Google’s Fei-Fei Li said that “Artificial Intelligence (AI) can understand a photo and write description” at Women in Data Science (WiDS) Conference 2017. 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, Dr. Fei-Fei Li is briefly discussing the key ideas and the cutting edge advances in the
Google Artificial Intelligence (AI) Chief Scientist Professor Fei-Fei Li, Director at Stanford Artificial Intelligence Lab, talked about “Artificial Intelligence in Medicine” and how it could transform the workflow in healthcare and the way we diagnose, treat and prevent disease. I actually feel inadequate to be in this audience. I know very little about medicine. So I’m here to learn and interact with you. My talk title is “Guardian Angels: Towards Artificial Intelligence assisted
Google gets aggressive in Artificial Intelligence with new acquisitions, new products, new APIs, a 30 billion platform and new hires like A.I. guru Fei Fei Li, now Chief Scientist of Google Cloud and Machine Learning. “My name is Fei Fei Li, and the chief scientist of Google Cloud Artificial Intelligence and Machine Learning. In Google’s code word, I’m still a noogler and it’s quite an honor and privilege to be on the stage to share with
Mike Abbott, Partner of Kleiner Perkins Caufield & Byers, sits with Dr. Fei Fei Li, Associate Professor in the Computer Science Department at Stanford, and the Director of the Stanford Artificial Intelligence Lab and the Stanford Vision Lab. “I have been at Google for two months and it is actually the first time I took a deep dive into the industry and a very fortunate to have that sabbatical opportunity.
When a very young child looks at a picture, she can identify simple elements: “cat,” “book,” “chair.” Now, computers are getting smart enough to do that too. What’s next? In a thrilling talk, computer vision expert Fei-Fei Li describes the state of the art — including the database of 15 million photos her team built to “teach” a computer to understand pictures — and the key insights yet to come.