>> You're not going want to miss this episode of
The AI Show where Jeff Mendenhall shows us how to
reduce time to value with
Azure Applied AI Services. Make sure you tune in.
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>> Hello my friends and welcome to this episode of The AI Show.
Let me put the title up here so you can see it.
We're talking about reduced time to
value with Azure Applied AI Services with Jeff Mendenhall.
How are you doing, Jeff? Tell us who you are and what you do, bud.
>> I'm doing great. Thanks, Seth.
Well, great to be here. Thanks for having me on.
I'm Jeff Mendenhall, I'm the Principal PM
on Azure Applied AI Services and Decision AI,
which is really about applying AI to different business problems.
>> This is cool. Look, I'll be honest with you
because I try to be honest.
There are so many cognitive services that sometimes I
feel like I'm getting lost. What are your thoughts?
>> We've heard the exact same thing from our customers,
and so that's why we've created
this new category called Azure Applied AI Services.
Because as you're looking at
different facets of what you want to solve for your company,
I want to solve a video problem, hey,
I could go and look at the vision pillar within
cog services but if you want a specific scenario,
I want to analyze video and
streaming in real-time to do something with it,
I have Azure Video Analyzer now.
If I wanted to make a decision in monitoring or metrics,
I have Azure Metrics Advisor to tell me what to do,
who to notify when something happens.
Conversation, I've got Azure Bot Service.
You're going to hear from Gary a little more about that later.
Documents, I'm going to talk Azure Form Recognizer.
How can I simplify this?
Azure Cognitive Search, same
thing for search and knowledge capabilities.
Then for this great category for inclusion and accessibility,
we have Azure Immersive Reader,
which is going to help folks to be able to
read with any ability they have.
>> This feels like awesome solutions but can
people still go granular with cognitive services?
>> Absolutely. I think one of the key things we looked
at is start at the top and make it as easy as possible.
If you think of Azure Applied AI Services,
they already solved the scenario you want.
Again, it drops it down from months to days of development,
so we solve these scenarios super quick.
But if it doesn't solve your scenario,
then you drop down and take
the great AI models in Azure Cognitive Services,
which by the way, Azure Applied AI Services are
built each one on one or more of those services.
Again, just like if those didn't work and I'm
a data scientist and I really want to go deep,
I go to Azure Machine Learning.
>> I see. It's like a tiered approach.
If you have something you're trying to solve,
the Azure Applied AI Services are your best bet.
If you're going to go more granule,
you can go down the stack, so to speak.
>> Absolutely. Our goal is,
how do we make it as easy as possible?
The higher in the stack you are,
the quicker time to value that it will be.
>> Can you dive into specific scenarios
to drive this point home a little bit more?
>> Absolutely. Let me go and
pick apart a little bit on Form Recognizer.
If you think about that concept of, hey,
if I have Azure Cognitive Services,
OCR is one of the AI models within vision.
If you think about, hey, if I wanted
to take an image or a document,
I pass it through the OCR model.
It's going to tell me what's on that picture of that document,
and then I've got to go do something with that.
What we really wanted to solve here was, hey,
a lot of companies are writing all of
the orchestration and the specific document models around OCR,
and doing it again and again, and we're like,
"These are common problems most companies face.
Why don't we just go solve that for them?"
That's one of the genesis.
If you think about it, not only do we
take the documents and forms in, hey,
we still run it through that great OCR model,
but we also add on top of it pre-built models.
If you have a government ID, you have
an invoice, you have receipts,
and other categories, it'll
automatically detect what those are, and pre-label it,
and then format it out so that you have true understanding,
and then we wrap it all in a nice UI,
so you don't even have to drop down into [inaudible] ,
you can stay at the UI level.
Again, months of development to reorchestrate that today.
>> That's really cool because it's reminiscent
of what we always have done in programming.
We built little building blocks to make bigger solutions,
and sometimes we just want the solution and
not necessarily the little building blocks. This is really cool.
>> Right. It's the maturation of AI I think.
>> This is cool. Let's talk
specifically Microsoft Build just recently happened.
Is there anything new-new from Build?
>> Yea, there is. There's a couple of key things we're releasing.
One Is the preview of Azure Video Analyzer.
Adding Video Analyzer, think of
the capability of what you can do with streaming data.
Think of what airlines go through.
There's so many planes that land at gates every day.
Think of the accumulation of
those events over the course of the year.
Airlines really want is
a NASCAR experience where they can fine-tune and tweak,
how quickly can the plane land,
how quickly can I turn it around and get it back at the air?
We really looked at that.
One of the airlines determined that this was
$100 million a year problem or
opportunity if they could make this more efficient.
Our great partners, zero G with Lufthansa created
this portal that will tell you when the plane lands, hey,
when does the fuel truck come up,
when is the baggage cart come to
take the baggage off and the new one
come to take it on and it will do it in SLAs.
If you look at the chart on the right here,
that'll actually time the events.
Later, thousands of flights a day,
it'll tell you the insight of how did I perform?
Where do I need to put my investment or
time to make this operation better, huge opportunity.
Think of any operation
where you have a lot of streaming data that you want
to make a more optimal experience for your company.
>> This is really cool because I can see
all the little bits and pieces of AI.
Like for example, there might be text on there,
there might be motion, there might be people.
It's really cool to see the foundational blocks in there.
Is there anything else that's new-new from Build?
>> Absolutely. Would I disappoint you, Seth?
Of course, I've got something else for you.
Metrics Advisor also went
GA at Build this week and think of what you can do.
Instead of just having a tool that tells you these
are all the great anomalies
that you need to understand to do something with,
what we did was wrap that again with specific models on top of
what anomaly detector does and
created a great portal experience too.
You cannot only see, hey,
here's the anomalies that happened
but in these ranges, who should know?
Who should I notify that they need to go do something?
Will I send it to DevOps or do I send it to your e-mail?
I can now notify people and then tune and tweak
this throughout the process so I understand how my company,
my line, my satellites,
whatever it is I'm monitoring,
I can have this great experience
and understand visually what's going on.
>> This is awesome.
I saw a little bit of this a couple of months ago.
But the amazingness of it,
it's pretty cool, and now, for example,
you can test multiple variables,
you can see where it's coming from.
It's actually really cool stuff.
Here's another question.
I'm hoping maybe you have some answers to it.
Is anyone using these services to great effect?
>> They are. One of the cool things we did with
Bot Service is how do you create a brand's experience?
How do you carry that through
a chat modern experience for your customers as well?
Azure Bot Service was able to
recreate flow as a bot with a personality.
You can do it with a voice.
All of these aspects carry
progressive's brand on through that, and again,
because this was done with Azure Applied AI Service,
it was done very quickly because it was able to orchestrate
3-4 different cognitive services
and Azure communications services together in one package.
Just incredibly great way to do it,
and again in the UI portal experience.
>> That's cool. Anybody else?
>> Yeah. We also
have Chevron who was able to with Form Recognizer.
Again, think of all the different oil wells out there and they do
manual documentation with engineers
in the field to determine what's going on.
Think of all those forms and have different handwriting styles and
different way people address things across the world,
and again save hundreds and thousands
of hours and able to transcribe,
looking at what the forms are extract the intelligence,
and put it in citable format that Chevron can use.
It's just incredible. We're seeing
huge lift in a ton of customers with these.
>> This is really cool. If you could summarize for everybody,
how would you describe Azure AI Applied Services?
>> I think it's really how can I immediately take and update
my business processes so that they incorporate
artificial intelligence in days of work?
All I need is a developer.
I do not need someone with data science or deep machine learning
expertise so that we've abstracted that all the way.
You can quickly get to every developer's access
to these tools and really help
your business grow and expand by taking advantage.
>> I love it. Where can people go to find out more?
>> You can go to, well,
right here look at that link.
>> I just put it out there for you [inaudible]
>> Thank you. aka.ms/AIShow/AppliedAIServices or
obviously the Azure Applied AI Services will work as well.
You can see the documentation of all of these and flow through.
We release them at
Build so we're excited to see the uptake coming up.
>> Well, Jeff, it's been a pleasure being with you.
My friends, thank you so much for watching.
We're learning all about how to reduce time to value using
Azure Applied AI Services with Jeff Mendenhall.
Thank you so much for watching and
hopefully we'll see you next time. Take care.
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