Machine learning has returned with a vengeance. I still remember the dark days of the late ’80s and ’90s, when it was pretty clear that the current generation of machine-learning algorithms didn’t seem to actually learn much of anything.
These results are meaningful because even at Google, few people have the requisite expertise to build next generation AI systems. It takes a rarified skill set to automate this area, but once it is achieved, it will change the industry.
Your daily selection of the hottest trending tech news! According to AWS Blog Post by Dr. Matt Wood Today, AWS and Microsoft announced Gluon, a new open source deep learning … Continue reading Introducing Gluon: a new library for machine learning from AWS and Microsoft
Your daily selection of the latest science news! According to Phys.org – latest science and technology news stories A new learning algorithm is illustrated on a molecule known as malonaldehyde … Continue reading Scientists develop machine-learning method to predict the behavior of molecules
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Conventional computer algorithms rely on programmers entering reams of rules and facts to guide the system’s output. Machine-learning systems — and a subset, deep-learning systems, which simulate complex neural networks in the human brain — derive their own rules after combing through large amounts of data.