How Gemini is improving care in Japanese hospitals
Ubie, a health tech startup in Japan, is using Google AI to change patient — and healthcare worker — experiences for the better.
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The Check Up with Google Health
At The Check Up 2025, we shared more about the potential of AI in health and our latest health AI research, partnership and product updates.
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Intelligent healthcare assistants: Empowering stakeholders with personalized support and data-driven insights
Large language models (LLMs) have revolutionized the field of natural language processing, enabling machines to understand and generate human-like text with remarkable accuracy. However, despite their impressive language capabilities, LLMs are inherently limited by the data they were trained on. Their knowledge is static and confined to the information they were trained on, which becomes
New AI Collaboratives to take action on wildfires and food insecurity
Learn how our AI Collaboratives for wildfires and food security are taking a new funding approach to help people around the world.
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The first FireSat satellite has launched to help detect smaller wildfires earlier.
The first satellite for the FireSat constellation officially made contact with Earth. This satellite is the first of more than 50 in a first-of-its-kind constellation de…
The first FireSat satellite has launched to help detect smaller wildfires earlier. Read More »
Inside the launch of FireSat, a system to find wildfires earlier
Learn more about Google Research’s FireSat project, built to detect small wildfires.
Inside the launch of FireSat, a system to find wildfires earlier Read More »
Getting started with computer use in Amazon Bedrock Agents
Computer use is a breakthrough capability from Anthropic that allows foundation models (FMs) to visually perceive and interpret digital interfaces. This capability enables Anthropic’s Claude models to identify what’s on a screen, understand the context of UI elements, and recognize actions that should be performed such as clicking buttons, typing text, scrolling, and navigating between
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Evaluating RAG applications with Amazon Bedrock knowledge base evaluation
Organizations building and deploying AI applications, particularly those using large language models (LLMs) with Retrieval Augmented Generation (RAG) systems, face a significant challenge: how to evaluate AI outputs effectively throughout the application lifecycle. As these AI technologies become more sophisticated and widely adopted, maintaining consistent quality and performance becomes increasingly complex. Traditional AI evaluation approaches
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Google’s comments on the U.S. AI Action Plan
Google shares policy recommendations in response to OSTP’s request for information for the U.S. AI Action Plan.
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How GoDaddy built a category generation system at scale with batch inference for Amazon Bedrock
This post was co-written with Vishal Singh, Data Engineering Leader at Data & Analytics team of GoDaddy Generative AI solutions have the potential to transform businesses by boosting productivity and improving customer experiences, and using large language models (LLMs) in these solutions has become increasingly popular. However, inference of LLMs as single model invocations or