Andrew Wooten retweetledi
Andrew Wooten
20 posts
Andrew Wooten
@andrewwooten96
Co-Founder & Chief Product Officer @ Rhoda AI
Palo Alto, CA Katılım Eylül 2011
50 Takip Edilen189 Takipçiler
Andrew Wooten retweetledi
Here’s something we’ve never seen done before.
Real-world tasks are long and ambiguous. Solving them requires visual memory and state tracking. Most robot policies only see the last few frames. Ours doesn't.
We put our DVA, FutureVision, to the perfect testbed: the shell game 🐚. The DVA nails it.
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Andrew Wooten retweetledi
I keep hearing that real-world manipulation is the 'final frontier' for robotics. Maybe I’m just the optimistic new kid on the block, but I think we've actually solved this at Rhoda. Our Direct-Video-Action (DVA) models are doing things the industry said were still years away.
Rhoda AI@RhodaAI
Most robot demos are “golden runs”: a perfect take selected from many attempts. But real-world deployment is about Continuous Operation. Watch our DVA model tackle a real-world decanting task for 1.5 hours straight: Uncut, Zero human intervention. 🧵👇
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A+ commitment to the bit from this robot 🕺🤖
That said, every customer I’ve talked to views an e-stop as table stakes. All commercial automation that moves has a stop button - powerful robots shouldn’t be an exception
ABC News@ABC
A dancing humanoid robot got a little too funky during a performance in Cupertino, California and had to be restrained by staff after knocking items off a table.
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This demo is a new high water mark. There have previously been many demos featuring short videos of complex tasks and a few long videos of very simple tasks. Showing a one-off “golden” run does little to demonstrate the capability of a model. The robotics industry should shift to >1hr uncut videos to showcase capabilities.
Rhoda AI@RhodaAI
Most robot demos are “golden runs”: a perfect take selected from many attempts. But real-world deployment is about Continuous Operation. Watch our DVA model tackle a real-world decanting task for 1.5 hours straight: Uncut, Zero human intervention. 🧵👇
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Building AI for the physical world has long had a data problem. The dominant approach to building robots today is based on Vision Language Models (VLAs) which attempt to bake in physics during post-training. In practice, however, this approach requires a combinatorial explosion of incredibly costly post-training samples. Every embodiment, environment, and task demands its own mountain of demonstrations collected via teleoperation or simulation. Because of this, VLAs end up lacking a strong prior over physical dynamics and fail to generalize to the messy variability of real-world industrial deployments.
We’re pumped at Premji Invest to back @rhodaai, who takes a fundamentally different approach. Their Direct Video Action (DVA) model — a new class of robotics foundation model — pre-trains on internet-scale video to first learn motion priors and physical interaction patterns. It then post-trains only lightly on embodiment-specific data — requiring roughly four orders of magnitude less data than the teleoperation-heavy VLA paradigm. The result is robots with much stronger generalization that can handle the variability of the physical world.
Thrilled to partner with @startupjag, @andrewwooten96, and the rest of the incredible Rhoda team! Excited for what’s ahead!
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@tongzhou_mu Tongzhou’s work on the end to end model has made the difference between lab demos and real operation at customer sites. It’s exciting to see robots finally break out of the lab!
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Proud to share what I’ve been working on with my colleagues at Rhoda AI: Direct Video-Action Models (DVA).
TL;DR:
- We pre-train causal video models from scratch to control robots
- They handle complex production tasks for hours without intervention
- Only use ~10 hours of robot data
How? 🧵👇
Rhoda AI@RhodaAI
To bring generalist intelligent robots to the real world, we have to overcome the data scarcity problem. At Rhoda, we are solving it by reformulating robot policies as video generation. Today, we introduce the Direct Video-Action Model (DVA)
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@ericryanchan Eric’s is one of the most brilliant minds on the planet - Rhoda’s DVA approach will change how everything in the world is made and moved
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Today, we announce our team’s progress in pursuing a different type of foundation model for robotics: the Direct Video Action Model (DVA), which does our best to take robotics and turn it into a generative modeling problem we can scale.
Technical blog: rhoda.ai/research/direc…
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@AidanPak Great to be partnering with you on bringing generalist intelligent robots into the real world!
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Andrew Wooten retweetledi
Observe. Predict. Act. Repeat. In closed loop. We call this the Direct Video-Action (DVA) model, and it’s why Rhoda can operate beyond lab conditions in real production environments.
Jagdeep Singh@startupjag
After operating in stealth for the last 18 months @rhodaai , we’re excited today to finally show the world what we’ve been working on. We believe we’re on a path to physical AGI with the launch of our brand new foundation model, the Direct Video Action (DVA) model.
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Huge congrats to @rhodaai team on the launch out of stealth and the new round of funding! $1.7B is definitely just the beginning.
I must say this stealth mode was the hardest for me to maintain because it takes noticeable effort to keep my mouth shut when I’m so excited. Thanks for allowing @dvc_collective and me to be a small part of this - we’re thrilled to help build the most advanced autonomous robotics system in the world!
Rhoda AI@RhodaAI
The gap between robotics in the lab and robotics in the real world has been one of the hardest unsolved problems in the industry. We’re excited to come out of stealth and show the research community how we’re tackling the issue. Bloomberg article in comment.
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Learning motion priors from internet-scale video moves us toward generality and robustness. Generalist robot policies expand the surface area of what can be automated and will materially impact global productivity.
Jagdeep Singh@startupjag
After operating in stealth for the last 18 months @rhodaai , we’re excited today to finally show the world what we’ve been working on. We believe we’re on a path to physical AGI with the launch of our brand new foundation model, the Direct Video Action (DVA) model.
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@startupjag @rhodaai The product challenge in robotics isn’t getting the demo to work - it’s getting the system to hold up when a customer changes their line, swaps a component, or moves the fixture six inches. Rhoda's DVA model solves this.
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After operating in stealth for the last 18 months @rhodaai , we’re excited today to finally show the world what we’ve been working on. We believe we’re on a path to physical AGI with the launch of our brand new foundation model, the Direct Video Action (DVA) model.
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Proud of the team for getting this out into the world. A huge amount of deep technical work went into making these systems work in real industrial environments.
Rhoda AI@RhodaAI
The gap between robotics in the lab and robotics in the real world has been one of the hardest unsolved problems in the industry. We’re excited to come out of stealth and show the research community how we’re tackling the issue. Bloomberg article in comment.
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@rhodaai The last decade of AI progress has come from learning from internet-scale data - applying that same principle to physical intelligence opens up an entirely new frontier for robotics.
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Andrew Wooten retweetledi
Andrew Wooten retweetledi
Andrew Wooten retweetledi
For the last 18 months, I’ve been focused on one question:
Why do robots break when the real world changes?
More soon.
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Andrew Wooten retweetledi
1/ General-purpose robotics is the rare technological frontier where the US / China started at roughly the same time and there's no clear winner yet.
To better understand the landscape, @zoeytang_1007, @intelchentwo, @vishnuman0 and I spent the last ~8 weeks creating a deep dive on humanoid robotics hardware and flew to China to see the supply chain firsthand.
Here's everything we've created + our takeaways about the components, humanoid comparisons, supply chains, and geopolitics👇
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