- 40 Speakers
- 450 Attendees
- San Francisco
Ian Goodfellow
Staff Research Scientist
Google Brain
Brendan Frey
Co-Founder & CEO
Deep Genomics
Shivon Zilis
Partner
Bloomberg
Andrej Karpathy
Director of Artificial Intelligence
Tesla
Andrew Tulloch
Research Engineer
Ofir Nachum
Brain Resident
Stefano Ermon
Assistant Professor
Stanford University
Toru Nishikawa
CEO
Preferred Networks
Avidan Akerib
VP of the Associative Computing
GSI Technology
Durk Kingma
Research Scientist
OpenAI
Eli David
CTO
Deep Instinct
Chelsea Finn
PhD Student
UC Berkeley
Roland Memisevic
Chief Scientist
Twenty Billion Neurons
Stacey Svetlichnaya
Software Development Engineer
Flickr
Sergey Levine
Assistant Professor
UC Berkeley
Chris Moody
Data Scientist
Stitch Fix
Brad Folkens
Co-Founder & CTO
CloudSight
Alex Dalyac
Co-Founder & CEO
Tractable
Danny Lange
VP of AI and Machine Learning
Unity Technologies
Augustin Marty
Co-Founder & CEO
Deepomatic
Andres Rodriguez
Senior Technical Lead for Deep Learning
Intel
Ilya Sutskever
Research Director
OpenAI
Alexei Efros
Associate Professor
UC Berkeley
Tony Jebara
Director of Machine Learning Research
Netflix
Modar Alaoui
CEO & Founder
Eyeris
Shubho Sengupta
AI Research
Facebook AI Research (FAIR)
Inmar Givoni
Director of Machine Learning
Kindred
Judy Hoffman
Postdoc Researcher
Stanford Computer Vision Group
Will Jack
CEO
Remedy
Bryan Catanzaro
VP of Applied Deep Learning Research
NVIDIA
Rumman Chowdhury
Senior Manager
Accenture
Nathan Benaich
Investor
Playfair Capital
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.
Facebook recently published a paper detailing its personal approach to speeding up training for visual recognition models. The company says it has managed to reduce the training time of a ResNet-50 deep learning model on ImageNet from 29 hours to one.
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.
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.
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.
View the summit brochure and all the information you need to convince your boss that attending the summit will help future-proof your business.
Neural Networks
Machine Learning
Deep Learning Algorithms
Voice Recognition
NLP
Computer Vision
Pattern Recognition
Speech Recognition
Predictive Intelligence
AI Assistants
Image Retrieval
Autonomous Vehicles
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.
View more information on hotels & things to do in San Francisco on our Pinterest page.
Chief Knowledge Officer, NASA
@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
@seanlorenz
"'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
@fet_eu
"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
21 September 2017, London
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.
21 September 2017, London
The next generation in predictive intelligence. Anticipating user & business needs to alert & advise logical steps to increase efficiency. The summit will showcase the opportunities of advancing trends in AI Assistants & their impact on business & society. What impact will predictive intelligence have on business efficiency & personal organization?
21 September 2017, London
Following day 1 of the summit, attendees will come together for an evening of networking, discussions and fine food & wine. Mix with leaders on topics including NLP, speech recognition and image analysis, as well as applications in sectors including manufacturing, transport, healthcare, finance and security.
The Challenges of Artificial Intelligence in Retail
AI Assistants: in the news: what have you missed?
Google DeepMind's Avatar Learns to Walk
