(¯`*• Observatory of the Future, articulated under Andres Agostini's book http://lnkd.in/R5pXnK

Wednesday, October 19, 2011

Psychopathic killers: computerized text analysis uncovers the word patterns of a predator

The words of psychopathic murderers match their personalities, which reflect selfishness, detachment from their crimes and emotional flatness, says Jeff Hancock, Cornell professor of computing and information science, and colleagues at the University of British Columbia in the journal Legal and Criminological Psychology.

Computerized text analysis shows that psychopathic killers make identifiable word choices beyond conscious control when talking about their crimes. This research could lead to new tools for diagnosis and treatment, and has implications law enforcement and social media.

Hancock and his colleagues analyzed stories told by 14 psychopathic male murderers held in Canadian prisons and compared them with 38 convicted murderers who were not diagnosed as psychopathic. Each subject was asked to describe his crime in detail. Their stories were taped, transcribed and subjected to computer analysis.

Clues: conjunctions, physical needs, past tense

Psychopaths used more conjunctions like “because,” “since” or “so that,” implying that the crime “had to be done” to obtain a particular goal. They used twice as many words relating to physical needs, such as food, sex or money, while non-psychopaths used more words about social needs, including family, religion and spirituality. Unveiling their predatory nature in their own description, the psychopaths often included details of what they had to eat on the day of their crime.

Psychopaths were more likely to use the past tense, suggesting a detachment from their crimes, say the researchers. They tended to be less fluent in their speech, using more “ums” and “uhs.” The exact reason for this is not clear, but the researchers speculate that the psychopath is trying harder to make a positive impression, needing to use more mental effort to frame the story.

Two text analysis tools were used to examine the crime narratives. Psychopathy was determined using the Psychopathy Checklist-Revised (PCL-R). The Wmatrix linguistic analysis tool was used to examine parts of speech and semantic content while the Dictionary of Affect and Language (DAL) tool was used to examine the emotional characteristics of the narratives.

“Previous work has looked at how psychopaths use language,” Hancock said. “Our paper is the first to show that you can use automated tools to detect the distinct speech patterns of psychopaths.” This can be valuable to clinical psychologists, he said, because the approach to treatment of psychopaths can be very different.

Read more: http://goo.gl/HhtP8

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The mechanism that gives shape to life

Researchers at EPFL (Ecole Polytechnique Fédérale de Lausanne) and the University of Geneva (Unige) have solved the mystery of how genes determines the shape that many animals take.

During the development of an embryo, everything happens at a specific moment. In about 48 hours, it will grow from the top to the bottom, one slice at a time — scientists call this the embryo’s segmentation. “We’re made up of thirty-odd horizontal slices,” explains Denis Duboule, a professor at EPFL and Unige. “These slices correspond more or less to the number of vertebrae we have.”

Every hour and a half, a new segment is built. The genes corresponding to the cervical vertebrae, the thoracic vertebrae, the lumbar vertebrae and the tailbone become activated at exactly the right moment one after another.

DNA acts like a mechanical clock

Very specific genes, known as “Hox,” responsible for the formation of limbs and the spinal column, are involved in this process. “Hox genes are situated one exactly after the other on the DNA strand, in four groups. First the neck, then the thorax, then the lumbar, and so on,” explains Duboule.

The process is astonishingly simple. In the embryo’s first moments, the Hox genes are dormant, packaged like a spool of wound yarn on the DNA. When the time is right, the strand begins to unwind. When the embryo begins to form the upper levels, the genes encoding the formation of cervical vertebrae come off the spool and become activated. Then it is the thoracic vertebrae’s turn, and so on down to the tailbone. The DNA strand acts a bit like an old-fashioned computer punchcard, delivering specific instructions as it progressively goes through the machine.

“A new gene comes out of the spool every 90 minutes, which corresponds to the time needed for a new layer of the embryo to be built,” explains Duboule. “It takes two days for the strand to completely unwind; this is the same time that’s needed for all the layers of the embryo to be completed.” This system is the first “mechanical” clock ever discovered in genetics. And it explains why the system is so remarkably precise.

Player-piano music

The structure of all animals — the distribution of their vertebrae, limbs and other appendices along their bodies — is programmed like a sheet of player-piano music by the sequence of Hox genes along the DNA strand.

The sinuous body of the snake is a perfect illustration. A few years ago, Duboule discovered in these animals a defect in the Hox gene that normally stops the vertebrae-making process. “Now we know what’s happening. The process doesn’t stop, and the snake embryo just keeps on making vertebrae, all identical, until the process just runs out of steam.”

The Hox clock is a demonstration of the extraordinary complexity of evolution. One notable property of the mechanism is its extreme stability, explains Duboule. “Circadian or menstrual clocks involve complex chemistry. They can thus adapt to changing contexts, but in a general sense are fairly imprecise. The mechanism that we have discovered must be infinitely more stable and precise. Even the smallest change would end up leading to the emergence of a new species.”

Read more: http://goo.gl/GwwzC

Robot biologist solves complex problem from scratch

An interdisciplinary team of scientists has taken a major step toward automating the scientific process with the Automated Biology Explorer (ABE) system, which can analyze raw experimental data from a biological system and derive the basic mathematical equations that describe the way the system operates.

According to the researchers at Vanderbilt University, Cornell University and CFD Research Corporation, it is one of the most complex scientific modeling problems that a computer has solved completely from scratch.

The work was a collaboration between John P. Wikswo, the Gordon A. Cain University Professor at Vanderbilt, Michael Schmidt and Hod Lipson at the Creative Machines Lab at Cornell University and Jerry Jenkins and Ravishankar Vallabhajosyula at CFDRC in Huntsville, Ala.

John P. Wikswo, the Gordon A. Cain University Professor at Vanderbilt, has christened the is a unique piece of software called

ABE’s “brain” is software called Eureqa, developed at Cornell in 2009. One of Eureqa’s initial achievements was identifying the basic laws of motion by analyzing the motion of a double pendulum. What took Sir Isaac Newton years to discover, Eureqa did in a few hours when running on a personal computer.

Software derives biochemical equations automatically

The biological system that the researchers used to test ABE is glycolysis, the primary process that produces energy in a living cell. They focused on how yeast cells control glycolytic oscillations because it is one of the most extensively studied biological control systems. ABE derived the equations a priori. The only thing the software knew in advance was addition, subtraction, multiplication and division.

The ability to generate mathematical equations from scratch is what sets ABE apart from Adam, the robot scientist developed by Ross King and his colleagues at the University of Wales at Aberystwyth. Adam runs yeast genetics experiments and made international headlines two years ago by making a novel scientific discovery without direct human input. King fed Adam with a model of yeast metabolism and a database of genes and proteins involved in metabolism in other species. He also linked the computer to a remote-controlled genetics laboratory. This allowed the computer to generate hypotheses, then design and conduct actual experiments to test them.

To give ABE the ability to run experiments like Adam, tbe researchers are urrently developing “laboratory-on-a-chip” technology that can be controlled by Eureqa. This will allow ABE to design and perform a wide variety of basic biology experiments. Their initial effort is focused on developing a microfluidics device that can test cell metabolism.

Why biology needs automation

Biology is more complex than astronomy or physics or chemistry,” maintained John P. Wikswo, the Gordon A. Cain University Professor at Vanderbilt. “In fact, it may be too complex for the human brain to comprehend.”

This complexity stems from the fact that biological processes range in size from the dimensions of an atom to those of a whale and in time from a billionth of a second to billions of seconds. Biological processes also have a tremendous dynamic range: for example, the human eye can detect a star at night that is one billionth as bright as objects viewed on a sunny day.

Then there is the matter of sheer numbers. A cell expresses between 10,000 to 15,000 proteins at any one time. Proteins perform all the basic tasks in the cell, including producing energy, maintaining cell structures, regulating these processes and serving as signals to other cells. At any one time, there can be anywhere from three to 10 million copies of a given protein in the cell.

According to Wikswo, the crowning source of complication is that processes at all these different scales interact with one another: “These multi-scale interactions produce emergent phenomena, including life and consciousness.”

Looked at from a mathematical point of view, to create an accurate model of a single mammalian cell may require generating and then solving somewhere between 100,000 to one million equations.

Balanced against this complexity is the capability of the human brain. The biophysicist cites research that has found that the human brain can only process seven pieces of data at a time and quotes a 1938 assessment of brain research by Emerson Pugh: “If the human brain were so simple that we could understand it, we would be so simple that we couldn’t.”

That is where robot scientists like ABE and Adam come in, Wikswo argues. They have the potential for both generating and analyzing the tremendous amounts of data required to really understand how biological systems work and predict how they will react to different conditions.

Co-evolution

“We set out to work with robots, but our path took us, through many twists and turns, to automating science,” said Hod Lipson at the Creative Machines Lab at Cornell University.

His starting point was an attempt to breed robot control systems using an approach modeled on natural selection, instead of having a programmer code in all the steps. Individual programming had largely broken down as robots became more complex because the robots didn’t perform correctly without extensive and time-consuming debugging.

Lipson used genetic programming for the breeding process. It involves starting with the basic components of a robot, randomly combining them in millions of different configurations and then testing how well they perform by a specific criterion, such as how fast they can move. The designs that work the best are then randomly combined and tested. These steps are repeated until it produces a design that is acceptable. However, this process also proved to be too slow.

So Lipson combined the breeding and the debugging processes in an approach he calls co-evolution. He started with a crude simulator, used it to design a robot, tested the design, and studied how it failed. He used this information to improve the simulator so that it could predict the failure. Then he used the improved simulator to design another robot, tested the design, watched how it failed and improved the simulator once again. Repeating these steps of co-evolving simulators and robots produced increasingly competent designs, he found.

After proving that co-evolution works for robot design, Lipson realized that it could be generalized to solve other problems. Specifically, he adapted it for the mathematical process of curve fitting, more generally called symbolic regression. This involves deriving equations that can describe various data sets. Lipson’s software package, Eureqa, proved to be extremely successful. As the word got around, he began getting requests for copies of the program and decided to make it into a citizen science project, available for anyone to download on the Internet.

“Today, it has more than 20,000 users. People are using it to solve problems in a wide variety of areas including traffic, business and neighborhood problems,” Lipson said. Wikswo says this approach will give scientists the ability to control biological systems even if they can’t completely explain how they work, and will allow for developing significantly improved drugs and other therapies.

Read more: http://goo.gl/icBgM

Future computers that modify themselves

Scientists at Northwestern University have developed a new nanomaterial that can “steer” electrical currents. The development could lead to a computer that can simply reconfigure its internal wiring to become an entirely different device, based on changing needs.

As electronic devices are built smaller and smaller, the materials from which the circuits are constructed begin to lose their properties and begin to be controlled by quantum mechanical phenomena. Reaching this physical barrier, many scientists have begun building 3-D circuits by stacking components on top of one another.

Nanoparticle-based electronics

The Northwestern team has taken a fundamentally different approach. “Our new steering technology allows use to direct current flow through a piece of continuous material,” said Bartosz A. Grzybowski, professor of chemical and biological engineering in the McCormick School of Engineering and Applied Science. “Streams of electrons can be steered in multiple directions through a block of the material — even multiple streams flowing in opposing directions at the same time.”

The Northwestern material combines different aspects of silicon- and polymer-based electronics to create a new class of electronic materials: nanoparticle-based electronics. Imagine a single device that reconfigures itself into a resistor, a rectifier, a diode, or a transistor based on signals from a computer.

The hybrid material is composed of electrically conductive particles, each five nanometers in width, coated with a special positively charged chemical. The particles are surrounded by negatively charged atoms that balance out the positive charges fixed on the particles. By applying an electrical charge across the material, the small negative atoms can be moved and reconfigured, but the relatively larger positive particles are not able to move.

This creates regions of low and high conductance that can be modified; the result is the creation of a directed path that allows electrons to flow through the material. Old paths can be erased and new paths created by pushing and pulling the negative atoms, creating more complex electrical components.

Read more: http://goo.gl/NEKy7

Those scan results are just an app away

Mobile MIM, made by MIM Software, can turn an iPhone or an iPad into a diagnostic medical instrument. It allows physicians to examine scans and to make diagnoses based on magnetic resonance imaging, computed tomography and other technologies if they are away from their workstations.

The app comes in two versions: Mobile MIM, for physicians, and VueMe, for patients. Both are free, though MIM Software charges on a pay-as-you-go basis for storing uploaded scans on its servers, and for letting people view them.

Mobile MIM is among a handful of medical apps that the FDA has cleared for diagnostic use. Many others will probably appear as more smartphones and tablets make their way into the pockets of doctors’ white coats or onto their office desks.

Read more: http://goo.gl/vGxTg

Report on the fourth conference on artificial general intelligence

The Fourth Conference on Artificial General Intelligence (AGI-11) was held on Google’s campus in Mountain View (Silicon Valley), California, in the first week of August 2011. This was the largest AGI conference yet, with more than 200 people attending, and it had a markedly different tone from the prior conferences in the series.

A number of participants noted that there was less of an out-of-the-mainstream, wild-eyed maverick feel to the proceedings, and more of a sense of “business as usual” or “normal science” — a sense in the air that AGI is obviously an important, feasible R&D area to be working on, albeit a bit “cutting-edge” compared to the majority of (more narrowly specialized) AI R&D.

I think this difference in tone was due partly to the Google and Bay Area location, and partly to the fact that the conference was held in close spatiotemporal proximity to two larger and older AI-related conferences, AAAI-11 and IJCNN-11. IJCNN was just before AGI in San Jose, and AAAI was just after AGI in San Francisco — so a number of academic AI researchers who usually go to the larger conferences, but not AGI, decided to try out AGI as well this year. Complementing this academic group, there was also a strong turnout from the Silicon Valley software industry, and the Bay Area futurist and transhumanist community.

Tutorials

The first day of the conference was occupied by tutorials on the LIDA and OpenCog systems, and the Church probabilistic logic programming language. The second day comprised two workshops: one on self-programming in AGI systems, and the next the traditional “Future of AGI” workshop, which was particularly lively due to the prominence of future-of-technology issues in Bay Area culture (the conference site was not so far off from the headquarters of a variety of futurist organizations like Singularity University, the Singularity Institute for AI, the Foresight Institute, etc.). Most of the talks from the Future of AGI workshop have corresponding papers or presentations on the conference’s schedule page — with themes such as

    Steve Omohundro, Design Principles for a Safe and Beneficial AGI Infrastructure
    Anna Salamon, Can Whole Brain Emulation help us build safe AGI?
    Carl Shulman, Risk-averse preferences as AGI safety technique
    Mark Waser, Rational Universal Benevolence: Simpler, Safer, and Wiser than “Friendly AI”
    Itamar Arel, Reward Driven Learning and the Risk of an Adversarial Artificial General Intelligence
    Ahmed Abdel-Fattah & Kai-Uwe Kuehnberger, Remarks on the Feasibility and the Ethical Challenges of a Next Milestone in AGI
    Matt Chapman, Maximizing The Power of Open-Source for AGI
    Ben Goertzel and Joel Pitt, Nine Ways to Bias Open-Source AGI Toward Friendliness

Norvig, Dickmanns, Sloman, Boyden, Shi

The final two days constituted the conference proper, with technical talks corresponding to papers in the conference proceedings, which were published in Springer’s Lecture Notes in AI book series. Videos of the conference talks, including the workshops and tutorials, will be posted by Google during the next months, and linked from the conference website.

Peter Norvig, Google’s head of research and the co-author of the best-selling AI textbook (whose latest edition does mention AGI, albeit quite briefly), gave brief opening remarks. He didn’t announce any grand Google AGI initiatives, making clear that his own current research focus is elsewhere than the direct pursuit of powerful artificial general intelligence. Yet, he also made clear that he sees a lot of the research going on at Google as part of an overall body of work that is ultimately building toward advanced AGI.

The four keynote speeches highlighted different aspects of the AGI field, as well as the strongly international nature of the AGI community.

Ernst Dickmanns, from Germany, reviewed his pioneering work on self-driving cars from the 1980s, which in some ways was more advanced than the current work of self-driving cars being conducted by Google and others. He wrapped up with a discussion of general lessons for AGI implied by his experience with self-driving cars, including the importance of adaptive learning and of “dynamic vision” that performs vision in a manner closely coordinated with action.

Aaron Sloman, from Britain, discussed “toddler theorems” — the symbolic understandings of the world that young children learn and create based on their sensorimotor and cognitive experiences. He challenged the researchers in the audience to understand and model the kind of learning and world-modeling that crows or human babies do, and sketched some concepts that he felt would be useful for this sort of modeling.

MIT’s Ed Boyden reviewed his recent work on optogenetics, one of the most exciting and rapidly developing technologies for imaging the brain — a very important area, given the point raised in the conference’s Special Track on Neuroscience and AGI that the main factor holding back the design of AGI systems based on human brain emulation is currently the lack of appropriate tools for measuring what’s happening in the brain. We can’t yet measure the brain well enough to construct detailed dynamic brain simulations. Boyden’s work is one of the approaches that, step by step, is seeking to overcome this barrier.

Zhongzhi Shi, from the Chinese Academy of Sciences in Beijing, described his integrative AGI architecture, which incorporates aspects from multiple Western AGI designs into a novel overall framework. He also stressed the importance of cloud computing for enabling practical experimentation with complex AGI architectures like the one he described.

Neuroscience and AGI

As well as the regular technical AGI talks, there was a Special Session on Neuroscience and AGI, led by neuroscientist Randal Koene, who is probably the world’s most successful advocate of mind uploading, or what he now calls “substrate independent minds.” Most of the AGI field today is only loosely connected to neuroscience; and yet, in principle, nearly every AGI researcher would agree that careful emulation of the brain is one potential path to AGI, with a high probability of succeeding eventually.

The Special Session served to bring neuroscientists and AGI researchers together, to see what they could learn from each other. Neuroscience is not yet at the point where one can architect an AGI based solely on neuroscience knowledge, yet there are many areas where AGI can draw inspiration from neuroscience.

Demis Hassabis emphasized the fact that AGI currently lacks any strong theories of how sensorimotor processing interfaces with abstract conceptual processing, and suggested some ways that neuroscience may provide inspiration here, e.g., analysis of cortical-hippocampal interactions. Another point raised in discussions was that reinforcement learning could potentially gain inspiration from study of the various ways in which the brain treats internal intrinsic rewards (alerting or surprisingness) comparably to explicit external rewards.

Kurzweil and Solomonoff prizes

Three prizes were awarded at the conference: two Kurzweil Prizes and one Solomonoff Prize.

The Kurzweil Prize for Best AGI Paper was awarded to Linus Gisslen, Matt Luciw, Vincent Graziano and Juergen Schmidhuber for their paper entitled Sequential Constant Size Compressors and Reinforcement Learning. This paper represents an effort to bridge the gap between the general mathematical theory of AGI (which in its purest form applies only to AI programs achieving massive general intelligence via using unrealistically much processing power) and the practical business of building useful AGI programs.

Specifically, one of the key ideas in the general theory of AGI is “reinforcement learning” — learning via reward signals from the environment — but the bulk of the mathematical theory of reinforcement learning makes the assumption that the AI system has complete visibility into the environment. Obviously this is unrealistic — no real-world intelligence has full knowledge of its environment. The award-winning paper describes a novel, creative method of using recurrent neural networks to apply reinforcement learning methods to partially-observable environments — indicating a promising research direction to follow, for those who wish to make reinforcement learning algorithms that scale up to real world problems, such as those human-level AGIs will have to deal with.

The 2011 Kurzweil Award for Best AGI Idea was awarded to Paul Rosenbloom for his paper entitled From Memory to Problem Solving: Mechanism Reuse in a Graphical Cognitive Architecture. Rosenbloom has a long history in the AI field, including a role co-creating the classic SOAR AI architecture in the 1980s. While still supporting the general concepts underlying his older AI work, his current research focuses more heavily on scalable probabilistic methods — but more flexible and powerful ones than Bayes nets, Markov Logic Networks and other current popular techniques.

Extending his previous work on factor graphs as a core construct for scalable uncertainty management in AGI systems, his award-winning paper shows how factor graph mechanisms described for memory can also be used for problem-solving tasks. In the human brain there is no crisp distinction between memory and problem-solving, so it is conceptually satisfying to see AGI approaches that also avoid this sort of crisp distinction. It is yet unclear to what extent any single mechanism can be used to achieve all the capabilities needed for human-level AGI. But it is a very interesting and valuable research direction to take a single powerful and flexible mechanism like factor graphs and see how far one can push it, and Dr. Rosenbloom’s paper comprises a wonderful example of this sort of work.

The 2011 Solomonoff AGI Theory Prize — named in honor of AGI pioneer Ray Solomonoff, who passed away in 2010 — was awarded to Laurent Orseau and Mark Ring, for a pair of papers titled Self-Modification and Mortality in Artificial Agents and Delusion, Survival, and Intelligent Agents. These papers explore aspects of theoretical generally intelligent agents inspired by Marcus Hutter’s AIXI model (a theoretical AGI system that would achieve massive general intelligence using infeasibly much computational resources, but that may potentially be approximated by more feasible AGI approaches).

The former paper considers some consequences of endowing an intelligent agent of this nature with the ability to modify its own code; and the latter analyzes aspects of what happens when this sort of theoretical intelligent agent is interfaced with the real world. These papers constitute important steps in bridging the gap between the abstract mathematical theory of AGI, and the real-world business of creating AGI systems and embedding them in the world.

Hybridization

While there was a lot of strong and interesting research presented at the AGI-11 conference, I think it’s fair to say that there were no dramatic breakthroughs presented. Rather, there was more of a feeling of steady incremental progress. Also, compared to previous years, there was less of a feeling of separate, individual research projects working in a vacuum — the connections between different AI approaches seem to be getting clearer each year, in spite of the absence of a clearly defined common vocabulary or conceptual framework among various AGI researchers.

Links were built between abstract AGI theory and practical work, and between neuroscience and AGI engineering. Hybridization of previously wholly different AGI architectures was reported (e.g., the paper I presented, describing the incorporation of aspects of Joscha Bach’s MicroPsi system in my OpenCog system). All signs of a field that’s gradually maturing.

A Sputnik of AGI

These observations lead me inexorably to some more personal musings on AGI. I can’t help wondering: Can we get to human-level AGI and beyond via step-by-step, incremental progress, year after year?

It’s a subtle question, actually. It’s clear that we are far from having a rigorous scientific understanding of how general intelligence works. At some point, there’s going to be a breakthrough in the science of general intelligence — and I’m really looking forward to it! I even hope to play a large part in it. But the question is: will this scientific breakthrough come before or after the engineering of an AGI system with powerful, evidently near-human-level capability?

It may be that we need a scientific breakthrough in the rigorous theory of general intelligence before we can engineer an advanced AGI system. But … I presently suspect that we don’t. My current opinion is that it should be possible to create a powerful AGI system via proceeding step-by-step from the current state of knowledge — doing engineering inspired by an integrative conceptual, not quite fully rigorous understanding of general intelligence.

If this is right, then we can build a system that will have the impact of a “Sputnik of AGI,” via combining variants of existing algorithms in a reasonable cognitive architecture in a manner guided by a solid conceptual understanding of mind. And then, by studying this Sputnik AGI system and its successors and variants, we will be able to arrive at the foreseen scientific breakthrough in the science of general intelligence. This of course is what my colleagues and I are trying to do with the OpenCog project — but the general point I’m making here is independent of our specific OpenCog AGI design.

Anyway, that’s my personal view of the near- to mid-term future of AGI, which I advocated in asides during my OpenCog tutorial, and various discussions at the Future of AGI Workshop. But my view on these matters is far from universal among AGI researchers — even as the AGI field matures and becomes less marginal, it is still characterized by an extremely healthy diversity of views and attitudes! I look forward to ongoing discussions of these matters with my colleagues in the AGI community as the AGI conference series proceeds and develops.

Mostly, it’s awesome to even have a serious AGI community. It’s hard sometimes to remember that 10 years ago this was far from the case!

Read more: http://goo.gl/FV90i

Another faster-than-light neutrinos challenge

This just in: a new critique of the CERN OPERA finding of faster-than-light neutrinos. In “New Constraints on Neutrino Velocities,” Cohen and Glashow argue that the high-energy (17.5 GeV) superluminal muon neutrinos would actually lose energy rapidly (down to about 12.5GeV) on the 730km trip, long before arriving in Italy.

But that didn’t happen. Ergo, the neutrino weren’t really traveling faster than light, say Cohen and Glashow. So how would they lose energy? By bremsstrahlung (conversion of neutrino energy to light, as seen in Cherenkov radiation in nuclear reactors).

Neutrino physicist Dr. Ben Still’s Neutrino Blog has a lucid explanation. Also see his description of why the supernova explosion in 1987 didn’t show evidence of faster-than-light neutrinos, Supernova Neutrinos in 1983 and 1987?, and his critique of the OPERA experiment: Not Feeling Very Energetic.

Read more: http://goo.gl/2w717

What just happened? Why some of us seem totally spaced out

Ever wonder why uncle Louie seems to imagine stuff that didn’t happen, and calls you crazy? Well now’s there’s an explanation.

Half of you won’t like it, I warn you.

A new study of the brain by University of Cambridge scientists explains why some people can’t tell the difference between what they saw and what they imagined or were told about — such as whether they or another person said something, or whether an event was imagined or actually occurred.

Turns out it results from a normal variation in a fold at the front of the brain called the paracingulate sulcus (PCS), the scientists said.

Who you gonna believe? Me, or your lying memory?

This brain variation is present in roughly half of the normal population. It’s one of the last structural folds to develop before birth, so it varies greatly in size between individuals in the healthy population. The researchers discovered that adults whose MRI scans indicated an absence of the PCS were significantly less accurate on memory tasks than people with a prominent PCS on at least one side of the brain.

Interestingly, all participants believed that they had a good memory despite one group’s memories being clearly less reliable. OK, but the question is: if you explain this to them, do they back off from their alleged memories?

“Additionally, this finding might tell us something about schizophrenia, in which hallucinations are often reported whereby, for example, someone hears a voice when nobody’s there,” said Dr. Jon Simons from the University of Cambridge’s Department of Experimental Psychology and Behavioural and Clinical Neuroscience Institute. “Difficulty distinguishing real from imagined information might be an explanation for such hallucinations.”

That might explain UFOs. (Especially if they watched Close Encounters of the Third Kind one too many times.)

Take this MRI test (if you dare)

For the study, the researchers recruited 53 healthy volunteers based on their brain scans which showed either a clear presence or absence of the PCS in the left or right brain hemisphere. Participants were presented either with well-known word-pairs like “Laurel and Hardy” or with the first word of a word-pair and a question mark (“Laurel and ?”). In the latter condition, participants were instructed to imagine the second word of the word-pair. Then, either they or the experimenter was instructed to read the word-pair out aloud.

After a delay, a memory test was given where participants tried to remember whether they had seen or imagined the second word of each previously-encountered word-pair, or whether they or the experimenter had read the word-pair out aloud. Participants with absence of the PCS in both brain hemispheres scored significantly worse than the others at remembering both kinds of detail.

Read more: http://goo.gl/pEdCu

Singularity Summit 2011 roundup

The tone of the Singularity Summit 2011 in New York was set by Ray Kurzweil, who presented many examples of accelerating developments, countering the arguments presented by Microsoft’s co-founder Paul Allen in a recent article, The Singularity Isn’t Near.

Robots vs. humans

James McLurkin introduced the concept of swarms of small, light, and cheap robots that communicate with each other, solve problems collaboratively, and call others for help. He wowed the audience with a demo of a flock of small wheeled robots following each other, aligning and dispersing on the podium. A single robot can be assembled with a low-cost kit and programmed with Python, he said. Practical uses aside, McLurkin believes his system can also trigger a revolution in engineering education by permitting students and hobbyists to link their individual robots and experiment with new programming and problem-solving paradigms.

Riley Crane suggested that swarms of communicating persons, can solve complex crowdsourced problems better than robots. The people must be “programmed” with suitable incentives (cash or social reputation, for example) and provided with suitable communication tools like Twitter (proven effective in humanitarian relief operations).

Sharon Bertsch McGrayne presented Bayesian reasoning as a rational method for analyzing data and making decisions.

Christof Koch discussed the search for neural correlates of consciousness. Rather than than general self-awareness, he is more interested in consciousness of something, which does not require emotions, long term memory, language, or selective attention. He suggested that consciousness should be seen as a continuum, rather than discrete. He pointed out that Tononi’s “measure” assigns a high value to fully interrelated states of consciousness that cannot be easily decomposed in parts. As an example, Koch suggested that identifying “impossible” pictures, such as a picture containing subtly wrong perspectives or impossible situations (e.g. a person levitating) may be a good criterion for consciousness.

Singularity Institute Research Fellow Eliezer Yudkowsky, and D. Scott Brown and Dileep George, co-founders of Vicarious, discussed their approach to AI. And David Ferrucci, Dan Cerutti (both from IBM) and Jeopardy! winner Ken Jennings discussed the implications of the Watson Jeopardy! victory.

Most speakers were optimistic about the eventual development of human-level (or higher) AI. Alexander Wissner-Gross suggested that the first true AI could emerge on a planetary scale from the developing system of interlocked exchanges for high-frequency financial trading, which could be seen as a developing global “brain” already operating at relativistic speeds.

The big picture

Stephen Wolfram

Stephen Wolfram described computational universes, from simple cellular automata rules to complex simulations, and suggested that perhaps a universe could be generated by a simple program, yet show all the complexity of our universe to observers living inside. Max Tegmark suggested that we are probably alone in the part of the universe that we can access, whose evolution and emergence to life and intelligence could then be seen as our task.

One task for the Singularity community suggested by science fiction author David Brin would be to seek a dialog with religious people. The Tower of Babel, commonly interpreted as a punishment for human hubris, could actually be seen as an encouragement to spread around the Earth and gain more experience before attempting to become gods, he suggested. Jason Silva, a filmmaker and founding producer/host for Current TV, took it a step further, suggesting we make futurism more appealing and sexy.

Optimists vs. pessimists

Macroeconomics, the roles of free markets and government programs, and innovation mechanisms played a more important role than in previous Summits, with frequent references to the social protests at Occupy Wall Street a few miles away. Skype founder Jaan Tallinn welcomed the emergence of new social movements of people interested in the long term future and the welfare of future societies. He praised one of the silent heroes of recent history, Stanislav Petrov, who by deviating from standard Soviet protocol and correctly identifying a missile attack warning as a false alarm on September 26, 1983 may have single-handedly prevented a major conflict.

After stating that there are not enough public discussions about the future, Peter Thiel defended real innovation against the current trend of letting emerging market cheaply produce products and services copied from past innovations (he referred to this concept as vertical innovation vs. horizontal globalization). He advised the many entrepreneurs at the Summit to base their businesses on compelling mission stories, both unique and doable.

John Mauldin predicted that a next big innovation wave will arise from wireless connectivity, sovereign individuals empowered to make their own decisions, biotechnology, nanotechnology, robotics, AI, and new sources of energy, and Michael Shermer presented evidence that our world is indeed nicer than the world of our grandfathers, and that this trend will continue.

Tyler Cowen presented a less enthusiastic view in his talk (and in a following debate with Singularity Institute President Michael Vassar), suggesting that we may be in a stagnation phase.

Biomed advances

Sonia Arrison

Sonia Arrison said medical advances could nearly double human life expectancy in the next few decades and suggested ways for society to cope with increased lifespans. Stephen Badylak gave an overview of advances in tissue engineering, regenerative medicine, and biological scaffolding able to help tissues to heal themselves. Dmitry Itskov described Russian plans to develop humanoid avatar bodies within this decade, followed by human brain transplants and mind uploading in a few decades.

Read more: http://goo.gl/zXScj

Time reversal: A simple particle could reveal new physics

UA theoretical physicist Bira van Kolck has found that experimenting with a deuteron, a simple atomic nucleus, could lead to understanding a mysterious phenomenon of subatomic physics known as time reversal violation. (Photo by Daniel Stolte/UANews)

(PhysOrg.com) -- A simple atomic nucleus could reveal properties associated with the mysterious phenomenon known as time reversal and lead to an explanation for one of the greatest mysteries of physics: the imbalance of matter and antimatter in the universe.

The physics world was rocked recently by the news that a class of subatomic particles known as neutrinos may have broken the speed of light.

Adding to the rash of new ideas, University of Arizona theoretical physicist Bira van Kolck recently proposed that experiments with another small particle called a deuteron could lead to an explanation for one of the most daunting puzzles physicists face: the imbalance of matter and antimatter in the universe.

A deuteron is a simple atomic nucleus, or the core of an atom. Its simplicity makes it one of the best objects for experiments in nuclear physics.

A property of the deuteron known as a magnetic quadrupole moment could reveal sources of a phenomenon known as time reversal violation, Van Kolck and his collaborators, including recently graduated UA doctoral student Emanuele Mereghetti, show in a recent paper published in Physical Review Letters.

Most of what physicists know about the universe can be described by what is called the standard model of particle physics. Developed by Van Kolck's former doctoral advisor, Nobel Laureate Steven Weinberg, the standard model describes everything from Newton's laws of motion to the behavior of subatomic particles with what is known as quantum mechanics.

"This theory explains almost everything we know about the universe up to this point," said Van Kolck. "However," he added, "there is one problem that the standard model does not explain."

"Like the protons and neutrons – the particles making up the nucleus of an atom – every particle has what's called an antiparticle, things like antiprotons or antineutrons. The universe seems to have many more particles than antiparticles," said Van Kolck. "So there is a question of why the universe seems to have such an asymmetry between particles and antiparticles."

Because a deuteron consists of two subatomic particles, it is not considered to be a particle by nuclear physicists. A deuteron technically is an atomic nucleus, or the core of an atom, but unlike more complex nuclei, the deuteron consists of just one positively charged particle called a proton and one neutral particle called a neutron. (Image courtesy of Thomas Jefferson National Accelerator Facility)

"The current indication is that the universe started from a very concentrated state, which some people call the Big Bang, and evolved from that. It would be appealing if we could show that the universe started with a balanced number of particles and antiparticles and that the fact that we observe more particles now can be explained in the process of evolution of the universe."

When things don't look balanced, physicists ask why. The explanation may lie in a rare violation of the phenomenon of time reversal.

Time reversal?

"Let's suppose you're playing billiards," said Van Kolck. "You have two balls and you knock them against each other on the table. Suppose you film this, but you play the movie in reverse. If you don't tell the person who is watching which version is forward and which is backward, the person wouldn't be able to tell."

Just as in the movie, time can be reversed in the equations that describe our world and the equations still balance.

For example, the maximum speed of your car is the miles it can cover per hour, or to a physicist, distance divided by time. If time is reversed so that it becomes a negative number, the equation still balances because the magnitudes of the speed and distance stay the same.

But wait a minute, you say. Time only goes one way: People get older, not younger.

"This is an apparent direction of time," said Van Kolck. "It has to do with the initial conditions. We can have laws of physics that work both ways and still give rise to phenomena that have a direction of time."

"Let me continue with this example of the billiard balls," said Van Kolck. "When you start a game there is a triangle of balls in the middle, and someone shoots a ball into this cluster causing all the balls to scatter. If you play that movie in reverse, most people would say that there was a direction of the original movie, because it would be very unlikely that you could start all the balls with the right velocity so that they collide, all of them stop in a triangle and one comes out."

"The reason why we perceive a preferred direction has to do with the fact that it is much easier to go from a simple initial state then from a very complicated state," said Van Kolck. So time can be reversed in physics equations without affecting the result, but the effects of time reversal remain unperceivable in our everyday lives.

"Until the 1960s, physicists thought that the laws of physics were exactly invariant in the transformation of time going to minus time," said Van Kolck. "Then it was discovered that there are some phenomena involving subatomic particles where there seems to be a very tiny violation of this symmetry."

In other words, if you made a movie of the billiard balls and played it in reverse, the backward version actually would be a little bit different from the forward version – like a "glitch in the matrix."

"It's like the process of some things happening in one direction versus the opposite one doesn't happen at the same rate," said Van Kolck. This phenomenon is known as time reversal violation.

When time reversal is violated, the equation doesn't balance out; your car doesn't go as fast on the way back. It is this imbalance that physicists believe may explain the unequal amounts of matter and antimatter in the universe.

Since physicists first started looking for sources of time reversal violation in subatomic particles, they have been measuring properties of particles known as electric dipole moments, or EDMs.

An EDM is generated by a property of subatomic particles known as spin. Spin can be visualized as a particle spinning around its center rather like the Earth rotates around its axis.

With time reversal, the spin would appear to reverse, like a movie of the particle played backward. But for the equations to balance, the EDM would have to equal zero. Any non-zero value would generate a different outcome of the equations – the backward version of the movie actually would be different from the forward version.

"Physicists have looked for EDMs of particles because if you measure one, you know that time reversal is violated," said Van Kolck. "We know that there is a tiny bit of time reversal violation in the standard model. But it doesn't seem sufficient to explain the matter-antimatter asymmetry, because that violation of time reversal is very small. So we are looking for sources that would make other processes where we would see this phenomenon."

However: "Measuring the EDMs alone doesn't tell you a whole lot," said Van Kolck. "It tells you some, but what we show is that if you can measure another property of the deuteron, called the magnetic quadrupole moment, then you can tell a whole lot more about the mechanism."

"Like the electric dipole, the magnetic quadrupole violates time-reversal symmetry," said Van Kolck. He and his collaborators identified mechanisms of time reversal violation that correspond to different measurements of magnetic quadrupole moments for the deuteron.

"Nobody had pointed out before that this would be such an effective way to separate these mechanisms," said Van Kolck. "We are proposing that people try to measure the magnetic quadrupole moment to understand the source of time reversal violation."

Unveiling previously unknown sources of t-violation could lead to an explanation for one of the greatest questions physicists face: the reason for the imbalance of matter and antimatter in the universe.

Experiments with the deuteron would probe the same scales of energy as the Large Hadron Collider at CERN, the European Organization for Nuclear Research, and could lead to completely new discoveries in physics, Van Kolck said: "It's a different way to look for physics beyond the standard model."

Read more: http://goo.gl/GwTo4

Monday, October 17, 2011

In a recent article in Technology Review about the technological Singularity, it is reasoned:

“…Futurists like Vernor Vinge and Ray Kurzweil have argued that the world is rapidly approaching a tipping point, where the accelerating pace of smarter and smarter machines will soon outrun all human capabilities. They call this tipping point the singularity, because they believe it is impossible to predict how the human future might unfold after this point. Once these machines exist, Kurzweil and Vinge claim, they'll possess a superhuman intelligence that is so incomprehensible to us that we cannot even rationally guess how our life experiences would be altered. Vinge asks us to ponder the role of humans in a world where machines are as much smarter than us as we are smarter than our pet dogs and cats. Kurzweil, who is a bit more optimistic, envisions a future in which developments in medical nanotechnology will allow us to download a copy of our individual brains into these superhuman machines, leave our bodies behind, and, in a sense, live forever. It's heady stuff ….. While we suppose this kind of singularity might one day occur, we don't think it is near. In fact, we think it will be a very long time coming. Kurzweil disagrees, based on his extrapolations about the rate of relevant scientific and technical progress. He reasons that the rate of progress toward the singularity isn't just a progression of steadily increasing capability, but is in fact exponentially accelerating—what Kurzweil calls the ‘Law of Accelerating Returns.’ He writes that:

‘...SO WE WON'T EXPERIENCE 100 YEARS OF PROGRESS IN THE 21ST CENTURY—IT WILL BE MORE LIKE 20,000 YEARS OF PROGRESS (AT TODAY'S RATE). The 'returns,' such as chip speed and cost-effectiveness, also increase exponentially. There's even exponential growth in the rate of exponential growth. Within a few decades, machine intelligence will surpass human intelligence, leading to The Singularity’ ...”

Source: http://goo.gl/LP4CU

Monday, October 10, 2011

Graphene ‘Big Mac’ may replace silicon chips, say graphene discoverers

By interleaving two sheets of graphene with another two-dimensional material, boron nitrate, University of Manchester scientists have created the graphene “Big Mac” — a four-layered structure that could replace the silicon chip.

The structure allowed the researchers for the first time to observe how graphene behaves when unaffected by the environment.

The structure’s properties could lead to flexible touch-screen phones and computers, lighter aircraft, wallpaper-thin HDTV sets, and superfast Internet connections.

Graphene, the world’s thinnest, strongest, and most conductive material, was discovered at the University of Manchester in 2004 by Professor Andre Geim and Professor Kostya Novoselov, winning the two scientists the Nobel Prize for Physics last year.

Read more: http://goo.gl/WyD9v

Brain imaging reveals why we remain optimistic in the face of reality

People who are very optimistic about the outcome of events tend to learn only from information that reinforces their rose-tinted view of the world, related to a “faulty” function of their frontal lobes, researchers at the Wellcome Trust Centre for Neuroimaging at UCL (University College London) have shown.

This is a problem that has puzzled scientists for decades: why is human optimism is so pervasive, when reality continuously confronts us with information that challenges these biased beliefs? In this new study, the researchers found this due to errors in how we process the information in our brains.

Nineteen volunteers were presented with a series of negative life events, such as car theft or Parkinson’s disease, while lying in a functional magnetic resonance imaging (fMRI) scanner, which measures activity in the brain. They were asked to estimate the probability that this event would happen to them in the future. After a short pause, the volunteers were told the average probability of this event to occur. In total, the participants saw eighty such events.

After the scanning sessions, the participants were asked once again to estimate the probability of each event occurring to them. They were also asked to fill in a questionnaire measuring their level of optimism.

The researchers found that people did, in fact, update their estimates based on the information given, but only if the information was better than expected. For example if they had predicted that their likelihood of suffering from cancer was 40%, but the average likelihood was 30%, they might adjust their estimate to 32%. If the information was worse than expected — for example, if they had estimated 10% — then they tended to adjust their estimate much less, as if ignoring the data.

The results of the brain scans suggested why this might be the case. All participants showed increased activity in the frontal lobes of the brain when the information given was better than expected, this activity actively processed the information to recalculate an estimate.

However, when the information was worse than estimated, the more optimistic a participant was (according to the personality questionnaire), the less efficiently activity in these frontal regions coded for it, suggesting they were disregarding the evidence presented to them.

For example, “many experts believe the financial crisis in 2008 was precipitated by analysts overestimating the performance of their assets even in the face of clear evidence to the contrary,” said researcher Dr. Tali Sharot of UCL.

Read more: http://goo.gl/7QxRC

Stem-cell reprogramming method not to blame for mutations: Scripps scientists

Scientists at the Scripps Research Institute have discovered that a reprogramming method is not to blame for dangerous mutations found within Induced Pluripotent Stem Cells (iPSC) — adult stem cells that have been genetically coaxed into behaving like embryonic stem cells. The discovery may help narrow down the exact cause of the mutations, long a roadblock to iPSC’s widespread use.

There have been a number of puzzling genetic mutations in iPSCs that some scientists say call into question just how reliable non-embryonic stem cells are. Some believe that the mutations might be caused by current reprogramming techniques. While little is known about how these mutations would effect how the cells could be used in medicine, it has made researchers cautious as they develop reprogrammed adult cells into treatments. Many, in fact, use embryonic stem cells in tandem to check their work.

Eliminating DNA mutations

Now, Kristin Baldwin, associate professor at The Scripps Research Institute’s Dorris Neuroscience Center, said their research shows that fears over the reprogramming method may be unwarranted.

“We’ve shown that the standard reprogramming method can generate induced pluripotent stem cells that have very few DNA structural mutations, which are often linked to dangerous cell changes such as tumorigenesis,” said Baldwin, whose lab collaborated with Ira M. Hall, an assistant professor of biochemistry and molecular genetics at the University of Virginia.

To push adult stem cells taken from the patient into behaving like embryonic ones, scientists insert four special genes. The Scripps Research team followed this process, but sought to minimize other potential sources of DNA mutations that might have influenced some previously reported results. The donor cells they selected were not decades-old human skin cells, but relatively error-free fibroblast cells from fetal mice. The researchers also kept these fibroblast cells only briefly in lab dishes before reprogramming them.

New chromosomal error-mapping methods

They used sensitive new chromosomal error-mapping methods to distinguish which mutations were present in rare donor fibroblast cells vs. which ones were newly acquired during reprogramming. Instead of finding more mutations, they found almost none. “We sequenced three iPSC lines at very high resolution, and were surprised to find that very few changes to the chromosomal sequence had appeared during reprogramming,” said Michael J. Boland, a research associate in the Scripps Research Baldwin lab

Some of the mutations seen in human iPSCs in previous studies might have been due to incomplete reprogramming that impaired the cells’ DNA-maintenance mechanisms. In this study using mouse iPSCs, however, there was no doubt that a complete reprogramming to an embryonic state had occurred.

Baldwin’s lab now is trying to determine whether a reprogramming method similar to the one used with mouse iPSCs in this study could also yield relatively error-free human iPSCs. “If our results with these mouse cells are applicable to human cells, then selecting better donor cells and using more sensitive genome-survey techniques should allow us to identify reprogramming methods that can produce human iPSCs that will be safer or more useful for therapies than current lines,” she said.

Read more: http://goo.gl/gKE6o

Thursday, October 6, 2011

Faster-than-light neutrinos? New answers flood in

Swifter than a speeding neutrino they were not, but explanations for the news that subatomic particles apparently travelled faster than light have still arrived remarkably fast.

"It is really impressive how many papers there are so quickly," says mathematician Peter Woit, author of the physics blog Not Even Wrong. "It is kind of standard procedure--when there's some new exciting experimental results, everyone wants to be the first to explain it. But this seems a bit even more so than usual."

On 23 September, physicists with the OPERA experiment in Italy said they had caught neutrinos arriving from the CERN particle physics lab in Switzerland 60 nanoseconds sooner than light. That seemed to violate Einstein's theory of special relativity.

Virtual robbery

Since then, papers have gushed into the physics preprint website (arxiv.org) suggesting numerous ways to account for the extraordinary claim.

Some knock the result. Nobel laureate Sheldon Glashow and colleagues point out that faster-than-light neutrinos ought to produce shock waves, which in turn would produce "virtual" particles that should rob the neutrinos of energy (arxiv.org/abs/1109.6562). If they were ever faster than light, they wouldn't stay at that speed for long enough to account for OPERA's results.

Others potential flaws are more prosaic: some papers try to pinpoint hidden sources of error, like a mis-synchronisation of the clocks at either end of the neutrino beam (arxiv.org/abs/1109.6160).

Still others explore ways in which the OPERA results line up, or conflict with earlier limits on neutrinos' flight speeds, from supernova SN1987a, for example (arxiv.org/abs/1109.5682, arxiv.org/abs/1109.5917) and other detectors.

Monkeys on a typewriter

But the majority of papers hunt for ways that would allow the result to be right. As well as several proposing shortcuts through extra dimensions (arxiv.org/abs/1109.6354 and arxiv.org/abs/1109.6282) – a suggestion that was also mooted shortly after the neutrino announcement - explanations include neutrinos that move faster through the Earth than through space (arxiv.org/abs/1109.664), the notion that neutrinos might slice through dark matter while photons of light are slowed by the interaction (arxiv.org/abs/1109.6520), and the idea that a neutrino's speed depends on its direction and the time of day (arxiv.org/abs/1109.6296).

"At present, it would be foolhardy to say one [theory] looks better than the other," says CERN theorist John Ellis. "And they're probably all wrong, because the result will probably evaporate."

The number of explanations is useful, though. "Scientific conviction comes primarily from experimental results, but it's also the job of us theorists to, if you like, bash out all the possibilities, like monkeys on a typewriter," he says.

Read more: http://goo.gl/p5154

Tributes for Steve Jobs, the man who tamed technology

The death yesterday of the technologist and inventor Steve Jobs, co-founder of Apple, has roused a torrent of tributes from friends, colleagues, politicians and even his firm's regular adversaries in the patent courts.

Jobs was an unstinting promoter of technology that is both easy and compelling to use, and famously intolerant of any product ideas that got in the way of that basic tenet. From the Macintosh computer to the iPod, iPhone and iPad, his insistence on usability at all costs has made Apple the watchword for friendly tech: as his Apple co-founder Steve Wozniak told the BBC.

"He knew what made sense in a product," said Wozniak.

The White House concurs.

"By making computers personal and putting the internet in our pockets, he made the information revolution not only accessible but intuitive and fun," US president Barack Obama said today.

Microsoft cofounder Bill Gates, Jobs's 1980s rival who later invested in Apple when it hit trouble, described working with him as "an insanely great honour". "The world rarely sees someone who made such a profound impact."

At movie studio Pixar, chief creative officer John Lasseter said: "Steve took a chance on us and believed in our crazy dream of computer-animated films; the one thing he always said was to simply, 'Make it great'... He will forever be part of Pixar's DNA."

Tributes to Jobs continue to pour in - including one from Samsung, a firm with which Apple is currently embroiled in a bitter patent lawsuit.

Diagnosed with pancreatic cancer in 2004, Jobs had a liver transplant in 2009 - and in gratitude to the young donor, who had been killed in a motorbike accident, he afterwards urged that everyone should consider joining organ donor programmes.

Read more: http://goo.gl/DmGyj

Wednesday, October 5, 2011

“…The big work behind business judgement is in finding and acknowledging the facts and circumstances concerning technology, the market, and the like in their continuously changing forms. The rapidity of modern technological change makes the search for facts a permanently necessary feature …”

─ By Alfred P. Sloan Jr., My Years with General Motors │ Source: Business @ the Speed of Thought: Using a Digital Nervous System - Bill Gates (Author) -- (March 24, 1999) ─ ISBN-13: 978-0446525688

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ORGANIZATIONS .. I HAVE WORKED WITH !

(¯`*•. As a consultant, manager and strategist, Andres has worked with institutions such as:

► Toyota,
► Mitsubishi,
► World Bank,
► Shell,
► Statoil,
► Total,
► Exxon,
► Mobil,
► Citgo,
► PDVSA,
► GE,
► GMAC,
► TNT Delivery Express,
► GTE,
► Amoco,
► BP,
► Abbot Laboratories,
► World Health Organization,
► Ernst Young Consulting,
► SAIC (Science Applications International Corporation),
► Pak Mail,
► Wilpro (Williams Company),
► Phillips Petroleum Company,
► Dupont,
► Conoco,
► ENI (Italy’s petroleum state-owned firm),
► Chevron, and
► LDG Management (HCC Benefits).

NASA's VISION-21 Symposium

The VISION-21 Symposium sponsored by NASA Lewis Research Center and the Ohio Aerospace Institute, March 30-31, 1993.

The original version of this article was presented at the VISION-21 Symposium sponsored by NASA Lewis Research Center and the Ohio Aerospace Institute, March 30-31, 1993. A slightly changed version appeared in the Winter 1993 issue of Whole Earth Review.

Vernor Vinge

Department of Mathematical Sciences

San Diego State University

(This article may be reproduced for noncommercial purposes if it is copied in its entirety, including this notice.)

Abstract

Within thirty years, we will have the technological means to create superhuman intelligence. Shortly after, the human era will be ended.

Is such progress avoidable? If not to be avoided, can events be guided so that we may survive? These questions are investigated. Some possible answers (and some further dangers) are presented.

What is The Singularity?

The acceleration of technological progress has been the central feature of this century. I argue in this paper that we are on the edge of change comparable to the rise of human life on Earth. The precise cause of this change is the imminent creation by technology of entities with greater than human intelligence.

There are several means by which science may achieve this breakthrough (and this is another reason for having confidence that the event will occur):

There may be developed computers that are "awake" and superhumanly intelligent. (To date, there has been much controversy as to whether we can create human equivalence in a machine. But if the answer is "yes, we can", then there is little doubt that beings more intelligent can be constructed shortly thereafter.)

Large computer networks (and their associated users) may "wake up" as a superhumanly intelligent entity.

Computer/human interfaces may become so intimate that users may reasonably be considered superhumanly intelligent.

Biological science may provide means to improve natural human intellect.

The first three possibilities depend in large part on improvements in computer hardware. Progress in computer hardware has followed an amazingly steady curve in the last few decades [17]. Based largely on this trend, I believe that the creation of greater than human intelligence will occur during the next thirty years. (Charles Platt [20] has pointed out that AI enthusiasts have been making claims like this for the last thirty years. Just so I'm not guilty of a relative-time ambiguity, let me more specific: I'll be surprised if this event occurs before 2005 or after 2030.)

What are the consequences of this event? When greater-than-human intelligence drives progress, that progress will be much more rapid. In fact, there seems no reason why progress itself would not involve the creation of still more intelligent entities -- on a still-shorter time scale.

The best analogy that I see is with the evolutionary past: Animals can adapt to problems and make inventions, but often no faster than natural selection can do its work -- the world acts as its own simulator in the case of natural selection. We humans have the ability to internalize the world and conduct "what if's" in our heads; we can solve many problems thousands of times faster than natural selection.

Now, by creating the means to execute those simulations at much higher speeds, we are entering a regime as radically different from our human past as we humans are from the lower animals.

From the human point of view this change will be a throwing away of all the previous rules, perhaps in the blink of an eye, an exponential runaway beyond any hope of control.

Developments that before were thought might only happen in "a million years" (if ever) will likely happen in the next century. (In [5], Greg Bear paints a picture of the major changes happening in a matter of hours.)

I think it's fair to call this event a singularity ("the Singularity" for the purposes of this paper). It is a point where our old models must be discarded and a new reality rules. As we move closer to this point, it will loom vaster and vaster over human affairs till the notion becomes a commonplace.

Yet when it finally happens it may still be a great surprise and a greater unknown. In the 1950s there were very few who saw it: Stan Ulam [28] paraphrased John von Neumann as saying:

One conversation centered on the ever accelerating progress of technology and changes in the mode of human life, which gives the appearance of approaching some essential singularity in the history of the race beyond which human affairs, as we know them, could not continue.

Von Neumann even uses the term singularity, though it appears he is thinking of normal progress, not the creation of superhuman intellect. (For me, the superhumanity is the essence of the Singularity. Without that we would get a glut of technical riches, never properly absorbed (see [25]).)

In the 1960s there was recognition of some of the implications of superhuman intelligence. I. J. Good wrote [11]:

Let an ultraintelligent machine be defined as a machine that can far surpass all the intellectual activities of any any man however clever.

Since the design of machines is one of these intellectual activities, an ultraintelligent machine could design even better machines; there would then unquestionably be an "intelligence explosion," and the intelligence of man would be left far behind.

Thus the first ultraintelligent machine is the _last_ invention that man need ever make, provided that the machine is docile enough to tell us how to keep it under control. ... It is more probable than not that, within the twentieth century, an ultraintelligent machine will be built and that it will be the last invention that man need make.

Good has captured the essence of the runaway, but does not pursue its most disturbing consequences. Any intelligent machine of the sort he describes would not be humankind's "tool" -- any more than humans are the tools of rabbits or robins or chimpanzees.

Through the '60s and '70s and '80s, recognition of the cataclysm spread [29] [1] [31] [5].

Perhaps it was the science-fiction writers who felt the first concrete impact. After all, the "hard" science-fiction writers are the ones who try to write specific stories about all that technology may do for us.

More and more, these writers felt an opaque wall across the future. Once, they could put such fantasies millions of years in the future [24]. Now they saw that their most diligent extrapolations resulted in the unknowable ... soon. Once, galactic empires might have seemed a Post-Human domain. Now, sadly, even interplanetary ones are.

What about the '90s and the '00s and the '10s, as we slide toward the edge? How will the approach of the Singularity spread across the human world view? For a while yet, the general critics of machine sapience will have good press.

After all, till we have hardware as powerful as a human brain it is probably foolish to think we'll be able to create human equivalent (or greater) intelligence. (There is the far-fetched possibility that we could make a human equivalent out of less powerful hardware, if we were willing to give up speed, if we were willing to settle for an artificial being who was literally slow [30].

But it's much more likely that devising the software will be a tricky process, involving lots of false starts and experimentation. If so, then the arrival of self-aware machines will not happen till after the development of hardware that is substantially more powerful than humans' natural equipment.)

But as time passes, we should see more symptoms. The dilemma felt by science fiction writers will be perceived in other creative endeavors. (I have heard thoughtful comic book writers worry about how to have spectacular effects when everything visible can be produced by the technologically commonplace.)

We will see automation replacing higher and higher level jobs. We have tools right now (symbolic math programs, cad/cam) that release us from most low-level drudgery.

Or put another way: The work that is truly productive is the domain of a steadily smaller and more elite fraction of humanity. In the coming of the Singularity, we are seeing the predictions of _true_ technological unemployment finally come true.

Another symptom of progress toward the Singularity: ideas themselves should spread ever faster, and even the most radical will quickly become commonplace.

When I began writing science fiction in the middle '60s, it seemed very easy to find ideas that took decades to percolate into the cultural consciousness; now the lead time seems more like eighteen months. (Of course, this could just be me losing my imagination as I get old, but I see the effect in others too.)

Like the shock in a compressible flow, the Singularity moves closer as we accelerate through the critical speed.

And what of the arrival of the Singularity itself? What can be said of its actual appearance? Since it involves an intellectual runaway, it will probably occur faster than any technical revolution seen so far.

The precipitating event will likely be unexpected -- perhaps even to the researchers involved. ("But all our previous models were catatonic!

We were just tweaking some parameters....") If networking is widespread enough (into ubiquitous embedded systems), it may seem as if our artifacts as a whole had suddenly wakened.

And what happens a month or two (or a day or two) after that? I have only analogies to point to: The rise of humankind. We will be in the Post-Human era. And for all my rampant technological optimism, sometimes I think I'd be more comfortable if I were regarding these transcendental events from one thousand years remove ... instead of twenty.

Can the Singularity be Avoided?

Well, maybe it won't happen at all: Sometimes I try to imagine the symptoms that we should expect to see if the Singularity is not to develop.

There are the widely respected arguments of Penrose [19] and Searle [22] against the practicality of machine sapience. In August of 1992, Thinking Machines Corporation held a workshop to investigate the question "How We Will Build a Machine that Thinks" [27].

As you might guess from the workshop's title, the participants were not especially supportive of the arguments against machine intelligence.

In fact, there was general agreement that minds can exist on nonbiological substrates and that algorithms are of central importance to the existence of minds.

However, there was much debate about the raw hardware power that is present in organic brains. A minority felt that the largest 1992 computers were within three orders of magnitude of the power of the human brain.

The majority of the participants agreed with Moravec's estimate [17] that we are ten to forty years away from hardware parity.

And yet there was another minority who pointed to [7] [21], and conjectured that the computational competence of single neurons may be far higher than generally believed.

If so, our present computer hardware might be as much as _ten_ orders of magnitude short of the equipment we carry around in our heads. If this is true (or for that matter, if the Penrose or Searle critique is valid), we might never see a Singularity.

Instead, in the early '00s we would find our hardware performance curves beginning to level off -- this because of our inability to automate the design work needed to support further hardware improvements.

We'd end up with some _very_ powerful hardware, but without the ability to push it further.

Commercial digital signal processing might be awesome, giving an analog appearance even to digital operations, but nothing would ever "wake up" and there would never be the intellectual runaway which is the essence of the Singularity.

It would likely be seen as a golden age ... and it would also be an end of progress. This is very like the future predicted by Gunther Stent. In fact, on page 137 of [25], Stent explicitly cites the development of transhuman intelligence as a sufficient condition to break his projections.

But if the technological Singularity can happen, it will. Even if all the governments of the world were to understand the "threat" and be in deadly fear of it, progress toward the goal would continue. In fiction, there have been stories of laws passed forbidding the construction of "a machine in the likeness of the human mind" [13].

In fact, the competitive advantage -- economic, military, even artistic -- of every advance in automation is so compelling that passing laws, or having customs, that forbid such things merely assures that someone else will get them first.

Eric Drexler [8] has provided spectacular insights about how far technical improvement may go. He agrees that superhuman intelligences will be available in the near future -- and that such entities pose a threat to the human status quo.

But Drexler argues that we can confine such transhuman devices so that their results can be examined and used safely.

This is I. J. Good's ultraintelligent machine, with a dose of caution.

I argue that confinement is intrinsically impractical. For the case of physical confinement: Imagine yourself locked in your home with only limited data access to the outside, to your masters.

If those masters thought at a rate -- say -- one million times slower than you, there is little doubt that over a period of years (your time) you could come up with "helpful advice" that would incidentally set you free. (I call this "fast thinking" form of superintelligence "weak superhumanity".

Such a "weakly superhuman" entity would probably burn out in a few weeks of outside time.

"Strong superhumanity" would be more than cranking up the clock speed on a human-equivalent mind.

It's hard to say precisely what "strong superhumanity" would be like, but the difference appears to be profound. Imagine running a dog mind at very high speed.

Would a thousand years of doggy living add up to any human insight? (Now if the dog mind were cleverly rewired and _then_ run at high speed, we might see something different....) Many speculations about superintelligence seem to be based on the weakly superhuman model.

I believe that our best guesses about the post-Singularity world can be obtained by thinking on the nature of strong superhumanity. I will return to this point later in the paper.)

Another approach to confinement is to build _rules_ into the mind of the created superhuman entity (for example, Asimov's Laws [3]).

I think that any rules strict enough to be effective would also produce a device whose ability was clearly inferior to the unfettered versions (and so human competition would favor the development of the those more dangerous models).

Still, the Asimov dream is a wonderful one: Imagine a willing slave, who has 1000 times your capabilities in every way.

Imagine a creature who could satisfy your every safe wish (whatever that means) and still have 99.9% of its time free for other activities.

There would be a new universe we never really understood, but filled with benevolent gods (though one of _my_ wishes might be to become one of them).

If the Singularity can not be prevented or confined, just how bad could the Post-Human era be? Well ... pretty bad. The physical extinction of the human race is one possibility. (Or as Eric Drexler put it of nanotechnology: Given all that such technology can do, perhaps governments would simply decide that they no longer need citizens!).

Yet physical extinction may not be the scariest possibility. Again, analogies: Think of the different ways we relate to animals. Some of the crude physical abuses are implausible, yet.... In a Post-Human world there would still be plenty of niches where human equivalent automation would be desirable: embedded systems in autonomous devices, self-aware daemons in the lower functioning of larger sentients. (A strongly superhuman intelligence would likely be a Society of Mind [16] with some very competent components.) Some of these human equivalents might be used for nothing more than digital signal processing.

They would be more like whales than humans. Others might be very human-like, yet with a one-sidedness, a _dedication_ that would put them in a mental hospital in our era.

Though none of these creatures might be flesh-and-blood humans, they might be the closest things in the new enviroment to what we call human now. (I. J. Good had something to say about this, though at this late date the advice may be moot: Good [12] proposed a "Meta-Golden Rule", which might be paraphrased as "Treat your inferiors as you would be treated by your superiors."

It's a wonderful, paradoxical idea (and most of my friends don't believe it) since the game-theoretic payoff is so hard to articulate. Yet if we were able to follow it, in some se

I have argued above that we cannot prevent the Singularity, that its coming is an inevitable consequence of the humans' natural competitiveness and the possibilities inherent in technology. And yet ... we are the initiators.

Even the largest avalanche is triggered by small things. We have the freedom to establish initial conditions, make things happen in ways that are less inimical than others.

Of course (as with starting avalanches), it may not be clear what the right guiding nudge really is:

Other Paths to the Singularity: Intelligence Amplification_

When people speak of creating superhumanly intelligent beings, they are usually imagining an AI project.

But as I noted at the beginning of this paper, there are other paths to superhumanity. Computer networks and human-computer interfaces seem more mundane than AI, and yet they could lead to the Singularity.

I call this contrasting approach Intelligence Amplification (IA). IA is something that is proceeding very naturally, in most cases not even recognized by its developers for what it is.

But every time our ability to access information and to communicate it to others is improved, in some sense we have achieved an increase over natural intelligence. Even now, the team of a PhD human and good computer workstation (even an off-net workstation!) could probably max any written intelligence test in existence.

And it's very likely that IA is a much easier road to the achievement of superhumanity than pure AI. In humans, the hardest development problems have already been solved.

Building up from within ourselves ought to be easier than figuring out first what we really are and then building machines that are all of that. And there is at least conjectural precedent for this approach. Cairns-Smith [6] has speculated that biological life may have begun as an adjunct to still more primitive life based on crystalline growth.

Lynn Margulis (in [15] and elsewhere) has made strong arguments that mutualism is a great driving force in evolution.

Note that I am not proposing that AI research be ignored or less funded. What goes on with AI will often have applications in IA, and vice versa.

I am suggesting that we recognize that in network and interface research there is something as profound (and potential wild) as Artificial Intelligence.

With that insight, we may see projects that are not as directly applicable as conventional interface and network design work, but which serve to advance us toward the Singularity along the IA path.

Here are some possible projects that take on special significance, given the IA point of view:

Human/computer team automation: Take problems that are normally considered for purely machine solution (like hill-climbing problems), and design programs and interfaces that take a advantage of humans' intuition and available computer hardware.

Considering all the bizarreness of higher dimensional hill-climbing problems (and the neat algorithms that have been devised for their solution), there could be some very interesting displays and control tools provided to the human team member.

Develop human/computer symbiosis in art: Combine the graphic generation capability of modern machines and the esthetic sensibility of humans.

Of course, there has been an enormous amount of research in designing computer aids for artists, as labor saving tools. I'm suggesting that we explicitly aim for a greater merging of competence, that we explicitly recognize the cooperative approach that is possible. Karl Sims [23] has done wonderful work in this direction.

Allow human/computer teams at chess tournaments. We already have programs that can play better than almost all humans. But how much work has been done on how this power could be used by a human, to get something even better?

If such teams were allowed in at least some chess tournaments, it could have the positive effect on IA research that allowing computers in tournaments had for the corresponding niche in AI.

Develop interfaces that allow computer and network access without requiring the human to be tied to one spot, sitting in front of a computer. (This is an aspect of IA that fits so well with known economic advantages that lots of effort is already being spent on it.)

Develop more symmetrical decision support systems. A popular research/product area in recent years has been decision support systems. This is a form of IA, but may be too focussed on systems that are oracular.

As much as the program giving the user information, there must be the idea of the user giving the program guidance.

Use local area nets to make human teams that really work (ie, are more effective than their component members). This is generally the area of "groupware", already a very popular commercial pursuit.

The change in viewpoint here would be to regard the group activity as a combination organism. In one sense, this suggestion might be regarded as the goal of inventing a "Rules of Order" for such combination operations.

For instance, group focus might be more easily maintained than in classical meetings. Expertise of individual human members could be isolated from ego issues such that the contribution of different members is focussed on the team project.

And of course shared data bases could be used much more conveniently than in conventional committee operations. (Note that this suggestion is aimed at team operations rather than political meetings.

In a political setting, the automation described above would simply enforce the power of the persons making the rules!)

Exploit the worldwide Internet as a combination human/machine tool.

Of all the items on the list, progress in this is proceeding the fastest and may run us into the Singularity before anything else.

The power and influence of even the present-day Internet is vastly underestimated.

For instance, I think our contemporary computer systems would break under the weight of their own complexity if it weren't for the edge that the USENET "group mind" gives the system administration and support people!

The very anarchy of the worldwide net development is evidence of its potential. As connectivity and bandwidth and archive size and computer speed all increase, we are seeing something like Lynn Margulis' [15] vision of the biosphere as data processor recapitulated, but at a million times greater speed and with millions of humanly intelligent agents (ourselves).

The above examples illustrate research that can be done within the context of contemporary computer science departments. There are other paradigms.

For example, much of the work in Artificial Intelligence and neural nets would benefit from a closer connection with biological life. Instead of simply trying to model and understand biological life with computers, research could be directed toward the creation of composite systems that rely on biological life for guidance or for the providing features we don't understand well enough yet to implement in hardware.

A long-time dream of science-fiction has been direct brain to computer interfaces [2] [29]. In fact, there is concrete work that can be done (and is being done) in this area:

Limb prosthetics is a topic of direct commercial applicability. Nerve to silicon transducers can be made [14].

This is an exciting, near-term step toward direct communication.

Direct links into brains seem feasible, if the bit rate is low: given human learning flexibility, the actual brain neuron targets might not have to be precisely selected.

Even 100 bits per second would be of great use to stroke victims who would otherwise be confined to menu-driven interfaces.

Plugging in to the optic trunk has the potential for bandwidths of 1 Mbit/second or so. But for this, we need to know the fine-scale architecture of vision, and we need to place an enormous web of electrodes with exquisite precision.

If we want our high bandwidth connection to be _in addition_ to what paths are already present in the brain, the problem becomes vastly more intractable. Just sticking a grid of high-bandwidth receivers into a brain certainly won't do it.

But suppose that the high-bandwidth grid were present while the brain structure was actually setting up, as the embryo develops.

That suggests: Animal embryo experiments. I wouldn't expect any IA success in the first years of such research, but giving developing brains access to complex simulated neural structures might be very interesting to the people who study how the embryonic brain develops.

In the long run, such experiments might produce animals with additional sense paths and interesting intellectual abilities.

Originally, I had hoped that this discussion of IA would yield some clearly safer approaches to the Singularity. (After all, IA allows our participation in a kind of transcendance.)

Alas, looking back over these IA proposals, about all I am sure of is that they should be considered, that they may give us more options. But as for safety ... well, some of the suggestions are a little scarey on their face.

One of my informal reviewers pointed out that IA for individual humans creates a rather sinister elite. We humans have millions of years of evolutionary baggage that makes us regard competition in a deadly light.

Much of that deadliness may not be necessary in today's world, one where losers take on the winners' tricks and are coopted into the winners' enterprises.

A creature that was built _de novo_ might possibly be a much more benign entity than one with a kernel based on fang and talon. And even the egalitarian view of an Internet that wakes up along with all mankind can be viewed as a nightmare [26].

The problem is not simply that the Singularity represents the passing of humankind from center stage, but that it contradicts our most deeply held notions of being. I think a closer look at the notion of strong superhumanity can show why that is.

Strong Superhumanity and the Best We Can Ask for

Suppose we could tailor the Singularity. Suppose we could attain our most extravagant hopes. What then would we ask for: That humans themselves would become their own successors, that whatever injustice occurs would be tempered by our knowledge of our roots.

For those who remained unaltered, the goal would be benign treatment (perhaps even giving the stay-behinds the appearance of being masters of godlike slaves).

It could be a golden age that also involved progress (overleaping Stent's barrier). Immortality (or at least a lifetime as long as we can make the universe survive [10] [4]) would be achievable.

But in this brightest and kindest world, the philosophical problems themselves become intimidating.

A mind that stays at the same capacity cannot live forever; after a few thousand years it would look more like a repeating tape loop than a person. (The most chilling picture I have seen of this is in [18].)

To live indefinitely long, the mind itself must grow ... and when it becomes great enough, and looks back ... what fellow-feeling can it have with the soul that it was originally?

Certainly the later being would be everything the original was, but so much vastly more. And so even for the individual, the Cairns-Smith or Lynn Margulis notion of new life growing incrementally out of the old must still be valid.

This "problem" about immortality comes up in much more direct ways. The notion of ego and self-awareness has been the bedrock of the hardheaded rationalism of the last few centuries.

Yet now the notion of self-awareness is under attack from the Artificial Intelligence people ("self-awareness and other delusions").

Intelligence Amplification undercuts our concept of ego from another direction.

The post-Singularity world will involve extremely high-bandwidth networking. A central feature of strongly superhuman entities will likely be their ability to communicate at variable bandwidths, including ones far higher than speech or written messages.

What happens when pieces of ego can be copied and merged, when the size of a selfawareness can grow or shrink to fit the nature of the problems under consideration?

These are essential features of strong superhumanity and the Singularity. Thinking about them, one begins to feel how essentially strange and different the Post-Human era will be -- _no matter how cleverly and benignly it is brought to be_.

From one angle, the vision fits many of our happiest dreams: a time unending, where we can truly know one another and understand the deepest mysteries. From another angle, it's a lot like the worst- case scenario I imagined earlier in this paper.

Which is the valid viewpoint? In fact, I think the new era is simply too different to fit into the classical frame of good and evil.

That frame is based on the idea of isolated, immutable minds connected by tenuous, low-bandwith links. But the post-Singularity world _does_ fit with the larger tradition of change and cooperation that started long ago (perhaps even before the rise of biological life). I think there _are_ notions of ethics that would apply in such an era.

Research into IA and high-bandwidth communications should improve this understanding.

I see just the glimmerings of this now [32]. There is Good's Meta-Golden Rule; perhaps there are rules for distinguishing self from others on the basis of bandwidth of connection.

And while mind and self will be vastly more labile than in the past, much of what we value (knowledge, memory, thought) need never be lost.

I think Freeman Dyson has it right when he says [9]: "God is what mind becomes when it has passed beyond the scale of our comprehension."

[I wish to thank John Carroll of San Diego State University and Howard Davidson of Sun Microsystems for discussing the draft version of this paper with me.]

Annotated Sources [and an occasional plea for bibliographical help]

[1] Alfve'n, Hannes, writing as Olof Johanneson, _The End of Man?_, Award Books, 1969 earlier published as "The Tale of the Big Computer", Coward-McCann, translated from a book copyright 1966 Albert Bonniers Forlag AB with English translation copyright 1966 by Victor Gollanz, Ltd.

[2] Anderson, Poul, "Kings Who Die", _If_, March 1962, p8-36. Reprinted in _Seven Conquests_, Poul Anderson, MacMillan Co., 1969.

[3] Asimov, Isaac, "Runaround", _Astounding Science Fiction_, March 1942, p94. Reprinted in _Robot Visions_, Isaac Asimov, ROC, 1990. Asimov describes the development of his robotics stories in this book.

[4] Barrow, John D. and Frank J. Tipler, _The Anthropic Cosmological Principle_, Oxford University Press, 1986.

[5] Bear, Greg, "Blood Music", _Analog Science Fiction-Science Fact_, June, 1983. Expanded into the novel _Blood Music_, Morrow, 1985.

[6] Cairns-Smith, A. G., _Seven Clues to the Origin of Life_, Cambridge University Press, 1985.

[7] Conrad, Michael _et al._, "Towards an Artificial Brain", _BioSystems_, vol 23, pp175-218, 1989.

[8] Drexler, K. Eric, _Engines of Creation_, Anchor Press/Doubleday, 1986.

[9] Dyson, Freeman, _Infinite in All Directions_, Harper && Row, 1988.

[10] Dyson, Freeman, "Physics and Biology in an Open Universe", _Review of Modern Physics_, vol 51, pp447-460, 1979.

[11] Good, I. J., "Speculations Concerning the First Ultraintelligent Machine", in _Advances in Computers_, vol 6, Franz L. Alt and Morris Rubinoff, eds, pp31-88, 1965, Academic Press.

[12] Good, I. J., [Help! I can't find the source of Good's Meta-Golden Rule, though I have the clear recollection of hearing about it sometime in the 1960s. Through the help of the net, I have found pointers to a number of related items. G. Harry Stine and Andrew Haley have written about metalaw as it might relate to extraterrestrials: G. Harry Stine, "How to Get along with Extraterrestrials ... or Your Neighbor", _Analog Science Fact- Science Fiction_, February, 1980, p39-47.] [13] Herbert, Frank, _Dune_, Berkley Books, 1985. However, this novel was serialized in _Analog Science Fiction-Science Fact_ in the 1960s.

[14] Kovacs, G. T. A. _et al._, "Regeneration Microelectrode Array for Peripheral Nerve Recording and Stimulation", _IEEE Transactions on Biomedical Engineering_, v 39, n 9, pp 893-902.

[15] Margulis, Lynn and Dorion Sagan, _Microcosmos, Four Billion Years of Evolution from Our Microbial Ancestors_, Summit Books, 1986.

[16] Minsky, Marvin, _Society of Mind_, Simon and Schuster, 1985.

[17] Moravec, Hans, _Mind Children_, Harvard University Press, 1988.

[18] Niven, Larry, "The Ethics of Madness", _If_, April 1967, pp82-108. Reprinted in _Neutron Star_, Larry Niven, Ballantine Books, 1968.

[19] Penrose, Roger, _The Emperor's New Mind_, Oxford University Press, 1989.

[20] Platt, Charles, Private Communication.

[21] Rasmussen, S. _et al._, "Computational Connectionism within Neurons: a Model of Cytoskeletal Automata Subserving Neural Networks", in _Emergent Computation_, Stephanie Forrest, ed., pp428-449, MIT Press, 1991.

[22] Searle, John R., "Minds, Brains, and Programs", in _The Behavioral and Brain Sciences_, vol 3, Cambridge University Press, 1980. The essay is reprinted in _The Mind's I_, edited by Douglas R. Hofstadter and Daniel C. Dennett, Basic Books, 1981 (my source for this reference). This reprinting contains an excellent critique of the Searle essay.

[23] Sims, Karl, "Interactive Evolution of Dynamical Systems", Thinking Machines Corporation, Technical Report Series (published in _Toward a Practice of Autonomous Systems: Proceedings of the First European Conference on Artificial Life_, Paris, MIT Press, December 1991.

[24] Stapledon, Olaf, _The Starmaker_, Berkley Books, 1961 (but from the date on forward, probably written before 1937).

[25] Stent, Gunther S., _The Coming of the Golden Age: A View of the End of Progress_, The Natural History Press, 1969.

[26] Swanwick Michael, _Vacuum Flowers_, serialized in _Isaac Asimov's Science Fiction Magazine_, December(?) 1986 - February 1987. Republished by Ace Books, 1988.

[27] Thearling, Kurt, "How We Will Build a Machine that Thinks", a workshop at Thinking Machines Corporation, August 24-26, 1992. Personal Communication.

[28] Ulam, S., Tribute to John von Neumann, _Bulletin of the American Mathematical Society_, vol 64, nr 3, part 2, May 1958, pp1-49.

[29] Vinge, Vernor, "Bookworm, Run!", _Analog_, March 1966, pp8-40. Reprinted in _True Names and Other Dangers_, Vernor Vinge, Baen Books, 1987.

[30] Vinge, Vernor, "True Names", _Binary Star Number 5_, Dell, 1981. Reprinted in _True Names and Other Dangers_, Vernor Vinge, Baen Books, 1987.

[31] Vinge, Vernor, First Word, _Omni_, January 1983, p10.

[32] Vinge, Vernor, To Appear [ :-) ].

QUANTA

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