ImageNet has become one of the most influential visual datasets in the fields of Deep Learning and AI. More than 14 million photographs were gathered through a benchmarking effort that propelled the outbreak of Computer Vision and its wide range of applications such as surveillance, phone filters, medical imaging, biometry and autonomous cars. ImageNet is organised through 21,000 categories that are still being used today to train computational models. In September 2019, ImageNet creator Fei-Fei Li gave a talk at The Photographers’ Gallery as part of a 10th anniversary of ImageNet party, talking through the events and key people that led to the datasets creation. The event also featured a series of activities and presentations to showcase the impact of ImageNet, including a discussion by Dr. Alan Blackwell and a performace on annotation by Nicolas Malevé. https://thephotographersgallery.org.uk/imagenetbirthday
The stories of three components needed for AI to go from science fiction to practical fact… combined with the stories of three people who led major early projects in these three areas before it was cool: 1) Algorithms for AI 2) Datasets for AI 3) Platforms for AI Check out the rest of the MFML course playlist here: http://bit.ly/mfml_000​ If you prefer to learn in bulk, you can get access to longer chunks of the course by signing up for the newsletter at http://decision.substack.com Don’t forget to hit subscribe+notify! If you found this useful or enjoyable, the best way to say thank you is by sharing it.
The more human-like artificial intelligence becomes, the more we understand about how our brains actually work. Through that discovery process, researchers are identifying ways to design artificial intelligence in ways that factor in the safety and morality of their potential impact. Greylock general partner Reid Hoffman interviews Dr. Fei-Fei Li, the co-director of Stanford’s Institute for Human-Centered AI, and Mira Murati, the CTO of OpenAI. In this interview, they discuss how technology like GPT-3 is being trained with human safety in mind, and how academia, industry, and policymakers are coming together to ensure AI is developed and deployed in ways that benefit all. This interview took place during Greylock’s Intelligent Future event, a daylong summit featuring experts and entrepreneurs working in artificial intelligence. You can read the transcript from this interview here: https://greylock.com/greymatter/ais-human-factor/
John Etchemendy, Provost Emeritus, and Patrick Suppes Family Professor in the School of Humanities and Sciences, Stanford University; Co-Director, Stanford Institute for Human-Centered Artificial Intelligence Fei-Fei Li, Sequoia Professor, Computer Science Department; Co-Director, Stanford Institute for Human-Centered Artificial Intelligence Rob Reich, Professor of Political Science, Stanford University; Associate Director, HAI
On Ep.20 of The Robot Brains Podcast, Pieter Abbeel is joined by Fei-Fei Li. Her legendary status in the field of AI precedes her on our podcast because she’s been discussed frequently by many of our previous guests – many of whom are her former students. She is the Sequoia Capital Professor of Computer Science at Stanford University, Co-Director of the Stanford Institute for Human-Centred Artificial Intelligence (Stanford HAI). She was also the leading scientist and instigator of ImageNet, arguably the most momentous episode in the history of AI which allowed vision systems and neural nets to break out of academia and into real industries all over the world. On the show we talk to Fei-Fei about her illustrious career in academia, her involvement in the ImageNet and AlexNet breakthroughs, and her new, deeply personal reasons for focusing her latest work on transforming healthcare with AI. What’s in this episode: 00:00 Introductions 03:49 From the dry cleaners to AI 05:20 An education: Princeton, Physics and Academia 10:59 Fei-Fei’s role in AlexNet/ImageNet 27:34 The 2012 Competition 40:17 A new journey into Healthcare AI 49:16 Ageing and Care with AI 51:38 Stanford HAI 55:00 AI and Public Policy 1:01:42 The US National AI Research Resource Taskforce 1:05:40 Is the US still a leader for AI academia? 1:07:43 The future of AI Links: Fei-Fei’s Twitter: https://twitter.com/drfeifei Fei-Fei’s LinkedIn: https://www.linkedin.com/in/fei-fei-li-4541247/ Fei-Fei’s Academic Profile: https://profiles.stanford.edu/fei-fei-li Fei-Fei’s Wikipedia: https://en.wikipedia.org/wiki/Fei-Fei_Li Subscribe and listen to our podcast today: Spotify: https://spoti.fi/3CAcyWx Amazon: https://amzn.to/3xy3PjK Acast: https://bit.ly/3jJDYR8 Google: https://bit.ly/3yE2Ob3 Apple: https://apple.co/3vRqBlV [More]
Fei-Fei Li is professor of computer science and co-director of the Stanford University Human-Centered AI Institute (HAI). A pioneering expert in AI, inventor of ImageNet, and thought leader, Dr. Li challenges us to be the stewards of technology to serve humanity at its broadest and most diverse extent. Dr. Li has also been recognized as a 2016 Global Thinker by Foreign Policy and formerly served as the vice president of AI and machine learning at Google Cloud. In this session, Dr. Li will discuss the transformative potential that AI and machine learning pose for society from her unique perspective as a scientist and an ethical leader who advocates for future technologies to incorporate an understanding of how to augment, not replace, elements of the human experience. Support contributed by: Elsevier
Learn why Fei-Fei Li, computer scientist and co-director of the Stanford Institute for Human-Centered Artificial Intelligence, was the Further Award recipient at the 2019 National Geographic Explorers Festival. Considered one of the top artificial intelligence researchers, her natural curiosity of the human world drives her to push the boundaries of AI. Photography by Philip Montgomery. WHO WE ARE The National Geographic Society is a global nonprofit organization that uses the power of science, exploration, education, and storytelling to illuminate the wonder of the world, define critical challenges, and catalyze action to protect our planet. Since 1888, National Geographic has pushed the boundaries of exploration, investing in bold people and transformative ideas, providing more than 14,000 grants for work across all seven continents, reaching 3 million students each year through education offerings, and engaging audiences around the globe through signature convenings and content. www.nationalgeographic.org MORE VIDEOS FOR YOU “Discovery in the Technological Age” https://youtu.be/QjpEhf5vPBw “Meet the Sumatran Rhino” https://youtu.be/4X2jl3kWRY8 WHERE TO FIND US On YouTube: https://www.youtube.com/c/insidenatgeo On Facebook: https://www.facebook.com/InsideNatGeo/ On Twitter: https://www.twitter.com/InsideNatGeo On Instagram: https://www.instagram.com/insidenatgeo
Original video: https://www.youtube.com/watch?v=Mu3scWZvZKo Cut at 7:20 and 12:52. My answer here: https://medium.com/@mostafab/how-ai-startups-must-compete-with-google-reply-to-fei-fei-li-35dda19c8a3f
If AI is to serve the collective needs of humanity, how should machine intelligence be built and designed so that it can understand human language, feelings, intentions and behaviors, and interact with nuance and in multiple dimensions? Stanford University computer science professor Dr. Fei-Fei Li and Greylock general partner Reid Hoffman discuss the ethical considerations researchers, technologists and policymakers should make when developing and deploying AI. This episode was recorded as part of Greylock’s Iconversations virtual speaker series. You can also find the podcast and transcript of this discussion here: greylock.com/greymatter/fei-fei…human-centered-ai/
Support my work on Patreon: https://www.patreon.com/whatsai A curated list of the latest breakthroughs in AI by release date with a clear video explanation, link to a more in-depth article, and code. Full list on Medium: https://medium.com/towards-artificial-intelligence/2020-a-year-full-of-amazing-ai-papers-a-review-c42fa07aff4b The GitHub repository: https://github.com/louisfb01/Best_AI_paper_2020 ►Subscribe to my newsletter: http://eepurl.com/huGLT5 Interested in computer vision? Here is my top 10 CV research papers of 2020: https://youtu.be/CP3E9Iaunm4 AI Debate 2 – Hosted by Montreal AI: https://youtu.be/VOI3Bb3p4GM Chapters: 0:00 Hey! Tap the Thumbs Up button and Subscribe. You’ll learn a lot of cool stuff in 2021, I promise. 0:28 2020, A year in review 9:06 Where do you want AI to go? #StateOfAI #ArtificialIntelligence #AI2020
With the current pandemic accelerating the revolution of AI in healthcare, where is the industry heading in the next 5-10 years? What are the key challenges and most exciting opportunities? These questions will be answered by HAI’s Co-Director, Fei-Fei Li and the Founder of DeepLearning.AI, Andrew Ng in this fireside chat virtual event.  This event will be moderated by Curtis Langlotz, Director of the Center for Artificial Intelligence in Medicine and Imaging (AIMI Center). If you’d like to submit and upvote questions for our speakers, please register for the Q&A + General access ticket. Submit your questions through the Slido link in your order confirmation email.
On May 11, Twitter announced that it had added former Google VP and A.I. guru Fei-fei Li to its board of directors, because of her “unparalleled expertise in engineering, computer science and artificial intelligence”. It was reported that Twitter took this action “as it grapples with coronavirus misinformation”. This news immediately sparked a lot of discussion and concerns, especially among overseas Chinese people, including myself. The main reason is because of Fei-fei Li’s ties with China, or the Chinese Communist Party, the CCP. Some call her “Red Expert”. Today I’d like to talk about some deeper ties she has with the CCP that many people may not be aware of yet, as well as why we should be very worried. 免翻牆短鏈接:https://is.gd/39xpyn,https://is.gd/SSJu6Y Truth saves lives. Please support! 真相能救命,敬請支持! Subscribestar 會員頻道: https://www.subscribestar.com/inconvenient-truths-by-jennifer-zeng GoFundme 衆籌網:https://www.gofundme.com/f/telling-the-truth-about-covid19-ccp-amp-china Patreon 網站:https://www.patreon.com/InconvenientTruths Paypal 捐款帳號:https://www.paypal.me/JenniferZeng97 ************************* Jennifer’s Twitter Account 曾錚推特:https://twitter.com/jenniferatntd Jennifer’s Facebook Page 曾錚臉書粉絲專頁 :https://www.facebook.com/pg/jenniferzeng97/ Jennifer’s website 曾錚個人網站 :https://www.jenniferzengblog.com Email 電子郵件:heavenlyriver9707@gmail.com Jennifer’s Bio 曾錚簡歷 :https://www.jenniferzengblog.com/about/ #FeifeiLi #Twiter #CCPTies
Fei-Fei Li, Stanford Artificial Intelligence Lab, Vision Lab
Abstract: Artificial intelligence has begun to impact healthcare in areas including electronic health records, medical images, and genomics. But one aspect of healthcare that has been largely left behind thus far is the physical environments in which healthcare delivery takes place: hospitals, clinics, and assisted living facilities, among others. In this talk I will discuss our work on endowing healthcare spaces with ambient intelligence, using computer vision-based human activity understanding in the healthcare environment to assist clinicians with complex care. I will first present pilot implementations of AI-assisted healthcare spaces where we have equipped the environment with visual sensors. I will then discuss our work on human activity understanding, a core problem in computer vision. I will present deep learning methods for dense and detailed recognition of activities, and efficient action detection, important requirements for ambient intelligence, and I will discuss these in the context of several clinical applications. Finally, I will present work and future directions for integrating this new source of healthcare data into the broader clinical data ecosystem. Bio: Fei-Fei Li is a Professor in the Computer Science Department at Stanford, and the Director of the Stanford Artificial Intelligence Lab. In 2017, she also joined Google Cloud as Chief Scientist of AI and Machine Learning. Dr. Li’s main research areas are in machine learning, deep learning, computer vision and cognitive and computational neuroscience. She has published almost 200 scientific articles in top-tier journals and conferences, including Nature, PNAS, Journal of Neuroscience, New England Journal of Medicine, CVPR, [More]
Title: ImageNet: Where Have We Been? Where Are We Going? Speaker: Fei-Fei Li Date: 9/21/2017 Abstract It took nature and evolution more than 500 million years to develop a powerful visual system in humans. The journey for AI and computer vision is about half of a century. In this talk, Dr. Li will briefly discuss the key ideas and the cutting edge advances in the quest for visual intelligences in computers, focusing on work done to develop ImageNet over the years. Speaker Bio Fei-Fei Li is currently on sabbatical as the Chief Scientist of AI/ML at Google Cloud. She is an Associate Professor in the Computer Science Department at Stanford, and the Director of the Stanford Artificial Intelligence Lab. Her 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. Li obtained her B.A. degree in physics from Princeton with High Honors, and her Ph.D. degree in electrical engineering from the California Institute of Technology (Caltech). 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 and University of Illinois Urbana-Champaign. 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 [More]
SUBSCRIBE: http://www.youtube.com/user/kaggledotcom?sub_confirmation=1&utm_medium=youtube&utm_source=channel&utm_campaign=yt-sub About Kaggle: Kaggle is the world’s largest community of data scientists. Join us to compete, collaborate, learn, and do your data science work. Kaggle’s platform is the fastest way to get started on a new data science project. Spin up a Jupyter notebook with a single click. Build with our huge repository of free code and data. Stumped? Ask the friendly Kaggle community for help. Follow Kaggle online: Visit the WEBSITE: http://www.kaggle.com/?utm_medium=youtube&utm_source=channel&utm_campaign=yt-kg Like Kaggle on FACEBOOK: http://www.facebook.com/kaggle?utm_medium=youtube&utm_source=channel&utm_campaign=yt-fb Follow Kaggle on TWITTER: http://twitter.com/kaggle?utm_medium=youtube&utm_source=channel&utm_campaign=yt-tw Check out our BLOG: http://blog.kaggle.com/?utm_medium=youtube&utm_source=channel&utm_campaign=yt-blog Connect with us on LINKEDIN: http://www.linkedin.com/company/kaggle?utm_medium=youtube&utm_source=channel&utm_campaign=yt-lkn Advance your data science skills: Take our free online courses: http://www.kaggle.com/learn/overview?utm_medium=youtube&utm_source=channel&utm_campaign=yt-learn Get started with Kaggle Kernels: http://www.kaggle.com/docs/kernels?utm_medium=youtube&utm_source=channel&utm_campaign=yt-krnl Download clean datasets from Kaggle: http://www.kaggle.com/docs/datasets?utm_medium=youtube&utm_source=channel&utm_campaign=yt-datast Sign up for a Kaggle Competition: http://www.kaggle.com/docs/competitions?utm_medium=youtube&utm_source=channel&utm_campaign=yt-comps Explore the Kaggle Public API: http://www.kaggle.com/docs/api?utm_medium=youtube&utm_source=channel&utm_campaign=yt-docs Fireside Chat with Dr. Fei-Fei Li & Anthony Goldboom | Kaggle https://www.youtube.com/watch?v=ElDWanLOc4c Kaggle http://www.youtube.com/user/kaggledotcom
Bringing together thought leaders in large-scale data analysis and technology to transform the way we diagnose, treat and prevent disease. Visit our website at http://bigdata.stanford.edu/.
It takes nature and evolution more than five hundred million years to develop a powerful visual system in humans. The journey for AI and computer vision is about fifty years. In this talk, I will briefly discuss the key ideas and the cutting edge advances in the quest for visual intelligences in computers. I will particularly focus on the latest work developed in my lab for both image and video understanding, powered by big data and the deep learning (a.k.a. neural network) architecture. Fei-Fei Li, Chief Scientist, AI/ML, Google Cloud, Professor of Computer Science, Stanford University Director, Artificial Intelligence Lab
Fei-Fei Li came to the U.S. from China at 16 with a love for science and she never looked back. Educated at Princeton and Caltech, her early work in robotics revolutionized machine learning and AI. Her focus on inclusion in tech careers and diversity in what we teach machines suggests that tomorrow’s robots won’t be sexist.
Stanford professor, Fei-Fei Li, discusses her work teaching computers to “see” images and to understand them as humans do in her eDay 2012 presentation “Computers that See” at Stanford Engineering.
Teaching Computers to See Dr. Fei-Fei Li is currently chief scientist of AI/ML at Google Cloud, associate professor in the computer science department at Stanford, and the director of the Stanford Artificial Intelligence Lab and the Stanford Vision Lab. SATURDAY, APRIL 15, 2017 | NICHOLS HALL | UPPER SCHOOL CAMPUS
We have security cameras everywhere, but they still can’t alert us when a child is drowning, says Fei-Fei Li, associate professor of computer science at Stanford. While humans have used vision to make better sense of the world for millions of years, our machines and computers are still in the dark ages. At “The Future of Artificial Intelligence” partner event of the 2016 Global Entrepreneurship Summit, she explains that the daunting task ahead of us is to develop artificial intelligence algorithms to allow our computers to make smarter use of content in images and videos.