News from the AI & ML world
DeeperML - #edgeai
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Google has made significant strides in the realm of artificial intelligence, introducing several key advancements. One notable development is the launch of Edge Gallery, an application designed to enable the execution of Large Language Models (LLMs) directly on smartphones. This groundbreaking app eliminates the need for cloud dependency, offering users free access to powerful AI processing capabilities on their personal devices. By shifting processing to the edge, Edge Gallery empowers users with greater control over their data and ensures enhanced privacy and security.
The company has also quietly upgraded Gemini 2.5 Pro, Google's flagship LLM, to boost its performance across coding, reasoning, and response quality. This upgrade addresses prior feedback regarding the model's tone, resulting in more structured and creative outputs. In addition to enhancing its core AI models, Google is expanding access to Project Mariner, an AI-driven browser assistant, to more Ultra subscribers. Project Mariner is designed to interact with the user’s active Chrome tabs via a dedicated extension, enabling it to query and manipulate information from any open webpage. Furthermore, Google has introduced an open-source full-stack AI agent stack powered by Gemini 2.5 and LangGraph, designed for multi-step web search, reflection, and synthesis. This research agent stack allows AI agents to perform autonomous web searches, validate results, and refine responses, effectively mimicking a human research assistant. This initiative underscores Google's commitment to fostering innovation and collaboration within the AI community by making advanced tools and resources freely available. Recommended read:
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Ashutosh Singh@The Tech Portal
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Google has launched the 'AI Edge Gallery' app for Android, with plans to extend it to iOS soon. This innovative app enables users to run a variety of AI models locally on their devices, eliminating the need for an internet connection. The AI Edge Gallery integrates models from Hugging Face, a popular AI repository, allowing for on-device execution. This approach not only enhances privacy by keeping data on the device but also offers faster processing speeds and offline functionality, which is particularly useful in areas with limited connectivity.
The app uses Google’s AI Edge platform, which includes tools like MediaPipe and TensorFlow Lite, to optimize model performance on mobile devices. A key model utilized is Gemma 31B, a compact language model designed for mobile platforms that can process data rapidly. The AI Edge Gallery features an interface with categories like ‘AI Chat’ and ‘Ask Image’ to help users find the right tools. Additionally, a ‘Prompt Lab’ is available for users to experiment with and refine prompts. Google is emphasizing that the AI Edge Gallery is currently an experimental Alpha release and is encouraging user feedback. The app is open-source under the Apache 2.0 license, allowing for free use, including for commercial purposes. However, the performance of the app may vary based on the device's hardware capabilities. While newer phones with advanced processors can run models smoothly, older devices might experience lag, particularly with larger models. In related news, Google Cloud has introduced advancements to BigLake, its storage engine designed to create open data lakehouses on Google Cloud that are compatible with Apache Iceberg. These enhancements aim to eliminate the need to sacrifice open-format flexibility for high-performance, enterprise-grade storage management. These updates include Open interoperability across analytical and transactional systems: The BigLake metastore provides the foundation for interoperability, allowing you to access all your Cloud Storage and BigQuery storage data across multiple runtimes including BigQuery, AlloyDB (preview), and open-source, Iceberg-compatible engines such as Spark and Flink.New, high-performance Iceberg-native Cloud Storage: We are simplifying lakehouse management with automatic table maintenance (including compaction and garbage collection) and integration with Google Cloud Storage management tools, including auto-class tiering and encryption. Recommended read:
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Ken Yeung@Ken Yeung
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Ken Yeung
, www.marktechpost.com
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Microsoft is aggressively pushing artificial intelligence to the edge, demonstrating advancements in various applications at Build 2025. A key focus is enabling developers to build dynamic AI agents that integrate into browsers, websites, operating systems, and everyday workflows. This strategic shift moves away from standalone AI assistants towards integrated ecosystems where agents can operate across multiple use cases and seamlessly connect with digital infrastructure. The company aims to empower human workers by partnering them with autonomous agents, enhancing overall productivity through these AI-driven collaborations.
Microsoft is also making significant strides in weather forecasting with its new AI model, Aurora. This model promises accurate 10-day forecasts in seconds, potentially revolutionizing how weather predictions are made. Unlike traditional models, Aurora doesn't rely on the laws of physics, allowing it to generate results much faster. Beyond weather, Aurora's capabilities extend to forecasting other environmental elements like air pollution and cyclones, demonstrating its versatility and potential impact on various Earth systems. Microsoft is currently running this model in Europe's largest weather centers. In addition to environmental forecasting, Microsoft has introduced Magentic-UI, an open-source agent prototype designed to collaborate with users in completing complex tasks that require multi-step planning and browser use. Unlike autonomous agents that may sideline user control, Magentic-UI blends automation with real-time human input, leading to more accurate and trusted results. This approach addresses the challenge of visibility and intervention in web-based tasks, allowing users to guide and supervise agent behavior dynamically. This ensures that AI-driven actions align with user expectations and goals, especially in scenarios involving critical decisions. Recommended read:
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Ken Yeung@Ken Yeung
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Microsoft is significantly expanding its AI capabilities to the edge, empowering developers with tools to create innovative AI agents. This strategic move, unveiled at Build 2025, focuses on enabling smarter and faster experiences across various devices. Unlike previous strategies centered on single-use AI assistants, Microsoft is now emphasizing dynamic agents that seamlessly integrate with third-party systems through the Model Context Protocol (MCP). This shift aims to create broader, integrated ecosystems where agents can operate across diverse use cases and integrate with any digital infrastructure.
Microsoft is empowering developers by offering the OpenAI Responses API, which allows the combination of MCP servers, code interpreters, reasoning, web search, and RAG within a single API call. This capability enables the development of next-generation AI agents. Among the announcements at Build 2025 were a platform to build on-device agents, the ability to bring AI to web apps on the Edge browser, and developer capabilities to deploy bots directly on Windows. The company hopes the developments will lead to broader use of AI technologies and a significant increase in the number of daily active users. Microsoft is already demonstrating the impact of its agentic AI platform, Azure AI Foundry, in healthcare, including streamlining cancer care planning. In addition to their AI initiatives, Microsoft has introduced a new AI-powered orchestration system that streamlines the complex process of cancer care planning. This orchestration system, available through the Azure AI Foundry Agent Catalog, brings together specialized AI agents to assist clinicians with the analysis of multimodal medical data, from imaging and genomics to clinical notes and pathology. Early adopters include Stanford Health Care, Johns Hopkins, Providence Genomics, and UW Health. Recommended read:
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