Why do we labor when reading some words but not others? AI offers a partial answer
Peer-Reviewed Publication
Updates every hour. Last Updated: 27-Oct-2026 19:16 ET (27-Oct-2026 23:16 GMT/UTC)
Why do we breeze through some sentences in a book or article but have to reread others to comprehend their meaning? A team of linguists and data scientists has found a partial answer in AI—some of this processing parallels that of neural-network-based large language models. However, other aspects of why we read this way cannot be explained by these technologies, revealing where human and AI language processing diverge and maintaining the mystery of some stages of the reading process.
It has long been recognized that chiral materials can selectively transport electron spins, yet their role in electrochemical energy storage remained unclear. Now, writing in National Science Review, researchers led by Prof. Hongsen Li at Qingdao University demonstrate that regulating the chiral asymmetry factor enhances spin polarization at catalytic sites, accelerates sulfur redox reactions, and significantly improves the electrochemical performance of lithium–sulfur batteries.
In a paper published in SCIENCE CHINA Earth Sciences, a research team led by Professor Chengbang An reconstructed 4,000 years of dietary evolution in the central-eastern Eurasian Steppe from the Bronze Age to the Tang Dynasty, revealing synchronized dietary shifts across multiple regions: increased millet and meat consumption from the Early Iron Age to the Han Dynasty, followed by a return to wheat- and barley-based C₃ diets during the Jin-Tang periods. The study further demonstrates that these transitions were jointly driven by climate change, intensified interregional interaction among pastoralist groups, and innovations in grain processing technology. This work provides a critical reference for understanding human-environment interactions in the Eurasian Steppe.
The new technology identifies the tumor's biological fingerprint with more than 90% accuracy and could complement CT scans in monitoring patients' response to treatment.
Conventional tribotronic devices, that convert mechanical stimuli like touch into electrical signals, offer fixed sensitivity and pose challenges in large-area integration. In a new study, researchers have developed a new vertically integrated dual-gated tribotronic transistor architecture, that offers tuneable sensitivity, reliable contact and proximity detection, as well as minimal pixel footprint for high-density array integration. This technology can pave the way for electronic skin systems that allow robots and prosthetics to reliably perceive human touch.
Soft, shape-changing materials are attracting growing interest in applications ranging from robotics to wearable devices, but conventional 3D printing methods are limited to a single actuation mode in each printed component. A new study demonstrates the first 3D-printable smectic liquid crystal elastomer ink that can switch molecular alignment during printing, allowing the same filament to either elongate or contract when heated. The advance could enable more versatile soft robots, adaptive surfaces, and minimally invasive biomedical devices.
Halide cathode materials are reshaping all-solid-state lithium batteries (ASSLBs) by enabling multi-electron reactions that dramatically boost energy density. A new review traces their evolution from liquid to solid-state systems, spotlighting single-phase electrode designs that eliminate inactive components and the rational design of multi-electron cathode materials. Looking ahead, it highlights AI-driven material discovery and integrated architectures to overcome energy challenges, charting a course toward cheaper, higher-energy ASSLBs.
Shaping electromagnetic waves at will is a long-standing goal in modern science and engineering. Programmable metasurfaces offer a promising route, but existing schemes are often too simple and fixed for real-time, task-oriented, and diverse control. A team from Zhejiang University has now developed a deep-learning-enabled temporal sequencing framework that maps target illusion patterns to modulation sequences, enabling rewritable and customizable electromagnetic illusions in experiments. This work is published in National Science Review.