“PyTorch is the most important open-source project at this moment in history.” https://t.co/lJv4TYnKy7

And that’s a wrap. Thanks for an amazing first-ever #PyTorchCon Europe 2026! https://t.co/pRmqjLTGzn

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NEW paper from Google on multi-agent research agents. It's one of the first systems that handles end-to-end LaTeX generation, targeted literature reviews, and conceptual diagrams as a decoupled, standalone writer. Automated research frameworks can run experiments, but their writing modules remain the weakest link. Literature reviews are shallow, citations are sparse, and no system generates conceptual diagrams. This new research introduces a standalone writing framework that addresses all of this. PaperOrchestra is a multi-agent system that transforms unconstrained pre-writing materials, raw ideas, experimental logs, notes, into submission-ready LaTeX manuscripts. It uses specialized agents for deep literature synthesis, plot generation, conceptual diagram creation, and iterative refinement. The team also releases PaperWritingBench, the first standardized benchmark with reverse-engineered materials from 200 top-tier AI conference papers. Why does it matter? In side-by-side human evaluations, PaperOrchestra achieved absolute win rate margins of 50 to 68% in literature review quality and 14 to 38% in overall manuscript quality over autonomous baselines. Paper: https://t.co/HExJojfQPG Learn to build effective AI agents in our academy: https://t.co/LRnpZN7L4c

⏰ ICYMI — #PyTorchCon North America 2026 CFP is open! Got a session or poster idea? Submit for Oct 20–21 in San Jose. We're looking for work on training, inference, kernel engineering, responsible AI & more. 👉 Submit a session by June 7: https://t.co/Mz2gMtNnFc ⚡Submit a poster by July 26: https://t.co/kp9yuHyVtv

NEW paper: Memory Intelligence Agent (MIA) MIA boosts GPT-5.4 by up to 9% on LiveVQA. Quick summary: Most memory-augmented agents treat memory as a static retrieval problem. They store trajectories, retrieve similar ones, and hope for the best. But memory that doesn't evolve becomes stale, and storage costs grow without bound. This new framework combines a non-parametric Memory Manager for compressed trajectory storage, a parametric Planner trained via RL to produce search strategies, and an Executor that carries them out. The key innovation is bidirectional conversion between parametric and non-parametric memory, plus test-time learning that updates the Planner on-the-fly during inference. MIA boosts GPT-5.4 by up to 9% on LiveVQA. With a lightweight 7B Executor, it achieves 31% average improvement across eleven benchmarks, outperforming the much larger 32B model by 18%. Memory systems for agents need to evolve, not just accumulate. MIA's alternating RL training and bidirectional memory conversion show that treating memory as a living system, not a database, produces substantially better deep research agents. Paper: https://t.co/eSQa0URWCk Learn to build effective AI agents in our academy: https://t.co/1e8RZKs4uX

first company i've seen with the stated goal of climbing the kardashev scale that actually might do it https://t.co/h07TvAMUj7

SKY FULL OF STARS: @elonmusk reaffirms his hope for humanity to reach new heights in outer space after NASA releases breathtaking new photo of the Milky Way galaxy captured by Artemis II astronauts. https://t.co/hEERowg4RF

PyTorch Ambassadors are making a big difference, spanning 21 countries and 5 continents. During the #PyTorchCon Europe 2026 Ambassador Meetup, ambassadors met with PyTorch Foundation leadership to share experiences https://t.co/KMFyvpRcKK

Glad to see that Mytos is putting back cybersecurity in the spotlight. Our main contribution to the topic has been the creation of Safetensors by @narsilou @huggingface in collaboration with @AiEleuther @StabilityAI. It has become the most popular way to share models safely and today @LysandreJik announced at #PyTorchCon that the project is joining the @PyTorch foundation to continue to scale (for example with torch core integration). Let's turn talks about cyber-security into action!

Google CEO Sundar Pichai on current frontier model's ability to break the security of almost all current software. "These models are definitely, like really gonna break pretty much all software out there, maybe already, we don't know." https://t.co/ezjPcSehiG

This is a great tutorial (credits @itsclelia + @lancedb) on how to build a practical retrieval pipeline that integrates directly with your agent harness. 1. Ingest a massive pile of docs with liteparse. 2. Store data in a vector db (despite my memes to the contrary, you will need some database for larger scale retrieval). 3. Pair with image screenshotting tools that allow the agent to "dive deeper" into data. When you pair this with the Claude Agent SDK / Claude Code, the agent will do some initial retrieval pass to pull the relevant doc, and then use screenshotting/VLM-enabled capabilities to do deeper analysis. Blog: https://t.co/mbdy4I5oAh

Safetensors is joining the @PyTorch Foundation as a foundation-hosted project It has always been open-source. Going forward, strategy and direction is now open Now, safetensors has a clear path towards integration in torch core ML is big, so is making it safe. Come contribute! https://t.co/yLQFgxNJDs

Your brand is an afterthought for out-of-the-box AI tools. Of course it is. They weren’t built for you, they were built for everyone. You deserve a creative production platform that puts your brand first, exactly how you envisioned. Introducing Brand Studio by Stability AI, the creative production platform powered by your brand. Get started here: https://t.co/WUWML6YJ28

Our team (@kstonekuan , @Artylo99) came in 2nd at the OpenAI x January Capital hackathon! We're grateful for the organizers' generosity and support. Excited to keep building alongside the community. https://t.co/hIT0jPoya0

We released Gemma 4 last week, and seeing the community's response has been amazing! 🚀 Honored to lead the vision efforts in which we made huge performance leaps from Gemma 3, I wanted to help you make the most of the new capabilities. Deep dive 🧵 https://t.co/nP6ogGgghf

ETERNO is supercharging healthcare by transforming pen and paper practices into cloud-based clinics that support patients and clinical teams. Built on AWS, its platform streamlines operations, strengthens data protection, and provides a foundation for ETERNO to scale in Europe. https://t.co/IAgkYi0WjL

People of pi. BIG NEWS. I've sold out. Let me know how you feel about this in the comments below. https://t.co/dy1ffkhMRf

Strong release! GLM-5.1 is a DeepSeek-V3.2-like architecture (including MLA and DeepSeek Sparse Attention) but with more layers. And the benchmarks look better throughout! Looks like THE flagship open-weight model now. https://t.co/8kzTXaFcJv

PS: I finally got around to trying out @randal_olson 's Tufte Test tool to prettify the benchmark plot. Great tool 👌! https://t.co/146ZnHsbgn

Hierarchical planning unlocks long-horizon, non-greedy behavior in JEPA world models. Paper: https://t.co/lp5xR5RFnJ Website: https://t.co/CCFKfmTffk Code: https://t.co/S3WIFSn2MH https://t.co/SKWjtos8Up

Full release on @MetaQuestVR in May! Next step will be publishing on @PICOXR and @PlayStation VR. App link for Quest bellow https://t.co/g9lqZC9kK0

By optimizing for token efficiency and memory footprints, we unlock a new class of applications that are faster, private, and more accessible. During #PyTorchCon EU keynote, Léonard Hussenot, Research Scientist at @GoogleDeepMind explores the philosophy and engineering behind Gemma 4, arguing that the future of AI isn't only about size, but about "intelligence per byte."

Normalization methods (LayerNorm/RMSNorm) are foundational in modern deep learning models. We evaluate and improve torch.compile performance for LayerNorm/RMSNorm on NVIDIA H100 and B200 to reach near SOTA performance on a kernel-by-kernel basis, whilst providing automatic fusion capabilities with torch.compile for peak e2e performance. 🔗 Read our latest blog from Shunting Zhang, Paul Zhang, Markus Höhnerbach, Elias Ellison, Jason Ansel, and Natalia Gimelshein: https://t.co/ie5UZag3qx Today at PyTorch Conference EU: Lightning Talk: Faster Than SOTA Kernels in Torch.compile With Subgraph Fusions and Custom Op Autotuning - Elias Ellison & Paul Zhang, Meta, 15:40 - 15:50 #PyTorch #torchcompile #OpenSourceAI #PyTorchCon

THIS AI TOOL TURNS SCREEN RECORDINGS INTO APPLE-LIKE VIDEOS someone spent 3 weeks building a tool finally shipped it. opened loom. hit record. sent the demo out nobody watched it turns out boring screen recordings don't sell your product dropped it into https://t.co/zeL64H5mnP instead 3d device mockups...ai camera follow.. animated text...synced music looked like apple made the demo...took 20 minutes free. 4k export. no signup needed

@ClimStefan I built a better way to keep up with the AI community here on X: https://t.co/kiuZ7QXLzb

怎么这玩意又突然火了？？？说实话我就没用过几次 OpenClaw，太垃圾了，又慢又丑的。自从 Hermes 出现就一直用，团队有品位，功能更强大。以防你不知道，这还有个 Web UI 可以用。 https://t.co/SMso6w4h53 https://t.co/1ByVDBCsJZ

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怎么这玩意又突然火了？？？说实话我就没用过几次 OpenClaw，太垃圾了，又慢又丑的。自从 Hermes 出现就一直用，团队有品位，功能更强大。以防你不知道，这还有个 Web UI 可以用。 https://t.co/SMso6w4h53 https://t.co/1ByVDBCsJZ

Lysandre Debut, Chief Open-Source Officer, @huggingface speaks about The Hub as Infrastructure: From Open PyTorch Models, to a Safe and Performant Distribution Hub at #PyTorchCon Europe https://t.co/iAAkwHg0WG

As AI moves from frontier labs into mainstream production, the operational challenges start to look increasingly cloud native: orchestration, autoscaling, routing, security, policy, and observability. @jbryce, Executive Director, Cloud and Infrastructure, @linuxfoundation @CloudNativeFdn explores why the next phase of AI adoption will move faster if PyTorch and cloud native communities work together to extend proven open source patterns during #PyTorchCon EU keynote

I met with the founders of https://t.co/VDKFa8U1Su today. Building an AI scientist. About to launch something new that is beating all the evaluations. Their AI is next level. Evolves faster than competition that got a lot more money. Has a better memory. And it is turning the humans who have it into superhumans in their corporations. It is helping scientists around the world discover new materials and come up with new drugs. I kept up because the one I am using to build https://t.co/8L5xphk0qQ is the same. Superior. And evolving the same. Built by a 21-year-old genius. Building with AI has made me a better interviewer. There are tiny startups out there that are beating the big labs. I am so hopeful for the future because of them.

At #PyTorchCon Europe, @tms_jr Chief Architect - Inference Engineering at @RedHat presents the latest updates on @vllm_project https://t.co/6ArfMfNI0Q

At #PyTorchCon EU Artur Niederfahrenhorst, Member of Technical Staff at @anyscalecompute presents the latest updates on @raydistributed https://t.co/ijxtiel9Qw