AWS TR Marketing

AWS AI ML Application Services - 24 September - 11:00

Published: October 13, 2019

AWS Loft Istanbul 2019 AWS AI ML Application Services - 24 September - 11:00

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AWS AI ML Application Services - 24 September - 11:00

1. Slide269 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | •Updated on Sept 23, 2019 •Any questions, please reach out to gautheyb@ •Any ideas and suggestions for this deck, please submit here
2. Slide109 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Centerpiece for digital transformation AWS Machine Learning
3. Slide4 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | CENTERPIECE FOR DIGITAL TRANSFORMATION 40% of digital transformation initiatives supported by AI in 2019 —IDC 2018 Innovation Decision making Customer experience Business operations Competitive advantage
6. Slide270 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | WHY AWS FOR ML? 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 AWS Named as a Leader in Gartner’s Infrastructure as a Service (IaaS) Magic Quadrant for the 9th Consecutive Year
7. Slide273 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | More machine learning happens on AWS than anywhere else More than ten thousand customers | 2x the customer references | 85% of TensorFlow projects in the cloud happen on AWS
8. Slide98 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Technology Bringing ML into your digital transformation requires a new “stack” that makes it easier to put ML to work
9. Slide281 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | AI Services Broadest and deepest set of capabilities THE AWS ML STACK ML Services ML Frameworks + Infrastructure POLLY TRANSCRIBE TRANSLATE COMPREHEND & COMPREHEND MEDICAL LEX FORECAST REKOGNITION IMAGE REKOGNITION VIDEO TEXTRACT PERSONALIZE Amazon SageMaker FPGAS EC2 P3 & P3DN EC2 G4 EC2 C5 INFERENTIA GREENGRASS ELASTIC INFERENCE DL CONTAINERS & AMIs ELASTIC KUBERNETES SERVICE ELASTIC CONTAINER SERVICE
10. Slide285 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | AI Services Broadest and deepest set of capabilities THE AWS ML STACK ML Services ML Frameworks + Infrastructure POLLY TRANSCRIBE TRANSLATE COMPREHEND & COMPREHEND MEDICAL LEX FORECAST REKOGNITION IMAGE REKOGNITION VIDEO TEXTRACT PERSONALIZE Amazon SageMaker FPGAS EC2 P3 & P3DN EC2 G4 EC2 C5 INFERENTIA GREENGRASS ELASTIC INFERENCE DL CONTAINERS & AMIs ELASTIC KUBERNETES SERVICE ELASTIC CONTAINER SERVICE
11. Slide248 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Bringing machine learning to all developers AMAZON SAGEMAKER Collect and prepare training data Choose and optimize your ML algorithm Set up and manage environments for training Train and tune model (trial and error) Deploy model in production Scale and manage the production environment
12. Slide249 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Bringing machine learning to all developers AMAZON SAGEMAKER Collect and prepare training data Choose and optimize your ML algorithm Set up and manage environments for training Train and tune model (trial and error) Deploy model in production Scale and manage the production environment Pre-built notebooks for common problems
13. Slide250 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Bringing machine learning to all developers AMAZON SAGEMAKER Collect and prepare training data Choose and optimize your ML algorithm Pre-built notebooks for common problems Built-in, high performance algorithms •K-Means Clustering •Principal Component Analysis •Neural Topic Modelling •Factorization Machines •Linear Learner (Regression) •BlazingText •Reinforcement learning •XGBoost •Topic Modeling (LDA) •Image Classification •Seq2Seq •Linear Learner (Classification) •DeepAR Forecasting
14. Slide251 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Bringing machine learning to all developers AMAZON SAGEMAKER Collect and prepare training data Choose and optimize your ML algorithm Set up and manage environments for training Train and tune model (trial and error) Deploy model in production Scale and manage the production environment Pre-built notebooks for common problems Built-in, high performance algorithms One-click training
15. Slide252 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Bringing machine learning to all developers AMAZON SAGEMAKER Collect and prepare training data Choose and optimize your ML algorithm Set up and manage environments for training Train and tune model (trial and error) Deploy model in production Scale and manage the production environment Pre-built notebooks for common problems Built-in, high performance algorithms One-click training Optimization
16. Slide253 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Bringing machine learning to all developers AMAZON SAGEMAKER Collect and prepare training data Choose and optimize your ML algorithm Set up and manage environments for training Train and tune model (trial and error) Deploy model in production Scale and manage the production environment Pre-built notebooks for common problems Built-in, high performance algorithms One-click training Optimization One-click deployment
17. Slide254 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Collect and prepare training data Choose and optimize your ML algorithm Set up and manage environments for training Train and tune model (trial and error) Deploy model in production Scale and manage the production environment Pre-built notebooks for common problems Built-in, high performance algorithms One-click training Optimization One-click deployment Fully managed with auto-scaling, health checks, automatic handling of node failures, and security checks Bringing machine learning to all developers AMAZON SAGEMAKER
18. Slide271 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | REDUCE COSTS INCREASE PERFORMANCE EASE-OF-USE One-click model training and deployment Train once run anywhere 10x better algorithm performance 2x performance increases from model optimization with Neo 70% cost reduction for data labeling using Ground Truth 75% cost reduction for inference with Elastic Inference AMAZON SAGEMAKER 90% cost reduction with managed spot training 90% AWS-optimized TensorFlow SECURITY & COMPLIANCE SOC, PCI, ISO, FedRAMP, DoD CC SRG, HIPAA, C5, OSPAR, HITRUST CSF
19. Slide272 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | •Fully-managed training and hosting •Near-linear scaling across 100s of GPU •75% lower inference costs with Amazon Elastic Inference •3x faster network throughput with EC2 P3 THE BEST PLACE TO RUN TENSORFLOW Amazon SageMaker is the best place to run TensorFlow in the cloud 65% Stock TensorFlow Scaling efficiency with 256 GPUs AWS-optimized TensorFlow 90%
20. Slide259 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Fueling product innovation Using AWS ML, Intuit developed ML models that can pull a year’s worth of bank transactions to find deductible business expenses for customers. Using SageMaker, Intuit reduced machine learning deployment time by 90%, from 6 months to 1 week.
21. Slide260 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | WATCH VIDEO >> Enhancing the fan experience One week of NFL games now creates 3 TB of data. NFL uses AWS ML to analyze telemetry data to predict plays. Computations that could take months to refine now take only weeks or days.
22. Slide261 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Driving better healthcare outcomes Using AWS ML, GE Healthcare developed an ML model that can learn from thousands of medical scans to detect anomalies more accurately and efficiently, allowing radiologists to prioritize patients needing immediate attention.
23. Slide265 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Accelerating financial analysis Using AWS ML, Siemens Financial Services developed an NLP model to extract critical information to accelerate investment due diligence, reducing time to summarize diligence documents from 12 hours down to 30 seconds.
24. Slide266 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Personalizing the gaming experience Using AWS ML, Sony Interactive Entertainment modernized the PlayStation Store, using predictive ML to drive highly personalized customer experiences, improve enterprise data reporting, and drive product feature innovation.
25. Slide286 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | AI Services Broadest and deepest set of capabilities THE AWS ML STACK ML Services ML Frameworks + Infrastructure POLLY TRANSCRIBE TRANSLATE COMPREHEND & COMPREHEND MEDICAL LEX FORECAST REKOGNITION IMAGE REKOGNITION VIDEO TEXTRACT PERSONALIZE Amazon SageMaker FPGAS EC2 P3 & P3DN EC2 G4 EC2 C5 INFERENTIA GREENGRASS ELASTIC INFERENCE DL CONTAINERS & AMIs ELASTIC KUBERNETES SERVICE ELASTIC CONTAINER SERVICE
26. Slide299 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Modernize your contact center to improve customer service Voice of the customer analytics | Automated service agents | Multi-lingual text support Workforce forecasting and agent analysis | Next best action recommendation POLLY TRANSCRIBE TRANSLATE COMPREHEND LEX
27. Slide298 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Use AI services to strengthen safety and security Risk assessment | Threat detection | Identity verification | Alarm prioritization REKOGNITION IMAGE COMPREHEND REKOGNITION VIDEO
28. Slide314 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Fighting human trafficking Marinus Analytics uses AWS ML to find human trafficking victims, then help law enforcement prosecute the traffickers.
29. Slide307 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Automate media workflows to reduce costs and monetize content Media metadata tagging | Highlight clipping | Subtitling and localization | Content moderation | Compliance | Contextual ad insertion REKOGNITION IMAGE REKOGNITION VIDEO COMPREHEND TRANSCRIBE TRANSLATE TEXTRACT
30. Slide180 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Scaling video indexing C-SPAN uses AWS ML to automatically index video news footage for search. C-SPAN reduced indexing time per video from 1 hour to 20 minutes and uploaded 97,000 images in under 2 hours.
31. Slide301 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Reduce localization costs and improve accuracy Website & document translation | Recorded call analysis | Video subtitling POLLY TRANSCRIBE TRANSLATE COMPREHEND
32. Slide295 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Understand the voice of your customer Problem detection | Sentiment analysis | Campaign targeting | Personalized service REKOGNITION IMAGE REKOGNITION VIDEO TRANSLATE TRANSCRIBE COMPREHEND
33. Slide305 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Personalize customer experiences with targeted recommendations Personalized recommendations | Personalized search | Personalized notifications PERSONALIZE
34. Slide224 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Personalizing customer experiences Domino’s uses AWS ML to customize and scale relevant marketing communications to customers based on time, context, and content, thereby improving and enhancing their experience with the Domino’s brand.
35. Slide296 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Accurately forecast future business outcomes Workforce planning | Product and advertising demand | Sales by store | Web traffic projection | Inventory optimization | AWS usage FORECAST
36. Slide303 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Increase efficiency with automated document analysis Fast archive search | Automated form processing | Systematic redaction TEXTRACT COMPREHEND & COMPREHEND MEDICAL
37. Slide304 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | PROTECT USERS FROM UNSAFE CONTENT UGC curation | Media compliance marking | Ad adjacency assurance REKOGNITION IMAGE TRANSCRIBE COMPREHEND
38. Slide284 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | AI Services Broadest and deepest set of capabilities THE AWS ML STACK ML Services ML Frameworks + Infrastructure POLLY TRANSCRIBE TRANSLATE COMPREHEND & COMPREHEND MEDICAL LEX FORECAST REKOGNITION IMAGE REKOGNITION VIDEO TEXTRACT PERSONALIZE Amazon SageMaker FPGAS EC2 P3 & P3DN EC2 G4 EC2 C5 INFERENTIA GREENGRASS ELASTIC INFERENCE DL CONTAINERS & AMIs ELASTIC KUBERNETES SERVICE ELASTIC CONTAINER SERVICE
39. Slide86 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Setting your organization up for success Culture
40. Slide107 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Setting your organization up for success 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
42. Slide291 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Partnerships with MOOCs AWS DeepRacer Reinforcement Learning ML learning devices AWS DeepLens Deep Learning Training & Certification ENABLING THE NEXT MACHINE LEARNING DEVELOPERS AWS ML Training and Certification
43. Slide292 ‹#› © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | THE AMAZON MACHINE LEARNING SOLUTIONS LAB More than 150 deployed ML engagements Ideation through to production Global footprint

AWS TR Marketing

AWS AI ML Application Services - 24 September - 11:00

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AWS AI ML Application Services - 24 September - 11:00