Co-Founder & CEO
VP of the Associative Computing
Twenty Billion Neurons
Software Development Engineer
Co-Founder & CTO
Co-Founder & CEO
VP of AI and Machine Learning
Co-Founder & CEO
Senior Technical Lead for Deep Learning
Director of Machine Learning Research
CEO & Founder
Facebook AI Research (FAIR)
Director of Machine Learning
Stanford Computer Vision Group
VP of Applied Deep Learning Research
Ian Goodfellow is a Senior Research Scientist on the Google Brain team. He studies new methods for improving neural networks. Recent publications include: Adversarial Autoencoders; Net2Net: Accelerating Learning via Knowledge Transfer; and Explaining and Harnessing Adversarial Examples.
"To understand deep learning in the context of genetic disease, you need to understand shallow learning first. Shallow learning relates mutations to diseases by looking for mutations that commonly occur in patients with a disease. It’s a commonly used method", Brendan Frey, Deep Genomics.
Despite the noisy hype, which sometimes distracts, machine intelligence is already being used in several valuable ways. Machine intelligence already helps us get the important business information we need more quickly, monitors critical systems, feeds our population more efficiently, reduces the cost of health care, detects disease earlier, and so on.
Karpathy and colleagues have created artificial intelligence software capable of recognizing and describing the content of photographs and videos with far greater accuracy than ever before, sometimes even mimicking human levels of understanding.
Ofir Nachum will be sharing his latest work from the recently published paper: 'Improving Policy Gradient by Exploring Under-appreciated Rewards' - presents a novel form of policy gradient for model-free reinforcement learning (RL) with improved exploration properties.
Preferred Networks took part in the 2016 Amazon Picking Challenge and used Deep Learning algorithms & Chainer, a Python-based Open Source Deep Learning framework, on input data obtained from image and 3D location sensors for object detection and localization.
Sergey Levine, Assistant Professor at UC Berkeley has been listed as one of the 35 Innovators Under 35 by MIT Technology Review for his work creating a robot that supervises its own learning. “It’s reverse-engineering its own behavior,” Levine said.
A Brief Overview of Deep Learning from Google's Ilya Sutskever. What’s so special about deep learning? Why does it work now, and how does it differ from neural networks of old? How will it impact your industry? Hear more from Ilya at the summit.
Tony Jebara and colleagues at Columbia University will work with oceanographers to understand what has caused an unusual plankton-like species to rapidly invade the Arabian Sea food chain, threatening fisheries that sustain more than 100 million people living at the sea's edge.
A new technology developed at Berkeley from a team including Alexei Efros, claims to be able to create photorealistic images from just a few simple digital brush strokes. It uses machine learning to edit images based on an understanding of what looks real and what doesn't.
Discover advances in deep learning algorithms and methods from the world's leading innovators. Learn from industry experts in speech & pattern recognition, neural networks, image analysis and NLP. Explore how deep learning will impact healthcare, manufacturing, search & transportation.
The summit will showcase the opportunities of advancing trends in deep learning and their impact and successful applications in business. Where do the challenges still lie in research and application? Learn the latest technological advancements & industry trends from a global line-up of experts.
A unique opportunity to interact with industry leaders, influential technologists, data scientists & founders leading the deep learning revolution. Learn from & connect with 450+ industry innovators sharing best practices to advance the smart artificial intelligence revolution.
Deep Learning Algorithms
Natural Language Processing
A block from Market Street in the Downtown neighborhood of SoMa, the Park Central is a contemporary hotel, a 2-minute walk from Montgomery Street BART/Muni Metro station, and a 9-minute walk from Union Square.
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Chief Knowledge Officer, NASA
"Excellent event. Good combination of highly technical and broader presentation that gave me a good understanding of the current state and potential of the Deep Learning" RE•WORK Deep Learning Summit San Fran 2015
Director of IoT Market Strategy, Xively
"'I’ve been to countless IoT events, and this was hands down one of the most interesting. It was nice to see actual people building actual connected products giving their perspective." RE•WORK IoT Summit Boston 2015
Future & Emerging Technologies Unit
"RE•WORK provided a unique mix of technology, from the exploration of latest scientific findings to startups that can make them a reality" RE•WORK Technology Summit London 2014
27 April 2017, Singapore
The Deep Learning Summit is the next revolution in artificial intelligence. Explore the impact of image & speech recognition as a disruptive trend in business and industry. How can multiple levels of representation and abstraction help to make sense of data such as images, sound, and text. Hear the latest insights and technology advancements from industry leaders, startups and researchers.
27 April 2017, Singapore
The Deep Learning in Finance Summit is a multidisciplinary event bringing together data scientists, engineers, CTOs, CEOs & leading financial corporations to explore the impact of deep learning in the financial sector. Applications include identifying and preventing risks, revolutionising financial forecasting & compliance. Explore the latest technology trends & innovations with influential research scientists, startups & business leaders across the industry.
25 May 2017, Boston
The Deep Learning in Healthcare Summit will explore recent breakthroughs in technical advancements and healthcare applications, from algorithms that learn to recognise complex patterns within rich medical data, to analysing real world evidence for personalised medicine, to discovering the sequence specificities of DNA- binding proteins and how it can aid genome diagnostics.