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The China vs. India framing here is interesting, though I'd extend it a step further.
China's advantage in self-driving isn't just technology spend — it's data density. Shanghai and Shenzhen generate the kind of edge-case training data (chaotic intersections, mixed traffic, irregular pedestrian behavior) that you can't simulate easily. Waymo's advantage in the US is similar: years of real-world miles in specific urban environments. The cars learn from the city they're trained in.
The commercial deployment gap is also worth watching. Robotaxi services like Baidu Apollo Go are running at scale in Chinese cities with no safety driver. That's not a trial anymore — it's a service. The US equivalent (Waymo in SF and Phoenix) is years behind in geographic coverage.
What I'm less certain about: whether full autonomy is actually the goal most people need. The 80% case — highway driving, predictable environments — is already largely solved. The last 20% (school zones, construction, unpredictable weather) is where the hard problems live and where the regulatory questions get complicated.
The crypto parallel: decentralized physical infrastructure networks like DIMO are starting to tokenize vehicle data. If your car is generating training data for AI systems, there's a question of who should capture that value. Still early, but worth watching.