Things Made Possible by the Machine Learning Revolution

One of the hottest areas of technology today, Machine learning promises to have a profound impact on our world and the way we live. Perhaps most exciting is the fact that we have reached the point where it is much more than just hype, as evidenced by the massive amount of investment from the corporate world in talent and resources dedicated to this space.

Usually described as a subset of artificial intelligence, machine learning involves computers using large amounts of data to teach themselves and improve their performance of certain tasks. Already, we are seeing machine learning applied in a variety of areas, from transportation to healthcare, retail and cybersecurity, among others.

Self-driving cars

Probably the most high-profile example machine of learning becoming reality is in the autonomous vehicles space. While widespread adoption is still several years away, self-driving cars have been in development for some time, and are currently in test pilots in 50 cities around the world – with about half of them in the U.S. The algorithms that allow these vehicles to operate autonomously are heavily reliant upon machine learning technologies. As these algorithms learn and become “smarter,” driver safety is increased. Some experts believe autonomous vehicles could reduce traffic fatalities by up to 90 percent.  

Increased Patient Privacy and Smarter Healthcare

The healthcare industry has long been criticized for its use of outdated and inefficient legacy technologies. One of the challenges that has held the industry back is the difficulty in optimizing its systems while still maintaining and protecting sensitive patient records. But without the need for human interaction, machine learning algorithms can process large sets of healthcare data while avoiding the risk of confidential contracts being breached. At the same time, machine learning algorithms can be used to make faster and more accurate diagnoses and to better understand and analyze potential health risk factors based on age, genetic history and socio-economic status


A Better Shopping Experience

The recent boom in the retail industry has been well publicized. Over the past few years, it has consistently generated more than $20 trillion in sales annually. A major driver in this tremendous growth is the increasing strength of online sales, which comes with a huge amount of data being compiled on consumer behavior, shopping trends and tendencies. But because much of this data is housed in disconnected warehouses, many retailers have not been able to take full advantage of these valuable insights.

That is beginning to change, however, as machine learning models are being implemented that use previously acquired data to predict such things as which products to recommend and the optimal time to offer discounts. As that happens, retailers will gain a much better understanding of their customers’ behavior and be able to provide an even more personalized online shopping experience. These are likely significant factors in estimates placing the global retail market at close to $32 billion by 2023.

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