Dr. Fei-Fei Li, the Chief Scientist of AI/ML at Google joins Melanie and Mark this week to talk about how Google enables businesses to solve critical problems through AI solutions. We talk about the work she is doing at Google to help reduce AI barriers to entry for enterprise, her research with Stanford combining AI and health care, where AI research is going, and her efforts to overcome one of the key challenges in AI by driving for more diversity in the field.
Dr. Fei-Fei Li
Dr. Fei-Fei Li is the Chief Scientist of AI/ML at Google Cloud. She is also an Associate Professor in the Computer Science Department at Stanford, and the Director of the Stanford Artificial Intelligence Lab. Dr. Fei-Fei Li’s main research areas are in machine learning, deep learning, computer vision and cognitive and computational neuroscience. She has published more than 150 scientific articles in top-tier journals and conferences, including Nature, PNAS, Journal of Neuroscience, CVPR, ICCV, NIPS, ECCV, IJCV, IEEE-PAMI, etc. Dr. Fei-Fei Li obtained her B.A. degree in physics from Princeton in 1999 with High Honors, and her PhD degree in electrical engineering from California Institute of Technology (Caltech) in 2005. She joined Stanford in 2009 as an assistant professor, and was promoted to associate professor with tenure in 2012. Prior to that, she was on faculty at Princeton University (2007-2009) and University of Illinois Urbana-Champaign (2005-2006). Dr. Li is the inventor of ImageNet and the ImageNet Challenge, a critical large-scale dataset and benchmarking effort that has contributed to the latest developments in deep learning and AI. In addition to her technical contributions, she is a national leading voice for advocating diversity in STEM and AI. She is co-founder of Stanford’s renowned SAILORS outreach program for high school girls and the national non-profit AI4ALL. For her work in AI, Dr. Li is a speaker at the TED2015 main conference, a recipient of the IAPR 2016 J.K. Aggarwal Prize, the 2016 nVidia Pioneer in AI Award, 2014 IBM Faculty Fellow Award, 2011 Alfred Sloan Faculty Award, 2012 Yahoo Labs FREP award, 2009 NSF CAREER award, the 2006 Microsoft Research New Faculty Fellowship and a number of Google Research awards. Work from Dr. Li’s lab have been featured in a variety of popular press magazines and newspapers including New York Times, Wall Street Journal, Fortune Magazine, Science, Wired Magazine, MIT Technology Review, Financial Times, and more. She was selected as a 2017 Women in Tech by the ELLE Magazine, a 2017 Awesome Women Award by Good Housekeeping, a Global Thinker of 2015 by Foreign Policy, and one of the “Great Immigrants: The Pride of America” in 2016 by the Carnegie Foundation, past winners include Albert Einstein, Yoyo Ma, Sergey Brin, et al.
Cool things of the week
Terah Lyons appointed founding executive director of Partnership on AI article & site
Fully managed export and import with Cloud Datastore now generally available blog
How Color uses the new Variant Transforms tool for breakthrough clinical data science with BigQuery blog & repo
Google Cloud and NCAA team up for a unique March Madness copmetition hosted on Kaggle blog
AI4All site, they are hiring and how to become a mentor
Cloud AI site
Cloud AutoML site
Cloud Vision API site and docs
Cloud Speech API site and docs
Cloud Natural Language API site and docs
Cloud Translation API site and docs
Cloud Machine Learning Engine docs
TensorFlow site, github and Dev Summit waitlist
ImageNet site & Kaggle ImageNet Competition site
Stanford Medicine site & Stanford Children’s Hospital site
Additional sample resources on Dr. Fei-Fei Li:
Stanford Vision Lab site
Fei-Fei Li | 2018 MAKERS Conference video
Google Cloud’s Li Sees Transformative Time for Enterprise video
Past, Present and Future of AI / Machine Learning Google I/O video
Research Symposium 2017 - Morning Keynote Address at Harker School video
How we’re teaching computers to understand pictures video
Melinda Gates and Fei-Fei Li Want to Liberate AI from “Guy with Hoodies” article
Dr. Fei-Fei Li
Question of the week
Where can I learn more about machine learning?
Listing of some of the many resources out there in no particular order:
How Google does Machine Learning coursera
Machine Learning with Andrew Ng coursera and Deep Learning Specialization coursera
Machine Learning with John W. Paisley edx
Machine Learning Columbia University edx
International Women’s Day March 8th
International Women’s Day site covers information on events in your area, and additional resources.
Sample of recent women in tech events to keep on radar for next year:
Women Techmakers site
Lesbians Who Tech site
Women in Data Science Conference site
Where can you find us next?
Mark will be at the Game Developer’s Conference | GDC in March.