Deep learning neural networks mimic the decision-making processes of the human brain by making a series of calculations to reach a conclusion. Machines can process massive amounts of data that humans can’t, but sound governance structures are needed to ensure positive results. Financial Sense brought this interesting information to us in their article, “Deep Learning Moves into the Corporate Sphere.”
While working a problem or issue requiring a decision, sometimes it might feel like going through a checklist. But that’s not how the human brain operates: it processes in a non-linear pattern. And this is essentially how deep learning, a subset of artificial intelligence (AI), works.
Neural networks are not new. They’ve been around since the 1940s, and more than 70 years later, deep learning has exploded in sophistication and use, primarily because of expanded computing power, better modeling, and the ubiquity of data.
Deep learning requires massive amounts of data, but it’s not a problem: it’s estimated that the data we generate every day is 2.6 quintillion bytes.
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Melody K. Smith
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Sponsored by Access Innovations, the intelligence and the technology behind world-class explainable AI solutions.
