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In our latest Nature publication, we introduce a new quantum computational task measuring Out-of-Time-Order Correlators (OTOCs). This work demonstrates a verifiable quantum advantage and paves the way for solving real-world problems like Hamiltonian learning in Nuclear Magnetic Resonance (NMR). Nature is brimming with chaos, a phenomenon characterized by the high sensitivity of a system toward small perturbations.
Google Earth AI is our family of geospatial AI models and reasoning agents that provides users with actionable insights, grounded in real-world understanding. Today, we’re sharing our latest Earth AI innovations and expanding access to these new capabilities on Google Earth and Google Cloud. For years, Google has developed AI models that enhance our understanding
The personal health coach is built with Gemini models to deliver personalized and adaptive coaching, grounded in science and informed by expert oversight. Historically, health and fitness journeys have been fragmented, generic and inaccessible, whether within existing apps or through general health and fitness journeys outside of apps. For instance, a primary care provider might
Afrimed-QA, a collection of contextually relevant datasets for evaluation of LLMs on African health question answering tasks, developed in partnership with organizations across Africa. Large language models (LLMs) have shown potential for medical and health question answering across various health-related tests spanning different formats and sources, such as multiple choice and short answer exam questions
AfriMed-QA: Benchmarking large language models for global health Read More »
We introduce StreetReaderAI, a new accessible street view prototype using context-aware, real-time AI and accessible navigation controls. Interactive streetscape tools, available today in every major mapping service, have revolutionized how people virtually navigate and explore the world — from previewing routes and inspecting destinations to remotely visiting world-class tourist locations. But to date, screen readers
StreetReaderAI: Towards making street view accessible via context-aware multimodal AI Read More »
Google Researchers share user insights from a novel research AI agent that helps people find their way to better health information through proactive conversational guidance, goal understanding, and tailored conversations. The ability to find clear, relevant, and personalized health information is a cornerstone of empowerment for medical patients. Yet, navigating the world of online health
We detail how confidential federated analytics technology is leveraged to understand on-device generative AI features, ensuring strong transparency in user data handling and analysis. Generative AI (GenAI) enables personalized experiences and powers the creation of unstructured data, including summaries, transcriptions, and more. Insights into real-world AI use [1, 2] can help GenAI developers enhance their tools
Learn about Google Researchers research prototype, an LLM-powered personal health agent that analyzes data from everyday wellness devices paired with health data, such as blood biomarkers, to offer evidence-based health insights and to provide a personalized coaching experience. The rapid advancement of large language models (LLMs), combined with data from wearable devices, presents a transformative opportunity
Algorithms & Theory Google Researchers invoke AlphaEvolve, an LLM-based coding agent, to find and verify combinatorial structures that improve results on the hardness of approximately solving certain optimization problems. Recently, large language models (LLMs) have demonstrated surprising capabilities in competitive mathematics and competitive programming, demonstrating world-leading performance across both of these fields. However, their successes in mathematical discovery
