“This $2 million grant for pioneering research represents a significant step toward unlocking the potential of AI, aligning it with the efficient temporal learning principles of the human brain,” said Eric Brey, interim dean of the Margie and Bill Klesse College of Engineering and Integrated Design at UTSA. “The implications are vast, promising a future where AI systems are not only efficient but also adaptive and lifelong learners, revolutionizing industries and benefiting society at large.”
The team will draw ideas from the Temporal Scaffolding Hypothesis, a theory that mirrors the human brain’s ability to process temporal patterns during both wakefulness and sleep. Unlike contemporary AI models, the human brain is great at doing lots of different things and handling information relating to different time frames, all while exerting very little energy. This stark contrast serves as the driving force behind the quest to create AI models that can emulate the human brain’s adaptability and efficiency.
According to the hypothesis, our brains are good at understanding patterns by replaying our daily experiences quickly while we sleep. The research team wants to create computer systems that work similarly, helping us solve complex problems efficiently. These systems could be used in important areas like health care, self-driving technology and national security.
“This research will help create new computer programs that quickly simulate and understand our past experiences in a simpler way. By combining brain science ideas and real-life experiments, we can test and improve how these computer programs work, changing the way we study them,” Kudithipudi said. “Copying how our brain learns about time helps AI require less power, which is a big issue in today’s AI technology.”
