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The Computer and the Brain

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This work represents the views of a mathematician on the analogies between computing machines and the living human brain.


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This work represents the views of a mathematician on the analogies between computing machines and the living human brain.

30 review for The Computer and the Brain

  1. 4 out of 5

    Hadrian

    Impressive little book which along with Turing's work, et al., founded the field of computer science as we know it. Of most interest if you are interested in the history and foundations of modern computer science, otherwise the concepts here will be so familiar that you will know many of them already.

  2. 3 out of 5

    Chrissy

    A short and accessible historical gem that explores, well before its time, points of convergence and divergence between natural and artificial intelligence systems. It's particularly interesting as a meter stick of progress between the 1950's and the current day: whereas the computer side of the question is in some ways quaintly outdated, von Neumann's outline of the human nervous system and the functioning of individual neurons remains near the limit of what we understand even today. Not quite A short and accessible historical gem that explores, well before its time, points of convergence and divergence between natural and artificial intelligence systems. It's particularly interesting as a meter stick of progress between the 1950's and the current day: whereas the computer side of the question is in some ways quaintly outdated, von Neumann's outline of the human nervous system and the functioning of individual neurons remains near the limit of what we understand even today. Not quite exactly at the limit, but certainly not as dreadfully short of it as 1950's computer science is to our current level of technological understanding. Psychologists often point to the youth of our field as if it were an apology for the slow progress-- still waiting for our Newton or our Einstein--, but the contrasts laid out in this book, as a modern reader, question the validity of the excuse. Computer science is younger still than psychology, yet the speed of knowledge acquisition dramatically outpaces that of psychology. Nevertheless, as von Neumann outlines presciently, the points of divergence may overwhelm the points of convergence, rendering the comparison moot. The essay stands as a reminder of the limits of artificial intelligence when compared to biological intelligence: we may never be able to build real brains from artificial components running current computer architectures. I was especially piqued by his closing remarks that the mathematics of the nervous system may reflect different mathematics than the ones we currently understand. He compares our known mathematics to assembly language and the hypothesized neural mathematics to higher-level programming languages, suggesting that we may simply not have found the right method for interpreting the latter. I really enjoyed the quick read and recommend it to anyone who works with computers, brains, or-- most especially-- both, as an important historical document.

  3. 3 out of 5

    Mengsen Zhang

    It's really sad that this is not completed. It's like you just finish an appetizer and get thrown out of the restaurant. Anyhow, I love his writing and recommend it as an important text. He carefully analyze the computer-brain analogy in terms of memory, logic, arithmetic, capacity, precision and processing time etc. I wish all neuroscientists could do the same job before making certain assertions. There are a few discussions on the functioning of the brain are especially interesting, e.g. (1) w It's really sad that this is not completed. It's like you just finish an appetizer and get thrown out of the restaurant. Anyhow, I love his writing and recommend it as an important text. He carefully analyze the computer-brain analogy in terms of memory, logic, arithmetic, capacity, precision and processing time etc. I wish all neuroscientists could do the same job before making certain assertions. There are a few discussions on the functioning of the brain are especially interesting, e.g. (1) work of the brain relies on back and forth digital-analog conversions, which, I think, suggest current modeling efforts to look beyond complete digital simulations; (2) language of the brain is not the language of logic and mathematics as how we use it, otherwise nothing would work with its low arithmetic precision; (3) memory relies on the activities neurons and their genetics, but not sure where it's stored. - Probably just a few things I like to keep in mind as a student of the subject. He spent substantial passages on memory, which also fascinated many greatest minds in the past. But as a random nerd, I find the analogs (not just by von Neumann) between computer memory and human memory the funniest of all time. We objectify some of our memories as physical markers in the computer, but are these markers also memories of the computers as they would call it? Maybe there is some asymmetry.

  4. 5 out of 5

    Brandon Henke

    A short series of lecture notes written by the great mathematician and physicist John von Neumann while on his deathbed. The book is split into two sections, the first of which details early computing devices and their functioning. Essentially, logical "organs" are orchestrated in sequential patterns to perform intensive arithmetic and memory-related procedures. Here we find some of the first mentions of random access memory (RAM), short code (high-level programming), and other elements that are A short series of lecture notes written by the great mathematician and physicist John von Neumann while on his deathbed. The book is split into two sections, the first of which details early computing devices and their functioning. Essentially, logical "organs" are orchestrated in sequential patterns to perform intensive arithmetic and memory-related procedures. Here we find some of the first mentions of random access memory (RAM), short code (high-level programming), and other elements that are ubiquitous in modern computing. The second portion of the book presents a balanced assessment of the computational nature of neurological systems. Much to my liking, von Neumann exhibits a healthy dose of skepticism while drawing comparisons between constructed and natural systems. After initially hazarding a hypothesis about the digital nature of neuron-axon-synapse transmissions, he proceeds to point out that these are, in actuality, complex systems that exhibit analog/continuous characteristics at the molecular level in which the mechanical, electric, and chemical realms begin to blur together. Though they possess considerable disadvantages in "clock speed" and precision, natural systems make up for their lack of logical depth by being massively parallel. Despite vast improvements in our understanding of computer science and neuroscience, von Neumann's ideas hold up remarkably well. 4.0/5.0

  5. 5 out of 5

    Sai

    This book is the manuscript of a lecture that Von Neumann planned to give at Princeton in the 50's. Owing to that, it is terse in a way, and that makes it a bit dry to read. That said, it goes over the state of the art in computing in the middle of the twentieth century, and tries to draw parallels between the computer logic processing and memory hardware of the time, with the then nascent understanding how neurons worked. It was a good history lesson of computers, though not comprehensive by any This book is the manuscript of a lecture that Von Neumann planned to give at Princeton in the 50's. Owing to that, it is terse in a way, and that makes it a bit dry to read. That said, it goes over the state of the art in computing in the middle of the twentieth century, and tries to draw parallels between the computer logic processing and memory hardware of the time, with the then nascent understanding how neurons worked. It was a good history lesson of computers, though not comprehensive by any measure. Moreover, there were a few back of the napkin calculations that compared brain hardware with computer hardware which were fun to ponder. The book is unfinished, because of the author's death before completing the book, so it does end abruptly. Towards the end of the book, he seemed to be going in an interesting direction, comparing software programming with information that is coded and translated in the mesh of neural connections in the brain; their similarities and differences as then understood. Would have been an interesting analysis had he gotten the chance to complete it.

  6. 3 out of 5

    Pranjal Dhole

    The book is very well-written; however lack of illustrative figures makes it hard to digest the content unless you already know about it. This is the only reason that I rate it one star less. The book might represent state of the art knowledge at 1956 however our understanding of operations of the brain has significantly changed. This book serves as a good read for historical comparison of our understanding of the brain and its similarity to modern computing machines.

  7. 3 out of 5

    Evaldas Svirplys

    John von Neumann's ideas was so influential that now a days they sound intuitive and plain. Makes you remember once again that even the ideas you take for granted needed to be comprehended and relished by someone(-where)(-how)(-time-ago). No need to read this.

  8. 5 out of 5

    Nick Black

    Too short to really bring anything new to the table (save some tantalizing references to analog computing I need chase down in more detail), but also too short to piss you off or demand more than a half hour. More like a pamphlet than a real book, I was worried I might put this in my pocket and send it through the wash.

  9. 4 out of 5

    David

    My 3-star rating has nothing to do with my awe at John von Neumann as a towering genius. I'm also not rating the three introductions to the book. Instead, I'm using strictly as a rating of my enjoyment of this unfinished lecture. However, I would like to talk about the introductions to this Third Edition published in 2012. My favorite, by far, is Ray Kurzweil's. It is the most recent and the most fun to read. I was particularly thankful for his summaries of where our knowledge of computing and of My 3-star rating has nothing to do with my awe at John von Neumann as a towering genius. I'm also not rating the three introductions to the book. Instead, I'm using strictly as a rating of my enjoyment of this unfinished lecture. However, I would like to talk about the introductions to this Third Edition published in 2012. My favorite, by far, is Ray Kurzweil's. It is the most recent and the most fun to read. I was particularly thankful for his summaries of where our knowledge of computing and of the physiology of the brain have come since 1957. I also found his explanations of Claude Shannon's Mathematical Theory of Communication to be incredibly lucid. I have a couple of Kurzweil's books on my shelves and based on the strength of this introduction, I'll be bumping those up on the reading queue! The second introduction was written in 2000 by the Churchlands. It is also helpful, covering similar ground to Kurzweil. It's short, but I found it quite dry. The third introduction was written by Klara von Neumann and is an excellent summary of how the unfinished book came to be. Klara was John's wife and the introduction is particularly heartbreaking when you realize that it was written in September, 1957. John had finally succumbed to cancer in the February of that year. In all, there are 51 pages of introduction and then 80 pages of the lecture material. Though von Neumann never lived to give the lecture, or even finish the written work, it still stands as a testament to his ability to absorb and understand vast amounts of material. For the most part, this book is nothing more than a time capsule describing the very state of the art in computer architecture and brain physiology at that point in time. I'm not sure if we even know where he was heading with this material - would he have proposed avenues for simulating human brains with computers? One thing that really stuck out immediately in the actual lecture material were the terms that von Neumann used to describe how computing architecture is organized: he refers to the different parts of a computer as "organs" such as the "memory organ", "input" and "output" organs. In fact, it's very interesting to consider the need, at the time, to describe in analogy to biological systems, the parts of computing that we now take for granted. Nowadays, we're probably just as likely to use computing terms as analogies to simplify the function of biological systems! The von Neumann architecture of the 1950s is completely recognizable in today's computers. This struck me, in particular, when reading the section titled Modus Operandi of the Memory-Stored Control. In this section, he describes what we would now call the storage of programs in memory: "In this case, since the orders that exercise the entire control are in the memory, a higher degree of flexibility is achieved than in any previous mode of control." He then goes on to describe in-memory self-modifying code, which was in vogue in "the old days" (however you choose to define that) when programs were written for specific machines in assembly (or even bytecode!) and whenever there was a need for extracting extreme performance from limited hardware. It's a heady concept, but generally frowned upon for maintainability and "graspability" reasons. At the halfway point, the computer lessons turn into biology lessons as we switch from the architecture of the computer to the architecture of the brain. It's all very carefully written, admitting gaps in our knowledge (then and now!) about how, exactly, certain parts of the brain actually function. For me, the highlight of the brain portion is the end, starting with a section snappily titled "Arithmetical Precision or Logical Reliability, Alternatives." "It should be noted that the message-system used in the nervous system...is of an essentially statistical character. In other words, what matters are not the precise positions of definite markers, digits, but the statistical characteristics of their occurrence...nearly periodic pulse-trains, etc." The book ends with a general statement that "the nervous system appears to be using a radically different system of notation" than that of mathematics (and traditional computing) and then concluding that the "language" of the brain may be in layers (which remind me of the layers of network protocols we enjoy today: physical voltage and timing, data link, routing, error correcting, and ending at the application level.) I'm not sure modern readers will "learn" from this book. But it's certainly worth a visit to read a description of modern computing at the moment time of its birth straight from one of its creators.

  10. 5 out of 5

    Phrodrick

    Perhaps more so than Alan Turing, (If we accept the intro by Kirtzweil, a man with serious credentials), John von Neuman was one of the most important figures in developing the basic architecture of the modern digital computer. The two did work together, but von Neuman was the senior and I propose had a better grasp of the juncture of math and machine. The Computer and the Brain is the last published work by von Neuman and was an attempt to bring together what was known about the machine qualitie Perhaps more so than Alan Turing, (If we accept the intro by Kirtzweil, a man with serious credentials), John von Neuman was one of the most important figures in developing the basic architecture of the modern digital computer. The two did work together, but von Neuman was the senior and I propose had a better grasp of the juncture of math and machine. The Computer and the Brain is the last published work by von Neuman and was an attempt to bring together what was known about the machine qualities of the brain and what the machines of 1957 might one day be able to accomplish. As such almost everything is dated and new discoveries in neuroscience more so than in computers place limits on the absolute value of his comments. That said, there was a head line in recent science news that there is a prototype computer in testing that combines both digital and large scale parallel computing in the manner von Neuman suggests as the model for how the brain may work. The Computer and the Brain is the printed from of a lecture. He was too ill (mortally) for the series he was offered to conduct. So great was the respect for the man that he was allowed to present only these papers, sufficient for one lecture and about 3 hours reading. I do not think he read the paper; he had just the strength to write it. Besides having been a vitally important mathematician, he was active in the cause of scientific ethics and as the man who drafted the letter, signed by Einstein credited with America committing to atomic research he is therefore a originator of the atomic age. He was a man of great thought and influence. Reading this book is a chance to listen to a great mind. I make no claim to have understood all of it. I suspect that no one should read it in an effort to be at the leading edge of math, computers or neurology. It is a hard, but worth it read, and a glass into our recent history.

  11. 3 out of 5

    Howard Accurso

    This 1956 monograph is a series of notes for a projected series of lectures in the"The Silliman Memorial Lecture Series" at Yale. Part of the guidelines for these lectures was that they be appropriate for a general audience. Unfortunately, manuscript remained unfinished and the lectures were not delivered, because von Neumann died while he was working on it. The premise of the book was to explain how analog and digital computers process information, then compare that with the way the brain proce This 1956 monograph is a series of notes for a projected series of lectures in the"The Silliman Memorial Lecture Series" at Yale. Part of the guidelines for these lectures was that they be appropriate for a general audience. Unfortunately, manuscript remained unfinished and the lectures were not delivered, because von Neumann died while he was working on it. The premise of the book was to explain how analog and digital computers process information, then compare that with the way the brain processes information. In the days of ferro-magnetic core memories, cards and tapes, before Moore had a chance to observe his law, the terminology used to describe how computers work is a bit alien to the modern reader. Von Neumann seems concerned about issues, like error correction and reliability, which are second nature to us 60 years later. And although he surveys many computing devices from history, the focus is on the computers that use the "von Neumann" architecture, which includes most modern computers. I wanted to read this book to sample von Neumann's style, the way I read Freud on psychology. I was impressed with his method not only to offer theories, but to quantify them with estimated calculations. The brain might consume 10 watts of energy. The computers of those times would consume much more. I worked on a minicomputer in the 1970's that required a 600 volt power supply to operate the ferrite core memories. And as primitive as neuroscience was in 1956, to his credit the author deduced that the brain was conducting massively parallel processing with billions of slow firing neurons, while computers were using much faster electronic switching to solve math problems a step at a time. The quality of the prose trails off a bit toward the end, because of the state of his declining health. I enjoyed the glimpse of greatness and a nostalgic return to the 1950's.

  12. 4 out of 5

    Brock Jones

    A very quick read primarily interesting as a tool for gaining perspective on how much the fields of computer science, neurobiology, and machine learning have changed. The basics of computer science covered are still accurate and relevant to some extent ,even if the scales of size and speed have progressed by orders of magnitude. In contrast, it's almost shocking how outdated and primitive the neurobiology and machine learning discussions are. There is an unstated premise throughout much of the b A very quick read primarily interesting as a tool for gaining perspective on how much the fields of computer science, neurobiology, and machine learning have changed. The basics of computer science covered are still accurate and relevant to some extent ,even if the scales of size and speed have progressed by orders of magnitude. In contrast, it's almost shocking how outdated and primitive the neurobiology and machine learning discussions are. There is an unstated premise throughout much of the book that neurobiological structures/processes are universally analogous to digital computing principles that most would now view as quaint and hopelessly reductive.

  13. 3 out of 5

    Stefano

    L'unica grande pecca di questo libro è che l'autore non abbia potuto terminarlo. Nonostante sia stato pubblicato decine di anni fa molte considerazioni relative alle neuroscienze sono corrette. Inoltre questo libro è stato, di fatto, la base da cui è nata l'architettura dei moderni computer.

  14. 4 out of 5

    Michal

    This book captures wholesomely the great intellect that was John von Neumann. Truly a visionary, he predicted things that would come to be in years and decades after him. Full appreciation of this book requires some knowledge of computing and artificial intelligence.

  15. 4 out of 5

    Rama

    John von Neumann on computer logic Von Neumann is one the brilliant mathematician and an expert of computer logic. This book is dated, manuscript written in 1957, but from the historical perspectives it still well worth reading. Neumann's pioneering work lead to considerable advances in computers and his ideas lead to advances in computer automation and robotics. The thoughts of Klara von Neumann, the wife of John Neumann provides a brief sketch of events that lead to the presentation at the Sill John von Neumann on computer logic Von Neumann is one the brilliant mathematician and an expert of computer logic. This book is dated, manuscript written in 1957, but from the historical perspectives it still well worth reading. Neumann's pioneering work lead to considerable advances in computers and his ideas lead to advances in computer automation and robotics. The thoughts of Klara von Neumann, the wife of John Neumann provides a brief sketch of events that lead to the presentation at the Silliman Foundation lectures at Yale University. Neumann was diagnosed with bone cancer that confined him to the wheelchair. His health deteriorating by the day until his death in early 1957, unable to deliver the prestigious lecture and unable to complete the manuscript for the lecture, Yale University eventually published his partly-completed manuscript as a part of the prestigious Silliman lectures. This book is described in two parts; the computer and the brain. The basic concepts of analog and digital procedures, the characteristics of digital machine types and their basic components, memory-stored controls, memory capacities, and the concept of access time are discussed with regards to the machine. In the second part the author discusses the structure and function of human brain and compares the common characteristics between the brain and computer. The author provides a comparative analysis of the nerve cell (neuron); how it generates and propagates nerve impulses compared with generation and propagation of computer messages. The author looks at the complexity on neurons and its functions; the nature of the nerve impulses, the process of its stimulation, digital character, the problem of memory within the nervous system. Although the author still refers to vacuum-tube machines, the flip-flops, and transistor technology, but the basic concepts underlying the development of memory elements in a computer is well worth the reading. The recent advances in automation and robotics illustrate the early contribution of von Neumann in this field. In a recent study, Christopher Macleod and his colleagues in Aberdeen, UK, have created a robot that evolves like a living species in biological evolution. When the incremental evolutionary algorithm (lEA) realizes that its evolutions are no longer improving the robot's speed it freezes the neural network it has evolved, denying it the ability to evolve further. The sensors determine what it needs to carry out a given task most effectively. As animals evolved, the robots can evolve similarly. The robot can also adapt to newly acquired vision, and learn how to avoid or seek light when given a camera. This is just like the way the brain evolved building up in layers.

  16. 5 out of 5

    Emil Petersen

    John Von Neumann intended this book to be used for lectures at Yale, but he died sick of bone cancer before he could finish either lectures or the book itself. It's very short. The preface, foreword(s) and introduction account for about 2/5 of the entire book. Since it's written in the 50's I'm not entirely sure how much is still applicable to the brain and computers today in terms of scientific and practical structure. The Von Neumann Computer Architecture is touched upon in the foreword, and i John Von Neumann intended this book to be used for lectures at Yale, but he died sick of bone cancer before he could finish either lectures or the book itself. It's very short. The preface, foreword(s) and introduction account for about 2/5 of the entire book. Since it's written in the 50's I'm not entirely sure how much is still applicable to the brain and computers today in terms of scientific and practical structure. The Von Neumann Computer Architecture is touched upon in the foreword, and is what is described in the first part of the book. Its concepts are still essential to the architecture of the modern computer. Still, I hope (and am sure) we know more about both computers and the brain than was known in the time of Von Neumann. At least one of them have gotten smaller. If you do not know who the author is, I suggest you read his Wikipedia before reading any further; the man was out of this world! The book is split into part 1 on the computer and part 2 on the brain. I suspect the structure of a series of lectures can be seen here. The difference between the analogue- and the digital computer is briefly explained, which is not all that interesting. There's a bit about arithmetic, logical controllers, memory and precision. In a historical context, this is fine; otherwise it's way to shallow and you're not going to understand what he is talking about from just this brief explanation (at least I don't think so!). It feels like the notes you write on slides for a presentation, which it is, kind of. The more exciting part is the second, where the brain and its comparison with the computer is described. The digital character of the neuron (either it's firing or it's not), the computing speed of a brain, namely the number of neurons and their reaction time, and energy consumption of brains vs. computers. His discussion of parallel procedures vs serial procedures is ahead of its time and problems we still work on today. Less so is his comparison of memory. If nothing else, just read the foreword by Ray Kurzweil. That will give you a great sense of what this book is about, and why some of us still read it today.

  17. 5 out of 5

    Eloi Pereira

    I should start this review with a disclaimer: the work of John von Neumann is a major influence and inspiration for my own research work. Having said that, I will try not to be biased. John von Neumann was a mathematician, physicist, and economist, mostly known for his work on computer architecture. Von Neumann was contemporary with another founding father of computer science - Alan Turing. While Alan Turing established a mathematical model of computation - the now called Turing Machine, von Neu I should start this review with a disclaimer: the work of John von Neumann is a major influence and inspiration for my own research work. Having said that, I will try not to be biased. John von Neumann was a mathematician, physicist, and economist, mostly known for his work on computer architecture. Von Neumann was contemporary with another founding father of computer science - Alan Turing. While Alan Turing established a mathematical model of computation - the now called Turing Machine, von Neumann took influence in such model to design the computer architecture that is still used nowadays - the von Neumann Machine (a.k.a. von Neumann Architecture). If Turing is considered by a lot the first modern computer scientist, then von Neumann must be seen as the first modern computer engineer! In my opinion, von Neumann took the same approach in these lectures. He his not attempting to be a neuroscientist. This is a book about the brain written by an engineer. Von Neumann divides his lectures into two parts, in the former he presents the field of analog and digital computing machines, and in the later he analyses the brain as a natural automaton, i.e. a natural computing machine. This analysis is preformed systematically, supported strongly on evidences and rarely on conjectures. Though, when a conjecture is needed to follow-up the discussion, von Neumann states it and explains its consequences. The book feels incomplete. Von Neumann was never able to finish his lectures. He tragically died after fighting against bone cancer while he was writing them. Nonetheless, I still recommend this book to anyone that is interested in the first parallelism drawn between artificial and natural computers.

  18. 5 out of 5

    Jovany Agathe

    Von Neumann was one of the most celebrated and prolific mathematicians of the 20'th century; his contributions were legion, and always bore unmistakable creativity and elegance. "The Computer and the Brain" is a record of a lecture series that von Neumann delivered at Yale University in 1957. In these lectures, von Neumann set out to explore connections between computing hardware and their biological counterparts; brains. Von Neumann compared neurons with physical computing elements in terms of Von Neumann was one of the most celebrated and prolific mathematicians of the 20'th century; his contributions were legion, and always bore unmistakable creativity and elegance. "The Computer and the Brain" is a record of a lecture series that von Neumann delivered at Yale University in 1957. In these lectures, von Neumann set out to explore connections between computing hardware and their biological counterparts; brains. Von Neumann compared neurons with physical computing elements in terms of size, speed, heat dissipation, capacity, etc., in an attempt to discover what, if anything, could be said to unite them or to set them apart. He drew from what had been learned in designing computer instructions and memories in an attempt to glean some insight into what the brain might be doing. Ever the consummate mathematician, von Neumann was guarded in his statements, never over-reaching or confusing speculation with fact. The ideas contained in these lectures will come as no great surprise to most scientists today; indeed, I would expect most to simply nod in agreement at most of von Neumann's observations. For example, von Neumann notes that neurons are essentially digital in that they have an all-or-nothing activation energy. However, it is interesting to see how seriously he pursues the idea that the brain may rely upon a mixture of analog and digital encodings; he took absolutely nothing for granted, and may well have been vastly ahead of his time. Although von Neumann's many references to vacuum tubes and differential analyzers may seem archaic today, his central points remain essentially intact

  19. 3 out of 5

    Maurizio Codogno

    Questo breve saggio di von Neumann nasce come una serie di lezioni che il grande matematico avrebbe dovuto tenere a Yale: la sua malattia gli impedì non solo di presentarle ma anche di terminarle e controllarle (Paolo Bartesaghi nella traduzione segnala un paio di punti in cui i risultati delle operazioni matematiche sono banalmente errati). Io non sono così d'accordo con i peana delle prefazioni alla seconda e terza edizione del libro sulla visione del funzionamento del cervello: al più si può Questo breve saggio di von Neumann nasce come una serie di lezioni che il grande matematico avrebbe dovuto tenere a Yale: la sua malattia gli impedì non solo di presentarle ma anche di terminarle e controllarle (Paolo Bartesaghi nella traduzione segnala un paio di punti in cui i risultati delle operazioni matematiche sono banalmente errati). Io non sono così d'accordo con i peana delle prefazioni alla seconda e terza edizione del libro sulla visione del funzionamento del cervello: al più si può affermare che se le cose stanno davvero così allora negli ultimi 60 anni non si è in realtà fatto nulla di nuovo. La prima parte del testo però è molto interessante sia dal punto storico - in quanti sanno come era fatto un computer negli anni '50? - che da quello teorico. La prosa di von Neumann è sintetica ma molto chiara, e dato che è vero che la struttura odierna di un computer è fondamentalmente la stessa da lui creata il suo resoconto ci permette di avere un'idea della logica che portò alla creazione di tale struttura. Inoltre, anche se nel testo le differenze tra computer e mente non sono molto enfatizzate, leggere il testo con le conoscenze odierne - e soprattutto ricordarsi che la capacità di memoria del primo è enormemente aumentata - aiuta a capire che in realtà non sappiamo affatto come funzioni davvero il nostro cervello :)

  20. 5 out of 5

    Kyle

    In this unfinished short collection of lectures on the brain and the computer, von Neumann hints at some deep connections between artificial and neurological machines (brains!). Some of the insights really are amazing and indicative of what would come. While some of the figures are, of course, out of date (particularly for transistor switching speeds and densities), the qualitative arguments he makes more or less still hold. It's unfortunate that he wasn't able to finish these lectures, because In this unfinished short collection of lectures on the brain and the computer, von Neumann hints at some deep connections between artificial and neurological machines (brains!). Some of the insights really are amazing and indicative of what would come. While some of the figures are, of course, out of date (particularly for transistor switching speeds and densities), the qualitative arguments he makes more or less still hold. It's unfortunate that he wasn't able to finish these lectures, because some of the most salient material really comes to light in the final pages, where he begins to draw parallels between Universal Turing Machines (then yet unnamed as such) and our understanding of logic and mathematics as it relates to the 'computation' performed by our brains. Another interesting example of Johnny's foresight arises when he mentions the intrinsic inability to parallelize some algorithms. I'm not sure how well known this notion was at the time, but this would essentially later become formalized in what is now known as Amdahl's Law, and still is one of the thorns in the side of modern computing.

  21. 3 out of 5

    ferhat

    Fascinating in spite of the time and situations in which it's written. * Stronger impulse can override the result during recovery time of neuron. (i.e. To me; instinct, prejudice, habit etc.) * Trade-off arithmetic for the logic. (i.e pattern recognition) * Memory's like a flip-flop (recent chemical structure) and most traveled trails on the grass (tolerance to threshold via changes in the nature of neuron). * Hierarchy in artificial memory makes it fast and to be seemed as infinite from the point Fascinating in spite of the time and situations in which it's written. * Stronger impulse can override the result during recovery time of neuron. (i.e. To me; instinct, prejudice, habit etc.) * Trade-off arithmetic for the logic. (i.e pattern recognition) * Memory's like a flip-flop (recent chemical structure) and most traveled trails on the grass (tolerance to threshold via changes in the nature of neuron). * Hierarchy in artificial memory makes it fast and to be seemed as infinite from the point of arithmetic computation unit. In brain, it even starts from input. (i.e filtering in sense organs and pattern recognition again) * Brain can be seen an example of Turing machine so it can imitate anything. For sure, it is speaking/executing in one language but it can totally be different than what we are used to. (i.e catch all case ;)) * To my knowledge, there is not even one example of optimum in extremes where brain is no exception. It's not pure analog or digital but it's a good mix of both.

  22. 4 out of 5

    Scott Stirling

    1958, incredible. Boils down how computers and the brain work by describing how to do math in analog and digital ways, describes the essential concepts for decimal machine math and how that leads to binary machine math as a more efficient way of representing numbers in a logic machine. Talks about statistics and logic being the main fundamental aspects of math involved in computers and brains. Explains why memory area is essential for computing machines and requirements for memory, in principle. 1958, incredible. Boils down how computers and the brain work by describing how to do math in analog and digital ways, describes the essential concepts for decimal machine math and how that leads to binary machine math as a more efficient way of representing numbers in a logic machine. Talks about statistics and logic being the main fundamental aspects of math involved in computers and brains. Explains why memory area is essential for computing machines and requirements for memory, in principle. The foreword by the Churchlands added in 2000 is a fascinating update that explains how the circuitry of computers then (over a decade ago) are millions of times faster, but the brain is yet a massively parallel analog machine that runs at a peak of around 100 Hz. They claim an electronic computer as powerful as the brain (because being electronic rather than biochemical the connection speed is way way faster) could do in 30 seconds what would take the brain a year (constantly processing).

  23. 4 out of 5

    Roberto Rigolin F Lopes

    Here we have the very computer architect comparing the 50's machines to the human nervous system. He starts describing the 'current' (1956) digital/analog computers. If you are not into machines, the first chapters will bore you down (but hold on and wait for it). Else, you are going to enjoy this pre integrated circuit/microchip description. Then, he goes about making ingenious comparisons between the natural and artificial machineries. You may have lots of fun updating his figures to recent co Here we have the very computer architect comparing the 50's machines to the human nervous system. He starts describing the 'current' (1956) digital/analog computers. If you are not into machines, the first chapters will bore you down (but hold on and wait for it). Else, you are going to enjoy this pre integrated circuit/microchip description. Then, he goes about making ingenious comparisons between the natural and artificial machineries. You may have lots of fun updating his figures to recent computers. Hey, note that the human nervous system is pretty much the same (sic), but the computers evolved a bit last ~60 years.

  24. 3 out of 5

    Harrison

    Brilliant and succinct. Von Neumann's description of computers and their analogies to the brain seem obvious, until you realize that no one had thought about it like this before he did. He helped design the modern architecture of computers, and thought about what we could learn from thinking about neuroscience in tandem with computer science. A very short read as well.

  25. 3 out of 5

    Chris S

    Dry as the desert, but, when viewed in its historical context, an important work concerning ideas about the computational similarities and differences between natural and artificial computing devices. Recommended for engineering enthusiasts with too much spare time on their hands.

  26. 3 out of 5

    Angelo

    I'll admit it, this was not quite what I expected. It is a very serious and solid analysis of the analogies between computing machinery of the 1950s and the brain. Very solid, but also very slow. I guess I just had to be at the actual lectures...

  27. 4 out of 5

    Akshay Bakshi

    This a great history lesson and a wonderful introduction to the (first?) bridge between neuroscience and computer science. Von Neumann was bloody smart. This book would have been 5 stars if I had read it 50 years ago.

  28. 4 out of 5

    Robert

    This is an amazing set of thoughts around computing and the human brain. It's not easy reading, but it's worth the payoff in the end. It definitely helped me refine/further develop my own opinions on the subject. If you are a computer programmer, this is essential reading.

  29. 5 out of 5

    Artem

    I always wonder why Turing is far more recognised in popular culture, while nobody knows about von Neumann. Not an easy read. Fascinating how he calls everything "organs" - modules, components, parts.

  30. 3 out of 5

    Kyle

    Interesting, but a modern annotated edition (even at time of publication for this edition), saying things like "He's referring to cache here" or "modern speeds are in the such and such range" would have been helpful.

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