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#4 [Basics] The LLM Ecosystem Tools and Intelligent Application Development
🎙️ Episode Title: Inside the LLM Jungle: Tools, Techniques & the AI Frontier
📡 Show: Journey to the Center of the AI
What do vector databases, prompt engineering, and intelligent agents have in common? They’re all key players in the booming world of large language models (LLMs)! In this episode, we dive deep into the modern LLM ecosystem—breaking down the chaos, the clarity, and the clever tech behind today’s most powerful AI systems.
🚀 We’ll take you on a journey through:
🛠️ Model Development: From pre-training giants to fine-tuning your own models for niche tasks.
🧠RAG & Vector Databases: Why retrieval-augmented generation is redefining how LLMs access knowledge.
🤖 Agent Frameworks: Explore LangChain, Semantic Kernel & others powering autonomous decision-making bots.
🧪 Prompt Engineering: The science (and art) of crafting the perfect prompt—and how to evaluate it.
📦 Infrastructure & Deployment: From inference speed to multi-modal support, we decode what it takes to build production-ready LLM apps.
đź”® Future Trends: Open-source LLMs, cost vs. performance battles, hallucination issues, and the rise of fine-grained evaluation tools.
Whether you're an AI enthusiast, a developer navigating the noisy world of LLM tools, or someone wondering if your app idea can be powered by ChatGPT or Claude—this episode gives you the map to the ever-evolving terrain of intelligent applications.
đź’ˇ Expect insights, humor, and a little sci-fi flair as we journey to the center of the AI... and back.
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By Shanmuga Ganesh Kalasalingam🎙️ Episode Title: Inside the LLM Jungle: Tools, Techniques & the AI Frontier
📡 Show: Journey to the Center of the AI
What do vector databases, prompt engineering, and intelligent agents have in common? They’re all key players in the booming world of large language models (LLMs)! In this episode, we dive deep into the modern LLM ecosystem—breaking down the chaos, the clarity, and the clever tech behind today’s most powerful AI systems.
🚀 We’ll take you on a journey through:
🛠️ Model Development: From pre-training giants to fine-tuning your own models for niche tasks.
🧠RAG & Vector Databases: Why retrieval-augmented generation is redefining how LLMs access knowledge.
🤖 Agent Frameworks: Explore LangChain, Semantic Kernel & others powering autonomous decision-making bots.
🧪 Prompt Engineering: The science (and art) of crafting the perfect prompt—and how to evaluate it.
📦 Infrastructure & Deployment: From inference speed to multi-modal support, we decode what it takes to build production-ready LLM apps.
đź”® Future Trends: Open-source LLMs, cost vs. performance battles, hallucination issues, and the rise of fine-grained evaluation tools.
Whether you're an AI enthusiast, a developer navigating the noisy world of LLM tools, or someone wondering if your app idea can be powered by ChatGPT or Claude—this episode gives you the map to the ever-evolving terrain of intelligent applications.
đź’ˇ Expect insights, humor, and a little sci-fi flair as we journey to the center of the AI... and back.