Automatic suggestion of domain-specific knowledge

A computer system, comprising:

• one or more processors;
• and
• one or more non-transitory computer-readable storage media coupled to the one or more processors and storing instructions which, when executed by the one or more processors, cause the system to execute:
• receiving a text input from a computing device, wherein the text input comprises a plurality of words;
• accessing, from a server computer, common knowledge associated with a data store;
• generating, using a generative artificial intelligence model, contextual features in a query associated with the text input, wherein the generative artificial intelligence model has been trained to generate the contextual features in the query based on the common knowledge associated with the data store;
• generating, using the generative artificial intelligence model, a text output using the contextual features in the query associated with the text input;
• sending, to the computing device, instructions for presenting a user interface comprising the text output.

One or more computer-readable non-transitory storage media embodying software that is operable when executed to:

• receive a text input from a computing device, wherein the text input comprises a plurality of words;
• access, from a server computer, common knowledge associated with a data store;
• generate, using a generative artificial intelligence model, contextual features in a query associated with the text input, wherein the generative artificial intelligence model having been trained to generate the contextual features in the query based on the common knowledge associated with the data store;
• generate, using the generative artificial intelligence model, a text output using the contextual features in the query associated with the text input;
• and
• send, to the computing device, instructions for presenting a user interface comprising the text output.

A computer-implemented method executed using a text processor that executes a programmed knowledge suggestion check that is programmatically coupled to a generative artificial intelligence model having a programmatically accessible similarity function, the computer-implemented method comprising:

• receiving at the text processor, from a client computing device executing a browser and a text processing extension that extends functions of the browser, a text input from a computing device, wherein the text input comprises a plurality of words of a web page rendered by the browser;
• distribute sentences of the text input to a first check, a second check, and a third check that execute in parallel, the first check being configured to check grammar, the second check being configured to detect a tone, and the third check being configured to detect at least one of entities, acronyms, or keywords;
• accessing a data store of common knowledge;
• generating, using the generative artificial intelligence model, contextual features in a query associated with the text input, wherein the contextual features include definitions for the detected at least one of the entities, acronyms, or keywords;
• the generative artificial intelligence model has been trained to generate the contextual features in the query based on the common knowledge;
• generating, using the generative artificial intelligence model, a text output using the contextual features in the query associated with the text input;
• sending, to the client computing device, instructions for presenting the text output in the browser in a graphical user interface panel near the plurality of words of the web page.