The announcement we made yesterday and now completes our vision and the
execution of the strategy. We have been through over the last four
to five years, which Green Lake is our cloud platform where we offer edge
services, hybrid cloud services, and now we're going to offer a service.
And so in many ways complete the entire portfolio, because in 2018 I stated that
the enterprise in the future will be HD centric, cloud enable and data driven.
And obviously I is a nationally rated the data driven strategy and we made
available an amazing set of services yesterday with the leading service being
the cloud meaning of public offer so customers can come in privately to train
their models in the most sustainable infrastructure.
Well, let's talk about shareholder value.
What are we looking at in terms of the addition to growth, whether it's
profitability or revenue? Obviously, a I would be a huge boost of
revenue growth. And we talked about this in the Q2
earnings where we specifically could call out in 90 days, just in Q2, we
booked an incremental 800 million dollars just for these type of work
loads. Since then, our pipeline has grown now
to over 3 billion dollars. And so this is what do you see the
momentum accelerate? And the reason why they are coming to us
is because they know we have the capabilities, but also we have to trust.
Trust is everything when it comes down to where I and to build trust.
You need to have mobile completion and to have multiple completion need to have
this capability. So we expect this business to continue
to grow and thrive. Profitable growth for Russia.
Well, as you seek to get a little bit more traction on this, particularly when
it comes to revenue growth. Is that going to be enough, Antonio, to
make up for some of the lag that we've been seeing in the compute segment?
No, listen. Last year, the compute business grew
double digits and we drove a amazing profitability.
And we know compute tends to be cyclical.
You know, they are, Peter, the times when you're more than ISE and you add
compute capacity depending on where you want to host the world.
Right. And there will repeaters that will go
through digestion. But remember, Green Lake Innes on the
accelerator, a lot of compute demand because ultimately that could be the
demand stays there for a longer period of time with high gross margin and
obviously high get attach rate. So that's why we are growing the edge.
We are growing the hybrid cloud. And now we've got on growth there
together with the data. And computing will continue to be a very
important aspect of our portfolio. But over time, the portfolio mix is
going to go to those business businesses just mentioned.
That was HP CEO Antonio Neri. A.I.
is attracting attention across sectors ranging from education to health care.
But while the use of the nascent technology might vary, the concerns are
similar. Some even characterize A.I.
as an existential threat. I sat down with neurologic CEO Jana
Eggers a little bit earlier to ask her about where A.I.
is headed. In most people's opinion, you know, they
think of a ISE. When is it going to be like the human?
I think we're very, very far from that. But where we are, which is exciting, is
we're at a point where I can really augment humans and help us out.
And you're seeing that with Tom Keene and some of the excitement that people
have around the things that it's able to do for them as far as generating ideas,
maybe for a vacation or for a new marketing campaign, that it's coming up
with different ways than they were thinking.
I was speaking with the CEO of Hewlett-Packard Enterprise.
They just had a big splashy rollout this week of some new A.I.
tools that they're integrating really into their larger cloud and enterprise
software products here. You advise a lot of companies, you deal
with a lot of companies that are looking to build out into this space.
Is there sort of a scale up factor here that you think is viable, particularly
when it comes to software and a lot of cloud services?
Well, I typically actually. I advise companies to scale back rather
than scale. You know, most companies aren't going to
use something like CAC t for it for their business unless it's an HP has an
offering there, unless it's really focused on their business.
So. So they're training models not to be the
whole web of information, but to be their corporate information.
And I mean, I do think that's really important.
And so I wouldn't you know, it's obviously their use cases will scale.
But I think the data self scaled back, even though, again, things like charging
you can't give us those ideas of what could be done.
We have to talk a little bit here about some of the risk or at least the
perceived risk of this. This week at Bloomberg Technology held a
big a ISE summit. They had a sit down with the open API
co-founder. And there was a little bit of a pushback
here to some of the, I guess, worst case scenarios that have been posited about
what A.I. ends up being for us, for humanity.
So I'm I'm again, excited that consumers are able to use it because they start
seeing more of what's wrong with it. And because of that, I think now I'll
learn a bit more about A.I. and start questioning, which I think is
terrific. I think.
And, you know, some of those fears I'm not I'm more worried about hype than I
am actually worried about A.I. cells.
So people start believing that it's something that it's not.
That's what worries me. And so I'm I am more excited where
people can use it, understand that there's some hype around it and then
they can start questioning it more and demanding more demanding things like
transparency and explain ability so that we know what data is used, how it used,
and what data was actually led to this this suggestion or this information and
whether it was created or not. I mean, you've seen some examples of Tom
Keene t making up and people call it hallucinating citations.
So if I know that that actually didn't come from a real site, I should be able
to see that. So, Jackie, you should tell me.
It's amazing. Well, that gets to this whole idea of
just how reliable the use of this can be.
Also, it raises a lot of questions about bias.
You know, the idea that the charge IPT or whatever other generator they
products are using, the output is only be as good or as qualitative as the
inputs. Right.
And I could even say if you have you may have some really good data, but the
question is, is it good for that use case?
So people understanding I always talk about A.I.
is really three parts. First part is the data.
Second part is the algorithm. And the third part is the objective to
making sure that those are all aligned and and that this is good data for that
use case and of the right size. Again, you may not need the whole
Internet of information. You may just need your corporate
information to actually give you better answers than what the whole Internet
would give. And then you go back to my point about
transparency and explain ability, being able to understand which data from which
data set or which aggregation of data sets really drove.
The answer is, is actually quite important now and becoming more
important as we go down this path. And this does appear to be kind of the
future in some form or another. There's been a lot of discussions about
the data itself, the ownership of that data.
We know at least with some of these consumer products, if you're just
scraping the web, the question is, do you have a right to use something that
someone else produced without their permission?
And more importantly, without compensation?
How do you sort of reconcile that, given the large data needs that are required
for this? Yeah, I'm I am actually very much in the
protect and protect people's copyrights and really respect their data.
This is why when I talk about corporations.
I'm going with their own data. When our customers come to us and say,
hey, can you also help us find data? I always push back and say, let's start
with your data first. Maybe we'll need that eventually.
But let's start with your data first, because most corporations have plenty of
data. They don't need to go outside of their
their corporate walls to do well.
The data say that to me, the amount of data is a red herring.