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Speaker 1: Bloomberg Audio Studios, podcasts, radio news.

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Speaker 2: IBM and Grock are announcing a strategic partnership to give

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Speaker 2: clients ultra high speed, low latency AI capabilities via Grock's

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Speaker 2: inference technology. For more and how this partnership is going

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Speaker 2: to provide greater access to the full potential of enterprise AI,

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Speaker 2: We're joined by Rob Thomas, Senior Vice president of Software

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Speaker 2: and Chief Commercial Officer at IBM, and Jonathan Ross, CEO

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Speaker 2: and founder of GROC and Jonathan, I want to start

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Speaker 2: with you. You know, the way that I look at this

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Speaker 2: is it's a very interesting go to market channel for you,

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Speaker 2: a sales channel. Think about all of the clients that

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Speaker 2: IBM has and how you've tried to grow the company.

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Speaker 2: Explain how people will access LPUS through this or through

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Speaker 2: the cloud matrix.

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Speaker 1: Absolutely, it's an extraordinary opportunity for both of us. IBM

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Speaker 1: is going to have their sellers sell Grock SKEW and

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Speaker 1: so now you'll be able to directly access our speed.

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Speaker 1: The advantage which is that we offer you could think

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Speaker 1: of it a little bit like offering broadband in the

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Speaker 1: era where dial up wasn't fully rolled out and people

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Speaker 1: were still trying to connect to the internet. Our lpus

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Speaker 1: are just significantly faster, but we also keep the cost down.

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Speaker 1: Just imagine if you were to offer broadband and you

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Speaker 1: charged more per bit of data that was sent over

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Speaker 1: the line, it would be on economical Broadband increases a demand.

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Speaker 1: With agentic use cases, it's particularly important to reduce the speed.

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Speaker 1: You don't want to ask a question, wait ten minutes

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Speaker 1: later and come back. You'd rather get the answer under

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Speaker 1: a minute.

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Speaker 2: Rob Under this arrangement with Jonathan, does IBM make any

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Speaker 2: sort of financial investment into GROC or is there some

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Speaker 2: kind of sales or revenue split. Explain the economics of

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Speaker 2: this deal for you guys.

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Speaker 3: Big pictures.

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Speaker 4: We have a lot of momentum in AI with Watson X,

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Speaker 4: as we said on our earnings last quarter seven and

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Speaker 4: a half billion dollars as a book of business, and

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Speaker 4: we're trying to solve the client problem of how do.

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Speaker 3: They deploy AI faster.

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Speaker 4: So this partnership is all about what Jonathan said, which

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Speaker 4: is five x performance at twenty percent of the cost.

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Speaker 4: We've seen it with Watson X running on GROC and

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Speaker 4: so we will be distributing GROC as part of our

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Speaker 4: go to market and there's a revenue share as part

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Speaker 4: of that. We are really excited because we've seen clients

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Speaker 4: already getting an impact to how they're deploying AI because

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Speaker 4: of the integration of our technology together.

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Speaker 5: Let's talk about that, Rob a little bit more. Because

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Speaker 5: you're the man who's in charge of the software business,

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Speaker 5: you're also really responsible for the world revenue and profitability

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Speaker 5: of your company. So help us understand why grow was

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Speaker 5: the obvious choice. How is it helping your clients get

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Speaker 5: outs as faster? On the inference side of.

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Speaker 4: Things, we looked at every possibility in the market, and

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Speaker 4: the clients are looking for significant performance, so some of

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Speaker 4: that changes how your call center operates or how you're

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Speaker 4: supply chain runs, and then you combine that with a

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Speaker 4: fraction of the cost.

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Speaker 3: Suddenly the economics makes sense.

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Speaker 4: AI does have a cost problem, and we think this

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Speaker 4: breaks through that. And IBM we've said we're going to

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Speaker 4: drive four and a half billion of productivity by the

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Speaker 4: end of this year. That's another example of AI truly

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Speaker 4: having an impact. And the number one question I get

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Speaker 4: from clients now is how are you doing that at

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Speaker 4: IBM and can you help us do that? And we

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Speaker 4: think the combination of IBM and GROC can make this

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Speaker 4: a reality for any company.

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Speaker 5: Well, let's dig into that a little bit now with you, Jonathan,

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Speaker 5: because the integration with what's the next orchestraate? What does

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Speaker 5: that look like on your side? How does that happen

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Speaker 5: and happen seamlessly?

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Speaker 1: So the wantsonex API is available for anyone to use today,

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Speaker 1: It'll be invisible to most users. It'll simply work. We

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Speaker 1: have a compatible API and this is something we've been

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Speaker 1: working on. We will also work on some lower level

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Speaker 1: integrations with VLM, which is a technology that IBM is

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Speaker 1: very deeply involved in. But it should just be transparent.

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Speaker 1: You should just get more speed. Just imagine one day

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Speaker 1: you come home, you had dialogue and now you have

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Speaker 1: broadband in a cost less.

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Speaker 2: Rob where's the demand coming from on your side, like IBM,

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Speaker 2: Granite or some other agentic workload that they want to

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Speaker 2: run using the GROC lpus. Are these public sector names?

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Speaker 2: Are they private sector SMEs? I'm trying to understand who

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Speaker 2: you're serving with it.

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Speaker 4: As often happens, I would say financial services have been

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Speaker 4: early adopters. But the thing that has changed in the

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Speaker 4: market in the last six months is everything is moving

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Speaker 4: to multimodel. We have IBM models that we open source,

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Speaker 4: which are the Granite models. We announced the partnership with Anthropic.

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Speaker 4: We have a partnership with Mistraw and Lama, just to

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Speaker 4: name a few. What is incredible about what Jonathan and

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Speaker 4: team have built is any model can run and get

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Speaker 4: instant improvement run.

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Speaker 3: The LP used from ROCK.

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Speaker 4: So I think this is a combination of a multimodel

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Speaker 4: world accelerating inference with ROCK.

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Speaker 3: I think this is a great combination.

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Speaker 2: Jonathan, does this capacityority exist or are you supply constraints still?

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Speaker 2: You've got to go out and build it either in

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Speaker 2: Saudi Finland here in the States.

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Speaker 1: So the entire world is supply constrained, and I would

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Speaker 1: actually expect that to continue for at least the next

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Speaker 1: five to ten years when it comes to AI. Our

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Speaker 1: advantage is that we have a supply chain that actually

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Speaker 1: ramps much faster, so customers will be able to come

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Speaker 1: to IBM, put in an order and we will be

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Speaker 1: able to fulfill that faster than you would be able

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Speaker 1: to with other technologies. But the supply constraints that are real,

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Speaker 1: and this is another reason to start working with IBM

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Speaker 1: sooner the sooner you get access to that capacity, the

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Speaker 1: sooner you're going to have it. I can't tell you

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Speaker 1: how many startups come to us and other companies come

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Speaker 1: to us and they are looking for capacity, because some

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Speaker 1: of them are actually growing twenty or even thirty percent

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Speaker 1: per week or per month, which is an astronomical growth rate.

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Speaker 1: But by approaching us early, we can build to your needs.

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Speaker 5: You were just mentioning Rob about all the partnerships you

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Speaker 5: have when it comes to llms and the offerings that

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Speaker 5: you're intertwining within yours. Will you go to others to

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Speaker 5: ensure that inference is as fast as possible or is

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Speaker 5: it this exclusive with GROC.

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Speaker 4: We are open to working with anybody in the ecosystem

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Speaker 4: of AI around what we're doing specifically on the acceleration

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Speaker 4: with GROC. We want to lean into this partnership. That's

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Speaker 4: why this is the one that we've announced today, because

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Speaker 4: we have confidence working together with GROC. As Jonathan mentioned,

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Speaker 4: we're also enabling some of the lower level technologies and

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Speaker 4: open source like VLM. So this is the right place

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Speaker 4: to be when it comes to inference. But when you

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Speaker 4: think broadly about what's happened in AI, we have many

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Speaker 4: companies working with us on agents. Last week we announced

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Speaker 4: SMP Global is now running on Watsonnext Orchestrate as an example.

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Speaker 3: So we're always open to new partnerships.

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Speaker 5: And let's just talk about Jonathan the go to market

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Speaker 5: strategy here of teaming with the age old Juggernau that

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Speaker 5: is IBN, that has so many deep relationships across global enterprises.

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Speaker 5: But is that how you're going to work this going forward?

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Speaker 5: It is teaming up with companies that have those legacy relationships,

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Speaker 5: or do you still go out there and win the

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Speaker 5: business yourself.

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Speaker 1: So I would say this is a peanut butter and

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Speaker 1: jelly sort of relationship in the sense that oftentimes when

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Speaker 1: we meet with sea level executives, those sea level executives

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Speaker 1: turn to their tech teams and ask them to evaluate GROC.

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Speaker 1: And I've been in meetings where the CTO did that

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Speaker 1: and the response from the person is I already use GROC.

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Speaker 1: It's my default for everything. So we already have the

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Speaker 1: bottoms up. We have two point three million developers already

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Speaker 1: building on us. For comparison, open Aie has four million

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Speaker 1: now going to those deep relationships from IBM, and the

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Speaker 1: fact that IBM is a trusted partner who's been delivering

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Speaker 1: for decades. You put those two together and that's an

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Speaker 1: amazing go to market motion.

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Speaker 5: Wow, it's been great having you both on to talk

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Speaker 5: about the go to market strategy. Jonathan Ross, CEO Grock,

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Speaker 5: of course, Rob Thomas of Senior Vice president of Software

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Speaker 5: over at IBM. We thank you both very much.

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Speaker 3: Indeed,