IBM and Cornell Produce New Processor Composed of Artificial Neurons

Photo: IBM

A team of researchers from Cornell and IBM are calling the new processor TrueNorth and its something special  with Its 5.4 billion transistors include over 4,000 individual cores, each of which contain a collection of circuitry that behaves like a set of neurons.

The goal of the new technology is to create a processor that can act more asynchronously, handling erratic spikes in activity, which can behave more like neurons in systems that entail consciousness.

According to arstechnica each core has over 100,000 bits of memory, which store things like the neuron’s state, the addresses of the neurons it receives signals from, and the addresses of the neurons it sends signals to. The memory also holds a value that reflects the strength of various connections, something seen in real neurons. Each core can receive input from 256 different “neurons” and can send spikes to a further 256.




Computer transistors work in binary; they’re either on or off, and their state can only directly influence the next transistor they’re wired to. Neurons don’t work like that at all and the goal of designing a processor to mimic a neuron  is to create a a more flexible processing architecture. Neurons  can accept inputs from an arbitrary number of other neurons via a structure called a dendrite, and they can send signals to a large number of other neurons through structures called axons. Finally, the signals they send aren’t binary; instead, they’re composed of a series of “spikes” of activity, with the information contained in the frequency and timing of these spikes.

 Again, according to arstechnica,  while it’s possible to model this sort of behavior on a traditional computer, the researchers involved in the work argue that there’s a fundamental mismatch that limits efficiency. While the connections among neurons are physically part of the computation structure in a brain, they’re stored in the main memory of a computer model of the brain, which means the processor has to wait while information is retrieved any time it wants to see how a modeled neuron should behave. The TrueNorth processor allows each “neuron” to behave semi-independently and communicate with a different number of other “neurons,” depending on the operation.




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