OpenAI may get most of the attention, but these two-dozen companies finding their way in AI by making vibe-coding software, building robots, and developing drones.
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Key to human intelligence lies in how brain networks work together, neuroimaging study suggests
Modern neuroscience understands the brain as a set of specialized systems. Aspects of brain function such as attention, perception, memory, language, and thought have been mapped onto distinct brain networks, and each has been examined largely in isolation.
While this approach has yielded major advances, it has left unresolved one of the most basic facts about human cognition: its overall unity as an integrated system.
Now, researchers at the University of Notre Dame have conducted a neuroimaging study to investigate how the brain is organized and how that integrated system gives rise to intelligence. Their study was published in the journal Nature Communications.
Deep-learning algorithms enhance mutation detection in cancer and RNA sequencing
Researchers from the Faculty of Engineering at The University of Hong Kong (HKU) have developed two innovative deep-learning algorithms, ClairS-TO and Clair3-RNA, that significantly advance genetic mutation detection in cancer diagnostics and RNA-based genomic studies.
The pioneering research team, led by Professor Ruibang Luo from the School of Computing and Data Science, Faculty of Engineering, has unveiled two groundbreaking deep-learning algorithms—ClairS-TO and Clair3-RNA—set to revolutionize genetic analysis in both clinical and research settings.
Leveraging long-read sequencing technologies, these tools significantly improve the accuracy of detecting genetic mutations in complex samples, opening new horizons for precision medicine and genomic discovery. Both research articles have been published in Nature Communications.
New insight into the Origin of Water on the Earth
Scientists have found the interstellar organic matter could produce an abundant supply of water by heating, suggesting that organic matter could be the source of terrestrial water.
There remains a number of mysteries on our planet including the elusive origin of water on the earth. Active studies suggested that terrestrial water had been delivered by icy comets or meteorites containing hydrous silicates that came from outside the “snow line” – the boundary beyond which ice can condense due the low temperatures. More recent studies, however, have provided observations opposing to cometary origin theory, yet still failing to suggest plausible substitutions for the source of terrestrial water. “Until now, much less attention has been paid to organic matter, comparing to ices and silicates, even though there is an abundance inside the snow line” says planetary scientist Akira Kouchi at Hokkaido University.
In the recent study published in Scientific Reports, a group of scientists led by Akira Kouchi demonstrates that heating of the interstellar organic matter at high temperature could yield abundant water and oil. This suggests that water could be produced inside the snow line, without any contribution of comets or meteorites delivered from outside the snow line.
Radiowaves enable energy-efficient AI on edge devices without heavy hardware
As drones survey forests, robots navigate warehouses and sensors monitor city streets, more of the world’s decision-making is occurring autonomously on the edge—on the small devices that gather information at the ends of much larger networks.
But making that shift to edge computing is harder than it seems. Although artificial intelligence (AI) models continue to grow larger and smarter, the hardware inside these devices remains tiny.
Engineers typically have two options, neither are ideal. Storing an entire AI model on the device requires significant memory, data movement and computing power that drains batteries. Offloading the model to the cloud avoids those hardware constraints, but the back-and-forth introduces lag, burns energy and presents security risks.
NASA Webb Pushes Boundaries of Observable Universe Closer to Big Bang
NASA’s James Webb Space Telescope has topped itself once again, delivering on its promise to push the boundaries of the observable universe closer to cosmic dawn with the confirmation of a bright galaxy that existed 280 million years after the big bang. By now Webb has established that it will eventually surpass virtually every benchmark it sets in these early years, but the newly confirmed galaxy, MoM-z14, holds intriguing clues to the universe’s historical timeline and just how different a place the early universe was than astronomers expected.
“With Webb, we are able to see farther than humans ever have before, and it looks nothing like what we predicted, which is both challenging and exciting,” said Rohan Naidu of the Massachusetts Institute of Technology’s (MIT) Kavli Institute for Astrophysics and Space Research, lead author of a paper on galaxy MoM-z14 published in the Open Journal of Astrophysics.
Due to the expansion of the universe that is driven by dark energy, discussion of physical distances and “years ago” becomes tricky when looking this far. Using Webb’s NIRSpec (Near-Infrared Spectrograph) instrument, astronomers confirmed that MoM-z14 has a cosmological redshift of 14.44, meaning that its light has been travelling through (expanding) space, being stretched and “shifted” to longer, redder wavelengths, for about 13.5 of the universe’s estimated 13.8 billion years of existence.
Individual trapped-ion addressing with adjoint-optimized multimode photonic circuits
Momenzadeh, M., Sun, K., Wu, Q. et al. Individual trapped-ion addressing with adjoint-optimized multimode photonic circuits. npj Nanophoton. 3, 3 (2026). https://doi.org/10.1038/s44310-025-00102-4
Brewing possibilities: Using caffeine to edit gene expression
What if a cup of coffee could help treat cancer? Researchers at the Texas A&M Health Institute of Biosciences and Technology believe it’s possible. By combining caffeine with the use of CRISPR—a gene-editing tool known as clustered regularly interspaced short palindromic repeats—scientists are unlocking new treatments for long-term diseases, like cancer and diabetes, using a strategy known as chemogenetics.
The work is published in the journal Chemical Science.
Yubin Zhou, professor and director of the Center for Translational Cancer Research at the Institute of Biosciences and Technology, specializes in utilizing groundbreaking tools and technology to study medicine at the cellular, epigenetic and genetic levels. Throughout his career and over 180 publications, he has sought answers to medical questions by using highly advanced tools like CRISPR and chemogenetic control systems.
