UC Berkeley Research Presents a Machine Learning System that Can Forecast at Near Human Levels

A research team from UC Berkeley has developed a novel LM pipeline, a retrieval-augmented language model system specifically designed for forecasting. The system achieved an average Brier score of .179, closely approaching the human aggregate score of .149, indicating that the language model-based forecasting system closely approximates, and in some instances surpasses, the accuracy of human forecasters aggregated from competitive platforms.


Source: [https://app.daily.dev/posts/Op9crOnZn](https://app.daily.dev/posts/Op9crOnZn)

artificial berkeley forecast forecasting human language language model machine machine learning near novel pipeline research research team retrieval retrieval-augmented team uc berkeley