Descubra cómo la pila de AWS ML / AI puede ayudar a impulsar estas iniciativas para todos los niveles de conocimiento y necesidades.

2. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Daniel M. Bernao
Solution Architect
13th November 2019
Big Data e Inteligencia Artificial en
AWS

3. Agenda
• Intro to Machine Learning and AI in AWS
• Our approach to Machine Learning
• ML/AI Stack
• Demo

4. 40% of digital transformation initiatives
supported by AI in 2019
—IDC 2018
InnovationDecision
making
Customer
experience
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

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

6. 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
Why AWS for AI

7. Customer-focused
90%+ of our ML roadmap is
defined by customers
Pace of innovation
200+ new ML launches
and major feature updates last year
Breadth and depth
A wide range of AI and ML services
Multi-framework
Support for the most
popular frameworks
Security and analytics
Deep set of security with robust encryption
and analytics
Embedded R&D
Customer-centric approach
Our Approach to Machine Learning

8. 10,000+ customers | 2x customer references | 85% of TensorFlow in the cloud on AWS

9. 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
The AWS ML stack: Broadest & deepest set of capabilities
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

10. 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
& C O M P R E H E N D
M E D I C A L
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
D L
C O N T A I N E R S
& A M I s
E L A S T I C
K U B E R N E T E S
S E R V I C E
E L A S T I C
C O N T A I N E R
S E R V I C E

11. Demo

12. Thank you

13. Biblioteca multimedia automática
Amazon
S3
Video
De
Comparecencia
Amazon
Rekognition
Amazon
S3
Amazon
Comprehend
Transcripción
Caras, personas, etiquetas
Clasificación
Amazon
DynamoDB
AWS
Lambda
Proceso Automático
Biblioteca de Video
etiquetada por
persona y contenido
Video Análisis

14. 1a. Scan ID
2. Submit
details
4. Verify ID
5. Return reference
picture
6a. IndexFaces
ExternalImageID
7. CompareFaces
SearchFacesByImage
8. Store Metadata and
final decision
1b. Live pic
3. Store live
pic
API Gateway
Amazon
Rekognition
Amazon
Rekognition
Amazon
DynamoDB
Secure verification source
Lambda
6b. FaceId
ValidaciondeImagenes