Cutoff

A cutoff is the point where an AI model’s training data ends, so it may not know later events, prices, or news.

Cutoff refers to the point at which the data learned by the AI model is up to. It is like a person who has finished studying by reading only the newspapers published by a certain date, and in principle does not know about events that have occurred since then, changed prices, or new people.

This concept arose because once an AI model has finished learning, its knowledge is fixed at that point. The basics of using AI are to explain why an incorrect answer is given when asking AI about the latest news or current market prices, and to distinguish whether a question requires the latest information or not.

Recently, there have been many services that combine web search or RAG to supplement information after the cutoff. However, even if search is attached, the fact that the knowledge of the model itself still remains in the past does not change.

✅ Why it matters

• Helps you understand exactly why AI is weak against the latest information
• It serves as a standard for deciding whether to trust AI or use search depending on the type of question
• It serves as a background for understanding the need for a search-combined AI service

⚠️ Limits and debates

• When asked for information after the cutoff, instead of saying they don't know, they may make up a plausible wrong answer.
• In services with a search function, it is easy for users to forget the existence of the cutoff.
• The cutoff point revealed by the model may not exactly match the actual knowledge distribution.