Slashdot Mirror
MIT Creates Chip to Model Synapses
MrSeb writes with this excerpt from an Extreme Tech article: "With 400 transistors and standard CMOS manufacturing techniques, a group of MIT researchers have created the first computer chip that mimics the analog, ion-based communication in a synapse between two neurons. Scientists and engineers have tried to fashion brain-like neural networks before, but transistor-transistor logic is fundamentally digital — and the brain is completely analog. Neurons do not suddenly flip from '0' to '1' — they can occupy an almost-infinite scale of analog, in-between values. You can approximate the analog function of synapses by using fuzzy logic (and by ladling on more processors), but that approach only goes so far. MIT's chip is dedicated to modeling every biological caveat in a single synapse. 'We now have a way to capture each and every ionic process that's going on in a neuron,' says Chi-Sang Poon, an MIT researcher who worked on the project. The next step? Scaling up the number of synapses and building specific parts of the brain, such as our visual processing or motor control systems. The long-term goal would be to provide bionic components that augment or replace parts of the human physiology, perhaps in blind or crippled people — and, of course, artificial intelligence. With current state-of-the-art technology it takes hours or days to simulate a simple brain circuit. With MIT's brain chip, the simulation is faster than the biological system itself."
I agree with everything about this statement except the word "never."
Never is a pretty bold word. It puts you in a pretty gutsy mindset; one that isn't entirely productive to rational scientific analysis. The word "never" is pretty commonly seen in the company of "famous last words."
I think you have to credit MIT researchers for knowing better where the cutting edge is than you, and the writers of the article for including the 1960s in this paragraph:
'Previously, researchers had built circuits that could simulate the firing of an action potential, but not all of the circumstances that produce the potentials. “If you really want to mimic brain function realistically, you have to do more than just spiking. You have to capture the intracellular processes that are ion channel-based,” Poon says.'
More than just spiking; from my AI lectures years ago I recall that the McCulloch-Pitts neuron model of the was a spiking model (excitatory inputs, inhibitory inputs, thresholds) etc.