Explainers
Transformers Explained: The Fast Librarian Analogy
Think of a transformer as a very fast librarian who somehow reads every book at once and guesses which sentence you'll want to hear next.
Fine-Tuning Explained: Teaching Models New Tricks
Fine-tuning is like giving a model a specialized course after it's already learned the basics. Here's how it works and why it matters.
Reinforcement Learning Explained: Training AI Like a Dog
Reinforcement learning is like training a dog: reward good behavior, ignore bad behavior, repeat until the model learns the trick.
Neural Networks Explained: The Brain Analogy That Actually Works
Neural networks are inspired by brains, but they're not brains. Here's how they actually work, without the biological confusion.
AI Benchmarks Explained: What Those Numbers Actually Mean
Benchmarks measure AI performance, but they don't tell the whole story. Here's how to read them without getting misled.
Prompt Engineering Explained: Talking to AI the Right Way
Prompt engineering is the art of getting AI to do what you want. Here's how to do it without sounding like you're talking to a robot.
Choosing an AI Model: A Practical Guide
With so many models available, choosing the right one is confusing. Here's how to pick based on what you actually need.