News from the AI & ML world
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Thomas Claburn@The Register
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Microsoft is significantly advancing human-agent collaboration with the latest upgrades to its Microsoft 365 Copilot. The tech giant is rolling out new updates, including Researcher and Analyst agents designed to enhance workplace productivity by providing in-depth research and data analysis. These AI agents, powered by OpenAI's deep reasoning models, are envisioned as digital colleagues capable of performing complex workplace tasks, helping professionals tackle intricate challenges with advanced reasoning capabilities. This aligns with Microsoft’s broader AI-first strategy, aiming to scale digital labor and drive substantial productivity gains for companies adopting these technologies.
Microsoft is also unveiling a redesigned Microsoft 365 Copilot app featuring AI-powered search and an Agent Store, positioning it as the central hub for human-agent collaboration. The new AI-powered enterprise search tool, Copilot Search, organizes data across the enterprise, providing rich, context-aware answers from first-party and third-party apps like ServiceNow, Google Drive, and Jira. The Agent Store provides access to Microsoft’s Researcher and Analyst agents, initially introduced in March and available to those enrolled in Microsoft’s Frontier program. Moreover, Microsoft is adding new capabilities to its Control System feature to assist IT professionals in overseeing and measuring bot usage effectively. These updates are part of a broader effort to integrate AI across the Microsoft ecosystem, addressing the increasing demand for AI-powered solutions in the enterprise. According to Microsoft’s 2025 Work Trend Index report, a significant majority of companies are rethinking their strategies to leverage AI, signaling a decisive move toward full-scale AI transformation. Key features include AI-powered enterprise search, personalized memory capabilities, specialized reasoning agents like Researcher and Analyst, and the Agent Store. The Researcher agent helps with multi-step research tasks, while the Analyst agent provides data science capabilities. Recommended read:
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Ken Yeung@Ken Yeung
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Google has launched the Agent2Agent (A2A) protocol, a groundbreaking open interoperability framework designed to facilitate seamless collaboration between AI agents across different platforms and vendors. This initiative addresses the challenges posed by siloed AI systems by establishing a standardized method for agents to communicate, coordinate actions, and securely exchange information. A2A aims to streamline complex workflows, improve productivity, and foster a dynamic ecosystem where AI agents operate as composable primitives in enterprise-scale operations.
The A2A protocol is built upon key principles, including capability discovery, task management, collaboration, and user experience negotiation. Agents can publish their capabilities using JSON-formatted "Agent Cards," which allows client agents to identify the most appropriate remote agent for a given task. The protocol supports the complete lifecycle management of tasks, enabling real-time synchronization between agents. By leveraging established standards like HTTP and JSON-RPC, A2A ensures compatibility with existing infrastructure while prioritizing security with built-in authentication and authorization mechanisms. The protocol is also modality-agnostic, accommodating text, audio, video, and embedded UI components. Google envisions A2A as a foundational layer for future AI systems, promoting collaboration and interoperability across various environments. The company has released A2A as open source, inviting the broader community to contribute to its refinement and expansion. This approach aligns with Google's strategy of fostering innovation in AI, ensuring trustworthiness, and promoting scalability. Industry experts believe A2A represents a significant step toward realizing the full potential of multi-agent ecosystems, particularly as enterprises increasingly adopt AI agents for diverse tasks, from customer service to supply chain management. Recommended read:
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Ken Yeung@Ken Yeung
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Google has launched Agent2Agent (A2A), an open interoperability protocol designed to facilitate seamless collaboration between AI agents across diverse frameworks and vendors. This initiative, spearheaded by Google Cloud, addresses the challenge of siloed AI systems by standardizing communication, ultimately automating complex workflows and boosting enterprise productivity. The A2A protocol has garnered support from over 50 technology partners, including industry giants like Salesforce, SAP, ServiceNow, and MongoDB, signaling a broad industry interest in fostering a more cohesive AI ecosystem. A2A aims to provide a universal framework, allowing AI agents to securely exchange information, coordinate actions, and integrate across various enterprise platforms, regardless of their underlying framework or vendor.
The A2A protocol functions on core principles of capability discovery, task management, collaboration, and user experience negotiation. Agents can advertise their capabilities using JSON-formatted "Agent Cards," enabling client agents to identify the most suitable remote agent for a specific task. It facilitates lifecycle management for tasks, ensuring real-time synchronization. Built on established standards like HTTP and JSON, A2A ensures compatibility with existing systems while prioritizing security. Google has released A2A as open source, encouraging community contributions to enhance its functionality. Enterprises are beginning to use multi-agent systems, with multiple AI agents working together, even when built on different frameworks or providers. By enabling interoperability between specialized agents, A2A addresses a critical barrier to scaling agentic AI solutions, unifying workflows and reducing integration costs. Vertex AI is enhancing its services to help move towards a multi-agent ecosystem, including Agent Development Kit, Agent2Agent Protocol, Agent Garden, and Agent Engine. The protocol aims to foster innovation in AI while ensuring trustworthiness and scalability as enterprises adopt AI agents for various tasks. Recommended read:
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@www.analyticsvidhya.com
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Google Cloud Next '25 saw a major push into agentic AI with the unveiling of several key technologies and initiatives aimed at fostering the development and interoperability of AI agents. Google announced the Agent Development Kit (ADK), an open-source framework designed to simplify the creation and management of AI agents. The ADK, written in Python, allows developers to build both simple and complex multi-agent systems. Complementing the ADK is Agent Garden, a collection of pre-built agent patterns and components to accelerate development. Additionally, Google introduced Agent Engine, a fully managed runtime in Vertex AI, enabling secure and reliable deployment of custom agents at a global scale.
Google is also addressing the challenge of AI agent interoperability with the introduction of the Agent2Agent (A2A) protocol. A2A is an open standard intended to provide a common language for AI agents to communicate, regardless of the frameworks or vendors used to build them. This protocol allows agents to collaborate and share information securely, streamlining workflows and reducing integration costs. The A2A initiative has garnered support from over 50 industry leaders, including Atlassian, Box, Cohere, Intuit, and Salesforce, signaling a collaborative effort to advance multi-agent systems. These advancements are integrated within Vertex AI, Google's comprehensive platform for managing models, data, and agents. Enhancements to Vertex AI include supporting Model Context Protocol (MCP) to ensure secure data connections for agents. In addition to software advancements, Google unveiled its seventh-generation Tensor Processing Unit (TPU), named Ironwood, designed to optimize AI inferencing. Ironwood offers significantly increased compute capacity and high-bandwidth memory, further empowering AI applications within the Google Cloud ecosystem. Recommended read:
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