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Even after $100B, self-driving cars are going nowhere

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Re: Even after $100B, self-driving cars are going nowhere

#431

Post by dionidium »

grandmczeb wrote: post #335
dionidium wrote: post #291

Earlier quoted context omitted.

> 1.3 million deaths worldwide, annually (94% cause by human error) You don't need full autonomy to mostly fix this, but the fixes are politically untenable (currently). The cars should be speed-governed, they should be speed-limit aware -- the car should routinely be overriding the desire of the driver. No, you can't go into the bike lane to get around traffic. No, you can't make the split-second decision to swerve…

In the real world political tenability matters a lot, so I don’t really think ”fixes” that ignore it are very interesting to discuss. But if we’re already assuming politics doesn’t matter there’s a much more effective solution: ban cars entirely.

I'm not so hopeless as this. Seatbelts, speed limits, and drunk driving laws were similarly unpopular. That opposition was overcome primarily, I think, because it's so stupid, in the end, and the argument for those things is so compelling that it can't be ignored forever.

We will find ourselves in the same position with speed regulators, etc. Once some country does it, the reduction in lives lost will be impossible to ignore.

Re: Even after $100B, self-driving cars are going nowhere

#432

Post by dolni »

binarymax wrote: post #325
adgjlsfhk1 wrote: post #311

Earlier quoted context omitted.

The counterargument to this is that since humans reach acceptable safety levels with vision only, it must be possible to do self driving with vision only. That said, augmenting vision with other methods does seem like a no brainer for better performance.

We have a lot more signal than vision only. For example audio, the “feel of the road”, like feedback on the steering wheel and traction that we physically experience. Most of all we have actual intelligence and reasoning - not just pattern recognition.

Do you drive much? It would be QUITE the stretch to say most drivers have "actual intelligence and reasoning."

Pattern matching for driving is probably better, frankly. You don't have people who are stressed out, pissed off, inattentive or in a hurry doing risky stuff on the road.

Re: Even after $100B, self-driving cars are going nowhere

#433

Post by D13Fd »

Fiahil wrote: post #306
D13Fd wrote: post #200

Earlier quoted context omitted.

That’s really not true. Americans love good public transportation where it’s available and works well. Most US cities have lots of buses, and many have light rail. But in a big country with a spread-out population, public transportation is tough. American corporations perhaps aren’t as interested in public transportation, because there is no money to be made. And that is who is largely funding this self-driving vehic…

> Americans love good public transportation […] Most US cities have lots of buses So… Apparently not… The USA is probably the worst place in the world for 1) high speed trains 2) buses. And the only place I know where the train _waits_ for cars to go through. If only they could see by themselves how bad it is during their next trip to Switzerland, the Netherlands, Japan, London, Paris (even France in general) and man…

I said they love it, not that they have it. Big difference.

Re: Even after $100B, self-driving cars are going nowhere

#434

Post by ben_w »

nuker wrote: post #410
ben_w wrote: post #403

Earlier quoted context omitted.

Even ignoring that "AI" is generally accepted as a term of art: What do you mean by "reasoning", such that there is no example of a ML system that does this?

Nope, not one. And not on any car for sure. https://en.m.wikipedia.org/wiki/Automated_reasoning From actual AI wiki article: “highly mathematical-statistical machine learning has dominated the field”. This will never be able to drive as good as humans.

None of what you have written answers my question (my question wasn't a yes/no one), your quotation isn't in the link, the link is full of examples of things which constitute automated reasoning, and there's no reason for me to doubt the possibility of ML ever achieving what is currently being done by the large number of tiny warm bags of chemicals that is an organic brain.

Re: Even after $100B, self-driving cars are going nowhere

#435

Post by flutas »

flutas wrote: post #382
nichochar wrote: post #283

Earlier quoted context omitted.

[Disclaimer] I worked for Cruise for 4 years. I agree with everything you said, but chuckled at this particular part (which is very wrong): > Tesla is significantly ahead of everyone else. Everyone in the industry knows that Tesla is nowhere near the tip of the technology. What Tesla does is _fantastic marketing_. Their whole self-driving division is just a mechanism to sell more cars. At a high level, this is why: -…

My favorite case so far of the '5%' that you mention happened on my Tesla irt:(object recognition) and I still laugh about it to this day. I was driving down the road as normal, 4 lane divided highway that's a bit hilly. Suddenly my car starts having what I can only describe as a panic attack saying I'm running a stop sign and blaring alarms. It was detecting a giant 40ft tall red circle sign a bit away as a stop sig…

Replying to my own comment because I just remembered this as well...

I definitely saw a case of them overfitting their neural networks lately.

Going over a single lane bridge that's an exit ramp, the car started decoding the "other side" of the concrete barrier as oncoming traffic lanes...when there was nothing there.

Re: Even after $100B, self-driving cars are going nowhere

#436

Post by tim333 »

daydream wrote: post #321
adgjlsfhk1 wrote: post #311

Earlier quoted context omitted.

The counterargument to this is that since humans reach acceptable safety levels with vision only, it must be possible to do self driving with vision only. That said, augmenting vision with other methods does seem like a no brainer for better performance.

The counterargument to THAT is that human safety levels aren’t acceptable. They are tolerable perhaps, but I wouldn’t call the number of accidents and fatalities we have today acceptable.

Though human accidents are seldom due to the inherent limitations of vision.

Re: Even after $100B, self-driving cars are going nowhere

#437

Post by camgunz »

dolni wrote: post #432
binarymax wrote: post #325

Earlier quoted context omitted.

We have a lot more signal than vision only. For example audio, the “feel of the road”, like feedback on the steering wheel and traction that we physically experience. Most of all we have actual intelligence and reasoning - not just pattern recognition.

Do you drive much? It would be QUITE the stretch to say most drivers have "actual intelligence and reasoning." Pattern matching for driving is probably better, frankly. You don't have people who are stressed out, pissed off, inattentive or in a hurry doing risky stuff on the road.

Like all drivers I also hate other drivers, but "actual intelligence and reasoning" means "I can tell that person is gonna try and cross the street" or "I can tell that's a picture of a bicycle instead of an actual bicycle". This stuff is hard just by vision alone--humans use a lot of context to reach these conclusions (bicycles don't float, they don't hang out on the side of advertising boards, they aren't 30 ft. tall) that computer vision machines don't have.

Re: Even after $100B, self-driving cars are going nowhere

#438

Post by dontreact »

cs702 wrote: post #241
dontreact wrote: post #232

Earlier quoted context omitted.

I'd sum up your points 1,2,3 as "more data". This would be a reason to think they can one day be ahead if they can take advantage of this, but not evidence that they are currently ahead. Occupancy networks: waymo has published research on this before Tesla announced this at AI day (not clear to me who got there first though https://arxiv.org/pdf/2203.03875v1.pdf ) Tesla's Dojo -> Waymo has TPUs to train on To me all…

> I'd sum up your points 1,2,3 as "more data". This would be a reason to think they can one day be ahead if they can take advantage of this, but not evidence that they are currently ahead. I'd sum up those three points as "more data and more real-world, open-ended, large-scale testing by regular people." Big difference. > Occupancy networks: waymo has published research on this before Tesla announced this at AI day (…

TPUs are hard to use outside of Google, (I have tried in and out of Google). I think the situation is improving, but the efficiency from using a large pod is really remarkable. What topology did you train AI models on? Within Google it's common to train across a whole pod or even across multiple pods 8x16x16 is the largest currently.

Also if Tesla actually published numbers on an MlPerf benchmark, I would be more inclined to believe claims about 36x better efficiency.

https://mlcommons.org/en/training-normal-20/

The fastest times I'm seeing here for image classification and for object detection (not the same, but probably closest proxy out of the tasks benchmarked) are for TPUs.

To know who has better training technology I don't think you should be using a cost-efficiency metric, it seems to me the best thing to use would be who can train networks the fastest. Cost metrics are easy to game especially if you are the ones making the chips (Of course them making chips is cheaper than buying Nvidia chips for them once the capital investment is made). To measure who is ahead in technology, I think you have to look at who can train models the fastest, and right now as far as I can tell, TPUs are unbeat for this. (Although practically speaking it's hard to pull off these large topology things externally and there are also other caveats with ML perf related to how the training setups are optimized, but nonetheless, it's a better signal than what Elon says in a presentation :) )

Re: Even after $100B, self-driving cars are going nowhere

#439

Post by dontreact »

cs702 wrote: post #241
dontreact wrote: post #232

Earlier quoted context omitted.

I'd sum up your points 1,2,3 as "more data". This would be a reason to think they can one day be ahead if they can take advantage of this, but not evidence that they are currently ahead. Occupancy networks: waymo has published research on this before Tesla announced this at AI day (not clear to me who got there first though https://arxiv.org/pdf/2203.03875v1.pdf ) Tesla's Dojo -> Waymo has TPUs to train on To me all…

> I'd sum up your points 1,2,3 as "more data". This would be a reason to think they can one day be ahead if they can take advantage of this, but not evidence that they are currently ahead. I'd sum up those three points as "more data and more real-world, open-ended, large-scale testing by regular people." Big difference. > Occupancy networks: waymo has published research on this before Tesla announced this at AI day (…

And as far as safety scores, my point is that the safety score is calculated incorrectly because of obvious false positives with "close following". I'm talking being nowhere near a car, getting an alert that says I'm following too close, and that dropping my safety score. I understand why the bar is high, but at this point I honestly suspect there is some tomfoolery going on with how that score is calculated.

Re: Even after $100B, self-driving cars are going nowhere

#440

Post by GekkePrutser »

tttttt5ts wrote: post #369
GekkePrutser wrote: post #367

I think it would go significantly better if we make roads for self-driving cars. Right now cars are trying to drive like a human. Based on the same cues and road markings, signs etc. What if we started embedding road signs with radio beacons. Cars with transponders like aircraft have. Road markings in a digital way that's easier to follow for a machine. We could start with some lanes dedicated to automated traffic. I…

Why not just invest in public transport instead? To date all cars with any self driving tech are expensive and only available to the wealthy.

Good point. I have not even driven a car in the last 3 years myself.

I do think in some areas this will not be feasible. But these are also probably the very last areas to consider when building smart car infrastructure.

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