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Tesla AI Day [video]

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Re: Tesla AI Day [video]

#91

Post by lttlrck »

abc_lisper wrote: post #74
ModernMech wrote: post #30

Earlier quoted context omitted.

Yes. This is exactly what LIDAR is for. This is the reason every single team in the 2007 DARPA Urban challenge that finished the race was equipped with a Velodyne laser. We knew it was a critical enabling technology 14 years ago, and it baffles me Tesla is eschewing it. Tesla's lack of this technology is the main reason I feel they will never achieve what they claim to without a huge breakthrough in AI.

Idk.. animals seem to do fine without a lidar

If Tesla switches to stereoscopic vision with fully articulated cameras that can move independently of the vehicle (not fully independent, but limited 3 degrees of motion), and then they manage to integrate the output into something meaningful then maybe it would be comparable.

Re: Tesla AI Day [video]

#92

Post by pyinstallwoes »

TigeriusKirk wrote: post #87
jmportilla wrote: post #81

No one here talking about the freaking humanoid bot?!? Also interesting to see how focused they are still on pure vision input to construct the vector space instead of just using LIDAR, but I wonder how limited they are by existing models already being out there with set hardware.

I wonder if the focus on pure vision over lidar isn't related to the humanoid bot...

Of course it is. Elon has said that before. They use the human physics as a baseline of technology to mimic. If humans don't need lidar and can operate with vision, then they can do was the logic.

Re: Tesla AI Day [video]

#93

Post by ajross »

mdorazio wrote: post #51
rnaud wrote: post #36

Earlier quoted context omitted.

Too expensive + Your eyes already do the distance estimation and they are basically cameras so we can do this just as well or better.

> Your eyes already do the distance estimation and they are basically cameras so we can do this just as well or better. This is not really accurate. Our brains do the distance estimation, and they use all kinds of tricks and contextual clues to do it, not just parallax (~2.5 inch parallax for objects more than ~100ft away isn't all that helpful). And this is the whole problem with vision-only autonomous driving - ML…

> Our brains do the distance estimation, and they use all kinds of tricks and contextual clues to do it

So, first, this presentation we're talking about is literally about problems like that.

Second: your brain isn't nearly as good as you think it is, it's just constructing a coherent story to fool you into thinking it is. Try this on the highway sometime as a passenger: close your eyes and recite the distances to the vehicle in front of you and the one to either side. I bet you anything a Tesla is going to do that better.

Third: they pretty much cracked this already. They stopped shipping radar on US Model 3's and Y's in the spring, have shipped hundreds of thousands of them now, and there's not a hint of signal that something is off with distance measurements with the cars. My car doesn't get this perfectly (you can actually watch the animations on screen bounce around a bit as the estimates change) but I think it objectively does better than I do.

Distance/Lidar framing is old news, basically. Vision works fine. The worst bugs remaining with all the FSD Beta footage on Youtube are almost entirely pathing and planning issues. The car sees its environment just fine.

Re: Tesla AI Day [video]

#94

Post by karpierz »

joshuamorton wrote: post #76
karpierz wrote: post #44

Earlier quoted context omitted.

Suppose that you train a neural network to predict the next number in an arithmetic sequence (a, a+b, a+2b, a+3b, a+4b, ...). As input it gets two numbers, the last number and the current number and has to predict the next one. Suppose you had 1.4 trillion examples in the following test set (using a model with 175 billion parameters): (1,2)->3 (2,3)->4 (3,4)->5 ... Do you think it is possible to overfit and score per…

I think you've specified this problem in a very strange way. But if you're saying that you're trying to train on the specific dataset where a = 1 and b = 1, then your model will fit the data perfectly with 175 billion parameters. It will also fit the data perfectly with, like, 15 parameters. If you're trying to fit to some more complex space where a and b are unknown and you're given 3 numbers in the sequence, then w…

I didn't specify the training set, just the test set. It's possible that your model actually models an arithmetic series. Or that it simply overfits. The point is that it doesn't require trillions of parameters to overfit to a trillion-sized test set.

Re: Tesla AI Day [video]

#95

Post by ajross »

notdonspaulding wrote: post #85
ajross wrote: post #68

Earlier quoted context omitted.

> My example is contrived. Pretty much. I think if you're going to make an argument like "accidents by teenagers, senior citizens and drunks don't matter" you need to put some numbers behind that. I mean, if you had a teenager or a family member with a substance problem, would you feel safer with them in a Tesla? If so, then I really don't think I understand your point. Basically you're just saying that you, personal…

> And you (if you're being rational about it) want them in a Tesla Right. Rationally, we all want folks who are worse than the state-of-the-art FSD AI to be using FSD. But thinking that the "very low bar" that has to be cleared is drunk drivers misses the point that most drivers are not drunk . So it's much less impressive to a "safe" human driver to clear the low bar.

> But thinking that the "very low bar" that has to be cleared is drunk drivers

I said median, not drunk driver. Existing shipping autopilot is already saving DUI fatalities. This feels like a strawman to me...

Re: Tesla AI Day [video]

#96

Post by karpierz »

FeepingCreature wrote: post #56
karpierz wrote: post #44

Earlier quoted context omitted.

Suppose that you train a neural network to predict the next number in an arithmetic sequence (a, a+b, a+2b, a+3b, a+4b, ...). As input it gets two numbers, the last number and the current number and has to predict the next one. Suppose you had 1.4 trillion examples in the following test set (using a model with 175 billion parameters): (1,2)->3 (2,3)->4 (3,4)->5 ... Do you think it is possible to overfit and score per…

That isn't overfit, that's fit. Nothing can protect you if your training set just doesn't have any indication of the thing you want it to learn.

I didn't specify that the training set wasn't representative.

All this shows is that you don't need parameters anywhere close to the number of test examples to overfit.

Re: Tesla AI Day [video]

#98

Post by [deleted] »

tru3_power wrote: post #34
ModernMech wrote: post #30

Earlier quoted context omitted.

Yes. This is exactly what LIDAR is for. This is the reason every single team in the 2007 DARPA Urban challenge that finished the race was equipped with a Velodyne laser. We knew it was a critical enabling technology 14 years ago, and it baffles me Tesla is eschewing it. Tesla's lack of this technology is the main reason I feel they will never achieve what they claim to without a huge breakthrough in AI.

What was their reasoning for not using Lidar?

[deleted]

Re: Tesla AI Day [video]

#99

Post by cycrutchfield »

lttlrck wrote: post #91
abc_lisper wrote: post #74

Earlier quoted context omitted.

Idk.. animals seem to do fine without a lidar

If Tesla switches to stereoscopic vision with fully articulated cameras that can move independently of the vehicle (not fully independent, but limited 3 degrees of motion), and then they manage to integrate the output into something meaningful then maybe it would be comparable.

They already have multiple cameras; it's not clear why articulation of cameras would be required as they do not have foveas that require such articulation; they already do integrate the output of each camera into a view of the vehicle's surroundings.
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