https://satonaoki.wordpress.com/2022/06/26/ml15min-azure-ai-build-2022-updates/

1. Azure AI – Build 2022 Updates and more...
SATO Naoki (Neo)
Senior Software Engineer, Microsoft

3. How customers adopt AI
 Knowledge
Mining
60
%
 Reduction in cost
of compliance
 Conversational
AI
30
%
 Of all e-commerce will be
through voice by 2030
 Document Process
Automation
46
%
 Cost savings with process
automation in IT enterprises
 Machine
Translation
78
%
 Of language services utilize
Machine Translation
 Speech
Transcription &
Analytics
64%
 Of online education
experts use automated
transcription
Build, deploy and manage custom ML models
Solve common business scenarios
Knowledge
Mining
Conversational
AI
Business Process
Automation
Machine
Translation
Speech Transcription
& Analytics

5. ML platform
Azure Machine Learning
Azure AI
Vision Speech Language Decision OpenAI Service
Customizable, high quality AI models
Cognitive Services
Bot Service Cognitive Search Form Recognizer Video Indexer Metrics Advisor Immersive Reader
Scenario specific AI services
Applied AI Services

6. Preview
Preview
Preview
Auto-tuning capability Preview
Gated Preview
Gated Preview
Gated Preview

7. Preview
Document & Conversation Summarization Preview
Custom Named Entity Recognition Generally Available
Custom Text Classification Generally Available
Conversational Language Understanding Generally Available
Document Translation Generally Available

8. Public Preview

9. GitHub Copilot
https://github.com/features/copilot/

10. ML platform
Azure Machine Learning
Azure AI
Vision Speech Language Decision OpenAI Service
Customizable, high quality AI models
Cognitive Services
Bot Service Cognitive Search Form Recognizer Video Indexer Metrics Advisor Immersive Reader
Scenario specific AI services
Applied AI Services

11. Data
Preparation
Model
Building
Model
Training
Model
Management &
Monitoring
Model
Deployment
Responsible AI
MLOps

12. Structured Data
Unstructured Data Analytics
Business Apps
Prepare Data Build & Train Manage & Monitor
Deploy
across clouds and on-premises
Serverless
Compute
Managed
Kubernetes
Azure Edge & Hybrid
Azure Arc-enabled
Kubernetes
Edge/IoT Devices
Azure ML

13. MLOps

14. Preview
Generally Available
Preview
Generally Available
 Support for natural language processing and image tasks
 Generation of model training codes
 Enhancements for product integration and MLOps

15. Azure ML
Azure ML
Your editor of choice

16. Pipeline Metadata
name, display_name, version, type, etc.
Interface
input/output specifications (name, type,
description, default value, etc).
Command, Code & Environment
command, code and environment required
to run the component
SDK
CLI
UI

17. Fairness Inclusiveness
Privacy &
Security
Transparency
Reliability &
Safety
Accountability
Microsoft’s AI
Principles

18. Responsible AI investments and safeguards for facial recognition
https://azure.microsoft.com/en-us/blog/responsible-ai-investments-and-safeguards-for-facial-recognition/

20. Azure Machine Learning
Responsible AI Dashboard
& Responsible AI Scorecard
Managed endpoints
Python SDK v2
Arc support
Command Line Interface v2
Custom reusable
components (in pipelines)
Automated ML new features
Support for natural language
processing and image tasks
Generation of model
training codes
Enhancements for product
integration and MLOps
Integration with
RStudio Workbench