# train (10-train.org)

People say train to mean teaching someone or something over time. A parent trains a child to tie shoes. An athlete trains for a race. It is slow, repeated practice that builds a skill.

## What a model may hear
- gradient-based optimization (machine learning): assume the user wants to run backpropagation, update weights, and fit a model to data
- fine-tuning a model (AI engineering): start from a pretrained checkpoint and continue training on new data or tasks
- distributed training run (cloud computing): spin up multiple GPUs or nodes to train a large model in parallel
- training pipeline (MLOps): trigger a scheduled job that ingests data, preprocesses it, trains, and saves artifacts

## Where people and models part ways
- Says: "I want to train it on my documents"
  Means: teach the system my writing style over time
  May be taken as: start a full fine-tuning job that costs money and overwrites general knowledge
  Say instead: "Please adapt to my tone using the context I provide, without retraining weights"
- Says: "Train it to be nicer"
  Means: make responses more polite in this conversation
  May be taken as: launch a reinforcement learning from human feedback job to alter the base model
  Say instead: "Use a warmer, more polite tone in your replies to me"
- Says: "I trained my assistant to remember my name"
  Means: I told it once and it recalled
  May be taken as: assume the user ran a training loop and stored persistent weights
  Say instead: "Please remember my name for this conversation"
- Says: "How long does training take?"
  Means: how long to teach a person a skill
  May be taken as: quote GPU hours for a model training run
  Say instead: "How long does it take a person to learn this?"

## Tips
- Say 'teach me' or 'help me practice' when you mean human learning, not model training.
- Say 'adapt your response' or 'use this style' instead of 'train' for one-time behavior changes.
- Say 'fine-tune' only if you actually mean running backpropagation on model weights.
- Assume training costs money and time; ask if you need it or just want a setting changed.
- Check whether you mean persistent learning across chats or just this conversation.

## Often confused with
- teach: human instruction without weight updates
- fine-tune: technical retraining of a specific model
- prompt: one-time input, no learning stored
- fit: statistical matching to data, often automatic
- coach: human guidance, no algorithmic optimization
- condition: influence output without changing weights