DeepMind and UC Berkeley shows how to make the most of LLM inference-time compute
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Given the high costs and slow speed of training large language models (LLMs), there is an ongoing discussion about whether spending more compute cycles on inference can help improve the performance of LLMs without the need for retraining them. In a new study, researchers at DeepMind and the University of California, Berkeley explore ways to improve