The Road Ahead: Machine Learning’s Future

Article by Bettina Warburg

Machine learning already seems pretty futuristic. After all, it allows a computer to teach itself and continuously improve, like something out of science fiction.
But as we proceed into the future, machine learning algorithms and other AI systems will get even more advanced. Read on to learn about how we expect machine learning to develop, and how these changes may affect your life.

More Is More

The AI market is growing with some studies predicting that it will surpass $40 billion in revenue by 2020. And by the same period, 30% of all companies are expected to use machine learning to augment at least one primary sales process. More organizations than ever before are going to be able to afford powerful computers. This means that they will have access to machine learning for the first time. Because more organizations will be using machine learning to collect and analyze data, algorithms, across the board, will improve. Expanded access to hardware is going to be one of the key factors leading to improved machine learning algorithms in the future.
Another way that machine learingI will spread and improve is via Machine Learning as a Service (MLaaS). In coming years, more companies are going to use the cloud in order to offer other organizations access to machine learning services when they need. This means that companies who can’t afford hardware can still afford to use machine learning when they need it, which will greatly expand its reach.

The Ever Improving AI

Machine learning is a type of AI that is—by its nature—continuously improving.

Each time a machine learning algorithm is used, it can determine how it succeeded and how it failed—then it can improve upon itself so it performs better next time. Because continuous learning is integral to the function and purpose of machine learning, it is inherent that the algorithm will get better and better over time.

Thus, as we proceed into the future, and machine learning algorithms have more time to improve, we’ll end up with computing systems that can be more accurate and powerful (in terms of data analysis, prediction, pattern detection, etc.) than ever before.

Personalization Gets More Personalized

Today, people value and seek out personalized experiences. In fact, studies show that 80% of people are more likely to do business with a company that offers personalized experiences. Companies can provide meaningful and helpful personalization by harnessing machine learning.
Machine learning can do things like power a recommendation engine so that Netflix shows you movies you want to watch. It can also do real time bidding on ads so that a company’s ad shows up in front of the best person in the best place at the best time for the best price (a personalized, targeted ad experience). Finally, marketers can use machine learning to create more relevant ad content, identifying patterns within large datasets and revealing demographics that can be marketed to in specific ways.

Robots are Real

With the spread of machine learning in the future, robots are going to become more commonplace than ever before. The technology is going to power machines that improve logistical efficiency and reduce labor costs. Machine learning will also power intelligent drones that can monitor things like agricultural fields from above to optimize farming processes.
While the rise of robots may sound scary, humans don’t need to panic. Robots aren’t coming for their jobs, nor are they going to take over the world. In reality, robots will always rely on humans. They have to be built and programmed! So we’re not heading for the apocalypse just yet.

Faster, Simpler, Sharper

As we look to the future, expect to see personalization get even better than it is now. The more people use personalization algorithms, the more they can be fine tuned. So with time, personalization will become more accurate and tailored to consumers.
The nature of machine learning is that it improves and gets smarter as it works. Stay tuned! You may end up astounded where this technology will be able to take us as it develops.
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