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The hypothesis was that LIDAR was a crutch, humans manage with just vision. Whether this is correct for delivering self driving cars, we will find out soon eno
by fooker 2y ago
The hypothesis was that LIDAR was a crutch, humans manage with just vision.
Whether this is correct for delivering self driving cars, we will find out soon enough. Long term though, it definitely makes sense. We just don't know what the missing pieces of the puzzle are.
- seanhunter 2y ago> humans manage with just vision this is commonly repeated but very obviously untrue. We don't only have vision. We have a general intelligence, coupled with vision. In the absence of AGI, the base assumption has to be the sensor apparatus needs to be significantly superior to humans for an FSD system to drive at a comparable level.
- vel0city 2y agoNot to mention it is also untrue because we use senses other than just vision when we drive. We use our ears for acceleration information, sometimes hearing, and the feeling of the wheel when we drive.
- fooker 2y agoWe don't have anything close to LIDAR though
- seanhunter 2y agoAnd a car doesn't have anything close to a human brain. Humans process sensory data in a fundamentally different way to anything that's possible for a self-driving car. The idea that we should base the decision about the sensors on what humans have just fundamentally makes no sense. Lidar substitutes hardware for something which humans find easy and CV systems find hard - creating a map of the environment. Humans do that by using a brain. CV systems based purely on video really struggle to do that in lots of edge cases. You can shortcut that in a car by using something like lidar.
- fooker 2y agoYou are right. Would you agree then, that if the goal was to develop AGI, just relying on vision is a credible choice?
- seanhunter 2y agoNo. Why should the design parameters for AGI be limited by what a human can do? If the goal was AGI then I'd want all kinds of additional sensor input that humans don't have.
- fooker 2y agoOnce it's a solved problem, yes, it makes sense to think about design parameters. When learning how to solve problems, that is not as helpful.
- Zenzero 2y ago> humans manage with just vision. But they don't. I can't see how anyone could look at modern driving and see an optimal state. Driving isn't being managed at all, it's killing droves of humans. If we put the same restrictions on airplanes (flying by instrument is a crutch), everyone would rightfully find that ridiculous. They appear to have bet on the wrong technology. The failure happened back in the design phase.
- fooker 2y agoAircrafts often don't have vision at all, in regular operation. If a driver doesn't have vision, the right decision is to figure out how to safely stop.
- have_faith 2y agoHuman vision has a dynamic range of roughly ~21 stops, plus other differences, do we have any cameras that come close to the human eyes "specs"?
- fooker 2y agoYes. https://www.cined.com/canon-claims-to-have-developed-a-sensor-with-24-stops-of-dynamic-range/ https://www.cined.com/canon-claims-to-have-developed-a-senso...
- beaglesss 2y agoThe missing piece may be a different mode of transport like trains. Humans adapted from creatures that lived in trees over millions of years, a computer has nothing on that evolutionary process of the bad tree jumper getting eaten or breaking a leg and dying. Spend a few million years programming a computer to swing through trees and they'll probably get something that can drive a car.
- fooker 2y agoWe have close to that much in training data in the form of cars driven by humans. What we lack is (still) the fundamental algorithms to learn from video. Tokenization like LLMs or diffusion are starting to fall short of this goal.
- drcongo 2y agoThe missing piece is LIDAR.
- fooker 2y agoGreat, I hope I can someday be this confident about predicting the future!