Artificial intelligence model and data collection/development platform

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.

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.