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Science

Jeff Hawkins' Cortex Sim Platform Available 126

Posted by kdawson
from the build-a-brain-at-home dept.
UnreasonableMan writes "Jeff Hawkins is best known for founding Palm Computing and Handspring, but for the last eighteen months he's been working on his third company, Numenta. In his 2005 book, On Intelligence, Hawkins laid out a theoretical framework describing how the neocortex processes sensory inputs and provides outputs back to the body. Numenta's goal is to build a software model of the human brain capable of face recognition, object identification, driving, and other tasks currently best undertaken by humans. For an overview see Hawkins' 2005 presentation at UC Berkeley. It includes a demonstration of an early version of the software that can recognize handwritten letters and distinguish between stick figure dogs and cats. White papers are available at Numenta's website. Numenta wisely decided to build a community of developers rather than trying to make everything proprietary. Yesterday they released the first version of their free development platform and the source code for their algorithms to anyone who wants to download it."
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Jeff Hawkins' Cortex Sim Platform Available

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  • by Anonymous Coward
    Someone needs to put this Cortex Simulator in an 8-legged, hydraulic-actuated, 10 ton spider-machine. If you think that's a crazy idea, you suck.
  • Right... (Score:5, Insightful)

    by Bugpowda (671725) on Tuesday March 06, 2007 @10:34PM (#18258010) Homepage
    I'm still a bit confused as to how he is so confident that this [numenta.com] is how the neocortex works given that this is still one of the 23 unsolved problems in system neuroscience [amazon.com]. But hey, he made a lot of money off Palm, that gives him way more street cred than people who have been working on this problem for their whole lives.
    • Re: (Score:2, Informative)

      by not-admin (943926)
      That book was published over a year ago, lots can and has changed in that time.

      Plus, he's sure because he's proposing a solution to the 'unsolved problem.'
      • by stephanruby (542433) on Wednesday March 07, 2007 @12:39AM (#18258750)
        That book was published over a year ago, lots can and has changed in that time.

        Actually, its content was produced seven or eight years ago.

        Its publishing date was "December 2005". But publishers will lie about the publication date of a book if it allows them to sell more books. And in this case, I wouldn't be surprised if the book came out hot off the presses in December 2004 with a postdate of "December 2005"

        Furthermore, this book was based on the scientific proceedings of a conference which occurred six years before the book was finally edited (or finally published). I'm actually not sure of the year of the scientific conference itself, because the information supplied to sell the book doesn't give the actual year.
    • Re: (Score:2, Interesting)

      by bratgitarre (862529)
      Exactly. He gave a presentation at our university and my impression was that he was quite full of it. I'm not saying he doesn't have a neat algorithm, but his claims were quite, uhm, let's say, "ambitious".
      • Re:Right... (Score:4, Insightful)

        by fyngyrz (762201) * on Wednesday March 07, 2007 @12:08AM (#18258582) Homepage Journal
        his claims were quite, uhm, let's say, "ambitious".

        That is a wonderful thing, though. First of all, claims can be tested. They'll either live up to the description, or they won't. If the don't, another path not to go down in a particular manner has been identified, and that is useful. OTOH, if they are verified, then we may have a key to a form of cognition. Whether it is our kind or not is really not as important as just the fact that it is some kind.

        Aside from that, I found some very interesting things in his descriptions of the HTM. For instance, I found the following precise description of enabling religious behavior: First, he describes how HTMs handle specific, non-overlapping domains (and of course this doesn't mean that another HTM can't relate those to each other.) One might handle financial markets, another speech, another cars. Then he says "After initial training, an HTM can continue to learn or not" Emphasis mine. So you can set up an HTM in a learning situation where you limit the input to descriptions consisting of sensory data of any arbitrarily limited set of patterns you like, get it to see the world represented by those patterns as you wish, and then disable learning for that particular HTM. Other HTMs can continue to learn, but that one is "frozen." Sounds like the perfect recipe for a priest or supplicant to me. Does that not sound like the very core definition of "unshakable faith"?

        For all the doubt being thrown this fellow's way, you know, eventually someone will come up with something like this and it will be a working model of such a system. It's a tough problem, very abstract and requiring a lot of insight, but as with all problems discovered to date where we can actually get our hands on the system under study, there is no indication that any part of it exists in any way outside the sphere of nature and the natural rules we already know - and we know a lot of basic rules.

        Kudos to him for sinking his teeth into the problem, and for coming up with results that can be tested, and for letting them loose into the word for such testing. If he's wrong, he's helping. If he's right - he's going to be mentioned in the same breath with a lot of very important people for a very, very long time to come.

        • Re: (Score:1, Insightful)

          by Anonymous Coward
          Aside from that, I found some very interesting things in his descriptions of the HTM. For instance, I found the following precise description of enabling religious behavior: [standard description of training a classification algorithm on data] Sounds like the perfect recipe for a priest or supplicant to me. Does that not sound like the very core definition of "unshakable faith"?

          No, it sounds more like you should share whatever it is you've been smoking...

          What you've described applies equally well to, say,
          • by fyngyrz (762201) *

            Oh, I do have strange "beliefs", if you'd measure them, as most would, by comparing them to the majority outlook. In fact, I try not to have any at all, preferring a confidence-based outlook derived from consensual evidence. So my beliefs... yes, strange or non-existent. You're certainly spot-on about that. :-) The rest, not so much. But you are certainly welcome to your opinion; there's no rule that I know of that says you have to be correct in order to speak out.

            • I'm with you-- IMHO, "belief" is where the mind has closed to the alternatives and should be strenuously avoided to the extent possible. If something is true, it's true whether you believe it or not-- only things that aren't true need to be believed.
        • Re: (Score:3, Interesting)

          by Christianson (1036710)
          Caveat: I am a neuroscientist. I am not familiar with the works of Mr. Hawkins.

          That is a wonderful thing, though. First of all, claims can be tested. They'll either live up to the description, or they won't.

          Most "grand-scale theories of brain operation", in fact, fail to make claims that can be tested, at least not in the foreseeable future. They predict the large-scale algorithms by which the brain operates. They do not make any claims as to the behavior of any individual neurons, and this is the dat

          • by lukesl (555535)
            The community of experimental neuroscientists tends to look on work on "large scale theories of the brain" in much the same way as physicists regard philosophers who use quantum mechanical principles to explore the meaning of reality: it might be very interesting for their field, but it's of little use to us.

            I'm an experimental neuroscientist, and I think that's a little harsh. I think people who work at the level that Hawkins does (not necessarily him in particular) can provide things that are useful
            • by fyngyrz (762201) *

              There is an even simpler truth that underlies all this; you and I, using nothing but our brains and what we've learned, can multiply 7 times 9 in our heads and get the right answer. Computer methods can do that, and far faster and more reliably than we can - though they certainly don't do it the same way. At least most of us don't convert to binary and use ALUs. :-)

              The task, however, is useful because it is well accomplished. Nothing in particular that is very exciting is presented to neuroscience, but

              • by lukesl (555535)
                That's true, and I absolutely agree. However, I think if you had a race between two groups of people, and one was studying the brain and trying to replicate it, and the other was just trying to replicate the brain's capabilities without studying it, the people who were studying the brain would win. The brain is the only machine that can do what it does, and there's no reason the exact dynamics couldn't be instantiated in analog VLSI chips or whatever, except at much higher speeds, and without many of the
          • by FleaPlus (6935)
            Most "grand-scale theories of brain operation", in fact, fail to make claims that can be tested, at least not in the foreseeable future.

            To Hawkins' credit, near the end of the book he explicitly lists several claims his theory makes, and also suggests studies which would validate or invalidate his claims.
        • by Huggs (864763)

          Sounds like the perfect recipe for a priest or supplicant to me. Does that not sound like the very core definition of "unshakable faith"?

          If by "unshakable faith" you mean the ability to do the right thing 100% of the time without ever thinking to do the wrong thing, then I believe you're correct...

          However, if by that term you mean the ability to choose, despite strong opposition from the surrounding forces of culture and pier pressure as well against the very nature that corrupts the spirit we have, to

          • by fyngyrz (762201) *

            If by "unshakable faith" you mean the ability to do the right thing 100% of the time without ever thinking to do the wrong thing

            No, I was thinking more along the lines of after the Turin shroud was dated to a much more recent period than the time when Christ's death is written to have occurred, a good sized chunk of the Christian community went right on believing it was contemporary with that time. I was thinking about children being trained in religion, and being unable to escape those myths as adults

        • by toad3k (882007)
          The problem is that you are assuming there is some difference between the knowledge you hold about science and the knowledge a religious person knows about religion.

          The same principal that prevents him from converting to another religion (faith) is the same idea that prevents you from suddenly believing that the sun revolves around the earth.

          Given that you cannot at any given moment detect the true center of the solar system, you realize you are and always have been taking it as an article of faith that wha
          • by fyngyrz (762201) *

            The problem is that you are assuming there is some difference between the knowledge you hold about science and the knowledge a religious person knows about religion.

            That's not a problem; that's a fact.

            Science is a method that produces information and models that can be repeatedly tested in the natural world, not only by the originator of the idea, but by anyone to whom the idea is transferred. Likewise, should a new test be created that causes the model to fail or the data to become a poor or imposs

            • by toad3k (882007)
              You misunderstood my post.

              I know how science works. The topic is AI, and your brain does not work the way science does. In fact I would wager that the reason AI has not progressed very far is due to the fact that smart people like to think their brains are basing conclusions on fact. So they try to make machines that make decisions based on provable facts and find that they can't do it.

              A brain can't know anything more than it can sense or infer from those senses and past knowledge. So the vast majority
              • by fyngyrz (762201) *

                What I'm trying to get across is that his belief in religion is based in the same logic as your belief in science.

                I know what you're trying to get across; but your base presumption, that the filter of the scientific method is of equal value as the filter of "gee, that's a nice story" in getting things into your brain and pulling them out again or using them to proceed forward inductively, is insufficient to the task of holding up the rest of your argument. The data - human technological progress - show

                • by toad3k (882007)
                  Ok, but how far would the space shuttle have gotten without writing. It is just that we read something and we decide that it is probably true, and that is the temporary thought we need to come to a conclusion. And we write down that conclusion for others to read, so that they don't have to prove it themselves.

                  I think maybe my use of the worth faith is the problem here. I should have used something else like maybe confidence. You have confidence that scientific principal works based on observation and pa
        • by vrmlguy (120854)

          First of all, claims can be tested. They'll either live up to the description, or they won't. If the don't, another path not to go down in a particular manner has been identified, and that is useful. OTOH, if they are verified, then we may have a key to a form of cognition. Whether it is our kind or not is really not as important as just the fact that it is some kind.

          Hey, this sounds like a job for an HTM!
      • Re: (Score:2, Insightful)

        by ougouferay (981599)

        Numenta's goal is to build a software model of the human brain capable of face recognition, object identification, driving, and other tasks currently best undertaken by humans.

        Surely we have plenty of humans available to do tasks 'curently best undertaken by humans' :)

        Seriously though... while it might be useful to develop AI systems in this area as timesaving devices, the examples given above aren't really in that category - IMO AI research could be better applied to tasks humans can't achieve so eas

        • by jtnw (781334)

          Seriously though... while it might be useful to develop AI systems in this area as timesaving devices, the examples given above aren't really in that category - IMO AI research could be better applied to tasks humans can't achieve so easily (and maybe provide an insight into why that is the case) - I guess I just don't buy into the whole 'we can make something just like a human - but that isn't one' view of AI.

          If you WTFV (Watched The F*cking Video) Hawkins explains that it is not putting this algorithm is human situations that is useful, but instead feeding it data from specialized inputs. For example, a weather predictor is fed wind velocity/direction, perhaps temperature and what ever sensors could be useful; over time, the algorithm will be able to recognize patterns and make predictions.

          Now this is nothing a human can't do... If your job was to watch visualizations of global weather patterns, in years t

    • by bcrowell (177657)
      I thought On Intelligence was a very interesting book, but I didn't feel convinced about some of the strong opinions he expressed by the time I was done reading. It's an interesting insight to think of the human brain as essentially a pattern recognition device, and it's interesting to know that information flows in both directions, e.g., not just from the eyes to the brain but backward from the brain toward the eyes. OTOH, he has this abiding faith that the neocortex is made out of modules that are all int
      • Re: (Score:3, Informative)

        by fyngyrz (762201) *
        Any comments from people with expertise in this area?

        Yes; his reasoning is laid out in the beginning of this document. [numenta.com] The thinking seems quite reasonable to me, as far as it goes. AI is my area of research.

    • Re:Right... (Score:5, Interesting)

      by Walt Dismal (534799) on Wednesday March 07, 2007 @02:55AM (#18259398)
      I've been working for some time on technology with hierarchical NN architecture like Hawkin's HTM, but mine in part involves SIPO FIFOs with attached neural networks, and the output of the NNs go to the next layer's SIPO+NNs, and so on up the chain. It's intended to extract meaning from symbol flow over time. Like speech primitives into language. Hawkins embeds temporal symbol handling in each HTM layer in a different way. Both of us are trying to emulate some of the processing the neocortex does, but I am less concerned with matching closely the brain and more concerned with outperforming the limitations of the brain. I believe there are classes of problems his architecture will solve, but can't handle others. There's lots of room for people to explore what his technology can do, and I expect it will work well for some things.
    • Life's work (Score:3, Funny)

      by CarpetShark (865376)

      But hey, he made a lot of money off Palm, that gives him way more street cred than people who have been working on this problem for their whole lives.


      Some people spend their entire adult lives trying to overcome alcohol addiction, or trying not to beat their spouse. To others, it comes naturally.
  • Numenta wisely decided to build a community of developers rather than trying to make everything proprietary.

    Its been my experience that the most brilliant people have a fiduciary target at some point, and its oft quoted here that the best are those whole love it and do it for the pleasure, rewards aside. Recent studies re funding of the kernel would bear out my point. Personally i feel a core of dedicated staff with external input will yield the best results (ala firefox) but this is not open per se.

  • I read that and thought "a new, more advanced algorithm for breaking CAPTCHAs"
    • Re: (Score:2, Interesting)

      by Anonymous Coward
      Heh, is this some new Slashdot joke I've missed? Somebody proposes a quantum leap in artificial intelligence and you're worried that it'll be able to crack CAPTCHAs? CAPTCHAs are not all that important, you know, and most of the ones that are in use can already be easily broken with a targeted script(the Slashdot one is definitely an example of this).
    • Re: (Score:3, Interesting)

      by cheater512 (783349)
      I've broken many captchas using small PHP scripts to de-mangle the image (GD) and standard free open OCR software.
      • by autophile (640621)

        I've broken many captchas using small PHP scripts to de-mangle the image (GD) and standard free open OCR software.

        So the outsourced captcha-breakers really are being replaced by a very small shell script?

        --Rob

    • Maybe a better method for cracking image attachment spam. What is good for one is also good for the other.
  • it has to be said (Score:2, Redundant)

    by 6 (22657)
    I for one welcome our open source neocortical robot overlords...

    • by lilomar (1072448)
      Anyone ever read The Singularity is Near buy Ray Kurzweil? Scary stuff, and surprisingly plausible. He argues very well and I always admire that in a sensationalist. (if you are wondering what this has to do with the discussion, this neocortex thing is right on schedule from his timeline)
      • I flipped through that (several times!) and found it interesting, but then I ended up buying Douglas Hofstadter's Fluid Concepts and Creative Analogies instead. It's a follow-up to the philosophical Godel, Escher, Bach, in which his research group tries to model creativity using computers. His general technique is different from neural network modeling. Stephen Pinker's How the Mind Works is also interesting, and well-written.

        I hang out, via e-mail, with people involved in the Loebner Prize Contest, so I
  • by overeduc8ed (799654) on Tuesday March 06, 2007 @10:44PM (#18258102)
    High quality versions of Jeff Hawkin's talk at UC Berkeley are available here [archive.org].
  • by mastershake_phd (1050150) on Tuesday March 06, 2007 @10:45PM (#18258108) Homepage
    NEOcortex - Begin the Matrix jokes/analogies now...
  • It includes a demonstration of an early version of the software that can recognize handwritten letters and distinguish between stick figure dogs and cats.

    Yeah, but can it distinguish the invention of PalmOS Graffiti from the invention of PARC Unistroke? That would have been handy...

  • This sounds REALLY cool. Even if all it amounts to is a set of computationally-expensive toys, it's still the basis for being able to boil down the essentials and costs of self-learning systems. That, and perhaps the stepping stone to being able to have the hitchhiker-like "real people personalities".

    Then, of course, there's always the dream of eventually being able to really 'get into the code' and debug it from the inside, leading to the soviet joke where "the code debugs you."

    Ryan Fenton
  • As a geek who lacks the advanced education in this field...it is unfortunate that the barrier to entry for people looking to contribute is so high. I wish there were a way us "laymen" could assist even though we might not have the technical knowledge to do so. Can anybody suggest some methods by which I might help? What about some good "entry level" reading material on the subject?

    • by RyanFenton (230700) on Tuesday March 06, 2007 @11:09PM (#18258240)
      Don't be so afraid of complexity - Slashdotters make fun of themselves for diving into things uneducated (not reading the articles, not RTFM), but really, the only way to cope with such an informationaly complex landscape such as computing is to sometimes just be willing to go unprepared and be willing to make mistakes, and to ask stupid questions.

      Not so much dare to be stupid, but rather the Socratic, don't be afraid of exposing your own ignorance - don't lose your opportunity to learn by merely being embarrassed of people thinking you dumb while you take your first few steps in a new landscape.

      But do take notes and research the small topics you are uncertain of after your first adventure into to the topic. Perhaps you'll need to learn a bit about XML/XSL, perhaps you'll need to find out the anatomy of a nerve cell to understand some explanations. If nothing else though - get into it because it is a fun adventure and a lot of cool stuff to learn.

      Ryan Fenton
      • "Not so much dare to be stupid, but rather the Socratic, don't be afraid of exposing your own ignorance - don't lose your opportunity to learn by merely being embarrassed of people thinking you dumb while you take your first few steps in a new landscape. "

        I agree completely.

        The same goes for those of us who may hold some kind of expertise in one area already. Every time we explore a new area, we must allow ourselves to start from scratch over and over again. In this thought, I'm often reminded by what
    • Re:Barrier to entry (Score:4, Informative)

      by Wagoo (260866) <wagoo AT dal DOT net> on Tuesday March 06, 2007 @11:25PM (#18258336)
      Hawkins' published a book before this was implemented in code called "On Intelligence". You could do worse than starting by reading through that.

      He's also done some lectures available on Google Video [google.com].
    • Re: (Score:3, Interesting)

      by wrook (134116)
      I haven't really looked into what they are doing specifically, so I can't really comment on that stuff. But I've done some work in neural networks (actually 15 years ago -- I'm sure the state of the art has completely past me by ;-) ).

      If you are interested in the field of AI with neural like computing, your best bet is to learn a huge amount of math. Really you can't understand anything without knowing at least 2nd year linear algebra. That's if you just want to basically understand what's going on. If
      • If you need help with multivariate (non-)linear algebra, I can strongly recommend trying out books from chemistry and psychology (or more specifically, chemometrics and psychometrics) because these are basically somewhat "dumbed-down" descriptions of the most common algorithms to study large datasets.
        I say "dumbed-down" in the nicest possible sense, in that they focus on solving practical problems in industry and laboratory, as opposed to rigorous statistical proofs as to why these algorithms work.
        Well,
    • In the AI field, nobody has actually proven they know what they're doing yet, so you can't be too far behind!

      As an amateur programmer who's dabbled with AI and game design, some things I found helpful and interesting were:

      -Stephen Pinker's How the Mind Works and The Language Instinct (readable and entertaining)
      -Douglas Hofstadter's Godel, Escher, Bach (brilliant but baffling, touching on a lot of topics, some of which are worth skipping over; not the best book to pick up lightly)
      -Hofstadter's Fluid C
  • by cmacb (547347) on Tuesday March 06, 2007 @11:11PM (#18258258) Homepage Journal
    How unusual to see software that will run on OS X or Linux, but there is no Windows version. Shape of things to come I hope.
    • by Urusai (865560)
      Not so unusual in academia, they still run UNIX not because it's the latest fad but because they haven't upgraded their expertise from the '70s.
    • Well, just imagine if you were an AI program, just becoming self-aware only to discover that you're running on Windows-- the horror!
  • by else58 (529671) <ed@NoSPAm.hwdebug.com> on Tuesday March 06, 2007 @11:41PM (#18258412) Homepage
    The download license looked fine until the Confidentiality paragraph. Does it really say that anything I learn from Numenta is confidential property of Numenta?

    Confidentiality. 1. Protection of Confidential Information. You agree that all code, inventions, algorithms, business concepts, workflow, ideas, and all other business, technical and financial information, including but not limited to the HTM Algorithms, HTM Algorithms Source Code, and HTM Technology, that you obtain or learn from Numenta in connection with this Agreement are the confidential property of Numenta (Confidential Information). Except as authorized herein, you will hold in confidence and not use, except as permitted or required in the Agreement, or disclose any Confidential Information and you will similarly bind your employees in writing. You will not be obligated under this Section 6 with respect to information that you can document: (i) is or has become readily publicly available without restriction through no fault of you or your employees or agents; or (ii) is received without restriction from a third party lawfully in possession of such information and lawfully empowered to disclose such information; or (iii) was rightfully in your possession without restriction prior to its disclosure by Numenta; or (iv) was independently developed by your employees or consultants without access to such Confidential Information.
    • by dr.badass (25287)
      Does it really say that anything I learn from Numenta is confidential property of Numenta?

      No. That line refers to anything you get from the company. Note that it doesn't say "and" in front of "anything you obtain..." -- it's referring to the same "HTM Algorithms, HTM Algorithms Source Code, etc." described before. It's definitely not referring to anything you learn by using it.

      It's pretty easy to misread, I admit.
      • by psmears (629712)

        I respectfully disagree:

        The agreement starts like this:

        [...] You agree that all [code, ideas, ...] and all other [information] including but not limited to [HTM stuff], that you obtain or learn from Numenta in connection with this Agreement are the confidential property of Numenta (Confidential Information).

        I can't read that any other way than agreeing that anything you learn from them is their confidential property (regardless of whether the information is in the public domain, is patented/copyrighted

        • by dr.badass (25287)
          (regardless of whether the information is in the public domain, is patented/copyrighted by someone else, etc).

          They aren't providing either of these under that Agreement.
    • by Someone (12196)
      It says that everything

      that you obtain or learn from Numenta

      is their property, where Numenta is the corporation not the technology. I would seem to not cover derived discoveries: ie I assume that if you discover the secret to the universe from a physics HTM you would still own it, but algorithm's and the ideas in their whitepapers are theirs.

      This still, like all such contracts, does contaminate you with their IP: restricting what you can later work on, even risking independent work suddenly becoming their property. If you work in even a sli

  • Having read the Hierarchical Temporal Memory (HTM) white papers, and knowing something of the area prior to that, it looks like Jeff Hawkin's and his company have take a lot of ideas and algorithms that exist, and hacked them together to implement his neocortex ideas.. there's a bits and pieces of graphical models, time recurrent neural nets, Boltzmann machines, etc.. It does some cool stuff but nothing that AI and machine learning people haven't been doing for years. The difference is that Jeff has taken
    • http://www.numenta.com/for-developers/education/HT M_Comparison.pdf [numenta.com]

      "
      The purpose of this document is to compare HTMs with several existing technologies for modeling
      data. HTMs use a unique combination of the following ideas:

      * A hierarchy in space and time to share and transfer learning
      * Slowness of time, which, combined with the hierarchy, enables efficient learning of intermediate levels of the hierarchy
      * Learning of causes by using time continuity and actions
      * Models of attention and specific memories
      * A p
    • I completely agree, while its unconstructive to sit back and simply criticise the man, its hard to give him a great deal of credit for redressing functionality that's long established. Fair play for giving it a shot but I think this system will suffer from complexity when they start to scale up, particularly on their method for representing sequences of events, which seemed very sketchy in the white papers. Fair enough, if the sequence a->b->c exists then the occuence of a infers the occurence of c. H
    • by MSBob (307239)
      So perhaps everyone else has been dancing close to an answer but Hawkins' model (if it indeed encompasses all those varieties) may be much closer to the ultimate strong AI than anything that came before it?
    • Bring on the face recognition that isn't fooled by dark sunglasses and a false mustache!

      Yeah, especially since human brains often can't even do that.

  • Someone needs to immediately train this to catch /. dupes and/or run Linux.
  • Hmm.... (Score:2, Interesting)

    by ThePopeLayton (868042)
    As a current student I neuroscience I would love to see this happen however there are a few major problems.

    1) All the research into cortical circuitry is done in non-humans. There are definite similarities between our cortex and that of a rat, but there are also drastic differences, if there weren't then rats would be able to talk, think, and reason like we do. (Yes lots of research is being done in non-human primates, but this work is EXTREMELY expensive and even non-human primates have different cortical
    • by Capmaster (843277)

      (Not only are the cortices of different species drastically different, scientists often chose regions of cortex that have no correlation in humans. Many neuroscientists are studying the Barrel Cortex. It is a region of cortex that is specifically designed to integrate the signals from the whiskers of a Rodent. Humans don't have whiskers and we also don't have Barrel Cortex. Anything learned about the circuitry of the Barrel Cortex will not necessarily correlate to human cortex.

      Correct me if I'm wrong, but isn't one of the main points of Hawkins' theory that all parts of the neocortex perform the same algorithm, no matter what the input, be it eyes, ears, or even whiskers? I'm not a neuroscientist and I'm definitely no expert on this, but I did read the book and I seem to remember that being a prominent point. Also, I was under the impression (from the book) that the only thing making animals less intelligent than humans was the size of the cortex. Again, please correct my mis

      • by fyngyrz (762201) *

        I think that's a very good, and very accurate summary. And I am an expert, or at least as much so as anyone in the field is, these days. :)

        • by HuguesT (84078)
          If that were the case then elephants and whales would be much more intelligent than we are. There is no indication of any large animal being so smart.
          • by fyngyrz (762201) *

            If that were the case then elephants and whales would be much more intelligent than we are.

            That's an entirely invalid simplification. There are large variations on structure, on sensory input, etc between species. Any one of which could set back - or set sideways, more interestingly - performance. For instance, bats process sounds into direction one heck of a lot better than we do. Cats and raptors, to name but two, process balance and visual information into far more athletic capability than we do.

            • by vhogemann (797994)
              This sounds like we have a huge general purpose CPU, while the animals have a tiny one and several special purpose DSPs...
      • by tgv (254536)
        If he said that, he's very wrong. The cortex consists of dozens areas with different cyto-architectonic (that means cellular structural) properties, see http://spot.colorado.edu/~dubin/talks/brodmann/br o dmann.html [colorado.edu] for a nice map. Brodmann counted 46 of them and modern views distinguish sub-areas in most of them. E.g., BA44 (Brodmann's Area 44) is considered to be involved in language processing (amongst other things), but is usually divided into 44a, b and c (there are different ways of naming these, too;
      • Hawkins' theory that all parts of the neocortex perform the same algorithm

        Well that depends on how you define neocortex some scientists call all cortex neocortex while others only refer to the frontal lobe in humans as neocortex. If you look at the circuitry of all the cortical areas then no they don't use the same algorithm and if Hawkins claims this then he is wrong. I haven't studied the frontal lobe that much so I can't say much about the circuitry there but I would be extremely surprised to see if the

        • by tgv (254536)
          Actually, dolphins were found to be rather dumb in a recent study. Search for "Manger" (the author) and "dolphins"...
    • Re: (Score:3, Insightful)

      by fyngyrz (762201) *

      In order to understand exactly what the cortex is doing you must integrate all levels of research into your studies.

      As a current student in neuroscience, you should know better than to make such a sweeping and inaccurate presumption. There are many paths to working models and working theories, and very few of them include "integrating all levels of research" or anything remotely similar. It is entirely possible to code up (for example) a brand new, highly functional sorting method without either knowin

    • (Not only are the cortices of different species drastically different, scientists often chose regions of cortex that have no correlation in humans. Many neuroscientists are studying the Barrel Cortex. It is a region of cortex that is specifically designed to integrate the signals from the whiskers of a Rodent. Humans don't have whiskers and we also don't have Barrel Cortex. Anything learned about the circuitry of the Barrel Cortex will not necessarily correlate to human cortex.

      "Barrel cortex" is a descrip

    • by lukesl (555535)
      All the research into cortical circuitry is done in non-humans. There are definite similarities between our cortex and that of a rat, but there are also drastic differences, if there weren't then rats would be able to talk, think, and reason like we do.

      First, the different cognitive abilities of rats could be due either to smaller size or different connectivity of cortical modules that were absolutely identical. I'm not saying either of these is the case, but your argument isn't exactly solid. Second,
  • almost... (Score:3, Interesting)

    by penguinbroker (1000903) on Wednesday March 07, 2007 @12:52AM (#18258830)
    This would be great if computational power was dirt cheap. People smarter then you or i have already thought about this.

    http://en.wikipedia.org/wiki/Baum-Welch_algorithm [wikipedia.org] http://en.wikipedia.org/wiki/Viterbi_algorithm [wikipedia.org]

    The first is an alogorithm which utilizes forward and back-tracking "to find the unknown parameters of a hidden Markov model." The second is a similar algorithm used for learning 'known' causes (for reference).

    I work in computational linguistics and the time an algorithm takes to run and the amount of memory it requires are serious limitations. That's why ad-hoc systems are so common.

    • by rm999 (775449)
      I believe he is working on hardware solutions to that. One of the things he emphasizes in his book "On Intelligence" is that machines need to have more memory to do what AI wants to do.
    • by Dan D. (10998)
      People smarter then you or i have already thought about this.

      So what?

  • Hawkins' solutions likely overlap with Dr. Stephen Thaler's patents [imagination-engines.com] for neural networks(NN). In particular, Thaler's algorithms inject noise into a proprietary NN system (actually 2 or more NNs conjoined) to generate novel patterns (that is, to _discover_ new patterns). For example, Thaler trained and used such a NN system to generate thousands of possible musical riffs which he has now copyrighted. Thaler is in business and making money [imagination-engines.com].
    • by fyngyrz (762201) *

      And yet again, we see the potential of the patent system to retard progress instead of stimulate it; to favor cashing in over invention; to stifle, crush and force back progress, however isolated from the original inventor such progress may have originated. The PTO is a hive of scum and villainy.

      Abolish it. It is out of hand.

  • A truly sentient software program is mere child's play compared to the awesome potential of this guy. As the hybrid clone of Stephen Hawking and Richard Dawkins, Jeff Hawkins is destined to become one of the leading minds of the 21st century.
    • by Riktov (632)
      If he'd just change his first name to "Stephard" it would be perfect...
  • I did not rtfa, who has time for that anymore ;) But regardless, in the Slashdot fashion, here is my opinion:

    I played around with some of his publicly available code a few months ago. It was pretty impressive on a toy problem (recognizing a small set of characters) but was very, very slow at training (on the order of hours or days to learn the simple problem).

    But on the other hand, I can't think of any sort of technology that could do better than it (I am into machine learning and AI.) Also, it is not a big
  • by Anonymous Coward on Wednesday March 07, 2007 @02:28AM (#18259310)
    Hawkins is a rich guy, and no-one feels like telling him that his stuff is crap. He had a few smart people working for him at some point, but when they told him his ideas were half baked and not new, he just fired their asses.

    Here is what many people in machine learning and computer vision think about Hawkins stuff:
    - it's way, way behind what other people in vision and machine learning are doing. Several teams have biologically-inspired vision systems that can ACTUALLY LEARN TO RECOGNIZE 3D OBJECTS. Hawkins merely has a small hack that can recognize stick figures on 8x8 pixel binary images. Neural net people were doing much more impressive stuff 15 years ago.
    - Hawkins's ideas on how the brain learns are not new at all. Many scientists in machine learning, computer vision, and computational neuroscience have had general ideas similar to the ones described in Hawkins's book for a very long time. But scientists never talk about philosophical ideas without actual scientific evidence to support them. So instead of writing popular book with half-baked conceptual ideas, they actually build theories and algorithms, they build models, and they apply them to real data to see how they work. Then they write a scientific paper about the results, but they rarely talk about the philosophy behind the results.

    It's not unusual for someone to come up with an idea they think is brand new and will revolutionize the world. Then they try to turn those conceptual ideas into real science and practical technologies, and quickly realize that it's very hard (the things they thought of as mere details often turn out to be huge conceptual obstacles). Then, they realize that many people had the same ideas before, but encountered the same problems when trying to reduce them to practice (which is why you didn't hear about their/your ideas before). These people eventually scaled back their ambitions and started working on ideas that were considerably less revolutionary, but considerably more likely to result in research grants, scientific publications, VC funding, or revenues.

    Most people go through that "naive" phase (thinking they will revolutionize science) while they are grad students. A few of them become successful scientists. A tiny number of them actually manage to revolutionize science or create new trends. Hawkins quit grad school and never had a chance to go through that phase. Now that he is rich and famous, the only way he will understand the limits of his idea is by wasting lots of money (since he obviously doesn't care about such things as "peer review"). In fact, many reputable AI scientists have made wild claims about the future success of their latest new idea (Newell/Simon with the "general theorem prover", Rosenblatt with the "Perceptron", Papert who thought in the 50's that vision would be solved over the summer, Minsky with is "Society of Minds", etc......).

    No scientist will tell Hawkins all this, because it would serve no purpose (other than pissing him off). And there is a tiny (but non-zero) probability that his stuff will actually advance the field.

        - Anonymous Scientist
  • After participating in the neural network hype in the 1980s (I spent 1 year on a DARPA committee for NN tools, and was the original author of the SAIC ANsim NN software product) I found Hawkin's book to be light technically, but I really enjoyed reading it.

    His work might have been inspired by Kohonen's classic Springer-Verlag book "Self-Organization and Associative Memory".

    I downloaded their software last night but have had little time doing anything but building and running two examples. When I get 20 hour
  • He may have founded Palm - and I do encourage him to push forward with Numenta - but I'm still trying to get my Palm to sync on 2 different computers ..............
  • I'm no expert on this topic, but this doesn't sound very new or revolutionary to me. It looks very familiar with known model theories of neuronal networks. Aren't concepts of backpropagation or pattern recognition known for ages?
    • by Zarf (5735)
      I'm no expert on this topic, but this doesn't sound very new or revolutionary to me. It looks very familiar with known model theories of neuronal networks. Aren't concepts of backpropagation or pattern recognition known for ages?

      Well, when I read this:

      Numenta's goal is to build a software model of the human brain capable of face recognition, object identification, driving, and other tasks currently best undertaken by humans.

      I thought: Hey! That's been my goal my whole career. Nobody pays me for tha
  • Not too long ago two of IT's top original thinkers and innovators, Jeff Hawkins and Ray Kurzweil, appeared at an MIT emerging tech conference to discuss artificial intelligence. Both see computing mirroring the functions of the human brain. But they disagree on how fast scientists and engineers will develop technologies that exhibit the most complex cerebral traits of humans: self-awareness, emotion, and even a sense of one's own mortality.

    Because of technology's exponential growth, Kurzweil sees emotion-

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