[MUSIC] What advice would you give to someone who wants to learn AI, or perhaps even get into a career in AI? >> So I believe artificial intelligence is going to permeate every sphere of human endeavor. So the first thing I would say is I would congratulate the person who've chosen to study and apply AI as having made the right choice. The second part I would say is because the technology is moving so fast, because we have not yet discovered what we're going to discover, I think it's really important to keep an open mind. It's important to keep an open mind and not get too attached to any particular technology, any particular technique, any particular implementation. But to really think forward and think outside of the box, and think about what may, think about the art of the possible, think about what may come. And the number one advice I would give is apply what you learn. Don't make it academic, make it practice. >> The first thing I would say is take a look at a great Coursera course, like this one, and grasp the basics of AI. Get a fundamental lay of the land and understand what is involved in various types of AI systems. And perhaps find the niche that you're most interested in. And then, of course, look at academic programs that can help you to learn more about that specific area. And for students who are coming up through high school, for example, I would say definitely spend time focusing on math and science. Certainly, all disciplines are valuable, but your knowledge of mathematics and science will certainly pay off when you're working on AI systems. Because there are tons of opportunities and you'll need mathematics to really fully understand how the AI systems operate. So take your mathematics and your science seriously. And then look at Coursera and then beyond to other educational programs that can give you the basis you need to really jump into the industry. >> The field of AI has changed a lot in the last five years. No longer require a PhD in some kind of advanced mathematics or know some obscure programming language. You just have to know how to use the software APIs and understand the problem. For example, you can use Watson, and you just have to understand the problem and understand how the API works. But you still require some advance knowledge if you would like to build your own algorithm. >> So artificial intelligence machine learning, this is a very important field. It is the future of technology. Because it essentially opens up this whole new world of interaction with computers. A world that so far, we barely even knew existed. And it enables us to interact with computers in an implicit way. But what I would say is that while machine learning technology is important, it's not something that you can learn in isolation. Machine learning technology is not its own standalone subject. It's another algorithm in the toolbox of a plethora of algorithms that programmers will use in their applications, albeit a much more intelligent or a much more powerful algorithm than most. But still, it's another algorithm. So before you learn machine learning technology, it's very important to understand the actual programming and the technology that goes behind machine learning technology. Specifically because machine learning actually requires this kind of next generation of programming, hardware acceleration, so much more, that regular programming and regular algorithms don't necessarily require. So I'd really recommend making sure that, first of all, you are passionate about technology itself. If you are, continue, learn about programming, learn about coding, learn how to actually speak the computer's language. Learn about the computational thinking behind code. And then go ahead and learn about machine learning from the very, very basics. Start off with an API like IBM Watson to help you get an idea of what it's capable of. Then move on to more advanced, custom techniques and the math behind them. >> So AI is a fascinating field. But it's built on a huge number of foundational domains or foundational fields of study. So you really need to know your mathematics, you really need to know your probability statistics, your optimization. And you have to be able to program. You have to be able to take advantage of the tools that are out there to train these networks and understand how they work. So AI is really a broad field that requires a lot of specialists and a lot of specialization in a lot of areas. So one of the best things you can do is get started quickly. Start playing with some simple tasks. Try to identify digits or try to find cats on Internet pictures, right, things like this. These are wonderful challenges that can get you going in understanding what you need to learn about that field. >> Getting into AI now is like getting into anything to do with Internet, 20, 30 years ago. It's kind of the Renascence of software right now. It's possible now, it wasn't possible ten years ago. We have the computing technology. We have the computing power. We have the knowledge. And this is a field that will only grow. So I think you need to get in yesterday [MUSIC]
