(upbeat music)
- Welcome to Azure AI essentials.
In this video, I'll walk you through
what artificial intelligence or AI can enable
and how you can harness the power of Azure AI services
to create breakthrough experiences in your applications.
So let's start with the basics.
What is AI?
Simply put, AI is the ability of computers to perform tasks
that are typically characteristic of humans.
AI enables computers to learn from massive amounts of data
and to interact and respond more naturally with the world.
With AI computers can now see
with computer vision capabilities,
that allow them to interpret the world visually
through video and images.
They can listen and translate, transcribe
and interpret written or spoken language
and are even able to carry on a dialogue
through chat and speech,
which is known as conversational AI.
And they can reason by understanding relationships
between people, things, places, and events,
which enables them to automatically detect
unusual activity in a system,
personalized recommendations for an individual,
and much more.
AI was once limited to researchers and institutions,
but with cloud AI services and tools, now every developer
can leverage AI to create innovative applications
that solve complex problems and enhance customer experience.
We aim to empower you to use AI in your applications
regardless of skill level.
And to enable you to develop on your terms
using the tools and languages of your choice.
Azure AI services are the result of years of research.
Our Microsoft research team
has made significant breakthroughs
in the AI categories of vision, speech, and language.
In fact, we were the first to reach parody with humans
for tasks like object recognition,
speech recognition, machine translation,
conversational QnA and most recently image captioning.
These breakthroughs are not just academic.
Customers are taking advantage of them today.
These are industry leading AI models
that have been tested at scale.
And that provide enterprise grade security,
availability, compliance, and manageability
for your most mission critical applications.
In fact, Microsoft infuses AI into many of our products.
From facial recognition via Windows Hello,
to real time translation
while you're speaking in PowerPoint,
to advance threat detection across multiple products.
Azure AI has helped create
a billion PowerPoint designer slides,
deliver 6 million personalized experiences per day on X-Box,
and transcribed 10 million hours of speech every month
with Microsoft Teams.
we also have an uncompromising commitment to responsible AI.
We don't use customer data to train our models
and we ensure your data privacy is always respected.
At every stage of our AI research,
development and deployment,
we keep principles like inclusiveness, fairness,
transparency, and accountability in mind.
And Azure has the best privacy controls
and responsible AI capabilities,
as well as the most compliant certifications
of any cloud in the world.
We also offer tools and resources to help you understand,
protect, and control your AI at every stage of innovation,
including responsible ML tool kits,
responsible bot development guidelines and more.
Azure AI portfolio has options for every developer.
Whether you're looking for prebuilt AI models,
advanced machine learning capabilities,
or a low-code/no-code development experience.
In the next few minutes I'll walk you through
our AI services and capabilities,
and how you can use them
to enhance your applications with AI.
So let's start by looking at Azure Cognitive Services.
Azure Cognitive Services provide
the most comprehensive portfolio
of customizable AI models on the market.
And the first AI services to achieve human parody
in computer vision, speech and language.
Azure cognitive services can be grouped
into four core categories:
Vision, language, speech and decision.
All it takes is an API call to embed the ability to see,
hear, speak, search, understand
and accelerate decision-making into your apps.
And you can also customize AI models using your own data
without any machine learning expertise required.
These models can also be deployed to containers
so you can run them anywhere.
Let's start with vision.
Vision AI models enable your apps to identify
and analyze content within images and videos.
Embed pre-built models into your apps to help label content,
extract printed and handwritten text and recognize objects.
You can also create a custom vision model
for your specific domain and scenario simply by uploading
and labeling a few images.
GE Aviation uses Azure Computer Vision
to quickly convert handwritten and printed documents
to digital format, providing a single source of truth
for their maintenance record system.
Next, we have language models.
To build applications that can understand natural language,
create custom language models to enable users to interact
with your applications, bots and IOT devices
by using natural language.
You can also translate texts in real time,
across over 70 languages
to support translation for call centers,
multi-lingual conversational agents and more.
And take advantage of pre-built models,
which can identify key phrases and entities in text
and perform sentiment analysis.
So you can better understand customer perception.
Developers at the BBC
use Azure's language understanding service
to help their virtual assistant understand user requests.
And we're able to train a custom model
with relatively few examples.
The speech models allow you to integrate speech processing
into your apps and services.
Save time by easily transcribing speech to text,
whether you're cataloging customer service calls
or creating a voice enabled virtual assistant.
Translate speech in real time and build custom models
to translate terms specific to your business.
Leverage over 110 voices to build applications
that can speak naturally
or customize the voice unique to your brand.
Using Azure speech to text and text to speech models,
Motorola solutions helps emergency first responders
gain faster access to important information
through a voice powered virtual assistant.
Finally, decision models enable you
to make smarter decisions faster,
create safe and positive user experiences
with content moderation capabilities that can detect
and filter potentially offensive
or inappropriate images, texts and videos.
Deliver personalized experiences for every user
of your website or application with models
and improve over time based on user behavior.
And build apps that can help you identify potential problems
before they happen.
Airbus is running Azure's decision AI models
in containers to help identify potential issues
with their satellites.
Accelerating the troubleshooting process.
These cognitive services are powerful building blocks
for developers to add AI to applications.
For business users, we provide access to the same AI models
through AI builder.
Which provides a no-code experience to train models
and integrate them into apps
within Microsoft power platform.
For common solutions like chat bots and AI powered search,
we've gone a step further providing services
which accelerate development for these solutions.
These scenario specific services often bring together
multiple cognitive services along with business logic
and a user interface to solve for a common use case.
Let's take a look at just a few
of the scenario specific services Azure provides.
Azure Bot Service enables you to develop intelligent bots
that help you enrich your customer experience.
Build a Q&A bot in just a few clicks
or create your own branded virtual assistant
using the open and extensible bot framework.
To better engage their customers, insurance provider,
Progressive, use Azure bot service to build a chat bot
with the voice and personality
of their iconic spokesperson flow.
Next, we have Azure Cognitive Search.
Today's organizations have a wealth of information
at their fingertips, but it can be difficult to search
and make sense of all this content.
Azure Cognitive Search is a search as a service solution
with built-in AI capabilities.
That gives you APIs and tools to deliver
a rich search experience over all kinds of content at scale.
A great example is Penguin Random House,
a leading book publisher that's using Cognitive Search
to index data on their consumers,
retailers and book sales.
Form recognizer helps automate business processes
by extracting key information from documents
such as forms and receipts.
Chevron chose to use Form Recognizer
because of its ease of implementation.
And they've been able to drastically reduce time
by automating data extraction from reports
in a wide range of formats.
And Metrics Advisor monitors the performance
of your organization's growth engines
from sales revenue to manufacturing operations.
It helps you quickly identify and fix problems
through a combination of monitoring in near real time,
adapting models to your scenario,
offering granular analysis with diagnostics and alerting.
Noss telecommunications is using Metrics advisor
to identify potential network device failures
to improve customer service.
Finally, if you're looking to develop
advanced machine learning models,
Azure Machine Learning enables you to quickly build,
train and deploy machine learning models
with experiences for all skill levels ranging from
code first to a drag and drop no code experience.
Food and beverage company Nestle,
chose Azure Machine Learning to help them
build a custom cybersecurity solution, which has resulted
in faster detection times and reduced false positives
around malicious phishing attacks.
Azure AI provides services that empower all developers
to responsibly and easily
build mission critical AI powered solutions.
In future videos,
I'll walk you through foundational concepts and demos
to help you get started
building AI powered applications on Azure.
So stay tuned.
(upbeat music)