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Google at ICLR 2023

Google Research AI blog

If you’re registered for ICLR 2023, we hope you’ll visit the Google booth to learn more about the exciting work we’re doing across topics spanning representation and reinforcement learning, theory and optimization, social impact, safety and privacy, and applications from generative AI to speech and robotics.

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Research directions Open Phil wants to fund in technical AI safety

The AI Alignment Forum

This guide provides an opinionated overview of recent work and open problems across areas like adversarial testing, model transparency, and theoretical approaches to AI alignment. Were interested in more research on this, and other stress tests of todays state-of-the-art alignment methods.

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Stanford AI Lab Papers and Talks at NeurIPS 2021

Stanford AI Lab Blog

Kochenderfer Contact : philhc@stanford.edu Links: Paper Keywords : deep learning or neural networks, sparsity and feature selection, variational inference, (application) natural language and text processing Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss Authors : Jeff Z.

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Google at NeurIPS 2022

Google Research AI blog

Platt , Fernando Pereira , Dale Schuurmans Keynote Speakers The Data-Centric Era: How ML is Becoming an Experimental Science Isabelle Guyon The Forward-Forward Algorithm for Training Deep Neural Networks Geoffrey Hinton Outstanding Paper Award Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding Chitwan Saharia , William Chan (..)

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AXRP Episode 40 - Jason Gross on Compact Proofs and Interpretability

The AI Alignment Forum

Daniel Filan (00:28:50): If people remember my singular learning theory episodes , theyll get mad at you for saying that quadratics are all there is, but its a decent approximation. (00:28:56): Because okay, if Im imagining were doing this as a test case for thinking about some super big network.

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