In this episode, Byron and Manoj discuss cognitive computing, consciousness, data, DARPA, explainability, and superconvergence.
Byron Reese: This is Voices in AI, brought to you by Gigaom. Today my guest is Manoj Saxena. He is the Executive Chairman of CognitiveScale. Before that, he was the General Manager of IBM Watson, the first General Manager, in fact. He’s also a successful entrepreneur who founded and sold two venture-backed companies within five years. He’s the Founding Managing Director of the Entrepreneur’s Fund IV, a 100-million-dollar seed fund focused exclusively on cognitive computing. He holds an MBA from Michigan State University and a Master’s in Management Sciences from the Birla Institute of Technology and Science in Pilani, India. Welcome to the show, Manoj.
Manoj Saxena: Thank you.
You’re well-known for eschewing the term “artificial intelligence” in favor of “cognitive computing”; even your bio says cognitive computing. Why is that?
AI, to me, is the science of making intelligent systems and intelligent machines. Cognitive computing, and most of AI, is around replacing the human mind and creating systems that do the jobs of human beings. I think the biggest opportunity and it has been proven out in multiple research reports, is augmenting human beings. So, AI for me is not artificial intelligence; AI for me is augmented intelligence. It’s how you could use machines to augment and extend the capabilities of human beings. And cognitive computing uses artificial intelligence technologies and others, to pair man and machine in a way that augments human decision-making and augments human experience.
I look at cognitive computing as the application of artificial intelligence and other technologies to create—I call it the Iron Man J.A.R.V.I.S. suit, that makes every human being a superhuman being. That’s what cognitive computing is, and that was frankly the category that we started off when I was running IBM Watson as, what we believed, was the next big thing to happen in IT and in enterprise.
When AI was first conceived, and they met at Dartmouth and all that, they thought they could kind of knock it out in the summer. And I think the thesis was, Minsky later said, it was just like physics had just a few laws, and electricity had just a few laws, they thought there was just a couple of laws. And then AIs had a few false starts, expert systems and so forth, but, right now, there’s an enormous amount of optimism about it, of what we’re going to be able to do. What’s changed in the last, say, decade?