THURSDAY - OCTOBER 18, 2018
 
04:00 PM
04:45 PM

AI Engine for Autonomous Shoping Carts

Tracxpoint is building the new Retail AI-Pipeline that guarantes an individual shopping experience with cashier-les on-card payment. Our system includes a unique combination of AI-Engines, IoT- & proprietary sensor fusion. We wil present our progres towards recognizing one hundred thousand individual products in under a second on a NVIDIA...


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Presenter:
Felix Goldberg, Chief AI Scientist, Tracxpoint LLC
Room: Hall F/G

SIL8120 - Autonomous Machines and IoT, Deep Learning and AI
04:00 PM
04:35 PM

Deep Learning Infrastructure for Autonomous Vehicles

We'll introduce deep learning infrastructure for building and maintaining autonomous vehicles. This includes techniques for managing the lifecycle of deep learning models from definition, training and deployment to reloading and life-long learning. DNN autocurates and pre-labels data in the loop...


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Presenter:
Adam Henryk Grzywaczweski, Solution Architect, NVIDIA
Room: Hall B

SIL8114 - Deep Learning and AI, Autonomous Vehicle Technologies, AI in Healthcare
04:00 PM
04:45 PM

Load-And-Go GPU Analytics: Overcoming the I/O Bottleneck for AI

In this session, learn how to efficiently arrange data for consumption by GPUs for analytics. We'll take a look at how combining several modular components and ideas can deliver fast AI performance by limiting the effect of I/O on data-intense queries and models. We'll show how arranging data for the GPU, combined with fast GPU compression, metadata mapping....


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Presenters:
Arnon Shimoni, Product Marketing Manager, SQream
Eyal Hirsch, GPU Software Developer, SQream

Room: Hall I

SIL8127 - Deep Learning and AI, Accelerated Data Science
03:00 PM
03:45 PM

Pushing the Boundaries - Simulation vs. Real Life

The greatest challenge regarding simulation is finding the matrix that compares it to real life. In this session, Danny will present a mathematical matrix that defines this relation and show how a proper simulation can be constructed based on deep learning techniques. He will also supply live examples of the Cognata simulation platform.


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Presenter:
Danny Atsmon, CEO, Cognata Ltd.
Room: Hall B

SIL8122 - Deep Learning and AI, Autonomous Vehicle Technologies, VR and Simulation
05:00 PM
05:45 PM

Reinforcement Learning with A* and a Deep Heuristic

Inspired by the recent achievements of methods which combine trees and DNNs (e.g. AlphaZero), this study demonstrates how to effectively combine AI with a deep heuristic represented by a DNN. AI is a highly popular and successful path-planning algorithm, but it's usability is limited to only those domains where a good heuristic is known. This new algorithm, which we call Aleph-0, enables us to replicate the success of AI in new domains, including that of autonomous vehicles.


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Presenter:
Ariel Keselman, Chief Architect, Imagry
Room: Hall B

SIL8124 - Deep Learning and AI, Autonomous Vehicle Technologies
05:00 PM
05:45 PM

Solving Challenges in Future Mobility Solutions Using AI

Advances in AI and machine learning present new challenges in the form of supporting and operating the future mobility solutions. We need to actually train these future mobility solutions to overcome real-world challenges and operational workflow. The industry needs to ensure the reliable functionality for the increasing automatic and future mobility solutions. ...


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Presenters:
Amir Hever, CEO, UVeye
David Oren, VP Business Development, UVeye

Room: Hall F/G

SIL8125 - Autonomous Machines and IoT, Deep Learning and AI
05:00 PM
05:45 PM

The Deep Learning Approach to Natural Language Processing

Deep Learning is revolutionizing Natural Language Processing (NLP). Written text is available everywhere, from text messages and social media posts and all the way to lengthy emails and blog posts. As an organization, being able to extract information from your customers' communications has the potential to give you a great advantage. ....


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Presenter:
Yuval Mazor, Solution Architect, NVIDIA
Room: Hall K/L

SIL8106 - Deep Learning and AI, Accelerated Data Science
02:00 PM
02:45 PM

The Missing Sense - Enabling Autonomous Vehicles to "feel" the Road using Tactile AI

Like people, Autonomous Vehicles (Level 2 through 5) need to "see" and "feel" the road to best perform (in an enjoyable, efficient and safe way). To date, this "feel" aspect has been under-served. In this session, we will list novel methods for applying Artificial Intelligence to vehicle sensors in order to provide vehicles with advanced tactile sensing capabilities and augment the vastly-used visual sensors. ...


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Presenter:
Boaz Mizrachi, Founder and CTO, Tactile Mobility
Room: Hall B

SIL8113 - Deep Learning and AI, Autonomous Vehicle Technologies
02:00 PM
02:45 PM

Using Deep Learning to Predict Activity and Drug Response of Unknown Mutations

By applying deep learning to images of mutated cells interacting with drugs, we can predict how cells with unknown mutations respond to these drugs. State-of-the-art cancer treatment starts with sequencing a tumor biopsy. Alas, we don't know how most mutations act or respond to drugs. Therefore, the treating physician cannot integrate this data into the treating protocol. To solve this, ...


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Presenter:
Michael Vidne, CCO, NovellusDx
Room: Hall M

SIL8108 - Deep Learning and AI, AI in Healthcare
01:00 PM
01:45 PM

Deep Learning and Beyond

Attend this session to learn how Deep Learning is delivering breakthrough results across a wide range of industries and applications. We'll review the most effective neural networks for a variety of use cases, the latest GPU-accelerated algorithms...


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Presenter:
Will Ramey, Sr. Director, Deep Learning Institute, NVIDIA
Room: Hall K/L

SIL8142 - Deep Learning and AI, Autonomous Vehicle Technologies, Accelerated Data Science, Professional Visualization, AI in Healthcare
02:00 PM
02:45 PM

Deep Learing for Image Understanding

In this session, Amir will describe deep learning models that can use context to make predictions. Specifically, he will describe recent models for image annotation and text categorization. The models we consider iteratively refine their prediction by considering how each prediction components is influenced by other components...


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Presenter:
Amir Globerson, Associate Professor of Computer Science, Tel Aviv University
Room: Hall K/L

SIL8135 - Deep Learning and AI, Autonomous Vehicle Technologies, Accelerated Data Science, Professional Visualization
02:00 PM
02:45 PM

How to Design a Practical Real-Time AI Robotics Application using GPUs

Attend this session to hear experts provide guidelines on how to maximize GPU performance for fast prototyping, designing, training, and testing of AI robotics applications. ....


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Presenter:
Yaniv Maor, Founder, CEO, Tevel Aerobotics Technologies
Room: Hall F/G

SIL8112 - Autonomous Machines and IoT, Deep Learning and AI
10:00 AM
12:00 PM

Opening Keynote: Accelerated Platforms: The Future of Computing

NVIDIA's miss the Bill speaks this Dally, keynote he on of from future computing. Don't Scientist, Chief as


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Presenter:
Bill Dally, Chief Scientist, NVIDIA
Room: Hall B

SIL8138 - Deep Learning and AI
09:00 AM
05:30 PM

Fundamentals of Deep Learning for Natural Language Processing

In this course, you will receive hands-on training on the latest techniques for understanding textual input using Natural Language Processing (NLP). You’ll learn how to: convert text to machine understandable representation and classical approaches, implement distributed representations (embeddings) and understand their properties...


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Presenter:
Yuval Mazor, Solution Architect, NVIDIA
Room: Halls C4&C5
- Deep Learning and AI
01:00 PM
03:00 PM

Medical Image Classification Using the MedNIST Dataset

This training applies convolutional neural networks (CNNs) to a medical imaging dataset. Students will learn how to collect, format, and standardize medical image data. They will architect and train a CNN on their dataset, and use it to classify novel medical images. This lab provides a practical introduction....

 


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Presenter:
Nicola Rieke, Solution Architect, NVIDIA
Room: Hall C1
- Deep Learning and AI, AI in Healthcare
03:30 PM
05:30 PM

Develop Scalable IVA Applications using DeepStream

Learn how to create AI-based video analytics applications using DeepStream to transform video into valuable insights. Understanding video requires multi-stream decoding/encoding, scaling, color space conversion, tracking, and multi-stage inference. DeepStream SDK allows developers to focus on core deep learning development, while offering the best system level software optimization and performance. By attending this, you'll learn how to: .....


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Presenter:
Adam Henryk Grzywaczweski, Solution Architect, NVIDIA
Room: Hall C2
- Deep Learning and AI, Intelligent Video Analytics
03:00 PM
03:45 PM

Revolutionizing a 4 Trillion Dollar Industry using Sub-Millimeter Imagery and AI

In this session, CEO Ofir Schlam will talk about the huge opportunity in agriculture, a 4 Trillion dollar industry that saw little disruption in recent decades. Another unbelievable number is 35% - the amount of crop losses every farmer in the world faces annually by weeds, diseases, insects, and fertilizer deficiencies. Ofir will explain Taranis' unique AI challenges in developing AgroBrain – our AI agronomist and AgroSet the...


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Presenter:
Ofir Schlam, CEO, Taranis
Room: Hall K/L

SIL8133 - Deep Learning and AI, Accelerated Data Science
05:00 PM
05:45 PM

Simplifying AI Infrastructure: Lessons in Scaling on DGX Systems

While every enterprise is on a mission to infuse its business with deep learning, few know how to build the infrastructure to get them there. Short-sighted approaches to data center design can lead to long-term consequences that make the ROI of AI elusive. NVIDIA has distilled the insights and best practices learned from deep learning deployments around the globe...


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Presenter:
Renee Yao, Senior Product Marketing Manager, Deep Learning and Analytics, NVIDIA
Room: Hall I

SIL8139 - Deep Learning and AI, Accelerated Data Science
01:00 PM
01:45 PM

Integrating AI Based Solutions into the Radiology Workflow - Stroke Use Case

In this presentation attendees can expect to gain a deeper understanding of the challenges and needs surrounding the integration of AI-based solutions into the clinical workflow, driving adoption and enabling maximal benefit. AI-based solutions have the potential to significantly improve healthcare processes, across the entire care-continuum. ....


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Presenter:
Tamar Schirman, Marketing Director, New Product Development, Radiology Informatics, Philips HealthTech
Room: Hall M

SIL8144 - Deep Learning and AI, AI in Healthcare
05:00 PM
05:45 PM

The Path to GPU as a Service in Kubernetes

Kubernetes modern production patterns for Deep Learning applications and a deep dive into the Kubernetes GPU subsystem and its challenges (performance, scheduling, monitoring). Autonomous vehicles, face recognition, High Performance Computing, Virtual Reality, NVIDIA GPUs are enabling a new computer era with cloud computing at its center. ....


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Presenter:
Adam Henryk Grzywaczweski, Solution Architect, NVIDIA
Room: Hall D

SIL8143 - Deep Learning and AI, Developer Tools
01:00 PM
01:25 PM

DDN A3I Storage Solutions: Extract More Answers From Your Data at Any Scale (Presented by DDN Storage)

DDN is a leader in storage solution for data intensive workflows at scale. This session will cover DDN's activity across the various markets of data intensive AI and Machine learning. The session is built from market coverage down to the underlaying technology that DDN provides and its advantages for NVIDIA DGX and GPU accelerated workflows. ...


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Presenter:
Ran Pergamin, Senior Storage Solution Architect, DDN Storage
Room: Hall H

SIL8150 - Deep Learning and AI, Autonomous Vehicle Technologies, Accelerated Data Science, AI in Healthcare
04:30 PM
04:55 PM

OpenSeq2Seq: A Deep learning Toolkit for Speech Recognition, Speech Synthesis, and NLP

OpenSeq2Seq is an open-source, TensorFlow-based toolkit, which supports a wide range of off-the-shelf models for Natural Language Translation (GNMT, Transformer, ConvS2S), Speech Recognition (Wave2Letter, DeepSpeech2), Speech Synthesis (Tacotron 2), Language Modeling and transfer learning for NLP tasks. OpenSeq2Seq is optimized for latest GPUs. It supports multi-GPU and mixed-precision training. Benchmarks on machine translation and speech recognition tasks show that models built using OpenSeq2Seq give state-of-the-art performance at 1.5-3x faster training time.


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Presenter:
Boris Ginsburg, Deep Learning Principal Engineer, NVIDIA
Room: Hall H

SIL8152 - Deep Learning and AI
04:00 PM
04:25 PM

Real-time Edge Computing Deployment on Railway Applications (Presented by RailVision)

The train world is going through a massive change in order to increase safety and efficiency. One of the ways to do that is by increasing digitalization and implementing more intelligent systems for safety, maintenance and efficient operation to pave the way for autonomous train operating. RailVision company is a pioneer of implementing AI/DL technologies into this market and already involved in revolutionary projects deploying this technology. In this talk we will show a safety-related train application with maintenance capabilities that uses edge computing. Real-time considerations will be presented as a part of an overall view of deep learning implementation in a system. The connection between the training phase through optimization to the inference will also be discussed. Demos of edge computing capabilities will be presented.


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Presenter:
Shahar Hania, VP R&D, Co-Founder, RailVision
Room: Hall H

SIL8151 - Deep Learning and AI, Autonomous Vehicle Technologies
03:00 PM
03:45 PM

Super-Resolution for Aliased Images

In this talk we discuss different techniques for training the super resolution algorithm with the focus on producing high quality results on the highly aliased and noisy data. Though such artifacts are not often present in the real images, they frequently appear in gaming and animation images and videos....


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Presenter:
Ahmad Kiswani, Deep Learning Engineer, NVIDIA
Room: Hall D

SIL8154 - Deep Learning and AI, Professional Visualization
01:30 PM
01:55 PM

Ubiquitous Machine Learning (Presented by Cisco)

Data is the lifeblood of an enterprise, and it's being generated everywhere. To overcome the challenges of data gravity, data analytics, including machine learning, is best done where the data is located. Come to this session to understand how to overcome the challenges of machine learning everywhere.


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Presenter:
Han Yang, Senior Product Manager, Cisco
Room: Hall H

SIL8155 - Deep Learning and AI
02:30 PM
02:55 PM

Medical Imaging and Deep Learning on PowerAI: Creating Technologies for Assisting Radiologists (Presented by IBM)

In this talk we will focus on how AI based healthcare support-systems can assist radiologists in analyzing medical imaging and clinical data. We will present a state-of-the-art DL based system for detection and prediction of Breast Cancer using mammography images and medical history and show how it can be used to improve cancer detection rate and optimize physician decision making.


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Presenter:
Adam Spiro, Research Scientist, IBM
Room: Hall H

SIL8156 - Deep Learning and AI, AI in Healthcare