Lesson 1554 of 1570
AI Benchmarks: What 'GPT Beats Human' Really Means
How AI labs measure progress and why the headlines often mislead.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1The big idea
- 2benchmark
- 3evaluation
- 4contamination
Concept cluster
Terms to connect while reading
Section 1
The big idea
Every time a new model drops, you'll see headlines about it 'beating humans' on some benchmark. Sometimes it's real progress, sometimes the test was leaked into training data, sometimes the benchmark doesn't measure what you'd think. Knowing how to read these claims keeps you grounded in hype cycles.
Some examples
- MMLU: a multi-subject knowledge test (now mostly saturated).
- GPQA: harder graduate-level science questions.
- SWE-bench: real software engineering tasks from GitHub.
- Vibes-eval: how the model actually feels in real use (no formal score).
Try it!
Pick three real tasks you've used AI for. Try them in two different models and pick a winner based on your own use, not benchmarks.
Key terms in this lesson
End-of-lesson quiz
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