"a village is going to help them stay in their homes"

"For many older Americans and their families, the devastating COVID-19 outbreak — which caused more than 200,000 deaths in nursing homes nationally — was a persuasive argument for living at home as long as possible.

Now, as the pandemic grinds into its third year, a loose-knit band of tech gurus, gerontology researchers, and volunteer-powered elder support groups, called “villages,” is seeking to overcome the obstacles to aging in place. Among the toughest: a worsening shortage of home care workers, who can assist the oldest residents with walking, dressing, or showering.

Coronavirus sped up the deployment of “age-tech,” technology that helps older people age in place, by seven to 10 years, said Joe Coughlin, director of MIT AgeLab in Cambridge. "

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https://www.bostonglobe.com/2022/04/18/metro/pandemics-lesson-many-older-folks-stay-your-home-long-you-can/ 

Dale Orzalli, a Seaglass Village volunteer, arrived at Maureen Neumann's front door to take her to a doctors appointment at Lahey Medical Center in Peabody.MATTHEW J LEE/GLOBE STAFF

MIT: The mysterious origins of COVID-19 (audio)

A new 5-part investigative series on the origins of covid-19

A new investigative series on the origins of covid-19 Dive into the mysterious origins of covid-19 with our thrilling new podcast series Curious Coincidence, hosted by MIT Technology Review investigative science reporter Antonio Regalado. Learn why it's so hard to find its origin and why it matters. Episodes 1-3 are out now wherever you listen to podcasts.  Learn More View this email in your browser Copyright © 2022 MIT Technology Review, All rights reserved. You are receiving this email because you opted in to receive newsletters and/or initiatives and events emails from MIT Technology Review. Our mailing address is: MIT Technology Review 196 Broadway, 3rd fl, Cambridge, MA 02139

What it will take to unleash the potential of geothermal power?

"Untapped potential: There's enough heat inside the earth to meet total global energy demand twice over. But harnessing it requires drilling deep underground and transforming that heat into a usable form of energy. That's difficult and expensive, which is why geothermal power only makes up only about 0.3% of electricity generation worldwide, despite the fact it's more consistent than virtually every other form of renewable energy. However, it's now getting a boost, thanks to a $84 million Department of Energy project to build four demonstration plants. They'll test enhanced geothermal systems, an experimental form of the technology.

Exhausted supplies: The most accessible geothermal resources in the US have been tapped, and it's hard to figure out how many more potential sites may be out there, and where they might be. Some researchers and startups are trying to expand into new places by pumping fluid into impermeable rock to force cracks open. This creates space where water is free to move around and heat up, producing the steam needed for power.

Barriers: Despite geothermal's vast potential, reaching these resources won't be easy. The process has been shown to trigger earthquakes, and despite the injection of government cash, financing geothermal projects can also be a challenge. "

Read the full story from The MIT Technology Review  =>   https://www.technologyreview.com/2021/12/08/1041511/potential-geothermal-power-infrastructure-bill/

What it will take to unleash the potential of geothermal power

"systems couldn’t tell when words in a sentence were jumbled up"

From the MIT Technology Review, we find that while Artificial Intelligence (AI) continues to make strides, it also contains a significant flaw.

"Many AIs that appear to understand language and that score better than humans on a common set of comprehension tasks don’t notice when the words in a sentence are jumbled up, which shows that they don’t really understand language at all. The problem lies in the way natural-language processing (NLP) systems are trained; it also points to a way to make them better.

Researchers at Auburn University in Alabama and Adobe Research discovered the flaw when they tried to get an NLP system to generate explanations for its behavior, such as why it claimed different sentences meant the same thing. When they tested their approach, they realized that shuffling words in a sentence made no difference to the explanations. “This is a general problem to all NLP models,” says Anh Nguyen at Auburn University, who led the work."

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https://www.technologyreview.com/2021/01/12/1016031/jumbled-up-sentences-ai-doesnt-understand-language-nlp-bert-fix/

 

From the MIT Technology Review, we find that Artificial Intelligence (AI) contains a significant flaw