Appeal-to-authority arguments are always uncompelling, but they are especially uncompelling against Musk. Authorities said hydrogen fuel cells were the future.

Appeal-to-authority arguments are always uncompelling, but they are especially uncompelling against Musk. Authorities said hydrogen fuel cells were the future. Authorities said EVs will never outperform gas cars. Authorities said batteries will always cost too much. Authorities said reusing rockets will never work. With each of these breakthroughs, Musk presented a well-reasoned view that was highly contrarian against the authority consensus; and in each case, his view turned out to be not only correct, but so correct that it became the new authority consensus. Maybe this time he is wrong and you are right. But if you are wondering why the market and the masses believe him, it's because he continues to provide reasonable explanations for what he's proposing, and he has a track record to back them up. If history predicts the future, then in a few years, we'll add "authorities said you needed LIDAR for self-driving" to the list above. This is already starting to play out in the SDC space, with Hotz of Comma.ai sharing Musk's views on vision, and Levandowski sharing his more generalized concern about LIDAR (the latter is more recent if you're not familiar): > Levandowski contends that this “race” to deploy autonomous vehicles has yet to start in earnest largely due to shortcomings from “crutch technologies,” a descriptor he uses for hardware like LiDAR and HD maps. His position is that while these provide sensing and localization for the vehicle in the present moment, they have serious compromises and don’t produce the level of predictive ability required to commercially deploy autonomous vehicles. https://techcrunch.com/2018/12/18/anthony-levandowski-prontoai-self-driving-trucks/ https://techcrunch.com/2018/12/18/anthony-levandowski-pronto... Karpathy was able to explain in very simple and understandable terms this week why Tesla's approach is advantageous. If the critics understand this domain so well, how come they can't provide a straightforward retort? If Feinman could do it with quantum physics, surely a machine learning expert can do it with neural networks. I would love to read/hear/watch such a retort if anybody is interested in presenting one.