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Machine Learning: A Stepping Stone in the Big Picture of Artificial Intelligence
Big Data focuses on being able to extract information and insight from massive amounts of information. The results of Big Data are then usually paired with visualization and analytics reporting to enable understanding of the information. A step beyond that is to develop machine learning algorithms that automate prediction of behavior based on information and that are able to make decisions.
Machine learning is closely related to work done in the field of artificial intelligence. While the goal of artificial intelligence is to get machines to ‘think’, a more realistic goal of machine learning is to get machines to be able to learn and to predict outcomes based on previously collected information.
Michael Schmidt, CEO at Nutonian, said that “machine learning is a small part of AI. We actually call it machine intelligence. We don’t call it AI because that is such a broad term.”
Joshua Saxe, senior principal research engineer at Invincea Labs, said that “there are proven applications of machine learning that will continue to grow as the underlying machine learning algorithms mature… As academically oriented work improves the accuracy and efficiency of computer vision, natural language processing and network analysis algorithms (which these application areas depend on) these applications will benefit and improve.”
