A new book claims AI has been built on a flawed assumption dating back to Alan Turing's famous 1950 paper. Peter J. Denning argues that the most important parts of human intelligence, including common sense, intuition, culture, and practical know-how, cannot be encoded into computers. He believes this makes true human-level AI impossible, regardless of how large language models become.
A new study suggests the brain begins making decisions much earlier than scientists previously thought. Researchers found that even primary sensory regions are influenced by higher brain areas through rapid feedback loops, rather than simply passing information forward. This more dynamic view of brain function could help engineers design future AI systems that think more like biological brains while using far less power.
Scientists have created a silicon chip that can write dozens of DNA sequences simultaneously using electricity and water-based enzymes, offering a cleaner alternative to conventional DNA manufacturing. The breakthrough could eventually support portable DNA-writing devices and even massive DNA data storage, although new chemistry will be needed to scale the technology further.
Water’s odd behavior becomes even more dramatic when it is supercooled, but scientists have struggled to compare the many different ways of describing its microscopic structure. Researchers at the University of Osaka used an AI model trained on computer simulations to evaluate 16 different structural descriptors. The system identified the most effective ways to distinguish between water’s two competing liquid states, providing a clearer framework for studying one of nature’s most mysterious substances.
Researchers have created an AI-based simulation that makes it much faster to model how neutron star mergers produce many of the universe's heaviest elements. The new tool could improve predictions of these powerful explosions while helping scientists better connect observations in space with experiments on Earth.
A new AI-powered framework could transform how astronomers measure the expansion of the Universe. By analyzing images of Type Ia supernovae and modeling their environments in unprecedented detail, researchers can estimate cosmic distances with near-spectroscopic accuracy. The technique is designed for the flood of data expected from the upcoming Vera C. Rubin Observatory and may greatly improve our understanding of dark energy.
The race to build data centers in space is gaining momentum as AI drives unprecedented demand for computing power. Orbital facilities could tap into abundant solar energy and avoid many of the environmental challenges faced on Earth. Yet space remains a harsh and expensive place to operate, with major hurdles including cooling, maintenance, radiation exposure, and orbital debris.
Scientists discovered that rice behaves in a highly unusual way: it weakens under rapid compression but stays stronger when pressure is applied slowly. Using this effect, they engineered a new material that reacts differently to gentle movements and sudden impacts. The material can adapt its stiffness automatically, opening the door to safer soft robots and protective equipment that responds instantly to collisions.
Scientists found that transfer learning can make the search for new physics in the universe much faster, slashing the need for expensive simulations. Yet the approach can backfire when AI relies too heavily on familiar patterns, potentially missing evidence of something truly new.
Researchers gave top AI models a classic attention test used in psychology and found a major flaw. While the models could correctly name colors in short lists, their performance deteriorated sharply as the task became longer and more complex. Some leading systems fell from over 90% accuracy to nearly complete failure.