When we observe technology across timelines, we can see how its evolution has been intertwined with ours. Humans have always been known for their unique quality of cognitive thinking among all primates, but it has not been long since machines developed this trait too. Machines can learn like us, which is both scary and fascinating at the same time. This intriguing field of technology is called Machine learning. Machine learning is a subset of artificial intelligence(AI) which enables systems to learn on their own from experiences or past data without being externally programmed by humans. Isn’t that fascinating?
How do machines learn?
In simple terms, machines learn through algorithms that analyze historical data fed to them. It finds trends and patterns and frames a prediction model. Now, whenever new data is input, it will predict a possible outcome for it. All this requires minimum to no human intervention. Ever wondered how you get traffic alerts while using GPS navigation, or how Google comes up with the best product recommendations for you? Well, it is all machine learning powered by AI. Machines can predict the future pretty much accurately, as long as the future doesn’t deviate much from the past. This is majorly regulated by the amount of data available for analysis. The more, the merrier.
Today, the need for machine learning is paramount, simply because of the sheer volume of data available. It is practically impossible for humans to collect, organize and analyze such enormous amounts of data to make valuable predictions about the future. Machine learning, therefore, saves the day for us.
The applications of machine learning algorithms are boundless. Nearly every sector is benefiting from it-be it healthcare, e-commerce, education, social networking, finance, retail, or even cybersecurity.
Machine Learning in Healthcare
In healthcare, improving medical imaging and diagnosis using pattern recognition, aiding drug discovery, analyzing genomic patterns, personalized and precision medicine, and hence, reducing the overall cost of treatment.
Machine Learning in Finance
In finance, machine learning quickly detects any security breach and declines transactions based on analysis, which occurs in real-time. It makes trading predictions that are not emotion led. Apart from these, loan underwriting, portfolio management, and many more are aided by machine learning.
Machine Learning and Artificial Intelligence, and social media
Across various social platforms, the application of machine learning ranges from tailoring personalized news feeds to targeted adverts. Machine learning can effectively mimic marketing campaigns run by humans. For instance, the ‘for you’ section on Netflix or Amazon Prime Video presents you with entertainment that best suits your mood.
The future of Machine Learning and Artificial Intelligence
Machine learning has huge untapped potential. The machine learning market is expected to grow from USD 1.03 Billion in 2016 to USD 8.81 Billion by 2022. Certain refinements like algorithms improving with no human intervention, incorporation of quantum computing, enhanced cognitive functioning, enhanced personalized recommendations, and ultimately development of machines identical to humans is the future of machine learning. Machine learning is, in essence, an effort to educate computers to think, learn, and behave like people. Machine learning has grown dramatically and is now a crucial component of practically every business.
The author is based in Toronto, Canada, and has more than a decade of experience in Technology design and implementation in diverse industries such as retail, health, logistics, energy, and consulting. Currently, the author is the strategic advisor to the CIO at Canadian Nuclear Laboratories Ltd, and a technology solution partner for the University of Toronto for the Cannabis & Vaping research and development campaign.
