There 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=Hxoke1l

There 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).