This article provides an overview of the existence and workings of Large Language Model (LLM) benchmarks, as well as their future implications. It discusses the increasingly specific and generalistic capabilities of LLMs and their impact on language understanding and reasoning. The article is useful for AI Engineers, Founders, VCs, and anyone familiar with LLMs. It emphasizes the limitations of traditional metrics in evaluating LLMs and proposes the use of benchmarks to measure and compare their performance across various language tasks. The article was originally published on Towards AI and is available for free on Medium.
source update: LLM Benchmarks in 2024. – Towards AI