Building smart applications with conversational interfaces and language services on AWS

Transcript

1. Alex Casalboni Technical Evangelist, AWS @alex_casalboni @ 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved Building smart applications with conversational interfaces and language services on AWS
2. About me • Software Engineer & Web Developer • Data Science background • Startup experience for 4+ years • AWS Customer since 2013
3. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Myth: AI is dark magic
4. AI Machine Learning Deep Learning What are we talking about?
5. The Advent of AI Data GPUs & Acceleration Cloud Computing Algorithms
6. How to ”build” intelligence?
7. Data Visualization & Analysis Business Problem – ML problem framing Data Collection Data Integration Data Preparation & Cleaning Feature Engineering Model Training & Parameter Tuning Model Evaluation Are Business Goals met? Model Deployment Monitoring & Debugging Yes No Data Augmentation Feature Augmentation The AI Process Re-training Predictions
8. Where to look at in your organisation ? Where data is being analyzed to help making decisions: • Sales • Marketing • Social media • Customer supports  • Logs
10. “Data is gold”
11. Pro-tips Make it ridiculously easy to collect and store any type of data. One line of code should be all it takes for anyone in the company to start collecting and storing new data points Make data ingestion cheap and highly scalable with managed services such as Amazon Kinesis Make data aggregation and exploration easy and accessible to everyone with services such as Amazon Athena and Amazon Quicksight
12. ML @ Amazon
17. Where do you start? The Low Hanging Fruits
18. Put machine learning in the hands of every developer Our mission
19. Some of our machine learning customers…
20. 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 Amazon ML Stack A I S E R V I C E S R E K O G N I T I O N I M A G E 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 R E K O G N I T I O N V I D E O Vision Speech Chatbots A M A Z O N S A G E M A K E R B U I L D T R A I N F O R E C A S T T E X T R A C T P E R S O N A L I Z E D E P L O Y M L O P S & A L G O S F r a m e w o r k s I n t e r f a c e s I n f r a s t r u c t u r e E C 2 P 3 & P 3 d n E C 2 C 5 F P G A s G 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 Language Forecasting Recommendations NEW NEW NEW NEW
21. Language capabilities Vision (OCR) Speech-to-Text (STT) Text-to-Speech (TTS) Natural Language Understanding Language Translation Chatbot Interface
22. Language capabilities on AWS Vision (OCR) Speech-to-Text (STT) Text-to-Speech (TTS) Natural Language Understanding Language Translation Chatbot Interface Amazon Rekognition & Textract Amazon Transcribe Amazon Polly Amazon Comprehend Amazon Translate Amazon Lex
23. How do you let your applications see the world? Amazon Rekognition Amazon Textract
24. Image and Video Analysis
25. Optical Character Recognition (OCR)
26. Amazon Textract – OCR++
27. Textract – How it works
28. How do you give your applications a voice? Amazon Polly
29. Amazon Polly “Good morning! My name is…” Text-to-speech (TTS) ! " # $
30. Polly • Content creation • Mobile & desktop applications • Internet of Things (IoT) • Education & e-learning • Telephony • Game development Use cases • 58 voices across 28 languages • Lip-syncing & text highlighting • Fine-grained voice control • Custom vocabularies • Available in 18 AWS Regions Key features
31. “With Amazon Polly our users benefit from the most lifelike Text-to-Speech voices available on the market.” Severin Hacker CTO, Duolingo
32. How do you make your applications listen? Amazon Transcribe
33. “Hi, how are you?” Amazon Transcribe Speech-to-text (STT)
34. English Italian French Spanish Portuguese New! Supported languages
35. Use cases Call centers Subtitles for VOD Broadcast closed captions Transcribe meetings
36. How do you extract insights from unstructured text? Amazon Comprehend
37. Sentiment Entities Languages Keyphrases Topic modeling Syntax Natural Language Understanding (NLU)
38. English Italian French German Portuguese New! Supported Languages
39. « Amazon Comprehend helps us analyze the key sentiments, objects, and geos in our 30 million plus reviews & testimonies. Now we are able to discover new insights into the unique experiences available at each property, so our customers can make the best decision possible for their travel.” Matt Fryer, VP and Chief Data Science Officer, Hotels.com
40. Comprehend Medical Extract health information from patient notes clinical trial reports electronic health records
41. Comprehend Medical
42. How do you make your applications multilingual? Amazon Translate
43. Supported languages Arabic Simplified Chinese French German Spanish Portuguese Japanese Traditional Chinese Italian Russian Turkish Czech (417 translation combinations) Danish Dutch Finnish Swedish Polish Hebrew
44. Think high volume and time-sensitive data Share of worldwide digital content Machine translation • User-authored content • Text Analytics • Real-time communication • Content discovery Post-edited machine translation • Legal documents • Healthcare documents • Advertising materials
45. How do you make your applications conversational? Amazon Translate
46. Amazon Lex End to End Speech to Intent ASR+NLU integrated into one API Dialog Management Native support & maintains context Text to Speech Amazon Polly integrated into API Business Logic Native integration with AWS Lambda Deployment One click deployment Security Encrypted data in transit & at rest Scale Completely managed service Analytics Monitor and improve End to End
48. Demo time!
49. Alex Casalboni Technical Evangelist, AWS @alex_casalboni @ 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved Thank you!