(authoritative music) Live from Miami, Florida, it's
theCUBE covering IBM's Data and AI Forum.
Brought to you by IBM.
>> Welcome everybody to the Port of Miami.
My name is Dave Vellante, and you're watching theCube,
the leader in live tech coverage.
We go out to the events, we extract the signal
from the noise, and we're here at the IBM and Data AI Forum.
The hashtag is #DataAIForum.
This is formerly known as the IBM Analytics University.
It's a combination of learning, peer network,
and really the focus is on AI and data.
And there are about 1,700 people here, up from about half
of that last year when it was the IBM Analytics University.
About 600 customers, a few hundred partners,
there's press here, there's analysts, and of course,
theCUBE is covering this event.
We'll be here for one day.
128 hands-on sessions, 35 hands-on labs.
As I say, a lot of learning, a lot of technical discussions,
and a lot of best practices.
What's happening here, for decades our industry has marched
to the cadence of Moore's Law, the idea
that you can double the processor performance every
18 months, doubling the number
of transistors within the footprint.
That's no longer what's driving innovation in the
IT and technology industry.
Today, it's a combination of data
with machine intelligence applied to that data and cloud.
So data, we've been collecting data,
we've always talked about all this data
that we've collected, and over the past 10 years,
with the advent of lower cost warehousing technologies
and file stores like Hadoop, with activity going on
at the edge with new databases and lower cost data storage
that can handle unstructured data
as well as unstructured data.
We've amassed this huge amount of data that's growing
at a nonlinear rate, the curve is steepening
and exponential.
So there's all this data, and then applying a
machine intelligence or artificial intelligence
with machine learning to that data is the blending
of a new cocktail.
And then the third piece of that, third leg of
that stool is the cloud, why is the cloud important?
Well it's important for several reasons.
One, is that's where a lot of the data lives.
Two, it's where agility lives, so cloud, cloud native,
DevOps, and being able to spin up infrastructure
as code really started in the cloud and it's sort
of seeping to on-prem slowly and hybrid
and multicloud architectures.
But cloud gives you not only that data access,
not only the agility, but also scale, global scale.
So you can test things out very cheaply,
you can experiment very cheaply with cloud and data and AI.
And then once your POC is set
and you know it's going to give you business value
and the business outcomes you want
you can then scale it globally,
and that's really what cloud brings.
So this forum here today with the big keynotes.
Rob Thomas kicked it off, he... actually, I take that back.
A gentleman named Ray Zahab, he's an adventurer
and ultramarathoner, kicked it off.
This dude one time ran 4,500 miles in 111 days
with two ultramarathoner colleagues.
They had no days off, they traveled through six countries,
they traversed Africa, the continent,
and they took two showers in 111 days.
And his whole mission is really talking about the power
of human beings and the will of humans
to really rise above any challenge with no limits.
So that was the tone that was set for this conference.
Then Rob Thomas came in and invoked the metaphor
of superheroes and superpowers, of course AI
and data being two of those three superpowers
that I talked about in addition to cloud.
So, Rob talked about eliminating the good to find the great.
He talked about some of the experiences with
Disney's Ward Kimball and Stan Lee.
Ward Kimball went to Walt Disney with this amazing animation
and Walt Disney said, "I love it.
It was so funny, it was so beautiful, it was so amazing.
You worked 283 days on this. I'm cutting it out."
So Rob talked about cutting out the good to find the great.
He also talked about AI, it's penetrated only about four
to 10% within organizations.
Why is that, why is it so low?
He said there are three things that are blockers there,
one is data, and he specifically is referring
to data quality.
The second is trust, and the third is skillsets.
So he then talked about of course, Dovetail, the bunch
of IBM products and capabilities into those blockers,
those challenges.
He talked about two in particular.
IBM Cloud Pak for Data, which is this way
to virtualize data across different clouds and on-prem
and hybrid, and basically being able
to pull different data stores in, virtualize it, combine,
join data, and be able to act on it
and apply machine learning and AI to it.
And then Auto.AI, a way to basically machine intelligence
for artificial intelligence.
In other words, AI for AI, what's an example?
How do I choose the right algorithm that's best fit
for the use case that I'm using?
Let machines do that, they've got experience
and they can have models that are trained
to actually get the best fit, so we talked about that.
Talked about a customer panel, Miami-Dade County,
Wunderman Thompson, and the Standard Bank of South Africa.
These are incumbents that are using machine intelligence
and AI to actually try to supercharge their business.
We heard a use case with the Royal Bank of Scotland,
basically applying AI and driving their net promoter score,
so we'll talk some more about that.
And were going to be here all day today interviewing executives
from IBM, talking about what customers are doing with AI,
getting the feedback from the analysts.
So this is what we do, keep it right there buddy,
we're in Miami all day long.
This is Dave Vellante, you're watching theCUBE.
We'll be right back right after this short break.
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