Artificial intelligence model and data collection/development platform

1. A method of facilitating development of a machine learning model via a service platform, the method being implemented by a computer system that comprises one or more processors executing computer program instructions that, when executed, perform the method, the method comprising:

providing a service platform that enables a developer to obtain training item information for training a machine learning model, the training item information comprising inputs and prediction outputs derived from one or more machine learning models' processing of the inputs;

obtaining, via the service platform, a request for information to train a first machine learning model, the request indicating a requested concept on which the first machine learning model is to be trained;

obtaining, via the service platform, input and output information derived from machine learning models, the input and output information comprising (i) first items provided as input to at least one model of the machine learning models, (ii) first prediction outputs derived from the at least one model's processing of the first items, (iii) second items provided as input to at least one other model of the machine learning models, and (iv) second prediction outputs derived from the at least one other model's processing of the second items; and

providing, via the service platform, based on the requested concept, at least a subset of the input and output information derived from the machine learning models to update the first machine learning model, such that the subset of the input and output information comprises:

(i) the first items and the first prediction outputs in response to the first prediction outputs being determined to correspond to a first concept that matches the requested concept; and

(ii) the second items and the second prediction outputs in response to the second prediction outputs being determined to correspond to a second concept that matches the requested concept, the second concept being different from the first concept,

wherein the first machine learning model is updated based on the subset of the input and output information being provided as input to the first machine learning model.

2. The method of claim 1 , wherein the first machine learning model is stored as a first instance at the service platform, the method further comprising:

generating a second instance of the first machine learning model,

wherein providing the subset of the input and output information to update the first machine learning model comprises providing the subset of the input and output information as input to the second instance of the first machine learning model to train the second instance of the first machine learning model, the training of the first machine learning model based on the subset of the input and output information causing updating of the second instance of the first machine learning model;

analyzing accuracy of the updated second instance of the first machine learning model; and

causing, based on the accuracy, the updated second instance of the first machine learning model to be stored at the service platform as a version of the first machine learning model.

3. The method of claim 2 , wherein one or more machine learning models hosted at the service platform (i) analyzes the accuracy of the updated second instance of the first machine learning model and (ii) causes, based on the accuracy, the updated second instance of the first machine learning model to be stored at the service platform as a version of the first machine learning model.

4. The method of claim 2 , wherein one or more machine learning models hosted at the service platform (i) provides the subset of the input and output information as input to the second instance of the first machine learning model to train the second instance of the first machine learning model, (ii) analyzes the accuracy of the updated second instance of the first machine learning model, and (iii) causes, based on the accuracy, the updated second instance of the first machine learning model to be stored at the service platform as a version of the first machine learning model.

5. The method of claim 2 , wherein one or more machine learning models hosted at the service platform (i) generates the second instance of the first machine learning model, (ii) provides the subset of the input and output information as input to the second instance of the first machine learning model to train the second instance of the first machine learning model, (iii) analyzes the accuracy of the updated second instance of the first machine learning model, and (iv) causes, based on the accuracy, the updated second instance of the first machine learning model to be stored at the service platform as a version of the first machine learning model.

6. The method of claim 1 , wherein the first machine learning model is stored as a first instance at the service platform, the method further comprising:

generating a second instance of the first machine learning model;

obtaining code information indicating one or more code-related changes for the first machine learning model;

updating the second instance of the first machine learning model based on the code information;

analyzing accuracy, speed, or cost of the updated second instance of the first machine learning model; and

causing, based on the accuracy or cost, the updated second instance of the first machine learning model to be stored at the service platform as a version of the first machine learning model.

7. The method of claim 6 , wherein one or more machine learning models hosted at the service platform (i) generates the second instance of the first machine learning model, (ii) updates the second instance of the first machine learning model based on the code information, (iii) analyzes the accuracy or cost of the updated second instance of the first machine learning model, and (iv) causes, based on the accuracy or cost, the updated second instance of the first machine learning model to be stored at the service platform as a version of the first machine learning model.

8. The method of claim 1 , wherein the request indicates a domain associated with the first machine learning model, and wherein providing the subset of the input and output information comprises:

determining a first domain associated with at least one machine learning model from which the first prediction outputs are derived;

determining that the first domain matches the requested domain; and

in response to the first domain being determined to match the requested domain and the first prediction outputs being determined to correspond to the first concept matching the requested concept, including the first items and the first prediction outputs in the subset of the input and output information to be provided to update the first machine learning machine.

9. The method of claim 1 , wherein the request indicates an input type associated with the first machine learning model, and wherein providing the subset of the input and output information comprises:

determining a first input type associated with at least one machine learning model from which the first prediction outputs are derived;

determining that the first input type matches the requested input type; and

in response to the first input type being determined to match the requested input type and the first prediction outputs being determined to correspond to the first concept matching the requested concept, including the first items and the first prediction outputs in the subset of the input and output information to be provided to update the first machine learning machine.

10. A system comprising:

a computer system that comprises one or more processors programmed with computer program instructions that, when executed, cause the computer system to:

provide a service platform that enables a developer to obtain training item information for training a machine learning model, the training item information comprising inputs and prediction outputs derived from one or more machine learning models' processing of the inputs;

obtain, via the service platform, a request for information to train a first machine learning model, the request indicating a requested concept on which the first machine learning model is to be trained;

obtain, via the service platform, input and output information derived from machine learning models, the input and output information comprising (i) first items provided as input to at least one model of the machine learning models, (ii) first prediction outputs derived from the at least one model's processing of the first items, (iii) second items provided as input to at least one other model of the machine learning models, and (iv) second prediction outputs derived from the at least one other model's processing of the second items; and

provide, via the service platform, based on the requested concept, at least a subset of the input and output information derived from the machine learning models to update the first machine learning model, such that the subset of the input and output information comprises:

(i) the first items and the first prediction outputs in response to the first prediction outputs being determined to correspond to a first concept that matches the requested concept; and

(ii) the second items and the second prediction outputs in response to the second prediction outputs being determined to correspond to a second concept that matches the requested concept, the second concept being different from the first concept,

wherein the first machine learning model is updated based on the subset of the input and output information being provided as input to the first machine learning model.

11. The system of claim 10 , wherein the first machine learning model is stored as a first instance at the service platform, and wherein the computer system is caused to:

generate a second instance of the first machine learning model,

wherein providing the subset of the input and output information to update the first machine learning model comprises providing the subset of the input and output information as input to the second instance of the first machine learning model to train the second instance of the first machine learning model, the training of the first machine learning model based on the subset of the input and output information causing updating of the second instance of the first machine learning model;

analyze accuracy of the updated second instance of the first machine learning model; and

cause, based on the accuracy, the updated second instance of the first machine learning model to be stored at the service platform as a version of the first machine learning model.

12. The system of claim 11 , wherein one or more machine learning models hosted at the service platform (i) analyzes the accuracy of the updated second instance of the first machine learning model and (ii) causes, based on the accuracy, the updated second instance of the first machine learning model to be stored at the service platform as a version of the first machine learning model.

13. The system of claim 11 , wherein one or more machine learning models hosted at the service platform (i) provides the subset of the input and output information as input to the second instance of the first machine learning model to train the second instance of the first machine learning model, (ii) analyzes the accuracy of the updated second instance of the first machine learning model, and (iii) causes, based on the accuracy, the updated second instance of the first machine learning model to be stored at the service platform as a version of the first machine learning model.

14. The system of claim 11 , wherein one or more machine learning models hosted at the service platform (i) generates the second instance of the first machine learning model, (ii) provides the subset of the input and output information as input to the second instance of the first machine learning model to train the second instance of the first machine learning model, (iii) analyzes the accuracy of the updated second instance of the first machine learning model, and (iv) causes, based on the accuracy, the updated second instance of the first machine learning model to be stored at the service platform as a version of the first machine learning model.

15. The system of claim 10 , wherein the first machine learning model is stored as a first instance at the service platform, and wherein the computer system is caused to:

generate a second instance of the first machine learning model;

obtain code information indicating one or more code-related changes for the first machine learning model;

update the second instance of the first machine learning model based on the code information;

analyze accuracy or cost of the updated second instance of the first machine learning model; and

cause, based on the accuracy or cost, the updated second instance of the first machine learning model to be stored at the service platform as a version of the first machine learning model.

16. The system of claim 15 , wherein one or more machine learning models hosted at the service platform (i) generates the second instance of the first machine learning model, (ii) updates the second instance of the first machine learning model based on the code information, (iii) analyzes the accuracy or cost of the updated second instance of the first machine learning model, and (iv) causes, based on the accuracy or cost, the updated second instance of the first machine learning model to be stored at the service platform as a version of the first machine learning model.

17. The system of claim 10 , wherein the request indicates a domain associated with the first machine learning model, and wherein providing the subset of the input and output information comprises:

determining a first domain associated with at least one machine learning model from which the first prediction outputs are derived;

determining that the first domain matches the requested domain; and

in response to the first domain being determined to match the requested domain and the first prediction outputs being determined to correspond to the first concept matching the requested concept, including the first items and the first prediction outputs in the subset of the input and output information to be provided to update the first machine learning machine.

18. The system of claim 10 , wherein the request indicates an input type associated with the first machine learning model, and wherein providing the subset of the input and output information comprises:

determining a first input type associated with at least one machine learning model from which the first prediction outputs are derived;

determining that the first input type matches the requested input type; and

in response to the first input type being determined to match the requested input type and the first prediction outputs being determined to correspond to the first concept matching the requested concept, including the first items and the first prediction outputs in the subset of the input and output information to be provided to update the first machine learning machine.

19. One or more non-transitory storage media comprising instructions that, when executed by one or more processors, cause operations comprising: providing a service platform that enables a developer to obtain training item information for training a machine learning model, the training item information comprising inputs and prediction outputs derived from one or more machine learning models' processing of the inputs; obtaining, via the service platform, a request for information to train a first machine learning model, the request indicating a requested concept on which the first machine learning model is to be trained; obtaining, via the service platform, input and output information derived from machine learning models, the input and output information comprising (i) first items provided as input to at least one model of the machine learning models, (ii) first prediction outputs derived from the at least one model's processing of the first items, (iii) second items provided as input to at least one other model of the machine learning models, and (iv) second prediction outputs derived from the at least one other model's processing of the second items; and providing, via the service platform, based on the requested concept, at least a subset of the input and output information derived from the machine learning models to update the first machine learning model, such that the subset of the input and output information comprises: (i) the first items and the first prediction outputs in response to the first prediction outputs being determined to correspond to a first concept that matches the requested concept; and (ii) the second items and the second prediction outputs in response to the second prediction outputs being determined to correspond to a second concept that matches the requested concept, the second concept being different from the first concept, wherein the first machine learning model is updated based on the subset of the input and output information being provided as input to the first machine learning model.

20. The media of claim 19 , wherein the request indicates a domain associated with the first machine learning model, and wherein providing the subset of the input and output information comprises:

determining a first domain associated with at least one machine learning model from which the first prediction outputs are derived;

determining that the first domain matches the requested domain; and

in response to the first domain being determined to match the requested domain and the first prediction outputs being determined to correspond to the first concept matching the requested concept, including the first items and the first prediction outputs in the subset of the input and output information to be provided to update the first machine learning machine.