Jason Ma

Introducing Dynamism v1 (DYNA-1) by @DynaRobotics – the first robot foundation model built for round-the-clock, high-throughput dexterous autonomy. Here is a time-lapse video of our model autonomously folding 850+ napkins in a span of 24 hours with • 99.4% success rate — zero human intervention • 60% human throughput speed • 4.3/5 quality ratings (set by the client) A thread on our motivation, insights and results:

@chris_j_paxton @DynaRobotics is my favorite when it comes to actual deployments

We had a lot of Red-Bull @JasonMa2020 left at GRASP 😂，very fun and entertaining to see Dynasaur doing well in such a noisy flashy and long scenario! Congrats

These guys are the kings of live autonomy demos. Always impressive

Zero-shot. Plug-and-play. Dexterous manipulation. Running continuously in production. We keep pushing robotics out of the lab and into the real world — bringing the technology to everyone. 🌎

Everyone at Red Bull Mirage brought a DJ. We brought a robot. The robot worked out of the box, no additional training onsite. 8 hours. 700+ Red Bulls served. 99%+ success rate. No humans, no breaks, no resets. Shifting desert light. Cans handed in at every angle. Thousands of people are moving around it. The robot just kept serving. 🤖🥫

real festival footage is restricted, so just footage during our onsite trials for now :)

Dyna x RedBull We partnered with RedBull, and started opening and serving hundreds of RedBull drinks to A-tier celebrities and VIP guests at music festivals! 🥂 The result is 100% zero-shot success rate day and night, without additional on-site data collection. Getting a 99+% success rate in our own lab was something we mastered a year ago, now it’s getting to any task, anywhere.

Robotics becomes real when the question from customers changes from “can it do this” to “how much does it cost?” More to come.

From talking to many friends in robotics recently, there is a strong shared feeling of demo fatigue and vibe shift towards real-world deployments. The moravec paradox of 2026 may be that demos that look hard are easy, but deployments that look mundane are actually very hard! Our co-founder York has been a leader in deploying physical hardware to real-world environments for a decade, from his previous company Caper to now at Dyna. Please read this great insight piece from him and learn what's actually important and hard about real-world robotics!

"Model ≠ foundation model ≠ pre-training-only" Thank you for your so timely and insightful thoughts @yorkyang5050!

@aaronistan 🙌🙌

Most people assume our lamp form factor is just an aesthetic choice, but it is actually a direct response to the exact deployment problems outlined here. Positioning as a lamp allows us to: - tap into existing distribution channels - deliver value on day 1 (without relying on perfect autonomy) - get into homes fast -> starts the data flywheel Humanoids can't do this because they require near-perfect physical ai to be a viable consumer product. This means until physical ai is solved, there will be limited real-world adoption -> limited deployment data -> limited improvement. I wrote a lot on this internally at @bySyncere. Will share more soon.

A must read. True lesson. Honest hot takes from @YorkYang5050 , a second time founder and cofounder of @DynaRobotics

“The fastest way to shorten the robot gap is not better demos. It is harder, more honest engineering against real customer ROI, and the patience to let the deployment flywheel compound before declaring victory.” 👊

A must read. York is sharp as always.

Hear what we @DynaRobotics learnt from the bitter lesson in the past 10 months in production

There is a massive misconception in the AI and robotics space right now. People think that once a model is "smart" enough in the lab, deploying it into the real world is the easy part. It’s not. The real world is chaotic, unpredictable, and entirely unforgiving. At Dyna Robotics, we are taking breakthrough embodied AI out of the lab and putting it into commercial environments, today already. To do that successfully, we realized we had to completely rethink what a Forward Deployment Engineer actually does. If you look around the industry, most "forward deployment" roles are essentially field operations or customer integration. You're handed a model and told to make it work on-site. That is NOT what this role is. I’m looking for a hardcore engineer who can straddle the line between our AI research and our systems architecture. I need someone who wants to build the connective tissue that makes general-purpose robots a reality at scale. Rather than just acting as a consumer of our models, you’ll be actively participating in applied research—building out model evaluation infrastructure, ensuring stability, and solving complex edge cases. At the same time, you'll be architecting the end-to-end infrastructure that bridges off-board computing operations all the way down to the application-level software running natively on the robots. We don't need someone to just string APIs together. We need someone with a deep, first-principles understanding of computer science who is excited to build the data pipelines, tooling, and fleet management systems that allow our robots to operate autonomously in the wild. If you want to push beyond traditional software boundaries and be the critical bridge between state-of-the-art AI research and the physical world, I want to talk to you. Link to apply is below, or feel free to DM me directly. My DMs are open. jobs.ashbyhq.com/dyna-robotics/…

@xiaolonw @LerrelPinto @Meta Congrats!

Excited to share that Assured Robot Intelligence (ARI) has joined @Meta to help build the future of humanoid intelligence! When we started ARI one year ago, our mission was clear: achieve physical AGI. Through deep customer engagements and real-world deployments, it became clear to us that serving the massive opportunity ahead requires training a truly general-purpose physical agent. We believe this agent will be humanoid — and that scaling will come from learning directly from human experience, not teleoperation alone. Meta’s ecosystem brings together the key components needed to make this vision possible. We will be joining Meta Superintelligence Labs (MSL) to help bring personal superintelligence into the physical world. We are incredibly grateful to the brilliant minds, robotics researchers, engineers, partners, and supporters who have worked with us on this journey. Thank you to our investors and angels, led by @aixventureshq , for believing in our mission. This is just the beginning.

@LerrelPinto @Meta Congrats!

ARI is joining @Meta! Over the past year, we have been building ARI (Assured Robot Intelligence) with the mission to build industry-grade physical AI for humanoids. The ARI stack is built on human experience, condensed into actionable tokens that can be rapidly adapted to real-world hardware. But the most rewarding part of ARI has been the people. I feel truly blessed to have worked alongside some of the world's best roboticists, a top-notch investor pool led by @aixventureshq, and the many supporters pushing for us behind the scenes. Starting next week, ARI will join the Meta Superintelligence Labs (MSL) to continue advancing frontier robotics models that advance personal superintelligence in the physical world. We have the potential to transform AI that can think and talk to AI that can do, assisting humans safely and reliably in the physical world. To the many people behind the scenes who supported us: Thank you! This is just the beginning. More in the Bloomberg article:

Claude can actually do CAD now in @Onshape Here it worked for an hour and built a 4-part monitor arm, starting only from a sketch and description. The trick was to give it the tools to look at its own work. Introducing: Jarvis Onshape MCP