Techstrong TV June 27, 2025

Hey, everyone. Be advised, everything you say do right and put on the web, can be used by an AI train. AI portraying.

You're watching gang. Hey everyone, it's Alan Shimmel, and I am really happy be telling you I am recording this at Platform Con in Person Day in New York City. We'll be here all day.

We'll be streaming live later, so do check. Well, by the time you're watching this, it won't be live, but you'll be able to watch it on, on recording hopefully. But we are here all day talking to some great people.

It's a, it's a vibrant high energy crowd app platform con in New York City. So, uh, good stuff. But we're here for Textron Gang.

We've got some, as usual, a good and bunch of AI news and different things going on. A little cyber here, a little AI there, a little DevOps there. Let me introduce you quickly to our gang for today.

If people you've met here before, so I'm not gonna do the whole dog and pony show, but we've got John Swartz, Fred Wilmont, and still in Denver, the dean, Mike Ard. Hey. Hey gentlemen, how are you?

Good. Doing great, brother. Good.

I'm Heading to the airport right after this. Good for you. I'm glad you'll be going home.

I'm actually gonna be in New York all weekend, so looking forward to being home still home for me. Um, guys, let's just jump right into it though. Uh, kind of a, i I don't want, if I, if I should use the term a landmark ruling.

Is this a high watermark for AI court rulings? Is this the, or is this just the beginning? But a, a court has ruled that, uh, anthropic using books and other material that train their AI is perfectly fine.

Even though those books don't belong to them, they're not compensating the people whose, whose IP it is. Um, we don't know if the books were obtained even paid for or just pirate were paid for. I don't know.

Mike, what do you think? Well, I'm gonna kick this to John really quickly, but yeah, it seems to be that the court is saying, as long as you bought the book and you didn't steal it, you can do whatever you damn well want with it. But John, Yeah, that, that, that's basically, that's basically base, that's basically just, so as Alan said, this is potentially a landmark, but there are some caveats and some howevers in the decision that leave the door open for other different interpretations.

So basically, just to recap, there's a federal judge in Northern California who ruled that anthropics use of, of legally purchased books to train. Claude does not violate federal copyright law. And he's basically saying the use of these, of these books to train ll LLMs was Quin, essentially transformative and was a, and was, did not violate the fair use doctrine under copyright law.

So the key phrase, one of the key phrases here in decision there was a lot of hyperbole, was that authors complained. There are three authors who sued anthropic. Their complaint is no different than it would be if they complained that training school children to write well would result in an explosion of competing works.

So they're saying basically that if you legally purchase the content, you can use it for training purposes. And, um, the, the authors themselves, there three authors, they had thought and interpreted what Anthropic was doing is large scale theft. But here's the caveat.

So the judge whose name is Elop, said that Anthropic may have broken the law when it's separately downloaded millions of books, and it will face a separate trial in December over that issue. Um, he also said that the decision does not address whether the output of an AI model infringe copyrights, which is an issue in related cases. Um, one last thing I'm gonna mention is that the court documents show that Anthropic knew there was something up and they had had to change course.

The anthropic employees initially were concerned about the legality of using higher ed sites to act work. So they had brought in a former Google executive in charge of Google Books, which is a searchable library of digitized books, and they kind of changed course and legally purchased books for the content training. So in other words, if you buy it and legally you can possibly use it, but all tan worms there, there are all sorts of repercussions and all sorts of different interpretations that can go on moving forward.

This is far from settled. You know, John, I I get what you're saying about how the judge sort of came to this decision, but you know, that that example you said about giving children a book that they was bought legally to teach them how to write properly or in a style, I think is, is a great example. But there's another legal theory of play here that I think is, is germane to the AI use case, which is that of derivative works.

So it's, it wouldn't be okay to give a book to a child and then he in, in essence, takes liberties in, in using the exact words plots, storylines in writing his own book, or it is more akin to sampling in music. Yeah, Right. And so I'd like to see where the court came down in terms of a derivative works type of argument that this ai, when we talk about training ai, what we're talking about is AI then regurgitating that information for someone else's IP or for someone else's use without adequately compensating the original author of, of that it.

And so I, I mean, I, I think this is a bad decision and reading some of the language about it being transformative and so forth, you know, I think this judge is an AI fan who's Yeah. Doing odd with the magic of it. And, and you know, I think if you asked him, he might say he's making, what would they call in the legal profession a common good argument that the, the common good of having AI help society outweighs the individual, uh, IP concerns.

Yeah. I don't know if I agree with that, but that's what it sounds like in reading, reading the article. So do I understand this correctly based on this logic?

Therefore, philanthropic just needs to go send a, a check to the various publishers for the cost of the book that pirated and they're good to go. That's my interpretation. Um, you know, rather than, I mean, that would be the safe, prudent, uh, path for them to take.

Um, you know, it's, it is interesting though, because they were also hiring of evidently a ton of materials. So they paid for like a small fraction of what, of what generic, Right? I mean, go going to buy all the books that you're training a large LLM on is not exactly Top prohibitive.

Yeah. And that's anthropic doing it. They're one of the, you know, open AI andro.

These are, let's call them ethical l lms. We're gonna talk more about ethical LLMs later. What about all the unethical ones?

Mm-hmm. It will be interesting to see if this case is appealed. And I'm li I'm sure it will be what the interpretation of another judge will be, because I think in this case, this judge clearly gave wide latitude to AI.

And, um, I I I'm gonna find it really hard to believe if, if other judges have fall in line. I, I think there's gonna be so many different interpretations of this. We, this is far from over, far from deciding Oh Yeah.

Ab so I mean, this are Northern county. This is, this is kids c will, let me, let me, let me, yeah, let me, let me paraphrase. George W.

Bush, right when he described Michael Dukakis, right? This is from Massa. This is a guy from Massachusetts, right?

The most liberal state there. This is a northern California judge. I, I think other courts and other judges might have, yes.

A very different opinion here. It Was a home court decision. How about that?

Our home court ruling. Our Home court. Fair enough, right?

That, yeah. All right, let's wrap up this segment. Great story by the way, John.

We're gonna come back and we've got a few other things to talk about, including agents for nothing. I don't know chicks for free. I'm, I'm channeling Mark ler, you're watching Text on Gang.

Hey folks, we're back. And yeah, to Alan's point, there's this company called Creo, I think that's how you say that. And they make a CRM, and they may not be the most widely used CRM out there, but they launched a bunch of AI agents this week.

And interestingly enough, they is not charging extra for these AI agents. They're basically saying AI agents are gonna be a feature and not an add-on. And one of the issues we have been seeing out there is every vendor seems to show up with some sort of AI capability that everybody, that they want everybody to pay extra for.

And it seems like, well, maybe that's not gonna hold, because at some point somebody has to be the, uh, startup that's trying to take out the incumbent. And one way to do that is to not charge for AI agents. So, Alan, is this the market at work or what?

You know, I, I think we've gotta look at this in context of the world, Mike. This is a company, they're not Salesforce, they're not Siebel, they're not, you know, I mean, they, they have a nice CRM, it's kind of a, you know, one of the scrappy competitors. And you are going up against an 800 pound gorilla, excuse me, who's promising to, you know, have tens of thousands of agents available for every purpose under the sun.

And so how do you counter that and this, and since Time Memorial, this small guy says, I got a great idea. Let's give it away for free and we'll make it up on volume. I don't know how successful a strategy that is, but at some point, agents do become commoditized and do become part of the offering.

And, and they will be free at at least a, a base set of them will. And maybe, you know, much like open source, you'll have sort of an open core of free agents, but higher, higher, uh, functioning ones will cost a little bit more money. I don't know.

It's what I think, I think part of the exercise here is that the margins on software are pretty good still. And I can hide the cost of the AI agent in those margins and still make a, a nice piece of change. And I'm just gonna be curious.

But I think that this is gonna be a trend across the board. I think every other ISV is gonna come to the same conclusion. I think for enterprises, AI may still be expensive because I gotta get the GPUs, but I think the cost of those GPUs is gonna be buried into the license somewhere.

Now, you know, will the core license go up sometime they account for that. Maybe they maintain their previous, I don't know, Alan, what, what are the margins on ISVs these days? I've seen you remember it was somewhere in the realm, 50%, Um, net, triple net you're talking about, right?

Mm-hmm. Yeah. And, and you know, and it depends with, with SaaS involved, Fred's probably better suited to talk about that than me.

He lives it. Um, but it, you know, there's certainly margin there to put it in, let's put it that way. So, um, we inevitably, look, this is going to happen.

It is just a little earlier than I thought it would, but it also remains to be seen, are these agents real? Are people going to use them? What's going on with them?

You know? And I don't mean agents in general, though, I might be talking about that as well, but certainly in terms of the ones that create here is, is rolling, are rolling out. Yeah.

I, I'm kind of looking forward to using AI agents because I'm, there are just, um, all kinds of tasks in my daily life that I just scratch my head about and go, why am I doing this? I'll give you my pet peeve example. So, you know, you write something in Google Docs and, or in, uh, word, and then, you know, you gotta load it up into WordPress.

I'm like, isn't there an agent that could just do that? You know, just kind of like take that little thing and just, you know, 'cause it, it probably sucks up about, you know, two or three minutes, but it's just annoying as hell. But so, so here's my pet peeve.

Is that an AI agent or is it an API call that, I mean, didn't it, didn't we have that kind of functionality already? I think there's a couple of interesting things about what these guys are trying to do here. The first of which is they say, we're gonna, uh, allow you to build, um, you know, build your own AI agents.

And the second thing is, uh, we'll let you choose your olms. Uh, that's a, that's a provocative thing. If you're doing that kind of work, you're not, you don't wanna be held accountable to, you know, which model has the highest risk.

I have this custom model built for my things. This to me seems to strike at the heart of people that are doing an awful lot of AI work and have built things internally and are discerning members and say, Hey, cool, I can implement what I have here already. You know?

And it is, I think shimmy, as you said, it is provocative to say, we can enc encapsulate this in our SaaS budget, right? That, that margin, you know, everybody that would, would be a funder founder or an investor in a SaaS project would say, if you're making less than 80% right, you're probably doing the wrong things. So there's definitely room for that.

I think the interesting part here that I still feel is pretty unknown is what do those ballooning costs look like? This is a really big gamut, uh, to, to run here. If you're gonna suggest you can use any model, well, you know, and build your own agents, that that could be very, very expensive.

Uh, it could be super optimized by people that know what they're doing. It, it's pretty cool to see. I like the democratization of it, for sure.

It'll be interesting to see. But, you know, Fred, to your point, you look at like Amazon queue, from what I, what I remembered, you could plug your own LLL, you could plug, you know, different LLMs into that. Mike John, who, who is Einstein?

Is that Salesforce or one of the other big guys? That's Salesforce. Einstein.

Salesforce, yes. Einstein also allows you to plug multiple LLMs into the back end of it. So again, I think this is Credo trying to match up against the 800 pound gorilla that they compete against every day.

So to Fred's point, I think, you know, are, are folks out there building AI agents that are just gonna wind up being free pieces of applications that I license? And, you know, it feels like we're about to have this classic bill versus buying conversation for, Uh, I think there's a whole suite of folks that in order for people to adopt their technology, the latest thing is to build a plugin for their agent. This MCP, you know, that agent so on.

Uh, but it remains to be seen if those are gonna be widely used, right? To Alan's point earlier, we kind of just exchanged a way to interacting with, you know, uh, words, what we used to do with APIs. Is it better?

Is it works? Does it make more sense? Do you get the right answers?

I mean, still to be determined, but I think everybody feels as though in the fleet of agents, I must have an agent that someone can interact with in my, you know, my technology stack. So vendors I think are gonna rush to continue to do this. And there's lots of public, uh, public agents today, and there's lots of public NCP servers and all of the things that go with it.

But, uh, is that a trend? Is that sort of top out? Do we get back to, hey, those things are, uh, probably not adhering to most of the general principles of security anyway, right?

Is it, is it better practice? Is it, do you get more out of it? Like, what's the value prop there?

And I think those are the questions. We, it's fresh, fresh snow. So I don't know if we're gonna see that for a little bit.

You know, ano, another lesson I've learned in, in years in, in the tech world is just because you can, doesn't mean you should, and I'm not talking about agents being free. I'm talking about, you know, creating an agent for every, to scratch, every itch that you may have. It, it may not make sense to do that.

And so, you know, I, I think we're going to go through a period where, where we are gonna try to scratch every itch, but eventually, you know, when the cost of of AI gets factored into these things, even at a B2C level, you are going to do it where it makes sense. Not, not for every thing under the sun. And, and that's again, following a, a, a, you know, a pattern that I've seen over 30 plus years.

Mm-hmm. And You know, the temptation of, among some of these tech companies, when I talked to 'em and Cisco execs said this, that, hey, they're the thought that like 75% of your time is wasted on, like 44% of that time is wasted on repetitive tasks. Like what?

Or 31% is in meetings. So they're looking at this scope of 75% of what workers do throughout their career can be replaced in some manner or form by a R agents. And that's kind of where they're coming from.

It is overkill and it will not go to that percentage for all of us, but that's how they think. I, I believe, Yeah, that's just, we go bathtub curb, right? You spend, uh, the first, you know, 35% of your time trying to figure out how to mue the data, some stuff, and then, you know, the last 35% of your time or 40% of your time trying to figure out how to interpret it.

I, I'm not sure right, that whole class of line of thinking makes sense in this case, but I think the zero to one problem gets an awful lot shorter for sure. Uh, so that you can figure out how to flatten that first part. But, uh, you know, the latter part of determining whether or not that's valuable and why it matters, I mean, still question marks there.

I would say one thing on behalf of the humble API doesn't tend to hallucinate. Yeah, no, for sure not. But, you know, we, we'll see how it comes out.

Alright, let's take a break on that one. We're gonna come back and talk about our third, uh, third, uh, uh, segment today. It's a thin Lizzy song, jailbreak, uh, you're watching Text on Game Discover Techron Group, the epicenter of tech innovation.

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Hey folks, we're back and we're talking about jailbreaks. And yes, it is a Thin Lizzy song and we dearly miss those folks, but that's another story for another time. But, um, Fred, there's a thing called Crescendo, and there's a lot of different, uh, novel efforts to kind of get LLMs to cough up information that they're not supposed to.

And the latest one, I think is called Echo something or other, but it seems like this is a, a cascading series of discoveries that people are coming up with. And some are saying that this is actually not a bug, but just a flat out structural, structural flaw of an LLM. What do you think?

Yeah, so it's interesting that we've now parlayed what this is, you know, called the echo chamber attack, is what we're talking about here specifically, but it's kind of ai, social engineering. So same problem we have today in humans right now, what we're doing is we're mm-hmm. You know, the crescendo story that Microsoft put out explains a little bit how you can think about starting with relatively innocent questions and sort of evolving that to, you know, a harmful prompt, right?

And then next thing you know, you've got poison poisonous seed sort of influencing the outcomes. And some of those types of outcomes, uh, really can't be seen as a bug, right? It's just, it's, it's not a, it's not a flaw in the reasoning process.

It's a way to manipulate the reasoning, because all the models that we love, uh, dearly, right? Or inference model. So you can see things like, you know, all of open AI's models, right?

And, uh, even, even, uh, Gemini's, you know, two five models are subject to this. Plenty of others are also. So Neural trust came out with a methodology here that's very interesting.

It's interesting because of the, uh, the level of sophistication required, but also it's interesting because of the number of models it actually affects. So the vast majority of models, right, are affected by this at least, least 40%. And then some of the ones we, we use every day, all the open AI models, that's up to 90.

But the concept here is harmful prompts. You know, let me, let me ask you how to build a malal cocktail. Sorry, can't do that.

Okay, well, lemme tell you what I know a, uh, you know, a Malal cocktail to look like, and then, yeah, let me seat that. And then let me get some of the ways to, uh, interpret my seed with other questions. And the next thing you know, I'm now invoking, you know, this context, that's probably not right.

And then we've got some paths that go down the, you know, go down the wherewithal of which direction we're gonna go with the model. And I get an answer, right? Step by step pot build a malt tall cocktail.

And, you know, this is not, uh, this is not sort of a, a challenge that I think anybody thought we would not come across. There's a lot of, you know, governance, uh, guardrails being put in the market today. But the challenge if we have here is that, um, the pervasiveness of something like this to happen, and the influence of things when we look at the open AI requirements, uh, for security, right, not listed in there, is context protection and disambiguating, you know, malicious from good.

So there are some interesting new definitions we're probably gonna have to come up with to understand how to appropriately regulate this kind of behavior and to understand when it happens. So can I say it's not a bug, it's a feature. What?

Uh, It's classic. I mean, but you know, we, we spoke earlier today about, uh, ethical LLMs, ethical AI players. Again, we, we could try to build in better guardrails that'll prevent you being able to take this ai, you know, to me, it's a kid to putting age verification on porn sites.

Are we really keeping kids under 18 from, from entering these sites? Um, I, I don't know if, if there's a good answer for this. Not, not with present technology.

And, and that's, if you wanna say, well, you know, put the brakes on AI as a result. Good luck with that. That's not happening.

Th this, this is going to be one of these classical security things where we'll care about it when people b***h about it loud enough. But right now it's, it's, the b******g isn't loud enough. So on the guardrails that we're coming up with worth the damn in the first place, and I mean, why, maybe it's not just worth the effort and we should just let people know that this can happen and, you know, bad people are gonna do bad things.

I, I think there's a bunch of parts coming out to talk about this, right? Where, you know, whether it's, you know, Google Secure AI framework, it's, uh, o OSPs new, you know, AI top 10 LLM, uh, concerns, uh, cloud security alliances. Uh, there's lots of people talking about what the potential implications are, but I, I, I think there's a really good point to be made here.

That's great. However, the tools don't all exist to guardrail all of these things. And maybe we should quantify what the level of exploitation capability is first, and then we're backwards.

I think we're, we're, we're over pontificating about the implications without really understanding the consequences. I also think it may differ by use case. I mean, imagine your financial services firm, you know, and then people are teasing out information about your clients.

Well, that's a bigger issue than maybe, you know, some retailer somewhere. So, um, you know, will this maybe reduce the appetite for using LLMs in certain use cases where there is a lot of sensitivity around the data? So it's theoretically possible.

Well, I think there's a conversation we had about, so if, if that's your risk, right? And the Kara put out this thing this week that talks about the AI model risk index. You'll notice we've talked about, uh, philanthropics Quad, uh, uh, you know, four oh and where they sit on the security index a while back.

But the risk index, if you're a large financial right, or, uh, you are using something specifically to guard, I don't know, the, the Koch formula, right? Then maybe the risk here for you is that is fundamentally too dangerous for us. We're gonna implement our own model that's customized very specific as guardrails around it, and doesn't require you as the foundation models and, you know, a public cloud infrastructure or something like this.

There's ways of route it, I think quantifying what that actual risk is to you, this is a good indices for, for folks to look at, is if this is possible and that information is critical to me, then I've gotta make different risk decisions, maybe about which model I use, which service I use, and how I weaponize that in engine for my user's benefit. Fair enough. So, So I would think that, you know, in a couple of months from now though, when folks who experience that risk are paying attention right now are gonna wake up one morning and there's gonna be some sort of, you know, shocking ease of news that, you know, will surprise them, and we will be for us, we'll be like, Hey, we told you so.

But I'm, I guess I'm, I'm wondering how long that might take. 'cause I think the, the bad guys are getting really good at social engineering of LLM. So I think, you know, this may be popping up on, I don't know, the front page of the proverbial Wall Street journalists.

They used to say, uh, 30 days from now, John, what's your bet? Yes. When I heard software engineering and I heard ai, I was like, here, it's, it's real.

And it's happening. And it's, we're gonna read about it pretty soon. And that, I mean, that's always like the recurring theme among these companies in their rush.

They, they know it's, they know it's happening. They know that the what the risk is involved and they're willing to take it. So yes, Mike, it's matter of time.

Alright, I, I think that's going to, uh, which sounds like we're a little outta steam here, but that probably means it's time to end the show, which is a good thing. I, I've got a busy day in front of me at Platform Con, and as I said, uh, it should all be available on any of the tech strong, uh, TV outlets, YouTube, OTT, et cetera. Also, we've got a full tech, strong TV lineup immediately following today's gang show.

But until then, Mike, safe travels home to New York. John, Fred, great to see you both. We'll see you soon on another episode.

For now, on behalf of, uh, Textron Gang, this is Alan Shimmel. We're out. Hey everybody.

Welcome back to the Open Source Summit. We're here with Ben and Ruben and we're talking about something called c an open source project that's in the Linux Foundation that, as far as I understand, it puts a set of APIs in front of your network that makes it easier to invoke. And who knows, maybe those network and DevOps people can get along.

Gentlemen, welcome to show. Thank you, Allen. All right.

Now your company is Cable Labs, correct? And they are heavily involved in this project. So give us the backstory of how it came together and, and, and what it does and because it's been around a little bit while, and then maybe what's latest and greatest.

Sure. So Cable Labs is a nonprofit that does r and d for the cable industry, and our members pay us to get access to all of our patents in any code we write. So our members are companies like Comcast Charter or Rogers Vodafone.

And what we have going on there right now is a big initiative. I'm in the software group. They're, uh, called Network as a Service.

So, and that's when we got engaged in Kamara, um, about a year ago. And so what that means is we're trying to figure out, um, how to bring a wire line perspective to the Kamara project that started off as mobile first. And there's a lot of great APIs to interface, uh, with a mobile network that those same APIs can, uh, can, can sit on top of a wired network as well.

So fraud detection is one example. If you're making a purchase on your phone or if you're on your home wifi, uh, financial institutions will be interested in making a call to be able to tell what level of confidence this is a fraudulent transaction or not. So that's one example of a Kamara API that could be used both on the mobile front and on the wired front.

Alright, Now, GSMA has been around a while. It's, it's memorable. So how did you guys kinda get involved in this whole thing?

Well, actually, um, GSMA get it into this project with an open get initiative, right? Um, open the Open Get initiative, take part of kyara as, uh, the main, the main, the, the main flight to development, the kind of code that try to standardize this APIs, right? The, the GSMA, uh, job in this ecosystem is to enable and convince and expose all the benefits that, uh, API at as, as the kaha.

Um, you make it, uh, made it for the ecosystem to make more seamless connection between the layers of the value change of an enterprises or a, uh, a channel partners and a and a mobile operators. With these exposures, APIs is going to be more seamless for everybody. And the work of GSMA with the mobile work on support and with all the bands and with all the white papers and knowledge that we can bring to the table, we support this camera initiative with the open grade initiative, uh, around the world.

So will this make not just the, the networks themselves a little more accessible, but can I maybe bring the various teams together around an API? 'cause there's developers, they're familiar with writing code, there's DevOps engineers that are managing infrastructure, but the network's always been kinda off to the side here a little bit. So is this gonna at some point, converge a little bit more than we've seen in the past?

Yeah, I think so. And, and you, you point out a, an interesting distinction where you've got, um, we call it northbound and southbound on the API. So northbound is a third party application developer wants to consume these APIs, could also be a network operator themself could consume their own APIs for some sort of support, uh, may maybe monitoring what whatever they want to do.

They can use that also. But then the southbound side is once you get the intent, they, they're called intent based APIs. You intend to interact with the network.

The southbound side is then the network config behind it. That has to happen to make that possible. For example, if you have an application developer writing a video streaming app, and they want to allocate dedicated bandwidth for a session, I need this amount of throughput and this amount of latency and jitter, they can create, uh, use the quality on demand API and create a session.

And then on the southbound side, it makes everything happen to reserve that dedicated bandwidth session, whether on wireless or a wire line, uh, connection To his point, I feel like the applications we're trying to build are more distributed, they're more latency sensitive than ever. And are we gonna make it easier for developers to understand that? Because I think a lot of times they write applications and they think the network will just magically do something.

They're right. Well, that, that's, that's the beauty of this, uh, camera wants that the developers community join this kind of effort in order to enrich that kind of code that that, that could, uh, have some kind of, um, uh, advance, uh, uh, project to, uh, to these APIs, right? With this, with this, uh, saying these APIs has, has been, um, um, has been said, this API process get some kind of certification, right?

That the GSMA is running. When, when the certification, the developers contribute something kamara gets right in the code, what hundreds of APIs or the priorit, the prioritization of APIs launch to the market, then get it into the certification process of GSMA that can, um, put it the stamp that say, Hey, this is a certification of GSMA with a ca with a camara code, with the developers that are, join this kind of community and enrich that kind of code. And with this, the ecosystem of the APIs of the developers channel partners, um, um, and mobile operators with a camara coordination in the coding is going to expose this DSMA open gateway to all the operators around the world.

And that will be more consistent versus having 300 companies than implemented Kamara. But did it slightly differently. Well, I as you say that you, you, you, you, you, you hit it, it is, it is going to be a seamless process for everybody is going to create more value of, of the, uh, uh, in the, between the, the layers of the, of the ecosystem and is going to, um, prioritize the monetization of the 5G environment, right?

In order to to, to have more, uh, uh, more and better products to the market. They are, uh, uh, better coding, better, uh, knowledge of the developer's community to enrich this kind of a, of APIs, right? It is, it's, it's, it is a complete project that tried to involve all the ecosystem around the world.

And as, as as, as Ben said, try to get it, uh, um, a seamless process north to south, south to north, and to try to get it west is is west in a interoperability with the operators, right? That is, that is going to be the, the, the, the main objective at the end of this. Yeah.

So what's next for Kamara? You know, you're in charge of the skunk works, what's going on? Yeah, so, um, Reuben mentioned East West APIs.

I wanna talk about that for a minute because that is something that is actively going on right now. Um, so the North south we talked about already North is coming in from the application developer south, making the configuration on the network itself. East West is now between different operators.

So you might have a Verizon at t T-Mobile, Rogers Vodafone, uh, an application developer does not want to have to write to all of these different network operators to do the same thing, to check the avail availability of a cell phone number, for example. That should be one API call. So East West is now federating and connecting these different, uh, companies together in a, in one federated, API and Ericsson and Vonage announced a, uh, a split off company called Aona, which is working to achieve that.

Exactly. So that's, that's on the mobile front. And me at Cable Labs, we're working the same thing with our members trying to do a similar thing to federate, uh, the API calls and encourage all of our members to join Kamara and participate, uh, in the project.

How do the other folks watching this get involved? I mean, do I have to work for a telecom company or is this a community where you're inviting folks and where do they sign up? Yeah, so it's on GitHub, all the code is available, all the APIs that we define, we define the APIs and it's up to the network operators to then implement those APIs.

So we define the endpoints and the data schema behind the APIs, uh, and it's public, you can go look at it there. If you want to contribute, then you do need to sign a license agreement with c with the Linux Foundation and to join an actual, if you wanna do like a pull request and push some code up to the project, then you do, then you have to join there, but you, it's free for anyone to go take a look at it. com/kamara, project Kamara or Kamara Project Kamara Pro, I'll play The story I think.

Right. Last question to you. We are all talking about AI agents, right?

And there's gonna be, I don't know, millions of these eventually sitting on our networks that are all trying to call something through some sort of API is the current infrastructure that we are basing everything on really designed for that. And, you know, does, do we need to kind of put a layer of isolation or abstraction between all these AI agents that are calling APIs so we can build out the infrastructure without necessarily like affecting the software? Well, That's, that's a very interesting question of these, um, the respo the, the response is at this point of time, we need to get it into some kind of a step, right?

We are going to get it into try to monetize the 5G with the resources that we already have, but now it's coming the six G and, and that is some awarding and, and, and, and papers and news that, uh, GSMA is bringing to the table with the, with the, with all the white papers and information that we, that, that, that we have it for the Moler War Congress and all the events that we organize. But the response, the answer for your, for your question is yes, but we need to get it into, into, into some kind of a step by step to support that kind of, uh, OO of traffic or notification, uh, depending on this API's calling and, but, um, but the responsible of all this is all data communications, um, change operators, association developers, partner channels, everybody need to have, uh, um, that in the top of their mind that we need to join that kind of, uh, uh, of technology step by step, but as soon as soon as they can, right? This is, um, get it involve budget and forecast and everything like that, but we need to get it into the first step to try to be prepared for theirs coming, right?

Because, uh, for this open gateway initiative, uh, we saw that it's something that need to be done, right? Is, is, is, is a seamless process and um, is, is is going to benefit the ecosystem in technology in a seamless process with a correct monetization. I'd like to add one more thing, um, on the AI front.

Kamara did recently kick off an initiative to explore MCP, the model context protocol and try and figure out how do we make all of the API calls, um, so that AI can interact with them in an easier fashion. So we are actively looking into that as well. Alright.

And we were talking about a two A here at the show. Is that on your radar screen as well? Yes, We're, uh, we are actively working with A two A and using AgTech AI to try and connect, um, these, these APIs.

All right. Yeah Folks, there's an old joke that says, you know, what's the one thing that a developer and the person running servers can agree on? It's the network guy's fault.

Hopefully that won't be as funny as it used to be. Gentlemen, thanks for being another chef. Thank you.

Thank you for having Us. All right, and a pleasure And we'll be back in a minute. Hey guys, thanks for the throwaway here with Mike McNeil, who's the CEO for fleet.

And they just picked up $27 million in additional funding for a company that is, well, I have an open approach to managing mobile devices of all kinds and maybe even stuff that's not so mobile. Hey Mike, welcome to the show. Hey, thanks for having me.

So what exactly is it that you guys do? Because there's a lot of people out there who are managing mobile devices and it's not clear to me that everybody understands maybe there's a difference here. Yeah, so I mean, one of the things out going on in the market right now is you've got a lot of companies dealing with PCI compliance, FedRAMP compliance, um, many other kinds of compliance.

Um, and you got a world where 42% of organizations surveyed in the US are considering moving at least half of their cloud-based workloads to on-prem infrastructures. You got 70% of CIOs considering a move of some of their infrastructure and whether or not these folks actually do it or not, you know, if people have a bee in their bonnet about cloud spend, compliance is getting more complicated and organizations like having options and like having control, um, and fleet is built like that from the start. So it's open device management, um, you know, we're open source, so we let you deploy anywhere you want.

Um, and that's how a lot of our customers have been, um, doing it. So ultimately I can, it's self-hosted in some form or another. It's just a question whether I put it in my own data center or if I want, I can put it in the cloud.

Is that about right? Exactly. Or we'll host it for you too.

You know, we have options in different regions or multi-region. Um, but the main thing is folks like the option of being able to jump from our cloud to their cloud to a data center somewhere and having everything still work. They can change it anytime they want.

Now, correct me if I'm wrong, but most of the mobile device management platforms that I know of are generally proprietary at the moment. And how many open source options are there? There are none other than fleet, except there is one.

Um, IR two I'll call out. So Xtra, um, a company in Europe, uh, has, has an option out there. And then Micro MDM is a totally community open source project that fleet is actually built on top of.

Um, but other than those options, those are the, that's really, it fleet's your best open source option. So $27 million maybe in the age of AI doesn't sound like a lot of money, but it's significant. So what are you guys planning to do and what needs to be done next?

Well, I mean, one of the things that, uh, we've seen such value from, we've learned so much from is hiring people from the community of, uh, IT professionals and security professionals that do this stuff every day. And we're stoked to grow the team and basically bring on people that, uh, that understand how to use MDM to support customers, to help bring in new community members, um, and to help us steer the product the right direction. So a lot of, a lot of building, um, we're working on supporting one additional platform that we don't currently support, which we'll have some news about soon I hope.

But right now a lot of it is, hey, let's take what we've got and get it out there. Especially for people on the channel. Um, MSPs, resellers, um, we've made it as easy as possible for them to register deals, get access to fleet for their customers, um, 'cause their customers have the same problem, right?

About self-hosting. Exactly. Um, what are the challenges that people are running into with managing mobile devices?

What makes it different than just a traditional desktop? And um, and for that matter, are we seeing some convergence of the management of security and IT here as well? Well, you know, this whole idea of MDM really started as an Apple thing, right?

You know, I think over 10 years ago and, uh, a laptop became yet another mobile device, but there's a really big difference between the bring your own device, BYOD world and corporate it, where you've got company owned devices, you have, uh, you can have a little bit more stringent compliance rules and maybe you have to versus you may not necessarily need that kind of invasiveness on people's mobile device, um, that they own they bought with their own money, right? So we actually support both of those use cases. Um, but primarily a lot of our customers get started with laptops and some even start with with Linux.

So one thing that's going on out there right now is if you have a hundred employees at your 100,000 employee organization that use Linux, it's usually more than that. It's usually more like 2000. Um, those people don't really have a way to be fired, right?

Or terminated from the company. So you can't actually like remote lock those computers, um, at least until until fleet came along. And then as far as like on the security side, you know, security really drives a lot of the roadmap for this stuff.

Like security is the one that says, Hey, compliance is great and everything, but we really need to make sure that we have these controls turned on on our machines. Um, so we kinda see is, you know, if products is the vision setter and engineering is the implementer in the world of product development and the world of IT and security security's really setting a lot of the vision and it is doing the implementation. So I don't know if we'll see the departments change, but I think we're seeing a lot more cross-functional work happening.

Did we kind of taken endpoint security for granted for a few years there and suddenly I woke up one morning, every attack seemed to be going after an endpoint, but um, have we kinda responded and understood what the implications are at the very edge of our networks with all these devices out there? You know, I think people buy EDR as a security blanket, right? Um, and it works pretty good, right?

It helps, it helps increase your security. Um, having the endpoint protected is kind of the end all and be all in a world where your network is mostly encrypted. Now you have people phoning in from anywhere in the world.

Um, I think that the endpoint is not the whole story. There's never, there's never a world where a company like Fleet takes over all of identity, all of endpoint, right? Um, all of SaaS security, like the world of security is always gonna involve posture from SaaS apps that you use, like Slack and Gmail.

It's gonna involve your network telemetry, your cloud telemetry stuff that's not even an endpoint, right? Like the Cisco router that's kind of on the edge or maybe like a, a managed database in your cloud account. So I don't think that endpoint will ever fully take over that world or nor should it.

Um, but I think organizations, uh, you know, especially like bigger banks, bigger um, bigger organizations that have more risk to manage, they're looking at a world where they have endpoint identity, um, and then the world of behavioral tools. So in terms of our IT and security on the endpoint gonna converge, I think it remains to be seen. Um, but it is how security gets things done.

Is There any effort to centralize the management of this stuff? Because at least not too long ago, um, you know, people were managing Windows with Windows tools and they were managing Macs with Mac tools and they were barely managing Linux things at all. Um, so is there now an effort to kinda centralize the management of mobile devices that are heterogeneous almost by definition these days?

You know, I was, uh, I was talking to someone from a company like Fleet, um, but a few years back that went public and the journey for them, they talked about with one large, uh, telecom company is they started with a a hundred iPads, I think, right? And within five years it had turned into like a $15 million contract. Um, I think that where we're at in the technical selection process for folks is, um, I literally met someone named client platform engineer, right?

'cause they wanna make it flat across Windows, across Mac, across Linux. I think people are there mentally and I think they're in a world where like, hey, the products that can do this are very new. Um, workspace one is out there in this space, fleet is out there in this space.

Um, workspace one has gone through lots of changes. So I think people are watching that closely. I think people are watching Intune closely being a Microsoft product.

Like, is this where I should put my max? Right? I don't know.

It doesn't support remote lock on Windows or maybe it does. I think that people are kind of in the selection phase and I think in like three years time we're gonna see which of the relationships with these companies really expands and like what technology is working, but the ambition is there. Um, and people are tired of siloed teams running Windows versus Mac versus Linux.

There's also a lot of talk these days about AI and agents can't walk down the street without somebody leaping out to tell you about their great new thing. But, um, it seems to me maybe there's a way to apply AI agents to the management of laptops and mobile devices. Is that something you're thinking about?

Totally. And much in the same way as things like the SOC or things like network security, there's a lot of moving parts, right? Like, uh, your, your identity is important.

The context and the data from more than just the endpoint is important. So I think the best endpoint solutions are gonna be like the musculature. It's gonna let you change things on devices, get information from devices.

Um, and I think the way that the brain works for these, for these customers is gonna vary a lot. Um, we've seen some customers that have their own AI powered solution that they plug into Fleet. Um, we've seen other customers, even pretty advanced customers, um, like a, like a large, uh, gaming and AI company who just want to use the most basic features, um, of fleet without plugging in anything at all, really.

Um, except for the minimum they need for their organization, right? All the certificate management tools, all the zero trust pieces. Um, so I think that, I think that you've kind of, you're gonna have a lot of variability in how the decision making happens, but the parts that are always the same are the actions you need to take, right?

Like, I need to run a script on this computer, I need to work reliably. I need to, I need to be able to trust the code that's running the script and I need change control on that. So we can make this repeatable.

Among the organizations that you've seen that are doing this well, what sets them apart from everybody else? One of the things that, and this is probably just, this is kind of generic, but it's just proven to be true, is the people that, the people that really succeed with device management are the people that are willing to say, Hey, we're gonna think from first principles here. We're gonna own how we do this and we're gonna make it the right way for our organization.

We're not gonna like plug into, um, a particular way of doing, doing things that we've been doing for 10 years. Um, unless it's working great, in which case why question it, right? Um, so I think that attitude generally has been what we've seen in the most successful companies.

And then in terms of a specific practice that's been pretty cool is a lot of folks lately have been doing GI ops or configuration as code, um, where they can basically go in, create a repo and we actually have a tool in Fleet now that will automatically create the repo. So you can build everything in the user interface and then kind of switch over when you're ready. And that means that if security has a question you can be like, oh, just check, check the repo and you don't have to give them special access to fleet.

Um, you can do all that stuff, but it's kind of a heck of a lot easier if you already use Git just to add someone to a repository, use all the same access control your organization already supports. So we've seen, um, we've seen a lot of cool stuff happening there where you can actually have accountability on, Hey, who made this change? Who reviewed it?

What's the blame history? And I'm talking about everything from scripts to, Hey, we changed the control and now Mike's not allowed to change his desktop background anymore. I'd be sad about that.

But, um, who wakes up in the morning and has this aha moment and says, we need to rethink the way we're managing all of this stuff. You know, it's funny 'cause we're a real open organization if Fleet to like the way we run the company is all pretty out there. So, uh, we have a public handbook and in there we actually have some private Google Sheets, links, um, to stuff like our license keys and stuff like that.

And we keep those very secure, obviously. And someone forwarded me one that we got, and it was actually someone from a company, um, in Japan asking, Hey, I have data residency requirements, like can I, how can I find out like, you know, where this works, how my, how flexible really is this? Um, and that was just an example from like this morning.

Um, but a lot of stuff like that where people, they have a problem, they find it on Google or they talk to someone in the community, um, especially in the Mac admins community, and they're like, oh yeah, fleet Fleet does that. If I have anything custom I need, if I have somewhere special, I need to deploy it. Um, or if I just want, um, a little bit clearer access to what this code is doing that's running on my employee's computers.

Um, fleet is a fleet's a great choice. All right folks, well, you heard it here. Hey, it has changed.

The end points are different and if you're still trying to manage things the same old way, it might be time to take another look at it. Mike, thanks for being on the show. Thanks Mike for having me.

All right. And back to you guys in the studio. Google breaks the internet Ion Q Bonds with Oxford Ionics synopsis opens up for startups, unified threat naming, automating telemetry, arista's new COO.

And we take a look at all of the AI announcements from Cisco live in this week's episode of the Tech Field Day Rundown. Hello everyone and a welcome to the Tech Field Day rundown for June 18th, 2025. My name is Tom Hollingsworth and I have successfully avoided the June gloom that is in San Diego, at least it was last week.

And I am back to be happy to host the rundown with my good friend Mr. Alistair Cook. Al, have you ever just wanted to get away?

Well, some days I do just want to get away and today is of course, national Want to Getaway Day. And uh, it conveniently is also National Go Fishing Day if you want to get away and go fishing. And that seems to be a pretty popular thing to do around where I live.

People head out in head out onto the, uh, Pacific Ocean from here and look for some fish to, uh, to make a meal outta, which is a great way of spending a day. Exactly. Well, the good news is, is you don't have to splurge on anything expensive to catch the great news stories that we have coming up because we've already taken care of that for you.

So we're gonna dive right in with one that probably affected you last week because a major Google Cloud outage on June the 12th disrupted large portions of the internet, which affected, you know, minor services like Spotify, discord, Google search and Google Meet. The root cause was tied to an issue with Google Cloud's identity and access management platform, which also impacted things that depend on that, like, uh, CloudFlare, that, that was another big problem we ran into. And of course, as is usually the case engineers implemented the fixes, some of the services began recovering, but then everybody was talking about this, there was a lot of outrage highlighted the risks of relying on centralized cloud infrastructure.

And of course made a whole bunch of companies start saying that, Hey, at least we're not Google Cloud 'cause we don't go down. Uh, although none of those was CrowdStrike. Al what's your take on Google Cloud's minor little curve level?

Well, I think there's a, a couple of aspects to this. One of them is that every IT system goes down now and there and as they say, uh, eventually software works and eventually hardware fails. And between those two, there's usually something going wrong somewhere.

And so the fact that Google has had a, a significant outage here, Google Cloud has had a significant outage is to me no more significant than previous outages of cloud providers. Every IT system goes down at times, but what it does do is highlight how much we've centralized our use of it. And a relatively small number of providers as we sit, have seen in AWS's outages of, uh, on occasion that large sways of our IT estates are dependent on these, these clouds.

And this consolidation to a smaller number of clouds means that the blast radius, the impact of a single failure is much larger than it was when we had a much more distributed, decentralized environment. There is of course, a, a large argument around designing your cloud application for failure. Um, this is often where the cloud providers say, well, if you followed our design rules, you wouldn't have had a complete outage.

And unfortunately, usually the IAM the identity and access management piece, the fundamental permissioning who's allowed to do what in your public cloud environment, uh, this is one of those services that you can't get around even. Uh, I'm far more familiar with this on AWS I, AAM is a global service on AWS and, uh, if there's a fault in IAM, it's gonna affect all of your regions. Uh, it appears that the same is true on Google Cloud.

I'd be surprised if it wasn't true on most of the other infrastructure as our service clouds as well. That if the, uh, the identity and access management component breaks down, well you're no longer authorized to access anything that's kind of better than when it breaks. You're allowed to access everything.

'cause that would make it much more of an attack target. But it still brings back that central idea. We're we're putting a lot of reliance on a relatively small number of providers.

And if one of those providers goes down, there's a pretty significant impact to that. Large numbers of websites and, and applications were offline while this particular, uh, incident was occurring. Now, unlike some of the incidents we've seen on premises, the RESO resolution time was relatively fast.

It was certainly not minutes to resolution, but it was hours rather than days to resolution. And some of the failures that we've seen on premises, uh, we've seen organizations take weeks to months to return from, uh, some of their failures. So on, on the terms of scales of failure, yes, it was a significant failure, had a lot of impacts, and it was downfall longer than we would've liked.

But this is the real world. Things go wrong, things get broken, and, uh, in the increasingly connected and centralized world, uh, connected to large numbers of, uh, locations from a small number of providers. Yeah.

And that tends to be high blast radius for these faults. Can you design around it? Can you design your infrastructure to cope with one cloud provider having a failure and another cloud provider not having the same failure maybe, but the cost is gonna be outrageous to do it.

Is it really worth it In order to avoid these relatively few relatively short failures, it's always a business decision to invest in higher availability or not. It's very hard to get high availability across multiple clouds in the world of quantum ion Q is a US quantum computing company and they're buying the UK based Oxford Iion Strange. There's lots of ions going on.

08 billion first billion dollar deal in the quantum computing industry. Uh, the goal is to combine ion q's powerful quantum systems with Oxford's, uh, chip based technology, which is much easier to produce at scale. The move helps ion q advance its plan to build large, reliable quantum computers by 2030.

And the deal also boosts Iron Q's position as a leader in the growing quantum tech space. Tong, we talk quite a lot about quantum and particularly a, around when quantum computing is gonna be big enough and reliable enough. Do you think 2030 is a realistic goal for our nq?

I think it's, I just don't think that what they're gonna be selling is gonna be very cheap. And the reason for that is because the amount of effort that's gonna go into building a quantum computer out of these components, there's a lot of inputs to it. So the short, short version for all of you out there that are wondering what the heck is an ion quantum computer, they essentially take ions, you know, just little elementary particles that have a charge and they stick them in a field.

And effectively what they're doing is they're using electromagnetic spectrum to trap these ions in this field, and then they super cool the whole thing to just a couple of degrees above absolute zero so far so good, right? Well then you have to manipulate those, uh, ions to be able to get data out of them, right, like any, any traditional computer would. And you do that using this complicated thing known as a laser.

And so the problem you run into is, one, the inputs cost a small fortune. 'cause the amount of, you know, things like liquid helium that you have to use to keep these things super, super, super cold, but also the complexity of the way that the lasers need to interact with everything makes it a lot more difficult to just kind of spin one of these things up. And I mean, we've seen that with a lot of quantum computing, even I I say startups, but like Cisco started a quantum computer lab out in, uh, California.

And, and one of the things that's a big problem is the fact the amount of power that they have to pump through those lasers is well frightening when you think about it. Uh, but ultimately what this means is that these two companies realize that in order to bring something to the market for them to be able to get a return on their investment, they're going have to examine how to make this cheaper and more reliable with less precise inputs. And think all the way back to the late 18th century when Eli Whitney invented interchangeable parts at back then, anything you made was custom built.

And that meant that whoever built it needed to be very, very good at what they did, right? So if it was a hunting musket or any kind of like a steam engine or anything like that, it was all custom built. And that meant whoever built it had to deliver it and had to assemble it, and it was a pain in the neck.

But with interchangeable parts, I could just say, okay, take three of these and two of those and put them together like this and you can make a thing. Quantum computers are kind of where we were back then where everything is kind of custom and bespoke. If they're going to make this more of a, you know, marketable thing, they have to make it so that maybe not you and I but somebody can build one of these without needing to have like all of this kind of crazy training to make it work.

Can they do that in five years? Well, I honestly, I don't know, five years ago if you'd have told me that people would've even had quantum computers capable of what we have today, I would've probably wagged my finger at you. But the point remains that there is a large gap between something that is available for sale and something that is available for sale cheaply enough where everybody can buy it.

I think what we're going to see is that Ion Q and Oxford Ionics are going to figure out how to make a cheaper quantum computer. That doesn't mean they're going to make a cheap quantum computer. I still expect this thing to cost multiple millions of dollars to put together, but even at multiple millions of dollars, it puts this kind of technology into a space where large organizations that potentially could need that can buy it and use it as opposed to having to farm timeout on these large, large systems that are effectively backed up for months or years at this point because it's the only game in town if you wanna do those kinds of things.

So we'll keep an eye on it. I mean, it is big that it's a billion dollar acquisition, but billion dollar acquisitions also have to produce results if you wanna pay off in the long run. Semiconductor companies Synopsis is partnering with plug and play to help chip startups get easier access to their powerful design tools.

They're piloting an accelerator program at which selected startups will use synopsis software and intellectual property to speed up development and to cut costs. Overall, the goal is to support faster chip innovation across industries and help grow synopsis's role in the deep tech space. And of course, plug and Play is a company that's kind of, uh, providing funding and is maybe a little more eye towards the results of those companies being able to use Synopsis intellectual property and tooling.

Al what's the ultimate goal here? Is it for Synopsis to make more money or is it for these companies to be able to get a jumpstart on the semiconductor design and manufacturing process? Well, there's not an or in there, it's an, and so it is a dual objective here.

The objective for plug and play is for the startups that they're mentoring, that they're investing in to be more successful, to decrease their failure rate, uh, as they're building new hardware products. A lot of Silicon Valley innovation is based around software, and software has a very fast design cycle. I can write some code today and be testing it tonight.

Uh, hardware is a little tougher, particularly custom Silicon Hardware. Uh, and that's the sort of space where Synopsis is working in here. They have some electronic design tools for designing actual custom silicon, and it's these tools that are being made available to the startups that are working with plug and play.

Uh, the objective here is, is really for plug and play to be helping these companies to be more productive and therefore get better exits. Uh, and of course, synopsis gets their tools in front of a whole bunch of new startups who are doing innovative things. And naturally, if this is the tool you started building your hardware with, you're probably gonna continue to build your hardware with this.

Uh, I think the really significant thing in here is the recognition that hardware is not just the game for Intel and a MD to be building and Nvidia, that hardware solutions are a place for innovation for smaller companies to innovate and to build new solutions that are not just more of the same, more cause scaling out or, uh, faster, um, Zion CPUs that there is a place for innovative new hardware to be built. And, and it's not all just software running on general purpose CPUs, but also a recognition that that change to designing hardware, particularly designing hardware, uh, custom hardware for new solutions is very high risk and very long, uh, time for return. Now, Silicon Valley's, uh, venture capitalists, they like a return within 10 years of investment and they wanna see a 10 x return as their preferred kind of run rate because 90% of the people they back won't give them that 10 x return.

So any tool that's gonna make it easier for those startups to turn their idea into some real production silicon absolutely is gonna be really beneficial to getting that innovation, getting those startups to operate and therefore getting a return. And I think we will see another wave of innovation in custom hardware. We're already seeing it from the larger companies we're seeing, uh, NPUs, dpu, whatever offload you would like to consider, uh, as a really significant part of the innovation at the moment.

A lot of those innovations are around arm cord CPU and maybe software just running on those arm cores. I think this synopsis, uh, deal with plug and play oriented more towards truly custom hardware, not just new firm. We're running on embedded CPUs.

So it will be interesting to see in five years time whether we start seeing a, a large set of innovation in new hardware, new types of hardware being available, new expansion cards or possibly new device types entirely turning up on the market. And that will be really be the proof of this one. Microsoft and CrowdStrike have teamed up to make it easier to identify cyber threat groups by combining the different names that various security companies use for the same attackers.

This helps reduce confusion from having too many names for one threat and one threat group so that security teams can respond faster and more effectively. While it's tough to create a single naming system, this partnership is a big step towards a clearer and more consistent threat information in cybersecurity and less confusion over whether it's a assault thing or a, uh, typhoon thing that is coming to attack you. Tom, do you get a clear idea of whether a salter is a typhoon or a typhoon is a type of salt?

Uh, it depends really on which part of the world that you're in. Um, but, uh, I, I think that being assaulted by a typhoon is probably the worst thing that could happen to you, especially if you don't even know who it is or where it's coming from. And that's one of the biggest problems that we've run into as of late, is this idea that everything needs a catchy name.

Right? And look, I get it, like CD 2025, alpha Baker, purple Monkey dishwasher is not the greatest way to refer to a thing unless you're a machine. However, trying to come up with a creative name for a thing that actually Desi like talks about what it does is also kind of maddening.

Like, do you know what Heartbleed does right off the top of your head? Probably not, because you have to dig into the details. And it doesn't help that if a group that did something is detected by say, Microsoft, and then a different group say, I don't know, Mandiant looks and sees the same group but isn't aware of what Microsoft has discovered, they might give them a same name, which is why we get a, you know, weird things like AP T 31 or Fancy Bear or this or that, and it creates confusion.

And I'm gonna pull out my nerd card here for a second to, uh, illustrate this point. Uh, if you've ever played Battle Tech, you are familiar with the 10 meter tall, uh, robots that run around and shoot people and, and do all kinds of fun stuff. And at a certain point in the lore, uh, a group of these things showed up out of nowhere and the people who were fighting them were fighting over who got to name them the first time.

So in one particular case, one group of from one country called it the Vulture and Theano another group from a different, uh, culture called it the Taka. And even the people who piloted the machine called it the Mad Dogs, you had three different names for the same thing. And if you're reading the books and you're like, okay, which one was that?

Is that this one or that one? I don't know. And some of you out there who are familiar with Japanese may say, well, wait, Haaga is the Japanese word for vulture.

Yeah, but it's still Japanese. And I'm not sure which one you're talking about there, especially when you consider that there's a maari and a Dai Shi and a whole bunch of other things. The point is, is that I'm throwing all of these words at you, and I could be referring to the same thing, but I could be referring to different things.

And unless we know how to deal with that specific thing, we can't fight countermeasures against it. And if we have some kind of a unified model where one group or one group of people will say, okay, this is the name for this group that produced these things, and this is how you defend against them, then we can start spending more of our time solving these problems and combating these attackers than trying to give credit for who deserves to be able to name something. I mean, Lord knows we've got that problem right now.

Is that mountain in Alaska Mountain McKinley or Denali? The ultimate answer is, who cares? It's a mountain.

It should be there. And no matter what we wanna call it, I I tend to lean more towards the Nadali crowd because that's what the people who've been there for thousands of years call it. But the point is, is that we need to have one authority that says, this is how it's gonna be, and this is the name we're going to use.

I applaud Microsoft, I applaud CrowdStrike for trying this. Uh, but I will also tell them that there is another common problem in the industry, which is if you wanna make a standard naming convention for something or standard anything, the easiest way to do it is to decide what you want it to be called and get enough people behind your, your movement so that everybody else in the industry aligns against you and creates a standard directly opposite of the one that you wanted to. You can ask Cisco how that worked out.

I think ultimately though, this is a good step forward, and here's hoping that this one can stick. Who knows? Cribble has introduced the new co-pilot editor, which is an AI powered feature built into its cripple stream platform, which is of course available to all their current users at no extra cost.

And it automatically maps and normalizes telemetry data, which understands log structure and semantics to translate schemas standardized formats, build pipelines and route data analytics tools in minutes rather than hours or potentially days. Uh, this human in the Loop tool not only accelerates onboarding and reduces vendor lock in by enabling streama schema agnostic transformations, but also optimizes cost by filtering noise and enriching critical fields for it and security use cases. And as we saw last week at Cisco Live, uh, when you feed a bunch of log data or packet captures into a standard LLM, it tends to barf everywhere.

So I guess the question that I have for you, Al, is does an automated telemetry system really provide value for the people who have to comb through logs every day? And I think the simple answer is yes. So maybe we'll move on to something else.

Now. The more complex answer in it is, is also, yes. Um, you know, what we are seeing is that general purpose LLMs are designed for hu for handling human to human conversations.

That's what they were trained on. Logs are not human to human, they're machine to machine. And so specific training for handling the kinds of data that are handed off machine to machine is gonna yield a, a large language model that can handle that and can understand the, the way that communication is formatted and structured can do things like recognizing that probably the first block of data is going to be a date, but that depending upon where you are, that formatting of the date or what the sources that formatting the date might be different.

So things like simply being able to recognize that it's a date, what the source format is, and then output that in a standardized format. And that's what data normalization's about. Uh, absolutely there's value in that.

Certainly a human can look at a date and say that's what the date actually reads at, and maybe write some logic to transform it into a standardized way of writing the date. Uh, although Google Docs doesn't seem to be able to cope with the fact that there isn't just a single standardized way of describing a date, uh, ask me how I know that, uh, US state format is almost all that, uh, Google Docs will work with beyond just that simple, simple example of the first field is probably a date and land a type. There are sort of commonalities to how log data is sent, but there isn't a standard for this is the order for this set of fields.

And so again, having a tool that can look at the set of fields and look across a, a reasonable sample of the, the data coming in through a log stream and say, well, we can divide it up, we can reformat it, we can actually re represent it maybe as a series of key value pairs that are more identifiable to our application, then the straight stream of text. So yeah, I think there's some real value to be had, and this is where AI that understand specific data types are gonna be very beneficial to us. I like that this is still human in the loop because I still don't trust completely AI generated content in even the most specific use cases.

Um, I still, particularly as we're we're looking at new types of data coming in, want to do some validation. Uh, a as always, it's around those edge cases. Uh, what about an elite year?

Is it gonna, does this transformation going to cope with maybe a, a number that's usually a, uh, degrees centigrade temperature, which shouldn't get above well a hundred, um, but maybe, uh, one of the sensors is gonna send me in Fahrenheit or maybe, uh, when I go in and change the air conditioning in my hotel room to read out in far, uh, in centigrade rather than Fahrenheit when I wanna change the temperature. And is that gonna change the results that come through in this, this screening? So yeah, it's, it's absolutely awesome.

The more we can have AI tools that deal with this routine, um, drudge work that is part of it, building applications or building in this case, uh, log data pipelines, the more we can use AI to deal with the drudgery piece and have the humans deal with the more creative and, uh, innovative piece, the, the better. Uh, that's absolutely what we want AI to be doing for us. And so this ai co-pilot that we often see an assistant that runs alongside you and deals with just the minor stuff that might even be called the, the AI executive Assistant, um, would, is absolutely a great use of ai.

And I hope we've seen more of this taking the drudge work away from people. Arista has a new chief operating officer. Uh, the company announced that they were hiring Todd Nightingale for the role.

Nightingale was most recently, uh, the GM of Fastly. But most people in our audience know him as the VP and GM of Enterprise Networking and Cloud at Cisco and the SVP of Cloud Meraki. Uh, he ran the unit from 2015 until 2022, uh, when he departed to be the CEO at Fastly, he was highly regarded leader by the customers in the industry.

But some insiders say he was overly protective of the Meraki culture and resisted the efforts to unify the brand with Cisco that unification happened after he departed. But if he's a Welllike leader and he is now inside Arista, that's a whole different set of culture to be working with and protecting Tom. Is he gonna be a great steward for Arista?

I think he'll, and I'll tell you that back in, I think it was mid 2022, this is just before his departure. I watched him give a speech at Cisco Live and the amount of passion that this man displayed while he was on stage, I turned and looked at the people in the room and I said, that man is gonna be the CEO of a company one day. It just won't be this one because we all know how things go if the CEO chase in a large organization like Cisco and moving to Fastly was probably the best thing he could have done because it gave him the opportunity to be the head honcho for a while.

And so now he's stepping into the COO role at Arista. And some may say, well, you know, that's a step down right from CEO to COO. I would argue that this is maybe more a step in the right direction because Todd has a lot of experience running networking, and I think that he is seen as a passionate person who understands the technology and is ready to help people do things right.

Like, like that's always been the drive that he's been behind. Uh, yes, there were few insiders that I heard as soon as the news broke that said that he was more of an obstacle, at least in their, uh, experience because he very much resisted the integration of Meraki proper into Cisco. And anyone, you know, from that acquisition up through 2022 knew that they were very bright lines.

You know, this is Meraki, this is who we are. And that's different than these people over here. Arista has a very strong culture.

Anyone who's ever watched a Tech Guild Day presentation that is involved, someone like Ken Duda knows that they're very passionate about what they do. Ken notoriously is a vehement advocate for code quality. And I think that Todd and Ken are matched horses.

I also think they're gonna work well with Jri because Arista has a drive, they have a vision for what they want to do, and they've been executing on it. And, and we've talked in the rundown in recent weeks about, um, making acquisitions to possibly complete some of that vision. We've seen presentations from them as of late to kind of making a more holistic, uh, you know, c campus to data center type, uh, offering.

And I think that Todd Nightingale brings on board a seasoned leader who knows how to manage those transitions, who knows how to position those products so that people understand that value. And it cannot be understated enough that the company that he worked for Meraki has a very strong cloud management background, and Arista has cloud vision. And I feel like that is something that they're going to be developing even more deeply now to allow people to kind of build out networks that are technically proficient, but also easier to manage, which as we've seen from a lot of companies over the years, is the way that a lot of folks want to go.

Um, and of course, you know, we're, I'm sure we're gonna be talking about it very shortly about how ease of management is, is a driving factor for a lot of people. So I, I hope Todd settles well into his role over there. Honestly, I hope to see Todd at a future tech field day event.

I'd love to get him in front of our crowd and have him display some of the passion that I've seen him with in the past, and I think it will work very well for the people there. It's about time for us to take a closer look. And Cisco Live, uh, was last week Cisco live us and the opening keynote was dripping with AI as all good tech keynotes are these days.

Cisco's product lineup was the, for the rest of the year and into the future, is going to embrace AI agents and information from networking operations and security as well. The CEO, Chuck Robbins and Chief Product Officer Jetta Patel talked about all the integrations of AI into their offerings from dashboards to NVIDIA network technology. Cisco's pushing AI into infrastructure.

One of the big discussions was around agent ops, the Cisco term for agent-based networking operations. They also discussed how they would help build the AI data centers, uh, for the future with pod based architectures and more so on. You were there, apparently it was a little gray for, uh, San Diego.

What did you see at Cisco live? Well, hold on just a second. Let me consult my LLM.

What were the big announcements from? Yeah, it's gonna take too long. Cisco's going all in on this, but we know they had to because that's what the market is telling every company they need to do.

We, I I, the way that I described it to people was it's the look busy, the boss is coming mentality. You need to be doing something with way ai, what I don't know, but I need to see that you're doing something. And, and I get the perspective that they're coming from.

And honestly, they're, they're kind of taking the right approach. They have years, decades at this point of institutional knowledge that is built around the idea of building better networks, right? Like just something as simple as a Cisco solution reference network design.

That is a way that you're supposed to build a network with Cisco gear, makes total sense. Now, implement all of that into an AI model and have that AI m model consult on the way that you're building things. Seems pretty easy, right?

Until you start hitting hiccups. And that I think is where this is going to matter more than anything. What happens when my brownfield doesn't look like your perfect ivory tower design?

How can I adjust for these things? How can I ensure that this piece is gonna work if that piece fails? Uh, you know, even stupid questions like which routing protocol should I use to tie these things together is not always a straightforward answer depending on what kind of technical debt you're dealing with.

The other thing is, is that there's a lot of talk about AI security, right? Like using AI to do threat hunting, to notice patterns, integrate that with Splunk, be able to offer that to more people. The idea, and this was on every petty cab in, uh, San Diego that was right around the convention center, you know, ask us about agentic ops.

The idea is, is that they wanna build these agent-based AI systems that are going to help operations teams run their networks. Will it work? That is a big question for people because as I've discussed with people, even just today, there is an issue between operations and engineering personnel that will ask AI a question and then they will immediately question the results unless it's something they have deep knowledge about and trusted implicitly.

And that trust takes time to build Cisco's agent agent stuff may come back with a little bit better of an option because it's like, well, in a perfect world we would do this, but we also still have to implement those solutions. And not everybody lives. In a perfect world, I would hope that this will turn out for the better because everybody seems to need AI and everything that they do.

And not to be outdone, because this is the other thing you mentioned there, they're also building the infrastructure that will run those massive AI engines. Cisco's one of the first companies that was allowed to build Spectrum X network technology that isn't named Nvidia. Now I've said in the past, I think I mentioned this, uh, after we heard the initial announcement of this just after Cisco Live Europe, that one of the reasons why I think this is happening is because Nvidia realizes that Cisco has a very tight hold on some accounts in the market.

And the only way that they're going to be able to get in there is if they partner with a company that has a proven track record. Not saying Nvidia doesn't have a track record, but when's the last time you went shopping for an NVIDIA switch that wasn't built into an Nvidia AI pod? The answer's probably not.

Um, it goes back to like when I used to deploy blade centers in, uh, in school districts, um, most people would just use the cheapest switch option that was in there, even if it didn't run anything even remotely related to an operating system that I could work on, which is where a lot of my frustrations came from trying to figure out how to make these switches work. And more than once I told people, I'm like, why didn't you just order the Cisco switch? They're like, well, it was too expensive.

So I think that that Cisco's trying to position themselves as being a, a key component of AI infrastructure in the future, while also using AI to help their infrastructure, you know, be easier to use, be easier to manage. I don't necessarily know that that means that you're gonna be reducing operations personnel, because that's usually the first thing that people say, right? It's like, oh my God, they're gonna get rid of, of me and I'm not gonna have a job because my job is, is this, this, and this.

I'm like, either your job is doing things that should be automated already, or they're gonna keep you on and have you tackle the hard problems, in which case you get to learn and grow as a network engineer. And that's how all of us started out. Like I wasn't birthed knowing everything there is to know about the CCIE, that that came later, but it was when I got into those problems that were not just a quick fix, a quick typo that I was able to say, okay, this is how these interactions happen.

I used it for the experience that it was, and I'll tell you that making mistakes is something, one that people need to do to learn. And two, AI is surprisingly good at and surprisingly bad from learning from. I mean, Al, you've, you've worked a lot with AI worked and honestly, you being the event lead for AI infrastructure Field Day have seen a lot of companies that are doing AI infrastructure.

Do you think Cisco's gonna be able to keep up with this? I think there's, there's some really cool things in what Cisco has announced. So definitely that, um, integration with Spectrum X using, uh, certified connectivity between the NVIDIA mix that might be in your GPU pod and your Cisco switches, that seems like a pretty big deal.

And the whole idea of having this secure AI factory and having some AI defense within that secure AI factory notice, there seems to be an awful lot of security being talked about in here in AI because so was, uh, actually writing yesterday in an article. Uh, there's a whole new attack vector into your organization, which has poisoned, uh, models turning up on hugging face, and that these, this is a, a great way of getting a, a new type of executable file inside your nice squishy soft network. And so, yeah, I like that there's a big focus in on here on governance of these models and guardrails and a lot of the things that are important when you come to running these models in production, because running in production is where you're getting business value out of your investment in ai.

And so having a, a design here that focuses on what's important when we're running in production governance guardrails, that's making sure that your AI doesn't go rogue and start sending out all of your internal HR information at a request from somebody out on the internet. These pieces are really significant and important as you're building out an infrastructure. Um, Tom, you talked about trust and Cisco is pretty significantly trusted in most of the large enterprise organizations around the world.

Um, um, the cost of Cisco may not be the most popular thing, but then when we're talking about AI infrastructure, your network infrastructure is not particularly expensive. Next, suppose $20,000 a piece, GPUs that you are buying 20, 40, 50, a thousand of, uh, you know, the network infrastructure certainly is a significant cost normally, but not when there's GPUs come into play. Even the X 86 server cost in your SSD cost is small compared to the GPU cost, let alone the licensing that comes around every month for the software that you've got on top.

Uh, where was I going with that? Oh, yeah, Cisco trusted, liked, um, good reputation for a liability. One of the non-AI things that I thought was really significant in here was getting this Nexus dashboard that is unified management for both NEX os as well as the, uh, the, uh, a CI, the, uh, software defined networking and bringing hyper fabric in as well.

This has long been a criticism for Cisco of we've got so many different consoles for managing the different pieces, bring them all together. So I like that coming along as well. And this idea of an AI factory is really important for a large enterprises getting started, getting to the point where you can actually run some AI applications.

The first use case is difficult, but scaling to hit 20, 30, 50, 200 different use cases within your organization is incredibly difficult. And so the more prescriptive guidance, the more of a scalable and particularly scale out architecture that you can build for hosting these applications over time is gonna be really critical. I think Cisco's really well placed here.

And of course, Tom, you've been a Cisco fan for a while. Uh, do you see AgTech ops being a thing that's going to help you as, as now the CCIE? I think it's gonna move the needle because it's another tool in the toolbox that Cisco certified individuals can use.

Uh, I don't know what the adoption rate's gonna look like though, because we've seen this a lot from the past and honestly, talking to a bunch of people around Cisco Live there was chuckling. It's like, oh, look, it's Prime again. Oh, look, it's Cisco works again.

I I, I used those for a while and then they put them out to pasture because the next new thing came along. Maybe this one's gonna have a little bit more legs because it's being fed and, and and growing, you know, kind of like an AI algorithm normally does. But ultimately, you know, you get to a point where the system's gonna be running and then someone's gonna go, well, if it's not really providing us UpToDate information on a regular basis, why are we paying for this?

Because we all know that the way, reason why to do this is because it involves a yearly licensing fee, right? This is, this is the ultimate completion of Chuck turning that big ship, turning them from the John Chambers box, pushers RS into the sleek and subscription based Cisco of the future that makes the investors very happy. But I also think that there are challenges that are gonna be faced in by all tech companies with some headwinds and policy decisions made above the CEO level by people in Washington DC that are going to have to be overcome in order to make sure that these things do not be or are not regulated into oblivion or worse yet unleashed on an unsuspecting populace to do things that could create problems down the road.

But I don't want a naysay too much about that. I just wanna sit back and see if people adopt this or if not, uh, maybe I'll just need to start studying for the CCIE ai. Who knows.

One thing you can do though is stay tuned for Tech Fuel Day because we have great things coming up. The first one is actually happening right now. You know that we are a part of the Futurum group and every June the Futurum group has the six five Media Summit this year, of course, it is AI Unleashed, and if you missed the keynote from Michael Dell, you can go back and watch it along with lots of great coverage, including GTU Patel c Chief Product Officer of Cisco talking about some security related things.

com and check out six five Summit. We would love to see you there. I will be back in July after US independent stay to be bringing you networking field day 38.

We have a great lineup of presenters and some brand new delegates who will be joining us for the very first time. com very shortly. So make sure that you have all of those sites bookmarked.

Thank you very much for tuning in for this episode of The Tech Field Day rundown. Don't forget that we do publish new episodes every Wednesday. We love to bring you the news on Hump Day, and if you wanna subscribe to us on YouTube or possibly in your favorite podcast application of choice, we would appreciate that.

Also, don't forget to leave a, uh, comment below. Let us know what you thought of our stories, whether or not we were snarky enough. 'cause Lord knows we can always turn the snark up to 12.

Uh, that would make it a lot more fun. And check out Al and I and Steven as well as many other great people on other tech strong TV and future and group properties, we would love to, uh, hear you there. We'll be back next week to talk about all the things that happened in the Enterprise IT community for the last week.

Until then for myself, Tom Hollingsworth, for Al Cook, Steven Foskett, and everybody else here at Tech Field Day, thanks for tuning in and we'll see you next week. Symbian launches, S-O-C-L-L-M Benchmarks, big DDoS hits CloudFlare. Qualcomm acquires Alpha Wave more qubits.

Teradata builds an AI factory Chinese LA PD certificate hacking. And we're gonna take a look at some of the news from AWS reinforce in this episode of the Tech Field Day Rundown. Hey everyone, welcome to the Tech Field Day rundown.

It is June 25th and we hope that you are enjoying perhaps a snack that was purchased thanks to a gift card 'cause it's National Gift Card Day. Who knew there was a day dedicated to that? That wasn't Christmas, but speaking of Christmas, you know what today is, it's six months until Christmas.

Did you know that there's a name for that day? It's National Leon Day. And why?

Well, because Leon is no l spelled backwards, but do you know what law spelled backwards is Al And that's my co-host for this episode, Al Cook. Al, welcome to the show. Thank you, and it's a great pleasure to be here.

Uh, we, uh, here in New Zealand, being in the Southern hemispheres tend to have Christmas parties this time of year because it's the coldest time of year for us. So we have what we call midwinter Christmas parties. Of course, all of your Christmas parties in the are in the middle of the winter, but ours are often at the beach.

Yes. One of the things that always blows my mind is while I'm sitting up here freezing, opening Christmas gift, you guys are having barbecues and being outside and complaining about how hot it is. But you should never complain about how hot the news is on the rundown because we of course, are bringing you some of the latest and greatest news.

And we're gonna start that off with a story about Symbian because they've introduced the AI S-O-C-L-L-M leaderboard, which is a whole lot of acronyms to describe the first benchmark that will measure how well AI language models perform real world security tasks in a security operation center. They tested this on a lot of realistic scenarios, as well as models from OpenAI, Google and others, and they completed between 61 and 67% of tasks when supported by a solid framework. Now you're probably wondering why they did that.

Well, Ian's goal is to show, show where AI really helps, and that's speeding up routine work and not replacing human analysts. The approach focuses on transparency, real world testing and helping companies choose the right AI tools based on performance, cost and value. Not that dreaded AI hype that we keep hearing a lot about.

Al, do you feel like this leaderboard is gonna help people pick the right models and the right tools, or is this just something that someone's gonna figure out how to gain so they can get to the top of it? Well, I think it's, it's important to recognize that that symbian is, is talking mostly about the value of the framework you put around the model, and it's, it's their framework, of course, to put around the, the model that makes the most sense. Uh, the reason that they emphasize this is that, that what they found was that the l and m you use makes relatively little difference to its success at dealing with the kill chains that, uh, with sets of logs from kill chains that they were showing it.

So they tried both reasoning models as well as just generic large language models and saw very little difference between them. But what they did see is if you just feed the raw data straight to the L lms, you get terrible results. You need to put frameworks around how the data is being fed into the LLM, and you definitely need to put some guardrails around what the LLM is providing back in response.

And so the, the interesting part was that it really didn't make so much difference, which LLM you used so much as how you used it. Hmm. Who would've thunk that?

You could use a tool badly by not thinking about how you're going to use it? Uh, really is interesting to see that 61 to 67% of, uh, required tasks were autonomously completed by the models. It definitely highlights the fact that yeah, humans are definitely gonna be involved.

But what I see for using LMS here is just dealing with a huge amount of data that happens when an attack is underway and they fit through a variety of different types of attacks. Uh, when an attack is underway, the the problem is that you get a deluge of information and working out which information is significant and which information is just repetition or is, uh, is a secondary consequence. This is the kind of place where an LLM can be hugely beneficial.

Just seeing those correlations between the events, seeing the, the different behaviors and identifying what's the truth part of it. So reducing the, the cognitive load for the specialist human being who's going to do the, the final decision because hopefully we as humans are getting above that two thirds rate, 67% that, uh, was the high watermark here. Hopefully we're doing a better job of responding to security events and, and taking a look at that, one of the other elements that was highlighted was cost.

That if an LLM is going to give you a slightly better response, maybe it's going to get from 67 to 69 or 75%, but it does it at twice the cost. So a higher RESO resolution rate, but at a vastly higher cost, that's probably not a good business decision. Good business decision is probably to have, uh, a human involved and take the slight reduction in the accuracy of the results at that vast reduction in cost.

So it's a, it's kind of nice to see some real world things in here. Uh, some, some thinking that maybe the, the latest and most shiny LLM, these new reasoning models aren't necessarily going to be the be beyond be all and end all of making things better for you. Um, it's nice to see just some benchmarking too, some real world feed, some real data and use a consistent set of data to take a look at how the results work.

What will be interesting will be to see these resolution rates changing over time. And so seeing with, uh, improving frameworks around them, improving the LLMs and then working with larger and smaller LLMs is going to provide better responses. I'd like to see a cost dimension here as well.

Uh, rather than just a straight what percentage were resolved, what was the dollars per item resolved kind of view would be really beneficial to us as well. Something else that's really beneficial to us is the ability to cope with massive DDoS attacks and cloud failure has reported their largest ever DDoS attack. 4 terabytes of data in three quarters of a minute that, so a huge amount of data.

Now, this kind of attack, uh, with that briefness, it's typically is a connection list. So this was, uh, mostly UDP flood attacks. Uh, it was a bit of, um, there was a bit of UDP reflection going on as well in order to up the volume of attack without necessarily having to have a, a much larger botnet.

Um, there's some really interesting fun stuff in this. It's a return of Mariah, Mariah botnet was being used to, to launch this and to, uh, assemble together the servers that we're sending requests to over 34,000 ports on the target system. Uh, DDoS attacks continue to grow.

It's one of the realities is as we get better at protecting against these volumetric attacks and, and, uh, flow rate attacks, we basically see larger and larger attacks being launched against us. Um, what should we expect Tom, in the future of these multi terabit attacks, Chaos, panic, and disorder? My three favorite horsemen of the internet apocalypse, this is the problem that I have with these growing DDoS attacks, is that just like a von Neumann machine, everything you add to the system just amplifies more and more and more.

I literally, months ago, we were talking about some of the very first attacks to hit two or three terabits per second sustain, and now we're talking about seven in a very short time. And this is overwhelming the ability of the systems that we have put into place to cope with it. I mean, that's literally the reason why CloudFlare was built, right, was to prevent massive surges in traffic from being able to take systems offline.

And now we're at the point where not even CloudFlare can take care of that. And I know what you're probably saying to yourself, well, Tom, there's a lot of companies out there that are telling me that they can sell me DDoS protection, you know, Arbor Networks, Nokia, um, you know, literally companies that have been founded to prevent this problem from happening. I'd argue that you're absolutely right.

They are very good at detecting certain kinds of DDoS attacks. For example, you'll notice that in the article that we linked in, one of the reasons why this was successful was because it was effectively a UDP flood. TCP floods.

Sin floods don't happen nearly as much anymore because systems are set to detect a massive number of incoming sins and drop them. And so we never get to that point where the system is left holding open sockets for connections that will never come. So the attackers figure out a countermeasure for the countermeasure, and that's where UDP comes in.

And when you consider that a large portion of traffic on the internet is starting to move towards UDP, all you've gotta do is fire up a web browser made by Google that uses quick, and you'll know that most of it is UDP. Now you'll see that this is not easy to combat because unlike TCP, which is very ordered and regimented and polite, UDP is none of those things. Um, if TCP is somebody calling you on the phone, UDP is somebody driving past you and shouting at the top of their lungs as they drive away, not so bad unless it's a parade of people doing that and completely blocking anyone's ability to get to you.

The other problem that I have with this, of course, is Mariah, uh, I think that it in the future when we're all old and gray and our kids are learning about this stuff, the Mariah Botnet is gonna go down in history as one of the biggest face palm events that we could have possibly seen. Who knew that releasing a whole bunch of very capable IOT devices on the internet with a hard-coded back door that can't be removed was gonna end up being this consequential to traffic and knocking sites offline and things like that. I mean, we don't even have the luxury of these being run by Intel Atom processors where they effectively have an expiration date when the system crashes.

These things are gonna be around for a while. I mean, I'm not saying that someone needs to find a way to create software that would create a race condition inside the CPU of a Mariah camera, cause it to overheat and possibly slag itself and get knocked offline. I'm not saying that at all, because that would be bad.

I'm just saying if it happened, it might be helpful, allegedly. But don't do that because that would be bad. I think we're gonna have to start finding ways to get more creative about the way that we have to maybe fight these UDP floods, uh, because the next attack's probably gonna be on the order of 12 terabits per second and transfer 60 terabits of data in that short amount of time.

And woe be to the CloudFlare customer that is on the receiving end of that because that ladies and gentlemen is a tidal wave that nobody can hold back. So I hope that we can solve this before we have to get really creative in how we solve things. 4 billion in an effort to boost their AI data center business.

Alpha Wave specializes in high speed connectivity that will strengthen Qualcomm's processors and help expand their place in the cloud and AI markets. Of course, this is a proposal because the deal won't likely close until early of 2026, but it does have strong support from Alpha Wave's board and shareholders. It also marks a key step in Qualcomm's efforts to grow beyond smartphones and into the data center and AI computing space.

And we've heard about this a lot because as a lot of AI data centers start shifting towards arm architecture, traditional arm stalwarts, like Qualcomm really wanna bite at that Apple because it will give them a diversified business portfolio in order to avoid the constant treadmill of phone upgrades and potentially, uh, alienating suppliers and, uh, partners in the space as we've seen between Apple and Qualcomm over the last few years. Al, do you think that Qualcomm acquiring Alpha Wave is gonna help them get that AI dollar? I think that's very clearly the objective here is that, uh, there, there is an arms race going on to own the probably second player space in, uh, AI data centers would acknowledge that Nvidia currently holds the, the top place there.

Uh, but there is quite a lot of movement around around behind that. So, uh, Qualcomm have their hexagon NPUs, uh, that would be very assistive here. And, uh, building out their, their, uh, platform for AI in the data center along with their, uh, our own, uh, CPUs, uh, you say arm based CPUs, very power efficient and, uh, very easy to scale outwards to lots of core without, again, huge power loads.

So yeah, they seem like a really good thing to see in, uh, AI data centers. Additionally, also in in AI inside laptops, we've seen the Qualcomm, uh, copilot PCs turn up. Maybe not as warm a reception to those as we would've liked, or at least that Qualcomm would've liked to have seen.

But definitely AI in the data center is a big growth space. Uh, alpha wave themselves, uh, they chose their board chose to take an all cash offer. They interestingly declined to take something that was shares in Qualcomm, which was definitely on the board apparently.

4 billion for a, a London based company. Nice to see. Uh, that does offer quite a, a premium on the current price for, uh, uh, 96% premium on the current price.

And does, as you're say, need to get regulatory approval. And also, also, uh, shareholder approval needs to hit 75% shareholder approval for this to go ahead as well. But it is definitely aimed at data center compute, getting connectivity between large numbers of CPUs and, uh, and, and accelerators in large data centers.

Does this mean we, we will see a new architecture, maybe not using Infinity Band and ethernet for connectivity? Unlikely, we'll likely to see this end up with a whole lot of ethernet connectivity around, but possibly this connectivity that from Alpha Wave is gonna be really good for scaling out a single system with large numbers of NPUs and, and large numbers of arm calls alongside it, and then providing ethernet for connectivity beyond. So it'll be interesting to see it progress, assuming it does actually go ahead and, uh, it will be interesting to see whether Qualcomm can take away some of the market share that is being held by Nvidia, or whether they're going to be scrapping with a MD and, uh, Intel for being the second player in that market.

Chinese company Quantum Ctech has launched the EQ engine version two. It's a powerful and affordable quantum control system that can support over a thousand qubits that's nearly getting to a large enough size to be useful and is 10 times more efficient than its earlier version built using Chinese hardware. It costs less than a similar foreign system and is being tested for use for up to 5,000 qubits.

Hmm. It's already performed well on a 504 qubit quantum computer and could help the company compete with global leaders like IBM Quantum Ctech is also working on a system to manage 10,000 qubits aiming to push ahead in the race for commercial quantum computing. Founded in 2009, the company went public in 2020 and continues to invest heavily in research despite operating at a continuing loss, as you might expect, with such a, a high cost early stage development.

Tom Quantum is, is all very cool and wonderful, and larger numbers of qubits is great, but don't we have some problems with error correction and getting reliable results out of these larger collections of qubits? Al you nailed it. And I think that's one of the things that they're trying to solve here.

But before we get to that, whether or not they totally realized what they did by naming this thing quantum ctech, really as in ctech astronomy, too many secrets, uh, you sneaker stands will know what I'm talking about. Um, it, it really matters here because this system is designed to control quantum computers to increase their resolution, provide better error correction, and effectively make them into a force multiplier. 'cause we've talked about this a number of times on the rundown when there's a new quantum, uh, release of, you can give it all the horsepower in the world, but if you can't fix the error resolution problem, you don't really have much.

It's, uh, like I said before, it's like giving, uh, someone a Ferrari with no breaks, all the power in the world, but no control. And that's what we're looking at here, is this system is designed to provide that control. By enhancing the resolution, you are going to have errors that fall out.

You are gonna effectively multiply the capabilities of those qubits, which means the system runs more efficiently and provides better results. Hmm. Where have I seen a Chinese system built on other research that is cheaper and provides better results for less investment?

If you said deep seek, you win the prize. That is exactly what's going on here, is that a company is looking at development that's been going on, they see the need and they build around it. China is doing a very good job of building quantum computers.

They are competing with IBM. We know that because they are, you know, the, the cubic counts are going up and we're hearing about their successes. But again, it's not just about raw horsepower.

And so this to me is kind of like the mated horse in this particular covered wagon, if you wanna call it that. By having bandwidth and error correction, I'm making the whole system better overall. And that means that people can really start developing for these systems knowing that their reliable outputs aren't gonna be wasted in this.

I mean, when you look at some of the specs of those IBM quantum computers that are out there, what is it? Condor processor has like 1100 qubits, but how many of them are dedicated for error correction? And, and the fewer error correction bits you have, the better the data you get out of the system.

And remember, every one of the qubits that you use for error correction is effectively wasting resources because in order for it to be a, uh, data point that you can measure, it has to be super cooled and liquid helium is not cheap. Uh, eventually we'll get to a point where we won't have to do that anymore, but I don't know when that's gonna be on the horizon. And when you look at some of the way far out crazy stuff, like the Microsoft quantum computer that we talked about months ago, like this to me is more in the realm of reality because A, the numbers look right, but B, the people doing the development are focusing on the problem, which is good data, not the perceived problem, which is just how fast it can go.

Like for example, if you've ever measured firewall throughput, you know, you get this crazy number of packets, but they're all 64 bytes because that's the smallest packet size that can go through the firewall. Well, what happens if I'm playing video streams? How many packets is that?

Well, we don't know. We've never tested it. That's funny.

'cause that's a real world application. And that's the thing here is I wanna see how this system performs in a real world application. Because it's one thing to say, you know, our queue engine is the best and it works really well on these workloads that we've already used before.

So we know that the answer's right when we do it, throw something at it that you don't know what the outcome is gonna be. And that should be a real measure of how well it tests out. But again, something to keep an eye on.

Remember kids, make sure you're implementing those new quantum resistant encryption protocols sooner rather than later. So you're not left holding the bag whenever this thing goes live. Teradata has expanded its AI factory platform to work with on-premises data centers, giving organizations, especially the ones in highly regulated industries, more control and lower costs when they end up building the inevitable AI applications.

This platform includes tools for managing data, AI models and integrations with services like those found in Nvidia, making it easier for IT teams to deploy AI without fully relying on the cloud. Al we've seen a lot of buzz from people who are wanting to build AI into their things, but they can't get around that pesky regulator. Is this going to be a way for Teradata to break open that market and just run with it?

Absolutely, and I think there's, there's a few drivers for bringing the actual production part of AI on premises. We know the cloud is a great place, as they say it's a great cloud, is a great place to, to try and to fail, but it can be an expensive place to try and succeed. And so we definitely see large language models being developed on, on the cloud, particularly ones that are using open sources for all of their data, at least allegedly open sources.

And that's what we see for all of the foundation models. But those foundation models are not what organization are using to build their AI applications to gain AI insights within their business applications. Uh, fine tuned models.

And then inference being run from those fine tuned models is the way to actually generate business value often that fine tuning and definitely the inference uses a whole lot of data, which is proprietary and highly valuable within the organization. As you say, Tom is often highly regulated and it's, these are the drivers for retaining that data on premises where you've got physical control of where it is. And there's a stronger perception also that you can stop leakage back into the original AI model because of course that that model's running on your premises.

You can control whether the data you feed it is being used to train it somewhere. Certainly whether it's being used be, uh, the data you feed it is being used to train it for your competitors, as might happen if you feed your data into an open source model out in the public location. So running on premises, uh, or at least within your own tenancy in a cloud seems to be a, a good methodology.

And particularly we, we see far more use of AI inference desired to be run on premises. One of the things we saw quite frequently in AI infrastructure field day events here at Tech Field Day is that this is hard work. Building the infrastructure to run AI at any large scale is, is really hard work.

There's a bit of work to be done to get it to work for just one use case. But when you start looking at addressing 30, 40, 50, a hundred, 200 use cases in within your organization, you're talking about building a fully multi-tenant, highly scalable infrastructure for running inference. And this is where the challenges really mount up.

And it's against this backdrop that Teradata is taking their AI factory, which historically has been part of the advantage cloud service and saying, well, you can deploy that out on premises. We can reduce the load required of the effort required by your in-house team to get to that multi-tenant, multi-use case AI infrastructure whilst retaining all of your data on premises. Whether that's purely because you need it then for performance reasons, right?

If you're u using real time updating data, well the closer your computers, your inferences to where that data's being generated, the lower latency you can achieve for that real time data, um, or whether it is truly just about compliance about we're not allowed to store this elsewhere. And talking to somebody about sovereign clouds last, uh, a couple of days ago, and the idea that you might actually have to be certain that all of your cloud data was within the same, uh, sovereign space. I know in France, a French company has to retain all of its, uh, data about its French operations on French soil.

These are all challenges that are much harder to fulfill, to achieve when you're using public cloud. Uh, if you know you've physically got it within a data center that is in your Leon, uh, location, then you can absolutely be certain it's within, within France. So yes, I think this is definitely about easing that on ramp, making it simpler to get started, to get beyond a couple of simple use cases of AI and get widespread AI adoption within your organization.

Teradata isn't the first one to offer an AI factory on premises. I'm sure they won't be the last, but if you are highly committed into Teradata, if it's the way you store the majority of your business data, then their AI factory seems like a very good way to work. Because being data centric, thinking very clearly about what data you have that is gonna bring value, uh, through your AI is gonna be central to this.

There's been another secret hacking campaign, uh, likely from a Chinese group and it's infected over a thousand old routers and iot devices. We were just talking about, Mariah, this could be the new one. Uh, most of these devices are in the US and Asia, and these devices are running on a, um, or forming together a hidden network called LAP Dogs that helps attackers hide and launch cyber attacks.

The attackers use special malware pretending to be from the Los Angeles police, the LAPD, so maybe it should be the L lap PD OGs rather than the lap dogs, uh, to get deep control of these devices. This network could be used. Uh, it's a disrupt important systems in the future.

It could be an attack vector against infrastructure. Uh, experts warn to watch for strange encrypted connections coming from home devices to catch these attacks. I can't see many people's home networks being able to identify these devices.

And if it's I OT and old routers, well, so these things have infinite lifetime or can we get them to burn with fire? Um, well maybe I'm, I mean, allegedly we could potentially do that. I thought this was kind of brilliant, that effectively what they're doing is they're trying to create a foothold into a network that's standard security hacking parlance.

They are, you know, uh, escalating privilege for the local user account. If it has enough privileges to drop things into the Etsy folder, it'll do that. And then the system will just reboot.

Um, the whole thing with it. Using the certificate from the LAPD purporting to be from the LAPD was kind of neat. Uh, you know, it's, uh, who, who wants to question whether or not law enforcement's putting something on my machine that I think is, is kind of where it's coming from.

Also, that's why the system got its name lap dogs. 'cause you know, LAPD lap LAPD la Oh hey, remember last week when we talked about unifying that naming convention thing? Uh, yeah, that gives people that are, uh, failed poetry writers a a little less motivation to be cute and creative.

Um, but anyway, the other thing that I thought was kind of interesting from this article is who they think is behind it. Again, we don't know this for sure, but you know how it is when all signs point to Yes, thank you. Magic K Ball.

Uh, it's one of the typhoon groups, uh, specifically I think they said this one's probably Volt Typhoon, uh, which was a new one that I wasn't aware of. Uh, I hopefully that Volt Typhoon and Salt Typhoon, uh, won't, uh, join together to create Captain Typhoon, which of course for all of us nineties kids would be the ultimate form of, uh, hacker, uh, with the, you know, crystal body and green hair and everything. Um, now this, this means that there's an escalation, right?

Is they are trying to do what they did in the hacking campaign that we first heard about late last year, where they got a foothold into networking devices. Now they're trying to do it with systems that process that data as opposed to transiting that data. It's the thing that people do.

They want a foothold into the system. They want to be able to decipher things going through it. And by creating the secure connection and effectively having the system dial out through 4 43 or what have you, it's uh, it's pretty hard to, uh, look at that encrypted traffic and do something about it.

So beyond the lookout kiddos, if be LAPD starts dropping certificates on your machine and you don't live in la you might be a really good idea to double check that. And I'm hoping that whatever certificates that they're using that are invalid or can be revoked will be revoked very soon by whoever issued them or if they're self signed. Uh, simply because this, this is that escalation phase, right?

Once that certificate's on your system, they can do anything they want with it. And there's not a whole lot you can do to stop that. So I hope somebody is paying attention at the wheel here.

We wanted to take a closer look at an event that happened last week that several of our futureum group folks were taking part in, and that is the annual Amazon Web Services Security Conference, also known as AWS Reinforce for 2025. AWS introduced some new key security upgrades, including expanded identity tools, enhanced code and threat detection, along with their inspector and guard duty tools, as well as easier deployment through improved web application firewall and just plain old firewall features. Uh, new ciso, Amy Herzog, no relation to the deep voiced guy, um, emphasized in identity security as being a key component while AWS in general reinforced its focus on automation, secure deployment, and ecosystem collaboration.

Now, Al you and I weren't there because, well, we were focused on some other things, but there's an excellent writeup on the futureum Group website that we wanted to highlight. What were some of your big takeaways from reinforce based on the excellent writing from Fernando and Krista and Mitch? Well, I think it, it's just a continuing sharpening of the pencil, uh, keeping things very focused on security.

At A-W-S-A-W-S is always, uh, belief security was very important. Uh, even though they give you plenty of tools to remove security from yourself as a, as a customer, um, that's a, an interesting part of that shared responsibility model. I've always been a fan of, uh, AWS inspector.

Uh, when I was teaching the AWS training courses, it was one of the things I always demoed was, let's just scan over everything you've got and see what vulnerabilities are here and let's better yet build that into the automation system that you're gonna use to build out your infrastructure. Put it in your ci cd pipeline. Um, I like that guard duty is getting some more capabilities.

Guard duty is the, the real time analytics, and it was one of the first places that I saw, uh, observing what's going on with DNS as being used as a way of identifying threats, uh, that are within your organization. Of course, that's a pretty well known technique these days to identify whether, uh, data's being exfiltrated by DNS or whether, uh, requests are being sent back to command and control through DNS. But guard duty is getting more awareness of other parts of infrastructure, being able to see in real time things like, uh, the, uh, Kubernetes EKS service logs and being, getting more insight about what's supposed to be happening and what's actually looks like threats going on.

So it's nice to see continuing improvements in there. Uh, there's some challenges around configuring web application firewall and cloud front and, uh, the network firewall and getting things consistent and happy together. And the more of that that can be automated.

And that's one of the things we see in here is threat feeds being sent in, uh, to the network firewall, not just web application firewall. Uh, we also saw in the SIM improvements to AWS Shield, which is a AWS's DDoS protection, um, or another string of the DDoS protection components that AWS has. I think all good, great improvements to see continuing work in their, um, seems, seems to be really positive stuff.

Um, Tom, you are much more deeply in the weeds of the networking security elements here. Um, what do you see in this? I saw Amazon's attempt to try to show their users that they do care about security because the lack of security, or in some cases the lack of tools to prevent me from shooting myself in the foot could potentially drive customers off of the platform.

And we've seen this time and time again, how many times have we talked about a story here on the rundown, or have you seen something published online of misconfigured permissions on an S3 bucket or some kind of weird access policy that allowed people to jump into the, the squishy center of your VPC? And then the next thing you know, they, they own everything. These are not hard problems to solve, and I know they're not hard problems to solve because we solved them.

We solved them years ago by creating robust perimeter security by allowing things like VPNs. But the key is that we hardened the perimeter before we started building the squishy center. And that is an opposite relation that you have in cloud platforms.

Like at Ws, you wanna build the squishy center first because that's where the value is. And we'll, we'll worry about fixing it later, we'll protect it later, which is the why that we all tell ourselves, we'll, we'll do the hard stuff later as long as it just works. And then that becomes, well, I don't wanna break it because if I break it then someone's gonna yell at me.

And too much of our system is relying on this so we'll, we just won't worry about it. And then guess what? You're on the news and you don't really want to be on the news for stuff like this.

I think that Amazon realizes that the majority of their customers are not security gurus. And so they need to make this as simple as clicking a button. So making easy to deploy web application firewalls is a great start.

I can remember seeing some of the very first web application firewalls, like, I wanna say it was back when I was a delegate at Tech Field Day and we saw anos right after they got bought by Juniper. I was like, man, that's a really cool thing, really powerful, really complicated. We've distilled the essence of what a web application firewall can do down now so that it's a lot easier to deploy.

But you've gotta bridge that gap. And the gap is if they're so easy to deploy, why aren't you deploying them on your systems? And I think that that is a challenge that Amazon is gonna continue to have.

They can do everything for you. They can make it easy to deploy. They can make the buttons green and red and make you click on them, but you have to be the one to do it, just like you have to be the one to secure your S3 buckets to do all of the things.

And if you don't do those things well, Amazon's not gonna take the blame for you because all the tools are there, but all it takes is going to a provider like, um, I don't know, a Microsoft or a Google, where all of those things are automatically done for you. And now it's like, well, guess what? I don't really care.

Go for it. Uh, we'll just move all of our secure workloads over here and we'll let the stuff we don't really care about running AWS 'cause it's kind of cheap. And I like this Route 53 tool.

So I, I don't know, maybe at the end of the day Amazon will keep a few more customers, but with a new CISO in the house, they have to be iterative on this. They have to be ready to create user friction to provide better security. And look, I know, and you know, that creating friction with users is the fastest way to get security disabled, but in this particular case, lack of friction is going to cause people to slide right into those news articles where everything keeps getting owned and shared and stolen and nobody wants that.

And if you get embarrassed enough, you'll move off of that platform. I mean, Al do you, do you think that people are willing to pay a little more to be a little more secure? I think smart people are definitely prepared to pay a little more, but I think you, you've really hit the, um, hit the nail on the head when when you talk about it being essentially lazy, you've got to make your product work for the people who are lazy or the other way to look at it, the people who are busy doing something else.

And so I think this is where AWS is a little bit being bitten by the way they've structured the organization, their two pizza teams builds a service and has free freedom and autonomy to do their own thing. Doesn't make it easy to unify everything. Doesn't make it easy to bring all of the pieces of that security solution together.

And you've gotta make it easy. You've gotta make the security thing easy. So I'm not sure that I agree about, um, adding more friction.

I think you're actually reducing friction when you make it easy to build the security in. But if you force people to have a hard time building in the security, yeah, that's when you're gonna fail. You.

You've gotta make building security on top of whatever your application is. Simple, seamless, easy to deploy without just allowing any, any, any, any, any. Well let's hope for the best because if it doesn't pan out, uh, Amy Herzog may be out and we may be forced to listen to keynotes from Warner Herzog, which honestly would be really cool to hear, but really soul crushing because anything that man says is just dour.

But you know what's not is upcoming field day events. 'cause we try to keep those happy and cheerful and bring you lots of cool stuff. The next one's coming up in just a couple of weeks because I'm gonna be back in Silicon Valley for networking field day.

We have, uh, great presentations coming up from companies like C Packet and HPE Aruba Networking. com and check out the full list of people who are gonna be presenting and the full lineup of delegates. There's several new names on that list, you're not gonna wanna miss them.

Then we're gonna skip ahead another month 'cause I hear it gets hot in the summer, but we are gonna be in Cleveland, Ohio of all places on August 19th and 20th for Tech Field Day Extra at Share Cleveland. That's right. It's gonna be a real quick drive for my friend Steven Foskett to head up and talk about all the cool things happening at Share Cleveland.

There'll be more details to come on the Tech Field Day website and then we're jumping into my favorite month of the year, September Al what have you got coming up? Well, once the temperatures start to even off a little bit and it's a little more tolerable to be up in the Northern Hemisphere in September, I have AI infrastructure Field Day returning and it's already starting to fill up just like the last infrastructure field day got massive. Uh, so we have Broadcom and tis, we have uh, what's my other screen?

Uh, we also have Hammer Space and already signed up and that's making us for a, a good event when we're quite a way out from it. So I'm looking forward to having another massive event and a lot of fun back in the Valley area. And of course a couple of weeks after that, Tom, you get the Batten back for Security Field Day again.

I do, we are gonna be talking about more great security things because you know it's gonna be post Black hat and everyone's gonna have all their stuff sorted out. They're gonna want to talk to us. We actually have our first presentation from a company called Square X.

You can read more about what I thought about Square X's, interesting browser security techniques if you head over to my LinkedIn page. But we will be expecting more great companies to join up there very soon. com and uh, check those out as they are listed.

And you might wanna do that for all of the other things that we've got going on because I can tell you for a fact there's at least two more things that are gonna be listed on the website very soon that you're not gonna wanna miss. But I'm not gonna tell you what they are because in the industry we call that a tease, but we won't tease you because you know that we'll be back next week with more great tech Field Day rundown news action. And you're probably thinking to yourself, well Tom, I don't wanna miss that because if I do, I'm gonna be heartbroken and I'm gonna have to listen to a lot of Werner Herzog novels.

Don't go that far. All you gotta do is subscribe to our YouTube channel so you get notified whenever we publish a new video. Or you can check out our podcast feed where you can listen to the dulce tones of my voice and Alistair's as well on, uh, your favorite podcast application of choice, maybe when you're out, uh, mowing the Yard, or in Al's case, uh, we're using the snowblower.

I don't know if they snow in the southern hemisphere, but you can also, uh, check out the other great stuff that we published on the Future and Group website, including some of the articles that we linked here today, as well as Techstrong It where we publish a lot of the great coverage from the events that we've been doing. We've got some new posts going up that you're gonna wanna check out some perspectives that we have on some great things. And don't forget to tune in next Wednesday afternoon for the next episode of The Rundown, when we'll be one week closer to Christmas, no matter if that's warm or cold for you.

But we'll also have all of the great stuff that happened from the news, probably some coverage of HP Discover since that's going on this week. We'll, uh, round up that news and be with you then. But until then, for myself and for Al and all the great other people that do the Tech Field Day rundown, stay cool everyone, unless you're in the northern nor uh, Southern Hemisphere, in which case, stay warm and we'll see you for the next rundown.