The Data Cards Playbook: A Toolkit for Transparency in Dataset Documentation

Favorite Posted by Mahima Pushkarna, Senior Interaction Designer, and Andrew Zaldivar, Senior Developer Relations Engineer, Google Research As machine learning (ML) research moves toward large-scale models capable of numerous downstream tasks, a shared understanding of a dataset’s origin, development, intent, and evolution becomes increasingly important for the responsible and informed

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Shared by Google AI Technology November 17, 2022

Mixture-of-Experts with Expert Choice Routing

Favorite Posted by Yanqi Zhou, Research Scientist, Google Research Brain Team The capacity of a neural network to absorb information is limited by the number of its parameters, and as a consequence, finding more effective ways to increase model parameters has become a trend in deep learning research. Mixture-of-experts (MoE),

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Shared by Google AI Technology November 16, 2022

A conversation with Thomas Friedman about AI

Favorite Technology has an unmistakable impact on society — the way we work, learn and play have all changed significantly over the past decade. As SVP of Technology and Society, part of my work at Google is connecting people and ideas to help shape the future of our most ambitious

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Shared by Google AI Technology November 15, 2022

ReAct: Synergizing Reasoning and Acting in Language Models

Favorite Posted by Shunyu Yao, Student Researcher, and Yuan Cao, Research Scientist, Google Research, Brain Team Recent advances have expanded the applicability of language models (LM) to downstream tasks. On one hand, existing language models that are properly prompted, via chain-of-thought, demonstrate emergent capabilities that carry out self-conditioned reasoning traces

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Shared by Google AI Technology November 8, 2022

Infinite Nature: Generating 3D Flythroughs from Still Photos

Favorite Posted by Noah Snavely and Zhengqi Li, Research Scientists, Google Research We live in a world of great natural beauty — of majestic mountains, dramatic seascapes, and serene forests. Imagine seeing this beauty as a bird does, flying past richly detailed, three-dimensional landscapes. Can computers learn to synthesize this

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Shared by Google AI Technology November 7, 2022

Beyond Tabula Rasa: Reincarnating Reinforcement Learning

Favorite Posted by Rishabh Agarwal, Senior Research Scientist, and Max Schwarzer, Student Researcher, Google Research, Brain Team Reinforcement learning (RL) is an area of machine learning that focuses on training intelligent agents using related experiences so they can learn to solve decision making tasks, such as playing video games, flying

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Shared by Google AI Technology November 3, 2022