Google Inc.

Jason Weng Wei

Quoc V Le

Maarten Paul Bosma

Dengyong Zhou

David J Bieber

Ed Huai-Hsin Chi

Aakanksha Chowdhery

Kelvin Gu

Augustus Quadrozzi Odena

Jacob Austin

David Martin Dohan

Dale Eric Schuurmans

Jiageng Luan

Anders Johan Andreassen

Xuezhi Wang

Yuzhe Zhao, Jr

Henryk Michalewski

Aitor Lewkowycz

Nathanael Schärli

Maxwell Nye

Olivier Jean Andrè Bousquet

Sharan Narang

Nathan Scales

Le Hou

Charles Aloysius Sutton

Guy Gur-Ari Krakover

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for performing a machine learning task on an input to generate an output. In one aspect, one of the method includes receiving input data that describes an input of a machine learning task; receiving candidate output data that describes a set of candidate classification outputs of the machine learning task for the input; generating an input sequence that includes the input and the set of candidate classification outputs; processing the input sequence using a neural network to generate a network output that specifies a respective score for each candidate classification output in the set of candidate classification outputs; and generating an output of the machine learning task for the input, comprising selecting, as the output, a selected candidate classification output from the set of candidate classification outputs using the respective scores.

Performing machine learning tasks using instruction-tuned neural networks

An example technique for image analysis is provided. An example image analysis method includes obtaining an instructive sequence descriptive of an instructive query, an instructive response, and an instructive trace of intermediate states from the instructive query to the instructive response. The example image analysis method includes inputting, to a machine-learned model, the instructive sequence and an operative image processing query that comprises image data, wherein the machine-learned model is configured to process the operative query with attention over the instructive sequence. The example method can include generating, using the machine-learned model and responsive to the operative query, an operative image processing response that comprises an analysis of the image data.

Image analysis by prompting of machine-learned models using chain of thought

Growing community of inventors

Mountain View, CA, United States of America

Jason Weng Wei