Scientists Create Brain-Inspired Computer That Learns Like Humans Using 90% Less Energy Than Current AI

Scientists at University of Texas at Dallas unveil a revolutionary brain-inspired computer that learns like humans while consuming 90% less energy than current AI systems, potentially bringing powerful machine learning capabilities to mobile devices and dramatically reducing the environmental impact of artificial intelligence.

• Researchers at University of Texas at Dallas develop a neuromorphic computer prototype that learns patterns using significantly fewer computations and less energy than traditional AI systems
• The brain-inspired hardware integrates memory storage with processing using magnetic tunnel junctions (MTJs) that mimic neural synapses and strengthen connections based on activity patterns
• This technology could reduce reliance on energy-intensive data centers and enable AI learning capabilities on mobile devices without requiring massive training computations that cost hundreds of millions of dollars