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Will Al achieve 85% or higher on the Humanity's Last Exam benchmark before 2030?
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Humanity's Last Exam (HLE) is a benchmark designed to evaluate Al systems' reasoning and problem-solving capabilities across a wide range of academic disciplines, including mathematics, humanities, and natural sciences.
- Developed collaboratively by the Center for Al Safety and Scale Al, HLE comprises 3,000 unambiguous and verifiable academic questions contributed by nearly 1,000 subject-matter experts from over 500 institutions across 50 countries.
- The dataset is multimodal, with approximately 10% of the questions requiring both image and text comprehension, while the remaining 90% are text-based.
- As of early 2025, state-of-the-art Al models have demonstrated limited success on the HLE benchmark.
- For instance, OpenAl's 03-mini (high) model achieved an accuracy of 13% when evaluated solely on text-based questions.
- OpenAl's Deep Research agent, which leverages the 03 model for extensive web browsing and data analysis, reached an accuracy of 26.6% on the HLE benchmark.