Techstrong TV August 11, 2025

Hey everyone. I've got my tar and feathers ready. You're watching Textron Gang.

Hi everyone, it's Alan Shiel. I'm still in Vegas and it's still hot, but you're watching Textron Gang. We, of course, record Textron Gang Day, usually business day before.

So it's Friday, though. You're your Monday. I hope you've had a great weekend.

Uh, it's a gonna be a busy week ahead. We've got a lot of news to go over with you today, including the, the tar and feathering of the Intel CEO. It appears, uh, as well as a report from Black Hat and you, AI really saving us money in this DevOps space.

We'll talk about all those things. Let me introduce you to a great panel. We've got to discuss 'em with, first of all, just back from picking up her birthday present.

We're not gonna tell you what it is, it's a surprise. Tracy Reagan, Mitch Ashley, Jack Poller, and of course, the dean, Mike Ard. Hey, gang, how are you today?

Great, great. Good. Glad to be here.

You know, for, for our audience out there, I hope you caught the last two days of last week's, uh, Textron gang. 'cause there were special, uh, gang episodes that we did hear out in Vegas, rather than having the usual gang, I, I actually spoke to people at, at booths and stuff in Vegas. If you didn't catch them, they're available on the YouTube TV channel, uh, text on tv, YouTube, Textron tv or text on TV or at Textron tv TT channel.

But we're here about Monday though, Mike. It's a busy Monday. Kick it off.

Yeah, I don't know. I've never seen anything quite like this, but the president of the United States is reaching out to share his opinion about who should be the CEO of Intel, And well, it's, And Go ahead. And, you know, that has something to do with the whole tariff fight.

And then there's an argument about whether or not Intel wants to be in the foundry business. And there's all kinds of backstory going on here. But, um, Alan, let's start with you on this thing.

I mean, it does seem, shall we say, um, a little surprisingly disjointed and maybe intrusive. So, Mike, I have in my hand here a paper, right? Anybody remember those lines?

Anybody remember? We're not old enough to remember those words. No.

Joe McCarthy, But that's Joe McCarthy. He never showed what was in the paper, but he had in his hand here a paper. And in that paper in his hand, people's careers were, were, were blotted out.

People's lives were ruined until someone finally stood up and said, have you no decency, sir. Mm-hmm. Have you no decency.

This, this president didn't appin a opine that Intel CEO should resign. He demanded it by, by Royal Fiat. We fought a war in this country not to be ruled by kings who get to tell us that, right?

This is a private company. What goes on between their board? And we could discuss what their board and this CEO says.

But what we've got here is Senator Tom Cotton, who's gone off on haywire trips before, says he believes, or it's come to his attention, or he has a paper in his hand that the Intel CEO has some connections to the Chinese Communist Party. Some companies he did business with or connected to the CPP or the CCP. Excuse me.

Look, if you've ever done business in China, you've done business with the Chinese Communist Party. They control the whole lock, stock and barrel. When I was running, when we had DevOps Institute, we had a very big partner in China, very nice people.

They came here to Boca Raton. I hung out with them. I went to China three times and met with them.

And then I realized why a 36-year-old man there, less than that, maybe 32, was running such a big operation. And then one day, one of his people told me his colonel was big in the party. That's how stuff gets done in China.

We could not do business in China because it happens like that, but to, to make these allegations. And we, we didn't even give the guy a chance to defend himself. It may very well be that innocent, but to make these allegations.

And then immediately before the ink is dry on, on the paper in his hand, if there's any ink on that paper, have the president demand that this guy resign right now, thank you for your attention to this matter. I'm not ready to put on my ground and march in lockstep just yet. That's not America.

That's not what we do here. We don't run the guy outta town par and feathered on a rail On top of that, it's not just about, and I don't even remember the CEO's name now, yang Gaan or whatever. It's about Intel itself.

This is the only American company making chips here. They're in a delicate phase where we, they're literally teetering, teetering on life or death. And this is just the, this is like pushing someone off the cliff or someone's extending a hand to get pulled out of the water and you turn your back on them.

Worse than that, turn the hose on them, right? This is, it's, it's, it's bad business on top of everything else. The other thing, and I mentioned it in the article I wrote, as much as it pains me to say this, if this guy's name was Smith or Jones and he looked like us on here, I don't know if we'd be so quick to judgment, to rush, to judgment that he has a connection to the ccp.

It's a lot easier. This is like, you know, the old movies they used to show the Japanese on World War ii, right? The old, you know, they had that very sort of Japanese kind of sneaky look, if you will.

And, um, it's, yeah, it's just un-American. That's all I got to say on it. Well, the guy's only been CEO since March.

The just, the board just appointed this guy. Um, so I think, I think the way to resolve this, Alan, is, uh, lip through tan needs to get a glass t something and with a 24 karat gold base and take it to Washington and present it to Trump. And, you know, I like the Apple guy did Just like, exactly, by the way, I think that's like the only saying that a lawyer said, 'cause it's actually Joseph Welsh or somebody like that that said that at the McCarthy hearing.

Uh, sir, you, you have no decency, sir. Oh, the o the other one I remember is you issued the code red, but that was Tom Cruise in a movie. So other than that, I don't know, don't remember any lawyer sayings, but, Well, you know, when McCarthy was around, we still had a democracy.

And I know we don't wanna admit to it, but we are full on in an authoritarian government. And Trump has made himself the boss. That is how it is right now.

And we, you know, we can try to say that that's not real, because it's easier to say it's not real than to acknowledge it, but it's real. It's, we're here. We, he has taken over every branch of the government, including, um, the judicial branch.

So, which means we are full on authoritarian mode. Um, the sad part about, uh, Mr. Tan is that, as Mitch pointed out, he is only been in charge for the last four months.

And if you look at the entire population of CEOs that could take and tell in the correct direction, he would be the only person. And I am certain that he is doing the best that he can to pull this company together and to, to turn the ship. And we need intel.

This is not impacting just Mr. Tan. It impacts thousands of employees of Intel.

And it, it impacts chip manufacturing across the board. It's a very serious problem, um, right now for, for the United States to have this kind of conversation going on with Intel in particular. So this is, this is scary stuff.

This is real. Um, and I am quite certain that if we checked on Elon Musk, that he would have plenty of contacts in the Chinese government and the Communist Chinese party as well as anybody else that's in high, uh, in a high ranking role in, uh, in, in any of these industries. So we have to, we have to check ourselves and we have to ask the question, how much does fascism cost the American people?

It's going to be a lot. We are going to pay a lot for fascism, and we're starting to feel it now. Okay, look, I'm, I'm, I appreciate the, uh, emotion and the, the drama and I think, you know, it's fashionable and it's, uh, there's a lot of people who can hate on Trump for a lot of different reasons.

But this is not a new issue with lip Bhutan. And to pretend that it is, is ignoring what's really going on here. So this was sparked by the fact that cadence where Lip Bhutan was CEO from 2009 to 2021, pleaded guilty to selling and giving, uh, intellectual property and cadence design software to design AI chips and other chips to the Chinese government, to the Chinese military, and to companies that are owned by the Chinese government and the military for which they plead guilty and are paying $140 million.

Fine. So let's not pretend that this is, because That's old news, Jack. That's old news that was in there.

And they made him the CEO anyway, so the obviously decided it wasn't an issue. The point is that this is not about the fact that he has contacts in China. He has a 30 year history of investing in companies in partnership with the, the People's Republic of China party.

Don't you think the time to, to talk about that was before you made him CEO? Well, and the time, I guess I do. Which is what?

Wait, wait, wait. You, I gave you guys plenty time, Alan, I gave You guys plenty of the United States who stole billions of dollars in Medicare fraud. Alan, I gave you guys plenty of time to talk.

It's here. I think it's fair to say to Intel, are you guys very sure that you wanna get in bed with a guy to run the company who has spent 30 years investing in the Chinese commun party? The time to say that was in March, not August, not This is a private company.

It's the board that gets to make this decision, decides. It's not until the, Let's be clear, let's be really clear, because you merely mouthing this. They didn't say to until, are you sure you want this guy as the CEO?

That's not what President Trump wrote. No, he said he could be Fired. He said he has to resign right now.

'cause I'm the boss here. Yes, That's what he said. And that's not American.

And if you, if you could swallow and let's, Let's be clear something here. If he was a fascist and we were in a fascist government, he wouldn't say you should fire him. He would actually take him out and shoot him, or take him out and arrest him causing died.

Jack, should we wait yet? Or should I wait till I wear a yellow star and I gotta own, oh, Come on, Alan. It's this, This is You and I are same.

This is Not, he did as good as shooting of Jack because he knew when he made that announcement until stock would tank. And that's as good as shooting him. You are an apologist.

I am not an apologist. I'm a realist that says, you cannot claim that this is a new issue that Trump did this willy-nilly, that Tom Cotton is doing this willy-nilly. The man has a very long history of dealing with China and Well appointed him.

And as Tracy pointed out, Intel is critical to the United States security. And it is valid as the President of the United States to say, I don't want somebody who is in bed with the potential enemy of the United States to be running a critical chip company for the United States. That is a valid concern of the President to say if as Tracy says, the company is so important to the country, which I believe it is.

Okay, now, I'm not saying he did or didn't do this. I am saying he has a very long history of not assist, not just associating with the people, but he was one of the very early investors in Esic. He was responsible for Esic becoming as big as they are and being as competitive as they are with Intel.

Right? And 40 or 50 other companies that we, that I know about, that he invested in, that are owned by the Chinese Communist Party that are in bed with Chinese Communist Party, I think it is reasonable. Now, Trump may have done this in a ham-handed way, but I think it is being very naive to say we should ignore that because Intel board decided we should ignore that as an investor and a stockholder and intel, which I am, I have my own concerns, and I think it is fair for the country to say that somebody who has these types of ties to the Chinese Communist Party may not be the right guy to run critical infrastructure semiconductor stuff.

Jack, Should we bring him in to run the do? Because I'm sure Elon Musk has a lot of, a lot of facts too. Alright, so it's a timeout, timeout.

So it is clear that there's no real form of due process being applied here. And so we are essentially having a jury, we we're having a jury one deciding the trial to put a trial together on somebody and indict them in a public format. And there isn't any formal investigation to go with that.

There may very well be issues here that are worth investigating, but this is not the way to do it by certain and not the way you do it in a democratic society. Second thing, and I'm gonna step away from Trump for a minute, but am I the only one who thinks maybe the board at Intel is just flat out dysfunctional at this point? Because it sort of seems that way?

That's What I'm wondering. There are factions on the Intel board, right? It, it led, it's why Pat Gelsinger left there.

There is a genuine discussion over whether Intel should go into the found foundry business making chips for third party customers versus just making their own chips, right? That, that was, that was the reason Gelsinger left. Mm-hmm.

And, and this guy came in, I, I remember when he was appointed, they said he wasn't as big a fan of the Foundry business. And I'm sure there's a faction of the board that still wants to do that or not want to do that. But Mike, you hit the nail on the head Jack.

These are allegations. These are, these are issues that need to be aired out. You don't shoot first and then ready, aim, and that's what's going on here.

They're shooting. Well, I will, I will, I will, I will simply point out that the shoe has been on the other foot and the other side has done plenty of shoot, aim ready? Who, who's the other side?

Oh, Look at Elon Musk. There's plenty of politicians who've called for and accused Elon Musk of the most heinous of heinous crimes while they were in office, right. With the same detrimental effect to Tesla and other Elon Musk stock.

So let's not pretend that this is only one side. I don't I agree with you. It's not Wait, wait, Jack, let me, are you trying to return, turn this into a Republican Democrat?

No, I am not. I am simply saying that your histrionics, while I understand them, are not exactly fair. We don't ar we don't operate in a vacuum.

Okay. Politicians For Jack, lemme tell you how we do operate. We are in nation and I guess of laws Politic.

And I Wanna point out, lemme politic All person, I wa listen, I would like to point out that Mr to himself had no charges filed against him personally. Okay? No.

It's a whole other question about whether or not CEO accountability is a whole nother topic. We can go into name the last CEO possibly that has been charged for the crimes of the company they have. Right?

But politicians continuously demagogue and demonize their political and economic opponents and for what they believe is right. And I don't think it is fair to say that we live in a fascist society, or that this is Trump being a dictator. If Trump was a fascist and a dictator, the he would not be saying, I think the guy should be gone.

He would be making him gone, and we would not be able to Have making him gone. That's the point. He said, the guy has to resign now.

And what can do that happen? Nothing. Joe Stalin didn't shoot people immediately.

First they had a show trial. Yes. Right?

We don't even have a show trial here. He just, he, he, you don't think he knew by putting that statement out that Intel's stock is going to take a hit? Are you that naive?

I think he knew exactly that intel stop gonna take a hit. So What he did is as good as shooting them. Jack And Alan, if you're gonna take that view, you have to take that view about all politicians' fine About, I do take that view about all politicians.

I do. All right, we're At a place though, as Jack, this is, this is not normal. Now there's a difference, there's a difference between all politicians and the guy who sits behind the desk at the Oval Office.

There's a difference. Let's not, let's not try to make all politicians, Let's, let's, let's give Tracy the last word here, because basically it is not normal. So Tracy, finish the thought.

I, this is just not normal and we can't normalize it. We really can't. And e every little misstep has to be, uh, everybody has to speak out about these missteps.

If we wanna call them that Jack, that he should have not have maybe said it out loud. He should have gone to them and spoke to them, is what we, I think is what we're trying to say. Do process, manage well, investigation, do processes.

We, we have processs for this. Okay? And to make that kind of a statement against a company, I can tell an impact more than just the CEO is so, it, it's just stupid and irresponsible.

And You're aware that we've been in custody Happening behind the scenes, Right? What, what could be happening behind the scenes is a different story, right? They could be, they could have been having boardroom discussions with these people and the board and sending somebody other than the president to speak out.

This is not normal. This it's not, nor we have process in place for these kinds of things. And there was Congressional 2023 about this.

2 billion. He co-invested with the Chinese Communist Party over 20 some odd years. And you know what, so did Klein of Perkins.

And so yes, there Were three other, there were three other there, sorry. There were four other VC firms identified, including Sequoia, right? And Sequoia, right?

They've all right, and they've all changed their name of their Chinese investment arms Or whatever. So it was not, it, it's not criminal for VC firms to invest in Chinese firms, all of which, all of which, including some of the best names, you know, have close ties to the Communist party there, because that's the way the Chinese economy works. But If, and if the department, if the Department of Justice feels that there's a problem, they should open a case and they should investigate him.

And the board now has to be dealing with that. It should not be a public discussion. Not in this way.

When You start short circuiting the law and the due process procedures, that's when you cross into fashion. I'm sorry. And next, and, and where does it stop?

Because next week it'll be who? Broadcom and Nvidia, and it'll just go out, it'll spin at, Oh, I'm sure Broadcom's on the list, no doubt. Mm-hmm.

Yep. Anyway, hey, we gotta take a break. Let's, let's take it down a notch.

We'll come back and talk about something silly like DevOps. You're watching Textron Gang, Discover Textron Group, the epicenter of tech innovation. We are your go-to for reaching IT, leaders and practitioners worldwide.

Our secret impactful content that sparks awareness, engagement, and top quality leads with us. You'll access editorial websites, streaming videos, virtual events, custom content analyst research, and more. Join our satisfied clients.

Let's revolutionize your tech journey. Contact us today and tell your story to the world in the most powerful way with Textron Group. All right, folks, we're back talking about something maybe a little less contentious, but we'll see.

It could be highly debated as well. But GitLab has a report out, they hired the Harris Poll organizations to go talk to a bunch of CEOs and ask them, well, are you actually seeing a return on your AI investments for software development? And, you know, they are apparently starting to see a lot of progress.

Productivity for developers is up 48%. Some folks are saying they're saving as much as 28,000. And more importantly, the CEOs seem to be firmly convinced that investments in software development are good for the business, driving value for the business.

And Mitch, I know you looked at this report, but I'm just wondering, you know, are we on the cusp of some sort of AI driven software? DevOps, engineering Renaissance? It, it, it is happening as we speak.

I mean, it is transforming, right? Right before our eyes when we think of it as code completion and some basic steps like that. But when you talk to people that are using AI tools, whether it's kind of going down the, the vibe, coding angle, or more using AI as part of the development process, not just for coding and automating steps, it, it, it was, it was a significant number.

I mean, they talked to 20, over 2,700 C-level executives in this study. And, uh, that what you mentioned at the end there was, the thing I took most note of is, uh, it was like 82% said that they're increasing or their, they would take half their IT budget and invest it in software innovation around ai. Something to that effect.

Uh, it was very substantial. Uh, my numbers from our studies aren't quite that high, but it definitely, there's a ramp up and increase in AI for development processes. So it's, it, it's bringing to light.

There are real benefits here. There are real productivity gains. And, you know, if you want to get on the, the an, I'm not in the protagonist seat like Jack, so don't attack me on this one, but Jack, um, it is, if you wanna get on the productivity bandwagon of ai, I think there's a lot to be set for what's going on here.

And, you know, GitLab was the sponsor of this, but I think a lot of vendors can make hay with these numbers and kind of do their own thing as well. There's, there's some substantial benefits here, and we're, and we're seeing it in our work directly at the Futurum group, right? Tracy, you seeing any of this?

What's the, what's your reaction? Blah, blah. I knew I shouldn't have gone.

No, I think we could take that article and put, uh, a date on it, like 2019 and change the ti the title or the, the term of the technology that we're using. And all those numbers would be exactly the same. I don't really see a whole big difference yet.

I mean, sure. We're, you know, I'm using AI to fix code. I, um, especially markdown.

Uh, I have to do a lot of work around it. It saves me time. So, but every time we go through a, some kind of a evolution in computer science, it saves me time.

This has been, this is who we are. This has been, been what we've been doing for the last 40 years as we've been saving time and making things easier. Is AI that big of a leap is cool?

I mean, some of the stuff that I use it for, I'm really happy about, um, just as happy as I was when I wrote my first query on DB two. So, um, you know, these articles, I think that a lot of it's, uh, you know, these studies and whatnot, I think they're, I, I take 'em with a grain of salt. But that being said, we, AI is in a position, especially agents, which, you know, everybody knows how much I love agents because they're hard to manage, uh, to change DevOps and platform engineering.

It has the, the, the structure and the bones for it. But we have such a long way to go. And the more I read these articles, the more frustrated I get because I see hallucinations all the time, and I want them fixed.

Please just fix them. We really do need to be thinking about how we can make the technology work well for us. I mean, I, I can see it in my code.

It's like, that is not, that is so wrong. I can read it and know that it's wrong. So we have a long way to go.

I can't believe it's helping that much, but it we're, it's in a position to make us, um, better DevOps engineers. Tra Tracy not part of the problem. Is it, it's a headlines problem.

It's the 750 billion, it's the 28,000, it's that kind of thing. And all those real numbers, yeah, maybe they are, maybe they aren't. Um, to me, what I looked beyond it, beyond that, and yes, they're planning on increasing their software investment, but there's some other key things said, which for example, I'm telling vendors is we have to, we have got to generate secure code, not fix secure code after it's been generated.

Because if you believe any kind of the multiples of, of how much code we will be generating over the next 6, 12, 24, 36 months as that increases, anything that's a manual process can't scale because you can't have that much time allocated to fixing, scanning and fixing vulnerabilities and code that's been generated, scanning and fixing or addressing hallucinations. To your point, Tracy, those issues have to be able to address, to be addressed in order for it actually to kind of deliver the promise at scale of what AI can do. So I think there's some vendors that need to step up around software security and really address it so that it's done upfront.

It doesn't require extra work, extra steps in human power to address it. Yeah. And in areas that we could really benefit from, like, um, we talked about backstage being so popular Backstage is, backstage is a scaffolding for putting together your pipelines and your workflows.

If that, if Backstage is still getting that much popularity and is being used in that many places, it means we're not using AI to do a lot of this work. And that's the kind of efforts that we need. That's, that's the kind of work that AI could be doing.

Um, not that I wanna see backstage replaced, but I'm just saying backstage is a good example of how we're not using AI to build DevOps platform DevOps workflows and platform engineering workflows. Alan, there's some, there's some confirmation bias in this, I would argue, and I'd love to get your opinion about it. So, so C levels, you know, are heavily invested in AI and think that, you know, this is the greatest.

And what did they know? Slice. I mean, they, this is what they're reporting up to them.

And, you know, look, who did this report? Harris? They have ties to the CCP.

No, they don't. I, I don't know. In all honesty, Wait, wait, wait.

Be before we get sued. Harris does not have ties to the ccb we know of, We know of Exactly. But I have here Should be looked into.

It should be looked into. When you, when you think of companies surveying tech people on tech subjects, tech subjects, Harris isn't the top of mind. They, they, I expect them more to see a political survey, frankly, in Harris.

Right? So, and the other thing is, look, didn't we just have a show two or three weeks ago, there were another survey that came out that said developers are actually 19% slower when using AI to develop it's 19% productivity hit. Who do I believe?

I I I don't know who, I believe the, the surveys sponsored by a tech vendor who's pushing You, you've come to the core issue though, right? There is a massive disconnect between what the C level thinks they're seeing and what they rank and file is seeing. Absolutely.

I Well, I was gonna say tra look, Tracy, Tracy stole my thunder. She was just off a couple of decades. All right, back in, you know, back in, what are the, the, the youngins today, call it the, the, you know, the tail end of the last century, right?

In the, the early 1990s, I spent two years at Novell trying to convince the architects of NetWare that writing an entire operating system in X 86 assembly was really kind of bad idea. And that we really needed to move it to a modern, that at the time, modern language called C. Right?

Right. And I learned, talked to them and, you know, train them how to write portable C and all of this stuff. And they looked at me after all this time and said, that's all great, but there's no way in hell a compiler will ever write, create assembly code that runs faster than we can, right?

And they can't generate code faster. They can't do this, they can't do that, right? As Tracy said, we have been doing this for years and years and years of software development tools that enable us to get faster, to produce more code that allows us to focus on feature functionality.

And as Mitch said, security rather than on actually writing code, writing code is the easiest part of the job. The hardest part is figuring out how to make the code, do what you want it to do correctly and securely. And the more time, the more ability we can get developers to focus on understanding their problem they're solving and figuring out the algorithms to create that, to solve that problem and do it securely, the better we are than taking them away from the mechanical road effort of translating their thought into code that's better for us overall.

Here's the danger. Go, here's the danger in this kind of study too, is it's real. You know, you can take numbers and use them however you want, right?

You can make a spreadsheet, say whatever you want, but these kind of numbers could easily be taken by C-level or any kind of executive and say, oh, good, well then that means we need half the number of people, half the num amount of investment in your product company. Who, who did this survey? Or who, whatever.

So there, there's a, a counterbalance to this, this kind of data that can be actually used against the people who paid to have a done. And I think you have to be very intentional about what the message coming out of it, and not just make it sensational headlines. I mean our, our numbers, and I don't have economic numbers like this, but my numbers are much more conservative.

You know, they're like 17%, you know, productivity gain when you take the people who are losing and the people who are gaining, and you know, maybe it's 35, maybe I'm being too conservative, but I'd rather be a little bit more on the conservative side than overhype it and fall into the Yeah, you were with all those people that were wrong. I'd rather be wrong by being a little bit conservative. But, but Mitch, to your point though, according to the this report, it's actually causing C-level people to say, we need to invest more money in software development.

They didn't say more money in developers. They didn't say hire. Well if you, if you, if you read it though, they did say that people were still core to the software Development effort.

So, and that goes to something I wrote this week, Mike, based upon what I saw someone, a very popular post I saw on LinkedIn that I, I didn't agree with. And, you know, it was, the article is like, cockroaches shall inherit the earth because this woman said, if you think AI codes, well you're not a good coder. If you think AI writes well, you're not a good writer.

If you think AI designs well, you're not a good designer. Cockroaches outnumber us a billion to one, but we're still superior. Look, cockroaches have been around 300 million years and they'll probably be here long after we're gone.

There's an argument to be made. We're not so superior. But that being said, what AI is, seems to be good at might in fact be the 60% of tasks that developers, testers, security people, humans doing our day-to-day jobs, right?

A lot of our, a lot of us in our day-to-day jobs kind of go through motions. It's relatively rote stuff, right? We don't get a chance to come on here and, and spout off on what we believe what's going on in the world, right?

A lot of people, they, 60% of what they do is very mundane, and maybe AI does that really well or, or better or as good, but allows the humans to concentrate on those other 40% of things that require human only, a human can do. Well, at least now for the, you know, foreseeable future, two to three years. Um, and, and that that will be a revolution that will spur productivity, that will justify these kinds of eye popping numbers.

Um, and, and not just in software development across the board. And maybe, maybe that is the lesson here that, you know, AI can help us do, but it's not, it's not, is it ever gonna write as well as the best human writer? I don't think so.

Is it ever gonna code as well as the best coders? I don't think, not not as I say in the foreseeable future. But if it does it good enough, let's not get per let's not let perfect get in the way and allow the best coders to do things that are worthy of their time.

I think, Alan, if you spend a little bit of time with people who are using these development tools with ai, and I don't code is a living anymore. I mean, it used to, but I still do some things with, it just took over an internal project, uh, for my part of it with the code base that was written through ai. And I don't understand the code base.

And you just look at some of the things that I know developers do I that I've done in the past, how much time you spend tracing down where errors are, where, where problems and issues are in the code. Understanding a code base that you're not familiar with. You didn't write just those two things alone.

And, and now I can see the productivity gains on my time. 'cause it take me a lot longer. 'cause I just don't do this any, every day.

It's just those kinds of solve, solving those kinds of issues. To Jack's point, it's not about writing the code. Yeah, you can write the code, you can generate a lot of code.

It's all the other things you have to do to make it all work and make it all work together and solve the issues that come up with it. You, I can see, I can see some great productivity gains. I mean, the fact that I could do what I'm doing with using AI tools is, uh, you know, it would take me a lot longer to get my skills back up to be able to do it at the same level.

Oh yeah. I think back when I was young and I used to go to the bookshelf to get a encyclopedia book to do research, I would've loved to had ai. But I'll tell you, I still miss my, you know what, my world was ignited when my mom got my brother and I World Book The World Book encyclopedia set.

I know. It was awesome, Man. I, I miss my encyclopedias.

Anyway. Hey, we're we're running late today 'cause we spoke so much on that first topic. We need to take a break.

Let's come back. We'll go to box C. com is the leading resource for news analysis and education on challenges facing the cybersecurity industry.

com covers all aspects of cybersecurity, including data security, DevSecOps, cloud security, application security, network security, security threats, and more. com has the largest selection of security content featuring breaking news, blog posts, podcasts, and more. com to learn more.

com. Home of Security Bloggers Network. Hey folks, we're back.

And as Alan mentioned, black hat USA was last week and Alan was at the show. So we're gonna do a little retrospective here and kind of say, you know, it's always interesting to think about what you saw at a show when you're at the show, but as you get some distance between you and the show, your memory of it and your thoughts about it seemed to change. So, Alan, what's your take here as you're looking back now at Black Hat and USA?

Because from where I sat on the other side of the country, it seemed like for the first time there was a lot of chat about DevSecOps and application security and software supply chains. Most of the announcements I saw had something to do with that. But you were on the show floor a lot.

What did you see? It was black hat. It was black hat and all its glory, but it was a different black hat.

You're right, Mike. Let me just quickly mention on software supply chains. I, I ran into my friend Alan Friedman.

Alan of course is the father of SBOs, if you will, the godfather of SBOs. And he left csa and this was his first black hat, not as part of the government. And I'll tell you, he's working on something called hbos Hardware Biller Materials.

And shout out to Alan, keep your eye open for that. Um, you know, I wrote a bunch of articles and as, as you're right Mike, as time goes on, my articles became more, I think, introspective, retrospective, sympathetic. I I will tell you, as the article highlighted here in your ticker says, there was definitely a subdued undercurrent of what's, when's the other shoe gonna drop?

Budgets are tight. Uh, people are worried about their jobs company spending, though. I don't know if you have any, I was talking to some friends of mine.

Do you know, black hat booths are two to three times the cost of RSA booths. There's a lot less booths at Black Hat. It's a much smaller, it's a huge floor, but much smaller than RSA, but it's two to three times the cost.

Um, but that being said, budgets are being cost. Almost every company I spoke to has recently done layoffs. There's been layoffs just about every single company.

Um, it's not just the security people, remember, it's the marketing people, it's the management, it's product management, it's product marketing. It's, it's, it's everyone up and down the, you, you know, uh, even the media companies doing layoffs announced around blackout, right? My friend Rebecca Kitchens president of Tech of Not Techstrong of, uh, tech Target and former Tech Target, they call it now, Rebecca was laid off and, and she's been there 20 something years.

She's an institution there, right? You, you're seeing things happen here that kind of, you know, I spoke to the my friends at Cyber, uh, risk Alliance and what's going, so even the tech media and the security media businesses are, are feeling this. I, I think, and it's not just security.

I think we're seeing it across the board in tech. People are, you know, there's no joy in Mudville. There was an article in The Times, another article that I wrote, uh, not necessarily on Security Boulevard.

Uh, but you know, the, the fun out of tech is, you know, is, is is deflating, right? A lot of us, well, me anyway, I'm Well Mitch, you're the same age as me. Uh, we grew up in a time where people who aren't to chase dollars went into Wall Street hedge funds and, you know, uh, financial and, and and, uh, that kind of thing.

But then there were some of us who chased tech, the startup life, the promise of that, the sushi's on Thursday and all the perks that came and the security of working in tech. And all that's gone. Tech Tech is running leaner and meaner, and I do mean meaner than I've ever seen it.

That being said though, let me give you the other side of it. Black Hat's about the People. It's another article I wrote.

It's about the people stupid, right? And, and I'm, I say that in two points. First of all, Jack, you've been in this industry long, longer than you wanna admit.

All of you, Mitch, Mike, you've been around it too, Tracy, you are more on the dev side, but you're involved in security coming to this and to RSA and seeing the people I came up with, Mitch, you and I, you knew most of them. You've seen the picture Rich and everybody. Yeah.

Yeah. It's people that I've known 25, 30 years who are some of the top people in, in, in the industry these days and seeing them and catch out. You know, we're Facebook friends or we're LinkedIn friends, I see what's going on.

But seeing them face to face, hearing, hearing from them, seeing what they're doing, hearing what they're thinking, it's Chicken Soup for the Soul, right? It really is. It, it's great to see those people.

But on top of that, I think the message is clear. It goes to what I said before about you're never gonna replace the best developers. You're never gonna replace the best security people because it's a thankless job.

There's a lot of burnout. It's far from perfect. But, you know, someone referenced Jack Nicholson in a Few Good Men, we sleep under the blanket, our freedom.

We sleep under the blanket that they provide. 'cause they are vigilant, they are on guard. They are constantly fighting a fight that's almost impossible to win, but they fight it anyway.

And we may give them better armor and more guns and weapons in the form of AI and, and everything else, but it's up to them who are on the front lines fighting this fight. And that's what security is about those people. So I'll end right there.

And I wanna say that, and I heard that Alan left, uh, uh, CSAW was happy that he found a, a spot, but I have to point out that it's a huge loss for, um, oh yeah, the government. It's, it, it is, it's a bad thing for the United States that he's not there, Jen. It really is Jenny.

Yeah, Jen Easterly left too. And of course she was denied a position at, at, uh, west Point because Laura Luma, who was elected by the people to be the purveyor of who's allowed to work in our government, decided she's not. Hey, Alan, I I love your perspective on people and I agree with you and as we talk, say That again for me, Jack, one time.

Come on. Thanks for joining us on this episode of Text Gang. We should end it right there.

Done. Um, you know, as we, as we discussed in before we kicked off the show this morning, that, you know, serious, you know, missing it this year didn't go, uh, partially to avoid being on the surface of the sun in Las Vegas in August is never fun. Um, there, you know, we are of an age cohort that is at the upper end and somewhat aging out of the working force.

And, you know, you talked about layoffs and I'm wondering and sort of that feeling, and you, you wrote a little bit about this in one of your articles. I wanted to get your perspective on sort of the age and possible age discrimination in hiring Age is, is real. You know what, talk to our friend, I don't know if you're ever on with j JP is on, but he, he's, he's written about this too, Jack.

I, I did, I saw some research, some article that if you're over 55 in tech and you get laid off, not just in security in tech, if you're over 55 in tech, you, you don't have a good shot at getting rehired or not anything near where you were when you got laid off. It. It's really, yeah, That's, that's of, of the people.

I know that's been a very big issue and you know, I'm, I wish that RSA and, um, black Hat and some of the other conferences, uh, that we participate in would talk about that a little bit. That people who are in their fifties and sixties are very capable of and have such a wealth of experience that, as you said, it's the people that they can bring to bear. And for most, for a lot of these people, it's not about I need to have a salary commensurate with the last position.

I was a, you know, vp, whatever, and therefore I need my quarter million dollar salary. It's, they still wanna be part of the community and contribute and, and want and need to have a job. And bringing somebody in at not, you know, maybe a lower level or a lower compensation is not necessarily a bad thing if you can leverage their experience.

Yeah. So I, I would say Def Con does a better job with that Jack than Black Hat and RSA does, I think Def Con really does kind of honor the OGs, if you will, you know what I'm saying? And, um, but, but it's true.

But, you know, but you mentioned this, I'll, I'll go a little further that that is the problem is most people who are in their, you know, mid fifties, they're at the height of, they're at their, the height of their earning potential. And to tell someone who's, you know, made 300,000 or, or more, and I, I know it sounds like a lot of money, but when you look at what it costs to live in America, but, you know, you tell someone who's made $300,000 that, Hey man, I'd like you to come in and help us. I could afford to give you a a hundred.

It's, that's a, that's a tough pill to swallow. Um, and, and it, you know, but you pay for what you get. But don't, I think we need to remember though, and, and it struck me really, I, I was invited, uh, Thursday night to a Cobalt ne uh, not Cobalt, cobalt io, you know, the testing as a service.

They had a party at the sphere I went to, and it was a lot of, I, a couple of hundred people, mostly Pentesters, a few journalists, analysts, but mostly Pentesters. And, um, you know, looking around, looking around, first of all, I was surprised at how many people I knew, to be honest with you. But, you know, it, it is a young man's game doing the, the pen testing thing, and our young persons getting better and, and more power to them.

And they, and, you know, and they're harnessing the best tools and they're making it happen. And black hat in general is like that. But here's an interesting observation, and Jack, Mitch, you guys are around the security business person for person.

I see more people my age at a security conference than I see more people than I see people my age, let's say at a DevOps conference or a cloud native conference, or, absolutely. Right. So I, I do think the security industry, and this is a gut thing, I don't have any numbers to back it up, but I do think the security industry has done a better job of holding onto their OGs, if you will, than, than maybe software in general.

Well, here's an idea to throw out, maybe not to make everything about ai, but maybe the last laugh of the aging population is we're the ones who will be training the AI as we, as we close, turn off the light and close out, close the door of our careers, right? I'm, these People are career. Yeah.

That's, that's ironic. Well, I mean, long careers as we, as we wrap things up when, when those stages occur, yeah, I think it's there, there's opportunity there, opportunity for, you know, folks that are a little far, very far down the, the row in their career. Yep.

And I think, uh, this is industries, uh, specific, I have been working much more with the, the DOD and the DOE and they have a respect for older people. Hmm. They acknowledge their, um, expertise and their contribution in a way that's different from the private sector.

It's the, it's part of the culture, right? Yeah. It's part of the, the, the military culture to respect the authority of those who may have done something before you.

So if You're, and you're in your fifties, there's a lot of money going into to defense right now, we can say all we want about Mr. Trump, but he is put a lot of money into the defense sector, especially space and Air Force and Well, You know, I usually have a lot of respect for anybody who can throw me in the Briggs. So that's how that works.

Exactly. Don't throw back there. We're going back.

Nice try Mike. Nice try. Well, Lemme, but lemme just close out the black hat stuff.

It is about the people, but the theme of Black Hat this year certainly was ai. What I thought was interesting in going from Booth to booth to talking to different vendors and people and so forth, was there's definitely people who market ai, right? They have AI in their marketing, and then there's people who are actually doing AI in their products.

Mm-hmm. And don't confuse, it's easy to confuse the two, but there's, there's definitely a de demarcation a delineation between those two types of companies. If it's on the label that's slapped on the product, you know, it's probably not built in.

Yep. True. True.

All right. Are we done, guys? Think so.

We are done. Jack, for anyone out there, we didn't hit Jack with anything and we didn't torture him. He was not harmed in the filming of this, but, but, but, but thank you, thank you for, for your opinions on this.

I think it was good to have a, you know, multifaceted discussion. Thank you Tracy, as always. And Mitch and Mike, thank you for watching this.

Hey, I probably did, I don't know, 18, 20 videos out here at Black Hat, the two days of the show itself. And, um, they'll be available on Textron TV and on the OTT channel and, uh, and the YouTube channel. So please do check them out.

There's some good ones in there, some stuff on Quantum and all kinds of good stuff. I, I had some great conversations. Um, we've got Textron tv immediately following, and of course we'll be back tomorrow with even more great Textron gang.

Until then, is Alan Shimmel? We're out. Hi everyone, it's Alan Shimmel here for Tech Drunk tv.

My next guest is Bjorn Toft. Matson Bjorn is Chief Product and Technology Officer at Lab. So, okay, if you don't know about Lobster, 'cause you will after this, let me bring Bjorn on and we'll get right to it.

Bjorn, welcome to Text Drunk tv. It's great to have you on. Thank you for having me, Alan.

I'm really excited to be here. I'm excited to have you on. Um, Biard we're gonna talk about lobster, but before we do, I mentioned you were basically your C-P-O-C-T-O.

That's a, that's a pattern I see a lot lately. Yeah, lately, earlier in my career, not so much. Right.

The Chief CTOs were very different than CPOs. Right. Was more likely that my CT o was a VP of engineering maybe, or heading development, not, not product, but give us a little bit of your background and how you came up to have these dual roles.

Yeah, certainly. Yeah. So my, my background is in games.

I started in, in low level engineering, uh, you know, doing memory managers and graphics code, et cetera. Worked my way up, uh, through, um, a, a bunch of roles at Xbox. Um, ended up doing a bunch of cross Xbox projects, shipped the avatar system, uh, and did a bunch of stuff to align data, uh, systems across Xbox.

Uh, then I went on to join, uh, uh, activism Blizzard King and shipped a bunch of mobile games there. And about seven years ago, I made the jump onto, uh, EdTech. Uh, I joined a, a business called Education first and last year I joined Laber as the CPTO.

And you're right that the, the title is, is more common these days. But, um, you know, my journey has really been leading engineering teams and I find on the product side, um, and the engineering side, you end up at, at, at, at a sufficient, at a high enough level, you end up sort of doing the same thing anyway. So engineering teams, large leadership, that's about, about the, the architecture.

And from the product side that's about mapping that architecture to, to a business problem. And so I, I've sort of ping pong between engineering roles and, and product ish roles. And, um, seven years ago when I took the jump into EdTech, that's when I did the actual jump into officially being in product.

And then I've rejoined engineering, so to speak, with lab here, uh, a year ago. So became chief Product and Technology Officer. I love it.

I love it. Good stuff. Um, I was just reading a lot going on with that, the Xbox team at Microsoft.

I had some layoffs, I may have some more, but yeah, we could talk about that off camera. Sure. Let's talk lobster.

Bjorn. Let's talk Lobster. I don't know if our, a lot of people in our audience are familiar.

What, what's lobster about. Yeah, lobster's a really interesting company, which is also why I joined it. We, we launched in 2012, so that, that's really when, when Lobster was formed and, um, really with a mission to try and digitize lab access and kind of, um, create immersive laboratory experiences on screen.

And, um, that sort of had, you know, a steady growth path, um, uh, pre COVID. And then of course during COVID, like many other tech companies lab, um, had a, a huge influx of, of customers. And, and in that process also acquired a, a different company called uim, which kind of does the same but in pre-licensure nursing.

So that was more of a VR based experience, but also really about immersive education. So today we have these two products, uh, lab are virtual labs, which really is aiming at getting students into doing, uh, lab experiences on a, a screen-based environment, still in 3D. And we run, uh, ubm, uh, which kind of does the same, but it's all about, um, learning to treat and, uh, and engage with a patient for nurses that are in training and, and not pre-licensed, uh, yet.

So that is VR based. And, and lab is, um, uh, is screen-based, but both of them 3D. Excellent.

So let me just make sure I got this right. These are sort of, I dunno, is VR still a term or is it ar Yeah, yeah, Yeah. Okay.

Yeah. So these are, Go ahead. VR is, uh, uh, juicy is VR entirely.

So, so it's very much virtual reality. So you put headsets on you, um, uh, you step into a, a, a completely digital environment. It's not mixed with, um, uh, with the reality that, uh, that, that you also in, uh, yeah, exactly.

And, um, uh, on the labs side, it's entirely, um, virtual as well, but it's, it's screen-based. So we really found to, um, to really hit as many students as as possible for, for lab environments. Getting onto the screen was, uh, was key for us.

So, while we have had VR experiences and labs before, we're now focused on the, on the screen entirely for, for laba for nursing. Of course, a lot of that is kind of kinesthetics and body memories, so really learning how to put hands on patients. And so we, um, virtual reality makes a lot more sense there.

Wow. Really cutting edge stuff. Now.

I'm sure AI is having a, an impact. What actually, before we jump into it, for people who just wanted to peel off and, and check labs throughout, what's the website? com.

Uh, and that will also, uh, provide a, a link off to, uh, uh, to UB simm, which we, uh, run as a, as a product with its own, own domain as well. com, you'll find all about our business and both ub, simm, and Ster. Excellent.

Alright. Back to ai. Yeah.

Can't, you can't walk, you know, three steps without tripping over it today, right? Indeed. Yep.

Talk to us about the impact that AI is, is, uh, having here on the, on the, on the lab and, and education world that LAP are plays in. Yeah, Yeah. Yeah.

So ai, like everywhere else, as you say, AI is having an enormous impact on, on education as well. That is true for education in general. It's certainly true for, for EdTech tools and, um, and digital tools like, like ours too.

Um, obviously in education especially, there's a lot of concerns around, um, last language models and generative AI and, and how it impacts education. And, um, and that of course leads to a weird sort of love-hate relationship with AI and education, where everyone can see the opportunities. Everyone can understand that to reflect together with a last language model can be really powerful.

And, and in some respects it can feel like an expert at everything, but it's also in a, in a sort of formal education environment, um, it can be felt like a, like a threat or something that really upsets, um, the, the normal loop of education, um, that students attend when they go to higher education, for example. So, um, we've obviously, um, feel that impact in lab as well. So we, um, we have to take account of how our customers are seeing ai, and also we have to jump on the opportunities that AI provide, and they are, uh, plenty, which of course, um, tons of detail to, to dive in there.

But, but certainly we are also trying to take a, a cautious approach to AI where we try and make the best use of the benefits that we can while avoiding some of the, the risks and the pitfalls that are really education are really feeling from, from generative AI today. I love it. I love it.

Now, you know, in my, looking through my notes here, we, there was this phrase, building AI that works for educators, not just for algorithms. Yeah. I hope we're not just building stuff for algorithms these days, but something tells me we are right.

A lot of times we, we just do things because it seems to fulfill a particular formula. Yeah, that's right. Yeah.

And you see, um, I think there's a lot of places in, in education, both more on the informal sort of business to consumer side where people self-select to do something to, to make them better. Um, but also in the, in the formal side, you know, we, we see a lot of use of education that, that really, um, I would say is, is about almost circumventing what education is, is trying to do. Um, so if you, and, and to have that debate, I think in, in the right way, you really gotta start having a debate on what, what does it actually mean to learn?

And it's something I I thought a lot about in the last seven or eight years, right? To for, because learning, we tend to think of, if you, if you wanna learn something, you gotta do it a lot. And, and that's of course true, but, um, but what we forget in that, uh, way of describing learning is that, uh, you've gotta do something for a long time, and then you've gotta have the time to reflect on, on what it is you you've done.

And without that reflection, you very rarely have, um, actual learning occurring. So you might be trying to ride a bike, ride a bike, ride a bike all day long, and then you take a break and, and you can't really explain what's happening inside of your brain. But the next time you try riding a bike, you've, you managed to aggregate and associate some of the experiences you've had, and now you are better at riding that bike.

And, and suddenly, of course, it will click in a bike, in a bike case. But, but for other things, you've really gotta go back and reiterate that, do something, do something, do something, and then reflect, reflect, reflect. And what we see in education today is that a lot of the, the reflection are happening by way of, um, essays.

And so we see, uh, teachers passing information onto students, asking them to reflect on something in an essay or in front of a classroom or online is in, is increasingly happening. And then what happens there is that that reflection suddenly now can be taken over by a generative ai. And then obviously, uh, teachers, uh, see that as a, as a risk students, um, very easily can get tempted by it.

We've all been young before, and sometimes we, we haven't quite prepped, and it's a normal thing to, to jump onto that. So that learning and reflection loop really gets upset by, by generative ai and forces us to rethink what, what is learning and how do we pass information on, and how do we get students to reflect? So we've taken a slightly, uh, different approach to it at, at lab for us.

Um, we are really seeing AI as both as an opportunity to create experiences for students to, to have, um, thereby prompting them to do that kind of painful, um, remodeling that happens in the neurons in, in the brain of, of, you know, you're pushing hard, you're pushing hard against something. So provide a lot of experiences. How do we support that with ai?

And then helping students and teachers reflect on those experiences, and how do we support that with ai? And if you suddenly see education as that loop about undergoing some experiences and then reflecting on it, then you can get outta that loop of being given information and having to do essays. And that that is a loop that is threatened by generative ai.

But that doesn't mean AI can't play a huge and beneficial role in that loop. And that's kind of how we're trying to apply it. How do we make more experiences and how do we make students and teachers reflect on those experiences?

And in those cases, when you cast it like that, AI can be a, a huge, um, uh, yeah, a huge power play for everyone. I, I agree with you. You know, right before I got on to record this interview with you, I was over on our other set in the studio here mm-hmm.

For our tech strong gang show. And we were talking about a recent, uh, report from Microsoft. Yep.

About, you know, over not being able to turn the off button on a lot of digital workers, especially, especially those of us working from home and so forth. You know, it, it re it's reaching crisis proportions where we're just, we're always on, and there is no time to reflect, and there is no time to learn or at least contemplate, right. You're working on a problem, and it's sort of information overload, right?

We're being constantly bombarded with information interruptions and, and so forth. And how do we, how do you, how does one learn? How does one make rational decisions without the time to reflect and, and kind of, you know, compute, if you will, what, what's the right thing to do?

Or are we heading to a world where humans don't do that? Our AI will do the reflection for us somehow, and just tell us what the answer is. I hope I'm not alive for that part, But I don't want to live in that world either.

Alan and I, um, I've got four kids that I'm trying to raise for my wife, and we see the interruptions, uh, the challenges that you're describing. We see them firsthand. We see it in their friends, we see it in our own children.

And that constant battle of how do you get a moment where your children or other children can reflect on, on the experiences they've had where they're not constantly interrupted. So we don't see, um, and, and this is, this is sort of a, a little bit about lab as well. 'cause we don't really see our role as being about constantly being in, in, in the face of a student or constantly demanding a student's attention.

We see it as a natural part of a qualified teacher's loop to say, how do I now create some experiences for my students? How do I assign those experiences? How do the students do those experiences?

And how do we reflect on them, um, together? So we are not driving for microtransactions and, and, and pushing hard to, uh, compete for, for attention at lab. So for us, it's really about go into an environment, have that experience, and then once you've had that experience, we're gonna help you reflect on that experience with some, some feedback.

And then we will help the teachers say, how do I reflect on this collective set of experiences that our students have had? So that is also what we are, um, uh, pushing for. And, and it, I have a personal stake in this.

As I say, it's, uh, that, that is the environment that I think students learn best in as well. The chance to really go deep on something where you're not distracted, and then the chance to really re reflect on that. Agreed.

Agreed. But you, I, I think it's important and, and you hit it. That's how people learn.

And if, and if we're in the educator business mm-hmm. Right? Where LTA clearly is, we, we, you know, that's the game, that's the goal here, to teach, to educate.

Yes. That's fine. And that's part of that education thing.

And, and you know, though the world is changing and like the sand is shifting beneath our feet. Yeah. I think we need to remember those, those things.

Yeah. Um, I wanna turn a little bit to ar, or not ar, excuse me, vr. Yeah.

Obviously AI is again, having huge impacts there, right? In terms of creating, well, your, your background was in the gaming world originally. That's fine.

Yeah. So you, you know, from this, right? But creating our environments, creating, you know, these VR labs that you guys are doing.

Yeah. Yeah. I gotta imagine AI's making that a little easier.

No, Well, that's exactly it. And, and this is really the first part of where we see AI playing a, a huge role in, in, in learning in general. But certainly for Laber specifically as well, we've obviously, um, you know, to align with the interest of, of our customers.

We spend a lot of time working with instructors, working with teachers to really understand the, the challenges they face. And then we try and we want to go and build content for that teacher group, which means that we have to have trusted, educated educators on, on our team as well. So we do.

So we have the scientific experts, we have people that come from academia, because otherwise we can't really understand the customer we are delivering for. But what we found, of course, over time is creating these kind of immersive experiences that are really make the student reflect and, and aren't just skin deep, but, but really allow the student to explore an area that is a, that is a resource intensive thing to do. And what we're trying to do is to say, how do we keep the scientific experts, um, at the reins and holding the reins of this process, but support them in some of the, the rote work that's happening and some of the, um, some of the heavy duty creation work that they gotta do.

So we're trying to build new pipelines, so that, that's what we're doing right now, is to build new pipelines. So we really have a couple of break points to say, okay, so we've had some AI support on X, now let's get a human expert involved. It's the human expert that reviews it.

It's the human experts that signs it and puts their name on it and says, I believe in this, and this is scientifically accurate. And it's aligned with the curriculum that, that the students are about to go and face. So for us, the creation of content isn't something we want to hand over to ai, but it is something where we really see AI playing a role as long as we keep humans in charge.

And it's a little bit of a reflection, Alan, on, on the learning bit, uh, as well, right? Where for, for you to learn, that doesn't mean that AI can't be involved, but you've gotta raise your abstraction level to now think in, in larger bits. And AI can play a role in amalgamating and synthesizing those larger bits, but you've still gotta do the thinking on top.

And that's what we're really tasking our academic experts with, is to say, okay, how do you remain in charge of this content creation? How do we make sure you feel convicted that what we're shipping out is something we're proud to put our name on, but at the same time enable you and empower you with all the tools that's happening? So yes, both on vr in eim and in our digital environments in Lab, we see a, a, uh, AI play a role in content generation, but not untrusted, not unguided, just steered and held working for us and working for our human experts.

Think you, Aren is something there beyond, it's, it's important that we remember this is a tool that's right. It, we can't, we can't lose our ability to think and reason by, by abdicating that to, to, to ai. Right.

Otherwise, we'll wind up in a world like that Wally Walleye Yeah, that's right. Kind of movie, right? Where we're all fat people walking around on those server chairs playing, you know, our games or what have you.

Yeah, yeah. That's right. You know, gotta keep people thinking.

Yeah. And so you're right. And so exactly that, and that is true in general as well as in in education, right?

And, and we're seeing some of the, you know, there's early research now, it's not quite gone through peer reviews yet. Maybe the studies aren't as big as we would like them to, but there is early research now that indicates some of the critical thinking that we really want to engender in our students. It does go amiss when you, when you just lean back and let AI take over.

And we kind of know this intuitively, but it, it is clear and it is it, you know, we can see it in the, in the data as well. And so, I I, we all see this at work too. I, I've seen some amazing output that has been steered and, and by a really smart individual who has used AI like a tool.

Um, and I've also seen, um, some absolutely AI slop come out of somebody that's just lent back and said, wow, we can let AI do the bit. So I think in both education and in the real world, allowing ourselves to, to not critically think is a huge danger. And so for us, it's now a matter in education.

And outside of how do we raise our abstraction levels above what the AI can do for us, and start thinking about this as larger chunks that still have to be critically analyzed, still have to be critically, you know, questioned, are these the right things, but then can be composed as bigger blocks. And that's kind of how we are thinking about, uh, content generation in, in lab that we have bigger blocks to play with, but we still gotta leave a human in charge of composing them and validating them and feeling convicted that it's the right thing to do. Agreed.

Hey, we're outta time beyond, you know, I feel like we barely scratched the surface here, but Yeah, that's right. It's okay. It's 15 minutes.

It goes quick, man. There's only so much you can cover, but hey, one more time for people who want to head over to Lobster. com.

Dot com. There you are. That's exactly right.

Bjorn to Mattis Madson, uh, chief Product Technology Officer at Laber here on Techstrong tv. We're gonna take a break. We'll be right back.

Hey everyone, it's Alan Schmo. We're back here at Tech Drunk TV, covering Black Hat on the show floor. We hope it's not too loud, but this is the first video we're doing since they opened the floor.

So it's probably a little louder than what we've done today. We're here at the booth of a company called En Enable. Let me show you how that's spelled N dash A-B-L-E-N Enable.

You get what it says though there. Let me introduce you to Robert Johnston and Vi Vikram Rakesh. Ramesh Ramesh, we tried, let me say that again.

Let me introduce you to Robert Johnston and Vikram Ramesh, Robert Vikram, welcome to Text Drunk tv. Robert, we're gonna start with you 'cause you have the mic in your head. Give people a little bit of your background, what you do at Enable, and how you got here.

Yeah, absolutely, Alan. Thank you. Um, so Robert Johnston, I'm the general manager of the Ad Lumen Business Unit, uh, here at Enable.

Uh, ad Lumen was acquired by Enable in November of 2024. And we, uh, spearhead the managed detection and response and extended detection response product line, uh, here at, at enable's broader cyber resiliency platform. I'm a security practitioner by trade, an engineer by trade.

Actually, I was the original founder of Ad Lumen. And, uh, and, you know, we built that business over the years and I, I spent about eight years in the Marine Corps doing mostly cybersecurity intelligence type work, brief stint at CrowdStrike, and then, and then founded, uh, at Lumen in, in 2017. And it's been a great ride.

And now we get to, to, you know, accelerate the incredible journey that we had, uh, at Ad Lumen under the Enable umbrella, uh, into, you know, their customer base worldwide. Fantastic. I've, I've been down that road as a founder who sold my company and then helped stayed on and helped build it all the way through to IPO.

So I I know that journey. Yeah. Yeah.

And it's a journey. It's a great ride. And there's so many exciting steps along the way and, and to see the product grow, to see the company grow, and then now to see Enable grow as well.

Uh, it's a, it's an amazing experience. We're doing such great things in the marketplace and I can't wait to talk about 'em today. We're Joe, we're gonna talk about it, but first let's introduce Vikram.

Thank you Alan. And, uh, great to be here with Techron tv. Uh, Vikram Ramesh, I'm the Chief Marketing Officer here at Enable.

I joined Enable through the Ad Lumen acquisition, where I was the CMO at Ad Lumen as well. My background is about 25 years in cyber. I'm also a security engineer by trade.

Uh, but I went to the dark side, or depending on who you ask, I came from the Dark side. I went to the Dark Side Uhhuh. My background is, uh, working at companies like Mandy and where I was A CMO, which led to the Google acquisition, helped build Google Security Marketing team.

Uh, been doing a lot of, uh, enterprise mid-market and SMB Security. Really excited to be here at Enable, where Enable is in this, uh, stage of transformation to a cybersecurity company. And with Ad Lumen and other awesome solutions that we have in place, we have a phenomenal opportunity to be that cyber resilience provider for the mid-market.

So guys, I gotta tell you, I feel right at home. I have about 30 years in, in, uh, cyber myself. That's amazing.

I started a few cyber companies. It's not often you get, you know, there's a lot of Johnny C*m. Late Lease Cyber became cool.

We were doing this when we called it security, right? That's right. And, and that's a big difference.

I'm afraid our, I don't wanna confuse our audience, Robert Vikram, either one of you give us like top down enable what they do, and then it sounds like there's been a few acquisitions in here with different product categories. Give me that. You're the CMO Vikram, we're gonna make you do this, if it's okay.

We do. Alright. Give me that overview from the top down on Enable.

Sure. So Enable, uh, originally started as an IT management and monitoring provider. So it was a spinoff from SolarWinds and they, they were an MSP business selling to about 25,000 MSPs globally.

They also have, uh, we also have a backup and recovery business that is doing, helping customers do cloud-based backups. It is a native cloud-based backup solution, help them recover in case there's an attack and manage the whole entire it. SA about 18 months back enable O Emed add Lumens, XDR and MDR platform.

And they sold the security operation solution to their end customers last year when the acquisition happened. Enable, uh, is has this vision of becoming the cyber resilience provider for the SMB and the mid-market. So what we have is a unified cyber resilience platform that helps customers manage, secure and recover their IT and security estate.

So if you break that down, uh, once they're further, we have a unified endpoint management business that helps IT teams do well management, patching, monitoring and management of all their endpoints, make sure they're up to date. And they are, they have the highest level of security. We have a security operations business, which came in through Ad Lumen, which has the XDR platform, and we offer that as a managed service.

This platform is unique in the sense that it, it is security agnostic or tool agnostic. We wanna meet the customers where they are with the tool they have to drive the best outcome. So we outta the box, we support about 27 different EDRs.

Wow. Right. So from all the way from, uh, CrowdStrike Falcon to Malwarebytes integrate with environment and provide value as an XDR and MDR platform.

And then we have a data protection business, which I call as backup recovery. But what we are actually doing is data protection, right? So if you look at the Lifecycle Protect endpoints, make sure there are no attacks on them in case there's an attack, get them back up and running, delivering resilience across every single stage endpoint.

Resilience, security, resilience and data resilience. That makes our end, end-to-end. Cyberresilience Platform's, ransomware proof kind of, uh, business, huh?

Yeah, it's important to where our fundamental thesis sits is there's, there's a convergence happening and what this company is building of IT operations and security operations are becoming one certainly in the channel and in the mid-market. Mm-hmm. And if you look at Enable as a three pillar platform, that unified Endpoint management, that's doing vulnerability, right?

It's doing patching, it's doing endpoint management, proactive security, very proactive in nature, right? You have the Data recovery Business cove, right? Backup and recovery is essential to ransomware recovery, essential to the recovery of from any security incident, right?

And then the SecOps platform, M-D-R-X-D-R, there's mail assurance, there's a, a variety of threat stopping power. And, and the three pillars we believe make one of the strongest, uh, security platforms, cyber resiliency platforms in the market today. Love it.

com? Is that the website or nothing? That's right.

Just wanna make sure we get that right. Let's talk, we're here at Black Hat AI's all over the place. Everybody's talking about ai, but black, I've been coming a black hat for about 25 years over at Caesar's Palace, if you remember in the day.

Right. What about this show kinda resonates with Enable and the various lines of business? Yeah.

The, the most significant one to me is probably no surprise. The, the, the rise in AI capabilities that are now making their way into, into every product category that exists in security. And, and the efficiencies that, that will be gained from that.

Mostly the beneficiary of that is, is the customer. When we look at the MDR business, our managed detection response, our job is fundamentally to find threats and stop threats as fast as possible. It is unequivocally true that an AI operation center, an AI SecOps operations platform can do that faster than a human being, and it can do it more accurately than a human being.

And these new capabilities are making their way into, into our platform like many other vendors here, uh, at Black Hat. And I, I think that's gonna fundamentally change the way security is implemented, uh, at at customers. It'll change, it'll, it'll be as impactful as Cloud was to the way security was delivered.

AI it will fundamentally change the way security is delivered as well to end customers. And I think that's the theme this year, and it'll be the theme probably for the next five years, are the leaps forward that, that technology makes. That's Bold.

Yeah. Who could look five years? I I, I'm, I'm lucky in two to three years, five years, it might be Quantum, who knows?

That's right. Right. But what, um, so at RSA this year, we launched our state of the SOC report that's looking at our SOC with the thousands of customers that we are supporting to see what is the experience they're having.

'cause we have AI built into the tooling before it was called AI soc and we've been leveraging it for threat hunting. Right. What is interesting is all in a production environment with thousands of customers, 70% of threat hunting and all our SOC operations are already automated ai.

Right. And now there are more capabilities that we are seeing where, how do I make my threat hunting team more efficient and more faster? They focus on the things that matter.

While the AI SOC focus on other things, I don't think it's, it's gonna replace the human element, but it's AI meets AI or how you wanna call it, but that I see is the future of the soc. Absolutely. Absolutely.

I know that the show floor just opened, but blackout's been going on now, you know, over the weekend it started. Uh, what are you hearing from people? Like from the attendees, the security pros out here?

Yeah. It's, it's, Uh, this year especially, right? And, and it's not that it's a big surprise.

You, you initially alluded to that it's about ransomware, it's about credential based attacks that keeps in increasing enable as a company is focused on SMB and the mid-market space. Yes. Right.

And we launched our inaugural threat intel report at Black ADD this year. What we've seen is it's almost been a 200 fold increase in attacks to the SMB space. Right?

Now, the attackers are not saying I have to target only enterprises. They're going down market. And Well, I I think it's because the enterprises are wise to ransomware.

They have the resources to kinda ransomware proof themselves. Exactly. Unfortunately, most SMBs don't.

Right. And it's probably the same IT person also managing security. Right.

And that's where I think you just don't have need a solution like, which is unified, which can say, you know what? I can manage across the board, still deliver the value you can while improving your posture, giving you enterprise class security at a mid-market price. Right.

Agreed. You know, when I first started in this business, there was no cyber crime. There was no ransomware and ecr, this was a game played, uh, by nation states.

Right? Now, today it's much different. Today you almost barely hear about nation states.

It's predominantly the criminal side of, of cyber that that is broken out. Well, Some nation states are doing it for the financial state. This very true.

You come to Lake North Korea, they estimate 30% of their G dt Very true. Comes from hacking. Very true.

Very true. But the, with that shift, right? Nation states typically care about hacking other nation states.

But with that shift e crime, right. What what has happened is the, the targets have shifted to the SMB in the, in the mid-market. They're just easier targets, very easier.

I think fundamentally they view them as as weaker long hanging fruit. Yeah. Which companies like ours need to make that not a reality.

Right? Yeah. And, and look, for as long as I've been in security, tell you a funny side.

I started a company called Still Secure, 2001 outta Boulder. 2007. I went to my board, said, security's too hard for most SMBs, it's just too hard.

We should become an MSSP and do it for them. 'cause we, we had something called a nack network, access control, vulnerability management, intrusion prevention, UTM, all that. And we, we bought a, uh, an MSSP and we started looking at buying others and growing organically, fundamentally, that has, that equation hasn't changed.

The SMBs just they don't have the resources to fight this on their own, Or the time or the time. Probably the most valuable asset Time's the resource. Yeah.

You got time, you got people, you got tools, people, process, technology. It hasn't changed. So, and it's always been a, uh, a solution starved market at this level.

Yep. If you look at the car customers that we support and how we sell through, we sell, we have 25,000 MSPs as customers that are servicing this market. Right.

So that's your general, that's a huge value. Right? Absolutely.

If you look at that market, they've traditionally bought IT solutions fifth, uh, with the rate at which MDR is growing, but only 25% of that MSP base is even adopting this. Right. So there's a huge upside to say, you know what, let me secure you with an enterprise class security and also give you resilience by making sure there's data protection so then you can manage it.

Right. And if you look at platformization, which is thrown about with all, every enterprise vendor out there, I think it applies more of the mid-market and SME space because they don't have the resources. They'd love to get single vendor that can give you and Absolutely.

And they've been, you know, the flip side of it is, if you didn't have that 25,000 strong channel going after, I forgot what it was, four or 6 million SMBs in the world, right? It's like herding cats to a certain extent. But when you have that strong channel you can offer, you know, to the people they're already dealing with, and that, that's a key piece of it.

And that channel is important. 'cause when you look at the SMB, you, you're talking a, a small credit union or a community bank or dentist office, that that individual that's there doesn't under secure understand security doesn't have a clue. He he does dentistry.

Right. I was gonna say doesn't understand it, let alone Security. Yeah.

And, and so they rely on that channel to be their trusted advisor, to be the decision maker that makes the right decision, that protects their business so they can get back to being a dentist or a community bank. It's funny you said this, I learned this lesson. So we became an MSSP, all of a sudden we started signing up all these orthodontists, you know?

Yeah. I don't know if your kids ever got braces or if you have kids that read the facts. Yeah.

So braces are somewhere between five and $10,000. Where I live in Boca. The kids go through two brace periods, the pre braces and then braces.

Turns out no one pays for their braces. And one fell swoop. You pay your orthodontist every month, whatever it is, I figure $150 or whatever, every orthodontist either keeps that credit card number in a spreadsheet or if they're very secure, they write it on paper.

Yeah. And some poor lady pulls out that paper every month that does the billing. We were doing PCI audits.

It's a nightmare. It's a disaster waiting to happen. And, and, but this is the entire orthodontics industry.

This is how they work. So a solution like this, it's really is a godsend to them. And what we found out is they had one IT person who's not a full-time, it's a hired IT person, an MSP, who comes in and does their it, their security, their email, their network.

And this, this is the state of art. I mean, this is what it is. And if you back it up, uh, a layer to the MSB, you have the, the, the problem where security is very much a 24 hours a day, seven day a week war.

You're not set for that With, with a very specific set of expertise that you need in order to fight that battle. And the managed service providers, they were providing help desk desktop support. They are security centric now, and they're evolving, but they're, they're oftentimes not equipped.

They need to be partner for that 24 hour a day, seven day a week war. Oh yeah. A hundred percent.

Yeah. And it's been an ev ongoing thing. Hey, this sounds like a great market.

I hope you enjoy the rest of Black hat. Thanks for coming on and, and getting us smart. A little bit about Enable.

Yeah. Thank you. We'll be talking more soon.

Yeah. All right. We're here at Black Hat at the Enable Booth.

We'll be back with another interview in just a minute. You're watching Tech Drunk tv. Hey guys.

Thanks, Withrow. We're here with Andrew Kaiser, who is VP of Sales for Huntress. And we're talking about, well, the 10th anniversary of a company that has often been at the forefront of all this push for managed services around security, ai, and all kinds of fun stuff.

Andrew, welcome to the show, Mike. Thank you for having me. You know, as you think back in time, does this cybersecurity landscape look anything like you might have first imagined or thought about?

I mean, the world seems to be a different place, but I don't know, it's then again, sometimes I feel like we're playing a big game of back to the future. But what's your take on what's going on here? Y you know, I, uh, um, so I've been in the cybersecurity space since 2010 and was at another, uh, security company prior to Huntress for about maybe eight or nine years.

Um, and back then cybersecurity was, you know, deploy an antivirus and have a firewall and you're good. And today you could probably come up with a list of 40 or 50 different, um, types of security solutions that you should have if you wanted to consider yourself fully secure. So, you know, it's a moving target, and it's something that I think every year, um, has evolved as quickly as the attackers and their methods have evolved.

Mm-hmm. It's clear that things are more complex, more challenging, and the attackers are getting access to more advanced tools. Um, can we win this game?

I mean, I feel like a lot of folks will complain, and I'm sure you hear these complaints where they're like, we keep throwing money at this, but we don't seem to be making a lot of progress. You know, uh, the, the challenge is that, um, from the attacker side, you only have to win once. So you can fail 99 times and on attempt number a hundred, um, if you get through, well, you know, you win as a defender, we have to be right every time.

And, uh, being right every time is just literally impossible. So it, it, it really comes down to, um, you know, having layers, um, making sure that you plan for, um, you know, catastrophe. But it is a, a really hard place to be.

And, you know, there is no silver bullet. So at the end of the day, it's, it's really about just being resilient. It feels like we're now in another iteration of that arms race you just described.

And this time it involves ai. Um, is this just the latest investments that we need to make? Or, and, and I guess the question I have, is security becoming a larger percentage of the overall budget, or is it still relatively even?

We just have to keep reinvesting at the same levels to ensure that we're relevant and able to fight the fight? So I think, uh, so a, a few thoughts actually. Um, so first, you know, there's lots of talk about, uh, AI attacks and, um, you know, like gender gener generative AI being used in like phishing attacks, for example.

And, and that stuff is absolutely scary as hell. Uh, some of the stuff that, that you hear about businesses that are tricked into wiring money when, you know, the AI generated CEO has sent you a video asking for that request. Like, like that stuff is really gonna be hard to protect against at scale.

What's wild though, is most organizations, and, and this is everyone from your 20 person law office to, you know, your 500 employee organization that, um, you know, has an IT team that is trying to, you know, own the security budget and the security stack. 'cause you don't have dedicated security personnel. We're talking about 99% of businesses, um, most of them are not equipped to handle the attacks of yesterday and the ones that we're dealing with today.

So, you know, I think there's a little bit of buzz going on about protecting against AI based attacks. Um, but I do think that it will make certain types of attacks, um, more prevalent and probably, um, you know, if if nothing else, it's a good thing that it's getting talked about because it will mean that there is more budget for cybersecurity programs at organizations that probably need it. One thing I do feel that has changed and arguably for the better is there seems to be less tension between managed service providers and internal IT and security teams.

And maybe they're all finally working a little more collaboratively together. Or are we finally all on the same team? You know, I, I think we're going in that direction.

Um, years ago, and this goes back to maybe pre COVID, let's say, so 2018, um, ish, there was a lot of talk of, um, this transition or this convergence, uh, between MSPs and mss ps. So your managed service provider and your managed security service provider. And I think what's changed over the last maybe five or six years is this acknowledgement that, um, most MSPs, 99% of managed service providers are not going to become managed security service providers.

They're not gonna build their own soc, they're not going to, you know, do their own threat hunting. They're going to partner with vendors like Hunts. Um, and, you know, kind of outsource that security component.

And I think that that shift in mindset also, um, trickles down to the way that managed service providers work with IT administrators and IT teams. Um, you know, having, um, um, portions of your stack, uh, co-managed by an MSP is becoming a lot more popular. Um, it administrative, uh, you know, orgs realizing that they can't do everything themselves and they have to outsource some of that maybe security to a third party.

Um, just to make sure that you're not trying to do more than you're equipped to is just becoming more normal. And I do think that there is, um, uh, a, a better understanding that this is a team sport now compared to five years ago. Mm-hmm.

I also feel like the term MSP is becoming a little more challenging to ascertain what that means. Exactly. I'm asking the question because, um, used to being MSPs, you know, they generally built their own stack and they had their own data centers in their own nos.

And now I will see people who I used to call resellers calling themselves MSPs 'cause they're reselling some sort of, um, cybersecurity platform from some vendor somewhere that is offering it as a managed service. Is there a difference in the quality of the managed services that you get? And how do I distinguish between, you know, those that are adding value by rolling some additional capability versus merely just reselling something I could buy as a SaaS app myself?

Yeah, it's a great question. Um, I do think that there is a lot of, um, a lot of value for an organization that resells products to try to, uh, pivot some of their business to reoccurring revenue. So we have seen, um, you know, organizations that would traditionally resell products, um, try to kind of dip their toe into that managed component and, and convert some of that revenue into reoccurring revenue.

Um, but you know, you said it, there is a big difference in value between reselling a service that somebody else manages and, you know, maybe checking some boxes versus all of the expertise and the bench strength that your, you know, true play MSP has. So, you know, again, for years, um, there have been vendors that have talking about how the, um, you know, heck, it started with the, the transition to the cloud was gonna put MSPs outta business. Well, hey, MSPs are here.

The cloud's been around for a while, they're not going anywhere. Um, and I think that as technology evolves, as security evolves, that, um, you know, managed service providers will evolve as well and figure out how to make sure that the value they're adding is value that, you know, organizations can't get without having that expertise, uh, from outside of their own organizations. So from where you sit, what does the next 10 years look like?

Because you'll hear about how the internal teams are gonna use AI agents and the MSPs are gonna use AI agents, and maybe my AI agent will call your AI agent and you, and I'll meet for drinks at five, and that'll be that. So, uh, you know, no matter what my prediction is, it'll be wrong. So I'll, I'll, I'll, I'll start off with that.

Um, I'll give you maybe our take on AI first and, and then a bit maybe of, of where I think, um, the industry will go. So, uh, hunt does not think that AI is going to overtake, um, the job of the really smart security analysts that are doing the threat hunting and the, the, you know, looking for the, the needle in the haystack. So we have no intention of replacing our soc, uh, the security operations center with AI agents.

Um, we definitely are looking at some interesting use cases of how we can use AI to make those people more efficient, um, to make their jobs easier, to make it easier for them to find that needle in a much bigger haystack. And I think there are some cool use cases there, but at the end of the day, at least with security, uh, you know, I, I think that when, you know, put yourself in the, in the business owner's shoes on the other end of, of the attack, uh, who is calling up their security partner on the worst day of their professional life and asking for help, if the person on our side is an AI agent talking to that business owner that's trying to figure out like if they can continue to operate this week and make payroll, if, if you're talking to an AI agent, you're looking for a new security partner right away. And I think that there is some truth to that, even when you consider non security.

So just in managed services and, you know, what's they do for small businesses, um, I'm sure that there will be places where you can, um, uh, you know, be more efficient with the use of ai, but it's gonna be hard to replace that human component of the relationship that, um, you know, small and mid-sized organizations just really love. Mm-hmm. You know, you run sales, so if something goes wrong, it's always your fault, but Yes.

Are there, Are there things you wish more customers would do to become savvier about working with MSPs to kind of make this thing a little more successful in a way that maybe, maybe not guarantee, but not with as much risk either? Huh. That's a good question.

Um, I think that a lot of, uh, businesses, um, you know, probably don't put enough thought into all managed service providers are not created equally. So, you know, again, going back 15 years when, um, security was really just, you know, install antivirus to play a firewall and, uh, you know, you're now secure, um, there are still a lot of managed service providers that are deploying tools, um, promising that they are managing those tools, tools and, you know, kind of, um, uh, using hope as a strategy that nothing goes wrong. So I do think that it's challenging for your average organization to, um, you know, qualify and, and understand, am I working with a managed service provider that actually has a, um, you, you know, a real security practice and, and works with, uh, best in breed vendors and, you know, has an incident response plan for, for that day when everything breaks and, and eventually does go wrong, versus the one that deploys the tool, um, and collects the monthly bill and, and, um, you know, hopes that that will continue to go well for them.

So it is a, a challenging, uh, thing for the, the, the end customer to make sure that they're working with a provider that really has a plan put together. Um, As you kind of think about the future of cybersecurity, um, is it gonna get melded more into the management of IT operations or will it always be a distinct category? 'cause you know, there's always been a shortage of cybersecurity expertise, and it seems like we're trying to deputize everybody, which is a good thing.

'cause now everybody's responsible for security, but does that mean if everybody's responsible, nobody's responsible? Yeah, that's a fair point. Um, so at Tres, for example, um, we knew from day one that we didn't want to build solutions for the 1% of companies that have dedicated security personnel.

So our target market has always been the other 90% of, or 99% of businesses that do not have dedicated security staff who you could literally give them some of the really expensive and fancy endpoint security tools and they just wouldn't know what to do with them. Or if they deployed them, they wouldn't know how to manage them. So I think the, the place where you, you know, it's kind of changing is that organizations are starting to admit and realize that just by buying a tool and checking the box that you have it on a cyber, uh, cyber insurance policy is not enough.

And if you don't have the resources to manage those in house, which most organizations do not have and will not have that, you have to have somebody doing that on your behalf. And whether that's a vendor like us, um, you know, somebody else that is offering, um, you know, the, the management of somebody else's technology, um, or you outsource it to some other organization, it, it just isn't enough to deploy tools anymore. And I think, as you mentioned earlier, the, the threats and the, the security landscape is getting more attention to the media, um, especially when it, you know, ties to the AI buzz, um, that just makes, uh, you know, the business owner is more, uh, in the loop of, of how big these risks and challenges are.

How do I evaluate one managed security service provider versus another? Because a lot of them will say the same thing, and then eventually people get a little frustrated and they're like, well, we'll just pick the lowest cost one. How do I know which one is, um, you know, better in a way that I can make some sort of qualitative assessment?

Yeah. So, um, you know, first off, you mentioned, you know, kind of picking the lowest cost one, I can almost guarantee you that picking the lowest cost one is not gonna be the one that you should pick. Um, so that's an easy place to start.

Uh, now that's not saying go for the one that's most expensive, but, um, you know, the same question could be asked about MSPs or, or any sized organizations that are looking at a vendor like interest that's gonna be, um, a security partner. And, you know, there are so many vendors out there and so many MSPs out there that will recycle the same messaging and, and tell the same stories. My favorite thing to do when we enter one of these conversations is, um, you know, tell them to ask their peers.

So, uh, go in the community, ask your peers, ask your competitors, um, find out, um, you know, what was it like when things did go, um, bri and, and s**t hits the fan? And, uh, you know, get, get some stories that are not from the vendor. I mean, listen, if, if you ask me as a vendor, as a VP of sales for a, for like a recommendation on, on a referral, I've got a hundred people that I can refer you to.

But if you go in the community and you ask for real life stories about what it's like working with a certain provider, you will get awesome feedback about, you know, the good, the bad, the ugly, and everything in between. Mm-hmm. Um, one of the things that does come up frequently is, um, what is gonna be the, the role of the MSP going forward, how much of it will be managed as a service, particularly in security, because there is a thought process that says, look, I'm never gonna have enough people to manage this myself.

Never gonna do this properly. So maybe this is not core expertise and it's not differentiated value. So maybe the whole thing should just be run as a service.

Maybe. Um, you know, I'll go back to that transition to the cloud example I gave earlier. Um, I mean, heck, how many years has it been since we've talked about how everything's moving to the cloud?

It's gotta be 15, 16, 20, almost. Um, and you know, back then there was this talk of how MSPs that don't embrace the cloud are gonna be gone. And, you know, now, 20 years later, I think we can agree everyone's embraced the cloud.

It's part of most of the solutions that we, um, we interact with. But, uh, you know, most businesses are still here. The ones that, that are, uh, you know, providing those services are still here.

So with security, uh, and, and MSPs, I I think that things will absolutely change. Um, you know, I think that budget will start to transition from the endpoint to the identity. Um, that's something that I think we expect to happen a lot over the next few years.

Um, but at the end of the day, there will never be enough security personnel to, um, staff and, and work at these small and mid-sized organizations, you know, the, the 99% of businesses that can't do this themselves. And unless that changes somehow, I, I think that, um, um, this industry will continue doing quite well. All right.

Last question. You've been around here 10 years now. Congratulations on that point, by the way.

But thank you. A lot of security companies have come and gone since then, and every morning we wake up, there seems to be yet another acquisition. So, um, do you think people need to take into appreciation the longevity of a company and say, Hey, there's something to that that adds value?

You know, I, I like to think so. Um, biased since we've, um, you know, now got 10 years under our belts, um, you know, for us, maintaining independence has been one of the most important things from, from day one of, of, of, of, um, you know, getting to know the founders. And, um, that can only happen if you're growing and, um, you know, kind of making sure that you're building a healthy business that the investors will kind of stay out of.

Uh, I I would like to think that we know how to build a security business and, and keep our customers and partners safe a lot better than any kind of venture capitalist or private equity firm. So for us, you know, we've raised hundreds of millions of dollars and, um, it's always been important that that money does not come with, um, somebody telling us how to build our business and keep our customers safe. So, uh, to answer your question, yes, absolutely.

The longevity, the, the track record, the growth, um, is important. And for us, it's been one of those things that's been a differentiator since we've been able to kind of call the shots and write our own roadmap and, you know, make decisions that aren't always popular with investors, but have, um, helped us build a really healthy and fast-growing company. All right, folks, you heard it here, hunters, it's entering its teenage years, so let's stick around and see what happens in the next decade.

Right. Awesome. Andrew, thanks for being on the show.

Appreciate You having me, Mike. Take care. All right.

And back to you guys in the studio. Welcome back to the six five Summit. In this cybersecurity spotlight, we're joined by Mark Vanderhoff, CEO of Mimecast, to explore how AI is reshaping the threat landscape and what it means for the human side of security.

From precision phishing to generative AI risks, we'll dig into how organizations can reduce complexity, manage human risks, and build more resilient defenses. Mark, welcome to the six five summit. Thanks for joining us.

It's great to be here, Danielle. Thanks for having me. Um, so you're, you know, you're pretty new in the role.

You just took over about a year and a half ago. Um, you know, quickly before we, we, we dive in, sort of what are your kind of early, often observations? Uh, I know you're, you're a veteran of the industry, but just since joining mcast, uh, MCAST is a fantastic company.

I took over for the founder who was here 21 years. We have 40,000 customers around the world approaching a billion dollars in revenue. Uh, but like with anything you take over from someone who's been 21 years, uh, Peter, the founder's a good friend of mine, but definitely some things that you, uh, you get a chance to remodel, fix up, redo the kitchen, move a wall, redo a bathroom, like, like moving into your parents' house.

So it's, uh, it's, uh, it's been an honor to move into, into that house and, and do a bit of remodeling, but, uh, on a very, very, uh, great foundation and, uh, and pivoting the company in a very exciting direction. I think. Well, as a founder, I know those, those goals that you're targeting, uh, are, are really significant.

And I know sometimes trying to take over for a founder is maybe a somewhat impossible job in some ways, but of course, seems you're gonna bring a lot of great expertise and get to that billion, that's such a big milestone. So congratulations on that. We'll be watching that.

So let's talk a little bit about, you know, AI and its, its impact and transformation, um, in the cybersecurity space specifically, how are you seeing AI reshape it and what do you think that means for organizations today? What I love about cybersecurity is you have competitors and customers in any SaaS space and in cybersecurity you have this third variable, which is the hacker. So I would just point out, first and foremost, before we all, uh, all, all the cool cyber folks and MBAs and the podcasters and the like of the world, uh, started using ai.

The hackers were using it. The hackers always use the technology first. In fact, criminals going way back, always pioneer technology.

So you remember, I mean, one of the businesses were in, were in human risk. Were we're in insider risk, we're in email security. Remember the old email you got from the Nigerian prince with grammar errors and, you know, using British English, if it was even spelled correctly as opposed to American English.

Now, you know, those hackers can make perfectly crafted emails using AI that target you specifically. And of course, with a little more research, they know what country club or golf club you're a member of or where you like to hang out, and they tailor it perfectly. So the first thing to remember is hackers got to it before we all did with our clever, uh, approaches to using ai.

And then on the defense side, cybersecurity for sure we're, you know, seeing lots of opportunities. I would say to keep it simple, there's two areas that I'm seeing us use it. One is, is in improving detection.

So we can detect, for example, things that are written by AI engines. We can detect, uh, people using shadow AI or using the wrong things. Um, and then the second is for productivity.

Like all these cyber products are pretty complex. Any software product's complex, we, you know, uh, give people kind of assistance on better using the product, being more productive using the product, spending less time on alerts and false positives, false negatives, all that stuff in the product using ai. You know, you said something profound, but um, there was a time in the past where someone of decent intelligence could sort of look at that email and be like, eh, that just doesn't look right.

Um, and I know that there was always a continuum of who could be duped and who couldn't. And obviously some of that was about technical knowledge. Some of that was about, um, you know, experience and awareness.

Uh, we've seen it hit next level. I mean, look, even, even me, uh, someone who has a lot of technical depth, mark, you know, at times I forward emails sometimes, or I'll screenshot a picture of one and be like, this looks like a real DocuSign and it looks like it's from someone that we do business with. I'm like, but there's just something that smells off about this to me.

And I can't tell you how many times our, our cyber team has come back and been like, good thing you didn't click that. Don't click that. Um, they've gotten a lot better.

But in the end, you know, most of breaches are still human error. It's like 95%. Um, what are you sort of teaching?

'cause, you know, giving the technology, I think this has a lot to do with kind of zero trust architectures, is that if we trust nothing, it reduces the chance for humans to make mistakes. And then you kind of have to validate everything. But we also know there's a push pull on how efficacy that is and how efficient that is.

Um, but you know, so overall kind of what do you recommend with, now you have ai, everything's gonna get harder. Like you said, the English is better or whatever language is better, things look more legitimate. Um, and once you click that wrong thing, it's hard to turn back.

I mean, it, there's not a lot of room for error. Yeah, yeah, yeah. I agreed, agreed.

Daniel, um, hackers don't break in, they log in. That's kind of the mantra of, of our strategy here around human human risk. And so there's been so much cyber technology layered into the infrastructure, into the technical, uh, aspects of every company's infrastructure.

But the end of that, the end of great network security, endpoint security, application security, identity security, app application security. You have a human, an employee still sitting there, millimeters away from the keyboard of mouse, and they're gonna do something. They're gonna click on the email, they're gonna open the attachment, they're gonna do something untoward, sometimes malicious.

By the way, I mean, I keep thinking about, you know, our current government employees without trying to get political at all, but how many disgruntled employees are there in the US government right now who may not be exactly excited about their employer and what's happening? What, what may they do in that situation? So I think you have to think about disgruntled employee, uh, the careless employee or the one that just gets owned by the hacker.

'cause the hacker's so good. And what we're doing is, um, you know, also leveraging AI in that is I think the days of sitting down and watching an hour long awareness training video are over. But what we can do is real time, insert a nudge, insert a block, insert a reminder to someone saying, Hey, you know, you shouldn't really be moving that source code into your personal GitHub.

I mean, I know you might think that you own that 'cause you created something so cool yesterday, you know, but it's company property, or you shouldn't be clicking on that email, or you shouldn't be using that kind of language in Slack teams and Zoom, right? There's, uh, there's just ways of kind of tuning the behavior with reminders. Sometimes with a block, sometimes with a smack on the wrist to tell those employees, you're taking risk that is not matching what the company would like you to do.

And here's just some reminders or blockers or corrections, uh, that make that much more difficult. And I think once you do that a few times, we always say that 80% of the risk is from 8% of your employees. It's just you don't know which 8% they are.

Once you can measure the employee risk, start to train and nudge them and then block it when it still happens, you're gonna improve your posture a lot. I imagine AI, by the way, can figure a lot of that out if it's sort of tracking the behavior. I still remember the old, um, Marissa Meyer coming into Yahoo and v VPNing and tracking everyone's activities.

And I know everybody was super unhappy about it. But you know, when people are working remote and you know, nowadays the way it sends it, there's so much BYOD, we're moving stuff between our devices, we're running work applications on personally. I mean, even to your point, like having that kind of nudge that hey, like you probably aren't even aware, but like, you really shouldn't have this app on this device 'cause it's not being, you know, there's a lot of easy opportunities.

And I think the way you have that 95%, then you have that 80, 88 rule that you kind of talked about is kind of a snowball effect of the way technology is diffused these days. 'cause very rarely are employees on like, just one work device. It's, you know, we all have an iPad or a a, our own laptop and a Mac and a company, a phone, and, um, it just creates so much opportunity.

Yeah, I think employees, I would say, you know, we're thrown around our percentages, but a large percentage of human error is not malicious. Right. Most employees, even honestly, when they copy that source code over, or a couple of addresses 'cause they wanna keep in touch with that customer even after they leave the company, they're not thinking of that in a malicious way.

Um, you know, but, but, but it is against company policy. It is, you know, in, you know, violating your intellectual property, the safety of your intellectual property. So usually a reminder is enough.

Again, some people are really out to get their employer, uh, and for them you need to take, uh, you know, to be a little harder. But, uh, yeah, people, I think to your earliest point, the definition of privacy is, is slipping and changing in our society. And I think people are much more comfortable and understand that they're, they're gonna be watched a bit, uh, by their employer, by, you know, by even more than that.

But I mean, people are getting watched all the time on, on an on, uh, Instagram and all these apps that they're using. So they're kind of used to, people will be taking a look at what they're doing and giving them a reminder when they're doing something weird. Yeah.

You gotta kind of assume these days that you, we, we all sign all these terms and policies and don't read 'em. We've pretty much, granted, you know, I was having a good laugh, uh, just recently with my wife about, you know, just the ads that we get fed based on, I didn't talk to anybody about this, but it was like, I was in this place and I tried clothes on and I'm getting, you know, it's like, it is so precise. And I mean, to that point, I mean, AI is, you know, if I'm reading the room right, mark, I mean, in your space, AI is just sort of a, it's like a turbocharger.

It's an accelerant, right? So everything not just kind of like the language and stuff, but just volume, right? The volume of which they can attack is also exponential.

Yeah. Volume and accuracy. And, you know, if you wanna get into, uh, the extreme version of that obviously is the deep fakes and those types of attacks that are taking that to a whole new level.

So, so let's talk a little bit about like governance. You remember when chat GPT came out, um, there was a couple of companies that apparently had, there were some great stories about, they literally had like fed some of their best data into chat GPT, like company strategy docs and stuff to summarize that. And, and, and this was a great example of like super proprietary company content that got dropped in.

And I'm sure small businesses do it all the time, don't even think much. They're like, this is such a great tool, I'm gonna use it to help me write, I'm gonna use it to help me summarize. I'm gonna use it to help me create.

But they didn't have enterprise, they didn't have anything sort of, you know, any partitioned off. It was just literally using the public application. Yeah, I mean, that's just one example.

So, you know, you, you have accidental data leaks and, and generative AI that certainly opens the door for some attacks. You, you know, you have model injection, you know, where people can do things to models to, to mess them up. Um, we saw the early days of bots that were created and then hacked.

You know, people created this. I mean, there's so much going on, but like, if you're a ciso, how are you thinking about kind of creating governance and ethical use? Because you want your people using app.

Like I think companies that don't have their people using AI are putting themselves at significant risk of falling behind, but you need 'em to use it intelligently to, you know, so what's the CISO policy strategy that Mimecast is recommending in, in you? Yeah, I think a lot of it is actually quite similar, even though the technology is so much more advanced and sophisticated, the CISO policies we recommend really are the same ones we recommend around data security generically. So anytime you are using a cloud provider and you're gonna put data in the cloud, you're gonna ask a whole bunch of questions.

And also the policies around shadow it, right? So, um, for years, uh, we've been, we've been obsessed with shadow IT often because we're worried that people are just gonna be spending money with corporate credit cards. You know, boy, this is, I need Canva to do my job, so I'm gonna swipe a corporate credit card.

Before you know it, a thousand people have Canva or Splunk. Back in the old days, they would, you know, put Splunk in place. So I think those two mindsets of, of data security and shadow IT governance are kind of what you need to combine for ai.

We have a product that detects usage of AI during, to your point, not just chat GPT, but the week that we had deep seek, we saw in a number of our customers that their employees, I mean, deep seek, right? They were taking confidential client documents up to deep seek just to see how good it was, and it was experimenting with it. So that's shadow it, and that's a data security violation.

So what we recommend on the data security side is you need to ask, uh, the usual questions of your, uh, provider, your AI provider, what are you doing with the data? Are you training the model? Is, uh, is the stuff that I upload, uh, gonna be kept in my domain or shared broadly?

So it's all those data questions. And on the shadow IT side, you need a product like the one that we have that can detect the use of shadow. It can block it if you say we're using chat GPT, but we're not using deep seek, you gotta be able to enforce that with a nudge or with a block.

So I think those are the two policies that, um, you don't really have to reinvent the wheel on this, you just have to apply them to this AI problem and enforce it because it is more viral than any other shadow IT problem I've seen. Yeah, it's, it's sounds like it's really substantial and, you know, there's been a lot of kind of companies getting value from tools that they invest in, and a lot of work has been done to help adoption mark of tools that companies invest and buy for their enterprise use. There's a little bit of that turning that on their head.

You know, that whole idea is like, how do we make sure people are using things correctly? And, you know, the idea of basically kind of prompting people along that's like, yeah, you shouldn't, don't download that, or, Hey, don't, don't, you know, run that application on this piece of hardware. Um, this stuff's important because like I said, I think don't know is probably one of the biggest challenges here.

Yeah. Uh, your point about the small number of malicious, those people are gonna be very creative and they're gonna try to work all around and up and down your software. Um, but the ones that are doing things by mistake, that can create huge vulnerabilities.

Hopefully those are the ones that you can move along. Um, let, let's kind of wrap this up, mark, with a broad question. You know, if, if you're a, you know, a board of directors or a CEO, maybe you're not even in the tech industry, maybe you're in manufacturing, well, every company's a tech company now, but you know, the, the tech isn't your every day.

You're not waking up every day thinking about tech and ai. Yeah. You know, what are you, what is the kind of best piece of advice that you're giving to organizations to navigate all this complexity?

Because it feels like it happens so fast that it just feels almost impossible to ever be out in front of this. Yeah. I guess my mantra lately has been on all these fronts is focus, focus on the people, focus on your people, focus on the humans, even when it comes in our company, to adopting AI across a function so that we become more sophisticated.

Forget in our product. Um, a lot of people think that's a technical problem. It's a human problem.

If, if, uh, you wanna hold a department to start coding with AI or doing customer support with ai, doing marketing with ai, a lot of that is a human issue, not a tech issue. How do you train them? How do you make them understand the risks?

How do you get them productive there and not feel threatened by it? Right? Let's face it, most employees out there right now are super scared.

Their job is about to be lost to ai. We have this conundrum that we're doing to, to our employees and expecting them to fall along. So I sat down with my amazing head of human resources here, and I said to her, I said, don't forget this AI thing.

You probably think it's a CIO problem. It's an HR problem. And I think the risk is the same way.

Focus on humans when it comes to the risk. What is the human risk? Again, people are not breaking in, they're logging in through the humans that make mistakes or are malicious, and they're taking the data by logging in, uh, and, and moving laterally.

So how do you train your people or secure around your people so that they don't become the point of entry for hackers leveraging ai? Mark, it was great chatting with you. There's been so many conversations about it.

I'm glad you brought up the human challenge because frankly, this is gonna be one of the most profound times. I, I stay optimistic. I hope you do too.

That with ai, we will see growth of productivity. Every industrial revolution in the past has created more jobs. I've never seen such a kind of confluence of impact where you have both blue collar, white collar knowledge, entry level advanced roles, all kind of being somewhat targeted at one time by technology.

But I hope it raises the sort of human, you know, uh, you know, the human capacity, the human uh, condition into identifying and finding the next big opportunity of growth. Um, it's, it's an encouraging time, but it is definitely going to be interesting. It's, uh, I'm optimistic, but as a cyber guy, I'm also paranoid.

And it was great to, uh, discuss all this with you, Daniel. It was really great to talk to you, mark. I really appreciate you joining us.

Let's have you back on the six five very, very soon. Thanks for joining me here at Summit. Alright, everyone, big thank you there to Mark and the Mimecast team for joining us.

As AI continues to drive both innovation and risk is clear that empowering people and understanding their role in cybersecurity has never been more critical. Stay with us for more insights here at the six five Summit. Welcome back everybody to this six five summit.

We're in our sixth year here, and we are talking about, uh, making AI work, uh, for the businesses and even the end consumers. Uh, you probably know this already, but you are in the intelligent edge track here, a track dedicated to networks, infrastructure, realtime systems, uh, powering AI at the edge. I am joined today by Justin Hotard, president, CEO of Nokia from Finland, by the way, for a timely discussion on what it really means to build secure and high performing AI ready networks.

And, you know, we talked a lot on the show about, hey, there's so much talk about GPUs and compute and memory and storage, but in the end, if you can't connect all that together, data centers together, enterprises inside, um, it's pretty much for Naugh or it's radically inefficient. Welcome, Justin. Pat, it's great to be with you today, and thanks for having me.

Definitely, definitely. Uh, I love the background. I love that you're broadcasting, uh, from your, from your headquarters here, but let's dive right in.

Uh, you've talked about trusted high performance connectivity a must have for ai, obviously. I agree. Um, but can you provide, uh, maybe break down on on why it, it, it is such a big deal out there based on what you're seeing technologically or what your customers are talking about?

About? Yeah, so I think first of all, I'll, uh, I'll start with the, you know, the distribution of networks. If you think about where AI data centers are being built today, uh, they're being built in new locations, right?

We're seeing lots of news about large data centers being built in, uh, in, in new markets, in, in some cases in new countries. You know, there's discussions. The latest discussions coming out are around these concepts of AI embassies.

And what this means is that our transport networks need to be modernized and scaled to support this demand because we're talking about incredible bandwidth. And in some cases, we're not actually keeping the data and the compute in the same locations. In some cases, the data and the computer's separate.

Uh, and so even in those cases, latency starts to matter as well. And so as we think about this metro, Metro networks, l long range transport networks, all of these need to be upgraded. And that's where, you know, we're seeing a huge, uh, increase in optical to, uh, demand and our frontend routing demand, uh, great growth opportunities for, for Nokia.

Then when you get inside the data center density, right, we're talking about, you know, NVL 72, if you're, if you're talking about an NVIDIA system or 144 GPUs in a, in a rack or two racks, you know, this goes back to some of my experience in supercomputing in the past where we were putting optical networks in to, uh, to manage all that data and handle all the density that we're building inside the data center. Well, that means new technologies, you know, pluggables, id, you know, new technologies for photonics inside the data center as well. And then the last one, which is coming is gonna be, uh, AI and mobile networks.

And that's gonna drive, uh, new, new bandwidth requirements, new latency demands, and that will require innovation as well for our mobile networks. And that's where we see 5G advance and ultimately six G headed. Yeah, I'm glad you, uh, you know, a lot of the discussion has has been about inside of the data center, and I'm glad you extended that.

First of all, data center to data center, but also even, even between different countries, uh, but also the industrial edge, which I believe, uh, we will see some tremendous growth there, uh, at, at least in the next three years. It's hard to predict, but what I do know is that historically speaking, um, the, the compute goes to where the data is generated, and it's, it's very efficient to be able to do that there as opposed to doing it all up, uh, uh, in the cloud. But, um, so let's boil this down to, you know, where should, uh, companies be putting their money, uh, to get the connectivity AI really needs.

You know, you did break down the different areas, but are there any priority areas between, you know, all the way from the edge, uh, to the hyperscaler data center and everything in between? Well, I, I think they're all priorities, pat, and I think you touched on an interesting one, which is the industrial edge. And this is where we're, you know, through a lot of our partners, we're already seeing investment.

You know, one application is defense. I mean, obviously there's, you know, some, some terrible, you know, conflicts and, and wars happening. But we're seeing that drive innovation in defense, autonomous, uh, you know, ai, robotic driven drones that are, that are providing defense capabilities.

That means that connectivity is, you know, now needs to be invested in, in the battlefield. And that's driving innovation in terrestrial networks. But it's not just in defense.

We're seeing it in public safety. And, uh, we're also seeing it in certain industries where connectivity is really critical and it's driving autonomous or semi-autonomous devices. And what's different about this is that if you think about connectivity, in the past, there's been some expectation of, um, of exceptions, right?

We'd say 5, 9, 6 nines, you know, we might say three nines in a, in an enterprise legacy enterprise environment, you can't have that now. You need something that's always connected, that's trusted, that's secure, and that means that companies need to upgrade those systems, even if they have existing connectivity. And, and as I touched on earlier, bandwidth latency, these are really important priorities.

Yeah, I love the edge. 0? But we've done a lot of research on that, a lot of thinking.

And you know, the biggest difference is that AI performance per watt at the edge is about a hundred times where it was seven or eight years ago. So what you could do on the edge was actually limited. And in the seven to eight year period as well, the management of that data, the management of those applications has become a lot more seamless, uh, than it was.

0. Uh, that's terrible. Uh, hey, but hey, I'd like to shift, you know, um, uh, Nokia has been the backbone for multiple telecoms for, for decades.

Uh, you've expanded the business to enterprise, but I did wanna auger in, uh, on, on telcos here. Um, how, how is AI gonna impact the telco networks and what does it mean to your customers? Yeah, I mean, I, I think first of all, you know, you look at the announcements that are just, that have come out recently.

You know, Google's announced an, uh, a new set of, uh, of, of, uh, smart glasses that's gonna create different bandwidth. If you think about AR and VR or even just the current ai, you know, gen AI activity that's happening, the uplink becomes much more critical because I actually need to process the data and the video and the uplink as well as the downlink. So that means bandwidth changes, that means upgrades and, and enhancements building on the 5G investments that many of our customers have made in mobile.

You know, and what's interesting about us is we're, you know, we're one of, uh, of only two major players in the Western world that, uh, that deliver the complete solution in this space. But it also means modernization to how they operate these networks. Because if we, if you think about what, uh, what availability and trust mean, it also means enhancements in operations.

We need to move to, to more autonomous operations. We need to have secure pipes. I mean, if I'm running a, uh, public, you know, public safety application, for example, I need things like network slicing.

'cause I need a, a secure slice so that the video I might get as a first responder can be connected in real time back. And you can start to see how these applications cascade. And so it is gonna drive a wave of investment.

So if you, if you think also about the, uh, the, the bandwidth demand, these new services are gonna create more bandwidth than backhaul. So that's driving investments in, in optical network upgrades. And, and one of the things, you're, one of the things you're seeing in the US in particular, which I think is always a, you know, an an early adopter in this space is a lot of investment in broadband.

And you're seeing, obviously consolidation. There's been, uh, a lot of news in that, you know, whether it's Verizon and Frontier Charter and Cox, uh, at and t buying some of Lumen assets, you know, that all of those point towards a trend of enhanced broadband investment. Well, that broadband investment also creates new opportunities for services and applications.

'cause now that broadband network is getting extended, and we're seeing higher and higher bandwidths for fiber to the edge, uh, which creates, you know, and obviously signals the demand that we're gonna see for these, uh, for these applications and services At Mobile World Congress this year, I was actually, I was very optimistic, uh, about, uh, some of these, these use cases. And I know, um, some of the advanced services maybe took a little bit longer than people had expected, but seeing real world companies doing it, uh, I think the best example, uh, are the first responders, uh, where they do need that incremental slice. But I saw that taken across the industrial edge with robotics, manufacturing, uh, and overall, uh, even overall, uh, healthcare.

So it was really exciting. That was one of my key takeaways for mobile world. Uh, mobile World Congress.

Uh, yeah. Yeah. I was gonna say, I'll, I'll jump in there on a couple things.

I mean, you know, we're seeing it with ports. So logistics is a great example where you think about the complexity of moving all these, these cargo containers around and, and starting to automate some of that, providing additional intelligence, uh, you know, allowing remote, you know, remote control, remote management of some of these capabilities. You know, the, the, the, we're seeing that in, in that space, you touched on, uh, on hospitals.

I think there's early trends around, you know, about network slicing for hospitals and healthcare, uh, potentially as an alternative. Uh, and then of course you get out into any, any environment where it's indoor outdoor, where you've got a, you know, a field service where, uh, you know, where, where wifi, you know, just, just doesn't really fit. And, and, you know, 5G, 5G advance, some of these services are really important.

And I think the shift for us in the telco industry, you know, if you think about in the past, we've missed a lot of these waves, pat, you know, it, it, you sort of, we were putting in 3G when the internet was happening. We were trying to build a better voice network than we were chasing it in 4G. And I think what's interesting with AI and what we're seeing with the early signals in 5G advance, but what's coming in six G is now we have an opportunity to jump ahead, anticipate where the technology's going, and build AI ready networks to be able to support the applications and services that will come from AR and vr, re robotics, autonomous solutions and others.

What does AI ready data centers mean to you? You just use that term. I mean, the way that, the way that we segment, uh, the AI ready data center, first of all, AI Ready is typically GPU or an accelerator.

Uh, it, it's, it could be doing training, but it a hundred percent is gonna be doing, uh, inference and spread across hyperscaler, tier two CSP, uh, telco, uh, data center, sovereign cloud, and even the edge where you have raised, uh, tile flooring. Yeah, I, I think, you know, it's very similar. I think what it means to me is we're building networks in a different way.

And, and the way I think about it really simply, and we saw this, again, going back to my supercomputing roots, we saw this in supercomputing, right? The cloud was all about virtualization. How do I put as many workloads onto one computer?

And in AI, it tends to be the opposite. How do I, how do I leverage the compute resources across one workload? And so it's really a complete inversion of what we thought about in the cloud era.

And that drives different networking demands, different security protocols, you know, and, and so I, I see us, you know, you know, supporting a lot of those early investments across all the markets that you described, because the customers that are at the front end of this recognize that, you know, it's great to have all this compute infrastructure, but if you don't have connectivity that actually performs, you're not actually gonna deliver the, the applications and services with the performance, the latency, the security that customers need to drive the kind of scale adoption that the market's anticipating. It's interesting, Justin, if, if enterprises of all kinds, including, including telcos, uh, they become, uh, AI ready, they're also cloud ready, right? If, if you look at the growth of the hybrid multi-cloud, uh, you had talked about separating the compute, uh, from the data, uh, there, there's that, but also the reality is that most companies have, have three or four hyperscaler, uh, contracts with different companies, and they, they're, they're really trying to get better at, um, organizing that data in the applications across all of that, plus their, their legacy infrastructure.

And this is where, where networking counts as well. I do see a downstream improvement. If people improve their networks for ai, they're gonna get, you know, a bonus, you know, we call it, uh, data center modernization, right?

That's the, the moniker, uh, that, that, that we're using. So, so in other words, they get a twofer. How, how do you view that?

Is that, does, does that fall into to what you and Nokia are looking at? Yeah, I I, I think it does, pat, and I think there's, you know, you touched on something, there's been this tradition of, of data, you know, being moved to the compute. The reality is that we're going through a cycle because of the pace, the scale, and the pace, uh, of demand for compute where, you know, power, you know, power, availability, density is gonna mandate, compute has to be in a certain location that's driving a whole modern, you know, modernization cycle on where, how we bring the data to that compute again.

And right now that means connectivity. But to your point, over time, you know, that we could see those workloads bifurcate back into the, you know, to the enterprise or the edge. 6, uh, terabit, uh, you know, connections that's gonna create flexibility so that your network is future ready irrespective of how the, uh, you know, how the technology evolves.

So, uh, it's been a great conversation so far. Thank you. Appreciate that.

Uh, our viewers, thank you too. Uh, but I do, I do wanna wrap here, Justin, with, uh, what I consider, uh, two areas that are just fundamental, uh, to ai, and that's security and, and reliability. You know, we've seen this historically, I dunno the last 50 years in it, which is the more things you can do, uh, and even the more disaggregated, uh, things are, uh, the, the higher the risk, higher the security risks and, and the reliability, uh, could take a hit as well.

How are, how are you making sure that networks stays secure and reliable in this new age of, of ai? Yeah, this is one of our core vectors of investment, because if you think about Nokia, what's unique about us is we are the only company in the Western world that plays across mobile, you know, fixed infrastructure and optical, and the reality with ai, and you, you said it, you said it brilliantly, pat, right? Every new application or new technology innovation is a new, is a new attack surface for, uh, you know, for bad actors.

And let's just take the example of smart glasses, you know, now I've got something that's delivering AR and vr. I, I need to not just think about threats in the core application, but I need to think about threats in, in intercepting, uh, you know, the actual device itself and potentially delivering, uh, you know, poor information to that, you know, that first responder, or it could be, uh, you know, it could be an autonomous drone. So there's a whole new surface of, uh, of potential attack points.

And what we're seeing is, is end, the end to end view and the cross network view to be able to look at all of that and say, look, it's not just that we're, you know, we're, we're having a denial of service, but how do we ensure that, uh, the model is the, the model and the inferencing engine that's delivering the insight is trusted, is authenticated as the one that we expect. And so we have to think about all of that in our network design, and our teams are doing a lot of work around that to make sure that it's all trusted, it's verified. And of course, I think for the telecom industry, which it sometimes has fallen behind, uh, you know, in it, we have an opportunity to really leap ahead with more extensibility.

It's why we invested in, you know, a small acquisition, and we came out with an open source strategy around APIs, you know, in our, in our network, uh, operations stack, because we see the value of, of providing that extensibility, you know, through core networks for provisioning, for new services. And, uh, and I think this is gonna be a place where it's, it's going to take, uh, you know, the entire technology ecosystem and new partnerships to be able to defend and anticipate and protect against some of these new challenges. So we're, you know, it's, it's an area we're very focused on and, and also one that I think, uh, you know, has a lot of, uh, a lot of potential for, for new innovation vis-a-vis what we've seen in the past in telco networks.

Yeah, I appreciate you turning up the contrast ratio, uh, on that. I don't think enough people are familiar with the only capabilities that, that Nokia provides. And, and by the way, as a side note, I've been, you know, watching from afar some of the things you've been doing inside of the company, uh, expanding the footprint, um, you know, making some tuck-in, uh, acquisitions, and it's pretty exciting.

Um, and it's a long way from HPC, uh, but maybe not. Well, it's, it's an exciting time to be in connectivity because as we used to say in, in, uh, in HPC, you know, compute without connectivity is pretty lonely. So, uh, we're, we're excited to help bridge this new, uh, this new era of AI and, uh, and, uh, and support all of the great innovation happening, uh, you know, from model developers to, uh, you know, to, to GPU and accelerator companies.

And, uh, I think it's an exciting time for, for Nokia and, and, uh, it's been an, you know, great, uh, first few months for me and, uh, you know, look forward to continuing the conversation as, uh, as we continue to innovate and enable this future. Yeah, I agree. Thanks again.

Thanks for tuning into the Intelligent Edge spotlight here at the six five Summit in its six year. Be sure to check out more sessions in this track as we explore the tech and the reality of it, and enabling AI in the edge, from telco to data center, to enterprise use cases and everything in between. com/summit, and we will be back with more insights and conversations shortly.

Successful edge infrastructure must be incredibly reliable and adaptable, especially in the AI age. This episode of Utilizing Tech focuses on the ultra converged infrastructure offerings with George Crump of Verge io joining Janice Roski and myself, Steven Foskett. Tune in to learn a little bit more about how Edge environments can be more flexible and more high performance with VI io.

Welcome to Utilizing Tech, the podcast about emerging technology from Tech Field Day part of the Futurum Group. This season is presented by Solidad and focuses on AI at the edge and related technologies. I'm your host, Steven Foskett, organizer of Tech Field Day, including our Edge Field Day and AI Field Day events.

And joining me from Soy this season is my co-host, Janice Norski. Welcome to the show. Thank you, Steven.

It's great to be back this season. It's great to have you. We had a lot of fun last season talking about the, uh, all the different components that make up infrastructure, and that's really what we're talking about today and this whole season in terms of AI and Edge.

Absolutely. We are diving in with various organizations talking about AI and edge and some of those organizations where you might not realize there is an AI or Edge component to it. So I'm excited that we have our special guest on today to give us a deeper dive on what that might look like.

Yeah, absolutely. It's, it's funny, um, you know, it's 2025, everything's AI now. Uh, but you know, some of it really is.

And so I'm really interested to hear how people are going to be building infrastructure to support AI applications. Now, when it comes to Edge, too, uh, we have talked about this on the first episode and, and last episode as well. You know, it's a, it's a pretty vast definition of what Edge really means, you know, it, it, it basically means things that are outside the traditional data center that have a different, um, environmental, different cost structure, different applications, different use case, different supportability and manageability.

And one of the companies that is doing an absolutely phenomenal job of stitching together all of the diverse components that make up IT infrastructure is Verge io. So, I'm thrilled to introduce our guest today, an old friend of mine, George Crump, who is the CMO over there. And, uh, George is gonna tell us a little bit more, but before we do that, uh, let's just hear from you.

Welcome to the show, George. Hi, Steven and Denise. Thanks for having me.

Um, yeah, great to be here. I, as you mentioned, I'm the, uh, CMO at, uh, verge io. Uh, we are a company that, uh, has created, uh, infrastructure software.

Uh, what's unique about it is all the components run as a service o of our operating system, and that, that gives us a lot of efficiency and things of that nature. Uh, and so, yeah, I'm really excited to talk about what we're doing at the Edge and what we're doing in AI with you guys. Well, let's start off by just kind of understanding what, what is Verge io Now, my feeling has been that essentially, uh, there was this whole phase of, um, of virtualization, and then there was hyper-converged infrastructure where they basically pulled storage into, uh, like basically a virtual machine or something like that.

Mm-hmm. But what you guys are talking is kind of next level. Essentially what you're saying is we're gonna abstract all of the resources, all of the infrastructure resources, we're gonna be, make it, you know, uniform, we're going to make it organized, we're gonna make it, um, repeatable and manageable, and we're gonna present that up the stack as basically sort of a, a super, uh, ultra virtualized, uh mm-hmm.

Tell us more about what exactly Verge IO is doing. Yeah, in fact, we use the term ultra converged and, and because what we've done, I kind of alluded to in the opening is, is instead of, uh, you know, in a hyper-converged infrastructure, to my knowledge, almost everybody's vsan runs as a virtual machine, right? If they're doing networking at all, it runs as another set of virtual machines.

E even vCenter or, or any of the management gooey, they all run as VMs. And so not all, you got all these VMs that have to coordinate with each other across, you know, potentially hundreds of nodes. It becomes very complex both from a development and infrastructure standpoint, and also from a user standpoint.

And so, in our world, everything is one piece of software. So when you install our product, you install one thing, you don't create a VM to do anything. Uh, uh, the first VM you create is your vm.

And then everything is a service. Storage is a service, virtualization is a service. All the networking functionality is a service, and you just turn on and off these services as you need them.

The result of that is a high level of efficiency, much, much easier to adapt. You know, we, we make people, if, if you look at it, networking is one of those skills that's kind of hard to really get up level on. You's a lot of storage guys, a lot of virtualization, guys.

Networking is kind of more abstract. We make people networking experts very, very quickly as a result of the way all this works together. And as you're kind of looking at, you know, just the different types of, of customers, George, right?

Who, who's really seeking this like seamless, uh, integration. You know, you mentioned, um, the compute and the storage and networking kind of all working together, but what, what kind of customers are you working with and, and what makes it so easy for those customers? Yeah, that's probably the question that gets me in the most trouble, because the answer is yes, right?

I mean, it, it can be, we've got customers that have, uh, hundreds of physical servers all part of a single, what we'll refer to as an instance. Um, and then I've got other customers that have, we have a large, um, pro name brand entertainment company that has locations throughout the United States, and each of those locations has two or three servers in it. All of those communicate back to the corporate office, and everything's managed out of the corporate office, right?

And so the, because of the way we wrote the, the software, and, and really to Steven's point, because we abstracted it so well, it, it, it almost can work in any environment. The, the only thing we don't do is a single server, right? We're not an operating system for a single server.

We're an operating system for the infrastructure. And, and I think that that's the key. When you're talking about Edge, we talked about that at Edge Field Day many times.

Um, we've talked about that on, on this, uh, utilizing tech podcast as well. The challenge at the edge is that you have, you don't have management and operational resources. You really need something that is kind of plug and forget, forget, I mean, it's not plug and play, it's plug and forget.

You, you, you bring the thing up and it just works and it's reliable and it's remote management, and it's completely integrated. And the last thing you wanna be doing is dealing with complexity. And one of the things you mentioned, George, um, that is I think very, very true is in, in many hyper-converged or just virtualized environments, you need specialized, uh, hardware.

You need v you know, VLANs for example. You need, you know, external switches that, that have all these, you know, capabilities. You need, um, specialists, you know, who, who can deal with a lot of this additional complexity.

Whereas, you know, when you have something like what you're talking about, it, it makes everything a lot more uniform and a lot more manageable. Um, how do you handle, um, diverse, um, hardware? Is it, is it possible to have multiple different kinds of hardware?

Yes, absolutely. You can have, um, so we can have, we can support, within the same instance, we can have, uh, servers that are from different manufacturers. We can have servers that are multiple generations of Intel processors.

We can even have Intel processors mixed with a MD processors. We can have GPUs, which, you know, obviously is gonna be part of the AI conversation, right? We can virtualize GPUs.

So, and, and, uh, we're not limited to the big guy in GPUs either, right? And, and that same abstraction helps us, and it's interesting, the two topics here, because we actually use, I I would define it as narrow ai. I don't wanna be like guilty of AI washing, but it's a very narrow ai, uh, component in our product that automatically optimizes our environment.

And, and so it doesn't, it means we don't have to write code to specific pieces of hardware, the software actually push the hardware, learn its capabilities, and then know how to utilize that hardware specifically. And so it's very adaptable. I've, I've got customers that have, within the same instance, they have servers that are seven years old and servers that are six months old, and they all work well together.

I've got customers with a MD and Intel in the same environment, all those different things. And then even at the Edge, it's the same thing. You know, you're, you're, you're generally getting some cases, you know, two very, very small servers, uh, and you gotta make sure they're highly available.

You gotta make sure you can manage 'em, all those sort of things. Now, I'm sorry to jump in here on you, Janice. You said two servers, right?

Not three. You don't need a cluster of three. That's correct.

We don't need, we don't need a cluster of three. We don't even need a witness. Um, we don't have any issues with Split Brain because, and, and that, you know, if you've been in this at all, a split brain always comes up as part of the conversation.

Yeah, That's why I bring it up. 'cause this is, this is one of the things about the Edge. 'cause if you're talking, if, if, if you're talking about difference between two servers and three servers, that is a 50% additional cost, right?

Yes. When You're talking about Edge locations and, and 50% times a thousand locations gets to be a pretty big cost, Right? And, and part of the challenge with Split Brain and why it's a thing and why you typically need a witness, uh, server, is none of those companies own the network, right?

We own the network. The network is a service for us. And so we can manage split brain functionality.

We have our own voting system that makes sure that the right server has the right data. All of those things, uh, are managed again, automatically in the product. The customer has to do nothing.

And, and so we can tell, uh, what's causing the problem because we own the single piece of code owns all the infrastructure. That's pretty interesting. Um, it, it makes me wanna just dive in and go backwards a little bit, Steven and George and, and just kind of ask, um, you know, what, what pitfalls do you see customers having with say, alternative solutions in the market?

And, and, you know, how is Verge, you know, uh, making this better? Yeah, I, I think the, you know, the, what most customers for obvious reasons are looking for in an alternative is something that's less expensive, right? Uh, I think that kind of goes without saying.

I think that that goal became easier to meet. Uh, but it, but it is one of those things. And I think the problem is, is as you look at what's out there in the market, are, are you finding anything that's any different, right?

Or are you finding stuff that's basically the same as just less expensive, not as mature, not as well supported, all of those sort of things. And so that typically be, becomes the number one thing that people struggle with. The other big problem comes back to kinda what you guys were talking about with hardware.

It, it, it's, most customers don't cooperate and have servers that are getting ready to come off a maintenance or CapEx at the moment. They're also ready to switch to another, uh, infrastructure software. And so the ability to run on, um, other people's hardware becomes critical, right?

And so, I I, I've got examples where we're running on what used to be storage nodes for a vendor's all flash array. Um, and, and we just basically install our software on that. It actually ends up making a really good server, uh, and we've got an eight node cluster running on something that has somebody else's logo on it.

Uh, and we've got multiple instances, uh, of that. When I first started here, I was interviewing a customer, like, oh, send me a picture. And I realized I couldn't publish the picture because as like most vendors when they do a turnkey solution has their logo all over it.

And I'm like, well, it's gonna look like an ad for them, not an ad for us, right? So, but it, but that's, that's the real world. There's, there's two things there.

One, you're, you're, you're probably not gonna throw away your existing servers and you might want the flexibility to buy something else in the future. And so the, the, this abstraction becomes a key element in that. Yeah, that's really important.

Again, at the in edge environments, because, you know, they, they may have, you know, for example, multi-generation, multiple generations of intel nos out there. Um, they might have, uh, as you said, uh, older systems that they're trying to migrate forward, they might want to extend some life out of those things and they, you know, might want to migrate these things forward by, I don't know, sending one new node to every location and adding that into a cluster and, you know, kind of retiring the oldest one or something like that. And, and I think you guys can do all that, right?

Yes, absolutely. Well, even more practical, let's say you've had one of those locations running for two or three years, and one of the nodes dies, right? One of the downsides of a, I I don't wanna pick on Intel, but one of the downsides of a nook or anything like that, and especially in an edge environment, they're not treated well, right?

By definition, they're not in a, you know, a lot of times they're under the cash register drawer, right? And that's not data center quality typically. So they break.

And so the problem is, two or three years from now, you might not be able to get the same server that you started with, right? And so what do you do? Do you have to send out two new servers and replace the whole thing even though you got one that's working perfectly well?

So again, with us, you just send what you got and the software will figure it out. I mean, so you're touching on a little bit around, you know, of overall cost savings and, uh, just overall quality and reliability at the edge. Um, but George, what, what do you see in terms of your overall components being, um, supportive of TCL?

Like, like how are you utilizing, say, storage differently today than you were maybe a year ago? Well, I think the, the big thing with storage is most of the world, if not, well, let's just say most of the world has, has definitely gone flash, but we, we now have, um, uh, generations if you will, in flash, right? Right now, you know, we're sort of in the shift probably for most of 2025, we're gonna be in a shift of moving from TLC to some form of QLC, either all or some, and how do you manage these dramatically different technologies, right?

And, and for some customers, frankly, it won't make a difference. They're just not pushing the hardware enough, right? Where other customers, it could make a significant difference.

So the, the ability to manage different styles of storage, again, with the same, within the same infrastructure, uh, is really, uh, key. The other thing that's interesting, you know, we've, we spent so much time as an industry working about, and, and I know Steven knows this, but auto tiering and moving data from here to there and all that kind of guess what, what you really need to be able to is most customers don't need that, but they need to be able to, is just move a VM from tier A to tier B whenever they need to, right? And to be able to do that without taking the VM down, that, that, that's, that's the kind of stuff that, that we focus on.

Now, uh, George, one of the things that we haven't heard you talk about too much yet is ai. And of course this is, you know, that's something that's really coming to the edge at this point. It's really coming everywhere to the enterprise at this point.

Um, what are you gonna do? How would you apply this ultra converged concept to systems that might need GPUs or special te tensor processors or something to process data at the edge? So there's a couple of things that, that we're gonna be able to do.

Um, so the, the first to set the, the, the le the first layer, remember we do have that narrow AI componentry built into the product, and that's what gives us our optimization. It, it can, you know, I don't wanna say the word think, but automatically optimize itself for the different hardware and things like that. Remember, as a, as a company, our philosophy is one piece of code.

Everything runs as a service. And we think there's an opportunity, a significant opportunity, and we're seeing it already in some of our customers where I want something like a chat GPT, but I don't want anybody else else to have access to it, right? The, the not great example I always use is, if I was the CEO of Coca-Cola, it might make sense for me to put my code into something like a chat GPT, but I'm not putting it out on chat GT or, and I'm not picking on chat GPT, but anything cloud-based, right?

I'm not gonna do that. So we think this idea of a sovereign AI cloud, uh, we're already seeing it and we think customers are, are gonna like that because now you can load your stuff, your secret sauce into this private thing and get assistance. You know, as an example, we're, we're now running this internal, uh, at Verge io.

And, and so our private, uh, LLM has our source code. It has all the technical documentation, it has every successfully answered support ticket. And, and, and so as an example, I can write a paper, which I do occasionally load it into that and say, is this accurate?

Did I miss anything? And instead of, you know, the, the kind of the cloud version of that where you get kind sometimes kind of wild answers, it knows it, it can actually answer that. So, so translate across that, across many different types of customers who are gonna have private sensitive data that it might make sense to have AI analyze, but they don't wanna put it out there.

Well, the challenge is now you're talking about a massive skills gap, right? Not everybody's gonna be able to hire a guy to go set up an LLM and and, and teach it and do all the things that need to happen to make that happen with our software. Within weeks, now, you're gonna be able to click a button and install an LLM automatically.

It's a service. It's not another vm. It remember, our philosophy is everything as a service.

So we'll install everything you need as a service mount. The n share, which is also, by the way, we have file sharing as a service. Uh, we'll mount the NASH share, you load your training data, it starts pulling in all the training data.

And within, you know, a few days you have a, you know, a functional thing that you can chat with to start getting information out of or doing whatever you would do with it. And so as a service, you say you're not necessarily locked in, right? Right.

But you have that, that, that support and the ease of integration to, to pivot very quickly from where you're sitting today. Yeah. So what what we're building essentially is the, the, the service will be the engine, and then the actual model you'll use will be handled, um, kind of in the same way we would do a VM today, right?

We, we don't have every, we have VM templates and you can pick whatever distribution of Linux you want or whatever, and it'll go out to the, to the internet, download it and configure your vm, right? That's exactly what'll happen here. We'll show you all the available LLMs, uh, or models I should say, and it'll pick the one you want.

You just pick the one you want, it'll pull it down and you're ready to go. And, and I think the other beautiful part of this is, I, I think, and I don't know how much of this stays, stays this path, but it, it seems like we have different models that are better at solving different problems. Like there's some that seem to be better at research, other that tend to be better at graphics, things like that.

Well, with, with this approach, you could very quickly spin up an LLM that's gonna focus on generating imagery for you. Another one that's gonna focus on research, another one that's gonna focus on general q and a and have all of those running very, very seamlessly. Now, the, the other part of this that gets very interesting is, you know, um, you know, Steven, you were talking about it, is the GPUs and things like that.

Well, what if you don't need a GPU? What if I can abstract it enough that I could just run this right off of processors? It might take a little longer, but if, you know, you look at the kind of publicly available options and you're expecting an answer instantly, well, if it's just you locally in your organization or at the edge, if it takes two minutes instead of 27 seconds, do, do we care if that means I don't have to buy a $10,000 GPU, you know, if I'm the CEOI, I can say, yeah, you're gonna wait two minutes to save that amount of money.

And so the ability to do that would also be part of this, uh, solution. And, you know, it, it, it does seem like, you know, what you're describing is going to be the sort of thing that people are gonna be wanting to deploy pretty soon, you know? Yeah.

I'm not sure that they're ready to truly transform the business with AI yet, but I think that they are gonna wanna start infusing AI into all aspects. And, you know, one of the other elements, the, of the picture that I, that we've seen at the edge is that the more businesses deploy ai, the more data they're collecting and the more data they're processing. And this is causing something of a storage crunch at the edge.

Because essentially people are, um, you know, turning up the resolution on cameras, adding additional cameras, adding additional sensors, adding additional, um, you know, metrics and observability and telemetry, uh, collection, turning up the frequency of, of data collection. And all of this is requiring just more and more and more storage. And that causes concerns in terms of the performance and the reliability of storage, especially in, you know, suboptimal environments that some of these things may be deployed, whether it's in a retail store like you mentioned earlier, or in a factory, or, uh, you know, as we were talking about earlier on the top of a windmill or in a military application or something.

Um, I think that's another aspect that, um, that you're bringing to the table here is because you have integrated storage, advanced storage features for reliability for redundancy, it, it really helps to make use of some of these bigger and bigger storage devices, right? Yeah, a absolutely. And you know, I, I don't know if you've met my friends at Soine yet, uh, Steven, uh, but they've rolled out this, I, yeah, maybe, uh, they rolled out this 122 terabyte drive, and we're gonna sell all of them, right?

Because, uh, that wasn't a commitment, by the way, genius. Uh, but the, uh, but, but that kind of ca that kind of density in a very, very small form factor becomes suddenly very interesting because of that, right? And the o the other thing I wanna touch on that you reminded me of is one of the, um, again, as a service in our product is the ability to do multi-tenancy.

We call 'em virtual data centers. And so there's a couple of reasons why I'm bringing that up. First of all, in the, um, edge type of deployment, that edge could be what we would call a virtual data center physically running on a, a couple of nooks there.

But we could copy that entire, because we've encapsulated at the macro level, the virtual da, the data center, instead of a vm. I could copy that entire data center to a central office. And if the, you know, one of the aspects of local offices, as we've already kind of touched on, is there the servers underneath the cash drawer or whatever.

If something goes wrong there, I can also have it immediately spin up at the corporate office until that remote office comes back online. Now, where that applies with AI is what you're saying is, I, I kind of wanna take a crawl, walk, run approach to this. I don't, I don't, I don't wanna turn everybody loose on this thing.

Well, we can also be, again, level of encapsulation because I can clone an entire data center. I can take a copy of your, your data center, put it right next to your production data center with all the same stuff, and you can start firing up AI on it and see what happens. If it doesn't work, you can delete the entire data center.

Who cares? 'cause you've got the production one right there. So it, it allows people to go through this experiment experimentation phase, uh, much more quickly and safely because you have this object.

Now, if you look at most solutions, they focus on doing things at the VM level. The problem with that is think of all the things you miss. If you're just copying a vm, you don't have any network settings kind of important in the edge, right?

You don't have any storage settings. Also kind of important in the edge. You really don't even get a lot of the VM configuration, uh, stuff.

And so the ability to encapsulate everything as one thing and do so consistently is a very powerful capability. It reminds me, George, of the demo you guys recently did, uh, I think live right? Uh, we were able to kind of recover everything.

Steven, we should bring George back and have him do a live demo at a future, uh, field day, is what I'm thinking. Sure. I think that would be very cool.

Um, and, and George, tell us a little bit about that demo, because I, I know it's recorded somewhere, but we could always definitely bring it back for, for a live audience at some point, but you guys failed everything and then just brought it all back up and ev all the data was there, correct? No, It doesn't sound great to say that he failed everything, but I, but I understand. I think we understand what you mean.

Yes, George, explain how you failed. I, it sounds like you're describing my college, uh, my college journey. Uh, but anyways, the, so there's two, we did it in two directions, right?

One is, uh, you know, two, if you will not edge data centers cross replicating to each other, basically protecting each other. And then we did an edge to, uh, a, a primary, right? So 'cause of this podcast, let's focus on that.

And, and what we used was, um, a, a protocol called, or a capability called BGP, which is build into our networking service. And what you could do with that is you can have, you can break the rules, you can have the same IP address coming out of both virtual data centers, the one that's running active in the edge, and the one that's running at the headquarters, except you set different priorities so that, you know, the, the corporate data center maybe is a priority five. And the, uh, the edge is a priority one.

Well, that means that the only IP address that ever gets seen is the higher, the higher priority item, right? Well, if there's a failure, obviously priority one goes away. Priority five is now all of a sudden the highest priority, and it starts broadcasting its IP address.

And so all that would have to happen. So imagine a, like a retail location, like a, a, a warehouse, uh, customer warehouse sort of thing where they're walking around with iPads or phones or whatever they're using. All they'd have to do is hit refresh, and it would immediately, without it doing anything, goes back to what you were talking about.

Steven is all of a sudden they're just connected to corporate. And with that type of device, you probably don't even notice a performance difference, right? It's, it's, you know, it's the wifi that's the bandwidth issue.

So, um, so all of that's built into the core product. Yeah, it's, it sounds, uh, uh, honestly, uh, almost too good to be true. And that's, you know, it's funny, George, I I think I remember the first time you told me about this.

I remember thinking, it just can't be, you know, that's just not, you know, but it, it is proven to work and you guys have, uh, successfully, you know, you got a bunch of customers signed up and you're, you know, you've got this deployed all over the place. It, it sounds, uh, it sounds great. And also, of course, um, as companies are looking for an alternative to VMware, I think a lot of them are looking at, um, you know, this as a potential, um, VMware alternative because y'all were already, uh, supporting many of the same workloads that people were, were with VMware.

Yeah. We, we, we kind of talk of it. If, if you're making that change, you're obviously gonna make a, um, an important dec infrastructure decision, right?

If you're gonna do that, why, even if AI isn't on your radar screen right now, why don't you do something that can do all that, the stuff you need to get done today? But if somebody throws an AI project on you, all you gotta do is click a button, start a service, and you're ready to go. Right?

It, it just makes sense. And, and by the way, less expensive, right? So it just makes a lot of sense to your too good to be true.

When I, before I joined, you know, my background, uh, as an analyst, I, I ran this thing for five months without even telling birds, uh, io that I was running it, right? Because I could not believe it, and I was just in shock. Uh, so it, it's, it's, it's a fun company to work for.

We're, we're just good people. Uh, we, right now we're enjoying a hundred percent customer satisfaction, uh, which always makes me a little nervous saying it. 'cause all you gotta do is make one guy mad.

But, uh, you know, it's, it's, uh, it's just rock solid product and works day in, day out. That's awesome. Um, you know, Janice, um, this has been a, a kind of a cool con conversation about how compute could work at the edge and, and the, the challenges that they're facing and, and a solution to those challenges.

You know, what's your reaction to this? I mean, let's wrap up with a, with a bit of a summary from both of you. You know, what's your reaction overall to how, uh, VIR io helps AI at the edge and, and what that means for customers?

Yeah. I, I think this is a fascinating solution and, uh, you know, a lot of organizations out there are, are running on VMware vsan and, and, you know, maybe some other options, but, but I think what Verge has here is really easy to integrate. Um, like George said, uh, it's an all-in solution as a service ready to go.

Um, it's very flexible. So I'm, I'm excited to see what they continue to, um, innovate on. I know we just came out of, uh, Nvidia, GTC and, and lots of excitement around, you know, AI and not just within, um, HPC, but now we're looking at, you know, HCI.

So I think this is, uh, a really exciting opportunity when it comes to what Verge is doing. Yeah. George, thanks for, uh, giving us this little, this overview.

I don't know if you have a, I I, I guess, what, what would you like to tell folks listening to this about, uh, AI at the edge and, and verges place in that? Yeah, I, I think the, the, the first thing is, you know, we're not taking our eye off the ball. We're, we're still focused on, uh, providing an infrastructure software alternative.

Um, but again, it kind of goes back to what I just said, right? If, if you're gonna go through that process and, and, and, you know, I'm not gonna kid anybody, no, no matter what you do, it, it, it's not like you just snap a button. You're not switching from like Microsoft Word to pages, right?

This is a pretty big deal, and, and so you need to think about it, but if you're gonna do that work, also have something that's gonna prepare you for, you know, an, you know, a larger edge deployment. Uh, you know, one thing I didn't mention, I probably should be fired for, we have a, you know, global, uh, display that you can see all the different sites and things like that. It's okay, this isn't recorded, and nobody, you know, nobody will know.

Okay, okay, good thing, uh, I love live. Uh, but anyways, so we have that. And then, you know, the, the ability to give this flexibility, so whatever comes down at you next, you've got an infrastructure that is, you know, not we're, it's not marketing, right?

We've proven the ability to adapt to new technologies incredibly quickly. Well, this sounds great, and, and thank you so much. Um, I'm sorry to inform you that this is actually recorded.

Thank you so much for joining us on this recorded episode of Utilizing Tech. Um, before we go, George, uh, where can people connect with you if they want to continue this conversation? Conversation?

Yeah, sure. io, uh, all the information you need, uh, right there. Uh, and there's, you know, essentially two paths, uh, today.

There's people that wanted, uh, look about, uh, an alternative infrastructure, and then there's guys that wanna, uh, talk about ai. So the both of those are pretty clear on the site, so I would just go there. Excellent.

Well, thanks for joining us, and, uh, Janice, uh, welcome back to another season of, uh, utilizing Tech. Uh, where can people learn more about Soy? Oh, thank you, Steven.

I appreciate it so much. Yeah, same. com board slash ai for more specific AI information, and then I'm just a message away on LinkedIn as well.

Excellent. Well, thanks so much for joining us. Um, and thank you for listening for this episode of, uh, utilizing Tech.

You can find this podcast in your favorite podcast applications, as well as on YouTube if you wanna see what we look like. If you enjoyed this discussion, please do leave us a rating or a review. We would love to hear from you.

This podcast is brought to you by Soy as well as Tech Field Day, part of the Futurum Group. com, or find us on X Twitter, uh, blue sky or Mastodon at utilizing Tech. Thanks for listening, and we will see you next week.