Join Joseph Sirosh, Corporate Vice President of the Cloud AI Platform, for a deep dive into the AI platform and exciting AI use cases. Joseph will showcase how every developer can infuse intelligence into their applications and create amazing new experiences with AI. In this exciting overview, you will learn about the application of AI technologies in the cloud. We will help you understand how to add pre-built AI capabilities like object detection, face understanding, translation and speech to applications. We will show how developers can build Cognitive Search applications that understand deep content in images, text and other data. We will also show how the platform can be used to build your own custom AI models for predictive applications and how to use the Azure platform to accelerate machine learning. Joseph will also show how companies assemble end-to-end systems of intelligence using the rich variety of data and application development services on Azure.
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The Microsoft AI platform: a State of the Union
1.
2.
3.
4.
5.
6. Helpicto Architecture
DATA PREP BUILD, TRAIN & DEPLOY INTELLIGENT APPS
Stored on
Azure Blob and SQL DB
Xamarin
Helpicto Images
Cognitive Services,
Azure Functions
7. Bringing the best of AI to Azure and the best of Azure to AI
Pre-Built AI
Azure Cognitive Services
Conversational AI
Azure Bot Service
Custom AI
Azure Machine Learning
8. How Developers Use AI in Azure
Build Modern Applications with AI
Understand & interpret meaning of data
including text, voice, images
Build Conversational Applications
Engage with users in natural ways
Optimize Business Processes with AI
Reason, learn & form conclusions from data
Azure
Cognitive Services
Azure
Bot Services
Azure
Machine Learning
9. Powerful prebuilt AI models exposed as API services
Simple REST APIs with .NET, Java, Python, Node SDKs
Easily customize for highest accuracy
Train in the cloud and deploy anywhere
Vision
Speech
Language
Conversation
Bing Search
Knowledge
10.
11. 1. Object Detection & Recognition for thousands of objects
2. Video Indexer (Preview)
3. Speech Recognition with customization
4. Speech Synthesis with customizable voice
5. Speech to Speech Translation
6. Text analytics with entity detection
7. Language Understanding (LUIS) with new integrated offer
8. QnA Maker is Generally Available
9. Bing Visual Search with smart identification
10.Bing Search SDK is Generally Available
Vision
Speech
Language
Conversation
Bing Search
Knowledge
24. 190,000 total bots registered
33000 active bots in service
>3200 bots created per week
25. What is a Bot?
{ Your Code }
Intelligence Cognitive Services
Tools Bot Framework
HTTP
REST Endpoint
Services Bot Service
Cortana OthersFacebookSkype
Conversational and
Business logic
Development
tools
40. Building your own AI models for Transforming Data into Intelligence
Prepare Data Build & Train Deploy
41. Quickly launch and scale Spark on demand
Rich interactive workspace and notebooks
Seamless integration with all Azure data services
Azure Databricks
Step 1: Prepare Data
Apache® Spark™ based analytics
platform optimized for Azure
42. Broad frameworks and tools support:
TensorFlow, Cognitive Toolkit, Caffe2, Keras, MxNET, PyTorch
Scale training from 1 100,000’s of servers
Azure ML Python SDK
Azure ML packages:
Computer Vision, Text, Forecasting
Azure Machine Learning
Step 2: Build and Train
44. Integrated with Azure Machine Learning
Create new deep learning projects easily
Monitor model training progress & GPU utilization
Visualize your model performance with integrated
open tools like TensorBoard
Get started quickly with the Samples Gallery
45. The Machine Learning framework made by and for .NET developers
Proven & Extensible
Open Source
Supported on Windows, Linux, and macOS
Developer Focused
Join at github.com/dotnet/machinelearning
ML.NET Preview
Cross-platform Open Source Machine learning framework for .NET
Extensively used across Microsoft: Windows, Bing, Azure
High productivity throughout the entire ML workflow
Extensible to other frameworks (TensorFlow, CNTK…)
Learn more: BRK 3203 on Tuesday, May 8th at 1:15pm.
46. ML.NET Usage at Microsoft
+ more!
Windows 10
Power Point
Excel
Bing
47. Forecasting
Text Analytics
Supported on Windows, Linux, and macOS
Computer Vision
Azure ML Packages Preview
Python packages for Computer Vision, Forecasting and Text Analytics
Easily build and deploy models on Azure Machine Learning
Provides high level APIs for data preparation, augmentation, training,
evaluating and deployment.
Model experimentation and comparison, run history, model
management and deployment through Azure ML
Join at BRK 3226 What's new with Azure Machine Learning (breakout session)
51. The Machine Learning framework made by and for .NET developers
Supported on Windows, Linux, and macOS
Azure ML and Project Brainwave
Real-time AI at cloud scale with industry-leading performance and lowest cost
Models are very easy to create and deploy as webservices
Record-setting DNN performance with accelerated ResNet50
Record speed: ResNet 50 on FPGA in <1.8 ms per image
Lowest cost: Only 21 cents per million images during preview
More accelerated models coming soon
52.
53. FPGAs for ultra-fast inferencing
DATA PREP BUILD TRAIN DEPLOY
Stored on
Azure Premium Storage
Azure Machine
Learning
Jabil Classification Model
ResNet-50
Circuit board images
Jupyter Notebook
Azure Machine Learning
Ultra-fast Inferencing
using FPGAs
58. Planet scale Real-Time Inferencing for GeoAI
svFreely Available Imagery Labeled Training Data Inferred Land Cover Map
59. 415K
images/sec
FPGA
Real-Time Low-Latency Inferencing with FPGAs
Setup:
800 FPGAs on Azure
195 Million Images; 20TB
Real-time inferencing 1 image at a time
Results:
415K inferences/second @ 1.8ms latency
10.6 minutes total
Order of magnitude better Price/Perf
over CPU & GPU (V100 with TensorRT
62. What we demonstrated
Build Modern Applications with AI
1. Content based indexing, search and analysis
Build Conversational Applications
2. Engaging with users in natural ways through chats,
speech, voice and translation
Optimize Business Processes with AI
3. Building custom AI models for classification
4. Real-time AI with FPGAs and edge support
Cognitive Search
(Azure Search +
Azure Cognitive Services)
Azure
Bot Services
Azure
Machine Learning
65. Why you should develop your next AI app on Azure
1. Broadest set of Pre-Built AI capabilities
2. Customizable and flexible AI services
3. Most advanced conversational AI
4. Most differentiated support for AI @ the Edge + unique
hardware for AI
5. The strongest enterprise cloud for Data + AI