This session was held by Vladimir Brenner, Partner Account Manager, Disruptors & AI, Intel AI at the Dive into H2O: London training on June 17, 2019. Please find the recording here: https://youtu.be/60o3eyG5OLM

1. Vladimir Brenner
Intel Corporation
vladimir.brenner@intel.com
Acceleratingaiadoptionwithpartners

2. 2
Business
Imperatives
AI with Intel
and Partners
agenda
… on AI/ML/DL

3. 3
Business
Imperative

4. 4
4TBAutonomousvehicle
5TBCONNECTEDAIRPLANE
1PBSmartFactory
1.5GBAverage internetuser
750pBCloudvideoProvider
DailyBy2020
Source: Amalgamation of analyst data and Intel analysis.
Business
Insights
Operational
Insights
Security
Insights
Thedelugeofdata

5. 5
46%of Chief Information Officers (CIOs) have developed
plans to implement AI, but only
4% have implemented
AI so far.
According to a recent Gartner survey…
Aiadoptionisnascent
Source: Gartner Says Nearly Half of CIOs Are Planning to Deploy Artificial Intelligence. February 2018 (https://www.gartner.com/newsroom/id/3856163)

6. 6
AI with Intel
and Partners

7. 7
hardware Multi-purpose to purpose-built
AI compute from cloud to device
solutions Partner ecosystem to facilitate AI in
finance, health, retail, industrial & more
tools Software to accelerate development
and deployment of real solutions
BringYourAIVisiontoLifeUsingOurcomprehensive Portfolio

8. 8
1GNA=Gaussian Neural Accelerator
All products, computer systems, dates, and figures are preliminary based on current
expectations, and are subject to change without notice. Images are examples of intended
applications but not an exhaustive list.
IOT SENSORS
(Security, home, retail, industrial…)
Display, Video, AR/VR, Gestures, Speech
DESKTOP & MOBILITY
Vision &
Inference Speech
SELF-DRIVING VEHICLES
Autonomous
Driving
SERVERS, APPLIANCES & GATEWAYS
Latency-
Bound
Inference
Basic Inference,
Media & Vision
Most Use Cases
SERVERS & APPLIANCES
DatacenterEdgeEndpoint
Flexible & Memory
Bandwidth-Bound
Use Cases
Onesizedoesnotfitall
HARDWARE Multi-purpose to purpose-built
AI compute from device to cloud
Varies to <1ms <5ms <10-40ms ~100ms
Dedicated
Media & Vision
Inference
Most Use Cases
Most Intensive Use
Cases
NNP-L
M.2 CardSOC
Special Purpose Special Purpose

9. 9
LeadingAIresearch
Choose a partner on the cutting-edge of AI breakthroughs
Neuromorphic
Computing Test Chip
Codenamed “Loihi”
Quantum Computing
49-Qubit Test Chip
Codenamed “Tangle-Lake”
NEW AI
Technologies
@Intel Labs
All products, computer systems, dates, and figures are preliminary based on current expectations, and are subject to change without notice.

10. 10
† Formerly the Intel® Computer Vision SDK
*Other names and brands may be claimed as the property of others.
Developer personas show above represent the primary user base for each row, but are not mutually-exclusive
All products, computer systems, dates, and figures are preliminary based on current expectations, and are subject to change without notice.
TOOLS Software to accelerate development and
deployment of real solutions
TOOLKITS
App
Developers
libraries
Data
Scientists
foundation
Library
Developers
*
*
*
*
FOR
DEEP LEARNING DEPLOYMENT
OpenVINO™
†
Intel® Movidius™ SDK
Open Visual Inference & Neural Network
Optimization toolkit for inference deployment on
CPU/GPU/FPGA for TF, Caffe* & MXNet*
Optimized inference deployment
on Intel VPUs for
TensorFlow* & Caffe*
DEEP LEARNING FRAMEWORKS
Now optimized for CPU Optimizations in progress
TensorFlow* MXNet* Caffe*
BigDL/Spark*
Caffe2* PyTorch* PaddlePaddle*
DEEP LEARNING
Intel® Deep
Learning Studio‡
Open-source tool to compress deep
learning development cycle
MACHINE LEARNING LIBS
Python R Distributed
•Scikit-
learn
•Pandas
•NumPy
•Cart
•Random
Forest
•e1071
•MlLib (on Spark)
•Mahout
ANALYTICS, MACHINE & DEEP LEARNING PRIMITIVES
Python DAAL MKL-DNN clDNN
Intel distribution
optimized for
machine learning
Intel® Data Analytics
Acceleration Library
(incl machine learning)
Open-source deep neural
network functions for
CPU / integrated graphics
DEEP LEARNING GRAPH COMPILER
Intel® nGraph™ Compiler (Alpha)
Open-sourced compiler for deep learning model
computations optimized for multiple devices (CPU,
GPU, NNP) from multiple frameworks (TF, MXNet,
ONNX)
* * * ** * * *

11. 11
*Other names and brands may be claimed as the property of others.
All products, computer systems, dates, and figures are preliminary based on current expectations, and are subject to change without notice.
solutions
IntelAI
Builders
builders.intel.com/ai/membership
Your one-stop-shop to find systems,
software and solutions using Intel® AI
technologies
Reference
solutions
builders.intel.com/ai/solutionslibrary
Get a head start using the many case
studies, solution briefs and more reference
collaterals spanning multiple applications
Partner ecosystem to facilitate AI in
finance, health, retail, industrial & more

12. 12
INFERENCE THROUGHPUT
Up to
277x
1
Intel® Xeon® Platinum 8180 Processor
higher Intel optimized Caffe GoogleNet v1 with Intel® MKL
inference throughput compared to
Intel® Xeon® Processor E5-2699 v3 with BVLC-Caffe
1 The benchmark results may need to be revised as additional testing is conducted. The results depend on the specific platform configurations and workloads utilized in the testing, and may not be applicable to any particular user's components, computer system or workloads. The results are not necessarily representative
of other benchmarks and other benchmark results may show greater or lesser impact from mitigations. Software and workloads used in performance tests may have been optimized for performance only on Intel microprocessors. Performance tests, such as SYSmark and MobileMark, are measured using specific
computer systems, components, software, operations and functions. Any change to any of those factors may cause the results to vary. You should consult other information and performance tests to assist you in fully evaluating your contemplated purchases, including the performance of that product when combined with
other products. For more complete information visit: http://www.intel.com/performance.Software and workloads used in performance tests may have been optimized for performance only on Intel microprocessors. Performance tests, such as SYSmark and MobileMark, are measured using specific computer systems,
components, software, operations and functions. Any change to any of those factors may cause the results to vary. You should consult other information and performance tests to assist you in fully evaluating your contemplated purchases, including the performance of that product when combined with other products. For
more complete information visit: http://www.intel.com/performance Source: Intel measured as of June 2018. Configurations: See slide 4.
TRAINING THROUGHPUT
Up to
241x
1
Intel® Xeon® Platinum 8180 Processor
higher Intel Optimized Caffe AlexNet with Intel® MKL
training throughput compared to
Intel® Xeon® Processor E5-2699 v3 with BVLC-Caffe
Deliver significant AI performance with hardware and software optimizations on Intel® Xeon® Scalable Family
Optimized
Frameworks
Optimized Intel®
MKL Libraries
Inference and training throughput uses FP32 instructions
Intel®Xeon®processors
Now Optimized For Deep Learning

13. 13
… on AI/ML/DL

14. 14
1

15. 15
automatingaitransformation…together
• Extensive Tech IP Leadership
• Comprehensive Partner Ecosystem
• End to End Analytics and AI Solutions
• Customer Value Driven
• Open Source AI Leadership
• AI Democratization Commitment
• Tremendous AI momentum
• Customer Value Driven
Project“bluedanube”
• Increase AI adoption in the Enterprise
• Enable H2O.ai technologies on Intel AI
platforms
• Optimize H2O.ai Machine Learning
algorithms, libraries and models on
Intel Architecture
• Advance Data Science education
through H2O.ai Academy
• Accelerate H2O.ai objective of “using
AI to optimize AI”
+
“Shared vision for accelerating and Democratizing AI in
the enterprise” – Sri Ambati, H2O.ai CEO & Founder

16. 16
Intelandh2o.aiIntegratedAISolutions
Source: Gartner Says Nearly Half of CIOs Are Planning to Deploy Artificial Intelligence. February 2018 (https://www.gartner.com/newsroom/id/3856163)
Intel® 3D NAND SSD
H2O Driverless AI
Intel® Xeon® Scalable Processors Intel® Ethernet Adaptors
Intel® Data Analytics
Acceleration Library
(Intel® DAAL)
Open Visual Inference and
Neural Network Optimization
(OpenVINO™ toolkit)
Intel® Optimized
Deep Learning
Frameworks
Intel® Math Kernel
Library (Intel® MLK)
H2O Open Source Platform H2O Sparkling Water
Intel Platforms
Intel Optimized Libraries and Frameworks
H20.ai Machine Learning Platforms
Business Verticals & Performance Efficient Customer Use Cases

17. 17
Calltoaction
Source: Gartner Says Nearly Half of CIOs Are Planning to Deploy Artificial Intelligence. February 2018 (https://www.gartner.com/newsroom/id/3856163)
Work with & for your AI / ML / DL Related Projects
Visit: h2o.ai - software.intel.com – 01.org

18. backup

19. 19
This document contains information on products, services and/or processes in development. All information provided here is subject to change without
notice. Contact your Intel representative to obtain the latest forecast, schedule, specifications and roadmaps.
Intel technologies’ features and benefits depend on system configuration and may require enabled hardware, software or service activation. Learn more at
intel.com, or from the OEM or retailer. No computer system can be absolutely secure.
Tests document performance of components on a particular test, in specific systems. Differences in hardware, software, or configuration will affect actual
performance. Consult other sources of information to evaluate performance as you consider your purchase. For more complete information about
performance and benchmark results, visit http://www.intel.com/performance.
Cost reduction scenarios described are intended as examples of how a given Intel-based product, in the specified circumstances and configurations, may
affect future costs and provide cost savings. Circumstances will vary. Intel does not guarantee any costs or cost reduction.
Statements in this document that refer to Intel’s plans and expectations for the quarter, the year, and the future, are forward-looking statements that involve
a number of risks and uncertainties. A detailed discussion of the factors that could affect Intel’s results and plans is included in Intel’s SEC filings, including
the annual report on Form 10-K.
The products described may contain design defects or errors known as errata which may cause the product to deviate from published specifications. Current
characterized errata are available on request.
No license (express or implied, by estoppel or otherwise) to any intellectual property rights is granted by this document.
Intel does not control or audit third-party benchmark data or the web sites referenced in this document. You should visit the referenced web site and confirm
whether referenced data are accurate.
Intel, the Intel logo, Pentium, Celeron, Atom, Core, Xeon, Movidius and others are trademarks of Intel Corporation in the U.S. and/or other countries.
*Other names and brands may be claimed as the property of others.
© 2018 Intel Corporation.
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