Application Domains for AI
There's all kind of different applications, obviously, there's healthcare, there's finance. The one that's closest to my heart, of course, is robotics and automation. Where the AI technologies really help us to improve our abilities to perceive the environment around the robot and to make plans in unpredictable environments as they're changing.
There's a great book out by an author, it was Kelvin Kelly, and he is an editor for the Wired magazine, he's written a great book about technologies that are going to be changing shaping our world, specifically 12 technologies. And he's got a fantastic definition in the book about specifically how AI is going to permeate our everyday life and it's all summarized in one excellent quote. So he says that the business cases for the next 10,000 startups are easy to predict, I have x and I will add AI to my x. The way I understand that is it's basically a notion that AI in one shape, way or form, in any shape or form, is going to permeate every aspect of human endeavor. Everything we do, everything we touch is going to be enhanced by AI. We have great benefits from taking any device, any machine, and make it just a little bit smarter. The benefit of that is just adding a bit of smarts to it, a bit of intelligence to it is exponential in its benefit.
So we work a lot with some really fun applications of AI. We do a couple of different things in the lab that I run. We work on self-driving vehicles as one aspect, so autonomy for self-driving. Which requires a lot of AI for the vision systems, for the navigational intelligence, for the planning and control aspects of the car, we do that. And we also have a large research program in what are called collaborative robotics, or cobots. So robots that are designed to work in and around and with people. And that presents a lot of challenges, because we want the robots to act intelligently and to interface with humans in a way that is natural. And that requires understanding how people behave, which requires intelligence. In addition to those, there are a myriad of other applications, drug discovery, medical treatments for cancer and other diseases. So, a bunch of extremely exciting applications.
The general use of AI so far has been taking large data sets and making sense of them. And doing some sort of processing with that data in real time. That's what we've been doing, and that's what we've seen most effective, in terms of creating some sort of larger scale impact in healthcare beyond just having a siloed device. And we've been seeing that across the board, across the whole healthcare spectrum.
We use AI all the time, and a lot of the times we're not even aware of it. We use AI every time we type in a search query on a search engine, every time we use our GPS. Or every time we use some kind of voice recognition system.
I like to focus on a particular segment of AI, if that's okay, around computer vision. Because it's just particularly fascinating to me. Now, when we think of computer vision, they're looking at AI in ways to help augment, or to help automate or to help train computers to do something that's already very difficult to train humans to do. Like when it comes to the airport, trying to find weapons within luggage through the X-ray scanner, now that could be difficult to do. No matter how much you train someone that can be very difficult to identify. But with computer vision that can help to automate, help to augment, help to flag, certain X-ray images so that maybe even humans can just take a look at a filtered set of images, not all of the images right? So computer vision is very disruptive. And so there's many ways in which computer vision can really help to augment the capabilities of humans in lots of different industries.
Now I mean applications of AI are really all around us. There's no limit to really what we're doing with artificial intelligence. When you do practically anything on any technology, you're most probably using some form of what we call machine learning or artificial intelligence. For example, when you check your email. Doing something as simple as checking your email. Spam filtering has been done for years with machine learning technology. More recently, Google came out with their features that enable you to do smart email compositions. So you can actually have text written for you on the fly as you're writing your email. Your subjects are automatically written as well, it'll recommend to you who you should be sending the email to, see if you missed someone. All of these things are powered by machine learning. But some of the main areas where I believe machine learning technology can make an impact are the fields of health care and education.
Avinash C. Pillai
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