News from the AI & ML world
DeeperML - #agent2agent
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@the-decoder.com
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Microsoft is embracing interoperability in the AI agent space by integrating Google's open Agent2Agent (A2A) protocol into its Azure AI Foundry and Copilot Studio platforms. This move aims to enable AI agents to seamlessly collaborate across diverse platforms and ecosystems. A2A defines how a client agent formulates tasks and a remote agent executes them, supporting both synchronous and asynchronous task handling with status updates exchanged via the protocol. By adopting A2A, Microsoft is fostering a future where AI agents can work together regardless of the underlying framework or vendor, promoting cross-platform compatibility and enhancing AI application development efficiency.
Microsoft's A2A support will allow Copilot Studio agents to interact with external agents, including those built using tools like LangChain or Semantic Kernel, even those outside the Microsoft ecosystem. This means agents can delegate tasks, share data, and act together to automate daily workflows. Microsoft promises full integration with existing security and governance systems, including Microsoft Entra and audit logging. Over 230,000 organizations already use Copilot Studio, including 90 percent of the Fortune 500. Developers can access sample applications, such as automated meeting scheduling between two agents. Google introduced the A2A protocol in April with more than 50 technology partners and is designed to let agents work together using standardized interfaces like HTTP and JSON-RPC. Microsoft is contributing to the specification work on GitHub and plans to help drive further development. A public preview of A2A in Azure Foundry and Copilot Studio is set to launch soon. Microsoft sees protocols like A2A as the foundation for a new kind of software architecture, where connected agents automate daily workflows and collaborate across platforms, without vendor lock-in, but with auditability and control. Recommended read:
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Ken Yeung@Ken Yeung
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TheSequence
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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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@developers.googleblog.com
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Google is aggressively advancing AI agent interoperability with its new Agent2Agent (A2A) protocol and development kit. Unveiled at Google Cloud Next '25, the A2A protocol aims to standardize how AI agents communicate, collaborate, and discover each other across different platforms and tasks. This initiative is designed to streamline the exchange of tasks, streaming updates, and sharing of artifacts, fostering a more connected and efficient AI ecosystem. The A2A protocol complements existing efforts by providing a common language for agents, enabling them to seamlessly integrate and normalize various frameworks like LangChain, AutoGen, and Pydantic.
The Agent2Agent protocol introduces the concept of an "Agent Card" (agent.json), which describes an agent's capabilities and how to reach it. Agents communicate through structured messages, indicating task states such as working, input-required, or completed. By establishing this open standard, Google, along with partners like SAP, seeks to enable agents from different vendors to interact, share context, and collaborate effectively. This move represents a significant step beyond simple API integrations, laying the groundwork for interoperability and automation across traditionally disconnected systems. The development of A2A aligns with Google's broader strategy to solidify its position in the competitive AI landscape, challenging rivals like Microsoft and Amazon. Google is not only introducing new AI chips, such as the Ironwood TPUs, but also updating its Vertex AI platform with Gemini 2.5 models and releasing an agent development kit. This comprehensive approach aims to empower businesses to turn AI potential into real-world impact by facilitating open agent collaboration, model choice, and multimodal intelligence. The collaboration with SAP to enable AI agents to securely interact and collaborate across platforms through A2A exemplifies this commitment to enterprise-ready AI that is open, flexible, and deeply grounded in business context. Recommended read:
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