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First published in 2016, predictors of chronological and biological age developed using deep learning (DL) are rapidly gaining popularity in the aging research community.

These deep aging clocks can be used in a broad range of applications in the pharmaceutical industry, spanning target identification, drug discovery, data economics, and synthetic patient data generation. We provide here a brief overview of recent advances in this important subset, or perhaps superset, of aging clocks that have been developed using artificial intelligence (AI).

It sounds like science fiction: a device that can reconnect a paralyzed person’s brain to his or her body. But that’s exactly what the experimental NeuroLife system does. Developed by Battelle and Ohio State University, NeuroLife uses a brain implant, an algorithm and an electrode sleeve to give paralysis patients back control of their limbs. For Ian Burkhart, NeuroLife’s first test subject, the implications could be life-changing.

Featured in this episode:

Batelle:
https://www.battelle.org/

Ohio State University

At first, the scientists wondered whether it was a mistake.

Just 21 days after leaving the Norwegian island of Spitsbergen, an arctic fox had arrived in Greenland. And in less than three months, it made it to Canada. The fox averaged nearly 30 miles a day (50 kilometers) — some days, though, it walked almost 100 (160 kilometers).

“When it started happening, we thought ‘is this really true?’” said Arnaud Tarroux, one of the researchers who tracked the female fox. Was there “an error in the data?”

Millions of solar panels clustered together to form an island could convert carbon dioxide in seawater into methanol, which can fuel airplanes and trucks, according to new research from Norway and Switzerland and published in the Proceedings of the National Academy of Sciences journal, PNAS, as NBC News reported. The floating islands could drastically reduce greenhouse gas emissions and dependence on fossil fuels.