EE Times Silicon 60: The Rise of Machine Learning
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Darktrace’s unsupervised-learning models sound the alarm before intruders can cause serious damage.
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While efficiency and risk analysis are the top use cases today, the data center industry is only scratching the surface of what will be possible in the future.
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Even the best AI tools are more artistry than science, require reams of carefully curated data from which they inherit significant biases, cannot generalize beyond their domains and are black boxes that even their creators don’t fully understand. In short, they are pattern extractors, not magic.
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Machine learning can also go terribly wrong, making you regret that enthusiastic rush to adopt
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How companies old and new are integrating machine learning in data center management tools to improve data center availability.
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Facebook provided more details on how it's using machine learning to combat terrorism-related content on its platform. But does it actually work?
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A combination of machine learning and new data gathering tools could help warn firefighters in California earlier and possibly even save lives.
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This simple spreadsheet of machine learning foibles may not look like much but it’s a fascinating exploration of how machines “think.” The list, compiled by researcher Victoria Krakovna, describes various situations in which robots followed the spirit and the letter of the law at …
Sourced through Scoop.it from: techcrunch.com
In the midst of a recent engagement an executive suddenly asked, “Are we using Machine Learning?”. This caught us off-guard; working in the field for many years, we use the “learning sciences” virtually every day to solve hard problems.
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