Anthropic Deals, IBM’s Confluent Buy, and Google’s Carbon Capture Push | TSG Ep. 982

Looks like IBM had $11 billion laying around, burning a hole in their pocket. You are watching Textron Gang. Hi everyone.

Happy Tuesday. It's Alan Hummel. I am back in the Boca Studios here for Techstrong, and I am damn glad to be home, to tell you the truth, after my AWS reinvent, uh, excursion.

Mitch, you were there with me, Mike Ard, you were there with me. It was, it was a full week of a lot of good stuff. We've got a ton of content.

If you check on Text Trunk TV and on all the various websites, you'll see it. But we're here today to talk about some fresh stuff, fresh news for this fine Tuesday. We got fine people to talk about it with.

I'm happy to see her here. I, I didn't see her at AWS my friend Hope Lynch. I hope Steven FoST.

He's about to jet off to New York City. He's such a jet setter. That FoST, but happy to have him here, Steven.

And then, as I mentioned before, Mitch and Mike, good to see you both. Not in Vegas. 'cause you know what happened there.

Stayed there. Anyway, Mike, we've got a busy day. Philanthropic is, you know, well, I have my own views on this, but I want to hear what you guys have to say.

Mike, why don't you kick it off? Anthropics been really busy. They acquired an outfit called BUN to get a new application development tool.

They signed a deal with Snowflake for a partnership for connecting data to various LLMs. And there's now rumors. There'll be an IPO in 2026.

But Mitch, what's your take on what's going on with philanthropic here? 'cause they always felt a little bit like, you know, the, the alternative to open ai. But, you know, are they starting to maybe emerge as a bigger, more powerful force with a little hope from our friends over there at AWS that we talked to last week?

Well, they're certainly beefing up the development space, right? 5 as a really strong, maybe the best of the models for generating software, orchestrating some of those processes. And BUN brings a probably not well known by a lot of people, but Fund brings a runtime job environment.

So I imagine what they're doing is kind of using this to create sandboxes, maybe production environments, things like that. Just accelerate the process of using the software that you're generating. Maybe they have other designs as well.

We'll see what they have. They didn't disclose an amount, so it's only, uh, 20, I think it's 2022 when the company started. So it's pretty young.

Um, they'll get folded in and assimilated, but I think it's, I think it's anthropic positioning Very Strongly. Go after the developer market. I, I, I think clearly Anthropic has set their sights on being the developer's AI tool of choice for coding, right?

You hear this over and over again. 0. But the Anthropic and Mitch, is it Sonic?

Claude, I forget now. 5, Right? Yeah.

5. 5. Mitch.

Four four Is the new one. It just came out. 5 has been considered the best, I should say.

Mm-hmm. I, I think, but, you know, every new one is, is the best one. But it Is.

Every new one is the best one. There's a, there's a meme on the internet that shows, uh, open AI with Gemini, with Claude, and there's an arrow. And every time someone releases a new model, there's a little bubble over it that says, now we have the best one Right?

Until the next one. Right? Right.

Just, But clearly they made this, their, this is the, the beach. They, or, you know, the hill they're gonna attack here, right? Hamburger Hill and, and power to them.

The other thing I'll say though is this, you know, it's the lesson. I've said it here before. Brad Feld taught us this.

Mitch be in the top three. You don't always, I mean, number one gets a good share of the money, but so is number two. And I think they've clearly enunciated or, or, you know, a number two space though.

Look, Google Gemini is, is a powerhouse, and they've got Google behind them. So there's an interesting race, and there are others. There's, there's x and, uh, and, you know, and, and others that are coming out.

But clearly Anthropic has staked their claim here. The deal with Snowflake, again, it goes right into their developer sweet spot, data management. Um, and you know, as far as an IPO goes, I think that'll depend on the broader market conditions.

Does is this bubble keep, you know, if you've seen Wicked, does Glenda keep hitting the, the pedal that makes the bubble grow? Or does poof, the bubble burst? Hey, hope, do you think that we're gonna see some bifurcation where maybe open AI and Google, or the AI platforms of choice for the consumers?

And anthropic is more of the corporate AI platform? I actually think we already see it, honestly. Um, most of anthropics growth has been with enterprise customers.

Most of open AI's growth, even if you just count, um, monthly active users, right, has been with consumers. But if you look at the revenue, both of them have, um, I think philanthropic is now at $7 billion in revenue hitting what, a a billion in six months. But OpenAI is two and a half times that.

But they are counting on converting non-paying users, which a lot of people I know who aren't paying, uh, don't, don't plan to start paying the money is in the enterprise. So Anthropic definitely has already diverged. Um, but then we have the other smaller players like, uh, meta, you know, they're saying, well, we're gonna give it away for free.

Maybe that's gonna make people adopt. But really, the, the horse race, to Alan's point, it's between Google, uh, open AI and Anthropic, but the divergence is already there. The Greek For Greek.

One more thing I'd like to add on that point too, is the difference in fundraising here. So Anthropic, uh, by all accounts, has raised a little under half as much as OpenAI. Uh, they're looking at an IPO, uh, as you mentioned, they seem to be aiming at enterprise customers.

I think this is part of a strategy from Anthropic to be more of a, I don't know, like a relevant Yeah, like, like, like they're trying to build a company that has more traditional, yeah, more traditional appeal to Wall Street, more traditional appeal to business. And I think that's a good strategy for 'em, at least. It's a good differentiator from open ai.

Yeah, No, they haven't pledged one and a half trillion dollars that they're going to spend on AI data centers and chips and so forth. You know, not to be left out of the discussion, AWS is announced Nova Nova two. So they're doing their own model now to, you know, so they aren't entirely dependent upon the anthropics and open ais of the world.

So the, the market is, is expanding. I think a, I think AWS's strategy is Nova's kind of their default for their preferred customers. And then Anthropic is choice number two.

And then everybody else is are, are you really? You really want that? Are you short?

Well, but you know, but that's the ai, that's the AWS model, right? We'll give you our in-house thing, 80% of the functionality, 20% of the price, or you could use best of breed, but you're gonna pay for it. And, and then, you know, and then there's Switzerland with Bedrock, it plugs into anything Leveraging those training chips, right?

Yep. Yep. Anyway, But one more, one more quick point on Anthropic, um, not to be overlooked is what they are doing.

What they're actually doing, in my opinion, is vertical integration, right? So they're saying we own the model, we are embedding it into enterprise data platforms through Snowflake, and now they own the runtime infrastructure. So for me, this is a little bit like, um, apple when they said, you know what, we're gonna, we're gonna build our own ships, Google, we're gonna build our own ships, Tesla, we're gonna make our own batteries.

So they are eliminating more dependencies, but trying to make themselves more valuable to the enterprise. I, the, the problem there, hope is, I think they vertical integration in the AI stack and Frontier model, Google, Google is, uh, in a power powerful position there. They really are, No doubt.

All right, if we don't have anything else on this one, it's big news. We'll keep our eyes on our friends at, uh, Claude Sonnet Anthropic and, uh, see what happens. Congratulations to the folks from Buno, by the way.

Uh, we're gonna come back and we're gonna talk a little more m and a activity from Big Blue. You're watching Textron Gang, You've Earned it. The spotlight, the responsibility, the weight of teams, companies, and entire industries fall on your shoulders.

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Black Clerk, digital executive protection, defending the new attack surface your personal life. Hey folks, we're back. And as Alan alluded to at the top of the show, IBM is spending an inordinate amount of money to buy Confluent a provider of a managed service around Kafka, which is a streaming data processing platform, open source originally developed by LinkedIn, and is now widely used to drive a lot of data in real time to where it needs to be.

And of course, that has a lot of implications for ai. But Alan, I know you've been looking lately into IBM and having some thoughts about them in general, but this is the latest in the series of acquisitions. And so, uh, to, to quote the new old book there by, uh, uh, Franz Kafka.

No, I'm sorry, yeah. Is it Kafka? Yeah.

Um, metamorphosis where I guess basically he thinks he's turning into a cockroach. But what is IBM becoming in all of this? You know what IBM is a cutting edge software provider.

I, I think you gotta look at, yes, I-B-M-I-B-M always makes a lot of acquisitions, right? Growing by acquisitions is near and dear to them. Not that they don't grow organically, but to me, you, you take Red Hat, you take HashiCorp, and now Confluent and you have a, a modern software stack, um, that is open source friendly.

IBM's gotta be, you know, there's a claim to be made that they're the most open source friendly of the, of the large tech companies out there, right? Look, think about all of the all, you know, red Hat Hashi. Yeah, Hashi changed their license a little, but they're still big on open and, and now Confluence, I, Apache, Kafka, uh, Kafka, um, it's, I think it's a great move by IBM is $11 billion a lot of money.

You know what I've learned sitting at this desk the day we announced the deal, it sounds extraordinarily expensive a year or two down the road, you know, with the, the hindsight, eh, it was a bargain, Right? Yeah. What did they pay?

What did they pay for Red Hat? A Few years? 34 and a half billion, I believe.

Right? So still One of the largest software deals ever. HashiCorp, they picked up for a song in a dance compared comparatively, but Hope, Hope, I think they also bought, uh, is it Databricks?

Is that one they Got? No, they don't know Databricks Data Stacks. It's one Of, I remember.

So yeah, red Hat Hashi, because then they got Terraform, they bought Vault for sequence management. Well, vault That comes with Terraform. Yeah.

Well, Vault Data Stack Vault. Um, but yeah, in cofluent, so, you know, for the real time data backbone, but yeah, That's right. They, they bought data stacks to clarify that they, okay, there we go.

Which is a NoSQL Vector database. So I think that, to me, I read this as to say that IBM's trying to make a play for the data, less for the AI models. And if I can own all the data and all the pipelines, maybe I will dominate this thing.

Steven, what do you think? This data King? Oh, data is king and Kafka is excellent.

I gotta say, this is a pretty exciting move in my mind for IBM. Um, they, as you said, I mean, they've acquired so many companies in especially the, um, this classic open source model of developing real open source software and then offering enterprise level support and, uh, managed services around it. Uh, that is exactly what they're doing here with this acquisition.

And what they've acquired here is one of the leading companies. If you go to, uh, talk to data people, you know, there's a lot of talk about all of them, incredible uses that you can make for Apache Kafka. Um, and also it would be important to mention that they don't just, um, you know, confluent didn't just make Kafka.

They also are responsible and, and of course they're managed services cloud, but also Apache Flink or Flink. Uh, I like saying Flink because it sounds like a sound like, I dunno, a lemur would make or something like that. Flink Flink, uh, which is a stream processing and batch processing framework.

Um, if I told you that IBM acquired batch processing and data, and you know, you'd be like, oh, yeah, oh yeah, like the Kool-Aid man. That's what IBM's all about. Um, good acquisition looks like a good amount of money for both sides, and I think they're really gonna make hay from this.

I Got a quick question. How would you know what kind of noise a lemur would make? I love lemurs.

Um, I actually have, um, on the wall of my office, a giant painting of lemurs. And, um, it turns out that they only say things like f flank to their friends. Oh, Okay.

That's probably why I've never heard it. Wasn't there a show about a lemur my kids watched when they were little bufu bufu? Yes.

That was it. That's what I thought you were gonna tell me, Steven, that Zafu said Flink All. So have you we're a LE center In North Carolina.

Let's, I'm sorry about I love here. You're The best. Yes.

Donate to the Duke University Lemur Center. Excellent. Jumping In on this.

That's, I'm glad we went down that broad. Go ahead, rich. I don't have any lemurs.

I'm sorry. No lemur stories. You know, this, this compliments what, uh, HashiCorp announced with their infograph earlier this summer, uh, graph database around the infrastructure through this contextual information for AI to use as part of its processing.

Now you add this real live, live streaming, you know, high volume data for data pipelines, both going into AI and traditional software, and they're, they're doing a good job of beefing up the, their data platform, if you will. I wouldn't be surprised to see more acquisitions in the data space for IBMI Think you're spot on. 'cause I think when I look at all this AI stuff, at the end of the day, it comes down to the right data's gotta be in the right place at the right time.

And that's easier said than done hope. But, you know, is what's your sense? Are we moving away from kind this batching mindset that joined a mindset that Steven mentioned?

And are we shifting over everything in the near real time? I think that's, that's the goal. That's what, uh, a lot of people want.

Um, and right now that is what people are hoping, hoping that they're, they're able to do so. Um, and if, and if people don't know, you know, this streaming data is like a, like the nervous system for the applications we have now. So think transactions when you swipe your credit card and it comes back and says yes, um, you click on a website, you have sensors with flowing data, um, those, those things matter.

So with that cloud native engine, hopefully handling gigabytes of data per second, um, yes, that becomes more and more of a reality and, you know, no lag. And I think even what we consider fast today, maybe in a few years, we will feel as slow. And if anybody remembers, I do the days of trying to download something and, you know, you'd be lucky if you could get 10 megabytes overnight, whereas now you can download a gig in a few seconds, I think, um, someday, right?

Hopefully we can scale to that point where we can look back and see those big differences. Well, Steven, I think that sound you heard was actually Watson X giving a big sigh of relief as it took a big go of data coming its way. Well, Yeah, absolutely.

I, I, And I think there's another method to the madness here of IBM. You know, I, I put up an article yesterday, I believe Run Techstrong AI about I-B-M-C-E-O. Uh, Arvin Krishna did an interview where he, he called out the industry on the, on the AI data center, uh, model.

And, and quite frankly, you know, quoting Bill Clinton, it's just arithmetic folks. It's just old arithmetic. And, and according to Arvin Krishna, the arithmetic doesn't work for AI data centers at under the current guise of things.

So I think knowing that, and you gotta assume that the people at IBM and Armand themself, they got a couple, they've got some experience in this space in data centers and economics of it and all of that. So I think that deliberately here, making a bet, how did they ride this AI wave without exposing themselves to the GPU waves and bubbles and so forth, being the data kinks, right? They'll run the data management, they'll run the underlying clouds and, and security and, and these things, right?

Without actually being exposed to, uh, an AI bubble, just throwing it out there. So I agree on Kafka, but I'm not entirely sure that, you know, it's open source, right? So IBM buys a company that provides managed services, okay?

But there are other companies that can provide managed services around Kafka. So it basically comes down to them acquiring the, the talent and the expertise to manage Kafka, which other people can get. So when I look at this a little bit, I'm kind of like, well, okay, but can you hold onto that expertise or are you just adding to the IBM services portfolio and a bunch of consultants?

But, you know, what is the thing that you bought? Because, well, Kafka has freed everybody, You know, I think it's more than Kafka. You're right about that.

'cause a lot, it is the most popular platform for streaming data, but it, it's, I think it's an integration strategy of how they tie this into their other products, uh, uh, you know, as well as the acquisitions Red Hat and HashiCorp. But, you know, things like, um, stream sets, e even going back, you said, we mentioned data stack, web methods. I mean, they have so many platforms that can benefit from a streaming data platform.

I think this is kind of a universal win. So, so I should look for that Red Hat OpenShift Kafka slash DataStax bundle any day now. Absolutely.

But, you know, A little bigger, but that joke is also that you've just made actually points to one of the challenges that IBM has ahead of them, right? So integration, this is a lot. This is a lot of technology to integrate and make sure it all plays well together, and that whoever is in sales for IBM, when they're out in the field, they cannot, they can make it make sense.

Mm-hmm. And people aren't, uh, you know, building their own Frankenstein monster. You know, I think the key is making one plus one plus one equals seven, right?

Because otherwise, yeah, you could go get the open source Kafka, or you could get someone else who gives you a managed Kafka, and you could get Susa or a different Linux over here and, and, and, and, you know, rancher for your cloud native and, and you open tofu for the Hashi stuff. It's how, it's the one plus one equals four model that IBM has to perfect and sell here. And there's Three words.

Enterprise, enterprise, enterprise. Yep. Yeah, yeah.

And you look at, You look at the success of Red Hat, and, um, and this is a model that is working. It's a model that's working for IBM. It's a model that's working for their customers.

I don't hear a lot of people complaining about Red Hat. I hear a lot of people that are really happy with that product and with the products that they're getting from IBM. Um, so yeah, I think that that's exactly how they make this work.

Their pattern is to leave it alone for a couple years, then, then start to integrate it. Well, They, they've got a little experience doing acquisitions, Mitch. Yeah, they, Yeah, they do.

You, you're right about that. I think somebody looks at this and starts to conclude that maybe, you know, the big winners in all of this are the providers of the storage and the networking platforms on which that day is gonna be moving around. This is the open source community.

It's the open source community because once again, open is the future. No one wants lock in. No one wants to be locked in.

We gotta take a break though and come back. We got our third block coming up here. A little green story about carbon capture.

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Contact us today and tell your story to the world in the most powerful way with Textron Group. Hey, folks, we're back. And on Tuesday, especially in the C block, we like to talk about climate ecology and all the things that go with that involving it.

And today is no exception. Google is talking about a way to capture carbon from data centers, and that's how we're gonna solve a lot of these AI issues. Steven, what do you think?

Is this a viable approach and is this gonna make more sense than, I don't know, putting a windmill in everybody's backyard? Uh, no, but it's a, it's better than a kick in the head, that's for sure. Um, but only moderately.

Uh, so Google, yeah. So what's going on here is, uh, there's this, uh, broad wing energy center that's being built in Illinois. Um, they're pitching it with very, very, very green, uh, looking, uh, prose and photos.

You know, they got, they got pictures of leaves, they even got pictures of solar panels in this thing. But this thing is a natural gas fired power plant. It don't, don't be fooled.

It is a hundred percent a natural gas fired power plant. The green-ish aspect of it is that they're using carbon capture technology that was developed by a, uh, little, uh, company. I believe that this is using, uh, ADMs, uh, carbon capture.

Essentially what they're gonna be doing is as they burn the natural gas, they're gonna capture the CO2 and sequester it on site, uh, to keep it from getting out into the atmosphere, which, like I said, better than a kick in the head, but really not of all that green, because this is still a fossil fuel powered car, uh, plant. And what's happening here is that this broad wing, they, they were building this 400 megawatt plant in Illinois, um, to essentially take advantage of the fact that there's a lot of Midwest natural gas available, and there's a demand for power. And they think they were kind of hoping, you know, if you build it, they will come in the old corn field here.

And, um, and they did come, in fact, Google is, uh, committed to basically absorbing pretty much all the output from this plant. So, uh, those of, uh, local folks or whatever, who thought that maybe this was gonna be something that was gonna benefit the, uh, local, uh, you know, uh, it is gonna benefit the local economy. But if they thought it was gonna benefit them in terms of, uh, power supply and stuff, well, not as much as you might think because Google's gonna buy most of the output.

But what this does, uh, you know, again, to be a little bit more optimistic is it is a stamp of approval on carbon capture, which is, again, better, you know, than not. It is a, uh, money that's gonna go into this process that's gonna help develop it and perhaps allow us to see more of it, uh, rolled out in other places, which would be good. Um, and of course, it means that Google is going to use a little less carbon producing fossil, uh, fuel power in addition to the many other eco-friendly power sources that they're using.

So it's not bad, it's just not all that green. It's sort of a, a pale gray, greenish color. What would we call that?

I don't know. Puke green. I always call the puke green.

Steven. Yeah. So, so explain this to me.

'cause I'm not up on my carbon capture thing, but I'm assuming I'm gonna look out behind my data center somewhere and there's, I don't know, 10 acres and am I like quite literally, like capturing carbon and just keep digging the hole in the ground until I No, no, that's not what they're doing here. My understanding is they're converting the carbon into CO2. So combining it with O2 right.

And pumping it into underground aquifers, which the middle of the US is riddled with what could go wrong? Yeah. Or people.

And that's exactly it. So, so a DM has been basically producing ethanol, which produces CO2 as well. And, uh, they're the big corn company.

Uh, they, they, you know, they're, they're big Corn arch isn't ADM very corn arch? You Daniel Mills that always gets sued for its kind of environmental disasters. Oh, I don't know What you're talking about.

They're fine. So, so, so let me make sure I understand what you're saying here. So at some point, do I have to like call the septic truck people and they come and pump all this out just like, you know, all those houses on Long Island, or how does this work?

I mean, where does it, you see On Long Island there, Mr. You'll Hear a giant, you'll hear a giant burp coming out of the Midwest just to periodically to expel that gas. We gotta hope there won't be.

Uh, yeah. The idea is that you pump it as, as Alan said, you pump it underground into limestone formations and depleted oil fields, that sort of thing. And you leave it there, and hopefully over time, either it'll stay there or it will, uh, combine with the shale and so on, that will keep it sort of, um, dissolved.

And not, not not tech chemically, but sort of it'll keep it in place. Yeah. It'll, and we better hope that there's not a carbon capture burp a hundred years from now, because if there is, that's a lot of carbon that's gonna suddenly get up into the atmosphere.

But wait, there's more, but wait, there's more. The cost of liquid gas powered energy combined with the cost of the carbon capture and storage makes it far more expensive then solar or wind powered energy. Oh, but there's tax credits.

Yes. It is far more expensive. It will be far more expensive.

And at the same time that we're doing this, China just rolled out a solar field the size of Chicago that is producing way more energy than this and is gonna produce no carbon that we have to store at about half Price. You know what one of my favorite sounds in the world is? It's the sound of that can, as it gets kicked down the road.

But to your point, um, so Google isn't just betting on this, right? So they signed, uh, the corporate agreement for those small modular reactors with Kairos power. Mm-hmm.

Um, and they are saying, what that's gonna be online by 2030, but really operating by 2035. So they, they are betting on both of these and what they are doing, um, for carbon capture that might be offline in 25 years. Right.

So really this is, you know, in my opinion yeah. All about the tax credits so That, that, Well then it's about the tax credit and it's about currying favor with the Don. Not, not to send Steven over the edge, but you know, this is the same Google who's now talking about building data centers in space with other people too.

But, you know Mm-hmm. Mm-hmm. It's, it's true, true Hopey And Google, Google Is doing a lot of different things.

Yes. They're, they're trying to support small modular nuclear reactors and whether those will work, who knows? They're also, for example, they have a new geothermal project that they're working on, uh, in Nevada, I believe.

Uh, they've got, uh, energy storage with a company called Energy Dome, which actually uses CO2 to, uh, store energy, uh, produced by, uh, actual renewables like wind and solar. Uh, so Google isn't the bad guy here. In fact, as I said, Google is probably, this is the positive side of the equation, but I really do think that this is all about politics.

It's about, you know, ha making the current, uh, administration, you know, kind of working with them in their framework in terms of what they'll accept in terms of power and what they'll accept. Uh, a, uh, natural gas powered power plant sounds exactly like what they'll accept. It's supporting a fossil fuels future.

I don't know. I think triples, I think they'll take, that's, they'll take the CO2, turn it into rocket fuel, and then that's how we'll get the data center in space. See, there you go.

Yeah. It's all sick here. And, and, and one more, one more point.

And you know, I'm, I'm not being completely down on this, believe me, but the contrarian in me comes out for this story. So carbon capture, um, it's been around for something like 50 years, right? They've been developing carbon capture and storage that long.

And over all of that time, they've captured and stored less than 2%. 1% of the annual global CO2 emissions, right? It feels to me we are solving the wrong problem.

Not that people don't know that, but the wrong problem is being solved. You know, you're catching everything after it's out versus the, the preventative measures that you could take. Agreed.

It's politics Absolutely endorse that. Yep. And to me, it reminds me a little bit of like post-consumer recycling, which again, is, um, is a feel good measure that really only affects a very small, um, a amount of the waste and, uh, you know, disposal of things that could be recycled.

It, it's about, um, you know, making people feel good about contributing to the solution, which they are. I mean, 1% is better than 0%. You know, 5% is better than 0%, but it's really not gonna solve the problem.

You Know, Stephen, down here in Florida, a lot of the municipalities have stopped the recycling because they have so much they don't know what to do with it, which is kind of ridiculous, but it is Florida. Yeah. So claim low carbon power while you enable high carbon infrastructure.

Anyway, soon, soon enough though, when you get your ai, you'll be able to check that box that says, do you want car? You know, do carbon credits with it, but who knows? So we're, So we're just handing out climate pinkies to everybody that we can just kind of maybe put some branded logos on.

Is that where we're going? I think that was the goal of the last administration. This administration wants toban.

Those, You know, we'll give everyone a participation trophy from fifa. Um, all right. That's a good place to end today's show.

Hope. Steven, Mitch, Mike, thanks for joining us. Thank you for joining us.

Hey, do go check out all our reinvent, uh, uh, content from last week. There's some great stuff up there, Steven. We, it's good to see you.

We'll see you next week. Hope. Always a pleasure.

Take care, everyone, until tomorrow. I'm Alan Hummel. We're out.