Computers may soon be like brains

up and firing only once a threshold is reached — more akin to a dial than a switch.

That observation led Boahen to try using transistors in a mixed digital-analog mode.

Doing so, it turns out, makes chips both more energy efficient and more robust when the components do fail, as about 4 percent of the smallest transistors are expected to do.

From there, Boahen builds on neurons’ hierarchical organization, distributed computation and feedback loops to create a vision of an even more energy efficient, powerful and robust neuromorphic computer.

Over the last 30 years, Boahen’s lab has implemented most of its ideas in physical devices, including Neurogrid, one of the first truly neuromorphic computers.

But, in another two or three years, Boahen says, he expects his team will have designed and built computers implementing all of the prospectus’ five points.

“It’s complementary,” Boahen says, adding that “it’s not going to replace current computers”.

But as most personal computers operate nowhere near the limits of conventional chips, neuromorphic computers would be most useful in embedded systems that have extremely tight energy requirements, such as very low-power neural implants or on-board computers in autonomous drones.