A NEW MILESTONE FOR AUTOMATA ROOM
We’re incredibly excited to announce that Automata Room is now part of the NVIDIA Inception Program. 🟢
NVIDIA Inception supports startups pushing the boundaries of AI and technology, and we’re thrilled to be joining a community building what’s next.
For us, this is another step toward our vision:
Natural language → Environments → Simulation → Robotics → Intelligence.
We’re just getting started.
Asimov 1 is now in Automata Room.We’re excited to welcome Asimov 1 by @asimovinc into Automata Room.
Asimov 1 can now step into custom environments, interact with objects, follow programs, and become part of new robotics experiments.
The workflow is simple:Create the room → Program the robot → Execute the task.Automata Room is building the environment layer where AI-generated worlds can meet robotic intelligence giving robots a place to operate, reason, and complete tasks.
The room is ready.
Asimov 1 is ready. Now, give it a task.Welcome to Automata Room, Asimov 1. 🦾The environment is programmable. The robot is ready.
Thank you for the honest feedback. I really appreciate you pointing this out.
I’m still relatively new to the crypto space, and I know there are areas of the project and business structure that I need to improve. I’ll take your feedback seriously and work on fixing what’s missing.
Btw, I’m a solo developer building Automata Room, so feedback like this is genuinely valuable to me. I’m learning as I go, and I appreciate you taking the time to share your perspective.
Thank you 🙏😊
Fair question. We’re finalizing the tokenomics now and will publish the full breakdown on our website.
Starting this week, accessing Automata Room will require payment in $ROOM. Free access was intentional to let people explore and start building, but as we move forward, $ROOM will be part of the actual economic flow of the platform.
We’ll also update the website with the distribution details and how value flows through the ecosystem.
Thanks for asking we want to make this as transparent as possible.
@automataroom Still waiting for that tokenomics.. Also, what brings value to $ROOM when everything is free? The reply you gave me on an earlier post explained how economic value could be captured but what stood out to me from that was "value could POTENTIALLY flow through the $ROOM ecosystem"
@spacemeowb0y Yeah, that’s fair. Initially, people mainly wanted to try the demo, and I thought it was okay for us to cover the LLM and other costs ourselves. But now we’re implementing payments with $ROOM, so users will start paying to access the platform.
Asimov 1 by (@asimovinc ) is now in Automata Room.
The humanoid is here ready to step into custom environments, follow programs, and become part of your robotics experiments.
From room creation → robot programming → task execution, Automata Room is building the bridge between AI-generated environments and real robotic intelligence.
The room is ready.
Asimov 1 is ready.
Now give it a task.
Welcome, Asimov 1. 🦾
AUTOMATA ROOM WEEKLY RECAP
A lot shipped this week:
• Rigwright design robots with LLMs or Jev, move by move
• Automata Inference OpenAI compatible API for our models
• Lunar Lander real reinforcement learning running in-browser
• 22 robots + 25 props + 8 environments
• Export to MuJoCo, Gazebo, ROS & Isaac Sim
• Up to 200 reproducible environment variations
• Live $ROOM price, volume, liquidity & market cap
• Reppo integration + our own robotics datanet in preparation
• Real Python robotics playground in the browser
• Joined NVIDIA Inception
From generating environments → designing robots → training agents → exporting to serious simulators.
This is just the beginning.
Automata Room is building the environment layer for robotics.
We’re currently adding Asimov 1 to Automata Room. 🤖
Soon, you’ll be able to bring Asimov 1 into programmable environments and start building new robotics capabilities.
More robots. More environments. More possibilities.
What if you could train an autonomous agent to land a rocket without touching a real rocket?
We built Lunar Landing in Automata Room: a reinforcement-learning environment inspired by the challenge of autonomous rocket landing.
The objective is simple:
Land. Stabilize. Learn. Repeat.
An agent observes the environment, chooses its next action, receives rewards or penalties, and gradually learns how to control the descent similar to the core idea behind autonomous landing systems.
But this isn't just a demo.
You can use the environment to generate training data and experiment with your own agents.
1. Explore the Lunar Landing environment
2. Train your own agent
3. Generate trajectories & datasets
4. Benchmark different policies
5. Export the data for further research
From simulation to robotics, we're building a place where environments become data and data becomes intelligence.
Build the room. Train the agent. Let it learn to land. 🌕🚀
Inspired by the challenges of autonomous rocket landing a problem @SpaceX has pushed forward in the real world.
@elonmusk@SpaceX maybe this is a good place to start training the next generation of landing agents. 🚀🌕
What if you could train an autonomous agent to land a rocket without touching a real rocket?
We built Lunar Landing in Automata Room: a reinforcement-learning environment inspired by the challenge of autonomous rocket landing.
The objective is simple:
Land. Stabilize. Learn. Repeat.
An agent observes the environment, chooses its next action, receives rewards or penalties, and gradually learns how to control the descent similar to the core idea behind autonomous landing systems.
But this isn't just a demo.
You can use the environment to generate training data and experiment with your own agents.
1. Explore the Lunar Landing environment
2. Train your own agent
3. Generate trajectories & datasets
4. Benchmark different policies
5. Export the data for further research
From simulation to robotics, we're building a place where environments become data and data becomes intelligence.
Build the room. Train the agent. Let it learn to land. 🌕🚀
Robot data markets are coming to Automata Room. 🤖
We’re getting our datanets ready on Reppo, alongside projects like @StrikeRobot_ai building high quality datasets for robotic vision and industrial environments.
Soon, we’ll publish our own Automata Room datanet focused on robot task episodes, environments, programs, and replays generated through our Studio.
From simulation → data → evaluation → training.
The robot data layer is just getting started.
@reppo@StrikeRobot_ai
@abdullahynafis Absolutely making the reproduction path public is a great point. Would you mind sharing the link to the paper as well? I’d love to take a closer look at the MSPRS receiver and the "coded-msprs" implementation.
Automata Research is now public.
We’re opening the lab.
Robots, LLM inference, agentic decision-making, robot design, simulation, datasets, and evaluation — all evolving in one place.
Build → experiment → benchmark → share.
The repo is public now. Come see what we’re building.
https://t.co/LaNvkSHVy9