Information processing method

Abstract

To provide incentives to a pre-trained model provider.SOLUTION: An information processing method includes: an acceptance step of accepting a request to use a pre-trained model registered on a distributed ledger; an issuance step of issuing a token to a wallet of a provider of the pre-trained model when the request is accepted; and a granting step of granting a non-transferable token to the wallet on the basis of a cumulative amount of tokens issued to the wallet.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to the technical field of information processing methods using distributed ledger technology.

Background Art

[0002] As this type of method, for example, a method of managing product development data using distributed ledger technology has been proposed (see Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] For example, by registering data in a distributed ledger, it is possible to share the registered data among multiple persons while preventing the registered data from being tampered with. For example, when a learned model as an output of machine learning is registered in a distributed ledger, a person different from the person who provided the learned model can also use the learned model. On the other hand, the person who provided the learned model is often not given an incentive.

[0005] The present invention has been made in view of the above circumstances, and an object thereof is to provide an information processing method capable of giving an incentive to a provider of a learned model.

Means for Solving the Problems

[0006] An information processing method according to an aspect of the present invention includes a reception step of receiving a usage request for a single learned model registered in a distributed ledger, an issuance step of issuing a token to a wallet of the provider of the single learned model when the usage request is received, and an assignment step of assigning a non-transferable token to the wallet based on the accumulated amount of the token issued to the wallet.

Brief Description of the Drawings

[0007]

Figure 1

Figure 2

Figure 3

Figure 4

Modes for Carrying Out the Invention

[0008] Embodiments of the information processing method will be described with reference to FIGS. 1 to 4. An information processing system to which the information processing method according to the embodiment is applied will be described.

[0009] (Concept of Information Processing System 1) First, the concept of the information processing system 1 will be described with reference to FIG. 1. In FIG. 1, the information processing system 1 includes a distributed network 10 and a data management system 20. The distributed network 10 is a network for realizing a distributed ledger. In the present embodiment, a blockchain is cited as an example of the distributed ledger.

[0010] The data management system 20 includes a database (DB) 220. For example, a learned model generated by machine learning may be registered in the database 220. For example, the learned model may be a learned model applicable to an automatic driving system of a vehicle. For example, the learned model may be a learned model applicable to a navigation device. Note that the learned model is not limited to a learned model applicable to at least one of the automatic driving system and the navigation device.

[0011] Note that in addition to or instead of the learned model, for example, at least one of learning data used for learning the learned model and source code used for learning the learned model may be registered in the database 220. Note that the data management system 20 may include at least one of a database in which the learning data is registered and a database in which the source code is registered, in addition to or instead of the database 220 in which the learned model is registered.

[0012] The learned model registered in the database 220 may be provided by the provider P. The provider P may access the information processing system 1 via the terminal device 30. For example, the provider P may generate a transaction for requesting registration of one learned model via the terminal device 30. For example, the generated transaction may include identification information for identifying the provider P and model information indicating one learned model. Note that an example of the identification information for identifying the provider P is a user account related to the provider P. An example of the model information is the file name of one learned model.

[0013] As a result of processing the generated transaction in the distributed network 10 (for example, as a result of registering the transaction in the distributed ledger), information for registering a single learned model in the database 220 may be provided to the provider P. The provider P may register a single learned model in the database 220 via the terminal device 30 based on the information. In this case, for example, a single learned model may be registered in the database 220 while being associated with the identification information related to the provider P. Note that an example of the information for registering a single learned model in the database 220 includes link information to the database 220.

[0014] When a single learned model is registered in the database 220, a person different from the provider P (for example, the user U) can use the single learned model. The user U may access the information processing system 1 via the terminal device 40. For example, when the user U wishes to use a single learned model, the user U may generate a transaction 41 for requesting the use of the single learned model via the terminal device 40. For example, the transaction 41 may include identification information for identifying the user U and model information indicating a single learned model. Note that an example of the identification information for identifying the user U includes a user account related to the user U.

[0015] As a result of processing the transaction 41 in the distributed network 10 (for example, as a result of registering the transaction 41 in the distributed ledger), information for obtaining a single learned model from the database 220 may be provided to the user U. The user U may obtain a single learned model (refer to the reference numeral "21" in FIG. 1) from the database 220 via the terminal device 40 based on the information. Note that an example of the information for obtaining a single learned model from the database 220 includes link information to the database 220.

[0016] The distributed network 10 that has processed transaction 41 may issue a token 11 to a provider P that has provided one trained model. The token 11 may be granted to the wallet 31 of the provider P. Note that the wallet 31 may be managed by a distributed ledger implemented by the distributed network 10, or may be managed by a distributed ledger implemented by a distributed network different from the distributed network 10.

[0017] The distributed network 10 may further grant a non-transferable token 12 to the wallet 31 of the provider P based on the cumulative amount of the tokens 11 issued to the provider P. For example, when the cumulative amount of the tokens 11 issued to the provider P is "1" or more, the distributed network 10 may grant a token indicating the first rank to the wallet 31 as the non-transferable token 12. When the cumulative amount of the tokens 11 issued to the provider P is "10" or more, the distributed network 10 may grant a token indicating the second rank, which is a rank higher than the first rank, to the wallet 31 as the non-transferable token 12. When the cumulative amount of the tokens 11 issued to the provider P is "100" or more, the distributed network 10 may grant a token indicating the third rank, which is a rank higher than the second rank, to the wallet 31 as the non-transferable token 12. Note that an example of the non-transferable token 12 is a soulbound token (SBT).

[0018] (A specific example of the information processing system 1) Next, a specific example of the configuration of the information processing system 1 will be described with reference to FIG. 2. In FIG. 2, the information processing system 1 includes a distributed network 10 and a data management system 20. The data management system 20 includes a management server 210 and a database 220. Each of the terminal devices 30 and 40 may be connected to the management server 210 via a wide area network such as the Internet.

[0019] The management server 210 may provide an application for viewing a distributed ledger realized by the distributed network 10 and an application for accessing the database 220 to the provider P and the user U. For this reason, the management server 210 may be referred to as an application server.

[0020] For example, when the provider P registers a single learned model in the database 220, the provider P may transmit registration request information for requesting registration of the single learned model to the management server 210 using the application provided by the management server 210. The management server 210 that has received the registration request information may generate a transaction for requesting registration of the single learned model. After the transaction is processed in the distributed network 10, the management server 210 may transmit display information for displaying information for registering the single learned model in the database 220 on a screen related to the application to the terminal device 30. The terminal device 30 that has received the display information may display information for registering the single learned model in the database 220. Thereafter, the provider P may register the single learned model in the database 220 using the application provided by the management server 210.

[0021] For example, when user U uses a single learned model, user U may transmit usage request information for requesting the use of the single learned model to management server 210 using an application provided by management server 210. Management server 210 that has received the usage request information may generate a transaction for requesting the use of the single learned model (for example, corresponding to transaction 41 shown in FIG. 1). After the transaction is processed in distributed network 10, management server 210 may transmit display information for displaying information for acquiring the single learned model from database 220 to terminal device 40 on a screen related to the application. Terminal device 40 that has received the display information may display information for acquiring the single learned model from database 220. Thereafter, user U may acquire the single learned model from database 220 using an application provided by management server 210.

[0022] Distributed network 10 that has processed a transaction for requesting the use of a single learned model may issue token 11 to provider P. In this case, management server 210 may assign token 11 to wallet 31 of provider P. Distributed network 10 may further issue non-transferable token 12 to provider P based on the accumulated amount of token 11 issued to provider P. In this case, management server 210 may assign non-transferable token 12 to wallet 31 of provider P.

[0023] Next, the operation of information processing system 1 will be further described with reference to the flowcharts of FIGS. 3 and 4. In FIG. 3, information processing system 1 (for example, management server 210) receives a request from user U to use a single learned model (step S101). Information processing system 1 (for example, management server 210) provides user U with a single learned model (that is, data) based on the received usage request (step S102). Information processing system 1 (for example, distributed network 10) issues token 11 to provider P who has provided the single learned model in parallel with the process of step S102 (step S103).

[0024] In FIG. 4, the information processing system 1 (for example, the distributed network 10) determines whether the cumulative amount of the tokens 11 issued to the provider P is equal to or greater than a threshold value (step S201). When it is determined that the cumulative amount of the tokens 11 is equal to or greater than the threshold value (step S201: Yes), the information processing system 1 (for example, the distributed network 10) issues a non-transferable token 12 to the provider P (step S202). On the other hand, when it is determined that the cumulative amount of the tokens 11 is not equal to or greater than the threshold value (step S201: No), the operation shown in FIG. 4 ends. Note that the operation shown in FIG. 4 may be performed when a new token 11 is issued to the provider P.

[0025] (Technical Effect) In the information processing system 1, when a certain learned model provided by the provider P is used by the user U, a token 11 is issued to the provider P. Therefore, the more a certain learned model is used by a large number of people, the greater the cumulative amount of the tokens 11 issued to the provider P. For example, it can be said that the greater the cumulative amount of the tokens 11 issued to the provider P, the more a certain learned model provided by the provider P contributes to others (for example, the user U). Therefore, it can be said that the cumulative amount of the tokens 11 issued to the provider P indicates at least one of the evaluation of the provider P and the achievements of the provider P.

[0026] Furthermore, in the information processing system 1, a non-transferable token 12 is issued to the provider P based on the cumulative amount of the tokens 11 issued to the provider P. When the cumulative amount of the tokens 11 is relatively large, the information processing system 1 may issue a non-transferable token 12 with a higher rank to the provider P than when the cumulative amount of the tokens 11 is relatively small. Therefore, it can be said that the non-transferable token 12 issued to the provider P indicates at least one of the evaluation of the provider P and the achievements of the provider P. Since the non-transferable token 12 is non-transferable, the reliability of at least one of the evaluation and the achievements of the provider P indicated by the non-transferable token 12 can be ensured.

[0027] Still, the non-transferable token 12 may be made public. In this case, the user U can refer to the non-transferable token 12 of the provider P and determine whether to use one trained model provided by the provider P. Still, the token 11 may be a transferable token. For example, the token 11 may be a token exchangeable for at least one of goods and services.

[0028] In this way, in the information processing system 1, when one trained model is used by the user U, the token 11 is issued to the provider P that provided the one trained model, and the non-transferable token 12 is issued based on the accumulated amount of the token 11. Therefore, the issuance of the token 11 and the non-transferable token 12 can be a motivation for the provider P to actively engage in providing the trained model. Therefore, according to the information processing system 1, that is, according to the information processing method applied to the information processing system 1, incentives can be given to the provider of the trained model.

[0029] (Modification example) The information processing system 1 (for example, the distributed network 10) may issue one token 11 each time one trained model is used. That is, the information processing system 1 may issue a fixed amount of the token 11 for one use of one trained model. The information processing system 1 (for example, the distributed network 10) may additionally issue the token 11 to the provider P that provided one trained model based on the request of the user U. For example, the user U who uses one trained model may evaluate the one trained model. Then, the user U may request the information processing system 1 to additionally issue the token 11 to the provider P according to the evaluation of the one trained model. In this case, the user U may be required to pay an amount of money corresponding to the amount of the token 11 additionally issued to the provider P. That is, the token 11 additionally issued to the provider P may be charged. Still, the information processing system 1 may constitute at least a part of an open data marketplace.

[0030] The various aspects of the invention derived from the embodiments and modifications described above will be described below.

[0031] An information processing method according to one aspect of the invention includes: a reception step of receiving a utilization request for a single learned model registered in a distributed ledger; an issuance step of issuing a token to the wallet of the provider of the single learned model when the utilization request is received; and a granting step of granting a non-transferable token to the wallet based on the cumulative amount of the tokens issued to the wallet.

[0032] In the information processing method, the non-transferable token may indicate at least one of the evaluation and achievements of the provider.

[0033] An information processing system according to one aspect of the invention includes a distributed network for realizing a distributed ledger and a management device for managing a single learned model registered in the distributed ledger. The distributed network receives a utilization request for the single learned model, and when the utilization request is received, issues a token to the wallet of the provider of the single learned model, and grants a non-transferable token to the wallet based on the cumulative amount of the tokens issued to the wallet. "Data management system 20" in the above-described embodiment corresponds to an example of the "management device".

[0034] In the information processing system, the non-transferable token may indicate at least one of the evaluation and achievements of the provider.

[0035] The present invention is not limited to the above-described embodiments, and can be appropriately changed without departing from the gist or idea of the invention that can be read from the claims and the entire specification. An information processing method involving such changes is also included in the technical scope of the present invention.

Explanation of Reference Numerals

[0036] 1... Information processing system, 10... Distributed network, 20... Data management system, 30, 40... Terminal device, 210... Management server, 220... Database

Claims

1. A receiving step of receiving a usage request for one learned model registered in a distributed ledger; An issuing step of issuing a token to the wallet of the provider of the one learned model when the usage request is received; An awarding step of awarding non-transferable tokens to the wallet based on the cumulative amount of tokens issued to the wallet; An information processing method, characterized by including the above.

2. The information processing method according to claim 1, wherein the non-transferable token indicates at least one of the evaluation and achievements of the provider.

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