What’s the difference between artificial intelligence (AI), machine learning, and deep learning?

RealKM Magazine
Jun 21, 2017 · 2 min read
  • Machine learning is one subfield of AI where machines take data and “learn” for themselves, unlike software programs that are hand-coded with specific instructions for task completion. Machine learning systems can quickly apply knowledge and training from large data sets to excel at a range of tasks including facial recognition, speech recognition, object recognition, and translation. Continuing with the Deep Blue and DeepMind examples, Deep Blue was rule-based and dependent on programming so not a form of machine learning, but DeepMind is because it trained itself on a large dataset of expert moves.
  • Deep learning is a subset of machine learning that solves real-world problems by tapping into neural networks that simulate human decision-making. Deep learning requires massive datasets to train itself on because there are a huge number of parameters that need to be understood by a learning algorithm, which can initially produce a lot of false-positives. For example, it would take a very massive dataset of images for a deep learning algorithm to understand the very minor details that distinguish a cat from a cheetah, panther, or fox. DeepMind is an example of deep learning.

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Syndicating the articles published on realkm.com