Ion-based artificial neurons mimic brain chemistry for AI computing

Researchers at USC have developed artificial neurons that physically replicate the electrochemical behavior of real brain cells, marking a significant advancement toward more efficient, brain-like AI hardware. Unlike conventional neuromorphic chips that digitally simulate brain activity, these new neurons utilize actual chemical and electrical processes, specifically relying on the movement of silver ions within a “diffusive memristor” structure. This approach mimics the brain’s natural signaling, where electrical signals convert to chemical signals at synapses and back again, enabling each artificial neuron to occupy the space of just one transistor—dramatically reducing size and potentially increasing speed and efficiency. The innovation addresses a key limitation of current computing systems: energy inefficiency. While modern computers are powerful, they consume excessive energy and lack the efficiency of the human brain, which learns from few examples using only about 20 watts of power. By leveraging ion dynamics rather than electron flow, the USC team aims to create hardware that supports more efficient, hardware-based learning akin to biological brains. Although the