Will Computers Be Able to Imitate the Human Brain?

Memristors (memory transistors) are silicon-based components that mimic the information-transmitting synapses of the human brain.

Researchers at Purdue University are building human brain-inspired hardware for artificial intelligence (AI) to help AI learn continuously over time. The goal of the project is to make AI more portable so that it can be used in isolated in environments such as in robots in space or for autonomous vehicles. By embedding AI directly into hardware rather than running it as software, these machines could operate more efficiently.

MIT engineers have designed a brain-inspired chip by putting tens of thousands of artificial brain synapses, or memristors, on just one chip that's smaller than one piece of confetti. Memristors (memory transistors) are silicon-based components that mimic the information-transmitting synapses of the human brain. This so-called "brain-on-a-chip" could one day be built into small, portable AI devices that could perform complex computational tasks currently only performed by supercomputers.

And researchers at Northwestern University and the University of Hong Kong have developed a device modeled after the human brain that simulates human learning. The device is able to learn by association via synaptic transistors that process and store information at the same time.

In a paper published in Science in February, Purdue researchers explained how computer chips could rewire themselves dynamically to take in new data as the brain does, enabling AI to continue learning over time.

To enable learning, the brain is continuously forming new connections between neurons. As such, to build a computer or machine inspired by the brain, the circuits on a computer chip also have to change. However, a circuit that a computer has been using for years is the same as the circuit that was built for the computer in the factory.

Consequently, researchers must be able to "continuously program, reprogram, and change the chip," according to Shriram Ramanathan, a professor in Purdue University’s School of Materials Engineering whose work involves discovering how materials could imitate the brain to improve computing.

Ramanathan and his team built new hardware that can be reprogrammed with electrical pulses on demand. The team's thinking is that because this device is adaptable, it will be able to take on all functions necessary to build a computer inspired by the human brain.

It will be critically important to ensure that these developments are handled in a way that benefits everyone and to deal responsibly with the relevant new technologies. This also means establishing strict ethical standards and creating models accepted throughout the world for managing these technologies. 

This view is echoed in the 2020 Digitalization Monitor recently published by the consulting firm Bearing Point: A survey revealed that 62% of executives say it is important or very important to consider the ethical implications of AI. And this is appropriate, because ultimately, intelligent machines should serve the needs of human beings, and not the other way around.