AI framework rooted in cognitive science could complete tasks more efficiently

This article has been reviewed according to Science X's editorial process and policies . Editors have highlighted the following attributes while ensuring the content's credibility:

Add as preferred source Credit: Image generated by the editorial team using AI for illustrative purposes. In recent years, computer scientists have developed a wide range of artificial intelligence (AI) models that can rapidly recognize patterns in data, generate content and solve other computational problems. Many of these AI systems are based on deep neural networks (DNNs), brain-inspired computational models that can make predictions based on specific data, or LLMs, models that can process human language, answer queries and generate text.

While both DNNs and LLMs often perform remarkably well, they generally require vast computational resources and consume large amounts of electricity. Some research teams have thus been trying to develop new models or computational strategies that could reduce the energy consumption associated with AI.