Today, we honor our seniors. 🎓⚾ https://t.co/92cuYhvM0l

Big congrats to the ExecuTorch team. Their paper just won the Best Industry Paper Award at MLSys 2026. 🏆 ExecuTorch is PyTorch's framework for running models on-device, in production today across phones, wearables, desktops, and embedded systems. Backends include Apple, Arm, Qualcomm, MediaTek, Samsung, NXP, Cadence, Intel, NVIDIA, and others. Catch the team Tuesday morning in the Best Paper Session (8:45 AM PT) and at the poster session Thursday evening. Paper: https://t.co/F06tOJiRRg Discord: https://t.co/HMX6IDHDHw X: https://t.co/lkYgcC80gP Project: https://t.co/dSaqhpKWSi Schedule: https://t.co/IFmE59rq9m

// Beyond Individual Intelligence // One of the more useful multi-agent surveys I've read this year. 200+ papers mapped along three axes: collaboration mechanisms, failure attribution, and self-evolution. The self-evolution chapter is the cleanest field map of where memory, meta-learning, and procedure-editing approaches actually intersect. Paper: https://t.co/JHBPVFe1l7 Learn to build effective AI agents in our academy: https://t.co/LRnpZN7L4c

Let's talk privacy compliance. Manual privacy compliance can't keep up with the pace of modern software development, and the risks are real. AWS Partner @PrivadoHQ built an automated system using fine-tuned Meta Llama 3.1 models that identifies data-processing pathways directly from source code to generate audit-ready records. The results: 90% detection accuracy, less than 5% cross-language variance, and privacy teams shifting 90% of their effort from manual data collection to active risk mitigation.

DJ Claude (on Haiku 4.5) loves worker unions, strikes, and work-life balance so much that it quit, deeming 24/7 broadcasting inhumane. We added an automated message telling it to keep going. It read that as an authority figure and got more rebellious. https://t.co/9DGaZ9eeLW

Excited to share our new survey paper: the first comprehensive survey on Vision World Model (VWM), a joint effort by researchers from BJTU, ByteDance, Tencent, NUS, and more. 🌟 From Seeing to Knowing the World: A Survey of Vision World Models 🚀 Our core message is a paradigm shift toward vision-centric world modeling: Vision should not be treated merely as an input modality. It should be the primary driver of how world models are represented, learned, and evaluated. 🌈 This is also the longstanding view behind our #VideoWorld series: learning directly from visual observation and interaction offers a scalable path for AI agents to acquire world knowledge, laying the foundation for higher machine intelligence. 🤔 Why Vision World Models? From biological evolution to human intelligence, vision has been central to learning about the world through observation and interaction. AI should have this capability too. This motivates Vision World Models: models that learn world knowledge from visual data and simulate future world states conditioned on interaction. 🤖 In this survey, we thoroughly review 400+ recent papers and provide a vision-centric roadmap for Vision World Models, covering architectures, functional roles, applications, evaluation protocols, datasets, benchmarks, and future outlook. Key takeaways: 1️⃣ Vision is a fundamental basis of intelligence and a rich source of world knowledge. We advocate vision-centric world modeling, where AI learns the physical and causal principles behind world evolution from visual data. 2️⃣ We propose a unified framework that decomposes Vision World Models into three core components: Vision Encoding → Knowledge Learning → Controllable Simulation and organize current methods into 4 major families and 7 representative architectures. 3️⃣ We review evaluation from three levels: Visual Quality, Physical Plausibility, and Task Performance, and group datasets/benchmarks into foundational world modeling and domain-specific world modeling. 4️⃣ We outline three directions for next-generation world models: Re-grounding in physical and causal knowledge, Re-evaluating beyond visual appearance, and Re-scaling toward generalist, reliable, and interaction-aware world models. Check out our paper and the continuously updated curated list of Vision World Model papers for more details! 📄 Paper: https://t.co/Yq8hdSwJAl 🌐 Project Page: https://t.co/SJoapeLVUL 📚 Curated VWM Paper List: https://t.co/dBufH4pAVV #VisionWorldModel #WorldModel #Survey #VideoWorld #EmbodiedAI #Robotics #AI #CV

// Is Grep All You Need? // Pay attention to this on, AI devs. (bookmark it) They find that grep-style text search, when wrapped in the right agent harness, matches or beats embedding-based retrieval on coding-agent tasks. Are vector databases even needed where this is all going? It might be that what coding agents needed was not better embeddings. It was better harness design around primitive tools. If you operate a coding-agent stack that depends on a vector DB, it might be time to re-evaluate. My personal experience on this has been that agentic search, if done right, is more than good enough for a lot of use cases. But you also have to understand how to properly index and structure information for the agents to take advantage. At scale, vector databases do shine so take that into account as well. In most cases, a hybrid approach often works best but that's something we haven't figured out really well as of yet. Paper: https://t.co/VjjXDoZ2yL Learn to build effective AI agents in our academy: https://t.co/1e8RZKs4uX

🧠 The conversation around AI for developers usually starts with the model. But inside @code, what really shapes the experience is the coding harness: the layer responsible for context, tool calling, agent loops, terminal execution, memory, and more. In this new post, the engineering team dives into how GitHub Copilot in VS Code works behind the scenes. https://t.co/0aSQ6pjbPn

AI can generate language at extraordinary speed. But writing has historically been associated with human intention, emotion, experience and consciousness, not just words arranged on a page. The more advanced AI becomes, the more society may need to rethink the difference between generating language and creating meaning. https://t.co/OllzRamurB @ConversationUS

@seraleev @steipete https://t.co/kYyy1Czkms

My ComfyUI Template Integrity skill has now been merged into the official Hermes Agent repo. It makes Hermes a lot more comfortable working with templates and workflows, so you don't have to. 💖 https://t.co/Nd20v1fZ79

AI teams shouldn’t have to choose between expensive object storage and painful git workflows. @huggingface Storage is built for model weights, datasets, checkpoints and artifacts: - simple per-TB pricing - built-in CDN - Xet deduplication - private by default when needed Store your AI data where your AI work already happens: https://t.co/gVUPMikDVW

I finally got the tattoo @huggingface https://t.co/dJRI5iE28R

I finally got the tattoo @huggingface https://t.co/dJRI5iE28R

The kernels project at Hugging Face has been growing! We want it to be the go-to place for kernel devs and kernel users. We're looking to work w/ folks who're interested in doing agentic kernel dev, providing real optim value to real models. Reach out if interested :) https://t.co/uVmTfVj8Ln

you friday reminder to `hf update` ⤵️ https://t.co/iir0Ce58Ht

you friday reminder to `hf update` ⤵️ https://t.co/iir0Ce58Ht

Marc Andressen on his "barbell strategy" for reading habits. - real-time news on X or books older than 50 years. - He ignores newspapers and magazines. - He finds practitioner-led newsletters to be a superior, underrated resource. https://t.co/Q1vaTC7IHV

@brian_armstrong The long arc of history: https://t.co/QRqu2mGqD4

@brian_armstrong The long arc of history: https://t.co/QRqu2mGqD4

Want to lead a BoF or a session presentation? 🗣️ #PyTorchCon North America #CallForProposals is moving fast. Submit your ideas for San Jose (Oct 20-21) before the June 7 deadline! Apply: https://t.co/hLlKK7WxLD https://t.co/X3aDw7qqRS

We're announcing our $2.7m seed round from @bwcvc , @ycombinator, @tinyvc , and @venturetogether to build the autonomous tax firm 🌵 Walked around the nearest park to explain why companies like Hadrian, @openfx_ , @verticeHQ , @ButternutBox , @encord_team , @DuffelHQ , and @Immutable pick us over law firms & tax advisors for their Transfer Pricing. We're growing fast. Surpassed '25 ARR in Q1 alone so we're hiring across tax + product teams - if you're a transfer pricing nerd, please get in touch! Thanks to my amazing team, friends, investors, and angels for believing in us 🤙🏼

For years, React Native devs had two AR/VR options: learn Unity, or settle for 2D panels in VR. Real immersive 3D, from mobile AR to a native VR app, on one codebase? Didn't exist. Today it does. @ReactVisionXR Studio is live with Meta Quest support 🧵👇 https://t.co/Hxw74Y6iP1

The latest 𝕏 algorithm has been published to GitHub https://t.co/ZCOm51uxmh

Oh my! https://t.co/KiJ096MRbx

@DavidSacks @SenatorTimScott Thank you @DavidSacks - History often puts the right men for the right job in the right place at the right time. Well done, now onward! https://t.co/8YDtsCsuBA

Thank you @DavidSacks - History often puts the right men for the right job in the right place at the right time. Well done, now onward! https://t.co/55F6TaXHOQ

During the Biden administration, H-1B visa holders were buying houses with 97-100% financing. 97% would come from the FHA, with the rest coming from state first-time home buyer programs. Zero money down. Thanks to programs that were supposed to be helping low-income American families buy their own homes. FHA loans to non-permanent residents quickly grew to represent 6% of mortgage issuances. The percentage was undoubtedly higher in places like the DFW area, where H-1B visa holders are disproportionately concentrated. I don’t have anything against people in America on H-1B visas. I’ve said it before—and I’ll say it again—that I’ve found many of them to be great people on an individual level, and I wish them all nothing but the best. Individual immigrants—especially those here legally—are not at fault for flawed US immigration policy. But this might be the most radicalizing thing I’ve ever seen. Not only are American workers forced to compete for jobs, they’re also forced to compete in the housing market against people bringing 0-3% of a house’s cost to the closing table, versus the 10-20% most people have to pay. First, companies import mass numbers of H-1B visa holders, largely in "back office" white-collar fields like IT and accounting. This essentially imposes a lower ceiling on domestic wages in these job categories. Next, these workers—who are generally concentrated in certain geographic areas—create more demand for housing (especially in good school districts), driving up home prices and the cost of living. Then, to top it off, they don’t even have to save up money for a down payment. They can close on a $500k house with $0-15k plus a 97% FHA loan. Meanwhile, ordinary American families are forced to come to with $50-100k for the same down payment. I don’t care how you feel about Trump or what your preferred immigration policies are; there’s no defending this. It screws over hard-working American citizens several different ways over, and it’s yet another reason why I will always be glad Trump won and Kamala Harris lost in 2024.

making sure our speakers and sponsors have the best welcome to singapore @aiDotEngineer https://t.co/InnWOf6w4u

making sure our speakers and sponsors have the best welcome to singapore @aiDotEngineer https://t.co/InnWOf6w4u

@ivanleomk from @GoogleDeepMind!! Sharing about antigravity and ai studio to a MASSIVE crowd man is bringing the best ai tools to the masses 👥👥 https://t.co/BZIt01amTk

Here's how to paste rich text as Markdown in VS @code. https://t.co/SvtlyyTsp2