Where are These Intelligent Robots of Which You Speak?

The brain's cerebellum (see illustration) has between 50 and 69 billion neurons.

Note that the rest of the brain is more like 16 billion neurons.
We are close to simulating the 16 billion neurons given that robots can fly an airplane from Boston to LA
without any human intervention.
We are not as close to simulating the 69 billion neurons in the cerebellum, which would allow us to
have a robot that could reach into "his" pant's pockets and retrieve a set of keys.
Since we can do the 16 billion neurons now, it gives us an idea as to how close we are to also
accomplishing those things whose function is more remote from our conscious minds.
Looks like we may have preliminary versions working by 2020-2025.

Full-blown versions should be working well and costs should be coming down by 2030 or so.

King Of The Chatbots , Agence France-Presse

Excerpts: George, who is 39, single and light-hearted, is looking for friends on the Internet. He has gifts:
the ability to speak in 40 languages and with 2000 people at the same time. There's just one quirk: he
doesn't really exist.

George is a piece of software, arguably the best of the speaking "chatbots" or talking robots, and he's
recently received the Loebner prize in Britain, a scientific award recognising the machines best capable
of matching the most realistic human dialogues with their own.

King Of The Chatbots, 2006/09/25, Agence France-Presse

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Audience, Inc.
From Audience, Inc.:
Lloyd Watts founded Audience, Inc., which is involved in simulating the human ear, cochlea and
auditory neural processing mechanism of the brain.  He described this in a 23 minute talk on May 3,
Lloyd Watts' first slide was the following:

"Audience is at the leading edge of the next generation of audio for telecommunications. Using
revolutionary core technology which duplicates human hearing biology, we are radically changing
the voice communications experience."
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Evolved Machines, Inc.

Paul Rhodes, Stanford & Evolved Machines, Inc., presented his company's simulation of growing
neurons in his presentation which you can find at:
His company can be found at: http://www.evolvedmachines.com/

From Evolved Machines:
"Visual object recognition systems
In the mammalian visual system, different retinal images of the same object may have no overlap, yet
trigger a largely constant representation in higher stations of the cortical hierarchy of cortical visual
areas.  This representation arises in concert with the report of perception of object identity, both
occurring in 140 ms in primates.  Since this time period is adequate for no more than 10 neuronal
input/output cycles it is likely that the invariant representation must be triggered by a largely
feedforward cascade of wiring-defined activation, rather than “computed” in an algorithmic sense.  Thus
it is the wiring which must embed this computation, so that when an image of an object is presented, the
representation is triggered, not computed.   Clearly the process by which the visual cortex is wired is
integral to any system of invariant object recognition based upon reverse engineering the brain.

"We simulate the self-organization of wiring patterns in a hierarchy of cortical areas by driving a filter
bank (either designed to be a center-surround or edge-detection array) with libraries of moving images,
and then employ a host of neural local mechanisms to drive the wiring process in an interconnected
cascade of arrays of electrically active branched neurons.  The intrinsic local neural mechanisms which
we found to be required for synthetic olfactory system function are employed in this more elaborate
hierarchical and somewhat topographic representation cascade, just as the mammalian visual cortex
circuitry is fashioned from neural components which evolved from the simpler and evolutionarily more
ancient olfactory cortex.  In each successive area the activity triggered by an object, its “representation”,
becomes more invariant to the classes of movements to which the system is exposed during the wiring
process, with activity in the later arrays in this “cortical” hierarchy furnishing the desired invariant
representation of its identity."

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DARPA Grand Challenge November 3, 2007
Race to Las Vegas
This time it is an urban race.

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R2 Corporation was purchased by Hologic.  Their computers have the ability to read breast X-rays for
cancer more accurately than any doctor.

About R2 Technology, Inc.
in the early detection of breast cancer, actionable lung nodules and other lung abnormalities. As a and
disease states R2 was given the 2004 Frost and Sullivan Product of the Year award. For information,
medical software company, R2 Technology is developing CAD systems for a variety of imaging modalities
and disease states R2 was given the 2004 Frost and Sullivan Product of the Year award. For information,
visit .

Film showing R2 technology of Computer Aided Detection:
Note that with multiple "slices" through breast, lung and colon with CT scans, the radiologist's job has
grown.  The computer is getting faster and has more experience.  The computer is trained on 6000
known cancer cases of breast cancer and a typical radiologist sees 10,000 patients and only 40 cases of
breast cancer.

R2 ImageChecker CT Lung CAD Featured on FOX KTVU 2 News

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Key Points

- I agree that compute capacity and memory of affordable machines will approach human-scale
levels by 2020-25.

- I remain optimistic that Neuroscience Knowledge will continue to advance over next 10-15 years
as needed to support neuroscientifically realistic algorithm development (cortical
structure/function-Callaway, Schuz, etc.)