Geoffrey Hinton spent 30 years on an idea many other scientists dismissed
>For more than 30 years, Geoffrey Hinton hovered at the edges of artificial intelligence research, an outsider clinging to a simple proposition: that computers could think like humans do—using intuition rather than rules.<p>This is so disrespectful to the 1000s of researchers who have been studying machine learning since well before 2012. It was well established that the future of teaching computers came from statistics and not rules in the 80s/90s by researchers like Michael Jordan (<a href="https://en.wikipedia.org/wiki/Michael_I._Jordan" rel="nofollow">https://en.wikipedia.org/wiki/Michael_I._Jordan</a>) and his students.<p>It was even engrained in popular culture: neural networks are how the AI brain worked in Terminator 2, in 1991! <a href="https://www.youtube.com/watch?v=xcgVztdMrX4" rel="nofollow">https://www.youtube.com/watch?v=xcgVztdMrX4</a><p>edit: I don't want to downplay Hinton's accomplishments, I've been lucky to have been surrounded by and motivated by his work since I started learning machine learning. I did my masters research on neural networks that were partly inspired by his work, and it was a deep networks paper he presented at a NIPS 2006 workshop that got me really excited to stay in machine learning while I was starting my career.