A new approach to Artificial Intelligence

 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.

 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

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”

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

 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

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

 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…

 “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

A new way to do Artificial Intelligence

 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

Consists of digital cells and synaptic memory

 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

How To Create An Artificial Brain