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Pentagon Outlines its First Artificial Intelligence Strategy

The plan calls for accelerating the use of AI systems throughout the military, from intelligence-gathering operations to predicting maintenance problems in planes or ships.

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The plan calls for accelerating the use of AI systems throughout the military, from intelligence-gathering operations to predicting maintenance problems in planes or ships. Pixabay

The U.S. military wants to expand its use of artificial intelligence in warfare, but says it will take care to deploy the technology in accordance with the nation’s values.

The Pentagon outlined its first AI strategy in a report released Tuesday.

The plan calls for accelerating the use of AI systems throughout the military, from intelligence-gathering operations to predicting maintenance problems in planes or ships. It urges the U.S. to advance such technology swiftly before other countries chip away at its technological advantage.

“Other nations, particularly China and Russia, are making significant investments in AI for military purposes, including in applications that raise questions regarding international norms and human rights,” the report says.

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The Pentagon outlined its first AI strategy in a report released Tuesday. Pixabay

The report makes little mention of autonomous weapons but cites an existing 2012 military directive that requires humans to be in control.

The U.S. and Russia are among a handful of nations that have blocked efforts at the United Nations for an international ban on “killer robots” — fully autonomous weapons systems that could one day conduct war without human intervention. The U.S. has argued that it’s premature to try to regulate them.

The strategy unveiled by the Department of Defense this week is focused on more immediate applications, but even some of those have sparked ethical debates.

The Pentagon hit a roadblock in its AI efforts last year after internal protests at Google led the tech company to drop out of Project Maven, which uses algorithms to interpret aerial video images from conflict zones. Other companies have sought to fill the vacuum, and the Pentagon is working with AI experts from industry and academia to establish ethical guidelines for its AI applications.

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“Everything we’ve seen is with a human decision-maker in the loop,” said Todd Probert, a vice president at Raytheon’s intelligence division, which is working with the Pentagon on Maven and other projects. “It’s using technology to help speed up the process but not supplant the command structure that’s in place.”

The Pentagon’s report follows President Donald Trump’s Monday executive order prioritizing AI research across the government. (VOA)

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Researchers Develop AI-enabled Tool to Detect Heart Attacks

It was found that compared to CAD-RADS and other scores, the ML approach better discriminated which patients would have a cardiac event from those who would not

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A commonly used drug for treating osteoporosis or bone pain may also help reduce the risk of death by cardiovascular, heart attack and stroke, according to a study.
Heart Attack risk can be decreased by drug of osteoporosis. Pixabay

Researchers have developed an Artificial Intelligence-enabled tool which uses Machine Learning (ML) algorithms that will soon play a critical role in predicting heart attacks and other cardiac issues.

The Coronary Computed Tomography Arteriography (CCTA) gives highly detailed images of the heart vessels and is a promising tool for refining risk assessment, said researchers in the study published in the journal Radiology.

While earlier tools like the Coronary Artery Disease Reporting and Data System (CAD-RADS) emphasise on stenoses or blockages and narrowing in the coronary arteries, CCTA shows more than just stenoses.

“While CAD-RADS is an important and useful development in the management of cardiac patients, its focus on stenoses may leave out important information about the arteries,” said study lead author Kevin M. Johnson, Associate Professor at the Yale University.

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The study compared people aged 41-50 years and 40 or younger heart attack survivors and found that among patients who suffer a heart attack at a young age overall is 40 or younger. VOA

The ML algorithm is able to pull out patterns in the data and predict that patients with certain patterns are more likely to have an adverse event like a heart attack than patients with other patterns.

For the study, the research team compared the ML approach with CAD-RADS and other vessel scoring systems in nearly 7,000 patients. They followed the patients for an average of nine years after CCTA.

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It was found that compared to CAD-RADS and other scores, the ML approach better discriminated which patients would have a cardiac event from those who would not.

“The risk estimate that you get from doing the Machine Learning version of the model is more accurate than the risk estimate you’re going to get if you rely on CAD-RADS,” Johnson said. (IANS)