The ābestā model lost - day 08
The model everyone calls ābestā lost my tiny test today. Learn why a cheaper, faster model might outperform state-of-the-art models for specific tasks.
The model everyone calls ābestā lost my tiny test today. Learn why a cheaper, faster model might outperform state-of-the-art models for specific tasks.
Evaluating the evaluator: why your LLM-as-a-judge is a system under test that needs its own validation.
Evaluating the logic behind having an LLM judge another LLMās output. Establishing a helpfulness rubric and confronting definitions.
Putting predictable constraints and standard expectations to the test, evaluating how the LLM judge grades standard formatting and basic rules.
You donāt need thousands of test cases to begin. Five carefully chosen examples are more than enough to boot up your AI evaluation pipeline.