**Automating Forecasting with Language Models**
Predictive forecasting is a crucial tool in decision-making across various sectors. While statistical methods have been prominent in this field, judgmental forecasting, which involves human intuition and diverse information sources, has emerged as a more nuanced approach.
**UC Berkeley’s Novel LM Pipeline**
A research team from UC Berkeley has introduced a new LM pipeline, a retrieval-augmented language model system tailored for forecasting. This system automates key components of forecasting, such as retrieving relevant information, reasoning based on data, and aggregating forecasts. By harnessing web-scale data and the rapid processing capabilities of LMs, this system offers a scalable alternative to traditional methods.
**The Future of Forecasting with Language Models**
With an average Brier score approaching that of human forecasters, UC Berkeley’s LM-based system shows promise in enhancing predictive accuracy at scale. By integrating language models into forecasting, we may see more reliable and efficient predictive methods that have a significant impact on decision-making processes.
*Check out the paper for more details on this innovative research project.*