“CHINA BRAIN” PROJECT Building China’s 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.

Prof. Dr. Hugo de Garis, Director of China’s first Artificial Brain Lab, Cognitive Science Dept, Xiamen University, Xiamen, CHINA

Artificial Brains – the Context The next decade or so will be exciting because :- a)By 2020, one bit of information will be stored on a single atom. b)That means we will have “Avogadro Machines” (with parts) c)Neuroscience is now learning the secrets of the micro-circuitry of the rat brain, e.g. the revolutionary work of Henri Markram. d)This micro-circuitry knowledge can be put into Avogadro Machines and speeded up a million times (electronic vs. chemical speeds). artificial e)This marriage will provide the technologies for building artificial brains brains (e.g. to control home robots). f) Home robots (AB controlled), world’s biggest industry by 2030.

Markram’s simulated rat brain cortical column. The rat has a few 1000s of such columns. Humans have about a million. Markram’s work creates “e-NS” (neuroscience in a computer).

“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 someone’s face, detect the color of an object, detect the direction of motion, …..), rather like Minsky’s “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.

Six Basic Components to this Project a)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

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 60*60 (RGB) pixels. This implies 60*60*3 = 10,800 input neurons. (If the neural net were fully connected => 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.

Chrm A chromosome is a pointer to NList A Hash is a hash table of pointers to a NeuronWt struct Neuron ID Weight Bits Weight Value NeuronWt struct HashPtr NList Population Chrm is a pointer to a population of chromosomes NListPtr Hash Data Structures of the “Parcone” Neural Net Model NList is a list of pointers to each neuron’s list of neurons pointed to.

Evolution Set Test Set 60*60 (pixel)*3 (RGB) = pixel values = input neurons to a Parcone module

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.

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.

NVidia’s PC Supercomputer, Tesla S processors, 4 teraflops, $10,000 We hope to get real time evolution from it!

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!

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 NOA’s “Choregraphe” motion control software iv) Executes simple functions with ordinary programming routines.

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 to the 3 rd input neuron of module 29458, with :- (48234, 4) => (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.

ii) Calculate the strengths of the neural output signals IMSI’s 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 robot’s “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 robot’s motors. iv) Simple-function programming modules Simple functions (e.g. “AND”) are executed in ordinary code.

d) NAO Robot Noone will “see” the artificial brain. It’s just a set of weights and connection numbers in a computer’s 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 France’s “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.

e) Language Processing Prof Ben Goertzel is working closely with Prof Hugo de Garis on the China Brain Project. Ben Goertzel’s 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 I’m pointing towards”.

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 Garis’s “territory”, is the low level domains of perception, motion control, operating system design, etc Prof Ben Goertzel’s 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, => world project !

Other Developments a)Special Issue on “Artificial Brains” for the Neurocomputing journal, to appear 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 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

“CABA” CABA (i.e. Chinese Artificial Brain Administration), (for USA) NABA (National Artificial Brain Administration) Similar to America’s NASA, i.e. a government run administration with 1000s of scientists and engineers aimed at building Artificial Brains for the country’s 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. a) One of the world’s biggest industries by 2030 (economics) b) Fascinating problem (science) c) Dominating this industry => national pride (psychology) d) International rivalry (China-US-EU-etc) (politics) e) “Species dominance debate” (philosophy)