Next-generation AI semiconductor devices mimic the human brain
A research team led by Prof. Kwon Hyuk-jun of the DGIST Department of Electrical Engineering and Computer Science has developed a next-generation AI semiconductor technology that mimics the human brain’s efficiency in AI and neuromorphic systems.
Neuromorphic computing system technology mimicking the human brain must overcome the limitation of excessive power consumption, which is characteristic of the existing von Neumann computing method. A high-performance, analog artificial synapse device capable of expressing synapse connection strength is required to implement a semiconductor device that uses a brain information…
Researchers combined synthetic DNA with a semiconductor to create an ultra-low-power memory device capable of storing and processing information in the same place. The bio-hybrid technology could eventually help make AI systems and next-generation computers far more energy efficient.
A national initiative in semiconductors provides a once-in-a-generation opportunity to energize manufacturing in the U.S. The CHIPS and Science Act includes an $13 billion R&D investment in the chip industry. Done right, it’s a recipe for bringing advanced manufacturing techniques to every industry and cultivating a highly skilled workforce. The…