Tim Green
@tfgg2
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Research Engineer at @GoogleDeepMind, co-led the AlphaFold team, now working on LLMs for science. Previously @democlub and physics.
London
Joined February 2011
Come join us working on LLMs for science!
We are expanding our efforts in LLM-based scientific discovery and are hiring for several roles. Come join my team and work with us on the future of natural language scientific AI! https://t.co/Jky2wMcHHt
https://t.co/teDVpQKm95 See RS and RE roles above.
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Every time I use the NHS they say there’s a new app and it’s not an app it’s a website on my phone and they’re like it’s on PatientIsRight it’s literally on getUbetter just log in to PatientAccess it’s on DrDoctor log onto DrDoctor right now DrDoctor has it for you
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About 9months ago I had a really frustrating call with people in the UK government following years of frustrating meetings with people in the UK government. An archive of the UK's bus open data, the location of every bus in real time, was going to be too hard to release,...
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Our team at DeepMind is growing (again). 🚀 We're tackling grand challenges in semiconductors, magnets, energy materials, superconductors, and beyond. Join us! Two positions below.
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Very excited about our progress on materials! Super cool work, come join the AI for Science team.
Our team at DeepMind is growing (again). 🚀 We're tackling grand challenges in semiconductors, magnets, energy materials, superconductors, and beyond. Join us! Two positions below.
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We’re looking for an engineer to build the system that runs our scientific simulations. You'll be fully embedded in our research teams, handling everything from optimizing quantum chemistry calculations at scale to training ML models and coordinating AI agents.
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We're pioneering new AI tools to accelerate scientific discovery, and we need exceptional engineers to help us build them. If you are passionate about using computers to help solve some of humanity's hardest and most important scientific problems, come join us.
Very excited about our progress on materials! Super cool work, come join the AI for Science team.
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We’re announcing a research collaboration with @CFS_energy, one of the world’s leading nuclear fusion companies. Together, we’re helping speed up the development of clean, safe, limitless fusion power with AI. ⚛️
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Super excited to be collaborating with Commonwealth Fusion Systems @CFS_energy to use AI to accelerate fusion development - and move closer to a sustainable future with limitless clean energy
We’re announcing a research collaboration with @CFS_energy, one of the world’s leading nuclear fusion companies. Together, we’re helping speed up the development of clean, safe, limitless fusion power with AI. ⚛️
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I’m up for an anti-big developer Housing Secretary! Big developers don’t want a more open market where urban densification is easier. Their business model is greenfield Barratt Boxes. Many planning reform attempts fail because they’re designed to just give them what they want.
The new Housing Secretary has just deleted this tweet attacking developers. We really hope this reflects a change of heart on planning reform.
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Official results are in - Gemini achieved gold-medal level in the International Mathematical Olympiad! 🏆 An advanced version was able to solve 5 out of 6 problems. Incredible progress - huge congrats to @lmthang and the team!
deepmind.google
The International Mathematical Olympiad (“IMO”) is the world’s most prestigious competition for young mathematicians, and has been held annually since 1959. Each country taking part is represented by…
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John Jumper (Distinguished Scientist @GoogleDeepMind) at @ycombinator AI Startup School talking protein folding and research leaps in biology. If you’re a scientist predicting protein structures, check out Alphafold protein structure database 👩🏽🔬
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Hey Colab users, we are looking at hardware capacity and planning and are wondering what things are most valuable to you when using Colab? Please vote and share thoughts in the comments!
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If "What are those?" is more than just a curious question to you, you've come to the right show. ⏮️ Listen to @GlobalPlayer's podcast, Vine: Six Seconds That Changed The World to hear @BenedictTown look back on the rise and fall of Vine. https://t.co/Ny2SIrLvYv
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Come work with us on advancing science using LLMs! Exciting times ahead 🧑🔬🤖
We are expanding our efforts in LLM-based scientific discovery and are hiring for several roles. Come join my team and work with us on the future of natural language scientific AI! https://t.co/Jky2wMcHHt
https://t.co/teDVpQKm95 See RS and RE roles above.
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Advancing Science is one of the most meaningful applications of AI. I would highly recommend joining this amazing team of researchers and engineers who are not only exceptional experts in Science and AI but are pursuing this vision with a mission focus.
We are expanding our efforts in LLM-based scientific discovery and are hiring for several roles. Come join my team and work with us on the future of natural language scientific AI! https://t.co/Jky2wMcHHt
https://t.co/teDVpQKm95 See RS and RE roles above.
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We are expanding our efforts in LLM-based scientific discovery and are hiring for several roles. Come join my team and work with us on the future of natural language scientific AI! https://t.co/Jky2wMcHHt
https://t.co/teDVpQKm95 See RS and RE roles above.
job-boards.greenhouse.io
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‘Vine: 6 seconds that changed the world’ is finally here! Possibly the best, nostalgic fun I’ve had as a journalist, and genuinely fascinating to get the inside scoop on the tech decisions that continue to change the way we communicate, think, and live. Give it a listen! #vine
Vine will rise again 🔥 Listen to 'Vine: Six Seconds That Changed The World' right now on @globalplayer or wherever you get your pods 🔗⬇️
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The online discussion seems to have largely missed this key point. The complaint wasn't "they didn't cite us wahhhh" but that prior work was selectively omitted to tell a misleading narrative that ANY amount of synthetic data can be toxic 1/3
>Our results show that even the smallest fraction of synthetic data (e.g., as little as 1 per 1000) can still lead to model collapse
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