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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... show more

General Robotics

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13,947 views • 2 months ago •via X (Twitter)

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NVIDIA Robotics

26,155 views • 2 months ago

Elon Musk says Optimus is the infinite money glitch. Not because robots are valuable. Because robots can make more robots. Musk explained that humanoid robots improve through three exponential trends multiplied together: digital intelligence, AI chip capability, and electromechanical dexterity. But the real unlock is that the robot can start making the robots. "So you have a recursive multiplicative exponential," he said. "This is a supernova." Musk's thesis is that once you have a physical robot capable of manufacturing, the production curve stops being linear and becomes self-replicating. Every robot built accelerates the building of the next one. The implication is that the companies that control physical manufacturing will control AI's future, not the ones with the best models. The bottleneck is not intelligence. It is atoms.

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Tiff In Tech (600K+ on YouTube) just dropped a new video: Robots Are ‘Doomed to Succeed’ and That’s a Problem. Excited to see OpenMind featured in the conversation, highlighting the missing gaps in physical AI we solve: - Robot understanding of human intent - Building real social intelligence in robots - Operating systems that work across all robot manufacturers and form-factors Check out the full video below👇

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“But can a robot play the panino?” Yes they can, just about any robot using the new GENE-26.5 AI model.

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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.

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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