The Applied Machine Learning Days channel features talks and performances from the Applied Machine Learning Days. AMLD is one of the largest machine learning & AI events in Europe, focused specifically on the applications of machine learning and AI, making it particularly interesting to industry and academia. Next edition will be held in January 25-28, 2020 @ EPFL, Lausanne, Switzerland. Follow AMLD on Twitter: on LinkedIn: on Facebook: AMLD Website:
Jeff Dean discusses the future of artificial intelligence and deep learning. This talk highlights Google research projects in healthcare, robotics, and in developing hardware to bring deep learning capability to smaller devices such as smart phones to enable solutions in remote and under-resourced locations. This talk was part of the AI in Real Life series presented by the Institute for Computational and Mathematical Engineering at Stanford University in Autumn 2018.
Jeff Dean, Head of Google Brain talks about using deep learning to solve challenging problems at the AI/ML Workshop on research and practice in India. Find all speaker decks for the workshop at: Subscribe to the Google Developers India channel: For more updates, follow us at:
Filmmaker Robin Hauser is a proven storyteller of complex topics. In her award-winning documentary, “Code—Debugging the Gender Gap” she examined the dearth of women in computer coding. Now, in her latest film, “Bias”, Robin posits compelling questions: how have primal human survival instincts made racial and gender bias an innate part of ourselves; and with the rise of machine learning, with increasing reliance on AI, can we protect Artificial Intelligence from our inherent biases? Her film is an engrossing exploration and clarion call that will frighten and also enlighten. Today’s Guest: Robin Hauser @biasfilm Interviewer: Jim Kamp @kampjames
On Tuesday, September 25th, Jeff Dean, Head of Google AI and Google Brain, visited ( at the German Cancer Research Center in Heidelberg: For the past seven years, the Google Brain team has conducted research on difficult problems in artificial intelligence, on building large-scale computer systems for machine learning research, and, in collaboration with many teams at Google, on applying our research and systems to many Google products. Our group has open-sourced the TensorFlow system, a widely popular system designed to easily express machine learning ideas, and to quickly train, evaluate and deploy machine learning systems. We have also collaborated closely with Google’s platforms team to design and deploy new computational hardware called Tensor Processing Units, specialized for accelerating machine learning computations. In this talk, I’ll highlight some of our research accomplishments, and will relate them to the National Academy of Engineering’s Grand Engineering Challenges for the 21st Century, including the use of machine learning for healthcare, robotics, and engineering the tools of scientific discovery. I’ll also cover how machine learning is transforming many aspects of our computing hardware and software systems. This talk describes joint work with many people at Google.