The Artilect War

From: www.cs.usu.edu
Date: 2001
By: Prof. Dr. Hugo de Garis

Chapter 1. INTRODUCTION

My name is Professor Hugo de Garis. I'm the head of a research group which designs and builds "artificial brains", a field that I have largely pioneered. But I'm more than just a researcher and scientist - I'm also a social critic with a political and ethical conscience. I am very worried that in the second half of our new century, the consequences of the kind of work that I do may have such a negative impact upon humanity that I truly fear for the future.

You may ask, "Well, if you are so concerned about the negative impact of your work on humanity, why don't you just stop it and do something else?" The truth is, I feel that I'm constructing something that may become rather godlike in future decades (although I probably won't live to see it). The prospect of building godlike creatures fills me with a sense of religious awe that goes to the very depth of my soul and motivates me powerfully to continue, despite the possible horrible negative consequences.

I feel quite "schizophrenic" about this. On the one hand I really want to build these artificial brains and to make them as smart as they can be. I see this as a magnificent goal for humanity to pursue, and I will be discussing this at length in this book. On the other hand, I am terrified at how bleak are some of the scenarios that may ensue if brain building becomes "too successful", meaning that the artificial brains end up becoming a lot more intelligent than the biological brains we carry around in our skulls. I will be discussing this too at length in this book.

Let me be more specific. As a professional brain building researcher and former theoretical physicist, I am in a position to see more clearly than most, the potential of 21st century technologies to generate "massively intelligent" machines. By "massively intelligent" I mean the creation of artificial brains which may end up being smarter than human brains by not just a factor of two or even ten times, but by a factor of trillions of trillions of trillions of times, i.e. truly godlike. Since such gargantuan numbers may sound more science fiction like to you than any possible future science, the next chapter of this book will explain to you the basic principles of those 21st century technologies that I believe will allow humanity, if it chooses, to build these godlike machines. I will try to persuade you that it is not science fiction, and that strong reasons exist to compel humanity to believe in these astronomically large numbers. I will present these technologies in as simple and as clear a way as I can, so that you do not need to be a "rocket scientist" (as the Americans say, i.e. someone very smart) to understand them. The basic ideas can be understood by almost anyone who is prepared to give their study a little effort.

Now, once you have read the next chapter which introduces to you all these fabulous 21st century technologies that will permit the building of godlike massively intelligent machines, a host of ethical, philosophical, and political questions will probably occur to you. The prospect of humanity building these godlike machines raises vast and hugely important questions. The majority of this book is devoted to the discussion of such questions. I don't pretend to have all the answers, but I will do my best.

One of the great technological economic trends of our recent history has been that of "Moore's law", which states that the computational capacities (e.g. electronic component densities, electronic signal processing speeds, etc) of integrated circuits or "chips", have been doubling every year or two. This trend has remained valid since Gordon Moore, one of the founders of the Intel microprocessor manufacturing company, first formulated it in 1965. If you keep multiplying a number by 2 many times over, you will soon end up with a huge number. For example, 2 times 2 times 2 times 2 ... (ten times) equals 1024. If you do it 20 times you get 1048576, i.e. over a million. If you do it 30 times, you get a billion, by 40 times you get a trillion, etc. Moore's law has remained valid for the past few decades, so that the size of the doublings recently has become truly massive. I speak of "massive Moore doublings".

Moore's law is a consequence of the shrinking of the size of electronic circuits on chips, so that the distance that electrons (the elementary particles whose flow in an electronic circuit is what constitutes the electronic current) have to travel between two electronic components, for example two transistors, is reduced. According to Einstein, the fastest speed at which anything can move is that of the speed of light (about 300,000 kms/sec) and this is a constant of nature that electronic currents have to respect. If one shortens the distance between two electronic components, then an electronic signal between them (i.e. the flow of electrons between them) has less distance to travel, and hence takes less time to traverse that distance (at the constant speed of light).

A huge amount of effort over the past few decades has been devoted by the chip manufacturing companies into making electronic circuits smaller, and hence denser, so that they function faster. The faster a microprocessor chip functions, the more economically attractive it is. If you are the CEO of a chip manufacturing company and your competitor down the road in California's "Silicon Valley" brings a rival chip onto the market that is 30% faster than yours and 6 months ahead of you, then your company will probably go out of business. The market share of the rival company will increase significantly, because everyone wants a faster computer. Hence for decades, electronic circuitry has become smaller and hence faster.

For how much longer can Moore's law remain valid? If it does so until 2020, then the size of the electronic components in mass memory chips for example, will be such that it will be possible to store a single bit of information (a "bit" is a "binary digit", a 0 or a 1, that computers use to represent numbers and symbols to perform their calculations) on a single atom. So how many atoms (and hence how many stored bits) are there in a human sized object, such as an apple? The answer is astonishing - a trillion trillion atoms (bits), i.e. a 1 followed by 24 zeros, or a million million million million.

Are you beginning to get an inkling for why I believe that massively intelligent machines could become trillions of trillions of times smarter than we are later this century?

Not only is it likely that 21st century technology will be storing a bit of information on a single atom, it will be using a new kind of computing called "quantum computing", which is radically different from the garden variety or "classical computing" that humanity used in the 20th century. The following chapter will attempt to give a brief outline of the principles of quantum computing since it is likely that that technology will form the basis of the computers of the near and longer term future.

The essential feature of quantum computing can however be mentioned here. It is as follows. If one uses a string of N bits (called a "register" in computer science, e.g. 001011101111010) in some form of computing operation (it doesn't matter for the moment what the operation is) it will take a certain amount of time using "classical computing". However in the same amount of time, using "quantum computing" techniques, one can often perform 2N such operations. (2N means 2 multiplied by 2 multiplied by 2 ... (N times)). As N becomes large, 2N becomes astronomically large. The potential of quantum computing is thus hugely superior to classical computing. Since Moore's law is likely to take us to the atomic scale where the laws of physics called "quantum mechanics" need to be applied, humanity will be forced to compute quantum mechanically, hence the enormous theoretical and experimental effort in the past few years to understand and build "quantum computers".

Quantum computing still has many conceptual and practical problems which need to be solved before quantum computers are sold to the public. But progress is being made every month, so personally I believe that it is only a question of time before we have functional quantum computers.

Now, start putting one bit per atom memory storage capacities together with quantum computing and the combination is truly explosive. 21st century computers could have potential computing capacities truly trillions of trillions of trillions ... of times above those of current classical computing capacities.

I hope you have followed me so far.

At this point in the argument, you may be racing ahead of me a little and object that I seem to be assuming implicitly that massive memory capacities and astronomical computational capacities are sufficient to generate massively intelligent machines, and that nothing else is needed. I have been accused by some of my colleagues of this, so let me state my personal opinion on this question.

There are people (for example, Sir Roger Penrose, of black hole theory fame, and arch rival of the wheel-chaired British cosmologist Stephen Hawking) who claim that there is more to producing an intelligent conscious machine than just massive computational abilities. I am open to this objection. Perhaps such critics are right. If so, then their objections do not change my basic thesis much, since I feel that it is only a question of time before science understands how nature builds us, i.e. before science understands the "embryogenic" process, used in building an embryo and then a baby, consisting of trillions of cells, from a single fertilized egg cell.

We have the existence proof of ourselves, who are both intelligent and conscious, that it is possible for nature to assemble molecules in an appropriate way to build us. When a pregnant woman eats, some of the molecules in her food are rearranged, and then self assemble into a large molecular structure consisting of trillions of trillions of atoms which becomes her baby. The baby is a self assembled collection of molecules that gets built to become a functional three dimensional creature that is intelligent and conscious.

Nature, i.e. evolution, has found a way to do this, therefore it can be done. If science wants to build an intelligent conscious machine, then one obvious strategy is to copy nature's approach as closely as possible. Sooner or later, science will end up with an artificial life form that functions in the same way as a human being.

Common sense says that it would be easier to build an artificial brain if science had a far better knowledge of how our own biological brains work. Unfortunately, contemporary neuroscience's understanding of how our brains work is still painfully inadequate. Despite huge efforts of neuroscientists over the past century or more to understand the basic principles of the functioning of the human brain, very little is known at the micro-neural circuit level as to just how a highly interconnected neural circuit does what it does. Science just does not yet have the tools to adequately explore such structures.

However, as technology becomes capable of building smaller and smaller devices (moving down from the micro-meter level to the nano-meter level (i.e. from a millionth of a meter (the size of bacteria) to a billionth of a meter (the size of molecules)) it will become possible to build molecular scale robots that can be used to explore how the brain functions.

Science's knowledge of how the biological brain works is inadequate because the tools we have at our disposal today are inadequate, but with molecular scale tools (called "nanotech" or "nanotechnology") neuroscientists will have a powerful new set of techniques with which to explore the brain. Progress in our understanding of how the brain functions should then be rapid.

Brain builders like me will then jump on such newly established neuro-scientific principles and incorporate them rapidly into our artificial brain architectures.

Hopefully in time, so much will become known about how our own brains function, that a kind of "intelligence theory" will arise, which will be able to explain on the basis of neuronal circuitry (a neuron is a brain cell) why Einstein's brain for example, was so much smarter than most other people's brains. Once such an intelligence theory exists, it may be possible for neuro-engineers like myself to take a more engineering approach to brain building. We will not have to remain such "slaves to neuroscience". We will be able to take an alternative route to producing intelligent machines (although admittedly initially based on neuro-scientific principles).

So with the new neuro-scientific knowledge that nanotech tools will provide, and the computational miracles that quantum computing and one bit per atom storage allow, brain builders like me will probably have all the ingredients we need to start building truly intelligent and conscious machines.

At this point, a host of questions start arising, and I will spend most of this book trying to answer a lot of them. Lets jump into the future for a moment and try to imagine how the above technological developments will impact on ordinary peoples lives.

Pretty soon, it will be possible to buy artificially brained robots that perform useful tasks around the house. If the price of such robots can be made affordable, then the demand for them will be huge. I believe in time that the world economy will be based upon brain based computers. Such devices will be so useful and so popular that everyone on the planet will want to own them. As the technologies and the economics improve, the global market for such devices will only increase to the point that most of the planet's politics will be tied up in supporting it. Not only will the commercial sector be heavily involved in the production of ever smarter and ever more useful robots and artificial brain based devices, but so too of course will the military forces of the world.

It is unlikely in the next few decades that the planet will have formed a truly global state, with a global police force to defend its global laws. I feel there will be a growing political rivalry over the next half century between the United States and China to be the world's most powerful nation. This rivalry will ensure that the ministers of defense of both countries cannot afford to allow the other country to develop more intelligent soldier robots and other artificial brain based defense than their own. Hence national governments will be heavily involved in pushing the development of military based artificial brain research, that will only spill over in time to the commercial sector, as has been the pattern for over a century.

Thus the rise of artificial brain based robotics and related fields, seems unstoppable. There will be so much military and commercial momentum behind it that it is difficult to imagine how it could be stopped, unless some mass political movement is formed to block its development.

How might such a movement get off the ground? It's not too difficult to imagine what might happen. Imagine in about a decade from now that millions of people have already bought household cleaning robots, sex robots, teaching machines, babysitter robots, companionship robots, friendship robots, etc, and that these brain based machines talk quite well and understand human speech to a reasonable extent. A few years later what happens? Not surprisingly, the models of that earlier year are now seen by their owners to be rather old fashioned and not as attractive as the latest models. The latest models will be more "intelligent" because their speech is of higher quality. They will understand more and give better, more appropriate answers. Their behavioral repertoire will be richer. In short, they will make the earlier models look quite inferior.

So what does everyone do? Of course, they will scrap their old robots and buy new ones, or have their old ones updated with better artificial neural circuitry. In a further few years, the same process will repeat itself, in a fashion similar to the way buyers of personal computers behaved in the 1980s and 1990s.

However, some of the more reflective buyers may start noticing that their household machines and robots are becoming smarter and smarter every machine generation, so that the IQ gap between human beings and robots keeps getting smaller. Once the robots start getting really quite smart, suddenly millions of robot owners will start asking themselves some awkward questions -

"Just how smart could these artificially brained robots become?"

"Could they become as smart as human beings?"

"If that's possible, is that a good thing?"

"Might not the robots then be smart enough to be a threat to humanity?"

"Could the robots become smarter than humans?"

"If so, how much smarter?"

"Should humanity allow these robots to become smarter than human beings?"

"If they become a lot smarter than human beings, might they decide that humans are a pest, a cancer on the surface of the planet, and decide to wipe us out?"

"Should humanity take the risk, that that might happen?"

"Should a limit be placed on the robot's AIQ (Artificial Intelligence Quotient), so that the robots are smart enough to be useful to human beings, but not too smart so as to be threatening?"

"Will it be possible to stop the rise of robot AIQ?"

"Will it be politically, militarily, economically possible to stop the robots becoming smarter every year?"

"There are lots of people who see the creation of massively intelligent machines as the destiny of the human species. These people will not like any limits being placed on AIQ levels. Won't this create conflict amongst human beings?"

You may be able to think of other such questions relating to the rise of artificial intelligence and the creation of artificial brains with ever-greater capabilities.

How do I see humanity facing up to the challenge of the rise of smart machines? My personal scenario that I find the most plausible I will now present to you. However, before doing so, I would like to introduce a new term that I will use from now on throughout this book, as it is a useful shorthand for the term "godlike massively intelligent machine". The new term is "artilect", which is a shortened version of "artificial intellect". The term "artilect" features in the very title of this book "The Artilect War", so it is probably the most important concept and term in this book.

I believe that the 21st century will be dominated by the question as to whether humanity should or should not build artilects, i.e. machines of godlike intelligence, trillions of trillions of times above the human level. I see humanity splitting into two major political groups, which in time will become increasingly bitterly opposed, as the artilect issue becomes more real and less science fiction like.

The human group in favor of building artilects, I label the "Cosmists", based on the word "cosmos" (the universe), which reflects their perspective on the question. To the Cosmists, building artilects will be like a religion; the destiny of the human species; something truly magnificent and worthy of worship; something to dedicate one's life and energy to help achieve. To the Cosmists, not building the artilects, not creating the next higher form of evolution, thus freezing the state of evolution at the puny human level, would be a "cosmic tragedy". The Cosmists will be bitterly opposed to any attempt to stop the rise of the 21st century artilect.

The second human group, opposed to the building of artilects, I label the "Terrans", based on the word "terra" (the earth) which reflects their inward looking, non cosmic, perspective. The Terrans, I strongly suspect, will argue that allowing the Cosmists to build their artilects (in a highly advanced form) implies accepting the risk, that one day, the artilects might decide, for whatever reason, that the human species is a pest. Since the artilects would be so vastly superior to human beings in intelligence, it would be easy for the artilects to exterminate the human species if they so decided.

But you may argue that if the artilects truly become very smart, they would realize that human beings gave birth to them, that we are their parents. Therefore the artilects would respect us and treat us well. This may be what happens, but the point is, I argue, is that you could not be certain that the artilects would treat humanity with the level of respect that we would like.

Don't forget, the artilects have the potential of becoming trillions of trillions ... of times smarter than we are, so there is always the possibility that they could become so smart that human beings would appear to them to be so inferior that we would simply not be worth worrying about. Whether humanity survives or not, might be a matter of supreme indifference to them.

It is not exaggerating to say that there is quite a close analogy between an artilect trying to communicate with a human being, and a human being trying to communicate with a rock.

To make another analogy, consider your feelings towards a mosquito as it lands on the skin of your forearm. When you swat it, do you stop to consider that the creature you just killed is a miracle of nano-technological engineering, that scientists of the 20th century had absolutely no way of building. The mosquito consists of billions of cells, each of which can be looked upon as a kind of molecular city, where a molecule in a cell is equivalent to a person in a city. The comparative scale of molecule to cell is about the same as person to city.

Despite the fact that the mosquitoes, which took billions of years to evolve, are extremely complex and miraculous creatures, we human beings don't give a damn about them, and swat them because from our perspective they are a pest. We have similar attitudes towards killing ants when we walk on them during a stroll through the forest, or when flushing spiders down the plug hole.

Who is to say that the artilects might not have similar attitudes towards human beings, and then wipe us out. With their gargantuan "artilectual" intelligence, it would be as easy as pie for them to do so.

The critical word in the artilect debate to the Terrans is "risk". The Terrans will argue that humanity should never take the risk that the artilects, in an advanced form, might decide to wipe out the human species. The only certain way that the risk remains zero, is that the artilects are never built in the first place.

When push comes to shove, if the Terrans see the Cosmists are truly serious about building artilects in an advanced state, then to preserve the survival of the human species, the Terrans will exterminate the Cosmists. Killing a few hundred or a few million Cosmists will be considered justifiable by the Terrans for the sake of preserving the survival of the whole human species, i.e. billions of people.

Such a sacrifice would be deemed reasonable by the Terrans. To make a historical analogy - when Stalin's troops were pushing west at the end of WW2, to capture Berlin and destroy Hitler's Nazi regime that murdered 20 million Russians, they were losing about 100,000 Russian soldiers killed or injured for every major east European city captured from the Nazis. To Stalin, such a sacrifice was considered justifiable for the greater good of ridding the Russian people of the horror of mass murdering Nazism.

You may now ask - "Would anyone in their right mind genuinely choose, when push comes to shove, to be a Cosmist, and truly risk the annihilation of the human species?"

I think that in the future, millions of people will answer yes to this most fundamental of questions. I think that as more people become fully conscious of what the artilects could become, many of these people will end up choosing in favor of their creation. This book will devote a whole chapter to arguments in favor of building artilects when it presents the Cosmist case.

These people, these "Cosmists", will place a higher priority on the creation of godlike, immortal, go anywhere, do anything creatures (where one artilect is "worth" a trillion trillion human beings) than denying the risk of the extermination of the human species at the hands of the artilects.

Let me spell this out, so that there is no doubt about the stance of the Cosmists. A Cosmist, by definition, is someone in favor of building artilects. The artilects, if they are built, may later find humans so inferior and such a pest, that they may decide, for whatever reason, to wipe us out.

Therefore the Cosmist is prepared to accept the risk that the human species is wiped out. If humanity is wiped out, that means your grandchildren will be wiped out, my grandchildren will be wiped out. It would be the worst calamity in human history, because there would be no more history, because there would be no more humans. Humanity would thus join the long list of over 99% of species that have ever existed on the earth, which have already become extinct.

Thus to the Terrans, the Cosmists are monsters incarnate, far worse than the regimes of Hitler, Stalin, Mao, the Japs, or any other regime that murdered tens of millions of people in the 20th century, because the scale of the monstrosity would be far larger. This time we are not talking about deca-mega mass murder, we are talking about the potential annihilation of the whole human species, billions of people.

But to the Cosmists, the survival or not of the human species, on an insignificant planet, circling a star that is one of about 200 billion in our galaxy, in a known universe of a comparable number of galaxies (also in the billions), and with probably as many universes in the "multiverse" (according to several recent cosmological theories) is a matter of miniscule importance. I have labeled the Cosmists Cosmists for a reason. Their perspective is cosmic. They will look at the "big picture" - meaning that the annihilation of one ultra-primitive, biological, non-artilectual species (i.e. human beings) on one insignificant little planet, is unimportant in comparison with the creation of artilect gods.

There will be two chapters later in the book presenting the Terran and the Cosmist cases, one for each viewpoint. There are very powerful arguments on both sides, which I believe will only make the inevitable conflict between Terranism and Cosmism all the more bitter as the artilect debate heats up in the coming decades.

What makes me particularly gloomy about the potential bitterness of this coming conflict is how evenly people's opinions are split along the Terran/Cosmist divide. For example, I often invite audiences to whom I present the Cosmist/Terran/Artilect scenario in public lectures, to vote on whether they would be Terran or Cosmist. I find that the voting is not what I first expected it would be (namely about 10% Cosmist, 90% Terran) but rather 50/50, 60/40, 40/60. This issue truly divides people.

What makes me even gloomier is that the artilect issue (i.e. should artilects be built or not) will heat up in the 21st century to such an extent, that it is almost certain it will lead to a major war between the Terrans and the Cosmists in the second half of this new century. This conflict will take place with 21st century weaponry. If one extrapolates up the graph of the number of major deaths in major wars from the beginning of the 19th century (e.g. the napoleonic wars) to the end of the 21st century, one arrives at the depressing figure of billions, what I call "gigadeath".

But the population of the earth is only several billion people, so we arrive at the tragic conclusion that to avoid the risk of the total annihilation of the human species by the artilects, humanity goes to war against itself and kills itself off (or almost).

This "Artilect War" as I call it, will be the most passionate in history, because the stake has never been so high, namely the survival of the whole human race. It will be waged with 21st century weapons and hence the casualty figures will be of 21st century grandeur.

The sad thing about this gloomy scenario is that despite considerable effort on my part, I have been unable to find a way out of this mess. I lie awake in bed trying to find a realistic scenario that could avoid "gigadeath". I have not succeeded, which makes me feel most pessimistic. In fact I am so pessimistic that I am glad to be alive today. At least I will die peacefully in my bed. However I fear for my grandchildren. They will see the horror of it and very probably they will be destroyed by it.

I will die within about 30-40 years, given my age, but that is not enough time I believe, for the artilect scenario to unfold. I believe it will take longer than that to obtain the necessary knowledge to build massively intelligent artificial brains or artilects. However, what I will see in my lifetime, and obviously this book is aimed at producing just that, is a vociferous debate over the artilect issue.

There are a growing number of researchers and professors like myself who are starting to see the writing on the wall, and who are claiming publicly in media appearances and books that the 21st century will see the rise of massive artificial intelligence. I am the only one so far who is saying that this rise of massive AI will probably lead to a major war, the "artilect war".

Thus the issue is really starting to hit the world media, and countries such as the US, the UK and France are leading the pack. In fact I believe that within only a few years, the issue will have passed from one that is confined largely to academic audiences, to a wider general public, with representatives from such fields as politics, religion, defense etc, with each field contributing its views from its own perspective.

The "artilect debate" will seem like science fiction, and set too far into the future, for most people to worry about, but as the machines start getting smarter and smarter every year, it will take on an intensity that will become truly frightening.

So what is my position on all this? Why am I writing this book?

Deep down, I'm a Cosmist. I think it would be a cosmic tragedy if humanity chooses never to build artilects. To illustrate my views on why I'm a Cosmist in my heart, I like to tell a little story.

Imagine you are an ET (an extra terrestrial) with godlike technological powers and you come to the earth 3 billion years ago. You observe the life forms at that time on earth and notice that they are still at the primitive bacterial single-celled stage. In a sweep of your magical technological wand, you fiddle all the DNA in all the bacteria of the planet so that (for the sake of the argument) it will never be possible in the future for these bacteria to evolve into multi-celled creatures. Hence, there will never be any plants, no animals, no human beings, no Einstein, no Beethoven's 9th. Is that a tragedy? Once multi-celled creatures did evolve on the earth, zillions of bacteria were eaten by them. The evolutionary rise of multi-celled creatures on the earth was no picnic for the bacteria.

I hope you see the analogy. If we build artilects and billions of human beings are wiped out as a result, what will be the equivalent of Beethoven's 9th that the artilects will produce with their godlike intellects? As human beings, we are too dumb to know. We are just too inferior to be capable of recognizing such things. It would be like asking a mouse to study Einstein's General Theory of Relativity. It just couldn't do it, because it doesn't have the necessary neural circuitry to allow it, nor do most humans, for that matter.

But, you may ask, if I'm a Cosmist at heart, why am I writing this book? The answer is that I'm not 100% Cosmist. If I were, I would be quietly getting on with my brain building work and not trying to raise the alarm on the artilect issue to the general public. Part of me is also Terran. On my death bed I would be proud to be considered the "father of the artificial brain", but if history condemns me as being the "father of gigadeath", then that prospect truly horrifies me. My second wife's mother was gassed by the Nazis at Auschwitz. I know to some extent what genocide means at an emotional level, and have had to live with its consequences for years.

I'm writing this book to raise the alarm, because I think humanity should be given the choice to stop the Cosmists before they get too advanced in their work, if that is what most human beings choose. So should I stop my brain building work now? No. I don't think so. I believe that producing near human-level artificial intelligence is a very difficult problem that will take decades to solve. Over the next 30 to 40 years, it is likely that the AIQ of robots will become high enough to be very useful to humanity. They will perform so many of the boring, dirty and dangerous tasks. Humanity will be liberated from such work, and hence have more time to pursue more rewarding tasks. The robots can do most of the work allowing human beings to do more fun things.

It would be premature to stop the research on artificial brains now. However, once these artificial brains really do start becoming smart and threaten to become a lot smarter and perhaps very quickly (a scenario called "the singularity") then humanity should be ready to take a decision on whether to proceed or not. Making an informed decision on an issue that concerns the survival of the whole species is something so important that the necessary discussion on the artilect issue should begin earlier. There should be enough time for all the issue's intricacies to be thrashed out before the artilect age is imminent.

So publicly I'm Terran. I'm trying to raise the alarm. Privately I'm Cosmist. Hence I feel quite schizophrenic, as I mentioned in the very first page of this book. I feel so torn on the issue, so ambivalent. I believe that similar feelings will be felt by billions of people in the future as the artilect debate really takes hold. From the Terran viewpoint, to be a Cosmist is to be a "speciecidal monster" (a species killer). A Cosmist accepts the risk of seeing the human species wiped out by the artilects. This is inherent in the nature of the situation. The decision whether to build artilects has a binary answer - we can build them or not. The decision to build them is the decision to accept the risk that they will wipe us out.

On the other hand, not to build them is the decision not to build gods, a kind of "deicide" (god killing). From the Cosmist viewpoint, Terrans are "deicidal monsters".

In passing, I should mention that there are some people who feel that the whole Cosmist/Terran conflict can be avoided by having human beings themselves become artilects by adding components to their heads etc to become "cyborgs" (cybernetic organisms, i.e. part human, part machine). Personally I find such arguments na�ve, since they would only work if the whole of humanity made the transition from human to artilect at the same rate, which obviously is not going to happen.

There is more potential computing capacity in a grain of sugar than there is in the human brain by a factor of trillions. Incorporating such a grain into the human brain would simply make the human cyborg an "artilect in human disguise" as seen from the perspective of a Terran. The Terrans would hate the cyborgs with as much venom as they would the artilects and would be motivated to destroy both. Having a human exterior would not make the cyborgs any less threatening to the Terrans.

Let me try to express this Terran revulsion against the cyborgs in an even more graphic way that may have a stronger appeal to women than to men. Take the case of a young mother who has just given birth. She decides to convert her baby into a cyborg, by adding the "grain of sugar" to her baby's brain, thus transforming her baby into a human faced artilect. Her "baby" will now spend only about a trillionth of its mental capacity thinking human thoughts, and the rest of its brain capacity (i.e. 99.9999999999% of it) will be used for thinking artilect thoughts (whatever they are). In effect, the mother has "killed" her baby because it is no longer human. It is an "artilect in human disguise" and totally alien to her.

Thus to me, the cyborg option will not avoid the Cosmist/Terran conflict. If anything, it will probably only worsen it, because it will increase the level of paranoia of the Terrans when they cannot distinguish easily a cyborg from a human at a distance.

For about 10 years I sat on the fence, presenting my ideas in a "on the one hand, on the other hand" kind of way, presenting the two cases, one in favor of the Terrans, and the other in favor of the Cosmists. After some years, my friends began to accuse me of being a hypocrite. "Hugo, you expect humanity to choose between being Terran or Cosmist, but you don't do the same yourself". "Fair enough", I thought, so I chose. In my heart I'm a Cosmist, and I'll try to present the many arguments and feelings in favor of building artilects in the chapter on the Cosmist viewpoint. This chapter tries to justify why I and other Cosmists feel so passionately about building artilects, that we are prepared to run the terrible risk of the extermination of the human species.

In the chapter on the Terran viewpoint, I will present the case why the Terrans feel that building artilects would be a total disaster.

Later on in this book, I will try to paint a picture as to how I see the conflict brewing and what the possible outcome might be.

This introductory chapter has given you an overview of what the "artilect war" is about. The later chapters will provide greater detail on the ideas sketched out so far.

I hope this book will make you think. It is written to help make you conscious of an issue that I believe will dominate the global politics of the 21st century, that will color and define the age, namely, the question of "species dominance", "Should humanity build artilects or not?" This question I believe will divide humanity more bitterly in the 21st century than the question which divided humanity so bitterly in the 20th, namely, "Who should own capital?" The bitterly opposed answers to that question led to the Capitalist/Communist dichotomy. The question which will dominate 21st century global politics will be "Who or what should be dominant species, artilects or human beings?"

I end this chapter with a little slogan that expresses rather pithily, the essence of the artilect debate.

"Do we build gods, or do we build our potential exterminators?"

Chapter 2 Who is this de Garis?

Who is this de Garis, who makes such outrageous claims - that machines will become trillions of trillions of trillions of times smarter than human beings by the end of the century - that there will be a major war over the issue of species dominance, and that as a result billions of human beings will die? Is he a mad man? Is he a science fiction writer? Does he deserve to be listened to, or can humanity afford simply to ignore him?

This chapter is about who I am. It is partly autobiographical, partly a description of my work, and attempts generally to paint a portrait of me the person, so that readers may be in a better position to judge the credibility of my ideas by knowing something about the person who wrote them.

This chapter will be divided into 3 main sections. The first gives a brief autobiography, the second is a longer description of my current work and the third is a presentation of my future work goals and dreams.

2.1 Autobiography
I was born in Sydney, Australia in 1947, making me a middle aged man at the time of writing. I've been divorced, widowered and will probably marry a third time in the near future. I have two children by the first wife. By temperament I am a passionate intellectual, with over 6000 books in my private library. I am scientist, a research professor, a social activist, a writer, and a social critic.

As an adolescent, growing up in Australia, I felt that my passionate intellectual values were not valued by Australia's phlegmatic anti-intellectual brawn-based culture. During the time of the Sydney Olympic games, a BBC journalist said of Australians that they would rather win a gold medal than a Nobel prize. By the time I was 23 and had finished my basic undergraduate degrees, in applied mathematics and theoretical physics, I wanted to leave the country for ever. I had been conscripted to fight in the Vietnam war, which simply made me hate my own government. "How dare they force me to risk my life to defend their ideology!" I found an antiwar psychiatrist who spoke with me for all of 2 minutes and wrote out a recommendation to the conscription medical board that I had a "severe personality disorder". I failed the medical and soon after took a boat for England.

The first day in London I felt overwhelmed by the feeling that I had set foot in an unquestionably superior culture. That night on BBC TV watching a debate, I was struck at its intellectual quality. I felt a great weight lift off my shoulders. I had found my home, a culture that valued my values.

A few years later, I was browsing a world atlas that I had bought for my first wife, an Australian whom I had met on the 5-week boat trip from Australia to England. The idea occurred to me that I could live in a cosmopolitan city like Brussels and hence benefit from the intellectual stimulus of several superior cultures. All I would need to do would be to learn a few languages and then move there. That's what I did. I got fluent in French, German and Dutch and absorbed those cultures into my personality. I loved it. My wife however, did not. After 5 years living in England where she was fairly happy - her mother was English - and a further 6 in Belgium, she longed to get back to her native Australia. This conflict of interests broke us up. She has since remarried and lives in Australia. After the breakup I lived in Brussels and married a French speaking Belgian woman, my second wife.

I got bored doing computer work for industry and decided at age 40 to return to university and get a Ph.D. in artificial intelligence (AI) and become a researcher. This I did at the University of Brussels (ULB). Early in 1992, I and my second wife left Europe to live in Japan. I had gotten a postdoc fellowship to do AI in Tsukuba in Japan. I and millions of others believed at the time that by the year 2000, Japan would be the world's dominant economic power, overtaking the US. It was not to happen. I spent 8 years in Japan, working towards building the world's first artificial brain.

I hated Japan. It was too feudal, too fascist, too repressive of individualism, too intellectually sterile, too socially backward for me to tolerate it for very long. I stayed as long as I did because at least Japan was paying for the construction of a remarkable new type of computer that I will talk more about in the next section.

I got a new job doing the same kind of work at a research lab in Brussels. I returned alone, because my second wife had recently died of lung cancer. Yes, the idiot smoked heavily in her younger years. Young women take note! During my stay in Japan I became increasingly friendly with a Japanese woman who may become my third wife. We Iphone (internet phone) each other every day, while she pays off her bank debt in Japan. Then we will live together to see how compatible we are. If we pass this "time test", we will marry.

I'm not just a research scientist. I'm also a social critic. I get very upset if I feel an injustice is being committed against me and fight hard against it. I am a "masculist", i.e. a men's libber, fighting for the liberation of men, largely from the traditional financial parasitism of women who expect to live off the money of their husbands. I find this a form of slavery. I have contempt for such women, whom I labeled "fluffies". I coined a whole vernacular of masculist terms, packaged the ideas and presented them to the European media. After a decade of feminism of the 70s, the media were very happy to hear from the men in the 80s. I was quite successful, and got on the media over 150 times in half a dozen countries.

I mention this masculist period of mine, because I think it gives some insight to what I am doing now with a new ideology that I call cosmism. The masculist period gave me the training and the knowledge that I was capable of pushing a new ideology to the media. I found in practice that I could do it quite well.

As an example of some of the masculist terms I coined, take the word "masculist" itself. It is the obvious equivalent of the word feminist. I spoke of FIPs, i.e. financially independent persons, i.e. women who had careers and pulled their financial weight more or less equally with men and took it for granted that they had a moral obligation to share the burden with the men of their lives in earning the family living. Traditional men who accepted unquestioningly the traditional male role of paying for fluffies, I labeled "robots". I hit the media warning young fluffies, that if they wanted to get a man, they would have to get a career. I tried to persuade robots that they would be better off with a FIP. FIPs are cheaper to divorce. They share the financial burden. They free up men from their traditional financial cages, and are generally more fun and sexier to be with than boring fluffie housewives. I argued that if large numbers of robots switched to relationships with FIPs, the fluffies would rot on the shelf and would be forced to convert themselves into FIPs. A fluffie can only survive if some robot is prepared to be parasited upon. The media lapped it up.

2.2 My Work
In this section I will describe at some length the work that I have done over the years, with emphasis on what I have been doing during the past decade, since it is most relevant to the theme of this book.

After arriving in the UK, and spending a year in London, with its awful air pollution in the early 1970s, I had constant catarrh and decided to move to beautiful and academic Cambridge. I became a free lance mathematics tutor to the undergraduates of some half dozen Cambridge University colleges. The students would come in pairs to my apartment and be helped with the problems they were having with the math questions given to them by their lecturers.

I loved Cambridge, its green, its beauty, and especially its intellectuality. My first wife finished her philosophy degree at a London college and wanted to get pregnant. I wanted to move to Brussels. I got a job in a large Dutch electronics/computer firm and then moved later to Brussels, working in the computer field, but became increasingly frustrated and bored. I missed the intellectual life of Cambridge and its academic lifestyle. After I split up with my first wife, and worked for a few years again with computers in industry, I began a PhD in artificial intelligence and artificial life at the University of Brussels.

I began to evolve neural networks using a form of software simulated Darwinism, called Genetic Algorithms (GAs). I started this work in about 1989 and began publishing a steady stream of scientific research articles. I had 20 published by the time I had finished my Ph.D.

A neural network can be envisaged as a 3D array of brain cells - neurons - interconnected by branch like fibers called axons and dendrites. In an axon, a signal originating from a neuron travels away from it. In a dendrite, the signal is sent to the neuron. When an axon connects with a dendrite or another neuron, the junction is called a synapse.

In a real biological brain, each neuron or brain cell can have tens of thousands of synapses, that is it can be influenced by signals arriving from tens of thousands of other neurons. Those neural signals arriving at the neuron at the same time get reinforced or "weighted" and then summed. If the total signal strength is above the threshold firing value of the neuron, then it will fire, i.e. it will send pulses of electricity down its axon at a frequency proportional to how much greater the summed value is above its threshold value. The axon pulses then travel down to their synapses to influence further neurons.

This kind of biological neural network can be simulated in software. Typically the number of neurons simulated in a single network in the 80s and 90s was tens to hundreds. For my Ph.D. work, I was using at most 16 neurons per network. This contrasts so sharply to my present work, which deals with nearly 100 million artificial neurons.

A genetic algorithm (GA) uses a software simulated form of Darwinian evolution to optimize the performance of whatever is being evolved. For example, take my application of GAs to the evolution of neural networks. I simulated the behavior of a neural net in the following way. The first problem was how to represent the neural net itself. I took 16 neurons and had them all connect to themselves and all other neurons, so that there was a total of 16*16 = 256 connections. The incoming signal strengths, represented by ordinary decimal pointed numbers, e.g. 10.47, were multiplied by a weighting factor, e.g. 0.537, and then summed. As an illustration of this idea, imagine a very simple network of only 2 neurons, hence 4 connections. Neuron 1 sends a signal to itself at connection or synapse C11 and to neuron 2, at connection or synapse C12. Neuron 2 sends a signal to itself at connection or synapse C22 and to neuron 1 at connection or synapse C21. Assume that the signal strengths at a given moment are S1 and S (e.g. 10.54 and 7.48).

Each connection Cij or synapse possesses a corresponding weighting factor wij which is used to multiply the signal strength of the signal coming through the synapse. So the sum of the signal strengths arriving at neuron 2 would be (w12*S1 + w22*S2). Similarly for neuron 1. There will be 4 of these weights. Assume that the value of each weight lies between -1 and +1. Thus each weight can be represented as a fractional binary number with say 8 bits (binary digits, 0s or 1s). 4 such numbers can be represented by 4*8 = 32 bits which can be laid out in a row of length 32 bits. With 16 neurons, I had a row or bitstring as it is called, of 16*16*8 = 2048 bits to represent the 16*16 weights of my neural network that I was evolving.

If I knew the 2048 bit values (0s or 1s) I could calculate all the 256 weight values, and hence construct a fully interconnected neural net from them. The reverse process was also possible. If one knew the values of all the weights, and the values of the initial incoming signals from outside the net, one could calculate the signal strength of each neuron as it fired. If one knew how each neuron fired, one knew how the whole neural network fired, or behaved. One could extract the signals from some of the neurons and use them as control signals to control some process, e.g. the angles of legs of a robot to make it walk.

To explain how to use a GA in this application, imagine generating 100 random bitstrings of length 2048 bits each. From each bitstring one can construct its corresponding neural net. To each net one applies the same initiating input signals to kick-start the signaling of the network. One extracts the output signals and uses them, for example, to make some stick legs walk by controlling the angles of the 4 lines that make up the stick legs. One then measures how far the legs walk in a given time.

Those bitstrings that generate neural nets that generate longer distance walking survive into the next generation. Those that generate shorter distance walking are killed off, Darwinian style, "survival of the fittest". The fitter bitstrings, i.e. those with higher performance scores or "fitnesses", have copies made of them, called their "children" or offspring. The children and their parents are then "mutated", meaning that at low probability, each bit may be flipped (a 0 to a 1, or a 1 to a 0) and/or crossed over. There are various ways to cross over, but one simple form is to take two parent bitstrings or "chromosomes" as they are usually called, cut them both at the same position, and then swap components. This is the equivalent of sex, which is basically only mixing of genes from two parents to form the offspring.

The fitter parents have more offspring. Each generation of the GA has a fixed population size, e.g. 100. Most mutations and crossovers cause the chromosomes to have lower fitnesses, so they get weeded out of the population. Occasionally, a mutation or crossover actually improves the fitness of a chromosome by a small amount, so that in time it squeezes its parents and other inferior chromosomes out of the population. By looping through this cycle hundreds of times, it is possible to evolve a neural network or whatever one is trying to evolve, that performs quite well.

For my Ph.D. at the University of Brussels I was evolving neural networks that gave time dependent output signals. As far as I know that was the first time that anyone had done such a thing. Previously, a few people had applied GAs to neural network evolution, but the applications were static, i.e. the signals being extracted did not change with time. This struck me as being unnecessarily restrictive. The GA should be able to handle time dependent outputs. Once I had this insight, I started to evolve a neural net that made some stick legs walk. It worked. It required a few tricks to get it to evolve, but it did work.

That initial discovery, that it was possible to evolve neural network dynamics (as distinct from statics) opened up a whole new world for me, and created a new research branch called "evolutionary neural systems". I began to wonder what I would do next. The thought occurred to me that if I could evolve one behavior with one neural net, I could evolve a different behavior with a second neural net, i.e. one with a different set of weights. The weight set determines the dynamics of the output signals.

I became more ambitious. Instead of playing with simple sticklegs confined to a 2D plane, I would evolve behaviors for a 3D simulated quadruped creature that I called "Lizzy". If I could evolve one behavior successfully, then I could evolve a whole library of behaviors, with one neural net per behavior. I could probably then switch behaviors by having Lizzy at first walk and then turn. To achieve a smooth behavioral transition, all that was necessary was to switch off the inputs to the "walk straight" behavior generating network (or module as I started calling them), and input the outputs of the walk module to the turn module. Simulation experiments showed that the motion transition was smooth. Great. I now knew I could get a quadruped creature like Lizzy to display a whole library of behaviors.

The question arose as to when one would want to switch behaviors. Perhaps such decisions might arise from stimuli from the environment. I started to see if I could evolve detector modules, e.g. signal strength detectors, frequency detectors, signal strength difference detectors, etc. Yes, it was possible. The next logical step was to attempt to evolve decision type modules, e.g. of the type - "if the strength of the 1st input signal is greater than S1, and the strength of the 2nd input signal is less than S2, then switch on action An", i.e. a stimulus signal would be sent to the module that executes action An.

Putting all 3 kinds of modules together, i.e. behavior generating or behavioral modules, detector modules and decision modules, it seemed to me that it would be possible to start making artificial nervous systems. If there were a lot of such modules, then I thought it would be fair to call such a collection, an "artificial brain". It was at this stage that I started to become very ambitious. I began to see myself as the future pioneer of artificial brains, as Mr. Brain Builder.

But there were problems. The computer I was using in the late 80s and early 90s was hopelessly slow for the task I had in mind. By the time I was playing with a dozen evolved modules, the simulation speed of Lizzy on the computer screen was becoming noticeably slow. Every time I added another module's weights, the simulation speed slowed further. It became obvious to me that this was not the way to go. How to get around this problem?

By this stage I had finished my Ph.D. and was now postdocing in Japan, in 1992. In the summer of that year I was in the US talking with an electronic engineer acquaintance of mine at one of the universities that I am associated with, namely George Mason University in Virginia. I was asking this acquaintance how it might be possible to use electronics to speed up the evolution of my modules. After about an hour's discussion, he mentioned something called an FPGA (a field programmable gate array). Not being an electronic engineer, I had never heard of such a thing. "What's an FPGA?" I asked. He told me that it was a special kind of chip that was programmable, i.e. one could send in a bit string that would instruct the chip how to wire itself up or configure itself, to use the technical term.

I suddenly got very excited. A vision flashed before my eyes. Since I had spent the past few years using GAs to evolve neural nets, my immediate inclination was to imagine the configuring bit string as a GA chromosome, so the idea that it might be possible to evolve hardware directly in the chip suddenly looked plausible. I began to grill my acquaintance. Can the configuring bit string be sent in an unlimited number of times? He thought for a moment, and replied that if the chip were based on RAM, i.e. computer memory, then like ordinary RAM in any computer, the programmable chip could be reprogrammed as often as one likes.

I felt overjoyed. It meant that it might be possible to send in random bit strings that would configure or wire up the programmable chip in a random way, generating a complex random circuit. If there was another circuit, programmed by a human being to measure the performance of the randomly programmed chip, then it might be possible to perform a GA directly in hardware at hardware speeds.

I was so excited by this vision, that as soon as I got back to my Japanese research group, I gave a seminar on my idea and launched the research field of "evolvable hardware". I wrote papers on this idea, preached it to colleagues, gave talks on it at conferences, etc. The research field of Evolvable Hardware, or just EH, is now an established research field, with its own conferences every year in the US, Europe and Japan, plus its own academic journals. I feel I am the father of this field, and use its basic ideas in my daily work.

The following year, 1993, I moved to a research lab in Kyoto, Japan where I began work on building an artificial brain. I was convinced after my discovery of the possibility of evolvable hardware, that I had found a tool that would make the building of an artificial brain practical.

I started writing papers announcing that I intended to build an artificial brain with a billion artificial neurons by the year 2001, which happens to be the year that I am in as I write this. In 1993, to make such an announcement invited disbelief, because at the time, most neural net researchers were dealing with tens to hundreds of neurons, as I had been in earlier years. To hear someone suddenly announce that he was going to use a billion, sounded ludicrous. I was laughed at, ridiculed.

But, I was convinced that my vision was sound. If one could build a special kind of computer based on the principles of evolvable hardware, then its electronic evolution speeds would make brain building practical. I did the math and reasoned that a billion neuron artificial brain by 2001 would be just about doable. I had a contract with my Japanese lab for 7-8 years, so I thought I had the time to be ambitious.

My first task was to choose some kind of medium in which to grow and evolve neural nets. I chose to use cellular automata (CA). Each cell of a cellular automaton can be likened to a square on a chess board, but with two differences. One is that the chess board has an unlimited number of squares. The other is that the squares are not confined to be only black or white but can be any of a finite set of colors. Each square can change its color into any other of the set only at the tick of a clock. The color that a particular square changes into depends on its current color, and the colors of its 4 immediate, touching neighbor squares. For example, if the North square is red, the East square is yellow, the South square is blue, the West square is green and the central square in question is brown, then at the next clock tick, the central square changes its color to purple.

By appropriately choosing thousands of such rules, it was possible for me to make these cellular automata cells behave like a neural network that grows and evolves. For example I could grow pathways 3 cells wide, in which I would send growth cells that moved down the middle of the path. When a growth signal hit the end of the growing path it would make the path extend, turn left, turn right, split etc, depending on the color of the growth signal. By mutating the sequence of these growth signals that were sent down the middle of the CA pathways, I was able to evolve the CA based neural net.

This process occurred in two phases. The first was the growth phase. After a few hundred clock ticks, the growth would saturate. No more 3-cell wide CA trails or paths could be grown. These trails were the axons and dendrites of the neural net. Once the growth phase was completed, i.e. the growth instruction cells had cleared themselves from the network, the grown neural net could then be used for the subsequent signaling phase. Input signals could be applied, which would propagate over the network. These signals behaved like the signals in the neural networks that I had evolved in earlier years. They could be extracted at output points and used to control processes whose fitness or performance quality could be measured. The fitness of the performance became the fitness of the network, which in turn was grown from a sequence of growth instructions, i.e. a random string of 6 different integers (whole numbers).

What I had done was marry neural nets with cellular automata. This had not been done before as far as I know. The reason for doing this was that I thought CAs would be a suitable medium in which to have billions of CA cells, more than enough for a billion neurons. It seems to me to be practical. The workstations (i.e. computers a bit more powerful than PCs) of the time would have a gigabyte (a billion bytes) of RAM memory in them. RAM is cheap, so since I could store the state or color of one CA cell in a single byte (8 bits) of RAM, and my workstation could have a gigabyte of RAM, that would allow me to store the colors of a billion CA cells, a billion! That's a lot, more than enough in which to put an artificial brain which a huge number of neurons. Space would not be a problem. The technology of the time would allow it. It would be practical.

It took me about a year to write all the rules (NorthEastSouthWestCenter type rules) to show that a 2D version of a CA based neural net would work, that it would evolve. I had to hand code (with software productivity tools to help me) about 11,000 such rules to get it to work, but work it did. I successfully evolved oscillator circuits, signal strength detection circuits, line motion detector circuits etc. It was time to move on to a 3D version which would have quite a different topology. In 2D, circuits have to collide. They cannot go past each other. Whereas in 3D, CA trails can pass each other using the 3rd dimension. The dynamics and evolvability of 3D circuits would be much richer than the 2D case.

I got the 3D version to work but only after another 2 years, and roughly 60,000 rules. By this stage I was feeling quite miserable in Japan. My immediate group boss had a policy of having only one person per project, which made me terribly lonely and intellectually sterile. I had noone to really talk with. After exerting some pressure I finally got a young German M.Sc. level student to help me for the year 1996.

I explained to him that the 3D version was pretty well finished, and that I was becoming increasingly disillusioned with the particular CA model that I had been using. I explained to him my dream of growing and evolving CA based neural circuits directly in electronics, at electronic speeds. I felt that together we would need to simplify the CA model, so that it would be possible to fit it all into the electronics of the time, i.e. 1996. He listened to my list of desiderata and then disappeared for 2 weeks. He returned with a new, much simplified neural net model that kept the essential features of my old model, but added features that simplified it to such an extent that indeed the new model could be put directly into electronics. This new model was called CoDi, and was conceived by Felix Gers.

At about this time in the second half of 96, I was contacted by a Russian/American electronic engineer by the name of Dr. Michael Korkin, who lived in Boulder, Colorado. He had found my papers interesting and wanted to collaborate. I sent him details of Gers's new model and asked him if he thought he could implement it in hardware using special FPGAs that were then on the market. He said he thought he could. My Japanese boss approved the financing of the idea and a close collaboration between Mike Korkin and myself then started. Unfortunately I lost Gers only after one year. He went to do a Ph.D. in Switzerland. My Japanese boss reverted to his old policy of one person per project and I became more miserable than ever. I was also becoming increasingly fed up with Japan, with its repression of individuality, its insularity, its social backwardness, its status as an unrepentant criminal nation after killing some 30 million people in the war and not feeling any guilt about it. The Japanese government keeps knowledge of its massive crimes hidden from the general population. I was starting to want to leave, but couldn't, because the new machine had just been approved for construction. How I survived 8 years in Japan seems a miracle to me now. After so many years in the same lab with my growing contempt for Japanese culture, it was only a question of time before the management there would be happy to see me go. Mitigating this was the fact that I was putting their lab on the world map with all the world wide media publicity I was getting. I was claiming to be the guy who was going to be the first on the planet to build an artificial brain. I must have been a real thorn to them. What do you do with a researcher who makes the lab famous, yet truly despises your culture?

Relations with my group manager became increasingly strained, especially after I discovered he employed a policy of putting his name on academic journal papers written by his subordinates to which he made absolutely no intellectual contribution. He asked me to put his name on one of my journal articles. I refused, and told him that in the west that would be considered disgusting, an abuse of power, and corrupt. After that, relations soured fast. I was allowed to stay on until the end of the year 1999, and then I would have to leave. Since two thirds of the division of some 100 researchers would have to leave at the same time, I felt only half fired. The Japanese economy had performed so badly during the 90s, "the lost decade", that the whole research division was considered too blue sky, too fringey to be funded in times of economic scarcity.

I got another job. Ironically it was in Brussels, and to do the same work as I had done at my Japanese lab.

During the years 1996 and mid 1999, Mike Korkin was working away solidly in the US on constructing the special piece of hardware that would fulfil my dream of building artificial brains. It was slow going for him. He had only a limited budget from my Japanese group boss. He could afford only one full time assistant plus a few part timers on limited term contracts.

During the course of his work, the US company making the FPGA chips that the machine was based on, decided to take them off the market. Mike then had to fight the company to get the remaining chips. This caused many months of delay. The chips were finally obtained, but were untested. Thus he had to test them himself, without the thorough testing software that the company would have - more delays.

It was not until mid 2000 that the machines that I called CAM-Brain Machines (CBMs) were finally debugged sufficiently that true evolution experiments could begin. CAM stands for Cellular Automata Machine, because the original work was to put an artificial brain inside cellular automata.

The first CBM was delivered to my Japanese lab in early 1999, but it still contained bugs. With untested chips and small manpower, work progressed slowly. But all was not gloomy. Other people became interested in the CBM. As I write in early 2001, there are 4 such machines in the world. The first remains at my old Kyoto lab in Japan. The second was bought by a Belgian speech-processing lab and later transferred to a bioinformatics company also in Belgium. The third was bought by my new Brussels lab, and the fourth is owned by Mike Korkin himself. Thus with 2 of the 4 machines in Belgium, Belgium is in a sense the world leader in this field. In 2000, I managed to get a million dollar grant from the Brussels government to build an artificial brain to control a small robot, giving it hundreds of behaviors. As you can see, my current work is really only a glorious extension of my old Ph.D. thesis work.

Just what can the CBM do? I believe it is truly a miraculous machine, that in time, once people appreciate its significance, will take its place in the history of computing. It implements the CoDi CA based neural net model directly in electronics. It evolves a neural net in a few seconds, i.e. it performs a complete run of a genetic algorithm, i.e. tens of thousands of neural circuit module growths and fitness measurements. It can change the color of CA cells at the phenomenal rate of about 130 billion a second. It can handle nearly 100 million artificial neurons. It has the processing capacity of about 10,000 PCs, so is definitely a supercomputer but costs only $500,000.

The CBM has two main roles. The first is to evolve individual neural circuit modules, or just modules, I call them. A neural net is grown/evolved inside a 3D CA space of 24*24*24 CA cells or little cubes. About 1000 neurons can fit inside this space. Branch-like axons and dendrites grow randomly inside this space. A programmed FPGA is used to measure the quality of the neural signaling of the network that is grown. The basic ideas are similar to what I was working on before 1996. Once a module is evolved, it is downloaded into a portion of a gigabyte of RAM memory. 64000 of such modules can be evolved one at a time, each with its own fitness definition (i.e. task or function) as specified by human "evolutionary engineers" (EEs) and downloaded into the RAM. Later, "brain architects" (BAs) interconnect by hand the downloaded modules to form their humanly specified artificial brain architectures to perform the tasks that they want.

2.3 Future Tasks and Dreams
At the present time I and a small team of full time collaborators at my present lab in Brussels have recently started using the CBM to evolve individual modules, mainly for pattern recognition tasks. For example, we can evolve a module capable of detecting whether a line of input stimulus moves up or down an input face. We are testing the level of "evolvability" of the neural net model we have implemented in the CBM. Of course this model is constrained by the state-of-the-art hardware that it is implemented in.

The modules do not always evolve the way we want or even at all sometimes. What I call "evolutionary engineering" is a black art. There is no theory to guide evolutionary engineers (EEs) on how to improve evolvabilities, a concept fundamental to this field. At the present time, we are getting a feel for what the CBM can do, its strengths and limitations. Noone has done this kind of thing before, so we are struggling in the dark. There are no signposts. This is research. Every step of the way is new and may often blunder into an unanticipated problem. But, we are making headway, even if at a slower pace than I had estimated way back in 1993 when I started this project.

If those people who had laughed at my preposterous assertion that I would build an artificial brain with a billion neurons by 2001 were able to see the CBM in 1993 as it exists in 2001, they would not have laughed. Admittedly the machine cannot handle a billion neurons. The actual figure is 75 million, but that's only one order of magnitude off. That's not bad. Admittedly also, the task of architecting the artificial brain, a huge task, still lies ahead of us, and will take several years. There is still a lot of work to do, and I still suffer from critics. With all the delays, whether for commercial, intellectual, managerial, or personal reasons, I still do not have an artificial brain to show off to people. Some journalists are starting to get impatient, and are wondering when I will deliver.

During the next year or so, if all goes ahead as planned, my team needs to complete its evolvability studies, evolving one module at a time. If the evolvability levels are not sufficient, we may have to change the fitness definitions we use in the CBM. We may also have to change the neural net model implemented in the reprogrammable FPGAs. Once that stage is over, the next will be to start building multi-module systems, with 10s of modules, then 100s, then 1000s, up to 64,000, to build an artificial brain aimed at controlling the behavior of robots. We intend to show off a robot with many behaviors controlled by an artificial brain. One will not need to have a Ph.D. to understand what is going on, as is the case with the CBM, but just by simple observation of the robot, one should be able to see that "there is a brain behind it".

In parallel with all this work, which should take several more years, is the need to start serious thinking about the next generation of brain building machine, that I call the BM2 (brain building machine, 2nd generation). I have started collaborating with another American colleague who has had some revolutionary ideas for the next generation of electronics that self configure. He has estimated that with a budget of a few million dollars, it should be possible to build a next generation machine within about 4 years which should be about 1000 times more performant compared with the CBM.

In fact, it is my ambition to continue trying to build a new generation brain building machine and its corresponding brain every 4-5 years. I'm now in my mid 50s, so if I choose to retire in my 70s, that gives me about 20 years, or 4 more generations. In 20 years, if Moore's law continues to be valid that long, it will give humanity the ability to put one bit of information on one atom. Once that happens it will be possible to build what I call "Avogadro Machines", i.e. machines with a trillion trillion components. Avogadro's number is the number of molecules in an object of human scale, e.g. an apple in one's hand.

If the second generation brain building machine can be funded and can be built within the next 4-5 years, then it will be possible to make the next generation brain more similar to the biological brain. The neural net model it implements can be more sophisticated and closer in its behaviors to those of biological neurons.

Within a mere 20 years, i.e. my own working lifetime, humanity, hence I and other brain builders, will have the technologies and the tools to build ever more performant artificial brains.

Is it any wonder then, that someone who is as politically and socially critical as I am, is beginning to feel alarmed at the rapid progress that brain building can be expected to make in the coming 20 years. What will our artificial brains be doing for humanity in 20 years? I would say it is highly likely they will be in our homes, cleaning them, babysitting our kids, talking with us, giving us infinite information from knowledge banks all over the planet. We will be having sex with them, be educated by them, be entertained by them, made to laugh by them etc. The brain building industry 20 years from now I estimate will be worth about a trillion dollars a year worldwide. By 2005 I hope and expect that if my own group can "prove concept" within the next year or so that brain building is doable, then a new "brain building" research field will have been established.

If we have all this within 20 years, where will humanity be in 50 years, in a 100? Given the exponential progress in the accumulation of our knowledge of brain science, all of which can be immediately incorporated into neuro- engineering the moment it is discovered, I feel that the initial positive feelings about artificial brains will later turn sour and develop into fear.

I am attempting to become the father of the artificial brain. I am already the father of evolvable hardware and of evolutionary engineering, which are the enabling technologies of this new field. If I were a traditionally minded engineer or scientist, I would probably be quite content to get on with my work and not worry about its longer term social consequences, but I'm not like that. I'm a very political animal, and I'm very worried. My rather unusual combination of being a scientist/engineer and at the same time a social critic and media person makes me an appropriate person I believe to raise the alarm on the artilect issue.

I'm hoping that my credibility or otherwise as a professional brain builder will aid my attempts to raise the alarm on the rise of the 21st century artilect. However, the two need not be connected. Even if I fail to build an artificial brain, others will succeed. For me to succeed with each brain-building-machine-generation, and the building of its corresponding brain, I will need to raise more money, hire more people as the scale of the enterprise keeps increasing. I will need to become like Goddard, the US rocket pioneer, or Werner von Braun, who put an American on the moon. Both these men started with toy rockets, but had a vision. In the 20s Goddard's first contraptions were not much better than 2m tall ancient Chinese style rockets. 20 years later both he and von Braun were heavily subsidized by their respective governments to build highly sophisticated rockets capable of travelling great distances. In the late 60s von Brawn played a major part in an organization that put Armstrong on the moon.

I have similar dreams. I dream of national projects paying billions of dollars to build artificial brains. I have talked of the J-Brain Project (Japan's national brain building project), the A-Brain Project (America's), the E-Brain and C-Brain Projects (Europe's and China's). Within 20 years, and in possession of Avogadro machines, there will be so much work to be done in building a brain with not billions of components but trillions of trillions of components, that a huge team of people will be needed. That's my longer term dream, 20 years from now.

After that, once I have retired, I hope I will be able to play the role of the wise old man who advises younger minds on where the whole brain builder effort ought to be headed. As this book shows, I am not optimistic about the future survival of humanity when faced with machines that become ever smarter at exponential rates.

My ultimate goal is to see humanity, or at least of portion of it, go Cosmist and to do it successfully by building truly godlike artilects that tower above our puny human intellectual, and other, abilities. That is my true goal. I won't live to see it unfortunately. True artilects won't be built within the 30-40 years I have left. I will not live to see the ultimate fruits of my work. This is a source of great frustration and disappointment to me, but there is one consolation