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#181 Max: The AI Engineer's Core Vocabulary – 10 Essential Concepts Explained (Part 1)
Tired of feeling lost when AI engineers start talking about "attention mechanisms" and "RAG"? 🤔 This is your guide to the 10 essential concepts that form the bedrock of modern AI engineering.
We’ll talk about:
- A complete, beginner-friendly guide to the 10 most critical AI concepts you need to know (Part 1).
- A deep dive into the fundamentals, from Large Language Models (LLMs) and Tokenization to Vectorization and Attention Mechanisms.
- A clear explanation of the building blocks of AI applications, including Transformers, Self-Supervised Learning, and Fine-tuning.
- How to give your AI a real memory: a simple breakdown of Retrieval Augmented Generation (RAG) and the Vector Databases that power it.
- Plus, a look at Few-shot Prompting and how all these foundational concepts fit together.
Keywords: AI Engineering, AI Concepts, Large Language Model (LLM), Tokenization, Vectorization, Attention Mechanism, Self-Supervised Learning, Transformer, Fine-tuning, Few-shot Prompting, Retrieval Augmented Generation (RAG), Vector Database
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Published on 1 day, 20 hours ago