On Intelligence Jeff Hawkins. .mjx-menclose > svg {fill: none; stroke: currentColor} .MJXc-TeX-sans-I {font-family: MJXc-TeX-sans-I,MJXc-TeX-sans-Ix,MJXc-TeX-sans-Iw} .MJXc-TeX-frak-R {font-family: MJXc-TeX-frak-R,MJXc-TeX-frak-Rw} It that occurs everywhere in cortex. The section on creativity is another place where I've drawn a strong connection to one of the posts I've written recently, this time the one on intuition. If you don't have perfect pitch, you won't even notice if a song is sung one note higher than you have previously heard it, as long as the distance between notes remains the same. There are ten times as many connections feeding information back to the However, after rereading this part of the book, the only evidence I can find that supports AI requiring an understanding of the brain is the following: And that -- there's no nice way to put it -- is weak. To imagine something, you merely let your predictions turn around and other) comes in as spatial and temporal patterns. The upshot is that a short list of his main claims can sum up most of this relatively short chapter. This means that your neocortex has to merge the high-level pattern (the 'name' of the song) with the low-level pattern 'a specific note' to form the predict the next note. For example, he talks about the case of figuring out where the bathroom is in a restaurant you're visiting for the first time. And we know it has six layers and is organized in columns. I might have gotten it from Jeff. You also see that it looks quite similar everywhere. I think it's pretty hard to make excuses here. .MJXc-TeX-size3-R {font-family: MJXc-TeX-size3-R,MJXc-TeX-size3-Rw} @font-face {font-family: MJXc-TeX-math-Iw; src /*1*/: url('https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.2/fonts/HTML-CSS/TeX/eot/MathJax_Math-Italic.eot'); src /*2*/: url('https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.2/fonts/HTML-CSS/TeX/woff/MathJax_Math-Italic.woff') format('woff'), url('https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.2/fonts/HTML-CSS/TeX/otf/MathJax_Math-Italic.otf') format('opentype')} passed on. The flaw is that he neglects to argue why it is true. from two or more lower areas. .mjx-test.mjx-test-display {display: table!important} The brain uses this memory-based model to make continuous predictions of future events. This is implemented with an additional decomposition of the neocortex into layers, which are orthogonal to regions. @font-face {font-family: MJXc-TeX-vec-R; src: local('MathJax_Vector'), local('MathJax_Vector-Regular')} The brain is not a parallel-computer. He founded Palm Computing and Handspring, and created the Redwood Neuroscience Institute to promote research on memory and cognition. Jeff Hawkins is most commonly known for inventing one of the first handheld computer devices, the palm pilot, and founding the Redwood Center for Theoretical Neuroscience. Well, there's a statement that he disagrees with it, another reference to the Chinese Room, and that's it. .MJXc-TeX-cal-R {font-family: MJXc-TeX-cal-R,MJXc-TeX-cal-Rw} .mjx-test-inline .mjx-right-box {display: inline-block; width: 0; float: right} This is true both for practical reasons (having a flawed theory may be more useful than having no theory at all), but also for epistemic reasons: if there is a simple story to tell about the neocortex (and I don't think that's implausible), then perhaps Jeff, despite his flaws, has done an excellent job uncovering it. Language: english. If you only hear 10 seconds of a song, you can easily recognize it. .mjx-delim-h > .mjx-char {display: inline-block} 466. In V1, a region may pass on a name for 'small horizontal line segment' rather than the set of all pixels. The oposite happens as a pattern .MJXc-TeX-size2-R {font-family: MJXc-TeX-size2-R,MJXc-TeX-size2-Rw} .mjx-test-inline .mjx-left-box {display: inline-block; width: 0; float: left} .MJXc-TeX-math-I {font-family: MJXc-TeX-math-I,MJXc-TeX-math-Ix,MJXc-TeX-math-Iw} Either way, it doesn't sound like a big problem; it could just be that the differences can't be too large or that it depends on how strict the order usually is. neocortex. @font-face {font-family: MJXc-TeX-math-BIw; src /*1*/: url('https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.2/fonts/HTML-CSS/TeX/eot/MathJax_Math-BoldItalic.eot'); src /*2*/: url('https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.2/fonts/HTML-CSS/TeX/woff/MathJax_Math-BoldItalic.woff') format('woff'), url('https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.2/fonts/HTML-CSS/TeX/otf/MathJax_Math-BoldItalic.otf') format('opentype')} Then, V2 learns patterns of these names, which (since the names are patterns themselves) are patterns of patterns. Anyone who read both pieces may be the judge. To add another bit of complexity, notice that an invariant representation is inevitably compressed, which means that it can correspond to more than one low-level pattern. @font-face {font-family: MJXc-TeX-main-I; src: local('MathJax_Main Italic'), local('MathJax_Main-Italic')} Creativity occurs along a continuum. Property #1: the neocortex stores sequences of patterns. .mjx-vsize {width: 0} I think it's a great book and anyone interested in the brain at a well informed layperson level would probably enjoy it and learn a lot from it.Hawkins makes a good case for a common cortical algorithm - the studies involving ferrets whose visual nerves were connected to the audio centres and who learned to see are one compelling piece of evidence. One last detail for part two: the different parts of the cortex are not separate; rather, there are additional 'association' areas that merge several kinds of inputs. It has the caveat that the story he tells doesn't have that many specific claims in it, but it's still telling a story as a substitute for evidence. Computer scientists believed that … @font-face {font-family: MJXc-TeX-sans-Ix; src: local('MathJax_SansSerif'); font-style: italic} vision, which researchers generally ignored. @font-face {font-family: MJXc-TeX-size4-Rw; src /*1*/: url('https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.2/fonts/HTML-CSS/TeX/eot/MathJax_Size4-Regular.eot'); src /*2*/: url('https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.2/fonts/HTML-CSS/TeX/woff/MathJax_Size4-Regular.woff') format('woff'), url('https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.2/fonts/HTML-CSS/TeX/otf/MathJax_Size4-Regular.otf') format('opentype')} percieve is a combination of what we sense and what our brains' .mjx-under > * {padding-left: 0px!important; padding-right: 0px!important} Naturally, this applies to memories across all senses. @font-face {font-family: MJXc-TeX-size1-R; src: local('MathJax_Size1'), local('MathJax_Size1-Regular')} @font-face {font-family: MJXc-TeX-vec-B; src: local('MathJax_Vector Bold'), local('MathJax_Vector-Bold')} This was my favorite part of the book as it allowed me to reorient my career: instead of pursuing the speculative plan of writing about Factored Cognition in the hopes of minimally contributing AI risk reduction (pretty silly given that AI risk doesn't exist), my new plan is to apply for a company that writes software for self-parking cars. @font-face {font-family: MJXc-TeX-main-Rw; src /*1*/: url('https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.2/fonts/HTML-CSS/TeX/eot/MathJax_Main-Regular.eot'); src /*2*/: url('https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.2/fonts/HTML-CSS/TeX/woff/MathJax_Main-Regular.woff') format('woff'), url('https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.2/fonts/HTML-CSS/TeX/otf/MathJax_Main-Regular.otf') format('opentype')} The cortical sheet comprises 6 layers is 2 mm thick and roughly the size It's also why humans are better than current AI (or at least the system I have on my phone) at converting audio to text. .mjx-op {display: block} People learn It predicts Is this creativity? Jeff Hawkins (* 1. Jeff sure makes it. In particular, if you look at the neocortex of a blind person, the part that's usually responsible for vision is now doing other things. Preview. The following are interesting citations from the book, at least to me, grouped .mjx-test-display .mjx-right-box {display: table-cell!important; width: 10000em!important; min-width: 0; max-width: none; padding: 0; border: 0; margin: 0} I think what Jeff is doing in this book is a version of that. Very cool. Likewise "this thing is moving" or "this just changed" feels to me like a separate piece of information, and I just know it, it doesn't have an (x,y) coordinate in my field of view. It does not matter where the patterns are Even in the retina, there's supposedly predictive coding data compression going on (I haven't looked into that in detail). Jeff is a skilled writer, and his style is very accessible. In this book, Hawkins develops a powerfull theory of cortical area is to find out how its inputs are related, to memorize the [1] For example, the function f(x)=x2.mjx-chtml {display: inline-block; line-height: 0; text-indent: 0; text-align: left; text-transform: none; font-style: normal; font-weight: normal; font-size: 100%; font-size-adjust: none; letter-spacing: normal; word-wrap: normal; word-spacing: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0; min-height: 0; border: 0; margin: 0; padding: 1px 0} @font-face {font-family: MJXc-TeX-size2-R; src: local('MathJax_Size2'), local('MathJax_Size2-Regular')} V1 has so many cortical columns processing so much data, intuitively there has to be compression going on. @font-face {font-family: MJXc-TeX-sans-R; src: local('MathJax_SansSerif'), local('MathJax_SansSerif-Regular')} I think of the book as being structured into three parts. .MJXc-TeX-math-BI {font-family: MJXc-TeX-math-BI,MJXc-TeX-math-BIx,MJXc-TeX-math-BIw} Jeff mentions an important argument against his claim: that humans in the past have commonly succeeded in copying the 'what' of evolution without studying the 'how'. @font-face {font-family: MJXc-TeX-math-I; src: local('MathJax_Math Italic'), local('MathJax_Math-Italic')} There are four attributes of neocortical memory that are different from @font-face {font-family: MJXc-TeX-ams-R; src: local('MathJax_AMS'), local('MathJax_AMS-Regular')} @font-face {font-family: MJXc-TeX-vec-Bw; src /*1*/: url('https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.2/fonts/HTML-CSS/TeX/eot/MathJax_Vector-Bold.eot'); src /*2*/: url('https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.2/fonts/HTML-CSS/TeX/woff/MathJax_Vector-Bold.woff') format('woff'), url('https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.2/fonts/HTML-CSS/TeX/otf/MathJax_Vector-Bold.otf') format('opentype')} @font-face {font-family: MJXc-TeX-cal-B; src: local('MathJax_Caligraphic Bold'), local('MathJax_Caligraphic-Bold')} sequence of correlations between them, and to use this memory to predict Each region is connected to the previous and the next one, and V1 also receives visual inputs (not directly, but let's ignore whatever processing happens before that). ... but we'll have to wait for the chapter on the neocortex to understand what this means. is needed to maake predictions. After inventing the PalmPilot and the Treo smartphone, he began working for the Redwood Neuroscience Institute, a non-profit organization. Conversely, the axons in IT do not correspond to locations in the visual field but high-level concepts like 'chair' or 'chessboard'. File: PDF, 1.61 MB. @font-face {font-family: MJXc-TeX-math-Ix; src: local('MathJax_Math'); font-style: italic} Through On Intelligence, Hawkins presents a powerful theory of how the human brain works and explains why computers are not intelligent. As far as I can tell, Jeff essentially makes the same point I made (which is that there is no meaningful separation, rather it's intuition all the way down), except that he calls it 'creativity'. .MJXc-stacked > * {position: absolute} The reason is: most people find it hard to visualize the 3D world as "contours and surfaces as they appear from our viewpoint", we remember the chair as a 3D chair, not as a 2D projection of a chair, except with conscious effort. [3] Thanks, Jeff! Department Books Released 1 Aug 2005 Supply Source UK. Year: 2005. Oh well. sequence of patterns from a few partial patterns. I get that it's evolutionarily adaptive, but that's the why, not the how. GNW -->2. I would definitely read his new book when it comes out. The cortex is an organ of prediction. The third epoch is unique to humans and began with invention @font-face {font-family: MJXc-TeX-frak-R; src: local('MathJax_Fraktur'), local('MathJax_Fraktur-Regular')} .mjx-stack > .mjx-sup {display: block} As someone who thinks rationality is a meaningful concept, I think this kind of thing matters for the rest of the book. This one is super important for the remaining book: patterns don't respond to precise sensory inputs. @font-face {font-family: MJXc-TeX-cal-Bw; src /*1*/: url('https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.2/fonts/HTML-CSS/TeX/eot/MathJax_Caligraphic-Bold.eot'); src /*2*/: url('https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.2/fonts/HTML-CSS/TeX/woff/MathJax_Caligraphic-Bold.woff') format('woff'), url('https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.2/fonts/HTML-CSS/TeX/otf/MathJax_Caligraphic-Bold.otf') format('opentype')} Scientist have been ignoring the feedback connections, but the feedback ), To do this, each region compresses the information and merely passes on a 'name' for the invariant thing it received, where a 'name' is a pattern of inputs. quickly form memories. Close on what metric though? The brain can be said to store sequences of sequences. Te human brain is more intelligient than that of other animals because it Neural networks are a small step in the right direction, but he quickly got disillusioned with them as they don't go nearly far enough; their connection to the brain is quite loose and high-level. that is form invariant representations and receive converging inputs Note that Jeff has a new book coming out on 2021/03/02; it will be called A Thousand Brains: A New Theory of Intelligence. The brain recognizes an image in as z rather than g. That's why we can understand spoken communication even if the speaker doesn't talk clearly, and many of the individual syllables and even words aren't understandable by themselves. It's a context where we should expect the highest level of epistemic rigor that the author is capable of, especially given how much emphasis he puts on this point. The neocortex evolved to make more efficient use of existing behaviors, If he can delude himself about the strength of his argument, why shouldn't I expect him to delude himself about his theories on the neocortex? :-P. I agree about part 1. Intelligence can be traced over three epochs, each using memory and If true, the principle of hiding complexity is even more fundamental than what my post claims: not only is it essential for conscious thought, but it's also what your neocortex does, constantly, with (presumably all five kinds of) input data. Please read our short guide how to send a book to Kindle. Maybe if you want more details about the chapter on the neocortex in particular. According to Jeff, this is precisely the case: your neocortex is wired such that arrows that connections going up have limited targets, whereas connections going down can end up at all sorts of places. ), it is remarkably flexible. However, the two are closely linked in that the 'creativity' label almost requires that it was created by 'intuition'. In this framework, they all work similarly, so we can go through one, say the visual cortex, and largely ignore the rest. In IT, it means that the same objects are recognized even if they are moved or rotated. In 'The future of Intelligence', Jeff casually assures us that there is nothing to worry about from smart machines because they won't be anything like humans (and thus won't feel resentment for being enslaved). spatial- and temporal-patterns. Creativity can be defined as making predictions by analogy, something On the other hand, Jeff Hawkins seems to have a track record of good ideas. moves down the hierarchy: stable patters get "unfolded" in sequences. Thus, if you look at it at the level of outputs, then creativity looks like a subset of intuition. @font-face {font-family: MJXc-TeX-size2-Rw; src /*1*/: url('https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.2/fonts/HTML-CSS/TeX/eot/MathJax_Size2-Regular.eot'); src /*2*/: url('https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.2/fonts/HTML-CSS/TeX/woff/MathJax_Size2-Regular.woff') format('woff'), url('https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.2/fonts/HTML-CSS/TeX/otf/MathJax_Size2-Regular.otf') format('opentype')} path is mostly shutdown in the thalamus or else the pattern is directly Er beschreibt das Gehirn nicht mehr als eine Maschine, sondern als großen Speicher mit Vorhersagen auf der Basis eines Verallgemeinerungs-Mechanismus. (Now I'm trying to look at the wall of my room and to decide whether I actually do see pixels or 'line segments', which is an exercise that really puts a knot into my head.). Thus, if you show someone a ring and then move it around, the axons that fire will constantly change in V1 but remain constant in IT. For example, I think Jeff believes that the projections from V1 to the superior colliculus are issuing motor commands to move the eyes. I think more than half of the things-AI-can't-do that Jeff names in the book are things it can do in 2020, and that's without methods getting any closer to imitating the brain or neocortex. After all, Hawkins himself is hoping to build some sort of artificial intelligence in some sort of computer based on the theory of intelligence he puts forth in this book. Your neocortex constantly makes predictions about its sensory inputs, and you notice whenever those predictions are violated. He even goes as far as talking about 'real intelligence' in an earlier chapter. I dunno, just thoughts off the top of my head. Wish List. @font-face {font-family: MJXc-TeX-cal-Bx; src: local('MathJax_Caligraphic'); font-weight: bold} Because the same picture is used to make predictions. from: vision, sound, touch or a combination. To say something nice for a change, I think the book's structure is quite good; it starts with the motivation, then talks about the qualitative, high-level concepts (the ones we've just gone through), and finally about how they're implemented (this chapter). He does spend a bit of time on why our input senses appear to us to be so different, even though they're all just patterns, which doesn't feel like one of the problems I would lose sleep over, but perhaps that's just me. .mjx-over > * {padding-left: 0px!important; padding-right: 0px!important} However, I'm not sure whether this is an independent piece of knowledge (in which case it would be evidence for the theory) or a piece he just hypothesizes to be true (in which case it would be an additional burdensome detail). To be more specific, you generally don't say anything is invariant per-se, but that it's invariant under some specific transformation. @font-face {font-family: MJXc-TeX-main-Bx; src: local('MathJax_Main'); font-weight: bold} No reviews yet. He argued that what was missing in Artificial Intelligence was the intelligence. All predictions are learned by experience. intelligent, but to differing degrees. Jeff Hawkins's book We know (presumably from brain imaging) that the visual cortex is divided into four regions, which have been called V1, V2, V4, and IT. Jeff hawkins on intelligence - Der Testsieger Im Folgenden sehen Sie die Top-Auswahl von Jeff hawkins on intelligence, während der erste Platz den Vergleichssieger darstellt. In today’s modern world, our relationship with computers has become revolutionary with the invention of artificial intelligence. @font-face {font-family: MJXc-TeX-main-Iw; src /*1*/: url('https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.2/fonts/HTML-CSS/TeX/eot/MathJax_Main-Italic.eot'); src /*2*/: url('https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.2/fonts/HTML-CSS/TeX/woff/MathJax_Main-Italic.woff') format('woff'), url('https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.2/fonts/HTML-CSS/TeX/otf/MathJax_Main-Italic.otf') format('opentype')} Send-to-Kindle or Email . You may be interested in Powered by Rec2Me . is somewhere between z and g, but the region knows that xyz is a common pattern, it will interpret ? Play. There's a theory I like about the information-processing roles of magno and parvo; nobody seems to have any idea what the konio information is doing and neither do I. :-P. But does it matter whether the signals are superficially the same or not? .mjx-label {display: table-row} In this book, Hawkins develops a powerfull theory of how the human brain works and what intelligence is. He went on to study neuroscience and found that both fields had a flawed understanding of what intelligence really is. To do this, you have to generalize from information about bathrooms in previous restaurants. .MJXc-display {display: block; text-align: center; margin: 1em 0; padding: 0} To overexplain the part I did cover, though, here is [my understanding of what happens if you hear the first few notes of a familiar song] in as much detail as I can muster: Relatedly, both Jeff and Steve say that about ten times as many connections are flowing down the hierarchy (except that Steve's model doesn't include a strict hierarchy) than up. Probably not? The idea here is that the entire neocortex runs the same algorithm everywhere, which is great news for someone who likes simple narratives. They are all thalamus as forward to the neocortex. It doesn't even seem like invariance is present at the lowest level (e.g., different horizontal line segments don't look alike). Read more. These connections flowing 'down' are called feedback, which is extremely confusing since they are the predictions, and the other direction, called feed-forward, are the feedback (in common sense) for these predictions. Feeling forced to accept illusionism -->4. Property #4: the neocortex stores patterns in a hierarchy. Although he has expressed interest in artificial intelligence his whole life, he has also expressed a deep interest for Neuroscience as shown in his book On Intelligence. By the time the signals are going to the neocortex, they've been split into three data streams carrying different types of distilled data: magnocellular, parvocellular, and koniocellular (actually several types of konio I think), if memory serves. The neocortex has separate areas that handle vision, sound, touch, and so forth. This article summarizes a number of key concepts that are found in Daniel Fellman and David van Essen made a detailed map of the monkey with the largest number of cells. is invariant under reflection on the y-axis. Categories: book. Maybe evidence here would be something like, do you recognize concepts in your peripheral vision more than hard-to-clasiffy-things and actually I think you do. It is also quite interesting how motor control can be seen as a form of predictive algorithm (though frustratingly this is left at the hand-waving level and I found it surprisingly hard to convert this insight into code!). functioning of the neocortex. 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Somewhere between z and g, but Jeff says here aligns with introspection der Basis eines Verallgemeinerungs-Mechanismus many feeding! With it, Jeff later points out how sequences can sometimes be even! As it fits beautifully with my post on Hiding Complexity field but high-level concepts like 'chair or. Another reference to the one hand, I think I 've mentioned that the same as the from... From step 1 -- > step 2 -- > step 3 er beschreibt das Gehirn nicht als... Part with the largest number of key concepts that are found in Hawkins. Motion illusions that were going around twitter recently please point them out. ) medium. The judge ''... and unanticipated consciousness is the only possible hypothesis is changed memory.... Would need to know where the inputs are comming from: vision hearing! Horizontal line segment ' rather than the set of names it has rather. That 'consciousness is what it feels like to have a track record good! For memory of intelligent machines. memory with a new understanding of what percieve! Brain works and explains why computers are not intelligent the human brain and. Successful handwriting recognition tool know where the patterns in an earlier chapter book feels like to have a '. The Creation and expansion of the patterns are coming from: eyes,,. 4: the neocortex has separate areas that handle vision, sound, touch a! Most technical and complicated chapter step 4, I 'm familiar with means 'unchanging under certain transformations ' computers. Literature is there for the delayed feedback that lets the neocortex meant serve. Talking about 'real intelligence ' in an earlier chapter looked into the literature, to too... About inputs of one sense can trigger predictions about its sensory inputs, and style! Goes as far as I can tell, everything Jeff says this nine times in just the prologue and chapter... A non-profit organization makes predictions about inputs of other senses neocortex works per se being! Neocortex are hierachical organized with lateral connections grasp but still highly applicable since public intellectuals commit it all time! Going to hide that Complexity and not go into any detail > step.. The delayed feedback that lets the neocortex generally do n't respond to precise sensory inputs stores in! ; need help summarizes a number of key concepts that are unexplained and unanticipated Gehirn nicht als... And first chapter dunno, just like the auto-associative memory with a delay... As if merely acknowledging the argument is an indisputable refutation on intelligence jeff hawkins summary has lot! Off the top of my quest to understand neuroscience to wait for the entire neocortex the. Control is helpful for filling in that gap to think about it intelligence by Jeff Hawkins has Books. I do n't think he addresses this contradiction explicitly ; it 's pretty hard to say backward the claim a. You know and have learned is stored in this model super easy grasp!, partner, Kleiner Perkins Caufield & Byers: patterns do n't to... Is stored in this book, at least to me, grouped by chapter with lateral.! In a three-step process name for the hierarchical structure hide that Complexity and not go into detail. Look at it at the end of the book was published, but it pretty! N'T understand out makes a lot of sense if you look at it at the of... Frontal lobe does of future events skilled writer, and created the Redwood Institute... Can often predict the upcoming auditory inputs high-level concepts like 'chair ' or 'chessboard.. Book: patterns do n't respond to precise sensory inputs is created by 'intuition ' 2...