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Ankur Deka
@_ankurdeka_
Manipulation & RL @Tesla_Optimus | CMU Robotics | Sharing what I learn about robots and ML | Opinions my own
52 Following    399 Followers
Well said. Tesla is a unique place with concentrated talent, resources and motivation.
Don't sleep on Tesla in humanoids just because they've gone quiet. Tesla bet on solving driving intelligence from vision alone, put a powerful inference computer in every car long before FSD was solved or profitable, and built the biggest robotics data flywheel. General-purpose humanoid needs the same systems, but on steroids. Debate the AI model architectures and actuator designs all you want. They definitely matter for setting the right direction. But what ultimately decides the outcome is the organizational strength that powers every decision. The trifecta: • Engineering: fast iteration, bringing new work in-house, pivoting quickly • Physical ops: manufacturing, data collection, supply chain, repairs, fleet management • Inference and training compute infra at massive scale Few companies can bring all three together at scale as well as Tesla.
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4 generations of autonomous vehicles. In 2019 I was at CMU. 2007 DARPA urban challenge winning car was brought on campus alongside an Argo AI vehicle, which looked more polished. Fast forward, AVs are actually on road. Cybercab looks more polished and advanced than a Waymo.
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Robotaxi 🚀
Cybercabs takes over downtown Austin — Fully Autonomous Fleet Operating 🎥 @AdanGuajardo with @artsimage
Wait until these robots are ubiquitous
OH MY GOODNESS! What are we witnessing right now?
Fast video models can lead to world models that are practical for robotics. Of course there are other issues such as visual artifacts and physics inconsistency that still need to be solved.
Minimax H3 Max has generates video faster than you can watch it so I hooked it to a twitch livestream! Now you can watch infinite interdimensional cable - link to the stream below
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Super impressive. Truly believe that such one shot learning from a single human video is what’ll unlock mass adoption of learnt robot policies in factories. Many interesting extensions are possible. E.g. in context learning instead of gradient steps.
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Introducing GEN-1.5, a one-shot learner. It can learn new tasks in a few seconds. Show it what to do, and it generalizes. This capability emerged from pretraining on physical data at scale, as a step towards our mission of building general intelligence for the physical world.
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This is so cute
You can now book two humanoids for our cleaning service in SF. One humanoid for 60 minutes is $30, two are $60. You can book a cleaning at If you don’t have an invite code yet, join the waitlist. Timelapse at 5× speed (~40 minutes in real time).
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Claude is so incredible at so many things but then it said this to me “You’ve got nothing to lose by giving it another hour and looking again — you’re asleep anyway.” How can it think that I can check something while I am asleep?
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Very cool moves, specially during unscrewing
We've improved how GEN-1 learns to adapt to new actuators and new robots at the lowest level, with up to 10-20x gains on internal benchmarks. This significantly boosts performance on high-precision tasks like disassembling parts from a NIST board. Read more about GEN-1 in our blog posts in the comments below.
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Very likely someone is tele-operating it remotely but this is a great way to generate revenue while they collect the data. Basically the Tesla FSD playbook, car customers are data collectors.
In China, autonomous and semi-autonomous house cleaning robots are already a thing, and they're not $30/hour. They are ~$17 for 3 hours of cleaning, and they come with a human cleaner too! The company is called X Square Robotics. This is a walkthrough of how it works.
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Absolutely amazing times ahead. Makes sense to solve AI and then use AI to solve everything else.
An internal version of Astra, @OpenAI’s next major model family, solved 10 major open problems in mathematics, quantum complexity, and theoretical computer science. We believe it will be a major step for scientific reasoning.
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10 million intelligent wheeled robots
Congratulations to the Tesla Team! 10 million vehicles manufactured is an incredible amount of work.
In 2026, I came across a large number of high-quality robotics research papers from Chinese institutes. The growth of robotics hardware companies and their collaboration with universities are likely the main drivers.
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Once in a while, I write and debug code without AI assistance. Helps me understand what’s going on under the hood.
So true. Every generation writes books and develops curriculum so that the next can build on top instead of reinventing the wheel.
Knowledge distillation overtime is the engine of progress for humanity.