message and removes the advertisements from the screen. The input data is the final output message and the advertisement list, and the output data is the final message displayed to the user and the advertisements to be hidden.

[1202] 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.

[1203] 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.

[1204] 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.

[1205] [Fourth embodiment]

[1206] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1207] 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.

[1208] 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).

[1209] 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.

[1210] 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.

[1211] 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).

[1212] 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.

[1213] 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.

[1214] 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.

[1215] 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.

[1216] 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.

[1217] 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.

[1218] 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."

[1219] This invention is a system that generates a search query based on a prompt input by a user and displays related advertisements. The advertisements are displayed while the AI ​​is waiting to generate the final output. When the final output is displayed on the device, the advertisements are hidden.

[1220] System program and processing description

[1221] 1. Receiving a prompt

[1222] A user enters a search prompt into a device, for example, "Tell me reviews of the latest smartphones."

[1223] 2. Generating a search query

[1224] The server generates a search query based on the prompt received from the user, for example, "latest smartphone reviews."

[1225] 3. Ad selection

[1226] The server selects advertisements from the database that are relevant to the generated search query, for example, "Smartphone Ad 1," "Smartphone Ad 2," and "Smartphone Ad 3."

[1227] 4. Display of advertisements

[1228] The device will display the selected ads, either randomly or sequentially, until the AI ​​generates the search results.

[1229] 5. Data Collection and Analysis

[1230] The server collects information from multiple sources based on the search query and analyzes this data, for example, by collecting and analyzing reviews and user ratings of the latest smartphones.

[1231] 6. Generative AI Generates Output

[1232] Based on the data collected by the server, a generative AI (e.g., a large-scale language model) generates a response to the user prompt, for example, "Reviews of the latest smartphones give high marks to the new model from company A."

[1233] 7. Display AI results and hide ads

[1234] The device displays the generated final output and simultaneously hides the advertisement. For example, it displays the output "The latest smartphone reviews have given high marks to the new model from company A," and then removes the advertisement from the screen.

[1235] Specific examples

[1236] 1. A user types the search prompt "What are the latest smartphone reviews?"

[1237] 2. The server receives the prompt and translates it into the search query "latest smartphone reviews."

[1238] 3. The server selects "Smartphone Ad 1," "Smartphone Ad 2," and "Smartphone Ad 3" based on the search query.

[1239] 4. The device displays the ads and shows them to the user while the generation AI generates the final output.

[1240] 5. The server collects and analyzes data related to "Latest Smartphone Reviews."

[1241] 6. The server uses the AI ​​to generate a response such as, "Company A's new model has received high marks in reviews of the latest smartphones."

[1242] 7. The device will display the final output and hide the ads at the same time.

[1243] These steps allow users to view relevant ads during the waiting time and then receive a response from the AI. This system uses advertising revenue to cover the operating costs of the AI, ensuring sustainable service provision.

[1244] The processing flow will be explained below.

[1245] Step 1:

[1246] A user inputs a search prompt into the device, for example, "Tell me reviews of the latest smartphones." The input prompt is sent to the server.

[1247] Step 2:

[1248] The server analyzes the received prompt and generates an appropriate search query based on the prompt content. For example, the prompt "Tell me reviews of the latest smartphones" is converted into the search query "Latest smartphone reviews."

[1249] Step 3:

[1250] The server selects relevant ads based on the search query. It retrieves ads related to the search query from the database and creates an appropriate ad list. For example, "Smartphone Ad 1," "Smartphone Ad 2," and "Smartphone Ad 3" are selected.

[1251] Step 4:

[1252] While the device is waiting for the final output from the AI ​​to be generated, the selected advertisements will be displayed. The advertisements will be displayed randomly or in order. For example, "Smartphone Ad 1," "Smartphone Ad 2," and "Smartphone Ad 3" will be displayed in sequence.

[1253] Step 5:

[1254] The server collects information from multiple sources based on the search query, for example, by using web scraping techniques to gather relevant reviews and user ratings.

[1255] Step 6:

[1256] The server analyzes the collected information, extracts the most relevant information from the collected data, and organizes the analysis results.

[1257] Step 7:

[1258] The server uses generative AI to generate the final output. Based on the analysis results, it generates an appropriate answer to the user's prompt. For example, it might generate a response like, "Reviews of the latest smartphones give high marks to the new model from company A."

[1259] Step 8:

[1260] The device displays the final output of the AI ​​generation. At the same time as showing the generated response to the user, the displayed advertisement is hidden. For example, a message such as "Company A's new model has received high praise in reviews of the latest smartphones" is displayed on the screen, and the advertisement disappears.

[1261] Through these steps, users can view relevant ads during the waiting time and then receive a response from the AI. This system uses advertising revenue to cover the operating costs of the AI, ensuring sustainable service provision.

[1262] Example 1

[1263] 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."

[1264] In conventional systems, if it takes a long time to generate search results, the user experience is degraded because nothing is displayed during the waiting time.In addition, the high operating costs of the generation AI make it difficult to provide a sustainable service.

[1265] 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.

[1266] In this invention, the server includes means for receiving a prompt from a user, means for generating a search query from the prompt, means for selecting relevant content based on the search query, means for displaying advertisements on the terminal until the final output of the generation AI for the generated search query is generated, means for collecting and analyzing information from multiple data sources, and means for displaying the final output of the generation AI on the terminal while simultaneously hiding advertisements. This makes it possible to improve the user experience while using advertising revenue to cover the operating costs of the generation AI.

[1267] "User" means an individual or entity who operates a terminal to enter prompts and obtain information using the system.

[1268] A "prompt" is a question or instruction that a user enters into a system.

[1269] "Search query" refers to a sentence or phrase used in a search that is generated based on a user prompt.

[1270] "Generative AI" refers to artificial intelligence models that generate natural language responses based on input data.

[1271] "Device" refers to the device (e.g., smartphone, computer, tablet) that a user uses to enter prompts and view generated AI responses and advertisements.

[1272] "Advertisement" means any text, image or video content displayed to a User for commercial purposes.

[1273] "Data Source" refers to the website, API, database, or other source used to collect information.

[1274] "Analysis" refers to the process of processing and analyzing collected data.

[1275] "Revenue" refers to the economic benefits derived from displaying advertisements.

[1276] The system of this invention allows users to input a prompt, retrieve related information based on it, and wait for the output of the AI ​​while displaying an advertisement. Specifically, the user, terminal, and server each play their respective roles to realize the overall process.

[1277] First, the user inputs a prompt such as "Tell me a review of the latest smartphone" into the device. The device detects this input and sends the prompt to the server using a communication method, primarily an internet connection.

[1278] The server receives the prompt and generates an appropriate search query using natural language processing (NLP) techniques. Specifically, it uses text analysis libraries (e.g., SpaCy, NLTK). For example, the prompt "Tell me reviews of the latest smartphones" is converted into the search query "Latest smartphone reviews."

[1279] The server then selects relevant ads from a pre-built ad database based on the search query. Each ad is associated with a specific keyword. For example, ads related to keywords like "smartphone" and "review" are selected.

[1280] The selected ad is sent to the device, which then displays it to the user. Ads are displayed randomly or sequentially, and are realized using UI components for displaying ads. Specifically, React and Vue.js libraries are used on the front end.

[1281] Meanwhile, the server collects information from multiple data sources (websites, APIs, databases, etc.) based on the search query. The collected data is processed using analytical libraries (e.g., Pandas, NumPy). For example, reviews and user ratings of the latest smartphones are collected and analyzed.

[1282] The server uses a generative AI model (e.g., GPT-3) based on the analyzed data to generate a response to the user prompt, such as "Company A's new model has received high marks in reviews of the latest smartphones."

[1283] Finally, the generated response is sent to the device, which displays it to the user. At the same time, the displayed ad is hidden. The UI components are updated to hide the ad.

[1284] This system allows users to view relevant ads while they wait, and then receive useful responses from the AI. Advertising revenue covers the AI's operating costs, enabling the service to be provided sustainably.

[1285] As a concrete example, let's assume that you input a prompt such as "Please tell me reviews of the latest smartphones." In response to this prompt, the server generates a search query for "latest smartphone reviews," selects relevant advertisements, and finally generates a response such as "Company A's new model is highly rated in reviews of the latest smartphones."

[1286] In this way, a mechanism is realized in which users can efficiently obtain information through the system while also compensating for operational costs by viewing advertisements.

[1287] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1288] Step 1:

[1289] Receiving prompts

[1290] The user inputs a prompt sentence into the terminal, such as "Tell me a review of the latest smartphone."

[1291] The terminal captures the prompt text entered and sends it to the server in its raw form.

[1292] Input: The prompt text entered by the user (e.g., "Tell me your review of the latest smartphones")

[1293] Output: Prompt sent from terminal to server

[1294] Step 2:

[1295] Generating a search query

[1296] The server parses the received prompt and converts it into an appropriate search query using natural language processing (NLP) techniques and parsing libraries (e.g., SpaCy, NLTK).

[1297] Input: Prompt sent from the terminal

[1298] Data processing: Using natural language processing technology, we analyze prompts and generate search queries (e.g., "latest smartphone reviews")

[1299] Output: Generated search query

[1300] Step 3:

[1301] Ad selection

[1302] The server selects relevant advertisements from an advertisement database based on the generated search query, filtering advertisements that match keywords in the query.

[1303] Input: Generated search query

[1304] Data processing: Filter and select advertisements from the advertisement database using related keywords (e.g., "Smartphone Ad 1," "Smartphone Ad 2," "Smartphone Ad 3")

[1305] Output: Selected ad list

[1306] Step 4:

[1307] Displaying ads

[1308] The device receives the advertising data sent from the server and displays it to the user. Front-end UI components (e.g., React, Vue.js) are used to display the advertisements.

[1309] Input: Ad list sent from the server

[1310] Specific operation: Advertisements are displayed randomly or sequentially on the user's device screen.

[1311] Output: Ad displayed on the user's device

[1312] Step 5:

[1313] Data collection and analysis

[1314] Based on the search query, the server collects relevant information from multiple data sources, including websites, APIs, databases, etc. The collected data is processed using analytical libraries (e.g., Pandas, NumPy).

[1315] Input: Generated search query

[1316] Data processing: Collect information from multiple sources and process and analyze the data using analytics libraries (e.g., reviews and user ratings of the latest smartphones).

[1317] Output: Analyzed data

[1318] Step 6:

[1319] Generative AI generates output

[1320] The server uses a generative AI model (e.g., GPT-3) based on the analyzed data to generate a response to the prompt.

[1321] Input: Parsed data, prompts for the generative AI model

[1322] Data processing: The generative AI model generates a response based on the prompt and the analyzed data (e.g., "Company A's new model is highly rated in reviews of the latest smartphones").

[1323] Output: The generated response text

[1324] Step 7:

[1325] Display AI results and hide ads

[1326] The device receives the generated response from the server and displays it to the user, simultaneously hiding the displayed ad, updating the UI components to hide the ad area, and displaying the response text.

[1327] Input: Generated response text

[1328] Specific operation: The advertisement display area is hidden and the response text is displayed on the user's device screen.

[1329] Output: The generated AI's response text displayed on the user's device

[1330] This process allows users to view relevant advertisements while they wait, and then obtain useful information from the AI. The advertising revenue can then be used to cover the operational costs of the AI.

[1331] (Application example 1)

[1332] 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."

[1333] A means of providing useful information to users during the waiting time between when they input a prompt and when the generation AI generates the final output is required. A mechanism is also required to effectively utilize revenue from displaying advertisements to cover the operational costs of the generation AI. Furthermore, it is also necessary to provide additional information related to the generated content in a timely manner.

[1334] 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.

[1335] In this invention, the server includes means for receiving a prompt from a user, means for generating a search query from the prompt, and means for selecting a relevant advertisement based on the search query. This makes it possible to display an appropriate advertisement between the time the user inputs the prompt and the time the generation AI generates the final output, and to display related data when the advertisement ends.

[1336] A "prompt" is a question or request that a user enters into a system.

[1337] A "search query" refers to a query to a search engine or database that is generated based on a user prompt.

[1338] "Advertisement" refers to content in the form of text, images, or video that introduces products or services to users.

[1339] "Generative AI" refers to artificial intelligence that provides a final output that is analyzed and generated based on user prompts.

[1340] "Data source" refers to the source of information, such as a website or database, from which information is collected.

[1341] "Terminal" refers to the device (e.g., smartphone, computer) that a user uses to enter prompts and receive output.

[1342] "Analysis" refers to the process of analyzing collected data and extracting information that meets the user's requirements.

[1343] "Hidden" refers to removing the advertisement from the device screen so that it is no longer visually perceptible to the user.

[1344] "Revenue" refers to the economic benefits obtained from displaying advertisements.

[1345] "Token cost" refers to the costs associated with the computing resources and data processing required to operate the generating AI.

[1346] "Additional display" refers to displaying supplemental information related to the generated content to provide the user with such information.

[1347] This invention is a system that generates search queries based on prompts entered by users, displays relevant ads, and provides the final output using a generative AI. Part of the system runs on a device such as a smartphone, while the other part runs on a server.

[1348] Hardware and software used

[1349] Hardware: Smartphones, computers

[1350] Software: Python 3, ad management software, generative AI models (e.g., GPT-3)

[1351] DETAILED DESCRIPTION OF THE EMBODIMENTS

[1352] 1. Receiving a prompt

[1353] The user types a prompt into the terminal. This prompt contains the user's question or request. For example, "What are the latest movie reviews?"

[1354] 2. Generating a search query

[1355] The device sends the input prompt to the server, which analyzes the prompt and generates an appropriate search query that is optimized for the user's needs, such as "latest movie reviews."

[1356] 3. Advertisement selection and display

[1357] Based on the generated search query, the server selects relevant ads from an advertising database. These ads can be in the form of text, images, or videos. The device displays the selected ads to the user while the generation AI generates the final output.

[1358] 4. Data Collection and Analysis

[1359] The server collects and analyzes the necessary information from multiple data sources based on the search query. This analysis process uses natural language processing technology to handle large amounts of data. Specific systems retrieve information by making database queries or API calls.

[1360] 5. Generative AI Generates Output

[1361] Based on the collected data and analysis results, the server uses a generative AI model to generate the final output in response to the user's prompt. For example, if the prompt is "Tell me the latest movie reviews," the output generated will be "Movie X is highly rated in the latest movie reviews."

[1362] 6. Display generated AI output and hide ads

[1363] The device displays the final generated output to the user while hiding the ads, and adds relevant data to the generated content, ensuring fast and accurate information for the user while also ensuring revenue from the ads displayed.

[1364] Example

[1365] If a user inputs the prompt "What is the recommended drama this month?", the system generates a search query "This month's recommended drama review" and displays advertisements such as "Products related to drama B are on sale!". While the advertisement is displayed, the server collects related data, and the generation AI generates the final output "This month's recommended drama is drama Y!", which is displayed on the device while hiding the advertisement.

[1366] Example prompt statement

[1367] "Tell me the latest movie reviews"

[1368] What's your recommended drama this month?

[1369] This embodiment allows users to efficiently obtain the information they expect, and advertising revenue can be used to cover the costs of operating the system.

[1370] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1371] Step 1:

[1372] The user enters the prompt

[1373] The user inputs a prompt into the terminal. The input prompt is a sentence containing the user's question or request. For example, the user might input "Tell me the latest movie reviews."

[1374] Type: "What's the latest movie review?"

[1375] Output: The prompt is typed into the terminal.

[1376] Step 2:

[1377] The terminal sends a prompt to the server

[1378] The terminal sends the entered prompt to the server, a process that occurs over the network.

[1379] Input: The prompt entered by the user

[1380] Output: A prompt is sent to the server

[1381] Step 3:

[1382] The server generates a search query from the prompt

[1383] The server analyzes the received prompt and generates a relevant search query, for example, "What are the latest movie reviews?"

[1384] Input: The prompt sent by the user ("What's the latest movie review?")

[1385] Output: Generated search query ("latest movie reviews")

[1386] Step 4:

[1387] The server selects relevant ads based on the search query.

[1388] The server selects relevant advertisements from the advertisement database based on the generated search query. The selected advertisements are then displayed on the device, so in this step the most relevant advertisement is selected. For example, for "latest movie reviews," movie-related product advertisements are selected.

[1389] Input: Search query ("Latest movie reviews")

[1390] Output: Selected advertisement ("Movie-related product advertisement")

[1391] Step 5:

[1392] Display ads on your device

[1393] The device displays selected advertisements sent from the server, which can be in image or video format.

[1394] Input: Ad sent by server

[1395] Output: Ads are displayed on the device

[1396] Step 6:

[1397] The server collects and analyzes information from multiple data sources.

[1398] Based on the search query, the server collects and analyzes relevant information from websites and databases. The collected data is then analyzed using natural language processing techniques. For example, the server collects and analyzes the latest movie reviews from a movie review site.

[1399] Input: Search query ("Latest movie reviews")

[1400] Output: Analyzed data (latest movie reviews)

[1401] Step 7:

[1402] Generative AI generates the final output

[1403] The server uses the parsed data to run a generative AI model and generate the final output in response to a user prompt, for example, "What are the latest movie reviews?", generating a response such as "Movie X is highly rated in the latest movie reviews."

[1404] Input: Parsed data

[1405] Output: Final output ("Movie X is highly rated in the latest movie reviews")

[1406] Step 8:

[1407] Display the final output on your device while hiding ads

[1408] The device displays the final output received from the server and simultaneously hides the advertisement that was being displayed. For example, it displays the output "Movie X is highly rated in the latest movie reviews" and removes the advertisement from the screen.

[1409] Input: Final output, currently displayed ad

[1410] Output: Show final output to user, hide ads

[1411] Step 9:

[1412] Viewing Additional Information

[1413] The device will display additional information related to the generated content in a timely manner, with the additional information primarily related to the final output.

[1414] Input: Data related to the final output

[1415] Output: Display additional information

[1416] 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.

[1417] The present invention is a system that generates search queries in response to user prompts and displays relevant advertisements. The system also incorporates an emotion engine that recognizes the user's emotions. The emotion engine identifies emotions from the user's prompts and adjusts the display of advertisements and the output of the generation AI based on the emotions.

[1418] System program and processing description

[1419] 1. Receiving a prompt

[1420] A user inputs a search prompt into the device, for example, "Tell me reviews of the latest smartphones." The input prompt is sent to the server.

[1421] 2. Emotional Recognition

[1422] The server analyzes the received prompt and uses an emotion engine to recognize the user's emotion, for example, emotions such as "excited," "excited," and "frustrated" are identified.

[1423] 3. Generating search queries

[1424] The server generates a search query based on the prompt and the recognized sentiment, for example, "latest smartphone reviews."

[1425] 4. Ad selection

[1426] The server selects relevant advertisements based on the generated search query and emotion. It retrieves advertisements that match the search query and emotion from the database and creates an appropriate advertisement list. For example, for a user in an "excited" state, "new product campaign advertisements" are selected.

[1427] 5. Display of advertisements

[1428] The device displays selected ads until the final output is generated by the AI. The ads are displayed randomly or in order. The display time and content of the ads are also adjusted depending on the user's emotions. For example, a "new product campaign ad" is displayed longer to an excited user.

[1429] 6. Data Collection and Analysis

[1430] The server collects information from multiple sources based on the search query, for example, by using web scraping techniques to gather relevant reviews and user ratings.

[1431] 7. Generative AI Generates Output

[1432] The server uses generative AI to generate the final output based on the collected information and the recognized emotion. For example, it generates a response such as, "Reviews of the latest smartphones give high marks to the new model from company A." If the emotion is "unhappy," it also details specific issues and areas for improvement.

[1433] 8. Display AI results and hide ads

[1434] The device displays the final output of the AI ​​generation. At the same time as showing the generated response to the user, the displayed advertisement is hidden. For example, a message such as "Company A's new model has received high praise in reviews of the latest smartphones" is displayed on the screen, and the advertisement disappears.

[1435] Specific examples

[1436] 1. A user types the search prompt "What are the latest smartphone reviews?"

[1437] 2. The server receives the prompt and uses the emotion engine to recognize the user's emotion as "excited."

[1438] 3. The server generates the search query "latest smartphone reviews" based on the prompt and the perceived sentiment.

[1439] 4. The server selects a "new product campaign ad" based on the search query and "excitement."

[1440] 5. The device displays the advertisement and shows the "New Product Campaign Ad" to the user until the generation AI generates the final output.

[1441] 6. The server collects and analyzes data related to "Latest Smartphone Reviews."

[1442] 7. The server uses the AI ​​to generate a response such as, "Company A's new model has received high marks in reviews of the latest smartphones."

[1443] 8. The device will display the final output and hide the ads at the same time.

[1444] These steps allow users to view relevant ads while they wait, and then receive a response from the generation AI. Furthermore, the emotion engine provides ad displays and responses based on the user's emotions, creating a more personalized experience. This system uses advertising revenue to cover the operating costs of the generation AI, ensuring sustainable service provision.

[1445] The processing flow will be explained below.

[1446] Step 1:

[1447] A user inputs a search prompt into the device, for example, "Tell me reviews of the latest smartphones." The input prompt is sent to the server.

[1448] Step 2:

[1449] The server analyzes the received prompt and uses an emotion engine to recognize the user's emotion, for example, emotions such as "excited" or "frustrated" are identified from the prompt.

[1450] Step 3:

[1451] The server generates a search query based on the prompt and the recognized sentiment. For example, the prompt "Tell me reviews of the latest smartphones" is converted into the search query "Latest smartphone reviews."

[1452] Step 4:

[1453] The server selects relevant advertisements based on the search query and the recognized emotion. For example, a user in an "excited" state might be shown a "new product campaign advertisement," while a user in a "dissatisfied" state might be shown a "specific problem-solving advertisement."

[1454] Step 5:

[1455] The device will display selected ads until the final output is generated by the AI. The ads will be displayed randomly or in order. For example, a "new product campaign ad" will be displayed longer to excited users.

[1456] Step 6:

[1457] The server collects information from multiple data sources based on the search query, for example, by using web scraping techniques to gather reviews and user ratings of the latest smartphones.

[1458] Step 7:

[1459] The server analyzes the collected information, for example, by processing the collected reviews and ratings data and extracting particularly important information.

[1460] Step 8:

[1461] The server uses generative AI to generate the final output. Based on the analysis results and the recognized sentiment, it generates an appropriate response to the user's prompt. For example, the response might be, "Reviews of the latest smartphones give high marks to the new model from company A."

[1462] Step 9:

[1463] The device displays the final output of the AI ​​generation. At the same time as showing the generated response to the user, the displayed advertisement is hidden. For example, a message such as "Company A's new model has received high praise in reviews of the latest smartphones" is displayed on the screen, and the advertisement disappears.

[1464] Through these steps, users can view relevant ads while waiting and then receive a response from the AI. This system uses advertising revenue to cover the operating costs of the AI, ensuring sustainable service provision. The emotion engine provides ad display and responses based on the user's emotions, enabling a more personalized experience.

[1465] Example 2

[1466] 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."

[1467] Previous systems simply generated search queries based on user prompts and displayed relevant ads. This resulted in uniform ad display without considering user sentiment, making it difficult to achieve a personalized experience. Furthermore, effective ad display was not possible during the waiting time for the AI ​​to generate a response based on the search query, making it difficult to optimize advertising revenue.

[1468] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1469] In this invention, the server includes means for [using an emotion engine to analyze prompts and identify emotions], means for [generating search queries based on the prompts and the recognized emotions], and means for [selecting relevant advertisements based on the search queries and emotions]. This enables personalized advertisement display that takes user emotions into consideration and appropriate response generation by the generation AI.

[1470] "User" refers to an individual or entity that utilizes the System to search for information and receive responses.

[1471] A "prompt" refers to a search or question keyword or phrase that a user enters into the system.

[1472] "Server" refers to a computer within a system that processes, analyzes, and provides information.

[1473] An "emotion engine" refers to natural language processing algorithms or software that identify emotions from user prompts.

[1474] "Search query" refers to the keywords or phrases used in a search that are generated based on prompts and perceived sentiment.

[1475] "Advertising" means commercial messages or content that are selected and displayed to users based on their search queries and user sentiment.

[1476] "Generative AI" refers to artificial intelligence algorithms or software that generate appropriate responses based on collected information and user sentiment.

[1477] "Data Source" means a website, database, or other source used to provide information relevant to a Search Query.

[1478] "Final output" refers to the final response or result generated by the generative AI and provided to the user.

[1479] "Device" refers to a device, such as a computer, smartphone, or tablet, used by a user to enter prompts and display responses and advertisements.

[1480] The present invention is a system that receives user prompts, performs emotion identification, and displays relevant advertisements to generate personalized responses. To implement this system, the following processes must be performed:

[1481] First, the user inputs a search prompt into the device. For example, the user inputs a prompt such as "Tell me reviews of the latest smartphones." The input prompt is sent from the device to the server.

[1482] The server then analyzes the received prompt using an emotion engine to identify the user's emotion from the prompt. This emotion engine uses natural language processing (NLP) techniques to extract emotions such as "excitement," "interest," and "frustration."

[1483] After the emotion is identified, the server generates a search query based on the prompt and the recognized emotion, for example, "latest smartphone reviews," which is used against databases within the server and sources on the Internet.

[1484] The server then selects relevant advertisements based on the generated search query and the user's emotions. The advertisements are retrieved from a database and the one that best matches the user's emotions is selected. For example, a user in an "excited" state might be shown a "new product campaign advertisement."

[1485] The device then displays the selected advertisements until the final output is generated. The advertisements are displayed randomly or sequentially, and the display time and content of the advertisements are adjusted according to the user's emotions. For example, a "new product campaign advertisement" may be displayed longer to an excited user.

[1486] The server then processes the search query to gather the necessary information from multiple sources. For example, it uses web scraping technology to gather reviews and user ratings. The collected data is then analyzed and the generative AI generates the final output, which also takes into account user sentiment.

[1487] Finally, the device displays the final output of the generated AI to the user. For example, it displays a response such as, "Reviews of the latest smartphones have given high marks to the new model from company A," while simultaneously hiding the advertisement. This allows the user to obtain efficient and personalized information.

[1488] As a concrete example of how this system works, the following series of procedures will be explained:

[1489] 1. A user types the search prompt "What are the latest smartphone reviews?"

[1490] 2. The server receives the prompt and uses the emotion engine to recognize the user's emotion as "excited."

[1491] 3. The server generates the search query "latest smartphone reviews" based on the prompt and the perceived sentiment.

[1492] 4. The server selects a "new product campaign ad" based on the search query and "excitement."

[1493] 5. The device displays the advertisement and shows the "New Product Campaign Ad" to the user until the generation AI generates the final output.

[1494] 6. The server collects and analyzes data related to "Latest Smartphone Reviews."

[1495] 7. The server uses the AI ​​to generate a response such as, "Company A's new model has received high marks in reviews of the latest smartphones."

[1496] 8. The device will display the final output and hide the ads at the same time.

[1497] This allows users to view relevant ads while they wait, and then receive personalized responses from the AI. This system uses advertising revenue to cover the operating costs of the AI, ensuring sustainable service provision.

[1498] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1499] Step 1:

[1500] A user inputs a search prompt into a device. The input prompt, for example, "Tell me reviews of the latest smartphones," is sent from the device to a server. Specifically, the user inputs text into the search bar and clicks the "Submit" button, which sends the prompt to the server.

[1501] Input: The prompt string entered by the user

[1502] Output: Prompt data sent to the server

[1503] Step 2:

[1504] The server receives a prompt from the user. The received prompt is sent for parsing. Specifically, the server takes the prompt string and converts it into a data format to be passed to the next processing step.

[1505] Input: Prompt data submitted by the user

[1506] Output: prompt data for analysis

[1507] Step 3:

[1508] The server uses an emotion engine to identify the emotion of the prompt. The emotion engine uses natural language processing technology to identify, for example, "excitement," "interest," or "frustration." Specifically, it analyzes the prompt string and generates emotion data by adding emotion tags.

[1509] Input: Prompt data for analysis

[1510] Output: Data containing the identified emotions

[1511] Step 4:

[1512] The server generates a search query based on the prompt and the identified emotion. For example, the prompt "Tell me reviews of the latest smartphones" is tagged with the emotion "excited," generating the search query "latest smartphone reviews."

[1513] Input: prompt data and emotion data

[1514] Output: Generated search query

[1515] Step 5:

[1516] The server selects relevant advertisements based on the generated search query and the identified emotion. For example, a "new product campaign advertisement" is selected for a user who is "excited" by searching the advertisement database.

[1517] Input: Generated search queries and sentiment data

[1518] Output: Selected advertising data

[1519] Step 6:

[1520] The device displays the advertisements sent from the server. The advertisements are displayed randomly or sequentially until the generation AI generates the final output. For example, a "new product campaign advertisement" is displayed on the user's screen, and the display time is adjusted according to the user's emotions.

[1521] Input: Selected advertising data

[1522] Output: Advertisement displayed on user device

[1523] Step 7:

[1524] The server collects relevant information from multiple data sources based on the search query, using web scraping technology to collect reviews and user ratings, which are used as input data for the generation AI.

[1525] Input: Generated search query

[1526] Output: Collected data (reviews, user ratings, etc.)

[1527] Step 8:

[1528] The server generates the final output from the generative AI based on the collected information and the identified emotions, for example, generating a response such as, "Reviews of the latest smartphones give high marks to the new model from company A."

[1529] Input: Collected data and identified emotion data

[1530] Output: The final output data (response) generated

[1531] Step 9:

[1532] The device displays the final output of the generated AI and hides the advertisement. For example, it displays "Company A's new model has received high praise in reviews of the latest smartphones," and at the same time, the advertisement that was being displayed up until then disappears.

[1533] Input: The final output data generated

[1534] Output: The final response and disappearing ad displayed on the user's device

[1535] (Application example 2)

[1536] 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."

[1537] Conventional advertising display systems can only display generic ads without considering user emotions, which does not improve the user experience and limits the effectiveness of ads. Furthermore, users become frustrated with the wait time it takes for the AI ​​to generate a response. Therefore, there is a need for a system that can identify user emotions and optimize the content and display time of ads based on those emotions.

[1538] 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.

[1539] In this invention, the server includes means for receiving a prompt from a user, means for generating a search query from the prompt, means for selecting a relevant advertisement based on the search query, means for displaying an advertisement on the terminal until a final output of the AI ​​for the generated search query is generated, means for collecting and analyzing information from multiple data sources, means for displaying the final output of the generated AI on the terminal while simultaneously hiding the advertisement, means for recognizing the user's emotions and adjusting the content and display time of the advertisement based on the emotions, and means for generating a search query based on the emotions and selecting an advertisement based on the search query. This enables personalized advertisement display according to the user's emotions, improving the user experience and maximizing advertising effectiveness.

[1540] The "means for receiving prompts from a user" is a function that receives prompts such as search requests or questions entered by a user into a terminal and transmits them to a server.

[1541] "Means for generating search queries from prompts" refers to a function that generates appropriate search queries based on received prompts. These search queries form the basis for information gathering and ad selection by the generation AI.

[1542] The "means for selecting relevant advertisements based on a search query" is a function for selecting advertisements corresponding to the generated search query from a database and displaying the advertisements appropriately.

[1543] "Means for displaying advertisements on a device until the final output of the AI ​​for the generated search query is generated" refers to a function that displays selected advertisements on a user's device during the waiting time until the final output of the AI ​​based on the search query is displayed.

[1544] "Means for collecting and analyzing information from multiple data sources" refers to a function for collecting necessary information from multiple information sources based on the generated search query and analyzing it.

[1545] "Means for displaying the final output of the generated AI on the device and simultaneously hiding advertisements" refers to a function that displays the final output of the generating AI on the user's device and simultaneously hides the advertisements that were displayed.

[1546] "Means for recognizing user emotions and adjusting the content and display time of advertisements based on those emotions" refers to a function that identifies the user's emotions from prompts and optimizes the content and display time of advertisements based on those emotions.

[1547] "Means for generating search queries based on emotions and selecting advertisements based on those" refers to a function that generates search queries taking into account recognized emotions and selects advertisements based on those queries.

[1548] This invention is a system that displays relevant advertisements based on a user's search prompts and emotions, and generates optimal output using a generative AI model. The system is mainly composed of a server, a terminal, and an emotion engine.

[1549] Program Overview

[1550] 1. Receiving prompts:

[1551] A user enters a search prompt into a terminal, for example, "What's the best destination for my next trip?"

[1552] The entered prompt is sent to the server.

[1553] 2. Emotion Recognition:

[1554] The server analyzes the received prompt and uses an emotion engine to recognize the user's emotions, for example, emotions such as "excitement," "anticipation," and "anxiety."

[1555] 3. Generating a search query:

[1556] The server generates a search query based on the prompt and the recognized sentiment, for example, "next travel destination."

[1557] 4. Advertisement Selection:

[1558] The server selects relevant advertisements based on the generated search query and emotion. It retrieves advertisements that match the search query and emotion from the database and creates an appropriate advertisement list. For example, for a user in an "excited" state, "new travel campaign advertisements" are selected.

[1559] 5. Display of advertisements:

[1560] The device displays selected ads until the final output is generated by the AI. The ads are displayed randomly or sequentially. The display time and content of the ads are also adjusted depending on the user's emotions. For example, a "new travel campaign ad" is displayed longer to an excited user.

[1561] 6. Data Collection and Analysis:

[1562] The server gathers information from multiple sources based on the search query, for example, using web scraping techniques to gather related travel articles and user ratings, using Python's requests library.

[1563] 7. Generative AI Generates Output:

[1564] The server uses generative AI to generate the final output based on the collected information and the recognized emotion. For example, it generates a response such as "Hawaii is a particularly good choice for your next trip." If the emotion is "anxiety," it also details safety and the weather. Generative AI uses language models such as GPT-3.

[1565] 8. Display AI results and hide ads:

[1566] The device displays the final output of the AI ​​generation. At the same time as showing the generated response to the user, the ad that was being displayed disappears. For example, a message saying "Hawaii is a particularly good choice for your next trip" appears on the screen, and the ad disappears.

[1567] Hardware and software used

[1568] Hardware:

[1569] User's device (smartphone, tablet, PC, etc.)

[1570] Server (data processing, storage, generative AI execution)

[1571] software:

[1572] Sentiment engine (using natural language processing libraries such as the BERT model)

[1573] Advertisement selection system (machine learning model, database system)

[1574] Data collection tools (such as the Python requests library)

[1575] Generative AI (language models such as GPT-3)

[1576] User interface (React Native, Flutter, etc.)

[1577] Specific examples

[1578] A user enters a search prompt: "What is the best destination for my next trip?" The server receives the prompt and uses an emotion engine to recognize the user's emotion as "excitement." Based on the prompt and the recognized emotion, the server generates a search query: "next travel destination." The server then selects travel-related advertisements and displays "New Travel Campaign Ads."

[1579] Based on the collected information, the server uses generative AI to generate the final output. For example, it might generate a response like, "Hawaii is a great place to visit next." This output is then displayed on the device, while the ad is hidden.

[1580] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1581] Step 1:

[1582] A user inputs a search prompt into a terminal. Specifically, the user inputs the prompt "What is the best destination for my next trip?", and the prompt is sent from the terminal to a server. The input data is the user's search request, and the output data is the prompt sent to the server.

[1583] Step 2:

[1584] The server analyzes the received prompt. In this step, the server passes the prompt to the emotion engine, which uses natural language processing techniques (e.g., the BERT model) to recognize the user's emotion. The input data is the user's prompt, and the output data is the recognized user emotion (e.g., "excited").

[1585] Step 3:

[1586] The server generates a search query based on the prompt and the recognized sentiment. Specifically, the server generates a search query for "next travel destination." The input data are the prompt and sentiment, and the output data is the generated search query.

[1587] Step 4:

[1588] The server selects relevant advertisements based on the generated search query and sentiment. Here, the server searches for appropriate advertisements from the advertisement database and selects "new travel campaign advertisements" for users in the "excited" state. The input data are the search query and sentiment, and the output data is the selected advertisement list.

[1589] Step 5:

[1590] The device displays the selected ads until the final output is generated by the AI. Specifically, the ads are displayed on the screen so that the user can view them. The input data is the selected ad list, and the output data is the ads displayed on the device.

[1591] Step 6:

[1592] The server collects and analyzes information based on the search query. In this step, the server collects relevant information using web scraping or API requests, and processes the data using analysis software (e.g., Python's requests library). The input data is the search query, and the output data is the collected and analyzed information.

[1593] Step 7:

[1594] The server uses generative AI to generate the final output based on the collected information and the recognized emotions. For example, the server uses GPT-3 to generate a response such as "Hawaii is a highly recommended destination for your next trip." The input data are the collected information and emotions, and the output data is the generated final output.

[1595] Step 8:

[1596] The terminal displays the final output of the generated AI and simultaneously hides the advertisements. Here, the terminal displays the generated response message and removes the advertisements from the screen. The input data is the final output message and the advertisement list, and the output data is the final message displayed to the user and the advertisements to be hidden.

[1597] 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.

[1598] 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.

[1599] 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.

[1600] 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.

[1601] 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.

[1602] 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.

[1603] 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).

[1604] 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.

[1605] 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."

[1606] 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.

[1607] 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).

[1608] 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.

[1609] 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.

[1610] 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.

[1611] 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.

[1612] 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.

[1613] 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.

[1614] 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.

[1615] 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.

[1616] 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.

[1617] 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.

[1618] The following is further disclosed regarding the above embodiment.

[1619] (Claim 1)

[1620] a means for receiving a prompt from the user;

[1621] A means to generate a search query from a prompt;

[1622] A means to select relevant ads based on a search query; and

[1623] [Means to display advertisements on the device until the final AI output for the generated search query is generated];

[1624] A means to collect and analyze information from multiple data sources;

[1625] [The final output of the generated AI is displayed on the device while the ads are hidden],

[1626] A system including:

[1627] (Claim 2)

[1628] [The advertisements based on the generated search queries include not only text advertisements but also image advertisements and video advertisements];

[1629] 2. The system of claim 1,

[1630] (Claim 3)

[1631] [Reimbursing the cost of the search result generation AI by using revenue from advertising display as a token cost],

[1632] 2. The system of claim 1,

[1633] "Example 1"

[1634] (Claim 1)

[1635] a means for receiving a prompt from the user;

[1636] A means to generate a search query from a prompt;

[1637] A means to select relevant content based on a search query;

[1638] a means for displaying advertisements on the device until the final output of the generation AI for the generated search query is generated;

[1639] A means to collect and analyze information from multiple data sources;

[1640] [Displaying the final output of the generated AI on the device while hiding advertisements],

[1641] A system including:

[1642] (Claim 2)

[1643] [The advertisements based on the generated search queries include not only text advertisements but also image advertisements and video advertisements];

[1644] 2. The system of claim 1,

[1645] (Claim 3)

[1646] [Reimbursing the operational costs of the result-generating AI by using revenue from displaying advertisements to cover the operational costs];

[1647] 2. The system of claim 1,

[1648] "Application Example 1"

[1649] (Claim 1)

[1650] a means for receiving a prompt from the user;

[1651] A means to generate a search query from a prompt;

[1652] A means to select relevant ads based on a search query; and

[1653] [Means to display advertisements on the device until the final AI output for the generated search query is generated];

[1654] A means to collect and analyze information from multiple data sources;

[1655] [The final output of the generated AI is displayed on the device while the ads are hidden],

[1656] A means for displaying additional data related to the generated content when the advertisement ends;

[1657] A system including:

[1658] (Claim 2)

[1659] 2. The system of claim 1, wherein the advertisements based on the generated search queries include not only text advertisements but also image advertisements and video advertisements.

[1660] (Claim 3)

[1661] The system described in claim 1 [compensates for the cost of the search result generation AI by using revenue from advertising display as token costs].

[1662] "Example 2: Combining Emotion Engines"

[1663] (Claim 1)

[1664] a means for receiving a prompt from the user;

[1665] [using an emotion engine that analyzes the prompt and identifies the emotion];

[1666] means for generating a search query based on the prompt and the recognized sentiment;

[1667] A means to select relevant ads based on search queries and sentiment;

[1668] a means for displaying advertisements on the device until the final output of the generation AI for the generated search query is generated;

[1669] A means to collect and analyze information from multiple data sources;

[1670] A means for generating a final output using generative AI based on collected information and emotions; and

[1671] [The final output of the generated AI is displayed on the device while the ads are hidden],

[1672] A system including:

[1673] (Claim 2)

[1674] [The advertisements based on the generated search queries include not only text advertisements but also image advertisements and video advertisements];

[1675] 2. The system of claim 1,

[1676] (Claim 3)

[1677] [Reimbursing the operating costs of the generative AI model by using revenue from displaying ads];

[1678] 2. The system of claim 1,

[1679] "Application example 2 when combining emotion engines"

[1680] (Claim 1)

[1681] a means for receiving a prompt from the user;

[1682] A means to generate a search query from a prompt;

[1683] A means to select relevant ads based on a search query; and

[1684] [Means to display advertisements on the device until the final AI output for the generated search query is generated];

[1685] A means to collect and analyze information from multiple data sources;

[1686] [The final output of the generated AI is displayed on the device while the ads are hidden],

[1687] A means to recognize user emotions and adjust the content and duration of advertisements accordingly;

[1688] A means to generate search queries based on sentiment and select ads based on those queries;

[1689] A system including:

[1690] (Claim 2)

[1691] [The advertisements based on the generated search queries include not only text advertisements but also image advertisements and video advertisements];

[1692] 2. The system of claim 1,

[1693] (Claim 3)

[1694] [Recovering the operational costs of the search result generation AI by using revenue from advertising display to cover the cost of tokens],

[1695] 2. The system of claim 1, [Explanation of symbols]

[1696] 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. means for receiving a prompt from a user; a means for generating a search query from the prompt; a means for selecting relevant advertisements based on a search query; a means for displaying advertisements on the device until the final output of the AI ​​for the generated search query is generated; a means for collecting and analyzing information from multiple data sources; A way to display the final output of the generated AI on the device while hiding advertisements, A system including:

2. A means for advertising based on the generated search query to include not only text advertising but also image advertising and video advertising; 2. The system of claim 1, wherein:

3. By using revenue from advertising display as a token cost, we can offset the costs of the search result generation AI.

2. The system of claim 1, wherein:

Images