CAIS and Scale AI are excited to announce the launch of Humanity's Last Exam, a project aimed at measuring how close we are to achieving expert-level AI systems. The exam is aimed at building the world's most difficult public AI benchmark gathering experts across all fields. People who submit successful questions will be invited as coauthors on the paper for the dataset and have a chance to win money from a $500,000 prize pool.
AI is developing at a rapid pace. Just a few years ago, AI systems performed no better than random chance on MMLU, the AI community’s most-downloaded benchmark (developed by CAIS). But just last week, OpenAI’s newest model performed around the ceiling on all of the most popular benchmarks, including MMLU, and received top scores on a variety of highly competitive STEM olympiads. Humanity must maintain a good understanding of the capabilities of AI systems. Existing tests now have become too easy and we can no longer track AI developments well, or how far they are from becoming expert-level.
Despite these advances, AI systems are still far from being able to answer difficult research and other intellectual questions. To keep track of how far the AI systems are from expert-level capabilities, we are developing Humanity’s Last Exam, which aims to be the world’s most difficult AI test.
We're assembling the largest, broadest coalition of experts in history to design questions that test how far AIs are from the human intelligence frontier. If there is a question that would genuinely impress you if an AI could solve it, we’d like to hear it from you!
Prizes may be awarded on question quality or question novelty compared to other questions. People who have already submitted questions prior to this announcement are also eligible for these prizes. A small set of questions will be kept private to catch if an AI is memorizing answers to public questions, but prizes can and co-authorship can be awarded to people who have their questions kept part of the private set.
Terms and conditions here.
Deadline: November 1, 2024
For a detailed list of instructions and example questions, please visit agi.safe.ai/submit.