David La

You know what's cool... a quadrillion tokens. We processed almost 1,000,000,000,000,000 tokens last month, more than double the amount from May. 📈

Big news for data science in higher ed! 🚀Colab now offers 1-year Pro subscriptions free of charge for verified US students/faculty, interactive Slideshow Mode for lectures, & an AI toggle per notebook. Enhance teaching & learning in the upcoming academic year! Read all about it here: goo.gle/40pxnl1. #GoogleColab #EdTech.

Major congratulations to my previous postdoc advisor David Baker @UWproteindesign and my current coworkers Demis Hassabis and John Jumper @GoogleDeepMind!

BREAKING NEWS The Royal Swedish Academy of Sciences has decided to award the 2024 #NobelPrize in Chemistry with one half to David Baker “for computational protein design” and the other half jointly to Demis Hassabis and John M. Jumper “for protein structure prediction.”

BREAKING NEWS The Royal Swedish Academy of Sciences has decided to award the 2024 #NobelPrize in Physics to John J. Hopfield and Geoffrey E. Hinton “for foundational discoveries and inventions that enable machine learning with artificial neural networks.”

Our AI for chip design method AlphaChip has transformed the way we design microchips. ⚡ From helping to design state-of-the-art TPUs for building AI models to CPUs in data centers - its widespread impact can be seen across Alphabet and beyond. Find out more → dpmd.ai/3ZDRtYY

We’re presenting AlphaProteo: an AI system for designing novel proteins that bind more successfully to target molecules. 🧬 It could help scientists better understand how biological systems function, save time in research, advance drug design and more. 🧵 dpmd.ai/3XuMqbX

Introducing Ithaca, the first deep neural network for textual restoration, as well as geographical and chronological attribution of ancient Greek inscriptions. Out today in @nature, Ithaca aims to assist historians & better understand ancient history: dpmd.ai/Ithaca-blog 1/

On the cover of @Nature today, our work ITHACA on restoring, locating and dating ancient texts using deep neural networks! So proud of our team @iassael @Sicilyepigraphy @BrendanShilling @_Mahyar_ @NandoDF @ionandrou @itpavlopoulos & all our collaborators

Today in @nature, with @EPFL, the first deep reinforcement learning system that can keep nuclear fusion plasma stable inside its tokamaks, opening new avenues to advance nuclear fusion research. Paper: dpmd.ai/fusion-paper

OK, this is one I’ve been waiting to share for a *long* time – the first ever demonstration of deep reinforcement learning on a nuclear fusion research device! nature.com/articles/s4158…

Introducing #AlphaCode: a system that can compete at average human level in competitive coding competitions like @codeforces. An exciting leap in AI problem-solving capabilities, combining many advances in machine learning! Read more: dpmd.ai/Alpha-Code 1/

Aversarial example in the human mind?

Can machine learning explain the world at the quantum level? New in @ScienceMagazine, with the code also released, our team shows that neural networks can radically improve density functionals with #DM21. Read more: dpmd.ai/density-functi… Code: dpmd.ai/density-functi… 1/

Ramanujan is my favourite mathematician. I’ve always loved his intuitive style, seeing hidden patterns in numbers noone else could. It inspired us to wonder about the potential of using AI as a tool to help the intuition of today’s top mathematicians: dpmd.ai/maths-blog

A new paper in @Nature details how machine learning was used to make significant new discoveries in pure mathematics by guiding the intuition of some of the world’s top mathematicians from @Sydney_Uni and @OxUniMaths: dpmd.ai/maths-blog Paper: dpmd.ai/nature-maths 1/

Thrilled to announce the launch of a new Alphabet company @IsomorphicLabs. Our mission is to reimagine the drug discovery process from first principles with an AI-first approach, to accelerate biomedical breakthroughs and find cures for diseases. Details: isomorphiclabs.com/blog

The #AlphaFold source code has been updated and now accounts for multi-chain protein complexes - providing a significant improvement in accuracy for predicting protein interactions: dpmd.ai/af-multimer-os Generate predictions from your browser via: dpmd.ai/alphafold-colab

@biaobinjiang Hi Biaobin. Thanks for reaching out. Good to see your excitement. Feel free to DM me whenever.

@davidla Hey David! Glad meeting you here! I am also working on how AI facilitates antibody development. We may have some common interests and let's chat more!

Structural insight to new protective antibodies against Ebola. goo.gl/d1IBrG

We’ve acquired the MuJoCo physics simulator (mujoco.org) and are making it free for all, to support research everywhere. MuJoCo is a fast, powerful, easy-to-use, and soon to be open-source simulation tool, designed for robotics research: dpmd.ai/mujoco-blog