Techstrong TV June 20, 2025

Hey everyone. Stablecoin the latest crypto craze here on Textron Gang. Happy Friday, man.

Do I love saying Happy Friday. Uh, happy Friday everyone. Welcome to our Friday edition of Textron Gang.

Uh, I'm Alan Shimmel of Textron. We've got a great lineup. We're gonna talk about crypto and AI anxiety and maybe a, a report from the field that reinforce.

But, um, let me introduce you to our gang members who are gonna be talking to us today. We'll start, I guess, out west. And we're gonna go northwest here to my friend Fred Wilmont of tech team.

Hey Fred, how are you? Great, brother. How you doing?

It's good. It's good to see you, my friend. Can.

Did I tell you it's been a pleasure having you. I, on this show, we haven't talked enough in too long and it's great to see you as often now, so Me too. Thank you.

Me too. A hundred percent. Staying out west.

We have our Silicon Valley dynamic duo of, uh, John Schwartz and Lisa Martin. We're gonna go with Lisa first. Hi, Lisa.

It's great to see you. I've, I haven't seen you on here in maybe a week or two, so it's so fantastic. I know.

It's great to see you too, Alan. I actually went to Spain to Malaga last week for Futurum to speak on a panel on modern marketing, so that's why I was out last week. It was, and, and to your point about coming home from Italy, it's always hard to leave Europe.

It's such a fantastic place, Especially this time of year. Absolutely. But it we're gr glad to have you back, John.

You haven't really, uh, gone anywhere exotic, huh? I used to live in London for a while. Um, and uh, that was a long time ago though.

My daughter. Oh, I was f*****g recently. I mean, other than maybe going to a Giants game.

Oh, you don't, oh, you don't think Las Vegas is, is, uh, yeah. Um, that's next week. It's exotic.

Yeah, I'm excited that Saturday I'm gonna go see the Giants in endeavors to see where, where they're going. Um, that should be interesting how that plays out. But yeah, next week at Las Vegas and HPE can't wait.

Oh, Okay. So you're headed to the, the, the, the, uh, city over there. Okay.

And then, uh, moving on from the West coast. We'll stop, we'll take a quick stop high in the Rocky Mountains. He, he's not high head.

It's pretty early in the morning. Mitch Ashley Fu analyst. Hey Mitch.

It is Colorado. Don't count that out, but good To be here. Good to be here.

It's good to have you on. I know you've been traveling a bit. And then finally still waiting for his Yankees to win a game, though.

They did score a run at two last night and then blow it on some airs. Mike Ard, I did go to an exotic place this week with Mitch. So, you know, Philadelphia gotta tell you from a New York perspective, it's exotic.

It was Tropical, rainy, you know, a Adrian. Alright. Um, yeah, they did play some rocky music.

So guys, let's jump into it. Mike. You know, Congress is, uh, taking up some legislation maybe on crypto, and of course our president is a big fan of it 'cause he's lining his pockets with it.

Um, but now it looks like the big retailers are saying, Hey, maybe there's something here. What, what's this story about? Yeah, I think this is gonna happen and now has some bipartisan support in Congress.

So it looks like that genius act is gonna pass. And some retailers like Walmart and folks and Amazon are trying to figure out, well, can I create a stable coin that is pegged to some sort of more stable currency? And that might help them with their, um, fees for transactions and all kinds of things that they might wind up doing with that.

'cause you probably use it for international trade, but Lisa, what's going on here? Is every company in the world gonna have a stable coin? It's so interesting.

This was a really fun one to dig into guys because Mike, you mentioned the Genius Act that would create basically this legal framework for stable coin use in the us And with that said, skeptic, there's obviously, there's always pros and cons and there's skeptics of stable coins. When, uh, is there potential security risks here? Is there regulatory uncertainty?

But basically a stable coin is a type of cryptocurrency that is aligned or pegged to a government issued currency. Either the dollar could be gold. There's some interesting use cases here that I think Walmart, Amazon, and other retailers are exploring payments, uh, as well as trading investing.

You mentioned international. My cross-border payments, um, even access to like financial services are supposed to be the stablecoin less volatile than tokens, like the traditional Bitcoin, Ethereum. And what we're seeing is retailers like Amazon, big ones, obviously Walmart, really strongly considering stablecoin as a way to reduce their dependence on credit card networks like Visa, MasterCard, there's so many billions in in interchange fees on prepaid and debit cards.

I think the most recent number was 32 billion in the year 2021, which is the most recent data. So it's looking like what retailers are wanting to do is, is really stable coins as part of a broader shift away from the costly and this legacy system. So it's an interesting time, but of course the security, um, factor is high there.

Especially as we look at the high volumes of card transactions and the cash that the Walmarts and the Amazons handle. Will this allow them to save billions of dollars in fees and really provide that security that the consumers are gonna demand You? You know, it's interesting.

I I've been involved in the, uh, payment card industry for a number of years. Um, I have a lot of friends who have been in that industry. And then, you know, when the whole PCI thing came out, I was doing some, you know, PCI work around it, so I'm very familiar.

Look, every merchant hates the fees. And what you don't realize, it's a great business. 'cause not only do they charge fees of the merchant, but they charge on the consumer's end too, right?

Your bank pays, so you got a credit card from Chase or Citi or Wells, they pay a fee on that end of it. So the, the credit card and payment processes make money on both sides of the street. It's a crazy business.

I'm almost amazed that the payment card industry lobby is letting this thing have any oxygen at all. Right? Because, you know, between Amex and Visa and MasterCard Discover, which is now part of Capital One was diners, um, you know, there's, those are some pretty big honchos that you're trying to cut out of the trial here.

And my bet is sooner or later they're too smart to be cut out of this trial. Sooner or later they'll find a boy back into the thow and to feed. That's what I'm thinking, Alan is what is, what is the credit card company's angle to get in on this, right?

They're not gonna let it swing by and suddenly all their, they're losing their feet. That's not gonna happen. It's gonna be a vicious fight for that's those dollars.

Mm-hmm. Would they issue their own stable coin? I mean, what the hell?

Amex can have its own stable coin. Well, you know, they're, they're ex Expedia and airlines are looking into stable coin. I think even with the, the banks are considered considering joining a merchant led consortium.

Um, so yeah, they're all gonna look for an angle. I mean, and with Amazon's interest in participation, I wonder what Apple and eventually Google and others do. So what is stablecoin peg to that makes it stable gold?

You can, you can pick a currency, you can pick a US currency or any other currency for that matter, I think. And so basically it, its value isn't tied just to the belief system in that like a, you know what you see a digital Current speculative, like his back Bitcoin and stuff. Let me ask you another, it's got treasury backing, right?

Is that right? Uh, yes. Yes.

It's, uh, backed by cash reserves or short term US treasuries. So it makes it less fault. So then it would be backed by the, it's, its Basically close, it's a close equivalent to cash and it's designed to maintain a fixed value essentially.

That's the, that's the theory. So It's not the speculative investment kind of thing. You we're not gonna have stable coin mining, are we?

I don't know, but can we have Walmart money? I mean, am I gonna get like, you know, instead of dollars I'm gonna get Walmart greenbacks. Is that how this is gonna, So I I get Walmart money, you know, so if you are a Amex platinum holder, you get like a free Walmart plus membership, which is like their version of Prime and, and you get, you get like a certain amount of Walmart dollars you could spend with it.

Not a lot, don't get me wrong, you know, but take stuff from Walmart's cheap. Um, so I'm might throw one thing out here, Alan. You, you know, there's some kind of a arbitrage tra you know, this is like a long distance carrier.

How many minutes did you use of your service versus that service and, and balancing that, you know, there's some kind of a arbitrage or, or or bridging network that the credit cards are gonna be because not everything's gonna shift to stablecoin. They're gonna support stablecoin on their platform, on their cards. There'll be fees involved for, you know, translating between stablecoin and whatever your credit card balance or, you know, cash.

There's money in there to be made. I think for the credit card companies, There's, there's two things here that I think are important to think as positives though. One, if you look at, you know, the credit card, uh, challenge your banking challenge for things like mass compromise and knowing where and when your card was compromised and what effects that has, account takeovers, uh, point of sale and point of compromise activities, all of that becomes a much, uh, faster analysis problem.

All of that becomes something that is owned by whomever owns the stable coin. So you really democratize a lot of that. Small businesses that want to get in the game of doing transaction, don't have to pay Visa member bank, you know, costs just to take transactions, right?

So, you know, there's a lot of, where there's probably still gonna be a ton of fees, right? Which fees are you willing to pay? Which ones mitigate your risk?

There's a lot of value to having something in between what my mom wants to invest in, in crypto and something stable you could actually operate. And I think there's a, there's a big plus here to be had possibly for consumers. And Walmart's gonna save a bunch of money in fees and give Alan more money And who's gonna back up the, when you're, when something, you know, end vendor merchant doesn't deliver and you want to go back and say, don't pay that, right?

Like you do with the credit card or with PayPal. So there's a lot of things to be worked out. I think if they have that, then I think there'll be more adoption by the consumers.

At least They have said that the transactions are supposed to be much faster. And obviously everyone demands speed these days. So potentially could clear instantly, which would be an advantage for the consumer, could be an advantage for companies that have really big global supply chains or or large amount of transactions.

So that speed could be a factor, a good factor, Right. Fred, do you think we'll see stable coin jacking the way we see crypto jacking and we'll see all these kind of fake Walmart stable coins out there that somebody hacked together by, you know, hacking into a cloud service somewhere and using some illicit CPUs and GPUs to create some fake money? Oh, for sure.

Uh, but I think that, uh, that problem's infinitely more trackable than the problem we have today. So, you know, uh, being able to find out where people are doing which particular things, which banks and which branches are, you know, handling the crypto behind it, there's a lot more traceability here than there is in, you know, just plain cash. So there's a lot of value I think in being able to do that.

And like everything, there will be a whole suite of new interesting, uh, phenomenon for different ways to defraud. But, um, you know, I think that's early days in any anything is gonna be that, like, like Al mentioned, the payment industry right, has had a lot of that. A 6% gain on mass compromise is billions of dollars when, you know, an organization can start to deflate that.

So you can see a bunch of that, but I think the, the interesting part will be how rapid that's going to change versus what we have today. So it's maybe more like fight club taking on some real proportions here. I don't know about Equifax and the rest of the players there, but it'll be interesting to see what happens.

Let me, let me introduce some geopolitics into this. I was waiting for that. No, no.

I'm not going where you may think. No, no, I was, I was gonna bring it up too, but Well, you Bring yours up. So my, my thought though is it's something, Mike, you said, well, you could just plug anything in the backend as the, you know, as the, as what we're gonna base it on.

Is this a way for the world to get off the dollar? Do we lose, you know, because many economists, many, you know, financial people will tell you that the United States' biggest asset today is that we're in a dollar based e economic world. And if, if, if coins like this become the defacto standard and the back end of what they're pegged to is, is frankly portable, do, do we lose our advantage there?

And is that a, is that really something that we should call a genius act? Maybe. I think, you know, you're gonna see a lot of countries anchor these things to Theon, right?

To the what? To the Chinese dollar to The one, or, or, or, yeah, maybe. Right?

So I think, you know, so I think they're all gonna break that. Do you think someday, you know, somebody's gonna like get a ransomware demand for, you know, 1 million Walmart stable coins? Yes.

That's inevitable. That's a distinct possibility. Yeah.

Lifetime. Of Just what you need. Just what you need.

John, where were you going with this? Oh, I was gonna go down on a different path. This is much better.

I I won't, I was just wondering when we're gonna see, uh, the Trump organization announce their stable coin. Well, They have their coin. They could just say it's a stable coin.

'cause he's a stable genius. Mm-hmm. Right.

It will be, it will be tied to the valuation of Mar-a-Lago though, right? Priceless. Priceless.

Yeah. Yeah. Um, spoken through.

But let's, let's, let's not go down that bridge of the river. Um, look, you know, it, a lot of people have predicted something like this, a long time are coming, right? And, um, and the other thing is, you know, who knows?

Is Congress really going to, yes, there's some bipartisan support for it, but by the time the lobbyists get done picking at the carcass here, is it gonna be what we think it's going to be? That that would be my biggest take on it, right? Or will it be a shell?

Mm-hmm. And anything else? All right.

If not, let's take a break here on Textron Gang, we're gonna come back and talk about AI anxiety. That's not the new movie by Mel Brooks or anything. You're watching Textron Gang.

All right, folks, we're back in. Yes, there's a lot of AI anxiety suddenly in the world. Microsoft is now reportedly gonna fire a bunch of salespeople and replace them with ai.

Uh, the CEO of Amazon put out a memo saying that the company will definitely be smaller in the age of ai. And every time you turn around lately, John, somebody's laying somebody off and blaming it on ai. ai, where it seems like we're evenly split as to whether or not we're afraid of AI or we think AI might be a good thing.

So, Right? Yeah, there was a national poll that NBC News put out Wednesday, and they were, they were asking a bunch of questions, but two of the questions that stuck out that were tech related were AI related questions. And what they found was this profound split in the way Americans look at ai.

Either they are embracing it or they are not touching it at all. And I think what is in play, and I think what's been in play, not just with this poll, but just in general, is this familiarity. So people are much more familiar with this new technology than they have been with previous waves.

And I think it breeds, uh, equal amounts of fear and fascination. Um, like, like the companies these, these people work for, they have strong feelings and attitudes about ai, and the more they find out about it, the more anxious they become. And I, and I, it'll be interesting to see how this plays out.

I mean, we see this at the corporate level now, we're seeing it, um, at the rank and file level. And, um, I I, what I think is eventually gonna happen is people are gonna learn to live with it. They're gonna learn it's not as scary as they think it is.

Um, like previous waves of technology, there's always this fear of change, especially among older people like me. But once somebody is exposed to it, then they become huge proponents of it. So I think maybe that's how it plays out.

But the other thing that's going on is that we've got the, we've got a lot of attention, as Mike points out to tech companies that are looking to be more pro productive and looking for more productivity. So they're gonna get rid of their employees. We're seeing it among media companies like Business Insider.

Even the New York Times is, is using AI much more thoroughly than than than we previously knew. According to the Washington Post. Uh, we're, we're moving in that direction.

And again, change foment fear. And I think it's just gonna accelerate like everything has with ai. Um, there, there was a book that just came out called Empire of ai.

It's a, basically about Sam Altman and Open ai. It's written by, uh, former Wall Street Journal reporter who now works, I believe, at the Atlantic. She's, um, it's a really interesting read.

It got a lot of attention. And basically, I'll just throw, this is something I wanna throw out to y'all. Her, the author's point is that these AI companies, the dominant ones are, are going to be the new empires, and they're gonna be very similar to old empires.

They're gonna chew up a lot of resources. They're gonna affect profoundly the working force, and they're gonna profoundly change our societal norms across so many gamuts, good and bad. So again, this is an understandable reaction to something that is going to, if not rule, our lives have a huge influence in our lives in everything we do.

Lisa, I think there's something wrong in the tone of these things, in these announcements. And part of the thing about AI was it will make people more efficient and we'll be freed up to go do more things that have interesting value. And that's all goodness on the face of it.

And yet it seems like, you know, every time you turn around now, somebody's talking about laying people off because of the eyes. So what are they, you know, it doesn't seem like they're actually doing the uplift part as much as they're just focusing on reducing costs and bottom line, pushing this through the bottom line, rather than thinking about a top line. Yeah, I agree with you, Mike, on that.

When Andy Jassy came out the other day, CEO of Amazon, and said that there will be less jobs in the age of ai, I thought, you know, the message that came out just a few months ago from the World Economic Forum, uh, state of jobs report for 2025, talked about the, and I'm, and I'm not gonna remember the actual million numbers and millions, but I, I think the net loss plus net gain of jobs in the next five years was projected to be 78 million new jobs created. And that narrative isn't getting out there. Um, I think Amazon could have done it could have, from your your point on tone, Mike, I think they could have done a better job of that.

I'm, I've always been glass half full when it comes to ai. I get to see a lot of the positives that it does, but also when I do iHeartRadio, I get to talk to the consumer audience. There's a lot of fear out there.

So this poll did not surprise me at all. For example, it's, it, it varies by industry. I've got family members that are in the entertainment industry and they're trying to break into Hollywood, and they're terrified of ai.

Obviously there were huge issues and strikes and things in the last couple of years because of that. But I think the messaging needs to be clear on let's identify where the cons are in the negatives and what types of jobs are already being replaced versus what the opportunities are that it's going to give to job seekers regardless of industry. I think that message is just not clear.

And to jaunt, to your point, and to the polls point, people are either all in on AI or completely against it, but doesn't seem to be a middle ground yet. I don't know if we're gonna get there anytime soon, but, um, it's, I I, but then I talk to people in different age groups, like my mom's best friend who's almost 80, who is a huge fan of chat, GPT uses it for inspiration on different things that she does in her life. And I thought that was a really cool, uh, example of somebody that in a different generation that could be scared of it, retired.

So not worried about it taking over jobs, but she's some value in what it can deliver for her life. You know, the, the word board to use Lisa that really stood out to me in this perfect word is messaging. The messaging's been so bad from the tech industry.

It, and it's, it's, it's, uh, as, as Mike mentioned, it's Amazon, it's Microsoft, it's, I think meta has made it clear that people are gonna be replaced by ai. I mean, it's just, it just, throughout the industry, there's this almost gleeful, um, anticipation of, of what AI can do in place of human beings. And I don't think that is the intent, but that is the, the takeaway that we're getting from a lot of these companies.

Even, I mean, anthropic of, of course, they're going to, they're gonna build up the fear as they try to raise money. But Dario, it's the CEO there has talked famously about losing half the white collar jobs because of AI related technology within five years. So they gotta do a better job.

And, and, you know, as long, as long as we keep hearing Nvidia and Salesforce and ServiceNow and everyone else talking about these digital workforces as if humans are just a small part of the equation, we're gonna just keep getting this reaction. I think the other part of it too is that it's, it's in a, an environment of constant opinionating about sort of the dystopian part of ai. And I don't mean, you know, in, in a true sci-fi sense, but just every job's going away, all these knowledge workers are going away, or the entry levels are going away, whatever statements are made.

And, and it's, it's by not by one person, it's by, you know, a lot of, a lot of people including leaders, company leaders as well. And I think what, what the, what the problem with those statements is, well, some of that may be true. Um, it doesn't help just to say, Hey, all this kind of jobs are going away, you know, paralegals are going away, so what should people do?

What, what do people do to prepare them? So that's the other part of the conversation we have to have is, okay, so you know what, we may not have paralegals as we know it, or pick your, pick your job. Maybe we'll still have plumbers, right?

But we, we may not have paralegals. So what, what does the legal profession look like and how do you prepare yourself to evolve and grow and shift and maybe make some substantial change if your, your kind of role does change or is eliminated, but new things come about, You know, that that's, so one of the frustrating things I encounter when I talk to these companies, uh, especially the tech companies about AI and its impact on jobs, they will say to me, invariably, well, it's gonna create new types of industries. It's not gonna just eliminate type X job, but it will bring in type Y.

And I'll say, well, give me an example. Give me a specific example in the vertical market, say the legal profession and how that might play out. And I get nothing but vague responses.

Um, 'cause and, and I sense in, in fairness to the, the people who are not answering, maybe they, either they don't know or they think it will evolve organically within the job or within the industries. Certainly. I mean, I, I believe John, there'll be jobs in companies.

We can't imagine. I mean, there will be things created that, that are now, now possible that are, will be created out of the opportunity. But other things will be, I don't know if wanna say evolutionary, it's kind of evolutionary and revolutionary at the same time.

In, in my world, I think about the software development environment and, you know, developers moving from coders to more orchestrators and communicators and using tools that more look like something like a StarCraft resource management, you know, game than, than it is a line of code editor. And same thing for developers or maybe, uh, workflow engineers, whatever it might be. But I think that's what you have to kind of paint for people as this, this is the skills that are transforming when you have those AI capabilities.

So first of all, invest in ai, your own skills of using ai, because you probably won't make the transition without having some of those to begin with. And if we could, oh, sorry. If we go back to the messaging for a second, what's ironic to me is that I get to talk to CMOs regularly and see, we're talking CMOs of CrowdStrike, Dynatrace, snowflake in ine finite, T Trellis, you name it.

All of them leaning heavily into Gen AI and agentic ai. They're seeing a lot of value. They're already seeing ROI.

So the fact that the messaging is inconsistent is just ironic to me that the CEOs like an Andy Jassy would phrase what he said in the way that he said it just Wednesday of this week on the Today Show, they were talking about ai, and I was actually, so I, I tuned in, I was very in curious as to what they were going to say about it. Were they going to be negative? Were they going to be neutral or positive?

And it ended up being fairly neutral, I would say, which I thought was, was a good thing in terms of identifying there are going to be jobs that will be replaced, but there's also gonna be a lot of opportunities and jobs that we can't even imagine yet. And that that message, that tonality is just not out there consistently. And I, and I struggle with that.

'cause I, I see it, My b******t meters off the chart on all this. And, and here's where it is. All these companies hired immense numbers of people over the years.

And so part of this, I think is them saying, well, we're gonna shrink the workforce juice the stock, and we're gonna attribute it to ai. But I don't think that they're anywhere nearly as far along with AI as they think. And maybe they're in anticipating some capabilities.

That's a hundred, that's a hundred percent correct, Mike. I was gonna say the same thing yet. So here's where we are today.

Today, AI is not necessarily replacing jobs. AI is augmenting people, right? It's not replacing them.

That's not to say it won't replace them at some point in the future, and maybe sooner than we think. But for Microsoft who's already done one round of layoffs based on AI and is announcing or expecting to do another pretty big round, uh, based on AI now saying that AI's replacing those people, that's covering up for some drunken hiring spree during COVID, Right? Yes.

They're all bloated and over they over the overhired. Yep. Yes.

And they're still cutting that. Yep. Now secondly though, you know, we, we did a story earlier this week where New York State is now tracking how many jobs are lost to ai.

And California is gonna take another crack at regulating ai. And you know, everyone is gonna try to put this genie back in the bottle and and try to figure, you know, how to control it. That train's left the station, right?

It's out of the box. AI is gonna do it. Ai I said this, remember when it first came out, the hundred scientists who said it's a threat to humanity and, and all of these things, the trains left the station, this thing's on is already on its path.

You could, you know, as Lee I Koka says, lead follow or get out of the way. And, and so I think, Mitchell, your advice is dead on. Go, go, go skill up, upskill yourself on AI, because you know what, when I went to school, they didn't have any web designers just saying, and, uh, I don't think we're gonna have web designers necessarily going forward.

I think AI will design your web. But, but for a brief moment in time, it was a hot little job. But let's, but let's look down the road a little bit.

And if New York State wakes up one morning and finds that the unemployment rate is off the charts because, and they're having to pay all these folks benefits, they're gonna come back to the tech companies and say, what did you do here? And how much are you gonna kick in to help fund this? Well, keep in mind those numbers are self-reported by how many jobs are laid off.

So are you gonna be over or under? I'm reporting that as a company. So, so imagine imagine that there's a, take this a little, little, a little bit differently.

And so imagine that there is a 70, 80 year olds, 90 year olds, don't have a lot of contact with their family, don't have a lot of reasons to get up in the morning, don't have a lot of ways to communicate fairly isolated from the world. Imagine there's 19 year olds who are stuck in college right now, highest suicide rate in the United States, 19 year olds. And imagine that there's organizations that produce the ability for adoption of things that we don't fully understand yet, your personal confidant, your personal collaborator, that is a, an ai uh, interaction that lives on a device in your home with you, right?

The commercial adoption of this isn't, you know, what's going to lead the adoption of the, of the industry. Those people have already proven that, that you're welcome to save about 45 to 50% of fee of people that have had this experience from committing suicide. And so some of the things to think about here are, hey, look, uh, the adoption isn't the fear of ai.

It's the fear of humanity. It's the fear of establishing a new, you know, leadership and, and control over society that no one has a input into. But when you look at some of the abilities and the things that are brought to light here, it's not, it, aside from not being doom and gloom, there's an example of a trade craft here that hasn't been built yet.

So your personal, you don't need a psychiatrist with, you know, 20 years of such and such. You have the ability to have somebody that knows you in the context of all your conversations to interact with you almost like a friend. That's a job that doesn't exist today.

And those are the types of opportunities that are available. But, you know, to Lisa's point and shimmy you too, these aren't clearly illustrated yet 'cause they don't exist yet. And I'm not sure we spent enough time thinking about, about that translation of the turn down in the economy, people doing, uh, something about playing offs for AI and what these new opportunities might be.

Yep. I mean, look what Chris Blas is doing with his Lumina partner as he calls her. I don't know if her's the right word, the red pron now.

But anyway, uh, it's pretty cool stuff and I think we're gonna see more of that. We'll see more of it anyway, certainly a lot going on and I'm sure we're gonna discuss this again. But for now, let's take a quick break here on the gang and we're gonna come back and AWS's big sec cyber show security show, reinforce not reinvent.

Um, was this week, Mitch, I think you were on the scene. And, and let's, let's talk some security. Discover Textron group, the epicenter of tech innovation.

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Hey folks, we're back, and Mitch and I were both in Philadelphia at the AWS Reinforced conference and there's been some criticism level that AWS and all the cloud service providers for may hiding a little bit too much behind shared responsibility, but it looks like to me at least that AWS stepped up its game considerably and it's making it easier to both see where the vulnerabilities are, what, how critical they are, and in some cases proactively going out to prevent them. So Mitch, you were there with me. What was your take on what was going on here?

Well, I think you, you coined the term, right? I think in one of your articles was it was a bevy of announcements. And, and of course AWS has, has never been known for underwhelming us with a number of announcements.

There's always a lot of them. Uh, probably the biggest one, frankly was, uh, Amy Herzog who came out as the new CISO for AWS. Um, she has been with a WSI think about a maybe couple of years and comes out of Mitre and VMware and some other experiences.

Um, Chris bets, the former CISO left so somewhat unexpectedly on his terms, he's going to start something new, but we don't know what that is yet. And Amy had three weeks to prepare to give the keynote to give a two and a half hour keynote. It was pretty remarkable.

She did a fantastic job and I think will be a great CSO four. There were a lot of announcements and, and some of them, like you said, Mike, there were kind of filling in the gaps, but more shoring up, pulling information together. They announced, um, a revamped AWS security hub about identifying vulnerabilities.

They did A-A-A-W-A-W-S Shield service, which is more of a dashboard around configuration mistakes and things that are happening with, uh, they can identify with Amazon queue. Um, there's a, a network firewall, uh, to be able to, you'll appreciate this, Alan, to do more automatic responses to traffic. Sounds like an I-D-S-I-P-S argument again, having PTSD on that one.

Um, so there are a number of things around, around kind of network security, cloud security, configuration security. There was an announcement with CrowdStrike, with Falcon being able to kind of integrate better with that, uh, service offer by Falcon and AWS or more endpoint security. Um, you know, Fernando Mon, uh, Montenegro, the, uh, lead of, uh, security for future.

Uh, it did a nice analysis of, it kind of called it sort of undifferentiated heavy lifting. Um, meaning there's, there's other areas where the cloud provider AWS can step in and help customers instead of them having to assemble all the tools into the monitoring management. I think where this is all going is more automation, not just at the firewall level, but across the board.

The area that that I was also particularly interested in, um, were things around their, uh, security incident, uh, response process. But also inspector is getting more into the, uh, scanning a code when it's pulled, as well as when you, when you push updates to the repository, uh, software composition analysis, it's, it's getting to into other people's business as well. But they're also doing things like integrating with GitHub and GitLab and the DevOps space.

So it isn't a total goal at it alone. So there's some some key partnering things that I think were announced there. Anyway, I, I could take 20 minutes and rattle off all the announcements that I don't think they're all worthy of that level of conversation, but I think those are the kinds of trends and things that I saw.

Um, mi Mike, what were your, what were your thoughts? Did I miss some key things? Yeah, there were two things that kinda leapt out at me.

One is they did a really awesome demo of Amazon Q developer being used to find vulnerabilities and then create the patch and test the patch and putting that in front of developers. So it was kind of like the ultimate shift left de demo for DevSecOps using AI tools. And the second thing is, they talked about how they are now, um, have a team that's investigating DDoS attacks and that goes and finds the networks where the OOP are coming through and then actually calls those people and says, Hey, you know, your system has been compromised.

And if they don't respond, then they go down the next level and they go after their dns. And if they get, don't get that, then they go down to the local telecom company and say, Hey, you know, you gotta cut these guys off. And so they were kind of suggesting that was gonna become a bigger model for them and they were gonna apply this to other things besides DDoS and it's felt like, you know, finally somebody was getting aggressive about this stuff.

So those are the two things that leaped out at me. You know, Fred, I got a question for you. As the CEO of a cyber company, you, you hear about what Amazon is doing to do a better job with cloud security.

Do you consider that friend or foe? Is that competition? Is that someone you work with?

Can they do a better job? I mean, typically Amazon rolls out things that are 80 20, they're 80% of what a private solution is at 20% of the price. And for some people that's enough.

How, how do you view you listening to this report, Fred? I think it's great. I don't fear, uh, anything that Amazon is doing.

I would say it's long overdue and, you know, as you said, right, it's, it's typically rollout a capability and, you know, sort of craft your own, you know, way of utilizing it. The challenge is, and a lot of this stuff sort of rolls up into the cloud security posture management problem space, which, you know, Amazon's getting eaten alive by their direct competitors for this. Similarly to the development lifecycle with, you know, a GitHub that's already doing the vast majority of this.

It's a little bit of, you know, I've gotta meet the market where the market is. And, uh, I like a lot of the ideas that make it easier to, you know, build infrastructure to validate your code is secure, to deploy code successfully and to operate your security controls as a practitioner. So, you know, when you, when you provide services to any of your customers and having the nice, you know, signed paper that says you're SOC two compliant, terrific shared responsibility, no, there's none of that.

So this opportunity allows people that build software, build services for customers to not only do a better job with what they already have, but it empowers folks that don't have a team to do those things to make it more successful for them. So I, I think it's terrific. I think it's long overdue, uh, how valuable it becomes over time, I think is what the market's gonna dictate.

But I'm thrilled to see it. It's, it's, it's about sound Friend. There was also another angle that I'd love to get your opinion on.

'cause while AWS makes its network and security services open enough to people to tweak themselves if they're so inclined, um, they were just suggesting that that was a pointless exercise. 'cause people can't respond fast enough to the attacks that are coming out there, and they might as well just lean on AWS to automate that whole thing end to end for them. And there's not a lot of point because humans can't update the firewalls fast enough, can't detect the attacks fast enough, and the whole thing needs to be automated in real time.

So it was time to move on from network and security operations constructs. That sounds awesome. Uh, heavy eye roll.

Uh, e everybody says that no one does. The problem that we have isn't, uh, the, the, the largest problem that we have isn't whether or not, you know, there is dynamic, uh, asymmetric attacking happening all day long. It does.

That's what happens on the cloud infrastructure in a public cloud provider. But you know, the challenge is that once a thing is compromised, you have 49 minutes for that to be broken out of and to expand laterally and do other things. If we said that, that really is just something that the cloud provider should handle.

And we know that 60% of the vulnerabilities on the kev, the, you know, the exposures and vulnerabilities as for for known exploited vulnerabilities are cybersecurity vendors. What makes a cloud provider any different? So I, I don't buy into that at all.

Uh, but I do believe that having more tools available to make better decisions is, is super important. I'd love to see some of the things they talk about around Kubernetes and, and, you know, container security and things that help influence that. They have services that don't offer that today.

So if you use EKS for example, please like, help me go back to the, you know, to the base images that you provide and make sure that those things are secure from the ground up. So, you know, let's, let's, let's mine the kitchen before we start talking about the front of the house, Sorry, guard duty. Now it supports EKS, but that's about the only thing they said about EKS.

Exactly. You know, there, there was one interesting use case, and this wasn't necessarily talked about as an announcement, um, but as I was going around and talking to different AWS people meeting with some folks, um, something that I wasn't really that familiar with, you know, it was probably rolls right off the tongue with for Fred, but, um, this idea of it, it's called domain, uh, domain generation algorithm. So in other words, it's automation, automated generation domain names that they do on a very short interval, and that's what they used to attack from new domains.

And then over time, you know, the, the cloud providers, others can start to identify that those are actually being used for nefarious per purposes and cutting those off. But then the bad guys are using more generative AI to create more familiar types of, uh, generated names. So it's not less obvious that those are generated through algorithms.

But I, I was talking to some folks about this is a good place where you bring together automation, you bring together machine learning because you have so much data in very short intervals that you can start to identify these more and then implement that into like their DNS firewall into guard duty and, and tools like that. So you can kind of see the combination of technologies, maybe it's a little bit of sausage making, but I found that interesting, like, okay, that that's a real use case where ai, in this case, machine learning is using, helping, being used to combat kind of gen AI generated attacks. The one thing I did continue to feel is there's too many damn skews I can't keep track of all the products and all the things that these things do, and I'm kind of like, can we just make This simpler or be better?

That was a common question in our meetings. Like, so is that a new KU or is that part of an existing one? AI will solve that, don't worry.

We're gonna, we're gonna, we're gonna start tracking SKU reduction caused by ai. Yeah, I think, I think Vermont's signing up for that one. Um, anyway, guys, good way to end our Friday.

Have a great weekend. My gang members, thank you so much for coming on. Thank you for watching us.

We as usual have a full text on TV schedule behind us. We'll be back Monday with a fresh gang show. But until then, on behalf of John, Lisa, Fred, Mitch, Mike, and myself, have a great weekend everyone.

We're outta here. Hey everyone, welcome back here to techron tv. You know, I'm really happy to have my next guest, uh, back with us.

His name is Danny Allen. Danny is the, uh, CTO over at Snyk, and I just found out Danny is an avid boater, in addition to being a crazy hockey player. He's an avid boater.

So we, we just spent way too much time probably talking about boating and, and all of that good stuff when we have work to do. But Danny, captain Danny, we should call you. Welcome back to Techstrong tv.

How are you? I am doing well, Alan. It's always great to talk with you and there's a lot of analogies here, right?

Because when you're out in the water, there's all kinds of chaos and big seas and similar to the tech industry, right? Yeah, it is. Say that again.

There's certainly waves in the tech tech industry that are crashing on here. Um, hey Danny, for people who haven't caught you before on Techstrong tv, give them a kind of sense of, you know, how you wound up here as the CTO at Snyk. Sure.

Well, I've been in the security industry for 25 years and mostly focused on application security testing software because of course most of the vulnerabilities and a lot of the threats that we face today come because of software. And so I started my career way back as a pen tester, but then failed my way to a company called watchfire that did dynamic application security testing, essentially would crawl web applications and look for vulnerabilities. And ever since then, I've been very fascinated in the software security space.

And I had the opportunity about 18 months ago to join a team that I'd worked with before here at snyk, really focused on the mission to secure all of the software that is coming through modern pipelines. And it was exciting and I joined up. Very cool.

And they're lucky to have you, Danny. Most of our audience is familiar with sny, but there might be some folks who aren't, you know, there's a new folks watching this. How would you describe Snyk to them?

Sure. So sny is about a decade old, and the founders of snyk really came in with a mindset of let's shift security left. Because security historically has been always the afterthought.

You bolt it on after you build the infrastructure, right, the application, and you do the testing at the end, and then you're first faced with this Sophie's choice of, you know, do I release the insecure software or do I slow things down and go back and fix it? And so the founders of SNY came in and said, let's take all the security testing, let's build it in at the very beginning of the software as it's being created. And they were really focused on, uh, open source software components and testing those for vulnerabilities.

And over the last decade, what we have done is taken one type of specific security testing, which was, uh, open source security testing and expanded it into static application security testing and IAC infrastructures code testing and container testing and all of these different things. But the, the real focus, Alan, has been on shift, it left so you, that you find the vulnerabilities as early as possible and then focus on remediation. Don't focus on finding issues, focus on remediating the issues and eliminating them early, early on in the cycle.

Fair enough? Absolutely. And, and, and, you know, look, SNY has been a, uh, a pioneer in this whole shift, left DevSecOps, and of course that's led to software supply chain security and the SBOs and, and everything.

And it's part of wrapped up now into platform engineering and, and all of these things. So it it, it's a big piece of it. Now, what I didn't mention, Danny, was AI can't have a tech conversation these days without mentioning ai.

And you knew it was only a matter of time until someone said, Hey, let's take AI into this shift. Left DevSecOps world, um, May 28th, almost a month ago, by the time people see this, um, Snyk launched a whole new platform around it. Tell us.

Yeah, well we were talking about boating and so I liken this to the, the perfect storm in term of a terms of ai because three things have been happening, three storms converging. One is that developers are using AI to write code more than ever. In fact, recent studies have said that, you know, 75, 80% of developers are using these coding assistance, and the result of that is more code faster than ever before.

The second thing that is happening, the second storm, if you will, is that there's a whole new type of software being written that is using ai. And so you have a whole new attack surface. We saw just last month with copilot this echo leaks vulnerability or the, you know, there was the, the lang chain, uh, vulnerability that came just recently.

And so all of these new AI applications also increase the attack surface. And then the third storm that is converging is that attackers are now starting to use AI to create even more sophisticated attacks. And so AI is causing a huge amount of change in the industry at a very, very rapid pace.

And of course, we have the opportunity to build security in from the very beginning. And so just like Snyk kind of flipped DevOps on its head and said, we're gonna do security early in DevOps, we believe at SNY that we have the opportunity to embed security early on as we adopt all of these AI technologies within our organizations. Sure.

Absolutely. Um, now Danny, and don't take it the wrong way, but everybody's announcing an AI strategy, right? What, so two things.

First of all, how real is, is this s sneak AI trust platform? Not that it won't be real or that it's a figment of someone's imagination, but how much of it is aspirational versus available right now? Right.

Well, Yep. Well, let's start with that. Well, I would say two things.

You're absolutely right. A lot of the AI that I hear about is marketing, sh marketing, like everyone's talking about AI because they wanna make themselves relevant. However, what I'll say is that SNY has been using AI specifically in machine learning within our platform for well over five years now.

It's, it's not something new for us. In fact, the way that we could do the analysis as quickly as we could do it was because we were using something known as symbolic regression analysis. It's an ML technique.

The second thing that we added a few years ago actually was also generative AI fixes, because we recognize that you're slowing down developers if you ask them to go figure out how to fix particular issues. So if they have a SQL injection vulnerability, you know, it slows them down to go read about it, figure out what they need to do and implement the fix. And so we actually implemented generative AI fixes within our platform almost two years ago now.

And as part of this AI trust platform, which I'll get to in a moment, we've expanded that. So it's not just doing it within the IDE, we're doing it within the workflows for the developers. And so what I'll say, Alan, is it's not just marketing with us.

We have been doing this for well over five years before AI was cool. Now, the interesting thing for me is not just AI for snyk, which is what I've been talking about, us using ai, but SNY for AI as organizations build these AI native applications. Of course, I talked about this increased attack surface.

And so one of the things that we're doing is, for example, giving organizations the ability to test for things like prompt injection. Again, that that is in our platform today. We track source to sync is, is the data going to an LLM?

Is it coming out of an LLM Or for example, we demoed, we've been doing sbo, OMS for a while, you mentioned that earlier. But what about an AI bomb? Give them the inventory of all the large language models that they're using and all the components used in conjunction.

And so all of these things are very real. And ultimately the purpose is to give our customers confidence, trust in AI as they adopt it within their organization. Absolutely.

Danny, just going over the notes, five new AI powered innovations in this platform. Could we just hit, hit the five? Sure.

So really quickly, AI security, posture management, I just talked about that, that's sneak for ai. So testing for things like prompt injection, giving an inventory of all the AI components. So very real, very tangible for, you know, the, the lead engineers who want to know what's being used where across the organization.

Secondly, sneak assist, it's basically an AI powered chat bot. So as your platform engineers or developers or security engineers have questions, it's powered by our learnings within the LLM so that they can say, what is secrets? How do I solve this particular issue?

And so that is sneak assist, um, is what that is called. The second, uh, or the third one I should say is NY Studio. Now, as developers are adopting copilot and Cursor and windsurf and Code Assist and all these different coding assistance, what we've done is exposed our capabilities via an MCP server that stands for model context protocol so that they can integrate with these coding assistant.

So as it generates code, we will secure that code. And that's called sny Studio. That's the third capability.

The fourth one is sny agent. So as I said before, we have been fixing issues using generative AI now for several years. And we were doing that within the integrated developer environment, the IDE for the developer.

We, but we've expanded that to do it as part of a PR check. So when you're, when you're checking code into GitHub or GitLab or Bitbucket or one of these scms, we will also not only test it, but generate the fix as part of that workflow. And so that is known as sneak agent.

And then the, the fifth one is sneak guard. And so we believe in the long run, Alan having policies and guardrails to prevent issues from being introduced is really the long-term objective. And so for a while we've had the ability, for example, to prevent critical vulnerabilities from being checked into your source control management.

And so it's really taking the guardrails that are needed by the organization and putting them on steroids, powered by AI to make your business smarter about the code and software that you're writing. Excellent. Very cool.

com, but like what's the on-ramp to, to start using this platform? What, you know, what's the path they should take? io.

That is our, our website. And you can sign up actually for a developer account for free. io.

And so our content on how to secure AI powered software, this isn't just traditional software. The content is all free. You can go learn about the top 10 LLM threats, you can learn about API AI security threats.

io is the starting place for most organizations. And like I say, the content to learn about it is free. Very cool.

Danny, you know what, I, I would expect SNY to be a leader in this field because you guys have been a leader, right? For going on, as you said, almost a decade now. So it'll be interesting to see how this plays out was to a certain extent.

The whole AI thing gives, it's like a little bit of throwing the cards up in the air and seeing where they land this time, right? But, um, you know, leaders lead and, and that's, uh, something that I've learned the hard way over the years in, in, in my business career. So looking forward to continuing to hear more about Snyk and what they're doing here with this AI trust platform.

Well, thank you, Alan. It's, it's definitely exciting to be out on the forefront on this. And we don't, uh, our focus is to enable organizations to use ai.

It's a very exciting time. We just want to do it in a way that gives them the trust in that AI as they, you know, increase the productivity and momentum of their respective businesses. Excellent.

Hey, thanks for coming on. Keep us posted. I hope to see you in person soon.

Maybe on the boat down here. We'll see how that goes. But for now, uh, captain Danny Allen, chief Technology Officer at Sneak here on Techstrong tv.

Keep up the great work. Danny gl, see no black ice from hockey today. So that's all good.

Uh, of course, our Florida Panthers are one game away from the cup over here, so people down here in South Florida are excited. But, um, we'll speak to you soon. Alright, thanks Alan.

All right. Danny Allen here on Text Drug tv. We're gonna take a break.

We'll be back with more in a moment. Hey, everyone, it's Alan Shimel. We're back here at Textron Gang.

Great to have you with us. Let me introduce you to our next guest. He's been with us before.

Always a pleasure meet, say hello to Michael Fanning Michael of, of course, is the CISO at Splunk, a Cisco company. Michael, great to have you back. I, I know you're suffering a little from allergies, so we're gonna go easy on you today.

Uh, hey, Alan. Great, thanks. Uh, thanks for having me back.

And yeah, it's, it's allergy season here in the Seattle area, so bear, bear with me please. A little congested today. Yeah, I know it.

It's, no one likes to feel like that. I, I feel for you. Um, Michael, I mentioned you're the CSO and you, you've been CSO at Splunk.

Now, I'm going to guess it has it been two years? So I've been in a deputy role for about three years, and then back in the September timeframe, uh, officially became CSO for the Splunk, be within Cisco. So about almost a year.

I, I think we had you on right after that. You did. You did.

Yeah. It's a good talk. Mm-hmm.

Absolutely. Michael, just to give people a kind of sense of your journey, you, um, as you mentioned, you were deputy CSO for a couple of years, but you've got a kinda long distinguished career in security. Yeah, you know, it, it began about 20 years ago.

I had actually at, at Symantec, and I won't drain, you know, my resume, but I kind of moved out west side unseen into, into Oregon. I, I, I was offered a role at Symantec and just kind of thought at the time, like the security thing might actually be something so moved out. And, and that's where I really started to kind of cut my teeth.

I really, from that was, that was really the beginning of cybersecurity and, and really incident response that my, primarily, my background has been on the incident response side and digital forensics, um, working within security operations centers, leading security operations centers, and having them in reported to me. And I've done that, you know, now in multiple companies. Um, you know, since my time at Symantec leading into where we're at today within Splunk.

So, very cool. You know, lot of experience there. A lot of good times and a lot of scars.

I know how that is. Here we go. Unfortunately not how it is.

Yeah. com is, is, uh, covering the Splunk State of security report. It's that time of year again.

Um, why don't you, well, let me just say, you know, we, the whole world gets a, a flood of, of security reports, state of security, cyber, what have you, usually right before the RSA net, uh, conference, and then right before Black hat or around black hat. This one, we, this report today is perfect timing because the RSA stuff's kind of in the rear view mirror. Black hat's still a little ways out.

What can you tell us, you know, so it's a good time to discuss the Splunk State of Security report. Tell us about the 2025 report, maybe how it relates to what has become a rich history of Splunk's state of security reports. Yeah, thanks, Alan.

So, you know, what we've done with the state of security report has taken a close look at Security operations centers and I have understanding what's it like to, to work in a soc. Uh, what are the problems that we have? What are some of the bigger opportunities?

And, you know, what's really standing out to me is just a lot of the problems that you, that you hear about today are the same problems that we had, you know, 10 years ago, which is, there's a lot of burnout from a so analyst. The reason for that, what we, you know, really kind of think about is just that alert fatigue and just, you know, the, the, the churn of what the day-to-day looks like. Uh, in a, in a soc I think over greater than 50% of those pulled, have, have effectively said they're just experiencing burnout, fatigue.

And it's even causing them to think about looking for, for jobs, even outside of cybersecurity. That's how much, that's how much of a frustration pain point it is for them. You know, unfortunately, burnout in, in the cyber and, you know, security world has been something we've been dealing with for, I'm in cyber 30 years.

It is, I mean, 'cause it's a, in many ways it's a thankless job, right? Because if nothing happens, that means you did your job. But when something happens, you know, the finger pointing starts immediately and before even the triage and, and, you know, recovery part is done.

And, and then it's a constant battle because it's, you know, it's the Tom and Jerry cartoon, and you are, you're, I always forget if Jerry's the mouse or Tom's the mouse, but we're the cat, right? We're always the guy running into the frying pan or something, you know what I mean? And, um, it, it's hard.

It, it's, it's hard and it gets burnt out. And though you, it, you know, no, no one works for free, don't get me wrong. But it's long hours, long hours, and a lot of thankless It is.

Tasks going on Can be, you know, what I think is, is super interesting, if you really think about it, what it would indicate if somebody was, was experiencing this churn as a SOC analyst, it would mean there are intrusions in their environment all the time. You know, they're constantly, they're constantly under attack and they actually have actual intrusions. And I don't think that that's necessarily the case, right?

Like, if you're dealing with an, a legitimate intrusion every hour of the day, every day, then that's a, then that's a major problem. I think that what this is indicative is, is really the quality of the way that we configure alerting our detection pipelines. How we, how we investigate alerts is ultimately what has that downstream impact on, on a SOC analyst.

And we, so we really placed this emphasis on detection as code, really treating the way that you think about engineering your detections. Similar to how a software engineer thinks about the software development life cycle. Really thinking about false positive, true positive, benign, positive detection, uh, detection metrics is something that can help you drive towards improving the quality of your detections.

And ultimately, you know, the quality of, of the experience For a SOC analyst, I think part of the, the burnout is I'm expecting all, I'm, I'm investigating all of these benign, um, events that, that actually don't have security value. And I think it's one thing to say, yeah, I'm actually dealing with an intrusion, and that's kind of fun, but I'm just, you know, if I'm looking at trash every day, that's, that's not a good time. Especially if it's not getting any better.

Yeah. You know, Michael, gears ago, uh, when I started still secure, we had an intrusion prevention product, vulnerability management network access control, and we were bidding, involved in replacing, it was actually a semantic I-D-S-I-P-S. Great.

I think about It. Remember that one at a large, a large US military network, probably one of the largest private networks in the world. Yeah.

And this network got on average about 400 thou, and I kid you not 400,000 intrusion attempts a day. Yeah. A day, you know, mostly foreign state actors, nation state, foreign, and I imagine being a, you know, the screen watcher there, the screen scraper guy there, the, the SOC analyst, the desensitize desensitizing doesn't even begin Yeah.

To describe it. Yep. Yeah.

Right. And, and the, the, the, the really crappy part of it is it takes one, it only takes one successful intrusion to just ruin everyone's day. Yes.

Right? Yep. And often it's a tough, tough world because of these problems.

You know, do you just, do you just become a little desensitized to the alerts and you don't, you don't spend the diligence, the due diligence investigating the, you know, the ones that matter because it's like a, you know, these other hundred that I looked at this past week were nothing but to your pointed, this one could be the one. So again, like prioritization and truly understanding your environment, do you really need to have for, to your, to your network, IDS, do you really need to fire on every single alert that's internet facing? Because I mean, someone's always gonna be knocking at the door, right?

But, but it's what's, what's gotten through the door that, you know, that you really need to understand. Yep. Sometimes the knock at the door is just a false Yep.

Alarm. Right. And they're low and slow behind you.

Yep. But let's turn to this 2025 report though, Michael, give us sort of our key findings. What are the top three things you think in here?

Yeah. Um, you know, some of the things that I, that, you know, that I had mentioned earlier, just teams just feeling overwork and, and, and in some, in a lot of socks, it's not even just that they're, they're running the investigations. Some of them are running the tooling, they're running the detection pipeline.

They have these hybrid roles. There's, there is no specialization. Right?

And so, feeling overworked, one, the, the tooling sprawl, um, things that we've, that we've kind of chatted about in the past and understood in the past is think on average the security organization's gonna have 20, 25 distinct tools that, that they need to operate to, to protect an infrastructure that, that feels very bloated, you know, to me. And, you know, where do you have opportunities to kind of consolidate and rationalize the tooling that you use to protect your infrastructure? And then, you know, the last piece being again, um, those that are actually looking to thinking about leaving their cybersecurity career, career behind all of this, exacerbated by, I think the downward pressure by leadership of like, Hey, I'm investing resources, money, time, you know, into your organization.

And, you know, when they see some of these kind of metrics come out with the false positives and, you know, where are the intrusions? You say you're overworked, but like, where are the intrusions? Like this is all just creating just this pressure cooker of an environment for a SOC analyst to work in that super unhealthy.

And, you know, I think we have an opportunity to, to help improve. Fair. Fair.

What about ai? AI has a, has a great opportunity to, to help support and, and I think alleviate, you know, the overall workload. And we, we love to stress, um, AI is going to help create efficiencies for a SOC analyst, but it's not necessarily that replacement.

If we think about it as an augmentation, the SOC analyst is still that human in the root, in the loop that validates, uh, some of these findings, you know, but a few examples that we've been working on, you know, within Splunk and the Splunk products are things like an AI assistant to help you engineer your own detection so that you don't necessarily have to be an expert in the Splunk processing language. It's just a great way to kind of maybe get you 80% of the way there. But then that expert helps you tie that together.

Another great feature that we've chatted about recently at, uh, Cisco Live last week was, um, this ability to create an incident report based on your case notes that you've, that you've created within, within Splunk. So the ability to, you know, distill all of these findings in your investigation notes, and then create an, an executive, you know, incident summary that we can then pass on. If you think about the incident response and the SOC role, it's not just that investigation.

It's, it's about conveying what happened to your leadership chain in a way that they can digest and understand what the impact is, what the risk is. And, you know, some AI just has that ability to just really kind of, not just uplevel someone from a technical perspective, but thinking about those soft skills and that ability to write a quality report is a just, you know, a really simple great opportunity for us. Agreed, agreed, agreed.

Um, Michael, I always, every report I've always been involved in, there's always some finding that I shake my head and say, well, I'm surprised. I'm not surprised, but I'm surprised or I didn't see that coming. Or, geez, was this a blip?

You know, what, what, what in this report kind of struck you like that. I'm surprised that we still have the same problems today that we have, we had 10 years ago. Yeah, that's, that's what I'm surprised at.

We're we, we still haven't solved it. Um, the, the standard, the, the detection, you know, the, the, the churn and the false positives, the quality of the detections, all, it's, it's all still there. It's, it's exactly the same that it, that it was 10, 10, 15 years ago.

So, you know, I think we need to, we need to find ways that enable, and I think to your point about ai, that's, that's a great opportunity to really, I think, enable and, and offset, you know, some of this churn and help understand what do we, what should we truly care about when we think about creating visibility into an infrastructure, uh, engineering our detections and that investigative workflow, right? Like, I think there's a lot of efficiencies to be gained along the way that, that are gonna, you know, help to really kinda take the stress off of an analyst. You know, maybe I'm old and cynical, but I, I've come to expect that, right?

You look at things like the f**k 10 and stuff like that. It doesn't really change very much year to year, to year to year the same problems. We're still battling the same problems.

And it's not that there's not new security threats and new security vectors and attack surfaces that we need to, you know, there's all, all of that. But we, in, in some ways, and it's frustrating and it, and it contributes to the burnout you're talking about. We can't get out of our own way dealing with the stuff we've been dealing with for 15 years.

How the heck are we gonna get to the new stuff? Completely, completely agree. Um, you know, what we really think about has been super helpful for us internally that we're happy to pass on to, to anyone listening is, is really that event correlation, right?

So I think a lot of, a lot of the way that socks are structured and detections are structured are, are one event equals a detection that warrants an investigation. But when you can tie these events together with correlation and in insulin products, that's gonna be risk-based alerting. When you, when you're able to say, these seven events are something that should be investigated as one investigation, it's one event that fires, that's your entire investigation of these seven events versus individually these seven events.

So a fish, a malware detection, a network connection, not just necessarily investigating each one individually, but when you're able to really kind of tune your detections in a way that does that event correlation for you, you're really gonna kinda get some great efficiencies right out of the gates. Agreed. Agreed.

Excuse me, Michael, we're about outta time, but for people who want to download the report Yeah. And kinda read it for themselves and digest it, what, what's their best bet to get it? Yeah.

Thanks for asking. Really the simplest way. Go to Google type in 2025, Splunk data security.

It's gonna be one of your top links. I think you'll also see last year's report there as well. com will get you there as well.

But the simplest path, just Google for the report then should pop right up for you. I love it. Hey Michael, good luck with your allergies.

This too shall pass. Enjoy. Appreciate it.

Keep up the great work. It's fun, man. We appreciate you and all you do.

Yep, Likewise. And thank you, Alan, for having me on. It's always great to be here.

My pleasure. Michael Fanning, be so at Splunk here on Tech Trunk tv. Go check out the report.

Google it. That's the Splunk state of security report 2025. We're gonna take a break.

We'll be back on Tech drunk tv. Hey guys. Thanks.

The throw we're here with Hal LOAs is the CTO for Truly You. And we're talking about fraud and how it's getting more sophisticated, especially in the age of ai. Hal, welcome to the show.

Yeah, thanks Michael. Thanks for, uh, having me. Fraud has always been with us.

It's kind of like death and taxes that way. But, um, I guess my first question is, how is this changing? 'cause I, I'm assuming the bad guys have access to ai, but how clever are they getting and how challenging is all this getting?

Yeah, you know, uh, it it's getting more sophisticated all the time. You're exactly right. The bad guys do have access to, to tools and techniques and, and things they, they didn't before.

And so, so we're seeing some of that come through now in, in these fraud attacks that, uh, that, that truly you seize. And by the way, we see millions of transactions. So we see, we see a lot of good, uh, transactions and a lot of good things.

But we also see, you know, a fair amount of bad things too. I don't think everybody watching this knows who you are. So how is it that you're able to see all these fraudulent transactions?

Yeah, great. Thanks you. So Trulio is a identity platform specialist across, uh, people and businesses.

So our customers use us to make sure that, that the people and businesses they're, they're dealing with or about to deal with are, are really who they say they are, and they're trustworthy, either individuals or businesses. So that's where we play, As I understand it, at least, uh, the bad guys have gotten exceptionally good and impersonating various legitimate people, transactions, business partners, whatever it may be. So what are the signals that we should be looking for to identify this fraudulent activity?

Uh, 'cause as I understand it, this is impacting the global economy into the two trillions of dollars. Yeah. So, you know, I I think most, uh, depend on, uh, partners, like, like truly you to do this.

Some very big entities take this on their own, but it's a very sophisticated business and, uh, that, that we're in and, you know, runs across payments and marketplaces and financial institutions and fin FinTech. And so it's gotten very sophisticated and, and really the, the kind of that specialty of knowing, uh, people and businesses are who they say they are does revolve around certain signals. So, and some of this depends on how much, uh, you know, what we in the industry call friction, uh, that, that our end customer wants to sort of apply to the process.

And what we mean by that is, you know, they can ask, uh, you know, very simple question or, or in some cases, no questions at all, and, and trust that people are who they say they are. But, uh, uh, you know, as as things get more sophisticated, fraud gets more sophisticated, uh, the, the questions need to get more sophisticated and move beyond from, uh, you know, just, Hey, what's your date of birth and your address and your name, where you live, you know, to more sophisticated techniques like, Hey, uh, I'd like you to show me a, a government document or Id, uh, we're gonna take a picture of it, and then we're gonna match your yourself, your a face, uh, your face, your selfie to, uh, to that picture on that document and, and make sure everything lines up. And, and that's a very, very sophisticated, uh, test that's quite often used these days to verify individuals.

And it's, it's, uh, you know, something that can be, uh, you know, attacked with, with, uh, the, the bad guys use AI to attack that. But it's also very, very hard to do, given all the sophistication we throw at checking those signals. They're making sure they're all correct.

How much friction are people willing to tolerate? 'cause it seems to me that's always been the issue is that, well, yes, we wanna check to make sure that this isn't fraudulent, but our patience level for that is really low. So how do we kind of balance the need for, uh, integrity of the transaction and the simplicity of the interaction that everybody seems to want no matter what.

Yeah, that, that, that's a really good question. And, and there's a bit of a, you know, it's complicated answer. So a lot of, a lot of players and a lot of forces kind of gather together to decide what's gonna be done.

For example, uh, you know, regulators and compliance people, of course, they want a, a, a lot of friction. Well, they don't want the friction, but they want a lot of assurance that, that the identity, uh, is who that person or business says it is. Um, on the other hand, as you said, if you apply too much friction, then people are just gonna drop out of the process.

They'll say, well, you know, I, I don't wanna, I don't want to, you know, do business with them that much, or I don't want to start up, uh, or, or kind of join this organization for, for that much friction. So they'll, they'll bail out. So there's a balance to be struck.

So what we've done at Tru U is actually enabled sort of very variable, uh, friction to come into play. So on a dynamic basis, uh, we can let our customers decide whether this looks like a risky person or transaction, uh, and then decide how much friction they wanna apply on a dynamic basis. So it might be as simple as like, Hey, Michael, like, you know, tell me, you know, your name and date of birth and, and hey, hey, we're good to go.

I, I, I know you have seen you before you, you look low risk. Uh, on the other hand, someone like, you know, Hal Lonas might get in and they say, Hmm, that seems sketchy. We don't like, we're you are, are applying for this, um, you know, transaction from geographically, or we think we've seen you before and seen bad behavior.

So we're gonna actually put you through the whole gamut of, of tests and, and put a little more friction purposefully on that, as well as gather a little more information for compliance reasons. So, you know, today, a actually the most sophisticated solutions allow you to sort of vary the friction even on a dynamic basis, rather than in the past where it was like a kind of a one size fits all. You either decided not much friction or a lot of friction.

Uh, we can now use, you know, facilities in our product line to decide case by case how much friction we wanna apply. Actually, not us deciding, but our customers deciding how much friction they wanna apply. Is there a sense of urgency in a lot of the fraudulent transactions, or there's usually some anomaly where there's somebody standing up and going, we need to do something different.

And that's part of, uh, the way they trick everybody into, uh, sending them money, essentially, whether it's millions or, or even just a small transaction. But as I think this through for a minute, um, is there another, is that a signal we should be tracking, or are there criminals just very patient now and they'll pretend to be a user for a very long time and then they'll strike? Uh, a another really good point.

So there's these kind of sleeper accounts that get created, right? Where it's like, Hey, you know, I don't really want to do many transactions. It's low dollar volume.

I'm just gonna create an account and sort sit there while you forget about me, and then fire up six months later and say, Hey, I'd like to move $10,000, you know, in this account. Or, I'd like to like to do something else that might look, uh, you know, a little more. But, but that's, that's a perfect example of sort of a step up, um, verification you can do, say like, okay, let's let people on the platform and if, if there's sort of thin file or we don't know much about 'em, it's okay.

But then when they do a, a higher value transaction, if they ever do it, uh, you know, our customers can decide to do sort of a step up verification at that time. So let's take a, let's take what we know and then let's add a little more to it and get some surety that they are who they say they are, and I feel good about this transaction. So, so the sleeper account and, and, and definitely the sense of urgency is there too.

So, you know, we all see that and hear about it and, and experience that ourselves. So, you know, we need to make care. We need to be sure, you know, personally that we don't kind of fall for that.

And that's sort of, you know, best practices from a, from a cybersecurity standpoint, but, but absolutely true. Yeah. We of course, hear about the bad guys are creating digital fakes and they have entire personalities and histories that are harder and harder to detect.

But how would the good guys use AI to kind of fort that? And, you know, because I'm assuming we fight firing with fire Ab Absolutely true. So you, you know, best practices now is, you know, your identity verification provider.

I know, you know, truly you is very well invested in this. You know, we, we, since we do see millions of transactions, uh, you know, good and bad, uh, we build very sophisticated models now using AI to recognize, you know, the, the real people from the fake people and the, the synthetic from the, you know, the, the authentic. So we, we do a lot of work to verify that.

And the signals, because the AI is getting more sophisticated, are getting more and more subtle. So the AI is getting better at creating people that look like people, you know, synthetically or, or license documents that look like real license documents synthetically. And, you know, used to be the old thing where, you know, a driver's license with the wrong background, right?

Uh, it doesn't look like a, it doesn't look like a British Columbia driver's license or a, or a, you know, state of Illinois driver's license. And now, um, the AI's becoming very, very good at, at replicating those, those details all the way down to holograms and making sure that the MRZ on the back matches the data on the front. Just a lot of work involved in doing that.

But the AI's getting better and better, so the sophistication of the detection side needs to get better and better too. And, and, you know, needs to be constantly retrained. And with those, those feedback loops to make sure the machine is, uh, learning, you know, what, what the bad stuff is, Is this platform of yours really aimed at very large enterprises, or can anybody kinda invoke this?

And it just kind of depends on the level of risk and what they're trying to protect. A anybody can use it. And, and we find that, you know, sometimes there's, I mean, obviously very, very big enterprises use us, uh, you know, payments and marketplaces and, and, uh, you know, uh, uh, very, very sophisticated customers are using us, but we also wanted to make it accessible to smaller businesses and smaller customers as well.

And, you know, where, um, bigger customers might use us, let's say through like an API only type of arrangement where they, they send us data or, or images or embed, you know, document verification in, in their application. Smaller customers can also access us through, uh, even like drag and drop interfaces. Uh, we have a facility called Workflow Studio that lets you build an onboarding process using simple drag and drop and filling out fields and putting on your own logo and making it look like your business.

So we, we really wanna make it accessible to a broad range of customers and, and a broad range of customers find it very, very useful, you know, from, from very high volume applications to, to lower volume applications. Yeah. And who wake up in the morning to drive this?

Is it the finance team or is it the security people? Or who's kinda coordinating the response here? Yeah, uh, you know, compliance people, uh, folks that are, uh, customers who are monitoring regulations have to keep up with the regulatory environment.

Uh, we, we also have more and more product people involved. So the, the, the product managers and the product people get involved and they say, and there's a bit of a, you mentioned before that, you know, the kind of the yin and yang of, of friction. So the, the product people wanna onboard people in the platform, they want to grow their business.

And that compliance and regulatory people tend to be the, you know, kind of kind of overwatch where they say, Hey, let's make sure we are onboarding the right people and performing the right transactions, and we know who our customers are. So even our customers, there's a bit of a, uh, you know, kind of both sides of that coin that, that are looking at it, trying to, trying to balance that out. But those, those are the main drivers, compliance and regulatory people and, uh, product managers, product people.

So what's the one thing you see folks still doing that just makes you shake your head a little bit? Go and go, folks. We need to be a little smarter than that.

Uh, uh, you know, a couple things I, I'd say one is, um, you know, just, just not employing any solution or thinking you can solve this manually. So it's very, very difficult and actually very extensive to have a review team. And we still see a lot of customers who are using manual efforts to try to do onboarding or, or kind of waterfall to that if it's not a simple case.

And that just gets very expensive. And, and then you have to build up expertise in that area. And, and it kind of makes me shudder to think like how fragmented that can get, and the bad guys exploit that.

So, you know, they can launch millions of attacks with very little additional cost, you know, for, for one or a thousand or a million additional attacks. It's, it's easy for them to push a button. So, you know, that, that worries me.

Uh, you know, a little bit, the, the other side of it too that I get worried about Michael, is actual customer participation. Um, you know, we can really all help each other by kind of having this, uh, herd mentality, right? Where we protect each other.

And, and customers sometimes are reluctant to participate if they feel like their data, uh, or their kind of transaction patterns might be used, uh, to protect them or others. E everyone's pretty worried these days about AI and models and how they'll be used. And certainly I think we all see examples of, you know, maybe kind of creepy ads, you know, where you'd think like, well, for sure someone's keeping track of what I'm saying and doing and kind of targeting me.

You know, on the other hand, from a security standpoint, you know, we want to be the good guys and protect our customers, but if we've seen an attack at one place, we'd love to be able to protect everybody from that same attack. So we, we kind of hope that in the future, companies will be more kind of, um, uh, you know, aware of, of different use cases for the data and different kinds of models where some are really used for sort of a, a, a, a a kinda a beneficiary for everybody. And, and, and others might be used for other purposes, but we, you know, we certainly want to use that data to help protect the broadest, uh, possible swath of customers and people, Hey, folks here, heard you're here.

The bad guys collaborate all the time, so maybe we should figure out how to work together to fort that. 'cause it's costing us quite literally trillions of dollars a year. Exactly right.

Hey, Hal, thanks for being on the show, Michael. Appreciate it. Thanks.

And back to you in the studio. Hello and welcome to the latest edition of the Techstrong AI Leadership series. I'm your host, Mike Bazar.

Today we're with Vic c Choudry, who's CTO for Buzz Solutions, and we're gonna be talking about, well, how AI might be applied to making our electric grids more efficient and power distribution and all that good stuff. Vic, welcome to Shah. Thank you, Mike.

We really do appreciate your time and happy to be here. We talk about the fact that AI needs power all the time, but I don't think we spend a whole lot of time talking about how AI might help us get more power and be more efficient and distribute power where it needs to be. So, explain to us, if you would, what is the opportunity here of using AI to kind of maybe solve a problem that's been around for a long time?

That's correct, yeah, Mike. So in terms of ai, as you can see with the rise of, you know, these generative AI models and LLMs and all the fancy stuff, there's a rise for more compute. So the data center load is increasing.

So AI requires more electricity and power, and it's even forecasted, uh, the data load or the, uh, the, the load forecast would be increase double and triple in the next five years because of these data centers. But at the same time, AI and machine learning, uh, does provide opportunities to even help power utilities, power delivery systems, and the grid itself to become much more, uh, optimized. So in a way, if we can use AI to optimize the flow of power, the flow of electrons to the, to the conductors, to the wires, that really helps, uh, the utilities kind of redirect power in ways that can serve the society in general.

One of the ways we are using BU solutions, um, one of the core capabilities of ours is computer vision ai, so visual analytics, visual, uh, intelligence, which basically emphasizes, uh, modernizing and then monitoring the grid itself. So any kind of, uh, inspection that the utilities are doing on the grid itself. So the power lines, their substations, there are different kind of infrastructure assets.

We are using all that visual data, so imagery and videos collected from drones, so helicopters or fixed cameras, we are taking that and then analyzing it in a much more efficient, much more faster and cost effective manner. For utilities. We are finding any kind of defective anomalies, you know, overheating in the lines, uh, transformers getting damaged, electrical equipment getting damaged or overheated, and even vegetation that's encroaching on the power lines that can cause a lot of problems, such as, you know, we've seen in cases like wildfires have sparked due to failed grid infrastructure.

So we are providing all these insights back to utilities with our ai, and then they can use that effectively, make them actions and do a much more proactive maintenance so that the grid remains, uh, less stress and strained due to climate factors or external factors, but also internal factors do rising due to demands, uh, but also it makes the utilities much more proactive and then, uh, much more smarter on using such operations for their, for their power line and grid network systems. It also seems to me that the grid itself is highly distributed. It's a physical piece of equipment everywhere.

The utilities folks have enough people to manage all this, or is AI gonna help them level that playing field a little bit? No, that's a great question. Um, the utilities are facing a lot of challenges in terms of resources itself.

And, uh, the, and the grid is expansion, it's expand, expanding. The grid is very distributed. There's more distributed energy resources coming online on the grid, for example, like renewable resources like solar, wind.

So that's adding a lot more power and strain on the grid itself. But managing the, and maintaining the grid is a challenge for utilities itself. So a lot of the field engineers, the inspectors, the linemen, uh, there is a workforce challenge and resource challenge that the utilities are facing.

A lot of this workforce is actually retiring, so there's a big gap in the workforce that is coming into these kind of roles. And that poses, uh, a problem where AI can be a solution where, you know, specifically for our example, we can help in resource optimization. So mundane tasks like looking at images for hours and for months, uh, finding out any kind of defects or anomalies on the grid, uh, is just such a mundane task.

Um, and it takes a lot of time. So instead of these specialized people and resources doing that, uh, why don't we give that to AI to kind of find trends and patterns and anomalies and defects, uh, in that data. And then all these specialized resources get that, uh, insights and those information that they can turn actions.

So now the resources are more optimized. They're the, they're, uh, they're time effective and they can be used in a much more efficient and optimized manner to do maintenance out in the field. Mm-hmm.

It also seems to me that a lot of the equipment is aging and replacing all of it overnight would be cost prohibitive. So how will AI kind of help us figure out maybe where the most chronic issues are? And maybe that's where we replace the gear sooner than others and 'cause not all aspects of the grid are equally, uh, shall we say warm?

Yeah, uh, that's a great point. Uh, the, the aging, we have seen examples where there's a lot of components that are decades old and they might have been, um, out of their shelf life as well, that are still deployed on the system in the network. So there is a big need to map all of the network from the physical space to a digital world, which the utilities are heavily investing in, is to building those digital, um, uh, twins, uh, digital transformation efforts and providing, uh, putting a lot of resources and efforts into that, but also figuring it out where these kind of assets, the, these equipment are located.

And what is the condition of that? Uh, first of all, to figure out when they would be, they would fail and cause problems on the network, but also due to supply chain issues that are happening. There's, you know, we have seen transformers that are backlogged by, uh, you know, three to five years, uh, that are needed.

So there's supply chain issues adding more problems, uh, for the utilities as well. And that's where the, these kind of AI solutions, which are more on the visual side, uh, which we are delivering, helps utilities to not only just inventory their assets and equipment that is on the grid. So we can tell the utilities how many transformers are located in a certain distribution feed relying or transmission corridor, how many insulators.

But on top of that, we tell them what is the condition of that? Are they, uh, are they degrading? Do they have any kind of, uh, anomalies or defects on that?

Do they have cracks, um, you know, broken insulators, broken conductors? So now they're getting information about what is the condition of that, and that impacts the shelf life of the equipment itself. But it also helps utilities to send out crews or maintenance people in the field and take actions accordingly on their, um, on the grid, uh, equipment itself.

So now they know what kind of asset, what kind of equipment is located at the assets, where it's located, and what is the condition of that. Now they can take a, a pre preemptive and proactive measure on how to repair it or replace it ahead of time. Mm-hmm.

And to that point, how predictive can we get with ai and can we see things coming sooner? Because I think a lot of the times, historically, at least we act like we're surprised, but I got a feeling it's a, some folks out there and knew something earlier, but they just didn't have the way that kinda share that. But maybe if we have ai, everybody can see what the issues are gonna be sooner.

Yeah, that's correct. So in terms of AI predictability, there's, again, I would, I always say that the world of AI is changing every six months now there's new techniques, new innovative solutions coming out, and we try to leverage all of them. So right now, what we are doing is we are detecting for utilities.

We tell them, uh, where their problems are happening on the grid and the network, what kind of problems they are and what, and what can they do about it. What we are trying to move towards, uh, where the utilities can leverage a lot of, um, uh, you know, benefits is, is the predictive capabilities. So since we are collecting a lot of visual data historically as well, so it it not only geographically, but over time, we are collecting all this data.

We are looking into feeding into a predictive analytics or predictive asset management system. So what it does is now we, we using time series data, we adding, uh, climatic, uh, you know, uh, features on that, you know, what is the humidity, temperature, pressure, wind patterns of the certain location. We are also looking at, um, you know, load patterns, uh, within the conductor or the line itself.

So what's happening within the line, uh, what's happening outside the line and what's happening on the equipment, and trying to feed that to a system that can check out these trends and basically find out areas that will require much more prioritization or much more, uh, you know, emphasis on maintenance. So for example, let's say we take an area where there's, uh, inspection being done over and over again, and utilities want to find out what is the likelihood of, you know, let's say a trans five transformers going bad. So this system would be able to forecast and predict into the future, uh, based on the data that's collected, that let's say in this specific area, there's like 90% likelihood that five, five transformers would go bad because, you know, let's say there were 50 electric vehicles added in that neighborhood, uh, you know, because of that.

So now the utilities can basically, uh, prioritize that area for maintenance and do much more inspection maintenance in that area instead of looking at, you know, thousands and thousands of miles of, uh, of distribution lines. I don't know if you're doing this or not, but are you also maybe playing around with digital twin technology so I can model the grid and do a lot of what if simulations? We are, I think that's the plan where we want to move towards.

Right now, as I said, we are, we are on the detection side and we are giving actionable insights, but we really want to take in different kind of data sets into our platform and different data sources so that we can build these digital twins, uh, for the utilities. And one great thing about taking the physical aspect of the grid to a digital world is, is basically creating these simulations and, and checking out various scenarios. One example is, let's say I want to add 50 electric vehicles in a neighborhood.

How would that impact the transformer for that neighborhood? Would it, you know, overload it, would it cause parking? Those kind of things.

And how would that impact the equipments itself that are deployed on the network? So we are looking to put more emphasis on that as we are going forward. Right now, what we are delivering to utilities is, uh, is a system that basically tells them the health of their system currently, but the value is what can we do to tell them what would happen in the future for their system?

Alright. A lot of local, state, federal governments are usually involved in anything to do with utilities. Um, is there something that they could be doing to help maybe drive adoption of these technologies to make the grid more robust?

Because frankly, we're all counting on it. Yeah. Um, I think one of the things I I say is a lot of times regulation has to catch up with technology.

Technology is always leading the charge over there. And I think the more education we can provide, uh, to the regulators, to the energy commissions, um, this, uh, the public utility commissions, uh, about the presence of this technology and how successfully it has been deployed with utilities, either through pilots or full scale deployments that we are doing with utilities like Dominion Energy, New York Power Authority, which are some of our biggest customers. The more education we can provide to the, to the regulatory commissions, the, the better it is for utilities to kind of incorporate newer technologies like, uh, like AI or IOT sensors or even drone inspections at a larger scale.

'cause now then they have the backing from the regulatory commissions, but also, uh, general public as well, that now they can test out these technologies even more. I like to say that utilities are facing a lot of complicated issues on the network. The grid is not the same as it was like 50 years ago.

Uh, it's a whole different world of the grid. The electricity and power is flowing, bidirectionally, uh, now you have distributed energy resources on the grid. You have electric vehicles, everything's getting electrified.

The low demands are increasing exponentially. So utilities have to find innovative solutions to tackle this. One of them is, is how we can leverage machine learning, data science and ai and the utilities really need backing from, from the regulators for that.

Hmm. And you didn't mention the data centers were building for ai, but that's one other source of, uh, consumption that's rather large. Um, is it your sense that the grids are gonna be able to handle that if we're smart about it?

Or is that gonna kind of tip us over the top and we just need a new structure altogether? Yeah, I think if we are smart about that and we, we make the grid more smarter, we, and we make the grid modernized, um, then we would be able to tackle those, those problems and tackle those challenges for utilities. As you know, the grid has, is, is a century old.

Uh, it, the grid was the biggest, you know, invention of the 20th century. I like to say AI is, is the biggest invention of, of the 21st century. And you can actually actually call AI the electricity of, uh, of the 21st century.

Um, the, the big thing for, for the utilities would be to figure out how can they use these innovative solutions that are tested out in the field and how can they deploy it successfully. The the grid I would say is, is think of it like a highway's getting, uh, congested because there is distributed energy resources like solar utility scale, solar farms, wind, wind farms, hydro hydropower, uh, electric vehicles, data centers that are driving a lot of power demand on the grid, both, you know, downstream and upstream. Uh, in order to not have this highway or the grid get congested and stress and strain, there is an emphasis on continuous monitoring, frequent monitoring and inspection, and making sure that the grid is much smarter when it's dealing with these kind of bidirectional flow of power.

All folks, you heard it here, electricity. We take it for granted, but looks like we need some advanced technologies to make sure it's gonna be around when we need it. Hey Vic, thanks for being on the show.

Thank you, Mike. Really appreciate it. ai video series.

You can find this episode and others on our website. We invite you to check them all out. Until then, we'll see you next time.

Although we live in a world of software, server hardware still matters. From the data center to the cloud to the edge, this episode of the tech field, a podcast features Scott Schafer, a VP and chief technologist at HPE, discussing the evolution of the server with Jack Poller, Vung F and myself, Steven FST servers really are still relevant and maybe more relevant than ever. Welcome to the Tech Field Day podcast, where we bring together a group of IT technical experts to discuss a single idea about key concepts in the industry.

This podcast features a variety of perspectives from members of the Tech Field Day delegate community, and is often recorded in association with one of our events. Tech Field Day is part of the Futurum group, and this podcast is also published on our sister company site techron tv. On this episode presented by HPE, we're discussing server hardware.

Is it still relevant in this age of cloud and platforms and software eating the world? Before that discussion though, let's meet who's on the panel today. Hi, I'm Jack Poller.

I am founder and principal analyst with Paradigm Technica. We are an industry analyst and research firm, uh, focusing on AI and cybersecurity. Hi, I am Vung fam.

I'm within generation. I'm a senior solutions architect. Uh, we are, you know, solutions provider.

We provide hardware, software solutions for maintenance customers, public and private, And howdy. I'm, uh, Scott Schafer. I'm the vice president of our, uh, advanced development group here and the chief technologist for our compute organization.

That's the group in, uh, Hewlett Packard Enterprise that develops our ProLiant and synergy and Superdome class servers. It's great to be here. And I'm Steven Foskett, organizer of the Tech Field Day event series, including, uh, the special, uh, event that we're holding with HP's ProLiant team today as you are listening to this podcast.

So let's start off, uh, by talking to, uh, the team here. You know, we live in the world of cloud. We live in the world of everything as a service.

Why does somebody really care about server hardware anymore, Scott? Well, I mean, uh, obviously the software's gotta run somewhere, and so we care. Um, but I say that somewhere part because I think that matters.

The, the location actually really matters. Um, we speak to, or I end up speaking to a lot of customers where that location is critical, uh, especially being really close to the data, uh, being able to, uh, access whatever you need whenever you need it to either run your AI or to build your services or to build whatever, uh, business solutions you're trying to, uh, to build there. Uh, being able to clo being close to the data is, is very critical.

And, uh, you know, I think we know that, uh, it's not, uh, cheap, uh, or, uh, effective to backhaul all that to cloud all the time. Uh, nor do many customers kind of want to have their proprietary data up in, uh, someone else's service. And so, uh, yeah, we, we definitely see a huge and continued interest in growing interest in, uh, making sure that, uh, the customer has on-prem server hardware for whatever they need.

Yeah, so it, it's, in part, it's a manifest destiny. You have control of your environment fully. You have control of the how long you use it, why you use it for everything.

And it's, it's at your controlling in your disposal. You don't have to be at anyone's whim. You have better economics, you have better control.

So why not, you know, you have to invest in yourself and not be at someone's whim. So that's, that's important in my opinion. And, and some topologies don't allow a public cloud to be honest, or any other hyperscaler.

Well, you know, you talk about location and you talk about sort of, you know, control and you know, on you said, why not? And I used to look at the world and say, um, why invest in the hardware? Right?

There was, it's, uh, a huge capital expense and a lot of what companies were doing was, um, migrating their capital expense to opex, uh, for and moving to the cloud. And that changed the budgeting equation. And then we sort of sort of divided the world into, um, companies that were born in the cloud that started out with cloud footprint and would never have anything on premises.

And then you had the older companies that had, uh, an on-premises footprint that they would always keep running because the cost of sort of migrating the entire environment to the cloud didn't make sense. But I think the age of AI is changing that. And you know, Scott, you mentioned the need to, um, have your compute close to your data rather than new foing.

The, the data transport cost, which is both a time and monetary cost. And so I think as more and more companies start doing and figuring out what they can do with AI beyond just simple chat bots, um, there's gonna be a lot more edge computing and the need for not, you know, for high density, high power compute in these weird remote locations. So I think in that case, you know, sort of servers really do matter now, and it's no longer sort of a why do we care?

It's of course we care. Well, yeah, I agree with you. Workflow is important.

Understanding our data, understanding how we consume our data, what, what our con competitors doing with their data. You may be just a service provider and that's important for its own mission, but when it comes down to it, even your service provider services has competition. And if other people, you know, privacy issues, there's all those reasons are reasons to keep, uh, hardware relevant in your space, whether it be your own data center, control that at a co-location, but it's still yours.

And you have, again, I'll re I'll re echo the fact that it, it's, you have control and then, then that's, it may sound crazy, but it's not. It's just something you have to be cognizant of it and control and cost, control and access, et cetera. Well, then we see, uh, plenty of, uh, systems.

Now it's funny, uh, you mentioned the edge, right? Because I mean, I'm, I I say funny because everybody defines edge slightly differently. Um, you know, I talk to some cloud providers and the edge is a colo in your city.

Uh, okay, that's not what I mean. What I mean at, at the edge. And by the way, but I don't mean all the way out to your house.

That's a little too far, uh, for us, um, when we talk about edge from a compute perspective, I mean, we're seeing, um, servers go in at retail locations, multiple servers now at retail locations. We see servers going into distribution centers, distribution warehouses. We see, um, uh, servers going in at, at manufacturing, uh, locations.

We see them at, um, at sites like, uh, out at oil rigs. We see them out at, uh, uh, you know, really just, uh, base of cell towers. Obviously.

It's like you, you see them in all kinds of, uh, locations. Uh, again, almost exclusively because you need the proximity, uh, to the data, right? Again, just back hauling.

All of it is, is too much. Um, but yet you absolutely want to process it. We're seeing lots and lots of different kinds of sensors.

I'm just gonna use the word sensor. You can insert whatever your favorite kind is there. Uh, from cameras to voice to temperature, there's all kinds of stuff.

But we're seeing all kinds of sensors at these locations that our customers really have to be able to, uh, uh, collect all the data, collect all that telemetry, analyze it, and then act on it locally. And that can only be done, you know, with systems right there. Well, you hit anything in on the nose, Scott, telemetry data.

Those are, those are pervasive in our society demands and our consumption of information. When you go to someone, you ask a question at a point of sale, you want to know a lot information. Where does the information live?

If it's too far away, it's in or in somebody's foul box or in a, in a, you know, granite Mountain somewhere, it's gonna be something that you, you want access to, right? And, and people don't have the patience. They want the information yesterday.

They want it immediately at their fingertips disposal. So AI is empowering that, uh, 'cause that does the analytics. We have smarter systems at the edge, which actually enable customer, uh, customer experience cus you know, endpoint user experience so they can get what they want to do and, and make a better decision.

'cause we're all about making better decisions and we, how can we do it? We don't have access to the data to make information happen. So, yeah, I echo that.

I think, I think part of that is because we're looking at different use cases with different desires of business outcomes, right? And if you, if you sort of roll back, I don't know, five, 10 years, the business outcomes and the use cases were very, very simple. It was virtualization and it was just running standard compute.

And at that point, you know, virtualization essentially said that your hardware platform was generic, right? It was, it was a commodity piece. And ultimately it really didn't matter what you were running on.

Now we've gone beyond sort of virtualization and to another use case where what you're running on does matter because of all these other things we're talking about, the ability to have different sensors that might not be able to do it, the locality of data, the latency, the cost, the speed, the environmental conditions of the edge, you know, this generic sort of place that's not really generic at all. It's very unique for every very each customer and different business outcomes, different workflows. So in this case, you know, as you start moving beyond sort of that, uh, generic use case of running virtualization, then the hardware really does start to matter again.

Yeah, I think that's the, the key point here is that when people think, oh, uh, hardware doesn't matter, what they're thinking of is this sort of, um, uh, I don't know, commodity space where you've got, uh, you know, generic hardware, whether it's virtualization or you know, containerized, you know, containerization. Uh, and they're imagining this world where you just stack up, I don't know, one u blade servers as, as deep as possible. And, and they are generic.

And, and, and, and honestly, those are generic to some extent if, if it's used for that use case. But what we look at, when we look at the server line of any large provider, especially the one we're talking to here, HPE, um, it's not generic servers, is it? I mean, these things are purpose built.

You have different servers for different purposes. And yes, one of the purposes is stack 'em tall and have 'em be identical. But many of the other purposes are, you know, memory intensive, io intensive, uh, accelerator, intensive edge servers, et cetera.

These servers are very different from each other. And yet, of course, they're all built with, um, many of the same components, but put together in meaningfully different ways. And, and Scott, that to me is what makes this world of servers still so interesting in that you look at them and you're like, okay, so they have, they, they look similar, you know, from a block diagram perspective.

But look what they did there. They made this one have, you know, all sorts of memory, or this one can handle all sorts of storage. And those two servers really are different, aren't they?

Well, you hit a, you hit a big paradigm, the catch 22 of software driving hardware, hardware driving software, and use cases on top of that. And when you get with a manufacturer that is understanding that balance, that equation, and making accelerations on both sides possible, that's amazing. And, and, and that's, that's, and that's the, the value that the, that, you know, hill Packard does.

They'll, they'll listen to the customer, they'll see what the use case is. CXL is not dead. CXL is is, it's still there and it's gonna be more and more important.

So it's, it's, it's in, it's, you'll see some new development with that shortly. And, uh, I'll leave it at that. Scott, you're gonna do something?

I'm sorry, go ahead. Yeah, I was gonna say, you know, we, we absolutely are building, you know, some servers optimize for purpose. You know, we, we recently introduced one that's designed for kind of these edge locations.

And you say, what, what makes a server unique for an edge location? Why, you know, isn't it just a regular thing you just, you know, put it on? It's like, no, we built one that, uh, that can be, uh, mounted to a wall.

It can mount it under a desk. And yes, you can absolutely put it in, in a rack kind of form factor if that's what you want. But having different mounting options is simple as, as simple as that is, is something that we definitely heard from customers and said, Hey, I've got all kinds of different locations.

This has to go, uh, uh, enable me to do that. Um, we have the ability to, uh, to have a filter physically on, on the front. Um, I was, uh, I was working with one customer and, uh, they sent me a picture of where the server was, the server's in the break room for the employees at the, at the retail location.

And so I was like, huh, what's in the atmosphere there? You know, I don't, I'm not sure. Uh, the, and so you don't want that kind of stuff, uh, in your server.

So we have, you know, filters that go on the front and, and make sure that they're, uh, protected, which is not something you worry about in the core data center, right? A data center, you don't care, you know, it's all filtered specific care, but, you know, on the edge, it's, it's not, right. So you'll Think you don't manage that.

But let me tell you, I cleaned the filter on my ProLiant, uh, ML one 10 the other day. It's been in a nice clean environment. That filter was filthy.

Yeah, you got a lot of dust in the air usually, right? But then, uh, uh, but then things like physical security, right? I mean, we wanna make sure that somebody can't physically tamper with or, or take items out of it.

You mean, you know, again, this is one of those things I think a lot of people don't think of. 'cause they're like, I physically control my data center. Uh, the racks are closed, that's great.

But when you're out at the edge, right? Think about it, you got that hourly wage employee going along there, you just do, you need to actually secure these things physically, um, in a way that, uh, perhaps we haven't. So that, that's like purpose built.

Um, but outside of even, I mean, I love talking about edge, we talk about it all day. But, um, outside of that, even in the core data center, and we're doing things to optimize, especially around efficiency. If I, if I had a, uh, of the buzzword for what I think we're doing now and in the future, it's gonna be about driving efficiency.

In the past, we've had other kind of things that we optimize for, like, uh, uh, density. Um, but I think we're, that's, that's not what we're hearing, right? We're not hearing from most customers.

They need that anymore. What they want is much more efficiency from, especially from an energy usage perspective. And so we've been doing a lot to ensure that, um, you can pick good efficient options.

If you need the absolute highest performance possible, I can give you that. Um, you know, and you don't care how much power it uses, that's great. But if you do care and you need more, uh, optimized for energy efficiency, power efficiency, you know, we, we'd give you that too as well.

Well, you, you talk about edge servers, Scott, you know, I've been in those single closet areas as they, they call it data center. And the airflow is, uh, is is not what you expect. You might not be able to breathe to be, uh, frank.

And yes, double is a HEPA filter. So you, you, you definitely have some environmental challenges, not just, not just the compute challenges, not just the use case challenges for driving the software. Telcos have that Because we, we, the server, you know, with the DL 1 45 Gen 11, uh, op can operate up up to 55 c.

That's, that's a hundred and what is that? 130 Fahrenheit. So, because as you said, yeah, you go in these environments, they don't have server, uh, sorry, data center class air handling.

Right. You know, they got whatever air conditioning's in there, and sometimes the back isn't air conditioned at all. Your ProLiant doubles as a HEPA filter, like I said, right, Steven?

Exactly. But you, you, you know, you talked about efficiency though, and it's, there's a number of considerations for efficiency. You talked about power efficiency, and I think we've been very focused about that recently, um, with, you know, uh, the amount of heat and power these things consume and generate.

Um, I think, you know, the other part of the efficiency is things like how do you manage your fleet of servers, right? And I think, um, it's management and it's how do you secure it? And physical security is one.

And, and the securing the firmware and guaranteeing the, the, the trust factor of your data center. Um, you know, you mentioned, you know, physical security and, you know, a minimum wage employee, when you look at these servers that are in a retail location, one of my favorite retail locations is a grocery store. Supermarkets, right?

Your server ends up in, there's no server closet, there's no data center. It's the only office in the building is the manager's office. And it sits there with their paperwork with everybody going in and out all the time.

And no cooling, no heating, uh, coffee spilled on it, all of those types of things. So anybody can come in and access it, can put a USB drive in it if it accepts USB drives, right? Can plug in a keyboard and mouse and screw around with it, pull disc drives out, all of those types of things.

But if that's the environment it lives in, how do you ensure the security of the boot firmware or the operating system, all of those things. So I think that's another consideration where, uh, a lot of work you're doing, right. I think you're, I think you're redefining DLP there, Jack.

It's the world we live in today. It's a completely different world than A, a machine stuck in the data center. A hundred percent.

Yeah. I mean, we spent a lot of energy with these, uh, proline gen twelves where, um, we've introduced a new IO new IO seven. It's an asic uh, design that we do ourselves.

I think a lot of people don't know that we, we develop our own ASIC care. Um, we don't buy it from the market E everyone else does that. I know of every other vendor buys theirs, which is fine.

Um, but we develop our own because we wanna make sure that it has, I always say everything I need and nothing I don't, right? I, I don't wanna pay for anything I'm not using. So it's got everything that we need in there, including our new, uh, secure enclave, which is a new secure vault built into the ASIC itself.

It's isolated from the rest of the asic from a, uh, from an access perspective. And that has its own memory and its own storage, completely separate, but it's inside the package. So nobody can come along with a chip clip and, and clip on and, and extract any information.

We use it to store all of the passwords, the keys, the configuration parameters. So none of that is exposed. And then we use that as well to allow us to make sure that all of the firmware that on that, that is on that platform, first of all, it's encrypted, it's managed by us, and it cannot be tampered with or modified in any way.

And if it is, we instantly detect it. And depending upon what it is, we either shut the system down, alert you, all those kinds of good things to let you know something's not going right. Uh, but that capability is rooted all the way down into the ASIC itself.

We call it silicon root of trust, because the, it's built into the ASIC hardware. So there can be no tampering with the supply chain. Nobody messing around with the server in transit and putting a different firm on.

You can't do any of that because the, our, uh, h HPEs, uh, protection is built right into the actual ASIC itself. The very first bit powers on. And the very first thing it does is load a little thing, you know, we call the boot loader.

That boot loader is protected by, uh, a, a digital signature in the asic. And so it, if it doesn't match, it doesn't load, just flat out doesn't load. Uh, and so then we chain the trust up from there, right?

The bootloader then checks the next piece and ensures it's signed with HP's keys, and off we go, uh, and build up that whole kind of, that whole root of trust that it's rooted all the way down into the silicon. Um, certainly something that's unique, uh, to HPE. Yeah, I think a lot of, a lot of people think of ilo, um, and, and other, uh, management capabilities of servers as being sort of, um, KVM, right?

I want to be able to reboot the thing. I wanna be able to see what's on the screen, et cetera. Um, but ILO is a lot more than that because you can also do things like, you can check firmware revisions, you can update, um, the firmware, you can update the software.

You can actually, uh, reconfigure the whole server from there. It's really, uh, you know, hands management and, you know, again, I, I, I have a ProLiant. Um, I'm still only at ILO five, but, um, but even with, even with that old thing, right?

I can do a lot, um, without having to have HandsOn, uh, on that server. In fact, I don't, I don't see a need to have a monitor on the thing, because you can do so much right there in ilo. But also due to that point, adding to that conversation, the, the calm management that HP provides is something that's, no one really talks about a lot in the field.

It's new, relatively new, but allows you to do upgrade lifecycle management for non-data center for, for a disorganized traditionally, uh, topology. And you have the ability for air gap. You have the ability for remote sites all from one central centralized location.

And that gives you the ability to be agile and flexible to the changing business landscape and how people can consume compute. Like you mentioned Jack, uh, you know, you need power at the edge. You know, Scott mentioned that as well.

And then there's AI use use case POS systems. And I think that shows the evolution of computing that, hello, this is gen 12. You know, they've been at it for a while, right?

So hopefully some lessons have been learned and, uh, and applied and there's a good strategic direction. And I see some of that, not all of it, but it's getting there, right? Yeah, I think, I think it's getting there.

And I think what we're seeing now is, um, a change, again, as I was talking about earlier, a change in the use case from I need generic compute, and I just need, uh, you know, my requirements are processor and memory and some storage to, uh, a much more comprehensive list of, uh, capabilities that I'm going to use, which is, you know, security, remote management, um, power efficiency, space efficiency, um, environmental conditions that are different, locations that are different hands-on, hands-off management. That's different than it used to be. And, uh, and I think we're also gonna see now, um, capabilities that will help us do, uh, a lot more automated management as we get bringing AI into, you know, our automation capabilities to reconfigure things on the fly depending on use cases and time of day and needs, et cetera.

Um, so it's gonna be pretty interesting what's moving in the future for servers in general. And, you know, for me, Steven, this sort of goes back to answer your question of does do servers matter anymore? And I think I would've said no, uh, a year ago.

And today, I say absolutely it does. Well, and then of course, as we've kind of alluded to here, you know, in this world of AI servers, um, there's an entire universe of, um, accelerators and expansion cards. There's disaggregation with CXL.

There's incredible capabilities in terms of memory and storage expansion. And all of this is leading us to a whole new world where not only do do servers and server technologies matter, but server technologies are almost the defining thing that allows us to move into the future with some of these AI servers. You know, you look at what's being delivered now, um, to hyperscalers and to the AI factories as well as to end users who are trying to do inferencing so and so on.

Um, we've got an unprecedented level of power, uh, requirements and power. Of course, every, every watt you put into that server comes out as heat. So you've gotta deal with, uh, with heat, we're looking at incredible liquid cooling technologies.

We're looking at, um, you know, just absolutely, um, amazing demands being put on the hardware. And Scott, I know, you know, the teams that you have at HPE are dealing with this almost existential question of how can I possibly build a server that contains this fireball of a processor, uh, a stack? How do I build a server that, that can support that?

Yeah, absolutely. You know, when we talk, most customers that we talk to, they, they really, um, they rely on air cooling. I mean, I, I love the liquid cooling stuff.

It's really fun. Um, and our HPC customers use it all the time, which is great, but most of the enterprise and, and certainly the, uh, uh, medium sized businesses, lot of colos just don't have liquid as an option. So, um, yeah, we're, we have really interesting solutions, uh, for, for liquid, which can take the absolute highest wattage, highest heat parts that exist.

But we also have to solve the problem for error. And, uh, we've been doing a lot of work on figuring out how to adapt the server design so that we can take on 10, 650 watt power supplies for exam, uh, excuse me, uh, 650 watt GPUs, um, in a four U server, and still be able to cool them plus cool the, um, the SSDs and the CPUs and the memory that's in those servers, right. You know, we focus on those GPUs, which is very understandable, right?

'cause they're really high, high power. But we still have the CPUs and memory and SSDs as well that have to get, oh, and as does, my friends always remind me, gotta always talk about those, uh, transceivers, right? The, uh, the optical transceivers are also now power draws and they also demand, um, a lot of air cooling.

So, uh, yeah, that's one of the things we focused on in gen 12 is ensuring we have really strong options for customers that are doing AI that, that need those high wattage GPUs and being able to continue to use their air cooling for those solutions. I, I remember going to Houston years ago and seeing some of the incredible stuff. You guys were engineering your own fans, you guys, guys were, you know, and obviously, you know, you've got a incredible yes, um, work done on baffles and heat sinks and so on.

I remember seeing all that stuff in person, and then I remember opening up a server and, and seeing it right there in front of me and saying, yeah, this stuff from the lab. Here it is on the, on the server. Yeah.

We, we, you know, I got, we take tours of people through our facility here in Houston, and a lot of people are surprised to learn that we have wind tunnels, by the way I say wind tunnel. And immediately someone thinks that it's some big thing you can get a car or an airplane In our wind tunnels are very small. They're designed to put a server in or they're designed to just put the fan assembly in.

Um, but yeah, we design fans, we de design shrouds, we design all of baffling. Um, Pete sink is a really, uh, hot topic, no pun intended, uh, right now as we are working on, like I said, on, on trying to figure out how to do that. Um, but, you know, one thing we tell customers, and you know, it's just is really simple, is that, you know, losing density can often buy you a lot.

Um, if you think of the exact same server load, say an 850 wat load, just add it up, you know, all the components in a one U server versus a two U. The one u will consume an extra a hundred watts for its fans alone to cool that 850 watt load. If you put it into a two watts, a two U server, it only takes 17 watts of fan power.

And, and then when Scott, when you sit that on underneath the desk in somebody's little manager's office, right? Yeah. It changes the, so it changes it.

So it doesn't seem like you have a jet engine running under your desk. My office server under my desk was just fine. Thank you very much.

No, no. The acoustics are important. Yeah, we actually do care about that as well for those servers that are clearly designed for edge locations.

Yeah. Because you don't know where they're gonna end up, right? And you can't have it next to someone's head running like that.

But, uh, but no, you know, we we're trying to help customers understand that if they don't need density, don't pay for it. And what I mean is not, not paying me paying the power budget, so you could lose density. It's a good, it's a good thing and it'll really benefit you.

But I think he's hit something very important there, Scott. You know, Stevens mentioned, do you need servers? Well, yeah, we don't need, don't need commodity servers, Jack, we need engineered solutions for something with lot of, with a lot of thought behind it that solves problems that you don't even think about and don't want to deal with.

Heat, power, longevity. So, and then when you have an organization that does look at the whole equation and solves that for you without you, you know, stressing about it, that's a win. That's a win right there.

And well, when you talk about engineering too, we're not just talking about the server itself. I mean, we're talking rack scale in these cases too. I mean, you know, in, in, again, I have seen HP's production floor, you guys are building whole racks for customers, right?

I mean, it's not just the, you know, it's not just servers that you're shipping. Yeah, for sure. And I mean, not only racks, but rows and, and depending on what the customer needs, right?

We, we have HPC systems, which are multiple rows and can consume, you know, uh, you know, mul thousands of servers and tens of thousands of GPUs. Uh, we can build everything from, from yes, one server all the way up. You guys are the number one supplier in H-P-H-P-C, right?

We Are, and we are the top of all the big charts, uh, uh, in terms of the best and the, the best supercomputers built from Frontier to Elk, Capitan to, uh, as the most recent two. But, uh, yeah, the first, uh, some of the first and, and largest supercomputers ever built. Incredible.

Wow. Um, so I, I think that as we're kind of, uh, you know, getting here, uh, on, in the episode, uh, honestly, I think all of us are of, of agreement that servers still matter. I mean, that's why we're coming out here, right?

That's why we're flying to Houston. To to, to visit h hp HPE and learn a bit more about what they're doing. I almost said HPC, um, I guess we're visiting HPC too.

Mm-hmm. Um, learn about, uh, what, what you're doing in HPC and AI and the edge and so on. Um, you know, Jack, uh, what are you looking for in a conversation with HPE about servers?

Um, I'm looking to see how we, the conversation has moved from what used to be server consolidation to really now server expansion and what are all the different ways h is meeting the customers, these new use cases. And in particular, thinking about all these various use cases, how are we going to secure servers and the server environment? Um, I'm, I'm, you know, big on security, big on ai, and these are the things I think that are gonna drive computing in the near future.

And so what is HP doing to meet these customer requirements and the new workflows and new ways of thinking about the computing world? How about you VI know that you know the HPE product line very, very well, but, uh, what are you learning? What are you expecting to learn here?

Uh, You know, I, I wanna see some of the people behind the scenes. I wanna see their thought process, what, what drives them, what motivates them and what, and how they bring that to the HPO product line because that, that ethos is so important and that, that's part of that culture of HPE has always been engineering, and people don't get it. And I think they need to really leverage that to help people understand that HP does care about your, your, your compute requirements, care about your mission, your outcome, and this is why.

It's just that not a me to copy this, copy that, and we'll just tear apart. And it's, it's more than agnostic. It's purpose built.

So we, we need to help them understand that it's purpose built so we can derive the outcomes that are expected and exceed their expectations in most cases. 'cause how sometimes how old is your, your, your little proline, Steve, it's probably like, and it's still chunking along, right? Oh, come on.

It's a Gen 10 man. It's not that old. Right, right, right, right.

I've seen up times, amazing up times with HPE servers and, uh, it, it, like, again, it's the balance between software and hardware and how they're really engineered well. So, kudos And Scott, um, I guess, what's your message? Uh, you know, so, so when this e when this episode airs, uh, it will be the day of the event.

Um, we will be, uh, coming live on, on LinkedIn, on, uh, Textron TV and so on. We're gonna be posting these videos on YouTube. Um, what do you want the audience to learn about what HPE is doing in the server market?

Well, yeah, what I'm hoping is that, um, and get a sense of that, you know, we really, uh, we really do care about building the best, uh, server system possible. That we work hard to engineer it, and it's by design to be secured. It's by design to be optimized.

It's by design to be automated so that it, uh, can fit in. All the servers we build can fit all kinds of different locations, as well as, of course, core data centers and be the best, uh, solution we can build. I mean, our, our whole goal, we really do believe that we build the best servers in the world.

And I hope, I hope that comes across Excellent. I mean, I, uh, I think it's, uh, well, I, I've had very good experiences with HPE ProLiant, let me just say that. Um, uh, thank you very much, uh, for showing this, and I'm very glad that we are able to, to kind of give people a look inside, like one was saying inside the, the, the factory, inside the server factory.

Talk to the people. Learn from the people who are doing the work, who are engineering these next generation servers. I know we're on gen 12 now.

Um, is it here, Scott, can I put you on the spot? Is it gonna be a Gen 13 or are you gonna skip 13? Like, like a hotel elevator?

Yes, That's, people bring that up all the time. We absolutely are working on a next generation. What it, what it gets named is, uh, kind of not up to me in engineering, but, uh, we'll see what the marketing team comes up with.

We'll see, we'll see Indeed. Well, thank you very much for this. And, uh, those of you listening, uh, please do, uh, check out the tech field, a website.

You can see a lot more detail about these servers. Basically all of the things that we've been talking about here today, including a very, very sweet little edge server, uh, the DL 1 45 that was, uh, recently released, um, checkout on YouTube as well. If you've missed these things, you, you just Google, uh, tech Field, A HPE, ProLiant, you'll find the videos there.

Um, and I think you're gonna learn something. Even even v who knows more about this than me. I, I is for sure is gonna learn something.

I guarantee it. So thank you for listening to this episode of The Tech Field, a podcast. If you enjoyed the discussion, please do subscribe.

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