Elon Musk on Cameras vs LiDAR for Self Driving and Autonomous Cars

Its an interesting video but its an edited video. The company website mentions the system was able to negotiate the challenges of the driving conditions, looks like an euphemism... Very few details, no scientific publications I could find on their Asimov system on a quick search, not sure if this is a technological breakthrough or a fine tuning of existing processes and methods. Because if its a fine tuning of current algorithms not sure how long they can push this. They are relying on Lidar (and other sensors) but even as of last year, it seems most teams already realized Lidar would not be the solution for Snow, and were now pushing Ground Penetrating Radar ( sounds expensive...) "Autonomous Cars Struggle in Snow, but MIT Has a Solution for That" [link] Even Tesla, already realized its not just a sensor problem, solving self-driving needs a higher level algo than can put the different sensors, in context of situational awareness. Note that in no any other way I would consider Tesla an example to follow ;-) And do not think they are any closer to getting a working system. Some of the statements show at least a second level understanding of what is required. Sensors are a means to it. Its about situational awareness but also inference. "LIDAR is a fool’s errand… and anyone relying on LIDAR is doomed. — Elon Musk" [this video]

Anyone who owns a Tesla and has used the new V12.3 understands why Elon is so bullish about the Robo-Taxi's. He's said they've internally seen a 5x-10x reduction in disengagements on 12.4 (already trained, out soon), and that 12.5 is even better. Their GPU stack by end of the year will also be 8x the size it was earlier this year. Combine all this together, and the "feedback loop" with millions of people using FSD, it's looking like the "vision only" strategy will work. My question is what happens to all other car markers if it turns out Elon and Andrej Karpathy's strategy ( [this video] ) is the correct one?