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A woman in Lagos, Nigeria, peels cassava to make flour. Diseases and pests can threaten the crop. Photo: Sunday Alamba / AP

Researchers at Penn State University and the International Institute for Tropical Agriculture in Tanzania have trained a neural network running on a smartphone to spot cassava disease with 93% accuracy.

Why it matters: Diseases and pests threaten cassava, a root vegetable that is critical for food security in sub-Saharan Africa, and can lead to losses of over a $1.2 billion each year.

The vision: "In the same way we have personalized medicine, I think we can have personalized agriculture on scale for hundreds of millions of people in real time," Penn State's David Hughes told Wired. He envisions farmers and gardeners using artificial intelligence to help them diagnose their crops.

How it works: Neural networks are typically trained with millions of images. Instead of starting from scratch, the researchers took advantage of something called transfer learning in which an existing network is retrained with new data. In this case, they used 2,756 images of cassava leaves with tell-tale signs of disease.

Go deeper

2 hours ago - World

U.S. and NATO answer Putin in writing while bracing for Ukraine invasion

NATO Secretary-General Jens Stoltenberg. Photo: Dursun Aydemir/Anadolu Agency via Getty

The U.S. and NATO provided Russia with written proposals on Wednesday to advance a "diplomatic path forward," even as they warned that Russia could invade Ukraine within days.

Why it matters: This is a delicate diplomatic balancing act. The U.S. and NATO want to show they're serious about diplomacy but unwilling to compromise on "core principles" — all without providing Vladimir Putin with an additional pretext for escalation.

The political leanings of the Supreme Court justices

Data: Martin-Quinn scores; Chart: Axios Visuals

The Supreme Court will continue to have a solid conservative majority even with Justice Stephen Breyer's retirement.

How to read the chart: An analysis by political scientists Andrew Martin and Kevin Quinn, known as the Martin-Quinn Score, places judges on an ideological spectrum. A lower score indicates a more liberal justice, whereas a higher score indicates a more conservative justice.

The front-runners for Biden's Supreme Court pick

Judge Kentaji Brown Jackson (left) and Justice Leondra Kruger (right) Tom Williams-Pool/Getty Images and Lonnie Tague, US Department of Justice

Two highly accomplished Black female judges — Ketanji Brown Jackson, a judge on the D.C. Circuit Court of Appeals; and Leondra Kruger, a justice on the California Supreme Court — are seen as the early front-runners to replace retiring Supreme Court Justice Stephen Breyer.

The big picture: Jackson is a powerful federal judge with a record that progressives feel they can trust. Kruger was a highly regarded litigator and has carved out a reputation for working well with conservative judges.

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