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Neuromorphic Chips: Building Intelligent Systems that are ‘Always On’
Neuromorphic chips are designed to mimic the computing pathways and characteristics of neurons in the brain. The idea of modeling computers on the workings of human brains isn’t new. Scientists made early attempts in the 1980’s using analog circuitry.
Standard computers are based on a central processor and memory chips that process calculations sequentially. But sequential processing can be painfully slow when dealing with things like image and pattern recognition. GPUs are a big improvement, but neuromorphic architectures promise even more.
Neuromorphic chip architectures have the potential to be much more powerful than sequential processing. Peter Suma, CEO of Applied Brain Research, said that “in the nearer term neuromorphics will enable many types of context aware AIs. Imagine, for example, a SIRI that listens and sees all of your conversations and interactions. You’ll be able to ask it for things like – ‘Who did I have that conversation about doing the launch for our new product in Tokyo?’ or ‘What was that idea for my wife’s birthday gift that Melissa suggested?'”
Unlike today’s AI that go dead when you are off-line, neuromorphic aims to be ‘always on’. Dr. Chris Eliasmith, a theoretical neuroscientist at Applied Brain Research, told Wired that “the ‘always on’ component is a necessary step towards true machine cognition. The most fundamental difference between most available AI systems of today and the biological intelligent systems we are used to, is the fact that the latter always operate in real-time. Bodies and brains are built to work with the physics of the world.”
