Recently, Adobe had the pleasure of welcoming Dr. Andrew Ng, a globally recognized leader in artificial intelligence (AI), cofounder of Coursera, and CEO of landing.ai, to Adobe for a fireside chat with Scott Prevost, Adobe’s Vice President of Engineering, Sensei & Search. During their fireside chat, Andrew and Scott hit on a variety of topics as they pertain to the Evolution & Future of AI, which ranged from education, how customers should use customer data, and the implications AI and technology have on creating a better world. Here are the top takeaways from their discussion.
There’s tons of great science going on in the field of machine learning, but Andrew expects it to mature as an engineering discipline. He likens it to how bridges used to be built—in those early days of bridge engineering, there were wise old men with accumulated tribal knowledge and reliable intuition who trained their networks to build bridges. But as bridge engineering matured, it became systematic. Andrew hopes for the same shift to happen in machine learning—that instead of being driven by tribal knowledge and gut instincts, we’ll develop principles and practices that allow machine learning to become a systematic engineering discipline.
And while the university educational systems are doing a great job teaching more and more people new technology trends, it’s equally as important that corporations do the same and help their employees with continued learning. We need a different educational system to help people to always keep on learning new things, so that someone whose job is displaced can retool themselves and learn a new trade.
One of the most fundamental ideas in the evolution of the human race is humanity’s realization that you can program a computer. It’s such a big idea and we haven’t even finished sorting out all the implications of that yet. But it’s possible that the idea that you can teach a computer would be an equally fundamental idea. Today, we have giant computer science departments focused just on programming computers. In the future, we could have equally large numbers of students and faculty focused on teaching computers.