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A new approach to Artificial Intelligence.  There are HUGE differences between brain architecture and computer architecture  The difficulty to emulate.

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Presentation on theme: "A new approach to Artificial Intelligence.  There are HUGE differences between brain architecture and computer architecture  The difficulty to emulate."— Presentation transcript:

1 A new approach to Artificial Intelligence

2  There are HUGE differences between brain architecture and computer architecture  The difficulty to emulate one system on another system increases linear with the number of differences in architecture between the two systems.

3  The brain is an interactive information carrier.  Computer Emulation Issues: ▪ Making compromises in reduced neuron complexity ▪ Simplify the thousands of connections between neurons ▪ Simplify sensory devices (camera no match for the eye) ▪ Learning by feedback - a computer has no hardware for measuring timing differences between millions of input pulses. Learning is compromised

4 No computer is capable of emulating the entire human brain in real time at this present time Simulation of the brain on an IBM Blue Gene /P supercomputer: Model 1.6 billion neurons: 0.15% of real time 0.5% of capacity * Source: IBM publication “The cat is out of the bag”

5 Intelligent robots? FICTION C3PO is an intelligent, interacting robot…. R2D2 shows initiative and determination

6  To create this type of behavior would take approximately 4000 times the performance of current super-computers:  IBM Blue Gene/P – emulation of 1.6 billion neurons and 8.9 trillion synapses at 0.15% of real time. Ref. IBM publication ‘The cat is out of the bag’  IBM Blue Gene/p – emulating 900 million neurons and 9 trillion synapses at 1.2% of real time  Human brain: 88 billion neurons and an estimated 100 trillion synapses at 100% real time

7 REALITY: Violin playing robot (© Toshiba) Intelligent robots?

8  Recreating intelligence by program control involves a fundamental error in thinking:  The brain is not an analysis and control system  The brain is the only intelligent entity that we know off, consisting of memory and integrating cores  Learning is a fundamental function of the brain  Artificial Intelligence systems need to learn to control rather than being programmed to control  INTELLIGENCE is defined as the ability to acquire knowledge and to subsequently apply this knowledge, to combine it to form new solutions…

9  “Artificial Intelligence is the ability to perform a task that would require intelligence if done by a human being” – Minsky  We only use 10% of our brain (anonymous)  Bigger brains means smarter, and humans have the biggest brains of any animal  We have to emulate the entire human brain to create intelligence

10 A new way to do Artificial Intelligence

11  The brain is an interactive information carrier. Information is stored in synapses  Synapses are everywhere in the brain, therefore memory is everywhere - Fundamental  Learning is essential, it is how intelligence emerges and how the synapses are ‘programmed’, within a DNA-built Framework  A digital architecture that is similar to the cells that make up the brain, with analog synaptic parameters expressed as multi-bit digital values  Wired as a cortical column, a single chip contains 10,000 neurons and 500,000 synapses

12 Consists of digital cells and synaptic memory

13  A Synthetic Neuro-Anatomy will function like the brain when its neural cell emulation is sufficiently realistic and the network is the same as the biological model  The model needs to operate at real-time speed to allow learning to take place, in sync with the real world around us  Learning is the method by which a neural network acquires function

14 How To Create An Artificial Brain


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