Getting Started with AI
Start with a small task whose result you can check yourself.
Choose a task, explain it clearly and check the answer
Recommended reading
How to Choose Your First AI Task: Start Small, Low-Risk, and Reviewable
Use four criteria to choose a small task whose result you can review.
AI Concepts
- AI ConceptsLLMs Are Not Knowledge Bases: Why Next-Token Prediction Can Produce Confidently Wrong AnswersUnderstand why fluent LLM output is not factual verification, and when AI applications need external data, retrieval, tools, validation, permissions, or human review.
- AI ConceptsTransformer Without the Math: What Attention and Embeddings Actually DoUnderstand Attention, Embeddings, and KV Cache without deriving matrices. Connect context, semantic search, RAG, and inference cost for AI application engineering.
- AI ConceptsWhat Exactly Is an AI Agent? From Chatbots to Closed-Loop Decision SystemsLearn why an AI Agent is more than an LLM with tools, and how Goal, State, Observation, Decision, Action, and Feedback form a closed-loop system.
- AI ConceptsWhat Is an AI Agent? Chat, Work, and Agentic Tasks ExplainedCompare chat, longer-form AI work, and agents by steps, tool use, external actions, and human control so you can choose the safer entry point.
- AI ConceptsHow Does Generative AI Produce Answers—and Why Can It Be Confidently Wrong?Learn why generative AI can produce fluent but incorrect answers, then use a simple boundary map to separate drafts, facts, and decisions that need verification.
- AI ConceptsHow AI Semiconductors Power Model TrainingAI training relies on matrix computation and specialized chips. Compare the roles of GPUs, TPUs, and ASICs, and how training needs differ from inference.