@maxxx___w https://t.co/WjOuJgtVIn

@romi_hoshino https://t.co/WjOuJgtVIn

@hex6u https://t.co/WjOuJgtVIn

NVIDIA's (@nvidia) Anjulie Agrusa, Ryan Spring, and Bruce Zitelli will show how the latest NVFP4 pretraining recipes can accelerate large-scale LLM training while closing the quality gap to BF16 at PyTorch Conference North America 2026. Their October 21 session, “Efficient Pretraining of LLMs in NVFP4,” will cover the recipe and PyTorch tooling that make this possible, including recipe design, kernel choices, and the API surface needed to bring NVFP4 training into native PyTorch workflows. The recipes are being upstreamed into the PyTorch ecosystem through TorchAO and TorchTitan, with dense linear NVFP4 training available in TorchAO today. Register by September 4 to save on your conference pass. 🔗 Register: https://t.co/GIZUAha5wA #PyTorchCon

⚙️ Performance starts here. The Kernel Engineering Track at #PyTorchCon North America (Oct 20-21 in San Jose) explores compilers, custom kernels, optimization, and the low-level technologies that make AI run faster. Learn more: https://t.co/rg8DxFJpyv 📅 Full Schedule: https://t.co/Bh6SgicfzA 🎟️ Join us! https://t.co/1z0jDhdUZm

It's fun posting about evals b/c I can reply like this to bots https://t.co/RcVSXBk9hg

This also got me thinking about this tweet from @karpathy a few months back. Not entirely interactive neural videos/simulation but I think somewhere between 3 and n (much closer to n). https://t.co/Yu1mSflOjE

GitHub wants to learn about the tools, product settings, and personal adaptations developers use to do their best work. You don't need to identify as someone with disabilities or already consider yourself an accessibility-tool user to participate. Submit your response by September 30 ⬇️ https://t.co/qtQvUWJZ9t

My friend Puffie created this whole cinematic universe where all of our friends have a unique character. Anyways, he’s playing Portola with SG Lewis and you should come. https://t.co/EXCjch7yCW

Oh yea, and also reduced default context used by ~50%! https://t.co/7kqzMYVyf4

@Scholars_Stage https://t.co/eZ6wdBTGvE

@polymarketjapan https://t.co/aoCdx2PU5L

@MaxForAI @albertwenger https://t.co/zmTCUT1KUS

Sequoia partner Doug Leone reveals he got a root canal with no Novocaine to see if he was really a badass "I had to get a root canal. And I had to go to a meeting right after that. I told the dentist, drill without any Novocaine.” “My whole life, I wanted to see if I was a badass or not. Am I a fake badass that has this envelope nobody could tell, or am I really a badass on the inside?" "He drilled and I jumped. And I told the dentist, I won't move again. And I didn't move again. I used the trick of thinking what it must be like to go to war and lose an arm or two legs. That's pain with consequences. Mine was pain with no consequences." “It’s just nerve endings from there to my brain to my spine, f*ck it I’m not moving.” "I had to go home and change my shirt because I was a puddle of sweat. But I didn't move. And so I love fear. It does wonders for me."

Drug development generates mountains of critical knowledge, but most of it stays trapped in PDFs and spreadsheets. Startup QbDVision is helping pharma and biotech businesses move beyond disconnected documents with AI-powered workflows built on AWS. Their platform structures CMC data into a connected foundation, then delivers credible, auditable answers in seconds. Teams spend less time searching and more time developing medicines.

Made in Boston with AWS: Lior Div, Founder & CEO of 7AI. Startup 7AI builds autonomous AI agents that investigate and action cybersecurity alerts. Learn how its collaboration with AWS goes beyond infrastructure to enable long-term growth and why it sees Boston’s startup culture as ‘second to none.’

I just used instinct and stripe link to buy my niece a hot pink piano… entirely from the messaging interface 🤯🤯 Instinct was even kind enough to find me a 15% off discount!!!! https://t.co/yP7Dl7p3fO

@KUMAN_R https://t.co/6y8KYuaIau

@gigazine https://t.co/WjOuJgtVIn

@MrTacticalX https://t.co/WjOuJgtVIn

@thsottiaux https://t.co/WjOuJgtVIn

@shiri_shh https://t.co/WjOuJgtVIn

@PratikSinhatwt https://t.co/I3ejAgCgY4

Hey, Fable: "create the worlds most annoying CAPTCHA" "Okay, here is a 14 stage CAPTCHA plus ambient harassment" It is actually quite funny and entirely "winneable" without real frustration. Is this alignment? Play: https://t.co/Ro1f98yC7q https://t.co/ULSCd1zPZ8

Today we're releasing TimesFM 3.0 on Hugging Face - Open foundation model for time series forecasting - Complex multivariate scenarios with zero-shot - 330m parameters Excited about the research and new use cases this will unlock! https://t.co/0q5oRbV2Mw

Introducing TimesFM-3, a state-of-the-art time series foundation model that enables accurate multivariate time series forecasting in a single forward pass, significantly outperforming other forecasting models across major benchmarks. More on the blog →https://t.co/uSlnIdUJ4Q https://t.co/NfbONpFYDz

Today, we're sharing new research on Solaris, our first Interface World Model. Solaris is a new kind of operating system that generates interactive interfaces frame by frame, in real time, with no code. We find that Solaris outperforms frontier LLMs when generating new interfaces, across structural similarity and information retention. Read more and request early access at the link below.

We just killed…everything. Introducing Monid, the OpenRouter for agent tools. Today we crossed 4M agent transactions. And raised a $2.1M pre-seed to kill every subscription in the world. Your agents can now: > discover, run, and pay for tools at runtime > one connection to 1,800 APIs: SEO, leads, search, ecommerce, stocks, video/image/music/3D gen, private company data > all pay per call, 0 subscriptions

Interesting paper from Tencent. Tencent trains an agent to manage its own working context, and assigns credit at the level of individual context edits. Long-horizon tasks force a model to retrieve, integrate and maintain scattered information across many turns, and keeping every interaction history makes the working context grow without bound. Recent proactive methods let a model edit its own context with tools, but the toolset stops at search, deletion and summarization. ContextPilot adds global planning, long-term memory and adaptive soft compression, so the agent can offload information rather than only discard it. The training side is where it gets interesting. Standard RL hands the final trajectory reward to every intermediate edit equally. ContextPilot uses context and entropy variation to find which editing decisions actually mattered, samples branches at those points, and estimates action-level advantages from all branched trajectories passing through that edit. On long-context QA and deep search it beats existing baselines across several base models while holding a more compact working context. Code is available. Paper: https://t.co/buM6galu4x Chat with Paper: https://t.co/VN5J5PO4Rt

Loop engineering has emerged as a new skill for AI engineers But there is very little research measuring how effective it is. The best results on full tasks in a new benchmark is ~25%. LoopArena from AMAP evaluates the outer loop rather than the coding agent. A Controller model receives a structured summary after each round and instructs a separate fixed Worker agent on what to do or verify next, or decides to stop. Holding the Worker constant makes the result readable, since an end-to-end run cannot tell you whether success came from the guidance or from the agent carrying it out. The named failure modes will be familiar to anyone running long agent sessions: - Trusting a stale progress note - Skipping needed verification - Spending budget in the wrong direction - Stopping before the task is safe to submit Paper: https://t.co/ZGiooDsN34 Chat with Paper: https://t.co/jSeFFp3CBc

Made a Microduck sticker pack because apparently owning the robot wasn’t enough. Thoughts? https://t.co/CNJpSPggnn

Made a Microduck sticker pack because apparently owning the robot wasn’t enough. Thoughts? https://t.co/CNJpSPggnn