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Byte-Pair Encoding Explained: Why Tokenization Isn’t Just Splitting on Spaces (Ep.01.00)
Every episode of Module 00 quietly relied on .split() — text broken into whole words at whitespace, no questions asked. It was a deliberate simplification, flagged twice and never resolved.…
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Is Your AI Agent Actually Intelligent, or Just a Very Good Parrot?
Every AI agent demo looks intelligent. That’s the problem. A demo is, almost by definition, a curated set of inputs the builder already knows the system handles well. The interesting…
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What Is Intelligence, Really? (From Zero to Agents, Episode 00.01)
Last episode ended with a question. Here’s a definition worth pressure-testing (a very common first instinct — someone may say): “A system is intelligent if it can analyze requirements and…
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From Zero to Agents: A Foundational AI/ML Course Built From First Principles (Episode 00.00)
Most “learn AI” content today teaches you to assemble — wire an LLM API into a framework, call it an agent, ship it. That’s a real and useful skill. It…
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How to Build an AI Chatbot App with Ollama Llama: Complete Tutorial for Beginners
Building an AI chatbot app with Ollama Llama allows developers to create powerful, privacy-focused applications that run entirely on localhost without expensive API costs. This comprehensive tutorial will guide you…
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LLaMA Model Fine-Tuning: How We Built a Custom AI Coaching Assistant and Reduced Costs by 85%
Learn how LLaMA model fine-tuning helped us build UncleMatt.ai, a custom AI coaching assistant, while reducing costs by 85% compared to GPT-4 solutions.
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How We Built UncleMatt.ai – A GPT-4 Powered Coaching Tool with RAG, LangChain & Pinecone
UncleMatt.ai is a custom GPT-4 powered AI coach designed using LangChain’s RAG architecture and integrated with Kajabi and WordPress. Learn how we built it step-by-step in this case study.
