Dr. David Ferrucci is one of the few people who have created a benchmark in the history of AI because when IBM Watson won Jeopardy we reached a milestone many thought impossible. I was very privileged to have Ferrucci on my podcast in early 2012 when we spent an hour on Watson's intricacies and importance. Well, it's been almost 8 years since our original conversation and it was time to catch up with David to talk about the things that have happened in the world of AI, the things that didn't happen but were supposed to, and our present and future in relation to Artificial Intelligence. All in all, I was super excited to have Ferrucci back on my podcast and hope you enjoy our conversation as much as I did. During this 90 min interview with David Ferffucci, we cover a variety of interesting topics such as: his perspective on IBM Watson; AI, hype and human cognition; benchmarks on the singularity timeline; his move away from IBM to the biggest hedge fund in the world; Elemental Cognition and its goals, mission and architecture; Noam Chomsky and Marvin Minsky's skepticism of Watson; deductive, inductive and abductive learning; leading and managing from the architecture down; Black Box vs Open Box AI; CLARA – Collaborative Learning and Reading Agent and the best and worst applications thereof; the importance of meaning and whether AI can be the source of it; whether AI is the greatest danger humanity is facing today; why technology is a magnifying mirror; why the world is transformed by asking questions.
David Ferrucci will deliver a keynote at the O'Reilly Artificial Intelligence Conference in NYC, June 26-29, 2017. His colleague Jennifer Chu-Caroll will also give a talk, "Beyond the state of the art in reading comprehension," at the same conference. Subscribe to the O'Reilly Data Show Podcast to explore the opportunities and techniques driving big data, data science, and AI. Find us on Stitcher, TuneIn, iTunes, SoundCloud, RSS. In this episode of the Data Show, I spoke with David Ferrucci, founder of Elemental Cognition and senior technologist at Bridgewater Associates.
David Ferrucci's official title is "IBM Fellow and Leader of the Semantic Analysis and Integration Department at IBM's T.J. Watson Research Center." But to the world, he's the genius behind Watson, the question-answering supercomputer system that bested two humans in a nationally televised broadcast of the popular game show Jeopardy! On Monday, Ferrucci delivered a fantastic keynote at the ACM's 2011 Federated Computing Research Conference in San Jose, CA. Ferrucci walked the audience -- nearly 2,000 computer scientists from around the country -- through the creation of Watson, from its initial conception in 2004 to its nationally televised victory this past February. "The story goes," he began, "that an IBM vice president was dining at a restaurant" when, suddenly, everyone around him got up and rushed toward a TV.
Things are going insanely well for people in computer science. I mean, our work is everywhere. Nearly every process imaginable is powered by a machine at the middle. The computer has transformed communication, retail, how we access information and how we navigate around the world. Things are even better in A.I. We are at the beginning of a renaissance of interest and utilization of intelligent systems in an ever-widening sphere of influence.
Machines can learn a lot of things--probably more than you can imagine. But can they learn common sense? At his company, Elemental Cognition, Ferrucci described how his AI team gave an advanced language program the sentence, "Zoey moves her plant to a sunny window. The AI program was tasked to complete the second sentence. In the real world, it's common knowledge that plants need light. Unfortunately, the AI program couldn't deliver this common observation. Instead, the AI completed the sentence by analyzing statistical patterns. It came up with these possible answers: "she finds something, not pleasant," "fertilizer is visible in the window," and "another plant is missing from the bedroom." This story is an entry point to myriad "common sense" issues that face today's AI. "Solving this problem is, we would argue, the single most important step towards taking AI to the next level.