Full Program


Time Title Room
09:00 AM
04:15 PM

Fundamentals of Deep Learning with Computer Vision

Explore the fundamentals of deep learning by training neural networks and using results to improve performance and capabilities. In this course, you’ll learn the basics of deep learning by training and deploying neural networks. You’ll learn how to: implement common deep learning workflows, such as image classification and object detection, experiment with data...


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Presenter:
Adam Henryk Grzywaczweski, Solution Architect, NVIDIA
- Autonomous Vehicle Technologies


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
- Deep Learning and AI





Time Title Room
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

SIL8138 - Deep Learning and AI


01:00 PM
01:45 PM

Debug and Approve your Deep Networks by Overcoming the Black Box Problem

Deep Learning AI may learn to perform tasks by cheating in unknown and unexpected ways, which may be a liability for the developer. Feedforward networks are the basis of artificial neural networks such as deep, convolution, recurrent, and even machine learning regression methods. However the internal decision processes of feedforward networks are difficult to explain: they are known to be a "black-box". ...

 


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Presenter:
Tsvi Achler, Optimizing Mind

SIL8146
02:00 PM
02:45 PM

GPU Accelerated Machine Learning

Artificial Intelligence is a wide field where different types of learning models serve different kinds of tasks. Deep neural networks (DL), for example, are great for data with spatial-temporal locality like images, audio, and text. However, for data without inherent locality, non-neural network machine learning algorithms....


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Presenter:
Paul Mahler, Senior Data Scientist and Technical Product Manager for Machine Learning, n

SIL8137 - Professional Visualization
03:00 PM
03:45 PM

GPU Accelerated Data Science

Data Science/Data Mining is the exploration of data to extract novel knowledge and insight. That discovery process often involves a considerable amount of trial and error, after all, if you know what you are looking for you are not doing discovery. The Python programming language has grown in popularity amount data scientists for its flexibility, ease of programming, and readability. 


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Presenter:
Keith Kraus, Engineering Manager Data Analytics, NVIDIA

SIL8136 - Accelerated Data Science
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


SIL8127 - 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

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

SIL8144 - Deep Learning and AI, AI in Healthcare
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

SIL8108 - Deep Learning and AI, AI in Healthcare
03:00 PM
03:45 PM

Project Clara: AI Deployment in Healthcare

Although deep learning models have already demonstrated great capabilities when applied to medical image analysis tasks, their deployment and usage in clinical workflows is often inefficient and cumbersome. In this talk we discuss NVIDIA's solution to this issue: Project Clara. Clara is a platform built to facilitate deployment of DL algorithms in an efficient, scalable, and safe manner. We have designed Clara to tackle healthcare specific tasks and therefore ensure reliability and compatibility with current medical systems. 


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Presenter:
Eliron Amcir, Nucleai

SIL8128 - AI in Healthcare
04:00 PM
04:45 PM

AI Powered Revolution in Cancer Diagnostics

Cancer diagnostics, in many ways, has not changed much in the past century. Tissue biopsies are manually inspected under the microscope by Pathologists, performing "Pattern Recognition" with their eyes on microscopic images equivalent in size to 1000 X-ray images.


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Presenter:
Eliron Amcir, Nucleai

SIL8147 - AI in Healthcare
05:00 PM
05:45 PM

Deep Learning in Medical Imaging: Solving the Data Augmentation Challenge for Enhanced-Value Radiology Reporting

In this talk, Hayit will give an overview of the Deep Learning computer-aided detection and diagnosis tools they are developing, which can support the detection, segmentation and the characterization tasks of the radiologist. Examples will be presented in Chest Xray pathology identification....


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Presenter:
Hayit Greenspan, Associate Professor of Biomedical Engineering in the Faculty of Engine, Tel Aviv University

SIL8153 - AI in Healthcare


01:00 PM
01:45 PM

How GPU Compute has Enabled Next Level Functionality and Robustness for Driver Monitoring

As autonomous vehicles make progress, it is important for cameras to better "understand" the driver, occupants, and the entire cabin. With the progress of deep learning, it is now possible to provide extremely accurate driver and cabin monitoring, in real time, using inexpensive camera sensors and available GPU ....


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Presenter:
Ophir Herbst, CEO, Jungo Connectivity Ltd.

SIL8107 - Autonomous Vehicle Technologies
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

SIL8113 - Deep Learning and AI, Autonomous Vehicle Technologies
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.

SIL8122 - Deep Learning and AI, Autonomous Vehicle Technologies, VR and Simulation
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

SIL8114 - Deep Learning and AI, Autonomous Vehicle Technologies, AI in Healthcare
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

SIL8124 - Deep Learning and AI, Autonomous Vehicle Technologies


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

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

SIL8135 - Deep Learning and AI, Autonomous Vehicle Technologies, Accelerated Data Science, Professional Visualization
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

SIL8133 - Deep Learning and AI, Accelerated Data Science
04:00 PM
04:50 PM

Deep Reinforcement Learning Leading Industry 4.0

Deep Reinforcement Learning (DRL) is an emerging technology that is now allowing optimization of business processes that were not possible before, increasing efficiency and process output in the process. DRL opens a door into automation and optimization of systems that were considered chaotic...


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Presenter:
Michael Zolotov, Co-founder and CTO, Razor Labs

SIL8119 - Accelerated Data Science
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

SIL8106 - Deep Learning and AI, Accelerated Data Science


01:00 PM
01:45 PM

Optimizing CUDA Applications for the Volta/Turing GPU Architecture

This session will cover details of performance features released in the latest version of CUDA, new features of Turing architecture alongside a wealth of optimization techniques, and in-depth information to get the most out of the Volta/Turing GPU architecture.


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Presenters:
Vishal Mehta, Developer Technology, NVIDIA
Maxim Milakov, AI DevTech, NVIDIA


SIL8140 - Developer Tools
02:00 PM
02:45 PM

Boost DNN Training Performance using NVIDIA Tools

Learn how to boost DNN training performance using NVIDIA Tools. See how NVIDIA experts profile DNN training applications using Nsight Systems to significantly reduce training time.

 


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Presenters:
Yuval Mazor, Solution Architect, NVIDIA
Yaki Tebeka, Distinguished Engineer, Developer Tools, NVIDIA


SIL8105 - Intelligent Machines
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

SIL8154 - Deep Learning and AI, Professional Visualization
04:00 PM
04:45 PM

Practical Realtime Raytracing with RTX - From Concepts to Implementation

Bring real-time raytracing into your raster-based application using NVIDIA RTX and Microsoft DXR or Vulkan. This session will cover and connect the RTX principles with the implementation details to add raytracing from the ground up. You will learn all about setting up acceleration structures, raytracing pipelines and shader binding tables through simple and progressive additions. 


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Presenter:
Pascal Gautron, Senior Developer Technology Engineer, NVIDIA

SIL8149 - Professional Visualization
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

SIL8143 - Deep Learning and AI, Developer Tools


01:00 PM
03:00 PM

Anomaly Detection with Variational Autoencoders

At this session you will be training a variational autoencoder to detect anomalies within data. Variational autoencoders are rooted in Bayesian inference and can outperform traditional techniques. There are use cases for anomaly detection in almost every industry including: cyber security, finance, healthcare, retail, telecom, ....


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Presenter:
Adam Henryk Grzywaczweski, Solution Architect, NVIDIA
- Intelligent Video Analytics
03:30 PM
05:30 PM

Training Semantic Segmentation for DRIVE PX

The level of accuracy needed for urban driving is different than highway driving due to the density of different objects in a given scene. Using CamVid dataset, this mini course will go through all the steps required to do semantic segmentation given the computation capabilities of DRIVE PX. You’ll learn how to:....


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Presenters:
Oliver Knieps, Deep Learning Software Engineer, NVIDIA
Jan Jamaszyk, Software DevTech Engineer, NVIDIA

- Autonomous Vehicle Technologies


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
- Deep Learning and AI, AI in Healthcare
03:30 PM
05:30 PM

Genomics: Using Deep Learning to Accelerate the Identification of Genetic Variants

Identifying genetic variants, interpreting the change (annotation), and determining whether it is pathogenic are critical steps in applying genomics to healthcare. Attendees will implement deep learning methods on genomic data to identify pathogenic variants with high accuracy and speed. They will perform data reduction and train their own models. ....


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Presenter:
Nicola Rieke, Solution Architect, NVIDIA


01:00 PM
03:00 PM

Introduction to Object Detection with TensorFlow

This workshop is a lightning introduction to object detection and image segmentation for data scientists, engineers, and technical professionals. This task of computer-based image understanding permeates many major fields such as advertising, smart cities, healthcare, national defense, robotics, and autonomous driving. .....


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Presenters:
Oliver Knieps, Deep Learning Software Engineer, NVIDIA
Jan Jamaszyk, Software DevTech Engineer, NVIDIA

- Autonomous Vehicle Technologies
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
- Deep Learning and AI, Intelligent Video Analytics


01:00 PM
01:45 PM

The Future of Robotics with NVIDIA

Artificial intelligence is the most powerful technology of our time. For robotics, it enables new levels of autonomy, giving machines the ability to perceive and navigate the world as well as seamlessly interact with people and handle objects. In this talk, we'll discuss how AI is critical to driving robotics breakthroughs and do a technical dive into NVIDIA’s Isaac robotics platform. 


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Presenter:
Deepu Talla, Vice President and General Manager of Autonomous Machines, NVIDIA

SIL8121 - Autonomous Machines and IoT
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

SIL8112 - Autonomous Machines and IoT, Deep Learning and AI
03:00 PM
03:45 PM

Accelerating Image Processing by 1000x using CUDA and V100 GPC

The goal of this session is to demonstrate and explain how GPU & CUDA can significantly accelerate image processing algorithms. In order to leverage the amazing power of GPU, the roofline model will be explained, demonstrating how to reduce memory bottlenecks using CUDA by increasing operation intensity(Fusion). 


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Presenter:
Eyal Rot, SW and Computing Architect, Applied Materials Israel

SIL8134 - Autonomous Machines and IoT, AI in Healthcare, Developer Tools
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

SIL8120 - Autonomous Machines and IoT, Deep Learning and AI
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


SIL8125 - Autonomous Machines and IoT, Deep Learning and AI


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

SIL8150 - Deep Learning and AI, Autonomous Vehicle Technologies, Accelerated Data Science, AI in Healthcare
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

SIL8155 - Deep Learning and AI
02:00 PM
02:25 PM

Acelerating Research to Production with PoTorch 1.0 and ONX (Presented by Facebok)

Facebok's strength in AI inovation comes from its ability to quickly bring cuting-edge research into large scale production using a multi-faceted tolset. Learn how...


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Presenter:
Sarah Bird, Technical Program Manager, Facebook

SIL8141 - Autonomous Vehicle Technologies
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

SIL8156 - Deep Learning and AI, AI in Healthcare
03:00 PM
03:25 PM

Accelerating Deep Learning Applications (Presented by Mellanox Technologies)
Come join us and learn how to build a data-centric GPC cluster for artificial intelligence. Mellanox is a leader in hig-performance, scalable, low-latency network interconnects for bot InfiniBand and Eternet. We will briefly present the state of the art techiques for distributed machine learning and what special requirements they impose on the system,
 


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Presenter:
Gil Bloch, Principal Architect, Mellanox Technologies

SIL8145 - Accelerated Data Science
03:30 PM
03:55 PM

The Role of IT in Production-Grade AI Applications (Presented by HPE)

In this talk we will discuss how to approach the new architectural challenges that AI and DL introduce to your IT infrastructure. Your traditional compute, storage and networking is probably not enough! New AI and DL applications require much higher volume, performance and velocity, and you need to be prepared for it. Come and find out how container platforms, big data & analytics and specialized compute, storage & network solutions will assist your data scientists to bring the most out of their applications.


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Presenters:
Nir Oran, CTO, HPE
Eviatar Levy, Presales Consultant, HPE


SIL8148 - Accelerated Data Science
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

SIL8151 - Deep Learning and AI, Autonomous Vehicle Technologies
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

SIL8152 - Deep Learning and AI
05:00 PM
05:45 PM

Optimizing NVIDIA GRID Virtual GPU for the Best VDI User Experience

Gartner states that user experience is the single most important predictor of VDI success. From evolving design and engineering workflows to the new performance challenges of Windows 10, traditional performance metrics can no longer capture true user experience. NVIDIA has taken standard testing to the next level, enabling customers to achieve successful enterprise-wide VDI deployments. 


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Presenter:
Erik Bohnhorst, Manager, Professional Visualization Performance Engineering, NVIDIA

SIL8103 - Professional Visualization