Workshop on Foundation Models: Day 1 скачать в хорошем качестве

Workshop on Foundation Models: Day 1

The Center for Research on Foundation Models (CRFM), a new initiative of the Stanford Institute for Human-Centered Artificial Intelligence (HAI), hosted the Workshop on Foundation Models from August 23-24, 2021. By foundation model (e.g. BERT, GPT-3, DALL-E), we mean a single model that is trained on raw data, potentially across multiple modalities, which can be usefully adapted to a wide range of tasks. These models have demonstrated clear potential, which we see as the beginnings of a sweeping paradigm shift in AI. They represent a dramatic increase in capability in terms of accuracy, generation quality, and extrapolation to new tasks, but they also pose clear risks such as use for widespread disinformation, potential exacerbation of historical inequities, and problematic centralization of power. Experts from a diverse array of perspectives and backgrounds convened to address the opportunities, challenges, limitations, and societal impact of these models. Day 1: Introduction Fei-Fei Li, Sequoia Professor, Computer Science Department, Stanford University; Denning Co-Director, Stanford Institute for Human-Centered Artificial Intelligence Foundation Models Percy Liang, Associate Professor of Computer Science, Stanford University Session I: Opportunities and Responsibility What Has Happened, Where Are We Going, and Who Gets to Build Them Jack Clark, Co-Founder, Anthropic; Co-chair of the AI Index; Co-chair of the OECD's working group on classifying and defining AI systems Threshold Effects Michael Bernstein, Associate Professor of Computer Science, Stanford University Foundation Models for Law & The Law of Foundation Models: A U.S. Perspective Dan Ho, William Benjamin Scott and Luna M. Scott Professor of Law, Professor of Political Science, Associate Director for the Stanford Institute for Human-Centered Artificial Intelligence (HAI) Joint Q&A Panel Jack Clark, Co-Founder, Anthropic; Co-chair of the AI Index; Co-chair of the OECD's working group on classifying and defining AI systems Su Lin Blodgett, Postdoctoral Researcher, Microsoft Eric Horvitz, Technical Fellow; Chief Scientific Officer, Microsoft Joelle Pineau, Co-Managing Director, Facebook AI Research; Associate Professor and William Dawson Scholar of Computer Science, McGill University Jacob Steinhardt, Assistant Professor of Statistics, University of California, Berkeley Percy Liang (moderator), Associate Professor of Computer Science, Stanford University Break Session II: Technological Foundations David V.S. Goliath: the Art of Leaderboarding in the Era of Extreme-Scale Neural Models Yejin Choi, Brett Helsel Professor at the Paul G. Allen School of Computer Science & Engineering, University of Washington; Senior Research Manager, Allen Institute for AI Broad Robot Generalization Requires Broad Offline Data Chelsea Finn, Assistant Professor of Computer Science and Electrical Engineering, Stanford University Theory for Foundations Models: Analysis Framework, Recent Results, and Challenges Tengyu Ma, Assistant Professor of Computer Science and Statistics, Stanford University On the Inductive Bias of Masked Language Modeling: From Statistical to Syntactic Dependencies Tatsu Hashimoto, Assistant Professor of Computer Science, Stanford University Joint Q&A Panel Yejin Choi, Brett Helsel Professor at the Paul G. Allen School of Computer Science & Engineering, University of Washington; Senior Research Manager, Allen Institute for AI Sanjeev Arora, Charles C. Fitzmorris Professor of Computer Science, Princeton University Kavita Bala, Dean of the Ann S. Bowers College of Computing and Information Science, Cornell University Jitendra Malik, Arthur J. Chick Professor of Electrical Engineering and Computer Science, University of California, Berkeley Natalie Schluter, Senior Research Scientist, Google Brain; Associate Professor of Computer Science, IT University of Copenhagen Chris Manning (moderator), Thomas M. Siebel Professor in Machine Learning, Professor of Linguistics and Computer Science, Stanford University; Associate Director, Stanford Institute for Human-Centered Artificial Intelligence Watch Day 2 here:    • Workshop on Foundation Models: Day 2   Learn more about the Center for Research on Foundation Models: https://crfm.stanford.edu/index.html