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AI is trapped in bits. It's time to set it free into atoms. Last week @karpathy open-sourced autoresearch. It ran 126 ML experiments overnight and found optimizations he'd missed in 20 years. Most people saw "AI is replacing researchers." I saw something else: the boundary of AI's current world. AI's superpower isn't intelligence. It's relentless trial and error. Give it a clear loss function and instant feedback, it'll try ten thousand things overnight. In code and math, this is devastating. No human can compete with a system that never sleeps, never gets bored, and runs experiments at the speed of electrons. But SpaceX — the fastest hardware iterators in human history — still took ten years to get Starship right. Each launch takes months to prepare. You can't blow up 126 rockets in one night. The physical world simply won't give AI the fast feedback loop it needs. Today, AI is like a genius locked in a library. It can read every book ever written, but it can't step outside and touch the grass. This isn't a limitation to fear. It's a frontier to build toward. Software has been optimized for decades. But manufacturing, energy, materials, biology? Century-old processes that have never seen a million experiments. The inefficiency in the physical world dwarfs anything left in the digital world. The real gains — the 100x gains — are hiding in atoms, not bits. The question is: how do you give AI a fast feedback loop in the physical world? Three things need to exist. First, streams of real-world physical data — from sensors, cameras, devices, machines — flowing continuously into AI systems. Not static datasets scraped from the internet, but live signals from the world itself. Second, verifiable computation — so AI's conclusions about the physical world can be trusted and reproduced, not hallucinated. Cryptographic proofs, not vibes. Third, a decentralized workforce — machines and people that can execute AI's hypotheses in the real world, run the physical experiments, and close the feedback loop. Data from the world. Verified by math. Executed by a swarm of agents. This is what we're building at IoTeX. Not because we want AI to be dangerous, but because we believe AI's true potential is wasted if it stays trapped in bits. The physical world is where the real problems are — climate, energy, manufacturing, health — and solving them requires AI that can iterate on reality, not just on text. Autoresearch proved that AI's iteration speed is essentially unlimited when feedback is fast. The unlock isn't making AI smarter. It's making the physical world legible and responsive to AI. Whoever builds that bridge — from bits to atoms, from tokens to reality — defines the next era. We're building that “bridge”. Open, verifiable, decentralized. Not because it's trendy, but because when AI finally learns to experiment on reality at the speed it experiments on code, the stakes are too high for that loop to be closed and opaque.