- So Will, thank you so much for joining us here at AWS.
- Thank you for having me.
- I know you, but I'd love for you to introduce
what you do at SK Telecom, what your passion is.
- Sure, so it's been about two decades already
for me to work for SK Telecom and security companies.
And my role at this point
is to lead the strategic partnership
with peer telecom companies
but at the same time, companies like AWS.
So building cohesive partnership
to grow value not only for both sides of us
but at the same time, external partners.
- So how did this cooperation
between AWS and SK Telecom work, in your opinion?
How did we cooperate?
What went well?
What could we have done better in supporting you?
I'd love some insight from you.
- It's been really exciting journey for us
to work with AWS for the past few years.
And I think there are three companies involved
in this project, and each party brings unique value
to this partnership.
For SK Key, we have expertise in, Vision AI algorithm
and all those behind the scene technologies
and SK shieldus number two security company in Korea.
They bring, they have expertise
in security businesses, and at the same time,
they bring a lot of vision data
and this is where AWS comes in.
So AWS's expertise in cloud business and technology
can be a really unique asset
to make this partnership unique.
And we can unlock a lot of opportunities
that actually exist in this industry
by solving users problems together.
- We're really pleased to work with you
and SK Telecom in co-developing this new platform
that we hope drastically simplifies
the whole computer vision industry and how you deploy it.
But to start off with,
could you give us a little background about SKT's vision
in the AI space?
- What we want to achieve together with AWS
and other allies is to support industry,
transform into AI company
and harness is the true power of AI
and we want to unlock opportunities
across different industry domains.
- So what you're basically saying
is it's moving from a digital,
technology-enabled transformation
to an AI enabled transformation?
- Yes. - Right?
- Yes, exactly.
- Okay and so why computer vision?
I mean, why was this the right first step?
Is this a geographical need?
Was it a customer need globally that you saw?
What drove this particular use case?
- Sure, for your information, SK has
security in a subsidiary company
which is called SK shieldus.
So SK shieldus is specializing in physical security
but we just combined cybersecurity arm together
and we want to solve bigger problem
that industry faces today.
And for the past decade,
what we have done is SKT's AIX,
the AI and technology unit
worked really closely with SK shieldus.
So one of the key findings
was there are so many companies
and organizations wanted to solve security issues
leveraging visual data
and SK Shieldus has an extensive user base.
So with the close relationship between our two companies
we have an access to those data
and then using the data, trained our algorithm
to upgrade it to the next level.
So having said that, we saw a lot of testimonials
from different clients saying they relied on human labor
to monitor existing videos and then find the right footages.
But by leveraging our analytics and algorithm,
they could actually replace some of the human labor
but at the same time, focusing more
on the fundamental side of their business issues.
- Yeah, we call that at AWS,
"Removing the undifferentiated heavy lifting."
So thank you for cooperating with us on that.
I mean, what would you say is the first set of use cases,
like what kind of facilities does this get deployed in?
What kind of monitoring?
Love to understand a bit more about that.
- Sure, so if you look into video footages accumulated,
right, that comes through those in CCTV,
typically, one of the key use case
we providing to our client is anomaly detection.
So late at night, suddenly you have intruder
at your facility and alarm goes on
and you dispatch your patrol to the site
but you found out that it was a dog
or it was a spider, right?
Moving on the glasses.
So it actually cost a lot of money.
At the same time, it was also burden for SK Shieldus too,
because of those false alarm cost a lot of resources.
So using our AI capacity, we could actually pinpoint
whether this is a right alarm or not.
So it is kind of mutually beneficial for both side of us.
- Oh, that's cool. (laughs)
It's really cool.
I didn't think about the spider on the camera, personally.
But yeah, I can absolutely see that.
But why partner with AWS?
I mean, what made you pick us?
We just want to improve, so we just want to know
what we did well, what we could do better?
- I think it all started from the users' pain point.
So typically, a lot of domestic companies
are using very light and simple camera
but the problem with the camera
is it cannot discern or it doesn't,
since it doesn't have AI capacity,
it just record footages, right?
And lack of AI capacity
actually create a lot of different problems.
For example, you cannot detect anomalies in real time
at the same time, even though after the event
you wanted to search those in a specific events.
But it takes a lot of human labor
to view the whole footage and find out that event, right?
We can cut through the clutters
and pinpoint the right footages
but at the same time, detecting anomalies in real time,
that's the kind of value we can bring together.
But previous traditional camera doesn't have the capacity.
So what we have done together with AWS
is offloading those burden for those camera
to record all those footages, right?
So we can actually unbundle those heavy duty responsibility
to record those data and analyzing data on the cloud.
So edge and cloud can goes really nicely
to share the burden, right?
- So is this South Korea's specific implementation
or do you see this applicable regardless of region?
Or could you talk me through that?
- Yeah, if you drop by SK Telecom booths,
there are so many telecom companies
that would show the interest to leverage this technology.
So we have a dedicated section for AI
and one of the key corner, the booths, using Vision AI,
and many companies express difficulties
handling these security issues.
So they wanted to work with us
and there a lot of discussion going on at this point.
- Oh, it's great to hear.
I'm sure all of my other customers
who are in the Telco domain would love to partner on this.
So what are the next steps?
I mean, if, let's say one of my Telco customers at AWS
expressed an interest in this, how do we go about it?
Do we just introduce you to them?
What's the next steps?
- I think the first step is understanding customers,
AWS and Amazon known for customer obsession.
Without understanding the pain point
and reality customer is facing,
we can provide overshoot product to them.
So understanding what's the use case they wanted to address
and what are the context around that use case.
I think having clear understanding
and then we can design solutions
tailored to meet our customer's pain points.
- Okay, that's, thank you for the clear guidance
and again, thank you so much for doing this with AWS.
We can't wait to see it like really expand globally
and start providing real value to our mutual customer base.
- Sure, right.
We're such, it has been great journey for us
to work with AWS.
We are like-minded partners
and focusing on the same customer problems
and we can unlock a lot of opportunities together.
- Thank you, I'll be sure to talk about this solution
and this platform to the rest of my customer base.
I'm actually excited about talking about this, so.
- Looking forward to it.
- So thanks again.
- Thank you, thanks for having me.
- Thanks for your partnership.