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    <lastBuildDate>Sat, 20 Jun 2026 18:00:45 GMT</lastBuildDate>
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      <title>Running GPUStack with NVIDIA MIG: A Deep Dive into Multi-Instance GPU Orchestration</title>
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      <description>Multi-Instance GPU (MIG) technology promises to maximize GPU utilization by partitioning a single GPU into isolated instances. But getting MIG to work with container orchestration tools like GPUStack requires navigating a maze of CDI configuration, device enumeration, and runtime patches. This technical deep-dive shares our battle-tested solutions.</description>
      <pubDate>Sun, 01 Feb 2026 00:00:00 GMT</pubDate>
      <category>Infrastructure</category>
      <dc:creator>Frederico Vicente</dc:creator>
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      <title>Small AI Models in Production</title>
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      <description>Discover how small, highly capable AI models are enabling faster, more cost-effective, and more controllable AI systems in real production environments. Learn why efficient models matter and when lighter architectures outperform larger ones.</description>
      <pubDate>Thu, 29 Jan 2026 00:00:00 GMT</pubDate>
      <category>Artificial Intelligence</category>
      <dc:creator>Frederico Vicente</dc:creator>
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      <title>Unlock AI for your ERP</title>
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      <description>Process invoices in seconds with Vision AI. A step-by-step implementation guide to integrate AI into your ERP system and unlock new efficiencies.</description>
      <pubDate>Sat, 03 Jan 2026 00:00:00 GMT</pubDate>
      <category>Artificial Intelligence</category>
      <dc:creator>dypsis.ai Team</dc:creator>
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      <title>Churn Prediction: From Logistic Regression to Foundation Models</title>
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      <description>Customer churn costs businesses billions annually. This technical deep-dive compares statistical methods, gradient boosting, and cutting-edge transformer models like TimesFM 2.5 and Chronos 2 for churn prediction - with benchmarks, architecture diagrams, and implementation insights.</description>
      <pubDate>Tue, 23 Dec 2025 00:00:00 GMT</pubDate>
      <category>Machine Learning</category>
      <dc:creator>Frederico Vicente</dc:creator>
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      <title>Building High-Value AI Systems That Deliver Real ROI</title>
      <link>https://dev.dypsis.ai/insights/building-high-value-ai-systems-ebook</link>
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      <description>A comprehensive guide to implementing AI systems that generate measurable business value. Learn practical strategies for building, deploying, and scaling AI solutions that deliver real return on investment.</description>
      <pubDate>Mon, 15 Dec 2025 00:00:00 GMT</pubDate>
      <category>Artificial Intelligence</category>
      <dc:creator>dypsis.ai Team</dc:creator>
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      <title>The Future of Development with AI Coding Agents</title>
      <link>https://dev.dypsis.ai/insights/future-of-development-ai-coding-agents-webinar</link>
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      <description>Join Frederico Vicente for an exclusive webinar exploring how AI coding agents are transforming software development. Discover cutting-edge tools, workflows, and the future of intelligent development.</description>
      <pubDate>Thu, 27 Nov 2025 00:00:00 GMT</pubDate>
      <category>Software Engineering</category>
      <dc:creator>Frederico Vicente</dc:creator>
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      <title>Model Context Protocol: Standardizing Context and Tool Integration for Agentic AI</title>
      <link>https://dev.dypsis.ai/insights/model-context-protocol-mcp</link>
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      <description>As LLMs evolve from stateless prompt responders to stateful, tool-using agents, fragile hand-wired orchestration is breaking down. MCP provides a vendor-neutral protocol for connecting models with structured context, tools, and external systems at runtime.</description>
      <pubDate>Sat, 15 Nov 2025 00:00:00 GMT</pubDate>
      <category>Artificial Intelligence</category>
      <dc:creator>Frederico Vicente</dc:creator>
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      <title>Enabling Private LLM Execution: Trusted Execution Environments and Encrypted Containers</title>
      <link>https://dev.dypsis.ai/insights/private-llm-execution-tees-encrypted-containers</link>
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      <description>Running LLM inference and fine-tuning on private datasets requires bridging theoretical cryptography with practical high-throughput systems. Learn how TEEs and encrypted containers create compliance-ready, hardware-isolated execution environments for confidential AI workloads.</description>
      <pubDate>Sat, 15 Nov 2025 00:00:00 GMT</pubDate>
      <category>Infrastructure</category>
      <dc:creator>Frederico Vicente</dc:creator>
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      <title>Rethinking AI Coding Agents: From Prompt Completion to Structured Engineering</title>
      <link>https://dev.dypsis.ai/insights/ai-coding-agents-structured-engineering</link>
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      <description>The bottleneck in AI-assisted development isn</description>
      <pubDate>Sat, 15 Nov 2025 00:00:00 GMT</pubDate>
      <category>Software Engineering</category>
      <dc:creator>Frederico Vicente</dc:creator>
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      <title>Architecting AI Agent Systems: A Strategic Framework for Production Deployment</title>
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      <description>Choosing the right LLM framework is a strategic business decision that determines scalability, cost control, and system resilience. Learn how to navigate the trade-offs between speed, flexibility, and governance when building production-grade AI automation.</description>
      <pubDate>Sat, 15 Nov 2025 00:00:00 GMT</pubDate>
      <category>Artificial Intelligence</category>
      <dc:creator>Frederico Vicente</dc:creator>
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      <title>RAG vs Fine-Tuning: Why the Best AI Systems Combine Both</title>
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      <description>Should you choose Retrieval-Augmented Generation (RAG) or fine-tuning to optimize your LLM? The answer is not either-or. Learn how combining RAG with fine-tuning delivers accuracy, adaptability, and cost efficiency in real-world AI systems.</description>
      <pubDate>Tue, 23 Sep 2025 00:00:00 GMT</pubDate>
      <category>Generative AI</category>
      <dc:creator>Frederico Vicente</dc:creator>
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      <title>RAM vs VRAM in Mixture of Experts Models: The Hidden Bottleneck in Next-Gen LLMs</title>
      <link>https://dev.dypsis.ai/insights/moe-experts-ram</link>
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      <description>Explore how GPU VRAM and system RAM shape the performance of Mixture of Experts models like Qwen3-Next. Learn why memory hierarchy is the real bottleneck in modern LLM deployments and how to optimize infrastructure for speed and scalability.</description>
      <pubDate>Tue, 23 Sep 2025 00:00:00 GMT</pubDate>
      <category>Infrastructure</category>
      <dc:creator>Frederico Vicente</dc:creator>
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      <title>Data Labeling: The Overlooked Bottleneck in AI and Machine Learning</title>
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      <description>Model architectures often get the spotlight, but real-world performance in AI depends heavily on data labeling quality. Learn why annotation workflows, human-in-the-loop systems, and synthetic data strategies are critical for building robust ML models.</description>
      <pubDate>Tue, 23 Sep 2025 00:00:00 GMT</pubDate>
      <category>Data Annotation</category>
      <dc:creator>Frederico Vicente</dc:creator>
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      <title>Federated Learning: Privacy-First AI</title>
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      <description>Discover how Federated Learning is revolutionizing AI implementation...</description>
      <pubDate>Mon, 19 Feb 2024 00:00:00 GMT</pubDate>
      <category>Artificial Intelligence</category>
      <dc:creator>Frederico Vicente</dc:creator>
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