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AI can spot your eye disease with 94.5 percent accuracy

Even more impressive, it can explain its choices. Explain yourself: The black box has long been a challenge in artificial intelligence. This refers to the tendency of algorithms to spit out results without explaining what went into them–and it can make weeding out bias difficult.

The news: In a paper released in Nature Medicine yesterday, DeepMind researchers described an AI system that can identify more than 50 diseases, refer them to a specialist, and, most important, indicate which portion of a medical scan prompted the diagnosis.

Why it matters: Explainability is crucial if AI is to see increased use in medicine. “Doctors and patients don’t want just a black box answer, they want to know why,” Ramesh Raskar, an associate professor at MIT, told Stat. “There is a standard of care, and if the AI technique doesn’t follow that standard of care, people are going to be uncomfortable with it.”

Source:Image credit:

  • Amanda Dalbjorn | Unsplash

Why the future of the power grid depends on giant batteries

Say “battery,” and most people think of the device that powers our phones, our laptops, and — maybe if they’re being ambitious — our electric vehicles. But it’s time to think bigger: At their core, batteries are simply a way to store energy, and with some creativity, they’re capable of powering electric vehicles, houses, and entire cities.

There’s the Tesla batteries acting as backup for a wind farm in Australia. There’s PG&E building the world’s biggest battery in California to store electricity for its grid.

And there’s the £3 billion project to turn the Hoover Dam into one big battery.

Being able to store energy is key, and there are plenty of ways to do it. The Verge explores the latest developments in energy storage, from those giant batteries to infinitely spinning flywheels to bottling gas in underground caverns.

We’ll talk to Tesla, and explore the pros and cons of each method and what they mean for how we’ll power our lives in the future.