Block, Inc.

Rayhane Mama

Marc Tyndel

Ragavan Thurairatnam

A computer-implemented method includes receiving, from a first device of a first participant of a videoconference, a first compressed video stream and a customized first machine-trained decoding model. The first compressed video stream is compressed using a customized first machine-trained encoding model. The first decoding model and the first compressed video stream are transmitted to a second device of a second participant in the videoconference. A second compressed video stream and a customized second machine-trained decoding model are received from the second device. The second compressed video stream is compressed using a customized second machine-trained encoding model. The second decoding model and second compressed video stream are transmitted to the first device by the server. The first compressed video stream is decoded on the second device using the first decoding model and the second compressed video stream is decoded on the first device using the second decoding model.

Machine-learning based data compression for streaming media

Technology to encode/compress and decode/uncompress video streams is described. According to one example, a computer-implemented method includes receiving, by a server and from a first device associated with a first participant of a videoconference involving a second device associated with a second participant, a first compressed video stream and a first decoding model. The first decoding model is trained via machine learning, and the first compressed video stream is compressed using a first encoding model trained via machine learning. The first encoding and decoding models are customized to the first participant. The server is adapted to transmit to the second device, the first decoding model and the first compressed video stream.

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Rayhane Mama