>> You're not going to want to miss this episode of
The AI Show where Rob, Albert,
and Ashish take you through a no-code,
low-code solution for AI called AI Builder.
Make sure you tune in.
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>> How is the going everybody. Welcome to this episode of
The AI Show where myself and Albert are co-hosting.
I know you guys are used to seeing Seth on the show,
but we've taken over today for
an incredible episode with our good friend Ashish here.
We're going to be opening up a world of
low to no-code AI solutions with AI Builder.
I'll pass it over to Albert to introduce himself and we'll
get into this amazing demo.
>> Thank you for that Rob and great intro.
Hi, I'm Albert Dankwa.
I am a Content Program Manager over into land of Xbox,
but data and AI is everywhere.
Which is why that has brought me and Rob both to The AI Show.
Hopefully this will be the first of a number
of appearances from my both he and I, but enough chatting.
Let's get down to what we're really here for today.
>> Awesome. Ashish, I leave it to you.
>> Hello, everyone I'm super excited to be here.
My name is Ashish Bhatia,
manager in the AI BuilderTeam.
Today we're going to talk a little bit about low-code AI and
how we make the entire world of low-code and no-code
available in AI and have people play
around and democratizing AI for everyone one.
>> Let's see.
>> Let's go to the next slide.
Software development in today's macroeconomic situation
is almost everybody's job.
Docker says by 2025,
70 percent of new software development
will happen in low-code and no-code.
A lot of pro developers are also starting to leverage
the low-code platform to do
accelerated go-to-market of their solutions.
This thing is taking off and we're seeing a lot of traction,
especially with intelligent application and intelligent workflows.
>> Absolutely amazing and I love to see this Ashish, I mean,
thinking about AI and especially coming
from a world of a non-developer background,
being able to see how low-codes has
accelerated and how AI has accelerated in that space
is absolutely amazing and I'd love to continue
to learn more about AI Builder fits into that equation.
>> Absolutely. I come from visual basic days.
I used to use visual basic in school.
That draggy droppy interface was super-interesting for me and that
has come a long way when we've seen power Platform.
Let's go to next slide and talk
a little bit about Power Platform, the low-code platform.
This is the landscape of low-code,
no-code AI in Microsoft.
On the top you will see Power BI,
which is the business analytics too.
Power Apps. You could do application development in that.
With Power Pages, you can do website development.
Power Automate can be used for workflow automation,
and with Power Virtual Agents you
can develop intelligent chatbots.
Having all of this low-code,
no-code tools is an underlining
of data management which is Dataverse.
There's a local programming language which is Power Fx,
and then AI for all of Power Platform.
>> Well, wow, that's quite deep offering there, Ashish.
Actually, I do have a question.
I do see the AI Builder there within the Power Platform.
I am wondering though,
does AI Builder weave into
all these different apps and platforms here,
or is it something that's only like a few of them?
I'm definitely interested to see and learn more about this.
>> Most of the Power tools are built on that common fabric.
Slowly, we are bringing AI to all of these tools.
But we started off at Power Apps and Power
Automate some of the new tools like Power Pages.
This is a new entrant into this low-code development tools,
so gradually you will see AI
proliferate into those Power tools as well.
>> Absolutely amazing. My question Ashish,
and real quick before we even happen to
any of the demo content here is,
can we just really quickly explain how AI Builder
fits within the Azure ecosystem and
when does it make sense to be using AI builder versus
using Azure Machine Learning or Azure services in general?
>> Absolutely great question,
Rob, my next slide talks about that.
This is Microsoft AI Stack.
At the bottom you will see
Microsoft ML platform or
Azure ML platform as they're commonly known as.
This platform is for pro data scientists.
They have full control within modern architecture.
They train jobs when they want to deploy the model.
They have all the dials to tweak the models.
You can develop custom models
for your workloads and your solutions.
The pro data scientists are in control here.
They can peak performance.
This is for serious business.
The next layer is cognitive services layer or Azure AI services.
It adds cognitive dimensions to the underlining ML platform,
so vision, speech,
language decision, you'll see stuff like that.
This layer comes with a pre-built and customizable models.
But you still working with code in this layer.
It's still well appeals to
Pro-Developers and sometimes data scientists also use that.
But again, it will still see this coding business like,
when you come to the top layer,
that's the AI will relate the no-code,
low-code near and you'll see
the goodness of the underlining bubble up.
It's a conference of
all the underlying goodness into that top layer.
You still get a lot of pre-built models,
but you can also fine tune some of the models.
Then this layer is deeply
integrated as we talked in the previous slide,
into the Power Platform so you can get faster time to market.
It also comes with model governance
because to be honest admins
want to control which models go to production,
who builds the model and who has access to AI.
>> That's absolutely amazing.
I love the way this is broken down to really defined where
these areas sit and to what individual persona's they cater to.
I want to pause here and get to see this in action Ashish.
I would love to see AI Builder in
action and get to see some of the scenarios.
I would love to hop into that.
>> Let us go and see some demos.
What we trying to do here is create a simple Power App
using pre-built AI and the goal is
that we should be able to click an image of
a receipt or upload an image of a receipt.
Then the model should be able to extract
key pieces of information that you need for
your expense report and should be able to create
an expense report automatically. Let's see.
Again, this is very simple Canvas page.
We have scan your receipt and just an X button here.
I'll click and upload the receipt.
I went to buy lunch
yesterday and I had a receipt from there and opened that up.
As soon as the images uploaded,
model starts to identify information from the receipt.
Once it's done the identifying,
we can go to the next screen and submit the expense game.
You see the blue rectangles they can show identification
and we'll click "Next" in
populated a setup for you that I have chosen.
Just this simple example.
Merchant name, transaction date and total.
The expense is submitted.
We will get over to the SharePoint list,
which is a list where
all the expense reports should
show up and we should have a new entry then.
>> Just like that. Look at that.
>> Just like that.
>> Yes, it brings all the relevant information
that I chose to be there.
Then it uploads the image as well that it pick from.
>> Incredible.
>> Amazing choice of sandwiches.
By the way, I'd heard Albert mentioned
sandwich earlier and I agree.
>> Thinking about hungry.
>> But amazing to see
how quickly you were able to pull that data from that receipt.
>> Again, the application looks very similar and way simple.
It has two screens. One screen,
which is just a scanner tool which scans the image.
As soon as the image is uploaded,
the AI model runs underneath and extracts all the information and
the second screen is
mostly a harm with submits to a SharePoint list.
We have a working application.
This is pre-built AI receipt understanding
is the preferred model in AI Builder,
and could we leveraged any way
you're processing receipts for example.
>> Incredible.
>> That's amazing. Well, first of all,
before you even continue,
it's unrelated, but I hope you've
got some honey mustard on that sandwich.
I think it's the top tier topping,
but other than that,
is there something that can be done with expense reports?
Maybe I might have went on a trip recently
and it would be great to be able to
upload these receipts the same way he
was able to upload the sandwich.
>> Again, one of the other demos that I wanted to talk about is
a custom email demo where are actually
building the email component or the model behind it,
and let's take a look at that.
What we have here is invoices.
We get invoices at work a lot of times when we're working with
external vendors and we need to process that invoice.
Again, very similar example.
This time I'll upload the invoice in
a SharePoint and not an application so let's go to that.
>> Wonderful.
>> Go pick some invoice data that I have.
The first example was an example of working with power apps.
This example we're working with
public sets and automation workflow,
so you won't see any application running,
but what's happening is we have uploaded an invoice to
SharePoint and what happens is
there is a power app which is waiting for that clue.
As soon as a new invoice or file is uploaded to that SharePoint,
it'll get into action.
It'll take that PDF in this case,
extract all the relevant information
that I've already trained it for,
and then move that information somewhere else
so that an approval workflow can happen there.
What happened was the file got uploaded.
The automated flow would be running in the background.
If I refresh, let's see if the flow has finished.
We should see a third entry here, so not yet.
>> Let's give it one more refresh to see if it pops up.
>> That's right. There you go.
>> There we go. >> The [inaudible].
As it's extracting it, again,
key information that I have asked it
for so invoice number, due date,
billing address, some shaping total,
and then link to the original invoice as well.
Then what to date in the flow was I had it send an email to me.
As soon as my email opens,
we can see a new email that has this new invoice process.
Under the hood here is
a simple flow and the flow is waiting for a file to be
created in a given midpoint
and when the file is there it kicks in.
It extracts that file content and runs it through
an AI model that I have trained and it
finds out all those key pieces of information that I asked it
to look for and then it sends an email.
It also moves it to a new SharePoint list.
The model building experience was very simple.
This is something I'm passionate about I want to show.
For example, this is the model that I had trained.
If we go to the edit the draft again,
give it a few seconds to load i.
You see, it's a workflow here.
It's a Wizard approach so you not writing code.
You're dragging and dropping, your telling the system things.
In this case I've told it these are the things that I want
to extract from invoices
and I have given it a collection of training data.
My collection of training data has files,
so I gave it five documents,
and then I tag those documents.
If I look at a few documents,
this is my data I would have to
[inaudible] to where is the invoice.
I could drag and drop,
rectangular down various pieces
of information that are of interest and say,
hey, here's what I want to extract.
If I have invoice,
I have said, go train the model,
and out of it is a trained model.
These are examples of that.
It is simple. [inaudible].
>> Absolutely. Just taking a look at this and just
seeing how easily you were able to create this flow,
and be able to extract that data from the invoices.
Just thinking about this at scale,
and thinking about it from
an industry level and how much time can be saved,
how much money can be saved because this is
a task that nobody wants to do on a day to day basis.
Just being able to automate this process and have
the AI do the work for you I think it's instrumental,
and I think it's absolutely incredible to actually see this in
action and just see how simple and easy it is.
Like you said, the drag and drop
capabilities of this without a single line of
code being used is
something that's music to my ears, to be honest with you.
>> It could be said that saving
time like this can really boost work life balance.
It can really pave the way for innovation and
creativity just having more time
to make your best work so this is a truly outstanding.
>> Absolutely. Again,
when you come to AI Builder,
and again, you can come to AI Builder
via aka.ms, Try AI Builder.
If you go to the website,
you will land here in the Explorer Page.
In Explore Page shows you the collection of models that we have.
The collection has pre-built models and custom model as well.
The first example was a pre-built model
and then the second one was a custom model that I
have train based on
my own data to get a customer out of that training.
There we have AI Builder.
>> Amazing. That was awesome Ashish and again,
thank you so much for being part of the show today and
showcasing AI Builder and all the amazing capabilities for it.
Looking forward to having you on the show again to
dive a little bit deeper into some of those scenarios.
Albert, I'll pass it to you if you have
any other words that you want to close out with.
>> Of course, again, I want to echo Rob.
Thank you so much for taking us through all of this.
It really gets me more comfortable to try out AI because,
again, it's something that can seem
very out there and challenging,
but just seeing stuff such as pre-built models and really having
these opportunities to build and
create without doing too much like in a low code settings,
I'm very excited for this,
so thank you for this again Ashish.
>> Well said Albert.
IA can be very daunting,
especially for citizen developers and our mission is to make
that simple and easy to understand and easy to use,
and that's what we're after.
Thank you. It was a pleasure talking with you guys.
>> Absolutely. Thank you all for watching
and see you on the next episode.
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