SESKStuff Everyone Should Know
SESK: Stuff Everyone Should Know · sesk.info/ai-inference-vs-training

In machine learning, what is inference?

Using a trained model to make predictions on new, unlabeled examples.

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  1. Adjusting the weights to reduce loss
  2. Collecting and labeling the training data
  3. Using a trained model to make predictions ✔

Why: Training is when the model learns its weights from data. Inference comes after: the finished model is applied to new examples to produce predictions.

Huh, didn't know that: Generating a chatbot reply runs inference; it does not retrain the model's weights.

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My model finished training and asked for a raise. I said, let us see your inference first.
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References

Answer: Using a trained model to make predictions. Training is when the model learns its weights from data. Inference comes after: the finished model is applied to new examples to produce predictions.

  1. Google Machine Learning Glossary: inference developers.google.com/machine-learning/glossary
    the process of making predictions by applying a trained model to unlabeled examples.
    Checked 2026-10-10.

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