There's a coin with virtually zero competition, abstracting away the most complex tasks in what may be the fastest growing sector we'll ever see.

Where the team behind it is even getting direct input from Hugging Face's LeRobot team to build an open SDK for world simulations. In other words, they're working with open source AI leaders to make their development kit as efficient as possible for simulating reality.

This vertical is crucial because humanoid robots don’t deal in text or code, they operate in the atoms and physical objects. An AI agent can analyze text, but a humanoid needs to perceive and manipulate the 3D world in front of it.

One reason why Tesla has a head start with its Optimus humanoid, the wealth of real world neural network data gathered by Tesla’s fleet. Tesla’s cars collectively log around 50 billion miles per year, feeding a near infinite dataset to train vision and control AI.

Yet training robots in the real world remains painfully slow and resource intensive. Progress has been limited because no one has fully cracked synthetic data for humanoids, the “sim to real” gap. It can take hundreds of hours of physical training to teach a robot a simple task and simulations often fall short of reality.

All the pieces are there, humanoid bodies are approaching human level capability, but the missing link is the brain, the software that tells these robots how to do things. A robot may have arms and legs, but without intelligent code, it can't even cook your dinner while you watch Netflix.

Just like smartphones were useless until app stores unlocked third party apps, humanoids will be useless without a library of high quality skills. The biggest value will come from whoever builds the infrastructure that lets developers easily create new “apps” (tasks) for robots. The platform that makes programming robot behavior easy will become the “app store” of the robotics era.

Individual devs are struggling because they often lack the compute power and hardware to train robotic tasks at home (as seen in the Hugging Face robotics community discord). This is why an open platform with cloud simulation is much needed.

We’re already beginning to see releases which highlight developers having the capabilities to run full robot simulations on remote servers, so anyone can train and test complex tasks without specialized hardware on hand.

Multi modal models now tie vision and language together, a robot can ‘see’ through multiple cameras and act on natural commands. This makes fine tuning new skills possible with smaller datasets and lighter compute. Much like what we’ve seen with Figure’s Helix VLA model.

I’ll give you one guess who this might be.