A new paper by researchers from Google Research and UC Berkeley shows that a simple sampling-based search approach can enhance the reasoning abilities of large language models (LLMs) without needing specialized training or complex architectures.
TimesFM is a pretrained time-series foundation model developed by Google Research for time-series forecasting, focusing on point forecasts for univariate time series up to 512 time points with any horizon length and an optional frequency indicator.
