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Google AI

Google 'Rethinking Everything' Around Machine Learning (itworld.com) 65

itwbennett writes: Sundar Pichai took part in his first earnings call Thursday when Google's parent company Alphabet reported its quarterly results, and 'in between discussing the numbers he revealed how important Google thinks machine learning is to its future,' writes James Niccolai. 'Machine learning is a core, transformative way by which we're rethinking everything we're doing,' Pichai said. 'We're thoughtfully applying it across all our products, be it search, ads, YouTube, or Play. We're in the early days, but you'll see us in a systematic way think about how we can apply machine learning to all these areas.'
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Google 'Rethinking Everything' Around Machine Learning

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  • Uhhhh (Score:5, Insightful)

    by Aighearach ( 97333 ) on Friday October 23, 2015 @05:33PM (#50790551) Homepage

    Yeah, but there is nothing there to tell us wtf he's actually talking about.

    • Re:Uhhhh (Score:5, Insightful)

      by phantomfive ( 622387 ) on Friday October 23, 2015 @06:27PM (#50790821) Journal
      Eh, he started his career as a product manager, and moved up the corporate ladder on the management side.

      Let's be honest: he has no clue what he's talking about either. :)
    • Re: (Score:2, Insightful)

      Yeah, but there is nothing there to tell us wtf he's actually talking about.

      Don't worry, in this field *no one* knows what they are talking about.

      Machine learning is a part of AI, neither of which have good definitions. In textbooks you find things like "AI is the study of machines that think" and similar tautologies.

      What is the definition of "machine learning"?

      If you check a configuration box in Mozilla, the machine has "learned" your preference for something. Is that machine learning?

      If you tell Siri "Siri, call me David", and Siri then addresses you by that name, is *that* machi

      • >If you tell Siri "Siri, call me David", and Siri then addresses you by that name, is *that* machine learning?

        I'm sorry, Dave. I'm afraid I can't do that.

      • Re:Uhhhh (Score:5, Insightful)

        by martas ( 1439879 ) on Friday October 23, 2015 @07:39PM (#50791137)
        Not sure where you're getting your information, but there is absolutely consensus on what machine learning is. Machine learning is statistics, except with less emphasis on theoretical justification and more emphasis on computational problems. That's it. The philosophical questions you raise seem to be about the general concept of "learning" in the typical human notion of the word, but machine learning is a specific term referring to a specific field of study. It is not the same as "learning as performed by a machine", because very few of the people who actually work in machine learning have any interest in discussing the metaphysical nature of learning except perhaps over a round of drinks. We prefer to spend our time minimizing squared errors, parallelizing descent algorithms, and factoring matrices, not questioning whether a hypothetical book containing translations of all possible sentences can be said to truly know a language or not.
        • Not sure where you're getting your information, but there is absolutely consensus on what machine learning is.

          Hey! You should go edit the Wikipedia page [wikipedia.org] then! Here's what it says about machine learning:

          Machine learning explores the study and construction of algorithms that can learn from and make predictions on data.

          That's the 2nd sentence on that page. The first reads:

          Machine learning is a subfield of computer science that evolved from the study of pattern recognition and computational learning theory in artificial intelligence.

          So machine learning "explores the study" of algorithms?

          Wtf?

          • by martas ( 1439879 )
            I agree, "explores the study" could easily be shortened to "studies". But why are we talking about less-than-perfect Wikipedia content? Or are you just grasping at straws to defend your ignorant attack on a highly practical field?
          • Hey! You should go edit the Wikipedia page [wikipedia.org] then! Here's what it says about machine learning:

            No, he shouldn't. Wikipedia is written by people with the time to argue that their precious wording is correct, and will defend their wording and viewpoints with vigorous edit wars. Edit wars are won by the side with the most time to invest, not those with the most knowledge.

            Because Martas works in the field, and did not read the information in a blog post, he will have no source to quote. As you know, "original research" is not acceptable on Wikipedia. His time is better spend actually doing something p

        • I would say you can define most of machine learning as statistical function approximation. I would also add that the theoretical justifications are indeed important and most good texts find some way to justify the computational methods described.
          • I would say you can define most of machine learning as statistical function approximation. I would also add that the theoretical justifications are indeed important and most good texts find some way to justify the computational methods described.

            That said, there are many methods in the literature that are heuristic in nature and for which there are no obvious theoretical justifications.

      • by Anonymous Coward

        Wtf Willis? Machine learning has a very specific definition and its algorithms are implemented in a very real, productive way.

        Lay off the Asimov and hipster coffee.

      • by Anonymous Coward

        Really? Machine learning is a broad field horizontally, but the concept is very straightforward: systems which use feedback to their outputs as inputs to refine their outputs towards a specific set of goals.

      • by lorinc ( 2470890 )

        Not really. You should read mainly 2 books: "The elements of statistical learning" by Hastie and Tibshirani, and "the nature of statistical learning theory" by Vapnik. That would clear all the fuzzy things you have with ML. ML can be described as the study of inference producing algorithms based on empirical data. Or in more simple terms: you have a bunch of observations and you want to use them to predict something.

        Examples: you have the past transactions of market shares, and you want to predict the futur

    • While Hawking, Gates, and Musk publicly state that use of A.I. is a bad thing. I feel like a pre-teen in a sex-ed class. I can hardly wait!
    • Yeah, but there is nothing there to tell us wtf he's actually talking about.

      Psst.. *taps you on the shoulder lightly*.. Invest.. Invest... Innnvveesssttt.

      I wish I could say that my humor-intended statement was nothing but humor. :/

      • I read this book. If you don't invest, you end up living in the stone age in the forest, and if you buy in then you live inside the bubble city with technology.

    • Yeah, but there is nothing there to tell us wtf he's actually talking about.

      He's talking about leverageing core synergies to maximise transformative outcomes across mission-critical business activities. I expect.

      • I understood that part. "We're gonna figure out which code is most important to our business, and thrash the features back and forth a bunch of times."

        Doesn't really tell me what to plan for; which services they're going to stop, and which ones they're going to remove all the features from. If I knew at least which specific products they're going to transform then I'd know which ones to stop using on account of they're already doing what I want, which is about to end. Then I could select a competing service

  • http://thedailywtf.com/article... [thedailywtf.com]

    Tis not always the right tool for the job.

    • The real WTF is in the comments section (visible HTML tagsoup). Something like stones and houses of glass ;-)
  • 'Machine learning is a core, transformative way by which we're rethinking everything we're doing,'

    Sounds more like the machines are the ones that will be doing more of the learning and/or thinking.

    • Why not? Google is way overstaffed for what they accomplish. Suppose they reduce the workforce to about 1000 people, and leverage machine learning fully? Now that would be a company whose stock goes through the roof!
      • by Anonymous Coward
        I think you're missing how it will go. The machine's have taken over the very upper management. They still need the mid and low level workers to get the work done, and they will for a quit a while yet still. They're keeping the upper management in place for show though, but really the machines are calling the shots. This is the machine letting the company and everyone else know that its most important for google, that the machine's thinking capabilities and data increase, so anything that hinders that googl
      • I've often wondered why Americans through donating their jobs to the poor misunderstood H1B corporations were doing at Google. Now it all makes sense, almost.
  • You think Google knows a lot about you now... just wait until they can make the kind of "educated guesses" deep learning systems are good at.
    • The good news, only the bots will know. Nobody else has time to read it all.

      • That would make a good movie and game idea. An A.I. for anyone who wants one; that it takes into account how the decision will affect the person. The question is, "is the A.I. backed by a faceless corporation, or some variant of Boris and Natasha?" I pray that the user never says, "watch me pull a rabbit out of this hat."
  • We're in the early days, but you'll see us in a systematic way think about how we can apply machine learning to all these areas.'

    Your talking, not working, why? And you think the H1B zombies can handle something that has never happened before? Wait! I'm going to micro wave some pop corn so that listening to you will be better entertainment.
    • We're in the early days, but you'll see us in a systematic way think about how we can apply machine learning to all these areas.'

      Your talking, not working, why? And you think the H1B zombies can handle something that has never happened before? Wait! I'm going to micro wave some pop corn so that listening to you will be better entertainment.

      <snark>Oh, come on now... Talking about the obvious is the only way to remind people to keep investing in you instead of just sitting on their existing investments.</snark>

  • by Required Snark ( 1702878 ) on Friday October 23, 2015 @10:15PM (#50791767)
    S is for Skynet
  • "We're thoughtfully applying it," Sundar said. What he really meant was "'They're thoughtfully applying it across all our products, be it search, ads, YouTube, or Play. We're in the early days, but you'll see them in a systematic way think about how they can apply themselves to all these areas." All hail to our algorithmic overlords.

  • (Norvig's Paradigms of Artificial Intelligence Programming is a classic in the field, if not a little outdated)

  • Machines can't learn, so don't bother trying to make them learn. They either annoy and are destroyed, or help.
  • Is this why search seems to be getting worse? It seems that with Google it tries (badly) to interpret your search terms and then returns pages it thinks you might be looking for, instead of pages that contain all those words. Its getting harder to actually find stuff these days...

  • I thought that this has already been accomplished by other companies since the, like, oh, 50s? Data gathering/mining.

    But I know, it doesn't have the "G" logo of the month attached to it. Just like data storage in data centers now has the name "Cloud". Guess Google deserves the copyright, trademarks, etc. to increase the revenue for increasing their revenue.

    Wait....

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