John von NeumannReseñas

Indeholder "Klara von Neumann: Preface", "Introduction", "Part 1. The Computer", " The Analog Procedure", " The Conventional Basic Operations", " Unusual Basic Operations", " The Digital Procedure", " Markers, Their Combinations and Embodiments", " Digital Machine Types and Their Basic Components", " Parallel and Serial Schemes", " The Conventional Basic Operations", " Logical Control", " Plugged Control", " Logical Tape Control", " The Principle of Only One Organ. for Each Basic Operation", " The Consequent Need/or a Special Memory Organ", " Control by "Control Sequence" Points", " Memory-Stored Control", " Modus Operandi of the Memory-Stored Control", " Mixed Forms of Control", " Mixed Numerical Procedures", " Mixed Representations of Numbers. Machines Built on This Basis Precision", " Reasons for the High (Digital) Precision Requirements", " Characteristics of Modern Analog Machines", " Characteristics of Modern Digital Machines", " Active Components; Questions of Speed", " Number of Active Components Required", " Memory Organs. Access Times and Memory Capacities", " Memory Registers Built from Active Organs", " The Hierarchic Principle for Memory Organs", " Memory Components; Questions of Access", " Complexities of the Concept of Access Time", " The Principle of Direct Addressing", "Part 2. The Brain", " Simplified Description of the Function of the Neuron", " The Nature of the Nerve Impulse", " The Process of Stimulation", " The Mechanism of Stimulating Pulses by Pulses; Its Digital Character", " Time Characteristics of Nerve Response, Fatigue, and Recovery", " Size of a Neuron. Comparisons with Artificial Components", " Energy Dissipation. Comparisons with Artificial Components", " Summary of Comparisons", " Stimulation Criteria", " The Simplest~Elementary Logical", " More Complicated Stimulation Criteria", " The Threshold", " The Summation Time", " Stimulation Criteria for Receptors", " The Problem of Memory within the Nervous System", " Principles for Estimating the Capacity of the Memory in the Nervous System", " Memory Capacity Estimates with These Stipulations", " Various Possible Physical Embodiments of the Memory", " Analogies with Artificial Computing Machines", " The Underlying Componentry of the Memory Need Not Be the Same as That of the Basic Active Organs", " Digital and Analog Parts in the Nervous System", " Role of the Genetic Mechanism in the Above Context", " Codes and Their Bole in the Control of the Functioning of a Machine", " The Concept of a Complete Code", " The Concept of a Short Code", " The Function of a Short Code", " The Logical Structure of the Nervous System", " Importance of the Numerical Procedures", " Interaction of Numerical Procedures with Logic", " Reasons for Expecting High Precision Requirements", " Nature of the System of Notations Employed: Not Digital but Statistical", " Arithmetical Deterioration, Roles of Arithmetical and Logical Depths", " Arithmetical Precision or Logical Reliability, Alternatives", " Other Statistical Traits of the Message System That Could Be Used", " The Language of the Brain Not the Language of Mathematics".

Bogen starter med lidt indledning og lidt forklaring om analoge computere. En differentialanalysator har fx (x+y)/2 og (x-y)/2 som naturlige operatorer i stedet for x+y og x-y. Jeg tror det var en skam at von Neumann ikke nåede at tænke over kvantecomputere.
Han gennemgår kort addition, subtraktion, multiplikation og division som nødvendige for den digitale computer og at det er nemmere i binært, men også sagtens kan gøre decimalt. Præcision i digitale udregninger er meget billig at lave sammenlignet med analog præcision. Nydelig gennemgang af hvordan en digital computer kan opbygges og hvordan registre og memory og eksternt lager kan håndteres.
Derefter kigger han på hjernens opbygning. Han forsøger at bestemme antallet af komponenter, størrelse, energiforbrug, reaktionstid og funktioner. Konklusionen er selvfølgelig at hjernen er meget anderledes end en computer.

Paul Erdős, Paul Halmos, Theodore von Kármán, John G. Kemeny, John von Neumann, George Pólya, Leó Szilárd, Edward Teller og Eugene Wigner blev for sjov kaldt marsmændene, fordi de kom fra et obskurt land (Ungarn) og talte indbyrdes i et uforståeligt sprog og var superintelligente. John von Neumann (28 december 1903 - 8 februar 1957) blev ramt af knoglekræft kort efter at han i starten af 1955 var blevet bedt om at holde en forelæsningsrække "Silliman Lectures" på Yale i forårssemesteret 1956 og selv om han prioriterede artiklerne her meget højt, nåede han ikke i mål.

The first part consists of heavily edited versions of von Neumann's famous 1949 lectures given at the University of Illinois. Burks' commentary is interesting though I would like to see the complete lectures.

The second part is a construction of the text von Neumann was working on at the time of his death. This is heavy reading because it's the foundational work of a new field. If one's interest is playing around with CAs there are probably more accessible options.

The book design unfortunately has the figures and schematics for the CA appended instead of intermingled.

The book was of interest mostly for historical reasons but the comparisons between computing and neurophysiological components (as they were known at the time) and some of the analogising between computing machines and the human neurobiological system were interesting. It's a pity von Neumann didn't finish and deliver the lectures before he died.

Von Neumann's unfinished last work comparing digital computers with the human brain. Works through his estimations and comparisons of various capabilities, e.g., that the human brain has about 3.5 PB of storage. Concludes that the architecture of the brain and central nervous system is so different from that of the digital computer that it implies a completely different (programming) language of mathematics and logic is used.

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 davvero funzioni il nostro cervello :)

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.

One of the titanic founding works of Game Theory. Requires an extensive background of mathematics to understand, but it is very comprehensive, covering many types of games (including a version of poker). Some significant advances have been made in the field after this was published (Nash, etc.) but still something worth reading if you can handle it.

Brilliant insights that have informed all thinking on the subject for the past 50 years. Main argument: despite some obvious similarities in architecture (digital signals, memory) the human brain must work on a different computational model.

After 50 years, this book by the genius John von Neumann is still relevant in many aspects. I wish I had read this before I started my cognitive science education or before I have written my cog. sci. thesis. Neumann's insights into the architecture of the information processing of the brain is what many scientists today consider a nearly standard framework.

Anybody in interested in the intersection of computing science and brain research should read this short and sharp book, not only for its contents but also for Neumann's style.

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.

Are you kidding, here is the man. Do kidz in skool knows'im, hellz nah. It is essential.