The AI Benchmark: Do PhD-Level Tests Really Measure Intelligence?

In this episode we dissect a rigorous study that puts large language models through the GPQA Diamond Dataset—a suite of PhD‑level questions across physics, chemistry, and biology—to see how “smart” they really are. We explore three passing standards (complete accuracy, high accuracy, and majority), why 100% correctness isn’t guaranteed, and how models can be inconsistent even on repeated prompts. The episode also digs into prompting tricks, politeness effects, and formatting choices, showing why evaluation is nuanced, context‑dependent, and essential for real‑world deployments.

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