> As Google and other tech giants adopted the technology, no one quite realized it was learning the biases of the researchers who built it.<p>Woah, this came out of nowhere and it’s completely wrong. The problem isn’t that deep learning is picking up biases of the researchers, it’s that it picks up biases from the training data.
"The idea of a neural network dated back to the 1950s, but the early pioneers had never gotten it working as well as they’d hoped. By the new millennium, most researchers had given up on the idea, convinced it was a technological dead end and bewildered by the 50- year- old conceit that these mathematical systems somehow mimicked the human brain."<p>This is not only false, but in the context actually intentional misrepresentation. Most of the issues with the model was solved by introduction of hidden layers and backpropagation learning, which is at least in my opinion required knowledge in CS since at least early 90's and probably earlier (it is not clear when the idea was formulated in usable form, put the most cited publications are from late 80's, eg. Rumelhart, D., Hinton, G. & Williams, R. Learning representations by back-propagating errors. Nature 323, 533–536 (1986). <a href="https://doi.org/10.1038/323533a0" rel="nofollow">https://doi.org/10.1038/323533a0</a>).<p>On the other hand obviously more complex modern approaches to the "throw bunch of poorly understood linear algebra at he problem" problem have value and there is definitive generational shift in the current "AI-anti-winter" (for lack of better word), but still...
Whole article: <a href="https://archive.is/uL2y1" rel="nofollow">https://archive.is/uL2y1</a><p>Key Quote:<p>"Inevitably, the next bid wouldn’t arrive until a minute or two before the top of the hour, extending the auction just as it was on the verge of ending. The price climbed so high, Hinton shortened the bidding window from an hour to 30 minutes. The bids quickly climbed to $40 million, $41 million, $42 million, $43 million. “It feels like we’re in a movie,” he said. One evening, close to midnight, as the price hit $44 million, he suspended the bidding again. He needed some sleep." (So Google paid north of $40m to hire Hinton and his lab).<p>That all makes $2m a year for Ilya Sutskever, or $600k a year for some run-of-the-mill dude with a degree in AI seems like a bargain. The founders of Nuro got $40m each to leave Google and start their own company. Hopefully we get some more transparency about pay to bring up the whole field rather than just "AI." After all, at the time of writing software tends to have a higher accuracy rate than machine learning ...
As soon as I read this part I figured they’d end up selling to Google, because only PR people would include a defensive aside like this :)<p>“In the days before the auction, [Microsoft] complained that Google, its biggest rival and likeliest competitor in the auction, could eavesdrop on private messages and somehow game the bids. Hinton had raised the same possibility with his students, though he was less expressing a serious concern than making an arch comment on the vast and growing power of Google.”
Hinton has an incredible press agent, from articles like these you would think only his and a few other minds are actually working on AI. Nothing against Hinton, just wish others in the AI field got as much press, there are alot of incredible things happening in AI the past few years.<p>NYTimes is positively in love with him, are a few other articles - <a href="https://www.nytimes.com/2017/11/28/technology/artificial-intelligence-research-toronto.html" rel="nofollow">https://www.nytimes.com/2017/11/28/technology/artificial-int...</a>
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<a href="https://www.nytimes.com/2016/12/14/magazine/the-great-ai-awakening.html" rel="nofollow">https://www.nytimes.com/2016/12/14/magazine/the-great-ai-awa...</a>
> It included only two other people, both young graduate students in his lab at the university. It made no products. It had no plans to make a product. And its website offered nothing but a name, DNN-research, which was even less inviting than the sparse page.<p>Were the students or Hinton under any obligation to stay at DNN-research?
Have the proposed impact of Neural Nets come to light yet? I don’t say this in a snarky way. In my life I don’t encounter them much or at all and thinking about Google specifically their search results don’t seem to be getting better.
And today projects like <a href="https://numer.ai/" rel="nofollow">https://numer.ai/</a> have made ongoing business out of AI auctions.
An ascending auction is strategically equivalent to a 'Vickery' 2nd price auction and logistically simpler, since it only requires one round of bidding.<p><a href="https://en.wikipedia.org/wiki/Vickrey_auction" rel="nofollow">https://en.wikipedia.org/wiki/Vickrey_auction</a><p>This ignores phycological factors, and some minor quirks relating to minimum bid increases.
Wish I had met Hinton while at U. Of Toronto. I was slated to do a PhD with a guy from the Medical and Zoology schools studying human vision and who was applying NN’s with Hinton’s help. Early ‘90’s when ‘soft computing’ was all the rage.
I see this journalist (Cade Metz) everywhere these days it seems: this article, a NYT article about the Google ethical AI debate, and the article about Slate Star Codex..
The race for AI supremacy started when people started doing CRISPR in their basement. It's not "ideological" for the US to go first, it's the only option.