AI learns to balance internal knowledge and tool use, improving efficiency
Researchers from UC San Diego and Tsinghua University have developed a method that improves artificial intelligence’s ability to understand when to use external tools versus relying on built-in knowledge, similar to how human experts approach problem-solving. Using a relatively small language model with 8 billion parameters, the team achieved a 28% improvement in answer accuracy …