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Why Google Hired Ray Kurzweil

Posted by samzenpus on from the getting-the-scoop dept.

An anonymous reader writes "Nataly Kelly writes in the Huffington Post about Google's strategy of hiring Ray Kurzweil and how the company likely intends to use language translation to revolutionize the way we share information. From the article: 'Google Translate is not just a tool that enables people on the web to translate information. It's a strategic tool for Google itself. The implications of this are vast and go beyond mere language translation. One implication might be a technology that can translate from one generation to another. Or how about one that slows down your speech or turns up the volume for an elderly person with hearing loss? That enables a stroke victim to use the clarity of speech he had previously? That can pronounce using your favorite accent? That can convert academic jargon to local slang? It's transformative. In this system, information can walk into one checkpoint as the raucous chant of a 22-year-old American football player and walk out as the quiet whisper of a 78-year-old Albanian grandmother.'"

13 of 117 comments (clear)

  1. Awesome post by iliketrash · · Score: 3, Insightful

    OK--this is probably the stupidest and worst-informed /. post I have ever seen.

    1. Re:Awesome post by spazdor · · Score: 4, Informative

      Many of the "language processing" problems the OP describes are actually "cognition" problems. If Google is serious about algorithmically translating from "academic jargon to local slang", then they're looking at writing an AI which can in some sense understand what is being said.

      I guess it's a good thing Kurzweil's on board.

      --
      DRM: Terminator crops for your mind!
    2. Re:Awesome post by Genda · · Score: 4, Interesting

      You need to investigate the entire initiative Google is spearheading around its acquisition of Metaweb. They are building an ontology for human knowledge, and are ultimately building the semantic networks necessary for creating an inference system capable of human level contextual communication. The old story about the sad state of computers' contextual capacity, recounts the story of the computer that translates the phrase "The spirit is willing, but the flesh is weak." from English to Russian and back and what they got was "The wine is good but the meat is rotten."

      The new system won't have this problem. Because it will instantly know about the reference coming from the Bible. I will also know all the literary links to the phrase, the importance of its use in critical historical conversations, The work of the Saints, the despair of martyrs, in short an entire universe of context will spill out about the phrase and as it takes the conversational lead provided by the enquirer it will dance to deliver the most concise and cogent responses possible. In the same way, It will be able to apprehend the relationship between a core communication given in context 'A' and translate that conversation to context 'B' in a meaningful way.

      Ray is a genius for boiling complex problems down into tractable solution sets. Combine Ray's genius with the semantic toy shop that Google has assembled, and the informational framework for an autonomous intellect will become. The real question is how you make something like that self aware. There's a another famous story about Helen Keller, before she had language. symbolic reference, she lived like an animal. Literally a bundle of emotions and instincts. One moment, one utterly earth shattering moment there was nothing, then Annie Sullivan her teacher placed her hand in a stream of cold water and signed water in her palm. Ellen understood... water. In the next moment Ellen was born as a distinct and conscious being, she learned that she had a name, that she was. I don't know what that moment will look like for machines, I just know its coming sooner than we think. I also can't be certain whether it will be humanities greatest achievement or our worst mistake. That awaits seeing.

    3. Re:Awesome post by TapeCutter · · Score: 3, Insightful

      I would say that Keller already "knew she was", she just didn't have the mental tools to describe it to herself or others, the "internal dialogue" that gives us an ever present narrative in a modern human's mind is impossible without language. If you get into a highly emotional state (such as rage or terror), the narrative is silenced and the senses are more acute, reflexive responses take over, adrenaline pumps through you, pain is suppressed. A champion boxer wins because he is in control of his emotions, if he loses that control for an instant his opponent may very well lose an ear.

      What astounds me is the mild interest in IBM's Jeopardy winning computer, to me it's comparable to the moon landing (which I witnessed), when you question the unimpressed it's clear they don't understand the difficulty of the problem or the significance of the win. Sure the game of Jeopardy is a restricted domain, but it's far broader than what's needed for a search engine that is "smart" enough to "understand" it's user and ask pertinent follow up questions. However that's not where I see the biggest impact on society, the most significant impact will come from widely available and "cheap" expert systems that use this technology, an "academic in a box" that professionals can kick under their desk and consult at will (much like software developers use google as their default documentation but with far less frustrations and dead ends). We already have machines that can organise and rummage through the world's knowledge far better than humans can do with a manual system, for instance software developers such as myself are constantly referring to google for advise on esoteric questions.

      What we are starting to see are machines that can make sense of that pile of factoids significantly better than humans can, machines that understand natural language (or at worst the subset that is human text), they can relate facts, discover new patterns, create and test novel hypothesis to discover new facts within existing data. Sure it takes 20 tons of air-conditioning alone for a "computer" to beat the speed and accuracy of the small blob of jelly inside the head of a Jeopardy champion but the basic "AI"* problem has been well and truly cracked over the last decade, squeezing it into an iphone or scaling it up to a totalitarian demigod is now an engineering problem.

      AI* - as opposed to what is known as the "hard problem of consciousness". The kind of AI that would pass the basic idea of a Turing test for the majority of people, you can claim that such a machine is "intelligent" or argue against it, in a pragmatic sense it's irreverent since there is no agreed definition of "intelligence". Attributes such as intelligence and understanding are applied to computers because we don't have any other words that describe their behavior. Listen to any developer explaining a bug, you will hear expressions such as "it thinks X", "it wants Y", these are universal metaphors for discussing computers, not a description of reality, it's how humans communicate about the behavior of ALL objects (particularly animated ones) and is intimately related to mankind's highly evolved (and innate), "theory of mind".

      --
      And did you exchange a walk on part in the war for a lead role in a cage? - Pink Floyd.
  2. He did an interview with NPR on this subject. by Kenja · · Score: 5, Informative

    The main thing he says he will be working on is artificial intelligence that can understand "context". The goal is for Google search to be able to find pages etc based on what you mean rather then on word counts of what you type.

    --

    "Have you ever thought about just turning off the TV, sitting down with your kids, and hitting them?"
    1. Re:He did an interview with NPR on this subject. by Anonymous Coward · · Score: 5, Funny

      I've spent 10 years learning to think like a search engine if this ruins everything and makes me spend another 10 years to learn to think like a normal person again just so the search engine can translate my thoughts correctly I am gonna be pissed.

    2. Re:He did an interview with NPR on this subject. by Anonymous Coward · · Score: 3, Insightful

      That's great, but I wish they'd somehow find it in their hearts to turn back on exact word matching, even if it's obscurely hidden.

  3. Languages cannot all be translated into each other by MisterSquid · · Score: 3, Interesting

    That can convert academic jargon to local slang? It's transformative.

    That right there is going to be one hell of a translation. Presuming all statements from one language can be translated into statements in a different language assumes (or seems to assume) that languages are isomorphic.

    However, there are things that cannot be communicated in the limited vocabulary available to, say, a young adult compared to the expansive vocabulary of, say, a scholar of comparative literature. The same applies for concepts that can only be delivered in medical specialized terminology (disparagingly referred to as "jargon") an that cannot be communicated in layperson language.

    None of which is to say that some ideas (even very important ideas) cannot be translated across linguistic groups, but the idea that Google and Kurzweil are somehow going to produce the Internet equivalent of a Babel Fish is nothing more than a wish.

    --
    blog
  4. Google Could use some Fresh Ideas in AI by slacka · · Score: 3, Interesting

    This is a great move for Google's AI research, since their current Director of Research,Peter Norvig, comes from a mathematical background and is a strong defender the use of statistical models that have no biological basis.[1] While these techniques have their use in specific areas, they will never lead us to a general purpose strong AI.

    Lately Kurzweil has come around to see that symbolic and bayesian networks have been holding AI back for the past 50 years. He is now a proponent of using biologically inspired methods similar to Jeff Hawkins' approach of Hierarchical Temporal Memory.
    Hopefully, he'll bring some fresh ideas to Google. This will be especially useful in areas like voice recognition and translation. For example, just last week, I needed to translate. "We need to meet up" to Chinese. Google translates it to (can't type Chinese in Slashdot?)
    , meaning "We need to satisfy". This is where statistical translations fail, because statistics and probabilities will never teach machines to "understand" language.

    Leaders in AI like Kurzweil and Hawkins are going to finally crack the AI problem. With Kurzweil's experience and Google's resources, it might happen a lot sooner than you all expect.

    [1] http://www.tor.com/blogs/2011/06/norvig-vs-chomsky-and-the-fight-for-the-future-of-ai

    1. Re:Google Could use some Fresh Ideas in AI by raddan · · Score: 5, Insightful

      Yeah, but there's a reason why statistical models are hot now and why the old AI-style of logical reasoning isn't: the AI stuff only works when the input is perfect, or at least, planned for. As we all know, language doesn't really have rules, just conventions. This is why the ML approach to NLP is powerful: the machine works out what was probably meant. That's far more useful, because practically nobody writes well. When Abdur Chowdhury was still Twitter's main NLP guy, he visited our department, and guess what-- people even write in more than one language in a single sentence! Not to mention, in the old AI-style approach, if you fill a big box full of rules, you have to search through them. Computational complexity is a major limiting factor in all AI problems. ML has this nice property that you can often simply trade accuracy for speed. See Monte Carlo methods.

      As you point out, ML doesn't "understand" anything. I personally think "understanding" is a bit of a squishy term. Those old AI-style systems were essentially fancy search algorithms with a large set of states and transition rules. Is that "understanding"? ML is basically the same idea except that transitioning from one state to another involves the calculation of a probability distribution, and sometimes whether the machine should transition is probabilistic.

      I think that hybrid ML/AI systems-- i.e., systems that combine both logical constraints and probabilistic reasoning-- will prove to be very powerful in the future. But does that mean these machines "understand"? If you mean something like what happens in the human brain, I'm not so sure. Do humans "understand"? Or are we also automata? In order to determine whether we've "cracked AI", we need to know the answers to those questions. See Kant and good luck.

    2. Re:Google Could use some Fresh Ideas in AI by raftpeople · · Score: 3, Informative

      "Leaders in AI like Kurzweil and Hawkins"? Are you sure you're following who is making real progress in "AI" or at least machine learning? Go check out people like Hinton.

  5. The Bayesian Bandwagon by qbitslayer · · Score: 5, Interesting

    The problem with people like Kurzweil, Jeff Hawkins, the folks at the Singularity Institute and the rest of the AI community is that they have all jumped on the Bayesian bandwagon. This is not unlike the way they all jumped on the symbolic bandwagon in the last century only to be proven wrong forty years later. Do we have another half a century to waste, waiting for these guys to realize the error of their ways? Essentially there are two approaches to machine learning.

    1) The Bayesian model assumes that events in the world are inherently uncertain and that the job of an intelligent system is to discover the probabilities.
    2) The competing model, by contrast, assumes that events in the world are perfectly consistent and that the job of an intelligent system is to discover this perfection.

    Luckily for the rest of humanity, a few people are beginning to realize the folly of the Bayesian mindset. When asked in a recent Cambridge Press interview, "What was the greatest challenge you have encountered in your research?", Judea Pearl, an Israeli computer scientist and an early champion of the Bayesian approach to AI, replied: "In retrospect, my greatest challenge was to break away from probabilistic thinking and accept, first, that people are not probability thinkers but cause-effect thinkers and, second, that causal thinking cannot be captured in the language of probability; it requires a formal language of its own."

    Read The Myth of the Bayesian Brain for more, if you're interested.

    1. Re:The Bayesian Bandwagon by VortexCortex · · Score: 5, Insightful

      1) The Bayesian model assumes that events in the world are inherently uncertain and that the job of an intelligent system is to discover the probabilities.
      2) The competing model, by contrast, assumes that events in the world are perfectly consistent and that the job of an intelligent system is to discover this perfection.

      Then you have AI (machine intelligence) researchers like myself who realize that the world isn't persistent, perfect or consistent, and neither must intelligent systems be. It's plainly obvious that any sufficiently complex cybernetic (feedback loop) system is indistinguishable from sentience because that's what sentience is (your mind is merely a sentient cybernetic system). I have but to look at the hierarchical neural networks and structures of the human mind to realize it's only a matter of time before the artificial system complexity eclipses our own minds'. The true flaw is top-down thinking. That's not the way complex life was made, that's not the way we achieved sentience, that's not the way to cause it to happen artificially either... It's the bottom up approach that works. You can't design sentient intelligences outright, but you can create self organizing systems that have the capacity to acquire more complexity, and evolve more intelligence. Not all machine intelligence systems have an end to the training process -- These don't fit into your bullshit 1) and 2) classifications.

      Also: The level of intelligence that emerges from any complex system is not artificial, it is real intelligence; That the medium is artificial is not important in terms of intelligence. I think "Artificial Intelligence" is a racist term used by chauvinists that think human intellect is far more special than it really is.

      Want to see something funny? Ask an AI researcher if they believe in Intelligent Design. If they say "Yes" then say, "So you think yourself a god?" If they say, "No" then say, "What do you call yourself doing then?". Those working in emergent intelligence will happily reply that they're modeling the same processes that we already know work in nature, the others will be in quite a state!