“The Professor Who Refused to Quit, and the Bet That Changed Everything”
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Title: Genius Makers
Author: Cade Metz
Category: Technology & Innovation, AI, Data & the Future
What if the technology everyone dismissed for thirty years turned out to be the one that changed everything? Sam and Sophie open Cade Metz's Genius Makers in the middle of the AI winter, in Toronto, with a stubborn British psychologist named Geoffrey Hinton.
The episode walks through the fork in the road between symbolic reasoning and neural networks, then the mechanism that made it work: backpropagation. From there it's the 2012 ImageNet moment, when Hinton and two students, Alex Krizhevsky and Ilya Sutskever, trained a network on video-game GPUs and cut the error rate by more than ten percentage points. Google buys DNNresearch for 44 million dollars, the talent war erupts, and the story turns to DeepMind, Atari, and AlphaGo's 2016 win over Lee Sedol. The last stretch sits with the harder questions: surveillance in China, bias, autonomous weapons, and whether any of this actually understands anything.
If you've ever wondered how deep learning went from academic punchline to the engine of modern tech, this is the episode. The takeaway: it wasn't raw genius that did it, it was refusing to quit on an idea for thirty years.
Genius Makers by Cade Metz. For the full written summary, the whole library is on 7minutebooks.com/app — over 6,000 fiction and nonfiction titles you can read or listen to in any language, with infographics on many titles. Unlimited access from $2.99 a month, $9.99 a year, or $19.99 lifetime.
Chapters
00:00Hinton And The AI Winter00:52Symbolic Rules Versus Neural Networks02:09ImageNet 2012 And The GPU Bet03:05Google, DeepMind, And The Talent War06:33AlphaGo And The Ethics Reckoning08:33Takeaway: Stubbornness Over Genius