🤖 AI Summary
            At Tesla’s earnings call Elon Musk again hyped the company’s bipedal robot, Optimus, calling it an “incredible surgeon” and an “infinite money glitch,” and said Optimus Version 3 will be unveiled in early 2026 with a production goal of up to one million units per year. So far Tesla’s public demos show basic bipedal behaviors — kung fu, picking up eggs, and very slow popcorn-serving — and the company hasn’t demonstrated any medical or surgical capability. Musk framed Optimus as a potential mass-market product that could transform healthcare access, while also tying the project to governance talks (he urged support for a new CEO pay package and hinted at control concerns before building a “robot army”).
For the AI/ML community the claim is significant but provocative: realizing surgical-grade robotics demands far more than humanoid locomotion — it requires sub-millimeter manipulation, real-time high-resolution perception, robust tactile feedback, validated control policies, rigorous simulation-to-reality transfer, and heavy regulatory and clinical validation. Scaling to millions of units adds engineering, compute, data-collection, safety, and privacy challenges. Musk’s statement signals bold ambition and huge potential market impact, but also raises urgent questions about safety standards, certification pathways, dataset integrity, and how to verify claims before surgical deployment.
        
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