Model Training & Adaptation
Self-training
AI using its own guesses about new examples as material for further learning.
Example
AI adds selected guesses about new examples to its teaching material.
Why people use it
It can expand the examples available for learning by reusing selected predictions.
What you'll hear
“Use the strongest guesses for another learning round.”
What this means for you
Use independent checks between rounds so mistakes are not repeatedly reinforced.
Can you control it?
Developer-only
The people building or running the AI choose this setup. An everyday user generally needs their help to change how this part works.
Common questions
- Can self-training reinforce existing mistakes?
- Yes. Incorrect predictions can become misleading training targets.
- Can repeated rounds reduce variety?
- Yes. Favoring familiar, easy-to-label cases can leave uncommon cases behind.
- Does self-training mean no people are involved?
- No. People still choose the information, method and checks around the process.