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It is not "similar tech" at all. Yes, both approaches involve some machine learning (which is a huge field). But Cruise's approach is similar to Google/Uber's a
by argonaut 10y ago
It is not "similar tech" at all. Yes, both approaches involve some machine learning (which is a huge field). But Cruise's approach is similar to Google/Uber's approach in that it relies on LIDAR. I'd assume (but might be wrong) in that it also relies heavily on premapping, as does the Google/Uber approach.
Comma's approach was complete end-to-end learning with just a single camera (to give you some context, research problems involving two cameras are already considered distinct (but related) research problems from those involving one camera), which is an extremely different approach (the Google/Uber approach can be thought of as more "handcrafted"). From the deep learning researchers I know of there was heavy skepticism of Comma's approach. End to end learning makes for nice demos but is still an active research topic.
From what I can tell, Mobileeye is somewhere in between an end-to-end approach and a handcrafted approach, so I would guess Tesla is similar to Mobileeye on that spectrum.
- sedachv 10y agoThere are more details in this lecture Hotz gave at Berkeley this September: https://www.youtube.com/watch?v=Hxoke1lDJ9w https://www.youtube.com/watch?v=Hxoke1lDJ9w One of the things that seemed missing from the lecture when I watched it is how data was going to be collected for handling exceptional situations/collision avoidance. Hotz also glossed over the question in this interview from July: https://www.youtube.com/watch?v=2zy_07g2IrM#t=35m https://www.youtube.com/watch?v=2zy_07g2IrM#t=35m I suspect they ran into trouble with edge cases. Also suspicious is this job posting on their website right now: "Localization Lead Engineer DESCRIPTION We have over 50,000 miles of video data from cars, and will have millions by the end of the year. Looking for someone to build a SLAM algorithm capable of scaling to the world. Imagine an API that, given a picture, returns the exact location of the camera with cm accuracy. Build this REQUIREMENTS Strong math background. Ability to write concise, reliable, and readable code quickly. Github with stars is nice. Computer vision experience a plus. Basically someone who could have written https://github.com/mapillary/OpenSfM https://github.com/mapillary/OpenSfM or https://github.com/raulmur/ORB_SLAM2" https://github.com/raulmur/ORB_SLAM2" http://www.comma.ai/positions.html http://www.comma.ai/positions.html Hotz has been claiming that they would not need mapping and SLAM like Google's self-driving car. The whole "Looking for someone to build a SLAM algorithm capable of scaling to the world" sure sounds like "I guess this time he couldn't find anyone on IRC to finish the hard parts for him and let him take the credit" that lawnchair_larry posted elsewhere in this discussion (https://news.ycombinator.com/item?id=12818219 https://news.ycombinator.com/item?id=12818219).
- agumonkey 10y agoIs that IRC jab related to the PlayStation cryptosystem breaking ?
- deleted 10y ago[deleted]
- argonaut 10y agoYeah. Those are all really hard problems. Visual SLAM is far from solved, especially if since this is only monocular SLAM. And even if he did solve that to a pretty decent level (which is already multiple top-PhD theses worth of research), that would only get him to the point of where he would be is he had just mounted LIDAR on cars and said "now what?"
- nzjrs 10y ago> Looking for someone to build > a SLAM algorithm capable of > scaling to the world. This has got to be a joke. Text like this proves he was out of his depth