For writing your own kernels, sure, but a PyTorch built-in is almost always going to be faster than an implementation consisting of a series of simpler PyTorch functions.
MACHINE LEARNING
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AI4Science Panel at NeurIPS: Future of AI-Enabled Discovery
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AI is transforming scientific discovery at incredible speed Join us at NeurIPS for our AI4Science Panel with Rafael Gómez-Bombarelli, @jeffclune @james_y_zou as they discuss what the future of AI-enabled science might look like. Link to signup below
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SEA Workshop on Scaling Environments for AI Agents
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Next week at #NeurIPS2025 → the SEA Workshop on scaling environments for agents. If you care about eval, RL, or containerized rollouts — this is the room. Proud to sponsor this workshop. Shoutout to @guohao_li , @lawhy_X , @douglas_ym and @celineee_xie , along with the rest
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SAM 3D Advances Rehabilitation Through Human Movement Analysis
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SAM 3D is helping advance the future of rehabilitation.
— AI at Meta (@AIatMeta) 25 novembre 2025
See how researchers at @CarnegieMellon are using SAM 3D to capture and analyze human movement in clinical settings, opening the doors to personalized, data-driven insights in the recovery process.
🔗 Learn more about SAM… pic.twitter.com/UkQyD2qLeVSAM 3D is helping advance the future of rehabilitation. See how researchers at @CarnegieMellon are using SAM 3D to capture and analyze human movement in clinical settings, opening the doors to personalized, data-driven insights in the recovery process. Learn more about SAM
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Pretraining and Finetuning Outperform Algorithm Discovery in AI
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AI has crushed it since this post way beyond expectation. I made the same category of mistake all of AI was making, of thinking we have to discover and write the algorithm. You don't. You pretrain and then finetune a BIG neural network on lots of tasks and it just falls out. lol.
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Grok 4.1 Thinking ranks #2, Grok 4.1 #3 on LMArena; #1 by Jan?
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Grok 4.1 Thinking claims the top 2 spot on the LMArena text leaderboard (preliminary), with Grok 4.1 following with the top 3. Top 1 by Jan?
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PyTorch Built-in Functions Outperform Custom Tensor Rearrangement Code
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Always a slightly mixed feeling to write pretty good first-principles code to do some tensor rearrangement, only to find that PyTorch has a built in function that does it faster. I had made a point of at least skimming the docs of every torch and tensor function, but if you
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Evolution Strategies at Hyperscale: Deep Learning Optimization
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Evolution Strategies at the Hyperscale Sarkar et al.: https://
arxiv.org/abs/2511.16652 #ArtificialIntelligence #DeepLearning #MachineLearning -
VLM Benchmarking for Long Horizon Robotic Household Tasks
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Our most recent work that benchmarks modern VLM and their efficacy for long horizon household activities in robotic learning, using BEHAVIOR benchmark environment.👇 https://t.co/8Ibx8IA7MW
— Fei-Fei Li (@drfeifei) 25 novembre 2025Our most recent work that benchmarks modern VLM and their efficacy for long horizon household activities in robotic learning, using BEHAVIOR benchmark environment.
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Generative AI Tech Stack Framework for Autonomous Agents
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The Generative AI ecosystem is evolving into a full tech stack — powering autonomous AI agents.
From infrastructure and LLMs to RAG pipelines, agent behaviors and orchestration layers, this framework shows the 6 layers driving next-gen AI systems. Credit: @goyalshalini #AI