SpaceX option package for new Tesla Roadster will include ~10 small rocket thrusters arranged seamlessly around car. These rocket engines dramatically improve acceleration, top speed, braking & cornering. Maybe they will even allow a Tesla to fly …
A machine shop is full of machines that could do much more if they didn’t need humans to specify every variation. Give them a model that understands the part, fixture, and task, and the same hardware can handle far more.
An hour of continuous autonomy is a different milestone than 95% on a task. Long runs surface what short evals never see: drift, heat, a cable slowly working loose.
Here’s a more personal breakdown of how we built Dyna-2.1 - the first Physical Agent to achieve 1-hour-long, dexterous whole-body autonomy.
A lot of the system came down to a few fairly fundamental design choices.
A CNC machine can make almost anything. Forklifts can move almost anything. The bodies for much of the world's automation shipped decades ago. They just need a brain to decide what to do next.
In 8 weeks, we scaled our UMI data collection to 1M+ diverse tasks at $10 per hour of data.
How? Scripted tasks have low throughput, so we made a bet: collect massive amounts of freeform data, with operators interacting with objects on a table however they like. That gave us 5x+ more data than scripted collection.
The catch: freeform data is unusable without annotation, and VLMs couldn't annotate at scale yet when we started Pantheon.
Last month, VLMs finally got good enough. The bet paid off.
Check out the full blog post for more on our hardware, infra, and how a core team of 5 scaled to 90 operators in a few weeks!