The idea that machines shall learn through experience still looks ambitious to many of us. Taking the limited abilities of artificial intelligence, we expect machines to do exceptionally what they are programmed to. However, the evolution of machines and especially software brought engineers a new hope. It appears that machines can learn from data to produce reliable and repeatable results. Today algorithms allow to apply complex mathematical calculations to big data without being programmed to do so. Everything machines need to learn is data, affordable processing power, and a lot of cheap storage, which are all accessible today.
On the large scale, each of us uses machines and programs that learn. Online recommendations, ridesharing services, Google’s AI-powered predictions, email spam filters, and smart categorization all adapt to our needs as they learn from big data around them. Machine learning makes apps very flexible and well-adapted to our everyday needs. Autonomous vehicles also largely depend on AI and machine learning to produce the result we expect. Machine learning is also very common in finance. Most of our daily transactions rely on smart machines that make it easier to check deposits, prevent fraud, and make credit decisions.
As for now, most industries working with large amounts of data deploy machine learning. It allows them top work more efficiently or gain advantage over the competitors. Financial institution take machine learning as the major way of preventing fraud. The technology takes a new turn in healthcare where doctors can better analyze data and improve diagnosis. Websites recommendations are the least what machine learning can give to marketing and sales.