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AND BEYOND Will Ramey, Sr. Director, Global Head of Developer - PowerPoint PPT Presentation

Apr 29, 2023 •283 likes •582 views

DEEP LEARNING AND BEYOND Will Ramey, Sr. Director, Global Head of Developer Programs, NVIDIA Corporation ACCELERATED DATA SCIENCE 2 GPU-ACCELERATED DATA SCIENCE Use Cases in Every Industry CONSUMER INTERNET OIL & GAS Ad Personalization

  1. DEEP LEARNING AND BEYOND Will Ramey, Sr. Director, Global Head of Developer Programs, NVIDIA Corporation

  2. ACCELERATED DATA SCIENCE 2

  3. GPU-ACCELERATED DATA SCIENCE Use Cases in Every Industry CONSUMER INTERNET OIL & GAS Ad Personalization Sensor Data Tag Mapping Click Through Rate Optimization Anomaly Detection Churn Reduction Robust Fault Prediction FINANCIAL SERVICES MANUFACTURING Claim Fraud Remaining Useful Life Estimation Customer Service Chatbots/Routing Failure Prediction Risk Evaluation Demand Forecasting HEALTHCARE TELECOM Improve Clinical Care Detect Network/Security Anomalies Drive Operational Efficiency Forecasting Network Performance Speed Up Drug Discovery Network Resource Optimization (SON) RETAIL AUTOMOTIVE Supply Chain & Inventory Management Personalization & Intelligent Customer Interactions Price Management / Markdown Optimization Connected Vehicle Predictive Maintenance Promotion Prioritization And Ad Targeting Forecasting, Demand, & Capacity Planning 3

  4. BEYOND DEEP LEARNING Opportunities to Accelerate Data Science ARTIFICIAL INTELLIGENCE Deep Learning Machine Learning (Regressions, Decision Trees, Graph) Analytics Dense Data Tabular/Sparse Data MACHINE LEARNING / DATA ANALYTICS 2.2 exabytes (2.2B GB) of data created daily – McKinsey $166B in 2018 revenues for big data and business analytics – IDC 4

  5. RAPIDS DATA SCIENCE PLATFORM GPU-accelerated Open Source Libraries Data Preparation Model Training Graph Analytics cuDF cuML cuGRAPH PYTHON DEEP LEARNING FRAMEWORKS RAPIDS DASK/SPARK CUDF CUML CUGRAPH CUDNN CUDA APACHE ARROW in GPU Memory www.rapids.ai 5

  6. DL IS CRITICAL FOR INTERNET APPLICATIONS Users Expect Intelligence in Services Source: Jeff Dean, leads the Google Brain team, making machines intelligent. www.wsdm-conference.org/2016/slides/WSDM2016-Jeff-Dean.pdf 6

  7. DEEP LEARNING IS SWEEPING ACROSS INDUSTRIES Internet Services Medicine Media & Entertainment Security & Defense Autonomous Machines Image/Video Classification Cancer Cell Detection, Video Captioning Face Recognition Pedestrian Detection Speech Recognition Diabetic Grading, Content Based Search Video Surveillance Lane Tracking Natural Language Processing Drug Discovery Real Time Translation Cyber Security Recognize Traffic Signs news.developer.nvidia.com 7

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  9. WHAT PROBLEM ARE YOU SOLVING? Defining the AI/DL task EXAMPLE OUTPUTS BUSINESS INPUTS AI / DL TASK QUESTIONS HEALTHCARE RETAIL FINANCE Is “it” present Detection Cancer Detection Targeted Ads Cybersecurity or not? Text Data What type of thing Classification Image Classification Basket Analysis Credit Scoring is “it”? Images To what extent is Tumor Size / Shape Build 360° Customer Segmentation Credit Risk Analysis “it” present? Analysis View What is the likely Survivability Sentiment & Video Prediction Fraud Detection outcome ? Prediction Behavior Recognition What will likely Therapy Recommendation Recommendations Algorithmic Trading satisfy the objective? Recommendation Engine Audio 9

  10. CAMBRIAN EXPLOSION Convolutional Recurrent Generative Adversarial Reinforcement New Networks Networks Networks Learning Species Capsule Nets Encoder/Decoder ReLu BatchNorm LSTM GRU Beam Search 3D-GAN MedGAN Conditional GAN DQN Simulation Mixture of Experts Neural Collaborative Filtering Concat Dropout Pooling WaveNet CTC Attention Coupled GAN Speech Enhancement GAN DDPG Block Sparse LSTM 10

  11. DEEP LEARNING APPLICATION DEVELOPMENT 11

  12. DEEP LEARNING APPLICATION DEVELOPMENT Untrained Neural Network Model 12

  13. DEEP LEARNING APPLICATION DEVELOPMENT TRAINING Learning a new capability from existing data Deep Learning Untrained Framework Neural Network Model 13

  14. DEEP LEARNING APPLICATION DEVELOPMENT TRAINING Learning a new capability from existing data Deep Learning Trained Model Untrained Framework New Capability Neural Network Model 14

  15. DEEP LEARNING APPLICATION DEVELOPMENT TRAINING Learning a new capability from existing data Deep Learning Trained Model Untrained Framework New Capability Neural Network Model Trained Model Optimized for Performance 15

  16. DEEP LEARNING APPLICATION DEVELOPMENT INFERENCE TRAINING Applying this capability Learning a new capability to new data from existing data Deep Learning Trained Model App or Service Untrained Framework New Capability Featuring Capability Neural Network Model Trained Model Optimized for Performance 16

  17. CHALLENGES DEEP LEARNING NEEDS WHY Data Scientists New computing model Latest Algorithms Rapid evolving Fast Training Impossible -> Practical Deployment Platforms Must be available everywhere 17

  18. THE PREMIERE AI CONFERENCE MARCH 18-22, 2019 | SILICON VALLEY | #GTC19 ADVANCE YOUR DEEP LEARNING KNOWLEDGE AT GTC Don’t miss the world’s most important event for GPU developers WWW.GPUTECHCONF.COM 18

  19. NVIDIA DEEP LEARNING INSTITUTE Hands-on Training for Data Scientists and Software Engineers Helping the world to solve challenging problems using AI and deep learning On-site workshops and online courses presented by certified instructors Covering complete workflows for proven application use cases Fundamentals, Autonomous Vehicles, Finance, Healthcare, Video Analytics, IoT/Robotics, … www.nvidia.com/dli 19

  20. Inception: Virtual Accelerator for AI Startups BENEFITS MEMBERSHIP IMPACT AI Expertise Showcasing Innovation ~10x 3600 Go-To-Market Support Creating a Global Community Technology Access 300 Jun 2016 Sep 2018 www.nvidia.com/inception 20

  21. NVIDIA DEEP LEARNING SOFTWARE PLATFORM TRAINING INFERENCE GRE + TensorRT Data center Data Management Training Training Trained Neural Data Network JETPACK SDK Embedded Model Assessment Automotive DriveWorks SDK NVIDIA DEEP LEARNING SDK and CUDA developer.nvidia.com/deep-learning-software 21

  22. NVIDIA GPU CLOUD Simple Access to a Comprehensive Catalog of GPU-accelerated Software Discover 30 GPU-Accelerated Containers Deep learning, third-party managed HPC applications, NVIDIA HPC visualization tools, and partner applications Innovate in Minutes, Not Weeks Get up and running quickly and reduce complexity Access from Anywhere Use on PCs with NVIDIA Volta or Pascal™ architecture GPUs, NVIDIA DGX Systems, and supported cloud providers ngc.nvidia.com 22

  23. END-TO-END PRODUCT FAMILY HPC / TRAINING INFERENCE FULLY INTEGRATED AI SYSTEMS DATA CENTER AUTOMOTIVE EMBEDDED DGX-1 DGX-2 VIRTUAL SERVER DESKTOP WORKSTATION DATA CENTER WS PLATFORM Tesla P4/T4 Jetson AGX Xavier Drive AGX Pegasus TITAN DGX Station Virtual GPU Tesla V100 HGX1/HGX2 Tesla V100 23

  24. SOLUTIONS DEEP LEARNING NEEDS SOLUTIONS Data Scientists Deep Learning Institute, GTC Latest Algorithms NGC, GPU Accelerated Frameworks, DL SDK Fast Training DGX, V100/T100, TITAN V Deployment Platforms TensorRT , V100/T4, Drive AGX, Jetson AGX 24

  25. DIGITAL CONTENT INTERNET SERVICES ROBOTICS CREATION READY TO GET STARTED? Project Checklist INTELLIGENT VIDEO ANALYTICS FINANCE What problem are you solving, what are the AI/DL tasks? What data do you have/need, how is it labeled? GENOMICS HEALTHCARE SECURITY & DEFENSE Which tools & environment will you use? On what platform(s) will you train and deploy? 25 MEDIA & ENTERTAINMENT AUTONOMOUS VEHICLES

  26. WHAT’S NEXT? Work through DLI online courses – www.nvidia.com/dli Review examples of AI in action - news.developer.nvidia.com Listen to the NVIDIA AI Podcast - blogs.nvidia.com/ai-podcast Register for GTC near you – www.nvidia.com/gtc THANK YOU 26

  27. www.nvidia.com/dli

  28. www.nvidia.com/dli 28

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