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Andrej Karpathy (Tesla): CVPR 2021 Workshop on Autonomous Vehicles [video]

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Re: Andrej Karpathy (Tesla): CVPR 2021 Workshop on Autonomous Vehicles [video]

#101

Tesla's decision not to use the LIDAR as a safety feature (i.e. having reliable high-resolution data about things the car can collide with) is so incredibly indefensible, since solving the last 1% of this using only vision likely requires a general artificial intelligence Prediction: Tesla will be the last of all major auto manufacturers to get to L5 autonomy. Time interval between when Tesla L5 FSD is finally availa…

Waymo etc do not use LIDAR for object sensing, only for positioning. LIDAR sucks for object sensing because it gives you no information about whether it's a plastic bag or a person — you still need vision for that. Even if you just err on the safe side and brake, that itself can cause an accident unecessarily.

Re: Andrej Karpathy (Tesla): CVPR 2021 Workshop on Autonomous Vehicles [video]

#102
What an annoying charlatan. Karpathy is a brilliant computer vision engineer, but he has let his expertise in that subfield cloud his judgement on achieving the overall goal of autonomous driving.

Musk and Karpathy have been dead wrong about LIDAR for years. Remember Musk making the absurd claim of a million Tesla robotaxis by 2020? I think most hilarious is that both Karpathy and Musk claim the LIDAR systems are too expensive. Yet, in the same 2019 Autonomy Day they simultaneously claimed that Teslas would be able to drive themselves and operate as robotaxis, earning their owners passive income and therefore justifying significantly increased MSRPs. So, the $7k LIDAR system (that accelerates safe autonomous driving) is not worth the cost, yet stumbling towards autonomy on vision only is? If the car becomes an money-earner, you should use all of the systems available. The 2019 Autonomy Day was an utter embarrassment. I'm sure 2021 will be more of the same.

So now it seems that they've realized their folly in logic. So what's the solution? Well, you can't just complain about COST of non-vision perception systems. Because, as noted above, that doesn't make sense if you're going to simultaneously claim that your car will be able to earn you money (augmenting any extra hardware cost that gets you to that point faster). No, now you have to smear all non-vision perception systems. You have to say that their data is worthless and detrimental to the overall effort.

The entire claim from the 2019 Autonomy Day that "vision is what humans use to drive" is also completely bogus. Humans use many senses to drive. They feel the pedals and steering wheel. They use their equilibrio sense to sense motion. And they use their hearing to hear other vehicles, sirens, and issues with their own car (driving with headphones in is illegal for a reason). Any modern car, even a Tesla, is also using far more than just vision when attempting autonomy. Forget about radar and LIDAR for a moment. There are endless sensors in the drivetrain. Steering angle sensors and multiple IMUs for the electronic stability control. Brake and wheel sensors for the ABS. Temperature sensors everywhere. And countless other ECUs. The notion that vision is getting you there exclusively is nonsense. There's no good argument against LIDAR today other than perpetuating a lie to sell cars that are cheaper to produce. And, Karpathy has a massive professional conflict of interest in making CV the main player -- he's a CV expert. He was never a fusion expert before his hire. If CV is the pathway forward, he's gets to remain "the guy". It certainly behooves HIM to make that claim.

Autonomous driving will not be achieved in this decade. Perhaps ever. Ask yourself honestly: if you were tasked with building an autonomous commercial aircraft OR an autonomous car, which would you choose? Most would say aircraft -- nothing to really hit in the air, fully mapped airport and runway systems, and far fewer variables. Yet autonomous aircraft still do not exist. Perhaps the edge cases always rule the roost. Ask yourself why driving would be any different...

Re: Andrej Karpathy (Tesla): CVPR 2021 Workshop on Autonomous Vehicles [video]

#103
post #81
post #46

Earlier quoted context omitted.

I predict the opposite. Tesla sold half a million cars last year and will sell nearly one million this year. The data they have access to is increasing by orders of magnitude. I bet there is a point, let's say 20 million cars total, where they can pull so much high quality data that they will be able to surpass lidar capabilities for the purposes of self driving. The lidar/no lidar discussion is a fun one because peo…

> The data they have access to is increasing by orders of magnitude. You can only go so far by dumping more data into it. Diminishing returns.

We are chasing the 9s... diminishing returns are still returns. If 10x the data improves from 99.999 to 99.9995, that is still progress. Maybe 100x data gets you to 99.9999.

Re: Andrej Karpathy (Tesla): CVPR 2021 Workshop on Autonomous Vehicles [video]

#104
post #7
post #4

Earlier quoted context omitted.

Thanks! Maybe it's best if we change the URL to that from https://twitter.com/vpj/status/1407000737423368197 .

That video is a screen capture from another video (which was screen capped from a livestream), but the original has much better audio quality. Here's a direct link: https://www.youtube.com/watch?v=eOL_rCK59ZI&t=28293s

Ok, I've switched to that link above (from https://www.youtube.com/watch?v=NSDTZQdo6H8). Thanks!

Re: Andrej Karpathy (Tesla): CVPR 2021 Workshop on Autonomous Vehicles [video]

#105
post #44

Earlier quoted context omitted.

You get sparse point cloud from LIDAR sensors, not accurate 3D maps. This is the main reason why some people think LIDAR may not work well (mostly, only comma.ai and Tesla folks). Vision can also get you 3D maps, either in active manner (IR floodlight or structured lighting) or not. I will reserve my judgement until see more from either side.

This framing is a common error in the debate. It's not cameras or lidar, it's cameras or cameras + lidar + radar. Nobody is driving on lidar alone. Many others actually have more cameras and are doing substantially more vision than Tesla is, they're just fusing lidar and radar perception with their vision pipeline. It gives you a more robust view of the world than using a single sensor modality.

If you have one piece of rotten meat in a perfect stew, you still have a disgusting dish. Good sensor fused with garbage in is still garbage in. That was one of the major points of the talk - the vision-only system is more accurate than the one with other modalities thrown in, even though the latter has more data. We intuit that the fusion network should just learn to ignore the bad sensor when it's unreliable, but this rarely happens in practice.

If anything, knowing when to reliably ignore a sensor modality is the kind of intuition more associated with general AI.

A similar paradox occurs when trying to fuse multispectral imagery. You'd think early fusion of RGB and IR would be better since it gives the higher-resolution filters access to more data, but it does worse than late fusion. My understanding is that late fusion forces the network to "work harder" to solve object detection using IR only, and then once you've wrung what you can out, then you fuse with RGB detections.

Since radar is "one pixel" there's essentially only one object detector possible: object or nothing. If yes-object, fusion tries really hard to make sense of the RGB filters to figure out what partial detection looks like an object, which is almost always a false positive.

Re: Andrej Karpathy (Tesla): CVPR 2021 Workshop on Autonomous Vehicles [video]

#107
post #90

Earlier quoted context omitted.

There is a lot of that on HN whenever Tesla is the subject.

If Elon was any good at keeping his word it wouldn’t be an issue.

Please don't perpetuate tedious flamewars.

Re: Andrej Karpathy (Tesla): CVPR 2021 Workshop on Autonomous Vehicles [video]

#108

Tesla's decision not to use the LIDAR as a safety feature (i.e. having reliable high-resolution data about things the car can collide with) is so incredibly indefensible, since solving the last 1% of this using only vision likely requires a general artificial intelligence Prediction: Tesla will be the last of all major auto manufacturers to get to L5 autonomy. Time interval between when Tesla L5 FSD is finally availa…

Why do you think the last 1% is dependent on LIDAR versus any of the other multitude of gaps between today’s autonomy and L5?

If the only way it becomes practical to achieve L5 is to use LIDAR, Tesla can obviously add it. But if they waited until LIDAR was cheap and practical, they still wouldn’t be shipping any hardware doing autonomy today, and not collecting the data needed to train their models and delivering value today.

Also, with vision based systems, it operates in somewhat an intuitive fashion given we have eyes too.

Re: Andrej Karpathy (Tesla): CVPR 2021 Workshop on Autonomous Vehicles [video]

#109

Tesla's decision not to use the LIDAR as a safety feature (i.e. having reliable high-resolution data about things the car can collide with) is so incredibly indefensible, since solving the last 1% of this using only vision likely requires a general artificial intelligence Prediction: Tesla will be the last of all major auto manufacturers to get to L5 autonomy. Time interval between when Tesla L5 FSD is finally availa…

Waymo etc do not use LIDAR for object sensing, only for positioning. LIDAR sucks for object sensing because it gives you no information about whether it's a plastic bag or a person — you still need vision for that. Even if you just err on the safe side and brake, that itself can cause an accident unecessarily.

You're wrong on that. LIDAR is used for object detection in every self driving car company that uses LIDAR. There's tons of research on it.

Previous generations of LIDAR were not great at classifying small objects and road debris but it works great for detecting cars, pedestrians, etc.

https://paperswithcode.com/task/3d-object-detection

Next-gen LIDAR has great density, and I bet it would do a decent job differentiating between a plastic bag or a rock in the middle of the road. In addition to depth LIDAR also returns intensity and several other metrics, which can be used as input to an ML model. It's why you can read the lettering on the side of the semi truck in this video of Waymo's next-gen LIDAR.

https://youtu.be/COgEQuqTAug?t=11601

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