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Today we're sharing structure predictions for six proteins associated with the virus that causes COVID-19, generated by the most up-to-date version of our AlphaFold system. We hope this contributes to the research community’s understanding of the virus: deepmind.com/research/open-…

Four years ago, #AlphaGo and the legendary Lee Sedol took on an unprecedented challenge. To celebrate the landmark anniversary, we’re releasing AlphaGo The Movie for free on YouTube. Relive the experience here: youtu.be/WXuK6gekU1Y

New blog post: 'Generating music in the waveform domain' benanne.github.io/2020/03/24/aud… A comprehensive overview of the field and some personal thoughts, based on a tutorial I gave at ISMIR2019 with Jordi Pons and Jongpil Lee back in November. Comments / feedback welcome!

Excited to share our new paper from Moorfields Eye Hospital NHS Foundation Trust @DeepMind Google Health published today in Nature Medicine. We develop a deep learning model to predict which eyes will progress to wet AMD - one of the leading causes of blindness, using only retinal images. nature.com/articles/s4159…

Moving away from negative pairs in self-supervised representation learning: our new SotA method, Bootstrap Your Own Latent (BYOL), narrows the gap between self-supervised & supervised methods simply by predicting previous versions of itself. See here: bit.ly/30MCugQ

Presenting AlgebraNets, a new formalism for building neural architectures which increase parameter efficiency of vision models & achieve SOTA parameter efficiency on language modeling tasks: bit.ly/30G7Zt7

Standard techniques for training sequence models have storage requirements that increase with sequence length. We introduce a practical technique for training sequence models on _unlimited_ length sequences within a *fixed* memory budget: bit.ly/2zy1IV6

Bilingual children learn two languages by associating words to visually similar situations. We show how we use related ideas to train bilingual word translation models with no access to paired training data. #CVPR20 Paper: bit.ly/30VpKEH Blog: bit.ly/2Yb1JYv

Our new paper "Self-Supervised MultiModal Versatile Networks" learns from vision, audio and (ASR) language, achieves SOTA self-supervised video and audio representations, and we can deflate nets trained on videos to apply them on images. arxiv.org/abs/2006.16228

📜🚨📜🚨 NN loss landscapes are full of permutation symmetries, ie. swap any 2 units in a hidden layer. What does this mean for SGD? Is this practically useful? For the past 5 yrs these Qs have fascinated me. Today, I am ready to announce "Git Re-Basin"! arxiv.org/abs/2209.04836

Happy to announce DreamFusion, our new method for Text-to-3D! dreamfusion3d.github.io We optimize a NeRF from scratch using a pretrained text-to-image diffusion model. No 3D data needed! Joint work w/ the incredible team of Ben Mildenhall Ajay Jain Jon Barron #dreamfusion

Excited to announce Imagen Video, our new text-conditioned video diffusion model that generates 1280x768 24fps HD videos! #ImagenVideo imagen.research.google/video/ Work w/ William Chan (陳俊樂) Chitwan Saharia Jay Whang Ruiqi Gao Alexey Gritsenko Durk Kingma Ben Poole Mohammad Norouzi David Fleet Tim Salimans

New paper: continuous diffusion for categorical data We train diffusion language models with cross-entropy, using score interpolation instead of score matching. The training distribution of noise levels is adapted on the fly with time warping. arxiv.org/abs/2211.15089 (1/3)

Did you know, that you can build a virtual machine inside ChatGPT? And that you can use this machine to create files, program and even browse the internet? engraved.blog/building-a-vir…

if i start going off, the openai board should go after me for the full value of my shares