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Andy Zeng
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Andy Zeng

@andyzengineer
Building robot foundation models @GeneralistAI, ex @GoogleDeepMind, PhD @Princeton. ✗DMs → email
andyzeng.github.io
Joined September 2017
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  • user avatar
    Andy Zeng
    @andyzengineer
    Aug 4
    The models are getting better everyday. This is a pretty contact-rich task, and forces us to reckon with the fact that our policies not only need to learn the quirks of different robots, but also have to do it in a way that generalizes to the fine-grained subtleties of friction
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    user avatar
    Generalist
    @GeneralistAI
    Aug 4
    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
  • user avatar
    Andy Zeng
    @andyzengineer
    May 12
    Decades of hardware development led to strong, fast, and precise robot arms. The moment we can put in general intelligence in these things, we can leverage the full spectra of capabilities that they were always meant to capture. We’re betting on a future where robot hardware
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    Generalist
    @GeneralistAI
    May 12
    GEN-1 delicately arranges potato chips, and lifts a heavy bag of potatoes — from a gentle touch to a strong grip. Read more about Gen-1 in our blog posts in the comments below ↓
  • user avatar
    Andy Zeng
    @andyzengineer
    Apr 30
    For the avid viewer -- there’s a brief moment when the robot loses it’s grip on the head of a ziptie, and so it decides to use the other hand to help readjust the grip for the pull. It’s gnarly passing by our robots everyday, and catching these random glimpses of improvisational
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    Generalist
    @GeneralistAI
    Apr 30
    Gen-1 ties zipties Read more about Gen-1 in our blog posts in the comments below ↓
  • user avatar
    Andy Zeng
    @andyzengineer
    Apr 21
    If anyone’s creating a benchmark for frontier physical AI models, this task is a great one to add to the roster. Sensorimotor end-to-end policies must exhibit the long-term visual memory to track and reason about where the object might be. It’s also harder to “cheat” on this
    user avatar
    Generalist
    @GeneralistAI
    Apr 21
    GEN-1 plays the 🐚 shell game, trained on just 1 hr of robot data. It also generalizes to unseen objects, like @BerkayAntmen 's car keys. Physical AI models should be capable of benchmark tasks like this one. It's interesting for the all the reasons @RhodaAI calls out --
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    Andy Zeng
    @andyzengineer
    Apr 13
    The first time we rolled a robot into a new warehouse, it didn’t perform as well as we expected. It took us an entire day of debugging, before we realized it was something simple… the cameras were wired completely wrong. 🤦 Left camera to right gripper 🔀 right camera to left
    user avatar
    Generalist
    @GeneralistAI
    Apr 13
    GEN-1 puts plushies into polybags, in a warehouse outside the lab in New Hampshire.
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