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GM Exec Says Elon Musk's Self-Driving Car Claims Are 'Full of Crap' (smh.com.au)
An anonymous reader quotes the Sydney Morning Herald:
Billionaire entrepreneur Elon Musk's claims about the self-driving capabilities of his upcoming Tesla vehicles are "full of crap", General Motors' self-driving Tsar says... "To think you can see everything you need for a level five autonomous car [full self-driving] with cameras and radar, I don't know how you do that"... GM's own solution involves several radar and Lidar sensors, as well as cameras and multiple redundancy systems. Each system costs hundreds of thousands of dollars, and GM are some way away from getting the cost low enough to be commercially viable. "The level of technology and knowing what it takes to do the mission, to say you can be a full level five with just cameras and radars is not physically possible," Mr Miller said.
Also, as to answer the question of how humans do it with "two cameras": logic. We don't have "stitching errors" in how we build up a model of the world around us from visual data because our brain constantly processes everything around us through the prism of "does that make sense?" But whether something "makes sense" or not is an AI-hard problem.
Building up 3d models with photogrammetry is an inherently error-prone process because a computer doesn't know if something makes sense. The approach is "Oh hey, these patterns from the left and right camera matched up - there's an object there at X distance based on how far the patterns had to be shifted to align". But what if the patterns happen to be different things that just happened to match up in patterning? Or what if, due to lighting / texturing / obstruction / material issues, the same thing didn't look exactly the same from different angles? Uncovering these problems is, as mentioned, AI-hard. I doubt anyone is even trying at this point; there's enough to work on just to get things to follow road lines correctly and not go chasing old tire tracks or poorly erased construction lines.
Ranging systems like LIDAR help let you just simply ignore the issue by telling you flat out, "I sent out a beam in this precise direction and got a reflection in precisely this length of time." But LIDAR has a number of problems, as described above.
"If there was an antonym to 'Elon Musk', it would be 'Richard Branson'."
Microsoft demonstrates the transition from a startup, growth oriented company to a mature, profit oriented one.
Jobs, by the way, hardly counts as an inventor. Visionary, sure, but that's not the same thing at all.
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Jobs did have a genius for marketing, but that wasn't the only role he had in Apple's success. I'd boil his genius down to three factors: (1) timing; (2) and appreciation of the value of design; and (3) discipline.
Timing: As you point out, Jobs didn't create any products people hadn't tried to create before; but they were all premature. Jobs was good at recognizing when all the technological pieces (display, battery, processor, UI) had reached the point where you could create a successful product.
Design: Apple is as much a design company as it is a tech company. That was Jobs doing. He recognized that design was valuable and useful in itself, and built his company around groundbreaking design. But as with inventing, he was not a designer of products himself. That was guys like Jonathan Ive. Jobs own personal contributions to Apple designs were minimal, and questionable (e.g. the skeuomorphic brushed aluminum surfaces on some version of the Quicktime player).
Discipline: One of the first things Jobs did when he returned to Apple was cut down Apple's broad and confusing product offerings, both simplifying marketing and the manufacturing process. This was a hallmark of his decision making process: not doing things that on paper looked reasonable but which collectively imposed a death-of-a-thousand-cuts on its manufacturing, design and marketing efforts.
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According to Google (who's a big LIDAR proponent), it's still $7,5k per unit. It still messes up your aerodynamics and looks dorky. It still can't see in adverse weather conditions, meaning you have to have developed an optical / radar based world-modeling system anyway. And you have to have image processing regardless to read signs, road lines, identify objects, see brake lights, and so forth.
There's real hope for further improvements in LIDAR and its variants in the future, however. We'll see where it goes.
Good lidar systems see much, much better than camera based systems in adverse weather. I work on FMCW lidar systems and I recall driving to work one day where the fog was so bad that I couldn't even find the road to my office. Once I got work, I turned on the lidar system I was working on and it imaged a building 100 meters away without issue. Road lines are trivial to identify in a lidar system since they have much different reflectivity than the road surface. Objects are also easier to identify because you aren't trying to pull three dimensional information out of two dimensional images. On an FMCW lidar system, you also get doppler information for free. You don't have to try and decide if an object is moving towards or away from you by comparing subsequent images. Every single point in the point cloud includes a meters/second doppler value.
I have to assume your familiarity is with those awful spinning Velodyne systems. They are utter garbage. No self driving car company that I've interacted with is even vaguely entertaining the idea of using them in a production car. They don't even really like using them in their mule cars but, until very recently, they were the only real option available.
The real problem with lidar is that people aren't good at consuming lidar data yet. Once they start to get some experience with it, I have zero doubt that lidar will be the primary sensor on the car. It's the only way you can really build a model of your surroundings with high accuracy, high refresh rate and high tolerance to ambient conditions. So, I actually agree with the GM guy here: Tesla is full of shit. They aren't going to make a level 5 autonomous car with cameras and radar.
That was surprising so I did some research and it is true.
For women. Deaf women have similar accident and ticket rates when checked.
But not for men.
https://cms.fmcsa.dot.gov/site...
D. Summary
" The well-designed study of deaf automobile drivers by Coppin and Peck in California
found that deaf men had 70% more road crashes than non-deaf men."
Not sure why there is a gender difference and the area needs more formal study.
But in 35 years of driving- I have seen accidents avoided due to sound queues many, many times. There is a reason there is a horn on vehicles.
But i agree- it looks like the current data shows female deaf drivers have similar driving records to the general female population.
She was like chocolate when she drank... semi-sweet at first and then increasingly bitter.