{
  "id": 4705291,
  "title": "Google’s new forecasting model beats everyone. You can’t use it at work (yet).",
  "url": "https://urgent.news/2026/08/31/googles-new-forecasting-model-beats-everyone-you-cant-use-it-at-work",
  "topic": "tech",
  "section": "Tech",
  "published": "2026-08-31T19:41:54.000Z",
  "source": {
    "name": "The New Stack",
    "slug": "the-new-stack",
    "url": "https://thenewstack.io/google-timesfm-3-multivariate-forecasting/"
  },
  "original_language": "en",
  "account": "On Monday, Google unveiled TimesFM-3, a sophisticated time-series forecasting model consisting of 330 million parameters and trained on more than a trillion data points. Currently accessible on Hugging Face under a non-commercial license, the model aims to predict data trends similarly to how large language models predict the next word. With the increasing complexity of real-world forecasting, which often involves multiple interconnected time series and auxiliary data, Google's TimesFM-3 stands out by being pre-trained to handle these intricate connections without requiring additional data. The model's architecture resembles that of prior transformer-based models, with a key distinction in its dual attention layers. The first layer processes time series data sequentially, ensuring causality, while the second analyzes cross-series relationships, enabling the model to account for external factors such as promotional activities or weather conditions. Unlike previous versions that generated forecasts sequentially, TimesFM-3 executes a single forward pass, appending masked tokens for the entire forecast horizon and infilling them simultaneously. Currently, TimesFM-3's weights are restricted to non-commercial, non-production use under a separate license, but Google anticipates transitioning to a commercial model in the near future.",
  "summary": "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 .",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}