Interface for machine teaching modeling

A computing device comprising:

• one or more processors;
• a memory in communication with the one or more processors, the memory having computer-readable instructions stored thereupon which, when executed by the one or more processors, cause the computing device to:
• instantiate a user interface configured to communicate with a machine learning model hosted on and integrated with a collaborative computing platform hosting a plurality of applications, the collaborative computing platform configured to manage execution and processing of uploaded documents for collaboration between one or more users in a distributed system, and retain and modify metadata associated with the uploaded documents;
• receive, via the user interface, a selection of one or more uploaded documents for input to the machine learning model, wherein the uploaded documents are stored on the collaborative computing platform and the uploaded documents are associated with one of the plurality of applications for creating and editing the documents;
• receive, via an interactive area on the user interface, selections of content in the uploaded documents for input to the machine learning model;
• receive, via the interactive area, one or more instructions for applying the selected content to the machine learning model;
• communicate, to the machine learning model, data indicative of the selected uploaded documents, selected content, and instructions;
• in response to selection of an option to publish the machine learning model:
• receiving a selection of a uploaded document of the collaborative computing platform;
• and
• sending an instruction to the machine learning model to apply the machine learning model to the selected uploaded document;
• wherein:
• the machine learning model is trained using the selected uploaded documents, selected content, and instructions;
• the trained machine learning model is operable to generate outputs based on the selected uploaded document as input data;
• the trained model and inputs are published using existing data structures of the collaborative computing platform without using a separate artificial intelligence platform;
• the uploaded document is classified and key metadata is extracted and written directly to the existing data structures of the collaborative computing platform;
• and
• when additional documents are subsequently uploaded to the platform, the published trained model and inputs are used to classify the additional documents, extract values, and write the values to fields in the existing data structures of the collaborative computing platform.

One or more non-transitory computer-readable media storing computer-executable instructions that, upon execution cause one or more processors of a computing device to cause the computing device to perform operations comprising:

• receiving, via a user interface configured to communicate with a machine learning model hosted on and integrated with a collaborative computing platform hosting a plurality of applications, the collaborative computing platform configured to manage execution and processing of uploaded documents for collaboration between one or more users in a distributed system, and retain and modify metadata associated with the uploaded documents, a selection of one or more uploaded documents for input to the machine learning model, wherein the uploaded documents are stored on the collaborative computing platform and the uploaded documents are associated with one of the plurality of applications for creating and editing the documents;
• receive, via an interactive area on the user interface, selections of content in the uploaded documents for input to the machine learning model;
• receive, via the interactive area, one or more instructions for applying the selected content to the machine learning model;
• communicate, to the machine learning model, data indicative of the selected uploaded documents, selected content, and instructions;
• in response to selection of an option to publish the machine learning model:
• receiving a selection of one or more directories of the collaborative computing platform;
• and
• sending an instruction to the machine learning model to apply the machine learning model to the selected directories;
• wherein:
• the machine learning model is trained using the selected uploaded document, selected content, and instructions;
• the trained machine learning model is operable to generate outputs based on the indicated uploaded document as input data;
• the trained model and inputs are published using existing data structures of the collaborative computing platform and independently of a separate artificial intelligence platform;
• the uploaded document is classified and key metadata is extracted and written directly to the existing data structures of the collaborative computing platform;
• and
• when additional documents are subsequently uploaded to the platform, the published trained model and inputs are used to classify the additional documents, extract values, and write the values to fields in the existing data structures of the collaborative computing platform.