I agree. However I think there is a gap of meta learning that someone may figure out how to fill. Imagine you could take the state of the art driving AI, deploy it, and then wait until it makes a mistake. And then... suppose you could just explain to it in english what it did wrong like you would interacting with a multi-modal LLM. The missing component (for now) is that AI taking your feedback and adjusting the weights in the driving model to fix that mistake. Not just adding additional training data, but correcting based on more fundamental understanding and abstraction of what just occurred and the key take-aways, etc. and then making sure not to repeat that mistake. Just like a new human driver would learn.

It's possible someone might figure out a way to create a training loop using a multi-modal LLM to generate synthetic training data based on the situation you just explained and then updating the driving model by training on this new data until its performance improves on the task.

Right, it's not about the conditions, it's about the ability to perceive those conditions. However this asserts that we won't change how we construct, manage and maintain the routes of travel. Is it unlikely roads will become retrofitted in an effort to enhance the needs of autonomous vehicles?

Seems likely to me; we built EV's before we built the infrastructure to support them and conversely we created in infrastructure for petroleum vehicles before they entered mass production at the largest of scale in the period (1950's) after the fact.

I don't see how autonomous vehicles are not going to become a reality. Perhaps not in my lifetime, but, absolutely likely and possible.

> Not in all conditions. The devil really is in the details.

I imagine we will reach a place where fully autonomous vehicles will pull off to the side of the road in certain weather. Which I wish we could force for humans, but seems infeasible to implement.