Introducing our hosts for The Tournament: Baxate Carter and Nader Khalil. https://t.co/wG93FAjyPg

Today we’re bringing @Gmail into the Gemini era, making it a personal, proactive inbox assistant to help you manage your life, not just your messages. Explore the new features launching today, many of which are made possible by Gemini 3 🧵⬇️ https://t.co/30ABrZBInv

Nature is healing https://t.co/kGE5gZUjOF

Some times you have to take pause and appreciate how blessed your life is. Such amazing conversations with brilliant and inspiring individuals. Thanks @NVIDIAAIDev crew and #ces2026, that's a wrap, interviews coming soon! Shout out @NaderLikeLadder & @Baxate_carter 💚🤙 family https://t.co/AtnNFRvymH

+2 more

Office hours with @NaderLikeLadder https://t.co/qpNaMVGjbY

Office hours with @NaderLikeLadder https://t.co/qpNaMVGjbY

Video message from Federal Reserve Chair Jerome H. Powell: https://t.co/5dfrkByGyX https://t.co/O4ecNaYaGH

Today, we’re super excited to announce @NVIDIA has integrated @shadeformai 's compute marketplace to supply NVIDIA GPUs to the NVIDIA Brev platform https://t.co/a0X4WQSWgc

Just kicked off the @alifdotbuild x @Replit Tournament!!! 🤩🤙 Gonna be a fun weekend https://t.co/C3p9HFEx92

Kicked off w/ a few words from the 🐐 @amasad https://t.co/uCTBFpeVMp

IBM’s Christian Jacobi (@IBM Fellow and CTO, IBM Systems Development) on why the PyTorch community matters for AI today, the role of open source, and what he’s hearing from clients deploying AI in core IT and business processes. 🎥 https://t.co/ZTwg7fz7xi https://t.co/TdHLMNkbiT

Need to accelerate inference for math problem solving? Large language models can solve challenging math problems. However, making them work efficiently at scale requires the right serving stack, quantization strategy, and decoding methods—often spread across different tools. This @nvidia blog post shows how to build a fast, reproducible inference pipeline with the NVIDIA NeMo-Skills library to manage NVIDIA TensorRT-LLM. 🔗https://t.co/OVfQSEstfj #PyTorch #OpenSourceAI #AI #Inference #Innovation

🔥 #PyTorchDayIndia is coming to Bengaluru on 7 February! Register NOW and save your seat for a full day of #PyTorch technical talks, discussions & networking with #AI & #ML leaders. Act fast! This event is just a month away! Register: https://t.co/HUq2BjyvyM https://t.co/fKuZBmTpHb

FlexAttention has been adopted across popular #LLM ecosystem projects, including Hugging Face, vLLM, and SGLang, reducing the effort required to adapt and experiment with newer attention variants in modern LLMs. 🔗 Read our latest blog from @Intel #PyTorch & Triton Teams: https://t.co/dZvUASpEbR #AIInfrastructure #OpenSourceAI

PyTorch Day India 2026 is coming to Bengaluru on 7 February 2026, bringing together the PyTorch community for a full day of technical talks, discussions, and poster sessions focused on open source AI and machine learning. Hosted by PyTorch Foundation and co-hosted with @IBM, @nvidia, and @RedHat, the event is designed for PyTorch users, machine learning engineers, AI researchers, and industry professionals working across the ecosystem. 🖇️ Register today: https://t.co/gqi47un8WZ #PyTorch #AIInfrastructure #OpenSourceAI

The Triton team at Meta shares a working implementation of warp specialization in the #Triton compiler, along with the current design and upcoming roadmap, and invites community feedback from the #PyTorch and open source AI community. 🔗https://t.co/ohoDJVCT5I #AIInfrastructure #OpenSource

Scaling RL for LLMs is hard. The #PyTorch team at Meta open sourced torchforge and shares #ReinforcementLearning lessons from evaluating it with Weaver on a 512 GPU cluster. 🔗 https://t.co/1iayWOGU26 https://t.co/cGTUg0hfYn

This @IBM tutorial shows how to build a spam text classifier from scratch using #PyTorch. AI Engineer and Developer Advocate Anna Gutowska walks through the full NLP workflow, from text preprocessing and #tokenization to training an LSTM model that reaches ~97% accuracy in a few epochs. 📖 Read and try it yourself: https://t.co/XNlWZD0mic #OpenSourceAI #MachineLearning

Prabha Ganapathy (@awscloud) shares how contributing optimizations back to the #opensource community benefits the broader ecosystem and why serving on the #PyTorch Foundation board matters. 🔗https://t.co/VRyvSMWr5I #PyTorch #OpenSourceAI https://t.co/IfaspdYs05

We have a mini conference lined up for you Wednesday, January 14, 2026 at 9:05 AM on Reinforcement Learning, Agents & OpenEnv with a heavyweight lineup of speakers from @PyTorch @huggingface and @UnslothAI See you tomorrow! https://t.co/PFz7csVRcd

📣 ICYMI: #PyTorchDayIndia is coming to Bengaluru on 7 February! Register NOW & reserve your seat for a full day of #PyTorch technical talks, discussions & networking with #AI & #ML leaders ➡️ https://t.co/sVYdosezcR https://t.co/w3hj6asC91

NVIDIA TensorRT LLM provides a high-level Python LLM API, with its PyTorch-native architecture enabling developers to experiment with the runtime or extend functionality. Learn how these latest TensorRT-LLM optimizations boost reasoning inference performance in our recent blog post. 🖇️ https://t.co/XOSjWAmvMP #PyTorch #OpenSourceAI #AI #Inference #Innovation

TorchAO Quantized Gemma-3 Models Now Available on HuggingFace 🚀 TorchAO quantized Gemma-3 models (4b, 12b and 27b) are now available in multiple quantized formats (FP8, INT4, AWQ-INT4, HQQ-INT8-INT4, QAT-INT4) on HuggingFace Hub! Our models: * Run efficiently on A100/H100 GPUs (with vLLM) & mobile devices (with ExecuTorch) * Deliver faster inference, big memory savings, and minimal accuracy loss compared to BF16 model * Include reproducible quantization recipes for your own models, including algorithms like AWQ, HQQ and QAT 🖇️ Check out the collection: https://t.co/hAEeQuqSIL #LLM #PyTorch #TorchAO #ExecuTorch #VLLM #Quantization #Gemma3 #HuggingFace #EdgeAI

2025 was a defining year for PyTorch Foundation. We expanded into an umbrella foundation, welcomed foundation-hosted projects vLLM, DeepSpeed, and Ray, added 16 new members, and strengthened our portfolio across training, inference, and distributed compute As we look ahead to 2026, we set priorities for the year with perspectives from @matthew_d_white, @joespeez (@Meta), and Luca Antiga (@LightningAI). 🖇️ Read it here: https://t.co/fbraqmTUKI #PyTorch #OpenSourceAI #AIInfrastructure

Reminded me of our older NeurIPS 2021 paper where we removed the positional encoding entirely, and by doing so, an agent can process an arbitrarily long list of noisy, sensory inputs, in an arbitrary order. I even made a fun browser demo to play with it: https://t.co/7NN4r9NOiM

Extending the Context of Pretrained LLMs by Dropping Their Positional Embeddings https://t.co/Fp5IJS4LIC Authors: Yoav Gelberg, Koshi Eguchi, Takuya Akiba (@iwiwi), and Edoardo Cetin. In the paper, we provide a theoretical analysis of this trade-off. We prove that while NoPE transformers struggle to learn attention patterns from scratch due to vanishing gradients, standard RoPE scaling inevitably warps semantic attention by compressing low frequencies. DroPE sidesteps both issues: utilizing RoPE for convergence, then removing it to avoid semantic shift during extension.

Since Core War is a Turing-complete environment where code and data share the same address space, the “warriors” Redcode programs produced by LLMs, selected through natural selection quickly exhibit rather chaotic self-modifying code dynamics. Full Paper: https://t.co/mynZXzXYOO https://t.co/b7o5forgWU

Digital Red Queen: Adversarial Program Evolution in Core War with LLMs https://t.co/zHNcl2xEtC TL;DR. With MIT, we propose a method for self-evolving assembly code. The process iterates code evolution through battles in Core War. By training new warriors against an ever-changing lineup of opponents rather than a static optimization objective, we can produce warriors that are both robust and general-purpose.

1/🧵 We prompted production LLMs with a short prefix of a book and asked them to complete the rest. How much of the book did they return? For Harry Potter and the Sorcerer’s Stone: (jailbroken) Claude 3.7 Sonnet→95.8%, GPT-4.1→4.0% (not jailbroken) Gemini 2.5 Pro→76.8%, Grok 3→70.3% Read on more details:

AI sovereignty vs. market concentration—can Europe have both? New data shows the EU cloud market shrinking to fewer providers, right as AI demands explode. But there's a path: distributed hybrid architecture lets nations capture economic value without sacrificing control. Is digital sovereignty the next competitive battleground? AI’s future: Plotting a path to competitiveness and digital sovereignty

Trillions are flowing into AI on the belief that progress toward AGI will keep accelerating. That belief may be more fragile than markets assume. Yoshua Bengio warns that AGI development could hit a wall, even as investment continues to surge. If expectations outrun reality, the risk won’t be technical alone. It could turn financial. https://t.co/sMKCVFIL6j

AI is already moving from assistant to operator. Some founders are building companies with AI as part of the core team, not just a tool. Yesim Saydan trained more than a dozen custom GPTs to run her solo consultancy, including one inspired by Steve Jobs to act as a mentor and decision sparring partner. AI may feel scary, but this is the shift to watch. Not AI replacing founders, but founders scaling their thinking. For some, AI is no longer optional. It is the edge. https://t.co/jVEw7atlyB @businessinsider