Commodity development support system, commodity development support method, and commodity development support program

Abstract

To generate attractive commodity development information by merging image information that is visual and linguistic information that shows appeal in a well-balanced manner while simultaneously satisfying the need to broaden commodity ideas and arm them with data in a commodity development process.SOLUTION: In a commodity development support system in which a data terminal and a server device 1 communicate via a network 21, the server device 1 includes: a language information generation function that generates a commodity development concept using a language generation AI service based on commodity concept parameters, commodity development resources, and specific user information acquired via an AI platform 1A; and an image information generation function that generates a commodity image reflecting the commodity development concept using an image generation AI service based on the commodity concept parameters, the commodity development resources, and the specific user information.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a product development support system, a product development support method, and a product development support program that utilize AI to automatically generate product concepts and support product development. [Background technology]

[0002] Traditionally, new product planning in the beverage and food industry usually begins with the product planning team coming up with product ideas, and the steps are as follows: Product idea coming up → Product idea verification (consumer research) → Prototype creation and testing → Launch. Each step is carefully carried out by multiple teams under time schedule management, with multiple teams sharing information in a complex manner.

[0003] In particular, the stakeholders involved in the process of broadening out product ideas ⇒ verifying product ideas (consumer research) ⇒ creating and testing prototypes ⇒ launch are product planning team ⇒ planning team · consumer ⇒ planning team · retailer. The number of ideas considered in this process is narrowed down as the process progresses from the initial stage to the launch stage. The consideration period required to broaden out product ideas often takes approximately three to six months.

[0004] Meanwhile, the following Patent Document 1, which proposes a system for detecting categories of products that are potentially in demand in the market, describes the proposed approach as follows: "Cars are classified into two or more categories based on attributes such as at least 'outdoor' and 'city', and these criteria are used to classify the names of celebrities, which are the first target group.

[0005] Next, the cars are classified again based on attribute criteria such as "family" and "suitable for one person." Entertainers are also classified in the same way. Next, cars and entertainers are associated with each of these attribute groups. This reveals that, since there is a group of entertainers with a specific attribute group, for example, a "family" group with an image of "luxury" and "adult," but no car with such an image exists, it is possible to develop a car with such an image and use an entertainer belonging to this group in advertising."

[0006] Furthermore, Patent Document 2 discloses a solution to the risk of extracting an inappropriate concept, which occurs when product concepts are extracted solely based on an individual's experience and intuition, by describing the system as follows: "A concept candidate generating means 3 generates a plurality of product concept candidates based on customer needs for the product and the product's quality characteristics, each of these concept candidates is evaluated by concept evaluation means 4, and a product concept is automatically extracted by concept extraction means 5 based on the evaluation results." [Prior art documents] [Patent documents]

[0007] [Patent Document 1] JP 2002-92292 A [Patent Document 2] JP 2000-67109 A Summary of the Invention [Problem to be solved by the invention]

[0008] However, product development planners must immerse themselves in the task of repeatedly refining the product concept by examining the vast amount of web information they have researched and using their own perspectives to combine internal data accumulated in a single company that is centrally managed with external data that can be viewed on the web, while keeping in mind the product concept to be developed. It has also been pointed out that the created product concept may not be evaluated as satisfactory by the production decision makers in the upper echelons who attend the development meeting, and the same process must be repeated, resulting in inefficient work. On the other hand, with the recent advancement of AI technology, AI that can be used in product development, such as chatbots (product name), has been attracting attention, but even if accumulated internal data is handed over to AI, the reality is that an efficient process for utilizing multiple AIs has not been established, because the product concept contains image information in addition to linguistic information.

[0009] The present invention has been made to solve the above-mentioned problems, and an object of the present invention is to provide a product development support system, a product development support method, and a product development support program that can acquire attractive product development information that is a balanced merger of visual image information and linguistic information that indicates appeal, while simultaneously broadening product ideas and arming them with data in the product development process, by utilizing multiple information generation AIs with different attributes of generated information in order to focus on sophisticated product concepts that far exceed the product knowledge grasped by individuals in charge. [Means for solving the problem]

[0010] The product development support system of the present invention, which achieves the above-mentioned objective, is a product development support system in which a data terminal that accumulates and manages product development resources considered for product development in a first storage via a network, and a server device that provides on an AI platform a language generation AI service that uses a second storage in which specific user information transmitted from terminals of registered users who use the first storage or a social network service is accumulated, for a fee, or an image generation AI service that generates image information based on image information accumulated in the first storage or the second storage, wherein the server device is characterized by comprising: a language information generation means that generates a product development concept by the language generation AI service based on product concept parameters obtained via the AI ​​platform, the product development resources, and the specific user information, and an image information generation means that generates a product image that reflects the product development concept by the image generation AI service based on product concept parameters obtained via the AI ​​platform, the product development resources, and the specific user information. Effect of the Invention

[0011] According to the present invention, it is possible to generate attractive product development information that combines visual image information and linguistic information that indicates appeal in a balanced manner, while simultaneously broadening product ideas and arming the product with data in the product development process in order to focus on a sophisticated product concept that far exceeds the product knowledge grasped by the person in charge, and provide suitable product information to web viewers, including consumers. [Brief description of the drawings]

[0012] The drawings show specific embodiments of the present invention, including essential features of the invention as well as alternative and preferred embodiments. [Figure 1] FIG. 1 is a block diagram illustrating a configuration of a product development support system according to an embodiment of the present invention. [Diagram 2] FIG. 2 is a block diagram illustrating the configuration of a server device shown in FIG. [Diagram 3] FIG. 2A is a block diagram for explaining the configuration of a terminal connected to the server device shown in FIG. 1, and FIG. 2B is a detailed block diagram of the main parts shown in FIG. [Figure 4] FIG. 4 is a process diagram for explaining a product concept processing process of the product development support system shown in the embodiment. [Diagram 5] FIG. 4 is a process diagram for explaining a product concept processing process of the product development support system shown in the embodiment. [Figure 6] FIG. 4 is a process diagram for explaining a product concept processing process of the product development support system shown in the embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] Next, the best mode for carrying out the present invention will be described with reference to the drawings. The following embodiments relate to the product development support system shown in FIGS. 1 to 6, and include not only essential configurations of the invention, but also optional and preferred embodiments.

[0014] <System configuration> [First embodiment] FIG. 1 is a block diagram for explaining the configuration of a product development support system according to this embodiment.

[0015] In Fig. 1, 1 denotes a server device, and when providing a service on the cloud, an AI platform 1A that accepts a request for creating a product concept is constructed on a memory resource (for example, read from an external memory 18 to a RAM 16), and the first data terminals 3-1 to 3-N, the second data terminals 4-1 to 4-N, the third data terminals 5-1 to 5-N, and the fourth data terminals 2-1 to 2-N are connected to be able to communicate with each other via a browser. Note that the first data terminals 3-1 to 3-N, the second data terminals 4-1 to 4-N, the third data terminals 5-1 to 5-N, and the fourth data terminals 2-1 to 2-N are assumed to store data resources related to product development that have been stored without being made public for internal management in storages DST1 to DST4 (storage secured by a storage service function connected to a network 21), respectively. In addition, the server device 1 is configured to have one server device that performs AI function processing, but it may be configured to have one server device that corresponds to the language generation AI1-1, AI1-3, and AI1-4 and the image generation AI1-2. In addition, the storages DST1 to DST4 are given parameters that are subdivided for each product development concept for data search, and store information that was adopted in past product development, information that was discarded, minutes of product development meetings (reason for adoption, reason for discard), product sales trends, post-sales monitor information, adopted product designs and their designer comments, examples of catchphrases proposed for product sales, adoption proposals, discard proposals, etc. Therefore, even in the development of products of the same type, the parameters that contribute most to the content to be focused on are ranked.

[0016] Here, a user who operates a first data terminal 3-1 to 3-N corresponding to a particular industry field, for example the sales promotion field, has past sales promotion minutes, market research, sales price settings and associated information stored in a storage DST1 connected to the network 21, but since this data is not intended to be made public, it is managed so that it cannot be accessed by other users of the network 21.

[0017] Furthermore, a user who operates a second data terminal 4-1 to 4-N corresponding to a particular industry field, for example the inventory management field, has past inventory management data and information associated with the inventory data stored in storage DST2 connected to network 21, but since this data is not intended to be made public, it is managed so that it cannot be accessed by other users of network 21.

[0018] In addition, a user who operates a third data terminal 5-1 to 5-N corresponding to a specific industry field, for example the intellectual property management field, has past technological development history data and information associated with patent application data stored in a storage DST3 connected to the network 21, but since this data is not intended to be made public, it is managed so that it cannot be accessed from the network 21.

[0019] In addition, a user who operates a fourth data terminal 2-1 to 2-N corresponding to a specific industry field, for example the product development field, has past product research details, purchase data, analysis results, and POS data stored in a storage DST4 connected to the network 21, but since this data is not intended to be made public, it is managed so that it cannot be accessed by other users of the network 21.

[0020] 7 is a paid data storage service that is constructed on the Web and aggregates and stores recent, highly popular information sources (including SNS trend information, etc.) accumulated using a paid API.

[0021] The storages DST1 to DST4 are data storages constructed online, and a good example is a storage service drive represented by Google (registered trademark) Drive (product name), which supports common file formats such as DOC, XLS, ODT, ODS, RTF, CSV, and PPT as extensions, and is configured to be able to import files created by other applications. In addition, the functions of the data storages are assumed to be equipped with the following functions.

[0022] It is assumed that the access to the data storages DST1 to DST4 is subject to strict access restrictions, with user registration and login information being managed in advance. Furthermore, the functions of the data storages DST1 to DST4 may evolve due to version upgrades and the expansion of service functions.

[0023] [Save file] For example, a file storage area of ​​approximately 10 to 20 GB can be secured, making the system flexible enough to withstand failures or power outages in the hard disks of the fourth data terminals 2-1 to 2-N, the first data terminals 3-1 to 3-N, the second data terminals 4-1 to 4-N, and the third data terminals 5-1 to 5-N.

[0024] [Access and edit from anywhere] As long as there is a data terminal with an Internet connection and a standard browser, access is possible from anywhere, including the fourth data terminals 2-1 to 2-N, the first data terminals 3-1 to 3-N, the second data terminals 4-1 to 4-N, the third data terminals 5-1 to 5-N, and the fourth data terminals 2-1 to 2-N.

[0025] [Create a basic document from scratch] It allows you to create documents, spreadsheets, and presentations online, and comes with an environment that provides basic editing features such as bullets, sorting, tables, images, comments, formulas, fonts, and styles.

[0026] Here, a user who operates a fourth data terminal 2-1 to 2-N corresponding to a particular industry field, for example the product development field, has past product research details, purchase data, analysis results, and POS data stored in a storage DST4 connected to the WEB, but since this data is not intended to be made public, it is managed so that it cannot be accessed from the network 21.

[0027] In addition, a user who operates the first data terminals 3-1 to 3-N corresponding to a particular industry field, for example the sales promotion field, has past sales promotion minutes, market research, sales price settings and associated information stored in the storage DST1 connected to the WEB, but since this data is not intended to be made public, it is managed so that it cannot be accessed from the network 21.

[0028] Furthermore, for users operating second data terminals 4-1 to 4-N corresponding to a particular industry field, for example the inventory management field, past inventory management data and information associated with the inventory data are stored in storage DST2 connected to the WEB, but since this data is not intended to be made public, it is managed so that it cannot be accessed from network 21.

[0029] In addition, a user who operates a third data terminal 5-1 to 5-N corresponding to a specific industry field, for example the intellectual property management field, has past technological development history data and information associated with patent application data stored in a storage DST3 connected to the WEB, but since this data is not intended to be made public, it is managed so that it cannot be accessed from the network 21.

[0030] Fig. 2 is a block diagram for explaining the configuration of the server device 1 shown in Fig. 1. For the sake of explanation, the figure shows a state in which the first data terminals 3-1 to 3-N, the second data terminals 4-1 to 4-N, the third data terminals 5-1 to 5-N, and the fourth data terminals 2-1 to 2-N shown in Fig. 1 are connected.

[0031] In FIG. 2, reference numeral 11 denotes a communication unit which connects first data terminals 3-1 to 3-N, second data terminals 4-1 to 4-N, third data terminals 5-1 to 5-N, and fourth data terminals 2-1 to 2-N connected to a network 21 and controls communication.

[0032] Reference numeral 13 denotes a CPU, which starts an operating system (OS) stored in an external memory 18 and starts various applications installed through an API. By using an installed search engine to connect to the AI ​​platform 1A provided by the server device 1, the CPU 13 can request an article creation process that matches a selected topic and automatically post the created article.

[0033] In this embodiment, the search unit 16-2 browses online contents (web information published by manufacturers who develop and sell products) published on the network 21, learns noteworthy contents, and stores them in the storages DST1 to DST4. It is assumed that a time stamp is given to each online content, and an index file including the number of views, the number of downloads, and the genre type is created and managed on the storages DST1 to DST4. The CPU 13 generally controls the hardware connected to the internal bus 12 based on a control program stored therein.

[0034] Reference numeral 15 denotes a keyboard, which is used to input numerical values, text, icon instructions, etc., for running applications. Reference numeral 16 denotes an expandable RAM, which expands and stores the basic program of the platform installed in the external memory 18.

[0035] 16-1 is an identification unit that identifies a product model related to the product development concept (for example, bottle design, product name, and concept in the case of a business selling beverages or alcohol) from the online content stored in storage DST1 to DST4 or the content published on the web based on the parameters of the product concept that contributes to the product development received by AI platform 1A.

[0036] Reference numeral 16-2 denotes a search unit which executes a process of extracting pieces of information which contribute to a product concept from the online content stored in storages DST1 to DST4 and product information published on the Web, based on the product model identified by the identification unit 16-1 in accordance with the users who operate the first data terminals 3-1 to 3-N, the second data terminals 4-1 to 4-N, the third data terminals 5-1 to 5-N, and the fourth data terminals 2-1 to 2-N connected to the network 21.

[0037] Reference numeral 16-3 denotes an AI creation unit, which executes a process of extracting a wide range of information that contributes to a new product concept from pieces of information searched by the search unit 16-2 based on a product index selected by the user on the web, and creating a list of items to be adopted as product concepts.

[0038] 16-4 is a product concept providing unit, which in this embodiment executes a process of creating multiple web pages introducing the final product concept using multiple AI models, an image generation AI, two language generation AIs, and storages DST1 to DST4, and providing them to the requesting first data terminals 3-1 to 3-N, second data terminals 4-1 to 4-N, third data terminals 5-1 to 5-N, and fourth data terminals 2-1 to 2-N. Note that, among the product concept providing unit 16-4, the language generation AI creates multiple product concept web pages to be newly proposed using past in-house surveys and analysis results, and online articles posted by consumers.

[0039] The first data terminals 3-1 to 3-N, the second data terminals 4-1 to 4-N, and the third data terminals 5-1 to 5-N also handle information specialized for a particular industry, but the data processing flow will be the same as that of the fourth data terminals 2-1 to 2-N. Also, a separate unique analysis process may be added to contribute to the creation of more detailed and sophisticated concept web pages.

[0040] FIG. 3 is a block diagram illustrating the configurations of the first data terminals 3-1 to 3-N, the second data terminals 4-1 to 4-N, the third data terminals 5-1 to 5-N, and the fourth data terminals 2-1 to 2-N shown in FIG.

[0041] 3(a), reference numeral 101 denotes a CPU, which executes various applications by loading an OS and a control program stored in a ROM 102 into a RAM 103 and executing them. Reference numeral 110 denotes a keyboard, which inputs various information and clicks on icons displayed on a user interface screen (UI screen) displayed on a display 111. Reference numeral 104 denotes a communication unit, which controls communication connecting to each terminal connected to the network 21 and the server device 1.

[0042] 3B, 103-1 is an account management unit that is started by installing a management application downloaded from the server device 1. The account management unit 103-1 manages account information (email address, password) for connecting to the server device 1.

[0043] Reference numeral 103-2 denotes a log management unit, which executes a login process to the server device 1 based on the account information. Reference numeral 103-3 denotes a request unit, which instructs the UI screen presented by the AI ​​platform 1A to create a new product concept web page.

[0044] An acquisition unit 103-4 executes a process of acquiring a plurality of product concept Web pages created by the server device 1.

[0045] Here, the multiple product concept WEB pages acquired by the acquisition unit 103-4 are configured to be able to be stored in an external memory (not shown) or displayed on a display 111. In this embodiment, a data terminal that accumulates and manages product development resources considered for product development in a first storage (corresponding to storages DBST1 to DBST4) via a network 21, and an AI program that provides a language generation AI service (corresponding to language generation AI1-1, 1-3, 1-4) that uses a second storage (WEB drives WDR1 to N) that accumulates specific user information transmitted from the terminals of registered users who use the first storage or social network services for a fee, or an image generation AI service (corresponding to image generation AI1-2) that generates image information based on image information accumulated in the first storage or the second storage. The product development support system is characterized in that the server device 1 communicates with the AI ​​platform 1A, and the server device 1 includes an AI creation unit that executes a language information generation function process to generate a product development concept by the language generation AI service based on the parameters of the product concept acquired through the AI ​​platform 1A, the product development resources, and the specific user information, and an AI creation unit 16-3 that executes an image information generation function process to generate a product image reflecting the product development concept by the image generation AI service based on the parameters of the product concept acquired through the AI ​​platform 1A, the product development resources, and the specific user information. Note that the AI ​​creation unit 16-3 shows a case where it is possible to process both the language information generation function process and the image information generation function process, but these may be configured separately for each function. In addition, the product introduction WEB page is characterized in that it includes language information and layout information that explain the concept of the product to be developed. Similarly, the product concept page is characterized in that it includes an exterior image showing the design of the product to be developed (see the WEB page information shown in FIG. 5). Furthermore, the product concept page is characterized in that it includes language information that explains the support data.The product concept page is characterized in that it is configured to include language information and layout information (AI determines document information size, image size, and allocated page size) that explain the concept of the product to be developed, and an exterior image that shows the design of the product to be developed. The product concept page is further characterized in that it includes language information that verifies comparison with similar products. The acquisition unit 103-4 is characterized in that it acquires multiple automatically generated concept pages.

[0046] [Explanation of the product concept creation process] 4 to 6 are process diagrams for explaining the product concept processing steps of the product development support system shown in this embodiment.

[0047] In order to compare with the product concept processing process according to this embodiment, the conventional product concept processing process is shown in the upper part, and the product concept processing process according to this embodiment is shown in the lower part.

[0048] In the conventional product concept processing process, as shown in the upper part, a user operating a fourth data terminal 2-1 to 2-N corresponding to the product development field searches through internal company data such as past product research details, purchased data, analysis results, and POS data stored in data storage DST4 connected via an internal LAN, and creates an original concept ORCM after several weeks of searching, research, and analysis. Since the research and analysis are carried out from the perspective of the user in charge of planning, there is a high probability that a biased product development concept will be presented, which will be rejected at the initial approval meeting with upper management, and the same planning and drafting process will have to be repeated, resulting in inefficient processing.

[0049] In contrast, according to the present embodiment, multiple generation AIs 1-1 to 1-4 linked to an AI platform 1A that accepts requests for product concept creation provided by the server device 1 are used to create a high-quality product concept from the vast amount of information related to the product concept that has been investigated, collected, and analyzed from multiple angles, by referring to the accumulated data that the multiple generation AIs have collected and learned from, faithfully following the parameters of the new product presented by the requesting user and from a broad perspective that delves deeply into the product idea.

[0050] Furthermore, even within the same industry, it is possible to create product concepts while incorporating product information accumulated in storage DST1 to DST4, which contributes to accelerating data armament within the same industry by quickly creating highly original product concepts that cannot be easily predicted by competitors.

[0051] As shown in Fig. 5, in this embodiment, at the input stage, while referring to the in-house assets accumulated in the storages DST1 to DST4 for the parameters of new products, that is, while referring to the product development history, and while placing importance on the product development process of each company, a product concept web page related to product development leading to product ideas and designs in collaboration with a language generation AI and an image generation AI can be created by the process shown in Fig. 6. Note that the product concept web page can be created including support data. In this embodiment, as shown in FIG. 6, the stored data including the free data available as in-house data stored in the storages DST1 to DST4 shown in FIG. 1 and the paid data stored in the WEB drives WDR1 to N, and the product concept created by the language generation AI 1-1 are handed over to the image generation AI 1-2, the new language generation AI 1-3, and the language generation AI 1-4. As a result, it is possible to create a highly complete page, as shown in the product concept WEB page example in FIG. 5, in which an image of a bottle showing a new shape of a new product: drinking water is laid out, and which also includes language information (automatically translated for each country in which the product is provided) that explains the product concept in detail, as well as support data and information on similar products that have been compared.

[0052] Here, the language generation AI1-4 takes in the in-house data stored in the storages DST1-DST4 and the paid data stored in the WEB drives WDR1-N and available via a paid data service API, and passes them over to the language generation AI1-1.

[0053] This makes it possible to incorporate widely available information, whether free or paid, such as product comments (including those with evaluation information) posted via SNS when generating a product concept, and to control the product concept generation process so that it is not based on biased data sources. Here, SNS includes Twitter (registered trademark), Instagram (registered trademark), Line (registered trademark), TikTok (registered trademark), Facebook (registered trademark), YouTube (registered trademark), mixi (registered trademark), Skype (registered trademark), etc., and also includes SNS to be developed in the future.

[0054] More specifically, before starting to generate a product concept, first, generation AI1-4 extracts insight information (for example, knowledge gained by analyzing past purchasing data, information about recent trends among Generation Z obtained from Twitter (registered trademark), etc.) from the internal data stored in storage DST1-DST4 and the paid data stored in WEB drives WDR1-N, and this information is also fed into generation AI1-1 as a parameter to generate a product concept, thereby enabling the generation of a more accurate product concept.

[0055] In addition, the multiple product concept pages may be composed of product ideas, product designs, and supporting data for product development, and product ideas, product designs, and supporting data for product development. Furthermore, the product concept page may also include information for verifying comparison with similar products.

[0056] In addition, the server device 1 that provides the language generation AI service on the web based on the parameters is automatically selected based on resource performance familiar with a specific industry, thereby preventing product developers from selecting a biased server.

[0057] Furthermore, the language information introducing the product development concept generated by the server device 1 is language information extracted from product development resources obtained from free drive services (drives DST1 to DST4) and paid drive services (drive services provided by WEB drives WDR1 to N).By first extracting insight information (e.g., knowledge obtained by analyzing past purchasing data, information about recent trends among Generation Z obtained from Twitter (registered trademark), etc.) from internal data and paid data using the language generation AIs 1-1 and 1-4, and then feeding this information into the language generation AI 1-3 as a parameter to generate a product concept, it has become possible to generate a more accurate product concept.

[0058] [Effects of the first embodiment] According to this embodiment, data provided free of charge and published on the web, and the latest information provided for a fee and published on the web are accumulated, and a product concept is generated from the accumulated product development information using a collaboration between language AI generation and image AI generation. This simultaneously satisfies the need to broaden product ideas in the product development process and arm the user with data in order to focus on a sophisticated product concept that far exceeds the product knowledge grasped by the person in charge, and generates attractive product development information that is a balanced merger of visual image information and appealing linguistic information, thereby providing web viewers, including consumers, with suitable product information.

[0059] Second Embodiment In the above embodiment, the hardware and software functions of the server device 1 as a system have been described. However, since the same technical effect as in the first embodiment can be expected by executing a program as a software resource downloaded from the cloud, for example, it is also possible to configure the characteristic configuration of the present invention as a program.

[0060] [Effects of the second embodiment] According to this embodiment, the functions of the server device 1 shown in this embodiment can be realized by changing the software configuration while sharing the hardware resources of the server device 1, and it is also possible to easily accommodate expansion and modification of the system shown in Figure 1.

[0061] Third Embodiment In the above embodiment, a case has been described in which a product concept is generated by AI processing, taking into account all of the parameters acquired from each data terminal shown in Figure 1. However, it may also be configured to provide a language generation AI service that is more focused on the product concept by evaluating the acquired parameters themselves in advance, by learning and memorizing diversification patterns that are adapted to the acquired parameters and identify the direction of diversification of product ideas in the product development process.

[0062] [Effects of the third embodiment] According to this embodiment, when the AI ​​identifies a product concept adapted to the attributes of the product to be developed, a more appropriate product idea selection process can be expected. The present invention can also be realized by a process in which a program realizing one or more functions of the above-mentioned embodiment is supplied to a system or device via a network 21 or a storage medium, and one or more processors in the computer of the system or server device 1 read and execute the program. It can also be realized by a circuit (e.g., ASIC) that realizes one or more functions. Therefore, the same effect can be expected from an embodiment in which the process executed by the server device 1 is a method.

[0063] The disclosure regarding the present invention described above can be summarized at least as follows. (1) A product development support system in which a data terminal that accumulates and manages product development resources considered for product development in a first storage via a network, and a server device that provides on an AI platform a language generation AI service that uses a second storage in which specific user information transmitted from terminals of registered users who use the first storage or a social network service is accumulated, for a fee, or an image generation AI service that generates image information based on image information accumulated in the first storage or the second storage, wherein the server device is characterized by having a language information generation means that generates a product development concept by the language generation AI service based on product concept parameters acquired via the AI ​​platform, the product development resources, and the specific user information, and an image information generation means that generates a product image that reflects the product development concept by the image generation AI service based on product concept parameters acquired via the AI ​​platform, the product development resources, and the specific user information. (2) The server device is characterized in that it generates the product development concept by utilizing multiple language generation AI services. (3) The server device is characterized by having a proposal means for proposing a plurality of product models by combining the language information generated by the language information generation means and the product image generated by the image information generation means. (4) The suggestion means is characterized in that it proposes a product concept page that is composed of language information and layout information that explain the concept of the product to be developed, and an exterior image that shows the design of the product to be developed. (5) The product concept page is characterized by including linguistic information for verifying comparison with similar products. (6) The data terminal is characterized in that it acquires a plurality of concept pages that are automatically generated by the server device. (7) The present invention is characterized in that it comprises a storage means for storing a breadth-finding pattern that specifies a direction of breadth-finding of product ideas in a product development process in accordance with the parameters. (8) A product development support method for a product development support system in which a data terminal that accumulates and manages product development resources considered for product development in a first storage via a network, and a server device that provides a language generation AI service or an image generation AI service on an AI platform that uses, for a fee, a second storage in which specific user information transmitted from terminals of registered users who use the first storage or a social network service is accumulated, wherein the server device is characterized by having a language information generation step of generating a product development concept by the language generation AI service based on product concept parameters obtained via the AI ​​platform, the product development resources, and the specific user information, and an image information generation step of generating a product image reflecting the product development concept by the image generation AI service based on product concept parameters obtained via the AI ​​platform, the product development resources, and the specific user information. (9) A server device of a product development support system including a data terminal that accumulates and manages product development resources considered for product development in a first storage via a network, and a server device that provides a language generation AI service or an image generation AI service on an AI platform that uses, for a fee, a second storage in which specific user information transmitted from terminals of registered users who use the first storage or a social network service is accumulated, characterized in that the server device functions as a language information generation means that generates a product development concept by the language generation AI service based on product concept parameters obtained via the AI ​​platform, the product development resources, and the specific user information, and an image information generation means that generates a product image reflecting the product development concept by the image generation AI service based on product concept parameters obtained via the AI ​​platform, the product development resources, and the specific user information. [Explanation of symbols]

[0064] 1. Server device 2-1~2-N 4th data terminal 3-1~3-N 1st data terminal 4-1~4-N Second Data Terminal 5-1~5-N 3rd Data Terminal DST1~DST4 Storage

Claims

1. A product development support system in which a data terminal that accumulates and manages product development resources considered for product development in a first storage via a network and a server device that provides, on an AI platform, a language generation AI service that uses a second storage, for a fee, in which specific user information transmitted from a terminal of a registered user who uses the first storage or a social network service is accumulated, or an image generation AI service that generates image information based on image information accumulated in the first storage or the second storage, The server device includes: A language information generation means for generating a product development concept by the language generation AI service based on product concept parameters acquired via the AI ​​platform, the product development resources, and the specific user information; an image information generating means for generating a product image that reflects the product development concept by the image generation AI service based on product concept parameters acquired via the AI ​​platform, the product development resources, and the specific user information; A product development support system comprising:

2. The server device includes: The product development support system described in claim 1, characterized in that the product development concept is generated using multiple language generation AI services.

3. The server device includes:

2. The product development support system according to claim 1, further comprising a proposal unit which proposes a plurality of product models by combining the linguistic information generated by the linguistic information generation unit and the product image generated by the image information generation unit.

4. The product development support system according to claim 1 or 2, characterized in that the proposal means proposes a product concept page consisting of language information and layout information explaining the concept of the product to be developed and an exterior image showing the design of the product to be developed.

5. 5. The product development support system according to claim 4, wherein the product concept page includes linguistic information for verifying a comparison with similar products.

6. 5. The product development support system according to claim 4, wherein said data terminal acquires a plurality of concept pages automatically generated by said server device.

7. 2. The product development support system according to claim 1, further comprising a storage means for storing a breadth-finding pattern that specifies a direction of breadth-finding of product ideas in a product development process in accordance with said parameters.

8. A product development support method for a product development support system in which a data terminal that accumulates and manages product development resources considered for product development in a first storage via a network and a server device that provides a language generation AI service or an image generation AI service on an AI platform that utilizes, for a fee, a second storage in which specific user information transmitted from a terminal of a registered user who uses the first storage or a social network service is accumulated, comprising: The server device includes: A language information generation step of generating a product development concept by the language generation AI service based on product concept parameters acquired via the AI ​​platform, the product development resources, and the specific user information; an image information generation step of generating a product image reflecting the product development concept by the image generation AI service based on product concept parameters acquired via the AI ​​platform, the product development resources, and the specific user information; A product development support method for a product development support system comprising:

9. A product development support system including a data terminal that stores and manages product development resources considered for product development in a first storage via a network, and a server device that provides a language generation AI service or an image generation AI service on an AI platform that uses, for a fee, a second storage in which specific user information transmitted from a terminal of a registered user who uses the first storage or a social network service is stored, the server device A language information generation means for generating a product development concept by the language generation AI service based on product concept parameters acquired via the AI ​​platform, the product development resources, and the specific user information; an image information generating means for generating a product image that reflects the product development concept by the image generation AI service based on product concept parameters acquired via the AI ​​platform, the product development resources, and the specific user information; A product development support program characterized by functioning as a

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