Serge Palaric, VP Sales & Marketing EMEA - Embedded

JETSON : AI AT THE EDGE

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NVIDIA: THE AI COMPUTING COMPANY

GPU Computing Visual Computing Artificial Intelligence

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AMAZING ACHIEVEMENTS IN AI

Play Go Play Doom Learn Paint Style Synthesize Voice

Write Captions Learn Motor Skills Learn to Walk Drive

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NVIDIA AI COMPUTING ECOSYSTEM

AI-powered Consumer Services

AI-as-a-Service AI for Enterprise >1,500 AI Startups

iQIYI JD.comGoogleFlickr

Amazon FacebookeBayBaidu

ShazamQihoo 360 Skype Sogou

PeriscopePinterestNetflixMicrosoft

TwitterTencent Yandex Yelp

AI for Auto

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GPU DEEP LEARNING IS A NEW COMPUTING MODEL

DGX-1

Training Datacenter Inference

Tesla

Inference at the Edge

Jetson

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WHY AI AT THE EDGE MATTERSLatencyBandwidth Availability

1 billion cameras WW (2020)

30B Inference/Second

30 images per second

200ms latency

“Billions of intelligent devices will take advantage of DNNs to provide personalization and localization as GPUs become faster and faster over the next several years.” — Tractica

50% of world at less than 8mbps

Only 73% 3G/4G availability WW

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JETSON: THE PLATFORM FOR AI AT THE EDGE

Industrial InspectionSearch and Rescue

Package DeliveryFactory AutomationEnterprise Collaboration Public Safety

Personal Assist

Service Robotics

Portable Medical Academia and Research

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AI Smart Industries

MiningLogisticsIntelligent FactoryIntelligent WarehouseSmart Operation….

Smart CameraNVRAppliancesServers

Service RobotsUniversities

LogisticAgricultureInspectionSecurityEmergency

PlanesRadarsTanksTrainsVision system….

CamerasScannersDiagnostic….

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AI: THE NEW INDUSTRIAL REVOLUTION

Intelligent FactoryPick and placeComplex/custom tasksVisual inspectionTask consolidationDynamic reconfigurationCollaborative roboticsEfficiency optimizationFactory simulation

Smart OperationsInfrastructure inspectionPredictive maintenancePhysical security

LogisticsAutopilot/self-driving trucksRobot/drone delivery and support

Intelligent WarehouseInventory managementBin pickingPallet movement

MiningEquipment automationOperational safety

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SMART FACTORY EXAMPLE

AOI • Autonomous Optical Inspection

Operational efficiency• Energy efficiency• Improved Uptime• Predictive Maintenance• Make one of many• Make many of one• Picking-placing• Screwing/fastening/rivetingMan-Machine Co-existence• Collaborative Human-RobotTraceability

Challenge• Inspection/Quality

assurance • DL-Picking and placing• Cobot applications

( Deep Learning)• Big Data analytics• Real time analysis of

data from sensors

Solution

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AI FOR INDUSTRIAL AND COMMERCIAL UAVS

LogisticsWarehouse automationPackage delivery

InspectionWind turbinesBridgesOil rigsPipelinesHigh-voltage power linesCell towers

Precision AgriculturePlantingSpraying

SecurityEnterprise securityAd hoc security systems

Emergency ResponseFirst ResponderSearch and Rescue

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ProblemAerial inspection is- Imprecise: often needs

multiple flights- Time consuming: manual

review of footage- Dangerous: drone

crashes into subject or operator

SolutionAutomate the process- Vision-enabled

navigation- On-board verification- On-board fault

classification

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AI CITY — 1B CAMERAS BY 2020

~1 billion cameras worldwide by 2020

Þ 30 billion inferences/sec

Tesla P40: 2,500 inferences/sec @ 720P

Þ AI City needs ~10M P40 servers

DATA: 1B cameras, IHS “Video Surveillance Intelligence Service, Aug. 2016”

14 NVIDIA CONFIDENTIAL. DO NOT DISTRIBUTE.

FROM CAMERA TO CLOUD

CAMERA APPLIANCE DATACENTER

Trained Neural Networks

+

ESLA

EDGE CLOUD

TRAINING DATA

JETSON

JETSON

TESLA

TESLA

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JETSON FOR AI AT THE EDGE

Decode DetectorsClassifiersTrackers

Composite Encode

4K display

4K video

Jetson TX1 AI Pipeline

JETSON TX13 DNNsObject tracking4K30 video decodeVideo compositing4K HDMI outputH.265 video encode

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Jetson TX1AI Computer on a ModuleAdvanced tech for intelligent machinesUnmatched performance under 10WSmaller than a credit card

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Develop and deployJetson TX1 Developer Kit & Jetson TX1 Module

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Jetson TX1 Developer KitJetson TX1Developer Board5MP Camera

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Jetpack SDKLibrariesDeveloper toolsDesign collateralDeveloper ForumTraining and TutorialsEcosystem

http://developer.nvidia.com/embedded-computing

COMPREHENSIVE DEVELOPER SITE - JEP

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JETSON TX1

GPU 1 TFLOP/s 256-core Maxwell

CPU 64-bit ARM A57 CPUs

Memory 4 GB LPDDR4 | 25.6 GB/s

Storage 16 GB eMMC

Wifi/BT 802.11 2x2 ac/BT Ready

Networking 1 Gigabit Ethernet

Size 50mm x 87mm

Interface 400 pin board-to-board connector

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NVIDIA JETPACK 2.3SDK for embedded AI computing

Deep Learning

TensorRTcuDNN

DIGITS Workflow

Computer Vision

VisionWorksOpenCV

Multimedia

ISP SupportCamera Imaging

Video CODEC

Also includes ROS compatibility, OpenGL, advanced developer tools, and much more

CUDACUDA Libs

GPU Compute

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JETSON TX1: 20X DEEP LEARNING EFFICIENCY

Footnotes:The efficiency was measured using the methodology outlined in the whitepaper: https://www.nvidia.com/content/tegra/embedded-systems/pdf/jetson_tx1_whitepaper.pdfJetson TX1 efficiency is measured at GPU frequency of 691 MHz.Intel Core i7-6700k efficiency was measured for 4 GHz CPU clock.GoogLeNet batch size was limited to 64; that is the maximum supported by Jetpack 2.0. With Jetpack 2.3 and TensorRT, GoogLeNet batch size 128 is also supported for higher perf.FP16 results for Jetson TX1 are comparable to FP32 results for Intel Core i7-6700k as FP16 incurs no classification accuracy loss over FP32. Latest publicly available software  versions of IntelCaffe and MKL2017 beta were used.For Jetpack 2.0 and Intel Core i7, non-zero data was used for both weights and input images. For Jetpack 2.3 (TensorRT) real images and weights were used.

1 2 640

5

10

15

20

25Inference (GoogLeNet)

Intel core i7-6700kJetson TX1/Jetpack 2.1 - Nov '15Jetson TX1/Jetpack 2.3 - Sept '16

Batch Size

Imag

es/se

c/wa

tt

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DEEP LEARNING END-TO-END

Train

Step 1: Train

Optimize Deploy

NVIDIA DGX-1: Train your model with NVIDIA DIGITS Software on DGX-1, this highest performance training solution for DNNs

TensorRT

TensorRT: Dramatically speed up and reduce memory usage for your model on Jetson TX1

Jetson TX1: Deploy your model to your fleet of Jetson TX1-enabled products. Jetson TX1 is the highest performance inference solution under 10W

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DEEP LEARNING INSTITUTELearn the latest Deep Learning techniques

Online coursesDeep Learning labsNanodegreesNetworking and events

www.nvidia.com/object/deep-learning-institute.html

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TWO DAYS TO A DEMODevelop a Deep Learning Demo on Jetson TX1 in two days

Prerequisites:• GPU-enabled PC or server• Jetson TX1 Developer Kit• One engineer

developer.nvidia.com/embedded/twodaystoademo

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PARTNERSHIPLatest Technology

GPU/DL Experts

Global Sales & Marketing Network

Training from Deep Learning Institute

INCEPTION

PROGRAM

CONNECTING WITH AI STARTUPS

nvidia.com/Inception

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Jetson (corp): www.nvidia.com/object/embedded-systems.htmlJetson (dev): developer.nvidia.com/embedded-computingEmbedded Country selector: www.nvidia.com/embedded

Jetpack (under develop/tools): https://developer.nvidia.com/embedded/develop/tools Jetpack is a one click installer that will perform BSP installation, plus all relevant SDK (CUDA, cuDNN, TensorRT, VisionWorks)

Success Stories: developer.nvidia.com/embedded/learn/success-storiesPartners and Ecosystem: developer.nvidia.com/embedded/communityDeep Learning Institute: www.nvidia.com/object/deep-learning-institute.html Two Days To A Demo: developer.nvidia.com/embedded/twodaystoademoInception Program: www.nvidia.com/inception

RESOURCES

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END TO END SOLUTIONONE ARCHITECTURE FOR ALL

HYPERSCALE HPC

TESLA

VISUALIZATION

QUADRO

RESEARCHERS/ EARLY ADOPTERS

DGX-1

EDGE COMPUTING

JETSON

THANK YOU