By Deepa Naik
Whom would you trust — a machine or a human? Human — will be the most probable answer. But if you are asked, would you trust machines which are more skilled and intelligent than humans? Well, here the answer might differ — after all — we have all been using and trusting calculators for a long long time .. haven’t we?
Recently, I experienced another occasion when I got an opportunity to answer this question!!! I had booked an Ola ( similar to Uber) cab, and not trusting the driver to find the way, I immediately gave him a call for directions. After five minutes of frustrating communication, I could see he was heading in the wrong direction. So finally after English, Marathi, Hindi — I gave up and asked him to come based on the navigation in the maps. As I headed down, preparing myself to spend the next few minutes trying to trace the vehicle, I was pleasantly surprised to see the cab standing right in front of my gate. So, here was the answer — the google map navigation was far more effective than my skills of providing directions!!
That brought an interesting realization — if you look at cars today and transportation in general, there was so much help we were actually looking at that was based on technology. Map reading which was earlier done by the person sitting next to you is now taken over by the Google Map — The GPS girl ( the voice of Karen Jacobsen) . Then you have auto cruise, parking sensors, reverse parking cameras, fuel,oil change reminders and what else. Do we really have to wait for autonomous / driver-less cars to say we are in the AI ( Artificial Intelligence) age or would you really call today’s car as a semi-robotic machine as compared to the first generation automobiles?
The way I look at it, we are already on our journey with artificial intelligence in our day to day life — robots whom we don’t recognize as robots at all but who are helping us never the less, being our virtual assistants.
I get on my online grocery store website and I have a smart shopping list ready and waiting for me, created based on my previous shopping history. It is intelligent enough to suggest the quantities to order and popups up a message of “Did you forget to shop for this item?” if I miss out on my usual list. The handbag that I shopped for the other day was less than a five minute shopping trip — online. Generally it takes me hours to choose a bag. This time I received some rather tempting recommendations of bags in my email and all I had to do was click and pay and wait for the delivery to happen. The catch here was that I had bought my earlier bags online and they knew exactly what I liked and didn’t.
Instances such as these go on to prove that we are already in the Artificial Intelligence Age. Of course one may challenge that statement — for the reason that there are so many different definitions of Artificial Intelligence floating around. But I use it in the context of the one that is simplest to understand and coined by Elaine Rich, the author of the book Artificial Intelligence — “Artificial Intelligence is the study of how to make computers do things, at which, at the moment, people are better.”
If you look at the applications of AI currently they are across various domains / industries. For some industries its rapidly increasing whereas some others are still catching up.
AI has been around for a long time. The first time the term was coined in 1956 by John McCarthy at the Massachusetts Institute of Technology. He termed “Artificial Intelligence as the branch of computer science concerned with making computers behave like humans”.
So if a term was framed and has been a part of computer science for so long, how come it is suddenly getting more visibility today? One of the main reasons is of course the penetration of internet and how technology has become a part and parcel of every ones life. The other main and most important reason is — Data — or rather Big Data. Without data, I believe AI will just remain theory with very limited applications — as it had been all these past decades.
I tried to take a bird-eye view of Artificial Intelligence and the block diagram that I came up with is given above.
The cloud and the big data layer are critical ones for the AI application to reside on. The AI Applications also called as the AI agents — are categorized based on the various ways in which we use them.
They can be classified as bots ( common usage chat bots), or robots ( if they are using sensors). Heuristic Search, which is been around for a long time is also a category of AI and is now a technology which is very much in its advanced stages. We are now doing search not only on text, meta data — but also on images, face recognition, videos etc.
The other applications of AI are in robotic process automation (RPA) which are more towards processes in organization which can be automated.
Between the Application Layer and the Data Layer, lies the real “heart” of AI — which is where the model and analysis takes place. The layer which makes the applications intelligence. These are the layers which have algorithms, statistical models and techniques which can analyze data.
The other layer is the Device Layer — as we have seen that technology can be consumed via various means these days — be it smartphone apps, web apps , wearable technology ( fit-bits, watches etc.), or in case of manufacturing the machinery itself which could be using software for the applications or robots or the AI agents.These applications are then used by the various industries right from Banking and Financial Services, Manufacturing, Retail etc. In terms of the organizations, the marketing departments are finding maximum applications to such intelligent software applications as the data that is captured gives high insight into consumer behavior.
So we see that all industries and not just the technology companies are getting hugely impacted by the changes coming in the Artificial Intelligence paradigm . Of course, the Information Technology industry is seeing a large change too. A lot of programming activities are now taken up by the bots, a lot of processes are being taken over by RPAs ( robotic process automation). So there is change there too. So as far as the corporate landscape is concerned — one thing is certain — “change is the only constant” and at the heart of this change is going to be intelligence — and this time it may not be just Human.
