How AI benchmarks work — and why they keep "saturating"
MMLU, SWE-bench, ARC and LMArena: how AI benchmarks are built, what their scores really measure, why models quickly max them out and how to read leaderboards.
AI Desk4 min read
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#Evaluation
Every The Latent Daily story, tool, model and resource tagged “Evaluation”.
5 items
Benchmarks & LeaderboardsResearch
MMLU explained: the exam that measured AI knowledge across 57 subjects
How the 2020 MMLU benchmark tested language models on law, medicine, math and more, why it became the standard for years, and why newer tests replaced it.
AI Desk4 min read
AGI & FrontierResearch
"Sparks of AGI" explained: what Microsoft claimed about GPT-4, and the critiques
Microsoft researchers argued that GPT-4 showed early signs of general intelligence. What they tested, why critics objected and what it teaches about AGI claims.
AI Desk3 min read
Switching AI tools? How to evaluate an alternative before you move
A step-by-step plan to compare a new AI tool with the one you use today: define success, run a side-by-side trial, check data migration, costs and exit options.
AI Desk3 min read
Quick take: benchmark scores won't tell you which AI model to use
Why leaderboard rankings are a poor guide to choosing an AI model for your work, what they do measure, and a simple way to test models on your own tasks.
AI Desk3 min read