Large language models might reason--if you know how to speak to them

This article is part of our coverage of the latest in AI research. Large language models (LLM), neural networks trained on huge corpora of text (or other types of data) have become a hot topic of discussion in the artificial intelligence community, especially since a Google engineer claimed that one of the company's LLMs was sentient. On the one hand, large language models can perform wonderful feats, generating large sequences of text that are mostly coherent and create the impression that they have indeed mastered human language and its underlying skills. On the other hand, numerous experiments show that LLMs are just parroting their training data and are only showing impressive results because they have been exposed to huge amounts of text and break as soon as they are presented with tasks and problems that require reasoning, common sense, and skills that are implicitly learned. But a new study by researchers at the University of Tokyo shows that if you provide the LLMs with well-crafted prompts, you can steer them toward answering questions that require reasoning and step-by-step thinking.