@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:
References :
- AI & Machine Learning: Vertex AI offers new ways to build and manage multi-agent systems
- Thomas Roccia :verified:: Google just dropped A2A, a new protocol for agents to talk to each other.
- Ken Yeung: Google Pushes Agent Interoperability With New Dev Kit and Agent2Agent Standard
- techstrong.ai: Google Unfurls Raft of AI Agent Technologies at Google Cloud Next ’25
- Analytics Vidhya: Google's new Agent2Agent (A2A) protocol enables seamless AI agent collaboration across diverse frameworks, enhancing enterprise productivity and automating complex workflows.
- techstrong.ai: Google Unfurls Raft of AI Agent Technologies at Google Cloud Next ’25
- Data Analytics: Next 25 developer keynote: From prompt, to agent, to work, to fun
- www.analyticsvidhya.com: Agent-to-Agent Protocol: Helping AI Agents Work Together Across Systems
- TestingCatalog: Google's new Agent2Agent (A2A) protocol enables seamless AI agent collaboration across diverse frameworks, enhancing enterprise productivity and automating complex workflows.
- www.aiwire.net: Google Cloud Preps for Agentic AI Era with ‘Ironwood’ TPU, New Models and Software
- PCMag Middle East ai: At Google Cloud Next, We're Off to See the AI Agents (And Huge Performance Gains)
- Ken Yeung: Google’s Customer Engagement Suite Gets Human-Like AI Agents with Voice, Emotion, and Video Support
- TheSequence: The Sequence Radar #531: A2A is the New Hot Protocol in Agent Land
- bdtechtalks.com: How Google’s Agent2Agent can boost AI productivity through inter-agent communication
- bdtechtalks.com: News article on how Google’s Agent2Agent can boost AI productivity.
- www.infoq.com: News article on Google releasing the Agent2Agent protocol for agentic collaboration.
- medium.com: Security Analysis: Potential AI Agent Hijacking via MCP and A2A Protocol Insights
Alex Woodie@BigDATAwire
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Google Cloud is making significant strides into the agentic AI era, showcasing new technologies at its annual NEXT conference. The company is introducing its seventh-generation Tensor Processing Unit (TPU), named "Ironwood," designed specifically for inference workloads. Google is also pushing agent interoperability with the Agent2Agent standard and a new developer kit. The company is focused on transitioning from model training to inference, aiming to solve real-world problems using AI systems.
The newly unveiled Ironwood TPU is a game-changer, with each pod scaling up to over 9,000 chips and delivering a staggering 42.5 exaflops of compute. This power surpasses the world's fastest supercomputer, El Capitan, by more than 24 times. Ironwood is built for the demands of complex AI models like Gemini 2.5, boasting improvements in power efficiency and liquid cooling. Innovations like optical switching have led to 100 times improvements in sustained performance.
Google is also focused on AI agent technologies, unveiling an open Agent2Agent (A2A) protocol to enable AI agent interoperability. Over 50 technology partners are supporting this initiative, aimed at facilitating the development of AI agents trained to automate tasks across various cloud portfolios. Additionally, Google is providing tools for building and deploying agents, along with broader access to AgentSpace, its framework for building AI agents. This move underscores Google's commitment to making AI more accessible and versatile for enterprises.
Recommended read:
References :
- Ken Yeung: Google Pushes Agent Interoperability With New Dev Kit and Agent2Agent Standard
- BigDATAwire: Google Cloud Preps for Agentic AI Era with ‘Ironwood’ TPU, New Models and Software
- techstrong.ai: Google Unfurls Raft of AI Agent Technologies at Google Cloud Next ’25
- www.bigdatawire.com: Google Cloud Preps for Agentic AI Era with Ironwood’ TPU, New Models and Software
- THE DECODER: Google unveils new AI models, infrastructure, and agent protocol at Cloud Next
- Compute: Introducing Ironwood TPUs and new innovations in AI Hypercomputer
- www.unite.ai: The artificial intelligence arms race among the cloud titans – Amazon Web Services (AWS), Microsoft Azure, and Google Cloud – is escalating rapidly.
- techstrong.ai: Google today unveiled an interoperability protocol for artificial intelligence (AI) agents, along with a bevy of AI agents that makes use of version 2.5 of the Gemini large language model (LLM)
- www.nextplatform.com: With “Ironwood†TPU, Google Pushes The AI Accelerator To The Floor
- insideAI News: Google Launches ‘Ironwood’ 7th Gen TPU for Inference
- NVIDIA Newsroom: NVIDIA Brings Agentic AI Reasoning to Enterprises With Google Cloud
- SAP News Center: SAP and Google Cloud Are Advancing Enterprise AI Through Open Agent Collaboration, Model Choice, and Multimodal Intelligence
- the-decoder.com: Google unveils new AI models, infrastructure, and agent protocol at Cloud Next
- The Next Platform: If you want to be a leading in supplying AI models and AI applications, as well as AI infrastructure to run it, to the world, it is also helpful to have a business that needs a lot of AI that can underwrite the development of homegrown infrastructure that can be sold side-by-side with the standard in the industry.
- Big Technology: Google Cloud CEO Thomas Kurian on AI Competition, Agents, and Tariffs
- www.marktechpost.com: Google AI recently announced Agent2Agent (A2A), an open protocol designed to facilitate secure, interoperable communication among AI agents built on different platforms and frameworks.
- AI & Machine Learning: Vertex AI offers new ways to build and manage multi-agent systems
- www.bigdatawire.com: Google Cloud unveiled a major round of database enhancements at its Next 2025 conference, including a host of new AI features in AlloyDB, a MongoDB-compliant API for Firestore, continuous materialized
- www.marktechpost.com: Google AI Introduces Ironwood: A Google TPU Purpose-Built for the Age of Inference
- BigDATAwire: Google Cloud Fleshes Out its Databases at Next 2025, with an Eye to AI
- www.itpro.com: Google Cloud Next 2025: Targeting easy AI
- cloud.google.com: Today we're unveiling new AI capabilities to help cloud developers and operators at every step of the application lifecycle.
- insidehpc.com: Google launches Ironwood 7th Gen TPU
- AI News | VentureBeat: Google’s Agent2Agent interoperability protocol aims to standardize agentic communication
- AI Accelerator Institute: The truth about enterprise AI agents (and how to get value from them)
- PCMag Middle East ai: At Google Cloud Next, We're Off to See the AI Agents (And Huge Performance Gains)
- Data Analytics: Next 25 developer keynote: From prompt, to agent, to work, to fun
- futurumgroup.com: At Google Cloud Next, Google Brings its Databases to Bear on Agentic AI Opportunity
- techhq.com: Google introduces AI-focused features in app development and infrastructure. Event features Ironwood, a TPU built for AI inference.
- AIwire: Google Cloud is focusing on the AI agent era by introducing new AI models, software, and hardware.
- www.aiwire.net: Google Cloud is gearing up for the agentic AI era in a big way, and its showing off its new wares this week at its NEXT conference.
- TestingCatalog: Google launches Agent2Agent protocol to connect AI agents across platforms
- Shelly Palmer: Greetings from Sin City. I'm here at Google Cloud Next 25—where it's all AI, all the time.
- bdtechtalks.com: Google's new A2A framework lets different AI agents chat and work together seamlessly, breaking down silos and improving productivity across platforms.
- www.infoq.com: At Google Cloud Next 2025, Google announced the Agent Development Kit (ADK), an open-source framework aimed at simplifying the development of intelligent, multi-agent applications.
- Salesforce: Consumer appetite for AI agents to help enhance their lives has silently surged according to recent Salesforce survey data that reveals customers aren’t just ready for agentic interactions — they’re actively expecting them.
@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:
References :
- Search Engine Land: Google AI Mode lets you ask questions with images
- Search Engine Journal: Google AI mode now understands images, allowing you to upload photos and ask questions about them. AI Mode is rolling out to more people.
- The Verge: Google is adding multimodal capabilities to its search-centric AI Mode chatbot that enable it to “see†and answer questions about images, as it expands access to AI Mode to “millions more†users.
- Glenn Gabe: AI Mode expands with multimodal functionality and it's rolling out to millions of more users -> Google AI Mode lets you ask questions with images “With AI Mode’s new multimodal understanding, you can snap a photo or upload an image, ask a question about it and get a rich, comprehensive response with links to dive deeper,†Robby Stein, VP of Product, Google Search wrote."
- PCMag Middle East ai: Google is also adding AI Mode to the Lens feature of its Google app for Android and iOS. Google is opening up , the web-search chatbot it , to 'millions more Labs users in the US.'
- www.searchenginejournal.com: Google AI mode now understands images, allowing you to upload photos and ask questions about them. AI Mode is rolling out to more people. The post appeared first on .
- www.tomsguide.com: Google's Search just got a whole lot more intuitive with the integration of Google Lens in AI Mode.
- www.zdnet.com: Google Search just got an AI upgrade that you might actually find useful - and it's free
- www.searchenginejournal.com: Google Maps content moderation now uses Gemini to detect fake reviews and suspicious profile edits.
- SAP News Center: How SAP and Google Cloud Are Advancing Enterprise AI Through Open Agent Collaboration, Model Choice, and Multimodal Intelligence
- Ken Yeung: Google Pushes Agent Interoperability With New Dev Kit and Agent2Agent Standard
- Thomas Roccia :verified:: Google just dropped A2A, a new protocol for agents to talk to each other.
- AI & Machine Learning: Delivering an application-centric, AI-powered cloud for developers and operators
- AI News | VentureBeat: Google’s Agent2Agent interoperability protocol aims to standardize agentic communication
- www.marktechpost.com: Google Introduces Agent2Agent (A2A): A New Open Protocol that Allows AI Agents Securely Collaborate Across Ecosystems Regardless of Framework or Vendor
- Maginative: Google just Launched Agent2Agent, an Open Protocol for AI agents to Work Directly with Each Other
- Analytics Vidhya: In today’s fast moving world, many businesses use AI agents to handle their tasks autonomously. However, these agents often operate in isolation, unable to communicate across different systems or vendors.
- www.analyticsvidhya.com: Agent-to-Agent Protocol: Helping AI Agents Work Together Across Systems
- developers.googleblog.com: Google's A2A Protocol for Seamless AI Agent Communication
- TestingCatalog: Google's new Agent2Agent (A2A) protocol enables seamless AI agent collaboration across diverse frameworks, enhancing enterprise productivity and automating complex workflows.
- bdtechtalks.com: Google's new A2A framework lets different AI agents chat and work together seamlessly, breaking down silos and improving productivity across platforms. The post first appeared on .
- TheSequence: Google just pushed the boundaries of multi agent communications
Emilia David@AI News | VentureBeat
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OpenAI is enhancing GPT-4o with improved instruction following and problem-solving capabilities. The company has updated GPT-4o to better handle detailed instructions, especially when processing multi-task prompts, thus improving performance and intuition. This model can be accessed by subscribers through the API as "chatgpt-4o-latest" and in ChatGPT.
OpenAI has announced its support for Anthropic’s Model Context Protocol (MCP), an open-source standard designed to streamline the integration between AI assistants and various data systems. With MCP, AI models can connect directly to systems where data lives, eliminating the need for custom integrations and allowing real-time access to business tools and repositories. OpenAI will integrate MCP support into its Agents SDK immediately, with the ChatGPT desktop app and Responses API following soon. This protocol aims to create a unified framework for AI applications to access and utilize external data sources.
ChatGPT Team users can now add internal databases as references, allowing the platform to respond with improved contextual awareness. By connecting internal knowledge bases, ChatGPT Team could become more invaluable to users who ask the platform strategy questions or for analysis. This allows users to perform semantic searches of their data, link directly to internal sources in responses, and ensure ChatGPT understands internal company lingo.
Recommended read:
References :
- Shelly Palmer: In a surprising move, OpenAI announced yesterday it will adopt rival Anthropic's MCP across its product line.
- THE DECODER: OpenAI has updated GPT-4o to better handle detailed instructions, especially when processing multi-task prompts.
- AI News | VentureBeat: OpenAI adds internal data referencing
- Analytics Vidhya: OpenAI has announced its support for Anthropic’s Model Context Protocol (MCP), an open-source standard designed to streamline the integration between AI assistants and various data systems.
Maximilian Schreiner@THE DECODER
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OpenAI has announced its support for Anthropic’s Model Context Protocol (MCP), an open-source standard. The move is designed to streamline the integration between AI assistants and various data systems. MCP is an open standard that facilitates connections between AI models and external repositories and business tools, eliminating the need for custom integrations.
The integration is already available in OpenAI's Agents SDK, with support coming soon to the ChatGPT desktop app and Responses API. The aim is to create a unified framework for AI applications to access and utilize external data sources effectively. This collaboration marks a pivotal step towards enhancing the relevance and accuracy of AI-generated responses by enabling real-time data retrieval and interaction.
Anthropic’s Chief Product Officer Mike Krieger welcomed the development, noting MCP has become “a thriving open standard with thousands of integrations and growing.” Since Anthropic released MCP as open source, multiple companies have adopted the standard for their platforms. CEO Sam Altman confirmed on X that OpenAI will integrate MCP support into its Agents SDK immediately, with the ChatGPT desktop app and Responses API following soon.
Recommended read:
References :
- AI News | VentureBeat: The open source Model Context Protocol was just updated — here’s why it’s a big deal
- Runtime: Why AI infrastructure companies are lining up behind Anthropic's MCP
- THE DECODER: OpenAI adopts competitor Anthropic's standard for AI data access
- Simon Willison's Weblog: OpenAI Agents SDK You can now connect your Model Context Protocol servers to Agents: We’re also working on MCP support for the OpenAI API and ChatGPT desktop app—we’ll share some more news in the coming months. — Tags: , , , , , ,
- Analytics Vidhya: To improve AI interoperability, OpenAI has announced its support for Anthropic’s Model Context Protocol (MCP), an open-source standard designed to streamline the integration between AI assistants and various data systems. This collaboration marks a pivotal step in creating a unified framework for AI applications to access and utilize external data sources effectively. Understanding the Model
- THE DECODER: Anthropic and Databricks close 100 million dollar deal for AI agents
- Analytics India Magazine: Databricks and Anthropic Partner to Bring AI Models to Businesses
- www.itpro.com: Databricks and Anthropic are teaming up on agentic AI development – here’s what it means for customers
- Runtime: Model Context Protocol (MCP) was introduced last November by Anthropic, which called it "an open standard that enables developers to build secure, two-way connections between their data sources and AI-powered tools."
- www.techrepublic.com: OpenAI Agents Now Support Rival Anthropic’s Protocol, Making Data Access ‘Simpler, More Reliable’
- Techzine Global: OpenAI is adding support for MCP, an open-source technology that uses large language models (LLMs) to perform tasks in external systems. OpenAI CEO Sam Altman announced the move this week, SiliconANGLE reports. This development is special, partly because MCP was developed by Anthropic PBC, the ChatGPT developer’s best-funded startup rival.
Maximilian Schreiner@THE DECODER
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OpenAI and Anthropic, competitors in the AI space, are joining forces to standardize AI-data integration through the Model Context Protocol (MCP). Introduced by Anthropic last November, MCP is an open standard designed to enable developers to build secure, two-way connections between data sources and AI-powered tools. The protocol allows AI systems like ChatGPT to access digital documents and other data, enhancing the quality and relevance of AI-generated responses. MCP functions as a "USB-C port for AI applications," offering a universal method for connecting AI models to diverse data sources and supporting secure, bidirectional interactions between AI applications (MCP clients) and data sources (MCP servers).
With OpenAI's support, MCP is gaining momentum as a vendor-neutral way to simplify the implementation of AI agents. Microsoft and Cloudflare have already announced support for MCP, with Microsoft adding it to Copilot Studio. This collaboration aims to improve AI interoperability by providing a standard way for AI agents to access and retrieve data, streamlining the process of building and maintaining agents. The goal is to enable AI agents to take actions based on real-time data, making them more practical for everyday business use, with companies like Databricks aiming to improve the accuracy of AI agents to above 95 percent.
Recommended read:
References :
- Analytics Vidhya: To improve AI interoperability, OpenAI has announced its support for Anthropic’s Model Context Protocol (MCP), an open-source standard designed to streamline the integration between AI assistants and various data systems.
- Simon Willison's Weblog: MCP � OpenAI Agents SDK You can now connect your Model Context Protocol servers to Agents: We’re also working on MCP support for the OpenAI API and ChatGPT desktop app—we’ll share some more news in the coming months.
- THE DECODER: OpenAI adopts competitor Anthropic's standard for AI data access
- The Tech Basic: OpenAI has formed a partnership with its competitor, Anthropic, to implement the Model Context Protocol (MCP) tool.
- www.techrepublic.com: OpenAI Agents Now Support Rival Anthropic’s Protocol, Making Data Access ‘Simpler, More Reliable’
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