About AI Salon
AI Salon is a roughly bi-weekly event on Fridays where the AI Lab gathers to discuss high-level topics in AI and machine learning. The goal is to encourage ourselves to think beyond our individual day-to-day research, and better see how our work fits into the long-term trajectory of scientific progress, and into society as a whole. Each Salon has a different topic for discussion, which is led by two speakers: typically one expert guest, and one AI Lab member. We hold the event in the spirit of Enlightenment-era salons, with no electronics or whiteboard allowed: only free-ranging discussion among attendees, starting with a 10-minute opening statement from the two speakers.
For the 2020-2021 academic year, Rose Wang (rewang@stanford.edu) and Nancy Xu (Stanford
Time and Place
AI Salon is typically held in Room 219 (2nd floor open area) of the Gates Computer Science building. The event is held from 4-5pm, with refreshments served from 3:45pm.
Attendance Policy
AI Salon is open to all current Stanford students, postdocs and faculty. We particularly welcome those who can bring interdisciplinary perspectives to the event. Due to space limitations, any other attendees must be invited by a current member of the AI Lab.
Occasionally, AI Salon is opened up to the public – for example the AI Salon with Yann LeCun on February 2, 2018. However, this is an exception to the usual format.
Mailing List
AI Salon announcements are automatically sent to the ai-all@cs.stanford.edu mailing list. If you would like to receive notifications about upcoming AI Salon events and are not already on the ai-all list, please join the ai-salon-announce@lists.stanford.edu mailing list.
Note: you can join the ai-salon-announce even without a @stanford.edu email address. Subscribing to the ai-salon-announce list is fully automatic; follow the link and follow the instructions. You do not need to email anyone to get on the ai-salon-announce list.
|
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 and the Brain | (Liqun Luo & Fei-Fei Li) |
| 01/12/2018 | AI in the Cloud | (Ruchir Puri & Fei-Fei Li) |
| 02/02/2018 | What innate priors should we build into the architecture of Deep Learning systems? | (Yann LeCun & Chris Manning) |
| 03/02/2018 | AI, Employment and Inequality | (Erik Brynjolfsson & Trevor Standley) |
| 03/16/2018 | Should AI researchers divert efforts away from competitions toward controlled experiments? | (Pat Langley & Andrey Kurenkov) |
| 04/06/2018 | How can we make AI more accessible? | (Rachel Thomas & Mark Whiting) |
| 05/11/2018 | How can AI cure cancer? | (Marty Tenenbaum & Kim Branson) |
| 05/25/2018 | Learning to learn | (Ilya Sutskever & Amir Zamir) |
| 10/19/2018 | Ethics in ML Systems | (Ben Recht & Emma Brunskill) |
| 11/02/2018 | Autonomous Driving – how close are we? | (Lex Frideman & Marco Pavone & Sarah Thornton) |
| 11/09/2018 | Best Practices for Ethical AI Research | (Timnit Gebru & Margaret Mitchell) |
| 11/15/2018 | Deep RL for real world systems | (Sergey Levine & Mykel Kochenderfer) |
| 12/07/2018 | AI and the Future of Work | (Kai-Fu Lee & Susan Athey & Erik Brynjolfsson) |
| 02/01/2019 | Countering Hype, Anthropomorphism, and Fear-mongering in AI | (Jerry Kaplan & William J Clancet) |
| 02/08/2019 | AI and Defense | (Lt. Col Kevin Childs & Lt. Col. Ryan Kappedal) |
| 02/22/2019 | AI Research in Industry and Academia | (Wojciech Zaremba & Ludovic Righetti) |
| 03/08/2019 | Flexible ML Systems | (Jeff Dean & Chris Re) |
| 03/14/2019 | Troubling Trends in AI Conferences | (Zacahary Lipton & Animesh Garg) |
| 04/12/2019 | Societal Impacts of Deep Fakes | (Maneesh Agrawala & Jeff Hancock) |
| 04/26/2019 | AI and Journalism | (Katyanna Quach & Cade Metz) |
| 05/17/2019 | Best Practices for Dual Use AI Research | Amanda Askell & Miles Brundage & Megan Palmer & Allison Berke |
| 05/21/2019 | Diversity & Inclusion in STEM & AI | (Barbara Grosz & Fei-Fei Li) |
| 05/24/2019 | AI Art | (Aaron Hertzman & Nolan Lem & Holly Grimm) |
| 10/18/2019 | AI & Government | Dan Ho & Shireen Santosham |
| 11/1/2019 | AI & Climate Change | David Rolnick, Sharon Zhou & Cindi Thompson |
| 11/15/2019 | AI & Legal Responsibility | Bryan Casey & Jerry Kaplan |
| 11/22/2019 | Has the AI Revolution Come Yet? | Emma Brunskill & Michael Jordan |
| 12/6/2019 | AI & Medicine | Nigam Shah & Elizabeth Mormino |
| 1/10/2020 | AI & the Mind | Barbara Tversky & Fei-Fei Li |
| 1/24/2020 | Unique Challenges of Physical AI Systems | Manuela Veloso & Dorsa Sadigh |
| 2/28/2020 | Future of NLP | Michael Auli & Chris Manning |