Information processing device, information processing method, and program

Abstract

Obtain appropriate answers based on the user's situation in the real world. [Solution] In the information processing device, the input information acquisition means acquires input information entered by the user. The retention means retains real-world information related to the user for a certain period in the past, starting from the time the input information was entered. The instruction information generation means generates instruction information based on the input information and the real-world information. The response information generation means generates response information based on the instruction information.

Description

Technical Field

[0001] This disclosure relates to a technique for generating answers using generative AI.

Background Art

[0002] The use of a system that generates an answer based on an instruction sentence input by a user using generative AI (Artificial Intelligence) has been progressing. Patent Document 1 describes an information processing apparatus that uses a language model, which is a type of generative AI, to enable an answer with higher accuracy for a question.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Conventionally, when generating an answer using generative AI based on the latest instruction sentence by a user, the past instruction sentences by the user are treated as the background and circumstances leading to the instruction (hereinafter also referred to as "context information"), and an answer is generated after considering the context information. However, since the context that can be grasped from past instruction sentences is limited, an answer cannot be generated based on the situation of the user who gave the instruction in the real world, and there has been a problem that an answer required by the user cannot be obtained from generative AI.

[0005] One of the objectives of this disclosure is to obtain an appropriate answer considering the situation of the user in the real world.

Means for Solving the Problems

[0006] To solve the above problems, from one aspect of this disclosure, an information processing apparatus An input information acquisition means for acquiring input information entered by the user, A means for storing real-world information related to the user for a certain period of time in the past, starting from the time the aforementioned input information was entered, Instruction information generation means that generates instruction information based on the input information and the real-world information, The system includes a response information generation means that generates response information based on the aforementioned instruction information.

[0007] From another perspective of this disclosure, the information processing method performed by the information processing device is: Retrieve the input information entered by the user, The system retains real-world information related to the user for a certain period of time prior to the time the aforementioned input information was entered. Based on the input information and the real-world information, instruction information is generated. Based on the aforementioned instruction information, response information is generated.

[0008] In yet another aspect of this disclosure, a program executed by an information processing device comprising a computer is: Retrieve the input information entered by the user, The system retains real-world information related to the user for a certain period of time prior to the time the aforementioned input information was entered. Based on the input information and the real-world information, instruction information is generated. The computer is instructed to perform a process to generate response information based on the aforementioned instruction information. [Effects of the Invention]

[0009] According to this disclosure, it is possible to obtain appropriate answers that take into account the user's situation in the real world. [Brief explanation of the drawing]

[0010] [Figure 1] An example of the general configuration of the information processing system related to this disclosure is shown. [Figure 2] This diagram schematically illustrates the processing performed by the server. [Figure 3] It is a block diagram showing an example of the hardware configuration of a server and a user terminal. [Figure 4] An example of real-world information and an acquisition method is shown. [Figure 5] It is a block diagram showing an example of the functional configuration of a server. [Figure 6] It is a diagram for explaining a data group. [Figure 7] It is a flowchart of answer generation processing. [Figure 8] It is a block diagram showing the functional configuration of an information processing apparatus. [Figure 9] It is a flowchart by an information processing apparatus.

Mode for Carrying Out the Invention

[0011] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. [First Embodiment] (Overall Configuration) FIG. 1 is an example of a schematic configuration of an information processing system 100 to which the information processing apparatus of the present disclosure is applied. The information processing system 100 is a system that generates an answer using a generation AI based on an instruction sentence (hereinafter, also referred to as a "prompt sentence") input by a user, taking into account real-world information of the user in a certain past period, and generates an answer to the instruction sentence.

[0012] In the information processing system 100 of FIG. 1, a server 1 and a user terminal 2 are communicably connected via a network 5 such as the Internet. The server 1 is an information processing apparatus that performs processing, storage, and transmission / reception of various data, and is connected to a real-world information database (hereinafter, the "database" is referred to as "DB") 31.

[0013] Figure 2 is a diagram schematically showing the processing by server 1. As shown in Figure 2, server 1 generates instruction information for the generation AI based on the past instruction sentence "What are the recommended tourist spots in Okinawa Prefecture?" entered by the user, the latest instruction sentence "What are other recommended tourist spots?" entered by the user, and the user's real-world information "Visit history to Churaumi Aquarium". By inputting the generated instruction information, the generation AI generates response information "You have already visited Churaumi Aquarium. Another recommended tourist spot is Kouri Island Beach."

[0014] Server 1 receives the instruction sentence input by the user from user terminal 2, or transmits response information regarding the response generated using the generation AI to user terminal 2. Note that server 1 may be a virtual server existing in a cloud environment. Server 1 is an example of the information processing apparatus of the present disclosure.

[0015] User terminal 2 is a smartphone, smartwatch, etc. used by the user, and transmits the instruction sentence input by the user and the real-world information obtained from sensors, etc. to server 1, or receives response information from server 1. User terminal 2 is an example of the terminal used by the subject of the present disclosure.

[0016] (Hardware Configuration) Figure 3(a) is a block diagram showing an example of the hardware configuration of server 1. As shown in the figure, server 1 includes an interface 11, a processor 12, a memory 13, a recording medium 14, a display unit 15, and an input unit 16. These components and the personal information DB 31 are interconnected via a bus.

[0017] Interface 11 exchanges data with user terminal 2. Interface 11 is used when receiving an instruction sentence or real-world information from user terminal 2, or transmitting response information to user terminal 2.

[0018] Processor 12 is a computer such as a CPU (Central Processing Unit) that controls the entire server 1 by executing pre-prepared programs. Processor 12 can be a CPU, GPU (Graphics Processing Unit), DSP (Digital Signal Processor), MPU (Micro Processing Unit), FPU (Floating Point Number Processing Unit), PPU (Physics Processing Unit), TPU (Tensor Processing Unit), quantum processor, microcontroller, or a combination of these.

[0019] Memory 13 consists of ROM (Read Only Memory), RAM (Random Access Memory), and other components. Memory 13 stores programs executed by the processor 12. Memory 13 is also used as working memory while the processor 12 is executing various processes.

[0020] The recording medium 14 is a non-volatile, non-temporary recording medium such as a disk-shaped recording medium or semiconductor memory, and is configured to be detachable from the server 1. The recording medium 14 stores various programs that the processor 12 executes. When the server 1 executes the answer generation process, the programs stored in the recording medium 14 are loaded into the memory 13 and executed by the processor 12.

[0021] The display unit 15 displays a predetermined image, for example, using an LCD (Liquid Crystal Display). The input unit 16 is used by the operator managing server 1, and can be a keyboard, mouse, touch panel, etc.

[0022] The real-world information DB31 stores real-world information related to the user for a certain period of time prior to the time the user inputs the latest instruction information. Real-world information is information obtained from devices and sensors that collect information about the state of the real world, such as information obtainable from smartphones and smartwatches. Examples of real-world information include temporal information related to time, spatial information related to space, information related to behavioral objectives, and attribute information related to user attributes. Specifically, attribute information includes health information related to the user's health, hobby information related to the user's hobbies, and occupational information related to the user's occupation.

[0023] Server 1, as will be described in detail later, defines specific parameters in advance for the acquisition methods of time information, spatial information, behavioral purpose information, and attribute information, and extracts each type of information from real-world data by filtering out irrelevant data and removing noisy information.

[0024] Server 1 is provided with a real-world information DB 31, but is not limited to this. It may also directly acquire and store real-world information from user terminal 2 for a certain period of time, starting from the time the user inputs the latest instruction information.

[0025] Figure 4 shows an example of real-world information and its acquisition method. As shown in Figure 4, time information includes timestamps, schedules, elapsed time, and periodic time, and is acquired via user terminal 2 using quartz, a time server, or a past scheduler. A timestamp is information indicating the exact date and time. A schedule is information indicating the period of time, showing the start and end dates and times of an event. Elapsed time is information indicating the length of time a specific activity was performed, such as sports, cooking, or watching videos, based on the start and end dates and times. Periodic time is information indicating the period of a specific activity that is performed periodically on each day of the week, each week, or each season. Time information may also be linked to spatial information, activity purpose information, and attribute information.

[0026] As shown in Figure 4, spatial information includes latitude, longitude, and altitude, address, facility name, direction, and distance, and is acquired via user terminal 2 using GNSS positioning (Global Navigation Satellite System), a camera, and a past scheduler. Latitude, longitude, and altitude are information that specifies a single point. The address is information that indicates a location on a regional basis, and the facility name is information that indicates a facility located at a predetermined location. Direction and distance are information that indicates the range of movement, for example, from point A to point B. Spatial information is not limited to absolute location specification that indicates a single point, but may also be relative location specification with respect to a certain point, such as direction and distance. Spatial information may also be linked to time information, action purpose information, and attribute information.

[0027] As shown in Figure 4, behavioral purpose information includes nature experiences, cultural experiences, social experiences, knowledge learning, sports, product purchases, and doing nothing (meditation). Behavioral purpose is estimated using various technologies that predict user behavior based on motion information acquired via user terminal 2 using a camera, IoT (Internet of Things) sensors, and past schedulers. For example, server 1 estimates the user's behavioral purpose, such as riding a train or playing sports, based on motion information acquired using an acceleration sensor. Behavioral purpose information may also be linked to time information, spatial information, and attribute information.

[0028] Furthermore, the user's objective may be estimated by integrating information obtained using, for example, cameras, IoT sensors, and past schedulers, and then inputting an instruction sentence into a generating AI that requests the estimation of the objective along with the integrated information.

[0029] Furthermore, the purpose of an action may be inferred not only from information about the action itself, but also from time information, spatial information, and attribute information. For example, based on information obtained from the scheduler, Server 1 will infer that the user's purpose of action is "travel" if "travel" is entered at a predetermined date and time. Also, based on information obtained from GNSS, Server 1 will infer that the user's purpose of action is "sightseeing" if the user is in a location far from their usual living area and it is a holiday.

[0030] If the attribute information is, for example, health information, as shown in Figure 4, the health information includes blood pressure, heart rate, pulse, body temperature, sweat volume, saliva volume, and step count, and is acquired via the user terminal 2 using healthcare devices, skin electrical signals, electroencephalograms, IoT sensors, etc. Furthermore, the attribute information may be linked to time information, spatial information, and behavioral purpose information, respectively.

[0031] Figure 3(b) is a block diagram showing an example of the hardware configuration of user terminal 2. As shown in the figure, user terminal 2 includes an interface 21, a processor 22, memory 23, recording medium 24, display unit 25, and input unit 26.

[0032] Interface 21 exchanges data with Server 1 via Network 5. Interface 21 is used to send instruction information and real-world information to Server 1, and to receive response information from Server 1.

[0033] The processor 22 is a computer such as a CPU, and controls the entire user terminal by executing a pre-prepared program. The processor 22 can be a CPU, GPU, DSP, MPU, FPU, PPU, TPU, quantum processor, microcontroller, or a combination thereof. For example, if the user terminal 2 is a smartwatch, it can be worn by the user and, by executing a predetermined program, acquire the user's heart rate, pulse, blood pressure, body temperature, etc.

[0034] Memory 23 is composed of ROM, RAM, etc. Memory 23 stores programs executed by the processor 22. Memory 23 is also used as working memory while the processor 22 is executing various processes.

[0035] The recording medium 24 is a non-volatile, non-temporary recording medium such as a disk-shaped recording medium or semiconductor memory, and is configured to be detachable from the user terminal 2. The recording medium 24 stores various programs executed by the processor 22. The display unit 25 displays a predetermined image, for example, an LCD. The input unit 26 is a touch panel or the like, and is used when the user performs a predetermined operation.

[0036] (Functional Configuration) Figure 5 is a block diagram showing an example of the functional configuration of Server 1. Functionally, Server 1 includes an input information acquisition unit 41, a real-world information acquisition unit 42, a selection unit 43, a related information acquisition unit 44, an instruction information generation unit 45, and a response information generation unit 46. The selection unit 43 and the related information acquisition unit 44 are provided by the instruction information generation unit 45.

[0037] The input information acquisition unit 41, the real-world information acquisition unit 42, the selection unit 43, the related information acquisition unit 44, the instruction information generation unit 45, and the response information generation unit 46 are realized by the processor 12 executing a program.

[0038] The input information acquisition unit 41 acquires the latest instruction sentence entered by the user from the user terminal 2 as input information. For example, as shown in Figure 2, the user uses the user terminal 2 to enter the instruction sentence "What other tourist spots do you recommend?" and sends it to the server 1 as input information.

[0039] The real-world information acquisition unit 42 acquires real-world information related to the user for a certain period of time in the past, starting from the time the user inputs the latest instruction information. The real-world information acquisition unit 42 may acquire real-world information by analyzing the real-world information stored in the real-world information DB 31 based on the input information, or it may acquire real-world information directly from the user terminal 2. For example, the real-world information acquisition unit 42 acquires "visit history to Churaumi Aquarium" as real-world information from the real-world information DB 31 based on the input information.

[0040] The instruction information generation unit 45 generates instruction information to be input to the generating AI based on input information and real-world information, and includes a selection unit 43 and a related information acquisition unit 44. The selection unit 43 selects a group of data for generating instruction information to be input to the generating AI. Specifically, the selection unit 43 extracts characteristic information related to the user from the instruction text and real-world information input by the user, and excludes data groups unrelated to the characteristic information from the selection target.

[0041] Figure 6 is a diagram illustrating the data set. As shown in Figure 6, Server 1 generates response information by inputting the input information and the search results of data sets A to C generated by Retrieval-Augmented Generation (RAG) as instruction information to the generating AI. Here, the generating AI is, as an example, a Large Language Model (LLM) capable of understanding multimodal information.

[0042] RAG is a mechanism that utilizes external data not registered in LLM. Server 1 searches the data set for data similar to the latest instruction sentence provided by the user, which is included in the input information, and inputs the search results along with the latest instruction sentence to the generating AI, thereby utilizing external data. The data set may consist only of information personally owned by the user, or it may include information from the web. Server 1 pre-assigns metadata about the information held by each data set, and by referring to this metadata, it searches for data sets that were not excluded by the selection unit 43.

[0043] Metadata can be obtained from real-world information, such as APIs (Application Programming Interfaces), URLs, folder addresses, filenames, or a combination of these. Specifically, metadata relates to temporal information, spatial information, behavioral purpose information, and attribute information. In the example shown in Figure 6, data group A is assigned "Japan," data group B is assigned "America," and data group C is assigned "United Kingdom." In this case, the selection unit 43 extracts the spatial information "Churaumi Aquarium (Okinawa)" as characteristic information from the real-world information "Visit History to Churaumi Aquarium," and excludes data group B ("America") and data group C ("United Kingdom"), which are unrelated to Churaumi Aquarium, from the selection. Searching for unrelated data groups can lead to errors in the answers obtained from the generating AI. By considering real-world information and narrowing down the data groups to be referenced, the accuracy of the answers can be improved by the selection unit 43. Note that Figure 6 is just one example, and the configuration of data groups and metadata can be set arbitrarily. Furthermore, when selecting data sets to exclude from the selection, it is acceptable to limit the selection to those that exceed a certain evaluation value.

[0044] The related information acquisition unit 44 retrieves related information related to real-world information by searching a predetermined data set based on the instruction text and real-world information entered by the user. The search method may be one or a combination of technologies such as "vector search," "keyword weighted search (BM25)," "keyword exact match search," and "Cross-Encoder." In the example shown in Figure 6, the related information acquisition unit 44 retrieves related information from the "Japan" data set A based on the latest instruction text "What other tourist destinations do you recommend?" and the real-world information "Visit history to Churaumi Aquarium" entered by the user. Furthermore, if any one of the behavioral purpose information, time information, spatial information, or attribute information related to the real-world information cannot be extracted from the data set, the unit may also have a function to periodically request permission from the user to obtain the real-world information.

[0045] If the instruction information generation unit 45 has obtained related information via RAG, it generates instruction information to input to the generating AI using the input information, real-world information, and related information. For example, using the latest instruction sentence "What other tourist spots do you recommend?" included in the input information, the real-world information "Visit history to Churaumi Aquarium," and related information, the instruction information generation unit 45 excludes places and facilities that the user has already visited, and if it can infer the user's hobbies and preferences from their purpose of action, it generates instruction information that requests detailed information that matches those hobbies and preferences.

[0046] The response information generation unit 46 generates response information by inputting instruction information into the generation AI. At this time, the generation AI extracts past instruction statements from the user stored in the cache and generates response information considering the past instruction statements. Specifically, the past instruction statements are the instruction statements made a predetermined number of times within the same session.

[0047] While past user instruction information is stored in the generating AI's cache, it is not limited to this and may also be stored in a designated database or similar. In this case, the instruction information generation unit 45 generates instruction information to be input to the generating AI based on the input information, real-world information, and past instruction information.

[0048] In the above configuration, the selection unit 43, related information acquisition unit 44, instruction information generation unit 45, and response information generation unit 46 of Server 1 are examples of the selection means, acquisition means, instruction information generation means, and response information generation means of the Disclosure, respectively. Furthermore, the real-world information DB 31 of Server 1 is an example of the storage means of the Disclosure.

[0049] (Answer generation process) Next, we will explain the response generation process by Server 1. Figure 7 is a flowchart showing an example of the response generation process by Server 1. This process is achieved by the processor 12 shown in Figure 3(a) executing a pre-prepared program.

[0050] First, Server 1 obtains the latest instruction entered by the user from User Terminal 2 as input information (Step S101). For example, Server 1 obtains the latest instruction, "What is the recommended marathon course I should take next?" as input information. Next, Server 1 obtains real-world information related to the user for a certain period of time prior to the time the user entered the latest instruction information (Step S102). Based on the input information, Server 1 obtains real-world information such as the user's "marathon course," "date and time the marathon was run," "heart rate during the marathon," and "pulse during the marathon."

[0051] Next, Server 1 selects a set of data to reference in order to generate instruction information to be input to the generating AI (step S103). Server 1 extracts characteristic information related to the user from the input information and real-world information, and excludes data sets unrelated to the characteristic information from the selection. For example, if the data set is as shown in Figure 6, Server 1 extracts the spatial information "Marathon course (Setagaya Ward)" as characteristic information from the real-world information, and excludes the data set B for "America" ​​and the data set C for "United Kingdom," which are unrelated to the marathon course in Setagaya Ward, from the selection.

[0052] Next, Server 1 acquires relevant information related to the real-world information from a predetermined data set based on the input information and real-world information (Step S104). For example, if the data set is as shown in Figure 6, Server 1 acquires relevant information from the "Japan" data set A based on the input information and real-world information. Server 1 uses the input information, real-world information and relevant information to generate instruction information to input to the generating AI (Step S105). For example, Server 1 excludes marathon courses that the user has already run and generates instruction information that seeks a marathon course with an appropriate load level for the user, provided that it is a nearby marathon course and the load can be estimated from the user's heart rate and pulse rate.

[0053] Next, Server 1 generates response information by inputting the instruction information into the generating AI (step S106). At this time, the generating AI extracts past instruction sentences from the user stored in the cache and generates response information considering the past instruction sentences. Server 1 presents the response to the user by sending the response information generated by the generating AI to User Terminal 2. This completes the response generation process.

[0054] Furthermore, real-world information is not limited to the example shown in Figure 4; it may also include sounds obtainable by a microphone, scents obtainable by an odor sensor, tastes obtainable by a taste sensor, and so on.

[0055] According to such an information processing system 100, the generating AI can generate an answer that takes into account not only the latest instruction but also the background and circumstances (hereinafter also referred to as "context") that led to that instruction or question. Therefore, the user can obtain an appropriate answer that takes into account the user's situation in the real world.

[0056] [Differentiation] In the above embodiment, the user uses user terminal 2, but this disclosure is not limited thereto, and the user may use a user terminal that has the functionality of server 1. In this case, the user terminal performs the response generation process that was performed by server 1, and uses the generation AI to obtain an appropriate response that takes into account the user's situation in the real world.

[0057] [Second Embodiment] Figure 8 is a block diagram showing an example of the functional configuration of an information processing device in this disclosure. The information processing device 90 comprises an input information acquisition means 91, a holding means 92, an instruction information generation means 93, and a response information generation means 94.

[0058] Figure 9 is a flowchart illustrating an example of processing by the information processing device 90. The input information acquisition means 91 acquires input information entered by the user (step S201). The retention means 92 retains real-world information related to the user for a certain period in the past, starting from the time the input information was entered (step S202). The instruction information generation means 93 generates instruction information based on the input information and real-world information (step S203). The response information generation means 94 generates response information based on the instruction information (step S204). The information processing device 90 can obtain an appropriate response that takes into account the user's situation in the real world.

[0059] In addition, some or all of the above embodiments (including modifications, the same applies hereinafter) may also be described as follows, but are not limited to the following.

[0060] (Note 1) An input information acquisition means for acquiring input information entered by the user, A means for storing real-world information related to the user for a certain period of time in the past, starting from the time the aforementioned input information was entered, Instruction information generation means that generates instruction information based on the input information and the real-world information, A response information generation means that generates response information based on the aforementioned instruction information, An information processing device equipped with the following features.

[0061] (Note 2) The instruction information generation means includes a selection means for selecting a data set for generating the instruction information based on the real-world information, The selection means is an information processing device according to Appendix 1, which extracts characteristic information related to the user from the real-world information and excludes data groups unrelated to the characteristic information from the selection target.

[0062] (Note 3) The information processing device according to Appendix 2, wherein the characteristic information is at least one of the following: information relating to the user's purpose of action, time information relating to the time of input, spatial information relating to the user's location, and attribute information relating to the user's attributes.

[0063] (Note 4) The instruction information generation means includes related information acquisition means that acquires related information related to the real-world information from a predetermined data set based on the real-world information, and the instruction information generation means generates the instruction information using the input information, the real-world information, and the related information as described in Appendix 1.

[0064] (Note 5) The response information generation means is an information processing device according to Appendix 1 that generates the response information by inputting the instruction information into a generating AI.

[0065] (Note 6) The response information generation means is an information processing device according to Appendix 5 that generates the response information by inputting the instruction information and the user's past instruction information into a generating AI.

[0066] (Note 7) The information processing device according to Appendix 3, comprising estimation means for estimating the action objective information by integrating the aforementioned real-world information and inputting it into a generating AI.

[0067] (Note 8) An information processing method performed by an information processing device, Retrieve the input information entered by the user, The system retains real-world information related to the user for a certain period of time prior to the time the aforementioned input information was entered. Based on the input information and the real-world information, instruction information is generated. An information processing method for generating response information based on the aforementioned instruction information.

[0068] (Note 9) A program executed by an information processing device equipped with a computer, Retrieve the input information entered by the user, The system retains real-world information related to the user for a certain period of time prior to the time the aforementioned input information was entered. Based on the input information and the real-world information, instruction information is generated. A program that causes the computer to perform a process to generate response information based on the aforementioned instruction information.

[0069] (Note 10) Based on the aforementioned real-world information, a set of data is selected to generate the aforementioned instruction information. The program described in Appendix 9, which causes the computer to perform a process of extracting characteristic information related to the user from the real-world information and excluding data sets unrelated to the characteristic information from the selection.

[0070] Furthermore, some or all of the configurations described in Appendices 2 to 7, which are dependent on Appendice 1 above, may also be dependent on Appendice 8 in the same way as in Appendices 2 to 7. Also, some or all of the configurations described in Appendices 2 to 7, which are dependent on Appendice 1 above, may also be dependent on Appendice 9 in the same way as in Appendices 2 to 7. Moreover, not limited to Appendices 1, 8, and 9, some or all of the configurations described as appendices may also be dependent on various hardware, software, various recording means for recording software, or systems, without departing from the embodiments described above.

[0071] While the present disclosure has been described above with reference to embodiments, the present disclosure is not limited to the embodiments described above. Various modifications to the structure and details of the present disclosure may be understood by those skilled in the art within the scope of the present disclosure. That is, the present disclosure includes the entire disclosure, including the claims, and of course, various modifications and alterations that those skilled in the art may make in accordance with the technical idea. [Explanation of symbols]

[0072] 1 server 2 User terminals 11, 21 Interfaces 12, 22 processors 13, 23 memory 14, 24 Recording media 15, 25 Display section 16, 26 Input section 31 Real-world information database 41 Input Information Acquisition Unit 42 Real-world information acquisition unit 43 Selection Section 44 Related Information Acquisition Department 45 Instruction information generation unit 46 Answer information generation section 100 Information Processing Systems

Claims

1. An input information acquisition means for acquiring input information entered by the user, A means for storing real-world information related to the user for a certain period of time in the past, starting from the time the aforementioned input information was entered, Instruction information generation means that generates instruction information based on the input information and the real-world information, A response information generation means that generates response information based on the aforementioned instruction information, An information processing device equipped with the following features.

2. The instruction information generation means includes a selection means for selecting a data set for generating the instruction information based on the real-world information, The information processing apparatus according to claim 1, wherein the selection means extracts characteristic information relating to the user from the real-world information and excludes data groups unrelated to the characteristic information from the selection target.

3. The information processing apparatus according to claim 2, wherein the characteristic information is at least one of the following: information relating to the user's purpose of action, time information relating to the time of input, spatial information relating to the user's location, and attribute information relating to the user's attributes.

4. The information processing apparatus according to claim 1, wherein the instruction information generation means includes related information acquisition means that acquires related information relating to the real world information and the input information from a predetermined data group, and generates the instruction information using the input information, the real world information and the related information.

5. The information processing apparatus according to claim 1, wherein the response information generation means generates the response information by inputting the instruction information into the generating AI.

6. The information processing apparatus according to claim 5, wherein the response information generation means generates the response information by inputting the instruction information and the user's past instruction information into the generating AI.

7. The information processing apparatus according to claim 3, further comprising estimation means for estimating the action objective information by integrating the aforementioned real-world information and inputting it into a generating AI.

8. An information processing method performed by an information processing device, Retrieve the input information entered by the user, The system retains real-world information related to the user for a certain period of time prior to the time the aforementioned input information was entered. Based on the input information and the real-world information, instruction information is generated. An information processing method for generating response information based on the aforementioned instruction information.

9. A program executed by an information processing device equipped with a computer, Retrieve the input information entered by the user, The system retains real-world information related to the user for a certain period of time prior to the time the aforementioned input information was entered. Based on the input information and the real-world information, instruction information is generated. A program that causes the computer to perform a process to generate response information based on the aforementioned instruction information.

10. Based on the aforementioned real-world information, a set of data is selected to generate the aforementioned instruction information. The program according to claim 9, which causes the computer to perform a process of extracting characteristic information related to the user from the real-world information and excluding data sets unrelated to the characteristic information from the selection target.

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