Speaker 1: Bloomberg Audio Studios, podcasts, radio news.
Speaker 2: IBM and Grock are announcing a strategic partnership to give
Speaker 2: clients ultra high speed, low latency AI capabilities via Grock's
Speaker 2: inference technology. For more and how this partnership is going
Speaker 2: to provide greater access to the full potential of enterprise AI,
Speaker 2: We're joined by Rob Thomas, Senior Vice president of Software
Speaker 2: and Chief Commercial Officer at IBM, and Jonathan Ross, CEO
Speaker 2: and founder of GROC and Jonathan, I want to start
Speaker 2: with you. You know, the way that I look at this
Speaker 2: is it's a very interesting go to market channel for you,
Speaker 2: a sales channel. Think about all of the clients that
Speaker 2: IBM has and how you've tried to grow the company.
Speaker 2: Explain how people will access LPUS through this or through
Speaker 2: the cloud matrix.
Speaker 1: Absolutely, it's an extraordinary opportunity for both of us. IBM
Speaker 1: is going to have their sellers sell Grock SKEW and
Speaker 1: so now you'll be able to directly access our speed.
Speaker 1: The advantage which is that we offer you could think
Speaker 1: of it a little bit like offering broadband in the
Speaker 1: era where dial up wasn't fully rolled out and people
Speaker 1: were still trying to connect to the internet. Our lpus
Speaker 1: are just significantly faster, but we also keep the cost down.
Speaker 1: Just imagine if you were to offer broadband and you
Speaker 1: charged more per bit of data that was sent over
Speaker 1: the line, it would be on economical Broadband increases a demand.
Speaker 1: With agentic use cases, it's particularly important to reduce the speed.
Speaker 1: You don't want to ask a question, wait ten minutes
Speaker 1: later and come back. You'd rather get the answer under
Speaker 1: a minute.
Speaker 2: Rob Under this arrangement with Jonathan, does IBM make any
Speaker 2: sort of financial investment into GROC or is there some
Speaker 2: kind of sales or revenue split. Explain the economics of
Speaker 2: this deal for you guys.
Speaker 3: Big pictures.
Speaker 4: We have a lot of momentum in AI with Watson X,
Speaker 4: as we said on our earnings last quarter seven and
Speaker 4: a half billion dollars as a book of business, and
Speaker 4: we're trying to solve the client problem of how do.
Speaker 3: They deploy AI faster.
Speaker 4: So this partnership is all about what Jonathan said, which
Speaker 4: is five x performance at twenty percent of the cost.
Speaker 4: We've seen it with Watson X running on GROC and
Speaker 4: so we will be distributing GROC as part of our
Speaker 4: go to market and there's a revenue share as part
Speaker 4: of that. We are really excited because we've seen clients
Speaker 4: already getting an impact to how they're deploying AI because
Speaker 4: of the integration of our technology together.
Speaker 5: Let's talk about that, Rob a little bit more. Because
Speaker 5: you're the man who's in charge of the software business,
Speaker 5: you're also really responsible for the world revenue and profitability
Speaker 5: of your company. So help us understand why grow was
Speaker 5: the obvious choice. How is it helping your clients get
Speaker 5: outs as faster? On the inference side of.
Speaker 4: Things, we looked at every possibility in the market, and
Speaker 4: the clients are looking for significant performance, so some of
Speaker 4: that changes how your call center operates or how you're
Speaker 4: supply chain runs, and then you combine that with a
Speaker 4: fraction of the cost.
Speaker 3: Suddenly the economics makes sense.
Speaker 4: AI does have a cost problem, and we think this
Speaker 4: breaks through that. And IBM we've said we're going to
Speaker 4: drive four and a half billion of productivity by the
Speaker 4: end of this year. That's another example of AI truly
Speaker 4: having an impact. And the number one question I get
Speaker 4: from clients now is how are you doing that at
Speaker 4: IBM and can you help us do that? And we
Speaker 4: think the combination of IBM and GROC can make this
Speaker 4: a reality for any company.
Speaker 5: Well, let's dig into that a little bit now with you, Jonathan,
Speaker 5: because the integration with what's the next orchestraate? What does
Speaker 5: that look like on your side? How does that happen
Speaker 5: and happen seamlessly?
Speaker 1: So the wantsonex API is available for anyone to use today,
Speaker 1: It'll be invisible to most users. It'll simply work. We
Speaker 1: have a compatible API and this is something we've been
Speaker 1: working on. We will also work on some lower level
Speaker 1: integrations with VLM, which is a technology that IBM is
Speaker 1: very deeply involved in. But it should just be transparent.
Speaker 1: You should just get more speed. Just imagine one day
Speaker 1: you come home, you had dialogue and now you have
Speaker 1: broadband in a cost less.
Speaker 2: Rob where's the demand coming from on your side, like IBM,
Speaker 2: Granite or some other agentic workload that they want to
Speaker 2: run using the GROC lpus. Are these public sector names?
Speaker 2: Are they private sector SMEs? I'm trying to understand who
Speaker 2: you're serving with it.
Speaker 4: As often happens, I would say financial services have been
Speaker 4: early adopters. But the thing that has changed in the
Speaker 4: market in the last six months is everything is moving
Speaker 4: to multimodel. We have IBM models that we open source,
Speaker 4: which are the Granite models. We announced the partnership with Anthropic.
Speaker 4: We have a partnership with Mistraw and Lama, just to
Speaker 4: name a few. What is incredible about what Jonathan and
Speaker 4: team have built is any model can run and get
Speaker 4: instant improvement run.
Speaker 3: The LP used from ROCK.
Speaker 4: So I think this is a combination of a multimodel
Speaker 4: world accelerating inference with ROCK.
Speaker 3: I think this is a great combination.
Speaker 2: Jonathan, does this capacityority exist or are you supply constraints still?
Speaker 2: You've got to go out and build it either in
Speaker 2: Saudi Finland here in the States.
Speaker 1: So the entire world is supply constrained, and I would
Speaker 1: actually expect that to continue for at least the next
Speaker 1: five to ten years when it comes to AI. Our
Speaker 1: advantage is that we have a supply chain that actually
Speaker 1: ramps much faster, so customers will be able to come
Speaker 1: to IBM, put in an order and we will be
Speaker 1: able to fulfill that faster than you would be able
Speaker 1: to with other technologies. But the supply constraints that are real,
Speaker 1: and this is another reason to start working with IBM
Speaker 1: sooner the sooner you get access to that capacity, the
Speaker 1: sooner you're going to have it. I can't tell you
Speaker 1: how many startups come to us and other companies come
Speaker 1: to us and they are looking for capacity, because some
Speaker 1: of them are actually growing twenty or even thirty percent
Speaker 1: per week or per month, which is an astronomical growth rate.
Speaker 1: But by approaching us early, we can build to your needs.
Speaker 5: You were just mentioning Rob about all the partnerships you
Speaker 5: have when it comes to llms and the offerings that
Speaker 5: you're intertwining within yours. Will you go to others to
Speaker 5: ensure that inference is as fast as possible or is
Speaker 5: it this exclusive with GROC.
Speaker 4: We are open to working with anybody in the ecosystem
Speaker 4: of AI around what we're doing specifically on the acceleration
Speaker 4: with GROC. We want to lean into this partnership. That's
Speaker 4: why this is the one that we've announced today, because
Speaker 4: we have confidence working together with GROC. As Jonathan mentioned,
Speaker 4: we're also enabling some of the lower level technologies and
Speaker 4: open source like VLM. So this is the right place
Speaker 4: to be when it comes to inference. But when you
Speaker 4: think broadly about what's happened in AI, we have many
Speaker 4: companies working with us on agents. Last week we announced
Speaker 4: SMP Global is now running on Watsonnext Orchestrate as an example.
Speaker 3: So we're always open to new partnerships.
Speaker 5: And let's just talk about Jonathan the go to market
Speaker 5: strategy here of teaming with the age old Juggernau that
Speaker 5: is IBN, that has so many deep relationships across global enterprises.
Speaker 5: But is that how you're going to work this going forward?
Speaker 5: It is teaming up with companies that have those legacy relationships,
Speaker 5: or do you still go out there and win the
Speaker 5: business yourself.
Speaker 1: So I would say this is a peanut butter and
Speaker 1: jelly sort of relationship in the sense that oftentimes when
Speaker 1: we meet with sea level executives, those sea level executives
Speaker 1: turn to their tech teams and ask them to evaluate GROC.
Speaker 1: And I've been in meetings where the CTO did that
Speaker 1: and the response from the person is I already use GROC.
Speaker 1: It's my default for everything. So we already have the
Speaker 1: bottoms up. We have two point three million developers already
Speaker 1: building on us. For comparison, open Aie has four million
Speaker 1: now going to those deep relationships from IBM, and the
Speaker 1: fact that IBM is a trusted partner who's been delivering
Speaker 1: for decades. You put those two together and that's an
Speaker 1: amazing go to market motion.
Speaker 5: Wow, it's been great having you both on to talk
Speaker 5: about the go to market strategy. Jonathan Ross, CEO Grock,
Speaker 5: of course, Rob Thomas of Senior Vice president of Software
Speaker 5: over at IBM. We thank you both very much.
Speaker 3: Indeed,