Techstrong Gang – October 29, 2024

Hey, everyone. Happy Tuesday. We are one week out from Election Day.

We are in the midst of the World Series and the New York Yankees need your support. You are watching Textron Gang. Hey everyone, it's Alan Shimmel.

Happy Tuesday to you. As I said in the opening a week from today, polls will be open all over the country. They're open in a lot of states right now for early voting.

If you haven't voted yet, go vote. If you are waiting for election day, make sure you make time. Lines may be long, but don't let that discourage you.

It's your duty vote. Um, beyond that, hey, I'm wearing the Yankees hat today in support of my New York Yankees. It's a tough series against the Dodgers.

They're a formidable team, but this is what the full classic's all about. In addition to this, though, we have a great text on gang date today for you. Our friend Steven Foskett from Tech Field Day, is gonna give us an update on Cloud Field Day, which took place last weekend is available on Tech Drug tv.

We're gonna talk a little bit about AI weather forecasting and how the race is on to give us the most accurate weather, blue weatherman ever. Give us the most accurate weather reports. Yes, well taken from the Weather Lady, um, and data center, heated greenhouses that's kind of selling sushi out the back of the bait store.

But, um, anyway, let me introduce you to our gang who we're gonna discuss this with today. First of all, I mentioned he's joining us with his Cloud Field Day report. He's the CEO, uh, founder of Cloud.

Uh, field Day Tech Field Day, part of the Futur Group, uh, friend Steve Foskett. Hey, Steven, how are you? Hey, it's good to be here.

Uh, good to have you have been enjoying the World Series so far as I know you have as well. Yeah. Yeah.

Win or lose. They've been exciting games. Exciting games.

Um, Steven, thanks for joining us. Joining us, our royalty from Silicon Valley. Who, who?

Me? Oh, oh, the Silicon Valley. He's an editor here, ad tech strong on, on all things tech.

John Swartz. Hey, John. Welcome.

Thanks for being on. Hey, Alan. I voted, uh, two weeks ago and turned in my ballots Ooh, early.

And I want you to channel the 1996 World Series. Remember what happened when Atlanta won The first I thought the same thing. I thought the same thing.

Right? You in the, what happened in the Yankees? The Yankees had a two oh lead on the Dodgers back in the early eighties, and the Dodgers came back in the strike.

Shortened year can Happen. Yeah. For the 2004 A LCS, you know, that was a good one too, From the Red Sox fan.

Yeah. From the Red Sox fan. Um, next, he, well, he was here, but he's not, he'll be back in a moment.

Joining us from up in Yankee Town, New York, our chief content officer, Mike Ard, he'll be right back. Hey, Mike, hope to see you in a minute. And then finally sitting next to me here, she, she's also a Yankee fan as well as a weather for a weather person extraordinaire.

She's written books on it and has been a, a media Well, that has been, yeah, she still is a meteor meteorologist, um, as well as covering the sustainable it, uh, field here as an analyst and and editor at Tech Trunk, our own Bonnie Schneider. Hey, Bonnie, how are you? Great to be here.

Great to have you on. And here he is. He's, he was back there.

He had to take a quick call from Aaron Boone, and Aaron wanted to know what he should do about the bullpen tonight. Um, oh, there you go. Eric could use the help, but anyway, let's, let's jump in right into things today, Steven.

It was last week was Cloud Field Day. Right? Why don't we, would you mind giving us maybe a, the 4 1 1?

Yeah, sure. Thanks a lot for that. Um, yeah, and, and you know, one of the things I think that we've been talking about, well, all of us in the industry have been talking about for quite a while is, uh, you know, what the heck even is cloud anymore.

Um, you know, I had this, uh, conversation with a friend of all of us, John Willis recently, um, when we were talking about, uh, cloud camp and all that stuff that we used to do, oh, those many years ago when cloud was really a, a, a cutting edge, uh, alternative operating environment. A whole new concept. Well, I think the one thing that came through loud and clear at Cloud Field Day this year was, um, that frankly, um, cloud is just, is everything now.

Um, if you're not doing things with, uh, modern applications, modern platforms, if you're not, um, at least virtualized, most, most people are container containerized and, and using orchestration software and, and, and, and scale out applications and scale out infrastructure, and all these things that were so alien and so exciting to talk about, you know, 10, 15 years ago, well, then you're clearly not doing it right. And I think that that was really, really evident here. And, and frankly, um, even more than ai, I think these cloud concepts are really dominating the conversation in, uh, enterprise tech.

So, cloud Field Day is an interesting one because essentially what used to be our general Data center event Tech Field Day has really morphed into, into Cloud Field Day. And we're seeing that increasingly with this event. Now, the star of the show, um, I, I'm sorry to say it was VMware, uh, I'm sorry, because of course there were other companies, but the star of the show was VMware, and I have to say, must watch TV is the first segment of the VMware presentation, because essentially they came right out there and they talked straight to the audience about what's going on with, um, the, uh, VMware in the enterprise.

And, and, and answered many of the questions, um, in terms of what to expect from VMware. Now that, uh, you know, now that, that things have changed under Broadcom. Uh, the speaker, uh, was, uh, Prashant Chano who knows this, uh, because he's, uh, basically responsible for the whole VMware Cloud Foundation product line within Broadcom.

And he was wonderfully candid, wonderfully forthcoming about how VMware sees the enterprise, how they see their customers, how they see the future of the cloud, how they see the future of the data center. And I think everyone around the table, number one, I don't wanna say we were surprised, but we were thrilled to get that kind of straight, no nonsense answer straight from the man who knows. And we were also, honestly on board with a lot of the things that he was saying, essentially, VMware has refocused.

And one of the most remarkable things he said, um, and, and I don't wanna quote him directly, was that essentially they knew, he knew the rest of the team, knew that VMware had kind of, I don't wanna say lost its way, but basically, um, had too many paths, too many products, too much going on, um, and really wasn't guiding the right customers in the right direction. And that the, the whole Broadcom refocus really allowed them to do what they knew they had to do, but just couldn't do under as an independent company. Again, it was a remarkable session.

Well worth watching, as you said, that's on Techstrong tv. I'm gonna be posting the video recording of that to YouTube, uh, today. So keep an eye on the Tech Field Day YouTube channel to watch that segment of the VMware presentation.

But of course, there was a lot more than that, that happened at Cloud Field. A, um, we also heard from, uh, platform nine who are delivering a very compelling alternative to VMware. And again, I don't think that that's controversial among VMware.

I think a VMware is basically thinking, you know, Hey, we're going in this direction with these customers. Other customers are going in this direction, and they can use a product like Platform nine. I, I think it's an opportunity.

I think it, there's even some friendliness there. Um, uh, despite what it may look from the outside. Another thing that we saw was, um, a reborn Qumulo.

Uh, this is a company that has basically been a, a leader in technology in terms of, of building out storage, um, building out, uh, basically a global fabric of data. Um, and they've got new management under, uh, a good friend of mine, uh, Doug Gole is their new CEO. He's directing them in the right direction.

They've got a lot of new folks in there. And essentially, um, they have this, this gold mine that has been built at Qumulo over the last 10 years. And they're gonna try to basically relaunch that into the market.

It's a good product. It's at the right time. It has a really nice fit, especially when it comes to ai.

So I'm pretty excited to see what happens there. And then finally, um, I, I need to call out. We had a lot of delegate discussions.

Um, we had Delegate Roundtable discussions on cloud repatriation and, and what even is that anymore? And, um, as well as, um, you know, just incredible overall discussions of what it means to be enterprise, what it means to be cloud, and what it means to go in this direction as an enterprise. Where are we all going in this new world when, when VMware maybe isn't the dominant force that they once were in the data center, ex to some companies, but, but even more important to others.

Really interesting event. So Steven, you know, interestingly, you led off by saying more than AI Cloud, you know, is, is is happening, well, to me, this is a, this class crossing the chasm, right? Cloud at this point is squarely mainstream, and not just the early mainstream, that 30, 35% that are early mainstream, but the 35% of the nut laggard, uh, the 35% of the later mainstream, right?

So the 70% of the market that represents critical mass plus your 15% early adopters, right? It's 85%. That's critical mass, yes, there were probably 15% of laggards that don't have anything at all in the cloud.

But this isn't 2006 as cloud. It's not just AWS anymore. Google and Microsoft and Oracle and IBM have valid cloud offerings.

And I think one of the biggest things that we didn't foresee back then was multi-cloud, right? I think we all kind of suspected hybrid cloud. I'm not gonna move everything to the cloud.

I'm gonna move some stuff to the cloud. I'm gonna keep some stuff in my data center, especially my mainframe and, and I'll, I'll, you know, do that hybrid cloud thing, but multi-cloud and the, and the how quickly it's caught on, I think was the surprise of, of it. And then how do we manage a multi-cloud environment?

How do we, you know, play nicely with multi-cloud and on-prem cloud? Is, is is the key to it? Um, as far as VMware, yes.

You know what? Sometimes a little pruning is a good thing to keep a plant healthy. And the same thing goes for companies.

Um, and that's what Broadcom does. But interestingly, to your point about this Platform nine versus VMware, right? Broadcom has a very interesting marketing approach.

They're not looking for new customers. They have enough customers, they want to go deeper into their customer base. And so they tend to go after the eight or 900 global 1000 accounts that they have and, and expand there.

If you're not in that profile, they don't really, they won't turn your business down, don't get me wrong. But they don't really go outta their way. And it is an opportunity for companies like a Platform nine to come in here.

I think the other thing is Edge. Edge is part of the cloud, right? When we think of Cloud nine, you can't just think of these big hyperscaler data centers.

You gotta think of what's going on on the edge and, and how that, you know, the flow of information, the flow of data, where it's stored, where it's processed, where that's gonna happen, and what role AI's gonna have on that, on that edge. You know, Mitchell and I host to show with our friends at Cloud Flare, and I would've loved to have seen that mc Cloud Field Day. Um, you know, there, the name of the show is the Last Great Cloud transformation, and it focuses on something they call the, um, oh, I'm gonna mess it up now.

The Continuity cloud, no, the Connectivity cloud. Because as we move into these multi-cloud, edge cloud, hybrid cloud environments, what becomes key networking between the cloud, we thought networking was dead. It's not right.

Networking between the cloud and security too big, the two big pieces of that puzzle, mm-Hmm. Oh, so, oh, well, you know, just kind of piggybacking off of what Steven has said, it all kind of plays into, in Silicon Valley, everything's about ai, but before that, we had the, the decade run decade dominance of cloud in which every major player had no choice but to get into that field. And I think AI, in a sense, kind of twins with, with Cloud, um, you mentioned Amazon, Oracle, IBM, Microsoft, Google, uh, it's, it's just part of the evolution, right?

That was, that was the great single quantum leap until AI came along. So, um, it's interesting, you know, the one thing I want to ask, uh, Steven, and I hopefully this is not, uh, just kind of too generic a question, but in the tech field day, can you kinda give us, give us, for people who may be unfamiliar with it, like gives kind of an out, uh, outline of what happens at one of these events? Well, sure.

That's a, that's a, a, a slam dunk for me. Uh, thanks for, for offering. Uh, no, I, no, it's interesting.

Yeah, essentially, um, we bring in a group of people like us, essentially the kind of people that come on Textron Gang, and, uh, we fly 'em to California and then companies come in and they present to us. The twist is that, um, we're not just passive. We're not an audience.

We're part of the show. Um, you know, we're asking questions, we're engaging and we're driving it. And, and, and for me, that's really what happened here.

I I always tell the presenters, um, the difference between Tech Field Day and basically anything else you're gonna do is the delegates, the delegate questions and the delegate interaction. And so you need to embrace that. And that's exactly what we saw.

And, and, you know, back to that presentation by Prash Chano from VMware, um, I was a little nervous because this guy's, I mean, he's the CMO, he's, he is way up there in the company. I was worried, well, how he would take it when the delegates came at him with questions, but of course, they're not coming at him with negative questions. They're asking pointed and thoughtful and, and, and topical questions.

And he really embraced those questions in a way that I, you know, it was really wonderful to see the best presenters do that because they come in there and they say, I see what you're saying. I see the validity in what you're asking. I know you're not trying to cut me down here.

Let's dig in. And, and for me, that's when, when Field Day gets real, whether it's a CMO knocking down difficult pointed questions about their product, or whether it's a demo where they're doing a live demo, and the delegates say, well, what happens if you do this? What happens if you do that when I'm starting to throw things in there?

And, and that's really the magic of Field Day, and that's really what companies are getting. And there's actually one more thing that they're getting too. And this is something that's not visible outside and really not something I've talked about ever.

At the end of each presentation, we have an off-camera feedback session where the delegates give, let's say even more pointed critique and discussion of the companies, um, you know, in a way that's not recorded and not shared. We call it Friend because it's not really secret, secret, but we're all friends here. But let me tell you what you did, right?

And let me tell you what you did wrong here, in my opinion, um, that's become so valuable that we actually have companies signing up just for that. So there's actually some companies that are participating in Field day events that you'll never hear about and you'll never see, because basically we're just having those behind the scenes conversations with them and, and giving them that kind of feedback from people who really, and this is to me, that the most important thing. People who truly care about the technology and the products, just like the people here, you know, it, it's like, we wouldn't do this if we didn't care about technology.

So it's like a constructive dialogue, basically. And, you know, and CEOs or CMOs, whatever the c title is, they want suggestions of what the customers want, where they wanna see things go, and then they adapt to it. That's the thing they've always done.

I mean, they do that from version to version of every product. Well, the good ones do, let me tell you that. Yeah, Yeah, that's true.

Everybody Appreciates that. Yeah, True. And maybe most people shouldn't come to field day.

Uh, you just have to work it in. Yeah, we actually have open nominations. Um, you know, we basically pick a group of people for each event.

I would love to have you there. I would love to see, you know, John, I mean, Alan, we've seen you there. Um, I really want to get, basically, like I said, pretty much anybody who would be on Textron Gang, um, would be a great delegate.

Sure. Well, we always have no shortage of opinions here on Textron Gang. Um, hey Steven, what's the next, uh, cloud field days, not obviously the cloud field days?

What are the next tech field days coming up? Well, we actually do have another Cloud Field Day event coming up. We just announced it, uh, on Friday or on Thursday, uh, February 19th and 20th.

Uh, we're gonna have Cloud Field Day, but the next Tech Field Day event is actually networking field day. So that's November 6th and seventh. That's next Wednesday and Thursday.

Um, we've got a bunch of great incredible group of networking companies coming in there. A lot of small ones, a lot of, uh, really kind of the interesting ones that are doing kind of new clever things. So, uh, keep an eye out for that one.

And then, um, really excited to be saying that we're gonna be taking Tech Field Day on the road to CubeCon for App Dev Field Day. I know you guys are gonna be there. Uh, that's beautiful.

You know, you, Mike, uh, come on. Maybe, you know, uh, it's be great to have you As all there. There's this invitation right here.

Here's your invitation. Boom. You Ask.

I feel like I did Tiny Tim's wedding or something. Yep. Live online.

Wow. Wow. That's going.

Some brothers would like that one. That's going back a while. Um, damn.

All right. So that's Q Con though. And that's no, the week of November 11th, if I'm not mistaken.

That's the, yes. That's right's. All right.

Sounds good. All right. So there's our, there's our tech field day field report from Steven.

He knocked it out of the park, keeping our baseball. You see what I did there? Little baseball theme.

Um, we're gonna take a break here. Our text Drunk Back gang. We're gonna come back and talk about the AI weather forecasting race.

You know, there was a race you're watching Text Drunk Gang. Hey everyone. We're back here on Text and Gang.

So is there a, a AI weather forecasting gap? Are we in an arms race around AI weather forecasting? The Washington Post seems to be stirring things up.

Of course, they never wanna express an opinion hate, but in this, in this one, in this one, they are. Mary Finally did this one. Yeah, Uhhuh.

Um, so John, but we had an article following up on this on Textron ai. John, I know you were watching it. What, what, what's your take?

Well, It's, it's interesting. So there, there are these AI weather models that have kind of, um, evolved or burst on the scene this year during the hurricane season. And basically what's notable about them is they provide these accurate forecasts of where a storm's gonna land several days in advance.

So you have a pretty good idea of where to evacuate and when, um, uh, evidently the private sector in Europe's Weather Agency have done a better job than the US in developing these models in recent years, raising concerns that, um, we've fallen behind in a high tech race that's transforming weather forecasting faster than anyone expected. So, in a sense, AI models, what they do is they're trained to recognize patterns in, based on decades of historical weather data. So they're gonna be more accurate and more accurate into the future, which to me is a great, uh, byproduct of ai.

Um, having li lived in the Bay Area most of my life, I'm frustrated by the microclimate forecast because it changes so often from city to city. Yeah. So the Forecast would Bay City, bay area.

Yeah, exactly. And Bonnie, maybe you could explain how that works. And then I, I was going to, I had another couple of questions, or a question at least for you about AI modeling and Sure.

And, and impact it would have on other industries. Well, It's interesting that you mentioned the, the microclimate forecasting. 'cause that's kind of a nice segue into the AI story in San Francisco.

Um, when I did a, a book signing for Extreme Weather, I spoke at San Francisco State, and I remember, uh, the change in weather from being in down in the city and then being up a little bit higher. It was dramatically different. And they were explaining to me about the microclimates of San Francisco and how you have to bring a jacket with you depending on where you are or, or be ready to take it off.

Um, so we do have these little nuances that are affected by topography, geography, buildings that are, that are up in different cities. And this is where there could be limitations with ai, because AI is, is definitely, has improved weather forecasting in terms of doing it faster and processing data from large data sets that would take a human much, much longer. Um, and you and the story talks about in the Washington Post about Europe being ahead of the game, and that's true because Europe has invested much more money than the US has on, on the government sector for ai.

Um, this, the second story talks about a little bit how they've done it for marine life, which is great because we're able to observe more and explore more to protect fisheries and marine life in our oceans. Um, but there, I just wanna also mention the limitations of ai, uh, as, as a meteorologist is that there, there has, there, there is a human aspect when it comes to looking at large data sets and models. And when we interpret a weather model of where a storm is going, for example, it's the, uh, the idea is there's not one model.

There's many of them, and they run six hours, three hours, you know, throughout the, the forecast. So the meteorologist job is to assess the best version of the model, the compilation of all of them. And that involves a process called model bias correction, where we kind of know, you know, patterns and recognize that and can make an, an assessment based on, on knowledge and skill and things like that.

So really, like any IA quandary ai, when you're talking about where does a human come in, I, I think that could be some of the resistance, um, with no, uh, uh, this is just my opinion, but, but it is coming and we're seeing it with big companies like Nvidia and Google. So, um, overall I think it's a positive. So I, Can I ask you a quick, can I ask you one quick follow-up question before?

Just before. Before, okay. Okay.

I just gotta say, listening to you guys talk about the, the, the gap and, and the AI weather forecasting race, I have visions of, of a guy riding a, riding a missile or a plane into the eye of the hurricane, Dr. Strange glove style, right? Who, who, what I Was gonna ask you about Yeah, because, so would an AI model, Bonnie, for instance, so one of my, the things that always confuses me is when we have a category five hurricane headed towards, say, Florida, south Florida or central Florida, and then by the time it hits land, it, it declines.

Would AI do a better job of telling us what its severity would be in terms of category by the time it hit lands? Or is that always gonna be okay? Yeah, I think there's, that, that's where you get into the local nuances, because when it comes in, this is why that we had the big threat with the last storm, very worried about Tampa.

I, uh, we're always told that's the worst case scenario because of the bays of, uh, you know, and the, the topography of the coastline. Um, how deep is that? The, the water where the storm is gonna come in?

There's so many factors and nuances, the terrain it's going to encounter as it comes on shore that are very specific and, and very local. There's an expression in weather that all weather is local. Um, so that's gonna be an issue for ai, but the combination of human input using the AI's fast computing, I think that's gonna be the sweet spot where we'll see, uh, meteorology advance.

I, I good to tell you. So look, we, I live here and, you know, there's another storm brewing maybe this weekend to next week. They send, hopefully that'll be the last, I don't know if There's a forecast out.

There's a November, November 30th is the last day of sea November, Uh, oh, I heard November 4th there was gonna be something getting self. No, there's a storm There potentially November 4th. November 30th is the official end of hurricane season, end of season.

And of course, my boat is due to come out of it's indoor storage this week. S like, we very rarely get anything in November. I'm gonna have to extend it.

But that being said, what we're really talking about here is what we call the spaghetti models, right? You've ever seen these spaghetti models? They look like spaghetti.

There's, it, there's like 12, 15, 18 different models, and they, and then the storm goes like this. And yes, maybe the European model the last couple years seems to have, have an inside track on, on being more accurate. But like this last storm, it, so it, it, there's never been a direct hit on tamper in the last a hundred and something years.

This last storm, again at the last second kind of veered south and went in near closer to Cyrus Solar to Bradenton, uh, long vote key. But what happened in that was, it wasn't that evening, the water, from what I read anyway, there was a, a high pressure or a low pressure system up high in the atmosphere that kind of flattened the storm, made it less powerful, but broadened the, the width of the, or radius of, of the storm. So it affected, and that's what helps spawn the tornadoes down south here as well.

Mm-Hmm. This is just such a large data set type of, of Yes. Issue that of course, I think it lends itself to AI because it's hard without AI to have a modeling, uh, environment that works.

And I think it's also going to be the X factor of climate change, because I've been doing this for, for a long time with weather and, and I speak with other meteorologists and we've seen changes, um, in terms, let's say in hurricane season, for example. Um, ending a lot later, having powerful storms in October. Um, that's something I remember back in with covering Hurricane Sandy in 2012.

But before that it, it just, it doesn't, it seems like it, it was a little bit less like it would end earlier. We would this, we wouldn't be talking in November about storms. No.

So there has been some shift, um, that some attribute to climate change. So with AI using that large data set, it's also gonna have to do predictive analytics in terms of climate, because I think there's gonna be nuances there, um, as well. And those spaghetti models are key because they give the consensus of, of where the models are going.

And the meteorologist job is to say, okay, how do we make sense of all these spaghetti models and, and what are the trends that we're seeing? But every hurricane, and we've seen this with many, they can wobble at the last minute and shift the path. And, and, and that slight shift of where it hits can make a big difference.

So I, I was thinking about the, the implications though. It'd be really positive implications for this and the ability to forecast more accurately, farther ahead for the shipping industry, the supply chain, airlines, et cetera, people who want to go on vacation and can plan around it. I mean, that, I think that's huge.

The Problem is I just don't know how truly, truly accurate at ever gets, right? Mm-Hmm. Yes.

'cause there's always the uncertainty, but, but let me be clear because I, I don't think you were, we are seeing more powerful storms than we've seen in the past. We are seeing our hurricane season extended further than it was before. If you don't think this is due to climate change and stock, you know, it's not.

Maybe could be potentially it's, we are undergoing climate change and not only in terms of storms. I live here, I boat here, our water in the summer is 88 degrees, 90 degrees, and that's the Atlantic Ocean, not the Gulf, which tends to get warmer, right? I'm on the Atlantic side, and it is so hot that of course, it's a, it's, it's a spawning ground.

It's a perfect environment to spin up large, powerful storms. You know, also, you Know, that's what the AI has to factor in, you know? Yeah.

What was the water temperature now versus years ago? And that data set is gonna be key. It has to recognize the, It's, it's affected our fish migrations, right?

We Definitely, You know, here in South Florida, We also think of the, the impact of a, of, of climate change on wildfires. There's, there's the same number of, of fires every year, but there's just, the intensity is larger Because, and the season has started earlier. Mm-Hmm, yep.

Yes. And it gets, the brush gets drier. I mean, it's just, We're at, we're seeing the effects of climate change.

Steven, go ahead. Yeah, it's interesting because, let me, lemme take the AI angle to this story and to Bonnie's point, I think that one of the interesting aspects here is that there's, in weather forecasting, there's sort of a combination of, um, analytical models, um, prob probability models that to your spaghetti, uh, graphs as well. But also intuition from, uh, weather forecasters, um, based on sort of historic knowledge.

And, and I could see that this could kind of have both pros and cons to use AI models here. 'cause on the, on the pro side, AI is extremely good at handling a large volume of data. Um, it doesn't get distracted or, uh, sidetracked, uh, or just bored, overwhelmed by the, by all the data points.

Um, so I could see a, um, a, uh, deep learning model, uh, being able to handle, um, all the complex variables that come together in a way that many other models can't. Another aspect that came out when we were doing, um, we did the utilizing AI as a podcast for years. Uh, one of the interesting facts that was brought up by one of our guests was, um, AI is not subject to the biases that humans bring when doing analytics.

Essentially. Um, you know, a human might say what you said about Tampa, right? No hurricanes hit Tampa, no hurricane's gonna hit Tampa.

And AI is gonna look at that with a more, um, analytical eye. They're not gonna say, Hey, nothing ever hit Tampa, or they're not gonna, you know, have gamblers' fallacy or, you know, any of these other things where they're like, oh, well, you know, an ai, a hurricane just hit this place so there's no chance that another hurricane hits it next week. That could happen.

It depends on the data. And so that's the pro side. On the con side, I do worry that AI is a little bit driving with the rear view mirror.

You know what I mean? It, it, it essentially, um, doesn't have the kind of intuition and, um, and, and, and prediction that some of these sort of human made models have. And so I could see that AI would do better, but I also think that there's a place for humans and a place for conventional weather models as well to sort of offset that.

And then finally, I'll say, absolutely. I mean, this is the definition of climate change. Say what you want.

But, but, but, uh, having more larger, more damaging hurricanes rising, I mean, that's climate, right? Uh, Bonnie, am I wrong about my definition? Uh, yeah.

Uh, well over time, yes. Absolutely. I'm, I'm a big believer in it.

You know, Stephen, you could make that same argument about AI in doctors, right? Once, gonna do a better job of diagnosing and, you know, recommending, uh, treatment. A doctor has the intuition of especially an experienced doctor of a lifetime of treating humans.

The AI tends to look at it very cut and dry. Um, but look, this, this is, this is an issue that's gonna get worse, right? We have ice, huge icebergs, cleaving off Antarctica, excuse me, cleaving off Antarctica that are going to melt.

What effect is this gonna have on, on this whole system? We had a double a Nina this year, which kind of helped us because a lot of the storms formed earlier, further north and wound up staying in the Atlantic. Um, but we need all the help we can get.

So if AI can help us with this full speed ahead. Anyway, let's take a break here on Text Trunk tv. We're gonna come back and, and, and we're gonna keep on this climate, climate Mm-Hmm.

Kinda, uh, and sustainability in green theme as we look at data center heated greenhouses. You're watching Textron Ag. I'm Bonnie Schneider, sustainability contributor to the Techron Group.

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Welcome back to the Techron gang. Well, you know, we all are aware that data centers emit excess heat and it, it can be a problem, but what if that heat is put to good use? I decided to investigate.

And what we found was that in certain parts of the world, like in Europe, there're actually implementing excess data center heat to heat greenhouses. So it's really productive. You're getting fresh vegetables as a result.

Let's take a closer look at this process, and also when we come back, I'm gonna talk a little bit about some of the challenges it faces. Hi everyone, I'm Bonnie Schneider with your Ecotech Analyst Insights data centers generate extreme excess heat, so why not put it to good use? That's the exciting solution underway for select greenhouses.

Leverage data center heat to grow fresh vegetables, plants, and even flowers. It's an effective way to boost energy efficiency, support sustainable agriculture, and raise urban food security. This clever concept is already taking root in the Netherlands where growing season is limited due to cooler temperatures.

A company called Block Heating uses waste heat from data centers to warm adjacent greenhouses the results fresh tomatoes and bell peppers year round. But before you go ahead and plant your own data center garden, keep in mind this approach does face challenges. Cost being the primary dissuaded as infrastructure is expensive.

Plus the setup requires close proximity between data centers and greenhouses to overcome these hurdles. Modular greenhouse designs are being tested to fit different urban environments. And tech and agriculture companies are partnering to cut costs, making these projects more practical.

Data center greenhouses are in their early stages, but they show great potential by repurposing waste heat, they could create valuable resources to help build more sustainable resilient communities. It sounds like a terrific idea. Imagine all the vegetables that you can get from this and putting two industries together that may not think of each other initially.

So there's a lot of great partnership that could be coming out of this, but there are also hindrances, and one of them is cost. Um, making sure that, that the co it's cost effective and location, there has to be the right climate and the right place, and where the data center's located, where the greenhouse is, is located. So a lot of other factors have to come together to make this successful.

But I can tell you that experiments and pilots like this are happening all over the world. So I think we're gonna see more of this. I'll tell you, I'm reminded, I, I was in, uh, Iceland, I guess it was right before Covid, so maybe 2019.

And we went for dinner. It was a tech conference surprise. We went for dinner, um, in a greenhouse.

This is a greenhouse. This single greenhouse, I believe it was like 5,000 meters big, a big greenhouse. It produced all of the tomatoes year round for the, that fed.

You know, the entire island of, of the entire island of Iceland is tomato independent. They import no tomatoes. They also use no oil, coal, or anything else to power this greenhouse that produces, I forget, a thousand pounds of tomatoes a day or something like that.

The entire greenhouse is geothermal, basically right outside the greenhouse. They dug a hole in the ground, tapped into a geothermal vet spins a turbine. Steam turbine produces the electricity to temperature control the greenhouse, control the grow lights in the greenhouse, um, melt the ice for water for the greenhouse from the glacier, and do everything else.

And they cook a great dinner there. Every dish, of course, had tomatoes as part part of, of the dish. I just read another article this weekend in a similar vein where they're now tapping into the actual magma cone of a, a volcano, which will put this thing on steroids.

It'll power it, it it'll power the entire island. Now, Iceland was the poorest country in Europe and had no oil or, or petrol or coal reserves at all that import everything. Their energy independent because of geothermal energy.

And, you know, the Iceland miracle, it comes and goes. They've had some ups and downs, but overall they've been a very successful economy. I don't think they're full EU members.

They're like partially EU members or something like that. But in any event, this is real. We, we have got to learn to reuse these, in this case, data center key to where, where we need it, right?

It, it's part of the whole efficiency loop, right? And, um, I, I for one say, let's see more of this, right? It's, it, it's the reverse of, you know, building your data center near the waterfall so you get the hydroelectric stuff or you know, near, near your energy source as the nuclear plant or what have you.

But this is, this is a great, I think it's a great thing. Well, it's certainly a cool idea. Um, I do have to point out that unfortunately, block heating of the Netherlands went bankrupt, um, because they were unable to actually bring the IT aspect of this, uh, to productivity.

Um, and, but I think that had more to do with, uh, what Bonnie was saying about location because, um, you know, part of the, the block heating concept was that they were going to place these containerized data centers next to or in, among, uh, greenhouses. And of course, uh, next to greenhouses is maybe not the ideal place for cloud computing. Um, I wonder if maybe it would've been more successful if they had in fact placed the greenhouses, um, or an indoor greenhouse next to an existing data center instead, uh, since of course, um, what what really hurt them was the data center aspect of the business, not the greenhouse aspect of the business.

But the other thing I I'm interested in here is, is, um, we've lately been hearing that, uh, in the eu and, and as well in the, in the US there's been a push for, uh, data centers to account for the heat production of their, um, of their compute activities and, and restrict the heat production. In fact, uh, I think that is Bonnie, maybe there, you, you wrote about this. There is a, a move to, uh, restrict the amount of waste heat that can be exhausted from data centers in in Europe.

I, I think this thing may have a a, a second life, which is I think probably why you're bringing it up at this point, because we need to find out what, we need to figure out what to do with all this waste heat, because most of the energy doesn't go toward AIing data. Most of the energy comes out as heat. And, and what are we gonna do with this Heat?

There's yeah, and there's pilot projects in the us They're, they're doing it in Paris and they're even looking at it on a smaller scale for urban environments where, where that's key. I mean, one of the, the drivers in this isn't just the data center heat and repurposing it, but it's also finding new ways to grow food and, and solve that. And that's why the un, um, overall is, is looking at this, uh, because it's hitting two of their goals at once, which is, uh, being more energy efficient and helping the world food Supply's a double, double win there.

Yeah, it's great stuff. Alright, John, did you have something? Oh, I was just gonna say one really quickly is that out here I've noticed, I actually met a, a friend of mine in Seattle when I was out at a conference and we were talking about the requirements of energy, uh, through ai, and she made a really good point.

Uh, there's kind of a growing backlash against the folks at NVIDIA and other companies about how, how impact they're having on the environments and the impact that what they require in terms of energy use and how some companies like Google, Amazon, Microsoft looking increasing more to nuclear. So I, it it's, it's, it's refreshing to see some sort of positive byproducts of the data centers, but it, it's becoming more and more of a topic out here in terms of these companies are gonna be consuming gobble of a lot of energy. And this what's gonna be the long-term impact of all this.

This is true. This is true. All right.

On that note, I think we're gonna call, uh, we're gonna pull the plug. How's that for a little segue, huh? We're gonna pull the plug on this version of the Textron Gang.

We will be back tomorrow with another great gang, but we, as I always remind you, we have a full day of Textron tv immediately following the gang. So stay tuned for that. Watch it.

If you're watching this on Wednesday, if you're watching this on demand, hey, thank, or on YouTube or on Textron tv, wherever. Thanks for joining in, Steve and John. Mike, thanks for joining us.

Bonnie is always great to have you here. Until next time, go Yankees. You've just watched Textron gang.