The smart artificial intelligence revolution. Explore software that can recognize patterns in digital representations of sounds, images, & data.

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“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.”

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“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.

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"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.

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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.

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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.

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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.

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“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.”

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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.

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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.

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"The easiest place for Amazon to bring its expertise to bear is in the warehouses, because that's where Amazon really excels," Hawkins said. "If they can reduce costs, they can show that on the store shelves and move Whole Foods away from the Whole Paycheck image."

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Why Attend

Speakers

Extraordinary Speakers

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.

Tech

Discover Emerging Trends

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.

Network

Expand Your Network

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.

Who

Who Should Attend

  • Data Scientists
  • Data Engineers
  • Machine Learning Scientists
  • Developers
  • Entrepreneurs
  • Director of Engineering
  • Big Data Experts
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Join the discussion

  • 50 speakers
  • 250 leading technologists & innovators
  • Group brainstorming sessions
  • Interactive workshops
  • 7 + hours of networking
  • Access to all the filmed presentations
  • Discover technology shaping the future
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Topics we cover

Neural Networks
Neural Networks
Machine Learning
Machine Learning
Deep Learning Algorithms
Deep Learning Algorithms
Pattern Recognition
Pattern Recognition
Image Retrieval
Image Retrieval
Computing Systems
Computing Systems
Speech Recognition
Speech Recognition
Chatbots
Chatbots

Companies Attending

capital one
Adelphic
ARK Invest
Frontline Ventures
LogMeIn
boston uni
nat film board canada
verint
harvard uni
udacity
princeton uni
dana farber
Amazon
samsung
Mitsubishi Electric
Hyundai
NVIDIA
PwC
Apple
Qualcomm

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