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CHINA BRAIN PROJECT Building Chinas First
Artificial Brain Prof. Dr. Hugo de
GARIS Director, Artificial Brain Lab, Cognitive
Science Department, School of Information Science
and Technology, Xiamen University, Xiamen,
CHINA. profhugodegaris_at_yahoo.com
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Prof. Dr. Hugo de Garis, Director of Chinas
first Artificial Brain Lab, Cognitive Science
Dept, Xiamen University, Xiamen, CHINA
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• Artificial Brains the
  Context
• The next decade or so will be exciting because -
• By 2020, one bit of information will be stored on
  a single atom.
• That means we will have Avogadro Machines (with
  1024 parts)
• Neuroscience is now learning the secrets of the
  micro-circuitry
• of the rat brain, e.g. the revolutionary
  work of Henri Markram.
• This micro-circuitry knowledge can be put into
  Avogadro Machines
• and speeded up a million times (electronic
  vs. chemical speeds).
• This marriage will provide the technologies for
  building artificial
• brains (e.g. to control home robots).
• f) Home robots (AB controlled), worlds biggest
  industry by 2030.

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Markrams simulated rat brain cortical column.
The rat has a few 1000s of such columns. Humans
have about a million. Markrams work creates
e-NS (neuroscience in a computer).
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CHINA BRAIN PROJECT
BASIC IDEA
Evolve 10,000s of neural net modules (in real
time?) to control the 100s of behaviors of a NAO
(French, Robocup standard) robot. So an
artificial brain is defined here to be a network
of (evolved neural) network modules. Each
module performs some simple task (e.g. recognize
someones face, detect the color of an object,
detect the direction of motion, ..), rather like
Minskys agents in his Society of
Mind. After the modules are evolved they are
connected to make an artificial brain (according
to the designs of human BAs (Brain
Architects)), whose neural signaling is
performed by the (IMSI) operating system.
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• Six Basic Components to
  this Project
• Parcone (Partially Connected Neural Evolutionary)
  model
• software used to evolve neural net pattern
  recognition modules
• b) NVidia PC Supercomputer, Tesla S1070, used to
  evolve
• neural net modules in (hopefully) real time,
  i.e. in about one second
• c) Operating system (IMSI, Inter Module
  Signaling Interface), used
• to perform the neural signaling of all the
  modules in the brain
• d) NAO robot, to be controlled by the
  artificial brain
• e) Language component, NAO robot talks, listens,
  understands,
• obeys simple commands, answers questions
• f) Consciousness component, self knowledge of
  own body, memory

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a)
PARCONE An essential ingredient in the China
Brain Project is the software that is used to
evolve neural net modules, called Parcone. The
artificial neurons evolved by this software are
partially connected. This allows users to
specify large numbers of input, middle and
output neurons (as parameters), e.g. an image of
6060 (RGB) pixels. This implies 60603
10,800 input neurons. (If the neural net
were fully connected gt 100,000,000s of
connections, too large!) Automated Evolution of
Positive and Negative Images Users supply M
positive images (of the pattern P to be learned)
and N negative images (i.e. not P). The module is
evolved to give strong positive output signals to
Ms, and strong negative signals to Ns.
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NList is a list of pointers to each neurons
list of neurons pointed to.

Data Structures of the Parcone Neural Net Model
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Parcone Experimental
Results Face recognition (90-95
accuracy). Color detection Motion
detection Hubel-Wiesel (slanted moving line of
light) detection Keys, shoes, . Counting
(3-ness, i.e. if 3 objects, the module
signals)
etc, etc. Parcone is a powerful pattern
detector. We plan to evolve 1000s of pattern
detector modules for our artificial brain.
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b) The NVidia PC Supercomputer, Tesla,
S1070 This PC supercomputer contain 960
processors, all working in parallel, at a total
speed of 4 teraflops, at the remarkable price of
only 10,000, a PC revolution! We are currently
learning how to program it (with a version
of the C language, called CUDA). 4 teraflops
is about 4000 times faster than an ordinary
PC. It takes about 30 minutes to evolve one
Parcone module on a PC. We therefore hope using
the Tesla, that we can do the same in about one
second, i.e. real time evolution.
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NVidias PC Supercomputer, Tesla S1070 960
processors, 4 teraflops, 10,000 We hope to get
real time evolution from it!
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Real Time
Percept Learning If the PC Supercomputer truly
allows us to evolve a neural net pattern
recognizer module in real time (i.e. about 1
sec.) then real time percept learning becomes
possible. We imagine that the NAO robot can
behave like a human baby, learning
constantly. When a new object is shown to the
robot, it checks all its previous pattern
recognition circuits. If none of them recognize
the object, i.e. all the pattern detector modules
give weak output signals, then, a new pattern
detector module is evolved and stored in
memory. The robot brain will be constantly
learning! Exciting prospect!
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• c) Operating System (IMSI)
• IMSI (Inter Module Signaling Interface), is the
  software
• operating system that performs the neural
  signaling of the
• whole artificial brain (of typically 10,000s of
  modules in real time)
• IMSI performs 4 major functions
• i) Specifies connections between modules
• ii) Calculates the neural output signals of all
  neurons in the brain
• iii) Interfaces with NOAs Choregraphe motion
  control software
• iv) Executes simple functions with ordinary
  programming routines.

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i) Specify connections
between modules IMSI prompts users (i.e. BAs
(Brain Architects)) to specify how the evolved
modules are to be connected to build an
artificial brain. Each evolved neural net module
has a unique integer identifier (ID). So too does
each input neuron and output neuron of a
module. e.g. a user can connect the 4th
output neuron of module 48234 to the 3rd input
neuron of module 29458, with -
(48234, 4) gt (29458, 3) These
connection data are stored in look up tables in
the IMSI, that are consulted when IMSI calculates
the output signals of all neurons.
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• ii) Calculate the strengths of the
  neural output signals
• IMSIs main job is to calculate the strengths of
  the neural output
• signals of all neurons in all the neural net
  modules in the artificial
• brain. To do this it uses the hash tables of each
  neuron, as well as
• the look up tables of the connections between
  modules.
• iii) Interfacing NAO robots Choregraphe
  motion control software
• The 100s of motions of the NAO robot are
  programmed by special
• software provided by Aldebaran (the French
  company that
• manufactures the NAO robots) called
  Choregraphe. Choregraphe
• generates (programmable) time dependent angle
  vectors, for the 25
• angles of the robots motors.
• iv) Simple-function
  programming modules
• Simple functions (e.g. AND) are executed in
  ordinary code.

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d) NAO Robot Noone
will see the artificial brain. Its just a set
of weights and connection numbers in a computers
memory. The intelligence and usefulness of the
artificial brain will be judged by the behaviors
of the robot it controls. The robot we chose for
the artificial brain to control was Frances
NAO (Chinese for brain coincidence?
marketing?) robot, waist high, 2 legs, 2 arms,
two fingers and thumb, 2 camera eyes, voice and
microphone. The NAO robot (made by Aldebaran,
Paris, France) has its own software, called
Choregraphe to control the time dependent angle
vectors of its 25 motors.
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e) Language Processing Prof
Ben Goertzel is working closely with Prof Hugo
de Garis on the China Brain Project. Ben
Goertzels role is to supervise two of the
components of the project, namely language
processing and consciousness Language The
NAO robot will be capable of NLP (Natural
Language Processing), listening, understanding,
obeying commands, answering questions, talking.
e.g. Go the door, Who is this?, It is Mr.
X, Who are you? I am NAO, an artificial
brain controlled robot. Where is the green
chair? In the corner that Im pointing towards.
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f)
Consciousness The NAO robot is to be given some
measure of consciousness or self knowledge, e.g.
recognizing parts of its own body, its reflection
in a mirror, meta knowledge of its own state,
etc. Hence, Prof de Gariss territory, is
the low level domains of perception, motion
control, operating system design, etc Prof Ben
Goertzels is the higher level domains of
language, consciousness, reasoning, logic,
etc. The NAO robot will be simulated so that
anyone on line can teach the NAO simulated robot.
This knowledge can then be used to control the
real world NAO robot, gt world project !
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• Other Developments
• Special Issue on Artificial Brains for the
  Neurocomputing
• journal, to appear 2010.
• Guest editors Prof. Dr. Hugo de
  GARIS
• Prof. Dr.
  John TAYLOR
• Prof. Dr.
  Ben GOERTZEL
• b) Book (contracted by World Scientific) on
• Artificial Brains An Evolved Neural Net
  Module Approach
• to appear 2010.
• Author Prof. Dr. Hugo de
  GARIS
• c) Dr. Ben Goertzel made a guest professor at
  Xiamen University
• d) Chinese NSF Funding Proposal A Humanoid
  Robot that
• Learns via Imitation and Reinforcement
• Proposers Prof. Dr. Hugo de GARIS, Prof.
  Dr. Ben GOERTZEL

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• CABA
• CABA (i.e. Chinese Artificial Brain
  Administration),
• (for USA) NABA (National Artificial Brain
  Administration)
• Similar to Americas NASA, i.e. a government run
  administration
• with 1000s of scientists and engineers aimed at
  building
• Artificial Brains for the countrys artificial
  brain industry,
• especially for the home robot industry.
• Prof de Garis is pushing the Beijing government
  to invest heavily
• in the creation of a CABA. There are strong
  reasons for this.
• One of the worlds biggest industries by 2030
  (economics)
• Fascinating problem (science)
• Dominating this industry gt national pride
  (psychology)
• International rivalry (China-US-EU-etc)
  (politics)
• Species dominance debate (philosophy)