Notes from the GTC 2026 Exhibit Hall
A visit to NVIDIA's premier conference for artificial intelligence
A horde of visitors just descended on San Jose, California; blocking off multiple city blocks, many wearing black and lime green, all of them talking unceasingly about artificial intelligence. Yes, it’s time for another NVIDIA GTC.
GTC is an interesting conference for me. It’s much more focused on business and sales than the conferences that I usually would go to, like the Conference on Robot Learning. Most of this is selling AI software, but there was a pretty good presence centered around physical and industrial AI — which is to say, robotics.
In this short post I’ll give some of the things I saw on the show floor.
All videos and photos in the article were taken by me.
Skild Assembles GPUs
First up, demoing robotics manipulation in the NVIDIA booth, it’s Skild!
Skild has just raised an incredible $1.4 billion Series C with $30 million in revenue, meaning it probably has the most revenue of any of the current-gen robotics “neolabs.” And here they’re demonstrating why: they have an incredibly precise manipulation demo showing server rack assembly.
From CEO Deepak Pathak on X:
This is showing fully end-to-end learning on a real industrial task
It’s just using cameras - no fancy, expensive sensors with arduous calibration procedures
Long-horizon reasoning and action via in-context learning
Robust to disturbances and easy to deploy for new tasks
According to the booth staff, they had 15-20 hours of real robot data for this demo, as well as use of NVIDIA Isaac Lab with Newton; and in fact we can see the task simulation in the NVIDIA promo videos for Newton.
Noble Machines Shows End to End Humanoids
Noble Machines just recently came out of stealth showing their brand-new industrial humanoid.
They showed demonstrations of whole body control for robot teleoperation, as well as a couple autonomous manipulation policies: picking and placing 2x4’s and pipes, and loading and moving a tote. Both worked flawlessly at least while I was watching.
I also like how this robot is wearing shoes; it might hurt motion aesthetics (because it’s unlikely to be modeled properly in Isaac) but it’s an easy solution to the incredible difficulty of some shop and real-world environments. Shoes are “ablative” and easy to replace, and they have a lot of grip on the floor by design.
Watch some more video of it in action:
Generalist Shows Incredible Dexterity
Robotics learning startup Generalist has quietly been building up impressive technology. In the Universal Robots booth, they showed their manipulation capabilities live. The task: putting a phone in its box. Some impressive details:
They only had the robots for a few days to prepare for the demo - this was a bit last minute
They claimed mere hours of on-embodiment data - a very fast setup process, though they likely had quite a but more data from the same task on other robots
They were constantly doing things like hitting the robots with hockey sticks, interrupting the manipulation and watching it recover.
Generalist has since gone on a bit of a press tour, so I will leave further details to them.
Agile Humanoids
Agile showed both humanoid robots performing a range of manipulation tasks, and a teleoperation system. Agile Robots is one of the small but growing number of European companies in the space, showing how the robotics race is going global.
The Unitree H2, In Person
My first time seeing this robot in person. I think this will be huge — likely the biggest humanoid robot in the world in 1-2 years.
You can also see it fighting at GTC — check it out on X.
Pony AI Car
Self-driving cars continue to scale up. I won’t say much about this, but you can check out my previous blog posts on their competitors like Baidu and Waymo.
Medical Robotics
We don’t see as much work on medical robotics making waves on social media. Medical robots don’t make for flashy videos, but they’re extremely important
Cheap Robots
Seeed studio builds a variety of open-source and low-cost robotics hardware, powered by NVIDIA Jetson. It’s interesting to see this here, as GTC is mostly aimed at larger businesses.
They are preparing to launch re-Bot, which is a larger, higher-payload arm more similar to the common YAM arm. The availability of extremely cheap open-source hardware like this will make robotics research and experimentation far more accessible, which is a bright sign for the future.
Olaf Walks The Floor
NVIDIA and Disney’s robotic Olaf the Snowman looked fantastic, like a Disney character come to life.
Interactive Humanoid Demo
Humanoid had an interactive demo running in the exhibit hall, where you could speak into a microphone and ask the robot to bring you something. This company has been moving incredibly fast to get their robots up and running and start early deployments.
Dexmate Robot Wanders the Hall
Dexmate didn’t have a specific booth, but they still brought a robot. The Santa Clara-based company is one of relatively few aiming to build a platform, with high-quality general-purpose hardware that people can build applications on top of. The Dexmate Vega itself looks highly capable, and was safe enough for them to take it on the show floor.
I liked seeing the teleop rig they were using; it’s easy to imagine a version of this being used to do mobile manipulation tasks in different locations.
Final Thoughts
Compared to previous years, we saw:
Far more end-to-end demos
More mobile manipulation
More teleop
Just more robots that appeared to work, in general. It’s also striking how these companies are all aggressively pursuing applications now; this did not feel like a crowd of researchers discussing their latest papers. Everything felt very substantial and tangible.
All in all, an exciting look at the current cutting edge in robotics.
The Seeed Studio and cheap open-source Jetson-powered hardware mention is underrated here. What's missing from most GTC coverage is the connectivity stack beneath these robots -- Skild's $1.4B raise and server rack assembly demos are impressive, but deploying those capabilities across distributed factory floors requires deterministic networking, eSIM-based multi-carrier failover for mobile assets, and OTA model governance pipelines that most robotics companies haven't solved yet. NVIDIA's Jetson ecosystem is creating the edge inference layer, but the fleet orchestration and connectivity middleware between Jetson nodes and cloud-trained models remains the biggest gap in physical AI deployment at scale.