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Microsoft forms new 5,000-person AI division
- snippet22 10y agoMaybe it'll make windows better.
- beau26 10y agoWe seem to be at an inflection point with AI -- companies across the board are investing billions of dollars into AI R&D and I expect that we'll start to see some really amazing products and services coming out of this in the coming decades.
- phreeza 10y agoIt's either that, or a great disillusionment in ~5 years when the investments don't pan out, followed by the next AI winter.
- cmarschner 10y agoThe next AI winter will come when we maxed out on the current technology, i.e. when model training will become too expensive. If all that is left to do is to run training on top of all of Youtube videos, one might have to wait for 10 years until that becomes feasible.
- a-priori 10y agoThis is a real concern. But as I see it, the difference is that the last time around, everyone was sold on the potential applications -- which turned out to be way harder than anyone realized. This time around, the technology is seeing real applications today, so the valuations are more grounded in reality. So while people are definitely investing based on the future potential, the worst case scenario -- that we're going to hit a wall next week where no further progress can be made in machine learning research -- wouldn't be as devastating as the last AI winter. At this point there's a lot of work to do, and money to be made, applying the current state of the art even if no further progress can be made.
- dragontamer 10y agoIt probably will be something more like the Kinect: a few products come out that aren't useful at all. It took decades before people figured out Aluminum was actually useful for things for example. It was a chemical curiosity for the later-half of the 1800s (hmm, this is a cheap metal that is found everywhere. But its weaker than steel, what should we use it for?) Just because you discover something useful doesn't mean you figure out what to do with it.
- phreeza 10y agoAluminum (metal, not ore) was actually extremely expensive until the discovery of the electrolytic Hall–Héroult process ca 1880.
- Florin_Andrei 10y agoYup. The reason why it was not used for a long time is that it was hard to make. Aluminum is a very reactive metal; when combined with oxygen or other stuff, it sits at the bottom of a deep pit of energy. It takes a lot of effort to get it out of there. The electrolytic process is basically a brute-force approach: throw enough energy at anything, and it will start moving eventually. Napoleon III had his fancy-dinner utensils made from aluminum, for those occasions when gold did not seem lavish enough. And then cheap manufacturing was invented, and the rest is history.
- Retric 10y agoThe Washington Monument is capped with Aluminum because at the time it was more expensive than gold to refine. https://en.wikipedia.org/wiki/Washington_Monument#Aluminum_apex https://en.wikipedia.org/wiki/Washington_Monument#Aluminum_a...
- Dowwie 10y agoWhich office location(s) are planned for this?
- danielcampos93 10y agomostly Seattle region. Since half of the division will be made up of Bing folks and there is a bunch of empty office space in Bellevue I would assume most would be clustered in the Bellevue office(as opposed to the regular Redmond Campus)
- pjc50 10y agoPrepare for Clippy 2.0! (Joke; Microsoft Research are actually highly respected, it's just that like Xerox they have some trouble turning it into products)
- DanBC 10y agohttp://robotzeitgeist.com/tag/bayesian-inference-engine http://robotzeitgeist.com/tag/bayesian-inference-engine Clippy is an interesting case because they had a good product and then they downgraded it for reasons. It's kind of frustrating that they could have introduced something brilliant but chose not to.
- douche 10y agoThe Clippy for Resharper[1] extension is my second favorite joke extension after the Visual Studio Achievements[2] extension. [1] https://blog.jetbrains.com/dotnet/2014/04/01/clippy-for-resharper/ https://blog.jetbrains.com/dotnet/2014/04/01/clippy-for-resh... [2] https://blogs.msdn.microsoft.com/zainnab/2012/02/28/visual-studio-achievements/ https://blogs.msdn.microsoft.com/zainnab/2012/02/28/visual-s...
- arethuza 10y agoPARC came up with the Laser Printer which was worth billions for Xerox: https://www.parc.com/about/parc-xerox.html https://www.parc.com/about/parc-xerox.html
- dave_sullivan 10y agoTo put this in perspective, 5000 people at $200k per year (which is conservative if you include benefits, etc.) is 1 billion dollars in comp per year. So OpenAI is spending a billion dollars over the next several years. Microsoft is spending a billion dollars per year. Google, etc. do the math. There's literally billions of dollars now being spent on moving deep learning forward. Pretty amazing when I think back to 2011 and there were machine learning conferences where literally no one I spoke to had heard of deep learning. People worrying about a second AI winter are like the people that have been worrying about an "internet bubble" since 2004. It's fine to be worried, there will be bubbles, but this time it's different and there are many reasons for that. There is no "internet industry" anymore; it's become more segmented and just plain bigger. Similarly, there will be no "AI industry"; it will branch out, and there are more potential applications of "understanding data and automating decisions" than there were in the 80s. > something that they are branding AI - I might wait and see how much of it is on real AI - what ever that is. Yeah, I wouldn't get hung up on that, they're calling it AI because that's easier to explain to reporters than deep learning. The difference is deep learning techniques are already being used in released products and companies are looking to do more of that, so there is a very real definition and set of goals associated with what these groups are doing, it's not just, "hey everyone, let's make an ai!"
- Angostura 10y agoWell, companies are certainly spending a lot of money on something that they are branding AI - I might wait and see how much of it is on real AI - what ever that is.
- seanmcdirmid 10y agoThey don't have to achieve "real AI"; they only need to come up with things that do more work for us to win. Real AI is a fool's goal. Once we achieve that, we will simply be obsolete, I'm in no hurry to get there.
- pamelabuck 10y agohaha yeah in this case, we want to shoot for the moon but definitely want to hit the tree
- emcq 10y agoIt always puzzled me why Microsoft laid off their ML heavy research group in mountain view, and continues to puzzle me after news like this!
- enigmo 10y agoa bunch of them now work at Google on the Brain/Tensorflow team. definitely was an odd move.
- abz10 10y agoThis was Satya sending the strong message that no-one is untouchable and everyone must get inline or they will be next. It's actually a common strategy that requires the victims to be their best people. Obviously you can't to this too many times. Politics as usual.
- shostack 10y agoCan you elaborate on how that works? If the victims are their best people who are doing solid, profitable work, laying them off seems like it would create a state of uncertainty which, in this climate, might just cause people to jump ship because competitive jobs are just around the corner. Or was there some issue with the group where they had to sacrifice the good with the bad due to lack of overall profitability?
- abz10 10y agoIt's about internal power, even at the expense of the companies wellbeing. These layoffs were in the context of a larger set of layoffs that Satya undertook as his first big move at MS. Satya was getting across the board pushback from lots of different warring orgs at MS. He even had to bring the Big G out of retirement to help him out. So by taking out the top dogs he becomes the top dog. I don't even blame Satya for doing it - it's human nature that required it. If he didn't do it he would have eventually been pushed out of MS for not getting anything done. It's why drug cartels are so violent, it's why our election choices are Clinton and Trump. At least he's less evil than Sinofsky and Ballmer who were both cartoonishly horrible. Good people have been leaving MS for a very long time. But big company corporate politics are really toxic in the US. MS is actually one of the better ones. Intel, Amazon, Netflix are much worse. Facebook and Google are on the decline. Yahoo.... yeah As for this AI thing, my bet is that it is mostly fluff. Most people will ignore it until the next re-org comes along. There was a similar thing with Big Data at MSR a number of years ago and look what happened there.
- coldcode 10y agoI wonder if they are successful, the next new AI division will have 0 people.
- kens 10y agoReading this carefully, the 5000-person group is "AI and Research" not just AI. (5000 people would be a lot to have working on AI.) This group includes Bing, Cortana and the current research group, so there are a lot of people not working directly on AI. That said, it is a significant change in focus, making AI a priority.
- danielcampos93 10y agoCorrect. The team still includes everyone who works on Bing and essentially the Non Office part of what Qi used to run. Its less 5000 person AI Group as 5000 people running various businesses whose collective mantra is now AI.
- vessenes 10y agoA friend of mine was an early investor in DeepMind. For like a year and a half, because that's how long it took Google to buy them out for somewhere around $400mm. At the time, I thought that sounded like an amazing exit (OK, it still sounds like an amazing exit), and wasn't clear how Google could get that value out in a reasonable timeframe. I was so, so, wrong. The amount of value hidden and public in that acquisition is astounding. Whoever put it together deserves a massive bonus, ideally in Alphabet stock. MS putting $1bn a year in on AI is a catch-up game. They may do very well at it, but make no mistake -- we are only seeing the public side of the value Google is generating. I don't imagine we'll ever see blogposts about how they're tuning adwords using AI, for instance. But you can bet the same sort of gains they are seeing with translations, audio generation, game playing they are seeing in the ad space.
- douche 10y agoHow would we know if they are doing amazing things with AdWords, if we're all running uBlock/AdBlock/etc?
- alexbeloi 10y agoThere was an internet marketing manager on a podcast I listened to once that said the number of people using adblockers on the internet is essentially negligible, it's in the millions but a small percentage of all users (<5% if I recall). edit: the Podcast was Talking Machines (about machine learning) http://www.thetalkingmachines.com/ http://www.thetalkingmachines.com/
- douche 10y agoThis[1] is from a year ago, before ad-blocking became widely available on mobile, and they're still looking at hundreds of millions of users using adblockers. I don't know how reputable PageFair is, but they estimate more than 20% of smartphone users are adblocking now[2]. [1] http://bits.blogs.nytimes.com/2015/08/10/study-of-ad-blocking-software-suggests-wide-use/?_r=0 http://bits.blogs.nytimes.com/2015/08/10/study-of-ad-blockin... [2] https://pagefair.com/blog/2016/mobile-adblocking-report/ https://pagefair.com/blog/2016/mobile-adblocking-report/
- macawfish 10y agoGet ready for patent disputes.
- safdeep 10y agoI love the fact that it took Ballmer to leave for them to really get serious about cutting-edge tech again. Bill Gates are probably wishing he never met Ballmer at Harvard.
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- nostrademons 10y agoTwo sides to this comment: 1) It took Ballmer to leave for them to really get serious about innovating again. 2) ...because under Ballmer, they were able to make billions of dollars without innovating. Bill Gates is probably pretty happy about #2 even if he's not thrilled about #1.
- j2kun 10y agoLet's hope they don't fire them all like they fired their research staff at MRSV
- jacquesm 10y ago5000 more people working hard to make themselves obsolete. I wonder how long it will take those working on AI to figure out that they're doing to themselves and the rest of the IT industry what the IT industry has already done to many others. If and when they succeed we'll finally know the true meaning of the term disruption.
- icebraining 10y agoWhy do you assume they don't know what they're doing? I'd be happy to get a nice salary to work on making myself obsolete.
- chadgeidel 10y agoI'm 100% behind making my personal job obsolete. I don't think it's going to happen in my career, but I'd love to see it.
- anoplus 10y agoMaking jobs obsolete is what tech is all about. What the jobless will do is a socio political problem.
- randartie 10y agoHow can they possibly staff a 5000 person ai division. Sounds to me like only a small-ish subset will be talented ai researchers.
- fma 10y agoYou're probably right. There's always overhead to a project. Testers, Analysts, Managers, Dev Ops...
- delegate 10y agoI feel like, as a solo app developer, I'm being left out of this 'revolution'. It seems like deep learning only makes sense if you have enough data to feed the algorithm with. The kind of data that only big companies can produce or harvest. Sure you can produce some video and audio data and you can spider the web a little bit, but that doesn't even come close to the resources that these big corporations have and the 'depth' of learning that they can achieve. So I'm not even trying. Or should I ? Is there any place for solo/indy developers in this field ?
- amenghra 10y agoI have seen small companies build better product targeting than Fb/Google/etc do with their ads. Yes you have less data, but your users are probably more similar to each other and less scattered all over the place. While I feel this is true for recommendation engines, it might not be true for other AI applications.
- amenghra 10y agoPrisma is an example of small team doing something novel with AI. Over time they are going to have a huge amount of data to further improve their product.
- skybrian 10y agoI don't know much about it, but there are public datasets you can train on and contests you can enter. But this seems more like doing research in hopes of coming up with something new that big companies will be interested in. Or, if that doesn't happen, learning enough so that they can hire you as a researcher or consultant.
- web007 10y agoDepending on what you're trying to do you have some options, but you should probably outsource. Option 1: If you're working on image recognition or anything similar, it's easy to get a ton of data. There are many corpora of image data available, probably on the order of hundreds of terabytes, with tags or at least some structured data. If you're going to "spider the web" you should use Common Crawl instead, and can access all of Blekko's data for the cost of data transfer via AWS. Same for text data, use the Google N-gram corpus. Knowing that all of that exists, I would still recommend Option 2: outsourcing your AI needs unless you're a researcher or have a decent budget for AI development. Go search "ai api" and pick one that matches what you want to do. Match your skill and risk tolerance; nobody got fired for using IBM, but you may get a better experience from a startup with the possibility of flaming out in a year. You'll get the leverage of whatever company is spending those dollars on your behalf, and you'll be able to concentrate on the user experience instead of the science-ey part. Option 3 is "if you can't beat 'em, join 'em". Go work for MS / GOOG / FB / IBM building something, and get access to those resources for yourself. Then at some point in the future you'll know their API interface, and you can go back to option #2 with much better data.
- amirathi 10y agoHow do you really start a 5000 person division at once and expect to succeed? I assume AI development is a niche field. And you would want smaller dedicated teams of brilliant researchers and practitioners focusing on a single problem. I can't imagine the overhead in maintaining and operating such a large division. I hope they know what they are doing.
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- visarga 10y agoWith a billion I could get a cloud of 10,000 servers with 16 GPU cards... mmm, lots of GPUs... Or 5000 employees and 5000 servers each with 8 GPUs.
- ww520 10y ago$100K for one server? Those are darn good servers.
- jsmthrowaway 10y agoIn this case, it's the GPUs. High six figure servers aren't unheard of in the commodity world (even before you start talking about bigger iron). Oh yeah, and one word: Fusion-IO.
- pazimzadeh 10y agoSomething something mythical man month?
- jomamaxx 10y agoExactly. The bulk of 'practical AI' don't come from massive products, like 'Office' - but from very specific neural algorithms, applied to very specific things - done by a few people. That said - this kind of research may benefit from a lot of concurrent research. Also - there are a couple of strategic issues: 1) Prestige - it's important to be recognized as 'a leader' to maintain brand cachet among tech talent 2) Talent Hoarding - Google, FB and MS are each big enough to tilt the landscape in any specific field. It's actually economically viable for them to pay the best talent to sit in a lab and fiddle, even while accomplishing little, over letting the talent go to competitors.
- modeless 10y agoI am intrigued by the mention of "Monthly Q&A" at the end of the email. Is this Satya Nadella's version of Google's TGIF meetings? If so I heartily approve. I left Microsoft for Google in 2010 and TGIF Q&A was one of the things I appreciated the most about Google culture (despite the occasional screwball live question). I think any company could benefit from a similar tradition.
- danielcampos93 10y agoYeah. They host a Q&A session every month and most leader down the totem pole do the same(Scott Guthrie hosts fireside chats)
- pesenti 10y agoI know IBM and Watson often get a bad rap here. But IBM made the same exact move almost 3 years ago with the creation of the Watson unit. There is way too much PR around Watson, but IBM should be credited for having called the current round of AI investments way before anybody else. Disclosure: I was part of the initial IBM Watson team, left recently.
- desireco42 10y agoLook and then in few years they will have to fire those people.
- sam36 10y agoWhat is the current fascination with AI? It seems to be talked about everywhere right now. Yet "AI" in a core sense has been around since the 70's...
- mkehrt 10y agoIn the past few years, both the hardware caught up to and new practical techniques have been developed for multilevel neural nets (deep learning). It turns out that these are very effective at many problems that were not as amenable to earlier techniques. The theory of neural nets has been around a long time, but there has been a recent increase in the practical applicability of them.
- andrewfromx 10y agothere's a really funny paper clip from office 95 joke here somewhere.
- hindsightbias 10y agoIt's funny, the internet isn't old enough to find links to the CYC project in Austin that blew through hundreds of millions of DoD money in the 80's and early 90's. What's old is new.
- Animats 10y agoCyc and Lenat are still around.[1] Here's Lenat at SXSW 2016.[2] [1] http://www.businessinsider.com/cycorp-ai-2014-7 http://www.businessinsider.com/cycorp-ai-2014-7 [2] https://vimeo.com/158956032 https://vimeo.com/158956032
- graycat 10y agoSo, Microsoft is going to put 5000 people on applications of artificial intelligence (AI). Likely they will also include machine learning (ML). IMHO, there is some value there. But, IMHO they would be better off just drawing all they can, including AI/ML but much more from the QA section of research libraries. There they will find oceans of material, where in comparison AI/ML look like farm ponds, in pure and applied math as math but also operations research, statistics, optimization, control theory, applied probability, stochastic processes, mathematical finance, mathematical parts of high end electronic engineering, signal processing, experimental design, quantitative methods in business, and much more.
- thr0waway1239 10y agoDespite the general positive spin around it ("we did it as a learning project"), most people would agree that Tay was both a technical and a PR failure. But the pattern does repeat: Microsoft releases an AI which fails. Tesla's autopilot cannot "see" white object on white background. Apparently, Google also had a crash which is recently being claimed as human error. My guess is that this list is not going to stop here. Suppose I ask you to build me a teleporting machine. You try, and like the movie Spaceballs, my torso and up comes out aligned wrong. This is now declared part of the iterative learning process, except that the cost borne by the corporations for the failure is quite minuscule compared to the cost borne by the affected party (risk asymmetry). So while people talk about the huge advancements in AI, shouldn't we be quite skeptical especially at this point? Since none of us have seen the alternate parallel universes, and considering a) the resources being thrown at the problem b) the risk asymmetry involved c) the privacy intrusion involved in the data collection (you knew I would bring it up, didn't you?) and not to mention d) the inability of anyone to demand any kind of transparency from these AI pioneers I can as well ask, are we as a society paying too high a cost for this progress? Could we really not do any better than this?
- danielsada 10y agoCertainly interesting ideas, but we only need an AI that is better than the current paradigm. If Teslas doesn't detect a white object, it is not as heavy as a human sleeping in the wheel. So if Tesla's kill 30k people a year, but humans die in the wheel at 120k people a year, an improvement would be nice, as it avoids 90k deaths a year. So if we are already using teleporting machines (and we accept the tradeoffs of using it, like cars) and 1 in a million fails, if AI makes a failure in 1 in 10 million, clearly we should use that technology right? So as Elon musk said recently: "Whatever this thing is you are trying to create.. What would be the utility delta compared to the current state of the art times how many people it would affect?" The wonderful thing about this AI algorithms is that we can rate them on their efficacy, they might be a black box, but the input and output are always known. If we see that google crashes 10x more cars, we wouldn't use their AI.
- thr0waway1239 10y ago