At GoDataFest 2019, Guy Kfir presented how AI delivers a new experience to Formula 1 fans across the world. AWS fuels the analytics through machine learning. Did you know a Formula 1 race car contains 120 sensors and generated 3 GB of data every race at 1,500 data points per second? AWS developed several applications, including overtake possibility, pitstop advantage. How important is it for your company to invest in Machine Learning and AI? There are three scenario's for AI/ML success: Automation, Enrichment and Invention. So, what are you waiting for: create the loop, advance your data strategy and organize for succes. To get started identify AI/ML use cases, educate yourself, start with AI services and move to Amazon Sagemaker, engage with AWS, consider the partner eco system (like GoDataDriven or Binx).

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Artificial Intelligence in action:
Delivering a new experience to
Formula 1 fans
Guy Kfir
AWS EMEA AI/ML Business Development

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How important is it for your
company to invest in Machine
Learning and AI?

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How important is it for your
company to build better products
and deliver a better customer
experience?

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More users Better outcomes
More data Better decisions
A Flywheel for Data
More data than ever, but how do you use it?

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40% of digital transformation initiatives
supported by AI in 2019
—IDC 2018
InnovationDecision
making
Customer
experience
A I a n d M L C E N T E R P I E C E F O R D I G I T A L T R A N S F O R M A T I O N
Business
operations
Competitive
advantage

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Recommendations Logistics Transportation Virtual assistants Shopping

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Formula 1 selects AWS as
Official Cloud and Machine
Learning Provider
F1 has been using AWS to extract critical race performance
statistics, make race predictions, and give fans insight into
the split second decisions and strategies adopted by teams
and drivers

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AWS Fuels Analytics Through Machine Learning
Each car
has
120
sensors
3GB of
data
1,500
data points
per second

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Applying Machine Learning to the F1 Data
Overtake probability

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Applying Machine Learning to the F1 Data
Pit Stop Advantage

14. “We are solving problems with
machine learning and artificial
intelligence that were in the realm of
science fiction for the last several
decades. Natural language
understanding, machine vision
problems, it really is an
amazing renaissance.”
Jeff Bezos
Founder and Chief Executive Officer
Amazon.com, Inc.
https://www.geekwire.com/2017/jeff-bezos-explains-amazons-artificial-intelligence-machine-learning-strategy/

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…how does this help me?

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Our mission at AWS
Put machine learning in the
hands of every developer

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a new “stack” that makes it easier to put ML to work
Technology

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M L F R A M E W O R K S &
I N F R A S T R U C T U R E
A I S E R V I C E S
Vision | Documents | Speech | Language | Chatbots | Forecasting | Recommendations
M L S E R V I C E S Data labeling | Pre-built algorithms & notebooks | One-click training and deployment
Build, train, and deploy machine learning models fast
Easily add intelligence to applications without machine
learning skills
Flexibility & choice, highest-performing infrastructure
Support for ML frameworks | Compute options purpose-built for ML

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FRAMEWORKS INTERFACES INFRASTRUCTURE
AI Services
Broadest and deepest set of capabilities
T H E A W S M L S T A C K
VISION SPEECH LANGUAGE CHATBOTS FORECASTING RECOMMENDATIONS
ML Services
ML Frameworks + Infrastructure
P O L L Y T R A N S C R I B E T R A N S L A T E C O M P R E H E N D L E X F O R E C A S TR E K O G N I T I O N
I M A G E
R E K O G N I T I O N
V I D E O
T E X T R A C T P E R S O N A L I Z E
Ground Truth Notebooks Algorithms + Marketplace Reinforcement Learning Training Optimization Deployment HostingAmazon SageMaker
F P G A SE C 2 P 3
& P 3 D N
E C 2 G 4 E C 2 C 5 I N F E R E N T I AG R E E N G R A S S E L A S T I C
I N F E R E N C E

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W H Y A W S F O R A I ?
200 new features and services
launched this last year alone
Unmatched flexibility
Broadest and
deepest set of AI
and ML services
70% cost reduction
in data-labeling
10x faster performance
75% lower inference cost
Accelerate your
adoption of ML
with SageMaker
Built on the most
comprehensive cloud
platform optimized for ML
AWS holds the top spots
on Stanford’s benchmark,
for fastest training time, lowest
cost, lowest inference latency

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Customer Success

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10,000+ customers | 2x the customer references | 85% of TensorFlow projects in the cloud happen on
AWS

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3 scenarios for AI/ML success
1. Automation
• Optimize existing processes
• Maintain (or improve) quality & reduce cost
2. Enrichment
• Add new features to products and services
• Increase engagement & attract new customers
3. Invention
• Create new products and categories
• Leverage industry experience + AI expertise

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Increasing
customer engagement
Using Amazon SageMaker, Tinder analyzes millions of
match requests a minute, billions of swipes a day, across
more than 190 countries to make the perfect match. With
Amazon Rekognition, Tinder creates tags to highlight
photos, resulting in 20% increase in engagement.

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Connecting
tasks and doers
fiverr uses Amazon SageMaker to trigger product
recommendations and help users find exactly what they
need—including predictively, before they ask for it.

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Helping saving lives of
dogs and cats in shelters
will use Amazon SageMaker and AWS analytics
services to predict shelter capacity, track the
behavior of animals within the shelter, optimize
pet placement, and improve the efforts around
reuniting lost pets with their families in
emergencies and natural disasters

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Using Machine Learning to
optimize game-levels
Rovio uses deep reinforcement learning on AWS
to help predict the difficulty of levels in Angry
Birds Dream Blast. Saving Rovio’s developers
from spending 50% of their time on manually
optimizing game levels to few hours

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Saving lives by putting
technology in people’s
hands
SkinVision offers a free-to-download app that
allows people to scan their bodies in their own
homes and have the pictures assessed by
SkinVision's machine learning-based algorithms
in 30 seconds.
https://aws.amazon.com/solutions/case-studies/skinvision/

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So what will you
build next?

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How to move forward with AI/ML on AWS
Getting Started

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1
Create
the loop
Connect technology initiatives
with business outcomes
2
Assess your structured and
unstructured data sources
Advance your
data strategy
?
3
Put machine learning in the
hands of your developers
Organize
for success

32. 33© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved |
Getting started
• Identify AI/ML use cases that help your business
• Educate yourself with AWS AI/ML services
• Start with AI services, then look at Amazon SageMaker
• Engage with AWS, consider our Partner ecosystem and ProServe-AI

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H O W W E C A N H E L P
• Business Transformation
• System Integration
• Point Solutions
ML Competency Partners
• Practical education on ML for new
and experienced practitioners
• Based on the same material used
to train Amazon developers
Training and Certification
• Tech strategy
• Migration Assistance
• ML Architecture review
ML Specialist SA team
• Brainstorming
• Custom modeling
• Training
• Work side-by-side with Amazon experts
ML Professional Services

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Partnerships with MOOCsAWS DeepRacer
Reinforcement Learning
ML learning devices
AWS DeepLens
Deep Learning
Training & Certification
AWS ML Training and
Certification

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SageMaker Expertise
Practical education on ML for new & experienced practitioners: link
Self-Service
ML Education
Machine Learning Training & Certification
SageMaker 10 min tutorial link
SageMaker technical deep dive link
Online SageMaker lab: link
edX SageMaker online course: link
Cloud Guru ML certification link
Getting started with AWS ML link

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ML.aws
Guy Kfir
kfir@amazon.lu
Thank you!