Scientists trying to merge human neurons with semiconductors, human brain to power the future

Scientists are working on a new level of technology that uses the neurons inside of the human brain, merging them with semiconductors (chips) to create something that's no longer constrained by the physical limitations of a microchip.

2

Researchers from the National University of Singapore (NUS) have showed off a single, standard silicon transistor that can function like a biological neuron and synapse when operated in a specific, unconventional way. The research team has presented its work as a highly scalable and energy-efficient solution for hardware-based artificial neuron networks (ANNs).

The human brain is an amazing piece of art as it is, with studies showing that the human brain is far more energy-efficient than electronic processors with almost 90 billion neurons that form around 100 trillion connections with each other, and synapses that tune their strength as time goes by, something called synaptic plasticity, which underpins learning and memory.

Scientists have tried to replicate the efficiency of the human brain using artificial neural networks (ANNs) for decades now, but ANNs have recently had huge advances in AI, inspired by how the brain processes information. This is where neuromorphic computing comes into play, where a future of chips processing information more efficiently, kinda like the human brain, closer to reality.

Led by Associate Professor Mario Lanza from the Department of Materials Science and Engineering at the College of Design and Engineering, NUS, which posted a study in journal Nature.

Professor Lanza explains: "To enable true neuromorphic computing, where microchips behave like biological neurons and synapses, we need hardware that is both scalable and energy-efficient. Other approaches require complex transistor arrays or novel materials with uncertain manufacturability, but our method makes use of commercial CMOS (complementary metal-oxide-semiconductor) technology, the same platform found in modern computer processors and memory microchips. This means it's scalable, reliable and compatible with existing semiconductor fabrication processes".