AI & ML
Neural nets, LLMs, recommendations, image generation, and the machine logic underneath.
How Prompt Engineering Works
Prompt engineering is the new literacy of the AI age. It's not about talking to machines - it's about thinking clearly enough to get them to think for you.
How AI Image Generation Works
You type a few words and a photorealistic image appears in seconds. The math behind it is stranger than the result.
How Fine-Tuning Works
GPT-4 didn't come out of the box knowing how to write code or answer medical questions. Fine-tuning is how we teach base models specialized skills, and it's the difference between a general-purpose tool and an expert.
How Self-Driving Cars Work
A self-driving car processes more data every second than a human brain handles in a day. And it still struggles with a plastic bag.
How Vector Databases Work
When you search for 'that song about summer' and Spotify plays the right one, a vector database made it possible. Here's how these databases store meaning instead of just data.
How Neural Networks Work
Neural networks learn by failing millions of times: they make a prediction, measure how wrong they were, adjust thousands of internal numbers slightly, and repeat until the errors become small enough to be useful.
How Recommendation Algorithms Work
Recommendation algorithms don't know what you'll like. They find people who behaved like you and surface what those people liked next, a surprisingly powerful trick that shapes what billions of people read, watch, and buy.
How Large Language Models Work
ChatGPT doesn't 'know' anything. It's a very sophisticated next-word predictor, and understanding that changes how you should use it.
How Spotify's Recommendation Algorithm Works
Spotify's algorithm does not just analyze songs. It analyzes your behavior and compares it with listeners who have similar patterns.