Question

A product team is explaining to executives how their new gen AI feature can group customer feedback by meaning rather than exact keywords. They want to describe the underlying concept that lets the system understand that 'the app keeps crashing' and 'it freezes constantly' are semantically similar. Which core generative AI concept are they describing?

Accepted Answer

Embeddings, which represent text as numeric vectors so that similar meanings are positioned close together in a shared space

Answer

Tokens, which split text into smaller units that the model processes one at a time

Answer

Context windows, which define how much text the model can consider at once

Answer

Hallucinations, which occur when the model produces plausible but incorrect output