In the last ten years, Artificial Intelligence has come on in a big way. It is no longer restricted to the pages of science fictions. Instead, it is a part of our everyday lives – whether it is determining our Facebook feed or correcting our wrong spellings on Google search.
Some of the biggest breakthroughs have been in machine learning. It is now all about supplying the computers with a huge amount of data and letting them learn to interpret it on their own. This is similar to a young mind encountering the world for the first time – spotting patterns and making connections between various elements. The result of this is a software that can manage a huge amount of data that can yield great insight which was too difficult for humans to process themselves. Once the data has been converted to a language that machines can understand, the scope of what they can then do with that data is unlimited.
Artificial Intelligence and Machine Learning have great potential in the current business scenario. Banks, for one, are utilising this technology to get better insights into transaction data that help them manage risk and prevent fraud. The way these algorithms work is they gather a full understanding of the user behaviour by observing millions of transactions. This helps them understand what normal looks like and any discrepancy is immediately spotted. Some of this data has been in the hands of businesses for decades, but companies didn’t know how to effectively use them, which has changed now.
This availability and use of data have changed how business is done. The data put in the machine learning systems is governed so that it can be converted into useful information for business. Here, it is important to note that the quality of the output from machine learning systems depends on the quality of data they are fed with.
One of the best examples of this is Google Translate. Over the years the more user data that has been fed into it, the better it has become at detecting grammar and correct phrases. The translation now is a lot more enhanced and coherent than compared to the earlier times.
Businesses are now catching up and experimenting with this sort of data-driven AI. Interest in machine learning is on a rise because the capability has improved and these advances coincide with a more data-savvy world. Companies are capturing and generating all sorts of data because effective use of them gives insights into behaviour that plays a key role in growth.
With the growing frequency and the apparent ubiquity of online communication & transactions, tons of data is being generated each day. It is almost impossible for humans to gauge emerging patterns from this data and gather insights. This is where Machine learning comes into play. More and more organisations are looking for people who can construct algorithms that can learn and respond to large databases and make effective predictions. As data grows in volume and becomes more complex, the applications of machine learning and artificial intelligence are becoming widespread and all pervasive. Some of the key applications include:
Recommender & Predictor Systems for Retail & E-Commerce
Predictive Techniques for Autonomous Vehicles
Trading Patterns & Efficiencies in Global Financial Markets
Fraud Prediction & Detection for Banks
Transportation Management & Traffic Shaping for Smart Cities
This has made machine learning the number one in-demand skill globally amongst programmers. Depending on their experience and capabilities, Machine Learning specialists usually get a substantial hike.
This constant growth in the practical application of artificial intelligence fuels high demand for machine learning engineers, data scientists, machine learning researchers, and other related professions. In addition to this, organisations operating in different verticals like voice recognition, cyber security, image recognition etc are on the look out for the right people with the skills and knowledge.
To stay on the top, companies need specialists and they need them now. Organisations cannot wait for universities to produce fresh graduates after five years. Individuals who are good at maths, physics and statistics and being picked up and trained in machine languages like Lisp, Prolog, etc.
There are multiple courses available online and other independent courses. Individuals interested can always opt for these courses if this field is something they want to work in.