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    <title>InfoQ - AI, ML &amp; Data Engineering - News</title>
    <link>https://www.infoq.com</link>
    <description>InfoQ AI, ML &amp; Data Engineering News feed</description>
    <item>
      <title>Google Opens Gemma 4 Under Apache 2.0 with Multimodal and Agentic Capabilities</title>
      <link>https://www.infoq.com/news/2026/04/google-gemm4/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/04/google-gemm4/en/headerimage/header-1776307607549.jpg"/&gt;&lt;p&gt;Google has announced the release of Gemma 4, a series of open-weight AI models, including variants with 2B, 4B, 26B, and 31B parameters, under the Apache 2.0 license. Key features include enhanced video and image processing, audio input on smaller models, and extended context windows up to 256K tokens.&lt;/p&gt; &lt;i&gt;By Hien Luu&lt;/i&gt;</description>
      <category>Large language models</category>
      <category>Edge Computing</category>
      <category>Generative AI</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Thu, 16 Apr 2026 17:05:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/04/google-gemm4/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-news</guid>
      <dc:creator>Hien Luu</dc:creator>
      <dc:date>2026-04-16T17:05:00Z</dc:date>
      <dc:identifier>/news/2026/04/google-gemm4/en</dc:identifier>
    </item>
    <item>
      <title>Cloudflare Launches Code Mode MCP Server to Optimize Token Usage for AI Agents</title>
      <link>https://www.infoq.com/news/2026/04/cloudflare-code-mode-mcp-server/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/04/cloudflare-code-mode-mcp-server/en/headerimage/generatedHeaderImage-1775438665018.jpg"/&gt;&lt;p&gt;Cloudflare has launched a new Model Context Protocol (MCP) server powered by Code Mode, enabling AI agents to interact with large APIs with minimal token usage. The server reduces context footprint across 2,500+ endpoints, improves multi-API orchestration, and provides a secure, code-centric execution environment for LLM agents.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Model Context Protocol (MCP)</category>
      <category>AI Architecture</category>
      <category>Agents</category>
      <category>Workflow / BPM</category>
      <category>Large language models</category>
      <category>API</category>
      <category>Orchestration</category>
      <category>TypeScript</category>
      <category>Optimization</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Thu, 16 Apr 2026 14:17:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/04/cloudflare-code-mode-mcp-server/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-news</guid>
      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-04-16T14:17:00Z</dc:date>
      <dc:identifier>/news/2026/04/cloudflare-code-mode-mcp-server/en</dc:identifier>
    </item>
    <item>
      <title>Cursor 3 Introduces Agent-First Interface, Moving Beyond the IDE Model</title>
      <link>https://www.infoq.com/news/2026/04/cursor-3-agent-first-interface/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/04/cursor-3-agent-first-interface/en/headerimage/generatedHeaderImage-1776081399414.jpg"/&gt;&lt;p&gt;Anysphere released Cursor 3, a redesigned interface built from scratch that shifts the primary model from file editing to managing parallel coding agents. The new workspace supports local-to-cloud agent handoff, multi-repo parallel execution, and a plugin marketplace. Community reaction has been divided, with developers questioning cost overhead and the move away from Cursor's IDE-first identity.&lt;/p&gt; &lt;i&gt;By Steef-Jan Wiggers&lt;/i&gt;</description>
      <category>Artificial Intelligence</category>
      <category>AI Development</category>
      <category>Developer Experience</category>
      <category>IDE</category>
      <category>Large language models</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Thu, 16 Apr 2026 09:37:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/04/cursor-3-agent-first-interface/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-news</guid>
      <dc:creator>Steef-Jan Wiggers</dc:creator>
      <dc:date>2026-04-16T09:37:00Z</dc:date>
      <dc:identifier>/news/2026/04/cursor-3-agent-first-interface/en</dc:identifier>
    </item>
    <item>
      <title>Google’s TurboQuant Compression May Support Faster Inference, Same Accuracy on Less Capable Hardware</title>
      <link>https://www.infoq.com/news/2026/04/turboquant-compression-kv-cache/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/04/turboquant-compression-kv-cache/en/headerimage/generatedHeaderImage-1776265077411.jpg"/&gt;&lt;p&gt;Google Research unveiled TurboQuant, a novel quantization algorithm that compresses large language models’ Key-Value caches by up to 6x. With 3.5-bit compression, near-zero accuracy loss, and no retraining needed, it allows developers to run massive context windows on significantly more modest hardware than previously required. Early community benchmarks confirm significant efficiency gains.&lt;/p&gt; &lt;i&gt;By Bruno Couriol&lt;/i&gt;</description>
      <category>Large language models</category>
      <category>Performance</category>
      <category>Compression</category>
      <category>Optimization</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Wed, 15 Apr 2026 16:53:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/04/turboquant-compression-kv-cache/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-news</guid>
      <dc:creator>Bruno Couriol</dc:creator>
      <dc:date>2026-04-15T16:53:00Z</dc:date>
      <dc:identifier>/news/2026/04/turboquant-compression-kv-cache/en</dc:identifier>
    </item>
    <item>
      <title>Claude Code Used to Find Remotely Exploitable Linux Kernel Vulnerability Hidden for 23 Years</title>
      <link>https://www.infoq.com/news/2026/04/claude-code-linux-vulnerability/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/04/claude-code-linux-vulnerability/en/headerimage/generatedHeaderImage-1775817662497.jpg"/&gt;&lt;p&gt;Anthropic researcher Nicholas Carlini used Claude Code to find a remotely exploitable heap buffer overflow in the Linux kernel's NFS driver, undiscovered for 23 years. Five kernel vulnerabilities have been confirmed so far. Linux kernel maintainers report that AI bug reports have recently shifted from slop to legitimate findings, with security lists now receiving 5-10 valid reports daily.&lt;/p&gt; &lt;i&gt;By Steef-Jan Wiggers&lt;/i&gt;</description>
      <category>Artificial Intelligence</category>
      <category>Linux</category>
      <category>Anthropic</category>
      <category>Claude</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Wed, 15 Apr 2026 09:36:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/04/claude-code-linux-vulnerability/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-news</guid>
      <dc:creator>Steef-Jan Wiggers</dc:creator>
      <dc:date>2026-04-15T09:36:00Z</dc:date>
      <dc:identifier>/news/2026/04/claude-code-linux-vulnerability/en</dc:identifier>
    </item>
    <item>
      <title>Anthropic Paper Examines Behavioral Impact of Emotion-Like Mechanisms in LLMs</title>
      <link>https://www.infoq.com/news/2026/04/anthropic-paper-llms/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/04/anthropic-paper-llms/en/headerimage/generatedHeaderImage-1776164869421.jpg"/&gt;&lt;p&gt;A recent paper from Anthropic examines how large language models internally represent concepts related to emotions and how these representations influence behavior. The work is part of the company’s interpretability research and focuses on analyzing internal activations in Claude Sonnet 4.5 to understand the mechanisms behind model responses better.&lt;/p&gt; &lt;i&gt;By Robert Krzaczyński&lt;/i&gt;</description>
      <category>Anthropic</category>
      <category>Large language models</category>
      <category>Claude</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Tue, 14 Apr 2026 11:35:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/04/anthropic-paper-llms/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-news</guid>
      <dc:creator>Robert Krzaczyński</dc:creator>
      <dc:date>2026-04-14T11:35:00Z</dc:date>
      <dc:identifier>/news/2026/04/anthropic-paper-llms/en</dc:identifier>
    </item>
    <item>
      <title>Google Released Gemma 4 with a Focus on Local-First, On-Device AI Inference</title>
      <link>https://www.infoq.com/news/2026/04/gemma-4-android-ai-inference/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/04/gemma-4-android-ai-inference/en/headerimage/gemma-4-android-inference-1776112478269.jpeg"/&gt;&lt;p&gt;With the release of Gemma 4, Google aims to enable local, agentic AI for Android development through a family of models designed to support the entire software lifecycle, from coding to production.&lt;/p&gt; &lt;i&gt;By Sergio De Simone&lt;/i&gt;</description>
      <category>Android Studio</category>
      <category>Mobile</category>
      <category>Agents</category>
      <category>Large language models</category>
      <category>Google+</category>
      <category>Android</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Mon, 13 Apr 2026 21:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/04/gemma-4-android-ai-inference/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-news</guid>
      <dc:creator>Sergio De Simone</dc:creator>
      <dc:date>2026-04-13T21:00:00Z</dc:date>
      <dc:identifier>/news/2026/04/gemma-4-android-ai-inference/en</dc:identifier>
    </item>
    <item>
      <title>Lyft Scales Global Localization Using AI and Human-in-the-Loop Review</title>
      <link>https://www.infoq.com/news/2026/04/lyft-ai-localization-pipeline/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/04/lyft-ai-localization-pipeline/en/headerimage/generatedHeaderImage-1775411926263.jpg"/&gt;&lt;p&gt;Lyft has implemented an AI-driven localization system to accelerate translations of its app and web content. Using a dual-path pipeline with large language models and human review, the system processes most content in minutes, improves international release speed, ensures brand consistency, and handles complex cases like regional idioms and legal messaging efficiently.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>i18n</category>
      <category>localization</category>
      <category>Translation</category>
      <category>Real Time</category>
      <category>App Engine</category>
      <category>Large language models</category>
      <category>Automation</category>
      <category>Batch Processing</category>
      <category>Internationalization</category>
      <category>Data Pipelines</category>
      <category>Web</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Mon, 13 Apr 2026 13:45:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/04/lyft-ai-localization-pipeline/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-news</guid>
      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-04-13T13:45:00Z</dc:date>
      <dc:identifier>/news/2026/04/lyft-ai-localization-pipeline/en</dc:identifier>
    </item>
    <item>
      <title>Anthropic Releases Claude Mythos Preview with Cybersecurity Capabilities but Withholds Public Access</title>
      <link>https://www.infoq.com/news/2026/04/anthropic-claude-mythos/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/04/anthropic-claude-mythos/en/headerimage/generatedHeaderImage-1775828239509.jpg"/&gt;&lt;p&gt;Anthropic has introduced Claude Mythos Preview, its most advanced AI model, improving significantly in reasoning, coding, and cybersecurity. Unlike previous releases, it will not be publicly available. Access is limited to a consortium of tech companies through Project Glasswing. Internal tests revealed the model's ability to discover critical security flaws effectively.&lt;/p&gt; &lt;i&gt;By Daniel Curtis&lt;/i&gt;</description>
      <category>Artificial Intelligence</category>
      <category>Security Vulnerabilities</category>
      <category>Anthropic</category>
      <category>Application Security</category>
      <category>Claude</category>
      <category>AI Coding</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Mon, 13 Apr 2026 06:35:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/04/anthropic-claude-mythos/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-news</guid>
      <dc:creator>Daniel Curtis</dc:creator>
      <dc:date>2026-04-13T06:35:00Z</dc:date>
      <dc:identifier>/news/2026/04/anthropic-claude-mythos/en</dc:identifier>
    </item>
    <item>
      <title>GitHub Copilot CLI Reaches General Availability</title>
      <link>https://www.infoq.com/news/2026/04/github-copilot-cli-ga/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/04/github-copilot-cli-ga/en/headerimage/header-1775595985599.jpeg"/&gt;&lt;p&gt;GitHub has launched Copilot CLI into general availability, bringing generative AI directly to the terminal. Integrated with the GitHub CLI, it offers natural language command suggestions and code explanations. Recent updates introduce "agentic" workflows with Autopilot mode and GPT-5.4 support, alongside new enterprise telemetry for tracking usage across development teams.&lt;/p&gt; &lt;i&gt;By Mark Silvester&lt;/i&gt;</description>
      <category>github</category>
      <category>AI Development</category>
      <category>AI Assisted Coding</category>
      <category>copilot</category>
      <category>AI Coding</category>
      <category>DevOps</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Sun, 12 Apr 2026 09:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/04/github-copilot-cli-ga/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-news</guid>
      <dc:creator>Mark Silvester</dc:creator>
      <dc:date>2026-04-12T09:00:00Z</dc:date>
      <dc:identifier>/news/2026/04/github-copilot-cli-ga/en</dc:identifier>
    </item>
    <item>
      <title>Etsy Migrates 1000-Shard, 425 TB MySQL Sharding Architecture to Vitess</title>
      <link>https://www.infoq.com/news/2026/04/etsy-vitess-sharding-migration/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/04/etsy-vitess-sharding-migration/en/headerimage/generatedHeaderImage-1774855136721.jpg"/&gt;&lt;p&gt;The Etsy engineering team recently described how the company migrated its long-running MySQL sharding infrastructure to Vitess. The transition moved shard routing from Etsy’s internal systems to Vitess using vindexes, enabling capabilities such as resharding data and sharding previously unsharded tables.&lt;/p&gt; &lt;i&gt;By Renato Losio&lt;/i&gt;</description>
      <category>MySQL</category>
      <category>Sharding</category>
      <category>Distributed Data</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Sat, 11 Apr 2026 07:13:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/04/etsy-vitess-sharding-migration/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-news</guid>
      <dc:creator>Renato Losio</dc:creator>
      <dc:date>2026-04-11T07:13:00Z</dc:date>
      <dc:identifier>/news/2026/04/etsy-vitess-sharding-migration/en</dc:identifier>
    </item>
    <item>
      <title>Google Cloud Highlights Ongoing Work on PostgreSQL Core Capabilities</title>
      <link>https://www.infoq.com/news/2026/04/google-cloud-postgresql/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/04/google-cloud-postgresql/en/headerimage/generatedHeaderImage-1775811962259.jpg"/&gt;&lt;p&gt;Google Cloud has outlined its recent technical contributions to PostgreSQL, emphasizing improvements in logical replication, upgrade processes, and overall system stability. The update reflects ongoing collaboration with the upstream community and focuses on enhancements to the core engine aimed at addressing scalability, replication, and operational challenges.&lt;/p&gt; &lt;i&gt;By Robert Krzaczyński&lt;/i&gt;</description>
      <category>Google Cloud</category>
      <category>Postgres</category>
      <category>SQL</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Fri, 10 Apr 2026 09:30:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/04/google-cloud-postgresql/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-news</guid>
      <dc:creator>Robert Krzaczyński</dc:creator>
      <dc:date>2026-04-10T09:30:00Z</dc:date>
      <dc:identifier>/news/2026/04/google-cloud-postgresql/en</dc:identifier>
    </item>
    <item>
      <title>AAIF's MCP Dev Summit: Gateways, gRPC, and Observability Signal Protocol Hardening</title>
      <link>https://www.infoq.com/news/2026/04/aaif-mcp-summit/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/04/aaif-mcp-summit/en/headerimage/generatedHeaderImage-1775743143926.jpg"/&gt;&lt;p&gt;The MCP Dev Summit North America 2026, held on April 2-3 at the New York Marriott Marquis, gathered about 1,200 attendees. Hosted by the Linux Foundation's Agentic AI Foundation, discussions focused on the Model Context Protocol's evolution and enterprise adoption, particularly by Amazon and Uber, emphasizing security, interoperability, and scaling for production.&lt;/p&gt; &lt;i&gt;By Andrew Hoblitzell&lt;/i&gt;</description>
      <category>Artificial Intelligence</category>
      <category>Model Context Protocol (MCP)</category>
      <category>Open Source</category>
      <category>Protocol</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Thu, 09 Apr 2026 13:10:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/04/aaif-mcp-summit/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-news</guid>
      <dc:creator>Andrew Hoblitzell</dc:creator>
      <dc:date>2026-04-09T13:10:00Z</dc:date>
      <dc:identifier>/news/2026/04/aaif-mcp-summit/en</dc:identifier>
    </item>
    <item>
      <title>Google Brings MCP Support to Colab, Enabling Cloud Execution for AI Agents</title>
      <link>https://www.infoq.com/news/2026/04/colab-mcp-server/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/04/colab-mcp-server/en/headerimage/generatedHeaderImage-1775721271681.jpg"/&gt;&lt;p&gt;Google has released the open-source Colab MCP Server, enabling AI agents to directly interact with Google Colab through the Model Context Protocol (MCP). The project is designed to bridge local agent workflows with cloud-based execution, allowing developers to offload compute-intensive or potentially unsafe tasks from their own machines.&lt;/p&gt; &lt;i&gt;By Robert Krzaczyński&lt;/i&gt;</description>
      <category>Artificial Intelligence</category>
      <category>Model Context Protocol (MCP)</category>
      <category>Agents</category>
      <category>Google</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Thu, 09 Apr 2026 08:30:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/04/colab-mcp-server/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-news</guid>
      <dc:creator>Robert Krzaczyński</dc:creator>
      <dc:date>2026-04-09T08:30:00Z</dc:date>
      <dc:identifier>/news/2026/04/colab-mcp-server/en</dc:identifier>
    </item>
    <item>
      <title>Cloudflare and ETH Zurich Outline Approaches for AI-Driven Cache Optimization</title>
      <link>https://www.infoq.com/news/2026/04/cloudflare-ai-caching-strategies/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/04/cloudflare-ai-caching-strategies/en/headerimage/aicrawler-1775341603564.jpeg"/&gt;&lt;p&gt;Cloudflare and ETH Zurich highlight how AI-driven crawler traffic challenges traditional caching in CDNs and databases. They propose AI-aware strategies including separate cache tiers, adaptive algorithms, and pay-per-crawl models to balance performance for human users and AI services while maintaining cache efficiency and system stability.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Artificial Intelligence</category>
      <category>CDN</category>
      <category>Database</category>
      <category>AI Architecture</category>
      <category>Retrieval-Augmented Generation</category>
      <category>BOTS</category>
      <category>Caching</category>
      <category>Performance</category>
      <category>Machine Learning</category>
      <category>Distributed Cache</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Wed, 08 Apr 2026 14:20:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/04/cloudflare-ai-caching-strategies/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-news</guid>
      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-04-08T14:20:00Z</dc:date>
      <dc:identifier>/news/2026/04/cloudflare-ai-caching-strategies/en</dc:identifier>
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