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Intelligent Agents: Powering Discovery and Personalized Experiences

Recent advancements are showcasing intelligent, autonomous AI systems designed to integrate models and tools for acting on behalf of users. Pioneering work from Google demonstrates these capabilities across diverse applications. The Gemini model, for example, functions as an expert astronomy assistant, accurately classifying cosmic events while providing explanations and assessing its own uncertainty. Google Earth AI, leveraging Gemini-powered agents, offers planetary-scale geospatial understanding for disaster preparedness and environmental analysis. In healthcare, initiatives include DeepSomatic for precision cancer medicine and an AI-powered personal health coach on Fitbit, utilizing agentic architectures with conversational, data science, and domain expert agents for personalized guidance. Accessibility is also enhanced by StreetReaderAI, making Street View navigable for blind and low-vision users through multimodal AI and interactive chat. Beyond Google's contributions, XR Blocks has introduced an open-source framework for rapidly prototyping AI-driven Extended Reality experiences. Complementing these developments, Amazon's Marc Brooker has outlined the essential infrastructure components for effective AI operations, with AWS's new AgentCore framework designed to empower developers in this space. These innovations collectively highlight the transformative impact of these systems in accelerating discovery and augmenting human capabilities.

calendar_today 2025-10-20 attribution research.google/blog/

Teaching Gemini to spot exploding stars with just a few examples

Astronomers face an overwhelming deluge of transient alerts, making traditional 'black box' machine learning models a bottleneck. Google's Gemini model now transforms into an expert astronomy assistant, classifying cosmic events with 93% accuracy using just 15 few-shot examples per survey. Crucially, it provides plain-language explanations for its decisions and accurately assesses its own uncertainty, creating a powerful human-in-the-loop system. This enables rapid scientific discovery and paves the way for future agentic assistants that reason, explain, and collaborate with researchers.
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calendar_today 2025-10-23 attribution research.google/blog/

Google Earth AI: Unlocking geospatial insights with foundation models and cross-modal reasoning

Google Earth AI introduces a revolutionary approach to geospatial understanding, leveraging powerful foundation models and intelligent reasoning agents. This innovation empowers users with actionable insights derived from complex, real-world data at a planetary scale. By combining state-of-the-art imagery and population models with a Gemini-powered agent, it orchestrates multi-step queries for enhanced disaster preparedness, public health, and environmental analysis, transforming how we derive insights from Earth data.
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calendar_today 2025-10-31 attribution research.google/blog/

Accelerating the magic cycle of research breakthroughs and real-world applications

Google Research is rapidly accelerating its "magic cycle" of scientific breakthroughs and real-world applications, powered by advanced AI and agentic tools. Recent innovations include Google Earth AI for unprecedented planetary understanding using LLM reasoning, DeepSomatic for precision cancer medicine through genetic variant identification, and Quantum Echoes, demonstrating verifiable quantum advantage for complex molecular interactions. This holistic approach, from health to quantum computing, underscores AI's role as an amplifier of human ingenuity, driving innovation at an unprecedented speed across diverse domains.
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calendar_today 2025-10-29 attribution research.google/blog/

StreetReaderAI: Towards making street view accessible via context-aware multimodal AI

Google Research unveils StreetReaderAI, a groundbreaking prototype making Street View accessible for blind and low-vision users through context-aware, real-time multimodal AI. This innovative system employs Gemini-backed AI Describer for dynamic scene descriptions and an interactive AI Chat agent for conversational navigation and spatial understanding. Users can explore virtually via voice or keyboard, receiving real-time audio feedback about their surroundings. Lab studies show high user satisfaction, especially with the AI Chat's ability to answer complex queries about object location and features. StreetReaderAI signifies a major leap towards inclusive virtual exploration.
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calendar_today 2025-10-09 attribution research.google/blog/

XR Blocks: Accelerating AI + XR innovation

XR Blocks introduces a groundbreaking open-source framework that bridges the gap between AI and Extended Reality, empowering developers to build immersive intelligent computing experiences. This toolkit dramatically accelerates prototyping novel AI-driven XR interactions by abstracting complex low-level systems. It offers a modular architecture with plug-and-play components for XR realism, interaction, and AI integration, built on accessible web technologies. XR Blocks' "Reality Model" and core engine separate interaction intent from implementation, allowing creators to focus on user experience and rapidly translate concepts into interactive prototypes for devices and desktops.
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calendar_today 2025-10-27 attribution research.google/blog/

How we are building the personal health coach

Google is launching an AI-powered personal health coach on Fitbit, leveraging Gemini models to deliver proactive, personalized, and adaptive guidance. This innovative system employs an agentic architecture, featuring a conversation agent, a data science agent capable of numerical reasoning on physiological time-series data and code-generation, and domain expert agents for tailored plans. Rigorous scientific grounding, expert validation, and extensive human-centered design, including a "FIT Score" evaluation framework, ensure safety and effectiveness as it rolls out for public preview.
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calendar_today 2025-10-16 attribution www.amazon.science/blog

Demystifying AI agents

Agentic AI represents a significant leap, enabling AI to act autonomously on behalf of users by integrating models and tools in a continuous loop. Marc Brooker, Amazon VP and distinguished engineer, demystifies these systems, outlining seven essential infrastructure components for their effective operation. These include development frameworks, model hosting, secure code execution via Firecracker microVMs, LLM-tool translation, robust memory management (short and long-term), and comprehensive observability. AWS's new AgentCore framework implements these components, empowering developers to build sophisticated and efficient agentic AI applications.
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