FSD v14.3.1 review after 10 drives and many hours, here are my thoughts (it’s a great one) - v14.3.1 feels like a big jump even compared to FSD v14.3, even for “just” a point release build. Everything’s polished and smoother overall as expected. - Always after a big update or fundamental architecture changes, there will be a couple rough edges. I was very impressed with how solid FSD v14.3 was, and .1 added a lot of polish to it. - First big thing I noticed with this build was improved lane bias and preference changes. Notably, v14.3 would like to sit toward the left lane on emptier highways, in my driving tonight I didn’t see any of that. Will drive a lot more tomorrow to verify. - In FSD v14.3, a new feature introduced was a new P parking icon at your destination. At first with v14.3, it didn’t show for me, then it did majority of the time. With v14.3.1, it has shown every single time now. Something new in .1 is you can now select it and change the arrival type from parking lot to garage, street parking, curbside etc. Nice improvement and quick to change. - As with v14.3, stop sign behavior is MUCH improved. It commits and doesn’t hesitate, no double stops I’ve seen and a smoother acceleration and deceleration curve, leading to a more comfortable drive. Notably, speed bumps and dip handling is also buttery smooth, great acceleration/deceleration curve as well. - Gated parking lots. One thing I noticed today with gated lots and garages is that it pulls up to the ticket dispenser way quicker and in a better position than before. It’s close and centered, exactly where I’d pull up. Goes right away when gate opens too, 10/10 no notes. Parking- This is a big change with FSD v14.3+. It now picks parking spots quicker and more decisive. With v14.3.1 it’s even better, it’s picking the first spot it sees and commits, and sometimes they are even corner spots which I personally love to avoid door dings. I saw a ton of corner spot parking today which is awesome. When it’s parking, it’s so quick to decide which spot to take, but sometimes once it starts pulling in the spot it’s a bit slow to finish the maneuver as well as a bit slow in parking lots sometimes now, the final 5 feet of the maneuver are the slowest understandably. I saw an instance of the twitchy steering wheel as well. Spot selection is so improved it’s hard to even compare to v14.2.x. What a massive upgrade and the decision making is so fast and confident. - Speed control was great on my drives tonight, mostly city but was behaving exactly how I would and expect of it now. Went perfectly with flow of traffic on the profiles I selected. Hurry mode is dialed in, and doesn’t sit in left lane, at least on the drives I did. - So cool to have Grok integrated with navigation. Tesla Self Driving and Grok took me to 5 separate destinations earlier with ZERO input, I just pressed start FSD and it drove, parked, unparked and got me to each destination without any intervention. Definitely worth watching the video I posted earlier of it. - Decision making and reaction times are next level as well, it reacted to multiple bad human drivers we encountered tonight extremely well and the reaction time is lightning fast. Will post some videos tomorrow of it reacting to other vehicles, its reasoning is fantastic. Overall, what a big polish upgrade to an already excellent build. Really excited to drive it more extensively tomorrow. Thank you to the legends @Tesla_AI for the hard work getting another fantastic build out to us, this one’s phenomenal.

We shipped a new repo type called "kernel" on the Hub. We want to democratize the whole ping-pong around packaging, distributing, and using custom kernels. This repo type is only available to a few community partners, @sgl_project being the first! Hop in 🧵for more details. https://t.co/8yiWzDbBPY

@norpadon The tensor engine was first implemented inside SN3 (before it was called Lush) in 1992 at Bell Labs by Léon Bottom and me. The naming convention has survived to this day in PyTorch and other libraries. The naming of the tensor operations was reused in EBlearn (C++ deep learning library written by Pierre Sermanet and me, with some help from @soumithchintala). It was recycled in Torch5 and Torch7, which was written largely by Ronan Collobert, and my students Clément Farabet, and @koraykv ). Clément and Koray had been brought up on Lush (the open version of SN) and knew the nomenclature. Then, Soumith used the same conventions in PyTorch.

The Hermes Agent is a truly impressive piece of engineering. I dissected its memory architecture and it's definitely better than mine 😅 Amazing work @Teknium and @NousResearch team. When on Lex Fridman podcast? It's about time. https://t.co/tNdFiMZs4F

🎉 After one year of teamwork, we are excited to release our 3D foundation model — LingBot-Map! Unlike DA3/VGGT, LingBot-Map is a purely autoregressive model for streaming 3D reconstruction ⚡ It achieves ~20 FPS on 518×378 resolution over sequences exceeding 10,000 frames — and beyond 🚀 Two key insights behind LingBot-Map: 🔑 Keep SLAM's structural wisdom: build Geometric Context Attention with long-context modeling while maintaining a compact streaming state 🔑 Make everything end-to-end learnable — no optimization, no post-processing Let's check out our demos 👇

People of pi. The great @steipete has graced our repository with a bespoke slop PR to fix cache affinity in the OpenAI Responses provider, which should lead to better prompt caching. And the new "pi contribution model (tm)" is now live. Here's how it works: - If you send a PR, it gets autoclosed, unless you've previously been approved by a maintainer. - If you send an issue, it gets autoclosed, unless you've previously been approved by a maintainer. All auto-closed issues are triaged daily. - Issues that follow CONTRIBUTING.md and are worthwhile will be reopened. - Issues that are exceptionally well written get an "lgtmi" comment from me or @mitsuhiko, which will approve all your future issues automatically. No more auto-closing. - Issues that are well written AND offer a PR get an "lgtm" comment from me or @mitsuhiko, which will approve all your future issues and PRs automatically. No more auto-closing. I, the idiot who has to go through all the closed slop daily, mark the last issue I processed with the "last read" label. If your issue is below that and hasn't been opened, then it did not meet the quality standard. You may or may not receive a reply on why the issue was not opened, depending on my time and mood. Accounts that: - Let their agents slop a book into the issue tracker repeatedly - Otherwise behave badly will get their account blocked across all my repositories. no exceptions. not takesies backsies. I get anywhere between 30-50 issues per day. Most of them are agent garbage. This is the only way to keep me sane and ensure the issue and PR trackers have actual good signal.

I built a physical notification device to prevent the tragedy of GitHub Copilot getting stuck waiting for user input, hidden behind dozens of windows! When it detects the "waiting for input" state, this little guy starts shaking its head and looking around for you... 3D models + firmware + step-by-step build guide here: https://t.co/tM7N0xzBOY

okok we officially have GLM 5.1 running on a 256gb mac studio with hermes agent next is linking it to hermes to see how good it is 🗣️ https://t.co/BQTlLiL3jm

Transformers.js v4.1 is out 🎉 Something that has literally never run in a browser before is now possible. One line of code. Can you guess what it is? 👇 (hint: think small 🤏) https://t.co/W4z5lQaoHB

trying to figure out which open model to run with my pi agent https://t.co/AAJEgNc9NW