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Generating scenarios for extreme events, without extreme data

Can a city’s seawall stand up to a blockbuster storm? Will a region’s power grid hold against record-breaking heat? And can a town’s fire-fighting resources contain a major wildfire? To answer these questions, communities will first need to know how such extreme events could unfold. How far is a wildfire likely to spread? How much of […]

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Paving the way for greener ammonia production

Ammonia is one of the most important chemicals produced in the world, ranking second only to sulfuric acid in the total volume produced each year. It is used mostly to make fertilizer, which is essential to feeding the world’s population. Yet its production accounts for up to 2 percent of the world’s energy consumption and

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When AI art has no author: Study finds generated images often can’t be traced to training data

When an artificial intelligence image generator produces a portrait, whose work went into it? The question sits at the center of lawsuits, licensing deals, and proposed regulations worldwide. Artists want credit. Companies want clarity. Policymakers want a way to assign responsibility.New work from a team of researchers at MIT’s Computer Science and Artificial Intelligence Laboratory

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Google AI health coach to use Abbott glucose data

Abbott and Google are linking continuous glucose monitoring data with Google’s AI-powered health coaching tools, giving the Gemini-powered service access to another source of personal health information. Under a multiyear agreement, data from Abbott’s Lingo continuous glucose monitor will be integrated into the Google Health app. Users will be able to view glucose trends alongside

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With a feel for physics, AI models simulate a wider range of real-world scenarios

Artificial intelligence models are jacks of many trades, including writing, generating images, and creating 3D models. But they aren’t as helpful when it comes to testing robots or designs for vehicles in diverse environments, since they don’t understand physics as well as they do pixels or text.To build an AI system that can reliably simulate

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What happens when medical students rely on AI – and never develop their own judgment? | Simar Bajaj and Joseph Sakran

AI’s danger isn’t just in experts losing the ability to reason. It’s that trainees may never learn how to do so in the first placeIn healthcare, there’s growing concern over doctors becoming less clinically adept as they increasingly rely on AI tools. But what about the trainees – medical students, residents and fellows – who

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Why health AI interfaces must adapt to user expertise

MIT researchers and collaborators found that AI explainability tools in the health sector can produce sharply different results depending on who uses them. When applied to skin disease diagnosis, non-experts improved their accuracy with AI assistance, although the improvement largely came from deferring to the model. Primary care providers showed a different pattern: they performed

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Solving the solvent problem

Lithium-ion batteries are the leading choice in today’s electric vehicle and battery energy storage system industries, but they contain a number of critical minerals — including lithium, cobalt, nickel, and graphite — that are considered essential for economic and national security reasons, and therefore vulnerable to supply chain disruptions. As renewable energy, electrified infrastructure, and

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The benefits of medical AI assistance vary based on user expertise

A one-size-fits-all approach likely isn’t the best strategy when designing artificial intelligence systems that assist users in disease diagnosis.A new study by researchers at MIT and elsewhere found that, while AI assistance generally improved the accuracy of non-experts and clinicians in diagnosing skin diseases, AI explainability methods had different impacts depending on the users’ knowledge

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Working to automate nuclear plant operations

For nuclear to be considered as a viable clean energy source, it has to be competitively priced and economical to produce. Lauren Fortier, a second-year doctoral student in the Department of Nuclear Science and Engineering (NSE), is helping the cause by developing remote operation protocols for autonomous control of nuclear plants. After an undergraduate degree in materials

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