I'm not talking about the state of today's self-driving cars, I'm talking about how we got to here. Also don't forget the overarching claim regarding lack of sensor and actuator fidelity in the parent comment; self-driving cars in contrast have expensive LIDAR in them and we still don't think camera-based self-driving cars are safe enough.
I don't know how you can read my comment, not respond to my comment saying that today's self-driving cars use LIDAR, and continue to reiterate your point.
I don't think I was clear and explicit, it being tedious to write, and I apologize for that. I also apologize for shifting the goalposts as I had not written out my own position, which is not exactly in the "grandparent commenter"'s position (that I had not previously given enough attention understanding), but it is also not in agreement with yours. I don't mean to say that we are not presently in the "bitter lesson" (your idea of what the bitter lesson says) regime. I definitely think that a lot of progress can be done right now by emphasizing the humanoid robotics platform as a foundation. What I mean to say is that I don't know if that platform with the hardware we have today is sufficient for parity with human housekeeping tasks in the domains that we wish it to have parity. The bitter lesson itself (not your understanding of it) is in fact silent on this as it is in relation to feature engineering, where it is a clear point, but you seem to be adapting it uncritically wholesale to mean something more than what it is written about. My position is that, it is unclear whether today's sensor platform is sufficient for parity. It is less strong than the blog post author's "Why Today’s Humanoids Won’t Learn", it is a "We can't say whether or not today's humanoids will learn", but it is something that also contradicts a "the bitter lesson means today's humanoids will learn" thesis.
The self-driving car supports my claim, because after so much investment in capital and time, we ended up with a car with comparatively expensive LIDAR sensors as our preferred platform.
Tesla's entire fleet runs on raw cameras. Including the driverless Robotaxi vehicles - which are basically a 1:1 match to how Waymo operates.
Plenty of hecklers were saying "you can't self-drive on cameras", and some still try. But Tesla's self-driving on cameras, and it seems to work fine. While Waymo's self-driving on fat sensor stacks, and it also seems to work fine. Sensors don't seem to be a differentiator of self-driving performance.
I don't think anything about self-driving tech supports your claim. Tesla was bullish on AI all the way, and Waymo has also shifted towards highly integrated end to end AI. It's the AI advances that make self-driving tractable - not anything else.
