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Researchers have unveiled SWiRL, a novel technique that dramatically enhances the multi-step reasoning abilities of large language models (LLMs). SWiRL achieves this improvement by training LLMs on detailed “reasoning trajectories,” which map out the step-by-step thought processes and tool utilization needed to solve complex problems. This approach allows the AI to emulate the efficient and effective problem-solving strategies of human experts. The enhanced reasoning capabilities offered by SWiRL unlock significant potential for business applications demanding sophisticated analysis and decision-making processes, making AI a more viable solution for intricate real-world challenges.