We are super excited to share with you our initial release of Lucky Engine. We are building a robotics engine from the ground up to be what we wished we could find in a simulator before

"Dominate Global Robotics" doesn't seem great Good read after @corememory @kyliebytes piece on Westmag, Atlas Motion Systems

China's Unitree Will Dominate Global Robotics The Fastest Iteration Cycle In Next-Gen Robotics Should See Unprecedented Acceleration newsletter.semianalysis.com/…

I spent the last week in over a dozen pitches with robotics companies across Silicon Valley, NY and Europe...then I looked at the US Census Bureau Data Turns out 88% of US manufacturing plants don't own a single robot...and that's the opportunity Founders are seeing. Despite the endless deluge of humanoid robot demos and "AI factory" hype in our feeds, nearly 9 out of 10 American factories look exactly the same as they did 20 years ago. Manual labor, mechanical machinery, a retiring workforce and challenges in filling roles. The reasons why they haven't been "updated" historically breaks down into two clear buckets that I call: 1. The Integration Iceberg: A robot arm might cost $25,000 and has come down in price, but the custom tooling, safety cases and software integrations to make it work cost $125,000. 2. The Agility Tax: A traditional robot does one thing a million times. But the average US shop does "high-mix, low-volume" work. To reprogram a robot for a new part has required an expensive software engineer and could take days depending on engineer availability. The next generation of massive robotics outcomes won't come from building shinier hardware for the 12% of factories that are already automated. It will come from the Founders solving the integration and business model friction for the 88% that aren't. If your GTM strategy doesn't solve the 18-month ROI math of a shop owner in Ohio who needs financing, fast onboarding and the ability for the robot to handle a variety of tasks, then you're likely going to struggle. If you're working on a robotics business solving our countries biggest talent bottlenecks, I want to chat.

A new blog post on robot hands: - why they are hard to build and why there are no good ones - why we probably need them anyway - what the trade offs are - a random sampling of startups and research papers in the space

The Eternal Sloptember geohot.github.io//blog/jekyl…

I asked Codex to set up ROS middleware, configure a CSI camera, benchmark Gemma 4 models on my Jetson Orin Nano, adapt an OpenClaw-style runtime for VLM reasoning (“Robotclaw” as I call it), and even build an iOS app to stream LiDAR, camera, GPS, and IMU data from an old iPhone to my robot rover. It’s honestly wild how capable these coding agents are now, and how much time they save. I even “write” way more tests now because the marginal cost is so low.

At #FestivusAI, we’re building a catalog for robotics. Our first milestone was simple but important: gather scattered robotics data from #HuggingFace, #GitHub, vendor sites, tinkerer blogs, and all the odd little corners of the internet where useful knowledge tends to live. We credit sources clearly. No mystery meat data. Then we brought everything into one searchable platform, so people can actually find what they need without opening 47 tabs and questioning their life choices. Now we’ve added an AI agent that makes pages easier to edit, improve, and keep current. Think Wikipedia for #robotics, but faster to contribute to, easier to maintain, and built for the people actually doing the work. And yes, our code and data are #opensource too. Why? Because that’s how innovation leapfrogs. People build faster when the map is shared.