Vignesh retweetledi
Vignesh
337 posts
Vignesh retweetledi
We're building physical AI for every moving machine.
🎧 Tune into the full @latentspacepod episode: youtube.com/watch?v=rv23_K…
YouTube
English
Vignesh retweetledi
Vignesh retweetledi
Amazing V14.3.4 clip that @jtesla47 just sent me and asked me to share from his M3P.
What I love most about this clip is that FSD understands what needs to happen and reacts BEFORE the lead car even throws it in reverse. This is such a critical indicator that FSD isn’t just reacting to objects in its path, but actually understands what happens next before it even needs to start backing up to clear the dodge ram.
This is one of my favorite edge cases in a minute.
FSD IS THE TRUTH
English
Vignesh retweetledi
本日、Applied Intuitionの自動運転システムが正式に日本へ上陸しました。日本の自動車業界は、サプライヤーに対して独自の基準を課しています。
私たちは長年にわたり、日本に拠点を持つチーム、日本でのデータインフラ、日本の企業とのパートナーシップを構築し、その基準を満たす準備を進めてきました。
自動運転を世界中でスケーラブルにするためのこの重要な一歩について、詳しくはこちら：appliedintuition.com/ja/blog/applie…
Today, Applied Intuition's Self-Driving System officially comes to Japan.
The Japanese automotive industry holds its suppliers to a different standard.
We've been building to meet it for years: local teams, local data infrastructure, local partnerships.
Learn more about this important step toward making autonomy scalable worldwide: appliedintuition.com/blog/applied-i…
日本語
Vignesh retweetledi
Upcoming releases of FSD will remember your parking preferences, so that the car goes to the right location at your home, office, school drop off, etc.
Destination parking is by far the biggest reason people now intervene with FSD. Critical safety interventions are extremely rare.
English
Some good stuff here. Pure vla doesn’t fit autonomy.
Fred Lambert@FredLambert
I had a fun interview with Dr. Xianming Liu, head of AI at @XPENG_Global, to gain some insights into the company's progress toward autonomous driving and physical AI. It's impressive what they have been able to do in a short period of time. VLA 2.0 is now roughly at parity with Tesla FSD.
English
Congrats on CVPR 2026 Best Paper 🏆 Amazing to see this on the humble single encoder transformer architecture. Super smart to avoid per frame decoding.
Chuhan Zhang@ChuhanZhang5
A SINGLE encoder + decoder for all the 4D tasks! We release 🎯 D4RT (Dynamic 4D Reconstruction and Tracking). 📍 A simple, unified interface for 3D tracking, depth, and pose 🌟 SOTA results on 4D reconstruction & tracking 🚀 Up to 100x faster pose estimation than prior works
English
Vignesh retweetledi
This is absolutely stunning. With FSD, your attention is freed from the steering wheel, giving you more time to enjoy the journey and the beauty around you.
@Tesla @Tesla_AI @elonmusk @aelluswamy @elonmusk @edgecase411 @wholemars #FSD
English
Vignesh retweetledi
.@aelluswamy will discuss our approach to foundation models for robotics at CVPR today
Room 603, 3:30pm local time
Covering architecture, large-scale multimodal training, end-to-end control, safety & deployment
Come swing by booth 255 for live demos after!
English
Vignesh retweetledi
You were all asking to not intervene @Tesla FSD when it gets into a pickle. Well, here you have an example where FSD encounters a van on a very narrow🇳🇱road and it squeezes itself in the tiniest gap with only centimetres to spare on each side! 😱 This one definitely puckered up our buttholes 😂 @pvandamcom @teslaeurope @TeslaOwnersNL @SawyerMerritt @wholemars @KRoelandschap #FSDEurope
English
Vignesh retweetledi
Here’s a long standing pet peeve of mine for FSD: waiting until all lanes are clear to make the left… this even has a purposeful merge lane.
English
Vignesh retweetledi
Soon it’ll be driving itself in to Austin city, reporting for duty!
Elon Musk@elonmusk
Cybercab driving itself out of the GigaTexas factory
English
Vignesh retweetledi
Recently met @srush_nlp and he started giving me an impromptu lecture on how targeted on-policy self-distillation works.
I asked him if I could record it on my iPhone.
The basic idea is this: if the model made a mistake at some point in the rollout (for example, calling a tool that doesn't exist), we want to discourage this specific error, but we don't want to just learn from the final reward, because it's a very noisy signal spread out over the whole trajectory.
So we have another model read this trajectory and figure where the error was made. It simply inserts some hint tokens to the part of the trajectory right above where the mistake was made.
Now with these injected hint tokens, have the model run a forward pass. You're not having to regenerate a new rollout - aka no new decode required.
The hint causes the model to assign lower probabilities to the error tokens. You then trains the original model to match these new probabilities, teaching it to downweight that specific mistake.
English
Vignesh retweetledi
You don't imagine the future by mentally rendering a movie. You trace how things move -- abstractly, sparsely, step by step.
We built a model that does exactly this. It predicts motion, not pixels -- and it's 3,000× faster than video world models.
Myriad, accepted at @CVPR 2026
English
Good safety value! Pre-crash detection from active safety is already there in other cars. So why aren’t others doing it?
Tesla@Tesla
Tesla Vision allows us to deploy airbags up to 70 milliseconds earlier if your Tesla detects an unavoidable collision This can be the difference between serious injury & walking away from a crash
English
Vignesh retweetledi
Vignesh retweetledi
The past year has been the happiest period of my life.
Genesis is a place of miracles.
We set countless ambitious goals.
None of them seemed possible with existing technology.
One by one, we made them real.
The density of breakthroughs coming from such a small team, across so many directions at once, feels almost rare in human history.
What you see here is fully autonomous, 1x speed, run on the exact same model.
Genesis AI@gs_ai_
We are back. After one year of quiet building. Introducing GENE-26.5, our first robotic brain that takes a major step toward human-level capability. For years, robotics has struggled to learn from the world’s largest and valuable data source: Humans. Solving it means rethinking the whole stack from the ground up: - A robotics-native foundation model. - A 1:1 human-like robotic hand. - A noninvasive data collection glove for motion, force, and touch. - A simulator that turns weeks of experiments into minutes. GENE-26.5 is trained across language, vision, proprioception, tactile, and action. We designed a set of tasks to test how far we can go with this new paradigm. Fully autonomous, 1x speed, one model, same weights. (Enjoy with sound on) We are approaching the endgame for robotics. And this is just a beginning.
English
Vignesh retweetledi
Nuro co-founder and co-CEO @zhujiajun recently completed his Autonomous Vehicle Operator (AVO) training, learning directly from the team that manages our engineering fleet day-to-day. Watch his first session!
AVOs play a huge role at Nuro, helping train and test the Nuro Driver while supporting safety in complex road environments. If you love driving and are excited by cutting-edge tech, we’re hiring! nuro.ai/careers
#autonomousvehicles #selfdriving #drivenbynuro
English
Vignesh retweetledi
I was shocked to learn that Tesla hasn't even applied for either the DMV driverless testing permit or the CPUC autonomous vehicle permit in California. Not denied — never applied. They operate under a limo/TCP permit and call it a 'Robotaxi.' Meanwhile Nuro just secured both. The contrast is stark.
$LCID $UBER $NURO
Nuro@nuro
CA permits secured! We’re excited to share that Nuro has received two key regulatory approvals for the next phase of our robotaxi program with @Uber and @LucidMotors: A @CA_DMV driverless permit to expand public-road validation without safety drivers, and a @californiapuc permit to begin carrying passengers in a regulated pilot. Learn more: nuro.ai/blog/nuro-secu… #selfdriving #autonomousvehicles #drivenbynuro
English