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ALISON B LOWNDES
AI DevRel | EMEA
@alisonblowndes
August 2020
2
NVIDIA
FUELLING THE AI
REVOLUTION
WITH GAMING
PROJECT SOL:
A Showcase for the Power of NVIDIA RTX
MINECRAFT RTX:
Real-time Ray Tracing in the World’s Most Popular Game
OMNIVERSE:
A Powerful Collaboration Platform for 3D Design
NASA MARS LANDER:
Visualizing NASA’s Supercomputer Simulations
Fuelling the AI Revolution with Gaming
4
5
66
25 YEARS OF ACCELERATED COMPUTING
X-FACTOR SPEED UP FULL STACK ONE ARCHITECTURESYSTEMS
GPU
CPU
7
ENABLING ENTERPRISE TRANSFORMATION WITH AI
End to End Application Frameworks
Desktop Development Data Center Solutions Accelerated Edge Supercomputers GPU-Accelerated Cloud
Jarvis Merlin Metropolis Clara Isaac Drive Aerial
Conversational
AI
Recommender
Systems
Smart Cities Healthcare Robotics Autonomous
Vehicles
Telecom
8
Original NVIDIA Campus
NVIDIA Endeavor (2017)
New Selene Datacenter (2020)
NVIDIA Voyager (2020)
9
10.5 MW
45,000 Sq. Ft.
10
NVIDIA’s DGX SuperPOD Deployment
THE SELENE SUPERCOMPUTER
27.6 PetaFLOPS HPL
20.5 GigaFLOPS/watt
1+ ExaFLOPS AI
Built from the NVIDIA DGX SuperPOD Reference Architecture
2nd generation SuperPOD Reference Architecture
NVIDIA DGX A100 and NVIDIA Mellanox InfiniBand network
The blueprint for AI power and scale, infused with the knowhow
from NVIDIA’s decade plus of AI experience
Configuration:
2,240 NVIDIA A100 Tensor Core GPUs
280 NVIDIA DGX A100 systems
494 Mellanox 200G HDR InfiniBand switches
7 PB of all-flash storage
One of the fastest and most efficient
supercomputers on the planet —
built in under one month
nvidia.com/en-us/data-center/dgx-a100/
11
NVIDIA A100
Greatest Generational Leap – 20X Volta
54B XTOR | 826mm2 | TSMC 7N | 40GB Samsung HBM2 | 600 GB/s NVLink
Peak Vs Volta
FP32 Training 312 TFLOPS 20X
INT8 Inference 1,248 TOPS 20X
FP64 HPC 19.5 TFLOPS 2.5X
Multi-instance GPU (MIG) 7X GPUs
12
NVIDIA CUDA-X AI ECOSYSTEM
13
EMBED SUPERNOVA VIDEO
14
NVIDIA BREAKS ALL 16 RECORDS IN AI PERFORMANCE
Among Commercially Available Systems
Benchmark Max Scale Records
(DGX SuperPOD)
Per Accelerator Records
(NVIDIA A100)
Recommendation (DLRM) 3.33 Min 0.44 Hrs
NLP (BERT) 0.81 Min 6.53 Hrs
Reinforcement Learning (MiniGo) 17.07 Min 39.96 Hrs
Translation (Non-recurrent) Transformer 0.62 Min 1.05 Hrs
Translation (Recurrent) GNMT 0.71 Min 1.04 Hrs
Object Detection (Heavy Weight) Mask R-CNN 10.46 Min 10.95 Hrs
Object Detection (Light Weight) SSD 0.82 Min 1.36 Hrs
Image Classification (ResNet-50 v1.5) 0.76 Min 5.30 Hrs
Per Chip Performance arrived at by comparing performance at the same scale when possible. Per Accelerator comparison using reported performance for MLPerf 0.7 NVIDIA A100 (8 A100s). MLPerf ID DLRM: 0.7-17, ResNet50 v1.5: 0.7-
18, 0.7-15 BERT, GNMT, Mask R-CNN, SSD, Transformer: 07-19, MiniGo: 0.7-20. Max Scale: All results from MLPerf v0.7 using NVIDIA DGX A100 (8xA100s). MLPerf ID Max Scale: ResNet50 v1.5: 0.7-37, Mask R-CNN: 0.7-28, SSD: 0.7-33,
GNMT: 0.7-34, Transformer: 0.7-30, MiniGo: 0.7-36, BERT: 0.7-38, DLRM: 0.7-17.
MLPerf name and logo are trademarks. See www.mlperf.org for more information.
15
NVIDIA JARVIS
Fully Accelerated Framework for Multimodal Conversational AI Services
End-to-End Multimodal Conversational AI Services
Pre-trained SOTA models-100,000 Hours of DGX
Retrain with NeMo
Interactive Response – 215ms on V100 versus 25sec on CPU
Deploy Services with One Line of Code
RETRAIN
video
audio
Multi-Speaker
TranscriptionNVIDIA GPU CLOUD NVIDIA AI TOOLKIT
Transfer Learning
NeMo
Service Maker
TRITON INFERENCE SERVER
Dialog Manager
Chatbot
Multi-
Speaker
Transcription
Look to Talk
Gesture
Recognition
Speech
Vision
NLU
Jarvis
Sign up for Early Access
https://developer.nvidia.com/nvidia-jarvis
16
17
MEGATRON
(August 2019)
https://devblogs.nvidia.com/training-
bert-with-gpus/
https://github.com/nvidia/megatron-lm
BERT-Large trained in 53 minutes on 92x
DGX-2H systems with model parallelism
2 millisecond inference with TRT/T4
18
ResNet-50
GPT
BERT-Base
BERT-Large
GPT-2
MegatronLM
T-NLG GPT-3
0 1 2 3 4 5 6 7 8 9 10
Model Size Comparison
HOW BIG?
Perspective
https://github.com/openai/gpt-3
19
TODAY’S AI
DATA CENTRE
50 DGX-1 systems for AI training
600 CPU systems for AI inference
$11M
25 racks
630 kW
20
5 DGX A100 systems for AI training
and inference
$1M
1 rack
28 kW
1/10th
COST
1/20th
POWER
$1M 28 kW
DGX A100
DATA CENTER
21
22
Fuelling the AI Revolution with Gaming
Currently get 1 day extreme rain forecast
which makes her crop vulnerable.
What if we could improve forecasting to
a 5 day forecast?
25% destroyed 95% harvested
25
26
AI REVOLUTION
AI in Space is More Critical Than Ever
Earth Observations Urban Planning Solar PredictionsPlanetary Defense
Planetary Exploration Manufacturing LunarMission Control
$400B INDUSTRY — Increase operational efficiency and safety across every challenge using AI
27
BUILDING AN AI MODEL
AI MODELFEATURES DEPLOYMENTDATA
DATA
ANALYTICS
MACHINE
LEARNING
MODEL
VALIDATION
NEW DATA
28
BUILDING AN AI PRODUCT
SENSORS
PERCEIVE REASON
PLAN
DATA
DATA
ANALYTICS
MACHINE
LEARNING
AI MODEL
VALIDATION
ACTUATORSAI MODEL
29
30
GoodAI talk by Kenneth Stanley (OpenAI) https://youtu.be/AwlLrugFcOc
“it is
biblical
in its
power”
https://arxiv.org/pdf/2003.
08536.pdf
31
32
NVIDIA ROBOTICS
RESEARCH LAB SEATTLE
Drive breakthrough robotics research
to enable the next-generation of
robots that safely work alongside
humans, transforming industries such
as manufacturing, logistics,
healthcare, and more
33https://arxiv.org/pdf/1810.05762.pdf
34
35
36
ISAAC PLATFORM FOR ROBOTICS
Nvidia's multi-tool for robotics
DESIGN
JETSON XAVIER
SIMULATE TRAIN DEPLOY
37
38
39
Virtual Production AECIsaac SimDriveSim
OMNIVERSE
DGX  EGX  RTX
EXPERIENCES BUILT ON OMNIVERSE
40
Fuelling the AI Revolution with Gaming
42
JETSON NANO
$99 NVIDIA CUDA-X AI Computer
CUDA-X acceleration stack | High-resolution sensor support | Runs all CUDA-X AI models
43
NVIDIA JETSON
Software-Defined AI Platform
Sensor Fusion & Compute Performance Expertise, Time to Market
JETSON COMPUTER
ECOSYSTEMSOFTWARE DEFINED
Jetpack SDK ∙ CUDA ∙ TensorRT ∙ TensorFlow ∙ ONMX ∙ ROS
Artificial Intelligence Computer Vision
Accelerated Computing Multimedia
Gesture rec
Obj detectPath planningDepth est
Pose est Speech rec
SDK, Design Tools, Libs, GEMs
Act
Sense
Reason
AI at the Edge
44
DEEP LEARNING INSTITUTE
Training  Labs
Nanodegrees
nvidia.com/DLI
TWO DAYS TO A DEMO
Create your first demo today
developer.nvidia.com/
embedded/twodaystoademo
JETSON DEVELOPER KIT
AGX Xavier Developer Kit $699
Xavier NX software patch
developer.nvidia.com/
buy-jetson
GTC
Largest event for GPU
developers
gputechconf.com
JETSON - START NOW
45
CLOUD NATIVE ON JETSON
Easier and Faster Deployment
- Eliminates complex, time-consuming builds and installs
Agile and Easier Development
- Update specific modules not the whole system
Scalability
- Push the right container to the right platform
Portable
- Deploy across various environments, from test to
production with minimal changes
Consistency Across Portfolio
- Update once and push broadly
Containers & Micro Services
46
GET STARTED WITH NGC
Deploy containers:
ngc.nvidia.com
Learn more about NGC offering:
nvidia.com/ngc
Technical information:
developer.nvidia.com
Explore the NGC Registry for DL, ML & HPC
47
PURPOSE BUILT PRE-TRAINED NETWORKS
Number of classes: 3
Dataset: 750k frames
Accuracy: 84%
Number of classes: 4
Dataset: 150k frames
Accuracy: 84%
Number of classes: 12
Dataset: 56k frames
Accuracy: 88%
Number of classes: 20
Dataset: 60k Frames
Accuracy: 92%
Number of Classes: 4
Dataset: 160k frames
Accuracy: 84%
Number of classes: 1
Dataset: 600k images
Accuracy: 95%
PeopleNet
TrafficCamNet
VehicleTypeNet
DashCamNet FaceDetect-IR
VehicleMakeNet
Highly Accurate | Re-Trainable | Out of Box Deployment
48
49
A massive Deep Learning challenge
50
BRIDGING THE REALITY GAP
https://arxiv.org/pdf/1804.06516.pdf NVR+University of Toronto
“leveraging the power of synthetic data improves upon results obtained using real data alone”
51
52
Oxford Nanopore
Sequence Viral
Genome in 7Hrs
Plotly, NVIDIA
Real-Time
Infection Rate Analysis
ORNL, Scripps
Screen
2B Drug Compounds in
1 Day vs 1 Year
Structura, NIH, UT Austin
CryoSPARC
1st 3D Structure of Virus Spike Protein
NIH, NVIDIA
AI COVID-19
Classification
Kiwibot
Robot Medical Supply
Delivery
Whiteboard Coordinator
AI Elevated Body Temp
Screening System
NVIDIA SCIENTIFIC COMPUTING FIGHTS COVID-19
Data
Analytics
Simulation &
Visualization
AI Edge
53
REVOLUTIONIZING
GENOMIC TESTING
Genome sequencing is the process of identifying
the DNA sequence of anything biological―animal,
food, water, air, plants. This ‘decoding’ is an
important step toward better scientific
understanding. Oxford Nanopore Technologies
is democratizing genome sequencing with
MinIT, a portable rapid analysis and device
control accessory to run the MinION
DNA/RNA sequencer. Powered by the
NVIDIA AGX System for high-throughput,
real-time analysis, MinIT will enable
DNA/RNA sequencing by anyone,
anywhere.
54
developer.nvidia.com
55
RICH
CONTENT
PORTFOLIO
Fundamentals and advanced
hands-on training in key
technologies and application
domains
AI for
Digital Content Creation
Deep Learning
Fundamentals
AI for HealthcareAI for Autonomous Vehicles
AI for
Intelligent Video Analytics
Accelerated Computing
Fundamentals
AI for Robotics
AI for
Predictive Maintenance
Accelerated Data Science
Fundamentals
Intro to AI in the Data
Center
AI for Anomaly Detection
AI for Industrial Inspection
nvidia.com/DLI
56
NVIDIA
INCEPTION
PROGRAM
Accelerates AI startups with a boost of
GPU tools, tech and deep learning expertise
Startup Qualifications
Driving advances in the field of AI
Business plan
Incorporated
Web presence
Technology
DL startup kit*
Pascal Titan X
Deep Learning Institute (DLI) credit
Connect with a DL tech expert
DGX-1 ISV discount*
Software release notification
Live webinar and office hours
*By application
Marketing
Inclusion in NVIDIA marketing efforts
GPU Technology Conference (GTC)
discount
Emerging Company Summit (ECS)
participation+
Marketing kit
One-page story template
eBook template
Inception web badge and banners
Social promotion request form
Event opportunities list
Promotion at industry events
GPU ventures+
+By invitation
www.nvidia.com/inception
INNOVATION NEVER SLEEPS
October 5 - 9, 2020 Register at www.nvidia.com/GTC
EXPERIENCE WHAT’S NEXT AT NVIDIA GTC ONLINE
This autumn’s GTC will run continuously for five days, across seven
time zones, showcasing the latest breakthroughs in AI, HPC,
graphics, networking, and more.
Attend live events in the time zone that works best for you or browse
an extensive catalog of on-demand content showcasing innovative
uses of GPU technology.
Use code: NVALOWNDES
58
THANK YOU
alowndes@nvidia.com

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Fuelling the AI Revolution with Gaming

  • 1. ALISON B LOWNDES AI DevRel | EMEA @alisonblowndes August 2020
  • 2. 2 NVIDIA FUELLING THE AI REVOLUTION WITH GAMING PROJECT SOL: A Showcase for the Power of NVIDIA RTX MINECRAFT RTX: Real-time Ray Tracing in the World’s Most Popular Game OMNIVERSE: A Powerful Collaboration Platform for 3D Design NASA MARS LANDER: Visualizing NASA’s Supercomputer Simulations
  • 4. 4
  • 5. 5
  • 6. 66 25 YEARS OF ACCELERATED COMPUTING X-FACTOR SPEED UP FULL STACK ONE ARCHITECTURESYSTEMS GPU CPU
  • 7. 7 ENABLING ENTERPRISE TRANSFORMATION WITH AI End to End Application Frameworks Desktop Development Data Center Solutions Accelerated Edge Supercomputers GPU-Accelerated Cloud Jarvis Merlin Metropolis Clara Isaac Drive Aerial Conversational AI Recommender Systems Smart Cities Healthcare Robotics Autonomous Vehicles Telecom
  • 8. 8 Original NVIDIA Campus NVIDIA Endeavor (2017) New Selene Datacenter (2020) NVIDIA Voyager (2020)
  • 10. 10 NVIDIA’s DGX SuperPOD Deployment THE SELENE SUPERCOMPUTER 27.6 PetaFLOPS HPL 20.5 GigaFLOPS/watt 1+ ExaFLOPS AI Built from the NVIDIA DGX SuperPOD Reference Architecture 2nd generation SuperPOD Reference Architecture NVIDIA DGX A100 and NVIDIA Mellanox InfiniBand network The blueprint for AI power and scale, infused with the knowhow from NVIDIA’s decade plus of AI experience Configuration: 2,240 NVIDIA A100 Tensor Core GPUs 280 NVIDIA DGX A100 systems 494 Mellanox 200G HDR InfiniBand switches 7 PB of all-flash storage One of the fastest and most efficient supercomputers on the planet — built in under one month nvidia.com/en-us/data-center/dgx-a100/
  • 11. 11 NVIDIA A100 Greatest Generational Leap – 20X Volta 54B XTOR | 826mm2 | TSMC 7N | 40GB Samsung HBM2 | 600 GB/s NVLink Peak Vs Volta FP32 Training 312 TFLOPS 20X INT8 Inference 1,248 TOPS 20X FP64 HPC 19.5 TFLOPS 2.5X Multi-instance GPU (MIG) 7X GPUs
  • 12. 12 NVIDIA CUDA-X AI ECOSYSTEM
  • 14. 14 NVIDIA BREAKS ALL 16 RECORDS IN AI PERFORMANCE Among Commercially Available Systems Benchmark Max Scale Records (DGX SuperPOD) Per Accelerator Records (NVIDIA A100) Recommendation (DLRM) 3.33 Min 0.44 Hrs NLP (BERT) 0.81 Min 6.53 Hrs Reinforcement Learning (MiniGo) 17.07 Min 39.96 Hrs Translation (Non-recurrent) Transformer 0.62 Min 1.05 Hrs Translation (Recurrent) GNMT 0.71 Min 1.04 Hrs Object Detection (Heavy Weight) Mask R-CNN 10.46 Min 10.95 Hrs Object Detection (Light Weight) SSD 0.82 Min 1.36 Hrs Image Classification (ResNet-50 v1.5) 0.76 Min 5.30 Hrs Per Chip Performance arrived at by comparing performance at the same scale when possible. Per Accelerator comparison using reported performance for MLPerf 0.7 NVIDIA A100 (8 A100s). MLPerf ID DLRM: 0.7-17, ResNet50 v1.5: 0.7- 18, 0.7-15 BERT, GNMT, Mask R-CNN, SSD, Transformer: 07-19, MiniGo: 0.7-20. Max Scale: All results from MLPerf v0.7 using NVIDIA DGX A100 (8xA100s). MLPerf ID Max Scale: ResNet50 v1.5: 0.7-37, Mask R-CNN: 0.7-28, SSD: 0.7-33, GNMT: 0.7-34, Transformer: 0.7-30, MiniGo: 0.7-36, BERT: 0.7-38, DLRM: 0.7-17. MLPerf name and logo are trademarks. See www.mlperf.org for more information.
  • 15. 15 NVIDIA JARVIS Fully Accelerated Framework for Multimodal Conversational AI Services End-to-End Multimodal Conversational AI Services Pre-trained SOTA models-100,000 Hours of DGX Retrain with NeMo Interactive Response – 215ms on V100 versus 25sec on CPU Deploy Services with One Line of Code RETRAIN video audio Multi-Speaker TranscriptionNVIDIA GPU CLOUD NVIDIA AI TOOLKIT Transfer Learning NeMo Service Maker TRITON INFERENCE SERVER Dialog Manager Chatbot Multi- Speaker Transcription Look to Talk Gesture Recognition Speech Vision NLU Jarvis Sign up for Early Access https://developer.nvidia.com/nvidia-jarvis
  • 16. 16
  • 17. 17 MEGATRON (August 2019) https://devblogs.nvidia.com/training- bert-with-gpus/ https://github.com/nvidia/megatron-lm BERT-Large trained in 53 minutes on 92x DGX-2H systems with model parallelism 2 millisecond inference with TRT/T4
  • 18. 18 ResNet-50 GPT BERT-Base BERT-Large GPT-2 MegatronLM T-NLG GPT-3 0 1 2 3 4 5 6 7 8 9 10 Model Size Comparison HOW BIG? Perspective https://github.com/openai/gpt-3
  • 19. 19 TODAY’S AI DATA CENTRE 50 DGX-1 systems for AI training 600 CPU systems for AI inference $11M 25 racks 630 kW
  • 20. 20 5 DGX A100 systems for AI training and inference $1M 1 rack 28 kW 1/10th COST 1/20th POWER $1M 28 kW DGX A100 DATA CENTER
  • 21. 21
  • 22. 22
  • 24. Currently get 1 day extreme rain forecast which makes her crop vulnerable. What if we could improve forecasting to a 5 day forecast? 25% destroyed 95% harvested
  • 25. 25
  • 26. 26 AI REVOLUTION AI in Space is More Critical Than Ever Earth Observations Urban Planning Solar PredictionsPlanetary Defense Planetary Exploration Manufacturing LunarMission Control $400B INDUSTRY — Increase operational efficiency and safety across every challenge using AI
  • 27. 27 BUILDING AN AI MODEL AI MODELFEATURES DEPLOYMENTDATA DATA ANALYTICS MACHINE LEARNING MODEL VALIDATION NEW DATA
  • 28. 28 BUILDING AN AI PRODUCT SENSORS PERCEIVE REASON PLAN DATA DATA ANALYTICS MACHINE LEARNING AI MODEL VALIDATION ACTUATORSAI MODEL
  • 29. 29
  • 30. 30 GoodAI talk by Kenneth Stanley (OpenAI) https://youtu.be/AwlLrugFcOc “it is biblical in its power” https://arxiv.org/pdf/2003. 08536.pdf
  • 31. 31
  • 32. 32 NVIDIA ROBOTICS RESEARCH LAB SEATTLE Drive breakthrough robotics research to enable the next-generation of robots that safely work alongside humans, transforming industries such as manufacturing, logistics, healthcare, and more
  • 34. 34
  • 35. 35
  • 36. 36 ISAAC PLATFORM FOR ROBOTICS Nvidia's multi-tool for robotics DESIGN JETSON XAVIER SIMULATE TRAIN DEPLOY
  • 37. 37
  • 38. 38
  • 39. 39 Virtual Production AECIsaac SimDriveSim OMNIVERSE DGX EGX RTX EXPERIENCES BUILT ON OMNIVERSE
  • 40. 40
  • 42. 42 JETSON NANO $99 NVIDIA CUDA-X AI Computer CUDA-X acceleration stack | High-resolution sensor support | Runs all CUDA-X AI models
  • 43. 43 NVIDIA JETSON Software-Defined AI Platform Sensor Fusion & Compute Performance Expertise, Time to Market JETSON COMPUTER ECOSYSTEMSOFTWARE DEFINED Jetpack SDK ∙ CUDA ∙ TensorRT ∙ TensorFlow ∙ ONMX ∙ ROS Artificial Intelligence Computer Vision Accelerated Computing Multimedia Gesture rec Obj detectPath planningDepth est Pose est Speech rec SDK, Design Tools, Libs, GEMs Act Sense Reason AI at the Edge
  • 44. 44 DEEP LEARNING INSTITUTE Training  Labs Nanodegrees nvidia.com/DLI TWO DAYS TO A DEMO Create your first demo today developer.nvidia.com/ embedded/twodaystoademo JETSON DEVELOPER KIT AGX Xavier Developer Kit $699 Xavier NX software patch developer.nvidia.com/ buy-jetson GTC Largest event for GPU developers gputechconf.com JETSON - START NOW
  • 45. 45 CLOUD NATIVE ON JETSON Easier and Faster Deployment - Eliminates complex, time-consuming builds and installs Agile and Easier Development - Update specific modules not the whole system Scalability - Push the right container to the right platform Portable - Deploy across various environments, from test to production with minimal changes Consistency Across Portfolio - Update once and push broadly Containers & Micro Services
  • 46. 46 GET STARTED WITH NGC Deploy containers: ngc.nvidia.com Learn more about NGC offering: nvidia.com/ngc Technical information: developer.nvidia.com Explore the NGC Registry for DL, ML & HPC
  • 47. 47 PURPOSE BUILT PRE-TRAINED NETWORKS Number of classes: 3 Dataset: 750k frames Accuracy: 84% Number of classes: 4 Dataset: 150k frames Accuracy: 84% Number of classes: 12 Dataset: 56k frames Accuracy: 88% Number of classes: 20 Dataset: 60k Frames Accuracy: 92% Number of Classes: 4 Dataset: 160k frames Accuracy: 84% Number of classes: 1 Dataset: 600k images Accuracy: 95% PeopleNet TrafficCamNet VehicleTypeNet DashCamNet FaceDetect-IR VehicleMakeNet Highly Accurate | Re-Trainable | Out of Box Deployment
  • 48. 48
  • 49. 49 A massive Deep Learning challenge
  • 50. 50 BRIDGING THE REALITY GAP https://arxiv.org/pdf/1804.06516.pdf NVR+University of Toronto “leveraging the power of synthetic data improves upon results obtained using real data alone”
  • 51. 51
  • 52. 52 Oxford Nanopore Sequence Viral Genome in 7Hrs Plotly, NVIDIA Real-Time Infection Rate Analysis ORNL, Scripps Screen 2B Drug Compounds in 1 Day vs 1 Year Structura, NIH, UT Austin CryoSPARC 1st 3D Structure of Virus Spike Protein NIH, NVIDIA AI COVID-19 Classification Kiwibot Robot Medical Supply Delivery Whiteboard Coordinator AI Elevated Body Temp Screening System NVIDIA SCIENTIFIC COMPUTING FIGHTS COVID-19 Data Analytics Simulation & Visualization AI Edge
  • 53. 53 REVOLUTIONIZING GENOMIC TESTING Genome sequencing is the process of identifying the DNA sequence of anything biological―animal, food, water, air, plants. This ‘decoding’ is an important step toward better scientific understanding. Oxford Nanopore Technologies is democratizing genome sequencing with MinIT, a portable rapid analysis and device control accessory to run the MinION DNA/RNA sequencer. Powered by the NVIDIA AGX System for high-throughput, real-time analysis, MinIT will enable DNA/RNA sequencing by anyone, anywhere.
  • 55. 55 RICH CONTENT PORTFOLIO Fundamentals and advanced hands-on training in key technologies and application domains AI for Digital Content Creation Deep Learning Fundamentals AI for HealthcareAI for Autonomous Vehicles AI for Intelligent Video Analytics Accelerated Computing Fundamentals AI for Robotics AI for Predictive Maintenance Accelerated Data Science Fundamentals Intro to AI in the Data Center AI for Anomaly Detection AI for Industrial Inspection nvidia.com/DLI
  • 56. 56 NVIDIA INCEPTION PROGRAM Accelerates AI startups with a boost of GPU tools, tech and deep learning expertise Startup Qualifications Driving advances in the field of AI Business plan Incorporated Web presence Technology DL startup kit* Pascal Titan X Deep Learning Institute (DLI) credit Connect with a DL tech expert DGX-1 ISV discount* Software release notification Live webinar and office hours *By application Marketing Inclusion in NVIDIA marketing efforts GPU Technology Conference (GTC) discount Emerging Company Summit (ECS) participation+ Marketing kit One-page story template eBook template Inception web badge and banners Social promotion request form Event opportunities list Promotion at industry events GPU ventures+ +By invitation www.nvidia.com/inception
  • 57. INNOVATION NEVER SLEEPS October 5 - 9, 2020 Register at www.nvidia.com/GTC EXPERIENCE WHAT’S NEXT AT NVIDIA GTC ONLINE This autumn’s GTC will run continuously for five days, across seven time zones, showcasing the latest breakthroughs in AI, HPC, graphics, networking, and more. Attend live events in the time zone that works best for you or browse an extensive catalog of on-demand content showcasing innovative uses of GPU technology. Use code: NVALOWNDES
  • 58. 58