Speaker 1: Bloomberg Audio Studios, Podcasts, radio News.
Speaker 2: Romain brings us a very important conversation right now against
Speaker 2: the backdrop of this market. Romain Bostik at the Mazuho
Speaker 2: Tech conference underway right now in New York with the
Speaker 2: CEO of IBM. This is live on Bloomberg. Romain, take
Speaker 2: it away.
Speaker 3: Thank you, Joe.
Speaker 1: I am here with the CEO of IBM, Arvind Krishna,
Speaker 1: here at the Miszoo Technology conference in Lower Manhattan.
Speaker 3: Great to have you here.
Speaker 4: Pleasure to be here with you. Roman.
Speaker 1: Obviously, all the talk is about AI. We talk about
Speaker 1: digital AI, we talk about biological AI, physical AI. Everyone's
Speaker 1: already looking around the corner, including you, to quantum, which
Speaker 1: of course many people think is going to be the
Speaker 1: next big thing, something that IBM has been working on
Speaker 1: for years. Two years ago, you laid out a relatively
Speaker 1: ambitious target that we would actually see quantum advantage using
Speaker 1: IBM hardware by the end of twenty twenty six, for
Speaker 1: halfway through the year.
Speaker 4: Are we going to get that? Absolutely?
Speaker 5: If I look at what some of our partners like
Speaker 5: the Creative and Clinic are getting done, what the national
Speaker 5: labs like Okage are getting done, I can already see
Speaker 5: the early signs of what they're getting, the progress they've made.
Speaker 1: When we talk about what that progress could mean not
Speaker 1: only for the world of business and finance, but as
Speaker 1: an application through our society.
Speaker 3: Is healthcare the first place that gets it.
Speaker 5: I think that materials or maybe simple molecules are the
Speaker 5: very first place. Maybe magnetic materials as alternates for some
Speaker 5: of these things that are very hard to get. I'll
Speaker 5: use the word rare as a bit of a fun
Speaker 5: over there. I think lubricants to maybe get more effective energy,
Speaker 5: maybe better ev batteries, and then small molecule drugs are
Speaker 5: there in the first set. But I also want to
Speaker 5: be equally excited about what we could do about modeling
Speaker 5: weather perhaps or modeling flows to improve how chemical plants work,
Speaker 5: maybe aerodynamics to improve how vehicles and airplanes work. These
Speaker 5: are really really exciting use cases for us.
Speaker 3: I am curious.
Speaker 1: So I mean, when we talk about actually starting to
Speaker 1: see some sort of proof of life on quantum advantage
Speaker 1: this year, your own head of research has said that
Speaker 1: that process might be a little bit more elongated. Is
Speaker 1: there a disconnect between your ambitions and what he's seen
Speaker 1: from the scientific perspective?
Speaker 3: No.
Speaker 5: So I'll take an example of what's happening on molecule properties.
Speaker 5: So last summer June of twenty five, we could maybe
Speaker 5: understand a five at of molecule you react with. That's
Speaker 5: not very exciting. You could do that on a piece
Speaker 5: of paper if you're smart enough.
Speaker 3: Okay, I'm not smart enough, but I trust here.
Speaker 5: If Yeah, last November, that team could do three hundred
Speaker 5: at of molecule. Okay, you'll say that's great progress, five
Speaker 5: to three hundred, but you could probably do that on
Speaker 5: a normal supercomputer. So okay, that's not one of an advantage.
Speaker 5: This April they did twelve thousand atoms. They did a
Speaker 5: half of a protein called tripsin. I think they're on
Speaker 5: their way to about thirty thousand items already. So five
Speaker 5: to three hundred, same amount of time, three hundred to
Speaker 5: twelve thousand.
Speaker 4: One more month, twelve to twenty one thousand.
Speaker 5: It gives you the rate of improvement, some of it
Speaker 5: from the hardware, some of it in algorithmic techniques that.
Speaker 4: People are learning of what can work.
Speaker 5: By the way, at this size, you can't actually do it.
Speaker 4: Any other way.
Speaker 1: Okay, Well, we talk about the commitment that you've made
Speaker 1: to this. You've been invested or committed to invest about
Speaker 1: ten billion dollars in this, which I assume is a
Speaker 1: tip of the iceberg. You got some pretty big backing
Speaker 1: from the federal government giving you one billion dollars, not
Speaker 1: that you need it, but certainly a vote of confidence.
Speaker 3: When you start to see.
Speaker 1: The government getting involved, obviously you have a lot of
Speaker 1: I guess quasi competitors in this space also getting involved.
Speaker 3: Does that accelerate this pace?
Speaker 5: That's what I believe the government investment is for. So
Speaker 5: if you look at it, it's not so big that
Speaker 5: it's controlling thing. However, it's a sign of endorsement, and
Speaker 5: it is a signal of them wanting to get speed, meaning, IBM,
Speaker 5: you're going to do this. If we commit to do this,
Speaker 5: will you do it faster? Will you open it up
Speaker 5: to everybody else? So it's open to the ecosystem, And
Speaker 5: we said yes, because we actually believe an ecosystem is important.
Speaker 5: And if government investment gets us there a year or
Speaker 5: two or three before we might otherwise, both of those
Speaker 5: are worth it. And that is what is important about that.
Speaker 1: The one billion dollar investment from the Trump administration is
Speaker 1: specifically to build up a chip boundary.
Speaker 3: If you are a quantum chip foundary.
Speaker 5: Quantum foundry that we have committed will be open to
Speaker 5: all comers that are acceptable to the United States. So
Speaker 5: the three dozen odd companies that are here, we are
Speaker 5: happy to give them our best technology, the same as
Speaker 5: we use for ourselves at that level, whether they all
Speaker 5: get access to it, and you say.
Speaker 1: All commers as to what's been approved, this is the
Speaker 1: idea that this is about furthering the US's aims to
Speaker 1: make sure that they have an advantage with regards to
Speaker 1: what gets made, and I would presume so that it
Speaker 1: doesn't get in the hands of the countries that we
Speaker 1: don't want to ask.
Speaker 4: Well, I think that is easy.
Speaker 5: I mean, like there have always been restrictions and advanced
Speaker 5: technologies that you cannot sell it or provide it to
Speaker 5: certain places.
Speaker 4: I think that is fine.
Speaker 5: But in a new area, it's really important to be first,
Speaker 5: both for the economic competitiveness long term, but also for
Speaker 5: national security. I think for those two reasons it's impetative
Speaker 5: that we get there first.
Speaker 3: Do you think the US will be there first.
Speaker 4: On quantum Absolutely, You're.
Speaker 1: Not concerned about some of the reports that we've heard
Speaker 1: about some of the progress that we've already seen in China.
Speaker 5: I'm paid to be paranoid, so I wouldn't say I'm
Speaker 5: not concerned. However, from everything I can see, I think
Speaker 5: we are ahead a head by a decade. Probably not,
Speaker 5: but are we a head by a couple of years,
Speaker 5: That would be my guess.
Speaker 1: I do want to talk about just AI in general.
Speaker 1: At your think conference last month, you talked a lot
Speaker 1: about this idea of the progress company are making with
Speaker 1: regards to the deployment of AI. More importantly, some of
Speaker 1: the progress they aren't making. You've talked about this idea,
Speaker 1: or IBM has certainly talked about this idea of the
Speaker 1: limited ROI that we've.
Speaker 3: Seen so far.
Speaker 1: You say that the companies that are getting this right
Speaker 1: aren't necessarily the ones that are just deploying more models,
Speaker 1: but they're finding ways to take the models that they
Speaker 1: already have and use them better.
Speaker 3: Explain that.
Speaker 4: I'll give you an example.
Speaker 5: So you can certainly improve productivity of individuals. We'll call
Speaker 5: that productivity apps. That's where both economists and CFOs get
Speaker 5: very concerned. But where's my bottom line on that? Is
Speaker 5: it leading to less expense or more revenue. Where is that?
Speaker 5: And that's hard to find. But let me give you
Speaker 5: a second example, and you'll say, okay, I can see
Speaker 5: that we are pretty acquisitive. Anybody who does MNA, you
Speaker 5: often bring the entity in and actually, normally your profits
Speaker 5: might decrease for the first year or two until you
Speaker 5: take all of the costs and get the cost s energy.
Speaker 4: Using AI tools, now we can.
Speaker 5: Probably add ten points of profit s energy on day
Speaker 5: one because the amount of time it used to take
Speaker 5: to move contracts over, to do all of the sales automation,
Speaker 5: to do all of the revenue forecasting, all of that
Speaker 5: now using AI can be shrunk down to literally a
Speaker 5: few weeks. If you can do that, I cannot take
Speaker 5: that ten percent. I'm not saying it's ninety percent, but
Speaker 5: ten percent and invest it instead in marketing and R
Speaker 5: and D and innovation to drive the revenue growth even higher.
Speaker 5: That's an example of what I mean by use the
Speaker 5: AI to really fundamentally change how you do business. Has
Speaker 5: got to become part of your operating model of the company.
Speaker 1: Are you taking that medicine yourself?
Speaker 3: Internally?
Speaker 4: We are.
Speaker 5: In the last acquisition we did, we actually managed to
Speaker 5: take out about sixty percent of the GNA on day one.
Speaker 1: What's the message though, that you have not only for
Speaker 1: your partners but also internally for your own workforce with
Speaker 1: the guards to how this actually not only helps, but
Speaker 1: maybe the idea that maybe it requires a smaller headcount.
Speaker 5: It's not necessarily going to be a smaller headcount. So
Speaker 5: a lot of people talk about this. So let me
Speaker 5: give you an example on early on college hires. We
Speaker 5: tripled our hiring in twenty twenty six compared to twenty
Speaker 5: twenty five. Okay, is the entry level for entry level
Speaker 5: positions tripled?
Speaker 4: Absolute number tripled.
Speaker 5: So you look at me and say why, Because my
Speaker 5: belief is if these tools make people who are coming
Speaker 5: in out of college more productive quicker, that means we
Speaker 5: are going to be advantaged by having more capacity to
Speaker 5: build things at a cheaper cost point, which means we
Speaker 5: can go get market shared. Will the shape of the
Speaker 5: workforce change, absolutely, but I think there will be more
Speaker 5: people in the value driving functions, be IT R and D,
Speaker 5: be IT sales, be IT marketing, and the creative activities
Speaker 5: and some of what I would call classic back office
Speaker 5: will decrease because you don't need so much there, So
Speaker 5: the shape of the workforce changes. Total employment is not decreasing.
Speaker 3: I want to talk about security.
Speaker 1: Obviously, we know the potential opportunities when it comes to AI,
Speaker 1: quantum and everything in between. You've invested about so far
Speaker 1: a commitment of about five billion dollars towards something called
Speaker 1: Project Lightwell, the idea that it gives your partners a
Speaker 1: little bit more visibility about flaws in that sort of
Speaker 1: AI chain, if you will, for my sort of uninformed
Speaker 1: framing of it. But talk about why that's necessary, and
Speaker 1: more importantly, is five billion going to be enough.
Speaker 5: It's hard to tell whether any amount is enough here.
Speaker 5: I think, look, this is like asking why are cyber
Speaker 5: criminals existing, and the old really sudden joke call as well,
Speaker 5: I draw banks because that's where the money is. Well,
Speaker 5: if money's inside the cyber infrastructure, they're going to come.
Speaker 5: Our investment in Light twelve. I think a lot of
Speaker 5: people can point out the problems and point out vulnerabilities.
Speaker 5: Our investment in light Trail is actually about fixing them.
Speaker 5: So we are saying that not just open source that
Speaker 5: we are good at, but if you have open source
Speaker 5: and the source code is known, we can use these
Speaker 5: same tools that I used to find vulnerabilities to also
Speaker 5: create the fix and give it back to the community.
Speaker 4: That is really what light Trail is about.
Speaker 5: Of course, in order to do that, you need cooperation
Speaker 5: around where people are finding things, how critical are they,
Speaker 5: where are they in the critical infrastructure? So that is
Speaker 5: the whole project. But it's actually about us coming up
Speaker 5: with an antidote, not just the problem.
Speaker 1: This I can just tell it by look at interface.
Speaker 1: This is probably an exciting time for you. IBM is
Speaker 1: obviously a storied company when it comes to computing, and
Speaker 1: we are clearly at the inflection point of something new,
Speaker 1: maybe something better. You've gotten a big bump in your
Speaker 1: stock price, largely because of at least the government backing
Speaker 1: or at least the government support. Is there a sense
Speaker 1: here when we talk about the potential for an acceleration
Speaker 1: in revenue growth the widening of profit margins, that that
Speaker 1: is something that is imminent or is that something still
Speaker 1: long term?
Speaker 4: Well depends on what you call long term.
Speaker 5: I kind of like in what we're doing on quantum
Speaker 5: and cyber to where GPUs were in twenty fifteen twenty sixteen,
Speaker 5: and each era of technology tends to go faster, so
Speaker 5: if I say QPUs plus cyber is.
Speaker 4: Going to go fast.
Speaker 5: I think in the next two three years being going
Speaker 5: to see incredible returns coming from these technologies into our numbers.
Speaker 1: And with those ambitions, you have the capital you need
Speaker 1: in order to do that. Any plans to maybe go
Speaker 1: to the market to look for a little bit more.
Speaker 5: We go to the markets all the time. We are
Speaker 5: always in the debt markets, and so far our debt
Speaker 5: investors have been very confident.
Speaker 4: In US and we get great rates there.
Speaker 5: We could maybe dip into other markets, but I think
Speaker 5: for what I'm pointing out over the next five years,
Speaker 5: I think we have the capital and we got the
Speaker 5: WAB withth All insight.
Speaker 3: Arvin really appreciate you joining us.
Speaker 4: My pleasure.
Speaker 3: That's Arvind questionna. He is the CEO of IBM