Models & Releases

Google’s latest AI weather model gives you no excuse to forget your umbrella

Scientists at Google Deepmind and Google Research released a new artificial intelligence model for weather forecasting today that sees our changing atmosphere more clearly and predicts its behavior more often. WeatherNext 3 is the latest wave of a sea change in meteorology brought out by deep learning techniques, and Google says it will start feeding […]

Get smart on it

Google has released a new artificial intelligence weather forecasting model that predicts atmospheric behavior more accurately and frequently than previous AI models and traditional government weather forecasts. The model improves upon earlier versions by predicting at higher resolution, performing better at forecasting rain, and generating hourly predictions instead of six-hour intervals by ingesting raw satellite data in real time. This advancement matters because AI weather forecasting is faster and cheaper than traditional government supercomputer-based systems, potentially bringing accurate forecasts to poorer regions and improving outcomes like crop yields and renewable energy reliability. The model will be integrated into Google's search, Maps, and Gemini products, continuing a broader shift in meteorology toward deep learning techniques replacing traditional physics-based forecasting methods.

The biggest AI stories, once a day

One short email a day with the stories that matter. Free. Unsubscribe with one click.

Relevant courses

Want to go deeper than the news? Explore live, cohort-based AI courses taught by practitioners.

Browse AI courses on Maven
Related news
Models & ReleasesOpen story →

Anthropic releases new Mythos and Fable models amid RSI concerns

Anthropic says the new models "show improvements in areas like coding, reasoning, and vision," as well as in communicating more clearly with users.

Also reported by The Verge, SiliconANGLE and MarkTechPost

Models & ReleasesOpen story →

Runway’s Praxis-1 world action model for robotics is now available

Praxis-1 builds on Runway’s work as a founding member of the Cosmos Coalition, advancing open world models for physical AI. | Source: Runway Runway AI Inc. yesterday released Praxis-1, its world action model for robotics. The model is now available to developers with open weights under the Apache 2.0 license. Runway first announced Praxis-1 in September with launch partners including Noble Machines, Standard Bots, and Ultra. Since then, these companies have been running the model on their own ha

Models & ReleasesOpen story →

Google releases Gemini 4 Carbon with agent ‘swarm’ feature

Google is rolling out its latest AI model, Gemini 4 Carbon, to the general public after releasing it to a select group of "cybersecurity defenders" two weeks ago. Google claims Carbon is its "strongest model" yet, and capable of competing with the very best systems from Anthropic and OpenAI. Google says Gemini 4 Carbon "pushes the frontier even further" than Argon, referring to the company's other frontier model that launched only last month. The company said Argon will likely

Models & ReleasesOpen story →

Gemini 4 Carbon is now available

The latest version aims to deliver improved performance while reducing the computational resources and energy required for AI operations.

Models & ReleasesOpen story →

Google Launches Gemini Decisions API With Gemini Decision 1 at $0.10/M Tokens

Google has launched the Gemini Decisions API, powered by a new model, Gemini Decision 1 (gemini-decision-1). The Gemini Decisions API does not generate text. It scores up to 1,000 typed questions against one shared input and returns calibrated probabilities. For developers, this targets the small branching calls inside agents: routing, policy checks, tool selection and grading. Google prices it at $0.10 per 1M input tokens, with zero output tokens billed. TL;DR Size: Context is 262,144 t

Also reported by SiliconANGLE

Models & ReleasesOpen story →

Introducing AlphaProof Code: a breakthrough in verifying complex software at depth

AlphaProof Code agents wrote three million lines of proofs in Lean to verify Signal’s core encryption.