~ Singularity

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"The Singularity" is a phrase borrowed from the astrophysics of black holes. The phrase has varied meanings; as used by Vernor Vinge and Raymond Kurzweil, it refers to the idea that accelerating technology will lead to superhuman machine intelligence that will soon exceed human intelligence, probably by the year 2030. The results on the other side of the "event horizon," they say, are unpredictable.

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Op zaterdag 27 januari 2007 15:54 schreef Angst het volgende:
kan je ff in een zin zeggen van singularity is?

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Op zaterdag 27 januari 2007 16:03 schreef Noin het volgende:
In 1 zin: er wordt iets zo slim gemaakt, dat wij te dom worden en dus onnodig zijn voor dat slimme ding.

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Op zaterdag 27 januari 2007 16:30 schreef Kjew het volgende:

[..]

Euh, dat is toch nu al? Toename van elektromagnetische golven, synthetische stoffen in voeding, etc.

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Op zaterdag 27 januari 2007 16:39 schreef soylent het volgende:
Op de Nederlandse wiki-pagina (klik mij) wordt het misschien duidelijker uitgelegd.

Ik geloof er zelf trouwens niet in. Er zijn bij technologie-ontwikkelingen ook vele dempende factoren, zoals gedane investeringen en lock-in. Probeer als voorbeeld daarvan maar eens een succesvolle verbetering op Windows te maken, of een auto met een niet-benzine aandrijving. Je kan het verzinnen maar je vecht tegen extreem succesvolle en alomvertegenwoordigde systemen.

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Op zaterdag 27 januari 2007 17:19 schreef alien8ed het volgende:

[..]

Daar komt ook nog bij dat de term singulariteit oorspronkelijk een wetenschappelijk natuurverschijnsel omschrijft, dat zich niet aan bestaande natuurwetten houdt.

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Op zaterdag 27 januari 2007 17:52 schreef alien8ed het volgende:

[..]

De bedenker van Technological singularity gelooft denk ik te veel in de korte termijn kennis die de laatste 20 jaar is opgedaan en baseert daar zijn grafiek op, zonder oog te hebben voor lange termijn natuur processen.

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Kurzweil grew up in Queens, New York. In his youth, he was an avid consumer of science fiction literature. By the age of twelve he had written his first computer program. Shortly after his discovery of programming, he appeared on the CBS television program I've Got a Secret, where he performed a piano piece that was composed by a computer he had built. In 1968, at the age of twenty, he sold a company he created that matched high schoolers with prospective colleges by answering a 200 question survey. He earned a BS in Computer Science and Literature in 1970 from MIT.

Kurzweil was the principal developer of the first omni-font optical character recognition system, the first print-to-speech reading machine for the blind, the first CCD flatbed scanner, the first text-to-speech synthesizer, the first electronic musical instrument capable of recreating the sound of a grand piano and other orchestral instruments (which he developed at the urging of Stevie Wonder, who was amazed by his OCR reading machine), and the first commercially marketed large-vocabulary speech recognition system.

He has founded nine businesses in the fields of OCR, music synthesis, speech recognition, reading technology, virtual reality, financial investment, medical simulation, and cybernetic art.

Kurzweil was inducted in 2002 into the National Inventors Hall of Fame, established by the United States Patent and Trademark Office. He received the $500,000 Lemelson-MIT Prize, the United States' largest award in invention and innovation, and the 1999 National Medal of Technology, the nation's highest honor in technology.

He has also received scores of other awards, including the 1994 Dickson Prize (Carnegie Mellon University's top science prize), Engineer of the Year from Design News, Inventor of the Year from MIT in 1998, the Association of American Publishers' award for the Most Outstanding Computer Science Book of 1990, and the Grace Murray Hopper Award from the Association for Computing Machinery and he received the Telluride Tech Festival Award of Technology in 2000.

He has received thirteen honorary doctorates, a 14th scheduled in 2007, and honors from three U.S. presidents.

He has been described as “the restless genius” by the Wall Street Journal, and “the ultimate thinking machine” by Forbes. Inc. magazine ranked him #8 among entrepreneurs in the United States, calling him the “rightful heir to Thomas Edison,” and PBS included Ray as one of sixteen “revolutionaries who made America” [1], along with other inventors of the past two centuries.

Kurzweil's musical keyboards company Kurzweil Music Systems produces among the most sophisticated and realistic (and expensive) synthesized-sound creation instruments. Ray sold Kurzweil Music Systems in the early 1990s to Korean piano manufacturer Young Chang. He has no current involvement with Young Chang or Kurzweil Music Systems.

Kurzweil has also created his own twenty five year old female rock star alter ego, "Ramona", who he regularly performs as through virtual reality technology [2] to illustrate the as-yet untapped possibilities of computers to enhance and alter our interpersonal interactions. This project inspired the plot of the movie S1m0ne.

In 2005, Microsoft chairman Bill Gates called Ray Kurzweil "the best at predicting the future of artificial intelligence".

Kurzweil has been associated with the National Federation of the Blind, many of whose members use his products. After speaking at their convention in 2005, he received a special award, an honor received by few sighted people.

He is on the Army Science Advisory Board and has testified before Congress on the subject of nanotechnology.

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Response to 'The Singularity Is Always Near'
by Ray Kurzweil



In "The Singularity Is Always Near," an essay in The Technium, an online "book in progress," author Kevin Kelly critiques arguments on exponential growth made in Ray Kurzweil's book, The Singularity Is Near. Kurzweil responds.


Published on KurzweilAI.net May 4, 2006

Allow me to clarify the metaphor implied by the term "singularity." The metaphor implicit in the term "singularity" as applied to future human history is not to a point of infinity, but rather to the event horizon surrounding a black hole. Densities are not infinite at the event horizon but merely large enough such that it is difficult to see past the event horizon from outside.


I say difficult rather than impossible because the Hawking radiation emitted from the event horizon is likely to be quantum entangled with events inside the black hole, so there may be ways of retrieving the information. This was the concession made recently by Hawking. However, without getting into the details of this controversy, it is fair to say that seeing past the event horizon is difficult (impossible from a classical physics perspective) because the gravity of the black hole is strong enough to prevent classical information from inside the black hole getting out.


We can, however, use our intelligence to infer what life is like inside the event horizon even though seeing past the event horizon is effectively blocked. Similarly, we can use our intelligence to make meaningful statements about the world after the historical singularity, but seeing past this event horizon is difficult because of the profound transformation that it represents.


So discussions of infinity are not relevant. You are correct that exponential growth is smooth and continuous. From a mathematical perspective, an exponential looks the same everywhere and this applies to the exponential growth of the power (as expressed in price-performance, capacity, bandwidth, etc.) of information technologies. However, despite being smooth and continuous, exponential growth is nonetheless explosive once the curve reaches transformative levels. Consider the Internet. When the Arpanet went from 10,000 nodes to 20,000 in one year, and then to 40,000 and then 80,000, it was of interest only to a few thousand scientists. When ten years later it went from 10 million nodes to 20 million, and then 40 million and 80 million, the appearance of this curve looks identical (especially when viewed on a log plot), but the consequences were profoundly more transformative. There is a point in the smooth exponential growth of these different aspects of information technology when they transform the world as we know it.


You cite the extension made by Kevin Drum of the log-log plot that I provide of key paradigm shifts in biological and technological evolution (which appears on page 17 of The Singularity Is Near). This extension is utterly invalid. You cannot extend in this way a log-log plot for just the reasons you cite. The only straight line that is valid to extend on a log plot is a straight line representing exponential growth when the time axis is on a linear scale and the a value (such as price-performance) is on a log scale. Then you can extend the progression, but even here you have to make sure that the paradigms to support this ongoing exponential progression are available and will not saturate. That is why I discuss at length the paradigms that will support ongoing exponential growth of both hardware and software capabilities. But it is not valid to extend the straight line when the time axis is on a log scale. The only point of these graphs is that there has been acceleration in paradigm shift in biological and technological evolution.


If you want to extend this type of progression, then you need to put time on a linear x axis and the number of years (for the paradigm shift or for adoption) as a log value on the y axis. Then it may be valid to extend the chart. I have a chart like this on page 50 of the book.


This acceleration is a key point. These charts show that technological evolution emerges smoothly from the biological evolution that created the technology creating species. You mention that an evolutionary process can create greater complexity—and greater intelligence—than existed prior to the process. And it is precisely that intelligence creating process that will go into hyper drive once we can master, understand, model, simulate, and extend the methods of human intelligence through reverse-engineering it and applying these methods to computational substrates of exponentially expanding capability.


That chimps are just below the threshold needed to understand their own intelligence is a result of the fact that they do not have the prerequisites to create technology. There were only a few small genetic changes, comprising a few tens of thousands of bytes of information, that distinguish us from our primate ancestors: a bigger skull (allowing a larger brain), a larger cerebral cortex, and a workable opposable appendage. There were a few other changes that other primates share to some extent such as mirror neurons and spindle cells


As I pointed out in my long now talk, a chimp's hand looks similar but the pivot point of the thumb does not allow facile manipulation of the environment. In contrast, our human ability to look inside the human brain and to model and simulate and recreate the processes we encounter there has already been demonstrated. The scale and resolution of these simulations will continue to expand exponentially. I make the case that we will reverse-engineer the principles of operation of the several hundred information processing regions of the human brain within about twenty years and then apply these principles (along with the extensive tool kit we are creating through other means in the AI field) to computers that will be many times (by the 2040s, billions of times) more powerful than needed to simulate the human brain.


You write that "Kurzweil found that if you make a very crude comparison between the processing power of neurons in human brains and the processing powers of transistors in computers, you could map out the point at which computer intelligence will exceed human intelligence." That is an oversimplification of my analysis. I provide in book four different approaches to estimating the amount of computation required to simulate all regions of the human brain based on actual functional recreations of brain regions. These all come up with answers in the same range, from 1014 to 1016 cps for creating a functional recreation of all regions of the human brain, so I've used 1016 cps as a conservative estimate.


This refers only to the hardware requirement. As noted above, I have an extensive analysis of the software requirements. While reverse-engineering the human brain is not the only source of intelligent algorithms (and, in fact, has not been a major source at all up until just recently because we did not have scanners that could see into the human with sufficient resolution until recently), my analysis of reverse-engineering the human brain is along the lines of an existence proof that we will have the software methods underlying human intelligence within a couple of decades.


Another important point in this analysis is that the complexity of the design of the human brain is about a billion times simpler than the actual complexity we find in the brain. This is due to the brain (like all biology) being a probabilistic recursively expanded fractal. This discussion goes beyond what I can write here (although it is in the book). We can ascertain the complexity of the design of the human brain because the design is contained in the genome and I show that the genome (including non-coding regions) only has about 30 to 100 million bytes of compressed information in it due to the massive redundancies in the genome.


So in summary, I agree that the singularity is not a discrete event. A single point of infinite growth or capability is not the metaphor being applied. Yes, the exponential growth of all facts of information technology is smooth, but is nonetheless explosive and transformative.

© 2006 Ray Kurzweil

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Op zaterdag 27 januari 2007 19:54 schreef Agno_Sticus het volgende:
Kweenie. Alhoewel ik nog maar één van de drie video's bekeken heb, vind ik hem niet echt overtuigend. Het gaat puur over technologie en niet zozeer over het tempo van de acceptatie in de samenleving.

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Op zondag 28 januari 2007 18:12 schreef Agno_Sticus het volgende:

of "je moet alle filmpjes kijken, dan piep wel anders".

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Op zondag 28 januari 2007 18:47 schreef gronk het volgende:

(waar meneer kurzweil op vegeteert)

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These are safe bets, but they fail to capture the Web's disruptive trajectory. The real transformation under way is more akin to what Sun's John Gage had in mind in 1988 when he famously said, "The network is the computer." He was talking about the company's vision of the thin-client desktop, but his phrase neatly sums up the destiny of the Web: As the OS for a megacomputer that encompasses the Internet, all its services, all peripheral chips and affiliated devices from scanners to satellites, and the billions of human minds entangled in this global network. This gargantuan Machine already exists in a primitive form. In the coming decade, it will evolve into an integral extension not only of our senses and bodies but our minds.

Today, the Machine acts like a very large computer with top-level functions that operate at approximately the clock speed of an early PC. It processes 1 million emails each second, which essentially means network email runs at 1 megahertz. Same with Web searches. Instant messaging runs at 100 kilohertz, SMS at 1 kilohertz. The Machine's total external RAM is about 200 terabytes. In any one second, 10 terabits can be coursing through its backbone, and each year it generates nearly 20 exabytes of data. Its distributed "chip" spans 1 billion active PCs, which is approximately the number of transistors in one PC.

This planet-sized computer is comparable in complexity to a human brain. Both the brain and the Web have hundreds of billions of neurons (or Web pages). Each biological neuron sprouts synaptic links to thousands of other neurons, while each Web page branches into dozens of hyperlinks. That adds up to a trillion "synapses" between the static pages on the Web. The human brain has about 100 times that number—but brains are not doubling in size every few years. The Machine is.

Since each of its "transistors" is itself a personal computer with a billion transistors running lower functions, the Machine is fractal. In total, it harnesses a quintillion transistors, expanding its complexity beyond that of a biological brain. It has already surpassed the 20-petahertz threshold for potential intelligence as calculated by Ray Kurzweil. For this reason some researchers pursuing artificial intelligence have switched their bets to the Net as the computer most likely to think first. Danny Hillis, a computer scientist who once claimed he wanted to make an AI "that would be proud of me," has invented massively parallel supercomputers in part to advance us in that direction. He now believes the first real AI will emerge not in a stand-alone supercomputer like IBM's proposed 23-teraflop Blue Brain, but in the vast digital tangle of the global Machine.

In 10 years, the system will contain hundreds of millions of miles of fiber-optic neurons linking the billions of ant-smart chips embedded into manufactured products, buried in environmental sensors, staring out from satellite cameras, guiding cars, and saturating our world with enough complexity to begin to learn. We will live inside this thing.

Today the nascent Machine routes packets around disturbances in its lines; by 2015 it will anticipate disturbances and avoid them. It will have a robust immune system, weeding spam from its trunk lines, eliminating viruses and denial-of-service attacks the moment they are launched, and dissuading malefactors from injuring it again. The patterns of the Machine's internal workings will be so complex they won't be repeatable; you won't always get the same answer to a given question. It will take intuition to maximize what the global network has to offer. The most obvious development birthed by this platform will be the absorption of routine. The Machine will take on anything we do more than twice. It will be the Anticipation Machine.

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And the most universal. By 2015, desktop operating systems will be largely irrelevant. The Web will be the only OS worth coding for. It won't matter what device you use, as long as it runs on the Web OS. You will reach the same distributed computer whether you log on via phone, PDA, laptop, or HDTV.

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And who will write the software that makes this contraption useful and productive? We will. In fact, we're already doing it, each of us, every day. When we post and then tag pictures on the community photo album Flickr, we are teaching the Machine to give names to images. The thickening links between caption and picture form a neural net that can learn. Think of the 100 billion times per day humans click on a Web page as a way of teaching the Machine what we think is important. Each time we forge a link between words, we teach it an idea. Wikipedia encourages its citizen authors to link each fact in an article to a reference citation. Over time, a Wikipedia article becomes totally underlined in blue as ideas are cross-referenced. That massive cross-referencing is how brains think and remember. It is how neural nets answer questions. It is how our global skin of neurons will adapt autonomously and acquire a higher level of knowledge.

The human brain has no department full of programming cells that configure the mind. Rather, brain cells program themselves simply by being used. Likewise, our questions program the Machine to answer questions. We think we are merely wasting time when we surf mindlessly or blog an item, but each time we click a link we strengthen a node somewhere in the Web OS, thereby programming the Machine by using it.

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The Singularity—a notion that’s crept into a lot of skiffy, and whose most articulate in-genre spokesmodel is Vernor Vinge—describes the black hole in history that will be created at the moment when human intelligence can be digitized. When the speed and scope of our cognition is hitched to the price-performance curve of microprocessors, our "prog-ress" will double every eighteen months, and then every twelve months, and then every ten, and eventually, every five seconds.

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Kurzweil believes in the Singularity. In his 1990 manifesto, "The Age of Intelligent Machines," Kurzweil persuasively argued that we were on the brink of meaningful machine intelligence. A decade later, he continued the argument in a book called The Age of Spiritual Machines, whose most audacious claim is that the world’s computational capacity has been slowly doubling since the crust first cooled (and before!), and that the doubling interval has been growing shorter and shorter with each passing year, so that now we see it reflected in the computer industry’s Moore’s Law, which predicts that microprocessors will get twice as powerful for half the cost about every eighteen months. The breathtaking sweep of this trend has an obvious conclusion: computers more powerful than people; more powerful than we can comprehend.

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So how do you know if the backed-up you that you’ve restored into a new body—or a jar with a speaker attached to it—is really you? Well, you can ask it some questions, and if it answers the same way that you do, you’re talking to a faithful copy of yourself.

Sounds good. But the me who sent his first story into Asimov’s seventeen years ago couldn’t answer the question, "Write a story for Asimov’s" the same way the me of today could. Does that mean I’m not me anymore?

Kurzweil has the answer.

"If you follow that logic, then if you were to take me ten years ago, I could not pass for myself in a Ray Kurzweil Turing Test. But once the requisite uploading technology becomes available a few decades hence, you could make a perfect-enough copy of me, and it would pass the Ray Kurzweil Turing Test. The copy doesn’t have to match the quantum state of my every neuron, either: if you meet me the next day, I’d pass the Ray Kurzweil Turing Test. Nevertheless, none of the quantum states in my brain would be the same. There are quite a few changes that each of us undergo from day to day, we don’t examine the assumption that we are the same person closely.

"We gradually change our pattern of atoms and neurons but we very rapidly change the particles the pattern is made up of. We used to think that in the brain—the physical part of us most closely associated with our identity—cells change very slowly, but it turns out that the components of the neurons, the tubules and so forth, turn over in only days. I’m a completely different set of particles from what I was a week ago.

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The Kurzweil Singularity goes like this: computers get better and smaller. Our ability to measure the world gains precision and grows ever cheaper. Eventually, we can measure the world inside the brain and make a copy of it in a computer that’s as fast and complex as a brain, and voila, intelligence.

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"We seem to have found one area of the brain closely associated with higher-level emotions, the spindle cells, deeply embedded in the brain. There are tens of thousands of them, spanning the whole brain (maybe eighty thousand in total), which is an incredibly small number. Babies don’t have any, most animals don’t have any, and they likely only evolved over the last million years or so. Some of the high-level emotions that are deeply human come from these.

"Turing had the right insight: base the test for intelligence on written language. Turing Tests really work. A novel is based on language: with language you can conjure up any reality, much more so than with images. Turing almost lived to see computers doing a good job of performing in fields like math, medical diagnosis and so on, but those tasks were easier for a machine than demonstrating even a child’s mastery of language. Language is the true embodiment of human intelligence."

If we’re not so complex, then it’s only a matter of time until computers are more complex than us. When that comes, our brains will be model-able in a computer and that’s when the fun begins. That’s the thesis of Spiritual Machines, which even includes a (Heinlein-style) timeline leading up to this day.

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Thought Experiments: When the Singularity Is More than a Literary Device
An Interview with Futurist-Inventor Ray Kurzweil by Cory Doctorow



Is the Singularity a spiritual or a technological belief system? Perhaps it is the melding of both, says science fiction author Cory Doctorow in this dialogue with Ray Kurzweil. "After all, this is a system of belief that dictates a means by which we can care for our bodies virtuously and live long enough to transcend them. It's no wonder that the Singularity has come to occupy so much of the science fiction narrative in these years. Science or spirituality, you could hardly ask for a subject better tailored to technological speculation and drama."


Originally published in Asimov's Science Fiction, April 18, 2005. Published with permission on KurzweilAI.net January 16, 2006.

It’s not clear to me whether the Singularity is a technical belief system or a spiritual one.

The Singularity—a notion that’s crept into a lot of skiffy, and whose most articulate in-genre spokesmodel is Vernor Vinge—describes the black hole in history that will be created at the moment when human intelligence can be digitized. When the speed and scope of our cognition is hitched to the price-performance curve of microprocessors, our "prog-ress" will double every eighteen months, and then every twelve months, and then every ten, and eventually, every five seconds.

Singularities are, literally, holes in space from whence no information can emerge, and so SF writers occasionally mutter about how hard it is to tell a story set after the information Singularity. Everything will be different. What it means to be human will be so different that what it means to be in danger, or happy, or sad, or any of the other elements that make up the squeeze-and-release tension in a good yarn will be unrecognizable to us pre-Singletons.

It’s a neat conceit to write around. I’ve committed Singularity a couple of times, usually in collaboration with gonzo Singleton Charlie Stross, the mad antipope of the Singularity. But those stories have the same relation to futurism as romance novels do to love: a shared jumping-off point, but radically different morphologies.

Of course, the Singularity isn’t just a conceit for noodling with in the pages of the pulps: it’s the subject of serious-minded punditry, futurism, and even science.

Ray Kurzweil is one such pundit-futurist-scientist. He’s a serial entrepreneur who founded successful businesses that advanced the fields of optical character recognition (machine-reading) software, text-to-speech synthesis, synthetic musical instrument simulation, computer-based speech recognition, and stock-market analysis. He cured his own Type-II diabetes through a careful review of the literature and the judicious application of first principles and reason. To a casual observer, Kurzweil appears to be the star of some kind of Heinlein novel, stealing fire from the gods and embarking on a quest to bring his maverick ideas to the public despite the dismissals of the establishment, getting rich in the process.

Kurzweil believes in the Singularity. In his 1990 manifesto, "The Age of Intelligent Machines," Kurzweil persuasively argued that we were on the brink of meaningful machine intelligence. A decade later, he continued the argument in a book called The Age of Spiritual Machines, whose most audacious claim is that the world’s computational capacity has been slowly doubling since the crust first cooled (and before!), and that the doubling interval has been growing shorter and shorter with each passing year, so that now we see it reflected in the computer industry’s Moore’s Law, which predicts that microprocessors will get twice as powerful for half the cost about every eighteen months. The breathtaking sweep of this trend has an obvious conclusion: computers more powerful than people; more powerful than we can comprehend.

Now Kurzweil has published two more books, The Singularity Is Near, When Humans Transcend Biology (Viking, Spring 2005) and Fantastic Voyage: Live Long Enough to Live Forever (with Terry Grossman, Rodale, November 2004). The former is a technological roadmap for creating the conditions necessary for ascent into Singularity; the latter is a book about life-prolonging technologies that will assist baby-boomers in living long enough to see the day when technological immortality is achieved.

See what I meant about his being a Heinlein hero?

I still don’t know if the Singularity is a spiritual or a technological belief system. It has all the trappings of spirituality, to be sure. If you are pure and kosher, if you live right and if your society is just, then you will live to see a moment of Rapture when your flesh will slough away leaving nothing behind but your ka, your soul, your consciousness, to ascend to an immortal and pure state.

I wrote a novel called Down and Out in the Magic Kingdom where characters could make backups of themselves and recover from them if something bad happened, like catching a cold or being assassinated. It raises a lot of existential questions: most prominently: are you still you when you’ve been restored from backup?

The traditional AI answer is the Turing Test, invented by Alan Turing, the gay pioneer of cryptography and artificial intelligence who was forced by the British government to take hormone treatments to "cure" him of his homosexuality, culminating in his suicide in 1954. Turing cut through the existentialism about measuring whether a machine is intelligent by proposing a parlor game: a computer sits behind a locked door with a chat program, and a person sits behind another locked door with his own chat program, and they both try to convince a judge that they are real people. If the computer fools a human judge into thinking that it’s a person, then to all intents and purposes, it’s a person.

So how do you know if the backed-up you that you’ve restored into a new body—or a jar with a speaker attached to it—is really you? Well, you can ask it some questions, and if it answers the same way that you do, you’re talking to a faithful copy of yourself.

Sounds good. But the me who sent his first story into Asimov’s seventeen years ago couldn’t answer the question, "Write a story for Asimov’s" the same way the me of today could. Does that mean I’m not me anymore?

Kurzweil has the answer.

"If you follow that logic, then if you were to take me ten years ago, I could not pass for myself in a Ray Kurzweil Turing Test. But once the requisite uploading technology becomes available a few decades hence, you could make a perfect-enough copy of me, and it would pass the Ray Kurzweil Turing Test. The copy doesn’t have to match the quantum state of my every neuron, either: if you meet me the next day, I’d pass the Ray Kurzweil Turing Test. Nevertheless, none of the quantum states in my brain would be the same. There are quite a few changes that each of us undergo from day to day, we don’t examine the assumption that we are the same person closely.

"We gradually change our pattern of atoms and neurons but we very rapidly change the particles the pattern is made up of. We used to think that in the brain—the physical part of us most closely associated with our identity—cells change very slowly, but it turns out that the components of the neurons, the tubules and so forth, turn over in only days. I’m a completely different set of particles from what I was a week ago.

"Consciousness is a difficult subject, and I’m always surprised by how many people talk about consciousness routinely as if it could be easily and readily tested scientifically. But we can’t postulate a consciousness detector that does not have some assumptions about consciousness built into it.

"Science is about objective third party observations and logical deductions from them. Consciousness is about first-person, subjective experience, and there’s a fundamental gap there. We live in a world of assumptions about consciousness. We share the assumption that other human beings are conscious, for example. But that breaks down when we go outside of humans, when we consider, for example, animals. Some say only humans are conscious and animals are instinctive and machinelike. Others see humanlike behavior in an animal and consider the animal conscious, but even these observers don’t generally attribute consciousness to animals that aren’t humanlike.

"When machines are complex enough to have responses recognizable as emotions, those machines will be more humanlike than animals."

The Kurzweil Singularity goes like this: computers get better and smaller. Our ability to measure the world gains precision and grows ever cheaper. Eventually, we can measure the world inside the brain and make a copy of it in a computer that’s as fast and complex as a brain, and voila, intelligence.

Here in the twenty-first century we like to view ourselves as ambulatory brains, plugged into meat-puppets that lug our precious grey matter from place to place. We tend to think of that grey matter as transcendently complex, and we think of it as being the bit that makes us us.

But brains aren’t that complex, Kurzweil says. Already, we’re starting to unravel their mysteries.

"We seem to have found one area of the brain closely associated with higher-level emotions, the spindle cells, deeply embedded in the brain. There are tens of thousands of them, spanning the whole brain (maybe eighty thousand in total), which is an incredibly small number. Babies don’t have any, most animals don’t have any, and they likely only evolved over the last million years or so. Some of the high-level emotions that are deeply human come from these.

"Turing had the right insight: base the test for intelligence on written language. Turing Tests really work. A novel is based on language: with language you can conjure up any reality, much more so than with images. Turing almost lived to see computers doing a good job of performing in fields like math, medical diagnosis and so on, but those tasks were easier for a machine than demonstrating even a child’s mastery of language. Language is the true embodiment of human intelligence."

If we’re not so complex, then it’s only a matter of time until computers are more complex than us. When that comes, our brains will be model-able in a computer and that’s when the fun begins. That’s the thesis of Spiritual Machines, which even includes a (Heinlein-style) timeline leading up to this day.

Now, it may be that a human brain contains n logic-gates and runs at x cycles per second and stores z petabytes, and that n and x and z are all within reach. It may be that we can take a brain apart and record the position and relationships of all the neurons and sub-neuronal elements that constitute a brain.

But there are also a nearly infinite number of ways of modeling a brain in a computer, and only a finite (or possibly nonexistent) fraction of that space will yield a conscious copy of the original meat-brain. Science fiction writers usually hand-wave this step: in Heinlein’s "Man Who Sold the Moon," the gimmick is that once the computer becomes complex enough, with enough "random numbers," it just wakes up.

Computer programmers are a little more skeptical. Computers have never been known for their skill at programming themselves—they tend to be no smarter than the people who write their software.

But there are techniques for getting computers to program themselves, based on evolution and natural selection. A programmer creates a system that spits out lots—thousands or even millions—of randomly generated programs. Each one is given the opportunity to perform a computational task (say, sorting a list of numbers from greatest to least) and the ones that solve the problem best are kept aside while the others are erased. Now the survivors are used as the basis for a new generation of randomly mutated descendants, each based on elements of the code that preceded them. By running many instances of a randomly varied program at once, and by culling the least successful and regenerating the population from the winners very quickly, it is possible to evolve effective software that performs as well or better than the code written by human authors.

Indeed, evolutionary computing is a promising and exciting field that’s realizing real returns through cool offshoots like "ant colony optimization" and similar approaches that are showing good results in fields as diverse as piloting military UAVs and efficiently provisioning car-painting robots at automotive plants.

So if you buy Kurzweil’s premise that computation is getting cheaper and more plentiful than ever, then why not just use evolutionary algorithms to evolve the best way to model a scanned-in human brain such that it "wakes up" like Heinlein’s Mike computer?

Indeed, this is the crux of Kurzweil’s argument in Spiritual Machines: if we have computation to spare and a detailed model of a human brain, we need only combine them and out will pop the mechanism whereby we may upload our consciousness to digital storage media and transcend our weak and bothersome meat forever.

But it’s a cheat. Evolutionary algorithms depend on the same mechanisms as real-world evolution: herit-able variation of candidates and a system that culls the least-suitable candidates. This latter—the fitness-factor that determines which individuals in a cohort breed and which vanish—is the key to a successful evolutionary system. Without it, there’s no pressure for the system to achieve the desired goal: merely mutation and more mutation.

But how can a machine evaluate which of a trillion models of a human brain is "most like" a conscious mind? Or better still: which one is most like the individual whose brain is being modeled?

"It is a sleight of hand in Spiritual Machines," Kurzweil admits. "But in The Singularity Is Near, I have an in-depth discussion about what we know about the brain and how to model it. Our tools for understanding the brain are subject to the Law of Accelerating Returns, and we’ve made more progress in reverse-engineering the human brain than most people realize." This is a tasty Kurzweilism that observes that improvements in technology yield tools for improving technology, round and round, so that the thing that progress begets more than anything is more and yet faster progress.

"Scanning resolution of human tissue—both spatial and temporal—is doubling every year, and so is our knowledge of the workings of the brain. The brain is not one big neural net, the brain is several hundred different regions, and we can understand each region, we can model the regions with mathematics, most of which have some nexus with chaos and self-organizing systems. This has already been done for a couple dozen regions out of the several hundred.

(..)

"We are getting exponentially more knowledge. We can get detailed scans of neurons working in vivo, and are beginning to understand the chaotic algorithms underlying human intelligence. In some cases, we are getting comparable performance of brain regions in simulation. These tools will continue to grow in detail and sophistication.

"We can have confidence of reverse-engineering the brain in twenty years or so. The reason that brain reverse engineering has not contributed much to artificial intelligence is that up until recently we didn’t have the right tools. If I gave you a computer and a few magnetic sensors and asked you to reverse-engineer it, you might figure out that there’s a magnetic device spinning when a file is saved, but you’d never get at the instruction set. Once you reverse-engineer the computer fully, however, you can express its principles of operation in just a few dozen pages.

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"Progress is exponential—not just a measure of power of computation, number of Internet nodes, and magnetic spots on a hard disk—the rate of paradigm shift is itself accelerating, doubling every decade. Scientists look at a problem and they intuitively conclude that since we’ve solved 1 percent over the last year, it’ll therefore be one hundred years until the problem is exhausted: but the rate of progress doubles every decade, and the power of the information tools (in price-performance, resolution, bandwidth, and so on) doubles every year. People, even scientists, don’t grasp exponential growth. During the first decade of the human genome project, we only solved 2 percent of the problem, but we solved the remaining 98 percent in five years."

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But Kurzweil doesn’t think that the future will arrive in a rush. As William Gibson observed, "The future is here, it’s just not evenly distributed."

"Sure, it’d be interesting to take a human brain, scan it, reinstantiate the brain, and run it on another substrate. That will ultimately happen."

"But the most salient scenario is that we’ll gradually merge with our technology. We’ll use nanobots to kill pathogens, then to kill cancer cells, and then they’ll go into our brain and do benign things there like augment our memory, and very gradually they’ll get more and more sophisticated. There’s no single great leap, but there is ultimately a great leap comprised of many small steps.

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Really, this is about augmenting our biological thinking with nonbiological thinking. We have a capacity of 1026 to 1029 calculations per second (cps) in the approximately 1010 biological human brains on Earth and that number won’t change much in fifty years, but nonbiological thinking will just crash through that. By 2049, nonbiological thinking capacity will be on the order of a billion times that. We’ll get to the point where bio thinking is relatively insignificant.

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It’s well and good to talk about all the stuff we can do with technology, but it’s a lot more important to talk about the stuff we’ll be allowed to do with technology. Think of the global freak-out caused by the relatively trivial advent of peer-to-peer file-sharing tools: Universities are wiretapping their campuses and disciplining computer science students for writing legitimate, general purpose software; grandmothers and twelve-year-olds are losing their life savings; privacy and due process have sailed out the window without so much as a by-your-leave.

Even P2P’s worst enemies admit that this is a general-purpose technology with good and bad uses, but when new tech comes along it often engenders a response that countenances punishing an infinite number of innocent people to get at the guilty.

What’s going to happen when the new technology paradigm isn’t song-swapping, but transcendent super-intelligence? Will the reactionary forces be justified in razing the whole ecosystem to eliminate a few parasites who are doing negative things with the new tools?

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Op maandag 29 januari 2007 08:41 schreef gronk het volgende:
Ah. Het is dus niet de bedoeling dat er gediscussieerd wordt, maar dat er braaf het evangelie van meneer kurzweil wordt doorgenomen.

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Op woensdag 31 januari 2007 14:45 schreef gronk het volgende:
Wat in dit soort discussies nog wel eens wordt vergeten is dat 'snel kunnen rekenen' niet betekent dat je ook dingen sneller begrijpt.

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Op woensdag 31 januari 2007 22:47 schreef gronk het volgende:

[..]

En dat is bullshit. Vraag dat maar aan de eerste de beste neuro-whatever. Zelfs op het niveau van een enkele zenuwcel is er nog een hoop onduidelijk. D'r zijn *tig* regelsystemen, die elkaar allemaal overlappen. En dat varieert van hele snelle (neurotransmiters die een signaaltje overdragen, of een signaaltje juist blokkeren) tot hele langzame (hormonen, waarbij de werking soms maaaanden kan na-ijlen), tot irreversibele (signalen die een gen tot expressie laten komen wat daarna 'aan' blijft staan, en wat *ook* bij je kinderen nog 'aan' staat'.)

Als hersenen echt zo eenvoudig waren, dan konden al die 'trends in current biopharmaconeurobla' wel inpakken. Want dan waren we nu zo'n beetje klaar, en konden de jansen-chimica's en de pfizers pillen draaien waar je elke willekeurige emotie mee kon afdwingen. Eeuwig berouw voor de crimineel, geilheid op commando, soma naar believen, zonder nadelige bijeffecten en verslavingsgevaar.

Oh, natuurlijk, 'gevoel' is geen onderdeel van intelligentie. Intelligentie bestaat alleen uit rationele processen. Jah. Da's waar ook.


Anyway, in de 'current hypes of modern research'-tijdschriften wordt nog steeds om de paar jaar een totaal nieuw receptorsysteem ontdekt en gehyped. Het gaat ondertussen wel wat sneller dan in de jaren 70, maar 't blijft behelpen. Daarnaast, bij mijn weten is er nog niemand die claimt dat-ie een volledig subsysteem kan doorgronden. Zelfs niet van een eenvoudig modelsysteempje.
[..]

In mijn vakgebied het een dooddoener om mensen plat te gooien met een overkill aan informatie. Als je echt intelligent bent, dan kun je ook even snel in een paar regels samenvatten wat er in al die linkjes staat. Was dat niet het kenmerk van de singulariteit? Een steeds snellere verwerking en reproductie van informatie?

]

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Op donderdag 1 februari 2007 09:40 schreef gronk het volgende:

[..]

Pot. Ketel.

Overigens, 't respect wat je ik voor je had is knap verdwenen. Goede actie van je!

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Op zaterdag 3 februari 2007 12:45 schreef gronk het volgende:

[..]

Dan moet je ook niet gaan miepen als iemand niet meteen hosanna met je meerroept.

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James Clerk Maxwell, who is ranked along Isaac Newton and Albert Einstein for his contributions to science, imagined an atom-sized device -- known as Maxwell's Demon -- that could trap molecules as they move in a specific direction.

Now scientists at the University of Edinburgh, inspired by Maxwell's thought experiment in 1867, have been able to create such a "nanomachine" for the first time with their own "demon" inside it to ensnare the molecules as they move.

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Research integrates photonic circuitry on a silicon chip
In work that could lead to completely new devices, systems and applications in computing and telecommunications, MIT researchers are bringing the long-sought goal of "optics on a chip" one step closer to market

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Using artificial atoms on a chip, Yale physicists have taken the next step toward quantum computing by demonstrating that the particle nature of microwave photons can now be detected, according to a report spotlighted in the February 1 issue of the journal Nature.

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Scientists have at last persuaded silicon to emit laser beams. In a few years, computers and other devices will handle light as well as electrons

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Researchers in the US have made the first ever liquid transistor. The revolutionary device, which works thanks to an "electrowetting" effect between two competing fluids, could find applications in biotechnology and in the rapidly developing world of flat panel displays.

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Call it the easy-bake nanosensor. Researchers report they have built an exquisitely sensitive biological detector from silicon using conventional tools, meaning it could in principle be mass-produced.
(..)
The device detected as few as 30,000 free-floating proteins in a cubic millimeter of fluid in a matter of seconds, which Reed says compares favorably with other nanowire sensors. It also recognized immune cells by the acid they emit when they bind to antibodies, the group reports. Co-author and Yale bioengineer Tarek Fahmy adds, "There's no other way to do this rapidly [with] high throughput. This is what we're really excited about."

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Supplementing the human brain with computer power has been a staple of science fiction. But in fact, researchers have taken several steps in melding minds with machines, and this spring a team from the University of Southern California may replace damaged brain tissue in rats with a neural prosthesis.

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Although no two brains are alike, they can display a comparable pattern of neural activity when exposed to similar sensory input. Scientists at the Max Planck Institute for Dynamics and Self-Organization in Göttingen have now developed a mathematical method to design networks from neural cells which exhibit a predefined pattern dynamics.

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Researchers have constructed a protein out of amino acids not found in natural proteins, forming a complex, stable structure closely resembling a natural protein. Their findings could help scientists design drugs that look and act like real proteins but won't be degraded by enzymes or targeted by the immune system, as natural proteins are.

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Researchers at the University of Rochester have demonstrated that optical pulses in an imaging system can be buffered in a slow-light medium, while preserving the information of the image.

The ability to delay an entire image and retrieve it intact opens a new avenue in optical buffering—short-term storage of information as optical images. While the initial test image consists of only a few hundred pixels, a tremendous amount of information can be buffered with the new technique.

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A material that is stiffer than diamond has been created by mixing particles of the mineral barium titanate and molten tin. Diamond was previously the stiffest material known.

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A prosthetic arm that moves and feels like the real thing is now a step closer thanks to a new surgical technique which allows the owner to intuitively control her limb and regain her sense of touch.

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German scientists have used igneous rock from Mount Etna to produce carbon nanotubes and fibers.

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Video games that contain high levels of action, such as Unreal Tournament, can actually improve your vision. Researchers at the University of Rochester have shown that people who played action video games for a few hours a day over the course of a month improved by about 20 percent in their ability to identify letters presented in clutter