Kurzweil Interviews Minsky: Is Singularity Near?

I'm Marvin Minsky and I teach at MIT in subjects of theories about how to make machines that are intelligent whatever that means and I come from a combination of mathematics and physics and electrical engineering and psychology and biology and I try to get my students to combine all those kinds of ideas to invent new things he wrote an essay in my first book the age of intelligent machines and you wrote only a few decades ago and this was 20 years ago the ability of organisms to reproduce seemed to be a deep and complex mystery yet as soon as they understood the elements of how our gene strings replicate themselves biologists wondered why it took so long to think of such a simple thing so how we doing in terms of understanding these mechanisms and of our thinking I see a problem with this field of artificial intelligence because biology and physics worked so wonderfully that the people trying to make intelligent machines would like to imitate it for example Archimedes discovered a few things about physics then there was a long silence and then Galileo and Newton came along and Newton discovered three simple laws that explained almost all of the mechanical phenomena we see and century or two later Maxwell did the same thing for electricity there were four simple laws and that explained electricity and magnetism and Einstein came along and reduced those seven laws to really just one or two and physics progressed wonderfully by finding these incredibly simple explanations so psychologists always wanted to do that too and they made little theories of how learning works by connecting thoughts and and so forth and we didn't see much we didn't see nearly so much progress after that because a hundred years ago there were some brilliant people Freud and wouldn't and William James and Francis Galton there were four great psychologists who made rather complicated theories about how the mind works but then a lot of psychologists tried to imitate the physicist and reduce these to a few simple laws and that didn't work so well and a hundred years went by without a great many discoveries here's what I think is the problem the brain doesn't work in a simple way because evolution has been going on for 400 million years in building structures of upon structures upon structures the neurons in our brains are almost the same as they were four hundred million years ago but the organizations are much more complicated so a good way to think of the brain is that it's four hundred different computers if you look in a book on Neurology in the index you see hundreds of different structures and they each work in different ways so I think it was a sort of mistake to look for the common principles because the common principles will tell you how a fish works but it won't tell you how a person works we are finding for example the appears to be some repetitive structures in the cerebral cortex and a different repetitive structure in the cerebellum I mean might there be some basic principles that are used as building blocks in different ways to build up these hierarchies of complex thoughts yes all the parts of the brain are similar but if you look inside a computer everything is made of transistors there are slight differences between them but but the properties of transistors are annoying they're not linear they're not so dependable but if you take just two transistors and put them in a certain circuit then you get a flip-flop and that behaves the same every time and I suspect that the important thing about the brain was that we evolved structures in fact most of the higher brain is made of cortical columns each of which have a few hundred cells and I suspected those insulate the rest of the mind from the properties of the neurons so you see a physicist might want to reduce everything to to how the individual neuron works but I think what we need to do is understand how the columns work and if you go from one part of the brain to another there are hundreds of regions and the wiring is a little bit different in each of those and that's my conclusion is that there isn't any general principle of how people think but the thing that makes us so smart and I don't use the word smart I used the word resourceful people rarely get stuck because if some way of thinking doesn't work they switch to another and I think you do that by turning on little bits of brain here and there and then switching into others so the most important thing about thinking is how some part of the brain will notice that another part isn't getting anywhere what does it do it says I'll turn some of those off and I'll turn some of those on and so it's that high-level management where you're hiring new consultants and not listening to old ones maybe you did this five times a second you switch how you think how do you see the role of really modeling and simulating the human brain in understanding how it works and also then building intelligent machines well many people think that the way to understand the brain is to understand how the parts work and then how the combinations of them work and and so forth and that's been successful in physics but you can't understand a computer by knowing how the transistors work so people haven't upside-down the way to understand the brain is to understand how thinking works and once you have a theory of that then you can look at this immensely complicated brain and say well I think this area does this and that you you can't do it from the bottom up because you don't know what to look for so neural Nets are good for something statistical recognition is good for something rule-based systems are very popular they're good for a lot of industrial processes there are things called genetic programs where you make random variations in a program and select the ones that are better and that works for some problems I never see papers saying here's what my neural network didn't do no matter how long I tried it by the way in our pattern recognition projects like speech recognition we built eight different recognizes one was one was neural nets one woods Markov models which is statistics others were rule-based and then we programmed an expert manager which actually learned the strengths and weaknesses of the different systems and but brings exactly what has to be done the higher levels of the mind aren't dealing with sensory experiences or that sort of thing they're dealing with patterns of thought that you've used and editing them and deciding learning which ones to use in what conditions you said that one notice is that this method isn't working in your stock and so you change and use a different approach that's you that's doing that is that a different part of the brain than the parts that are getting stuck I mean what is this sort of master management program that manages all these other resources one of these little critics said I'm not getting said there's been no progress toward this goal and different parts of the brain have different goals and this critic says five minutes have passed and there's no progress I will turn myself off and turn on these six other ones and they'll fight it out for a while so I don't think there's any self and I like Sigmund Freud's old theory which is that the brain starts out with a lot of little instinctive things every animal every higher animal has various behaviors it does things to move it does things to avoid unpleasant sensations and so forth but as we develop as humans and maybe some primates we also develop what Freud calls ideals and aspirations and ethics and constraints so that for example if little girl wants her baby brother's toy the best thing is to grab it and then she learns from her parents that you're not supposed to do that and Freud's image of development is that there are these low level instincts that are not very different from other animals there are these high level values and constraints and phobias and so forth up here which are developed in relation in social situations and then most of the mind is resolving conflicts so there's no person in here what there are these bunch of ideals and processes and high level goals and there are all these low level processes and then most of the brain is is negotiating and arbitrary arbitrating there's a popular idea that if you build a baby machine you could call it with a simple kind of learning a machine that associates ideas or remembers sequences and correlates things that if you keep reapplying that it'll get smarter and smarter and smarter and that that's sort of popular and in the last 20 years about a dozen baby machine projects were started and all subsequent baby programs have managed to learn a couple of skills and then you keep training them but they don't get much better so my the difference in my approach is I think all of these different techniques that people have worked on have uses and we just have to organize them into a larger architecture where there is also a vast amount of common sense knowledge about how to tell when one of these processes isn't working and how to and given the symptoms of a failure which of the other processes should you turn on so basically we get resourcefulness from having many resources not from having one very smart one so eventually we'll understand enough about the brain and have ability to send little scanners inside your brain and capture all those details whatever those details happen to be that are important basically upload enough details of your mind to create an indistinguishable copy and some other machine right a wonderful future where you have backup copies and then you can do skydiving with a little less apprehension because if you get killed maybe you have a backup copy you last week I know people who have all their valuable knowledge on a computer and they haven't backed it up for six months can you imagine and people will say can you imagine people didn't backup their brains a hundred years ago but would you consider well one of those backups to be you or just somebody also happens to be a lot like you I think it's the same thing I'm not exactly like I was five minutes ago especially after talking to Ray Kurzweil for a half hour I must noticeably different person so if we scanned your brain we had a really high-resolution scan and the ability to recreate you you'd be less concerned about skydiving and if something happened to marvin minsky number one absolutely but I probably wouldn't go skydiving anyway because my time is too valuable so if everyone had backup copies would murder be less of a crime or not in the essay you wrote in my first book you asked why are so many people annoyed at the thought that human brains are nothing more than mere machines people say well but surely I under I'm a person I'm I'm a single thing I I'm an entity and a machine that just has a lot of parts wouldn't have any such central device well I think it's an illusion you you don't really see yourself what you do is you make a model of yourself some part of your brains says what am i I am a body and a mind and the other part of the brain looks at then says oh I see I'm not just a machine most people believe the body and mind isn't enough so there's got to be something else which is correct namely an architectural theory of how all this works but since they don't know any computer science or for the most part any science at all you always make a third box and you can call it the spirit or the soul or the vital force there's nothing in the box but you feel much better and this might be a healthy thing that if you discovered something new you'd have to place to put it so the feeling that you have that you can't be just a machine is sort of recognizing that just looking at the parts of something doesn't tell how it works but there's nothing profound about it I believe that if you say some mental states are emotional and some are intellectual then you're back in Aristotle's time and he was very good at this I think the distinction is a way to avoid thinking about mental states rather than a helpful way it's like people say emotions are different from thinking it's like the difference between a black-and-white sketch and a colorful drawing well I think that's nonsense emotional states usually have less structure than other ways to think a person who is in love has turned off critics he sees the other person as not having any defects being very valuable very smart very beautiful the word beautiful to me means I'm in a state where I can't see all the flaws in it and so to me emotions are less than thinking not more and the distinction is is really bad a few years ago you said that if we had the right methods we could create human level AI with a Pentium chip and there has been discussion about is there some level of processing power that's a necessary but not sufficient condition to achieve AI what what what's your view there was a study which suggested that a chess master can recognize about 20,000 patterns that was the groats thesis he was a student of Herbert Simon and if we wrote a chess program that worked in terms of these strategies then a very much smaller the computer in here in this camera might be world chess champion but what's happened is that people have worked on chess for 50 years without putting any strategic thinking into the programs and so it's very low level and it has been some progress and that actually I mean recently chess programs running on PCs with 1% of the amount of computation of deep blue have actually performed better and now routinely defeat the world chess champion because of better pattern recognition but that's very interesting would nobody really is in a position to guess how big a computer you need or a bigger faster computer you need to do the highest levels of human thought and I suspect it's rather small and that each bit of what a computer does probably needs thousands of neurons and so most of the brain is because neurons are rather unreliable and noisy and flaky we need a lot of them but they're not computing very much another angle on this which may be not that useful in building a brain but terms of the complexity of the design of the brain it's in the genome including the epigenetic information and the gentleman is replete with redundancies and I've shown that a lossless compression applied to the genome would produce about 30 to 50 million bites so that's not simple but that's a level of complexity we can manage yes it's the that's probably less than the number of bits to make a 747 overall how optimistic are you about the prospects for a I particularly at the human level as we go forward it's a very important question because I think we're going to need a eyes before long and the reason is one that that you've considered but most people haven't which is that human longevity is going to grow very rapidly in the past 60 years in the developed countries the lifespan has been increasing about one year every four so that people live 15 years longer now than they did in 1940 and I expect that this will keep going on or accelerate because nobody knows the causes for Aging but there it's one reason to be optimistic is that we live twice as long as the chimpanzees they live about 40 years we live about 80 years and it's been only four or five million years not many genes have changed so it could be that you can double the lifespan by just changing a few genes or whatever and I expect that we'll discover what those are pretty soon and so we're going to face an interesting situation where people live for say 200 years and of course they'll only have one child per person because the planet can't stand too many people so there will be a 160 old child for each hundred and 60 year old semi retiree assuming people have to retire a goal basically there'll be no one to do the work so we're going to need very smart machines to make the beds and nail the solar panels to the tops of the telephone poles and all the things that have to be done so I hope we'll start working on trying to make resourceful versatile machines much sooner but once people start working on them I can't imagine any particular obstacle for why they shouldn't get smarter and smarter of course we have to worry that the first few hundred versions will be dangerous or treacherous or filled with mysterious bugs and you have to be careful not to put them in charge of anything for a while but that's true of any machine when cars came in you had to teach people not to scare the horses with them and there's nothing to stop them from reaching human levels and surpassing human levels is oh I shouldn't think so there was nothing to stop the chimpanzees from reaching human levels and there'll be nothing to stop our machines from reaching human levels and further unless we stop them and in fact we better be very careful in the transitional stages because it's not clear whose interests they have at heart well what will the impact be of machines that are more capable than humans well when no one has to work then they'll have to find something else to do and I'm not too worried about that because I understand that you can put fifty thousand people in a football stadium for several hours watching people kick balls back and forth and so I don't think people will have any trouble with the need to not do anything but there will be a few uncomfortable people who actually want to accomplish something and my heart goes out to them well my view is we're going to merge with the machines we're gonna put them in our bodies and brains we're gonna become part non-biological and ultimately that non-biological part will dominate and so we'll become machines yes the transition may happen in various ways there's been discussion about the downsides biotechnology gone awry killer biological viruses gray goo with AI the the concern is unfriendly AI if there's something more intelligent than you and has it has it out for you that's not good news how do we deal with that no one knows how did the chimpanzees deal with it their population is down to the point where they're kept in museums and zoos and there aren't enough wild ones and there are various reasons why that's very bad so we are part chimpanzee and these future machines I think will be part human because they'll have been derived from us they'll be derived but they they might recompile themselves and say well we have all these things we inherited from the humans and they make us so slow that let's rewrite all the code and take out the old comments I don't know whether one wants to have an attitude toward that one of the problems that often come up is people say scientists should be more responsible for what they do now the fact is a scientist is no better and possibly worse than the average person at deciding what's good and what's bad and if you ask scientists has spent a lot of time discovering deciding what to invent or not all you can get from that is that they won't invent some things that might be wonderful so someone has to decide and I don't know how what the best way is but I certainly don't think that asking scientists to to tell you their ethics will help question is the singularity near and the answer is yes depending on what you mean by near but it may well be within our lifetimes

Channel: Shiva Online

Views: 186,206

Rating: 4.8740516 out of 5

Keywords: Marvin Minsky, Ray Kurzweil, Singularity, Brain, Mind

Id: RZ3ahBm3dCk

Length: 24min 2sec (1442 seconds)

Published: Mon Jul 14 2014

Reddit Comments

[u/MasterFubar]

(C)opyright 2012, so it's not that new.

Anyhow, Marvin Minsky is probably the one living scientist I admire most.

The proudest moment of my own professional career was one time in 1993, just before the "internet" came into being, when I posted a comment into an on-line forum that got a response from Marvin Minsky.

I don't remember what was the subject of the discussion or the forum involved, all I can say is that there was a time when I posted a comment online and Marvin Minsky replied to my comment. WOW!

[u/youseeitp]

No audio?

[u/localroger]

I really think the truth is somewhere between these two views. Minsky is probably right that we should be more interested in how a column in the cortex works than an individual neuron, but Kurzweil is right that there is a lot of repetition, and a lot of the "different functionality" Minsky is on about arises due to environmental factors that program the relationships between the columns.