Tajikistan launches first AI model in national language - Muslim Network TV
<a href="https://news.google.com/rss/articles/CBMijgFBVV95cUxPcXRsYTl0VzVGOFgya0Q5S2tjcEU3b1NEQzItYmt4ZmZBS1hlV3NzeERqUlBVbHE4WHNZazluUk5zX0VpQ1N3QjJhMUlPblk3UGFCMUhob0R2SGVBYmdRUnJ5VFRvZFU5VjE0SDVKYlpZQ0taQzREWWd6S3FOWms2RngxVnUwLXJQd0ZGNGVR?oc=5" target="_blank">Tajikistan launches first AI model in national language</a> <font color="#6f6f6f">Muslim Network TV</font>
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Part 1 - Why I Picked LangChain4j Over Spring AI
<p>Distributed sagas are hard enough without AI. You're already dealing with compensating transactions, Kafka topics, state machines, and rollback chains across 5 microservices. Adding an AI layer on top sounds like a recipe for more complexity.<br> But that's exactly what this series covers: where AI actually helps in a saga-based architecture, and how to wire it up without making the system more fragile. The AI layer auto-diagnoses failures, dynamically reorders saga steps based on real failure data, and lets developers query the entire system in natural language.<br> This first post covers the foundation: why I went with LangChain4j as the Java SDK, the core concepts you need, and how to get a working agent running.</p> <h2> Why LangChain4j </h2> <p>If you're building AI-powered applica
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<p>Serving Large Language Models (LLMs) in production is notoriously difficult and expensive. While researchers focus heavily on making models smarter or training them faster, the operational bottleneck for deploying these models at scale almost always comes down to <strong>inference throughput</strong> and <strong>memory management</strong>.</p> <p>Enter <strong>vLLM</strong>, an open-source library that took the AI infrastructure world by storm. By tackling the root causes of GPU memory waste, vLLM achieves 2x to 4x higher throughput compared to naive HuggingFace Transformers implementations.</p> <p>Let's dive deep into the architectural breakthroughs that make vLLM the gold standard for high-throughput LLM serving: <strong>PagedAttention</strong> and <strong>Continuous Batching</strong>
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The United States, China, and AI Competition in Africa: Lessons for the Global South - gjia.georgetown.edu
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Text-To-Speech Voices & Machine Learning Robots Mean ARC Raiders Has An AI Problem (Or Does It?) - ScreenRant
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