Why Weve Been Optimizing the Wrong Thing in LLMs for Years

A recent breakthrough in large language model (LLM) training reveals that optimizing for next-token prediction alone has limited the models' foresight, inference speed, and reasoning capabilities. By shifting the training focus towards alternative objectives that better align with reasoning and predictive accuracy, researchers have demonstrated significant improvements in LLM performance, enabling faster inference and more sophisticated reasoning abilities.