Study Points to Better Hardware for Artificial Intelligence Using Lessons from a Sea Slug

To get any smarter, artificial intelligence (AI) must first match the intelligence of one of the most basic animals in the natural kingdom: the sea slug. The simulation of human intelligence processes by machines, particularly computer systems, is known as artificial intelligence. Expert systems, natural language processing, speech recognition, and machine vision are examples of AI applications.

According to a new study, a substance can duplicate the sea slug’s most important intelligence qualities. The discovery is a step toward developing hardware that might make AI more effective and dependable in a variety of applications, including self-driving vehicles, surgical robots, and social media algorithms.

Purdue University, Rutgers University, the University of Georgia, and Argonne National Laboratory collaborated on the study, which was published this week in the Proceedings of the National Academy of Sciences.

“Through studying sea slugs, neuroscientists discovered the hallmarks of intelligence that are fundamental to any organism’s survival,” said Shriram Ramanathan, a Purdue professor of materials engineering. “We want to take advantage of that mature intelligence in animals to accelerate the development of AI.”

Sea slugs have taught neuroscientists two important markers of intelligence: habituation and sensitization. Habituation is the process of gradually becoming accustomed to a stimulus, such as tuning out noises when driving the same route to work every day. Sensitization is the polar opposite; it involves a strong reaction to novel stimuli, such as avoiding terrible restaurant cuisine.

AI has a difficult time learning and storing new knowledge without overwriting information it has already learnt and stored, a problem known as the “stability-plasticity dilemma” by researchers exploring brain-inspired computing.

Sensitization could aid in the retention of fresh and critical knowledge, while habituation would allow AI to “forget” superfluous information (achieving more stability).

The researchers discovered a method to demonstrate both habituation and sensitization in nickel oxide, a quantum material, in this study. The substance is referred to as “quantum” since its qualities defy classical physics.

It may be possible to integrate AI directly into electronics if a quantum substance can reliably replicate various sorts of learning. And, if AI could work in both hardware and software, it might be able to complete more complex jobs with less energy.

Through studying sea slugs, neuroscientists discovered the hallmarks of intelligence that are fundamental to any organism’s survival. We want to take advantage of that mature intelligence in animals to accelerate the development of AI.

Shriram Ramanathan

“We basically emulated experiments done on sea slugs in quantum materials toward understanding how these materials can be of interest for AI,” Ramanathan said.

The sea slug exhibits habituation when it stops retracting its gill as much in reaction to being tapped on the siphon, according to neuroscience studies. An electric shock to the tail, on the other hand, causes the gill to withdraw considerably more dramatically, indicating sensitivity.

An increase in electrical resistance is the nickel oxide counterpart of a “gill withdrawal.” The researchers discovered that continually exposing the material to hydrogen gas leads the change in electrical resistance of nickel oxide to decrease over time, but that introducing a new stimulus, such as ozone, dramatically enhances the change in electrical resistance.

A research group lead by Kaushik Roy, the Edward G. Tiedemann Jr. Distinguished Professor of Electrical and Computer Engineering at Purdue, studied nickel oxide’s behavior and developed an algorithm that successfully leveraged these habituation and sensitization tactics to cluster data points.

“The stability-plasticity dilemma is not solved at all. But we’ve shown a way to address it based on behavior we’ve observed in a quantum material,” Roy said. “If we could turn a material that learns like this into hardware in the future, then AI could perform tasks much more efficiently.”

Researchers will need to figure out how to employ habituation and sensitization in large-scale systems if quantum materials are to be used as AI hardware. They’d also have to figure out how a material would react to stimuli while being embedded in a computer chip.

According to the researchers, this study is a beginning point for steering those future moves. A team from Rutgers University undertook rigorous theory calculations to comprehend what was happening within nickel oxide at a microscopic level to imitate the sea slug’s intelligence qualities, in addition to the Purdue studies.

The parameters of the nickel oxide sample were analyzed by Argonne National Laboratory, and conductivity was measured by the University of Georgia to further investigate the material’s behavior.