Running LLMs Locally — What You Really Need to Know

🎥 Running LLMs Locally — What You Really Need to Know Presented by Dr. Freeman Jackson Fourth Industrial Systems | https://4th.is Large Language Models (LLMs) might seem like magic — but behind the curtain, they’re built on math, massive datasets, and precise engineering. In this video, Dr. Freeman Jackson breaks down the truth about how LLMs really work — what you need to run them locally, and how to separate hype from reality. You’ll learn: ⚙️ What files and configurations an LLM truly needs 🧠 The difference between open weights and closed models 🚀 How quantization (int4, int8) makes massive models run on laptops 💡 When to choose local vs. cloud inference 🔒 How to keep your AI systems safe from jailbreaks, prompt injection, and data poisoning 🔁 Why retrieval-augmented generation (RAG) and tool use are critical for accuracy Fair Use Notice: This presentation is an educational and transformative work under 17 U.S.C. §107. Short excerpts and demonstrations are included solely for critique, commentary, and instruction — not for commercial redistribution. 🧠 Highlights The “two files” myth explained — why you need tokenizer.json, config.json, and model weights Open vs. closed models: LLaMA 2, ChatGPT, and real licensing trade-offs Quantization tricks to fit LLMs into 8GB–30GB Local runtime tools: llama.cpp, vLLM, and Ollama RAG for grounding and hallucination control LLMs as planners: using external tools safely and effectively The seven-day LLM challenge: from setup to red-teaming 🔗 Resources & Links 🌐 Fourth Industrial Systems 📚 Learn.4th.is — Courses on AI, Agentic Workflows & Compliance 🗞️ News.4th.is — Latest on Generative AI, Law, and Governance 💬 Connect with Dr. Freeman Jackson 📧 [email protected] 📱 WhatsApp/Text: +1 (754) 224-6952 💼 LinkedIn: Dr. Freeman Jackson, D.Sc., JM, PMP, CISSP, CISA 🧭 Hashtags #AI #LLM #AgenticAI #OpenSourceAI #EthicalAI #MachineLearning #DrFreemanJackson #FourthIndustrialSystems #AIResearch #GenerativeAI #LocalLLMs #AIEngineering