A new study put ChatGPT to the test by asking it to judge whether hundreds of scientific hypotheses were true or false—and the results were far from reassuring. While the AI got it right about 80% of the time on the surface, its performance dropped significantly when accounting for random guessing, revealing only modest reasoning ability. Even more concerning, it frequently contradicted itself when asked the exact same question multiple times, sometimes flipping answers back and forth.
As AI systems began acing traditional tests, researchers realized those benchmarks were no longer tough enough. In response, nearly 1,000 experts created Humanity’s Last Exam, a massive 2,500-question challenge covering highly specialized topics across many fields. The exam was engineered so that any question solvable by current AI models was removed. Early results show even the most advanced systems still struggle — revealing a surprisingly large gap between AI performance and true expert-level knowledge.
Neuromorphic computers modeled after the human brain can now solve the complex equations behind physics simulations — something once thought possible only with energy-hungry supercomputers. The breakthrough could lead to powerful, low-energy supercomputers while revealing new secrets about how our brains process information.
Spanish researchers have created a powerful new open-source tool that helps uncover the hidden genetic networks driving cancer. Called RNACOREX, the software can analyze thousands of molecular interactions at once, revealing how genes communicate inside tumors and how those signals relate to patient survival. Tested across 13 different cancer types using international data, the tool matches the predictive power of advanced AI systems—while offering something rare in modern analytics: clear, interpretable explanations that help scientists understand why tumors behave the way they do.