Google's new forecasting model beats everyone. You can't use it at work (yet).

Google's new forecasting model beats everyone. You can't use it at work (yet).

On Monday, Google launched TimesFM-3, a 330-million-parameter time-series forecasting model trained on over a trillion real-world and synthetic data time The post Google’s new forecasting model beats everyone. You can’t use it at work (yet). appeared first on The New Stack.

Google Announces TimesFM-3, A Foundation Model For Multivariate Forecasting

Google might not be quite at the frontier in general purpose models, but it’s coming up with interesting AI models all the same.... The post Google Announces TimesFM-3, A Foundation Model For Multivariate Forecasting appeared first on OfficeChai.

Google’s New TimesFM-3 Outperforms Rivals At Complex Forecasting And Will Soon Be Available In BigQuery

Google releases TimesFM-3, the first natively multivariate model in the series, achieving SOTA benchmarks with BigQuery integration arriving soon. The post Google’s New TimesFM-3 Outperforms Rivals At Complex Forecasting And Will Soon Be Available In BigQuery appeared first on Metaverse Post.

Google AI Releases TimesFM-3: A 330M Parameter Zero-Shot Foundation Model For Multivariate Time Series Forecasting

Google Research has released TimesFM-3, a 330 million parameter time series foundation model that forecasts multiple related series in a single forward pass. Unlike every TimesFM checkpoint through 2.5, it is pretrained natively for multivariate forecasting, accepting multiple targets, past covariates, and past-future covariates with no task-specific fine-tuning. It takes the top average rank among pretrained foundation models on GIFT-Eval, fev-…