Togo, a west african nation of around eight point five million people was just one of many countries that was facing a crisis here. Citizens were facing the prospect of hunger and malnutrition. As the pendemic closed down the world, the togales government wanted to do as much as it could to help the most vulnerable. Government officials from togo reached out to josh bloominstock, a computer scientist based at the university of california berkeley who has had previous experience using machine learning to identify people in poverty. Next up, reportra nick pertridge. How has been finding out how machine learning helped the government of togo.
00:45 A flexible, wearable, fabric microphone
Inspired by the ear, a team of researchers have developed an acoustic fibre that can be woven into fabrics to create a sensitive microphone. This fabric microphone is capable of detecting human speech and heartbeats, and the team think it could be used to develop new, wearable sensors for long-term health monitoring.
Research article: Yan et al.
News and Views: A smart sensor that can be woven into everyday life
08:38 Research Highlights
How a shark’s posture lets you know if it’s asleep, and the desert dust that helps cirrus clouds form.
Research Highlight: The secrets of shark sleep
Research Highlight: Wispy clouds are born of dust in the wind
11:31 How AI helped Togo target financial aid
Early in the COVID-19 pandemic, the government of Togo needed to distribute financial aid to citizens most in need of assistance. As running a nationwide survey to find out people’s financial situations was impossible, they turned to machine learning to discover how best to distribute aid.
Research article: Aiken et al.
19:02 Briefing Chat
We discuss some highlights from the Nature Briefing. Using machine learning to find meteorite fragments in a desert, and using radiocarbon dating to detect forged paintings.
Physics World: ‘Huge leap’ as scientists report first drone-assisted space rock recovery after observed meteorite fall
Nature: Police rely on radiocarbon dating to identify forged paintings
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