Welcome to Tech News Briefing, it's Tuesday, July 28th. I'm Imani Moise for the Wall Street Journal. Tech swag isn't just for employees anymore. We'll explain why companies are getting into the fashion business, and who's actually paying $175 for an open AI half-zip sweatshirt. Then, after the worst single-day stock loss in IBM's history earlier this month, CEO Arvin Krishna sat down with the Wall Street Journal to lay out the bullcase for the company. He'll explain why he thinks investors have it wrong. But first, if you think getting your hands on the latest Jordan's is hard, try getting a Palantir chore code. Tech firms are now treating merch releases like a side hustle, selling everything from hoodies, to water bottles, to rice cookers. The collections have sparked ridicule across the internet. But many products have sold out. Proving that while AI is feeling backlash, it's also building a fandom. Wall Street Journal features editor Jamie Waters looked into open AI's latest launch, and joins us now to unpack why these companies are suddenly looking like lifestyle brands. So Jamie, why are tech companies launching clothing lines? But in a funny moment, where obviously there's this big backlash against tech companies, it's not that there's never been merch for tech companies, but I think these releases, they're very stylized. You know, there's a shoot with the open AI merch, the Palantir chore codes and tennis collection. There's like a lot of effort put into these products, it's not just slapping a logo on a t-shirt. In terms of why now I think, in part, it's to support and fuel the enthusiasm for these companies because they have a lot of haters, but they also have a lot of people who are obsessed with them. And also, it's branding, you know, it's free marketing. So you're getting people to wear these clothes around, and you know, I spoke to a branding expert for this story who said that ads often aren't that effective because the public is often disinterested, very skeptical. This is actually a really effective way to do it is if you make products that people want to wear or carry around. Can you describe some of the merchandise that they're selling and how much are people paying for these items? So open AI launched this collection recently and it's a streetwear-leaning collection so there's a hundred dollar hoodie which has codex on it, the coding agent. There's a half zip appropriate for any finance bro which has research written on it in cursive. That's $175. There's my favorite thing, there's a green basketball that says chat GBT. And open AI's clothing line in particular sparked some pretty strong reactions online. How do these launches go over? But surprisingly, the fashion world was very critical. Some people said that this is a very data aesthetic from five or so years ago. And then there are a lot of people who are criticizing it because there's obviously so much animosity about AI and what it's doing and how it's shaping the world and what it's going to do to our future. And so there are a lot of people that are like, why are you supporting a brand, a company like this? And also, why do you want to wear it around? Despite all the criticism, these merch lines are selling out. Who's actually buying this stuff? Who's the target audience here? Yes, they have mostly sold out of them. So the audience is tech enthusiasts, open AI enthusiasts, and open AI employees. Those are the biggest customer bases. And then yeah, there's a lot of really dedicated supporters of this company. I spoke to two of them. They both work in the industry. One of them compared it to when your favorite band releases new merch. You know, it's kind of a funny thing to think of people as being like other supporters of an AI company like a tech groupie, a tech groupie totally. And then the one guy spoke to in Texas, he has an open AI tattoo and a codex tattoo on his wrist. He's worn some of the merch from previous limited edition drops. He said quite often two out of five times when he will leave the house in this. Some of them will come up to him and say, why are you wearing that? Don't you know what they're doing to our community? And he said he wasn't anticipating that people would be so confrontational about it. And he says to them essentially like to reach their own. The other thing is that he gets a lot of people who are kind of more curious about it. And they're like, where did you get that? So I guess it's a mixed bag. That was WSJ Features Editor, Jamie Waters. A quick reminder, we want to hear from you. Have you seen an AI-generated post that you thought was real? Shoot us an email to
[email protected] or leave us a voicemail at 212-416-2236. That's 212-416-2236. Or if you're a listener on Spotify, leave us a comment. Coming up. In over a century since its founding, IBM has reinvented itself countless times. And its current CEO believes the company can do it again in the age of AI. That's after the break. IBM Stock has been under pressure since the company lowered its growth outlook and announced disappointing earnings earlier this month. Waters' questioning of the 115-year-old company can survive the AI era. But in a recent interview with the journal, CEO Arvin Krishna said he's not worried. While other tech giants pour billions into AI data centers and developing new models, Big Blue was trying to convince Wall Street that there's more than one way to win. Our columnist, Christopher Mim, sat down with Krishna to discuss the role he sees IBM playing in the AI ecosystem. In the next frontier technology, he believes could become a trillion dollar market. Make the case for us that this AI boom that has investors so spooked in the medium to long run could actually be a boon for IBM. Like, what is your synthesis on that? I think AI is an incredible technology that is going to provide an incredible amount of productivity in a number of human endeavors, held education, how companies run, how governments operate. We actually believe all of that is going to go happen. Now, there are two ways that can happen. It can all fall into the hands of one or two providers. And that is what some of that boom you're talking about is being spent on. I actually believe it's going to be the exact opposite. I believe that the vast majority, 70% is going to be in a massive heterogeneous mix. A number of open-weight models are a number of models from other countries. We have yet to talk about the physical world coming into this where you need knowledge that is embedded deeply in the model and as well as models at the edge. So that is my view of what's going to transpire. This is going to take a couple of years to play out, not decades. And IBM's piece of that, the way that could be a boon for you is your deliverer of that democratized technology, right? We are a deliverer. And if I go beyond maybe the top 10 or 20 non-tech companies, they're not going to have the in-house skills to talk about what I'll call kernel engineering and model routing. So we can help them by giving all of that while being neutral or agnostic on, okay, which of these hundred different capabilities do you want to use? And how do you do it in a way that's safe? So let's take a step back and talk about some fundamentals because I think one of the challenges that a lot of analysts and journalists have with IBM is they don't actually, as far as I can tell, understand what your revenue mixes and how you make money in a quarter to quarter while everyone is building this AI future. It's 2026. I think people don't appreciate that the core of your business is still this thing called the main frame. And people don't even know what a main frame is, right? It's a very peculiar beast, but it's in everything. Like if main frame is one way tomorrow, like that would be like an asteroid, like extinction level event for global economies because you would take out like what eight out of ten of the biggest insurers, most of the world's banks, all of the airline booking systems, most of the world's insurance companies, right? They're all running core processes on your main frames and you have 90% market share. Now, main frame is not the majority of our business, but it's an important part of our business. Interim hardware is a quarter of the hardware revenue. And hardware is just 20% of our total business. But if I actually put a little bit broader question from just the main frame, a lot of the hardware and software we provide runs in what I would call mission critical parts of the enterprise. Not so much on the edge, not so much in where they are sort of experimenting around the edges, but it's doing billing. It's helping people store their data. It's helping people unlock data for other purposes in real time. When you look at that, that aggregate probably reaches 80%, and that is still going to carry on. You still need to run the enterprise, even as you're doing all this. And then people say, wait, don't you have software that is going to be replaced by an agent? We have very little software, yeah, that could get disrupted. I acknowledge that. Right. And so you've also said in the past, I think your CFO reiterated this on your most recent call for every dollar that somebody spends on IBM hardware. That's like two or three dollars.
that is going to occur in terms of recurring software revenue, right? So that makes hardware a keystone of what you're doing. Every dollar that they spend on mainframe, not all hardware, is three to four dollars that we get across the other parts of IBM. Some of it is in software that they buy from us to run on it. Let's maybe call that two. Some of it is from maintenance, probably another 30, 40 cents, in terms of giving them help to be able to go operate all of these infrastructures. So there is a multiplier effect effectively, but no different than a SaaS company. They sell you a capability, but then they're getting the money for running the hardware and backing it up and keeping it secure. You and I have talked about quantum before. And you just announced that you acquired something called HRL laboratories. Why are you excited about this acquisition? Why did you make this acquisition? For a few reasons, one, people with really deep quantum skills are pretty rare. Two, they're bringing some strength around quantum materials because of the approach they take, which is complementary and additive to what we have. Time will tell which of these technologies is the ultimate scaling answer. But I have actually up my estimate. I think quantum will be a trillion dollar value error by the end of the 30s. I'm really comfortable in that roadmap. That was WSJ columnist, Christopher Mims. And that's it for tech news briefing. If you're a listener on Spotify, be sure to leave us a comment. Today's show was produced by Pierre Bianna-May, with supervising producer Katie Ferguson. I'm Ymani Mali's for the Wall Street Journal. We'll be back later this morning with your TNB tech minute. Thanks for listening.
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