Université de Montréal
Senior Editor, Business Reports
MIT Technology Review
Director of the Center for Data Science
University of Massachusetts Amherst
Fast Forward Labs
CEO & Founder
Senior Principal Research Scientist
Mitsubishi Electric Research Labs
Lead AI Developer
VP of the Associative Computing
Director of Research
Director of Machine Learning Research
CTO & Chief Scientist
Assistant Professor of Computer Science
University of Michigan
University of North Carolina
CTO & Co-Founder
Chief Data Scientist
CEO & Co-Founder
Manager of Research and Advanced Development
MD, Technology Transformation Leader
“Today’s models can be trained on huge quantities of data, but that’s not enough,” says Bengio, who together with LeCun and Google’s Geoffrey Hinton is one of the original musketeers of deep learning. “We need to discover learning algorithms that can take better advantage of all this unlabeled data that’s sitting out there.”
“On our chip we bring the data as close as possible to the processing units, and move the data as little as possible,” Vivienne Sze. When run on an ordinary GPU, neural networks fetch the same image data multiple times. The MIT chip has 168 processing engines, each with its own dedicated memory nearby.
"A Deep and Autoregressive Approach for Topic Modeling of Multimodal Data". In this paper Hugo Larochelle explores how to successfully apply and extend DocNADE to multimodal data, such as simultaneous image classification and annotation.
Meet Partpic: After being licensed by a manufacturing company, PartPic obtains 360 degree photos and metadata of every part in the company’s inventory. A user can then can takes a photo of a specific part and PartPic’s software automatically identifies the name and model number of that part.
Learning Physical Intuition of Block Towers by Example - hear from Adam Lerer, Research Engineer at Facebook AI Research on exploring the ability of deep feedforward models to learn intuitive physics.
Conservation Metrics goal is to improve conservation by providing powerful new tools to monitor wildlife status, distribution, and population trends. They provide rigorous data for impact assessments, cost-effective tools for measuring ecological changes after restoration and management actions or development projects.
“The broad goal is to become the emotion layer of the Internet,” says Affectiva co-founder Rana el Kaliouby, a former MIT postdoc who invented the technology. “We believe there’s an opportunity to sit between any human-to-computer, or human-to-human interaction point, capture data, and use it to enrich the user experience.”
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.
Nervana Systems wants to make deep learning more accessible by developing custom hardware built to process all that data. Hear their latest developments from CEO Naveen Rao in a panel session at the summit.
Discover advances in deep learning & smart artificial intelligence from the world's leading innovators. Learn from industry experts & academics in speech & image recognition, neural networks & big data. Explore how deep learning will impact communications, manufacturing, healthcare & transportation.
The summit will showcase the opportunities of advancing trends in deep learning and their impact on business & society. Will smart artificial intelligence finally rival human intelligence? Learn the latest technological advancements & industry trends from a global line-up of experts.
A unique opportunity to interact with business leaders, influential technologists, data scientists & entrepreneurs leading the deep learning revolution. Learn from & connect with 200+ industry innovators sharing best practices to advance the smart artificial intelligence revolution.
Deep Learning Algorithms
The Renaissance Boston Waterfront Hotel is located in the heart of Boston's Seaport District and overlooks the beautiful harbour. The modern hotel is only 1.3 miles from Faneuil Hall and is only minutes away from Logan International Airport.
View more information on hotels & things to do in Boston on our Pinterest page.
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.