Techstrong Gang – April 4, 2024

Hey everyone, it's Alan Shimel for Techstrong Gang. We've got a great day. We've got what's going on with Intel, same old, new stuff.

Is AI really sustainable? Our LL LLMs commodities, we've got that more as well as a special guest on Textron Gang. Hey everyone.

Welcome back here. Happy Thursday to you. We've got a great text on gang today.

We've got three blocks we want to discuss. One is regarding a lot of information coming out on Intel. Some of it's good, some of it's bad.

We've got a very special guest who's gonna bring the intelligence on Intel to you today. We also have a, a great block on sustainable ai, sustainable by design with our own Echo Insights editor, Bonnie Schneider. And then we're gonna talk about in maybe the, the fastest instance of internet time, have LLMs already become commodities.

We're gonna discuss that more. Let's kick it over to our, uh, chief Content Officer, Mike Ard, who will jump in on this. Hey guys, always happy to be here.

We're gonna talk to Daniel about this next topic right away, but Intel's got a $7 billion operating loss in it's chip making unit. They're reorganizing the company. 5 billion from the government to go build some factories somewhere.

5 billion ahead here. I don't know. But Daniel, what's going on with Intel?

I know you follow him closely. Hey, wait. But before we do that, Mike, not everyone here knows Daniel.

Mm-Hmm. Really? Why did you introduced Daniel?

No, I just said we had a special Intel intelligence guest, but this gentleman right here, Daniel Newman. Daniel is the CEO founder of futurum. com is the website, isn't it?

Yes, Sir. Daniel, welcome to Textron Gang. Man, it's a pleasure to have you on here.

Yeah, it's great to be here. A number of the analysts of the Futurum Group have joined, uh, Techron over the years and over some different events. And, uh, it's, it's fun to be in the studio with you all.

Um, yeah, I mean, look, Intel, uh, first of all, chip making, uh, the chip industry is cool. Again, I just wanna point that out. There was a period of time where it was all about cyber DevOps and ai.

Well, thanks to what happened a few years ago, the shortages, people couldn't get vehicles, they couldn't get laptops, they couldn't get their phones. All of a sudden, chip making became the most important thing in the world. And I think you mentioned Mike, uh, when you talked, you said eight and a half billion dollars of grants.

They also got $11 billion of loans. They're building a super fab in Ohio that hopefully will bring the US back on parody, um, at least back to some level of parody on, in terms of what Taiwan is able to do. We don't make any leading edge chips here.

We make none. And that's a really important detail here for everybody out there in the audience, is that Intel has this kind of bifurcated role. First of all, they are a really important, uh, company in the United States.

Uh, Gina Raimondo, the, the, the treasurer, uh, I'm sorry, the Commerce secretary ca came out and said basically, they are a treasurer. But here's why it's important is ai, and we're gonna talk about AI probably all the time on this show, right? Y'all talk about it quite a bit.

Well, you can't run any of these software. You can't do any of these developer apps. You can't, you know, build security applications without chips.

In fact, Silicon will eat the world. I made a prediction three or four years ago, okay? I'm running a Uck here.

But the point about Intel is, yes, they reconfigured, they resegmented their business yesterday. So you talked about a $7 billion operating loss we we're talking about. There is, they've now split to a products and a foundry model.

So everybody thinks about these fabulous companies like a MD and Nvidia. Great business models make a ton of money. Well, Intel is actually a fully integrated, uh, design manufacturer of chips.

They make the whole thing from, they design them, they manufacture them, they sell them. They were presenting their business as an integrated model. And the market wasn't fully understanding it because now they're coming out and saying, Hey, we're a foundry.

We're a foundry as well. So if they're gonna be a foundry, that means they're gonna make chips for Qualcomm. They're gonna make chips for Nvidia.

They're gonna make chips for a MD By the way, they're gonna make potentially chips on arm, not just X 86, which crazy, which everyone knows them for. So yesterday, they came out and said, basically, our foundry business, it is not making any money, but we went back and we're actually gonna show you what our business would look like if we were running a FLI and we were running a foundry. Their foundrys losing a lot of money.

The fabs part of their business, though, is actually making a lot of money. So Pat Gelsinger and their CFO, David Isner came out and basically said, we're gonna show everybody how this works. Now, why this is really important in the end is one intel as a fabulous, does very well, makes a lot of money.

Two, they've executed what they call their five nodes in four years. And this was a really important thing because the company needed to get back in some shape of design, uh, leadership, their technology leadership. Mm-Hmm.

And let's face it, they fell behind. Nvidia obviously jumped way ahead in, in ai. They's still A-M-D-A-M-D across X 86, took market share, both in the data center and on pc.

Um, and now we basically need to understand is Kim Pat Inger, right? The ship, what he wants people to understand is he has help, right? The ship, but the foundry business, let's face it, if a US and the West cannot manufacture leading, leading edge, five nanometer, three nanometer, two 18 angstrom future nodes, we will fall behind on a, on a global scale.

And that yesterday is important. But, um, my last thought, I talk a lot. I'm sorry, my last thought is basically, when does this foundry become profitable?

We're gonna invest 8 billion in grants, or eight and a half billion grants, 11 billion in loans. They're building all these fabs. Everybody.

It's gonna take three or four years just to get to a return on invested capital. It could be before, it'll be that soon. I thought it.

Well, they're talking three, four years. 2030 is when they're really talking about being able to start. Well, I'm just talking about the whole foundry business.

Okay? Yes. Those foundries themselves, they definitely take time to recoup cash.

They came out, they were very honest about it. They were forthright investors, probably didn't love it. But now they've done this great reset Mm-Hmm.

And we now know what Intel's plans are and how they look as both a foundry and as a fabulous, I'm a little more cynical, um, and always am so Really Pat Gelsinger, is he not now the new modern Lee acoa and Chrysler. And this is a bailout from the United States government courtesy and the taxpayer, which is okay, but let's just say what it is. Well, they're not the only company getting grant money.

So you, you know, every one of these fabulous and design companies, whether it's global foundries, whether it's Intel, they're all looking to get capital soer. Companies like Nvidia, a MD Qual, they're all looking because there's innovation dollars, there's, there's foundry and development dollars. Um, look, when the, when the government's handing out dollars to push innovation, every company's gonna be looking to participate.

Having said that, the reason Intel is so important, Mike, and, and by the way, I'm, I'm, I'm, I can be cynical about this too. Um, the reason it's so important though, is that we don't have another option. We cannot completely outsource and offshore all of our leading edge development.

And right now, the only companies that are developing and building fabs in the US are not US-based companies. So you have TSMC building in the us, you have Samsung building us, and these are good partners. These are good allies.

But at some point, you have to understand geopolitical situations change. And if the US was ever required to be self-dependent, to be able to make its own leading as chips, so we can have these phones and these laptops on everything, next generation, vehicles and cars, you know, the lagging stuff we do, we do. Okay.

You know? Mm-Hmm. No one likes, when I call it lagging, by the way, Alan.

Um, but the leading stuff, like, we wanna win ai. And by the way, China, I don't care whether they get EEUV, whether A SML is shipping to them or not. This is all technical stuff, but, um, I Understand it.

China will not stop because of the controls that we're putting into place. They're figuring out their own ways. You saw iPhones down 33% last month.

That's because they've backed huawe. They're pushing Xiaomi harmony, and they're making it easier. More d desirable for people to buy Chinese made products.

And yes, the their, their economy has its own challenges as well. No, no. But yes, it does have their own challenges.

But iPhone, the iPhone market in China was like apple's, I, I wanna say third, second or third largest market. Second I believe. And it's tanking because the Chinese are very good.

The government, they're saying, Hey, one, buy the local one. Um, and, but I wanna be clear to take in your cynicism, in your point, when we talk about 8 billion and 11 billion, some people say, yeah, but they're building factories. It's gonna create all these jobs.

Well, no, a lot of these foundries and stuff, and fabs, they, it's all robotic. It's not a heck of a lot of jobs. But to your point, it is a strategic initiative on the, based on this country's need of high, you know, cutting edge chips.

We can't afford that. If there's a war in the Taiwan straits that we don't have chips or an earthquake, or an earthquake is yesterday, right. Or the day before.

Um, so, so it's important. Here's my cynicism though. I, I commend the loyalty to Intel.

They're a national treasure. They've been a national treasure for as long as I've been in technology. 30 something years.

Are we, are we, are we putting too much money into a, an older horse here? And is, is there some other ones that, you know, are we, are we kind of funding innovation by doing it primarily with Intel? Or should we be spreading those dollars around to some new growth?

Yeah, Well, they put about 53 billion into this with almost five times that in terms of loans and, and, and other investments and innovation. No one else has raised their hands. There's no other company that's willing, willing to build a 'cause.

It's hard. It's really, really hard. I mean, TSMC has built a very, very robust, very important business on a global scale.

But there's no other company that's saying we're willing to take on the manufacturing, the, the, the building, the plants, hiring the people, and building these leading edge chips. And the expertise is complicated. You know, we, what we've seen over the years has been a lot of distribution of, of, of capabilities.

You got these adas companies like Cadence and Synopsis with IP arm, Mm-Hmm. That have made companies like Nvidia able to develop, build and, and offshore their chip making in a very streamlined way. They don't necessarily have the, the Foundry expertise.

So someone has to take that on. Having said that too, I kind of find these, like, I actually put a tweet out this week. I said, we're gonna need chips act too.

$8 billion is nothing. We're, we're adding a trillion dollars to the deficit every 90 days in the United States. $8 billion on investment in the most important foundational technological advancements that are gonna happen in the world over the next couple of years.

I'm not jokingly, like in the next two decades, AI will rule the economy. The companies that are able to participate and play will be the winner. So it's not just about Intel, it's about can Microsoft continue to succeed?

Can Google continue? They need the silicon to do it. And by the way, they need a partner to manufacture.

'cause they're not all gonna run it on Nvidia. And that's a whole nother topic for another day. But Google's making chips.

Microsoft's making chips. Amazon's making chips, chips. And by the way, they're gonna be able to do it because of Foundry.

They need capacity. They need to not be 100% dependent on having it done in Taiwan. Just the microaggressions and geopolitical tensions between China and Taiwan is enough of a reason that the US has to get this right.

50 billion is nothing. And I hate to say that. 'cause I'd take, I'd take 1 billion of it.

I can make a good life of it, probably. Yeah. But we need to spend a heck of a lot more if we're actually gonna win this, it's Will, will this play out as we hope?

Or is it gonna be a situation where we're telling everybody to buy made in America, quote unquote, but then they're still gonna buy stuff that's ARM-based, made elsewhere. So what's the back end Of the thing? They, they can build arm right in these, so what we're really seeing here is the decoupling.

This is an Apple player. Remember you open your iPhone, it says designed in California. It's not built in California.

They're built over there. This is the decoupling of the chip business. Intel will still design killer chips, but they're gonna become a contract manufacturer.

You wanna build an arm, I got it for you. You wanna build a new A GPU for, for ai? We'll build it for you.

They're, they're gonna become a contract manufacturer. It lots Of places to build those chips around the world. We need to build them here.

Yeah. I think, I think the point is, there's gonna be some distribution here. We're at zero right now on These advanced chips.

We Need this. You know, Pat's been reasonable. Of course, he would love to see us get to 50 50, but I mean, look, being at 90 10 would be a, an incredible Zero.

Incredible progress. 10. That's a 10 that's improvement.

And and we need to have some level of self dependence here. And, and if you're not worried about that, we literally do not have a single industry that can function without silicon. Do you think That there's more awareness about this?

You mentioned, because we just went through the pandemic and we saw how dependent we were on China birth. We couldn't get face masks. Yeah.

Couldn't face masks. Or then we were like, what about Advil, Tylenol things, everything that we depend on, um, supply chain. So how do they balance what, what Intel needs to do and the time allotted, um, while they're not making money doing, you know, presenting profits with the need to be independence.

Yeah. That, that seems like that's gonna be a tough balance in the years Ahead. Yeah, that's a great question.

First of all, the, the, the company is very profitable on, its the, the fabulous part now, the way they're calling it products. Mm-Hmm. They make a lot of money on products.

They've carved out all that expense from the manufacturing side now, and they're putting reasonable arms length business relationship. So they're charging reasonable way for, you know, costs back to the products business. But they're treating it more like if Nvidia is buying from TSMC now, that's how products is buying from boundary.

So you can see how that actually works. So they make the money here, but over here, again, they're getting the grants, they're getting the loans. They have a smart capital, which is another way they've raised, and I think it's somewhere around 50 billion of total access that they've been able to get.

Um, there's no, there's no option to not get this right now. In the end, I, I will actually say I've gone on the record and I said, there is a, a better, it would be a better outcome. Now there's, it's not a good outcome to be very clear about this.

If Intel products fail, if the Foundry succeeds. I know it's crazy as that sounds, but in this current era with, with the eds, with the arm and the IP companies, you know, there are a lot that can now design chips. We can design CPUs.

You know, you got arm, you got risk. Absolutely. You got different ways to make phones.

You got different ways to make laptops. You got different ways to make cars. Um, you know, the silicon for cars.

But we cannot get the Foundry thing wrong because like I said, we're one, you know, tactical missile away from having no access to leading edge chips. And you know, we sometimes say that with est like, oh, well if China, you know, look, China believes it has a right to Taiwan. It believes this.

And no matter what we say, if at some point they decide that they want to no longer play nice, which we could argue whether they do today or not, um, it would put us in a situation we should never allow ourself to be in. So this, this has to get, this has to happen. This Has to be done, right.

No, this is too strategic. I, I, I don't disagree at all. I want to give a shout out.

I have a friend of mine down in Houston, my friend Misha Misha Stein. Misha was the founder of, uh, alert Logic. But he, he left there, he founded another company called, I think it's Macro Fab.

Five years ago. He told me this. He said, Alan, we're going to a world where we need to build our chips either in he, I think he was doing stuff in Mexico and the US and, and we're just gonna be a contract manufacturer for chips.

And I laughed at him back then. I, I didn't, you know, I said, how are you gonna compete with Intel? How are you going to compete with a MD?

See, there's gonna be a lot of people who want chip designs and, and he was dead on. So if you are watching this, Misha, good, good on you, man. Anyway, I think that's gonna wrap up.

Lock one here on Textron Gang. We're gonna be back. I think we've got Mitchell Ashley waiting in the wings, and we're gonna talk about sustainability and ai.

Something near and dear to Bonnie. We're a tech drunk gang. We'll be right back.

Hi everyone. Welcome back to the Techstrong Gang. Well, we are talking about sustainability because in the wake of the high demand for everything, AI, sustainability has to come into the conversation.

And recently Microsoft has been addressing that, especially with their ambitious goals of reducing carbon, um, emissions by 2030. If you wanna build lots of AI products and you wanted, at the same time, you have to address it. So some of the, uh, Microsoft points that were brought up where water usage, maybe we should be using air rather than water for cooling, perhaps turning to sustainable materials.

There's a lot of different solutions that can be done as we see the momentum build for ai, um, when it comes to sustainability. So I think this is gonna be a growing part of the conversation as we, as most companies are looking to reach these goals by 2030, you know, you, it, it's sort of like wanting to have your cake and eat, eat it too. You have to do it in a sustainable way in order for it to, to last and, and to not tap into the resources of the earth as everyone's doing this at the same time, clearly there'll be an impact.

Yeah, I think this particular blog article was almost like a position paper saying, here's what we think this is what we're gonna do and how we might do it. And there are also kind of secondary and tertiary uses of the byproducts of what, like, for example, air, like the heat coming out of a data center, uh, also using that to heat homes. I think I said like one data center could heat 6,000 homes.

So they're, they're thinking, they're sharing ideas about not just within their immediate ecosystem, but kind of broadly within their partners and then the community. Yeah, I agree with that. Especially when it comes to even building data centers using green construction materials, for example.

That's something on Ecotech insights. I've been interviewing a lot of people looking to do that from top to bottom. Make it a sustainable effort.

You know, an interesting thing, Mitchell and I have a friend, Terry Swack. Mm-Hmm. And, uh, she's the CEO founder of a company.

Is it Clean Minds, green Mines? Sustainable Minds. Sustainable Minds.

Yeah. It's actually Terry's birthday. Happy birthday.

Happy birthday, Terry. Um, But you know, I was with Terry a couple months ago. We had a few drinks and um, but she gave me an interesting fact.

25% or more of greenhouse gases are tied into building Mm-Hmm. Whether it's the manufacturer, the manufacturer of materials that we build with or in the act of building itself of construction, tremendous amounts. Data centers are at, you know, kind of at the top of that list, right?

That's why they, you know, for a while we were building data centers in the Arctic. Mm-Hmm. Because you can get cool it there, or they build the data center next to our hydroelectric dam to get access to it.

AI is exasperating this, but here's the golden lining for me. Let's use AI to figure out how to build better, more sustainable facilities for ai. I think this is a case where, you know, you, you can have your cake and eat it too.

To your point, And that's where, I'm sorry, go ahead. Go ahead. I think this is a watershed moment comes the day that Microsoft spends this amount of time and energy to create a blog that looks like a position paper.

It means that people are screaming in their ears about this and that they're hearing that this is a serious issue. And they're basically running a PR game here to say, you know, we're doing something about this while we continue to consume massive amounts of energy. So I kind of feel like, yes, it's great that we're talking about it, but I've, you know, been around this block with these guys a few dozen times and I know how they operate.

And when they start writing at this level, it means that, you know, they're trying to lobby somebody and they're trying to prevent some legislation from being crafted or something's up. So I think there's more here than what it looks like. You know, if, if, if AI is the engine, data is the fuel.

Mm-Hmm. That's the other half to the coin you're talking about. Yeah.

Which is think about the vast amounts of data. And Terry's company is one example who, who has a lot of data about the impact of the manufacturing materials and all of that. Think about all the data that we have now about products that we're creating and, and now that we're paying attention to it, gathering the right kind of data to be able to make the best decisions about reducing impact, about operating it more efficiently or building it more effectively, or reusing all those, all the byproducts of, of those activities.

So it's ai, but AI powered by a lot of really great valuable data. And you know, one of the things with AI when it comes to fighting climate change is we're seeing a surgence of companies that are creating twofold. One, monitoring, measuring carbon emissions within software and different companies.

But the other side is what kind of what Alan was talking about, the innovation and technology to reduce emissions, build more sustainably, um, track different areas where we're, we're not monitoring emissions, like let's say through drones. I interviewed someone from a company that does that. So I think that, um, the Microsoft blog does point to a bigger picture of like what Mike was saying, of what we're, um, what they're, what they're looking for going forward.

But underneath it all are these innovations that are happening around the world right now to track monitor carbon solutions and also create solutions just to mitigate the, the, the, if we're gonna use this much ai, we know we are. Okay, well then how are we gonna manage not tapping into water, which is limited already. So, um, I think it's all happening at the same time.

Can I ask you a question? Do you, do you think Microsoft's blog post is something that will be like to the watershed moment others will use as a, a pattern or a baseline to start doing now that's us put our, our position paper kind of validating or extending what that, is it that big of an impact? It, I mean it depends on, on who's looking towards Microsoft.

A hundred percent for leadership. But across the board, if you go to different websites of different companies, it is prominently displayed, displayed now. And something that I find that, um, people wanna push forward more in their messaging of how they're doing, um, their own ESG goals and their sustainability.

But a leader like Microsoft definitely could set off a chain reaction that validates It. Yeah. Yeah.

I think there's a guy somewhere or gal in Europe working for the eu, has their pencil out and is calculating right now what the carbon AI tax is gonna be for the impact that these things are having on the environment and what they're gonna come back to folks and say, Hey, this is what, this is a real cost that you're gonna have to bear. And I think that, you know, a lot of this stuff is pre-positioning to kind of get in front of that stuff. It's, it's Possible Shades of Al Gore Who reinvented the internet.

Right. Um, alright. Anything else on sustainable ai?

Well, it, we'll see what the ripple effect of this is and the outcomes might Be, right? Yeah. We'll see.

And I just think it's something, a topic to keep your eye on because it's gonna just keep coming up more and more. Vote, absolutely. Vote for more efficient LLMs.

That would be the way to go is just to reduce the amount of carbon being generated in the First place. Well, we're gonna talk about LLMs next, but first here's a break we're you're watching Textron Gang. Hey guys, this is JJ man with Mitch Ashley co-host of CSO Talk where we have engaging bite-sized conversations for current and next Gen CISOs.

You know, we have some of the best conversations on CISO talk with some of the greatest talent in security people like Andy Ellis who talked to us about optimizing security strategies and how to navigate the boardroom. Lisa Bradley came on and talked about vulnerability management bug bounty programs and Y SBOs aren't the solution to all your software security problems. Steve Reynolds was also another great guest and he talked to us about what not to do when a security incident happens.

The what not to dos are great, but we also had Eve Mailer and Steve bitten on talking about security, uh, and third party software, SaaS applications, and weaponizing ai. So go ahead and join us for the latest episode of CISO Talk. You can find us by going to Tech strong TV slash CISO talk.

All right folks, we're back. And as promised we're talking about LLMs. Tab nine is basically put out an announcement saying you can bring your own LLM to their tool that lets you write code or test code that will be automatically generated by their LLM, but now they're turning around and saying, Hey, you know what, you can bring open AI or whatever LLM you feel like.

And it seems like to me we just went from, wow, this is the most amazing innovation in the world to maybe an expensive commodity that I can just call through an API and I'll swap 'em out as I see fit. It's internet time baby. Well, it's interesting.

Time Crunch tab nine went through their own transition 'cause they own had their own proprietary non A LLM gen AI based product and they transitioned to a gen ai. Now they're transitioning to well, and you can add your own, because a lot of the concern is just about I don't want to code, I don't want put my code into a third party LLM that I'm gonna lose the data. I lose control over that.

I mean even, you know, I hear people talking about podcasts, so use LM Studio to just do your own LL take, take it from hugging face and work on it in your own environment. So it seems like that almost, um, you know, kind of the hotel of your own LLM and tools will be a trend to be able to protect it. I'm trying to figure out if people are gonna orchestrate LLMs across different tasks.

So I'll have an LLM that's optimized for a specific function and then I'll use another LLM for a different thing and then I'll have these agents stitched together. And as that become a workflow, I think it's early yet, but it feels like that's where it's going. That's Kind of what the Oracle announcement was about, right?

Yeah. They announced their, I called a broker to decide which LLM or gene AI system will answer what part of the prompt Look, I think we're moving to a modular future. We saw this when we were at reinvent guys, right?

When we were doing our interviews. The, the way of the future is sort of what, what's the sales one called? Einstein?

Yeah. Mm-Hmm. Where it, it's a front end and it can plug into multiple LLMs, it can plug into multiple ais.

You're not in a walled garden. Choice will be the rule of the day until one of these becomes dominant or something like that. But I don't, I I think the market has already spoken fairly quickly and early that they want choice when it comes to LLMs and they want choice when it comes to which ai, they don't want to be locked into open AI or, or Google's or, or anyones for that matter.

They also want specialized or don't domain specific LLMs. They want small SMS S SLMs, right? Mm-Hmm.

To, to be out to the efficiency point, right? Instead of throwing open ai AI at it chat GPT, let's do something that just does code for these kind of environments. That Example, I agree.

I think it does sound like it's a more efficient option. Um, but is it more taxing on energy overall if you're using, if, if the LMS are getting larger themselves? That's more of a question I guess I I, to to the other point we were talking about using ai, I think you'll be monitoring like, well I can run six of 'em, but this one, these two do the most efficient.

I can save a lot of money just by sending more as long as I'm getting the data from it. I think that'll be one of the factors of who wins. Yeah.

And there's a subtle difference between the training of the LLM requires massive amounts of data and energy. The inference engine that creates, it's only like in terabytes and you can kind of drop that at the edge. Not so much energy being consumed on the, on the inference engine side of the equation, but we saw, um, open AI and Microsoft were talking about building a hundred billion dollars data center somewhere to drive some massive LLM.

And you gotta wonder, do we really need a general purpose LLM to that size to do what for us? Because it seems like the smaller l LMS are more efficient. Maybe It'll be a bunch of small ones and they're just calling it one thing, you know, who knows?

You know, I, I think that's gonna be an interesting, uh, evolution. We need to watch on that. I I, you know, as an industry we always tend to go big or go home, right?

So let's build the super duper computer, LLM. But I, I think the fact of the matter is early I, and it's still early, so who the heck knows? But the early indications are that smaller, more focused give you better results than trying to boil the ocean.

Think About it. Do you want chat GPT to organize your calendar and prioritize things? Do you want a SLM that's really specialized at time management calendar, Whatever.

I, I, I think that, you know, but it'll be interesting how it plays out. But I, I look LLMs are going to be commodities how quickly their commodities there Are hugging face is Proving that, right? Yeah.

I mean, and that's, that's just the Way of this. And I think it becomes easier to swap because I may just be invoking the LLM output through an API. And if that's the case, then, you know, I'll just move between cloud service providers as I need and then I'll just take the inference engine and deploy that wherever I need and everything becomes disposable.

Swap 'em. Maybe you put the prompt to four LLMs and three of 'em agree. That's the right answer.

Or, you know, you arbitrize immutable. Immutable. Yeah.

Excellent. Interesting times. Yes, it is.

We and then you always live in interesting times. We're ending this on an Irish uh, I thought that was a Chinese proverb. A Chinese proverb.

No, I thought it was an Irish. We're already getting yelled at by the Chinese for today. Alright.

Alright. Let's keep the Irish out of it. Anyway, that's gonna wrap it for Textron Gang today.

Many thanks to Daniel Newman from, uh, futur for joining us on the Intel piece. Thank you Bonnie Mitchell. Mike, we will be back on Monday, so not Friday.

We'll do our best of, we'll be back on Monday with Fresh Techron Gang. Enjoy the rest of uh, techron TV today. We're out.

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