Some think that AI will arise spontaneously when computer network complexity and processing capability approach the level of the human brain. This appears to miss the fact that the human brain evolved with many different areas of specialization. It's not the tabula rasa that some suppose.
Others think that the first AI will be achieved via reverse engineering of the human brain -- duplicating its structures without fully understanding how it works.
Another possibility is that the first significantly super-human intelligence will be based on an augmented human intelligence, but would the human portion would remain a significant portion of the whole?
The five robots that successfully navigated a 132-mile course in the Nevada desert last weekend demonstrated the re-emergence of artificial intelligence, a technology field that for decades has overpromised and underdelivered.
At its low point, some computer scientists and software engineers avoided the term artificial intelligence for fear of being viewed as wild-eyed dreamers.
Artificial Development is building CCortex, a massive spiking neural network simulation of the human cortex and peripheral systems. Upon completion, CCortex will represent up to 20 billion neurons and 20 trillion connections, achieving a level of complexity that rivals the mammalian brain, and making it the largest, most biologically realistic neural network ever built. The system is up to 10,000 times larger than any previous attempt to replicate primary characteristics of human intelligence.
CCortex employs a layered distribution of neural nets and detailed synaptic interconnections, closely emulating specialized regions of the human cortex, basal ganglia, thalamus and hippocampus. CCortex also extends the classical neural network paradigm of Hebbian connectivity to include temporal, analog representations of neuron spiking, enabling dynamic, real-time communication between neuron populations.
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AD is creating a bio-realistic simulation of the whole human brain to enable highly functional computational systems. CCortex.
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The Netscape IPO wasn't really about dot-commerce. At its heart was a new cultural force based on mass collaboration. Blogs, Wikipedia, open source, peer-to-peer - behold the power of the people.
Ten years ago, Netscape's explosive IPO ignited huge piles of money. The brilliant flash revealed what had been invisible only a moment before: the World Wide Web. As Eric Schmidt (then at Sun, now at Google) noted, the day before the IPO, nothing about the Web; the day after, everything.
Computing pioneer Vannevar Bush outlined the Web's core idea - hyperlinked pages - in 1945, but the first person to try to build out the concept was a freethinker named Ted Nelson who envisioned his own scheme in 1965. However, he had little success connecting digital bits on a useful scale, and his efforts were known only to an isolated group of disciples. Few of the hackers writing code for the emerging Web in the 1990s knew about Nelson or his hyperlinked dream machine.
At the suggestion of a computer-savvy friend, I got in touch with Nelson in 1984, a decade before Netscape. We met in a dark dockside bar in Sausalito, California. He was renting a houseboat nearby and had the air of someone with time on his hands. Folded notes erupted from his pockets, and long strips of paper slipped from overstuffed notebooks. Wearing a ballpoint pen on a string around his neck, he told me - way too earnestly for a bar at 4 o'clock in the afternoon - about his scheme for organizing all the knowledge of humanity. Salvation lay in cutting up 3 x 5 cards, of which he had plenty.
Although Nelson was polite, charming, and smooth, I was too slow for his fast talk. But I got an aha! from his marvelous notion of hypertext. He was certain that every document in the world should be a footnote to some other document, and computers could make the links between them visible and permanent. But that was just the beginning! Scribbling on index cards, he sketched out complicated notions of transferring authorship back to creators and tracking payments as readers hopped along networks of documents, what he called the docuverse. He spoke of "transclusion" and "intertwingularity" as he described the grand utopian benefits of his embedded structure. It was going to save the world from stupidity.
I believed him. Despite his quirks, it was clear to me that a hyperlinked world was inevitable - someday. But looking back now, after 10 years of living online, what surprises me about the genesis of the Web is how much was missing from Vannevar Bush's vision, Nelson's docuverse, and my own expectations. We all missed the big story. The revolution launched by Netscape's IPO was only marginally about hypertext and human knowledge. At its heart was a new kind of participation that has since developed into an emerging culture based on sharing. And the ways of participating unleashed by hyperlinks are creating a new type of thinking - part human and part machine - found nowhere else on the planet or in history.
Not only did we fail to imagine what the Web would become, we still don't see it today! We are blind to the miracle it has blossomed into. And as a result of ignoring what the Web really is, we are likely to miss what it will grow into over the next 10 years. Any hope of discerning the state of the Web in 2015 requires that we own up to how wrong we were 10 years ago.
Forget about smartphones. Two of the big brains behind those essential toys say they will build the basis of smart--really smart, like humans--machines, everywhere.
Jeff Hawkins and Donna Dubinsky, creators of the Palm and Handspring personal digital assistants and the Treo smartphone, have formed a software company built around a powerful and unorthodox vision of how the human brain works. In its early stages, they hope to create predictive machines useful for things like weather forecasting and oil exploration. Further out--much further, says Hawkins--they plan to lay the basis for cosmologically attuned robots that conceive and reflect on the universe itself.
Okay, it is a big idea. And so far the Menlo Park, Calif.-based company, called Numenta, has built what the creators say is a set of tools for creating pattern-recognition software capable of "learning" shapes and events, with a goal of foreseeing what the pattern will next create. Yet these tools draw on decades of work that Hawkins has done on how the brain works. If it pans out--and there is an attractive logic to much of his thinking--Numenta may certainly oversee the creation of embedded software that adapts and improves its own performance.
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.
A research paper on the model is expected to come out this week.
The brain consists of roughly 28 billion cells, Peck explained. The 200 million minicolumns essentially gather sensory data and organize it for higher parts of the brain. The minicolumns also communicate with each other through interconnections. Minicolumns are roughly 1/20 of a millimeter in diameter and extend through the cortex.
The mathematical model created at IBM simulates the behavior of 500,000 minicolumns connected by 400 million connections. With it, "we were able to demonstrate self-organization" and behavior similar to that seen in the real world, Peck said.
Ask most companies how they bring value to the market and they’ll point to their products. Cycorp is a bit different. The 10-year-old company cares about the services it sells—but mainly because they bankroll its true quest: creating a “knowledge base” called Cyc that can endow computers with something approaching common sense. This quest has been so time-consuming that most venture capitalists would long ago have written off their investments—or demanded the CEO’s head on a platter. That Doug Lenat and his 54 employees have avoided this fate is a lesson in managing long-term, visionary R&D projects.
Among the handiest villains in science fiction are Computers That Know Too Much. Think of the dream-weaving despots of The Matrix or murderous HAL in 2001: A Space Odyssey. But in reality, even the most super supercomputer lacks the reasoning capacity of a child engrossed in a Dr. Seuss book. Computers can't read the way we do. They can't learn or reason like us.
Narrowing that cognitive gap between humans and machines — creating a computer that can read and learn at a sophisticated level — is a big goal of artificial intelligence researchers.
The Pentagon's Defense Advanced Research Project Agency, or DARPA, granted a contract worth at least $400,000 last fall to two Rensselaer Polytechnic Institute professors who are trying to build a machine that can learn by reading.
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, an adjunct professor in electrical and computer engineering at the University of California, San Diego’s Jacobs School of Engineering, has also been a vice president of R&D at Fair Isaac Corporation since the company acquired a software firm he co-founded, HNC Software. He 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.”
Aristotle was one of the world's greatest thinkers ever. Digital Aristotle, on the other hand, knows as much about chemistry as a reasonably bright high school student, and nothing else. Yet a Seattle boutique investment firm, Vulcan Inc., is spending millions of dollars over the next few years trying to turn Digital Aristotle into, well, a digital Aristotle.
And why not? That's just a fraction of a percent of Vulcan founder Paul G. Allen's net worth. Even a noble failure would surely be at least as worthwhile as the Portland Trail Blazers professional basketball team, another of Allen's many interests. Allen, whose fortune derives from his standing as Bill Gates's original partner in Microsoft Corp., created Vulcan in 1986 to manage his investments.
Digital Aristotle began in 2003 as a contest, dubbed Project Halo. Three sets of high-powered researchers competed to create software that could do well on a high school advanced-placement exam in chemistry. They all succeeded. The winning program, written by a collaborative team from SRI International, in Menlo Park, Calif.; the University of Texas at Austin; and Boeing Phantom Works, in Seal Beach, Calif., scored a 3.00 on the exam out of a possible 5.00. That's better than the human student median grade of 2.82.
The scientists and engineers spearheading the creation of artificial beings and bionic people are responding to the magnetism of the technological imperative, the pull of a scientific problem as challenging as any imaginable.
Fascinating scientific puzzle though it is, the creation of artificial beings is also expected to meet important needs for society and individuals. Industrial robots are already widely used in factories and on assembly lines. Robots for hazardous duty, from dealing with terrorist threats to exploring hostile environments, including distant planets, are in place or on the drawing boards. Such duty could include military postings because there is a longstanding interest in self-guided battlefield mechanisms that reduce the exposure of human soldiers, and in artificially enhanced soldiers with increased combat effectiveness. (For this reason, the Department of Defense, largely through its research arm — the Defense Advanced Research Projects Agency — is the main U.S. funding source for research in artificial creatures.) Artificial creatures can also be used in less hostile environments: homes, classrooms, and hospitals and rest homes, serving as all-purpose household servants, helping to teach, and caring for the ill or elderly.
Among these possibilities, the connection between artificial creatures and human implants might be the most important because it promises enormous medical benefits. This connection might be the single greatest motivation to develop artificial beings. Yet regardless of their potential good uses, and apart from any issues of blasphemy, we have concerns about robots and androids. One fear is that the limitations we think to design out of our creations, from cosmetic deficiencies to the existential realities of illness and death, are essential human attributes, and that to abandon them is somehow to abandon our humanity. Something in us, it seems, fears perfection, and artificial beings threaten us with an unwelcome perfection, expressed as rigid unfeeling precision.
There is another menace first conveyed nearly 200 years ago in “Frankenstein,” and now more compelling than ever: the fear that technology will grow out of control and diminish humanity for all of us. That concern is hardly limited to artificial creatures. It appears in many arenas — the loss of privacy associated with new forms of surveillance and data manipulation; the depersonalization of human relationships; the incidence of human-made ecological disaster; the growing gap between the world’s technological “haves” and “have-nots.” It is especially and deeply unsettling, however, to contemplate the literal displacement of humanity by beings made in the human image, only better.
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