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AI Skills & How They Work
What AI systems can actually do, how they learn, and how to use them without fooling yourself or your users.
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10 주제 · 10 편의 가이드
- What AI Skills Actually Are (and Are Not)
AI skills are not magic and not a product: they are specific capabilities, language understanding, pattern recognition, and genera…
- Prompt Engineering as a Science, Not a Trick
Prompt engineering is the practice of shaping model behavior through instructions, examples, and structure, and it is closer to ex…
- How Neural Networks Learn
Neural networks learn by adjusting billions of weights to reduce a loss function across training examples, using gradient descent …
- Fine-Tuning vs RAG: When to Use Which
Fine-tuning changes model weights to teach new behavior or style; RAG keeps weights frozen and injects relevant documents at query…
- AI-Assisted Development: Copilot and Friends
AI coding assistants autocomplete, explain, and refactor code inside your editor, and they change how fast you move more than how …
- Vector Embeddings Demystified
Embeddings turn text, images, or other data into lists of numbers so that similar items land close together in a high-dimensional …
- AI Literacy for IT Professionals
AI literacy for IT professionals means understanding what models can and cannot do, how to evaluate them, and how to integrate the…
- Human in the Loop: RLHF and Beyond
Human-in-the-loop systems use people to guide, correct, or approve AI behavior, and RLHF is the training technique that turns huma…
- AI Orchestration Frameworks
Orchestration frameworks chain models, tools, and data into multi-step workflows and agents. They save boilerplate and impose stru…
- Data Preprocessing for AI
Data preprocessing is the unglamorous work that determines model quality: cleaning, normalizing, chunking, and labeling the data b…