Artificial intelligence technology is undergirded by two intertwined forms of automation.
Artificial intelligence is everywhere these days, but the fundamentals of how this influential new technology works can be confusing. Two of the most important fields in AI development are “ machine learning ” and its sub-field, “ deep learning .” Here’s a quick explanation of what these two important disciplines are, and how they’re contributing to the evolution of automation. First, what is AI? It’s worth reminding ourselves what AI actually is.
For instance, if a company was training an algorithm to recognize a specific brand of car in photos, it would feed the algorithm huge tranches of photos of that car model that had been manually labeled by human staff. A “testing dataset” is also created to measure the accuracy of the machine’s predictive powers, once it has been trained. When it comes to DL, meanwhile, a machine engages in a process called “unsupervised learning.
Deep Learning Artificial Neural Networks One IBM Machine Learning In Video Games Computational Neuroscience SPOTIFY Artificial Intelligence Applications Of Artificial Intelligence Computational Statistics Cybernetics Jeff Crume IBM Training Validation And Test Data Sets Neural Network Artificial Intelligence In Healthcare Technology Internet Gizmodo
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