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    <title>InfoQ - Large language models - News</title>
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    <description>InfoQ Large language models News feed</description>
    <item>
      <title>Google Mantis: An Agentic Vulnerability Scanning Harness for Reducing False Positives</title>
      <link>https://www.infoq.com/news/2026/09/google-mantis-vulnerability-scan/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Large+language+models-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/09/google-mantis-vulnerability-scan/en/headerimage/google-mantis-scanner-1788693601725.jpeg"/&gt;&lt;p&gt;Google has open-sourced Mantis, an AI-agent framework designed to automate the software vulnerability lifecycle, from identifying and validating vulnerabilities to reproducing and fixing them. Google says it developed Mantis to address the high rate of false positives and hallucinated vulnerabilities produced by conventional AI-powered code scanning.&lt;/p&gt; &lt;i&gt;By Sergio De Simone&lt;/i&gt;</description>
      <category>Google</category>
      <category>Open Source</category>
      <category>Security Vulnerabilities</category>
      <category>Large language models</category>
      <category>Agents</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Sun, 06 Sep 2026 12:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/09/google-mantis-vulnerability-scan/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Large+language+models-news</guid>
      <dc:creator>Sergio De Simone</dc:creator>
      <dc:date>2026-09-06T12:00:00Z</dc:date>
      <dc:identifier>/news/2026/09/google-mantis-vulnerability-scan/en</dc:identifier>
    </item>
    <item>
      <title>Shopify Introduces Gisting: Compressing LLM System Prompts into Learned Tokens</title>
      <link>https://www.infoq.com/news/2026/09/spotify-gisting-llm-performance/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Large+language+models-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/09/spotify-gisting-llm-performance/en/headerimage/spotify-app-size-growth-process-1788462838475.jpeg"/&gt;&lt;p&gt;Shopify's engineering introduced gisting, a novel technique for compressing long LLM prompts into a smaller set of learned "gist" tokens, improving throughput and reducing inference cost.&lt;/p&gt; &lt;i&gt;By Sergio De Simone&lt;/i&gt;</description>
      <category>Model Inference</category>
      <category>Large language models</category>
      <category>Agents</category>
      <category>Performance</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Thu, 03 Sep 2026 20:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/09/spotify-gisting-llm-performance/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Large+language+models-news</guid>
      <dc:creator>Sergio De Simone</dc:creator>
      <dc:date>2026-09-03T20:00:00Z</dc:date>
      <dc:identifier>/news/2026/09/spotify-gisting-llm-performance/en</dc:identifier>
    </item>
    <item>
      <title>Cohere’s Parse 5 Promises Efficient Multi-Modal Information Extraction from Complex Documents</title>
      <link>https://www.infoq.com/news/2026/09/cohere-multimodal-parse/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Large+language+models-news</link>
      <description>&lt;img src="https://www.infoq.com/styles/static/images/logo/logo_bigger.jpg"/&gt;&lt;p&gt;Cohere has launched Parse 5, a multimodal foundation model designed to extract structured data from complex enterprise documents. The 2.3-billion-parameter system converts visually rich PDFs into Markdown while providing bounding box coordinates for visual grounding. It has been evaluated against over 2,000 enterprise pages, achieving an average score of 79.2 in key performance areas.&lt;/p&gt; &lt;i&gt;By Olimpiu Pop&lt;/i&gt;</description>
      <category>OCR</category>
      <category>Machine Learning</category>
      <category>Large language models</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Thu, 03 Sep 2026 06:06:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/09/cohere-multimodal-parse/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Large+language+models-news</guid>
      <dc:creator>Olimpiu Pop</dc:creator>
      <dc:date>2026-09-03T06:06:00Z</dc:date>
      <dc:identifier>/news/2026/09/cohere-multimodal-parse/en</dc:identifier>
    </item>
    <item>
      <title>OpenClaw 2.0 Releases with Simplified Setup and Collaborative Agents</title>
      <link>https://www.infoq.com/news/2026/09/openclaw-2-release/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Large+language+models-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/09/openclaw-2-release/en/headerimage/generatedHeaderImage-1788278004063.jpg"/&gt;&lt;p&gt;OpenClaw has released OpenClaw 2.0, a major update to the open-source personal AI agent that changes its installation process, browser interface, memory, skills, automations, plugins, security, and collaboration features.&lt;/p&gt; &lt;i&gt;By Daniel Dominguez&lt;/i&gt;</description>
      <category>OpenAI</category>
      <category>Anthropic</category>
      <category>Artificial Intelligence</category>
      <category>ChatGPT</category>
      <category>Large language models</category>
      <category>Agents</category>
      <category>Claude</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Tue, 01 Sep 2026 18:47:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/09/openclaw-2-release/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Large+language+models-news</guid>
      <dc:creator>Daniel Dominguez</dc:creator>
      <dc:date>2026-09-01T18:47:00Z</dc:date>
      <dc:identifier>/news/2026/09/openclaw-2-release/en</dc:identifier>
    </item>
    <item>
      <title>Cloudflare Extends AI Search to Make it Easier for Agents and Developers to Search Custom Data</title>
      <link>https://www.infoq.com/news/2026/08/cloudflare-ai-search/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Large+language+models-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/08/cloudflare-ai-search/en/headerimage/cloudflare-ai-search-1788105575745.jpeg"/&gt;&lt;p&gt;Cloudflare AI Search is a built-in search and retrieval service designed to give AI agents and applications a ready-to-use search engine over custom data. It supports agent integration, multimodal search, and seamless integration with other Cloudflare tools.&lt;/p&gt; &lt;i&gt;By Sergio De Simone&lt;/i&gt;</description>
      <category>Search Engine</category>
      <category>Cloud</category>
      <category>Large language models</category>
      <category>Cloudflare</category>
      <category>Agents</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Sun, 30 Aug 2026 19:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/08/cloudflare-ai-search/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Large+language+models-news</guid>
      <dc:creator>Sergio De Simone</dc:creator>
      <dc:date>2026-08-30T19:00:00Z</dc:date>
      <dc:identifier>/news/2026/08/cloudflare-ai-search/en</dc:identifier>
    </item>
    <item>
      <title>FreeToken Unlocks Frontier MoE Inference on Consumer Hardware via Dynamic Co-Execution</title>
      <link>https://www.infoq.com/news/2026/08/freetoken-local-inference/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Large+language+models-news</link>
      <description>&lt;img src="https://www.infoq.com/styles/static/images/logo/logo_bigger.jpg"/&gt;&lt;p&gt;Researchers from UC Berkeley and MIT have developed FreeToken, an open-source inference engine that enhances the utility of Mixture-of-Experts models on consumer hardware. By implementing a dynamic scheduling policy and optimising weight management, FreeToken improves decoding speeds and execution efficiency in edge AI applications, fostering self-hosted reasoning systems.&lt;/p&gt; &lt;i&gt;By Olimpiu Pop&lt;/i&gt;</description>
      <category>Model Inference</category>
      <category>Local First</category>
      <category>Local Inference</category>
      <category>Large language models</category>
      <category>Frontier Model</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Sat, 29 Aug 2026 05:05:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/08/freetoken-local-inference/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Large+language+models-news</guid>
      <dc:creator>Olimpiu Pop</dc:creator>
      <dc:date>2026-08-29T05:05:00Z</dc:date>
      <dc:identifier>/news/2026/08/freetoken-local-inference/en</dc:identifier>
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