Thomas Mesnard

166 posts

Thomas Mesnard

Thomas Mesnard

@Mesnard_Thomas

Research Scientist @Meta Superintelligence Labs. ex-@GoogleDeepMind - Gemma. PhD @IP_Paris_ | @Mila_Quebec | MSc MVA | @ENS_ULM

Paris Присоединился Ekim 2015
310 Подписки528 Подписчики
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Thomas Mesnard
Thomas Mesnard@Mesnard_Thomas·
🚀 After Gemma 3 1B, we’re going tiny: Gemma 270M — fast, on-device, low-power & privacy-first. A new vision: smaller models with strong instruction-following & finetuning, ideal for low-latency edge apps & automation. Congrats to everyone involved! huggingface.co/google/gemma-3…
Omar Sanseviero@osanseviero

Introducing Gemma 3 270M 🔥 🤏A tiny model! Just 270 million parameters 🧠 Very strong instruction following 🤖 Fine-tune in just a few minutes, with a large vocabulary to serve as a high-quality foundation developers.googleblog.com/en/introducing…

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Sundar Pichai
Sundar Pichai@sundarpichai·
An exciting milestone for AI in science: Our C2S-Scale 27B foundation model, built with @Yale and based on Gemma, generated a novel hypothesis about cancer cellular behavior, which scientists experimentally validated in living cells.  With more preclinical and clinical tests, this discovery may reveal a promising new pathway for developing therapies to fight cancer.
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Thomas Mesnard
Thomas Mesnard@Mesnard_Thomas·
Thrilled to announce the world’s most capable differentially private LLM! Huge congratulations to the entire team — and special kudos to Amer Sinha for his outstanding contributions. Take a look! services.google.com/fh/files/blogs…
Jeff Dean@JeffDean

VaultGemma is a release of an open model trained from scratch with differential privacy. The blog post below and the full tech report linked from the tech report have some nice analyses to present a scaling law for differentially private language models: Blog: research.google/blog/vaultgemm… Paper: arxiv.org/abs/2501.18914

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Sundar Pichai
Sundar Pichai@sundarpichai·
Introducing EmbeddingGemma, our newest open model that can run completely on-device. It's the top model under 500M parameters on the MTEB benchmark and comparable to models nearly 2x its size – enabling state-of-the-art embeddings for search, retrieval + more.
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Omar Sanseviero
Omar Sanseviero@osanseviero·
Introducing EmbeddingGemma🎉 🔥With only 308M params, this is the top open model under 500M 🌏Trained on 100+ languages 🪆Flexible embeddings (768 to 128 dims) with Matryoshka 🤗Works with your favorite open tools 🤏Runs with as little as 200MB developers.googleblog.com/en/introducing…
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Andreas Steiner
Andreas Steiner@AndreasPSteiner·
🚀🚀PaliGemma 2 is our updated and improved PaliGemma release using the Gemma 2 models and providing new pre-trained checkpoints for the full cross product of {224px,448px,896px} resolutions and {3B,10B,28B} model sizes. 1/7
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Éloi Zablocki
Éloi Zablocki@EloiZablocki·
📢 Exciting opportunity alert! We (valeo.ai) just posted our annual research internship openings in computer vision & ML. Check out the openings and the great achievements by our past interns here: valeoai.github.io/interns/
valeo.ai@valeoai

🌟 Calling all MSc students passionate about computer vision and ML! We’re offering research internships about diffusion models, multi-modal transformers, continual learning, & more. 4 exciting openings await! 🔗 Learn more: valeoai.github.io/interns/ RT to spread the word! 🙌

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Tris Warkentin
Tris Warkentin@triswarkentin·
Gemma 2 just got even better! 🚀 New Japanese-tuned 2B model AND a $150K Kaggle competition to build Gemma models for every language. Great to have @sundarpichai here to share the excitement! Read more: goo.gle/Gemma4Japan #GemmaDeveloperDay
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Markus Zimmermann
Markus Zimmermann@zimmskal·
Imagine a 27B LLM can beat a 405B model in writing quality code by investing a few milliseconds in static code repair. Now stop imagining and take a look at this chart 🌈 Just for Go, we have the following stats: - Increases score +22.9% across 45 applicable models - +26.2% response files compiled (avg. 17 files, 150 tasks total) - mistral-tiny has +71% in score: beats mistral-small and mistral-medium - Gemma 2 27B has +16% in score: beats GPT4o and Llama 3.1 405B Proof that the approach of doing code fixes over a static analysis should be the default for every code response and coding assistant. Makes code instantly more useful.
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