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IBM unveils its the brain-inspired TrueNorth cognitive computer

August 19th, 2015 |  Published in Cognitive computing, General Technology  |  1 Comment

IBM TrueNorth

Gregory P. Bufithis, Esq.

19 August 2015 – Most efforts to mimic the brain have focused on software, but in recent years, some researchers have ramped up efforts to create neuro-inspired computer chips that process information in fundamentally different ways from traditional hardware. This includes an ambitious project inside tech giant IBM and Big Blue just released (while I am on vacation, of course!) a research paper describing the latest fruits of these labors. With this paper, published in the academic journal Science, the company unveils what it calls TrueNorth, a custom-made “brain-like” chip that builds on a simpler experimental system the company released in 2011.

So just a few brief notes:

Modern computing is built around, at its very core, adding and subtracting numbers. Simple calculations running billions of times per second keep track of all the important values, from what operating system you’re running to your stage in Candy Crush. With the unveiling of the new TrueNorth chip, IBM is fundamentally challenging that method with a chip based off the human brain.

Even as we pack more cores into processors and design new forms of memory storage, our computing technology is nowhere close to the power of the human brain. The human brain has roughly 100 trillion synapses – a neural network that took 96 racks of the Lawrence Livermore National Lab Sequioa supercomputer to simulate, and even then, the supercomputer was only able to perform that simulation at a speed 1,500 times slower than your brain does.

TrueNorth comes packed with 4,096 processor cores, and it mimics one million human neurons and 256 million synapses, two of the fundamental biological building blocks that make up the human brain. IBM calls these “spiking neurons.” What that means, essentially, is that the chip can encode data as patterns of pulses, which is similar to one of the many ways neuroscientists think the brain stores information.

I saw a quote by Carver Mead, a professor emeritus of engineering and applied science at the California Institute of Technology who is often considered the granddaddy of “neuromorphic” hardware, which was: “This is a really neat experiment in architecture. It’s a fine first step. Traditional processors —like the CPUs at the heart of our computers and the GPUs that drive graphics and other math-heavy tasks — aren’t good at encoding data in this brain-like way. That’s why IBM’s chip could be useful. Representing information with the timing of nerve pulses … that’s just not been a thing that digital computers have had a way of dealing with in the past”.

We don’t completely understand how the brain works. But in his seminal work, The Computer and the Brain, John von Neumann himself said that the brain is something fundamentally different from the computing architecture that bears his name, and ever since, scientists have been trying to understand how the brain encodes and processes information with the hope that they can translate that into smarter computers.

Neuromorphic chips developed by IBM and a handful of others don’t separate the data-storage and data-crunching parts of the computer. Instead, they pack the memory, computation and communication parts into little modules that process information locally but can communicate with each other easily and quickly. This, IBM researchers say, resembles the circuits found in the brain, where the separation of computation and storage isn’t as cut and dry, and it’s what buys the thing added energy efficiency—arguably the chip’s best selling point to date.

But some question how novel the chip really is: “The good point about the architecture is that memory and computation are close. But again, if this does not scale to state-of-art problems, it will not be different from current systems where memory and computation are physically separated. That from Eugenio Culurciello, a professor at Purdue University, who works on neuromorphic systems for vision and helped develop the NeuFlow platform in neural-net pioneer Yann LeCun’s lab at NYU.

And Yann … a Twitter buddy … has more detailed thoughts on his Facebook page (click here).

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"The mind that lies fallow but a single day sprouts up follies that are only to be killed by a constant and assiduous culture."
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