Porton Down, the government’s top-secret science and technology campus, is home to what may be the world’s deadliest freezer
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Proving quantum computers have the edge
Quantum computers promise to outperform today’s traditional computers in many areas of science, including chemistry, physics, and cryptography, but proving they will be superior has been challenging. The most well-known problem in which quantum computers are expected to have the edge, a trait physicists call “quantum advantage,” involves factoring large numbers, a hard math problem that lies at the root of securing digital information.
In 1994, Caltech alumnus Peter Shor (BS ‘81), then at Bell Labs, developed a quantum algorithm that would easily factor a large number in just seconds, whereas this type of problem could take a classical computer millions of years. Ultimately, when quantum computers are ready and working—a goal that researchers say may still be a decade or more away—these machines will be able to quickly factor large numbers behind cryptography schemes.
But, besides Shor’s algorithm, researchers have had a hard time coming up with problems where quantum computers will have a proven advantage. Now, reporting in a recent Nature Physics study titled “Local minima in quantum systems,” a Caltech-led team of researchers has identified a common physics problem that these futuristic machines would excel at solving. The problem has to do with simulating how materials cool down to their lowest-energy states.
Human assembloid model of the ascending neural sensory pathway
A human ascending somatosensory assembloid model was developed, which integrates multiple organoids to simulate the spinothalamic pathway, demonstrating functional connectivity and responsiveness to stimuli and revealing insights into pain-related genetic mutations.
Which Biomarkers Are Associated With Cancer Cachexia?
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$115 million just poured into this startup that makes engineering 1,000x faster — and Bezos, Altman, and Nvidia are all betting on its success
Rescale secures $115 million in Series D funding to accelerate AI physics technology that speeds up engineering simulations by 1000x, backed by tech luminaries including Bezos and Altman.
Massive Ocean Hiding Inside Mars and More Incredible Discoveries
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Hello and welcome! My name is Anton and in this video, we will talk about major updates from Mars.
Links:
https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024JE008697
https://www.nature.com/articles/s43247-024-01837-2
https://www.science.org/doi/10.1126/sciadv.adr0010
https://www.nature.com/articles/s41561-024-01576-1
https://www.pnas.org/doi/10.1073/pnas.2409983121
https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024GL109133
https://www.hou.usra.edu/meetings/lpsc2025/pdf/1427.pdf.
https://www.nature.com/articles/s41467-025-56970-z.
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https://youtu.be/3JwwKxXi_qo.
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The forgotten history of New York’s first electric taxi fleet—in the 1800s
More than a century before Teslas hit the road, battery-powered taxicabs zipped silently through the streets of Manhattan.
World-first: Quantum computer tunes billion-parameter AI model
Chinese scientists recently made history after fine-tuning a billion-parameter artificial intelligence large model on their independently developed quantum computer named Origin Wukong.
According to a report by Global Times, this quantum computer is powered by Wukong, a 72-qubit superconducting quantum chip.
The experiment was conducted at the Anhui Quantum Computing Engineering Research Center, where this computer is operated.
The US must step up its artificial general intelligence game
The United States must escalate its efforts in the artificial general intelligence race. China cannot be allowed to win.
Scientists propose a targeted lysosomal dysfunction approach for glioblastoma treatment
Researchers at Nano Life Science Institute (WPI-NanoLSI), Kanazawa University, report in Nature Communications on how the targeted suppression of lysosome function may lead to brain cancer therapy.
Glioblastoma is a type of brain cancer with a very poor prognosis of survival. Causes of glioblastoma are not known, and there is no method for preventing the cancer. Traditional treatment includes the drug temozolomide (TMZ). In many cases, TMZ kills glioblastoma cells, but a significant portion of patients show resistance to the drug.
Changes in the levels of metabolites—small molecules playing key roles in metabolic processes in living organisms—have been observed in TMZ-resistant glioblastoma cells, pointing to the importance of understanding and targeting metabolic pathways in the context of cancer therapy.