Video conference content auto-retrieval and focus based on learned relevance

A non-transitory computer-readable medium comprising instructions, which when executed by a processing device cause a processing device to perform operations comprising:

• determining a plurality of collaborative documents each associated with at least one user of at least one of a plurality of client devices participating in a video conference;
• providing one or more first inputs to a machine learning model, the one or more first inputs identifying the plurality of collaborative documents, and comprising an indication of a request to identify a collaborative document that is most relevant to a first subject discussed during the video conference at a first point in time;
• determining, based on one or more first outputs of the machine learning model, the collaborative document that is the most relevant to the first subject discussed during the video conference at the first point in time;
• providing the determined collaborative document for presentation on one or more of the plurality of client devices while the first subject is being discussed during the video conference;
• and
• responsive to determining, at a second point in time during the video conference, that the first subject has changed to a second subject:
• determining, based on one or more second outputs of the machine learning model, that none of the plurality of collaborative documents is relevant to the second subject discussed during the video conference at the second point in time;
• and
• providing, for presentation on the plurality of client devices while the second subject is being discussed during the video conference, a media stream associated with a current speaker of the video conference.

A system comprising:

• a memory;
• and
• a processing device, coupled to the memory, to perform operations comprising:
• determining a plurality of collaborative documents each associated with at least one user of at least one of a plurality of client devices participating in a video conference;
• providing one or more first inputs to a machine learning model, the one or more first inputs identifying the plurality of collaborative documents, and comprising an indication of a request to identify a collaborative document that is most relevant to a first subject discussed during the video conference at a first point in time;
• determining, based on one or more first outputs of the machine learning model, the collaborative document that is the most relevant to the first subject discussed during the video conference at the first point in time;
• providing the determined collaborative document for presentation on one or more of the plurality of client devices while the first subject is being discussed during the video conference;
• and
• responsive to determining, at a second point in time during the video conference, that the first subject has changed to a second subject:
• determining, based on one or more second outputs of the machine learning model, that none of the plurality of collaborative documents is relevant to the second subject discussed during the video conference at the second point in time;
• and
• providing, for presentation on the plurality of client devices while the second subject is being discussed during the video conference, a media stream associated with a current speaker of the video conference.