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The auction that set off the race for AI supremacy
- cbsmith 6y agoI am so surprised they did not encrypt the e-mails with the bids.
- medicineman 6y agoIt would surprise me if professionals didn't. These guys are so ivory tower it hurts.
- jsnell 6y agoHow would somebody reading the emails game the system? The only effective moves are to pass if the price is too high, or bid the minimum increment if you think it is still cheap enough. Passing when the price is lower than your threshold is obviously losing. Raising more than the minimum has no value. You could drive up the price by continuing to bid even when past your threshold, but only after an opponent also bids. But first, that does not get you any benefit, it just inconveniences a rival. And second, this will lead to a tie, which presumably has 50/50 odds of you ending up the winner. I had a similar question about the backpack: they thought they could open it and find out what Baidu’s bidding strategy was. But that knowledge would have had no value to them. The outcome would not change.
- sokoloff 6y agoRaising above the minimum increment does have value. If Baidu is currently winning at say $21M, Google might bid $22M if they know Microsoft will not bid in that round, but might bid $22.1M if they know Microsoft will bid $22M in that round. (Or $23.6M if they know Microsoft will bid $23.5M.) Or suppose Microsoft is willing to go to exactly $22.5M, Baidu to exactly $23.0M, and Google to $40M. If Google can get that information, Google can bid $22.6M and beat both Baidu and Microsoft (if Baidu doesn’t bid this round, because they’re anticipating a $22M bid this round that they’ll cover at $23M next round).
- vl 6y agoBut it doesn’t really matter - they can just bid more in the next round. It’s not eBay - there is no time limit.
- sokoloff 6y agoThere’s value in paying $22.6M rather than $24.0M to win the auction. Around $1.4M in value.
- sdenton4 6y agoNot sure I buy it. The limits here are more 'go talk to your boss' than 'stop bidding when it gets to $XXMM' for everyone involved except for Deepmind (which was later also bought by teh googs). Furthermore, execs are creatures of emotion and whimsy, rather than strictly rational operators. As the price soars higher, they see that everyone at the table values the thing highly, and are likely willing to increase their max bid as their sense of FOMO increases... Subincrements aren't going to matter much, except to ratchet up the feelings at the table even higher, faster.
- vl 6y agoIt is a bit surprising that they didn’t use neutral 3rd party as arbiter, and that they didn’t go ahead with Dutch auction. They would be done in few hours with very close result. Another surprising thing is that there were no good will clause, ie that they could terminate auction and refuse to work for the winner (which they effectively did).
- sjg007 6y agoI mean this was just price discovery. Google could have reneged too. Really showed the value of incorporating
- bostonsre 6y agoMaybe Google really doesn't like Microsoft or vice versa and they would try to out bid each other to prevent the other from winning, but they would both let another 3rd party win.
- huitzitziltzin 6y agoThis depends on the exact nature of the object being auctioned. The details matter a lot. Some good economists have worked on this problem both in theory and empirically for a long time. Under independent private valuation (where the value of the object is completely idiosyncratic to you), your thought is (AFAIK) correct. Here think of art: ignoring resale value, how much someone else would pay for an object depends on how much he likes it, but doesn't have anything to do with how you should bid - your bid is a function of how much you like it. (To a first approximation - again the details of the auction format really matter.) In a common value situation (where the value of the underlying object to any player is the same, but players _signals_ (an input to their beliefs) about that value contain an idiosyncratic component), you might learn something about the quality of your own signal by knowing something about the bids of other players in the auction. For example: are you about to overpay b/c you believe Hinton's time is worth a lot more than Google and Baidu believe it to be worth?? The phrase "the winner's curse" was invented for this problem in the context of bidding for offshore oil leases. The value to all players (the number of barrels of oil in the field) is the same, but they have different beliefs about what that number is. The winner's curse is that the highest bidder was generally the most optimistic about the value of the field. It's a "curse" b/c the optimism was frequently not justified. What was actually being auctioned here is a little unclear - something like "the time and expertise of Hinton + two grad students", but it's plausible that Google, Microsoft and Baidu could have made equally good use of it. It reads more like a common value setting, that is. So knowing the bids can matter. If you want to know more about auction theory (this comment may already be more than you want to know!), I can recommend Krishna's "Auction Theory" or Milgrom's "Putting Auction Theory to Work."
- ArtWomb 6y agoWhile it seems reasonable to assume there is no advantage in the perfect information scenario, it feels wrong. For large auctions perhaps a pattern emerges in which a rival strategy could be inferred. Of course in the end it didn't matter! Hinton subconsciously knew he wanted to join Goog. And may have been inadvertently signalling such all along. And the American rivals themselves were probably colluding as well to keep China in check. I suspect this "history" of Deep Learning was quite dry to begin with. As it mostly featured academics. Some cloak and dagger style suspense was peppered in to make it a more exciting read ;)
- cjauvin 6y agoI 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..
- elefanten 6y agoHe’s an NYT tech reporter, so that lines up with your observations. He’s inherently a part of the ongoing NYT vs Silicon Valley spat, so probably being circulated more in tech circles as that plays out.
- macksd 6y agoThis spat is news to me. What's going on?
- offby37years 6y agohttps://greenwald.substack.com/p/the-journalistic-tattletale-and-censorship https://greenwald.substack.com/p/the-journalistic-tattletale... https://greenwald.substack.com/p/journalists-start-demanding-substack https://greenwald.substack.com/p/journalists-start-demanding...
- batty_alex 6y agoReading this sort of stuff will just make you bitter and resentful. It’s a step away from using a slur to describe journalists they don’t like.
- shard972 6y agothus proving the articles are true
- at_a_remove 6y agoWell, we're going to need a new slur for journalists, something which is reminiscent of their rampant hypocrisy, their agendas, and general desire to throw stones without repercussion. "My side's violence is speech; your side's speech is violence" is the new refrain and how I would love to hear coined a word which can adequately encompass that kind of loathsomeness.
- lawrenceyan 6y ago“The future is already here – it's just not very evenly distributed.” ― William Gibson
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- Lammy 6y agoAs 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 :) “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.”
- subsubzero 6y agoHinton 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. NYTimes is positively in love with him, are a few other articles - https://www.nytimes.com/2017/11/28/technology/artificial-intelligence-research-toronto.html https://www.nytimes.com/2017/11/28/technology/artificial-int... ... https://www.nytimes.com/2016/12/14/magazine/the-great-ai-awakening.html https://www.nytimes.com/2016/12/14/magazine/the-great-ai-awa...
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- hooloovoo_zoo 6y agoMaybe, but what to make of the towels? The story implies he doesn't know humidifiers exist.
- kortilla 6y agoIt’s a hotel. Humidifiers aren’t a common amenity and he took a train there.
- hooloovoo_zoo 6y agoOTOH, CVS is a block away.
- vlovich123 6y ago$44 million + the many more millions he makes annually hires a good agent. Also I’m sure it’s not unlikely that Google is using their PR contacts to pick the writer that does the profile can yield some favorable coverage.
- Bukhmanizer 6y agoHinton has such a good story that I think it’s was clear from the outset that he was going to be the “face” of AI. He was on one of the first backprop papers, worked pretty consistently on neural nets though the AI winter, and was pretty instrumental in the renaissance. Was he the only person working on this stuff? No, but I think we as a society like to tell ourselves a story about science and scientists. The narrative of the “lone scientist” wiling away their days in solitude until reaching a breakthrough probably hasn’t actually existed since the 19th century. Pretty much all significant discoveries nowadays are the product of intense collaboration and iterative progress. Science is a team sport, just one where 99% of the team happens to be invisible.
- LeegleechN 6y ago"I signed contracts saying I would never reveal who we talked to. I signed one with Microsoft and one with Baidu and one with Google"
- fggg444 6y agohilarious, you can't make this shit up
- redis_mlc 6y agoThe writing style of this article is "human-interest" - all about his slipped disc. Can somebody write a tldr; ?
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- howmayiannoyyou 6y agoAnd today projects like https://numer.ai/ https://numer.ai/ have made ongoing business out of AI auctions.
- oli5679 6y agoAn ascending auction is strategically equivalent to a 'Vickery' 2nd price auction and logistically simpler, since it only requires one round of bidding. https://en.wikipedia.org/wiki/Vickrey_auction https://en.wikipedia.org/wiki/Vickrey_auction This ignores phycological factors, and some minor quirks relating to minimum bid increases.
- harryposner 6y agoAn ascending price auction is strategically different from a second price auction when the bidders each have a noisy estimate of some underlying true value. With a second price auction, the only information you can incorporate into your bid is your own signal. With an ascending price auction, you can look at the prices at which the other bidders drop out (except the second highest bidder) and incorporate that information into the price at which you're willing to drop out. This also means that an ascending price auction raises more revenue than a second price auction, by the linkage principle. https://en.wikipedia.org/wiki/Linkage_principle https://en.wikipedia.org/wiki/Linkage_principle
- jtsiskin 6y agoEvidence by “That left Baidu, Google, and Microsoft. As the bids continued to climb, first to $15 million and then to $20 million, Microsoft dropped out too, but then returned. “. Microsoft could not have “returned” in a Vickrey auction
- bernardv 6y agoPhycological? Not sure what you mean - I don’t think you mean Fungi do you ;-)
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- nmfisher 6y agoGreat article, I had no clue Hinton had that amount of commercial savvy.
- bernardv 6y agoWish 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.
- david-cako 6y agoThe 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.
- trott 6y ago> 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. Were the students or Hinton under any obligation to stay at DNN-research?
- sjg007 6y agoYes.
- huac 6y agoprobably they had shares/cash payouts that would vest over some schedule
- fxtentacle 6y agoI believe what they effectively did was receive their salary upfront. for example: 3 people x 5 years guaranteed loyalty = $45 mio => $3 mio per person per year, paid upfront That's still high, but not that much higher than what Google already pays to top performers. Plus they get all the PR benefits, as we have seen.
- dfox 6y ago"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." 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). https://doi.org/10.1038/323533a0 https://doi.org/10.1038/323533a0). 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...
- astrange 6y agoI graduated in 2010 with a degree supposedly in "CS with AI specialization" and was taught that neural networks weren't useful for much of anything at the time. The best techniques we learned were MCMC and random forests, our computer vision was OpenCV and didn't work so well, and there wasn't any suggestion that buying a lot of GPUs and not bothering to understand the problem space would produce better results than our laptops.
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- vl 6y agoAI Renaissance
- QuesnayJr 6y agoIt's mostly right. "Early pioneers" is wrong, since the idea of neural networks predates backpropagation, but by the turn of the millenium they really were regarded as old fashioned, and attention had moved to things like support vector machines and Adaboost.
- rubiquity 6y agoHave 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.
- nl 6y agoEver searched for images and had it work? Neural nets are incredibly good.
- MattRix 6y agoThey’re everywhere! I can take a photo on my phone and it’s instantly given convincing artificial depth of field. I can search my photos for the name of anyone I know and instantly all the photos containing those people show up. I regularly use voice assistants, translation, and can dictate full length messages while I’m driving in my car. Neural nets can even drive cars now! This stuff is already making massive impacts, and yet it’s still in the early stages. The meeting in the article was less than 10 years ago. Just imagine in 20 or 30 years from now.
- somethingAlex 6y agoImage search by content, improved language translation, Siri/Alex/Google Assistant, automatic content moderation to name a few. With that said, I generally feel like my life has not been impacted greatly. Siri can barely tell me anything other than the first paragraph of a wikipedia page or today's weather. I don't search my photos often. I don't translate languages often, and I'm not in a back office in charge of moderation.
- fggg444 6y agothey coordinated the auction via gmail and Google won. there's no way Google didn't peek at their other correspondences.
- kemitchell 6y agoI hope he paid that lawyer on time.
- YaSamPoSebe 6y agoHinton, Hinton, Hinton.. What did this Hinton do? The breakthrough was not his.
- choppaface 6y agoWhole article: https://archive.is/uL2y1 https://archive.is/uL2y1 Key Quote: "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). 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 ...
- kortilla 6y ago> As Google and other tech giants adopted the technology, no one quite realized it was learning the biases of the researchers who built it. 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.
- tchalla 6y agoAlgorithmic bias is not ONLY a data problem, it’s also a model problem [0]. The bias from model developers are coded via learning rates, network hyper parameters and objective functions. [0] https://twitter.com/sarahookr/status/1361373527861915648?s=21 https://twitter.com/sarahookr/status/1361373527861915648?s=2...
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- visarga 6y agoModel bias is not a huge issue. Maybe something about class imbalance or regularization. The huge issue is deployment - what is the model used for? How is it affecting people in reality? What metric is it optimizing? Between all these the degree of L1 regularization or the class weights are minor things. Most models will perform similarly given the same data. It's mostly the data that makes the difference.
- tchalla 6y agoIs that your personal opinion? Research seems to disagree. Citations in the previous link.
- baylearn 6y agoCitations needed to back your claim. Research literature seem to support the opposite.
- yorwba 6y agoThere's an interplay between the two insofar as a model built to handle a specific dataset will involve design decisions informed by the data. E.g. you might pick a certain level of L1 regularization because it maximizes performance on the data you have, which can lead to bias against data you don't have. But if you take "model" to mean the pure mathematical description without parameters or hyperparameters that need to be determined by experimentation, then I agree that optimizing the model on a dataset will not lead to bias against specific groups of humans unless the data used contains such a bias.