How brain-like circuits could push computing power to the next level
Why it matters
The performance of computers israpidly reaching a limitbecause the size of the smallest transistor in integrated circuits is now approaching 20 atoms wide. Any smaller and the physical principles that determine transistor behavior no longer apply. There is a high-stakes competition to see if someone can build a much better transistor, a method for stacking transistors or some other device that can perform the tasks that currently require thousands of transistors.
This quest is important because people have become used to the exponential improvement of computing capacity and efficiency of the past 40 years, and many business models and our economy have been built on this expectation. Engineers and computer scientists have now constructed machines thatcollect enormous amounts of data, which is the ore from which the most valuable commodity, information, is refined. The volume of that data is almost doubling every year, which is outstripping the capability of today’s computers to analyze it.
What other research is being done in this field
The fundamental theory of neuron function was first proposed byAlan Hodgkin and Andrew Huxleyabout 70 years ago, and it is still in use today. It is very complex and difficult to simulate on a computer, and only recently has it beenreanalyzed and cast in the mathematics of modern nonlinear dynamics theorybyLeon Chua.
I was inspired by this work and have spent much of the past 10 years learning the necessary math and figuring out how to build a real electronic device that works as the theory predicts.
There are numerous research teams around the world takingdifferent approachesto building brainlike, or neuromorphic, computer chips.
What’s next
The technological challenge now is to scale up our proof-of-principles demonstration to something that can compete against today’s digital behemoths.
This article is republished fromThe ConversationbyR. Stanley Williams, Professor of Electrical and Computer Engineering,Texas A&M Universityunder a Creative Commons license. Read theoriginal article.
Story byThe Conversation
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