SWiRL: The business case for AI that thinks like your best problem-solvers

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Researchers from Stanford University and Google DeepMind have unveiled Step-Wise Reinforcement Learning (SWiRL), a technique designed to enhance the ability of large language models (LLMs) to tackle complex tasks requiring multi-step reasoning and tool use. As the interest in AI agents and LLM tool use continues to increase, this technique could offer substantial benefits for enterprises looking to integrate reasoning models into their applications and workflows. The challenge of multi-step problems Real-world enterprise applications often involve multi-step processes. For example, planning a complex marketing campaign may involve market research, internal data analysis, budget calculation and reviewing customer support tickets. This requires online searches, access to internal databases and running code. Traditional reinforcement learning (RL) methods use ... Read full article.