| ▲ | nlitened 2 hours ago |
| As I understand, lidars don't work well in rain/snow/fog. So in the real world, where you have limited resources (research and production investment, people talent, AI training time and dataset breadth, power consumption) that you could redistribute between two systems (vision and lidar), but one of the systems would contradict the other in dangerous driving conditions — it's smarter to just max out vision and ignore lidar altogether. |
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| ▲ | zozbot234 an hour ago | parent | next [-] |
| Why does this matter? You have to slow down in rain/snow/fog anyway, so only having cameras available doesn't hurt you all that much. But then in clear weather lidar can only help. |
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| ▲ | nlitened 34 minutes ago | parent [-] | | If your vision is good enough to drive in rain/snow/fog, you don't need lidar in clear conditions. If you planned to spend $10B on vision and $10B on lidar — you would be better off spending $20B on better vision. | | |
| ▲ | tw04 7 minutes ago | parent [-] | | We have actual proof this isn’t true. Waymo is light years ahead of Tesla despite spending less. Tesla is spending upwards of $6B/year to Waymo’s $1.5B. Only one of these companies makes an autonomous robotaxi that’s actually autonomous. |
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| ▲ | RobotToaster an hour ago | parent | prev | next [-] |
| > lidars don't work well in rain/snow/fog. Neither do cameras, or eyeballs. |
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| ▲ | dsr_ 44 minutes ago | parent [-] | | When it's not safe to drive, it's not safe to drive. I've been in zero-road-speed whiteout conditions several times. The only move to make is to the side of the road without getting stuck, and turning on your flashers. Low-light cameras would not have worked. Sonar would not have worked. Infrared would not have worked. | | |
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| ▲ | zemvpferreira 2 hours ago | parent | prev | next [-] |
| Limited resources? Billions per year are being thrown at the base technology. We have the capital deployed to exhaust every path ten times over. |
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| ▲ | nlitened 33 minutes ago | parent [-] | | Even if so, it doesn't mean that capital deployment efficiency and expected payoff make equal sense in all directions. Then again, it's good that we have self-driving companies with lidar and without — we will find out which approach wins. |
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| ▲ | heisenbit 2 hours ago | parent | prev | next [-] |
| The Swiss cheese model would like to disagree. |
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| ▲ | idiotsecant an hour ago | parent | prev [-] |
| This is silly. Cameras are cheap. Have both. Sensors that sense differently in different conditions is not an exotic new problem. The kalman filter has existed for about a billion years and machine learning filters do an even better job. |
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| ▲ | nlitened 30 minutes ago | parent [-] | | Cameras are cheap, but, as I understand: 1) it's not cheap to produce lidars at a stable predictable quality in millions; 2) car driving training data sets for lidars are much scarcer (and will always be much scarcer due to cameras' higher prevalence) and at a much lower quality; 3) combined camera+lidar data sets are even scarcer. |
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