Machine Learning

Recently, talk about Machine Learning (ML) has been one of the hottest topics among the C-suite discussion. With advanced ML techniques being developed and used more and more, the ability to analyze data and compute it is showing great promise and potential through the path of ML. Many of the world’s top businesses are starting to adapt and use ML to perform complex tasks faster and more efficiently than previously possible. With this up and coming trend taking place, there is a very strong belief among the technology industry that Machine Learning is the future. To put it into perspective, the machine learning market is expected to grow from $1.03 billion in 2016 to a whopping $8.81 billion by 2022, having an average Compound Annual Growth Rate of 44.1%. Company powerhouses such as Google, IBM, Microsoft, and Apple are already leveraging off the benefits which ML provides, giving great promise that ML is indeed the future of technology.


So first of all, what exactly is Machine Learning? Well, Machine Learning is an application of artificial intelligence that allows systems to learn and improve without the need for programming or supervision. In simpler terms, ML is the computational learning which machines go through, improving with experience. Being an intensely evolving language, continuous technological advancements are bound to hit the field of Machine Learning. So, what will the future of ML look like? 


One of the ML applications that will certainly shape the future is improved unsupervised algorithms. ML uses unsupervised algorithms to analyze results and uses that to make predictions from datasets (when one input variable is available without any corresponding output values). This type of algorithm differs from supervised algorithms, in which the output is already known in supervised learning. Unsupervised learning, in contrast, works on artificial intelligence. When algorithms are left alone to work on themselves, they discover and identify many hidden patterns within a dataset, many of which supervised algorithms could not do. As the language evolves further, more improvements in unsupervised algorithm learning can be seen, leaving almost no doubt that this ML application will be a big part of future technological advancements.


Another major application of ML which seems to be in trend right now is the adoption of Quantum Computing. Quantum Computing is the use of quantum-mechanical phenomena such as superposition and entanglement to perform computations at roaringly fast speeds. With the use of ML algorithms in unison with quantum computers, data processing becomes a lot faster while enhancing the ability to draw insights from datasets. This increased performance would not have been possible using classic ML techniques, making Quantum Computing a big tool in the future of ML, allowing its harnessed power to create more and more efficient techniques.


Finally, rendering enhanced personalization is yet another way ML algorithms can be used. A great example of enhancing personalization can be in the marketing aspect of business, where ML algorithms read the patterns and behavior of a customer to draw relevant conclusions, and potentially send product recommendations or personalized emails to targeted prospects. ML techniques understand the likes and dislikes of a customer and helps them stay hooked to your services or products. A recent study showed that 82% of marketing leaders are adopting AI and ML to improve their personalization strategies, going to show just how big ML can be in not just the data aspect, but also the marketing aspect of industries.


Above were just some of the many ways in which ML can be used in the future. There are many other applications that ML can be adopted in which can greatly shape the future of Machine Learning. A recent prediction by Gartner suggests that by 2022, 75% of new end-user solutions leveraging AI and ML techniques will be built with commercials instead of open-source platforms. All of the evidence in this blog along with the industry trends taking place right now strongly suggest that Machine Learning will play a valuable role in the technology of the future. With all the possibilities which ML can accomplish, it is undoubtedly true that tech and ML will continue to grow through language, together and for the better. In conclusion, the future of Machine Learning is huge and endless, as Machine Learning is the future.


Article by: Eshaan Shrivastava from the Heritage High Chapter