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Doing Machine Learning the Right Way

The work of MIT computer scientist Aleksander Madry is fueled by one core mission: “doing machine learning the right way.”

Madry’s research centers largely on making machine learning — a type of artificial intelligence — more accurate, efficient, and robust against errors. In his classroom and beyond, he also worries about questions of ethical computing, as we approach an age where artificial intelligence will have great impact on many sectors of society.

“I want society to truly embrace machine learning,” said Madry, a recently tenured professor in the Department of Electrical Engineering and Computer Science. “To do that, we need to figure out how to train models that people can use safely, reliably, and in a way that they understand.”

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Is the Pulp and Paper Industry Ready for Machine Learning?

Few industries have seen more transformation over the past decade than that of the pulp and paper industry. Gone forever is the ability of the business to rely heavily on staples such as newsprint and glossy magazine paper. Use of electronic devices and media have reduced considerably even the need for paper in the office environment.

Add to this the constant external pressures from government and other organizations pushing for stricter environmental standards. To compete, the paper and pulp industry must embrace efficiency producing new technologies that can save time and money.

While some see machine learning and related technologies as a threat to companies and jobs, these developments will help ensure the long-term survival of both.

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Eight Keys to Better Asset Reliability

If you’re a manufacturing plant manager, what don’t you want to see out to the production floor? Probably a significant number of things, but near the top of that list would probably be a large group of workers congregating around a critical piece of machinery that should be running—yet isn’t. Rarely does such a sight have positive implications.

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