>> You're not going to want to miss
this episode of The AI Show where we
look at what's new in the Cognitive Services Face API.
It's pretty cool. Make sure you tune in.
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Hello and welcome to this special build edition
of the AI Show where we're going to learn all
about what's new in the Cognitive Services, Special Face API.
I've got a special guest with me.
Hello, my friend. Tell us who you are and what you do.
>> Hello. Good morning.
My name is Boris Ganesh Golsky.
I work on the Face API Cognitive Services Team.
>> Fantastic. So for those that
don't know what Cognitive Services are,
can you give us just a little refresher?
>> Yeah. So Cognitive Services is a suite of
pre-built AI models that are
delivered via the Cloud and via the Edge,
and they allow developers to quickly infuse AI capabilities into
their applications without needing to
have machine learning or computer vision expertise.
>> So for those who don't know about face recognition,
can you give us a little primer?
>> Yeah. So facial recognition Cognitive Service
has three key capabilities.
One is face detection,
so you can provide the images and we will
return you back bounding boxes of faces,
if faces are found in images.
We will also return you additional information
for every face that's found in the image.
The number two capability is face verification.
So this is the ability to compare two faces
and determine whether they belong to the same person or not.
Capability number 3 is facial identification,
which is basically look at an image
and answer the question, who is it?
Relative to a list of enrolled faces.
>> I see now. Are these hard to use in the Face API?
What did the developer have to do to
make these functionality work?
>> Yeah. So to make this functionality work,
you need to create a Face API Resource in the Azure portal.
Then we offer a number of SDKs in various languages,
that you can use to quickly get started.
We also offer a number of
samples that you can use as a quick starting point.
Generally, the calling pattern for all of
these APIs is you take an image and you first call
detect and we will return you a set of information that you can
either use to reason over an image or
if you want to use verification or identification,
then the information we return from the Detect API
can be further used to make it verify or identify a call.
>> So not much just basically
call an endpoint and then it does it for you?
>> Yeah. Call an endpoint, it does it for you.
There's great samples and
documentation that you can use to quickly get started.
>> That's really cool. But now for
the part where everyone's come here
for what's new in the Face API for this years bill.
>> Yeah. So we have been investing in
a couple of big areas based
on what we hear from customers and partners today.
One is the infrastructure side of
our Cognitive services, including Face API.
So a few key things that we've been doing,
number 1 is, we've been expanding our regional coverage.
So bringing the service to
more and more regions as App Azure announces new regions.
If you look on the Face API website today on the documentation,
you can see all the regions where the service is available today.
We've also added a Azure Active Directory supports.
So now instead of just using
an App key to authenticate into the Face API service,
you can also use an Azure Active Directory Identity.
We've added VNET supports.
So now you can restrict what applications can
actually interact with the Face API service to
further lock-down the access rights to
the facial recognition APIs in your tenant.
Then last but not least,
we've started rolling out
the ability that we call customer managed keys,
which allows you to
specify the encryption key that should be used to
encrypt templates of faces
that are stored within the Face API service.
By default, we encrypt them with the Microsoft
managed key, with this capability,
you can encrypt them with your own key and you can rotate
the key as frequently as you require.
>> This is really cool because it basically,
we're giving customers the ability to
manage this at a more fine grain level, it looks like.
>> Yeah. We're putting customers in control of all of
these capabilities so that they can increase
the security posture of their end-to-end application.
>> So with a customer Manage key essentially
even Microsoft cannot see
what's in there because the keys are managed by the customer?
>> That is correct. The keys are managed by the customer and
it also allows the customer to
manage the rotation schedule of these keys,
which we have seen as important to a number of customers.
>> Amazing. So what's new on the AI side?
Because the infrastructure side is cool.
But let's see about the AI side.
>> So the on the AI side,
the first thing we've done after talking to many developers is,
we've actually added the ability for
first side-by-side support for detection and recognition models.
This is really meant to make sure that we do not introduce
backwards compatibility issues as we roll out
new face detection and face recognition models.
So what happens is,
when we have a new face detection or face recognition model,
we ship it as an additional model to
the models that are already supported in the service.
We empowered the developers to pick when they want,
if and when they want to use that new capability.
That allows them to test it with their data,
make sure that they set up the right thresholds and
only then roll-out changes into their service.
But this really protects developers from
any backwards compatibility issues
and puts developers and control.
>> That's awesome.
>> Number 2 is what we've heard from customers
is Wider Face API service works well for frontal faces.
We have seen that non frontal faces or
small faces would not always be detected by the Face API service.
>> So we've added a new detection model that is specifically
trained towards finding faces that are
non frontal or very small or partially occluded.
Then the other core capability that
we've added as a brand new facial recognition model.
Based on benchmarks that we have done,
we have seen improvements up to 25 percent in accuracy,
both in terms of false positives and false negatives.
This model is available in the service today,
you can use it.
The one challenge to be aware
of in order to use this new recognition model,
you need to recreate any enrollments that you already have.
Because we do not store images
or faces that are used for enrollment,
we only store the templates that are generated from these images.
In order to use the new model,
you need to re-enroll faces with that new model.
Again, I'll point to a link in
the documentation on the next slide.
>> Again, that's because we're not storing people's faces.
So it's like if you're using a new model,
we don't have your faces because we're
trying to be ethical here, which is really cool.
>> Yeah. Absolutely.
>> So let's see if I can recap.
Side-by-side support for multiple verification.
That's basically, if you're using a previous model,
it will work still.
But if you want to move to the next model,
you can do that as well.
>> Yeah, and you're absolutely in control of when you do it.
>> Fantastic. We have a new face detection model
that does non frontal faces,
which is pretty hard problem, I think.
>> Yeah, it's a hard problem,
and it also enables a new class of
applications where you want to understand
all the faces that are in the image that are
not necessarily for recognition purposes,
but for counting or blurring or other scenarios.
>> That's cool. Then finally,
we've been hard at work making a brand
new Machine Learning Models, exact faces.
This is the outcome of that effort.
Well, where can people go to find out more?
>> Here are the links to
the online documentation for Azure AD Identity support,
VNET, customer managed keys,
as well as to new recognition models.
>> This is all very cool stuff.
Thank you so much for spending some time with us on this,
The AI Show my friend.
>> Thank you. It's been a pleasure.
>> All right. My friends, we're learning all about what's new in
the Cognitive Services Face API here on The AI Show.
Thanks for watching and we will see you next time. Take care.
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