Most robot demos are scripted.
Generalist's GEN-1 is not.
> GEN-1 was doing a task
> Mid-task, an extra object was thrown into the bin
> GEN-1 quickly adapted to the new environment
> Still completed the task smoothly
This is the difference between a scripted policy (seen in viral launch videos) and a real foundation model.
GEN-1 was trained on 500,000 hours of proprietary, real-world dexterous manipulation data.
It has NEVER seen that exact scenario before.
This was the coolest demo at @AutomateShow@GeneralistAI@FlexivRobotics
Come see live demos of GEN-1 doing dexterous manipulation tasks at #Automate2026 — the largest automation show in America, with our friends @Universal_Robot and @FlexivRobotics
📍 UR @ at Booth #1250
📍 Flexiv @ Booth #2844
For early access to our models, please reach out 📧 [email protected]
🗺️Full floor plan: https://t.co/soz4aM7LTv
A jaw-on-the-floor moment for the whole team was when we had taught the robot to pick up a baggie and shake a usb-brick out with the left hand. During one rollout, it decided to do it with the right hand—and we all stopped. We were stunned, because no one taught it to do that.
This was one of the first models with our pretrained base, and it was the moment we realized there was something here that was very different from what any of us had ever built before.
We now know this to be part of the improvisational intelligence that emerges with large-scale pretraining on real manipulation data, and it continues to be one of the things that we believe to be worth pushing forward as capability.
Our CTO and cofounder Andy Barry joined @a3automate to share more about these moments, and how his time at Boston Dynamics and the Broad Institute drove him to focus on building the 🧠 for robots at Generalist.
Full ep 👇
Generalist is hiring our first product designer! Come help me build the Generalist design culture, and help shape the future of robotics! https://t.co/qHIjaCWTEo
Generalist CEO @peteflorence says robotics models are in a transition period similar to the step change between GPT-2 and GPT-3.
They're "starting to cross over into levels of performance where these things are commercially viable for a number of different applications."
"We think this is a crossover point where we have a general model starting to be able to hit levels of reliability, speed, and improvisational intelligence where we can start to get these things out there."
"Very much like — you take a GPT-2-level model, you scale it to a GPT-3-level model, and certain types of commercial applications start to become viable."
We are also hiring on many fronts across research, technical infrastructure, partnerships, and several others. We are incredibly proud of our team. If you'd like to chat about joining, let us know! https://t.co/RbXLdGNIBw
We've raised $400M in new funding. This capital goes toward one mission: building general intelligence for the physical world and making it useful to everyone.
In my first week at @GeneralistAI, I trained a robot to pour liquids using GEN-1 🤖💧
I wanted to challenge the robot with a non-rigid manipulation task, so liquid felt like the perfect choice. The task involved:
- unscrewing the bottle cap
- pouring liquid into espresso glasses
- rebalancing uneven pours
Best of all, the robot was able to complete the task fully autonomously 3 times in a row (out of 3)! Pour-fect 😉
Excited for the journey ahead and grateful to be building alongside such an incredible team!