conference overview
Technology has always been in the service of augmenting human capabilities. AI is our way of doing for mental work what the wheel, the plow, and the steam engine did for physical labor. Yet machine learning has the capability of going its own way, whether it’s Facebook bots inventing their own language or swarms of drones making collective decisions that can’t be attributed to any one node. What is the current state of the art, and how can we best harness its growing capabilities?

Topics to be explored
Smart everything. Data analysis. Human understanding. Human learning (e.g., “Algorithms to Live By”). Discovery. Programmable matter. Natural language processing. Visual recognition. TPUs and machine learning APIs. New networks and surveillance capitalism. Prediction. Neural Silicon Hybrids. Robot self-awareness. Complexity. AI and the future of work.

Speakers to date
Noam Brown, Carnegie Mellon University — Libratus: the winning poker bot
Greg D’Alba & Steve DeAngelis, VIDL — Fighting fake news with AI and blockchain
Paul Daugherty, Accenture — Reimagining work in the age of AI (tentative)
David Gunning, DARPA — The Explainable AI project (tentative)
Guy Hoffman, Cornell — A handmade approach to social robotics
Jeff Jonas, Senzing — Big data and the General Data Protection Regulation (GDPR)
Tim Kraska, MIT — Indexes as models
Gary Marcus, NYU — Deep learning: a critical appraisal (tentative)
David Prior, Xuvasi — Reorganizing business processes using applied intelligence
Simon Tong, FiveAI — Autonomous vehicles without maps
Bo Zhu, Harvard —Image reconstruction from MRIs to radio astronomy: a unified framework