Training
Training is the process of showing a model vast amounts of data and repeatedly adjusting its internal numbers until its predictions improve. It's expensive, slow, and happens once — when training ends, the model is frozen and no longer learns from new conversations. What you interact with in any AI product is the result of training that already happened, sometimes months earlier.
Videos explaining this concept
E005Notes on AI
What Is a Model, Really?
A model is a learned structure that predicts what comes next. The training process — analyzing massive amounts of text data — doesn't stay "alive" inside the model. It collapses and crystallizes in...
E006Notes on AI
Training vs Using a Model
Training and Inference are the two distinct phases of an AI model's lifecycle.
E010Notes on AI
The 5-Sentence Mental Model of GenAI
This episode provides a checkpoint after the foundational episodes, compressing the key concepts into five memorable sentences that serve as a mental compass for AI.
E017Notes on AI
"Forgetting" vs "Never Knew"
When AI gives a wrong answer, the instinct is to blame intelligence or memory. But if we narrow down to missing knowledge, there are only three structured causes: a training gap (the information wa...
E019Notes on AI
Why AI Sounds Confident
LLMs are optimized to produce fluent, grammatically correct, structurally coherent language. This is what they were trained to do. But fluency and accuracy are two different things. The model does ...