Azure Cognitive Service
Adoption in Business
26 October 2020
Korkrid Akepanidtaworn
Global Cloud Solution Architect (Data Platform & AI)
GSMO Digital Transformation Partnerships Team
koakepan@microsoft.com
AGENDA
Overview of Microsoft AI
Success stories scenarios
Challenges in data science adoption (FAQs)
Technical demo: Azure Cognitive Services
How to get started in machine learning?
Overview of Microsoft AI
Microsoft AI momentum and innovations
Reasoning Understanding Interacting
Vision Speech Language
Happiness
Meaningful
Innovation
Empowering
People
Responsible AI
Web Search
Language
Vision Decision
Speech
Bing Autosuggest
Bing Web Search
Bing Entity Search
Bing Custom Search
Content Moderator
Anomaly Detector
Personalizer
Language Understanding
Text Analytics
Bing Spell Check
Translator Text
QnA Maker
Speaker Recognition
Speech
Computer Vision
Face
Video Indexer
Custom Vision
Form Recognizer
Ink Recognizer
Container Support Customizable
Immersive Reader
Vision
Speech
Language
Fueled by breakthrough research
2016
Object recognition
human parity
2017
Speech recognition
human parity
2018
Reading comprehension
human parity
2018
Machine translation
human parity
2018
Speech synthesis
near-human parity
2019
General Language
Understanding human parity
2020
Document summary at
human parity
1.8M
Hours of meetings
transcribed in real-time
1B
PowerPoint Designer
slides used
Tested at scale in Microsoft solutions
80M
Personalized experiences
delivered daily
Machine translation
human parity
Object detection
human parity
Switchboard
Switchboard cellular
Meeting
speech
IBM Switchboard
Broadcast speech
Speech recognition
human parity
Conversational Q&A
human parity
First FPGA deployed
in a datacenter
AI in Teams
Mobile
Companion
Mode
Inline Message
Translation
Meeting Recording
Transcription
Background
Blur
Data Scientists Analysts End users
Sentiment Analysis
Key Phrase Extraction
Create ML models
Explore predictions
Python Integration
R Integration
Extend with Azure ML
Integrate into reports
AI Visualizations
Natural Language
Power Platform
Power BI Power Apps Power Automate Power Virtual Agents
Developers
and
Data
Scientists
Citizen
Developers
Azure
Azure AI
ML platform
Customizable models
Vision, Speech, Language, Decision
Scenario-specific services
Cognitive Services
Azure Machine Learning
Cognitive Search
Bot Service Form Recognizer Video Indexer
Demo: Azure Cognitive Services
Success Stories Scenarios
Situation: Solution: Impact:
—Matthieu Boujonnier, Analytics Application Architect and Data Scientist, Schneider Electric
Customer: Schneider Electric
Industry: Power and Utilities
Size: 137,000 employees
Country: France
Products and services:
Microsoft Azure
Azure Databricks
Azure IoT Edge
Azure Machine Learning service
Products and Services Organization Size Industry Country
Businesses predict
weather impact
using cloud-based
machine learning
Nearly two billion people worldwide rely on AccuWeather forecasts to help them plan their day, protect
their assets, and stay safe. AccuWeather has been analyzing and predicting the weather for more than 55
years. Today it uses Microsoft Azure Machine Learning services to create custom weather-impact
predictions for business customers and transform its own business faster. The company’s D3 Data-Driven
Decisions service provides automated weather analytics to businesses eager to outwit Mother Nature.
United States
550 employees
Azure API Management
Azure App Service
Azure Blob storage
Azure Data Factory
Azure Machine Learning
Azure SQL Database
Partner Professional Services
How to get started with machine learning?
In partnership with
Visitors
250K
Countries
182
Engagement
670%
Avg Rating
4.8/5.0
aka.ms/aibs
Thank you

Data Science & Analytics Talk @ ExxonMobil

  • 1.
    Azure Cognitive Service Adoptionin Business 26 October 2020 Korkrid Akepanidtaworn Global Cloud Solution Architect (Data Platform & AI) GSMO Digital Transformation Partnerships Team koakepan@microsoft.com
  • 2.
    AGENDA Overview of MicrosoftAI Success stories scenarios Challenges in data science adoption (FAQs) Technical demo: Azure Cognitive Services How to get started in machine learning?
  • 3.
    Overview of MicrosoftAI Microsoft AI momentum and innovations
  • 4.
  • 5.
  • 6.
    Web Search Language Vision Decision Speech BingAutosuggest Bing Web Search Bing Entity Search Bing Custom Search Content Moderator Anomaly Detector Personalizer Language Understanding Text Analytics Bing Spell Check Translator Text QnA Maker Speaker Recognition Speech Computer Vision Face Video Indexer Custom Vision Form Recognizer Ink Recognizer Container Support Customizable Immersive Reader
  • 7.
  • 8.
    Fueled by breakthroughresearch 2016 Object recognition human parity 2017 Speech recognition human parity 2018 Reading comprehension human parity 2018 Machine translation human parity 2018 Speech synthesis near-human parity 2019 General Language Understanding human parity 2020 Document summary at human parity
  • 9.
    1.8M Hours of meetings transcribedin real-time 1B PowerPoint Designer slides used Tested at scale in Microsoft solutions 80M Personalized experiences delivered daily Machine translation human parity Object detection human parity Switchboard Switchboard cellular Meeting speech IBM Switchboard Broadcast speech Speech recognition human parity Conversational Q&A human parity First FPGA deployed in a datacenter
  • 10.
    AI in Teams Mobile Companion Mode InlineMessage Translation Meeting Recording Transcription Background Blur
  • 11.
    Data Scientists AnalystsEnd users Sentiment Analysis Key Phrase Extraction Create ML models Explore predictions Python Integration R Integration Extend with Azure ML Integrate into reports AI Visualizations Natural Language
  • 12.
    Power Platform Power BIPower Apps Power Automate Power Virtual Agents Developers and Data Scientists Citizen Developers Azure Azure AI ML platform Customizable models Vision, Speech, Language, Decision Scenario-specific services Cognitive Services Azure Machine Learning Cognitive Search Bot Service Form Recognizer Video Indexer
  • 13.
  • 14.
  • 15.
    Situation: Solution: Impact: —MatthieuBoujonnier, Analytics Application Architect and Data Scientist, Schneider Electric Customer: Schneider Electric Industry: Power and Utilities Size: 137,000 employees Country: France Products and services: Microsoft Azure Azure Databricks Azure IoT Edge Azure Machine Learning service
  • 16.
    Products and ServicesOrganization Size Industry Country Businesses predict weather impact using cloud-based machine learning Nearly two billion people worldwide rely on AccuWeather forecasts to help them plan their day, protect their assets, and stay safe. AccuWeather has been analyzing and predicting the weather for more than 55 years. Today it uses Microsoft Azure Machine Learning services to create custom weather-impact predictions for business customers and transform its own business faster. The company’s D3 Data-Driven Decisions service provides automated weather analytics to businesses eager to outwit Mother Nature. United States 550 employees Azure API Management Azure App Service Azure Blob storage Azure Data Factory Azure Machine Learning Azure SQL Database Partner Professional Services
  • 18.
    How to getstarted with machine learning?
  • 19.
  • 20.