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However, labeling aging itself as a disease is both misleading and detrimental. Pathologizing a universal process makes it seem toxic. In our youth-obsessed society, ageism already runs rampant in Hollywood, the job market, and even presidential races. And calling aging a disease doesn’t address critical questions about why we age in the first place. Instead of calling aging a disease, scientists should aim to identify and treat the underlying processes that cause aging and age-related cellular deterioration.


Aging is associated with heart disease, Alzheimer’s, diabetes, and cancer, but what’s underlying all that?

In 1966, Japanese physicist Yosuke Nagaoka predicted the existence of a rather striking phenomenon: Nagaoka’s ferromagnetism. His rigorous theory explains how materials can become magnetic, with one caveat: the specific conditions he described do not arise naturally in any material. Researchers from QuTech, a collaboration between TU Delft and TNO, have now observed experimental signatures of Nagaoka ferromagnetism using an engineered quantum system. The results were published today in Nature.

Familiar magnets such as the ones on your refrigerator are an everyday example of a phenomenon called . Each electron has a property called ‘spin’, which causes it to behave like a miniscule magnet itself. In a ferromagnet, the spins of many electrons align, combining into one large magnetic field. This seems like a simple concept, but Nagaoka predicted a novel and surprising mechanism by which ferromagnetism could occur—one that had not been observed in any system before.

Last summer, the National Security Commission on Artificial Intelligence asked to hear original, creative ideas about how the United States would maintain global leadership in a future enabled by artificial intelligence. RAND researchers stepped up to the challenge.


“Send us your ideas!” That was the open call for submissions about emerging technology’s role in global order put out last summer by the National Security Commission on Artificial Intelligence (NSCAI). RAND researchers stepped up to the challenge, and a wide range of ideas were submitted. Ten essays were ultimately accepted for publication.

The NSCAI, co-chaired by Eric Schmidt, the former chief executive of Alphabet (Google’s parent company), and Robert Work, the former deputy secretary of defense, is a congressionally mandated, independent federal commission set up last year “to consider the methods and means necessary to advance the development of artificial intelligence, machine learning, and associated technologies by the United States to comprehensively address the national security and defense needs of the United States.”

The commission’s ultimate role is to elevate awareness and to inform better legislation. As part of its mission, the commission is tasked with helping the Department of Defense better understand and prepare for a world where AI might impact national security in unexpected ways.

Rice University computer scientists have overcome a major obstacle in the burgeoning artificial intelligence industry by showing it is possible to speed up deep learning technology without specialized acceleration hardware like graphics processing units (GPUs).

Computer scientists from Rice, supported by collaborators from Intel, will present their results today at the Austin Convention Center as a part of the machine learning systems conference MLSys.

Many companies are investing heavily in GPUs and other specialized hardware to implement deep learning, a powerful form of artificial intelligence that’s behind digital assistants like Alexa and Siri, facial recognition, product recommendation systems and other technologies. For example, Nvidia, the maker of the industry’s gold-standard Tesla V100 Tensor Core GPUs, recently reported a 41% increase in its fourth quarter revenues compared with the previous year.