[adastra22]

Removing LIDAR was the eye-opening moment for me re: Musk. The justification given at the time was technically bogus while it was so obviously in response to supply issues during COVID. If Tesla really wanted safe FSD they would prioritize sensor quality and multimodal input. They went for the bottom line instead.

[bryanlarsen]

Tesla's never had LIDAR to remove. They had short distance ultrasonic parking sensors that they removed.

[tzs]

They also had and then removed radar.

[adastra22]

Thank you, I think I’m conflating the radar that was present with his staunch anti-LIDAR stance. You can s/LIDAR/radar/ in my original comment.

[_giorgio_]

Not true, they had lidar in at least one model. It's written in his bio too.

[bryanlarsen]

They had lidar on some models they were using for internal testing, but they never sold them.

[_giorgio_]

No, they were production models.

[FireBeyond]

And now he's peddling more horseshit and expecting the public and investors to swallow it:

> One analyst asked about the reliability of Tesla’s cameras when confronting sun glare, fog, or dust. Musk claimed that the company’s vision system bypasses image processing and instead uses direct photon counting to account for “noise” like glare or dust.

I call bullshit. Photon counting requires specialized cameras that are simply not present on Teslas. Not to mention lab conditions (so you can direct photons at your sensor, versus you know, scattering into the atmosphere...) And that don't do anywhere near as well at regular image processing, for that reason.

But Musk thinks you're not smart enough to know this.

[queenkjuul]

So much of the stuff he's said about rockets is designed the same way, to sound smart to people who don't know any better.

Surely photon detection wouldn't be cheaper than LIDAR, given it's impossible to mount to a car lol

[adastra22]

The innovative stuff SpaceX has done is actually smart. I can't speak to anything else that Elon is working on, but he is actually a competent rocket engineer.

[Joel_Mckay]

Many LIDARs are blinded by direct Sunlight, and often see highly reflective surfaces like mirrors as black hole or distant ranged areas. These still need tertiary safety sensors like mm RADAR for safety in dust/rain/sunlight.

In cities, high-speed rail and e-bikes make more sense than a honking traffic jam at 4am. lol =3

[kamranjon]

The part that I always found difficult to square was not that Elon Musk towed this “no need for LiDAR” line so hard, but that Andrej Karpathy, who I generally consider a very reliable voice in this space, was also in strong agreement that cameras were all that was needed. Does anyone know if he still believes cameras is all you need?

Edit: Here is a link to Karpathy discussing the trade-offs: https://www.youtube.com/watch?v=cdiD-9MMpb0&t=5276s

[chronic0262]

> but that Andrej Karpathy, who I generally consider a very reliable voice in this space, was also in strong agreement that cameras were all that was needed.

You really expect a Tesla employee to speak out against Elon?

Especially when $10M+ TC is on the line?

[rumblefrog]

But Andrej is no longer with Tesla?

[sgt101]

Andrej "train it on more data and the problem will go away" Karpathy

[Grimblewald]

Right? Im not arguing against the skills he obviously has, but if we're always just piece wise approximating the underlying manifold, then there will always be new problems. The amount of data required to reliably approxate reality, in the absence of an inductive bias, is infeasible to expect to collect. Not to mention how computationally inefficient it becomes as your model blows out in size/complexity.

[sgt101]

I guess the gamble was that there would be a certain point where the edge cases disappeared into the noise and it didn't matter that the approximation was/is "wrong" because the behavior of the car would match the requirements of the situation even if it wasn't for the right reasons.

To be fair I remember reading about GPT2 and thinking that LLMs would blow out for similar reasons.

[adastra22]

Which they more or less have. Larger models are seeing negligible returns. It just turned out that scaling would hold out just enough longer to make LLMs generally useful.

[Grimblewald]

Yup, and if you normalise "improvements vs time" graphs to not linear time but gpu hours invested per unit improvement we're in extremely incremental/small improvement territory as of a year ago. There are no major jumps coming. There are no more gpu hours to allocate to dumping onto this partciular bonfire to keep things looking like exponential improvement, all to keep that vc cash flowing.

[satyrun]

Isn't it ultimately a cost trade off? I mean I can't see a valid argument against LiDAR and cameras if the cost of the vehicle is no concern.

If building a mass market product though the cost is a big deal.

I would assume LiDAR is much more expensive so it would be a big win to get the same performance out of cameras in the long run. I have always just assumed that was the bet.