NVIDIA reported its financial results for the last quarter yesterday and surprised Wall Street. The chip maker, which is now becoming an “AI company” according to its leadership, reported revenue of $2 billion on expectations of $1.7 billion and they also surpassed earnings expectations by a similar margin. On a conference call with CEO Jen-Hsun Huang following the results, analysts were particularly interested in the company’s push in AI and the automotive industry, especially since Tesla’s started delivering every single one of its vehicles with NVIDIA’s Drive PX2 supercomputer. Huang offered some very interesting insights into how he sees Tesla’s self-driving program playing out.He says that by introducing the necessary hardware for full autonomy now, Tesla “sent a shock wave through the automotive industry”:
“And I think what Tesla has done by launching and having on the road in the very near-future here, a full autonomous driving capability using AI, that has sent a shock wave through the automotive industry. It’s basically five years ahead. Anybody who’s talking about 2021 and that’s just a non-starter anymore. And I think that that’s probably the most significant bit in the automotive industry. I just don’t – anybody who is talking about autonomous capabilities in 2020 and 2021 is at the moment re-evaluating in a very significant way.”
For a tiny insight into the regulators, but one that unfortunately does not not delve deep enough.
Policing Driverless Cars an interview with Christopher Hart, who heads the National Transportation Safety Board. MIT TECHNOLOGY REVIEW, VOL. 119 | NO. 6 p 15.
The ideal scenario that I talked about, saving the tens of thousands of lives a year, assumes complete automation with no human engagement whatsoever. I’m not confident that we will ever reach that point. I don’t see the ideal of complete automation coming anytime soon. Some people just like to drive. Some people don’t trust the automation, so they’re going to want to drive. [And] there’s no software designer in the world that’s ever going to be smart enough to anticipate all the potential circumstances this software is going to encounter. The challenge is that when you have not-so-complete automation, with still significant human engagement, complacency becomes an issue.