In my other reply I tried to say you were wrong in a way that was rude, which I regret, so I want to try again in a more respectful way.

Initially, it was the thought of most people who thought about the problem that more sensors would be best. This was what Tesla thought, not just what you thought. It was what I thought. I've read Artificial Intelligence: A Modern Approach. I've read about Kalman filters and sensor fusion. I've implemented them. So intuitively, I think it makes a lot of sense that more sensors should be more effective. So it was surprising to me when Tesla decided to drop radar and it was even more surprising to me when they shared that the empirical results of dropping radar led to measurable improvements in vehicle safety and improved their accuracy in determining their position relative to other objects.

In the past I've made that claim and people have been surprised by it. It doesn't seem to be common knowledge. If you didn't know it or you doubt it, then I'd recommend you check out an engineering talk by Andrej Karpathy. This isn't a Tesla marketing piece. It was a workshop talk at the Computer Vision and Pattern Matching conference in 2021. Andrej Karpathy is the senior director of AI at Tesla. He was someone involved in this decision to switch from radar to vision only and in the talk he outlines the engineering reasons which motivate the switch.

[1]: https://www.youtube.com/watch?t=28257&v=eOL_rCK59ZI&feature=...

If you still doubt that it is a good idea to switch, I can contribute my own anecdotal experience. I have a Tesla. I drive in it. When I do, I use autopilot very frequently. The majority of my driving is done by autopilot. As such I've gotten experience which has informed me a bit about how autopilot tended to fail. One of the ways it could fail was by making me take over when going under an underpass or by breaking suddenly when doing so made little sense. This is a category of error that I have stopped experiencing since the switch away from radar.

So now we're in an interesting position, because if you recall you claim that people who believe vision only are naive. Naivety is usually defined as meaning to be wrong because of idyllic assumptions that are wrong, but which you don't realize are wrong because of ignorance. Yet the way things played out historically is that people assumed that sensor fusion was the best approach, empirical results suggested it wasn't the best approach, and consequent to that people changed their minds. In terms of the progression pattern, this is exactly opposite of what it means to be naive, because the beliefs are contingent on experience rather than a consequence of its lack.

Sometimes we have simple models of reality and they suggest one thing. Then we get experience in the real world, which is much more complex than our simple model, and that experience tells us something else. Telsa, like you, thought radars plus vision was better. They tried a model that dropped radars and the result was empirically measured as being safer.

Should we go back to the thing that we know to be less safe through empiricism? Well, if we do, but we do so without solving the reasons it was bad, then we are going to have the car making bad decisions. Those bad decisions put lives at risk. So I don't think we should go back. If we can address the root causes of why the sensor fusion approach introduces dangerous error, then we can do that, but just adding back radar? That would kill people. Probably the people directly behind a Tesla that breaks because of a hallucinated object detected by radar.

I wish I could delete my other reply, but I think the example in it is extremely important, because when people try to use the toy problems that fit in their head? They are choosing to exclude that very very real non-theoretical situation. That is exactly what the world with radar was generating as an inevitability and we need to be crystal clear on that when we reason out exactly how to avoid that type of error. Blindly saying that sensor fusion is better is really dangerous, because people can really die if we make the wrong decisions -- and because we can measure the results of different models empirically? It is blindness to say it, because it contradicts the evidence.