
Sheheryar Zaidi
@ShehZaidi
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Research Scientist at @GoogleDeepMind. Prev. PhD in Machine Learning at @OxfordStats. Google PhD Fellow in ML & Aker Scholar. Math @UniofOxford @Cambridge_Uni.
London, England
Joined September 2013
Mysterious observation: re-initializing neural nets during training can improve generalization, despite *no* change to the model, data or compute. We asked: when do re-initialization methods work?. Paper📄: Poster🖼️: . (1/6)
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RT @arkitus: This started as a prototype we built back in March 2024 which we called ‘Neural Google’. The core idea: wrap Gemini around Goo….
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RT @SuryaGanguli: Nice - we could have prompted our way to winning IMO gold on an already available model!.
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Exciting and unique opportunity in our team at @GoogleDeepMind: we're hiring a laboratory scientist to build out a materials-synthesis lab 🧪 . This lab will be a key part of our roadmap for training AI models capable of real-world materials discovery 🔁.
job-boards.greenhouse.io
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Another one that came sooner than I expected: gold medal at IMO in natural language with a generalist model! 🥇.
An advanced version of Gemini with Deep Think has officially achieved gold medal-level performance at the International Mathematical Olympiad. 🥇. It solved 5️⃣ out of 6️⃣ exceptionally difficult problems, involving algebra, combinatorics, geometry and number theory. Here’s how 🧵
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RT @BenBlaiszik: Sharing this very unique materials science role with @GoogleDeepMind. They are looking specifically for someone to build a….
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RT @alan_karthi: How might AI supercharge world-class expertise in medicine for everyone, everywhere? . We’re privileged to pursue this mis….
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🧠 Interested in pushing the scientific frontier with LLM post-training and RL? Our team is hiring a Research Engineer at Google DeepMind to accelerate materials science! 💡 Join us:
job-boards.greenhouse.io
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RT @simonbatzner: 🚨 Our team at GDM is hiring a research engineer to work on topics around RL, post-training + materials science! Role is b….
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RT @emidup: We introduce 🌸✨ AlphaEvolve ✨🌸, an evolutionary coding agent using LLMs coupled with automatic evaluators, to tackle open scien….
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RT @Rija_Zaidi_: How much do algorithmic and experimental choices drive the accuracy of reconstructing tumour evolution? . In this @CR_AACR….
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RT @Rija_Zaidi_: Our paper is out! We introduce the SPRINTER algorithm to infer clone proliferation rates from scDNAseq data 🧬 . Great to w….
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Congratulations to Demis, John and the whole AlphaFold team!. Two Nobels for deep learning in one year – wild times! 🎉.
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.”
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RT @pfau: I’m beyond thrilled to share that our work on using deep learning to compute excited states of molecules is out today in @Science….
science.org
We present an algorithm to estimate the excited states of a quantum system by variational Monte Carlo, which has no free parameters and requires no orthogonalization of the states, instead transfor...
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Incredible achievement. Only 1 point away from a gold medal + it solved P6! 🎉🥈This felt a bit further in the future than it was. Excited about the implications of such systems for open problems in math.
We’re presenting the first AI to solve International Mathematical Olympiad problems at a silver medalist level.🥈. It combines AlphaProof, a new breakthrough model for formal reasoning, and AlphaGeometry 2, an improved version of our previous system. 🧵
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Nuts rate of progress in the field!.
Gemini and I also got a chance to watch the @OpenAI live announcement of gpt4o, using Project Astra! Congrats to the OpenAI team, super impressive work!
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RT @oe_oevreboe: Exploring hyaluronic acid gels in your research? Check out our latest publication for a detailed, simple, reproducible, an….
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RT @OriolVinyalsML: Gemini 1.5 Pro has entered the (LMSys) Arena! Some highlights:. -The only "mid" tier model at the highest level alongsi….
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A very natural idea (in retrospect!) given that MLPs are most often illustrated as graphs – nice work.
🔍How can we design neural networks that take neural network parameters as input?.🧪Our #ICLR2024 oral on "Graph Neural Networks for Learning Equivariant Representations of Neural Networks" answers this question!. 📜: 💻: 🧵 [1/9]
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RT @emidup: We build neural codecs from a *single* image or video, achieving compression performance close to SOTA models trained on large….
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