The following is excerpted from the question-and-answer section of the transcript.
(Questions from industry analysts are provided in full, but answers are omitted - download the transcript to see the full question-and-answer session)
Question: Wamsi Mohan - Bank of America - Analyst
: <_ALACRA_META_ABSTRACT>Great to see you again. Well, let's start maybe big picture. Can you just at the highest level talk about IBM's AI strategy and how Red
Hat fits in?
Matt Hicks - International Business Machines Corp - President and Chief Executive Officer, Red Hat, Inc.
Yeah, absolutely. So I'll start with Red Hat, I think it's the easiest piece there if we have two offerings and first is RaiI AI and our goal
with Rail AI is to bring together a model, the ability to put your data into a model and the ability to run it. It's sort of that the smallest
unit of making a GPU work for you in that space.
And then if you're able to be successful, if I've trained the model and I can work it. OpenShift AI can expand that to a cluster. OpenShift
AI, we sort of say, like it brings the scale like I can, I cannot be successful with one model, I can be successful with 10 or 100 or a lot
of volume.
From that point, there are two really exciting paths for me. One is sort of depth to the infrastructure where we take this work, we
drive this all the way down to Z and the efficiencies and Z it's at the heart of a lot of businesses on it.
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DECEMBER 12, 2024 / 4:00PM, IBM.N - International Business Machines Corp at Bank of America Global AI
Conference (Virtual)
So the Telum or Spyre processors, we want to make sure Z can participate in that really efficient running of the models that you built.
But at the same point, if you built 10 or 100 models, we know the next journey for enterprises is I need to bring these closer and
closer to my business processes.
I need to bring more data to train fit for purpose models. And that expansion brings you into the watsonx portfolio like watsonx
data to help you bring your enterprise data in or say watsonx orchestrate to actually take these models and integrate them in your
business processes. And so that's sort of the software and infrastructure stack.
The last component of this, which is really powerful is IBM consulting. Because if you say I like this strategy, I like the software, but I
don't have the skills right now to move as fast as I want. IBM consulting they know this stack, they have expertise, they have
demonstrated, they can do this with like the US open use case.
So they're the accelerant in this. If you like this path and technology to help you get there faster. So that sort of is the AI, it is, our
goals with it is being open, being flexible but being able to apply it to your business problems in enterprise as well.
Question: Wamsi Mohan - Bank of America - Analyst
: Right. Yeah. No, I mean, it's obviously worked extremely well for Red Hat for a long period of time. How does IBM plan to monetize
this AI strategy then?
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DECEMBER 12, 2024 / 4:00PM, IBM.N - International Business Machines Corp at Bank of America Global AI
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Question: Wamsi Mohan - Bank of America - Analyst
: And when you think about the contribution from the -- how do you see that kind of maybe stack rank over time? Because I mean,
obviously the infrastructure needs to get built. But then I can see how applications kind of supersede that over time. So just curious
how you think about it.
Question: Wamsi Mohan - Bank of America - Analyst
: Yeah. No, that's a great analogy. Well, maybe switching gears a little bit, right? What's on everyone's mind is really trying to understand
what are people really using Gen AI for. And so it'd be helpful to see what are you hearing from customers as it comes to adoption
of Gen AI?
Question: Wamsi Mohan - Bank of America - Analyst
: What would you say 2025 becomes the year of enterprise AI.
Question: Wamsi Mohan - Bank of America - Analyst
: Yeah, I'm now looking forward to that too. What would you say are some of the industries or companies that have been early adopters
with Gen AI, do you see any particular trends over there?
Question: Wamsi Mohan - Bank of America - Analyst
: Right. So in terms of what would you say, then are the most common use cases that are being explored? And how does that change
as you know, companies get a little more mature down this path around implementing AI?
Question: Wamsi Mohan - Bank of America - Analyst
: What would you say in each of these cases Matt is kind of the ROI, right? I mean part of like what at least in that from an investment
community perspective folks worry about is there's a ton of investment being made but what is exactly the ROI of this and how
sustainable is it?
And I'm sure, pretty deep in the weeds, how that is but what can you share with us about maybe each of these different use cases
that you just spoke about? Like what kind of ROI people should expect and does that actually improve over time?
Question: Wamsi Mohan - Bank of America - Analyst
: Yeah. Okay, that makes a lot of sense. You recently announced the intention to acquire Neural Magic. Can you just talk about the
strategic rationale there and how it fits within your broader AI strategy?
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DECEMBER 12, 2024 / 4:00PM, IBM.N - International Business Machines Corp at Bank of America Global AI
Conference (Virtual)
Question: Wamsi Mohan - Bank of America - Analyst
: No, that's great. If we just go back a second to think about, how you view the broader competitive landscape. And maybe just like
when you talk to customers, what is the most common, maybe like stack that you're seeing from an infrastructure layer up to
application layers? And where do you think IBM has the most opportunity?
Question: Wamsi Mohan - Bank of America - Analyst
: Maybe another adjacent question is just around semiconductors, right? Like IBM obviously has long history there and obviously like,
you optimized for Z a lot of capabilities for running AI based workload. So I'm kind of curious as to how you think about the longer
term view of whether you would be using more third party kind of chips. Would you continue down this road of having more custom
silicon? And how do you think about that? And doesn't matter?
Question: Wamsi Mohan - Bank of America - Analyst
: Yeah. Okay, that makes sense. And then as you think about just within the Red Hat framework, right? If you think about where the
infrastructure is kind of maybe not just infrastructure but where you're seeing workloads within public cloud versus on premise.
How would you say has that -- has -- I mean, the last kind of 15 years have been a big march towards public cloud, but I think that's
decelerating fairly strongly now. At least in growth rate terms. I mean, obviously we've gone from [$0 to $400 billion] of spend on
public cloud in 15 years.
So when we think about like, how you are seeing workload movements because you have that visibility in some ways, how would
you characterize at the high level? Like what is actually happening with the use of multicloud architectures? And what kind of
dynamics could you share over there?
Question: Wamsi Mohan - Bank of America - Analyst
: Yeah. No, that's great. I know we're out of time. So I'm going to try to sneak in two questions there. One really quickly if I can.
Question: Wamsi Mohan - Bank of America - Analyst
: One is just what's your longer term view on training versus inference in the sense that, I mean, as these enterprises train based on
their proprietary data, how much of workload or volume do you think ultimately or time spent would be on training versus in the
enterprise world?
And then maybe just to wrap it up like what are you most excited about IBM's positioning here in AI. And thank you so much again
for taking the time.
Question: Wamsi Mohan - Bank of America - Analyst
: Amazing. Well, thank you so much, Matt. It was a pleasure to have you here and join us at our AI conference. We look forward to
catching up with you soon again and thanks everyone for joining us today. If you have any questions, please shoot us an email and
we'll try our best to get it answered. Thank you again. Thanks, Matt.
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