Are Brains Analogue or Digital? | Prof Freeman Dyson | Univeristy College Dublin

[Applause] yeah well I thank you everybody who had a hand in inviting me here I've been enjoying your hospitality and and I'm sorry I'm here on it's such a short time not to get to know more of you anyway I should apologize for reading from a text which are normally if I were talking about a subject that I actually understand I would I would talk extemporaneously but since I'm talking about a subject in which I know about as little as you I prefer to stick to the text so anyway here it goes so in February 1943 Dublin was an oasis of peace in a Europe at war one of the few places where deep thinkers and scholars could find refuge thanks to the hospitality of Ireland of the vimana de Valera the physicist Schrodinger was here he gave at Trinity College a series of seven lectures with the title what is life to an audience of 400 people he tells us with pride that the audience did not substantially dwindle he replied for the first time the way of thinking of a quantum physicist to the basic problems of biology and he has a good command of the English language fortunately his lectures were published in 1944 by the Cambridge University Press and I was lucky to buy a copy of the first edition in February in 1945 while the war was still raging his message came like a winter sunrise bringing light to the dawn of the new age of biology here is the opening statement from shredding his book so now I quote from Schrodinger we have inherited from our forefathers the keen longing for unified all-embracing knowledge the very name given to the highest institutions of learning reminds us that from antiquity and throughout many centuries the universal aspect has been the only one to be given full credit but the spread both in width and depth of the multifarious branches of knowledge during the last hundred and hundred years has confronted us with a career dilemma we feel clearly that we are now only beginning to acquire reliable material for welding together the sum total of all that is known but on the other hand it has become next to impossible for a single minds fully to command more than a small specialised portion of it I can see no other escape from this dilemma then the some of us should venture to embark on a synthesis of facts and theories albeit with secondhand and incomplete knowledge of some of them and at the risk of making fools of ourselves so much for my apology so that's the courts from Schrodinger so I take courage from Schrodinger's example like him I am a physicist venturing into biology like him I take the risk of making a fool of myself like him I'm asking a question his question what his life was timely and enormous Lee through for although he did not answer it I hope that mine will be equally timely and equally fruitful compared with his bold speculations mine are modest he gave seven lectures and explored his subject deeply I give only one and barely scratched the surface of mine with thanks to the hospitality of Ireland and the Dublin Institute for Advanced Studies I'll now begin I should then just give you a table of contents that just you get an idea of what the talk is going to be about so one homage to Schrodinger to the road not taken' three dynamic quantum boys clustering for the failure of artificial intelligence five Maps and feelings six the Endicott House meeting seven mathematics as a tool for understanding nature and eight quantum analog computing so this is now section two which is the road not taken' the title of the talk is our brains analog or digital we know that creatures like us have two quite separate systems for processing information the genome and the brain we know that the genome is digital and we can accurately transcribe our genomes onto digital machines we cannot transcribe our brains and the processing of information in our brains is still a great mystery I will be talking about real brains and real people asking a question that will have practical consequences when we are able to answer it of course I'm not able to answer it now all I can do is examine the evidence and explain why I consider it probable that the answer will be that brains are mainly analog Robert Frost said it two roads diverged in a wood and I took the one less traveled by and that has made all the difference so in the 1930s there were five kinds of computers available for doing serious calculations two of them were digital the march and calculator for doing accurate arithmetic and the Hollerith card punch machine for tabulating big masses of data three of them were analog the slide rule for doing fast arithmetic with three figure accuracy the Bush differential analyzer for solving differential equations and the leymah photoelectric number sieve for solving equations in integers and factorizing big numbers the lamer machine worked with integers but was still an analog machine it did calculations using finite Galois fields and identified integers by Counting holes in a wheel not by a digital code but then in 1936 Alan Turing wrote his paper on computable numbers which revealed the power and beauty of digital computing as an abstract logical construction after that analog computers slowly went out of fashion analog computers became the road not taken' I still used to use my slide rule for calculating my income tax and until the 1980s when the tax collectors of the state of New Jersey demanded for figure accuracy and [Laughter] in the calculation of interest rates for four-figure accuracy I was forced to switch to a digital calculator now we're so immersed in a world of digital computers that is hard to imagine things going the other way it is true that brains are analog then we must sooner or later take the road the Turing did not take and explore what analog computers can do there are good reasons why the world of science and commerce went digital in the 20th century digital data and digital calculation have huge advantages over analog in accuracy in speed and in reliability there are many situations in life and in business where 3 figure accuracy is not good enough there are even some situations in science where 12 figure accuracy is not good enough for all kinds of practical purposes digital computers are here to stay but the brain has big advantages in flexibility and versatility the brain somehow manages to do a dozen different different jobs seeing and hearing and walking and talking and thinking and controlling our vital functions all at the same time without getting confused if it is true that the brain is an analog machine then we should be able to build analog machines with the same kind of flexibility and versatility that possibility is the subject of my talk so section 3 dynamic quantum clustering one of the big unsolved problems of the modern world is to convert information into understanding this is a big problem in science in government in business administration and in economics in each of these areas we have huge amounts of information and very limited understanding as a result of the rapid progress of digital technology it has become far cheaper to collect information than to understand it recently a new method called dynamic quantum clustering has been invented to extract small nuggets of understanding from large amounts of information I'm grateful to my friend Marvin Weinstein who is one of the inventors of dynamic quantum clustering for telling me about it the idea of dynamic quantum clustering is to present the information in a large database to a human viewer in the form of a moving picture using a mathematical algorithm borrowed from the motion of systems of particles in quantum mechanics the quantum the quantum mechanical motion is entirely fictitious it does not represent any process happening in the real world it is designed simply to make a big collection of data understandable to a human brain the human brain is at home in the world of moving pictures it can pick out structures in moving pictures quickly and efficiently after the human viewer has called attention to a structure the dynamic quantum clustering program can record the structure and analyze it using digital processes the human eye and brain serve as a subroutine in the digital program making use of the brains peculiar skill in extracting structure from patterns of movement in space and time in Weinstein's paper that's which I give the reference to it in absolute published 2013 the dynamic dynamic quantum clustering method is illustrated by applying it to big databases in five different fields nano chemistry condensed matter physics biology seismology and finance in each field the method finds subsets of the data that contain important information the information remain hidden if the data is analyzed by digital processes for example in the field of nano chemistry the object of study is a fragment of an ancient Roman pot and the hidden structure is a filamentary distribution of oxidized and reduced phases of iron similar structures are found in the electrodes of lithium-ion batteries in human bones and in Roman pots the filaments are evidence that the same kind of chemical reactions are occurring in all three materials the chemistry of the lithium ion electrodes was understood first and the understanding could then be transferred to the bones and the pots materials that are less accessible to laboratory measurements Weinstein describes the purpose of dynamic quantum clustering look for the needle in the haystack determine what it is and find what this means the reason why dynamic clustering is powerful is that you discover the needle without knowing in advance what you're trying to look for you do not need to write a detailed description of the needle into the search algorithm the human brain has the capacity to make unexpected discoveries so I see dynamic quantum clustering as the first step on a long road to create islands of understanding in a sea of information to progress further along this road we must not only exploit the marvelous faculties of the human brain but also understand how they work practical use of dynamic quantum clustering for exploring databases must go hand in hand with neurological exploring of the brain the first big mystery to be to be attacked is the physical basis of memory we know that the brain has at least two systems for recording memory one short-term and one long-term we have no idea how memories are encoded either chemically or physically after that mystery is resolved we may go further to attack the second great mystery our memories are accessed and retrieved the logical structure of our memory system appears to be associative we retrieve a memory by following a chain of thought that connects it with another memory but we have no understanding if the language the brain is using to encode a chain of thought if we can ever develop a version of dynamic clustering that incorporates the chain of thought it will become a far more powerful tool for converting information into understanding I'm not here to talk about particle physics but I have to make a brief digression to discuss the application of dynamic quantum clustering to the understanding of particle experiments recently the world has been celebrating the discovery of the Higgs particle that the Large Hadron Collider in Geneva a huge and expensive particle accelerator at the European Center for Nuclear Research the Higgs particle is indeed an important discovery and Peter Higgs and Francois Anglia richly deserved the Nobel prizes which they won for predicting the existence of that particle forty years before I'm happy that the particle is finally discovered after many years of effort but I'm unhappy with the way the particle was discovered the Large Hadron Collider is not a good machine for making discoveries the collider mix program makes protons collide at very high energies and every collision makes a big cascade of uninteresting particles background that swamped the detectors only a tiny fraction of rare collisions produce Higgs particles the background of uninteresting events is so enormous that the machine cannot possibly look at them the only way to see the rare Higgs particles is to write into the program that controls the detector detailed instructions for saving those rare events and discarding the others the Higgs particle was only discovered with this machine because we told the Machine what we expected it to discover this is an unfortunate deficiency of the Hadron Collider it cannot make unexpected discoveries big steps ahead in science usually come from unexpected discoveries it remains to be seen whether an analysis of the Hadron Collider data with dynamic clustering methods might enable that the Hadron Collider to make unexpected discoveries unfortunately the data stream from the collider is so intense that it is impossible to display it without some drastic pruning if something unexpected is hidden in the data even if dynamic clustering is used to look at it there's a risk that the unexpected treasure gets chopped out in the pruning I think the future of particle experiments belongs to passive underground detectors these are detectives looking for rare high-energy particles coming from outer space nature provides a generous supply of astronomical accelerators distributed over the universe accelerating particles to far higher energies than we can reach with our biggest devices together with the rare high-energy particles come numerous numerous low-energy particles that do not penetrate so far underground detectors are put deep underground so as to eliminate almost all the uninteresting background events deeply penetrating particles are rare enough so that every event in the detectors can be recorded and examined in detail if some new species of particle or some new kind of interaction is present in the detectors it will be seen the detectors do not need to be told in advance what there opposed to discover fig passivity detectors are expensive but they're still much cheaper than the Hadron Collider if high-energy particle experiments are to make unexpected discoveries this is probably the best way to go section for the failure of artificial intelligence so and now I come back from the digression to particle physics to brains and computers I'm looking for evidence to confirm or to refute the hypothesis that the brain is more analog than digital in its operation so my first piece of evidence is the failure of artificial intelligence 60 years ago when the digital revolution was beginning and the pioneers of digital computer technology were dreaming of future triumphs one of their grand dreams was the creation of artificial intelligence artificial intelligence was imagined as a digital computer that could think and act and communicate like a human brain artificial intelligence meant a digital machine that would be as smart as a human many brilliant and ambitious people devoted their lives to this dream 20 years later my friend Sir James light Hill was asked by the British British government to advise the science Research Council about the support of research in artificial intelligence Life Hill wrote a famous report with the title artificial intelligence a general survey which made him a lot of enemies light Hill divided the artificial intelligence activities into three categories a B and C category a was advanced automation the development of automatic control machinery for practical purposes category C was central nervous system research the use of computers the scientific study of neurology and psychology category B was supposed to be the bridge between a and C category B was the building of robots not the utilitarian jobs but for imitating the behavior of human beings like Hill discussed the progress that had been made by the year 1972 that was when he was writing in those three areas and then delivered his verdict he concluded that areas a and C will legitimate programs of research a belonging to engineering and C to science the work in a and C was moving ahead more slowly than had been expected two of the most important projects in area a were automatic speech recognition and automatic translation both of which had failed miserably three important objectives in Area C with the understanding of memory and the understanding of learning and forgetting none of which had been achieved but work in the areas a and C still had great promise for the future and deserved continued support on the other hand area B had no scientific substance the bridge between a and C did not exist a and C should be supported as separate enterprises with separate tools and separate objectives area B did not deserve support so here is likely old sketch of area B which I quote now from light Hill most robots are designed to operate in a world like the conventional child's world as seen by a man they play games they do puzzles they build towers out of bricks they recognize pictures in books bear on rug with ball although the rich emotional character of the child's world is totally absent a relationship which may be called pseudo maternal comes into play between a robot and its builder now another 40 years have gone by and life yields verdict on artificial intelligence still stands a lot has happened in those 40 years in area a in area a after 40 years of blood sweat and tears the dragon programs of automatic speech recognition are finally working well and automatic translation programs are producing results that are imperfect but useful in Area C there's been less progress and in area B none at all progress in understanding the human brain has come from new physical tools functional magnetic resonance image and genome sequencing rather than from new ideas about neural circuitry progress in building autonomous robots has come from imitating insects rather than from imitating humans artificial intelligence after 60 years of strenuous efforts in many countries is still on balance a failure so I'm saying the failure of artificial intelligence was no accident it failed because the goal was to imitate an analog device the human brain with a digital device the electronic computer the successes in area a with speech recognition and translation were possible because speech and written language are handled by special areas of our brains which have evolved to process digital information if I'm right the successes of artificial intelligence using digital machines will be limited to those areas so next section five maps and feelings another striking fact that we know about brains is that they use maps to process information information from the retina goes to several areas of the brain where the pictures seen by the eye is converted into a maps of various kinds information from sensory nerves in the skin also goes to areas where the information is converted into distorted maps of the body the brain is full of maps and a big part of its activity is transferring information from one map to another as we know from our own use of maps mapping from one picture to another can be done either by digital or by another analog processes because digital cameras are now cheap and film cameras are old-fashioned and rapidly becoming obsolete many people assume that the process of mapping images in the brain must also be digital but the brain has evolved over millions of years and it does not follow our ephemeral fashions a map is in its essence an analog device using a picture to represent another picture and the imaging in the brain may be done by direct comparison of pictures rather than by translation of pictures into digital data introspection tells us that our brains are spectacularly quick in performing two tasks essential to our survival in the natural environment the recognition of images in space and the recognition of patterns of sound in time we recognize a human face or a snake in the grass in a fraction of a second we recognize the sound of a voice or a footstep equally fast the process of recognition requires the comparison of a perceived image with an enormous database of remember images how this is done in the quarter of a second with no conscious effort we have no idea it seems likely the scanning of images in associative memory is done by direct comparison of analog data rather than by digitalization and as a fact that we know for sure is that our processing of sensory information is strongly coupled with emotions seeing and hearing and smelling in externally mixed up with feeling a big part of human enterprise and creativity is devoted to the arts music to explore the emotional dimensions of hearing painting and architecture to explore the emotional dimensions of seeing our perception of sensory information is concerned with quality much more than with quantity subjective impressions may be misleading but our emotional response to music or to a beautiful landscape suggests we are processing sounds and images as shapes rather than as digits the glory of a desert sunrise or of a Rembrandt painting belongs to the whole scene and not to the individual pixels as a general rule our perception of sensory information appears to be continuous rather than discrete but there is one important exception to this rule the exception is our perception of language spoken language is digital using a finite set of discrete phonemes to convey meaning our auditory system is trained to convert a continuous flow of sound into a discrete sequence of phonemes and then to convert a sequence of phonemes into words and sentences there are specialized areas of the brain mainly in the left hemisphere where this digital processing of information is done written language is also digital and there are other areas of the brain where visual in translated into digital sequences of letters or ideograms the invention of Braille allows blind people to transfer the process of digital translation from visual to tactile information these capabilities give us proof that certain parts of the brain are digital processing phonemes or written symbols as discrete objects but our understanding of language is also associated with strong feelings and emotions that go far beyond the processing of sounds and symbols language is not perceived by us as a string of phonemes a big part of our culture is concerned with art forms arising from language poetry and drama and preaching and storytelling beyond the digital words and phrases there is a whole world of literature we perceive literature as having style and sparkle depth and resonance our perception of literature belongs to the overall shape of the language not to the individual words the quality of a poem such as Homer's Odyssey or Eliot's Waste Land is like the quality of a human personality a large part of our brain is concerned with social interactions getting to know other people learning how to live in social groups the observed correlation between the size of brain and the size of social groups and primate species makes it likely that large brains evolved primarily to deal with social problems our ability to see others as analogues to ourselves is basic to our existence as social animals the computer engineer Danny Hillis published 25 years ago a delightful speculation with the title intelligence as an emergent behavior or the songs of Eden this was published in 1988 he tells a story to describe how it might have happened in the evolution of humans that music came first and speech came second so now I quote from Hillis once upon a time about two and a half million years ago there lived a race of apes that walked upright the young Apes like many young Apes today had a tendency to mimic the actions of others in particular they had a tendency to imitate sounds some sequences of sounds were more likely to be repeated than others I will call those sequences songs the songs survived they bred competed with one another and evolved according to their own criteria no Fitness one successful strategy for the competition between songs was for a song to specialize to find a particular niche where it would be likely to be repeated once the songs began to specialize it became advantageous for an ape to pay attention to the songs of others and to differentiate between them by listening to songs a clever ape could gain useful information once the Apes began to take advantage of the songs a mutually beneficial symbiosis developed songs enhanced their fitness by conveying useful information Apes enhanced this their Fitness by improving their capacity to remember to replicate and understand songs so evolution created a partnership between the songs and the Apes which thrived on the basis of mutual self-interest eventually this partnership evolved into one of the world's most successful symbionts us so this fable of Danny Hillis may not be true but it explains two great mysteries of human evolution which are otherwise hard to understand why did we evolve people like Mozart and Beethoven and why did we evolve people like Sophocles and Shakespeare it seems that we have far greater capacity for composing and appreciating music and far greater capacity for elaborating and enjoying speech than would be required for surviving in a primitive environment Hillis explains the existence of Mozart and Beethoven by evolving music first with the songs competing for survival on the basis of musical quality he explains the existence of Sophocles and Shakespeare by evolving speech second with the songs competing for survival on the basis of meaning a song with meaning attached evolves into speech with the quality of the song evolving into quality of the speech this version of our history explains the amazing fact that a bunch of apes only only recently defend descended from the trees can produce great composers and poets the evolution of great works of art depends on the quality of the music and the poetry not on the digital language of the note of the notes and the syllables so I'm suggesting the brain is mainly an analog device with certain small regions specialized for digital processing it is certainly not true as sometimes claimed by pundits talking on television that the left hemisphere is digital than the right hemisphere is analog it seems to be true that most of the digital processing is done on the left side but the division of labour between the two hemispheres is still largely unknown so Section six the Endicott House meeting 33 years ago in May 1981 we had a meeting at the Endicott House a club house owned by MIT in the american cambridge talking about the future of computing the meeting was organized by tom thoughtfully and a lot of bright people were there including Danny Hillis richard fineman charles bennett and two people had not heard of before Marianne Perl and Ian Richards Charles Bennett talked about his recent discovery that digital computing could be done reversibly without erasing information and without dissipating energy Hillis talked about parallel computing and Fineman talked about quantum computing two subjects which later turned out to be important but to me the most exciting news at the meeting came from poor Ellen Richards two mathematicians who attended the University of Minnesota Mary Ann Perl and Ian Richards proved a theorem that says in a mathematically precise way that analog computers are more powerful than digital computers that was published in 1981 they give examples of numbers that are proved to be non computable with digital computers but are computable with a simple kind of analog computer Alan Turing had defined computable numbers to be those that can be computed with digital machines the numbers discussed by poor L and Richards analog computable but not curing computable an analog computer that deals directly with continuous variables while a digital computer deals with discrete variables the poor Ellen Richards computer is a classical field getting through space and time and obeying a linear wave equation the classical electromagnetic field obeying the Maxwell equations could do the job poor Ellen Richards show that the field can be focused on a point in such a way that the strength of the field at that point is not computable by any digital computer but it can be measured by a simple analog device the imaginary situations that they consider have nothing to do with biological information the pure Richards theorem does not prove that analog brains are better than digital brains it only makes that conjecture more plausible Charles Bennett recently sent me a picture of the people at the Endicott House meeting Purell and Richards are there in the picture two young people who had done something extraordinary I don't know what happened to them afterwards I had the feeling I was the only person at the meeting who took their work seriously they had done for analog computing the same job that Alan Turing had done for digital computing 45 years earlier cheering published his classic paper computable numbers in 1936 poor L and Richards published theirs in 1981 both papers took a long time to attract attention my son George recently published a book with the title Turing's Cathedral describing the Magnificent added edifice of knowledge and power that grew out of Turing's paper puroland Richard's Cathedral has not yet begun to grow science fiction writers gave us a picture of digital life and a picture of analogue life long before we could decide which picture comes close to describing humans to visualize digital life think of a human consciousness downloaded from a brain into a digital computer like the character how in the Stan Kubrick movie 2001 to visualize analog life think of a human consciousness uploaded into a black cloud as described in the science fiction novel by Fred Hoyle the black cloud is an analog device with its memories encoded in magnetic fields generated by just drains moving through the cloud if we are analog life downloading into a digital computer may involve a certain loss of our finer feelings and qualities that would not be surprising I certainly have no desire to try the experiment myself perhaps when the time comes for us to adapt ourselves to a cold universe and to abandon our extravagant flesh-and-blood habits we should upload ourselves into black clouds rather than download ourselves into silicon chips if I had to choose I would go for the black cloud every time so now I'm going to skip to section 9 the mathematics as a tool for understanding nature that so that will be in the written version and so now comes the last section quantum analog computing during the last 30 years the big new enterprise has grown up with the brand name quantum computing this enterprise aims to imitate the architecture of ordinary digital computers using quantum spins instead of classical on-off switches as carriers of information a quantum spin means an atom or a collection of atoms with a spin obeying the rules of quantum mechanics the machines built in this way a quantum digital computers the holy grail of quantum digital computing is to implement the SHA algorithm 18 years ago Peter Shaw astonished the world by inventing an algorithm which a quantum computer can in principle use to factorize large integers in polynomial time polynomial time means the number of computer operations required is less than some power of the number of digits in the integer to be factored the finding of factors of a large integer is a notoriously hard problem for classical computers not using quantum processes it is generally believed but not proved that the classical computer cannot factorize large integers involve in polynomial time the security of various public key encryption systems depends on the impossibility of rapid factorization the shor algorithm constitutes a threat to the security of such systems but if the threat to secure encryption becomes real only if the theoretical is superior power of quantum digital computers can be embodied in real Hardware quantum computing today is it roughly the same stage of practicality as classical computing in the days of Charles Babbage in the early 19th century Babbage had the right concepts but he lacked the physical tools to make his concepts useful he tried to build an analytical engine out of mechanical clockwork a project that absorbed his time and money and strengths for many years and inevitably failed when I was a boy in London I used to gaze in fascination at the relics of Babbage's analytical engine preserved in a glass case at the Science Museum in London if we should try to build a quantum computer today its fate would probably be similar the quantum devices that we have available today are not much better than Babbage's clockwork but I'm asking whether our brains or parts of our brains might be quantum analog computers I believe this possibility was first suggested by Richard Feynman the idea is that the brain might be an amplifier sensitive to the quantum states of some special molecules constituting a molecular memory and amplifying the molecular information until it becomes a signal strong enough to drive motor neurons to action in this way the brain would be able to use quantum jumps in the memory which are strictly unpredictable according to the laws of quantum mechanics to control the executive decisions the brain would be a device for amplifying quantum unpredictability so as to achieve freedom of will as soon as I begin talking about freedom of will I'm entering a philosophical hornet's nest in which many famous thinkers and writers have been stung but I consider philosophical discussion about quantum mechanics to be unprofitable I'm asking a practical question to be answered by observation and experiment not by philosophical speculation I'm asking whether there exists in the brain a structure embodying information in the quantum states of memory molecules and hooking up these quantum states to an amplifier which translates them into classical neurological signals if such a structure exists then the brain is a quantum analog device and the philosophers can continue to argue about whether it gives us free will how should we study experimentally the way working of a human brain the best experimental tool is probably a human baby what goes on inside the head of a three-month-old baby anyone who has raised a baby knows the problem how can we imagine what's going on inside that little head how did it happen that that little head grows to almost adult size and capabilities in two years in two years it sorts out the bewildering variety of neural inputs from eyes and ears it recognizes faces and voices it masters grammar and syntax it knows the difference between nouns and verbs it learns how to exploit the weaknesses of grownups in recent years experts in child development have found reliable ways of communicating with younger and younger babies a baby is young as three months old can communicate interest or lack of interest in something that it sees if the baby is interested it will move its eyes to follow the object if it's not interested it will disregard the object using this channel of communication it is possible to prove that very young babies can already tell the difference between speech and noise between known and unknown voices and faces between familiar and unfamiliar syllables and shapes as we move through the 21st century it's likely that new tools will become available scanning non-intrusive lis the brains of babies with high resolution in space and time by the end of the century we should be able to answer the question how do babies begin to think after that question is answered we will have a better chance of answering the more difficult question how do babies turn into grownups where does grown-up imagination come from how does a brain become creative where the music and poetry and the art and science come from how did a monkey recently descended from the trees become aware of itself and of the mysteries of the universe around it my dream is that sometime in the next hundred years we shall answer these questions and understand how the brain works as a quantum analog device then we will be able to copy nature's architecture and build quantum analog machines ourselves we will finally solve the problem of artificial intelligence as James like Hill defined it we will understand why digital artificial intelligence did not work we will have the power hands to build machines that think like humans but before that happens we must think very hard how to use that power for good rather than for evil thank you [Applause] [Applause] you you

Channel: UCD - University College Dublin

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Keywords: UCD, University College Dublin, Dublin, Ireland, UCD - University College Dublin, myucd, Freeman Dyson (Author), Theoretical Physics (Field Of Study), Mathematics Education (Website Category), Maths, Biology (Field Of Study), Artificial Intelligence (Industry), Computing (Exhibition Subject), Computer Science (Industry), Brain (Literature Subject), Robotics (Invention), Quantum Theory (Video Game), Quantum Computer (Algorithm Family), Analogue brain, digital brain, brain

Id: JLT6omWrvIw

Length: 50min 40sec (3040 seconds)

Published: Mon May 26 2014

Reddit Comments

[u/MisterGGGGG]

An analog system can absolutely be simulated (or at least approximated) by a digital system, it just takes more power.

I think physicists like Freeman Dyson and Carver Mead make a good point: AI will come from massively parallel special chips that will include silicon transistors used in their natural analog form.

[u/Weerdo5255]

I agree, digital processes can't replicate analog systems perfectly.

If however you throw enough raw power at it, you'll get a fidelity of simulation down to the point that you'd need to run both systems for a few billion years to notice a drift. That's good enough for a brain upload, and heck even if you lose some information during that process that happens daily on an analog brain anyway.

[u/vonHindenburg]

I am definitely a luddite who is disturbed by the implications of uploaded consciousness, but yeah... Gotta disagree.

I think of it this way: The fire control computers used during WWII were amazingly complicated analogue machines. They could constantly take in several dozen inputs of course, speed, wind at different altitudes, spin of the Earth, humidity, age of the shell, etc..... These factors would be constantly computed by a series of cams and gears into bearings at which the guns should be aimed so that, as soon as they were reloaded and ready to fire, they could match the calculated bearing and elevation and let off a salvo.

Analogue computers were better at this task up through the 50's because they could constantly compute new results, while digital computers would run a calcultaion, spit out a result, and then begin running it again with new, slightly adjusted inputs. Initially, these calculations took too long to be iseful. However, once digital computers became fast enough to run the calculations at a speed great enough to approximate their analogue predecessors, they took over.

I think that purely digital beings will quickly cease to think in a manner that we see as properly human, but it won't be their architecture that is the limiting factor.

[u/AbbydonX]

It's always worth remembering that while digital approaches are undoubtedly powerful they are still an approximation of the underlying analog problem. This is not ideal for time varying problems where a digital system has to necessarily approximate the problem and evaluate it at a single time before moving to the next discrete time. With increasing computational performance you can make the approximation better by making the steps smaller but this requires more power and therefore produces more heat.

For the sort of continuous differential problems associated with artificial intelligence and robotics this causes problems as it may not be possible to achieve suitable performance to deal with complex dynamic situations. Analog processing is however better suited for solving these types of problems in an energy efficient way. Since many people believe that the feedback loop between brain, body, environment and sensors is a requirement for true intelligence this suggests that perhaps analog processing is also required.

This type of approach was initially called neuromorphic as it attempted to model how biological neurons work, though it has more recently expanded to be called cytomorphic.

Biological information-processing systems operate on completely different principles from those with which most engineers are familiar. For many problems, particularly those in which the input data are ill-conditioned and the computation can be specified in a relative manner, biological solutions are many orders of magnitude more effective than those we have been able to implement using digital methods. This advantage can be attributed principally to the use of elementary physical phenomena as computational primitives, and to the representation of information by the relative values of analog signals, rather than by the absolute values of digital signals.

[u/[deleted]]

They simulate analog through digital all the time.

[u/JetScootr]

Didn't some mathematician prove, mathematically, that all information can be represented by numbers? If so, then (by the definition of "number") digital can simulate analog.

[u/pint]

to everyone in this conversation:

nobody is talking about precision. i mean, almost everybody here, but that's the crux of the issue really. it is not the claim that analog is more precise, the claim is, there are things it can practically calculate and a turing machine can't. similarly how a quantum computer can be simulated by classical computers, but i can easily conjure up a problem (e.g. factorization) that a classical computer can't practically solve, but a quantum computer can. it does not matter that given infinite time, a classical could solve the same problem. the question is always practicality.

[u/rapax]

Hey look, it's Clarke's first law.

[u/pint]

if this is true, that throws a wrench into the mechanism. no more brain uploading, unless someone invents good analog computers.