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July 27, 2006: Technology of human extinction - The geeks may well inherit the earth, but will mankind survive cyber evolution? Opinion by Miranda Devine. The Sydney Morning Herald. "All this may reflect poorly on the mental acuity of the abovementioned people. But it does also seem to be part of a new, fumbling evolution of the mind, as technology becomes indispensable in our daily lives and the boundary between human brain and machine blurs. Slowly, but surely, we are becoming our computers. Technology is altering our ways of thinking, if not the architecture of our brains, so fundamentally that it is changing what it is to be human. At the same time, roboticists are imbuing computers with more humanity, until the two species - man and machine - may finally morph, and cyborg and android are one. ... Then there is Google, which has eliminated the mental strain of racking your brain for a dimly remembered fact. Who knows what kind of cerebral flaccidity will ensue in future generations? Will intelligence suffer without this brain exercise, the sort you might get from doing a crossword, which is said to be a protection against Alzheimer's? Or will freeing us from brain-racking allow other, more creative parts of the brain to develop, generating a new type of human consciousness? On the other side of the fence, robots are being developed with artificial intelligence that involves 'learning' behaviours which some say will lead to sentient machines, with unpredictable emotional needs and desires. ... Some scientists believe 'conscious' machines will exist before 2020...."
>>> The Future, Ethical & Social Implications, Cognitive Science

July 26, 2006: Researchers study 'shogi' players in bid to unravel brain's mysteries. By Shoji Tsue. Kyodo News & The Japan Times Online. "Researchers study 'shogi' players in bid to unravel brain's mysteries The Japan Shogi Association have opened the Shogi Super-Brain Research Society with cooperation from the Institute of Physical and Chemical Research to study how the brains of professional 'shogi' players work. ... A game between a professional player and shogi software will be held in the fall to analyze the player's brain with MRI equipment and a device to measure brain waves. The researchers will look at brain activity during the games as well as the differences between professional and amateur players. This research will not only help the field of brain science but also fields such as robot engineering, medicine and psychology. It could even be a big step in the development of artificial intelligence."
>>> Shogi (@ More Games & Puzzles), Cognitive Science

July 25, 2006: AI set to exceed human brain power. CNN.com. "Mention Artificial Intelligence and most people are immediately transported into a distant future inspired by popular science fiction. Humankind either co-exists in blissful peace with subservient robots and conscious computers or faces a battle for survival against ultra-smart psychotic machines set on its destruction. Yet Artificial Intelligence (AI) has already been with us for half a century. The phrase was first coined by Professor John McCarthy for a conference on the subject at Dartmouth College in 1956. And while the AI fantasies imagined by science fiction writers such as Isaac Asimov, author of 'I, Robot,' may not have materialized, AI is already in more common usage than many of us might imagine. Nick Bostrom, Director of the Future of Humanity Institute at the UK's Oxford University, said that AI-inspired systems were already integral to many everyday technologies such as internet search engines, bank software for processing transactions and in medical diagnosis. ... In the short-term, developments in AI are likely to lead to more mundane technological improvements, such as more intuitive search engines and more sophisticated pattern recognition software. Yet Bostrom is confident that technological advances coupled with a growing understanding of the workings of the human brain could enable machines to exceed human brain power within a couple of decades."
>>> AI Overview, Applications, The AI Effect, Ethical & Social Implications, Science Fiction, Turing Test, Chess, Banking, Expert Systems, Information Retrieval, Neural Networks, Cognitive Science, The Future

July 20, 2006: A good robot has personality but not looks. By Celeste Biever. New Scientist (Issue 2561; subscription req'd). "Robots are poised to enter our homes, schools and hospitals as cleaners, educational aides and medical assistants. So how can designers ensure we make the most of our robotic helpers? Two new studies suggest robots need to act more like humans, but not look too much like us, if we are to accept them into our lives."

  • Also see: Putting a face on android science by exploring an uncanny valley - Informatics researcher, IU scientists poised to present at international conference. Indiana University press release (July 20, 2006). "We might be more responsive to robots designed to look human rather than mechanical, but other factors may determine what causes us to accept or shun these virtual humans. 'Recent evidence indicates that androids are better able to elicit human norms of interaction than less humanlike robots or animated characters,' said Karl F. MacDorman, associate professor at the Indiana University School of Informatics. 'However, there's a heightened sensitivity to defects in near humanlike forms -- an uncanny valley in what is otherwise a positive relationship between human likeness and familiarity.' ... 'Android science has great potential to help cognitive neuroscientists, and social and cognitive scientists understand human beings as well as improving medical training,' MacDorman said. 'We might be using androids, but what we're really studying is ourselves -- what motivates us and how we interact with one another as humans.' MacDorman and Ishiguro are organizing a long symposium on July 26 at the 28th Annual Conference of the Cognitive Science Society in Vancouver, Canada. 'Toward Social Mechanisms of Android Science' brings together some of the world's experts in robotics and the behavioral sciences. Information about the session is at www.androidscience.com, as is a full text of MacDorman's paper on the robot video clips."

>>> Robots, Cognitive Science, Applications, Conferences (@ Resources for Students)

July 20, 2006: Meet the Remote-Control Self. By Tim Hornyak. Wired News. "[Hiroshi] Ishiguro, a senior researcher at ATR Intelligent Robotics and Communication Laboratories outside Kyoto, has created a machine in his own image -- a robot that looks and moves exactly like him. ... But why bother to build robots that look like humans? Ishiguro views machines as good vehicles to learn more about human nature. He combines engineering with cognitive science with the aim of making very humanlike robots, which can be used as test beds for theories about human perception, communication and cognition. He calls his approach 'android science.' 'A robot is a kind of simulator for expressing human functions, especially the cerebellum or the muscles,' says Norihiro Hagita, director of the ATR lab that developed Geminoid."

>>> Robots, Cognitive Science

July 18, 2006: Brainy Robots Start Stepping Into Daily Life. By John Markoff. The New York Times [nytimes.com]. "Robot cars drive themselves across the desert, electronic eyes perform lifeguard duty in swimming pools and virtual enemies with humanlike behavior battle video game players. These are some fruits of the research field known as artificial intelligence, where reality is finally catching up to the science-fiction hype. A half-century after the term was coined, both scientists and engineers say they are making rapid progress in simulating the human brain, and their work is finding its way into a new wave of real-world products. The advances can also be seen in the emergence of bold new projects intended to create more ambitious machines that can improve safety and security, entertain and inform, or just handle everyday tasks. ... Today some scientists are beginning to use the term cognitive computing, to distinguish their research from an earlier generation of artificial intelligence work. What sets the new researchers apart is a wealth of new biological data on how the human brain functions. 'There’s definitely been a palpable upswing in methods, competence and boldness,' said Eric Horvitz, a Microsoft researcher who is president-elect of the American Association for Artificial Intelligence. ... 'There is a new synthesis of four fields, including mathematics, neuroscience, computer science and psychology,' said Dharmendra S. Modha, an I.B.M. computer scientist. 'The implication of this is amazing. What you are seeing is that cognitive computing is at a cusp where it’s knocking on the door of potentially mainstream applications.'"

  • Also see the related popup timeline: From Fantasy to Fact. The New York Times (July 18, 2006).
    • Correction (July 21, 2006): "A chart with the continuation of a front-page article on Tuesday about advancements in the research field known as artificial intelligence misstated the year in which a robot at Kawasaki killed a Japanese mechanic because of a malfunction. It was 1981, not 1985."

>>> AI Overview, History, Applications, Cognitive Science, Turing Test, Grand Challenges

July 6, 2006: ISU program awarded $1.34 million dollars. By Tony Sapochetti. Daily Vidette. "The Mind Project, a program of excellence at ISU, was awarded $1.34 million by the National Institute of Health in order to continue their research in cognitive and learning sciences. David Anderson, associate professor of philosophy, said what the goals and main research aspects of The Mind Project are, and how it will incorporate the newly awarded money towards student and faculty research and teaching practices. ... Anderson said the main aspects The Mind Project will be focusing on with their research will be based in medicine and robotics, by teaching students about robots and artificial intelligence in general and to learn about different types of surgeries."
>>> Medicine, Robots, Cognitive Science, Education, Academic Departments (@ Resources for Students), Applications

July 6, 2006: Scientists to automate thought - Neurological research could help develop machines that can make informed decisions. By James Brown. Computing. "A brain scanning experiment at University College London (UCL) could help to create computers that make decisions in the same way as humans, heralding huge potential benefits for businesses. Such computers would be able to identify trends and make accurate decisions about complex information much quicker than people, potentially replacing human participation in data analysis procedures. The project, conducted at the Gatsby Computational Neuroscience Unit of UCL, used a functional Magnetic Resonance Imager (fMRI) to scan volunteer’s brains as they played a computerised gambling programme. ... 'If we can understand how people solve problems using past experience we can design better decision-making machine algorithms that could be used in something like an autonomous robot, or in perfecting systems such as those used by Amazon.com to price books with,' said [Dr Nathaniel] Daw. ... BT futurologist Ian Pearson says this is only the tip of the iceberg, and that computational neuroscience could lead us to machines with self-aware artificial intelligence as early as 2015."
>>> Cognitive Science, Neural Networks & Connectionist Systems, Machine Learning, The Future, Applications

July 2006: The Search for Artificial Intelligence - For 50 years the finest minds have been telling computers what to do. What they haven't been able to instill in them is common sense. By Tom Bethell. The American Spectator (subscription req'd). "In a semi-official way, the search for artificial intelligence began 50 years ago. In the summer of 1956, a two-month conference at Dartmouth College set out to explore 'the conjecture that every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it.' Computers could do what the mind does, in other words. An attempt would be made 'to find how to make machines use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves.' The four authors of the grant proposal added -- optimistically it turned out: 'We think that a significant advance can be made in one or more of these problems if a carefully selected group of scientists work on it together for a summer.' The Rockefeller Foundation put up the money. The conjecture that machines could be built with the ability to think had been made by the British mathematician Alan Turing in the 1930s. By the end of the 20th century, he believed, 'one will be able to speak of machines thinking without expecting to be contradicted.' In 1950 he devised what became known as the Turing test. If a human behind a screen cannot distinguish human from machine responses, then the machine must be considered intelligent. Fifty years after the Dartmouth conference, the computer science people are still working on these problems. Computers have not yet passed the Turing test. A 'significant advance' has been made in solving some problems 'now reserved for humans.' But the advance belongs in the realm of what is called 'applied' artificial intelligence. Computers can do useful things like multiplication and division, and they are also very good at chess. An IBM program beat the world chess champion. As to machines forming abstractions on their own, there has been no progress. ... In the past half century, an important distinction has emerged: between 'strong' and 'weak' AI. It divides what is often called 'cognitive' and 'applied' artificial intelligence. It distinguishes between computers on the one hand actually knowing and thinking -- the still unattained goal of 'strong' AI; and on the other hand performing a programmed sequence of tasks in order to achieve a well-defined goal -- 'applied' AI."
>>> AI Overview, History, Commonsense, Expert Systems, Applications, Robots, Turing Test, Representation, Reasoning, Cognitive Science

June 20, 2006: The ideas interview - Steve Quartz: John Sutherland meets a man who knows what you are thinking. The Guardian & EducationGuardian.co.uk. "Cognitive philosophy - 'brain science', as its practitioners call it - is a rarefied academic field. ... 'I think brain science is really beginning to explore the relationship between objective measures and subjective measures of things like taste and preferences," he replies. "When we make a decision there are, of course, conscious components in play. But it turns out that our brain is also tracking a lot of things that we may not be consciously aware of.'... Quartz's ideas cross traditional boundaries. He's both a philosopher and an experimental neurobiologist. And he's also creating a nexus (a very profitable one) between the university lab and the marketplace. Is he happy about that? 'I'm very drawn to that nexus. I think from the philosophical perspective it's a very interesting new development. We are now with brain science where we were 20 years ago with biotechnology - that point in time, for example, when genetics was about to have significant real-world applications. With brain imaging we're at the point where we can look scientifically at decision-making. And from there we too will move on to applications in the political realm, or the economic realm, or the legal realm.'"
>>> Cognitive Science, Interviews

June 16, 2006: Seek new options and survive. By Clive Cookson. Financial Times & FT.com. "In an uncertain world, we are often pulled between sticking with what we know will reap rewards and exploring new options. Now neuroscientists have discovered which parts of the brain are involved in exploration and which in exploiting the familiar. ... To find out whether the subjects were using exploitative or exploratory gambling strategies, the scientists compared their human behaviour with the decisions made by intelligent robots; functional magnetic resonance imaging showed which brain areas were activated when exploring or exploiting. The research is published in Nature."

>>> Cognitive Science, Reinforcement Learning

June 14, 2006: Android research helps explain human behavior - Of device and men: because the Repliee Q1Expo android looks like a human being, we can expect it to elicit humanlike responses from those who come into contact with it. News release from Indiana University School of Informatics edited by Laboratorytalk. "Karl MacDorman is on a journey to better understand what makes human beings tick. And the companion who helps him has been known to make ticking sounds. MacDorman is among a handful of experts in the emerging field of android science, a cross-disciplinary approach to test and, if possible, verify hypotheses about human behavior. He now lends that expertise to the School of Informatics at Indiana University-Purdue University Indianapolis, where he continues his research and also teaches graduate courses in the psychology of human-computer interaction. 'It is not possible - nor is it ethical - to conduct many kinds of experiments on humans,' said MacDorman, associate professor in the school's human-computer interaction design programme. 'Very humanlike robots provide an experimental apparatus and test bed that has great potential to help neuroscientists, psychiatrists, social and cognitive scientists and others understand how and why we act the way we do.'"
>>> Cognitive Science, AI Overview, Robots

June 2, 2006: Baby Talk and Monkey Talk. By Victor D. Chase. ScienceCareers.org. "How does an infant learn language? Once the basics of a language are learned, there are rules that someone familiar with language instinctively applies, but a baby coming to language with no previous knowledge cannot apply such rules. So how does it learn? 'It’s a big question,' says Jessica Maye, an assistant professor of linguistics at Northwestern University in Evanston, Illinois, 'because it takes money to make money. If you know something about language, you can use that to learn something else about language, but how do you learn the very first thing?'... Early in her graduate school career at the University of Arizona, Tucson, Maye decided she wanted to focus on psycholinguistics, a relatively new branch of linguistics that draws on cognitive sciences, including psychology, computer science, artificial intelligence, speech and hearing, and neural imaging to explain how humans learn language. After receiving her Ph.D. in 2000, Maye spent 3 years as a postdoctoral fellow in brain and cognitive sciences at the University of Rochester in New York, where she began conducting experiments on how babies learn. ... The goal of the NSF-funded project is to determine why infants are so much more proficient than adults and monkeys. 'If we know more about how infants use the statistical information they have access to, we can incorporate that information into machine processing of language to better enable speech recognition to correctly process language as humans do,' says Matt Goldrick, an assistant professor in Northwestern’s Linguistics Department (which is separate from the Department of Communication Sciences and Disorders where Maye works). ... Apart from the implications about language therapy, there's another practical side to Maye's research. Computer scientists aiming to improve computer speech recognition need to enhance the ability of machines to achieve 'source separation,' the ability to distinguish and make sense of several voices talking at the same time even in the presence of background noise (although a phenomenon Maye has not researched herself). ... Another thing humans can do very well but machines cannot is find the edges of words."
>>> Cognitive Science, Natural Language Processing, Speech, Careers in AI (@ Resources for Students)

May 31, 2006: Outward Bound for Robots - A new approach teaches objects how to navigate unfamiliar territory as humans might. By Duncan Graham-Rowe. Technology Review. "A computer navigation system based on a part of the brain called the hippocampus has been tested on an autonomous robotic car. By enabling the robot to take what its creators call 'cognitive fingerprints' of its surroundings, the software allows the vehicle to explore and remember places in much the same way mammals do. ... Similarly, the system has been tested on an indoor robot by 'blindfolding' it, taking it to an unknown location, and getting it to find its way home, says Adriana Tapus, a roboticist at the University of Southern California in Los Angeles who developed the system. This 'kidnapping task' is much more difficult than it might seem, she says. Yet this problem, known as simultaneous localization and mapping (SLAM), is becoming increasingly important for robots, autonomous vehicles, and military unmanned aerial vehicles (UAV). The challenge is to create a map from which a robot can navigate while it is still exploring that same environment, says Chris Melhuish, director of the Bristol Robotics Laboratory at the University of the West of England and Bristol University in the U.K."
>>> Cognitive Science, Robots, Vision, Autonomous Vehicles

May 30, 2006: Intelligent Machines. By Jocelyn Kim. New Univesity Paper (UC Irvine). "According to Marvin Minsky, intelligent machines will preserve maps of human cognitive processes for all eternity. Minsky, a professor of electrical engineering and computer science at the Massachusetts Institute of Technology, spoke on the future of intelligent machines on May 25 at the Beckman Center Auditorium as part of the Chancellor’s Distinguished Fellows Series. 'Ultimately, we should be able to loan entire cognitive processes into one of these machines the size of a cubic centimeter and live forever,' Minsky said. Intelligent machines would also help prevent human mortality by performing dangerous missions, an idea proposed in many science fiction stories. 'I grew up in the world of science fiction and someone had a set of stories when it was possible to duplicate people and send them to do risky jobs,' Minsky said. Artificial intelligence can not only perform many tasks but also solve problems regarding immigration. 'In Japan, there are fewer young people so they have guest workers,' Minsky said. 'Older people think it’s ruining the culture. If we had robots, that problem might go away unless the robots developed cultures that you didn’t like.' Although robots can improve the quality of human life, Minsky argued that only robots that perform trivial tasks are being made, instead of more useful robots."
>>> Cognitive Science, Robots, Hazards & Disasters, Assisitive Technologies, Analogy, Emotion, Science Fiction, Applications

May 20, 2006: The question of consciousness. Philosopher's Zone, presented by Alan Saunders. ABC Radio National. (A transcript and audio downloads are available.) "Alan Saunders: Hello, I'm Alan Saunders, welcome to The Philosopher's Zone. This week, a virtuoso public performance by one of the most important philosophers in the English-speaking world today: John Searle, Professor of the Philosophy of Mind and Language at the University of California, Berkeley. He's talking at 'Towards a Science of Consciousness', a conference put on last month by the Center for Consciousness Studies at the University of Arizona. His subject is dualism. More than 350 years ago, the great French philosopher, Rene Déscartes, declared that the mind is a thing that thinks and does not occupy space, whereas the body occupies space and does not think. The decisive argument for this, he said, is that body is by its nature divisible: you can cut it up into little pieces, but you can't do that with a mind. This appears to imply that the mind and the body have a different ontological status - in other words, you don't lump them together when you draw up your ontology, that's to say your inventory of what the universe contains. This is dualism, and John Searle's not happy with the idea. John Searle: I have been trying to get out of the consciousness business for a very simple reason: I think once we get it in a kind of shape where it admits of empirical study, it's essentially a problem for a neurobiologist. I mean, there are a lot of other problems for psychology and cognitive science, but the problems that most interest me are things are like, well, how exactly does it work in the brain? That, I see as a neurobiological problem. ... Now people always tell me it was very hard to define consciousness, but I think if you're just looking for the kind of commonsense definition that you get at the beginning of the investigation, and not at the hard-nosed scientific definition that comes at the end, it's not hard to give a commonsense definition of consciousness. Consciousness consists of those states of feeling or sentience or awareness...."
>>> Philosophy, Cognitive Science

May 17, 2006: MIT's Speech Recognition Baby. By Jason Lee Miller. WebProNews.com. "The Massachusetts Institute of Technology (MIT) may be on the verge of a revolutionary development in speech and video algorithmic technology. Their test subject: a 9 month-old baby boy, who is the center of a project called 'The Human Speechome Project.' ... [Deb] Roy's team will be developing machine learning systems with a variety of speech and video processing algorithms to test hypotheses of how children learn and to make sense of behavioral and communication patterns embedded in the data collected. They hope to, though analysis, to expose basic movement patterns with the home (e.g., a person moving from room to room), as well as more complex behaviors (e.g., changing a diaper or putting away dishes). ... It's interesting enough what may come of what we learn about human speech development, but [Frank] Moss informs us that the research could have a wide impact on other technological realms. 'Equally exciting are the 'spinoff' opportunities that could result from this research. The innovative tools that are being developed for storing and mining thousands of terabytes of speech and video data offer enormous potential for breaking open new business opportunities for a broad range of industries -- from security to Internet commerce,' Moss said."

  • Also see: 'Big brother' informs baby talk. BBC News (May 17, 2006). "The team then hopes to build computers that can learn words and grammar, from hearing and seeing precisely the same images and sounds as the child, to understand the learning process in humans. As well as these insights into language development, Professor Roy and his team believe the technology that has been developed for the project may also have applications in other fields such as personal video or analysing images from security cameras."

>>> Cognitive Science, Machine Learning, Applications

May 11, 2006: Making Computers Smarter - Scientists at IBM cognitive conference hope to create computers that act just like the human brain. Red Herring. "Computers seeking to emulate the human brain will have to abandon current structures and become more organic, scientists and researchers said at IBM’s annual Almaden Institute conference in San Jose, California. The theme of this year’s conference, cognitive computing, had experts declaring Wednesday that traditional software programs emulating behavior should be tossed away. Computers based on neuroscience and psychology more accurately reflect the way the brain works, they said. ... 'The brain isn’t like a [current] computer. It’s more like an evolutionary jungle,' said Nobel Prize winner Gerald Edelman, director of the Neurosciences Institute, which devises and tests theories on how the brain works. 'They learn by making mistakes, just like we do,' said Dr. Edelman. He believes cognitive computing focuses on meeting a goal, while current artificial intelligence technology is concerned too much about following software instructions and can’t learn from errors. Though his organization focuses on theory, Dr. Edelman is also involved in practical applications -- such as creating robots like Darwin X and BrainWorks. They can learn similar to the way humans or animals do. BrainWorks won the 2005 RoboCup, a soccer-like event for robots."

  • Also see:
    • This is your brain on a microchip. By Stefanie Olsen. CNET News.com (May 11, 2006). "James Albus, a senior fellow and founder of the Intelligent Systems Division of the National Institute of Standards and Technology, made the most convincing case for why the era of 'engineering the mind' is here. He also proposed a national program for developing a scientific theory of the mind. "We are at a tipping point...analogous to where nuclear physics was in 1905. The technology is emerging to conduct definitive experiments. The neurosciences have developed a good idea of computation and representation of the brain," he said Wednesday at the two-day gathering. ... [M]oney is flowing into artificially intelligent systems. Car and truck companies, for example, are investing heavily in collision-warning systems and vehicles that can drive themselves. ([Jeff] Hawkins even acknowledged that several major car companies have contacted him and are showing interest in his intelligent platform.) And a study from the Department of Transportation said that robotic vehicles with safety warnings will likely save more lives than airbags and seatbelts together, Albus said."
    • Blueprinting the human brain. By Stefanie Olsen. CNET News.com (May 10, 2006). "A 3D computer simulation of 10,000 neurons firing in the human brain produces a terabyte of data--a fraction of what it would take to map the brain's billions of neurons in algorithms. That's according to Henry Markham, a scientist working on the Blue Brain project, a collaboration of IBM, the Ecole Polytechnique Federale de Lausanne, or EPFL, in Lausanne, Switzerland, and others. The project is an attempt to create a blueprint of the human brain to advance cognition research. ... 'This is the first step,' said Markham, speaking here Wednesday at the Cognitive Computing conference, a two-day gathering hosted by IBM's Almaden Institute."

>>> Cognitive Science, Machine Learning, Neural Networks & Connectionist Systems, Systems, Applications, Conferences (@ Resources for Students)

May 6, 2006: Q&A: IBM’s Dharmendra Modha - Cognitive computing guru wants to build smarter machines based on human brain. Red Herring. "In real life, computers that think like humans have eluded their would-be makers. Some experts believe that’s because scientists have focused too much on artificially creating intelligence rather than learning first how the mind works. The Almaden Institute at IBM’s San Jose, California, research facility will tackle the issue when it presents its cognitive computing conference Wednesday and Thursday. Dharmendra Modha, chair of the institute and IBM’s leader for cognitive computing, hopes scientists will accept his challenge to pursue neuroscience and psychology in order to create computers with minds. ... Q: Why use the term “cognitive computing” rather than the better-known “artificial intelligence”? A: The rough idea is to use the brain as a metaphor for the computer. The mind is a collection of cognitive processes -- perception, language, memory, and eventually intelligence and consciousness. The mind arises from the brain. The brain is a machine -- it’s biological hardware. Q: Are programs or algorithms that, for example, measure feelings and thoughts similar to this? A: No. Cognitive computing is less about engineering the mind than it is the reverse engineering of the brain. ..."
>>> Cognitive Science, Interviews, Conferences (@ Resources for Students)

May 5, 2006: 'Baby' robot learns like a human. By Tom Simonite.NewScientist.com news. "A robot that learns to interact with the world in a similar way to a human baby could provide researchers with fresh insights into biological intelligence. Created by roboticists from Italy, France and Switzerland, 'Babybot' automatically experiments with objects nearby and learns how best to make use of them. This gives the robot an ability to develop motor skills in the same way as a human infant. ... Babybot's 'brain' is actually a cluster of 20 computers running several neural networks. This is software that mimics a biological neural system and learns in a similar way - by establishing and altering the strength of links between artificial neurons. By adjusting the neural network software and observing the robot's learning behaviour, the roboticists can test different neuroscience models."
>>> Neural Networks, Machine Learning, Cognitive Science, Robots

May 2, 2006: BabyBot takes first steps. IST Results. "BabyBot, a robot modelled on the torso of a two year-old child, is helping researchers take the first, tottering steps towards understanding human perception, and could lead to the development of machines that can perceive and interact with their environment. The researchers used BabyBot to test a model of the human sense of 'presence', a combination of senses like sight, hearing and touch. The work could have enormous applications in robotics, artificial intelligence (AI) and machine perception. The research is being funded under the European Commission’s FET (Future and Emerging Technologies) initiative of the IST programme, as part of the ADAPT project. 'Our sense of presence is essentially our consciousness,' says Giorgio Metta, Assistant Professor at the Laboratory for Integrated Advanced Robotics at Italy's Genoa University and ADAPT project coordinator. ... 'We took an engineering approach to the problem, it was really consciousness for engineers,' says Metta, 'Which means we first developed a model and then we sought to test this model by, in this case, developing a robot to conform to it.' Modelling, or defining, consciousness remains one of the intractable problems of both science and philosophy. 'The problem is duality, where does the brain end and the mind begin, the question is whether we need to consider them as two different aspects of reality,' says Metta. ... ADAPT did not seek to solve it in one project. They made a very promising start and many of the partners will take part in a new IST project, called ROBOTCUB. In ROBOTCUB the engineers will refine their robot so that it can see, hear and touch its environment. Eventually it will be able to crawl, too. "
>>> Philosophy, Cognitive Science, Robots, AI Overview

May 2006: Android Science - Hiroshi Ishiguro makes perhaps the most humanlike robots around - not particularly to serve as societal helpers but to tell us something about ourselves. By Tim Hornyak. Scientific American 294(5): 32-34. "Director of Osaka University's Intelligent Robotics Laboratory, Ishiguro has a high furrowed brow beneath a shock of inky hair and riveting eyes that seem on the verge of emitting laser beams. Besides the justification for making robots anthropomorphic and bipedal so they can work in human environments with architectural features such as stairs, Ishiguro believes that people respond better to very humanlike robots. Androids can thus elicit the most natural communication. 'Appearance is very important to have better interpersonal relationships with a robot,' says the 42-year-old Ishiguro. 'Robots are information media, especially humanoid robots. Their main role in our future is to interact naturally with people.' ... To emulate human looks and behavior successfully, Ishiguro yokes robotics with cognitive science. In turn, cognitive science research can use the robot as a test bed to study human perception, communication and other faculties. This novel cross-fertilization is what Ishiguro describes as android science."
>>> Robots, Cognitive Science

April 19, 2006: Watching the brain 'switch off' self-awareness. By Gaia Vince. NewScientist.com News. "Self-awareness, regarded as a key element of being human, is switched off when the brain needs to concentrate hard on a tricky task, found the neurobiologists from the Weizmann Institute of Science in Rehovot, Israel. The team conducted a series of experiments to pinpoint the brain activity associated with introspection and that linked to sensory function. They found that the brain assumes a robotic functionality when it has to concentrate all its efforts on a difficult, timed task -- only becoming 'human' again when it has the luxury of time."
>>> Cognitive Science, Philosophy

April 18, 2006: CNN Future Summit technology profiles:

  • Cybernetics: Merging machine and man. By Michael Bay and Matt Ford. CNN.com (April 18, 2006). "'We are the species that goes beyond our limitations,' says futurist Ray Kurzweil. 'The science of control and communications in the animal and machine,' is how American mathematician Norbert Wiener defined cybernetics. The fields of neuroscience, biomechanics, robotics, mathematics, computer science, materials science and tissue engineering all play a role in the effort to use machines to help patients who have lost some control over their bodies, whether through accident or disease. 'By merging human and machine, by creating that intimacy,' says Hugh Herr of the MIT Biomechatronics Group, 'we will truly be able to rehabilitate people.' ... We already augment our intelligence by using computers: A quick Internet search helps us find information faster than ever before. ... photo caption: Replacement limbs powered by artificial intelligence could soon become commonplace."
  • Robots: The future is now. By Michael Bay and Matt Ford. CNN.com (April 18, 2006). "'The advances in robotics make it clear that many household chores will be easily handled by a robot in the near future,' says Bob Christopher, the CEO of UGOBE, a robotic technology company that is marketing a toy robot called Pleo. BT Futurist-in-Residence and CNN Future Summit Nominating Committee member Ian Pearson envisions a home where robots outnumber humans. 'I've only one child and one wife, but I could easily imagine five or six robots in the home as well.' ... Demographic changes, such as a rapidly aging population and a shrinking workforce will drive forward the application of new technology. ... 'Most of us would rather be attended to in a hospital by a robot than be ignored,' says [Joanne] Pransky, 'and given the choice to stay in our own homes with a nursebot or go to a nursing home, a robot would allow us to continue to live independently as well as offer a more cost-effective alternative.' ... 'I am afraid that the long term future we are building will have no space left for human beings,' says Daniela Cerqui, a social and cultural anthropologist at the Institute of Sociology and Anthropology of the University of Lausanne. 'I definitely do not like the idea of robots replacing human beings.' 'What it means to be a healthy human is to move, to do work, we shouldn't replace that or cancel it out,' says MIT's Hugh Herr. 'I'm personally disturbed by the notion of a world where we have these robots and better and better artificial intelligence, where systematically those systems replace humans, human services, human work. I think we're at our limit at what machines should do for us.'"

>>> The Future, Robots, Cognitive Science, Applications, Ethical & Social Implications, Science Fiction, Assisitive Technologies

April 10, 2006: Emergence timeline - Evolution of an idea. The history of emergence from the 1843 A System of Logic to the present debate in the scientific community. Science & Theology News. "1843: System of logic: English political theorist John Stuart Mill publishes A System of Logic, which includes a description of what would eventually become known as emergence.... 1951: Invention: Marvin Minsky, MIT researcher in artificial intelligence, invents the Stochastic Neural-Analog Reinforcement computer (SNARC), one of the first electronic learning machines based on neural network models. ... 1984: Network: The Terminator, starring Arnold Schwarzenegger, describes the evil emergent properties of a network of computers. ... 1989: SimCity: 'SimCity' is released by game designer Will Wright, one of earliest popular computer games to use emergent properties."

  • Emergence theorists expand our view of origins - Why is there something rather than nothing, and how did that something get here? Emergence seeks to answer these questions. By Matt Donnelly. Science & Theology News (April 10, 2006). "Among those who think about emergence, said Australian philosopher David J. Chalmers, two main positions have developed: strong emergence and weak emergence. Supporters of weak emergence make the claim that the more fundamental theory can in principle explain the phenomena of the higher-level theory. And many also argue that emergent laws and properties, even if they do exist, don’t cause anything on a lower level of reality to change in any way. 'The sense of emergence that I approve of is what I’ve called innocent emergence,' said Daniel C. Dennett, director of the Center for Cognitive Studies and Austin B. Fletcher Professor of Philosophy at Tufts University in Medford, Mass. Dennett said his definition of an emergent phenomena 'is one that is startling, surprising, one that allows us to use a higher-level description to characterize it, but it’s not in principle unpredictable or irreducible or anything like that.'"
  • Emergence glossary: Reducing the terms. By Britt Peterson. Science & Theology News (April 10, 2006). "Emergent property: Appears when a number of individual agents form to initiate complicated and unpredictable behavior. ..."

>>> Cognitive Science, Machine Learning, Agents, Philosophy, Neural Networks, Genetic Algorithm, Artificial Life, Video Games, Science Fiction

April 2006: Electric Thoughts? The latest computer designs draw inspiration from human neural networks. But will machines ever really think? By Yvonne Raley. Scientific American Mind. "[R]ecent technological advances are narrowing the gap between human brains and circuitry. At Stanford University, bioengineers are replicating the complicated parallel processing of neural networks on microchips. Another development--a robot named Darwin VII--has a camera and a set of metal jaws so that it can interact with its environment and learn, the way juvenile animals do. Researchers at the Neurosciences Institute in La Jolla, Calif., modeled Darwin's brain on rat and ape brains. The developments raise a natural question: If computer processing eventually apes nature's neural networks, will cold silicon ever be truly able to think? And how will we judge whether it does? More than 50 years ago British mathematician and philosopher Alan Turing invented an ingenious strategy to address this question, and the pursuit of this strategy has taught science a great deal about designing artificial intelligence, a field now known as AI. At the same time, it has shed some light on human cognition. ... [T]he Chinese Room Argument--was developed by philosopher John Searle of the University of California, Berkeley, to show that a computer can pass the Turing Test without ever understanding the meaning of any of the words it uses. ... [Stevan Harnad of the University of Southampton] proposes a revised Turing Test, which he calls the Robotic Turing Test. To merit the label 'thinking,' a machine would have to pass the Turing Test and be connected to the outside world. Interestingly, this addition captures one of Turing's own observations: a machine, he wrote in a 1948 report, should be allowed to 'roam the countryside' so that it would be able to 'have a chance of finding things out for itself.'"
>>> Turing Test, Machine Learning, Cognitive Science, Neural Networks, Commonsense, Philosophy

February 24, 2006: Robot capable of identifying objects by simple properties. By Harry Yeates. ElectronicsWeekly.com. "Researchers at the University of Birmingham have developed a robot that can identify objects by type. The system is still very primitive, but it is a step towards a cognitive machine with integrated language and vision processing. ... The aim of the four-year Cognitive Systems for Cognitive Assistants (CoSY) project is to combine natural language processing with vision, adding ‘attention’ to the robot’s behaviour. Combining language with vision requires a mediating layer of representation between the two. The attention behaviour allows the robot to find an object more quickly if it knows what it is looking for."
>>> Representation, Vision, Natural Language Processing, Robots, Cognitive Science, Agents

February 13, 2006: Big Brain Thinking - Stanford neuroscientist Bill Newsome wants to implant an electrode in his brain to better understand human consciousness. By Emily Singer. Technology Review. "Bill Newsome, a neuroscientist at Stanford University in Palo Alto, CA, has spent the last twenty years studying how neurons encode information and how they use it to make decisions about the world. In the 1990s, he and collaborators were able to change the way a monkey responded to its environment by sending electric jolts to certain parts of its brain. The findings gave neuroscientists enormous insight into the inner workings of the brain. But Newsome is obsessed with a lingering question: How does consciousness arise from brain function? He feels the best way to answer that question is by implanting an electrode into his own brain -- and seeing how the electric current changes his perception of the world. ... It's not certain that Newsome will get approval for such a radical undertaking. But, if he does, his experiment won't be in the interest of curing a disease or become a human machine. He's hoping to do something broader: understand consciousness. Technology Review: Why is understanding consciousness so important to you? Bill Newsome: I think that how consciousness arises out of brain function is one of the most fascinating and important questions in all of neurobiology. If we understand the system completely (from input to output) at a cellular level, but still do not know exactly what causes conscious mental phenomena, we will have failed. ..."
>>> Cognitive Science, Philosophy, Interviews

January 27, 2006: What happened to the Robot Age? Sony's decision to ditch its Aibo robotic dog, along with its entire robot development team, is a reminder that we are still a long way from the age of automated domestic servants. Architects of the Robot Age have been busy rethinking the future. BBC News Magazine. "It might seem as though the robot revolution we were promised 20 years ago has hit an almighty malfunction. On the outskirts of Hatfield, Hertfordshire, in a ground-floor flat in which two customised robots are the only full-time residents, a team of researchers have been grappling with just this issue. The University of Hertfordshire's human-robot interaction research group has, along with most other robot development programmes, gone back to basics. 'For a long time people thought the summit of human intelligence was our capacity for problem solving, IQ tests and the like. So in developing robots they designed them to do these complex tasks, like playing chess,' says Prof Kerstin Dautenhahn, the group's leader and professor of artificial intelligence. 'But now people are saying that its humans' ability to deal with complex social relationships that's made us intelligent. Primatologists suggest this is what has made us smarter.' ... These days, the watchword in robotics is 'multi-disciplinary' - bringing together people from sociology and psychology backgrounds, as well as the technical folk, to build a robot that could a true domestic goddess."
>>> Robots, Applications, Nature of Intelligence, Cognitive Science, Chess

January 23, 2006: Computer to User - You Figure It Out. Systems should leave something to the imagination. By Gary H. Anthes. Computerworld. "Researchers in the U.S. and the U.K. are developing computer systems that make deliberately ambiguous interpretations of human environments. What's more, the systems are often flat-out wrong. But the developers are delighted with their progress so far, saying that with computers, sometimes less is more. The work is a branch of 'affective computing,' which attempts to make computers recognize and respond to users' emotions. And then there's 'culturally embedded computing,' as Cornell University information science professor Phoebe Sengers calls it, which applies a twist to the concept. 'We are shifting from the idea that affective computing is about computers understanding emotions to thinking about how people can understand their own emotions better after interacting with computational devices,' says Sengers."
>>> Emotion, Cognitive Science, Smart Houses

January 10 - 17, 2006: Singularity - Ubiquity interviews Ray Kurzweil. Ubiquity (Volume 7, Issue 1). "Kurzweil: There are two key aspects to the concept of singularity -- the hardware and software sides of emulating human intelligence. We'll have sufficient hardware to recreate human intelligence pretty soon. We'll have it in a supercomputer by 2010. A thousand dollars of computation will equal the 10,000 trillion calculations per second that I estimate is necessary to emulate the human brain by 2020. The software side will take a little longer. In order to achieve the algorithms of human intelligence, we need to actually reverse-engineer the human brain, understand its principles of operation. And there again, not surprisingly, we see exponential growth where we are doubling the spatial resolution of brain scanning every year, and doubling the information that we're gathering about the brain every year. ... You may wonder: 'OK, what's the big deal with that? We already have human intelligence; in fact, we've got six billion human brains running around, so why do we need more?' One of the answers to that question is that it will be a very powerful combination to combine the subtle and supple powers of human pattern recognition with ways in which machines are already superior. Machines can think more quickly than we can. They're much better at logical thinking and much better at remembering things: a $1000 notebook computer can remember billions of things accurately whereas we're hard-pressed to remember a handful of phone numbers. And most importantly, machines can share their knowledge, their skills, and their insights at electronic speed, which is a million times faster than human language. My second point is that nonbiological intelligence, once it achieves human levels, will double in power every year, whereas human intelligence -- biological intelligence -- is fixed. ... Computers can't pass the Turing test today, but I'm predicting that they'll be able to do it in 2029. ... Ubiquity: Someone like H.G. Wells went from science and technology into world government and large social issues and such. Have you attempted to follow his example? Kurzweil: Well, I am involved with one important aspect, and that is to study the downside to these technologies. I'm not a utopian, and my view is not a utopian perspective. I've been articulating the dangers and downsizing of these technologies for a long time. Are you familiar with Bill Joy's 'Wired' cover story? ... "
>>> The Future, Cognitive Science, Pattern Recognition, Applications, Machine Learning, Systems, Turing Test, Philosophy, Ethical & Social Implications, Interviews

January 5, 2006: Bayes rules - A once-neglected statistical technique may help to explain how the mind works. The Economist. "Science, being a human activity, is not immune to fashion. For example, one of the first mathematicians to study the subject of probability theory was an English clergyman called Thomas Bayes, who was born in 1702 and died in 1761. His ideas about the prediction of future events from one or two examples were popular for a while, and have never been fundamentally challenged. But they were eventually overwhelmed by those of the 'frequentist' school, which developed the methods based on sampling from a large population that now dominate the field and are used to predict things as diverse as the outcomes of elections and preferences for chocolate bars. Recently, however, Bayes's ideas have made a comeback among computer scientists trying to design software with human-like intelligence. Bayesian reasoning now lies at the heart of leading internet search engines and automated 'help wizards'. That has prompted some psychologists to ask if the human brain itself might be a Bayesian-reasoning machine. They suggest that the Bayesian capacity to draw strong inferences from sparse data could be crucial to the way the mind perceives the world, plans actions, comprehends and learns language, reasons from correlation to causation, and even understands the goals and beliefs of other minds."
>>> Cognitive Science, Probability/Uncertainty, Information Retrieval, Bayes (@ Namesakes), Reasoning, Applications

January 2006: A Brief History of Decision Making - Humans have perpetually sought new tools and insights to help them make decisions. From entrails to artificial intelligence, what a long, strange trip it's been. By Leigh Buchanan and Andrew O'Connell. Harvard Business Review. "Future Nobel laureate Herbert Simon, Allen Newell, Harold Guetzkow, Richard M. Cyert, and James March were among the [Carnegie Institute of Technology] scholars who shared a fascination with organizational behavior and the workings of the human brain. The philosopher's stone that alchemized their ideas was electronic computing. By the mid-1950s, transistors had been around less than a decade, and IBM would not launch its groundbreaking 360 mainframe until 1965. But already scientists were envisioning how the new tools might improve human decision making. The collaborations of these and other Carnegie scientists, together with research by Marvin Minsky at the Massachusetts Institute of Technology and John McCarthy of Stanford, produced early computer models of human cognition -- the embryo of artificial intelligence. AI was intended both to help researchers understand how the brain makes decisions and to augment the decision-making process for real people in real organizations."
>>> Cognitive Science, History, Applications

December 23, 2005: Scientists predict what you'll think of next- Brain engages in 'mental time travel' when trying to recall memories. By Ker Than. LiveScience / available from MSNBC.com. "'When you have an experience, that experience is represented as a pattern of cortical activity,' explained Sean Polyn, a postdoctoral researcher at the University of Pennsylvania and leader of the study. 'The memory system, which we think lives in the hippocampus, forms a sort of summary representation of everything that's going on in your cortex.' The process can be compared to the way web crawlers work to browse and catalogue web pages on the Internet. Web crawlers are automated programs that create copies of all visited pages. Search engines like Google then tag and index the pages. In the same way, as we're trying to remember something, our brains dredge up the memory by first recalling a piece of it, scientists say. ... Scientists think that contextual reinstatement is unique to memories that involve personal experiences, so-called 'episodic' memories, but that similar processes might be at work in other forms of memory. The study was detailed in the Dec. 23 issue of the journal Science."
>>> Cognitive Science, Representation, Web-Searching Agents

November 16 - 22, 2005: Artificial and Biological Intelligence. View by Subhash Kak. Ubiquity (Volume 6, Issue 42). "The recent success of several teams in meeting the $2 million DARPA Grand Challenge 2005 ... raises the question if AI might be poised for another period of high support and increased expectations. The quest for AI is also the subtext to debates outside of the field of computer science. Physics, for example, is the discovery of formal structures in nature, and each of these formal systems could be interpreted as a natural machine. The claim of some physicists that the universe itself is a giant machine is taken to complement the belief that true machine intelligence and self-awareness should arise after machine complexity has crossed a critical threshold. But this leads to certain difficulties. Since machines only follow instructions, it is not credible that they should suddenly, on account of a greater number of connections between computing units, become endowed with self-awareness. On the other hand, if one accepts that machines will never become self-aware, one may ask why is the brain-machine conscious, whereas the silicon-computer is not? ... I have considered evidence that negates the view that the brain is an ordinary machine. I argue that even with self-organization and hitherto-unknown quantum characteristics one cannot explain the capacities associated with the brain. A summary of these arguments follows. ..."

  • Also see the Mailbag of comments (Ubiquity: Volume 6, Issue 44; November 29-December 5, 2005).

>>> Philosophy, Cognitive Science, Nature of Intelligence, Artificial Life

November 10, 2005: Brain Work Gets New Digs at MIT. By Mark Baard. Wired News. "Hundreds of researchers will soon move into new offices at the McGovern Institute for Brain Research at MIT.... Robert Desimone, a professor of brain and cognitive sciences at MIT and a specialist in attention disorders, is the institute's director. Desimone said in an interview before the dedication that the institute would offer opportunities for 'unparalleled collaboration,' resulting in new drugs and other therapies for mental illness, and yield breakthroughs in the field of artificial intelligence. In fact, the institute's researchers are already making breakthrough discoveries, Desimone said. Last week, McGovern scientists announced they had deciphered a part of the process the brain uses to recognize visual objects. The discovery could help AI researchers build better computer vision systems that mimic biological functions.
>>> Cognitive Science, Vision, Academic Departments (@ Resources for Students)

November 5, 2005: The robot that thinks like you... Scientists built a robot that thinks like we do and set it loose to explore the world. By Douglas Fox. New Scientist (subscription req'd.; Issue 2524). "The infant I am watching wander around its rather spartan playpen in the Neurosciences Institute (NSI) in La Jolla, California, is a more limited creature. It is a trashcan-shaped robot called Darwin VII, and it has just 20,000 brain cells. Despite this, it has managed to master the abilities of a 18-month-old baby – a pretty impressive feat for a machine. ... Darwin VII is the fourth in a series of robots that Jeff Krichmar and his colleagues at NSI have created in a quest to better understand how our own brains work. ... The idea of an artificial neural network that could perform computations was proposed as long ago as 1943, by Warren McCullough and Walter Pitts at the University of Illinois. ... [I]n the past few years, neuroscientists and AI researchers have started collaborating more closely, and their labours are beginning to bear fruit. Their conclusions challenge two decades of research into artificial neural networks."
>>> Cognitive Science, Robots, Neural Networks, Machine Learning, History, Systems

November 2005: Transforming America's Schools. By Jonathan Potts. Carnegie Mellon Today. "The technology that drives intelligent tutoring systems is grounded in research into artificial intelligence and cognitive psychology, which seeks to understand the mechanisms that underlie human thought, including language processing, mathematical reasoning, learning and memory. As students perform problems using these tutoring systems, the program analyzes their strengths and weaknesses and on that basis provides individualized instruction. Intelligent tutoring systems do not replace teachers. Rather, they allow teachers to devote more one-on-one time to each student and to work with students of varying abilities simultaneously."
>>> Intelligent Tutoring Systems, Education, Cognitive Science, Applications

October 24, 2005: Making computer work like a brain - Rutgers part of military project. By Kevin Coughlin. The Star-Ledger & NJ.com. "Rutgers University in Newark is among 15 institutions and companies sharing $9.5 million in grants for the first year of DARPA's Biologically-Inspired Cognitive Architectures program. When the field of artificial intelligence took shape in the 1950s -- spurred by pioneers at Bell Labs and Princeton University -- academics expected to build machines that reason and think like people, a branch of study later known as 'strong A.I.' But the task proved daunting and interest waned in the 1980s, starting a bleak 'A.I. winter.' Neuroscience research, meanwhile, has flourished. Techniques such as functional Magnetic Resonance Imaging, which tracks blood flow in the brain, have yielded clues about what each region of the brain actually does. 'We're saying there might be enough new information to build up computer models of how the brain works,' said [David] Gunning, a computer scientist and psychologist managing the DARPA project. ... DARPA is giving [Rutgers neuroscientist Mark] Gluck $172,000 to create a model of how memories begin in the hippocampus, a region of the brain within the temporal lobe on each side of the head. The hippocampus acts like a filter, tossing some tidbits and sending others for storage elsewhere. ... Ultimately, the Pentagon seeks smarter machines to fight wars with fewer soldiers. ... Civilian spinoffs could include smarter robots to clean your house or drive your car, or truly helpful programs to sift your communications. ... But the project troubles some people. Smart-yet-unfeeling war machines could make the battlefield 'an even nastier place,' says bioethicist Arthur Caplan of the University of Pennsylvania."

  • Also see: Understanding the mind. Rutgers-Newark professor to study artificial intelligence. Opinion column. The Daily Targum (October 25, 2005). "[Mark Gluck] has already used the hippocampus as a model for programming to solve problems on Navy helicopters. This program was able to detect unfamiliar vibrations in gear boxes of the helicopters before they resulted in crashes. Not only is this research a positive step toward increasing safety on military machines, but any research done on the hippocampus will most likely yield advancements in medical research.... There are those who fear certain of the project's long-term goals to design technology that will make machines - such as unmanned tanks - capable of fighting wars with fewer soldiers. However, these wary skeptics need to remain open-minded. People should eagerly take on any opportunity to seek out technological advances that may help the lives of many."

>>> Cognitive Science, Neural Networks & Connectionist Systems, Machine Learning, Military, Applications, Ethical & Social Implications, Emotions, AI Overview, History

October 6, 2005: Jeff Hawkins, computing pioneer, endows new center to develop model of brain. By Robert Sanders. UC Berkeley News. "Jeff Hawkins, creator of the first commercially successful handheld computer and author of the book 'On Intelligence,' has endowed a new research center at the University of California, Berkeley, to develop mathematical and computational models of how the brain works."
>>> AI Academic Departments (@ Resources for Students), Cognitive Science

October 3, 2005: USC's Michael Arbib. By Eric Smalley. Technology Research News. "Technology Research News Editor Eric Smalley carried out an email conversation with Michael Arbib, the Fletcher Jones Professor of Computer Science and a Professor of Biological Sciences, Biomedical Engineering, Electrical Engineering, and Neuroscience and Psychology at the University of Southern California (USC) in September 2005. ... Throughout his career Arbib has encouraged an interdisciplinary environment where computer scientists and engineers can talk to neuroscientists and cognitive scientists. ... TRN: Context -- the body, the physical environment, society -- seems to play a critical role in shaping consciousness and intelligence. What does this mean for building artificial intelligences? Will we be able to relate to truly intelligent machines? Arbib: ... I do think that there will be future robots that indeed have emotions -- as high-level indicators of process state that set an overall bias on decision making and condition patterns of communication with others. However, I also think that emotions that are useful (but sometimes harmful) for robots interacting with other robots (imagine a team of autonomous robots responsible for spaceship maintenance on a decades long mission, or a team of agents monitoring the whole Earth for ecosystem evaluation) need not necessarily be similar to the "mammalian humans" that are so much part of human life. TRN: One of the big challenges in robotics is simply giving machines the ability to accurately perceive their surroundings. What will it take to build machines that can operate effectively in unfamiliar, dynamic environments? Arbib: One part of the answer, clearly, is that learning will be necessary. ... TRN: Is there a particular image (or images) related to science or technology that you find particularly compelling or instructive? Why do you like it; why do you find it compelling or instructive? ..."
>>> Cognitive Science, Emotion, Reasoning, Machine Learning, Robots, Philosophy, Graduate School (@ Resources for Students), Ethical & Social Implications, Interviews

October 2005: R Is for Robot- What bots can teach tots (and vice versa). By Larry Gallagher. Wired (Issue 13.10). "For the past six months, the children in Classroom One [at "the Early Childhood Education Center, a preschool attached to UC San Diego"] have spent half an hour of each school day interacting with one of two robots. Rubi takes on the role of a teacher, leading songs and playing games that instill basics like ABCs, shapes, and colors. She alternates days with Qrio, Sony's swanky prototype humanoid, whose role is more peer-to-peer: He spends his time dancing with the kids. The class is taking part in a project developed by [Javier ] Movellan, who directs the university's Machine Perception Lab. For him, the short-term goal is to watch the kids and use what he learns to develop interactive teaching tools. ... Movellan hopes to distinguish Rubi from existing automated teaching software by adding an emotional component to the interaction between kids and the machine. "The success of Rubi as a learning system is going to depend on whether she can engage these children - make them feel good about learning," he says. Movellan is not the first AI researcher to propose this approach. Indeed, the past decade has seen the emergence of what's called affective computing, whose proponents believe we need to build emotions into robots."
>>> Education, Robots, Emotion, Vision, Cognitive Science, Applications

September 19, 2005: Intelligence in the Internet age - It's a question older than the Parthenon: Do new innovations and technologies make us more intelligent? [This is the first installment in a 3 part series.] By Stefanie Olsen. CNET News.com. "Today, terabytes of easily accessed data, always-on Internet connectivity, and lightning-fast search engines are profoundly changing the way people gather information. But the age-old question remains: Is technology making us smarter? Or are we lazily reliant on computers, and, well, dumber than we used to be?"

  • Part 2: From ape to 'Homo digitas'? By Stefanie Olsen. CNET News.com (September 20, 2005). "[U]ntil computers can think for us, or thread ideas together, we will still need to rely on our own brains to do the work. The Internet may be vast, but it can't do the critical thinking for us. 'The Internet is information-rich, but it is flat,' said John Davidson, a partner at venture capital firm Mohr Davidow who has specialized in investments in artificial intelligence. 'The notion of technology taking over the world is false. It may be frustrating when the power goes out, but there are not going to be smart computers taking it over; it might (be) dumb computers. The ubiquity of stupid computers might be more dangerous.' ... In his book, 'On Intelligence,' [Jeff] Hawkins presents a theory of the brain that argues that intelligence is measured by the ability to make predictions by seeing patterns in the world. He's attempting to make computers intelligent by teaching them to find and use patterns in specific trades. ... 'A real inflection point that's going to happen in the next three or four years will be when humans aren't the only ones exhibiting intelligence,' Hawkins said. ... But what happens if the power goes off? E.M. Forster's 'The Machine Stops,' published in 1909, is about a society that's heavily dependent on a machine, which among other things, cleans house and provides the food. One day, the machine stops...."
  • Are we getting smarter or dumber? By Stefanie Olsen. CNET News.com (September 21, 2005). "CNET News.com spoke with [Mike] Merzenich about how technology is affecting human intelligence. ... [Q] Will we be smarter with computers that can do abstract thinking for us? Or will that exacerbate a potential problem? Merzenich: This is a difficult question to answer because it is difficult to see just how this will evolve. Personally, I see this triumph of technology, if it occurs on a broad scale, as a rather astounding defeat of its inventors, don't you? I suppose our abstract thinking abilities will be substantially superseded by machines. One can imagine a future when the machine is consistently relied on for the answer, and in which, outside of setting up the question, the human is relatively redundant in this process. Of course, one can also imagine quite a few other scenarios. In general, the brain needs to learn, to reason, to act. Without it, it deteriorates. ..."

>>> Nature of Intelligence, Ethical & Social Implications, Cognitive Science, Information Retrieval, Applications, Science Fiction

September 9, 2005: Profs’ New Software ‘Learns’ Languages. By Ben Birnbaum. The Cornell Daily Sun. "Think a language-learning robot sounds like science fiction? The day may not be as far off as it seems, in light of new software, developed by Prof. Shimon Edelman, psychology, with colleagues from Tel Aviv University in Israel. The soon-to-be-patented program -- 'Automatic Distillation of Structure,' or 'ADIOS,' for short -- can derive a language's rules of grammar, and then produce sentences of its own, simply from blocks of text in that language. 'When scanning new input, the program looks for recurring patterns or interchangeable sequences,' explained Edelman.... ADIOS is not limited to human language, however. The program has also detected patterns in sequences of non-linguistic data, such as musical scores and DNA strands."
>>> Pattern Recognition, Machine Learning, Natural Language Processing, Representation, Bioinformatics, Cognitive Science, Applications

September 4, 2005: Deceit of the Raven. By David Berreby. The New York Times Magazine (registration req'd.). "This 'theory of mind,' cognitive scientists say, is what makes life with other people so rich and productive. ... The significance of research like [Brian] Hare's and [Thomas] Bugnyar's is that it adds mind reading to the long list of skills we can't claim for our own kind only. When it comes to mental abilities, animals aren't on the other side of a chasm: birds and dogs, as well as apes and sheep, stand with us on a continuum. And even as biology establishes that animals aren't automatons, another challenge to our sense of uniqueness arises in the field of artificial intelligence. Even automatons aren't acting like automatons anymore. They're increasingly apt and lively -- less like machines and more like living minds. The robot soldiers on the drawing boards at the Pentagon will be able to understand orders and make decisions (including decisions about whether to kill). Tiny computer sensors are designed to be flung as 'smart dust' over wide areas and to configure themselves with no human guidance. Earlier this year, researchers at Cornell described a robot that could make robots, a working example of machine reproduction. Machine-based intelligences can also read minds -- at least at one remove, after those minds express themselves in writing. Last spring a British software firm released Sentiment, an application that sums up the tone of press clippings.... So science is chipping away at the case for human uniqueness from two different angles. Not only is it showing that animals are more like us than we believed but it is also making machines that are more like us than we believed possible. What happens, as these trends continue, to the familiar guideposts for deciding what is human? How will people decide, without a checklist of yes-no criteria for human standing, who, or what, is entitled to privileges and rights?"
>>> Ethical & Social Implications, Cognitive Science, Applications

August 22, 2005: Jeff Hawkins’ AI Obsession - The Palm Pilot pioneer is concentrating on creating tools for developing artificial-intelligence applications. Red Herring (print issue). "Mr. Hawkins used funds from his previous companies to launch the Redwood Neuroscience Institute and last fall he co-wrote a book called On Intelligence with science writer Sandra Blakeslee to advance his new theory about how the mind works. That theory advances some controversial ideas that have intrigued both the neuroscience and AI communities. And now his hobby has turned into a real job. Mr. Hawkins has launched yet another startup with his longtime partner Donna Dubinsky, who worked with him at Palm and Handspring. The company, Numenta, will create software tools that others will license to create brain-like computer applications for functions such as pattern recognition and machine learning. Its name stems from mentis, the Latin word for mind. ... In his book, Mr. Hawkins argues that computers are dumb and that most AI approaches never got close to mimicking the brain because they weren’t modeled on its actual design. His theory suggests that the brain, in particular the neocortex, is not a processor. Instead, it is a hierarchical memory system that stores memories in sequences and retrieves them quickly."
>>> Cognitive Science, Neural Networks, Machine Learning, Representation

August 19, 2005: Supercomputer's key to the brain. The quest to simulate the mammalian brain on the world's most powerful supercomputer is neuroscience's most ambitious project yet. David Reid went to Lausanne in Switzerland to find out how the line is being blurred between man and machine. By David Reid. BBC News Click Online programme (video available via article sidebar). "Man has long wanted to discover the secrets of the brain, and has done so with varying degrees of success. Recently advancements in this area of science have been limited by the power of computers. But at Switzerland's École Polytechnique Fédérale de Lausanne, the Blue Brain Project aims to change this by simulating the structures and functions of the brain. The project's head, Professor Henry Markram, says that in the past there was no software environment capable of simulating the brain. ... 'We are not trying to build an intelligent device or robot or anything like that,' explains Professor Markram. 'We are trying to understand the brain, and one pathway is to take our available knowledge of the brain and put it to a test inside a model.' ... Mix brain research with one of the world's most powerful computers and people start wondering about artificial intelligence and whether a computer will ever be conscious or have, as they often appear to, a mind of its own. Markus Baertschi says that the computing power is not really up to it at the moment."
>>> Cognitive Science, Neural Networks & Connectionist Systems, Philosophy, Systems, Machine Learning

August 16, 2005: Brains, cancer and computers. By Daniel Winterstein. The Register. "The race is on to apply machine learning to biology. The starting gun was fired in 2002 when research company Correlogic stunned the medical world with the announcement of a vastly improved test for detecting ovarian cancer. The new test was simple - a few drops of blood are all that's required - yet reliable. What made it truly remarkable was that the test was discovered by machine. This formed a key theme at this month's International Joint Conference in AI (IJCAI) at Edinburgh. The computer program BLAST, which searches genetics databases looking for similar gene sequences, is now ubiquitous in genetics research. ... This is the new mechanised biology, created by a combination of developments. Modern biology - especially genetics, molecular biology and medicine -- throws up vast amounts of data. These are now available in various vast international databases. Put this together with advances in statistical artificial intelligence (AI), and the conditions are ripe for the creation of a new subject. Known as bio-informatics (the word has become ubiquitous in AI project proposals), it is the application of computers to biology. ... Medicine attracts the most attention. There is interest from practically every area of AI. One striking project is the robot Penelope.... Computers are also being used to unlock that warped and weird construct, the human brain."
>>> Bioinformatics, Medicine, Machine Learning, Robots, Cognitive Science, Applications

August 15, 2005: Musings from a Mouse. By Anita Chabria. Technology Review. "For years, cognitive scientists have described the human brain as operating like a computer when it comes to language, meaning it interprets letters and sounds in a binary, one-step-at-a-time fashion. It's either a Labrador or a laptop. But a recent study, led by Cornell psycholinguist and associate professor Michael Spivey, suggests that the mind may be comprehending language in a more fluid way. 'Our results have shown that the various parts of the brain that participate in language processing are passing their continuous, partially activated results onto each next stage, not waiting till it's done to share information,' says Spivey. 'It’s a lot more like a distributed neural network.' ... Whereas computers still perform calculations in a linear order, the human brain can make a continuous series of computations at the same time, passing information back and forth in a non-linear, self-organizing manner. ... [B]esides hinting at new understandings of human cognition and new kinds of computer-assisted research and design, Spivey's study might have implications for a field somewhere in the middle: artificial intelligence. As Spivey points out, biological neural networks might be a better model for creating AI applications, such as language-recognition systems, than binary-based computers. 'If you want to invent a mind, you probably don’t want to be using a computer format,' Spivey says. "
>>> Cognitive Science, Neural Networks, Machine Learning, Natural Language Processing

August 15, 2005: Long Live AI. Opinion by Ray Kurzweil. Forbes.com. "Many people think the so-called AI winter in the 1980s, when many AI companies folded, was the end of the story. But boom-bust cycles are sometimes harbingers of true revolutions (recall the railroad frenzy of the 19th century), and we see the same phenomenon in AI. Artificial intelligence permeates our economy. It's what I define as 'narrow' AI: machine intelligence that equals or exceeds human intelligence for specific tasks. ... AI programs diagnose heart disease, fly and land airplanes, guide autonomous weapons, make automated investment decisions for a trillion dollars' worth of funds and guide industrial processes. ... So what are the prospects for 'strong' AI, which I describe as machine intelligence with the full range of human intelligence? ... To understand the principles of human intelligence we need to reverse-engineer the human brain. ... The killer app of strong AI, combined with nanotechnology, will be blood-cell-size robots called nanobots. We'll have billions of them traveling in our bloodstream...."
>>> AI Overview, Applications, Neural Networks & Connectionist Systems, Cognitive Science, Systems, Machine Learning, The Future, The AI Effect

August 13, 2005 : Spotting the bots with brains. New Scientist (Issue 2512, page 27). "How do you tell just how smart your robot is? Simple: give it a universal IQ test. ... Shane Legg and Marcus Hutter at the Swiss Institute for Artificial Intelligence in Manno-Lugano have drafted an alternative test that will allow the intelligence of vision systems, robots, natural language processing programs or trading agents to be compared and contrasted despite their broad and disparate functions. Although there is no consensus on what exactly human intelligence is, most views appear to cluster around the idea that it hinges on a general ability to achieve goals in a wide range of environments, says Legg. The same can be applied to an AI system...."

  • Also see: IQ test for AI devices gets experts thinking. By Will Knight. NewScientist.com news (August 12, 2005). "[T]he test is likely to face a lot of resistance, says Blay Whitby, an expert in human and artificial intelligence at the University of Sussex in Brighton, UK. For one thing, some people would even dispute that intelligence involves goals, he says. Also it may imply that rather a lot of computer programs should suddenly be considered intelligent, he says: 'Some people may object to this.' But Legg’s test is a good place to start, says Whitby, not least because it throws down the gauntlet to the AI community to come up with a definition of intelligence that will work for all AI. 'This is a very important -- perhaps the most important -- issue to be resolved for the future of AI,' says Whitby."

>>> Nature of Intelligence, AI Overview, Cognitive Science, Turing Test

July 29, 2005: In Memoriam - Yale Psychology Professor Robert Abelson. Yale University press release. "Robert Abelson, retired Eugene Higgins Professor of Psychology and professor of political science at Yale, died July 13 at Hamden Health Care Center of pneumonia brought on by Parkinson's Disease. He was 76. ... In his book 'Scripts, Plans, Goals, and Understanding' ( with Robert Schank 1977), a Citation Classic, he contributed a social psychological perspective to the emerging field of artificial intelligence."
>>> Tributes, Cognitive Science, History

July 28, 2005: The neurology of consciousness - Crick's last stand. Francis Crick suggests where to find the seat of consciousness. The Economist. "Mechanistic explanations of consciousness are hard to come by because consciousness is so poorly understood. Indeed, it is one of the few unexplained phenomena that are genuinely mysterious rather than merely problematical. But Crick, together with his long-time collaborator Christof Koch, of the California Institute of Technology in Pasadena, focused on a part of the mystery that seems tractable. This is the integrated nature of conscious sensation."
>>> Philosophy, Cognitive Science, Emotion

July 22 - 28, 2005: I Think, Therefore I Am -- Sorta. The belief system of a virtual mind. Quark Soup column by Margaret Wertheim. LA Weekly. "Far more than mere cartoons, these virtual people have each been endowed with a virtual mind complete with its own internal 'desires' and 'goals.' Technically known as 'agents,' they are driven by a revolutionary software system known as PsychSim that enables programmers to simulate the cognitive faculties of human minds. Dr. Stacy Marsella, a leading agent researcher and one of the primary architects of PyschSim, declares that agents actually 'think for themselves.' Indeed, the ultimate goal of agent research is to create autonomous self-determining minds capable of a full spectrum of human behavior. A small, dark-haired man with a doctorate in artificial intelligence, Marsella is a project leader at USC’s Information Sciences Institute in Marina del Rey, one of the world’s top centers for agent research. ... Last year, Marsella and his colleague Dr. David Pynadath developed an agent-based game [Carmen’s Bright Ideas] in which parents of childhood cancer patients engage in virtual counseling sessions with a virtual therapist. ... But what does it mean to talk about a virtual mind? What, indeed, is a mind of any variety? ... Until very recently, artificial-intelligence researchers believed that modeling the mind was simply a matter of simulating rational cognition, an activity that was seen to be epitomized by strategical games such as chess and go -- but over the past decade, computer scientists have come to understand that a virtual mind needs a virtual psychology. To 'think' requires not just an ability to carry through a chain of logical inferences; it also requires a mental environment, or psychic context, in which such rationalizations can be given meaning. "
>>> Agents, Multi-Agent Systems, Video Games, Education, Military, Chess, Go, Cognitive Science, Representation, Reasoning, Chatbots (@ Natural Language Processing), Applications

July 11, 2005: 'Hard fun' yields lessons on nature of intelligence. By Chappell Brown. EE Times Online. "The RoBallet project run by MIT's Future of Learning Group doesn't look or sound like hard research: Nine children, dressed in sweats fitted with flexible sensor strips, stomp on pressure sensors to trigger changes in the ambient lighting and sound. The performances are choreographed by a professional ballet dancer in collaboration with the kids. The idea is to give students the experience of controlling technology to realize the stuff of imagination. Other projects use software, robotics and sensors as tools with which children can design environmental exploration projects, such as water-quality studies. It's what Future of Learning co-director David Cavallo calls 'hard fun' -- creative yet disciplined and purposeful uses for technology. ... EE Times: What was your first encounter with computers and digital technology, and how did it influence your intellectual development? David Cavallo: The first was in the '60s, when I was in high school. I grew up in Cleveland, and our math class had a connection to Case Western Reserve. We were able to do some work, things around Fortran, to think about math and computers. I thought programming was just a blast, a different way of thinking about problems. That led to thinking about how you could use computers for learning -- first thinking about artificial intelligence and intelligent tutoring systems. A professor at Rutgers, Ken Kaplan, introduced me to Logo [a programming environment widely used as a classroom tool], and that's when my interest really took off. ... EET: The computer and AI have been compared to the mind in some ways, but they are also very different from how the mind works. Is the computer the appropriate instrument for that type of work? Cavallo: What's really been rich in AI, what's really rich in the computer and what has helped us to understand minds better was trying to build models of minds. ... EET: What would you say is a seminal idea that has come out of this that was not known before? Cavallo: ... If you go back 50 years, the view of what developed minds did was mostly limited to just planning, reasoning, logic. We now realize the richness of thought --- that there are many ways of thinking. For example, [MIT's Marvin] Minsky is doing work on common-sense reasoning. [Earlier], people put so much work into building expert systems, and then we discovered that [building an expert knowledge base] was much easier to do than thinking about how you could cross the street safely, which a 3-year-old could kind of figure out. Intelligence is really mixed; there are tons of stuff going on that work together, and we learn from it [all]. What we've tried to do on the computer has helped break the more-restricted view of what intelligence really is. ... EET: So what is the future of learning? ... "
>>> AI Overview, Cognitive Science, Education, Nature of Intelligence, Commonsense Reasoning, Expert Systems, Interviews

July 11, 2005: Research on the brain was always in the back of his head. By Janet Rae-Dupree. Silicon Valley/San Jose Business Journal (from the July 8, 2005 print edition). " The world may believe the PalmPilot is Jeff Hawkins' greatest achievement, but Mr. Hawkins says that won't always be the case. The work he's doing now, he promises, soon will overshadow the PalmPilot legacy. In fact, creating the PalmPilot was in some ways simply a means for funding his passion for brain research. That passion ignited in 1979 when, as a Cornell grad with an electrical engineering degree, Mr. Hawkins picked up a special issue of Scientific American focused entirely on the human brain. ... Mr. Hawkins decided to devote himself to figuring out how the brain actually works so that he could eventually build an artificial one. He didn't want to work in artificial intelligence, an endeavor intended to make existing computer architectures perform in more human ways. Instead, he says, he wanted to create 'real intelligence,' a wholly new kind of computer that does its work in the same way a human brain does. ... The basic theory is simple: The human brain, more specifically the high-functioning neocortex, detects familiar patterns that allow it to predict what will happen next in the world around it. Teach a computer to do the same thing, he believes, and we can build the first truly intelligent machines."
>>> Neural Networks, Cognitive Science, Machine Learning

July 1, 2005: 125 Big Questions. Science (Vol 309, Issue 5731, 79). "In a special collection of articles published beginning 1 July 2005, Science Magazine and its online companion sites celebrate the journal's 125th anniversary with a look forward -- at the most compelling puzzles and questions facing scientists today. A special, free news feature in Science explores 125 big questions that face scientific inquiry over the next quarter-century; accompanying the feature are several online extras including a reader's forum on the big questions." Start with the editorial, 125, by Donald Kennedy, Editor-in-Chief, and then explore questions such as:

  • What Is the Biological Basis of Consciousness? By Greg Miller. "For centuries, debating the nature of consciousness was the exclusive purview of philosophers. But if the recent torrent of books on the topic is any indication, a shift has taken place: Scientists are getting into the game. Has the nature of consciousness finally shifted from a philosophical question to a scientific one that can be solved by doing experiments? ... The discourse on consciousness has been hugely influenced by René Descartes, the French philosopher who in the mid-17th century declared that body and mind are made of different stuff entirely. It must be so, Descartes concluded, because the body exists in both time and space, whereas the mind has no spatial dimension. Recent scientifically oriented accounts of consciousness generally reject Descartes's solution; most prefer to treat body and mind as different aspects of the same thing. In this view, consciousness emerges from the properties and organization of neurons in the brain."What Are the Limits of Conventional Computing? By Charles Seife. "In the 1940s, Bell Labs scientist Claude Shannon showed that bits are not just for computers; they are the fundamental units of describing the information that flows from one object to another. There are physical laws that govern how fast a bit can move from place to place, how much information can be transferred back and forth over a given communications channel, and how much energy it takes to erase a bit from memory. All classical information-processing machines are subject to these laws--and because information seems to be rattling back and forth in our brains, do the laws of information mean that our thoughts are reducible to bits and bytes? Are we merely computers? It's an unsettling thought. But there is a realm beyond the classical computer: the quantum. The probabilistic nature of quantum theory allows atoms and other quantum objects to store information that's not restricted to only the binary 0 or 1 of information theory, but can also be 0 and 1 at the same time."
  • What are the limits of learning by machines? Computers can already beat the world's best chess players, and they have a wealth of information on the Web to draw on. But abstract reasoning is still beyond any machine."

>>> The Future, Systems, Cognitive Science, Philosophy, Reasoning, Grand Challenges

June 29, 2005: Your brain - Search engine, or calculator? By Michael Kanellos. CNET News.com. "For years, cognitive theorists have likened the human brain to a computer that completes tasks by breaking down complex problems into a series of small yes/no decisions. A recent study, however, shows that the brain adjusts its thinking as more data arrives. In a study published online this week in Proceedings of the National Academy of Sciences, Michael Spivey, a psycholinguist and associate professor of psychology at Cornell University, tracked the mouse movements of 42 undergraduate students while working at a computer. ... Interestingly, the whole field of artificial intelligence has moved from a Boolean model, in which systems guide themselves through a series of embedded rules, to a Bayesian model, in which machines guide themselves by studying past experiences. Bayesian probability also underlies search engines."
>>> Cognitive Science, Machine Learning, Probability, Reasoning, Bayes (@ Namesakes), Information Retrieval

June 24 - 30, 2005: Tickle Me Elmo With an Inferiority Complex- The Needies want you to want them . . . or else --- just like real-life obsessives. By Chris Ziegler. Orange County Weekly (OC Weekly; Volume 10, Number 42). "Once upon a time, there was Tickle Me Elmo. But this year’s hottest holiday toy might just be the Needies, the gift that keeps on taking: a codependent stuffed animal with a supersophisticated computer brain that lets it know when you’re paying attention to it . . . and when you’re not. ... The Needies team -- known as Codependent Designs -- use the term 'bleeding-edge' to describe their toy, and they’re right. Emotions are the last real frontier of robot research; as artificial intelligence grows more and more sophisticated, it develops a concurrent capacity for artificial emotions. British futurologist Ian Pearson predicts superhuman machine consciousness -- a computer that can think and feel -- before 2020. ... Beneath the novelty of the Needies is a morass of psychology and philosophy, the sort of issues one might find not in Bradbury but in Philip K. Dick: As our machines become more human-like, do we ourselves become more machine-like?"
>>> Emotion, Interfaces, Applications, Philosophy, The Future, Cognitive Science

June 24, 2005: Sims on steroids - researchers to study society of computer-based agents. By Peter Clarke. EETimes.com. "A team of European academics is set to take the computer simulation of artificial worlds further than it has been taken before and create a world of beings that can interact, evolve and learn. The researchers hope the computer-hosted beings will create their own language and pass it from 'parents' to 'children', even at the risk that the language may not be understood by their academic observers. ... [T]he European Union's NEW-TIES project is expected to have implications for the design of computer systems, for agent-based computer programming, for ambient intelligence systems, and for the study of linguistics and sociology. ... The project is being conducted by a consortium of researchers in artificial intelligence, language evolution, agent-based simulation and evolutionary computing, drawn from universities in the Netherlands, the U.K. and Hungary.... The agent population is being given three types of ability to learn; individual learning, evolutionary learning and social learning."
>>> Agents, Multi-Agent Systems, Genetic Algorithms, Artificial Life, Machine Learning, Cognitive Science

June 23, 2005: The simple things are hardest. Alok Jha meets Igor Aleksander, an engineer who isn't afraid of treading on philosophers' toes as he attempts to replicate consciousness in a machine. The Guardian. "'Consciousness is an incredibly delicate subject because it offends,' says the emeritus professor of neural systems engineering at Imperial College London. 'It's a subject that scientific groups kept away from. They said it was a philosophical concept.' Traditionally, research on making a computer do anything remotely human-like has been the domain of artificial intelligence. Aleksander says he is too much of a maverick to follow that herd. 'I never went along with the mainstream of artificial intelligence,' he says. 'I don't like the words artificial intelligence because the intelligence of a human being has to do with being good at this, being good at that. Whereas the intelligence of an artificial system consists in doing very simple things.' ... [H]ow would consciousness be useful in a machine? ... 'The ethical question of any machine that is built has to considered at the time you build the machine,' says Aleksander. 'What's that machine going to be capable of doing? Under what conditions will it do it, under what conditions could it do harm?' He says these are engineering problems rather than ethical dilemmas. 'A properly functioning conscious machine is going to drive your car and it's going to drive it safely. It will be very pleased when it does that...."

  • Also see: Debate with 'father of artificial intelligence'. Editorial. Hampstead and Highgate Express (June 24, 2005). "Igor Aleksander, known as the father of artificial intelligence, hosted a lively debate on consciousness at St Joseph's Bookstore in Finchley Road. Professor Aleksander, who lives in Hampstead, was launching his new book, The World in My Mind, My Mind in the World, earlier this month. He said: "The idea of the talk was to try to bring about the subject of consciousness in a way that everybody could join in."

>>> AI Overview, Philosophy, Cognitive Science, Ethical & Social Implications, Neural Networks, Interviews; also see this related article

June 22, 2005: Robo-pups created with curiosity in mind. By Will Knight. NewScientist.com news. "A litter of robotic puppies exhibiting a form of artificial curiosity is being put through kindergarten at Sony's research and development lab in Paris, France. The Aibo pups display an innate artificial curiosity similar to that seen in baby animals. They slowly learn to explore the surrounding world, before playing with toys and trying to communicate with other Aibo dogs. ... Each of the new Aibo dogs was given two software control mechanisms. Firstly, a 'low-level learning system' which controls simple behaviour but also tries to predict how this will affect the surrounding sensory world - how kicking a ball will cause it to move across the floor, for example. Secondly, a 'meta-learning system' which analyses the accuracy of predictions made by the low-level system and controls overall 'motivation'. Interaction between these two components is critical to the reprogrammed Aibos' uncannily inquisitive nature. ... [Pierre-Yves Oudeyer] believes the research could eventually help robot designers create machines that are much more flexible and adaptive in unpredictable circumstances. But he also says the project could shed light on how human intelligence benefits from curiosity and experimentation." There is a link in the article to a video made available by the researchers.
>>> Machine Learning, Cognitive Science, Robotic Pets, Robots

June 14, 2005: Sony researchers create 'curious' Aibos. By Paul Kallender. IDG News Service / available from ITworld.com. "Sony Corp. has succeeded in giving selected Aibo pet robots curiosity, researchers at Sony Computer Science Laboratory (SCSL) in Paris said last week. Their research won't lead to conscious robots soon, if ever, but it could help other fields such as child developmental psychology, they said during an open day in Tokyo. ... [W]hat if a robot could be made inherently 'curious?' And what if its curiosity was backed by awareness of the value of its learning? Such qualities are precisely what [Frederic] Kaplan and his fellow SCSL researcher Pierre-Yves Oudeyer believe they have achieved with Aibo ERS-7 robot dogs in experiments over the last three years, Kaplan said. ... To achieve this, the researchers equipped the Aibos with what they call an adaptive curiosity system or a 'metabrain,' an algorithm that is able to assess the robots' more conventional learning algorithms, they said. In the experiments, the metabrain algorithm continually forced the learning algorithm to look for new and more challenging tasks and to give up on tasks that didn't seem to lead anywhere. ... The idea behind this approach to AI was to recreate the world of a human infant; in other words, an entity with a sense of being, with a notion for exploring its environment, and the ability to wiggle its body, arms and legs, Kaplan said."
>>> Machine Learning, Cognitive Science, Robotic Pets

June 13, 2005: The Ethics of Creating Consciousness. The Connection radio program hosted by Dick Gordon, with guests: Marvin Minsky, Brian Cantwell Smith, and Paul Davies. From WBUR Boston and NPR. "Next month, IBM is set to activate the most ambitious simulation of a human brain yet conceived. It's a model they say is accurate down to the molecule. No one claims the 'Blue Brain' project will be self-aware. But this project, and others like it, use electrical patterns in a silicon brain to simulate the electrical patterns in the human brain -- patterns which are intimately linked to thought. But if computer programs start generating these patterns -- these electrical 'thoughts' -- then what separates us from them? Traditionally human beings have reserved words like 'reasoning,' 'self-awareness,' and 'soul' as their exclusive property. But with the stirring of something akin to electronic consciousness -- some argue that human beings need to give up the ghost, and embrace the machine in all of us." Links to the broadcast are provided.
>>> Philosophy, Ethical & Social Implications, Cognitive Science, Neural Networks & Connectionist Systems; also see this trail of related articles

June 12, 2005: The People vs. Pixel - Will real actors lose out to computers? By Bill Muller. The Arizona Republic. "Director George Lucas often replaced actors, either whole or in part, with computer-generated images, and summer moviegoers doubtless will see more of the same in such action films as Fantastic Four (July 8), The Island (July 22) and Stealth (July 29). That leads to the question: Can actors be replaced with digital replicas? ... Lucas says it's the acting that will keep CGI actors limited to action sequences and other stunt work. 'We've never been able to teach a computer to act,' he says. 'It's a talent, it's a skill, it's something you learn, it's something you're born with, and I don't see in the foreseeable future that computers can become human enough in their artificial intelligence to have the same crazed psychology you need in order to relate to other people, so you can emotionally express ideas. The art of acting is to transfer emotions from one human to another by imitating various fabricated characters. A computer can make a perfect visual representation, but the computer cannot act.' ... Paul Giamatti, who's starring in the boxing film Cinderella Man with Russell Crowe, is less dismissive of simulated thespians, saying the constructs may lead to a new form of acting."
>>> Emotion, Applications; also see this related article

June 8, 2005: A case of mistaken identity crisis - People afflicted with multiple personalities reveal that the idea of the self is a fiction. Comment by Matthew Syed. The Times Online. "Pamela, the subject of a haunting documentary on Channel 4 tonight, developed a novel, if somewhat disquieting, mechanism to cope with her sadistic upbringing: she created new selves. ... What about the notion of the self as instigator of action? We naïvely suppose that we consciously decide to move, and then move. When Benjamin Libet conducted an experiment on voluntary action in 1985 he found that the brain activity began about half a second before the person was aware of deciding to act. The conscious decision came far too late to be the cause of the action, as though consciousness is a mere afterthought. Many reacted to this with astonishment. Why? Did they really suppose the body was animated by some ghostly mini me lurking behind the brain? A more plausible theory is that which is emerging from both biology and artificial intelligence. As Daniel Dennett, the philosopher, puts it: 'Complex systems can in fact function in what seems to be a thoroughly 'purposeful and integrated' way simply by having lots of subsystems doing their own thing without any central supervision.' The self, then, is not what it seems to be. There is no soul, no spirit, no supervisor. There is just a brain, a dull grey collection of neurons and neural pathways -- going about its business. The illusion of self is merely a by-product of the brain's organisational sophistication. Seen in this light, DID [Dissociative Identity Disorder] is neither a philosophical absurdity nor a medical fantasy but a vivid demonstration of the infinite adaptability of the human mind in the quest for survival."
>>> Cognitive Science, Philosophy

June 6, 2005: IBM Aims To Simulate A Brain. By Matthew Herper. Forbes.com. "IBM has embarked on a quest for the holy grail of neuroscience--the far-off goal of creating a computer simulation of the human brain. When the first mammals evolved from reptiles 200 million years ago, one of the biggest changes was inside their heads. Their brain cells were structured together into columns, an innovation that could be repeated like a computer chip to make larger and more powerful minds-- from mice to cats and dogs to humans. ... Now, [Henry] Markram is announcing a collaboration with IBM to create a computer simulation of these fundamental neurological units, called neocortical columns. ... Markram and IBM both emphasize that the project would not create artificial intelligence but a way to study how neurons in the brain interact with one another."

  • Modelling the brain - Grey matter, blue matter. The Economist (June 9, 2005). "The first serious attempt to build a computer model of the brain has just begun. ... Henry Markram, the boss of the Brain Mind Institute, and the leader of the EPFL's side of the collaboration, stresses that Blue Brain's formal goal is not to build an artificial intelligence system, such as a neural network. Nor is it to create a conscious machine. The goal is merely to build a simulacrum of a biological brain. If the outputs produced by the simulation in response to particular inputs are identical to those in animal experiments, then that goal will have been achieved. On the other hand, he also says, 'I believe the intelligence that is going to emerge if we succeed in doing that is going to be far more than we can even imagine.' Watch this space."
  • Mission to build a simulated brain begins. By Duncan Graham-Rowe. New Scientist News(June 6, 2005). "An effort to create the first computer simulation of the entire human brain, right down to the molecular level, was launched on Monday. The 'Blue Brain' project, a collaboration between IBM and a Swiss university team, will involve building a custom-made supercomputer based on IBM’s Blue Gene design. The hope is that the virtual brain will help shed light on some aspects of human cognition, such as perception, memory and perhaps even consciousness."
  • Images: Mapping the human brain. CNET News.com.

>>> Cognitive Science, Neural Networks & Connectionist Systems, Machine Learning, Systems

May 2, 2005: Boffins build robot that thinks like a human. By Gareth Morgan. Western Mail / available from icWales. "The team of computer scientists at the University of Wales, Aberystwyth, have secured a major grant to construct a machine that applies the same 'thought processes' used by the human brain. According to Professor Mark Lee, project leader, the purpose is to try to 'unravel' the way in which the brain works and then build a robot that can 'think' for itself. ... 'Humans and animals adapt their actions according to what surrounds them, and are able to do several things at the same time and learn from their mistakes,' he said. 'With this project we hope to solve this problem of multi-tasking by using our knowledge of how the brain works.'"
>>> Cognitive Science, Robots, Machine Learning, Science Fiction

May 2005: Neuromorphic Microchips - Compact, efficient electronics based on the brain's neural system could yield implantable silicon retinas to restore vision, as well as robotic eyes and other smart sensors. By Kwabena Boahen. Scientific American (subscription req'd.). "Computers, for instance, cannot match our ability to recognize a friend from a distance merely by the way he walks. And when it comes to operational efficiency, there is no contest at all. A typical room-size supercomputer weighs roughly 1,000 times more, occupies 10,000 times more space and consumes a millionfold more power than does the cantaloupe-size lump of neural tissue that makes up the brain. How does the brain--which transmits chemical signals between neurons in a relatively sluggish thousandth of a second--end up performing some tasks faster and more efficiently than the most powerful digital processors? The secret appears to reside in how the brain organizes its slow-acting electrical components...."
>>> Cognitive Science, Systems, Vision,
Neural Networks, Machine Learning

April 23, 2005: Whatever happened to machines that think? By Justin Mullins. New Scientist (Issue 2496; pages 32 - 37). "The first chatbot appeared in the 1960s. Back then, the very idea of chatting to a computer astounded people. Today, a conversation with a computer is viewed more on the level of talking to your pet pooch - cute, but ultimately meaningless. The problem with chatbots is a symptom of a deeper malaise in the field of artificial intelligence (AI). For years researchers have been promising to deliver technology that will make computers we can chat to like friends, robots that function as autonomous servants, and one day, for better or worse, even produce conscious machines. Yet we appear to be as far away as ever from any of these goals. But that could soon change. In the next few months, after being patiently nurtured for 22 years, an artificial brain called Cyc (pronounced 'psych') will be put online for the world to interact with. And it's only going to get cleverer. Opening Cyc up to the masses is expected to accelerate the rate at which it learns, giving it access to the combined knowledge of millions of people around the globe as it hoovers up new facts from web pages, webcams and data entered manually by anyone who wants to contribute. ... [Doug] Lenat's optimism about Cyc is mirrored by a reawakening of interest in AI the world over. In Japan, Europe and the US, big, well-funded AI projects with lofty goals and grand visions for the future are once again gaining popularity. The renewed confidence stems from a new breed of systems that can deal with uncertainty - something humans have little trouble with, but which has till now brought computer programs grinding to a halt. ... Where could the secret to intelligence lie? According to [Tom] Mitchell, the human brain is the place to look."
>>> AI Overview, History, Chatbots (@ Natural Language Processing), Commonsense, Neural Networks, Uncertainty, Bayes (@ Namesakes), Reasoning, Representation, Machine Learning, Robots, Games & Puzzles, Vision, Speech, Cognitive Science, Applications

April 18, 2005: Gordon Moore Looks Back -- And Forward. Intel co-founder coined computing's famous "Moore's Law" 40 years ago. James Niccolai, IDG News Service & PCWorld.com. "Forty years after he coined the most famous law in computing, Gordon Moore still has a few words of advice for the industry. For software developers: Simplify! Your interfaces are getting worse. Nanotechnology? Don't believe the hype; silicon chips are here to stay. Artificial intelligence? Try again, folks! You're barking up the wrong tree. ... Asked about artificial intelligence, he said computers as they are built today will not come close to replicating the human mind because they were designed from the outset to handle information in a different way. Scientists need to figure out more clearly how the mind works, and then build a computer from scratch to mimic it. ... Still, they may mimic parts of human intelligence, such as the ability to recognize language and distinguish, for example, between when a person is saying 'two' or 'too.' 'I think when it recognizes language that well, then you can start to have an intelligent conversation with your computer and that will change the way you use computers dramatically,' he said."
>>> Cognitive Science, AI Overview, Natural Language Processing, The Future

April 12, 2005: Pioneer In Artificial-Intelligence Software Devises New Theory Of Cognition. Science Daily (adapted from a news release issued by University Of California, San Diego). "A leading expert in artificial intelligence and neural networks argues that cognition in humans and many animals occurs in a very different, non-algorithmic and less complex way than has been widely assumed until now. [Robert Hecht-Nielsen] outlined his theory of the fundamental mechanism of cognition in a seminar on the UCSD campus yesterday, and details appear in the February issue of the journal Neural Networks, in an article titled 'Cogent Confabulation.' ... Hecht-Nielsen noted that the common method used in search engines, data mining and drug trial analysis - maximum a posteriori probability - is not the mechanism of cognition. 'Humans and animals don’t do this,' he argued. 'Instead, animal cognition maximizes cogency, and in a non-logic environment, cogency maximization implements what I call the ‘duck test’: if a small animal waddles like a duck, swims like a duck, quacks like a duck and flies like a duck, we conclude that it is a duck because that is the conclusion which most strongly supports the probability of the assumed facts being true.'"
>>> Cognitive Science, Neural Networks, Nature of Intelligence, Machine Learning

April 3, 2005: Computers obeying brain signals. By Malcolm Ritter. The Associated Press / available from BusinessWeek online. "Researchers and volunteers around the world are taking early steps toward a complex but straightforward technological goal: to use electrical signals from the brain as instructions to computers and other machines, allowing paralyzed people to communicate, move around and control their environment literally without moving a muscle. ... Research into harnessing brain signals goes back some 20 years. But lately it seems the research pot is starting to come to a boil, as advances in brain science, electronics and computer software have combined to push the field forward. ... To see firsthand what all the excitement is about, I signed on as an able-bodied research subject at [Jonathan] Wolpaw's Brain-Computer Interface lab, part of the Wadsworth Center of the New York State Department of Health."
>>> Cognitive Science, Systems, Interfaces, Assistive Technologies

April 3, 2005: Celebrating science. By Rod Ohira. The Honolulu Advertiser. "Can a computer model the activities of the human brain? ... The answers to these questions -- and many more -- can be found among 345 projects from 427 students on display Wednesday at the 48th Hawaii State Science & Engineering Fair at Blaisdell Center's Exhibition Hall.... Kimberly Reinhold's computer science projects have progressed into uncharted territory over a four-year period. The only child of Big Island pathologists Rhoda and Charles Reinhold, Kimberly became interested in artificial intelligence research after reading an article in one of her father's magazines, Scientific American. ... Reinhold, who has been accepted by Massachusetts Institute of Technology, said the Science Fair inflamed her interest in artificial intelligence research. 'I decided it's what I want to do in life,' she said. ... Kimberly Reinhold's favorite part of the Science Fair is the verbal requirement, which counts as 10 percent of the judging. 'If you can't articulate your project, people won't ever understand its significance,' Reinhold said."
>>> Cognitive Science, Resources for Students

March 24, 2005: A New Company to Focus on Artificial Intelligence. By John Markoff. The New York Times (registration req'd.). "Jeff Hawkins and Donna Dubinsky ... plan to announce the creation of Numenta, a technology development firm that will conduct research in an effort to extend Mr. Hawkins's theories. ... Artificial intelligence, which first attracted computer scientists in the 1960's, was commercialized in the 1970's and 1980's in products like software that mimicked the thought process of a human expert in a particular field. But the initial excitement about machines that could see, hear and reason gave way to disappointment in the mid-1980's, when artificial intelligence technology became widely viewed as a failure in the real world. In recent years, vision and listening systems have made steady progress, and Mr. Hawkins said that while he was uncomfortable with the term artificial intelligence, he believed that a renaissance in intelligent systems was possible. He said that he believed there would soon be a new wave of software based on new theoretical understanding of the brain's operations. 'Once you know how the brain works, you can describe it with math,' he said."
>>> Cognitive Science, AI Overview, Pattern Recognition, Neural Networks, Applications, AI Effect, Machine Learning, Expert Systems; also see these related articles: 1 & 2

March 22, 2005: IBM computing algorithm thinks like an animal. By Michael Kanellos. CNET News.com. "IBM has devised a way to let computers think like vertebrates. Charles Peck and James Kozloski of IBM's Biometaphorical Computing team say they have created a mathematical model that mimics the behavior of neocortal minicolumns, thin strands of tissue that aggregate impulses from neurons. Further research could one day lead to robots that can 'see' like humans and/or make appropriate decisions when bombarded with sensory information. ... Over the past two years, researchers have increasingly looked toward nature as a model to emulate."
>>> Cognitive Science, Neural Networks & Connectionist Systems, Machine Learning, Artificial Life

March 20, 2005: Computers gain power, but it's not what you think - Performing complex tasks at lightning speed is the machine's greatest strength; thinking, intelligence still in our heads. By Jon Van. Chicago Tribune. "[Donald] McLellan uses software called Watson, developed at Northwestern University and marketed by Chicago's Intellext Inc., which is part of a new wave of programs that provide computers with something akin to human intelligence. But these programs do not think for their users. Rather, after decades of trying to create machines that can think, researchers now just want to make computers that are less stupid. The results are impressive. ... Computers have long been likened to human brains, sparking fears and hopes that someday a collection of silicon and wires would think like a person. But even today's most powerful units are not smart enough to tie a shoelace or do anything most human 4-year-olds accomplish thoughtlessly. Even so, escalating computing power enables machines to recognize patterns and operate in ways that seem eerily intelligent. ... Northwestern professor Kristian Hammond, a co-founder of Intellext, was active in the artificial intelligence branch of computer science for years at Yale University and the University of Chicago before joining Northwestern. He no longer embraces the notion of intelligence commonly shared by artificial intelligence researchers. 'That model is that people have a clear, crisp idea of what they're thinking,' Hammond said. 'Our model is that there's never a clear idea; often it's just a collection of ideas in a context. You change the context and you change the intelligence.' A similar philosophy is at work at NICE Systems Inc., a Rutherford, N.J., firm that records call center conversations to monitor for quality. Its software can determine when a caller becomes emotional and can recognize specific words."
>>> Cognitive Science, Interfaces, Information Retrieval, Pattern Recognition, Neural Networks, Speech, Machine Learning, Systems, Applications

March 17, 2005: Complex instincts. The Engineer Online. "Robots already play a vital role in defence and security, space exploration and on the production line. They are also becoming increasingly important for entertainment applications and as human companions. But their usefulness doesn’t end there. According to Dr. Tony Prescott of the Department of Psychology at Sheffield University, robots can also play an important role in the search for answers to one of the most fundamental mysteries of life: The workings of the vertebrate brain. ‘Robots are a kind of physical model,’ explains Dr. Prescott. ‘We are simulating and building robots as a tool to gain a better understanding of what the brain is doing and how it is operating.’ ... By working to develop a robust control system for these multitasking robots, Dr. Prescott and his Sheffield-based colleagues - neuroscientist Professor Peter Redgrave, computational modellers Dr. Kevin Gurney and Dr Mark Humphries - make up one of the few groups internationally whose activities straddle neurobiological research, computational modelling and robot modelling. ... The group are also drawing inspiration for their work from the pioneering studies of artificial neural networks carried out in 1969 by Warren McCulloch at the Massachusetts Institute of Technology, a neuroscientist who was also interested in reverse engineering the brain to understand how it operates. ... [T]he Group’s work with robots is providing useful insights for applications such as computer games and the development of intelligent agents...."
>>> Cognitive Science, Robots, Neural Networks, Applications, Machine Learning

March 15, 2005: Sentient machines will raise human questions. Opinion by Tyson Durst. The Gateway (Volume XCIV, Issue 39). "To make this assumption and rule out the possibility that sentient machines will ever be created would be foolish and narrow-minded; so many of the technologies that we take for granted were once thought impossible. The race to build machines that possess consciousness is already underway -- one could argue that it's been underway since people first imagined artificial life. But today's scientists are looking at the data and theories that are available, re-examining the logic and flaws of this information and thinking about how we, as humans, think. For example, take the famous Turing test, proposed by Alan Turing in 1950. ... Scientists who are serious about research and development of true artificial intelligence, though, are very much interested in the internal processes going on in a computer. An example would be the simple action of walking.... For now, though, the days of computers that attain consciousness are still far off, although far from impossible. Before we will be able to finally build machines that think as we do, we will first have to figure out just how we think. ... A new field of science will likely be born -- 'artificial neuroscience' -- that will deal with the application of human consciousness within the construct of a computer, a 'ghost in the shell,' if you will."
>>> Cognitive Science, Philosophy, Turing Test, Ethical & Social Implications, Science Fiction

March 11, 2005: Where do i begin? By Stephen Pincock. The Financial Times. "Cyborgs are all around us. ... The dictionary definition of a cyborg is 'an integrated man-machine system'. They turn up in movies as flesh and metal characters such as Arnold Schwarzenegger’s Terminator, Darth Vader from Star Wars or, for those of an older vintage, Steve Austin, the Six Million Dollar Man. The term emerged in the 1960s, coined by researchers interested in how humans could adapt to space travel. ... Instead, I want to focus on a definition of cyborg that relates to our use of technology in a more general way. It is a definition that has sprung from a scientific view of the way our mind works and how its functions extend beyond our brains. ... The man I most wanted to contact was a philosopher of cognitive science, Andy Clark, professor of logic and metaphysics at the University of Edinburgh, and a leading proponent of the idea of the extended mind. Two years ago, Clark published a book entitled Natural-Born Cyborgs: Minds, Technologies and the Future of Human Intelligence, which explored the way that human minds interact with technology - from the pencil to web-enabled mobile phones. ... Clark argues that there is little significant conceptual difference between a highly accessible computer outside our body, and one implanted into our body. ... He urges us to give up the idea that the only things that matter about our minds are what goes on inside 'the ancient fortress of skin and skull'. Instead, technologies such as the internet should be seen as integral parts of the systems that constitute human intelligence."
>>> Nature of Intelligence, Cognitive Science, Systems, Robots

March 7, 2005: Ants - learning from the collective. By Peter Everett. BBC News. "The question that continues to fascinate myrmecologists (ant experts) is how ants manage to achieve such complicated results - elaborate nests, efficient food-supply, waste-disposal and so on - without having anyone in charge. ... When our present technology-driven society considers the ant, the aim is not to find moral guidance or to admire a perfect political system, but to gather clues that will help us to solve technical problems. In the Intelligent Autonomous Systems Laboratory at the University of the West of England, Dr Chris Melhuish presides over a fleet of 'U-bots'. A U-bot is a foot-high robot which glides around an arena on castors, carrying a U-shaped scoop in front of it. It is a very stupid robot, because it carries only three instructions:.... Following only those instructions, Dr Melhuish's robots, given enough time, can gather together a randomly distributed collection of frisbees and assemble them in a pile in the centre of their arena. ... Why would anyone want to design stupid robots that can do clever things? Dr Melhuish explains: 'If we want to build very small robots, there will be problems in getting computation on board, and sensing and communication. ... It would be nice to think that we could use nano-robots to carry out repair work inside the human body, but it's early days.' ... Myrmecologist Professor Nigel Franks, of the University of Bristol, has introduced the phrase 'collective intelligence' to describe ant behaviour.
>>> Multi-Agent Systems, Nature of Intelligence, Robots, Agents, Systems, Cognitive Science

March 3, 2005: New research opens a window on the minds of plants. By Patrik Jonsson. The Christian Science Monitor. "As trowel-wielding scientists dig up a trove of new findings, even those skeptical of the evolving paradigm of 'plant intelligence' acknowledge that, down to the simplest magnolia or fern, flora have the smarts of the forest. Some scientists say they carefully consider their environment, speculate on the future, conquer territory and enemies, and are often capable of forethought — revelations that could affect everyone from gardeners to philosophers. Indeed, extraordinary new findings on how plants investigate and respond to their environments are part of a sprouting debate over the nature of intelligence itself. 'The attitude of people is changing quite substantially,' says Anthony Trewavas, a plant biochemist at the University of Edinburgh in Scotland and a prominent scholar of plant intelligence. 'The idea of intelligence is going from the very narrow view that it's just human to something that's much more generally found in life.' To be sure, there are no signs of Socratic logic or Shakespearean thought, and the subject of plant 'brains' has sparked heated exchanges at botany conferences. ... 'If intelligence is the capacity to acquire and apply knowledge, then, absolutely, plants are intelligent,' agrees Leslie Sieburth, a biologist at the University of Utah in Salt Lake City. ... The new field of plant neurobiology holds its first conference - The First Symposium on Plant Neurobiology - in May in Florence, Italy."
>>> Nature of Intelligence, Cognitive Science; also see the toon, But Is It AI? (#2)

February 28, 2005: Business Notes. The Ann Arbor News. "Soar Technology Inc. of Ann Arbor reported that revenue grew by 44 percent in 2004.... The company is also adding professional staff, scientists, engineers and programmers. Soar is a spinoff from the Artificial Intelligence Laboratory at the University of Michigan. The company develops intelligent autonomous agent software and cognitive systems."
>>> Agents, Cognitive Science, Applications, Careers in AI (@ Resources for Students)

February 22, 2005: New university course puts the 'human' in the humanities - PSY 214 examines the the blurred lines of what it means to be human. By David Campbell. The Princeton Packet. "'The course is timely because of the great advances achieved in neuroscience and artificial intelligence over the past few decades,' said psychology Professor Daniel Osherson, who coordinated the course, offered for the first time at Princeton last fall. 'They prompt new reflection about the place of humans in the biological world and the world of intelligent devices,' he said. The new psychology class is interdisciplinary. In the fall term, it featured guest lecturers from 13 different academic departments, including classics, computer science, economics, molecular biology and genomics, philosophy and physics. Subjects ranged from Aristotle to artificial intelligence. ... 'It was a great introduction to the range of cognitive science research being done on campus, and I learned a lot in the course myself,' [Professor Adele Goldberg] said. Why this course, and why now? 'The explosion in neuroscience is a recent phenomenon, facilitated by new experimental techniques that make it possible to study the brain in noninvasive ways,' Professor Goldberg said. 'Impressive advances in intelligent systems have also been made in the last decade. The more understanding we gain about how our brains work, the more the question arises as to whether we are simply chemical machines.'"
>>> AI Courses (@ Resources for Students), Ethical & Social Implictions, Cognitive Science, Natural Language Processing

February 20, 2005: Who Do You Trust More: G.I. Joe or A.I. Joe? By George Johnson. The New York Times (registration req'd.). "In a story by Isaac Asimov, three technocrats are sitting in an underground cavern stuffed with electronics discussing how, with a computer named Multivac, they won the war. ... But the earthlings, relying on the help of an artificial, dispassionate intelligence - this sprawling subterranean computer - had ultimately prevailed. Recent reports that the Pentagon is planning to spend tens of billions of dollars over the next decade to perfect computerized warfare sound like science fiction. In fact, the plan, Future Combat Systems, was first dreamed up years ago. Its designers envisioned a 21st-century fighting force of automated tanks, helicopters and planes, remote missile launchers and even troops of robot soldiers - all coordinated by a self-configuring network of satellites, sensors and supercomputers. A way to get the human out of the loop. ... Ever since the catapult, warfare has been technology's driving force. Computers were first developed to calculate missile trajectories and break enemy codes. But so far it's been only in science fiction that anyone has dared to turn over decision making to machines. ... As the thinking machinery continues to evolve, the strategists will keep asking themselves the same question: Is there still a good reason to trust ourselves or should we defer to a computer's calculations?"
>>> Military, Autonomous Vehicles, Ethical & Social Implications, Science Fiction, History, Cognitive Science, Applcations

February 10, 2005: Spring comes to AI winter. By Heather Havenstein. Computerworld & IDG (Sweden). "For many people, artificial intelligence evokes the menacing computer Hal from '2001: A Space Odyssey,' a machine so intelligent that it could function independently of humans. Those inflated notions spawned by science fiction writers about the convergence of humans and machines tarnished the image of AI in the 1980s because AI was perceived as failing to live up to its potential. Still, the field has quietly produced advanced applications such as Google Inc.'s search engine, systems that trade stocks and commodities without human intervention, and software that detects credit card fraud. There's no precise definition of AI, but broadly, it's a field that attempts to provide machines with humanlike reasoning and language-processing capabilities. Researchers now are emerging from what has been called an 'AI winter' with renewed interest in the biology of the brain and research honed to practical applications in medicine, customer service, manufacturing, education and other areas."
>>> Applications, AI Overview, Natural Language Processing, Cognitive Science, Machine Learning, Education, Medicine, Customer Service, Manufacturing, Banking & Investing, Fraud Detection & Prevention, Information Retrieval, Science Fiction

January 8, 2005: Voicemail software recognises callers' emotions. By Celeste Biever. New Scientist Magazine. "A voicemail system that labels messages according to the caller's tone of voice could soon be helping people identify which messages are the most urgent. The software, called Emotive Alert, is designed by Zeynep Inanoglu and Ron Caneel of the Media Lab at the Massachusetts Institute of Technology. ... Another British company, Edinburgh-based Affective Media, will soon be selling software for cars that detects drowsiness and frustration in a driver's voice as he or she asks the in-car navigation system for directions, and will attempt to wake the driver up or calm them down, as appropriate. It could also be used in computer games to detect boredom levels and spice up the action accordingly."
>>> Speech, Machine Learning, Emotion, Interfaces, Natural Language Processing, Telecommunications, Transportation, Video Games, Cognitive Science, Applications

January 3, 2005: As robots learn to imitate. IST Results. "Can robots learn to communicate by studying and imitating humans’ gestures? That’s what MIRROR’s researchers aimed to find out by studying how infants and monkeys learn complex acts such as grasping and transferring it to robots. 'Our main motivation for the project was to advance the understanding of how humans recognise and imitate gestures,' says Professor Giulio Sandini, coordinator of the three-year IST-funded project, MIRROR. 'We did that by building an artificial system that can learn to communicate by means of body gestures.' ... Although the project is finished, all the members of the consortium now participate in a follow-up FP6 IST project called RobotCub...."
>>> Cognitive Science, Robots

January 2005: What We Can Learn from Robots. By Gregory T. Huang. Technology Review. "On a crisp october day last year, Carnegie Mellon University’s Robotics Institute kicked off its 25th-anniversary celebration.... On the third day, it was Mitsuo Kawato’s turn to speak. The lights went down, and the director of the ATR Computational Neuroscience Laboratories in Kyoto, Japan, made his way to the stage to the beat of rock music. ... [T] here is a difference between him and other attendees. Kawato loves robots not because they are cool, but because he believes they can teach him how the human brain works. 'Only when we try to reproduce brain functions in artificial machines can we understand the information processing of the brain,' he says. It’s what he calls 'understanding the brain by creating the brain.' By programming a robot to reach out and grasp an object, for instance, Kawato hopes to learn the patterns in which electrical signals flow among neurons in the brain to control a human arm. ... 'This is very different from the usual justification for building humanoid robots --- that they are economically useful or will help take care of the elderly,' says Christopher Atkeson, a robotics expert at Carnegie Mellon. ... The evolution of robots into something more humanlike is probably inevitable. Experts agree there is nothing magical about how the brain works, nothing that is too inherently complex to figure out and copy. As Kawato is learning in his lab, the ultimate value in closing the gap between humans and machines might lie in what new generations of robots can teach us about ourselves."
>>> Robots, AI Overview, Cognitive Science, Neural Networks & Connectionist Systems, Machine Learning, Interfaces, Systems, Assistive Technologies

December 31, 2004: Robots Are Learning, But No "Terminators" Are About To Appear. By David Isaac. Investor's Business Daily (subscription req'd.). "While we're not in danger of creating any Terminators soon, scientists are making robots more intelligent. They are teaching robots via a concept called machine learning. The specifics of machine learning are complex, but the basics are simple: Machines can 'learn' from their own experiences. Computers truly will learn, improve and become smarter with experience, says Tom Mitchell, director of the Center for Automated Learning and Discovery at Carnegie Mellon University. Robotics engineers have turned to machine learning because it's more effective and more practical than having to use computer programming to code every scenario a robot might encounter. ... Mitchell is using machine learning to find out what goes on in the human brain when a person reads. The research, he says, might offer insight into how the mind organizes conceptual categories, such as 'tools' and 'animals.' ... But, cautions Mitchell, machine learning is not creating human robots. The human mind is not like a computer, he says. 'It's a very different kind of machine. It's not so digital as it seems. We have a much more distributed network of neurons,' Mitchell said. His caution is well-grounded. There's a long tradition of comparing the human mind to the latest man-made technology. But the comparisons have proved inaccurate. ... On the other hand, it turns out aspects of machine-learning can be compared to the way the mind works. Take reinforcement learning, one approach that is part of machine learning and human learning. This approach involves giving the robot a reward, essentially pushing a green button for good and a red button for bad. ... It seems this is similar to how the mind functions. Mitchell says the chemical dopamine, which produces a sensation of pleasure, acts like the green button, as a reward signal."
>>> Machine Learning, Robots, Neural Networks, Reinforcement Learning, Cognitive Science, Speech, Vision, Multi-Agent Systems, Applications, AI Overview

December 23, 2004: Christmas, AI and 'The Uplift Wars.' Commentary by Paul Murphy. LinuxInsider News. "I've been rereading David Brin's first Uplift series -- as astonishingly self-consistent a vision of galactic life as any science fiction writer has ever offered and quite appropriate to the Christmas season. In Brin's imaginary universe, a mysterious and long gone race known as the progenitors set in place a unity of life across five galaxies largely by focusing moral valuations around the development and protection of sentience. ... Tracy Kidder's book, The Soul of a New Machine, isn't about the soul of the machine at all, but about the commitment of the engineers developing it. Implicitly, however, there are assumptions of both value and transfer in the book: value in the sense that the human commitment, emotions and drives are assumed to be worthwhile, and transfer in the sense that the effect of these factors among the developers is presented as adding value to the machine. You don't see consideration of anything remotely like that in the writings credited as fundamental among the artificial intelligence community. ... There isn't, for example, a working definition of intelligence that can be used to unambiguously differentiate what is, and is not, intelligent."
>>> Nature of Intelligence, Turing Test, Cognitive Science, Philosophy, Science Fiction

December 13, 2004: No End To His Imagination. By Ken Spencer Brown. Investor's Business Daily (reg. req'd.). "Imagination should have no limits. And for Alan Turing, it didn't. By refusing to envision only what was strictly practical, he expanded the bounds of what was possible. ... Turing's most advanced ideas became a foundation for computer science with the dawning of the digital age he'd envisioned. If things like software code, cryptography and artificial intelligence leave you scratching your head, just imagine wrestling with those concepts decades before the invention of the computer. ... Normally gentle in speech, Turing would defend his friends' views intensely when they were challenged. They often inspired him, too. The death of a close schoolmate in February 1930 sparked Turing's first published thoughts in metaphysics. In letters to the friend's mother, Turing pondered the connection between the human mind and the brain. These ideas sparked his thinking on artificial intelligence, which tries to model the human brain and the thought process. ... Turing described the functions of a machine that could solve any problem stated as a mathematical algorithm. Now known as a Turing machine, the theoretical device was the first to conceive of a general-use device that could store data and instructions and be programmed for lots of different math problems. ... Despite his work in artificial intelligence, Turing was no robot. He had a deep concern for other people."
>>> History, Turing Test, Turing (@ Namesakes), Cognitive Science

December 12, 2004: An Adventurous Thinker. Interview with Ray Kurzweil. DevSource. "DevSource: In your writing, you've mentioned that the human tendency to pervasively accept innovations --- such as AI and machine intelligence --- causes it to become invisible. And, as a result, AI has become 'the pursuit of difficult computer science problems that have not yet been solved.' That's surely true for my 85-year-old Mom, who isn't quite sure how e-mail works and simply accepts the magic as delivered. Are developers (the people creating tomorrow's innovative solutions, or at least tomorrow's payroll processing) equally blind? Should they be? Ray: As we master and understand a technique, we think in terms of that technique --- Markov models, genetic algorithms, search techniques, signal processing methods --- and not generally about 'AI.' As we progress through the reverse-engineering of the human brain, we will expand our AI tool kit to incorporate the brain's methods for learning, pattern recognition, and decision making. Brain reverse engineering has not contributed that much to AI to date because we have not until recently had the tools to see the brain in action at sufficient temporal and spatial resolution. ... Most mainstream applications in a wide range of fields incorporate techniques that were AI research projects only a decade ago. Examples include search engines, automated investing, credit card fraud detection, automated analysis of electrocardiograms and blood cell images, monitoring intensive care units, flying and landing airplanes, guiding weapon systems, and many others."
>>> AI Overview, Cognitive Science, Applications, Systems, Interviews

November 29, 2004: How scientists might soon be able to build a better brain. Book review by John Rooney. The Philadelphia Inquirer & philly.com. "Do humans possess the ability to build an artificial brain that is more intelligent than the brightest human? This is the challenge Jeff Hawkins throws out to current and aspiring scientists in On Intelligence. To some readers the idea will conjure up specters of black magic and evil scientists bent on controlling the world. Hawkins, however, is not writing science fiction. The man who created the Palm Pilot and the Treo smart phone has one foot planted firmly in neuroscience and the other in computer science as his mind imagines fascinating new ways of combing the two. Research in artificial intelligence (AI) and neural networks have already made remarkable advances. ... Hawkins holds that computer scientists have been focusing too much on the end product. Like B.F. Skinner, who held that psychologists should study stimuli and responses and ignore the cognitions that go on in the brain, scientists working in AI and neural networks have focused too much on inputs and outputs rather than the neurological system that connects them."
>>> Neural Networks & Connectionist Systems, Machine Learning, Cognitive Science; also see this related article

November 24, 2004: Toward a More Human Robot - Carnegie Mellon's Takeo Kanade explains why making smarter systems requires better understanding about how people really act. Interview by Cliff Edwards. BusinessWeek Online. "Q: What's ripe for innovation? A: Certainly, I'd like to comment on my own area, that is robotics, artificial intelligence [AI], and the like. My own thinking today is that I think we should understand how humans act and use that [insight] to develop a better system that serves for human. You can call it AI. I'm more interested in, and I believe it's useful and enormously valuable to understand, how humans function, not necessarily how humans are made. ... Q: What are the hurdles that robotics and AI need to overcome? A: The hurdle is we do not know ourselves, how we are doing. In general, I call it an invisible robotics -- environmental robotics. The environment as a whole is a robot, not the human individual humanoid or arm or mobile robot. ... Q: Is there a problem in the U.S. of underfunding areas of research? A: I'm less familiar about that area. I'm mostly dealing with places like DARPA [the Defense Advanced Research Projects Agency]. My concern is that we may be reducing what I call playfulness. In research, a large part of it is based on results. We're too result-oriented. The hallmark of the U.S., and I came from Japan and was very impressed with the difference I found, was what I call this playfulness -- people willing to pay money for those things which appeared to be somewhat ridiculous ideas. ..."
>>> Robots, Cognitive Science, Applications, Vision, AI Overview, Interviews, Resources for Students

November 13, 2004: Young guns in lab coats - They're fresh, they're smart and they're going to change our world. Here we introduce the brightest stars in medical science. By Mark Henderson, interviews by Seb Mackenzie-Wilson, and research by Zoe Strimpel. Times Online. "Lisa Saksida, 34, Unravelling Alzheimer’s: What does she do? Saksida develops artificial intelligence (AI) and computer models in the department of experimental psychology at Cambridge University to research how human and animal brains learn and remember. Originally, she applied knowledge of how human beings think to give robots AI. Now she has reversed that approach and is applying her knowledge of computers to increase our understanding of the mind."
>>> Assisitive Technologies, Medicine, Cognitive Science, Applications, Careers in AI (@ Resources for Students)

November 11, 2004: Emotional computing. By Ann Geracimos. The Washington Times. "People talking back to a computer is common enough -- usually in a moment of pique or frustration. Getting the computer to respond in kind is a far different task, one that computer scientists are undertaking with various degrees of success and consternation. The challenge isn't simply a matter of inventing new software and sometimes hardware, difficult enough as that is, but also of coming to grips with some of the ethics involved. If computers are to have emotional components, what role would they play in everyday life? Do human beings really want an emotional relationship with a mechanical mind? The field is called 'affective technology.' ... The term 'affective technology' has different meanings for different groups around the country doing research on human interaction with computers. ... Computers don't have emotional intelligence yet, in the sense of being able to express emotion intelligently, points out Ms. [Rosalind W.] Picard, who wrote at length on the subject in a 1996 MITPress book called 'HAL's Legacy: 2001's Computer As Dream and Reality.' HAL, of course, was the anthropomorphic computer in Stanley Kubrick's 1968 movie '2001: A Space Odyssey.'  Ms. Picard is especially interested in finding ways the technology could help children overcome frustrations in the learning process -- using the computer almost as a companion to work alongside the child who is attempting to process a great deal of information at once."
>>> Emotion, Interfaces, Ethical & Social Implications, Education, Science Fiction, Cognitive Science

November 10, 2004: Birmingham in €6m AI project. By Harry Yeates. ElectronicsWeekly.com. "Researchers in artificial intelligence (AI) at the University of Birmingham are participating in a €6.25m, four-year European project to develop a cognitive robot. One of the project's aims is to help throw some light on human cognition. The plan is to take the various AI systems that have so far been realised in some form or other ('natural language' systems that process human voice inputs and can use bits of our grammar and machine vision) and create a robot that combines those cognitive abilities. 'The idea is to put it all back together, and that's what's hard,' said Dr Jeremy Wyatt, a lecturer in computer science at Birmingham."
>>> Systems, Cognitive Science, Robots, Natural Language Processing, Vision, Reasoning, Representation, AI Overview

November 5, 2004: Hi robot. By Jon Excell. The Engineer & e4engineering.com. "UK researchers have received 1m Euros (£700,000) to investigate intelligent robots that can understand the ambiguities of natural speech and work more effectively alongside humans. The four-year project forms part of a wider European Commission initiative consisting of seven academic teams from around Europe known as Cosy (Cognitive Systems for Cognitive Assistants). ... Dr Jeremy Wyatt, who heads the Intelligent Robotics lab at Birmingham, said his group is looking at a number of significant problems involved in building 'thinking' robots. Wyatt referred to the recently published UN World 2004 robotics report - the theme of which was 'A robot in every home?' He explained that in order to arrive at such a situation, devices must be able to interact with us and satisfy our expectations about acceptable behaviour. One way in which they plan to do this is in the area of object recognition. Wyatt explained that his team will be working with computational linguists and cognitive psychologists in order to take ideas on how humans recognise things. He said that the team will begin by mounting a vision system on a mobile platform to watch an arm on a separate table and report back in natural language what it sees. An apparently humble aim, but it will nevertheless break new ground in the area of artificial intelligence."
>>> Robots, Natural Language Processing, Vision, Cognitive Science, Applications

November 1, 2004: Organised chaos gets robots going. By Will Knight. New Scientist Magazine(Organised chaos gets robot walking; issue of October 30, 2004 at page25). "A control system based on chaos has made a simulated, multi-legged robot walk successfully. The researchers behind the feat say it may have brought us closer to understanding how people and animals learn to move. ... ... Remarkably, the robot performed these tricks without any conventional programming. And its behaviour emerged far more quickly than it would if it had used genetic algorithms. Kuniyoshi suggests that his chaotic approach may have similarities to the way that biological systems learn to move. 'Many findings point to the presence of chaotic patterns in general in the human brain,' says Max Lungarella, who researches artificial intelligence at the University of Tokyo. But [Yasuo] Kuniyoshi and [Shinsuke] Suzuki’s approach is still unconventional, he says. 'It diverges radically from the traditional way of thinking about intelligence.'"
>>> Cognitive Science, Robots, Genetic Algorithms, Machine Learning, Artificial Life

October 22, 2004: Brain in a Dish Flies Plane. By Jennifer Viegas. Discovery News. "A University of Florida scientist has created a living 'brain' of cultured rat cells that now controls an F-22 fighter jet flight simulator. Scientists say the research could lead to tiny, brain-controlled prosthetic devices and unmanned airplanes flown by living computers. And if scientists can decipher the ground rules of how such neural networks function, the research also may result in novel computing systems that could tackle dangerous search-and-rescue jobs and perform bomb damage assessment without endangering humans. ... The brain can learn, just as a human brain learns, [Thomas DeMarse] said. When the system is first engaged, the neurons don't know how to control the airplane; they don't have any experience. ... This brain-controlled plane may sound like science fiction, but it is grounded in work that has been taking place for more than a decade. A breakthrough occurred in 1993, when a team of scientists created a Hybrot, which is short for 'hybrid robot.' The robot consisted of hardware, computer software, rat neurons, and incubators for those neurons. The computer, programmed to respond to the neuron impulses, controlled a wheel underneath a machine that resembled a child's toy robot."
>>> Neural Networks, Cognitive Science, Machine Learning, Robots, Autonomous Vehicles, Systems

October 22, 2004: What robots tell us about ourselves. Comment by Peter Foster. Financial Post. "This week, the Geneva-based United Nations Economic Commission for Europe and the International Federation of Robotics issued a report on world robotics. The best headline I saw on the report read 'UN: Robots to vacuum, do windows.' As suggested by Asimo, if robotics is the future, then it is a mundane future indeed. We have always overestimated the potential of robots because we have underestimated the complexity of ourselves. Industrial robots have been around for more than 40 years, but in what seemed like an astonishing move, some companies recently started replacing robots with humans. That's because humans have a level of flexible intelligence that a robot may never be able to match. ... Dr. Smith's fascinating book [Why We Lie, The Evolutionary Roots of Deception and the Unconscious Mind]-- which is filled with historical, literary and cultural references, from the Trojan Horse through Mark Twain to the Easter Bunny -- indicates that just as we overestimated the physical possibilities of robots by a failure to understand the complexity of our motor functions, so we underestimate even more the stunning complexity of our conscious and unconscious minds. What work in robotics and artificial intelligence has demonstrated above all is how remarkable we are."
>>> Cognitive Science, AI Overview, Robots, Science Fiction

October 21, 2004: Wizard of the Wireless Future - Palm pioneer Jeff Hawkins explains why one mobile device will soon do it all, how robots will evolve, and more. Interviewed by Cliff Edwards. BusinessWeek online. "Jeff Hawkins created the first Palm Pilot (PLMO ) digital organizer and then went on to create the Handspring Visor line as well as the popular new Treo 600 combination cell phone, e-mail device, and organizer. His new book, On Intelligence, explores the structure of the human brain and how that understanding will help create a new breed of truly intelligent machines. ... Q: Are you talking about artificial intelligence and moving it to the elderly population? A: I write about this in the book. The whole last chapter is dedicated to how this will play out. When people think of robotics, they think we're going to have these robots like in the movies and they're going to be talking to you and doing things. But the business of intelligent machines is different than people think. ..."
>>> Nature of Intelligence, Cognitive Science, AI Overview, Interviews; also see this related article

October 19, 2004: Insects could hold the key to artificial intellegence. By Lorraine Pace. North Texas e-News. "You have seen the movies in which robots are self-aware and joked about computer cockroaches, but scientists in their quest to understand intelligence and to develop artificial intelligence in robotics have actually turned to the study of insects and primitive vertebrates. They are looking at how these react to stimuli and how they develop memory, striving to replicate it in robotics for use in applications as diverse as medicine and space exploration. 'Something eluded us,' says Dr. Derek Harter, assistant professor of computer science and information systems at Texas A&M University-Commerce. 'We started off by studying human intelligence, but did not find the answers we were searching for.' ... 'Initially a lot of research into artificial intelligence was focused on human cognition in a top-down approach. The human capabilities that most impressed were chess playing and logical reasoning. However, we are now developing a different approach, starting with the study of insects and moving to primitive animals with a central nervous system -- like salamanders, in which we have found long-term brain memory'"
>>> Cognitive Science, Chess, Reasoning, Machine Learning

October 17, 2004: Book explains limits of AI, wonders of human brain. By Lynn Yarris. The Mercury News. "'I, Robot' was set in the year 2035. Is it possible that artificial intelligence (AI) will be that advanced in the next 30 years? Not if we continue down our current path of development, according to the man who was the creative genius behind the PalmPilot and the Treo smartphone. In 'On Intelligence,' Jeff Hawkins takes a detailed look at how the human brain works, compares this to how AI currently works and concludes that our machines will never get there from here. 'Many people today believe that AI is alive and well and just waiting for enough computing power to deliver on its many promises,' Hawkins says. 'I disagree. AI suffers from a fundamental flaw in that it fails to adequately address what intelligence is or what it means to understand something.' ... 'Why can a six-year-old hop gracefully from rock to rock in a streambed while the most advanced robots of our time are lumbering zombies?' Hawkins asks. ... The answer, as Hawkins and [Sandra] Blakeslee demonstrate, is that the human brain doesn't compute answers to problems; it retrieves answers from memory. While it takes a great many steps to compute something, it takes only a few steps to retrieve it from memory. The seat of human intelligence, where all this memory storage and retrieval takes place, is the neocortex.... As to the question of whether we can build truly intelligent machines, Hawkins believes the answer is yes, but those machines won't be the humanoid robots we're used to seeing in films like 'I, Robot.'"
>>> Nature of Intelligence, AI Overview, Cognitive Science, Robots

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