22 docs tagged with "ai-basics"

Learn what AGI and Superintelligence actually mean, why they don't exist yet, and how to spot hype. A honest, beginner-friendly guide for professionals.

Understand the difference between AI, Machine Learning, and Deep Learning. Learn how they nest, what each does, and which one fits your problem.

Learn how telling AI what NOT to do, setting word limits, and locking tone and format dramatically improve prompt results.

Learn what an AI context window is, why AI forgets between conversations, and how context size affects speed and cost. Practical tips to work around AI's memory limits.

Learn what embeddings are, how AI converts words into numbers that capture meaning, and why 'time off' finds 'vacation guidelines.' No math required.

Learn the three stages that turn raw AI into a helpful assistant: pre-training for knowledge, fine-tuning for focus, and RLHF for safety. Plain English, no math.

Understand how the Transformer architecture works — attention, multi-head attention, and why this 2017 breakthrough powers every AI tool you use today.

Learn what multi-modal AI is, how models like GPT-4o and Gemini process images, audio, and video alongside text, and where they still fail.

Learn what parameters and weights are, why model size matters, and why AI needs GPUs. A plain-English guide to understanding AI hardware and model architecture.

Learn when plain text prompting is enough, when to use the five-part structured formula, and how choosing the right approach saves time and improves results.

How to set the AI personality, save persistent preferences, and fine-tune creativity so every conversation starts on your terms.

Discover what the AI revolution means for your career. See how AI changes your workday, what it can do, and what it cannot do — explained for beginners.

Learn what tokens are, why AI reads chunks instead of words, and how tokenization affects your API costs and speed. Includes a hands-on tokenizer tool.

Learn the difference between AI training and inference, why training costs millions but inference is cheap, and why AI doesn't learn from your conversations.

Learn what vector databases are, how they search by meaning instead of keywords, and why they power AI search, RAG, and recommendations.

Understand what an API is using a simple restaurant analogy, why apps use them, and how they connect services you already know.

Learn what a Large Language Model is, how it differs from Google Search, and why it sometimes makes things up. A plain-English guide for professionals.

Learn what artificial intelligence is in simple words. Understand how AI differs from regular software and why it feels intelligent but isn't truly thinking.

Learn what generative AI is, how it differs from traditional AI, the five types of content it creates, and why hallucination is its biggest limitation.

Learn how MCP gives AI hands to use your tools — like a USB-C for AI. Discover what tools you can connect and why it matters for your daily work.

Learn what RAG is, how retrieval-augmented generation works in 3 steps, why it reduces AI hallucination, and when to use RAG vs fine-tuning.

Learn when to ask AI directly with no examples, and when to give two or three examples for better results.