There is a blurry line between what is considered artificial intelligence (AI), and what is considered machine learning (ML).
Simply put: AI is a much broader concept, with machines being able to carry out tasks in a way that humans would consider “smart”, while ML is a current application of AI based around the idea that we should really just be able to give machines access to data and let them learn for themselves.
One requires programming, and one requires slightly less programming but more upfront algorithms.
Either way, ML is becoming a ‘differentiator’ in industries like healthcare, insurance and financial services. Software that can intelligently analyse medical, financial or insurance records and make intelligent decisions or recommendations based on the information at hand, is becoming infinitely more commonplace.
Companies like Amazon, for example, have launched a program called Comprehend Medical, which can read and analyse medical records and mine the relevant insights and relationships.
Even car dealerships are getting in on the deal, with innovative global companies like Cox Automotive that sell services to car dealers and are using ML to tell those dealers and their customers when a particular car model is most likely to sell, and at what price.
However, this is where the line blurs for me. ML is considered to be a subset of AI, but it is actually more appropriate to think of it as the current state of the art. There are applications being developed that can read text and work out nuance: whether the person who wrote it is making a complaint or offering congratulations.
Applications are being built that help machines understand the vast nuances in human language.
Applications that can listen to a piece of music and decide what emotion will be evoked, such as is the piece playing more likely to make someone happy or sad and based on that knowledge will find other pieces of music that match the mood.
Astonishingly, these applications can even compose their own music that expresses similar themes, or compositions that they ‘know’ will be appreciated by the admirers of the original piece being listened to. Additionally, applications are being built that help machines understand the vast nuances in human language, and to learn to respond in a way that a particular audience is likely to comprehend.
All this brings to mind the movies of my youth: Terminator and the Rise of the Machines. Are we heading towards a future in which we fight with machines for the right to be human? Who knows?
What I do know is that all these technologies speak to a whole: AI, ML, neural networks (a computer system modelled on the human brain and nervous system) and natural language processing. They all speak to a source of hugely exciting innovation in recent years, and one which is heavily reliant on ML. They speak to the creation of applications that attempt to understand and mimic natural human communication, either written or spoken, and communicate in turn with us using similar, natural language.
These are but a few of the possibilities that are being offered by systems that are based around ML and neural networks. Thanks in no small part to science fiction and movies like Terminator, I might add. The idea has taken shape that we should be able to communicate and interact with electronic devices and digital information, much like we would with another human being.
Robots or machines that can talk to us and potentially even mimic human emotion and behaviour are not the only advances though.
ML also means that we will soon have unsupervised algorithms employed that will be able to make predictions from datasets with only input data being available and no corresponding output variables. Or an algorithm that can extrapolate from a customer’s browsing activity on an online retail Web site and discover what he/she has shown interest in, and offer up a tailor-made recommendation or special.
The benefits to the marketing, health, insurance and automotive industries are enormous: smart machines making smart decisions autonomously, with the bottom line at all times being the base of all decisions.
But actual mimicked ‘human’ interaction with a device, robot or machine? That is the stuff of the future. That being said, the future is now. Just ask Watson. Or Coseer. Or Facebook, which recently chose to switch off its AI robots after they started talking to each other in their own language.