A Skeptical Reaction To IBM's Cat Brain Simulation Claims

kreyszig writes "The recent story of a cat brain simulation from IBM had me wondering if this was really possible as described. Now a senior researcher in the same field has publicly denounced IBM's claims." More optimisticaly, dontmakemethink points out an "astounding article about new 'Neurogrid' computer chips which offer brain-like computing with extremely low power consumption. In a simulation of 55 million neurons on a traditional supercomputer, 320,000 watts of power was required, while a 1-million neuron Neurogrid chip array is expected to consume less than one watt."

Comments

nonlinear

[Garble Snarky]

Wouldn't power consumption grow more than linearly with neuron count? I would think the number of connections is the dominant factor - so the comparison of two data points of power consumption vs neuron count is meaningless.

long ways to go yet

[Anonymous Coward]

From the original FA: "The simulation, which runs 100 times slower than an actual cat's brain, is more about watching how thoughts are formed in the brain and how the roughly 1 billion neurons and 10 trillion synapses in a cat's brain work together."

So the most bad-ass computer simulation, assuming it worked, which this guy is saying it probably didn't, was still 100 times slower than a real cat's brain. A real cat's brain also fits inside a tiny furry space the size of a baseball... and it runs on a once-daily small bowl of cat food. We have a long ways to go.

Re:long ways to go yet

[Rod Frey]

Isn't there value in moving to a higher level of abstraction than a single neuron though? Or simplifying the basic elements for the sake of a tractable broader model?

Simulating a single atom, for example, is reasonably complex: it would be impossible with current computational resources to simulate the electromagnetic properties of a metal if we required accurate simulations of individual atoms. Yet despite ignoring what we know about the atomic models, the higher-level models are very predictive.

Not that we have such predictive, higher-level models for the brain. That's what some researchers are searching for: I'm just suggesting that those models hopefully won't require accurate simulation of individual neurons. That seems to be the pattern in other domains.

Brute force neurons...

[xtracto]

So according to this guy rant letter, the "cat-brain simulation" was nothing more than the simulation of a ANN wiht X number of neurons with X equal to the average number of neurons in a cat.

However, it seems the /complexity/ of the simulated neurons is not remotely similar to that of the neurons of a real cat.

With that view, yes it seems less breakthrough. The experiment reminds me of AI researchers that thought that we could get intelligent machines using a brute-force kind of approach; this by adding /enough/ knowledge-rules, /enough/ processing power, etc...

Re:Brain Power

[Yvan256]

In a simulation of 55 million neurons on a traditional supercomputer, 320,000 watts of power was required, while a 1-million neuron Neurogrid chip array is expected to consume less than one watt.

320kW / 55 = 5.818kW per million of neuro with a traditional supercomputer.
One watt per million of neuro with a Neurogrid chip array.

So if a cat's brain is 1 BILLION neurons, that would require 5818.182kW with a supercomputer and 1kW with the Neurogrid chip array.

A reduction of 5817.182kW.