AI Experts Ready ‘Humanity’s Last Exam’ to Stump Powerful Tech

Figurines with computers and smartphones are seen in front of the words "Artificial Intelligence AI" in this illustration taken, February 19, 2024. (Reuters)
Figurines with computers and smartphones are seen in front of the words "Artificial Intelligence AI" in this illustration taken, February 19, 2024. (Reuters)
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AI Experts Ready ‘Humanity’s Last Exam’ to Stump Powerful Tech

Figurines with computers and smartphones are seen in front of the words "Artificial Intelligence AI" in this illustration taken, February 19, 2024. (Reuters)
Figurines with computers and smartphones are seen in front of the words "Artificial Intelligence AI" in this illustration taken, February 19, 2024. (Reuters)

A team of technology experts issued a global call on Monday seeking the toughest questions to pose to artificial intelligence systems, which increasingly have handled popular benchmark tests like child's play.

Dubbed "Humanity's Last Exam," the project seeks to determine when expert-level AI has arrived. It aims to stay relevant even as capabilities advance in future years, according to the organizers, a non-profit called the Center for AI Safety (CAIS) and the startup Scale AI.

The call comes days after the maker of ChatGPT previewed a new model, known as OpenAI o1, which "destroyed the most popular reasoning benchmarks," said Dan Hendrycks, executive director of CAIS and an advisor to Elon Musk's xAI startup.

Hendrycks co-authored two 2021 papers that proposed tests of AI systems that are now widely used, one quizzing them on undergraduate-level knowledge of topics like US history, the other probing models' ability to reason through competition-level math. The undergraduate-style test has more downloads from the online AI hub Hugging Face than any such dataset.

At the time of those papers, AI was giving almost random answers to questions on the exams. "They're now crushed," Hendrycks told Reuters.

As one example, the Claude models from the AI lab Anthropic have gone from scoring about 77% on the undergraduate-level test in 2023, to nearly 89% a year later, according to a prominent capabilities leaderboard.

These common benchmarks have less meaning as a result.

AI has appeared to score poorly on lesser-used tests involving plan formulation and visual pattern-recognition puzzles, according to Stanford University’s AI Index Report from April. OpenAI o1 scored around 21% on one version of the pattern-recognition ARC-AGI test, for instance, the ARC organizers said on Friday.

Some AI researchers argue that results like this show planning and abstract reasoning to be better measures of intelligence, though Hendrycks said the visual aspect of ARC makes it less suited to assessing language models. "Humanity’s Last Exam" will require abstract reasoning, he said.

Answers from common benchmarks may also have ended up in data used to train AI systems, industry observers have said. Hendrycks said some questions on "Humanity's Last Exam" will remain private to make sure AI systems' answers are not from memorization.

The exam will include at least 1,000 crowd-sourced questions due November 1 that are hard for non-experts to answer. These will undergo peer review, with winning submissions offered co-authorship and up to $5,000 prizes sponsored by Scale AI.

"We desperately need harder tests for expert-level models to measure the rapid progress of AI," said Alexandr Wang, Scale's CEO.

One restriction: the organizers want no questions about weapons, which some say would be too dangerous for AI to study.



As Storm Bebinca Approaches, Taiwan Uses AI to Predict Typhoon Paths 

Waves break against the protecting walls as Typhoon Gaemi approaches in Keelung, Taiwan July 24, 2024. (Reuters)
Waves break against the protecting walls as Typhoon Gaemi approaches in Keelung, Taiwan July 24, 2024. (Reuters)
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As Storm Bebinca Approaches, Taiwan Uses AI to Predict Typhoon Paths 

Waves break against the protecting walls as Typhoon Gaemi approaches in Keelung, Taiwan July 24, 2024. (Reuters)
Waves break against the protecting walls as Typhoon Gaemi approaches in Keelung, Taiwan July 24, 2024. (Reuters)

As tropical storm Bebinca barrels towards waters off northern Taiwan gathering strength into a possible typhoon, weather forecasters in Taipei are using a new and so far successful method to help track its path - artificial intelligence (AI).

AI-generated forecasts, some powered by software from tech giants including Nvidia, whose chips are made by Taiwan's homegrown semiconductor champion TSMC, have so far outperformed traditional methods in predicting typhoon tracks.

In July, it was AI-based weather models, used for the first time, that helped Taiwan better predict the path and impact of Typhoon Gaemi, the strongest to strike the island in eight years that brought record-breaking rainfall.

The new technology impressed Taiwan forecasters by predicting a direct hit as early as eight days before Gaemi made landfall - handily outperforming conventional methods, which remain the mainstay of prediction planning.

"People are starting to realize AI indeed delivered some stunning performances compared to conventional models," said Chia Hsin-sing, director at the weather service provider Taiwan Integrated Disaster Prevention of Technology Engineering Consulting Company Ltd.

Bebinca is now being tracked using the same AI tools by people including Lin Ping-yu, a forecaster at Taiwan's Central Weather Administration (CWA), who said AI has given them a higher degree of confidence there will not be a direct hit.

"This (AI) is a good thing for us. It is like having one more useful tool to use," said Lin.

The AI weather programs on offer include Nvidia's FourCastNet, Google's GraphCast and Huawei's Pangu-Weather, as well as a deep learning-based system by European Center for Medium-Range Weather Forecasts.

"It is a hotly watched competition. We will know soon who is winning," said Chia.

Such AI models have also begun to be used to predict storms and hurricanes in other regions with good accuracy, according to forecasters and academics.

The AI-based software is trained using historical weather data to learn the cause and effect relationships of meteorological systems and can predict hundreds of weather variables days in advance - a process that requires only a few minutes to complete.

For all the typhoons in the Western Pacific this year up until mid-September, AI's accuracy in predicting storm tracks over a three-day window was nearly 20% higher than that of conventional models, according to data compiled by the CWA.

Ahead of Gaemi, AI helped the administration foresee an unusual loop in its path that prolonged its impact on Taiwan and prompted them to swiftly issue a rare warning for rainfall of 1.8 meters (5.9 feet), which was later proven accurate, according to CWA's deputy head Lu Kuo-Chen.

"(AI) boosted the confidence for forecasters to make that prediction," Lu said, adding the early warning gave extra time for authorities to carry out preparations.

Lu is also pinning hopes on a partnership with Nvidia, which this year announced a generative AI tool called CorrDiff that aims to forecast more precise locations of typhoon landfall and provide higher resolution images inside a storm.

"We are seeing the potential," Lu said.

For now, however, experts say the AI tools were not able to deliver quality forecasts for more detailed impact of a typhoon, such as its strength and winds, and more time is needed for the new technology to solidify its lead over more traditional ways.

"Was it just good luck?" said Chia, pointing to AI's stellar performance on Gaemi. "We need to give AI a bit more time. It is something to look forward to."