The Future of Machine Learning
Machine Learning is the Future – and it’s Already Here!
What is machine learning?
In machine learning systems, computers are primed with algorithms to discover patterns in datasets, and to discern these same patterns in the data they subsequently analyse. By analysing more and more datasets, these computers are able to constantly improve the accuracy of their pattern recognition and to refine their predictions of future data trends.
You’re likely to have come face-to-face with machine learning technology already. Even if you didn’t recognise it at the time, chances are it recognised you. Facial and speech recognition software, which we use (or have used upon us) more and more on a day-to-day basis, is powered by machine learning.
The increasing popularity of ‘smart loudspeakers’ (such as Amazon’s highly successful Echo, and Google’s recently announced Google Home) is just the latest highly visible sign of the growing importance that machine learning is assuming in our lives.
Machine learning is operating in all sorts of places behind the scenes; for example, if you’ve ever used Google’s search function, you’ll have been taking advantage of it. The function is continuously optimised using ‘deep learning’ neural networks. Don’t believe me? Google it.
The applications of machine learning are potentially as multifarious as the applications of human intelligence. But for the moment, let’s look at the role it has to play in dealing with the rise of another technological phenomenon of the early 21st century: big data.
What is big data?
Ever since the advent of the internet, data has been accumulating at an unprecedented rate, from all sorts of sources: e.g. online shopping interactions, social media interactions, clickstreams from web visitors, video camera footage, etc. The result of this has been termed ‘big data’. Big data is data which comes in a volume too great to process by traditional methods.
It isn’t only its size that makes big data difficult to deal with. But also the speed with which it accumulates, the variety of sources it comes from, and the forms that it takes. It should really be called ‘big, fast and highly complex data’… but that isn’t quite as snappy.
In today’s technologically driven world, data is seen by many as ‘the new oil‘ and is of potentially huge value to businesses. But the value of data is not readily accessible; the value of data is buried within the data itself. Like oil, this value can only be accessed with the use of the appropriate ‘drill’.
At present, the best data ‘drill’ on the market is machine learning technology, which is likely to be the ‘drill’ of choice for the foreseeable future too. (After all, how can improve on technology that improves itself?)
Machine learning is particularly suited to dealing with big data, because its optimisation is fuelled by, and indeed depends upon, big data. Machine learning refines its analytic and predictive capabilities through being fed large datasets, and the more data it is fed the more it can refine itself. This symbiotic relationship suggests that machine learning, as a technology, will be the only technology to ‘keep up’ with the exponential growth of big data.
Alongside Google’s use of ‘deep learning’ neural networks to improve its search function, there are numerous other examples of machine learning being used to deal with big datasets:
- Advertisers are increasingly using algorithms to help more accurately target consumers (programmatic advertising)
- The majority of trading on the stock marketing is now conducted automatically, by machines (algorithmic trading)
- Google is banking on AI to give its new messaging app ‘Allo’ the edge over its competitors
- Law firm Baker & Hostetler recently announced that they are to employ Ross, IBM’s ‘artificially intelligent lawyer’ to conduct legal research
- Outside the courts, machine learning is even being used to predict and prevent crime
The list goes on and on, so much so that you’d need a machine learning program to sort through it! There are innumerable businesses and institutions that can benefit by using big data, and machine learning, therefore, has something to offer each and every one of them.