If you’ve never heard of a memristor, you may soon, because it just might be the fundamental building block of what promises to be a revolutionary explosion you’ve heard coming for quite some time, the Internet of Things.
I am of a mixed mind about the potential for IoT to either be another tool that enhances the power of the individual and free associations or a tool of control wielded by coercive associations. To a degree, almost all technologies have that potential, but IoT, I believe offers the “opportunity” for central control and creating dependency on large-scale centrally controlled models than a lot of other technologies now emerging (like the blockchain or 3D printing).
Still, this Memristor offers a potential that might even go beyond IoT, and could even be a rival to quantum computing in terms of speed and power. Move over quantum computing (before you ever fully got out the door), here comes Neuromorphic Computing.
The internet of things is coming, that much we know. But still it won’t; not until we have components and chips that can handle the explosion of data that comes with IoT. In 2020, there will already be 50 billion industrial internet sensors in place all around us. A single autonomous device — a smart watch, a cleaning robot, or a driverless car — can produce gigabytes of data each day, whereas an airbus may have over 10,000 sensors in one wing alone.
Two hurdles need to be overcome. First, current transistors in computer chips must be miniaturized to the size of only few nanometres; the problem is they won’t work anymore then. Second, analysing and storing unprecedented amounts of data will require equally huge amounts of energy. Sayani Majumdar, Academy Fellow at Aalto University, along with her colleagues, is designing technology to tackle both issues.
Majumdar has with her colleagues designed and fabricated the basic building blocks of future components in what are called “neuromorphic” computers inspired by the human brain. It’s a field of research on which the largest ICT companies in the world and also the EU are investing heavily. Still, no one has yet come up with a nano-scale hardware architecture that could be scaled to industrial manufacture and use.
“The technology and design of neuromorphic computing is advancing more rapidly than its rival revolution, quantum computing. There is already wide speculation both in academia and company R&D about ways to inscribe heavy computing capabilities in the hardware of smart phones, tablets and laptops. The key is to achieve the extreme energy-efficiency of a biological brain and mimic the way neural networks process information through electric impulses,” explains Majumdar.
Basic components for computers that work like the brain
In their recent article in Advanced Functional Materials, Majumdar and her team show how they have fabricated a new breed of “ferroelectric tunnel junctions,” that is, few-nanometre-thick ferroelectric thin films sandwiched between two electrodes. They have abilities beyond existing technologies and bode well for energy-efficient and stable neuromorphic computing.
The junctions work in low voltages of less than five volts and with a variety of electrode materials — including silicon used in chips in most of our electronics. They also can retain data for more than 10 years without power and be manufactured in normal conditions.