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MILA Tea Talk

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MILA (Z-209 PCMcNicoll)

2900 Ch de la Tour

Montreal

Canada

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Come learn about NVIDIA's work in the Deep Learning and Artificial Intelligence sphere. This MILA Tea Talk will be led by Clement Farabet, NVIDIA's VP of AI Infrastructure.

Afterward, we'll will be hosting an intimate social/reception after the talk. In addition to food and drinks, a raffle will be held for attendees - you'll have the chance to win an NVIDIA Titan Xp!

Deep Learning Research at NVIDIA

Abstract: NVIDIA is the leading platform for Deep Learning research and invests in a broad range of research projects within key industries, such as graphics and self-driving cars. In this talk I will discuss a few of our projects in-depth: from leveraging synthetic data to reduce our need on data; ray-tracing for real-time virtual worlds; auto face animation for game designers; and auto image transforms for photo editing. I will also talk about how we apply this research work into a product and operate a fast-moving R&D team to build autonomous vehicles.

Bio: Clement Farabet is VP of AI Infrastructure at NVIDIA. His team is responsible for building NVIDIA's next-generation AI platform, leveraging NVIDIA's hardware to enable a broad range of new applications, ranging from self-driving cars to medical imaging. Clement Farabet received a Master’s Degree in Electrical Engineering with honors from Institut National des Sciences Appliquées (INSA) de Lyon, France in 2008. His Master’s thesis work on reconfigurable hardware for deep neural networks was developed at the Courant Institute of Mathematical Sciences of New York University with Professor Yann LeCun, and led to a patent. He then joined Professor Yann LeCun’s laboratory in 2008, as a research scientist. In 2009, he started collaborating with Yale University’s e-Lab, led by Professor Eugenio Culurciello. This joint work later led to the creation of TeraDeep (www.teradeep.com). In 2010, he started the PhD program at Université Paris-Est, co-advised by Professors Laurent Najman and Yann LeCun. His thesis focused on real-time image understanding/parsing with deep convolutional networks. The main contributions of his thesis were multi-scale convolutional networks and graph-based techniques for efficient segmentations of class prediction maps. He graduated in 2013, and went on to cofound Madbits, a company that focused on representing, understanding and connecting images. Madbits was acquired by Twitter in 2014. At Twitter, he cofounded Cortex, a team of software engineers, data scientists, and research scientists dedicated to developing state-of-the-art machine learning capabilities to refine and enable new products. He subsequently lead and managed a team called Cortex Core, which focused on building a high-leverage modular machine/deep learning platform to power every aspect of the Twitter product (recommendation systems, search, timeline ranking, etc.). This team focused on (1) developing models of text, images, video, users, and (2) making these models seamlessly importable as components of user-facing ML systems.




When: Monday, October 9, 2017
Time: 2:00PM - 4:30PM
Where: MILA (Z-209 PCMcNicoll), Pavillon Claire-McNicoll

Who it's for: MILA students, Postdocs, Researchers, Professors, and Faculty. Open registration to all.


Date and Time

Location

MILA (Z-209 PCMcNicoll)

2900 Ch de la Tour

Montreal

Canada

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