From Elon Musk, the book:
Almost every year, Musk would make another prediction that Full Self-Driving was just a year or two away. “When will someone be able to buy one of your cars and literally just take the hands off the wheel and go to sleep and wake up and find that they’ve arrived?” Chris Anderson asked him at a TED Talk in May 2017. “That’s about two years,” Musk replied. In an interview with Kara Swisher at a Code Conference at the end of 2018, he said Tesla was “on track to do it next year.” In early 2019, he doubled down. “I think we will be feature complete, Full Self-Driving, this year,” he declared on a podcast with ARK Invest. “I would say I am certain of that. That is not a question mark.”
So they’ll fail again in 2024? Maybe not.
For years, Tesla’s Autopilot system relied on a rules-based approach. It took visual data from a car’s cameras and identified such things as lane markings, pedestrians, vehicles, traffic signals, and anything else in range of the eight cameras. Then the software applied a set of rules, such as Stop when the light is red; Go when it’s green; Stay in the middle of the lane markers; Don’t cross double-yellow lines into incoming traffic; Proceed through an intersection only when there are no cars coming fast enough to hit you; and so on. Tesla’s engineers manually wrote and updated hundreds of thousands of lines of C++ code to apply these rules to complex situations.
C++?!?! Seriously?
According to the book, Tesla is shifting to a ChatGPT-style machine learning approach:
“Instead of determining the proper path of the car based only on rules,” Shroff says, “we determine the car’s proper path by also relying on a neural network that learns from millions of examples of what humans have done.” In other words, it’s human imitation. Faced with a situation, the neural network chooses a path based on what humans have done in thousands of similar situations. It’s like the way humans learn to speak and drive and play chess and eat spaghetti and do almost everything else; we might be given a set of rules to follow, but mainly we pick up the skills by observing how other people do them. It was the approach to machine learning envisioned by Alan Turing in his 1950 paper, “Computing Machinery and Intelligence.”
By early 2023, the neural network planner project had analyzed 10 million frames of video collected from the cars of Tesla customers. Does that mean it would merely be as good as the average of human drivers? “No, because we only use data from humans when they handled a situation well,” Shroff explains. Human labelers, many of them based in Buffalo, New York, assessed the videos and gave them grades. Musk told them to look for things “a five-star Uber driver would do,” and those were the videos used to train the computer.
During the discussion, Musk latched on to a key fact the team had discovered: the neural network did not work well until it had been trained on at least a million video clips, and it started getting really good after one-and-a-half million clips. This gave Tesla a huge advantage over other car and AI companies. It had a fleet of almost two million Teslas around the world collecting billions of video frames per day. “We are uniquely positioned to do this,” Elluswamy said at the meeting.
Despite grand claims by academics seeking funding, rules-based AI generally failed to do anything interesting or practical from 1970-2010 (see MYCIN and CADUCEUS, for example). Statistical approaches to AI, however, began to deliver useful systems, e.g., for speech recognition, starting around 2010.
How Tesla describes the future:
FSD would provide a huge lifestyle boost here in South Florida where there are a lot of 1- and 2-hour drives that lead to interesting places, such as parks, cultural events, theme parks, etc. The drives themselves, however, are boring: straight highways, a lot of traffic close to Miami and Orlando. FSD should work quite well. FSD would also be good for getting to/from international airports. There are a lot more flights from FLL and MIA than from PBI, which is closer to our house, but with a self-driving car it might become more sensible to fly out of farther-away airports.
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