Definition

Zero-shot learning is when an AI can do something new without being shown any examples first. It uses what it already knows and follows instructions or patterns to figure it out.

Example

Zero-shot learning lets an AI translate a sentence in a new language without training on that language first.

How It’s Used in AI

Used in language models, image classification, and voice recognition. For example, ChatGPT can answer questions or summarize topics it hasn’t been trained on directly—because it uses broad patterns it has already learned.

Brief History

The concept of zero-shot learning grew alongside few-shot methods and became popular with the release of large-scale models like GPT-3 in 2020, which showed strong performance with no prior task-specific examples.

Key Tools or Models

Models like GPT-3, GPT-4, PaLM, and Claude all support zero-shot learning by relying on massive, general training data and smart prompting.

Pro Tip

Zero-shot learning works best with clear instructions. Be specific about what you want the AI to do.