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In the rapidly evolving healthcare landscape, patients often find themselves navigating a maze of complex medical information, seeking answers to their questions and concerns. However, accessing accurate and comprehensible information can be a daunting task, leading to confusion and frustration. This is where the integration of cutting-edge technologies, such as audio-to-text translation and large language …

Revolutionizing clinical trials with the power of voice and AI Read More »

At The Check Up, we unveil how we’re using AI to reshape what’s possible in health and help people live healthier lives.

Ubie, a health tech startup in Japan, is using Google AI to change patient — and healthcare worker — experiences for the better.

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 …

Intelligent healthcare assistants: Empowering stakeholders with personalized support and data-driven insights Read More »

Learn how our AI Collaboratives for wildfires and food security are taking a new funding approach to help people around the world.

Learn more about Google Research’s FireSat project, built to detect small wildfires.

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…

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 …

Getting started with computer use in Amazon Bedrock Agents Read More »

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 …

Evaluating RAG applications with Amazon Bedrock knowledge base evaluation Read More »