Re: [MIT-OpenCourseWare-Discussion] What We Can Learn from Robots
Why should homo sapiens set the standard for what constitutes
intelligence? Why not see if robo sapiens can give us a new standard?
Imagine a robot like Hubo or Asimo in an MIT classroom giving lectures on
electrical engineering with Q-A sessions. Why not try it out if MIT
really wants to "reinvent teaching and learning" as Dean Magnanti says?
We might learn a new definition of intelligence.
POC
On Wed, 29 Dec 2004 thirtygrand@myway.com wrote:
>
>
> On a crisp october day last year, Carnegie Mellon University's
> Robotics Institute http://www.ri.cmu.edu/ kicked off its 25th-
> anniversary celebration, as the world's robotics experts came to
> Pittsburgh to see C-3PO, Shakey the robot, Honda's Asimo, and Astro
> Boy inducted into the Robot Hall of Fame. The next day saw
> demonstrations of running, snaking, and bagpipe-playing bots. 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 http://www.cns.atr.jp/ in Kyoto, Japan, made his way to
> the stage to the beat of rock music.
>
>
> Despite such a welcome, Kawato is an outsider here, dismissive of
> the self-congratulation that creeps into conversations about modern
> robotics. He begins his presentation by shuffling slowly across the
> stage, imitating how stiffly and deliberately today's humanoid robots
> walk. What this suggests, he says, is that scientists don't really
> understand how the human brain controls the body. If they did, they
> could re-create the process in a robot. Indeed, Kawato doesn't talk
> about improving robot vision or navigational controls, as many other
> speakers at the gala do. Instead, he describes the role of brain
> regions such as the cerebellum and basal ganglia in the acquisition
> of motor skills, carefully couching his explanations in terms that
> roboticists understand.
>
> On Kawato's lapel is a button that reads "I ♥ Robots!" But there 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.
>
> It's a surprising and controversial idea. Despite the increasing
> number of humanlike machines, robots and people are nothing alike.
> The human brain has billions of neurons interconnected in complex
> ways that no computer program can yet simulate. But Kawato believes
> that experiments on humanoid robots can, at least, provide
> simplified models of what certain groups of neurons in the brain are
> doing. Then, using advanced imaging techniques, he looks at whether
> brain cells in monkeys and humans accord with the models.
>
> "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. Rather, Kawato's motivation lies in using robots to
> gain insights into how people think, make decisions, and interact
> with the world. That information could help doctors design therapies
> for patients with brain injuries, strokes, and neurological disorders—
> even cognitive and behavior problems. Seeing what it takes to design
> a socially interactive robot, for example, might motivate a search
> for areas in the brain that are switched off in cases of autism.
> (Neural circuits in the basal ganglia are prime candidates.) A robot
> arm that becomes unstable when feedback signals are delayed might
> suggest a new source of tremors in the cerebella of Parkinson's
> patients.
>
> As a tool for understanding the mind, robots are "extremely
> valuable," says Antonio Damasio, head of neurology at the University
> of Iowa http://www.uiowa.edu/ and the author of three books on the
> brain that have popularized the notion of "embodied
> intelligence." "Robots can implement and test how processes like
> movement can occur," he says. By extending these models to develop a
> broader theory of the mind, Damasio adds, "we'll know more and more
> about what it takes for, say, human consciousness to operate."
>
>
>
>
>
> Lost in Translation
> There's a Japanese proverb that says, "To teach is to learn." Down
> the hall from Kawato's office at ATR, robot school is in session. In
> one corner, a researcher teaches the humanoid robot DB, short for
> Dynamic Brain, to interact with people. Built like a good-sized
> person, 1.9 meters tall and 80 kilograms, DB also moves like one:
> it's fast and graceful. The researcher stands in front of the robot,
> waving around a stuffed dog. DB watches, apparently intently, tilting
> its head and tracking the toy with its camera eyes. Then it reaches
> out with a hydraulic arm and pats the dog, a bit clumsily, on the
> head. A big screen nearby displays what the robot sees, as well as
> which algorithms it's running.
>
>
> But this isn't just another robot showing off its humanlike skills.
> Gordon Cheng, head of the humanoid robotics group at ATR, thinks of
> DB as an experimental subject that eats electricity and bleeds
> hydraulic fluid. Working with robots, says Cheng, teaches "how the
> pieces fit together to build a rich system" that can emulate the
> human brain and body.
>
> To control DB's arm, for instance, software computes what commands
> will produce the right sequence of joint movements to achieve a
> certain goal. Kawato and Cheng believe a similar process happens in
> the human brain: they think we use "internal models" to calculate
> relationships between neural signals and the resulting body
> movements. For example, when you're about to pick up a cup, neurons
> in your brain access internal models to figure out what series of
> signals to send to your shoulder, elbow, and wrist. It's as if your
> brain were carrying out calculations every time you drink your coffee.
>
> It is a system design that might seem intuitive to a roboticist, but
> for years most neuroscientists found it ridiculous. How, they asked,
> could neurons perform such complex computations? They believed the
> command signals from the brain were much simpler, and that muscles
> and reflexes—not some abstract model—largely explained motor
> behaviors. But over the last decade, Kawato has offered strong
> evidence to the contrary, arguing that internal models are in fact
> necessary for eye and arm movements and may even be important for
> interactions with people and with objects in the world.
>
> In practice, however, it's difficult to draw direct connections
> between robots and humans. To do so would require the robots and
> their algorithms to mirror human physiology and neurology as closely
> as possible. Yet DB's brain doesn't even reside in its head,
> occupying several racks of computers, and a different scientist is
> needed to fire up each of the robot's many behaviors, such as
> reaching or juggling. How DB carries out a task may or may not have
> much to do with how a human brain operates. To find out, Kawato's
> team is studying how people learn to solve problems.
>
> In experiments conducted in Kawato's lab, subjects lie in a magnetic-
> resonance imaging machine and learn to use an unfamiliar tool, a
> modified computer mouse, to follow a moving target on a screen.
> Certain areas in the cerebellum light up, indicating increased blood
> flow in certain clusters of neurons. The researchers believe these
> neurons represent an internal model of the coordinated actions
> required for using the tool—much like the ones programmed into DB.
>
> By combining magnetic-resonance imaging, which offers millimeter-
> level resolution, with electrical and magnetic recording techniques,
> which resolve brain activity down to milliseconds, Kawato's group
> hopes to understand more of the details of what is happening among
> these neurons. It's what Kawato calls "mind decoding"—reading out a
> person's intent based solely on neural signal patterns. If
> successful, it would be a breakthrough in understanding how the mind
> works.
>
> Translating the brain's messages into language that a robot can
> understand is a step toward realizing a long-term technological
> ambition: a remote "brain-machine interface" that lets a user
> participate in events occurring thousands of kilometers away. A
> helmet could monitor a person's brain activity and report it, over
> the Internet, to a remote humanoid robot; in nearly real time, the
> person's actions could be replicated by a digital double. To build
> the system, researchers will need to look in the brain for specific
> signals, translate them, transmit the data wirelessly without large
> delays, and use them to control a device on the other end. The puzzle
> is far from complete, but Kawato's mix of neuroscience and robotics
> could at least snap the first few pieces into place.
>
>
>
>
>
> Robots 'R' Us
> Using robots to understand the human brain could also produce more
> autonomous robots. That may not be saying much. MIT artificial-
> intelligence pioneer Marvin Minsky says, "Robots today seem uniformly
> stupid, unable to solve even simple, commonsense problems." The most
> successful product from iRobot in Burlington, MA, a leading robotics
> company, is a vacuum cleaner. Industrial robots paint cars and build
> microchips but can't do anything they're not programmed to do. But
> there is increasing interest, especially in Japan and Europe, in
> developing new humanoid robots using insights from neuroscience.
>
>
> That development has already begun in Kawato's lab. As part of a
> five-year, $8 million project, DB is getting an overhaul*, based in
> part on what Kawato has learned from probing the human brain. The new
> robot—designed, like DB, by Sarcos of Salt Lake City, UT—will be more
> humanlike in its anatomy, brain architecture, power requirements, and
> strength. It will have powerful legs that will allow it to walk and
> run. (By contrast, the current DB can't walk.) Once the new bot is
> operational in late 2005, one of its first uses will be as a test
> platform for studying gait disorders and falls among elderly people.
>
> *Click here to see the brain and
> body of "DB2" under construction.
> http://www.technologyreview.com/articles/05/01/issue/flash_robots.asp
>
> Kawato is also laying the foundation for a grander collaboration
> between robotics and neuroscience. Together with Sony and Honda, he
> is lobbying the Japanese government to help fund a worldwide project
> to build a humanoid robot that would have the intelligence and
> capabilities of a five-year-old child. In addition to the
> technological payoff, says Kawato, the benefits to neuroscience would
> be immense, though he believes it will take upwards of $500 million a
> year for 30 years to make it happen.
>
> 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.
>
>
>
>
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>
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>
> OCW: REINVENTING TEACHING AND LEARNING WITH A TEACHING-LEARNING MACHINE
>
> OCW, in collaboration with Microsoft in Project I-Campus
> "...aspires to reinvent teaching and learning for the 21st.
> century research university" says MIT Dean of Engineering
> Thomas L. Magnanti. How far might we go with the OCW Teaching-Learning Machine?
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