Google DeepMind and Google Research released WeatherNext 2 and WeatherNext Cyclones (WN-C), AI weather forecasting models that outperform previous models on 99.9% of forecast variables and deliver for…
Google DeepMind and Google Research introduced WeatherNext 3, a global weather AI model that generates hourly forecasts at up to 5-kilometer resolution, roughly five times sharper than its predecessor…
Google DeepMind and Google Research released WeatherNext 3, an AI weather forecasting model that outperforms leading AI and traditional models on the Operational WeatherBench benchmark, with 5km resol…
Google launched WeatherNext 3, an AI weather model that produces forecasts with up to 5-kilometer resolution and hourly updates using real-time satellite observations, five times sharper than its pred…
Google Research released TimesFM 3.0 in late August 2026, a pretrained foundation model for zero-shot time series forecasting that requires no training, and the new version adds multivariate support. …
Shrijith Venkatramana, developer of the AI code review tool LiveReview, explains the concept of loss landscapes in large language models, describing how gradient descent navigates high-dimensional par…
Google has added TabFM, a pre-trained foundation model for tabular data, to BigQuery in preview, enabling enterprise teams to generate classification and regression predictions from structured data wi…
A Google Research and Technion study of over 4 million responses across 13 large language models found that frontier models like Gemini-3-Pro and GPT-5 store facts correctly 95-98% of the time but fai…
Google Research engineers Vishal Batchu and Michelangelo Conserva developed MAPL-EMIT, a deep-learning framework that automates detection and quantification of methane plumes from NASA's EMIT hyperspe…
Google Research has released TimesFM-3, a 330-million-parameter foundation model for multivariate time-series forecasting that can reason across multiple related series and external signals zero-shot,…
Google announced TabFM, a pre-trained foundation model for tabular data, now available in preview in BigQuery, enabling instant predictions via SQL functions AI.PREDICT and AI.EVALUATE. Developed by G…
Google Research released TimesFM-3, a 330 million parameter time series foundation model that performs zero-shot multivariate forecasting in a single forward pass, accepting multiple targets and covar…
Google Research introduced TimesFM-3, a 330-million-parameter time series foundation model that performs multivariate forecasting in a single forward pass, pre-trained on over 1 trillion time points. …
Qdrant 1.19 introduces the Turbo4 datatype, a 4-bit-only storage format that eliminates the float32 copy, and a unified memory tier system, reducing storage footprint by 9x compared to the prior Turbo…
Google Research introduced WikiSkill, a framework that uses a persistent wiki-style knowledge base to let AI agents retain learned skills, boosting performance by double digits across five benchmarks.…
Google Research has introduced WikiSkill, a framework that gives AI agents a persistent knowledge base by documenting failures and successes in a wiki-like structure, enabling them to improve over tim…
Google Research introduced the planetary prediction engine (PPE), an experimental AI system that autonomously executes the full geospatial modeling workflow from data discovery to model training, redu…
Google Research's Lumiere paper, published in January 2024, introduced a Space-Time U-Net architecture that generates entire video clips in a single pass, solving the temporal consistency problem that…
Google Research introduced ME-POIs, a mobility-informed framework that adds human movement patterns to text-based point-of-interest (POI) embeddings. In evaluations on Los Angeles and Houston mobility…
Google Research introduced Mobility-Embedded POIs (ME-POIs), a framework that blends text descriptions with aggregated, anonymized mobility patterns to improve language models' understanding of places…