Rekognition

• Find objects, people, text, scenes in images and videos using Machine Learning

• Facial analysis and facial search to do user verification, people counting

• Create a database of “familiar faces” or compare against celebrities

• Use Cases:

  • Labeling

  • Content Moderation

  • Text Detection

  • Face Detection and Analysis (gender, age, emotions, etc.)

  • Face Search and Verification

  • Celebrity Recognition

  • Pathing (ex: for sports game analysis)

Rekognition – Content Moderation

• Detect content that is inappropriate, unwanted, or offensive (image and videos)

• Used in social media, broadcast media, advertising, and e-commerce situations to create a safer user experience

• Set a Minimum Confidence Threshold for items that will be flagged

• Flag sensitive content for manual review in Amazon Augmented AI (A2I)

  

Transcribe

• Automatically convert speech to text

• Uses a deep learning process called automatic speech recognition (ASR)

• Automatically remove Personally Identifiable Information (PII) using Redaction

• Supports Automatic Language Identification for multi-lingual audio

• Use cases:

  • transcribe customer service calls

  • automate closed captioning and subtitling

  • generate metadata for media assets to create a fully searchable archive

Polly

• Turn text into lifelike speech using deep learning

• Allowing you to create applications that talk

Polly - Lexicon & SSML

• Customize the pronunciation of words with Pronunciation lexicons

  • Stylized words: St3ph4ne => “Stephane”

  • Acronyms: AWS => “Amazon Web Services”

• Upload the lexicons and use them in the SynthesizeSpeech operation

• Generate speech from plain text or from documents marked up with Speech Synthesis Markup Language (SSML) – enables more customization

  • emphasizing specific words or phrases

  • using phonetic pronunciation

  • including breathing sounds, whispering

  • using the Newscaster speaking style

Translate

• Language translation service

• Can use to localize content:

  • translate websites and applications for international users

  • translate large volumes of text efficiently

Lex & Connect

Lex

• Same technology that powers Alexa

• Automatic Speech Recognition (ASR) to convert speech to text

• Natural Language Understanding to recognize the intent of text, callers

• Helps build chatbots, call center bots

Connect

• Receive calls, create contact flows, cloud-based virtual contact center

• Can integrate with other CRM systems or AWS

• No upfront payments, 80% cheaper than traditional contact center solutions

Comprehend

• For Natural Language Processing (NLP)

• Fully managed and serverless service

• Uses machine learning to find insights and relationships in text

  • Language of the text

  • Extracts key phrases, places, people, brands, or events

  • Understands how positive or negative the text is

  • Analyzes text using tokenization and parts of speech

  • Automatically organizes a collection of text files by topic

• Sample use cases:

  • Analyze customer interactions (emails) to find what leads to a positive or negative experience

  • Create and groups articles by topics that Comprehend will uncover

Comprehend - Medical

• Detects and returns useful information in unstructured clinical text:

  • Physician’s notes

  • Discharge summaries

  • Test results

  • Case notes

• Uses NLP to detect Protected Health Information (PHI) – DetectPHI API

• Store your documents in Amazon S3, analyze real-time data with Kinesis Data Firehose, or use Amazon Transcribe to transcribe patient narratives into text that can be analyzed by Amazon Comprehend Medical.

SageMaker

• Fully managed service for developers / data scientists to build ML models

Forecast

• Fully managed service that uses ML to deliver highly accurate forecasts

  • Example: predict the future sales of a raincoat

• 50% more accurate than looking at the data itself

• Reduce forecasting time from months to hours

• Use cases: Product Demand Planning, Financial Planning, Resource Planning, etc.

Kendra

• Fully managed document search service powered by Machine Learning

• Extract answers from within a document (text, pdf, HTML, PowerPoint, MS Word, FAQs…)

• Natural language search capabilities

• Learn from user interactions/feedback to promote preferred results (Incremental Learning)

• Ability to manually fine-tune search results (importance of data, freshness, custom, …)

Personalize

• Fully managed ML-service to build apps with real-time personalized recommendations

  • Example: User bought gardening tools, provide recommendations on the next one to buy

• Same technology used by Amazon.com

• Integrates into existing websites, applications, SMS, email marketing systems, …

• Implement in days, not months (you don’t need to build, train, and deploy ML solutions)

• Use cases: retail stores, media and entertainment…

Textract

• Automatically extracts text, handwriting, and data from any scanned documents using AI and ML

• Extract data from forms and tables

• Read and process any type of document (PDFs, images, …)

Machine Learning - Summary

• Rekognition : face detection, labeling, celebrity recognition, content moderation,..

• Transcribe: audio to text (ex: subtitles)

• Polly: text to audio

• Translate: translations from one language to another

• Lex: build conversational bots – chatbots

• Connect: cloud-based virtual contact center

• Comprehend: natural language processing

• SageMaker: machine learning for every developer and data scientist

• Forecast: build highly accurate forecasts

• Kendra: ML-powered document search engine

• Personalize: real-time personalized recommendations

• Textract: detect text and data in documents