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    <title>InfoQ - AI, ML &amp; Data Engineering</title>
    <link>https://www.infoq.com</link>
    <description>InfoQ AI, ML &amp; Data Engineering feed</description>
    <item>
      <title>Three InfoQ Certification Cohorts Start This August: Meet the Facilitators</title>
      <link>https://www.infoq.com/news/2026/07/infoq-online-cohorts-2026/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/07/infoq-online-cohorts-2026/en/headerimage/infoq-online-cohorts-2026-1784536581240.jpg"/&gt;&lt;p&gt;InfoQ has opened enrollment for three five-week online certification cohorts starting in August, each led by a senior practitioner applying QCon talk frameworks to participants' own work: architecture with Luca Mezzalira, engineering leadership with Michelle Brush, and AI security and privacy with Katharine Jarmul.&lt;/p&gt; &lt;i&gt;By Artenisa Chatziou&lt;/i&gt;</description>
      <category>Privacy</category>
      <category>Architecture ICSAET</category>
      <category>InfoQ Certification Program</category>
      <category>AI Security</category>
      <category>Software Engineering</category>
      <category>Leadership</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Mon, 20 Jul 2026 13:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/infoq-online-cohorts-2026/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering</guid>
      <dc:creator>Artenisa Chatziou</dc:creator>
      <dc:date>2026-07-20T13:00:00Z</dc:date>
      <dc:identifier>/news/2026/07/infoq-online-cohorts-2026/en</dc:identifier>
    </item>
    <item>
      <title>How Netflix Built GenPage: a Single GenAI Model to Build Personalized Homepages</title>
      <link>https://www.infoq.com/news/2026/07/netflix-llm-homepage-generation/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/07/netflix-llm-homepage-generation/en/headerimage/netflix-genpage-recommender-1784476882801.jpeg"/&gt;&lt;p&gt;GenPage is a generative AI system developed by Netflix to replace its traditional multi-stage recommendation pipeline by directly generating personalized user homepages. GenPage leverages user history and request context as a prompt to produce the entire page, resulting in improved user engagement and reduced serving latency.&lt;/p&gt; &lt;i&gt;By Sergio De Simone&lt;/i&gt;</description>
      <category>Generative AI</category>
      <category>A/B Testing</category>
      <category>Large language models</category>
      <category>Netflix</category>
      <category>Development</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Sun, 19 Jul 2026 20:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/netflix-llm-homepage-generation/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering</guid>
      <dc:creator>Sergio De Simone</dc:creator>
      <dc:date>2026-07-19T20:00:00Z</dc:date>
      <dc:identifier>/news/2026/07/netflix-llm-homepage-generation/en</dc:identifier>
    </item>
    <item>
      <title>Google's AlphaEvolve Reaches General Availability with Evolutionary Code Optimization as a Service</title>
      <link>https://www.infoq.com/news/2026/07/alphaevolve-generally-available/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/07/alphaevolve-generally-available/en/headerimage/generatedHeaderImage-1783873354690.jpg"/&gt;&lt;p&gt;Google's AlphaEvolve reached general availability on the Gemini Enterprise Agent Platform, turning the DeepMind research project into an evolutionary code optimization service. Evaluators run client-side so code never leaves the customer's infrastructure. Klarna doubled ML training throughput; practitioners note it only works where a measurable evaluation function exists.&lt;/p&gt; &lt;i&gt;By Steef-Jan Wiggers&lt;/i&gt;</description>
      <category>Cloud</category>
      <category>Google Cloud</category>
      <category>AI Architecture</category>
      <category>Code Generation</category>
      <category>Google Cloud Platform</category>
      <category>Development</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Sun, 19 Jul 2026 10:16:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/alphaevolve-generally-available/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering</guid>
      <dc:creator>Steef-Jan Wiggers</dc:creator>
      <dc:date>2026-07-19T10:16:00Z</dc:date>
      <dc:identifier>/news/2026/07/alphaevolve-generally-available/en</dc:identifier>
    </item>
    <item>
      <title>Pinecone Introduces Nexus Engine for Compiling Business Context into Structured Data for AI Agents</title>
      <link>https://www.infoq.com/news/2026/07/pinecon-nexus-knowledge-engine/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering</link>
      <description>&lt;img src="https://www.infoq.com/styles/static/images/logo/logo_bigger.jpg"/&gt;&lt;p&gt;Now generally available, Pinecone Nexus is a "knowledge engine" for AI agents that transforms enterprise data into a structured layer agents can query directly. It enables teams to ingest and curate business context once for all, making it reusable across agents and reducing token costs while improving accuracy.&lt;/p&gt; &lt;i&gt;By Sergio De Simone&lt;/i&gt;</description>
      <category>Enterprise</category>
      <category>Retrieval-Augmented Generation</category>
      <category>Large language models</category>
      <category>Agents</category>
      <category>vector databases</category>
      <category>Development</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Sat, 18 Jul 2026 14:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/pinecon-nexus-knowledge-engine/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering</guid>
      <dc:creator>Sergio De Simone</dc:creator>
      <dc:date>2026-07-18T14:00:00Z</dc:date>
      <dc:identifier>/news/2026/07/pinecon-nexus-knowledge-engine/en</dc:identifier>
    </item>
    <item>
      <title>Version Controlled SQL Database Dolt Releases 2.0 with Automatic Storage Cleanup and Compression</title>
      <link>https://www.infoq.com/news/2026/07/dolt-version-control/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/07/dolt-version-control/en/headerimage/generatedHeaderImage-1783067948773.jpg"/&gt;&lt;p&gt;DoltHub has recently released Dolt 2.0, a major update to the open source version-controlled SQL database. The latest major version adds automatic storage optimization, including garbage collection and compression, along with improved support for large and vector data types.&lt;/p&gt; &lt;i&gt;By Renato Losio&lt;/i&gt;</description>
      <category>Database</category>
      <category>Data Lake</category>
      <category>MySQL</category>
      <category>Git</category>
      <category>Version Control</category>
      <category>vector databases</category>
      <category>Development</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Sat, 18 Jul 2026 07:28:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/dolt-version-control/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering</guid>
      <dc:creator>Renato Losio</dc:creator>
      <dc:date>2026-07-18T07:28:00Z</dc:date>
      <dc:identifier>/news/2026/07/dolt-version-control/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: From OTEL to SLMs: Distilling Frontier Model Behaviour from Production Telemetry</title>
      <link>https://www.infoq.com/presentations/otel-slm-ai/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering</link>
      <description>&lt;img src="https://res.infoq.com/presentations/otel-slm-ai/en/mediumimage/benomahony-medium-1783500827260.jpeg"/&gt;&lt;p&gt;Ben O'Mahony discusses building custom AI-powered Language Server Protocols (LSPs) that go beyond standard rule-based checkers. He explains how to instrument AI agents natively with OpenTelemetry to track concrete user actions (accepting, dismissing, or regenerating code fixes) as implicit labels, creating a continuous data flywheel to distill frontier capabilities into cheaper, local SLMs.&lt;/p&gt; &lt;i&gt;By Ben O'Mahony&lt;/i&gt;</description>
      <category>Telemetry</category>
      <category>Artificial Intelligence</category>
      <category>QCon AI 2025</category>
      <category>Transcripts</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>presentation</category>
      <pubDate>Fri, 17 Jul 2026 13:17:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/otel-slm-ai/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering</guid>
      <dc:creator>Ben O'Mahony</dc:creator>
      <dc:date>2026-07-17T13:17:00Z</dc:date>
      <dc:identifier>/presentations/otel-slm-ai/en</dc:identifier>
    </item>
    <item>
      <title>Cloud Native Infrastructure Emerges as the Foundation for Trustworthy Agentic AI</title>
      <link>https://www.infoq.com/news/2026/07/cncf-trustworthy-agentic-ai/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/07/cncf-trustworthy-agentic-ai/en/headerimage/generatedHeaderImage-1783856714710.jpg"/&gt;&lt;p&gt;A new technical analysis published by the Cloud Native Computing Foundation (CNCF) argues that the future of agentic AI will be built not on entirely new infrastructure, but on the mature cloud-native ecosystem that already powers modern distributed applications&lt;/p&gt; &lt;i&gt;By Craig Risi&lt;/i&gt;</description>
      <category>Cloud Native Computing Foundation</category>
      <category>OpenTelemetry</category>
      <category>Agents</category>
      <category>Kubernetes</category>
      <category>GitOps</category>
      <category>Apache Kafka</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Fri, 17 Jul 2026 12:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/cncf-trustworthy-agentic-ai/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering</guid>
      <dc:creator>Craig Risi</dc:creator>
      <dc:date>2026-07-17T12:00:00Z</dc:date>
      <dc:identifier>/news/2026/07/cncf-trustworthy-agentic-ai/en</dc:identifier>
    </item>
    <item>
      <title>QCon AI Boston: Production AI Moves beyond Prompts to Platforms, Harnesses, and Evals</title>
      <link>https://www.infoq.com/news/2026/07/production-ai-platforms-evals/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/07/production-ai-platforms-evals/en/headerimage/production-ai-platforms-evals-header-1784186327712.jpg"/&gt;&lt;p&gt;QCon AI Boston 2026 focused on the operational challenges of deploying AI agents, emphasizing the need for robust production infrastructure. Key themes included improving context management, ensuring security through a "harness" around agents, and adopting a comprehensive engineering model for AI.&lt;/p&gt; &lt;i&gt;By Tatiana Fesenko&lt;/i&gt;</description>
      <category>Infrastructure</category>
      <category>Model</category>
      <category>Agents</category>
      <category>QCon AI Boston 2026</category>
      <category>Productivity</category>
      <category>QCon Software Development Conference</category>
      <category>Platforms</category>
      <category>Security</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Fri, 17 Jul 2026 09:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/production-ai-platforms-evals/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering</guid>
      <dc:creator>Tatiana Fesenko</dc:creator>
      <dc:date>2026-07-17T09:00:00Z</dc:date>
      <dc:identifier>/news/2026/07/production-ai-platforms-evals/en</dc:identifier>
    </item>
    <item>
      <title>AI Agents with Cloud Credentials Are Outrunning Billing Guardrails Built for Human-Speed Mistakes</title>
      <link>https://www.infoq.com/news/2026/07/ai-agents-billing-guardrails/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/07/ai-agents-billing-guardrails/en/headerimage/generatedHeaderImage-1783852122330.jpg"/&gt;&lt;p&gt;A three-person agency received a $14,000 AWS bill in one day after attackers extracted static access keys and burned Claude invocations on Bedrock. Combined with May's DN42 incident, where an autonomous agent provisioned $6,531 of oversized infrastructure in 24 hours, practitioners warn that cloud billing lags roughly a day behind agent-speed spend.&lt;/p&gt; &lt;i&gt;By Steef-Jan Wiggers&lt;/i&gt;</description>
      <category>Cloud</category>
      <category>Cloud Architecture</category>
      <category>Cost Optimization</category>
      <category>AI Architecture</category>
      <category>Development</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Thu, 16 Jul 2026 10:17:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/ai-agents-billing-guardrails/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering</guid>
      <dc:creator>Steef-Jan Wiggers</dc:creator>
      <dc:date>2026-07-16T10:17:00Z</dc:date>
      <dc:identifier>/news/2026/07/ai-agents-billing-guardrails/en</dc:identifier>
    </item>
    <item>
      <title>Stripe Benchmark Shows AI Agents Build Integrations but Struggle with Validation</title>
      <link>https://www.infoq.com/news/2026/07/stripe-ai-agents-benchmark/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/07/stripe-ai-agents-benchmark/en/headerimage/generatedHeaderImage-1783301844753.jpg"/&gt;&lt;p&gt;Stripe introduces a benchmark suite to evaluate whether AI agents can build real-world Stripe integrations across backend, frontend, and browser-based checkout workflows. The study examines end-to-end software engineering capability, focusing on execution, testing, and validation gaps in agentic systems under production-like constraints.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Integration</category>
      <category>Claude</category>
      <category>Web Browser</category>
      <category>AI Coding</category>
      <category>ChatGPT</category>
      <category>Stripe</category>
      <category>Validation</category>
      <category>Benchmark</category>
      <category>Agents</category>
      <category>AI Development</category>
      <category>Software Engineering</category>
      <category>payment</category>
      <category>AIOps</category>
      <category>Observability</category>
      <category>Development</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Wed, 15 Jul 2026 14:25:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/stripe-ai-agents-benchmark/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering</guid>
      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-07-15T14:25:00Z</dc:date>
      <dc:identifier>/news/2026/07/stripe-ai-agents-benchmark/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Postgres for Production Agents: Your Relational Foundation for Enterprise AI</title>
      <link>https://www.infoq.com/presentations/postgres-ai-agents/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering</link>
      <description>&lt;img src="https://res.infoq.com/presentations/postgres-ai-agents/en/mediumimage/gwen-shapira-medium-1783500671134.jpeg"/&gt;&lt;p&gt;Gwen Shapira shares how teams are scaling AI features using PostgreSQL for mission-critical apps. She explains how to leverage Postgres's multi-modal capabilities - including JSONB parsing and high-recall HNSW vector indexing - to deliver deterministic and semantic context to LLMs. She also discusses vector quantization to speed up queries by 4x and strategies for managing agentic memory.&lt;/p&gt; &lt;i&gt;By Gwen Shapira&lt;/i&gt;</description>
      <category>Postgres</category>
      <category>Agents</category>
      <category>Artificial Intelligence</category>
      <category>QCon AI 2025</category>
      <category>Transcripts</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>presentation</category>
      <pubDate>Wed, 15 Jul 2026 12:57:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/postgres-ai-agents/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering</guid>
      <dc:creator>Gwen Shapira</dc:creator>
      <dc:date>2026-07-15T12:57:00Z</dc:date>
      <dc:identifier>/presentations/postgres-ai-agents/en</dc:identifier>
    </item>
    <item>
      <title>AWS Ships Claude Apps Gateway as Self-Hosted Control Plane for Claude Code and Claude Desktop</title>
      <link>https://www.infoq.com/news/2026/07/claude-apps-gateway-aws/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering</link>
      <description>&lt;img src="https://www.infoq.com/styles/static/images/logo/logo_bigger.jpg"/&gt;&lt;p&gt;AWS and Anthropic have released the Claude apps gateway for AWS, a self-hosted control plane that centralizes identity, policy, telemetry, routing, and spend caps for Claude Code and Claude Desktop. The gateway runs as a single stateless container and routes inference to Amazon Bedrock or Claude Platform on AWS.&lt;/p&gt; &lt;i&gt;By Steef-Jan Wiggers&lt;/i&gt;</description>
      <category>AWS</category>
      <category>Access Control</category>
      <category>Claude</category>
      <category>Cloud</category>
      <category>Anthropic</category>
      <category>Cloud Architecture</category>
      <category>AI Architecture</category>
      <category>Amazon Web Services</category>
      <category>Development</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Wed, 15 Jul 2026 11:04:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/claude-apps-gateway-aws/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering</guid>
      <dc:creator>Steef-Jan Wiggers</dc:creator>
      <dc:date>2026-07-15T11:04:00Z</dc:date>
      <dc:identifier>/news/2026/07/claude-apps-gateway-aws/en</dc:identifier>
    </item>
    <item>
      <title>Google Cloud Workbench Notebooks Extension Connects VS Code to Google Cloud's Jupyter Notebooks</title>
      <link>https://www.infoq.com/news/2026/07/cloud-workbench-vscode-extension/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering</link>
      <description>&lt;img src="https://www.infoq.com/styles/static/images/logo/logo_bigger.jpg"/&gt;&lt;p&gt;The Google Cloud Workbench Notebooks extension for VS Code is a new tool that enables developers to connect their local IDE directly to managed Jupyter notebook environments on Google Cloud.&lt;/p&gt; &lt;i&gt;By Sergio De Simone&lt;/i&gt;</description>
      <category>Jupyter Notebooks</category>
      <category>Cloud</category>
      <category>Large language models</category>
      <category>Google Cloud</category>
      <category>Google</category>
      <category>Machine Learning</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Tue, 14 Jul 2026 22:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/cloud-workbench-vscode-extension/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering</guid>
      <dc:creator>Sergio De Simone</dc:creator>
      <dc:date>2026-07-14T22:00:00Z</dc:date>
      <dc:identifier>/news/2026/07/cloud-workbench-vscode-extension/en</dc:identifier>
    </item>
    <item>
      <title>Google and Industry Partners Announce Agentic Resource Discovery Specification for AI Agents</title>
      <link>https://www.infoq.com/news/2026/07/agentic-resource-discovery-spec/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/07/agentic-resource-discovery-spec/en/headerimage/generatedHeaderImage-1783309687458.jpg"/&gt;&lt;p&gt;Google and industry partners announced Agentic Resource Discovery (ARD) Specification, an open standard for publishing, discovering, and verifying AI tools, APIs, and agents. ARD introduces a discovery layer built on catalogs and registries, enabling dynamic capability discovery while leveraging existing protocols such as MCP and OpenAPI for execution and emphasizing trust and interoperability.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Specification</category>
      <category>Distributed Systems</category>
      <category>AI Coding</category>
      <category>Agents</category>
      <category>github</category>
      <category>Agent2Agent</category>
      <category>AI Security</category>
      <category>Cisco</category>
      <category>Salesforce.com</category>
      <category>Google</category>
      <category>GoDaddy</category>
      <category>AI Architecture</category>
      <category>Service Discovery</category>
      <category>Model Context Protocol (MCP)</category>
      <category>Microsoft</category>
      <category>AI Interpretability</category>
      <category>Platform Engineering</category>
      <category>Development</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Tue, 14 Jul 2026 13:40:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/agentic-resource-discovery-spec/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering</guid>
      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-07-14T13:40:00Z</dc:date>
      <dc:identifier>/news/2026/07/agentic-resource-discovery-spec/en</dc:identifier>
    </item>
    <item>
      <title>Meta's Noninvasive Brain–Computer Interface Brain2Qwerty Achieves 61% Accuracy</title>
      <link>https://www.infoq.com/news/2026/07/meta-brain-interface/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/07/meta-brain-interface/en/headerimage/generatedHeaderImage-1783863685064.jpg"/&gt;&lt;p&gt;Meta recently open-sourced Brain2Qwerty v2, a noninvasive Brain–Computer Interface (BCI) that can decode sentences from thoughts using electroencephalography (EEG) or magnetoencephalography (MEG) signals from the brain. In evaluations, the system achieved a word accuracy rate 61% on average, compared to 8% for other non-invasive methods.&lt;/p&gt; &lt;i&gt;By Anthony Alford&lt;/i&gt;</description>
      <category>Neural Networks</category>
      <category>Deep Learning</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Tue, 14 Jul 2026 13:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/meta-brain-interface/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering</guid>
      <dc:creator>Anthony Alford</dc:creator>
      <dc:date>2026-07-14T13:00:00Z</dc:date>
      <dc:identifier>/news/2026/07/meta-brain-interface/en</dc:identifier>
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