Backpropagation: Which Way Should Each Knob Turn?
Training nudges billions of weights at once. Roll a weight down a loss curve, trace blame backwards through a network, and race SGD against Adam.
A Field Guide to Today's AI Models
A walk through the major families of AI models — what they do, how they work, and what it takes to train them — for people who want intuition, not a textbook.
How to Write Good Prompts for Small Language Models
Learn best practices and techniques for writing effective prompts for small language models like Gemma and LLaMA, including evaluation methods and debugging strategies.
"Bully LLM into agreeing" — why it works and what's really going on
Large Language Models don't have opinions — they predict tokens. Discover why you can always steer them toward any answer you want, and what's really happening under the hood.
Your Domain in the Model Weights: Why Choosing the Right LLM Really Matters
Discover how training data shapes language models and why domain-specific knowledge compressed into model weights can dramatically improve reasoning in your field.
Few-Shot Approach: why it works and what it has in common with the way we think
Discover how few-shot prompting works in AI by giving models just a handful of examples - and why this mirrors exactly how humans learn through pattern recognition and context.