🚨🇦🇷 Lionel Messi when asked how many World Cup goals he can reach: “I am tired now, I’m not thinking about that. I just want to enjoy the win with my teammates”.
Announcing @xdofai: We’ve raised $70 million to build the core robotic infrastructure ecosystem for robot foundation models.
My cofounders Fred (@YideShentu), Nemo (@itsnemojin) and I have been pursuing the dream of general purpose robots for our entire lives. After work at Covariant, Meta and Tesla, it became clear to us that general purpose robots are coming, and we are building XDOF to help make them a reality.
For the last two years, we’ve been working behind the scenes to support major labs and companies deploying robots. In us, they have a partner with full-stack expertise, from hardware to operations to policy training.
As our first public contribution to the space, we are open-sourcing ABC-130K, the largest open source teleoperation dataset, in collaboration with our partners from UC Berkeley, Carnegie Mellon, MIT and Amazon FAR.
Thank you to our customers, partners, collaborators and investors for your trust and conviction in us. Together, we can accelerate the future of robotics!
The SpaceX iteration loop:
1. Question every requirement.
2. Delete any part or process you can.
3. Simplify and optimize.
4. Accelerate cycle time.
5. Automate.
Most engineering organizations skip directly to step five. They take a process that should not exist and then automate it.
SpaceX runs the steps in order, every time, on every part of the company. When the Algorithm has been run enough times on a piece of hardware, it starts to look like nothing else in the industry.
@elonmusk
Hub (@hubxyz) provides real-world training data to frontier AI labs and robotics.
Human labor is half of global GDP. Almost none of it has ever been recorded.
Hub opens access to it through a global network of contributors capturing hard-to-access data.
Congrats on the launch, @xarmin and @tim404x!
https://t.co/ndxHExv6DC
ETH Zurich just open-sourced their entire 2026 robot learning course.
Not a MOOC. The actual course. Slides, lecture recordings, coding assignments, GitHub repo.
The curriculum goes from imitation learning and RL all the way to Vision-Language-Action models and foundation models for robotics.
Guest lectures from the co-founder of Physical Intelligence. The creator of Diffusion Policy. Pieter Abbeel. Dieter Fox.
12 weeks. Free. No signup.
If you want to understand where robot intelligence is actually heading… this is the reading list the field is using right now.
📍[https://t.co/eKsIjILi60]
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Weekly robotics and AI insights.
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SpaceX has just officially unveiled its AI1 satellite, the first generation of its AI satellite.
Overall Specs:
• 150 kW peak compute payload
• 120 kW average compute payload
• 70 kW per ton
• Compute provider interchangeable
Dimensions:
• Wingspan: 70 meters
• Deployed height: 20 meters
Thermal System:
• 110 m² deployable liquid radiator
• Redundant pumping loops
• Integrated micrometeoroid shielding
• Deployable liquid radiators
Solar Power System:
• 150 kW solar array
• 250 W/m²
• SpaceX-manufactured solar technology from Bastrop, Texas
Architecture:
• Centralized compute module
• Large deployable solar arrays
• Deployable liquid-radiator thermal management system
• AI-focused compute satellite design ("AI1 satellite")
Elon: "The AI satellite is much simpler than a Starlink satellite. The AI satellite is essentially a lot of solar cells, you still need some laser links, but you don't have all of the super complex antennas that you have on a Starlink satellite. The easier one to design for is the AI satellite. It's bigger. A lot of this is technology we've already made with the Starlink V3 satellites."