Back to the AI glossary Models
Training vs. Inference
Training = AI learns. Inference = AI works.
Explanation
During training, a model learns from data and builds its knowledge. In inference, it applies this knowledge to answer queries. Training happens once (or rarely), inference runs constantly.
How it works
Training: Millions of texts are processed, the model adjusts its parameters. Inference: A user asks a question, the model generates an answer in real time.
Example
GPT-4 was trained (training) for months. When you ask ChatGPT a question, it uses this training to answer (inference).
Why it matters
Helps to understand why AI models can be expensive to develop but inexpensive to operate.