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      <loc>https://www.ashishkaul.com/perspectives/mcp-default-agent-standard</loc>
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        <image:title><![CDATA[Model Context Protocol Becomes the Default Agent Standard]]></image:title>
        <image:caption><![CDATA[How an Anthropic-incubated protocol crossed 97 million SDK downloads, got donated to the Linux Foundation, and replaced bespoke integrations as the way agents talk to enterprise systems.]]></image:caption>
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      <loc>https://www.ashishkaul.com/perspectives/mcp-default-agent-standard</loc>
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        <image:title><![CDATA[Model Context Protocol Becomes the Default Agent Standard]]></image:title>
        <image:caption><![CDATA[How an Anthropic-incubated protocol crossed 97 million SDK downloads, got donated to the Linux Foundation, and replaced bespoke integrations as the way agents talk to enterprise systems.]]></image:caption>
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      <loc>https://www.ashishkaul.com/perspectives/multi-agent-orchestration-tipping-point</loc>
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        <image:title><![CDATA[Multi-Agent Orchestration Reaches the Production Tipping Point]]></image:title>
        <image:caption><![CDATA[Why 2026 is the year teams of specialized agents replaced monolithic super-agents, and what enterprises learned the hard way about coordination, cost, and accountability.]]></image:caption>
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      <loc>https://www.ashishkaul.com/perspectives/multi-agent-orchestration-tipping-point</loc>
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        <image:title><![CDATA[Multi-Agent Orchestration Reaches the Production Tipping Point]]></image:title>
        <image:caption><![CDATA[Why 2026 is the year teams of specialized agents replaced monolithic super-agents, and what enterprises learned the hard way about coordination, cost, and accountability.]]></image:caption>
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      <loc>https://www.ashishkaul.com/perspectives/agentic-coding-ide-junior-engineer</loc>
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        <image:title><![CDATA[Agentic Coding: When the IDE Becomes the Junior Engineer]]></image:title>
        <image:caption><![CDATA[Claude Opus 4.7 hit 64.3% on SWE-bench Pro — not as a benchmark stunt, but as the floor for what agent-driven development now looks like in real codebases.]]></image:caption>
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      <loc>https://www.ashishkaul.com/perspectives/agentic-coding-ide-junior-engineer</loc>
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        <image:title><![CDATA[Agentic Coding: When the IDE Becomes the Junior Engineer]]></image:title>
        <image:caption><![CDATA[Claude Opus 4.7 hit 64.3% on SWE-bench Pro — not as a benchmark stunt, but as the floor for what agent-driven development now looks like in real codebases.]]></image:caption>
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        <image:title><![CDATA[Formal Math Reasoning: From Silver to Gold at the IMO]]></image:title>
        <image:caption><![CDATA[A year after AlphaProof reached silver-medal performance at the International Mathematical Olympiad, Gemini Deep Think hit gold — and produced rigorous proofs in natural language, end to end.]]></image:caption>
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    <url>
      <loc>https://www.ashishkaul.com/perspectives/formal-math-reasoning-imo-gold</loc>
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        <image:title><![CDATA[Formal Math Reasoning: From Silver to Gold at the IMO]]></image:title>
        <image:caption><![CDATA[A year after AlphaProof reached silver-medal performance at the International Mathematical Olympiad, Gemini Deep Think hit gold — and produced rigorous proofs in natural language, end to end.]]></image:caption>
      </image:image>
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    <url>
      <loc>https://www.ashishkaul.com/perspectives/embodied-ai-gemini-robotics-sim-to-real</loc>
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        <image:loc>https://images.unsplash.com/photo-1535378620166-273708d44e4c?w=1600&amp;h=1000&amp;fit=crop</image:loc>
        <image:title><![CDATA[Embodied AI: Gemini Robotics and the Closing Sim-to-Real Gap]]></image:title>
        <image:caption><![CDATA[Gemini Robotics ER-1.6 is the first model that treats physical-world reasoning as a first-class objective. What it gets right, what it still doesn't, and why this is the year robotics stopped being its own island.]]></image:caption>
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    <url>
      <loc>https://www.ashishkaul.com/perspectives/embodied-ai-gemini-robotics-sim-to-real</loc>
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        <image:loc>https://images.unsplash.com/photo-1518770660439-4636190af475?w=1600&amp;h=1000&amp;fit=crop</image:loc>
        <image:title><![CDATA[Embodied AI: Gemini Robotics and the Closing Sim-to-Real Gap]]></image:title>
        <image:caption><![CDATA[Gemini Robotics ER-1.6 is the first model that treats physical-world reasoning as a first-class objective. What it gets right, what it still doesn't, and why this is the year robotics stopped being its own island.]]></image:caption>
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    <url>
      <loc>https://www.ashishkaul.com/perspectives/agentic-ai-governance-code-in-production</loc>
      <image:image>
        <image:loc>https://images.unsplash.com/photo-1554224155-8d04cb21cd6c?w=1600&amp;h=1000&amp;fit=crop</image:loc>
        <image:title><![CDATA[Agentic AI Governance: From Policies on Slides to Code in Production]]></image:title>
        <image:caption><![CDATA[The 2026 Gartner Hype Cycle named agentic AI governance, security, and FinOps as new disciplines. The technology that produced that need is also producing the ways it actually gets enforced.]]></image:caption>
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    <url>
      <loc>https://www.ashishkaul.com/perspectives/agentic-ai-governance-code-in-production</loc>
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        <image:loc>https://images.unsplash.com/photo-1559526324-4b87b5e36e44?w=1600&amp;h=1000&amp;fit=crop</image:loc>
        <image:title><![CDATA[Agentic AI Governance: From Policies on Slides to Code in Production]]></image:title>
        <image:caption><![CDATA[The 2026 Gartner Hype Cycle named agentic AI governance, security, and FinOps as new disciplines. The technology that produced that need is also producing the ways it actually gets enforced.]]></image:caption>
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    <url>
      <loc>https://www.ashishkaul.com/perspectives/rise-of-gpt4-new-era-language-ai</loc>
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        <image:loc>https://images.unsplash.com/photo-1677442136019-21780ecad995?w=1200&amp;h=800&amp;fit=crop</image:loc>
        <image:title><![CDATA[The Rise of GPT-4: A New Era in Language AI]]></image:title>
        <image:caption><![CDATA[An in-depth analysis of GPT-4's capabilities, limitations, and its impact on various industries. Discover how this breakthrough in language AI is reshaping the future of work.]]></image:caption>
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      <loc>https://www.ashishkaul.com/perspectives/implementing-ai-enterprise-strategic-guide</loc>
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        <image:loc>https://images.unsplash.com/photo-1451187580459-43490279c0fa?w=1200&amp;h=800&amp;fit=crop</image:loc>
        <image:title><![CDATA[Implementing AI in Enterprise: A Strategic Guide]]></image:title>
        <image:caption><![CDATA[Learn how enterprises can successfully integrate AI solutions, from proof of concept to full-scale deployment. A comprehensive guide backed by real-world case studies.]]></image:caption>
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    <url>
      <loc>https://www.ashishkaul.com/perspectives/future-computer-vision-beyond-recognition</loc>
      <image:image>
        <image:loc>https://images.unsplash.com/photo-1561557944-6e7860d1a7eb?w=1200&amp;h=800&amp;fit=crop</image:loc>
        <image:title><![CDATA[The Future of Computer Vision: Beyond Image Recognition]]></image:title>
        <image:caption><![CDATA[Explore the latest advancements in computer vision AI, from generative models to real-time object detection. Understanding the technology reshaping visual computing.]]></image:caption>
      </image:image>
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    <url>
      <loc>https://www.ashishkaul.com/perspectives/ai-agents-next-evolution-automation</loc>
      <image:image>
        <image:loc>https://images.unsplash.com/photo-1485827404703-89b55fcc595e?w=1200&amp;h=800&amp;fit=crop</image:loc>
        <image:title><![CDATA[AI Agents: The Next Evolution in Automation]]></image:title>
        <image:caption><![CDATA[Discover how autonomous AI agents are revolutionizing task automation and decision-making processes across industries, from simple workflows to complex business operations.]]></image:caption>
      </image:image>
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    <url>
      <loc>https://www.ashishkaul.com/perspectives/multimodal-ai-bridging-text-vision-audio</loc>
      <image:image>
        <image:loc>https://images.unsplash.com/photo-1526374965328-7f61d4dc18c5?w=1200&amp;h=800&amp;fit=crop</image:loc>
        <image:title><![CDATA[Multimodal AI: Bridging Text, Vision, and Audio]]></image:title>
        <image:caption><![CDATA[Explore how multimodal AI models are breaking down barriers between different types of data, enabling new applications and more natural human-AI interaction.]]></image:caption>
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    <url>
      <loc>https://www.ashishkaul.com/perspectives/ai-powered-code-generation-future-development</loc>
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        <image:loc>https://images.unsplash.com/photo-1542831371-29b0f74f9713?w=1200&amp;h=800&amp;fit=crop</image:loc>
        <image:title><![CDATA[AI-Powered Code Generation: The Future of Development]]></image:title>
        <image:caption><![CDATA[An in-depth look at how AI code generators are transforming software development, from automated testing to full application generation.]]></image:caption>
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    </url>
    <url>
      <loc>https://www.ashishkaul.com/perspectives/responsible-ai-building-ethical-systems</loc>
      <image:image>
        <image:loc>https://images.unsplash.com/photo-1620712943543-bcc4688e7485?w=1200&amp;h=800&amp;fit=crop</image:loc>
        <image:title><![CDATA[Responsible AI: Building Ethical AI Systems]]></image:title>
        <image:caption><![CDATA[Understanding the principles and practices of responsible AI development, from bias detection to transparency and accountability in AI systems.]]></image:caption>
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    </url>
    <url>
      <loc>https://www.ashishkaul.com/perspectives/ai-infrastructure-scaling-ml-operations</loc>
      <image:image>
        <image:loc>https://images.unsplash.com/photo-1558494949-ef010cbdcc31?w=1200&amp;h=800&amp;fit=crop</image:loc>
        <image:title><![CDATA[AI Infrastructure: Scaling Machine Learning Operations]]></image:title>
        <image:caption><![CDATA[Learn about the infrastructure requirements and best practices for scaling AI operations, from model training to production deployment.]]></image:caption>
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    <url>
      <loc>https://www.ashishkaul.com/ai-news</loc>
      <image:image>
        <image:loc>https://images.pexels.com/photos/18475682/pexels-photo-18475682.jpeg?auto=compress&amp;cs=tinysrgb&amp;fit=crop&amp;h=627&amp;w=1200</image:loc>
        <image:title><![CDATA[Musk v. Altman week 1: Elon Musk says he was duped, warns AI could kill us all, and admits that xAI distills OpenAI’s models]]></image:title>
        <image:caption><![CDATA[In the first week of the landmark trial between Elon Musk and OpenAI, Musk took the stand in a crisp black suit and tie and argued that OpenAI CEO Sam Altman and president Greg Brockman had deceived him into bankrolling the company.  Along the way, he warned&#160;that AI could destroy us all and sat through&#8230;.]]></image:caption>
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    <url>
      <loc>https://www.ashishkaul.com/ai-news</loc>
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        <image:loc>https://images.pexels.com/photos/16380906/pexels-photo-16380906.jpeg?auto=compress&amp;cs=tinysrgb&amp;fit=crop&amp;h=627&amp;w=1200</image:loc>
        <image:title><![CDATA[Salesforce launches Agentforce Operations to fix the workflows breaking enterprise AI]]></image:title>
        <image:caption><![CDATA[Enterprise AI teams are hitting a wall — not because their models can&#x27;t reason, but because the workflows underneath them were never built for agents.  Tasks fail, handoffs break, and the problem compounds as organizations push agents deeper into back-office systems.]]></image:caption>
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    <url>
      <loc>https://www.ashishkaul.com/ai-news</loc>
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        <image:title><![CDATA[200,000 MCP servers expose a command execution flaw that Anthropic calls a feature]]></image:title>
        <image:caption><![CDATA[Anthropic created the Model Context Protocol as the open standard for AI agent-to-tool communication.  OpenAI adopted it in March 2025.]]></image:caption>
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    <url>
      <loc>https://www.ashishkaul.com/ai-news</loc>
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        <image:title><![CDATA[The AI scaffolding layer is collapsing. LlamaIndex's CEO explains what survives.]]></image:title>
        <image:caption><![CDATA[The scaffolding layer that developers once needed to ship LLM applications — indexing layers, query engines, retrieval pipelines, carefully orchestrated agent loops — is collapsing.  And according to Jerry Liu, co-founder and CEO of LlamaIndex, that&#x27;s not a problem.]]></image:caption>
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    <url>
      <loc>https://www.ashishkaul.com/ai-news</loc>
      <image:image>
        <image:loc>https://images.pexels.com/photos/16461434/pexels-photo-16461434.jpeg?auto=compress&amp;cs=tinysrgb&amp;fit=crop&amp;h=627&amp;w=1200</image:loc>
        <image:title><![CDATA[xAI launches Grok 4.3 at an aggressively low price and a new, fast, powerful voice cloning suite]]></image:title>
        <image:caption><![CDATA[While Elon Musk faces off against his former colleague and OpenAI co-founder Sam Altman in court, Musk&#x27;s rival firm xAI, founded to take on OpenAI, isn&#x27;t slowing down on launching competitive new products and services. Last night, xAI shipped a new, proprietary base large language model (LLM), Grok 4.]]></image:caption>
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    <url>
      <loc>https://www.ashishkaul.com/ai-news</loc>
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        <image:loc>https://images.pexels.com/photos/16027824/pexels-photo-16027824.jpeg?auto=compress&amp;cs=tinysrgb&amp;fit=crop&amp;h=627&amp;w=1200</image:loc>
        <image:title><![CDATA[Cyber-Insecurity in the AI Era]]></image:title>
        <image:caption><![CDATA[Cybersecurity was already under strain before AI entered the stack.  Now, as AI expands the attack surface and adds new complexity, the limits of legacy approaches are becoming harder to ignore.]]></image:caption>
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    <url>
      <loc>https://www.ashishkaul.com/ai-news</loc>
      <image:image>
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        <image:title><![CDATA[Operationalizing AI for Scale and Sovereignty]]></image:title>
        <image:caption><![CDATA[Companies are taking control of their own data to tailor AI for their needs.  The challenge lies in balancing ownership with the safe, trusted flow of high‑quality data needed to power reliable insights.]]></image:caption>
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    <url>
      <loc>https://www.ashishkaul.com/ai-news</loc>
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        <image:title><![CDATA[  Hidden IT problems are quietly creating risk, shadow IT, and lost productivity]]></image:title>
        <image:caption><![CDATA[Presented by TeamViewerEnterprise technology failures are largely invisible.  Research from TeamViewer, based on a global survey of 4,200 managers and employees, finds that the majority of digital dysfunction never reaches the IT help desk.]]></image:caption>
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      <loc>https://www.ashishkaul.com/ai-news</loc>
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        <image:title><![CDATA[The Download: a new Christian phone network, and debugging LLMs]]></image:title>
        <image:caption><![CDATA[This is today&#8217;s edition of The Download, our weekday newsletter that provides a daily dose of what&#8217;s going on in the world of technology.  A new US phone network for Christians aims to block porn and gender-related content A new US-wide cell phone network marketed to Christians is set to launch next week.]]></image:caption>
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    <url>
      <loc>https://www.ashishkaul.com/ai-news</loc>
      <image:image>
        <image:loc>https://images.pexels.com/photos/18068768/pexels-photo-18068768.png?auto=compress&amp;cs=tinysrgb&amp;fit=crop&amp;h=627&amp;w=1200</image:loc>
        <image:title><![CDATA[Inexpensive seafloor-hopping submersibles could stoke deep-sea science—and mining]]></image:title>
        <image:caption><![CDATA[Smack dab between Australia and South America, the US National Oceanic and Atmospheric Administration (NOAA) research vessel Rainier is currently on a mission to map more than 8,000 square nautical miles of the Pacific seafloor in search of critical mineral deposits.  But it isn’t doing it alone; for a month starting this week, it will&#8230;.]]></image:caption>
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      <loc>https://www.ashishkaul.com/ai-news</loc>
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        <image:title><![CDATA[A new US phone network for Christians aims to block porn and gender-related content]]></image:title>
        <image:caption><![CDATA[A new US-wide cell phone network marketed to Christians is set to launch next week.  It blocks porn, which experts in network security say marks the first time a US cell plan has used network-level blocking for such content that can’t be turned off even by adult account owners.]]></image:caption>
      </image:image>
    </url>
    <url>
      <loc>https://www.ashishkaul.com/ai-news</loc>
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        <image:title><![CDATA[Red-teaming a network of agents: Understanding what breaks when AI agents interact at scale]]></image:title>
        <image:caption><![CDATA[Safe agents don’t guarantee a safe ecosystem of interconnected agents.  Microsoft Research examines what breaks when AI agents interact and why network-level risks require new approaches.]]></image:caption>
      </image:image>
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      <loc>https://www.ashishkaul.com/ai-news</loc>
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        <image:title><![CDATA[Alibaba's Metis agent cuts redundant AI tool calls from 98% to 2% — and gets more accurate doing it]]></image:title>
        <image:caption><![CDATA[One of the key challenges of building effective AI agents is teaching them to choose between using external tools or relying on their internal knowledge.  But large language models are often trained to blindly invoke tools, which causes latency bottlenecks, unnecessary API costs, and degraded reasoning caused by environmental noise.]]></image:caption>
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      <loc>https://www.ashishkaul.com/ai-news</loc>
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        <image:title><![CDATA[Exclusive eBook: Inside the stealthy startup that pitched brainless human clones]]></image:title>
        <image:caption><![CDATA[The ultimate plan to live forever is a brand new body.  This subscriber-only eBook explores R3 Bio, a small startup that has pitched a startling and ethically charged vision for &#8220;brainless clones&#8221; to serve the role of backup human bodies.]]></image:caption>
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      <loc>https://www.ashishkaul.com/ai-news</loc>
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        <image:title><![CDATA[One tool call to rule them all? New open source Python tool Runpod Flash eliminates containers for faster AI dev]]></image:title>
        <image:caption><![CDATA[Runpod, the high-performance cloud computing and GPU platform designed specifically for AI development, today launched a new open source, MIT licensed, enterprise-friendly Python programming tool called Runpod Flash — and it is poised to make creation, iteration and deployment of AI systems inside and outside of foundation model labs much faster.  The tool aims to eliminate some of the biggest barriers and hurdles to training and using AI models today, namely, doing away with Docker packages and containerization when developing for serverless GPU infrastructure, which the company believes will speed up development and deployment of new AI models, applications and agentic workflows.]]></image:caption>
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        <image:title><![CDATA[Why OpenAI's 'goblin' problem matters — and how you can release the goblins on your own]]></image:title>
        <image:caption><![CDATA[AI is more than a technology — it&#x27;s magic. Don&#x27;t believe me.]]></image:caption>
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      <loc>https://www.ashishkaul.com/ai-news</loc>
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        <image:title><![CDATA[Claude Code, Copilot and Codex all got hacked. Every attacker went for the credential, not the model.]]></image:title>
        <image:caption><![CDATA[On March 30, BeyondTrust proved that a crafted GitHub branch name could steal Codex’s OAuth token in cleartext.  OpenAI classified it Critical P1.]]></image:caption>
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        <image:title><![CDATA[Writer launches AI agents that can act without prompts, taking on Amazon, Microsoft and Salesforce]]></image:title>
        <image:caption><![CDATA[Writer, the enterprise AI agent platform backed by Salesforce Ventures, Adobe Ventures, and Insight Partners, today launched event-based triggers for its Writer Agent platform, enabling AI agents to autonomously detect business signals across Gmail, Gong, Google Calendar, Google Drive, Microsoft SharePoint, and Slack — and execute complex multi-step workflows without any human initiating the process. The release, which also includes a new Adobe Experience Manager connector and a suite of enhanced governance controls such as bring-your-own encryption keys and a Datadog observability plugin, represents Writer&#x27;s most aggressive bet yet on fully autonomous enterprise AI.]]></image:caption>
      </image:image>
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        <image:title><![CDATA[This startup’s new mechanistic interpretability tool lets you debug LLMs]]></image:title>
        <image:caption><![CDATA[The San Francisco–based startup Goodfire just released a new tool, called Silico, that lets researchers and engineers peer inside an AI model and adjust its parameters—the settings that determine a model’s behavior—during training.  This could give model makers more fine-grained control over how this technology is built than was once thought possible.]]></image:caption>
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        <image:title><![CDATA[The Download: the North Pole’s future and humanoid data]]></image:title>
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        <image:title><![CDATA[Netomi raises $110 million as Accenture and Adobe bet on AI for customer service]]></image:title>
        <image:caption><![CDATA[Netomi, the San Francisco-based startup building AI systems for enterprise customer service, said Thursday that it has raised $110 million in new funding in a round led by Accenture Ventures, with participation from Adobe Ventures, WndrCo, Silver Lake Waterman, NAVER Ventures, Metis Strategy and Fin Capital.  Jeffrey Katzenberg, managing partner of WndrCo and co-founder of DreamWorks, has joined the company&#x27;s board.]]></image:caption>
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        <image:title><![CDATA[Cheaper tokens, bigger bills: The new math of AI infrastructure]]></image:title>
        <image:caption><![CDATA[Presented by NutanixAs enterprises move from AI experimentation into production deployment, the primary cost driver has shifted away from foundation model training and toward the infrastructure required to run thousands of concurrent inference workloads at scale, with agentic AI as the accelerant.  Where early enterprise AI projects involved a handful of large, scheduled training jobs, production agentic environments require continuous support for short-lived, unpredictable requests that consume GPU, networking, and storage resources in ways traditional infrastructure was never designed to handle.]]></image:caption>
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        <image:title><![CDATA[Amazon’s OpenAI gambit signals a new phase in the cloud wars — one where exclusivity no longer applies]]></image:title>
        <image:caption><![CDATA[Amazon Web Services on Tuesday launched one of the most consequential enterprise AI plays in the company&#x27;s 20-year history, simultaneously bringing OpenAI&#x27;s most powerful models to its Bedrock platform, unveiling a new agentic developer framework, releasing a desktop AI productivity tool called Amazon Quick, and expanding its Amazon Connect service from a single contact-center product into a family of four agentic AI solutions targeting supply chains, hiring, healthcare, and customer experience. The announcements, made at a live event in San Francisco titled &quot;What&#x27;s Next with AWS,&quot; landed just 24 hours after OpenAI and Microsoft publicly restructured their exclusive cloud partnership — a move that, for the first time, freed OpenAI to distribute all of its products across rival cloud providers.]]></image:caption>
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        <image:title><![CDATA[IBM launches Bob with multi-model routing and human checkpoints to turn AI coding into a secure production system]]></image:title>
        <image:caption><![CDATA[Bringing AI agents into the enterprise software development lifecycle is fast becoming the norm.  As developers experiment with new platforms, organizations are exposed to potential security and orchestration failures.]]></image:caption>
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    </url>
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      <loc>https://www.ashishkaul.com/ai-news</loc>
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        <image:title><![CDATA[AWS Quick's personal knowledge graph is making orchestration decisions most control planes can't see]]></image:title>
        <image:caption><![CDATA[Enterprise AI teams running centralized orchestration stacks now have a new variable to account for: AWS Quick, which expanded this week to a desktop-native agent that builds a persistent personal knowledge graph and executes actions across local files and SaaS tools — outside the visibility of most control planes. Unlike chat-based copilots that reset with each session, Quick now maintains a continuously updated knowledge graph built from the user&#x27;s local files, calendar, email and connected SaaS apps.]]></image:caption>
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        <image:title><![CDATA[Definity embeds agents inside Spark pipelines to catch failures before they reach agentic AI systems]]></image:title>
        <image:caption><![CDATA[For most data engineering teams, managing pipeline reliability often means waiting for an alert, manually tracing failures across distributed jobs and clusters, and fixing problems after they&#x27;ve already hit the business.  Agentic AI needs the data to be there, clean and on time.]]></image:caption>
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        <image:title><![CDATA[The Download: storing nuclear waste and orchestrating agents]]></image:title>
        <image:caption><![CDATA[This is today&#8217;s edition of The Download, our weekday newsletter that provides a daily dose of what&#8217;s going on in the world of technology.  It’s time to make a plan for nuclear waste Today, nuclear energy enjoys rare support across the political spectrum.]]></image:caption>
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        <image:title><![CDATA[How to build custom reasoning agents with a fraction of the compute]]></image:title>
        <image:caption><![CDATA[Training AI reasoning models demands resources that most enterprise teams do not have.  Engineering teams are often forced to choose between distilling knowledge from large, expensive models or relying on reinforcement learning techniques that provide sparse feedback.]]></image:caption>
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        <image:title><![CDATA[American AI startup Poolside launches free, high-performing open model Laguna XS.2 for local agentic coding]]></image:title>
        <image:caption><![CDATA[The AI race lately has felt a bit like a game of tennis: first, Anthropic releases a new, pricey state-of-the-art proprietary model for general users (Claude Opus 4. 7), then, a week or so later, its rival OpenAI volleys back with one of its own (GPT-5.]]></image:caption>
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        <image:title><![CDATA[The Download: Musk and Altman’s legal showdown, and AI’s profit problem]]></image:title>
        <image:caption><![CDATA[This is today&#8217;s edition of The Download, our weekday newsletter that provides a daily dose of what&#8217;s going on in the world of technology.  Elon Musk and Sam Altman are going to court over OpenAI’s future Elon Musk and OpenAI CEO Sam Altman head to trial this week in a case with sweeping consequences.]]></image:caption>
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        <image:title><![CDATA[Mistral AI launches Workflows, a Temporal-powered orchestration engine already running millions of daily executions]]></image:title>
        <image:caption><![CDATA[Mistral AI, the Paris-based artificial intelligence company valued at €11. 7 billion ($13.]]></image:caption>
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        <image:title><![CDATA[Elon Musk and Sam Altman are going to court over OpenAI’s future]]></image:title>
        <image:caption><![CDATA[After a yearslong legal feud, Elon Musk and OpenAI CEO Sam Altman are heading to trial this week in Northern California in a case that could have sweeping consequences.  Ahead of OpenAI’s highly anticipated IPO, the court could rule on whether the company is allowed to exist as a for-profit enterprise and might even oust&#8230;.]]></image:caption>
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        <image:title><![CDATA[Microsoft and OpenAI gut their exclusive deal, freeing OpenAI to sell on AWS and Google Cloud]]></image:title>
        <image:caption><![CDATA[Microsoft and OpenAI on Monday announced a sweeping overhaul of the partnership that has defined the commercial AI era, dismantling key pillars of exclusivity and revenue-sharing that bound the two companies together for years and replacing them with a looser, time-limited arrangement that gives both sides far more freedom to pursue rival relationships. The amended agreement, disclosed simultaneously in blog posts from both companies, marks the most significant restructuring since Microsoft first invested $1 billion in OpenAI in 2019 — and it transforms what was once the most consequential exclusive technology alliance in a generation into something that more closely resembles a strategic but arm&#x27;s-length commercial relationship.]]></image:caption>
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        <image:title><![CDATA[Open source Xiaomi MiMo-V2.5 and V2.5-Pro are among the most efficient (and affordable) at agentic 'claw' tasks]]></image:title>
        <image:caption><![CDATA[Xiaomi, the Chinese firm best known for its smartphones and electric vehicles, has lately been shipping some incredibly affordable and high-powered open source AI large language models. The trend continued today with the release of Xiaomi MiMo-V2.]]></image:caption>
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    </url>
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        <image:title><![CDATA[The missing step between hype and profit]]></image:title>
        <image:caption><![CDATA[This story originally appeared in The Algorithm, our weekly newsletter on AI.  To get stories like this in your inbox first, sign up here.]]></image:caption>
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    </url>
    <url>
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        <image:title><![CDATA[New AI framework autonomously optimizes training data, architectures and algorithms — outperforming human baselines]]></image:title>
        <image:caption><![CDATA[AI R&amp;D runs on a cycle of hypothesis, experiment, and analysis — each step demanding substantial manual engineering effort.  A new framework from researchers at SII-GAIR aims to close that bottleneck by automating the full optimization loop for training data, model architectures, and learning algorithms.]]></image:caption>
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    </url>
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      <loc>https://www.ashishkaul.com/ai-news</loc>
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        <image:title><![CDATA[Why supply chains are the proving ground for automation‑led iPaaS]]></image:title>
        <image:caption><![CDATA[Presented by EdgeverveSupply chains are where legacy integration models reach their limits.  As partner networks expand and operational volatility increases, traditional middleware is buckling under costs and complexity.]]></image:caption>
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      <loc>https://www.ashishkaul.com/ai-news</loc>
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        <image:title><![CDATA[Rebuilding the data stack for AI]]></image:title>
        <image:caption><![CDATA[Artificial intelligence may be dominating boardroom agendas, but many enterprises are discovering that the biggest obstacle to meaningful adoption is the state of their data.  While consumer-facing AI tools have dazzled users with speed and ease, enterprise leaders are discovering that deploying AI at scale requires something far less glamorous but far more consequential: data&#8230;.]]></image:caption>
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        <image:title><![CDATA[RAG precision tuning can quietly cut retrieval accuracy by 40%, putting agentic pipelines at risk]]></image:title>
        <image:caption><![CDATA[Enterprise teams that fine-tune their RAG embedding models for better precision may be unintentionally degrading the retrieval quality those pipelines depend on, according to new research from Redis. The paper, &quot;Training for Compositional Sensitivity Reduces Dense Retrieval Generalization,&quot; tested what happens when teams train embedding models for compositional sensitivity.]]></image:caption>
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    </url>
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        <image:title><![CDATA[The Download: DeepSeek’s latest AI breakthrough, and the race to build world models]]></image:title>
        <image:caption><![CDATA[This is today&#8217;s edition of The Download, our weekday newsletter that provides a daily dose of what&#8217;s going on in the world of technology.  Three reasons why DeepSeek’s new model matters On Friday, Chinese AI firm DeepSeek released a preview of V4, its long-awaited new flagship model.]]></image:caption>
      </image:image>
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        <image:title><![CDATA[Context decay, orchestration drift, and the rise of silent failures in AI systems]]></image:title>
        <image:caption><![CDATA[The most expensive AI failure I have seen in enterprise deployments did not produce an error.  No alert fired.]]></image:caption>
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    </url>
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        <image:title><![CDATA[AI synthetic audiences are already here and poised to upend the consulting industry]]></image:title>
        <image:caption><![CDATA[There is a war brewing between AI and consulting.  Akin to an armies slow march towards the castle, a new technology is coming to dethrone the expert guessers of Mckinsey, Nielsen, Gartner, Publicis and the rest.]]></image:caption>
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    </url>
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        <image:title><![CDATA[Monitoring LLM behavior: Drift, retries, and refusal patterns]]></image:title>
        <image:caption><![CDATA[The stochastic challengeTraditional software is predictable: Input A plus function B always equals output C.  This determinism allows engineers to develop robust tests.]]></image:caption>
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    </url>
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      <loc>https://www.ashishkaul.com/ai-news</loc>
      <image:image>
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        <image:title><![CDATA[Three reasons why DeepSeek’s new model V4 matters]]></image:title>
        <image:caption><![CDATA[On Friday, Chinese AI firm DeepSeek released a preview of V4, its long-awaited new flagship model.  Notably, the model can process much longer prompts than its last generation, thanks to a new design that helps it handle large amounts of text more efficiently.]]></image:caption>
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    </url>
    <url>
      <loc>https://www.ashishkaul.com/ai-news</loc>
      <image:image>
        <image:loc>https://images.pexels.com/photos/16027824/pexels-photo-16027824.jpeg?auto=compress&amp;cs=tinysrgb&amp;fit=crop&amp;h=627&amp;w=1200</image:loc>
        <image:title><![CDATA[CVSS scored these two Palo Alto CVEs as manageable. Chained, they gave attackers root access to 13,000 devices.]]></image:title>
        <image:caption><![CDATA[During Operation Lunar Peek in November 2024, attackers gained unauthenticated remote admin access — and eventual root — across more than 13,000 exposed Palo Alto Networks management interfaces.  Palo Alto Networks scored CVE-2024-0012 at 9.]]></image:caption>
      </image:image>
    </url>
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      <loc>https://www.ashishkaul.com/ai-news</loc>
      <image:image>
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        <image:title><![CDATA[DeepSeek-V4 arrives with near state-of-the-art intelligence at 1/6th the cost of Opus 4.7, GPT-5.5]]></image:title>
        <image:caption><![CDATA[The whale has resurfaced.  DeepSeek, the Chinese AI startup offshoot of High-Flyer Capital Management quantitative analysis firm, became a near-overnight sensation globally in January 2025 with the release of its open source R1 model that matched proprietary U.]]></image:caption>
      </image:image>
    </url>
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        <image:title><![CDATA[85% of enterprises are running AI agents. Only 5% trust them enough to ship.]]></image:title>
        <image:caption><![CDATA[Eighty-five percent of enterprises are running AI agent pilots, but only 5% have moved those agents into production.  In an exclusive interview at RSA Conference 2026, Cisco President and Chief Product Officer Jeetu Patel said that the gap comes down to one thing: trust — and that closing it separates market dominance from bankruptcy.]]></image:caption>
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    </url>
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        <image:title><![CDATA[The Download: supercharged scams and studying AI healthcare]]></image:title>
        <image:caption><![CDATA[This is today&#8217;s edition of The Download, our weekday newsletter that provides a daily dose of what&#8217;s going on in the world of technology.  We’re in a new era of AI-driven scams When ChatGPT was released in late 2022, it showed how easily generative AI could create human-like text.]]></image:caption>
      </image:image>
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        <image:title><![CDATA[Health-care AI is here. We don’t know if it actually helps patients.]]></image:title>
        <image:caption><![CDATA[I don’t need to tell you that AI is everywhere.  Or that it is being used, increasingly, in hospitals.]]></image:caption>
      </image:image>
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      <loc>https://www.ashishkaul.com/ai-news</loc>
      <image:image>
        <image:loc>https://images.pexels.com/photos/34804018/pexels-photo-34804018.jpeg?auto=compress&amp;cs=tinysrgb&amp;fit=crop&amp;h=627&amp;w=1200</image:loc>
        <image:title><![CDATA[Mystery solved: Anthropic reveals changes to Claude's harnesses and operating instructions likely caused degradation]]></image:title>
        <image:caption><![CDATA[For several weeks, a growing chorus of developers and AI power users claimed that Anthropic’s flagship models were losing their edge.  Users across GitHub, X, and Reddit reported a phenomenon they described as &quot;AI shrinkflation&quot;—a perceived degradation where Claude seemed less capable of sustained reasoning, more prone to hallucinations, and increasingly wasteful with tokens.]]></image:caption>
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      <loc>https://www.ashishkaul.com/ai-news</loc>
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        <image:title><![CDATA[OpenAI's GPT-5.5 is here, and it's no potato: narrowly beats Anthropic's Claude Mythos Preview on Terminal-Bench 2.0]]></image:title>
        <image:caption><![CDATA[After months of rumors and reports that OpenAI was developing a new, more powerful AI large language model for use in ChatGPT and through its application programming interface (API), allegedly codenamed &quot;Spud&quot; internally, the company has today unveiled its latest offering under the more formal name GPT-5. 5.]]></image:caption>
      </image:image>
    </url>
    <url>
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        <image:caption><![CDATA[For the past eighteen months, the corporate world has been obsessed with the &quot;builder&quot; phase of the generative AI revolution.  Enterprises have raced to deploy autonomous agents to handle everything from customer support to complex codebase refactoring.]]></image:caption>
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        <image:title><![CDATA[The Download: introducing the Nature issue]]></image:title>
        <image:caption><![CDATA[This is today&#8217;s edition of The Download, our weekday newsletter that provides a daily dose of what&#8217;s going on in the world of technology.  Introducing: the Nature issue When we talk about “nature,” we usually mean something untouched by humans.]]></image:caption>
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        <image:title><![CDATA[OpenAI unveils Workspace Agents, a successor to custom GPTs for enterprises that can plug directly into Slack, Salesforce and more]]></image:title>
        <image:caption><![CDATA[OpenAI introduced a new paradigm and product today that is likely to have huge implications for enterprises seeking to adopt and control fleets of AI agent workers. Called &quot;Workspace Agents,&quot; OpenAI&#x27;s new offering essentially allows users on its ChatGPT Business ($20 per user per month) and variably priced Enterprise, Edu and Teachers subscription plans to design or select from pre-existing agent templates that can take on work tasks across third-party apps and data sources including Slack, Google Drive, Microsoft apps, Salesforce, Notion, Atlassian Rovo, and other popular enterprise applications.]]></image:caption>
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        <image:title><![CDATA[Google and AWS split the AI agent stack between control and execution]]></image:title>
        <image:caption><![CDATA[The era of enterprises stitching together prompt chains and shadow agents is nearing its end as more options for orchestrating complex multi-agent systems emerge.  As organizations move AI agents into production, the question remains: &quot;how will we manage them.]]></image:caption>
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        <image:title><![CDATA[Are you paying an AI ‘swarm tax’? Why single agents often beat complex systems]]></image:title>
        <image:caption><![CDATA[Enterprise teams building multi-agent AI systems may be paying a compute premium for gains that don&#x27;t hold up under equal-budget conditions.  New Stanford University research finds that single-agent systems match or outperform multi-agent architectures on complex reasoning tasks when both are given the same thinking token budget.]]></image:caption>
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        <image:title><![CDATA[OpenAI launches Privacy Filter, an open source, on-device data sanitization model that removes personal information from enterprise datasets]]></image:title>
        <image:caption><![CDATA[In a significant shift toward local-first privacy infrastructure, OpenAI has released Privacy Filter, a specialized open-source model designed to detect and redact personally identifiable information (PII) before it ever reaches a cloud-based server.  Launched today on AI code sharing community Hugging Face under a permissive Apache 2.]]></image:caption>
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        <image:title><![CDATA[Google doesn't pay the Nvidia tax. Its new TPUs explain why.]]></image:title>
        <image:caption><![CDATA[Every frontier AI lab right now is rationing two things: electricity and compute.  Most of them buy their compute for model training from the same supplier, at the steep gross margins that have turned Nvidia into one of the most valuable companies in the world.]]></image:caption>
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    </url>
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        <image:title><![CDATA[AutoAdapt: Automated domain adaptation for large language models]]></image:title>
        <image:caption><![CDATA[Deploying large language models (LLMs) in real-world, high-stakes settings is harder than it should be.  In high-stakes settings like law, medicine, and cloud incident response, performance and reliability can quickly break down because adapting models to domain-specific requirements is a slow and manual process that is difficult to reproduce.]]></image:caption>
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        <image:title><![CDATA[Salesforce’s Agentforce Vibes 2.0 targets a hidden failure: context overload in AI agents]]></image:title>
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        <image:title><![CDATA[The Download: introducing the 10 Things That Matter in AI Right Now]]></image:title>
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        <image:title><![CDATA[The modern data stack was built for humans asking questions. Google just rebuilt its for agents taking action.]]></image:title>
        <image:caption><![CDATA[Enterprise data stacks were built for humans running scheduled queries.  As AI agents increasingly act autonomously on behalf of businesses around the clock, that architecture is breaking down — and vendors are racing to rebuild it.]]></image:caption>
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        <image:title><![CDATA[Google’s Gemini can now run on a single air-gapped server — and vanish when you pull the plug]]></image:title>
        <image:caption><![CDATA[Cirrascale Cloud Services today announced it has expanded its partnership with Google Cloud to deliver the Gemini model on-premises through Google Distributed Cloud, making it the first neocloud provider to offer Google&#x27;s most advanced AI model as a fully private, disconnected appliance.  The announcement, timed to coincide with Google Cloud Next 2026 in Las Vegas, addresses a stubborn problem that has plagued regulated industries since the generative AI boom began: how to access frontier-class AI models without surrendering control of your data.]]></image:caption>
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        <image:title><![CDATA[AI needs a strong data fabric to deliver business value]]></image:title>
        <image:caption><![CDATA[Artificial intelligence is moving quickly in the enterprise, from experimentation to everyday use.  Organizations are deploying copilots, agents, and predictive systems across finance, supply chains, human resources, and customer operations.]]></image:caption>
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        <image:title><![CDATA[Los Angeles is finally going underground]]></image:title>
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        <image:title><![CDATA[Roundtables: Unveiling The 10 Things That Matter in AI Right Now]]></image:title>
        <image:caption><![CDATA[Listen to the session or watch below Watch a special edition of Roundtables simulcast live from EmTech AI, MIT Technology Review’s signature conference for AI leadership.  Subscribers got an exclusive first look at a new list capturing 10 key technologies, emerging trends, bold ideas, and powerful movements in AI that you need to know about&#8230;.]]></image:caption>
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        <image:title><![CDATA[This tool could show how consciousness works]]></image:title>
        <image:caption><![CDATA[How does the physical matter in our brains translate into thoughts, sensations, and emotions.  It’s hard to explore that question without neurosurgery.]]></image:caption>
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        <image:title><![CDATA[A natural protein may protect the GI tract from infection]]></image:title>
        <image:caption><![CDATA[Embedded in the body’s mucosal surfaces, proteins called lectins bind to sugars found on cell surfaces.  A team led by MIT chemistry professor Laura Kiessling has found that one such protein, intelectin-2, both helps fortify the mucosal barrier and offers broad-spectrum protection against harmful bacteria found in the GI tract.]]></image:caption>
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        <image:title><![CDATA[Google’s new Deep Research and Deep Research Max agents can search the web and your private data]]></image:title>
        <image:caption><![CDATA[Google on Monday unveiled the most significant upgrade to its autonomous research agent capabilities since the product&#x27;s debut, launching two new agents — Deep Research and Deep Research Max — that for the first time allow developers to fuse open web data with proprietary enterprise information through a single API call, produce native charts and infographics inside research reports, and connect to arbitrary third-party data sources through the Model Context Protocol (MCP). The release, built on Google&#x27;s Gemini 3.]]></image:caption>
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        <image:title><![CDATA[Vercel breach exposes the OAuth gap most security teams cannot detect, scope or contain]]></image:title>
        <image:caption><![CDATA[One employee at Vercel adopted an AI tool.  One employee at that AI vendor got hit with an infostealer.]]></image:caption>
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        <image:title><![CDATA[The AI governance mirage: Why 72% of enterprises don’t have the control and security they think they do]]></image:title>
        <image:caption><![CDATA[Decision makers at 72% of organizations claim to have two or more AI platforms that they identify as their &quot;primary&quot; layer, according to a survey of 40 enterprise companies conducted by VentureBeat last month, revealing real gaps in security and control.  For enterprise management and technical leaders, and especially security leaders, these multiple AI platforms extend the attack surfaces of most enterprises at a time when AI-driven attacks have become increasingly potent.]]></image:caption>
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        <image:title><![CDATA[OpenAI's ChatGPT Images 2.0 is here and it does multilingual text, full infographics, slides, maps, even manga — seemingly flawlessly]]></image:title>
        <image:caption><![CDATA[It&#x27;s been only a few months since OpenAI released its last big improvement to AI image generations in ChatGPT and through its application programming interface (API) — namely, a new image generation model known as GPT-Image-1. 5, released in December 2025, which brought about improved instruction following, colors, and lighting.]]></image:caption>
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        <image:title><![CDATA[Building agent-first governance and security]]></image:title>
        <image:caption><![CDATA[As AI agents increasingly work alongside humans across organizations, companies could be inadvertently opening a new attack surface.  Insecure agents can be manipulated to access sensitive systems and proprietary data, increasing enterprise risk.]]></image:caption>
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    </url>
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      <loc>https://www.ashishkaul.com/ai-news</loc>
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        <image:title><![CDATA[What AI model should you use for revenue intelligence? Von says all the big ones, and it will automate mixing and matching for you]]></image:title>
        <image:caption><![CDATA[Looking at enterprise AI adoption, VentureBeat has anecdotally observed a fairly wide divergence when it comes to specific roles: For those who build—engineers and developers—the arrival of AI has been transformative, moving through the workflow with the speed of tools like Claude Code and Cursor to automate the heavy lifting of syntax and architecture.  Yet, for those who sell, the &quot;revenue stack&quot; has remained a fragmented collection of data silos, manual CRM entries, and anecdotal reporting.]]></image:caption>
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        <image:title><![CDATA[Three AI coding agents leaked secrets through a single prompt injection. One vendor's system card predicted it]]></image:title>
        <image:caption><![CDATA[A security researcher, working with colleagues at Johns Hopkins University, opened a GitHub pull request, typed a malicious instruction into the PR title, and watched Anthropic’s Claude Code Security Review action post its own API key as a comment.  The same prompt injection worked on Google’s Gemini CLI Action and GitHub’s Copilot Agent (Microsoft).]]></image:caption>
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    </url>
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        <image:title><![CDATA[The Download: turning down human noise, and LA’s stunning subway upgrade]]></image:title>
        <image:caption><![CDATA[This is today&#8217;s edition of The Download, our weekday newsletter that provides a daily dose of what&#8217;s going on in the world of technology.  The noise we make is hurting animals.]]></image:caption>
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      <loc>https://www.ashishkaul.com/ai-news</loc>
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        <image:title><![CDATA[Adversaries hijacked AI security tools at 90+ organizations. The next wave has write access to the firewall]]></image:title>
        <image:caption><![CDATA[Adversaries injected malicious prompts into legitimate AI tools at more than 90 organizations in 2025, stealing credentials and cryptocurrency.  Every one of those compromised tools could read data, and none of them could rewrite a firewall rule.]]></image:caption>
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        <image:title><![CDATA[Can we AI our way to a more sustainable world?]]></image:title>
        <image:caption><![CDATA[Doug Burger, sustainability expert Amy Luers, and optimization researcher Ishai Menache examine the global emissions implications of datacenter operations, efficiency gains, and AI's potential across electrification, materials, and food systems. 
The post Can we AI our way to a more sustainable world.]]></image:caption>
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        <image:title><![CDATA[The Download: murderous ‘mirror’ bacteria, and Chinese workers fighting AI doubles]]></image:title>
        <image:caption><![CDATA[This is today&#8217;s edition of The Download, our weekday newsletter that provides a daily dose of what&#8217;s going on in the world of technology.  No one’s sure if synthetic mirror life will kill us all In February 2019, a group of scientists proposed a high-risk, cutting-edge, irresistibly exciting idea that the National Science Foundation should&#8230;.]]></image:caption>
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        <image:title><![CDATA[Colossal Biosciences said it cloned red wolves. Is it for real?]]></image:title>
        <image:caption><![CDATA[If you want to capture something wolflike, it’s best to embark before dawn.  So on a morning this January, with the eastern horizon still pink-hued, I drove with two young scientists into a blanket of fog.]]></image:caption>
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        <image:title><![CDATA[Chinese tech workers are starting to train their AI doubles–and pushing back]]></image:title>
        <image:caption><![CDATA[Tech workers in China are being instructed by their bosses to train AI agents to replace them—and it’s prompting a wave of soul-searching among otherwise enthusiastic early adopters. &#160; Earlier this month a GitHub project called Colleague Skill, which claimed workers could use it to “distill” their colleagues’ skills and personality traits and replicate them with&#8230;.]]></image:caption>
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        <image:title><![CDATA[Train-to-Test scaling explained: How to optimize your end-to-end AI compute budget for inference]]></image:title>
        <image:caption><![CDATA[The standard guidelines for building large language models (LLMs) optimize only for training costs and ignore inference costs.  This poses a challenge for real-world applications that use inference-time scaling techniques to increase the accuracy of model responses, such as drawing multiple reasoning samples from a model at deployment.]]></image:caption>
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        <image:title><![CDATA[Most enterprises can't stop stage-three AI agent threats, VentureBeat survey finds]]></image:title>
        <image:caption><![CDATA[A rogue AI agent at Meta passed every identity check and still exposed sensitive data to unauthorized employees in March.  Two weeks later, Mercor, a $10 billion AI startup, confirmed a supply-chain breach through LiteLLM.]]></image:caption>
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    </url>
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        <image:title><![CDATA[Anthropic just launched Claude Design, an AI tool that turns prompts into prototypes and challenges Figma]]></image:title>
        <image:caption><![CDATA[Anthropic today launched Claude Design, a new product from its Anthropic Labs division that allows users to create polished visual work — designs, interactive prototypes, slide decks, one-pagers, and marketing collateral — through conversational prompts and fine-grained editing controls.  The release, available immediately in research preview to all paid Claude subscribers, is the company&#x27;s most aggressive expansion beyond its core language model business and into the application layer that has historically belonged to companies like Figma, Adobe, and Canva.]]></image:caption>
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        <image:title><![CDATA[Should my enterprise AI agent do that? NanoClaw and Vercel launch easier agentic policy setting and approval dialogs across 15 messaging apps]]></image:title>
        <image:caption><![CDATA[For the past year, early adopters of autonomous AI agents have been forced to play a murky game of chance: keep the agent in a useless sandbox or give it the keys to the kingdom and hope it doesn&#x27;t hallucinate a catastrophic &quot;delete all&quot; command. To unlock the true utility of an agent—scheduling meetings, triaging emails, or managing cloud infrastructure—users have had to grant these models raw API keys and broad permissions, raising the risk of their systems being disrupted by an accidental agent mistake.]]></image:caption>
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        <image:title><![CDATA[The case for fixing everything]]></image:title>
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        <image:title><![CDATA[How robots learn: A brief, contemporary history]]></image:title>
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        <image:title><![CDATA[Salesforce launches Headless 360 to turn its entire platform into infrastructure for AI agents]]></image:title>
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        <image:title><![CDATA[OpenAI debuts GPT-Rosalind, a new limited access model for life sciences, and broader Codex plugin on Github]]></image:title>
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        <image:title><![CDATA[OpenAI drastically updates Codex desktop app to use all other apps on your computer, generate images, preview webpages]]></image:title>
        <image:caption><![CDATA[Confirming it has reached 3 million weekly developers, OpenAI is massively updating its Codex developer environment via its Mac and Windows desktop apps today to bring it closer to the “Super App” the company has confirmed it is pursuing. Before today, Codex was primarily an environment for using OpenAI’s underlying language models to write, edit, debug and ship software as directed by the user.]]></image:caption>
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        <image:title><![CDATA[Anthropic releases Claude Opus 4.7, narrowly retaking lead for most powerful generally available LLM]]></image:title>
        <image:caption><![CDATA[Anthropic is publicly releasing its most powerful large language model yet, Claude Opus 4. 7, today — as it continues to keep an even more powerful successor, Mythos, restricted to a small number of external enterprise partners for cybersecurity testing and patching vulnerabilities in the software said enterprises use (which Mythos exposed rapidly).]]></image:caption>
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        <image:caption><![CDATA[The AI boom has hit across industries, and public sector organizations are facing pressure to accelerate adoption.  At the same time, government institutions face distinct constraints around security, governance, and operations that set them apart from their business counterparts.]]></image:caption>
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        <image:title><![CDATA[The Download: cyberscammers’ banking bypasses, and carbon removal troubles]]></image:title>
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        <image:title><![CDATA[Meta researchers introduce 'hyperagents' to unlock self-improving AI for non-coding tasks]]></image:title>
        <image:caption><![CDATA[Creating self-improving AI systems is an important step toward deploying agents in dynamic environments, especially in enterprise production environments, where tasks are not always predictable, nor consistent.  Current self-improving AI systems face severe limitations because they rely on fixed, handcrafted improvement mechanisms that only work under strict conditions such as software engineering.]]></image:caption>
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        <image:title><![CDATA[We tested Anthropic’s redesigned Claude Code desktop app and 'Routines' — here's what enterprises should know]]></image:title>
        <image:caption><![CDATA[The transition from AI as a chatbot to AI as a workforce is no longer a theoretical projection; it has become the primary design philosophy for the modern developer&#x27;s toolkit.  On April 14, 2026, Anthropic signaled this shift with a dual release: a complete redesign of the Claude Code desktop app (for Mac and Windows) and the launch of &quot;Routines&quot; in research preview.]]></image:caption>
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        <image:title><![CDATA[Anthropic’s Claude Managed Agents gives enterprises a new one-stop shop but raises vendor 'lock-in' risk]]></image:title>
        <image:caption><![CDATA[Anthropic announced a new platform last week, Claude Managed Agents, aiming to cut out the more complex parts of AI agent deployment for enterprises and competes with existing orchestration frameworks. Claude Managed Agents is also an architectural shift: enterprises, already burdened with orchestrating an increasing number of agents, can now choose to embed the orchestration logic in the AI model layer.]]></image:caption>
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        <image:title><![CDATA[Google leaders including Demis Hassabis push back on claim of uneven AI adoption internally]]></image:title>
        <image:caption><![CDATA[A viral post on X from veteran programmer and former Google engineer Steve Yegge set off a rhetorical firestorm this week, drawing sharp public rebuttals from some of Google’s most prominent AI leaders and reopening a sensitive question for the company: how deeply are its own engineers really using the latest generation of AI coding tools.  The debate began after Yegge summarized what he said was the view of his friend, a current and longtime Google employee (or Googler), who claimed the Gemini AI-firm&#x27;s internal AI adoption looks much more ordinary and less cutting-edge than outsiders might expect.]]></image:caption>
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        <image:title><![CDATA[Microsoft launches MAI-Image-2-Efficient, a cheaper and faster AI image model]]></image:title>
        <image:caption><![CDATA[Microsoft today launched MAI-Image-2-Efficient, a lower-cost, higher-speed variant of its flagship text-to-image model that the company says delivers production-ready quality at nearly half the price.  The release, available immediately in Microsoft Foundry and MAI Playground with no waitlist, marks the fastest turnaround yet from Microsoft&#x27;s in-house AI superintelligence team — and the clearest signal that Redmond is serious about building a self-sufficient AI stack that doesn&#x27;t depend on OpenAI.]]></image:caption>
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        <image:title><![CDATA[Databricks tested a stronger model against its multi-step agent on hybrid queries. The stronger model still lost by 21%.]]></image:title>
        <image:caption><![CDATA[Data teams building AI agents keep running into the same failure mode.  Questions that require joining structured data with unstructured content, sales figures alongside customer reviews or citation counts alongside academic papers, break single-turn RAG systems.]]></image:caption>
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        <image:title><![CDATA[43% of AI-generated code changes need debugging in production, survey finds]]></image:title>
        <image:caption><![CDATA[The software industry is racing to write code with artificial intelligence.  It is struggling, badly, to make sure that code holds up once it ships.]]></image:caption>
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        <image:title><![CDATA[The Download: the state of AI, and protecting bears with drones]]></image:title>
        <image:caption><![CDATA[This is today&#8217;s edition of The Download, our weekday newsletter that provides a daily dose of what&#8217;s going on in the world of technology.  Want to understand the current state of AI.]]></image:caption>
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        <image:title><![CDATA[NASA is building the first nuclear reactor-powered interplanetary spacecraft. How will it work?]]></image:title>
        <image:caption><![CDATA[MIT Technology Review Explains: Let our writers untangle the complex, messy world of technology to help you understand what’s coming next.  You can read more from the series here.]]></image:caption>
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        <image:title><![CDATA[Coming soon: 10 Things That Matter in AI Right Now]]></image:title>
        <image:caption><![CDATA[Each year we compile our 10 Breakthrough Technologies list, featuring our educated predictions for which technologies will have the biggest impact on how we live and work.  This year, however, we had a dilemma.]]></image:caption>
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        <image:title><![CDATA[Agentic coding at enterprise scale demands spec-driven development]]></image:title>
        <image:caption><![CDATA[Presented by AWSAutonomous agents are compressing software delivery timelines from weeks to days.  The enterprises that scale agents safely will be the ones that build using spec-driven development.]]></image:caption>
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        <image:title><![CDATA[Is Anthropic 'nerfing' Claude? Users increasingly report performance degradation as leaders push back]]></image:title>
        <image:caption><![CDATA[A growing number of developers and AI power users are taking to social media to accuse Anthropic of degrading the performance of Claude Opus 4. 6 and Claude Code — intentionally or as an outcome of compute limits — arguing that the company’s flagship coding model feels less capable, less reliable and more wasteful with tokens than it did just weeks ago.]]></image:caption>
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        <image:title><![CDATA[Why opinion on AI is so divided]]></image:title>
        <image:caption><![CDATA[This story originally appeared in The Algorithm, our weekly newsletter on AI.  To get stories like this in your inbox first, sign up here.]]></image:caption>
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        <image:title><![CDATA[Want to understand the current state of AI? Check out these charts.]]></image:title>
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        <image:caption><![CDATA[This is today&#8217;s edition of The Download, our weekday newsletter that provides a daily dose of what&#8217;s going on in the world of technology.  You have no choice in reading this article—maybe How do humans make decisions.]]></image:caption>
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        <image:title><![CDATA[You have no choice in reading this article—maybe]]></image:title>
        <image:caption><![CDATA[Uri Maoz loved doing his human research, back when he was getting his PhD.  He was studying a very specific topic in computational neuroscience: how the brain instructs our arms to move and how our gray matter in turn perceives that motion.]]></image:caption>
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        <image:title><![CDATA[Job titles of the future: Wildlife first responder]]></image:title>
        <image:caption><![CDATA[Grizzly bears have made such a comeback across eastern Montana that in 2017, the state hired its first-ever prairie-based grizzly manager: wildlife biologist Wesley Sarmento. &#160; For some seven years, Sarmento worked to keep both the bears, which are still listed as threatened under the Endangered Species Act, and the humans, who are sprawling into once-wild&#8230;.]]></image:caption>
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        <image:title><![CDATA[Designing the agentic AI enterprise for measurable performance]]></image:title>
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        <image:caption><![CDATA[Data drift happens when the statistical properties of a machine learning (ML) model&#x27;s input data change over time, eventually rendering its predictions less accurate.  Cybersecurity professionals who rely on ML for tasks like malware detection and network threat analysis find that undetected data drift can create vulnerabilities.]]></image:caption>
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        <image:title><![CDATA[Your developers are already running AI locally: Why on-device inference is the CISO’s new blind spot]]></image:title>
        <image:caption><![CDATA[For the last 18 months, the CISO playbook for generative AI has been relatively simple: Control the browser. Security teams tightened cloud access security broker (CASB) policies, blocked or monitored traffic to well-known AI endpoints, and routed usage through sanctioned gateways.]]></image:caption>
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        <image:title><![CDATA[AI agent credentials live in the same box as untrusted code. Two new architectures show where the blast radius actually stops.]]></image:title>
        <image:caption><![CDATA[Four separate RSAC 2026 keynotes arrived at the same conclusion without coordinating.  Microsoft&#x27;s Vasu Jakkal told attendees that zero trust must extend to AI.]]></image:caption>
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        <image:title><![CDATA[Intuit compressed months of tax code implementation into hours — and built a workflow any regulated-industry team can adapt]]></image:title>
        <image:caption><![CDATA[When the One Big Beautiful Bill arrived as a 900-page unstructured document — with no standardized schema, no published IRS forms, and a hard shipping deadline — Intuit&#x27;s TurboTax team had a question: could AI compress a months-long implementation into days without sacrificing accuracy. What they built to do it is less a tax story than a template, a workflow combining commercial AI tools, a proprietary domain-specific language and a custom unit test framework that any domain-constrained development team can learn from.]]></image:caption>
      </image:image>
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        <image:title><![CDATA[The Download: an exclusive Jeff VanderMeer story and AI models too scary to release]]></image:title>
        <image:caption><![CDATA[This is today&#8217;s edition of The Download, our weekday newsletter that provides a daily dose of what&#8217;s going on in the world of technology.  Constellations&#160; —Constellations is a short story by Jeff VanderMeer, the author of the critically acclaimed, bestselling Southern Reach series.]]></image:caption>
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        <image:title><![CDATA[OpenAI introduces ChatGPT Pro $100 tier with 5X usage limits for Codex compared to Plus]]></image:title>
        <image:caption><![CDATA[OpenAI is making moves to try and court more developers and vibe coders (those who build software using AI models and natural language) away from rivals like Anthropic. Today, the firm arguably most synonymous with the generative AI boom announced it will begin offering a new, more mid-range subscription tier — a $100 ChatGPT Pro plan — which joins its free, Go ($8 monthly), Plus ($20 monthly) and existing Pro ($200 monthly) plans for individuals using ChatGPT and related OpenAI products.]]></image:caption>
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        <image:title><![CDATA[Mythos autonomously exploited vulnerabilities that survived 27 years of human review. Security teams need a new detection playbook]]></image:title>
        <image:caption><![CDATA[A 27-year-old bug sat inside OpenBSD’s TCP stack while auditors reviewed the code, fuzzers ran against it, and the operating system earned its reputation as one of the most security-hardened platforms on earth.  Two packets could crash any server running it.]]></image:caption>
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        <image:title><![CDATA[New Future of Work: AI is driving rapid change, uneven benefits]]></image:title>
        <image:caption><![CDATA[For the past five years, the New Future of Work report has captured how work is changing.  This year, the shift feels especially sharp.]]></image:caption>
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        <image:title><![CDATA[Ideas: Steering AI toward the work future we want]]></image:title>
        <image:caption><![CDATA[Microsoft Chief Scientist Jaime Teevan and researchers Jenna Butler, Jake Hofman, and Rebecca Janssen unpack the New Future of Work Report 2025 and explore the ideal AI-driven working world.  Plus, is AI a tool or a collaborator.]]></image:caption>
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        <image:title><![CDATA[The Download: AstroTurf wars and exponential AI growth]]></image:title>
        <image:caption><![CDATA[This is today&#8217;s edition of The Download, our weekday newsletter that provides a daily dose of what&#8217;s going on in the world of technology.  Is&#160;fake&#160;grass&#160;a&#160;bad&#160;idea.]]></image:caption>
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        <image:title><![CDATA[Claude, OpenClaw and the new reality: AI agents are here — and so is the chaos]]></image:title>
        <image:caption><![CDATA[The age of agentic AI is upon us — whether we like it or not.  What started with an innocent question-answer banter with ChatGPT back in 2022 has become an existential debate on job security and the rise of the machines.]]></image:caption>
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        <image:title><![CDATA[Goodbye, Llama? Meta launches new proprietary AI model Muse Spark — first since Superintelligence Labs' formation]]></image:title>
        <image:caption><![CDATA[Meta has been one of the most interesting companies of the generative AI era — initially gaining a loyal and huge following of users for the release of its mostly open source Llama family of large language models (LLMs) beginning in early 2023 but coming to screeching halt last year after Llama 4 debuted to mixed reviews and ultimately, admissions of gaming benchmarks. That bumpy rollout of Llama 4 apparently spurred Meta founder and CEO Mark Zuckerberg to totally overhaul Meta&#x27;s AI operations in the summer of 2025, forming a new internal division, Meta Superintelligence Labs (MSL) which he recruited 29-year-old former Scale AI co-founder and CEO Alexandr Wang to lead as Chief AI Officer.]]></image:caption>
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        <image:title><![CDATA[New framework lets AI agents rewrite their own skills without retraining the underlying model]]></image:title>
        <image:caption><![CDATA[One major challenge in deploying autonomous agents is building systems that can adapt to changes in their environments without the need to retrain the underlying large language models (LLMs). Memento-Skills, a new framework developed by researchers at multiple universities, addresses this bottleneck by giving agents the ability to develop their skills by themselves.]]></image:caption>
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        <image:title><![CDATA[Mustafa Suleyman: AI development won’t hit a wall anytime soon—here’s why]]></image:title>
        <image:caption><![CDATA[We evolved for a linear world.  If you walk for an hour, you cover a certain distance.]]></image:caption>
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        <image:title><![CDATA[The Download: water threats in Iran and AI’s impact on what entrepreneurs make]]></image:title>
        <image:caption><![CDATA[This is today&#8217;s edition of The Download, our weekday newsletter that provides a daily dose of what&#8217;s going on in the world of technology.  Desalination plants in the Middle East are increasingly vulnerable&#160; As the conflict in Iran has escalated, a crucial resource is under fire: the desalinization technology that supplies water in the region.]]></image:caption>
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        <image:title><![CDATA[Amazon S3 Files gives AI agents a native file system workspace, ending the object-file split that breaks multi-agent pipelines]]></image:title>
        <image:caption><![CDATA[AI agents run on file systems using standard tools to navigate directories and read file paths.  The challenge, however, is that there is a lot of enterprise data in object storage systems, notably Amazon S3.]]></image:caption>
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        <image:title><![CDATA[Anthropic says its most powerful AI cyber model is too dangerous to release publicly — so it built Project Glasswing]]></image:title>
        <image:caption><![CDATA[Anthropic on Tuesday announced Project Glasswing, a sweeping cybersecurity initiative that pairs an unreleased frontier AI model — Claude Mythos Preview — with a coalition of twelve major technology and finance companies in an effort to find and patch software vulnerabilities across the world&#x27;s most critical infrastructure before adversaries can exploit them. The launch partners include Amazon Web Services, Apple, Broadcom, Cisco, CrowdStrike, Google, JPMorganChase, the Linux Foundation, Microsoft, Nvidia, and Palo Alto Networks.]]></image:caption>
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        <image:title><![CDATA[AI joins the 8-hour work day as GLM ships 5.1 open source LLM, beating Opus 4.6 and GPT-5.4 on SWE-Bench Pro]]></image:title>
        <image:caption><![CDATA[Is China picking back up the open source AI baton.  Z.]]></image:caption>
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        <image:title><![CDATA[LLM-referred traffic converts at 30-40% — and most enterprises aren't optimizing for it]]></image:title>
        <image:caption><![CDATA[For more than two decades, digital discovery has operated on a simple model: search, scan, click, decide.  That worked when humans were the ones doing the web searching; but with the advent of AI agents, the primary consumer of information is no longer always human.]]></image:caption>
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        <image:title><![CDATA[AI-RAN is redefining enterprise edge intelligence and autonomy ]]></image:title>
        <image:caption><![CDATA[Presented by Booz Allen AI-RAN, or artificial intelligence radio area networks, is a reimagining of what wireless infrastructure can do.  Rather than treating the network as a passive conduit for data, AI-RAN turns it into an active computational layer.]]></image:caption>
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        <image:title><![CDATA[As models converge, the enterprise edge in AI shifts to governed data and the platforms that control it]]></image:title>
        <image:caption><![CDATA[Presented by BoxAs frontier models converge, the advantage in enterprise AI is moving away from the model and toward the data it can safely access.  For most enterprises, that advantage lives in unstructured data: the contracts, case files, product specifications, and internal knowledge.]]></image:caption>
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        <image:title><![CDATA[Desalination plants in the Middle East are increasingly vulnerable]]></image:title>
        <image:caption><![CDATA[MIT Technology Review Explains: Let our writers untangle the complex, messy world of technology to help you understand what’s coming next.  You can read more from the series here.]]></image:caption>
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        <image:title><![CDATA[Enabling agent-first process redesign]]></image:title>
        <image:caption><![CDATA[Unlike static, rules-based systems, AI agents can learn, adapt, and optimize processes dynamically.  As they interact with data, systems, people, and other agents in real time, AI agents can execute entire workflows autonomously.]]></image:caption>
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        <image:title><![CDATA[Block introduces Managerbot, a proactive Square AI agent and the clearest proof point yet for Jack Dorsey’s AI bet]]></image:title>
        <image:caption><![CDATA[Block today announced Managerbot, a new AI agent embedded in the Square platform that proactively monitors a seller&#x27;s business, identifies emerging problems, and proposes actionable solutions — without the seller ever having to ask a question.  The product marks the most tangible manifestation of CEO Jack Dorsey&#x27;s controversial bet that artificial intelligence can fundamentally reshape how his company operates, builds products, and serves the millions of small businesses that depend on Square to run day-to-day commerce.]]></image:caption>
      </image:image>
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        <image:title><![CDATA[The Download: AI’s impact on jobs, and data centres in space]]></image:title>
        <image:caption><![CDATA[This is today&#8217;s edition of The Download, our weekday newsletter that provides a daily dose of what&#8217;s going on in the world of technology.  The one piece of data that could&#160;actually shed&#160;light on your job and AI&#160; Within Silicon Valley’s orbit, an AI-fueled&#160;jobs apocalypse is spoken about as a given.]]></image:caption>
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        <image:title><![CDATA[The one piece of data that could actually shed light on your job and AI]]></image:title>
        <image:caption><![CDATA[This story originally appeared in The Algorithm, our weekly newsletter on AI.  To get stories like this in your inbox first, sign up here.]]></image:caption>
      </image:image>
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        <image:title><![CDATA[How MassMutual and Mass General Brigham turned AI pilot sprawl into production results]]></image:title>
        <image:caption><![CDATA[Enterprise AI programs rarely fail because of bad ideas.  More often, they get stuck in ungoverned pilot mode and never reach production.]]></image:caption>
      </image:image>
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        <image:title><![CDATA[AI agents that automatically prevent, detect and fix software issues are here as NeuBird AI launches Falcon, FalconClaw]]></image:title>
        <image:caption><![CDATA[The mantra of the modern tech industry was arguably coined by Facebook (before it became Meta): &quot;move fast and break things. &quot; But as enterprise infrastructure has shifted into a dizzying maze of hybrid clouds, microservices, and ephemeral compute clusters, the &quot;breaking&quot; part has become a structural tax that many organizations can no longer afford to pay.]]></image:caption>
      </image:image>
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        <image:title><![CDATA[AI is changing how small online sellers decide what to make]]></image:title>
        <image:caption><![CDATA[For years Mike McClary sold the Guardian LTE Flashlight, a heavy-duty black model, online through his small outdoor brand.  The product, designed for brightness and durability, became one of his most popular items ever.]]></image:caption>
      </image:image>
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      <image:image>
        <image:loc>https://images.pexels.com/photos/18069696/pexels-photo-18069696.png?auto=compress&amp;cs=tinysrgb&amp;fit=crop&amp;h=627&amp;w=1200</image:loc>
        <image:title><![CDATA[Closing the data security maturity gap: Embedding protection into enterprise workflows]]></image:title>
        <image:caption><![CDATA[Presented by Capital One Data security remains one of the least mature domains in enterprise cybersecurity.  According to IBM, 35% of breaches in 2025 involved unmanaged data source or “shadow data.]]></image:caption>
      </image:image>
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        <image:title><![CDATA[Claude, OpenClaw and the new reality: AI agents are here — and so is the chaos]]></image:title>
        <image:caption><![CDATA[The age of agentic AI is upon us — whether we like it or not.  What started with an innocent question-answer banter with ChatGPT back in 2022 has become an existential debate on job security and the rise of the machines.]]></image:caption>
      </image:image>
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