Axis Weekly Last week, we improved policy takeover and verification, expanded TaskGen's articulated-scene coverage, and ran a second DAgger round. An eight-step policy-takeover constraint and cleaner derived tasks now sit alongside domain randomization, published LIBERO Pro,… Show more

I think the biggest problem in Physical AI isn't making robots move. It's making them learn enough about the physical world to move reliably. And that's where simulation starts to make a lot of sense. Hardware in the loop collection is expensive. Real world environments are… Show more

I’ve been looking at @axisrobotics from a different angle lately. The interesting part isn’t just the tasks or the Points. It’s what happens after you complete a task. Your actions are turned into trajectories, then they go through verification and scoring before becoming… Show more

The first week I used @axisrobotics I kept waiting for a download or a special controller. There is none. The whole collection layer lives in the browser. I learned that the hard way by failing a rotate and place task three times before I stopped yanking the arm like a… Show more

Robots Learning From Their Own Mistakes @axisrobotics Robotics is building a powerful learning loop that combines demonstrations with human guided corrections. Behavior cloning can teach a robot how to imitate successful actions, but it struggles when the robot encounters… Show more

Good robots don’t just see the world. They understand it Raw data only shows what happened. A camera sees an object. A sensor records a movement. A log captures an event. That is not intelligence. That is a snapshot. Understanding comes from context. The same object under… Show more