Have a look at the new Nvidia Microduck AI robots.
NVIDIA CEO Jensen Huang was joined onstage at GTC Berlin 2026 by four waddling Microduck robots. Developed by Hugging Face and France’s Pollen Robotics, the duck-shaped machines showed how NVIDIA AI technology can turn skills learned in simulations into real-world movements.
Standing around 25 centimeters (10 inches) tall, the open-source Microduck robots walked, sat and responded to Huang’s commands. One moment drew laughs when three ducks lay down for a “nap,” while the fourth hesitated. The hiccup highlighted both the progress and challenges of autonomous robotics.
Behind the spectacle was a technical demonstration. NVIDIA demonstrated a robot-training workflow using NVIDIA Isaac Lab, Isaac Sim and the Newton physics engine to practice movements in simulation. AI agents organized training, cloud systems handled calculations, and an NVIDIA RTX Spark computer evaluated results before the learned behaviors reached the physical robots.
Microduck is not a newly invented NVIDIA product. Hugging Face and Pollen Robotics first introduced the affordable, programmable robot in August 2026 at a starting price of $399. Its open-source design lets students, developers and robotics researchers explore reinforcement learning, customize behaviors and share improvements.
The GTC Berlin showcase comes as NVIDIA expands its Isaac robotics platform and invests in physical AI—technology enabling machines to perceive, learn and act in the real world. Although the Microducks are small, their demonstration points to a bigger ambition: making AI robot training faster, more accessible and easier to transfer from digital twins to physical machines.
Why it matters: NVIDIA’s Microduck robot demonstration offers a glimpse of how open-source robotics, AI simulation and accelerated computing could shape the next generation of intelligent robots.
The presentation highlights the advancement of Europe's AI economy through infrastructure and \"Physical AI.\" It introduces the DGX Pod for AI factories and demonstrates the creation of robotic agents using RTX Spark, digital twins in Omniverse, and cloud supercomputers, exemplified by the training and deployment of the MicroDuck robot.
Hey guys. Oh yeah. Okay.
Come on here. Come over here.
Show people you can walk and you have a
camera. Oh yeah.
Don't trip.
Can you guys sit down?
Okay. Stand up.
Take a nap. Take a nap.
You need to take a nap. Okay. Stand up.
Did you know that you were, you were created in here?
You were created on RTX Spark. I know.
And trained you in the cloud on a whole bunch of
Nvidia supercomputers.
And you learned your skills right here on RTX Spark and a digital twin,
the Omniverse Digital Twin. Isn't that incredible?
I know. I know. You guys are so cute.
And your parents are called Pollen. P-O-L-L-E-N.
Is that right? Uh-huh. Pollen Robotics. And
apparently, everybody loves you guys so much.
You're sold out. I know. So if you go to the
Pollen website, everybody, everybody watching this,
you know, there's going to be like 20
million viewers, everybody watching this,
go to the Pollen website and place an order. I think
this startup company is like 10 people. They might blow up.
It's going to be so exciting. Everybody
should have one. You guys are so cute.
And so we'll just have an RTX Spark and we'll teach you new
skills. Isn't that right?
Oh, look at that.
That's incredible.
Can you do a somersault?
That's so
good. That's so good. Wow. Okay. Well, guess what?
Okay. So today, what did we talk about?
We talked about Europe building its AI economy,
and it starts with infrastructure. And we announced
a brand new system called DGX Pod.
It makes it easy for you to build AI factories. And these AI
factories don't just run models anymore.
Pay attention. Stay focused. Come here. Come here.
come over here stay focused
and these AI factories don't just run there you go sit down yeah they
they don't just run AI models anymore they run entire agents
and these agents are consistent
of five things there's the large language model
that does the perception reasoning planning and
acting and it runs in conjunction with a harness
that turns it it's essentially an exoskeleton and
that harness sits inside,
runs inside a secure runtime we call OpenShell, which has just so
many people that have supported it.
And you give it access to knowledge and tools. And this agent
runs on top of these computers,
but we're also extending into the next generation, which is where
you guys come in, physical AI. So that's it.
That's what we talked about. Everybody can build
agents. Every company in Europe will become an AI company.
There's no question everybody will
become an AI company. And we're going to have
a thriving AI economy here in Europe. So after 33
years, what an incredible journey.
And we made a really cool video. You guys want to watch it
together? Okay. Come on. Come over here.
Just come over here. Just a little bit. We'll get out of the
way come here top speed top speed
so this this is the prompt
that is going to run the next
application and what what you're about to see
is this you're about to see a robotics application
and while you're watching this demo just remember there's
an agent running on this personal computer
this demo runs across three computers the first computer
is to train the second is a digital twin
And the third is to put that AI into the computer itself.
Okay, so two ideas.
The first idea is agents.
How do you build it and run it and what you can use it to do?
And the second is physical AI computing model,
which consists of three computers.
Let's take a look.
Meet Microduck, Hugging Face's robot.
Let's teach it to see and walk with NVIDIA RTX Spark.
I use Hermes as my agent harness.
Nemotron and OpenAI's GPT-6 Astra as my models,
and CUDA-X accelerated tools FreeCAD, Blender, and Isaac Sim,
Newton Physics Engine, and IsaacLab.
I'll run everything on my RTX Spark,
except when I need to burst larger workloads to cloud.
First, I describe the course
and what my MicroDuck needs to learn.
On RTX Spark, Hermes and Nemotron plan the course,
listing every object required.
Astra takes it from there.
using FreeCAD to model 3D objects,
Blender to apply materials,
and Omniverse SimReady libraries to add physical properties.
In IsaacSim,
Astra composes the scene.
Astra rigs MicroDuck's joints, actuators, and links,
and simulates how MicroDuck moves
with Newton Physics Engine.
Now, training begins.
In the cloud, thousands of MicroDucks
train in parallel
in IsaacLab.
Every fall, a lesson,
improving the policy every time.
Omniverse libraries simulate MicroDuck's cameras,
teaching it to see.
With perception and physics working together,
my MicroDuck can avoid obstacles,
navigate tight spaces,
and adapt to its surroundings.
I download the policy to RTX Spark
and use Nemotron and Isaac Sim
to evaluate my MicroDuck
with multi-robot orchestration.
I deploy the validated policy to the real duck
and he's on his way.
NVIDIA RTX Spark, build and run AI agents
and their accelerated tools right on your laptop.
GTC, I want to thank all of you.
I want to thank all of you, all the sponsors.
You can see all the names of companies that are here,
all the partners we've been working with for 33 years,
MicroDuck, my new friends.
Let's work together to build Europe's AI economy
and put AI to work.
All right, get ready.
Have a great GTC.
