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Autorater evaluation

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TL;DR. A hybrid evaluation method combining human judgment with an ML model trained to mimic human evaluators for generative AI quality.

Technical Definition

A hybrid evaluation method combining human judgment with an ML model trained to mimic human evaluators for generative AI quality.

How it works

Autorater evaluation is a technique used to assess the quality of generative AI outputs by blending human and automated assessment. An 'autorater' is itself a machine learning model trained on human-provided evaluations, aiming to replicate human judgment. While pre-built autoraters exist, fine-tuning them to specific tasks yields the best results for efficient and consistent quality assessment.

Related Concepts

  • Generative AI — An AI field focused on creating models that can generate novel and complex content, such as text, images, audio, and video, that is coherent and original.
  • Human evaluation — Assessing model performance by using human judgment to rate its outputs.

Further Reading

  • Google ML Glossary