I'm just curious if it does make them way ahead, and if so how much more ahead? Is this driving a car vs horse wagon levels?
It's obviously got some benefits, and I think most people in ML would agree that real world data from the "average person" (as in "not a Dev or paid to do this") is worlds better than simulations.
Still, "ahead" and "behind" isn't really a thing before you reach the finish line here. Many think Tesla will never reach full self driving or won't reach it without additional sensors, others think it's possible but decades or more away, still others think it's right around the corner and can be done with what is on a Tesla right now.
Until someone reaches that finish line, we won't have anything to compare it to, so we don't have any idea how close or far anyone really is.
The last minute of video before each crash would probably be more useful. Training on dashcam data of people doing stupid stuff from Youtube might be useful. You don't need steering, braking, and accel data; you can run a 3D SLAM algorithm to extract the path and get that.
In truth there are only 3 self driving products that I know of available today. Tesla's Autopilot, GM's Supercruise (only on CT6), and commma.ai's openpilot.
Of those Autopilot is easily the best.
I never know why a source would matter in these cases as the writers of these sources usually have no idea and the answer isn't clear anyways. But if you want you can use me as a source because I'm an engineer who worked in automotive and has driven all 3 of aforementiond products. I also am not sure Waymo will ever release a feasible product other than their LIDAR.
Yup. Carmack illustrated this very well in his interviews when he would not talk about unreleased games vs. Doom/Quake/whatever. He always said: "It's really easy to be the best graphics engine when it isn't available to the public."
I suppose I used the wrong word. Any expert or well-informed opinion is what I was after.
They are also completely different approaches, i.e. Waymo using LIDAR and Tesla relying on cameras as the primary sensor.
But the major question is can LIDAR _ever_ be financially feasible, and if so can it become feasible faster than camera gets good enough at vision. Right now the sensors on the Waymo van probably cost more than the van itself.
That's either a very expensive purchase for the consumer or a very large amount of cap-ex Waymo would have to put up for a fleet of self-driving taxis.
And if it turns out cameras were the right choice, or visa versa, that means the opposite company would have spent a LOT of their R&D funding on the wrong tech, and would be way behind.
Even discounting aesthetics, Tesla couldn't have bolted it on to every car sold in the hope that it'll work in a few years time. They'd be bankrupt by now. They were forced to use cameras if they wanted any intermediate progress.
I get that there's a lot of misinformation about Tesla and you're trying to correct it. Even as a Tesla bear I acknowledge that.
But don't do it by creating further misinformation about competitors. You're just adding to the noise.
These are not levels where it makes sense to question if it will "ever" be financially viable. It's less than the premium people paid gladly for a Model S.
A true level 3 on consumer cars would sell like hotcakes.
Not only that, but by using cheap hardware that consumers can reasonably afford, they really only need to get to level 3 (eyes off so you can work/entertain but driver still in the seat) for it to be massively beneficial for everyone who commutes to work.
Waymo pretty much requires level 4 as it's too expensive to be sold as a consumer car and nobody will be in a taxi when it is driving between customers.