Rarely is a driver having to take over from the car because of a problem that radar, or lidar, or stereovision would solve. Despite what you may read on the Internet, it’s not primarily a sensor issue! It’s a judgment issue! Watch a bunch of the YouTube videos and you’ll see what I’m talking about. Is current AI technology up to the task? Nobody knows… Although everyone is betting tens of billions of dollars on it. That’ll require a thousand-to-ten-thousand improvement in software reliability before I’m going to trust it with my life. (Oh sure, I’d love to have a car that would take me from my house to, say, Santa Cruz all by itself and even let me nap, if I so desired. ![]() To get to any useful level of autonomy the car has to do a whole lot better than that! What would I consider useful? Well, if I could ignore the car from the time I get on Interstate 280 in Daly City until I transfer from I 85 to Highway 17, I would be very happy! That’s 50-60 minutes of time I could spend reading, or writing, or whatever. Depending upon where I’m driving, I have to wrest control away from Autopilot (lest it crash my car) once every 30 to 500 miles. That is, you don’t have to pay CONSTANT attention to drive safely, but you do have to pay very frequent attention, because the car will make mistakes. Tesla’s current Autopilot, which is probably the best commercially available system, barely hits a low Level III on the autonomy scale. ![]() Machine learning can be utterly amazing.īut… to achieve some real level of automotive autonomy, it’s going to have to be. Algorithms for doing synthetic microscopy or holographic rendering that run a thousand to a million times faster than anything a human being ever came up with. In areas of scientific imaging and image construction, the results have been, on occasion, even more unbelievable. (That’s an important point, and I’ll get back to it.) There are times when I honestly can’t tell if the programs are simply making shit up, because it is such utterly convincing shit. The results they produce are sometimes extraordinarily, even unbelievably good. The Topaz image processing programs I’ve touted in several columns are based on AI-derived algorithms. On the one hand, machine learning is capable of generating some truly astonishing programs. Will this approach, in fact, lead to self-driving vehicles? At this point, we have no idea. Designing the best one for problem is, in itself, something of an art. “Artificial Intelligence.” (But not really - a computer-hype marketing term: These programs bear as much resemblance to real artificial intelligence as Tesla’s FSD does to real self-driving cars.) There are many different approaches to machine learning, many different architectures. The current approach to autonomous vehicles, used by all the players, is some flavor of machine learning a.k.a. I hope, with this column, to introduce a modest degree of enlightenment. The conversations inevitably degenerate into flame wars between the Tesla Fanbois and the Deniers, with neither side showing particular understanding the science or technologies involved. Note to self (and everyone): do NOT read online comments if you wish to retain a favorable view of humanity. Unfortunately, for my sanity, I also find myself reading some of the comments accompanying these articles and videos. Beta is no guarantee of there ever being a final release when it comes to Tesla.) ![]() (Side note: some components of the Tesla software have been in “beta” release for years. I figure if I’m lucky I’ll get the “beta” in November. I guess it’ll depend upon whether the ever-slipping deadline (up to four years and counting) represents a converging or diverging series. I’ve not decided if FSD falls into the category of Zeno’s Software or Godot’s Software. Of course, I may not ever see FSD in any form in my Model X. You can decide if this is a case of anticipating Santa or getting to know one’s enemy. ![]() Consequently I’ve been reading many articles and watching a metric ton of YouTube videos created by the current (small) group of beta testers- a kind of virtual driver’s training class. Many of you have read about Tesla’s imminent wide release of their “Full Self Driving” (snerk) software to the general auto ownership.
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