One of artificial intelligence’s most stubborn problems is enabling AI systems to accumulate new knowledge without losing what they previously learned. A team of researchers at the MATRIX AI Consortium at The University of Texas at San Antonio may have solved this issue with Genesis, a spiking neuromorphic accelerator chip that would enable on-device continual learning throughout its operational lifetime.

Imagine a security drone trained to patrol a dense forest to spot signs of wildfire. After months of honing its ability to identify smoke among pine trees, the drone is reassigned to a coastal region to watch for floods. The moment the drone learns to interpret these new types of images, it might completely lose its ability to detect a forest fire. In the world of artificial intelligence, this phenomenon is known as “catastrophic forgetting,” and it remains one of the biggest hurdles to creating truly intelligent, autonomous agents.