AlexNet and post-AlexNet eras. The AlexNet results came out in October 2012. To the relatively small number of people paying attention, it was shocking. Neural networks had been around for decades but they had stalled out. It was basically a research backwater. And then AlexNet showed that if you make them “deep” by throwing a huge amount of compute (for the first time in the form of GPUs rather than CPUs) and data at them then you can obtain a gigantic performance improvement.
The exact timelines for Elon aren’t clear but it seems he instantly understood the significance of AlexNet and by May of 2013 it was reported that Tesla was “
considering adding driverless technology to its vehicles
.”
If you go back to the pre AlexNet era, AI was broken into two distinct philosophical camps. Statistical learning vs Bayesian learning. After AlexNet, in my opinion, AI divided along new lines: vision vs language (computer vision vs NLP). After AlexNet, vision was in a renaissance, and language was in what turned out to be a short lived lull.
There was a casual debate at the time around if the best pathway to AGI was via vision or language? Nobody knew for sure but in 2013 it seemed like vision was the most promising.