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Home Sci-Fi

Supercomputer COVID-19 insights, ionic spiderwebs, the whiteness of AI – TechCrunch

August 7, 2020
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I see far more research articles than I could possibly write up. This column collects the most interesting of those papers and advances, along with notes on why they may prove important in the world of tech and startups. This week: supercomputers take on COVID-19, beetle backpacks, artificial spiderwebs, the “overwhelming whiteness” of AI and more.

First off, if (like me) you missed this amazing experiment where scientists attached tiny cameras to the backs of beetles, I don’t think I have to explain how cool it is. But you may wonder… why do it? Prolific UW researcher Shyam Gollakota and several graduate students were interested in replicating some aspects of insect vision, specifically how efficient the processing and direction of attention is.

The camera backpack has a narrow field of view and uses a simple mechanism to direct its focus rather than processing a wide-field image at all times, saving energy and better imitating how real animals see. “Vision is so important for communication and for navigation, but it’s extremely challenging to do it at such a small scale. As a result, prior to our work, wireless vision has not been possible for small robots or insects,” said Gollakota. You can watch the critters in action below — and don’t worry, the beetles lived long, happy lives after their backpack-wearing days.

The health and medical community is always making interesting strides in technology, but it’s often pretty niche stuff. These two items from recent weeks are a bit more high-profile.

One is a new study being conducted by UCLA in concert with Apple, which especially with its smartwatch has provided lots of excellent data to, for example, studies of arrhythmia. In this case, doctors are looking at depression and anxiety, which are considerably more difficult to quantify and detect. But by using Apple Watch, iPhone and sleep monitor measurements of activity levels, sleep patterns and so on, a large body of standardized data can be amassed.

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