/ IBM Research – Zurich


Reactions to the computer giant's press release about SyNAPSE, short for Systems of Neuromorphic Adaptive Plastic Scalable Electronic, have ranged from conservative to zany. Some even claim it's IBM's attempt to recreate a cat brain from silicon.

"Each neuron in the brain is a processor and memory, and part of a social network, but that's where the brain analogy ends. We're not trying to simulate a brain," said IBM spokeswoman Kelly Sims. "We're looking to the brain to develop a system that can learn and make sense of environments on the fly."

The human brain is a vast network of roughly 100 billion neurons sharing 100 trillion connections, called synapses. That complexity makes for more mysteries than answers -- how consciousness arises, how memories are stored and why we sleep are all outstanding questions. But researchers have learned a lot about how neurons and their connections underpin the power, efficiency and adaptability of the brain.


Dharmendra Modha: We see an increasing need for computers to be adaptable, to develop functionality today's computers can't. Today's computers can carry out fast calculations. They're left-brain computers, and are ill-suited for right-brain computation, like recognising danger, the faces of friends and so on, that our brains do so effortlessly. The analogy I like to use: You wouldn't drive a car without half a brain, yet we have been using only one type of computer. It's like we're adding another member to the family. So, you don't view SyNAPSE as a replacement for modern computers?

Modha: I see each system as as complementary. Modern computers are good at some things -- they have been with us since ENIAC, and I think they will be with us for perpetuity -- but they aren't well-suited for learning.


To deliver real-time and useful performance, you have to run this cycle very, very fast. And that leads to ever-increasing clock rates. ENIAC's was about 100 KHz. In 1978 they were 4.7 MHz.

Today's processors are about 5 GHz. If you want faster and faster clock rates, you achieve that by building smaller and smaller devices. And that's where we run into trouble, right?

Modha: Exactly. There are two fundamental problems with this trajectory. The first is that, very soon, we will hit hard physical limits. Mother nature will stop us. Memory is the next problem. As you shorten the distance between small elements, you leak current at exponentially higher rates. At some point the system isn't useful. So we're saying, let's go back a few million years instead of ENIAC. Neurons are about 10 Hz, on average. The brain doesn't have ever-increasing clock rates. It's a social network of neurons.


Latest on