Fundamentals
13 topics in AI & Machine Learning
AI Hallucinations
ChatGPT sometimes makes up facts with total confidence. Here's the weird reason why — and why it's not as simple as 'the AI lied.'
Artificial Intelligence
What is AI really? Think of it as a dog that learned tricks — impressive, but it doesn't know why it's doing them.
Bias-Variance Tradeoff
The fundamental tension in machine learning between being wrong in the same way vs. being wrong in different ways — and why the simplest model isn't always best.
Deep Learning
Why your phone can spot your face in a messy photo album — and why that trick comes from practice, not magic.
Embeddings
How do computers know that 'dog' and 'puppy' mean almost the same thing? They don't read definitions — they turn words into secret map coordinates, and nearby coordinates mean nearby meanings.
Generative AI
Generative AI doesn't look things up — it makes things up. Here's why that's either impressive or terrifying, depending on what you ask it to make.
Gradient Descent
How AI finds the right answer the same way a blindfolded hiker finds their way downhill — by feeling which direction the ground slopes.
Large Language Models
ChatGPT doesn't 'know' anything — it learned to complete sentences so well it looks like thinking. Here's the weird trick that makes it work.
Machine Learning
Machine learning isn't magic — it's a piano student who practices millions of songs until the music just flows. Here's what that actually means.
Model Evaluation
How we know if an AI model is actually good — the metrics and testing methods that separate genuinely useful AI from AI that only looks impressive.
Neural Networks
Your brain is made of billions of tiny switches that fire together to recognize your mom's face. Neural networks steal that same trick — and use it to beat you at chess.
Tokenization — Explain It Like I'm 5
Why does ChatGPT charge by 'tokens' and not words? The weird way AI reads text — and why it matters more than you think.
Transformer Architecture
Every AI you've talked to in the last 5 years runs on the same weird trick — paying 'attention' to words. Here's why that changed everything.