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Robots are maturing. AI models are advancing. Deployments are rarely scaling. Today, deploying a robot still means stitching together systems that were never designed to work together. For every robot. Every time. The industry needs a unified intelligence infrastructure that any robot, any model and any workflow can plug...

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General Robotics

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14,762 Aufrufe • vor 4 Monaten •via X (Twitter)

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🇺🇸 ELON: WE DESIGNED EVERY PART OF OPTIMUS “I was surprised that we had to develop every part of the robot ourselves. There were no off-the-shelf motors, electronics, or sensors; we had to develop everything. We couldn’t find a source of electric motors for any amount of money. There are tens of thousands, even hundreds of thousands, of electric motor designs. None of them were suitable for a humanoid robot. So we had to develop our own design, specifically for what a humanoid robot needs.” Source: Lex Fridman Podcast - November 2023
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🇺🇸 ELON: WE DESIGNED EVERY PART OF OPTIMUS “I was surprised that we had to develop every part of the robot ourselves. There were no off-the-shelf motors, electronics, or sensors; we had to develop everything. We couldn’t find a source of electric motors for any amount of money. There are tens of thousands, even hundreds of thousands, of electric motor designs. None of them were suitable for a humanoid robot. So we had to develop our own design, specifically for what a humanoid robot needs.” Source: Lex Fridman Podcast - November 2023

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I spent the last week in Beijing, first at world robot conference, then at the world humanoid robot games. It's very clear that China are way ahead of anyone else in Humanoid robotics, in every field, both complete robots and component supply chains. I had a fantastic time. I put together this short clip from the robot games. Full video coming soon.

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JUST IN: Dyna Robotics just published one of the most important research papers in robotics this year. It could fundamentally change how robot foundation models are trained. A scaling law that transfers from human video to robot performance. Dyna-2 is out and it's 🔥 Here's what that means in plain terms. Dyna-2 was pre-trained on ONE MILLION hours of egocentric human video, 170 years of continuous human experience, cooking, folding, assembling, cleaning. And as that human data scaled, robot performance improved. Predictably. Monotonically. Across 39 tasks on two different robot embodiments the model had never seen. → 1,000 hours pre-training → 20% normalised task performance → 10,000 hours → 28% → 100,000 hours → 45% → 1,000,000 hours → 53% Human video exists at effectively unlimited scale. Every cook, every factory worker, every craftsperson wearing a camera is generating training data for future robots. But the finding that stunned even the researchers, world modeling is what makes the transfer work. A model trained to predict future video AND actions massively outperforms one trained on actions alone. Video is the new scaling axis for robotics. One more jaw-dropping data point. 13 minutes of teleoperation data was enough to fine-tune Dyna-2 to open a bottle cap using two five-fingered robot hands. The robots are coming, and they're learning from us directly :D Read more here: Congrats Jason Ma and team! ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

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Everyone is asking about AI’s ROI. The use cases. The productivity gains. All of that matters, but it comes later. Because the bigger story isn’t about applications. It’s that a general intelligence is being industrialised. AI is no longer a software feature. It’s becoming the infrastructure layer of the next economy. The foundation upon which every industry, every transaction, and even future systems of governance will run. We’ve seen this before. Moore’s Law turned silicon into the backbone of the digital age. Now AI scaling laws are doing the same for intelligence — only faster, cheaper, and far more profound. Intelligence is becoming something we can manufacture, distribute, and embed everywhere. And once intelligence becomes industrial, the question shifts. It’s no longer what are the use cases? It’s who controls the infrastructure of intelligence? Because that answer won’t just determine which companies win — it will determine which nations do.

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Elon Musk on Optimus: "Everything in the Optimus robot is designed from Physics First Principles. Its not taken from a catalog. These are custom designed. Everything, literally everything. Optimus is designed to have a lot of intelligence and to have the same electromechanical dexterity, if not higher than a human. It's quite a big robot because it has to carry heavy objects for long periods of time and not overheat or exceed the power of its actuators. It's 5 11, so it's pretty tall and it's got a lot of intelligence. So it's going to be more expensive than a small robot that is not. Over time as Optimus robots build Optimus robots, the cost will drop very quickly."

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Collaborating like an ant colony Blue Worm Robotics from Xi'an has released a wheeled humanoid robot solution for warehouse automation. The wheeled humanoid robots move freely and quickly among warehouse shelves and workstations, using their lifting bodies to move, transfer, and sort goods. The robots collaborate with each other, and multiple robots can even work together to assemble another robot. As the collaborative tasks become more complex, swarm intelligence will emerge.

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Unloading trucks with robots! 📦 Bastian Solutions has developed a mobile robot system that automates high-volume, floor-level unloading of trailers. Let's have a closer look at how it actually works! The robot seamlessly drives itself in and out of trailers and docks without any fixed infrastructure. This system picks up cases via an extendable conveyor, lifts them using a retractable mast, and accurately places them inside the trailer using a dedicated gripper. In the video you can see the reversed process, unloading of a truck. 🚛 It's guided by LiDAR-based navigation and an omnidirectional base, enabling fast, precise, and infrastructure-free operation. Integrates smoothly with existing systems like conveyors, scanners, sorters, and depalletizers. Every time I see a robot loading and unloading a truck, I'm like: we are getting there :) ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

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What happens when mobile manipulators go on a grid❓ This week Brightpick announced Gridpicker, its new robotic system for high-throughput applications. Combining AI-powered mobile manipulation with a high-density grid design, Gridpicker achieves up to 2x the throughput of shuttle systems at 40% lower cost and using 5x less labor. Most fascinating: The cost of Gridpicker DECREASES as automation increases 🤯 Traditional systems separate storage and picking. If you want more robotic picking, you add expensive robotic cells, more infrastructure, and more complexity. Gridpicker was designed differently: Each robot both retrieves items and picks them. The greater the share of robotically pickable items: The more productive each robot becomes The fewer robots are needed The lower the cost per order That means progress in AI and VLAs directly translate into better system economics over time. Hats off to Jan Zizka that! 👏 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

29,457 Aufrufe • vor 5 Monaten