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Helion is a PyTorch-native hardware agnostic kernel DSL designed for writing high-performance kernels using a tile-programming model. In our latest blog post, Sean Chen (@RedHat) and Yanan Cao (PyTorch, @Meta) explored integrating Helion kernels with @vllm_project and evaluated their performance across a range of LLM inference workloads, showing impressive performance speedups thanks to Helionโs Ahead-of-Time autotuning and fine-grained runtime dispatching. Letโs dive into kernel fusion, framework design, and end-to-end benchmarking, showing how Helion can be easily integrated into vLLM and bring significant benefits. Read the full technical deep dive ๐ https://t.co/15zXb5Y3Kg
Submit your poster proposal for #PyTorchCon North America! Share your latest #AI, ML, #PyTorch, tooling, infrastructure, or research work with the community October 20-21 in San Jose, CA. ๐๏ธ Poster #CFP closes July 26: https://t.co/M7WmgnmuKJ https://t.co/Ozs2HtTFGs
Enable smarter, longer-thinking agents Scale agentic AI and reinforcement learning by shortening CPU execution time, increasing task throughput, and improving overall AI factory output. The @nvidia custom Olympus core in the NVIDIA Vera CPU uses a neural branch predictor to reduce stalls in branch-heavy code. Combined with other prediction mechanisms, it can sustain two taken branches per cycle with zero penalty, maintaining throughput for deep software stacks such as PyTorch, graph workloads, and scripting engines. Read the complete blog post: https://t.co/L6NmBJWgDY
๐งฑ DiffusionBlocks: Training Neural Networks One Block at a Time https://t.co/zw7kehHDYc
ไปๅค22:00ๆพ้ ใใฌใๆฑไบฌWBS (@wbs_tvtokyo) ็ต็ฃ็ใฎAI้็บๆฏๆดใใญใธใงใฏใใGENIACใๆกๆใซใคใใฆใๅๆใๅใใพใใใๅผ็คพCEOใฎDavid Ha (@hardmaru) ใจResearch Scientistใฎ่ ๆฒผใใ็งใใกใฎๆฆ็ฅใๆฅๆฌ็บใฎAIใไธ็ใๅคใใๅฏ่ฝๆงใซใคใใฆ่ชใใพใใใใฒใ่ฆงใใ ใใ๏ผ
Building AI that Builds AI: Introducing the Sakana AI RSI Lab ๐ https://t.co/AskX3J5oEJ Today, we are announcing the Sakana AI Recursive Self-Improvement (RSI) Lab: a dedicated research group in Tokyo tasked with redesigning the AI development process itself using AI. While the industry increasingly speculates about the theoretical potential of self-improving AI, weโve spent the last two years actively laying the foundations to make it a reality: โช LLMยฒ: AI models automating research to invent better preference optimization algorithms. โช Darwin Gรถdel Machine: Agents autonomously rewriting their own codebase to double software-engineering performance. โช ShinkaEvolve: Hyper-sample-efficient program evolution that builds novel loss functions for MoE models. โช ALE-Agent: Reinforcement agents outperforming hundreds of human experts via self-learning. โช Digital Red Queen: Open-ended adversarial coevolution laying the groundwork for RSI in cybersecurity. โช The AI Scientist: Towards end-to-end automation of AI research, recently published in Nature. Now, we are unifying these breakthroughs. The Sakana AI RSI Lab is officially tasked with building open-ended, adaptive architectures that collectively self-improve. Human intelligence did not emerge from limitless resources; it was forged through the open-ended, compounding process of evolution operating under strict constraints. We are applying this exact principle to AI. We believe recursive self-improvement is achievable on modest, sample-efficient compute. It shouldnโt be a winner-take-all asset locked inside hyperscale clusters, but a democratized public good. Weโre scaling our team to execute this mission. We are looking for frontier scientists and engineers who are entirely unsatisfied with the brute-force status quo. If you are ready to break away from standard benchmarking and build the self-improving future in Japan, come build with us.
Weโve been laying the foundations for RSI over the last 2 years. Now, I am looking for a select group of distinguished frontier researchers and engineers to join our core RSI team. https://t.co/1eEBgLdQhY If you have a proven track record at the frontier, but find yourself entirely bored with the status quo of brute-force scaling, this is your call.
Member of Technical Staff (RSI Lab) https://t.co/ptU2Xh4aO1 If you are a visionary builder ready to move to Tokyo and engineer the engine of recursive discovery, we invite you to apply. https://t.co/ydKhZQiup8
Not only do we want to train a good model, we want to know it'll be good before we even start training. About a month ago, the Marin team launched a 129B (16B active) 1e23 FLOPs MoE run and preregistered a loss of 2.252. The run finished this past week and landed at 2.234. https://t.co/OptaVa7jIO
This week, @classiclarryd kicked off a 129B (16B active) 1e23 FLOPs MoE run. In typical Marin style, we have fit scaling laws and have made a loss projection of 2.252. Stay tuned. https://t.co/QnwJ8YxT9H
A mic drop moment @ycombinator tonight @sama just offered $2M in OpenAI tokens to EVERY YC startup in the current batch in exchange for equity Just like Yuri Milner offering to invest in every startup back when Sam was a YC partner I can't wait to see what's unlocked when you let the most driven, creative and formidable founders tokenmaxx
Itโs Codex Thursday, and yes, we have updates for you. First up: Appshots, a new way to bring the context of what youโre working on into Codex. On your Mac, press Command-Command to attach your app window to a Codex thread. Codex gets both a screenshot and text from the window, including content beyond whatโs visible onscreen. Appshots are available across plans on Mac, with enterprise access coming soon.
AI should dramatically increase quality of life and individual freedoms for people around the world. The OpenAI Foundation is making an initial $250M commitment to measurement, transition support, and new approaches to broadly shared prosperity. https://t.co/zOD8O94RjQ
It's time to fly. https://t.co/ObUaCZ07EM
The AI race is no longer just about models. It is about energy. Chinaโs wind-powered underwater datacentre shows how the next wave of AI infrastructure may be built around new approaches to power, cooling and efficiency. The winners in AI may not only be the companies with the smartest algorithms, but also those with the most sustainable infrastructure.
https://t.co/IVGHTjLNTf
AI safety is becoming a launch strategy. Anthropicโs release of a Mythos-class model shows how leading AI companies are trying to balance powerful new capabilities with safeguards for high-risk areas. The real test is no longer whether models can do more. It is whether society trusts how they are released.
AI may help find the next football superstar, but it should not define what talent is. Data can make scouting faster and more disciplined, but football still depends on qualities that are hard to measure: instinct, resilience, creativity and the ability to surprise. The risk is not using AI in sport. The risk is believing the spreadsheet sees everything.
https://t.co/QGVSJcNhOB
The AI race is becoming a price war. If OpenAI cuts token prices to compete with Anthropic, lower costs could accelerate enterprise adoption but also pressure margins across the AI stack. The next battle may not be who has the most powerful model. It may be who can deliver intelligence at the lowest sustainable cost.
The future of work will not be human versus AI. The people who thrive will be those who combine human judgment, creativity and trust with AIโs speed, scale and pattern recognition. The real career risk is not being replaced by AI. It is being outpaced by people who know how to use it better.
The next AI race may be won as much in factories as in research labs. Chinaโs dominance in robot supply chains shows that building advanced AI is one challenge. Building millions of intelligent machines at scale is another. In the age of AI and robotics, manufacturing strength is becoming a strategic advantage again.
The AI IPO boom is turning into a capital tsunami. Demand for SpaceX shares suggests investors are no longer asking whether AI will reshape the economy. They are asking how much exposure they can get before the next phase begins. The biggest risk today may not be a lack of capital. It may be finding enough opportunities to deploy it.
@ScottPatterson0 @maticrobots Yeah, I'm so proud it was launched in my home here last year: https://t.co/fEkfcuLxjt We love ours for same reasons. @mehul is one of the best consumer entrepreneurs America has.
The new-fangled vacuum salesman. This is the best example I've seen of how AI and computer vision is changing consumer electronics. Here @maticrobots founder @mehul comes to my home to give me an in-depth demo (the good stuff starts about 30 minutes into the video). This al
โdonโt train your own modelโ is common ai advice. it's wrong. your token bill's the proof. today, weโre excited to launch castform into open preview. castform is the easiest way for you to train your own model, on your own data. open-weights models are performant and much cheaper. when trained on your task & proprietary data, they beat closed models. the thing standing between you and that was weeks of plumbing & years of ml expertise. with castform, model training is as simple as prompt engineering. @castformai bring your agent traces or raw corpora. castform turns it into training data, picks the right algorithmic recipes, manages gpus, and gives you an ide to watch and chat with your model as it learns. see what you can build with castform๐
Meet Coinbase for Agents. Give your agent its own account to: โ Execute trades & manage your portfolio โ Run autonomously under guardrails โ Pay for data & research tools via x402 (coming next week) Agentic finance is here, and it's powered by Coinbase. https://t.co/DK220fko0z
48 hours ago Apple announced its new Personal AI: Siri. Today Onairos announces Persona, the user data api to power all other Personal AIโs with context not even Siri has. https://t.co/ogBCIsM1xc
The next generation of Apple Intelligence powers an entirely new Siri: making the apps and experiences you rely on across iPhone, iPad, Mac, and Apple Vision Pro more personal and helpful than ever. https://t.co/aXiDIkqAKn
San Francisco comes through again. Spent a delightful hour with @khal_ism who is building a new brain computer interface that you will hear a lot about later this year. I wrote eight books about decade-long change coming. My first was about social media before this site were are all on started. If I write another it will be BCIs. Have a list of neuroscientists and builders working in this field. It will be a trend of new things coming over next decade. I already asked @elonmusk for a full neuralink. He said they arenโt ready for regular people yet, but told me โcognitive enhancementsโ are coming in three years. OpenAI, Meta, and others are working on them too. But now I know a lot more about how they work. Thanks X. This morning when I woke up I had no idea who I would meet. Another meeting in a few minutes. Canโt do this in most other places in the world. This morning I wrote that I had the day free, and already an amazing day. Plus the weather is so amazing today. And my other surreptitious meetings today? Entrepreneurs who are changing how we work. Deeply too, more on that soon.
Preview of some slides for this https://t.co/PcKT8T39Ax
Doing this on Thursday. Yes Iโll show you my skills, but more importantly Iโll talk about how you shoukd be VERY skeptical when adopting them (including my skills!) https://t.co/xDwgSTvjLu
Coming up against the same problems over and over? Tried a bunch of experiments to get unstuck but still not where you want to be? This year at Observe @HamelHusain will be hosting two 1-hour Offices Hours to work through challenges in what you're building. Grab your tickets for Observe now and don't miss out on this special session. https://t.co/NYEih97lij
Our evals course is 25% off this week! The next cohort will have completely refreshed material. @sh_reya and I will cover new topics like: using agents for evals (w/o the foot guns), thinking like a data scientist, optimization approaches for harnesses and more. Use this link to apply @lennysan 's special 25% off code: https://t.co/Fy8r7bAAxM
today, weโre excited to announce raindrop 2.0: self-healing agents. we now train custom models that autonomously detect hidden issues with your agent. i could tell you all about it, but wouldnโt you rather hear it from someoneโฆ else? https://t.co/dBGNNr9UNv
https://t.co/8HaeeSSfQL
