Generalist is an AI robotics company building general intelligence for the physical world and making it useful to everyone.
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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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A simple example of physical prompt steerability: same environment, different prompts, different behaviors.
Thanks @JagdeepBhatia8 for the suggestion.
Read more about GEN-1.5 in our blog post in the comments below.
Physical prompting is an elegant idea!
One request for the @GeneralistAI team: can we see an example of *physical prompt steerability*, where different prompts induce distinct behavior in the *same* environment?
I'm curious whether GEN-1.5 is listening to the physical prompt or simply executing the most likely action sequence for the scene under its pretraining prior.
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Other tasks our models can do:
piped.video/playlist?list=PL…
Read more about GEN-1.5, our latest foundation model for the physical world:
generalistai.com/blog/gen-1.…
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We've reduced the time it takes to go from physical prompt → robot behavior.
The faster anyone can teach a robot to do something new, the easier it becomes to scale physical work.
Read more about GEN-1.5 in our blog post in the comments below.
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Read more about GEN-1.5, our latest foundation model for the physical world: generalistai.com/blog/gen-1.…
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Generalist retweeted
Last week @willknight came by and got a preview of one-shot prompting and we had some fun improvisational moments with the robot. Thanks Will for helping capture the moment.
I'm usually wary about talk of "the ChatGPT moment for robots" because language is less complex than the physical world. After visiting @GeneralistAI, though, where I saw their robots perform impressive manipulation with just a prompt, I think you can see it happening in a limited way. (Thanks to @peteflorence and co for having me!) wired.com/story/generalist-a…
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Generalist retweeted
Good question thanks Ani. Here's a video that gives a sense of the answer here about the effect of prompting:
- in the first part, the model is just babbling with no prompt in context
- at the end, we add a prompt for taking money out of a pouch (generalizing to the wallet)
Very cool work, Pete! I'm curious if you've tried an extreme version of this: no in-context example at all; just place objects in front of the robot and see if it can infer the task.
I suspect this will have non-trivial success rates, which would also allow you to figure out how much of the benefit is actually coming from the prompt (rather than pure zero-shot task inference + capability).
I remember Russ showed something like this in his Stanford talk on LBMs last year:
piped.video/TN1M6vg4CsQ?si=-8J-…
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We started planning yesterday’s @generalistai GEN-1.5 announcement about 3 weeks ago. Two weeks ago, already feeling whiplash from new results, I asked ChatGPT to create this image to share in our internal meme channel.
Made with AI
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During a recent visit to Generalist AI, I watched a robotic arm improvise and use a banana as a tool. wired.com/story/generalist-a…
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RT @felixwyw: At 10:06pm on Aug 3, I watched a robot do something I thought was years away.
We were working on few-gradient learning with…
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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.
320
1,689
12,173
3,414,771
GEN-1.5 has been training continuously for over 8 months. We left it running because every metric we tracked kept improving with the engine: absorbing more data, scaling more efficiently, boosting post-training, and compounding step-change improvements through algorithmic advances.
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To us, GEN-1.5 represents a new frontier of generality — one that challenges our own understanding of how these models behave when pretrained at a scale of physical interaction data few thought possible without shortcuts. We do not yet see where this asymptotes.
Read more in the full blog: generalistai.com/blog/gen-1.…
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