For the last 3 decades, Microsoft has been powered by Machine Learning. Come to this session for a first time ever, under the hood look at how we use ML to improve every product and business at Microsoft. Then, see how that same technology is available to you in Azure.
The success of any organization in adopting AI to solve real-world problems is dependent on how we empower every developer to be productive using a comprehensive set of AI services, tools and infrastructure. Developers can build intelligent apps of the future by insusing AI, that delivers a unique, differentiated and personalized experience. In this demo and code heavy session, we will demonstrate how easy it is for every developers (without deep AI expertise) to build intelligence into their apps.
Microsoft has publicly committed $50 million over 5 years for artificial intelligence projects that support clean water, agriculture, climate, and biodiversity. Join us to learn about APIs that could literally change the way society monitors, models, and ultimately manages Earth’s life support systems.
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.
Building a website without a webserver on AzureTodd Whitehead
JamStack is a popular modern architecture for creating web apps apps using JavaScript, APIs, and prerendered markup all delivered without web servers. The end result is fast, dynamic and more secure web sites that can cost significantly less than traditional approaches. In this session I’ll share how I build retrodevops.com using the JamStack architecture, Hugo and Azure as well as lessons learned along the way.
Using Azure, AI and IoT to find out if the person next to you is a CylonTodd Whitehead
n this demo heavy session we will see how developers can combine Azure’s custom cognitive services and IoT Edge technologies to productionise AI models to the edge on something as small as a Raspberry Pi. In the past, machine learning at the edge required powerful and expensive machines known as “heavy edge” but are limited by continuous power supplies and direct connectivity to all sensors, making deployments constrained and expensive. By leveraging the computing power of Azure and easy to use services we will see how this is now in the reach of any developer.
The session will cover:
· Training Custom Cognitive AI in Azure
· Deployment options for your shiny new AI
· Using IoT Edge to deploy AI
· Rubbing a little DevOps on it
More data means better models, but it also means that you've got to scale in order to create those models. In this session we'll dive into scaling deep learning with Azure, showing how you can use any framework like Tensorflow, MXNet, PyTorch, Caffe, and more and take advantage of elastic GPU enabled hardware.
Inflight to Insights: Real-time Insights with Event Hubs, Stream Analytics an...Todd Whitehead
See how Azure can be used to provide real-time insights at scale using Event Hubs, Stream Analytics and unexpectedly an A10 Close Air Support attack aircraft! The session will demonstrate how to build an end to end solution to ingest, analyse and visualise insights quickly and affordably using the rich Azure platform. We will demonstrate the complete cockpit to insight solution, explaining the role and features of the various components as well as taking you step by step through how it was implemented. Finally we will explore other real-world workloads that would benefit from the power of real-time insights.
The success of any organization in adopting AI to solve real-world problems is dependent on how we empower every developer to be productive using a comprehensive set of AI services, tools and infrastructure. Developers can build intelligent apps of the future by insusing AI, that delivers a unique, differentiated and personalized experience. In this demo and code heavy session, we will demonstrate how easy it is for every developers (without deep AI expertise) to build intelligence into their apps.
Microsoft has publicly committed $50 million over 5 years for artificial intelligence projects that support clean water, agriculture, climate, and biodiversity. Join us to learn about APIs that could literally change the way society monitors, models, and ultimately manages Earth’s life support systems.
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.
Building a website without a webserver on AzureTodd Whitehead
JamStack is a popular modern architecture for creating web apps apps using JavaScript, APIs, and prerendered markup all delivered without web servers. The end result is fast, dynamic and more secure web sites that can cost significantly less than traditional approaches. In this session I’ll share how I build retrodevops.com using the JamStack architecture, Hugo and Azure as well as lessons learned along the way.
Using Azure, AI and IoT to find out if the person next to you is a CylonTodd Whitehead
n this demo heavy session we will see how developers can combine Azure’s custom cognitive services and IoT Edge technologies to productionise AI models to the edge on something as small as a Raspberry Pi. In the past, machine learning at the edge required powerful and expensive machines known as “heavy edge” but are limited by continuous power supplies and direct connectivity to all sensors, making deployments constrained and expensive. By leveraging the computing power of Azure and easy to use services we will see how this is now in the reach of any developer.
The session will cover:
· Training Custom Cognitive AI in Azure
· Deployment options for your shiny new AI
· Using IoT Edge to deploy AI
· Rubbing a little DevOps on it
More data means better models, but it also means that you've got to scale in order to create those models. In this session we'll dive into scaling deep learning with Azure, showing how you can use any framework like Tensorflow, MXNet, PyTorch, Caffe, and more and take advantage of elastic GPU enabled hardware.
Inflight to Insights: Real-time Insights with Event Hubs, Stream Analytics an...Todd Whitehead
See how Azure can be used to provide real-time insights at scale using Event Hubs, Stream Analytics and unexpectedly an A10 Close Air Support attack aircraft! The session will demonstrate how to build an end to end solution to ingest, analyse and visualise insights quickly and affordably using the rich Azure platform. We will demonstrate the complete cockpit to insight solution, explaining the role and features of the various components as well as taking you step by step through how it was implemented. Finally we will explore other real-world workloads that would benefit from the power of real-time insights.
Conversation Learner enables you to build task-oriented conversational interfaces that learn directly from example dialogues. Conversation Learner applies machine learning behind the scenes to decrease manual coding of dialogue control logic. Conversation Learner empowers developers to rapidly iterate to get to production quality and improve dialogues across multiple conversational channels.
Power BI is a cloud-based business analytics service that enables anyone to visualize and analyze data with greater speed, efficiency, and understanding. It connects users to a broad range of live data through easy-to-use dashboards, provides interactive reports, and delivers compelling visualizations that bring data to life.
Conversational AI and Knowledge Mining with Microsoft Cognitive Servicesİbrahim KIVANÇ
Compiled samples for Conversational AI and Knowledge Mining with Microsoft Cognitive Services. This slide deck is used in Microsoft Technology Summit 2019, Haliç Congress Center.
Meetup Toulouse Microsoft Azure : Bâtir une solution IoTAlex Danvy
Un tour d'horizon des solutions disponibles chez Microsoft pour bâtir une solution IoT. Il est question de Microsoft Azure bien-sûr, mais pas seulement. Windows, Machine Learning, Bots, OCF/AllJoyn, Hololens
Living on the (IoT) edge (Sam Vanhoutte @TechdaysNL 2017)Codit
In this session, Sam will dive deep into the new Azure IoT edge service that allows customers to build intelligent IoT solutions, combining the power of data intensive and low latency edge compute scenarios with the distributed, scalable power of the Azure cloud. Attendees will learn more about the architecture, use cases and programming possibilities of Azure IoT Edge and will understand how this technology can be applied to make modern IoT solutions in different industries. Expect a session with architecture design, scenarios and a lot of demos.
Learn how recent innovation at Google allows you to produce intelligence from IoT data. We will look at some use cases and you will get an overview of the building blocks we use to build truly intelligent IoT solutions in the cloud and on the edge.
Azure IoT Client SDK can be used to connect many different types of devices. At the lowest end, you can use it to connect a less than 3$ WiFi capable system on a chip microcontroller, such as the NodeMcu and WeMOS D1.
In this lecture we will see how to build a WiFI capable, Arduino based, cloud controlled IoT smart switch. We will then use a cross platform Xamarin based application to activate the smart switch. Using this application installed on a mobile phone we will open a car gate on stage as well as 7500 Miles (12,000 KM) away.
You will learn:
• An Internet of Thing system overview
• How to create and use the Azure IoT Hub
• Implementing an Azure IoT client SDK based solution
• Provisioning IoT devices, sending information to the cloud and receiving commands
• Arduino development using Visual Studio with Visual Micro
These slides are from Scott Guthrie's Windows Azure Overview presented on December 3rd 2013 in Dublin City University Ireland.
They give a overview of the difference features of Windows Azure and how Microsoft sees the Cloud landscape.
Real-Time Analytics with Apache Cassandra and Apache SparkGuido Schmutz
Time series data is everywhere: IoT, sensor data, financial transactions. The industry has moved to databases like Cassandra to handle the high velocity and high volume of data that is now common place. However data is pointless without being able to process it in near real time. That's where Spark combined with Cassandra comes in! What was one just your storage system (Cassandra) can be transformed into an analytics system and it's really surprising how easy it is!
Conversation Learner enables you to build task-oriented conversational interfaces that learn directly from example dialogues. Conversation Learner applies machine learning behind the scenes to decrease manual coding of dialogue control logic. Conversation Learner empowers developers to rapidly iterate to get to production quality and improve dialogues across multiple conversational channels.
Power BI is a cloud-based business analytics service that enables anyone to visualize and analyze data with greater speed, efficiency, and understanding. It connects users to a broad range of live data through easy-to-use dashboards, provides interactive reports, and delivers compelling visualizations that bring data to life.
Conversational AI and Knowledge Mining with Microsoft Cognitive Servicesİbrahim KIVANÇ
Compiled samples for Conversational AI and Knowledge Mining with Microsoft Cognitive Services. This slide deck is used in Microsoft Technology Summit 2019, Haliç Congress Center.
Meetup Toulouse Microsoft Azure : Bâtir une solution IoTAlex Danvy
Un tour d'horizon des solutions disponibles chez Microsoft pour bâtir une solution IoT. Il est question de Microsoft Azure bien-sûr, mais pas seulement. Windows, Machine Learning, Bots, OCF/AllJoyn, Hololens
Living on the (IoT) edge (Sam Vanhoutte @TechdaysNL 2017)Codit
In this session, Sam will dive deep into the new Azure IoT edge service that allows customers to build intelligent IoT solutions, combining the power of data intensive and low latency edge compute scenarios with the distributed, scalable power of the Azure cloud. Attendees will learn more about the architecture, use cases and programming possibilities of Azure IoT Edge and will understand how this technology can be applied to make modern IoT solutions in different industries. Expect a session with architecture design, scenarios and a lot of demos.
Learn how recent innovation at Google allows you to produce intelligence from IoT data. We will look at some use cases and you will get an overview of the building blocks we use to build truly intelligent IoT solutions in the cloud and on the edge.
Azure IoT Client SDK can be used to connect many different types of devices. At the lowest end, you can use it to connect a less than 3$ WiFi capable system on a chip microcontroller, such as the NodeMcu and WeMOS D1.
In this lecture we will see how to build a WiFI capable, Arduino based, cloud controlled IoT smart switch. We will then use a cross platform Xamarin based application to activate the smart switch. Using this application installed on a mobile phone we will open a car gate on stage as well as 7500 Miles (12,000 KM) away.
You will learn:
• An Internet of Thing system overview
• How to create and use the Azure IoT Hub
• Implementing an Azure IoT client SDK based solution
• Provisioning IoT devices, sending information to the cloud and receiving commands
• Arduino development using Visual Studio with Visual Micro
These slides are from Scott Guthrie's Windows Azure Overview presented on December 3rd 2013 in Dublin City University Ireland.
They give a overview of the difference features of Windows Azure and how Microsoft sees the Cloud landscape.
Real-Time Analytics with Apache Cassandra and Apache SparkGuido Schmutz
Time series data is everywhere: IoT, sensor data, financial transactions. The industry has moved to databases like Cassandra to handle the high velocity and high volume of data that is now common place. However data is pointless without being able to process it in near real time. That's where Spark combined with Cassandra comes in! What was one just your storage system (Cassandra) can be transformed into an analytics system and it's really surprising how easy it is!
Tour de France Azure PaaS 6/7 Ajouter de l'intelligenceAlex Danvy
Nous assisterons probablement à une rupture générationnelle entre les apps avec de l'intelligence artificielle et celles sans. Ces dernières, comme les applications en mode caractères à l'arrivée des interfaces graphiques, auront du mal à perdurer.
Azure met à dispositions 3 approches pour ajouter de l'IA dans une app, avec un niveau de difficulté graduel, de l'outil ne nécessitant aucune compétence particulière à celui dédié aux Data Scientistes.
2018 11 14 Artificial Intelligence and Machine Learning in AzureBruno Capuano
Slides used during my session "Artificial Intelligence and Machine Learning in Azure" for The Azure Group (Canada's Azure User Community) on November 14 2018.
Public group
Introduction to Machine learning and Deep LearningNishan Aryal
Overview of Machine Learning and Deep Learning. Brief introduction to different types of BI Reporting tools like Power BI, SSMS, Cortana, Azure ML, TenserFlow and other tools.
Big Data Advanced Analytics on Microsoft Azure 201904Mark Tabladillo
This talk summarizes key points for big data advanced analytics on Microsoft Azure. First, there is a review of the major technologies. Second, there is a series of technology demos (focusing on VMs, Databricks and Azure ML Service). Third, there is some advice on using the Team Data Science Process to help plan projects. The deck has web resources recommended. This presentation was delivered at the Global Azure Bootcamp 2019, Atlanta GA location (Alpharetta Avalon).
In this opportunity I spoke for almost 4 hours -with a lunch in between- about the analytics solutions on azure and it's tool for machine learning and cognitive services. I introduced the automated machine learning on Azure with some demos in real time.
Automated machine learning (automated ML) automates feature engineering, algorithm and hyperparameter selection to find the best model for your data. The mission: Enable automated building of machine learning with the goal of accelerating, democratizing and scaling AI. This presentation covers some recent announcements of technologies related to Automated ML, and especially for Azure. The demonstrations focus on Python with Azure ML Service and Azure Databricks.
Microsoft is working hard to make Artificial Intelligence available to everyone. We not only infuse AI in our products but also give you the platform to build your very own solution, that you are a developer, a citizen data scientist or a hard core data scientist.
This presentation covers some of the major data science and AI announcements from the May 2020 Microsoft Build conference. Included in this talk are 1) Azure Synapse Link, 2) Responsible AI, 3) Project Bonsai & Project Moab, and 4) AI Models at Scale (deep learning with billions of parameters).
In this session, we will take a deep-dive into the DevOps process that comes with Azure Machine Learning service, a cloud service that you can use to track as you build, train, deploy and manage models. We zoom into how the data science process can be made traceable and deploy the model with Azure DevOps to a Kubernetes cluster.
At the end of this session, you will have a good grasp of the technological building blocks of Azure machine learning services and can bring a machine learning project safely into production.
Visual Studio and Xamarin enable developers to create native Android and iOS apps with world-class tools in a fast, familiar, and flexible way. Join this tour of how you can use your existing C# and .NET skills to create fully native apps on every platform.
Best practices with Microsoft Graph: Making your applications more performant...Microsoft Tech Community
Learn how to take advantage of APIs, platform capabilities and intelligence from Microsoft Graph to make your app more performant, more resilient and more reliable
Build interactive emails for Outlook with Actionable Messages using Adaptive Cards. In this session, you will learn how to code a simple and great looking Actionable Message end-to-end.
As organizations deploy additional security controls to combat today’s evolving threats, integration challenges often limit the return of investment. The new security API in the Microsoft Graph makes it easier for enterprise developers and ISVs to unlock insights from these solutions by unifying and standardizing alerts for easier integration and correlation, bringing together contextual data to inform investigations, and enabling automation for greater SecOps efficiency. We will walk through real world examples of applications that leverage the security API to help customers realize the full value of their security investments.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
UiPath Test Automation using UiPath Test Suite series, part 4
AI @ Microsoft, How we do it and how you can too!
1.
2.
3. Agenda
Scaled out AI Platform with Search (Bing and
Ads)
AI Platform is now used across Microsoft
Microsoft needs and drives Open and
Interoperable AI
Azure AI Services
4. Several Billion dollar AI businesses at
Microsoft
Learned a ton as we built them
Bing Ads Story
My AI Story
7. Bing Ads Execution
Shipped once every 6 months
3 experiments / month
Big bets that didn’t work.
Created dev teams with core metrics
Pushed teams to move their metric
Developed AI Infrastructure to do
rapid experimentation.
Over a few years made >300x
improvement (1000/mo expr)
8. Experiment – 90% of ideas fail
Iterate – faster you try things, the more successful ideas you have
Build Infrastructure to enable fast iteration of experiments
14. Vector-based search:
Word is represented as vector.
Vector captures word meaning – its semantics.
Words with similar meanings get similar vectors.
In Bing, we trained a GloVe model over
Bing’s query logs and generated 300-
dimensional vector, enabled by deep
neural network.
Deep Learning: Semantic Understanding
15. Vector-based Retrieval
DL-generated vectors semantically represent queries, documents and passages
Doc retrieval based on query-doc-passage semantic similarity (vector distance)
AND
long
does
…
canned
how
Query: {how long
does a canned
soda last}
canned
does
how
long
…
Posting 1
Posting 2
Posting 3
Posting 4
…
Matching
BM25
Perfect Match
Sem. Similarity
Vector
Recall
…
(0.78, 0.8, 0.4, 0.3, …)
(0.75, 0.6, 0.1, 0.8, …)
…
Approximate Nearest Neighbor
Search (ANN)
RANKING STACK
16.
17. Bing AI Platform – Bing QnA
DATA PREP BUILD TRAIN DEPLOY INTELLIGENT APPS
ACTIONINTELLIGENCEDATA
Stored on
Cosmos
Æther with
TensorFlow
Philly
Ultra-fast Inferencing
using FPGAs
21. AI Transforms all businesses across Microsoft
AI is now done in almost every team
Products that don’t seem to obviously use AI are powered by it
Using the same tools and infrastructure to accelerate new teams
22. Took some time to warm up to the ideas…
To: Eric Boyd
From: xxxxx
Subject: ABC Experiment
…we have decided to ship the
XXX feature without running
the experiment first. We’re
quite confident in the
feature.
Our teams have a rich history
of shipping features without
any experimentation, something
that may be alien for folks
from Bing.
To: xxxxx
From: Eric Boyd
Subject: Re: ABC Experiment
I have a rich history of
driving my car with my eyes
closed. I’m quite confident I
know the way to work and have
only crashed a few times.
23.
24.
25. 0
5k
10k
15k
Dailykeptcount
Rule-based Machine learning
Models trained on
exploration data
Filter using user
interactions
Offline model
Machine Learning for SmartArt Suggestions
0
5
10
15
20
25
30
35
40
45
1-Apr 15-Apr 29-Apr 13-May 27-May 10-Jun 24-Jun 8-Jul 22-Jul 5-Aug 19-Aug 2-Sep 16-Sep 30-Sep 14-Oct 28-Oct 11-Nov 25-Nov
Slidekeptrate
26. Machine Learning for SmartArt Suggestions
0
50k
100k
150k
Dailykeptcount
Rule-based Machine learning
0
5
10
15
20
25
30
35
40
45
1-Apr 15-Apr 29-Apr 13-May 27-May 10-Jun 24-Jun 8-Jul 22-Jul 5-Aug 19-Aug 2-Sep 16-Sep 30-Sep 14-Oct 28-Oct 11-Nov 25-Nov
Slidekeptrate
More SmartArts,
trained on all data
Offline model
Filter using user
interactions
Models trained on
exploration data
27. Office – PowerPoint Designer
DATA PREP BUILD & TRAIN DEPLOY INTELLIGENT APPS
ACTIONINTELLIGENCEDATA
Stored on
Cosmos
Æther with
TLC (ML.NET)
Power Point
User Behavior
Data prep using
Azure Databricks
osi
31. Every business at Microsoft investing in AI
+ more!
1000s of Data Scientists & AI Developers
Classical ML & Deep Learning
Compliant & non-compliant data
Internal & OSS frameworks
Internal & OSS tools & languages
Deployments to Azure, AP, Windows, Mobile, Edge
32. Building your own AI models for Transforming Data into Intelligence
Prepare Data Build & Train Deploy
33. 8 Exabytes
30M events/sec
From 1B+ devices
Cosmos
Step 1: Prepare Data
GDPR compliant cloud data processing
system for near real-time ingestion &
processing
34. System for managing ML pipelines
Optimized for rapid prototyping, data reuse,
and collaboration
>20M Pipelines
>1.75M active Datasources (>2.7 total)
Æther
Step 2: Build and Train
36. Hyperparameter Tuning
As the models get more complex, the
space of hyperparameters to explore
increases exponentially!
Grid or Random Search becomes too
costly
Bayesian Optimization is used to optimize
Acquisition Functions
37. AI Platform
investments
Built an exabyte-scale data lake for everyone
to put their data of all types (structured and
unstructured)
Built AI tools approachable by any developer
Built machine learning tools for collaborating
across large experiment models
Summary
40. How do we get from raw point clouds to cloud intelligence?
Wall
Floor
Ceiling
Table
Chair
Background
Project Kinect for Azure
41. Depth and Deep Learning
Using the power of our AI tools and infrastructure, we can take that raw output and train a
model capable of high fidelity environment perception.
Input: Project
Kinect for Azure
Raw Depth +
Active Brightness data Labelling Tool
Labelled
“Ground Truth”
Training Set Test Set
Philly
CNTK model
Analytics Client
ONNX model
43. Labelled “Ground
Truth”
Raw Depth + Active
Brightness data
Labelling Tool Labelled “Ground
Truth”
Building the Training Data – How do we scale?
TABLE
50. ONNX enables models to be trained in one framework and transferred to another for inference.
CPUGPU
ML HW
DSPFPGA
High level API &
Framework Frontends
Hardware Vendor
Libraries & Devices
Any tools exporting ONNX models can benefit ONNX-compatible runtimes and libraries designed
to maximize performance on some of the best hardware in the industry.
Seamless Interoperability
ONNX.ai
52. Contribute
Get Involved
github.com/onnx
ONNX is a community project. We
encourage you to join the effort
and contribute feedback, ideas,
and code. Join us on Github.
Use ONNX
ONNX.ai
Start experimenting today. Check
out our Getting Started Guide,
Supported Tools, and Tutorials.
Follow Us
Stay up to date with the latest
ONNX news.
onnxai
onnxai
57. Intelligent Disease Prediction
Data Prep Build Train Deploy Intelligent Apps
Azure Machine
Learning
IoT Hub
WindowsML
IOT Edge
Model:
DenseNet-121
Code:
Keras +
TensorFlow
National Institute
of Health
Chest Xray Data
112,120 images
14 pathology labels
30,805 unique patients
Visual Studio
Tools for AI
Azure
Deep Learning GPU VM
VSTS +
CI/CD
CosmosDB +
Azure Functions
NuGet
60. With , you don’t have to be the
size of Bing to solve the problem
61. Bringing the best of AI to Azure and the best of Azure to AI
Pre-Build AI
Azure Cognitive Services
Conversational AI
Azure Bot Services
Custom AI
Azure Machine Learning
62. Integrated with Azure Machine Learning
Create new deep learning projects easily
Scale Out with Azure Batch AI
Monitor model training progress & GPU utilization
Visualize your model processing with integrated open
tools like TensorBoard
Get started quickly with the Samples Gallery
Productive AI developer tools to train
models and infuse AI into your apps
63. 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
Customizable
ML.NET Preview
Cross-platform open Source Machine learning framework for .NET
Extensively used across Microsoft: Windows, Bing, Azure
High productivity for complete workflow
Extensible to other frameworks (TensorFlow, CNTK…)
64. Microsoft scale Tools/Services available/coming to you
Cognitive Toolkit (CNTK)
ML.Net
ONNX
Azure Batch AI
Hyper Parameter Tuning in Azure ML
Project BrainWave (FPGA model acceleration) in Azure ML
Visual Studio Tools for AI
And more coming soon…
71. Cloud data processing system
Near real time ingestion
Near real time processing
Fully GDPR compliant
8 Exabytes
30M events/sec
From 1B+ devices
COSMOS Æther
System for managing ML
pipelines
Optimized for rapid
prototyping, data reuse, and
collaboration
• >20M Pipelines
• >1.75M active Datasources
(>2.7 total)
Data Prep -> Build/Train -> Deploy
DLIS
Run multiple models in
parallel
ML, DL, Transforms &
Featurizers
Abstracting platform details
(CPU/GPU/FPGA)
600K req/sec
<35ms latency