We are here at AWS re:Invent.
We are connecting with numerous executives.
Delighted to do so with David Rokeach
He is the VP Enterprise AI at Scale AI.
David, great to see you. Good to see you.
What problems are Scale AI helping to solve?
So Scale’s mission is to accelerate the deployment of AI applications
and we were founded on day one with the observation
that data is the bottleneck to creating great AI.
And so over the course of the last seven years, we've been working very closely
with the most sophisticated model builders in the world to power the data
that helps to train and improve the performance of their models.
So from all of the self-driving vehicle technology you see out there
to the commercial generative AI and large language models
that are now taking the world by storm, Scale has been quietly powering
the development of those capabilities over the past seven years.
And where we're now seeing that translate is into the enterprise.
And so some of those same needs in high-quality data
and being able to customize and improve performance of models is the same thing
that enterprises need to start really getting value from this technology.
So David, what kinds of challenges do the enterprise companies have?
Well, I think the biggest thing is that there's this real need
to get to a clear view of return on investment
and kind of the dirty little secret in
the space is that there are all these flashy demos
and all these exciting opportunities out there, but there are very few
applications really in production in the real world delivering value
and I think
what we're seeing in the enterprise is that there's this gap in being able
to deploy some of the technology quickly in a demo fashion,
but it's really, really difficult to get to production.
And so enterprise executives are looking for solutions that
help them to move faster on really hard challenges,
but also create the infrastructure they need to build on top of,
you know, the first couple of use cases and actually scale up the capability.
So we know that Scale AI and BCG are collaborating.
How does that work?
Well, BCG and Scale have really complementary skill sets and solutions.
on the BCG side,
really, truly global
expertise and industry expertise and being able to deliver, you know,
insight and solutions for large scale clients
driving business transformation and change management.
And then on the Scale side, we really focus on deploying production
grade infrastructure
that an enterprise team
can rely on for some of their hardest generative AI challenges.
And when you bring those two things together, you get to faster
return on investment, faster impact, production-grade quality
capabilities that can scale, and we do it responsibly and safely
with the infrastructure and support needed to really embed responsible
AI practices into the solutions that they're building.
So if 2023 is a stand out year, what are you excited about for 2024?
Well, you know, I think 2023 really it's the first inning,
maybe the bottom half of the first inning in generative AI,
what I'm excited about in 2024 is I think this is the time
when we really start to see enterprises deploying these solutions
in the real world.
And, you know, I think at the end of the day,
AI is going to be more impactful than the Internet.
But what it means to get there is that enterprises
and consumers need to start using it in real life settings.
And I think that's what we'll start seeing in 2024.
David, thank you very much.
David Rokeach. Thank you.