I work in the AV space, so I guess you’ll just have to trust me. I assume Cruise internals look very similar to the internals at other AV companies, which I think is a safe assumption.

>The sensors and automation decisionmaking is going to be identical, and that's where the hard parts are.

Sensors will be very different. LIDAR prices are coming down but we’re still a while off from incorporating it into consumer vehicles - and we’re way, way off from incorporating multiple high resolution, long range LIDAR pucks, plus short range LIDAR to cover blind spots, plus imaging radar, plus thermal cameras, etc. into commercial cars the way they’re integrated into Cruise cars right now.

Automotive decision making will also be extremely different. Modern robotaxis rely on very high detail HD maps that are continuously updated. It’s impossible to scale that nationwide in a way that would work in a consumer car. Fundamental parts of the stack assume these maps are present and accurate - remove that assumption and a ton of things have to be rethought from first principles.

Remote support is also a key part of AV stacks - that is, asking a human to clarify an ambiguous situation. There’s a video where Kyle says that Cruise cars request remote support approximately every 5 minutes. Again, fundamental parts of the stack rely on the availability of remote support and have to be rethought from first principles if it’s removed.

This isn’t even getting into the differences in compute on a Crusie car and a consumer car.

>Or alternatively: a less charitable way of making the point work would be to say that Cruise's stack was a bunch of special-case hacks for specific regions and vehicles and wasn't scalable to arbitrary environments nor regular passenger cars.

I mean you’re not wrong, but you can’t create a robotaxi without this. ML models just aren’t capable enough to handle edge cases in a safe way without tons of hacks in place.

> Automotive decision making will also be extremely different. Modern robotaxis rely on very high detail HD maps that are continuously updated. It’s impossible to scale that nationwide in a way that would work in a consumer car.

What are the challenges here? Is it simply the different scale required on the backend to handle tens (hundreds?) of millions of privately-owned cars, vs. that required for orders of magnitude fewer robotaxis? If so, I don't think that's all that insurmountable. I guess one thing that would worry me there would be bandwidth on that scale, as well as what happens when a privately-owned car is taken into an area where it doesn't have connectivity. I assume a robotaxi would just refuse to go where it can't talk to the internet, while that would be unacceptable for a private car to do. (Then again, the private car could still have manual drive controls, and require a driver to take over when internet connectivity is lost.)

I also work in the industry. You've got a couple misconceptions here about how AVs actually work. First, virtually all processing to determine what to do on the road is done locally, in real-time. Relying on internet connectivity would be a safety nightmare. This means you have to pre-train your models to deal with everything in a geofenced area before the car starts driving there. Hence the need for very high detail maps of the areas where robotaxis are going to run. Second, the concept of L3/L4/L5 driving doesn't quite match the reality of how things are playing out. Due to the limitations and cost of deploying current-gen self-driving systems, AV companies are designing vehicles to be L4/L5 within a specified design domain. That means a specific set of roads under specific weather conditions, light conditions, etc. Then those design domains will slowly expand until one day, years from now, vehicles are actually what the public now thinks of as "L4/L5" and at that time it will be possible to deploy the tech for privately owned vehicles. Until then, you're looking at commercial fleet vehicles in specific use cases only (robotaxis, automated heavy duty trucks, farming equipment, etc.)

But that’s not what Tesla is doing! You’re absolutely right and it’s also a safer route (for others on the road) to go with robotaxis first. This is precisely why you can’t focus too much on competitors. GM and their CEO (who seems to be really smart) is focusing on Tesla here and trying to compete with them.

Tesla isn’t focused on robotaxis - they’re focused on trying to sell a premium ADAS feature their CEO over promised half a decade ago. Whcih is necessarily designed very differently from a robotaxi. It doesn’t make sense to try to force a stack built for robotaxis into a consumer ADAS car because you’d have to fundamentally rewrite the stack anyways. This is why GM had its own ADAS team while Cruise focused on robotaxis. I’m sure they’re looking at Teslas market cap and hoping they can generate hype by trying to say they’ll integrate Cruise tech, but that’s just not how these stacks works.

That's exactly what OP is saying - GM is focusing on 'compete with Tesla' rather than pushing for progress/allowing Cruise to progress the technology on their own schedule.

And I’m saying it doesn’t make sense to do that with Cruise’s stack.

Not going to give my name for obvious reasons, but formerly at Cruise. Any sufficiently complex system has lots of hidden assumptions that aren't trivial to unwind when changing problem domains. I can think of at least a few design decisions I personally made that will have to revisited for personal vehicles. It's not impossible, but still nontrivial.