AI Salon

AI Salon

The AI salon is a semi-monthly gathering of the Stanford AI lab to discuss questions that go beyond the day-to-day research in AI. It is held in the style of 18th century French enlightenment-era salons, with no electronics, no whiteboard presentations, and an hourglass to keep time. The goal is to bring everyone together twice a month to contemplate the future of a fast-moving field. Past topics have included the ethics of autonomous driving, the role of theory in robotics, and intelligence augmentation. (Unless it is otherwise noted, AI Salon is only for current AI Lab members and their invited guests.)

Date
Title
Speaker
03/21/2014 Has IBM’s Watson driven forward research or was it primarily an engineering accomplishment?
04/11/2014 Are we overfitting to single-query datasets? (Gabor Angeli & Olga Russakovsky)
04/25/2014 Artificial Intelligence & Intelligence Augmentation (John Markoff & Arun Chaganty)
05/16/2014 Is interaction with the physical world necessary to acquire intelligence? (David Held & Oussama Khatib)
05/30/2014 AI & Neuroscience (Michelle Green & Ben Poole)
06/13/2014 AI in Movies (Andrej Karpathy & Vivek Srikumar)
09/26/2014 Machine Learning vs. Statistics (Will Fithian & Percy Liang)
10/10/2014 What should theory look like to be useful for robotics? (Leslie Kaelbling & Arun Chaganty)
10/17/2014 Phonemes and parts of speech: Are categories and symbolic structures a fundamental fact of language or fantasy of linguists? (Chris Manning & Andrew Ng)
11/07/2014 The Language of Food (Dan Jurafsky)
11/21/2014 The Ethics of Autonomous Driving (Silvio Savarese & Christian Gerdes)
12/05/2014 The End of Determinism (Stefano Ermon & Alex Ratner)
01/23/2015 Using neuroscience to build an AI (Jeff Hawkins and Surya Ganguli)
02/06/2015 The Turing Test (Will Hamilton and Fei-Fei Li)
02/20/2015 Robotics in the Air and Space (Mykel Kochenderfer & Marco Pavone)
03/06/2015 Robotics in the Air: Part II (Mykel Kochenderfer)
03/20/2015 AI100 Initiative and the Future of AI (Eric Horvitz)
04/07/2015 Dangers of AI (attendance by invitation only) (Elon Musk)
04/17/2015 Horizontal vs. Vertical Progress in AI (Matt Ginsberg & Jacob Steinhardt)
04/24/2015 Our Filtered Lives (Grace Muzny & Timnit Gebru)
05/08/2015 The History of AI (Ed Feigenbaum & Angel Chang)
05/15/2015 The Future of Human Labor (Michael Webb & Tudor Achim)
10/02/2015 AI’s Role in Human Disconnection (Timnit Gebru & Serena Yeung)
10/16/2015 Trust in AI Techniques/Algorithms (Maneesh Agarwala & Tum Chaturapruek)
10/30/2015 How to Build a Society in a World of Creative Destruction (Nils Nilsson & Russell Stewart)
11/06/2015 What’s Right About Machine Learning? (Sham Kakade & Yash Deshphande)
11/13/2015 AI and Health Care (David Sontag & Volodymyr Kuleshov)
12/04/2015 Artificial Intelligence — Boom or Menace? (Jerry Kaplan & John Markoff)
01/08/2016 AI & Genomics (Gill Bejerano & Irene Kaplow)
01/22/2016 AI and the Legal System (Tino Cuellar & Pratiksha Thaker)
01/29/2016 Gap Between Pattern Recognition and Intelligence (Michael Black & Amir Zamir)
03/11/2016 Pattern Recognition for Symbolic Reasoning: Deep Learning and Beyond (Tudor Achim & Jacob Steinhardt)
04/01/2016 The Role of Formal Logic in Semantics (Ray Mooney & Chris Manning)
04/15/2016 What Can AI Learn From How Babies Learn? (Jitendra Malik & Zayd Enam)
04/29/2016 The Master Algorithm for AI (Pedro Domingos & Volodymyr Kuleshov)
05/13/2016 AI and Accessibility (Joshua Miele & Timnit Gebru)
05/20/2016 Lessons from the Neocortex (Ray Kurzweil & Bharath Ramsundar)
05/27/2016 Diversity in AI (Serena Yeung & Arun Chaganty)
09/30/2016 Ai and the Economy (Kevin Leyton-Brown & Jacob Steinhardt)
10/07/2016 Software Engineering for Machine Learning (Peter Norvig & Aditya Grover)
11/04/2016 The Interaction of Future AI Algorithms and Hardware (Jen-Hsun Huang & Jim Fan)
11/18/2016 Challenges in Whole-Brain Simulation (Rosa Cao & Will Allen)
12/02/2016 Will Today’s AI Technology Be Able to Transform Healthcare? (Vijay S. Pande & Bharath Ramsundar)
01/20/2017 How Can We Make ML Interpretable (Anshul Kundaje & Avanti Shrikumar)
02/03/2017 AI That Understands Emotion (Noah Goodman & Sasha Sax)
02/17/2017 AI & Internet of Things (Frank Chen & Monica Lam)
03/03/2017 Adversarial Machine Learning (Ian Goodfellow & TBD)
03/17/2017 AI and Education (Emma Brunskill & Chris Piech)
04/21/2017 Media Portrayals of AI (Abigail See & Urvashi Khandelwal)
05/12/2017 Safe Reinforcement Learning (Animesh Garg & Andreas Krause)
05/26/2017 Issues as We Democratize AI (Pietro Perona & Phil Thomas)
10/13/2017 AI and Great Power Politics (Allan Dafoe & Ashwin Paranjape)
11/03/2017 Challenges of Human-Centered Assistive Robotics (Maja Matarić & Allison Okamura)
11/17/2017 Is General AI the Right Goal? (Aditya Grover & Steve Mussmann)
12/01/2017 AI in the Cloud (David Kenny & Fei-Fei Li)