An Evaluation (or "eval") is a crucial step in the development of Generative AI models. It involves assessing the performance, quality, and effectiveness of the AI-generated outputs, such as text, images, or audio. The evaluation process helps identify areas for improvement, ensures the model meets the desired standards, and validates its readiness for real-world applications. Common evaluation methods include human ratings, automated metrics, and comparative analyses against ground truth data or benchmarks. Regularly conducting evals is essential for maintaining the output quality of LLM-based services for end users.
The LLM Knowledge Base is a collection of bite-sized explanations for commonly used terms and abbreviations related to Large Language Models and Generative AI.
It's an educational resource that helps you stay up-to-date with the latest developments in AI research and its applications.