There's GM's Supercruise, talked about in the article, and then there's Cruise Automation, a startup acquired by GM which is focusing on robotaxis, and is at once more capable and more revolutionary than anything Tesla is doing.
> and is at once more capable and more revolutionary than anything Tesla is doing.
Yes and no.
Part of the reason why Tesla is behind is because they're gimping their engineers by focusing on optical-only solutions.
IIRC, Cruise Automation uses LIDAR, which gives better sensory data. IMO, this is where AI really has an edge: when they start to use sensors that humans don't have. LIDAR accurately maps the distance between the LIDAR and every physical thing in a certain radius.
Solving the problem with LIDAR isn't "revolutionary" per se. Its kind of the obvious way to do autonomous cars. It is a more expensive approach however.
I guess the end results are all that matters however. At which point, I am more bullish on any LIDAR approach. If LIDAR makes it easier to code and more reliable for AIs to detect where they are in 3d space, it should be used (and then you try to solve the mass-production problem to bring down the cost of LIDAR units).
>solving the problem with Lidar isn't revolutionary per se
Solving the problem in any capacity would be revolutionary. Autonomous vehicles operating in a commercial capacity on public roads technically don't yet exist.
There's the old saying 'it's easier to optimize a working system than it is to get an optimized system working',
Outfits using Lidar (and using about an order of magnitude more compute than what's going into Tesla's HW2) are much closer to solving autonomy than Tesla, and in time these systems will get cheaper.
However, you can see how an optical-based system should in theory work because all our roads and signs are designed based on that assumption and has never assumed LIDAR. If a human can do it optically, one can reason, so should a machine. That said, I think Tesla is making a big assumption about human optical systems and object recognition and our current ability to replicate it. One of the things my undergraduate classes in AI taught me is that people tend to underestimate the sophistication and complexity of human neuro/cognitive systems. We are only consciously made aware of the simplified end results but are often unaware of the complexity of the underlying sub-systems.
Yeah, I would never argue that an optical system won't ever work, I believe it will work someday. While the best optical/radar have shown alright capabilities in a demonstration capacity in straightforward driving situations, they're nowhere near having the kind of redundancy needed to safely remove a human from the driving task altogether.
With Waymo's robotaxis, who are the closest to a pilot commercial deployment, they spare no expense, they're riddled with sensors, they have giant computers in the trunk, there's an air-gapped backup computer that can take the vehicle to a minimal risk condition should the primary fail. They are maintenance intensive and require careful maintenance and oversight; Waymo (and GM) are building call centres filled with remote human monitors who can intervene when the vehicles get hung up, and they're geo-fenced. They are far away from being cheap enough or idiot-proof enough to put in the hands of private owners.
Assuming Tesla sticks to it's guns, I'm thinking maybe in 2025 we can revisit that and see how far Tesla has come towards full autonomy.
During the Waymo vs. Uber trial Judge Alsup asked Waymo CEO John Krafcik if Tesla uses Lidar.
