Practical AI for Business Growth | Utilizing AI Ep. 1

We are diving into enterprise ai, the practical applications on this, uh, brand new podcast from the futurum Group, tech Strong and Tech Field Day called Utilizing ai. Join us every Wednesday as we dive into the news of the week. And on this episode, Nick Patience and I at AI Field Day are gonna talk about, well, the podcast as well as what's going on in the industry, what companies matter, and what the latest earnings and CapEx spend news means for this AI industry.

Welcome back. We are here in Santa Clara for AI Field Day, and we are doing something well, a little unusual to wrap up field day. This time, we are gonna record a live episode, uh, the first episode, I guess you could call it Episode zero of our new AI podcast, which brings together, uh, basically, uh, all of futurum has to offer when it comes to ai.

So we're gonna have, um, myself, uh, Steven FST from, uh, the, uh, tech Field Day side. We're gonna have some folks from the Tech strong side, and we're gonna have, of course, some folks from the, uh, research and and analyst side over at, uh, Futurum itself. And we're gonna meet every week and have a podcast focused on ai.

I, if this sounds familiar to you, well, congratulations. You must be a subscriber to Security Boulevard, which is the podcast that we launched about a month ago, which has the same format. Essentially, uh, every Tuesday they publish a new security, uh, rundown.

Um, and, and that's really what we're going for here. So bear with me for a moment. We're gonna be introducing this.

Uh, we may have a little bit of, uh, behind the scenes fun here if we flub it up. We're gonna do a little edit for the final podcast, but, uh, we're going live here anyway. Uh, one more thing I wanna mention before we start is, uh, as I said, we just finished AI Field Day seven.

Um, I wanted to announce, uh, AI Field Day eight. Yeah, we'll be back for another AI Field Day event. Uh, it is May 13th and 14th.

And frankly, given the amount of interest we've had, maybe May 15th as well, uh, we'll be back in, uh, the Bay Area. We are gonna have a bunch of, uh, great AI companies presenting to an incredible panel of delegates. Once again, uh, for AI Field, A eight, uh, we actually already have two companies, uh, signed up for that one, which is kind of incredible.

We've got Hammer Space and Selector, uh, signed up to be there. And I actually know of two more companies that are, uh, filing paperwork, uh, for signing up as well. So if you keep an eye on the tech field, a social media, you'll see announcements of that as well.

So AI Field Day will return real soon. Tech Field Day itself will return actually very, very soon as well. We've got Networking Field Day, November 5th and sixth.

We're gonna gonna be at CubeCon, uh, the week of November 11th. We're also gonna be, uh, at, um, Commvault Shift, uh, that week. And then we've got AI Infrastructure Field Day in January.

So we've got a lot planned. But, um, the best way to keep in touch with that, if you're in the AI space, is to follow this podcast that we're recording. So let's, let's do this.

Let's dive in, um, and record the first episode of utilizing ai. Uh, here we go. Actually, put this down here.

'cause I don't think I'm thirsty. Is that in the shot? There we go.

Uh, people watching at home, they're like, oh, that's how it goes when you're recording stuff. You, yeah, usually I've got like a drink over there and, you know, all sorts of stuff just off the camera. Um, here we go.

Welcome to utilizing ai, a brand new podcast focused on the application of artificial intelligence from the Futureum Group. Each episode brings together diverse perspectives to explore how AI is transforming different sectors of enterprise IT and other industries. I'm your host, Steven Foskett, president of the Tech Field, a business unit here at the Futurum Group, and today I'm very thrilled to be joined by Nick Patients VP and practice lead for AI at the Futurum Group, who will be a co-host with me on many of these episodes.

Nick, welcome. Thanks, Steven. Good to be here.

Well, it's very good to have you here. I mean, this is, uh, your focus with, uh, rums, uh, research and, and, and analyst side. Uh, I cover it for the, uh, of course AI Field Day.

And, uh, I also participate on the Text Strong Side, and we're gonna have some folks from, uh, the various text strong channels, including Text Strong AI joining us as well. But, uh, if we could start out, Nick, maybe you can talk a little bit about the AI practice at the Futurum group. Sure.

Happy to. So, so, yeah, I'm the ai, um, platform's practice leaders as we, as we call it. So, uh, everybody, uh, Futurum is an AI analyst, uh, to, to some extent, or EE every, We like to joke that every Tech Field day event is just AI field day.

This is true with a different flavor. Yeah, It is kind of permeating. I it's a general purpose technology, isn't it?

So it, it kind of permeates everything. But yeah, I'm, I'm the kind of the principle one who gets to spend time focused on AI almost for the sake of ai. So I'm focused on the stuff that is peculiar to a a, to ai, um, to, that enables, you know, applications to be built using AI models to be trained model, to be tuned, deployed, run, um, all that kind of stuff.

So it really does, um, for me, it, it spans from the chips to the applications and everything in between. Meanwhile, we have people who are focused on chips and applications and storage and networking and, and all these other things as well, which are all, uh, integral parts of, of getting AI to work, um, you know, efficiently organizations. Yeah.

And I, and I think that we're probably gonna see a lot of those people as well. But, uh, I wanted to give a chance to introduce you to the audience right off the, right off the bat, because I think that you and I are gonna be kind of the primary drivers of this particular, uh, podcast series. Uh, but of course, in addition to that, uh, this goes out on the Futurum, uh, sister company, uh, which is Textron, which is the, uh, our media, uh, arm.

ai is the website that we're gonna be primarily focusing on with this particular podcast. Kind of like we have a Security Boulevard website with a Security Boulevard podcast. This is gonna be called Utilizing ai.

It's gonna be on the Techron ai, uh, website. And of course, from the Techron side, I'm thrilled to have folks like Mike Vard and John Schwartz joining us now. They are not analysts by any means.

They are veteran journalists. And in fact, I have been reading John and Mike's work for many years before I got to know them, before I got to work with them as part of Techron. And I am so excited to bring their, um, incredible perspective on the IT market, uh, to bear.

They actually, uh, are part of the, uh, Textron gang, which is the daily, uh, every weekday Textron, uh, news show, and I am happy to appear on that. I know you've been on that Textron gang too, right? Mm-hmm.

And, uh, many of the other folks from, uh, from Futurum join Textron Gang occasionally, but, uh, you know, frankly, Mike and John are fixtures over there, so it's gonna be a lot of fun to have them. And of course, we're gonna have some folks from research joining us too. Yeah, Sure.

It's a couple of my colleagues in particular. So, um, Olivier Blanchard, so he focuses on, um, what we call AI devices, but simply, yeah, the end points, but whether they be, you know, laptops, tablets, anything like that. And then the components that go into them.

And so obviously that's where, you know, as we look forward to a kind of future of where inference is the focus, that's where the inference happens. And so it's always, uh, you know, it's always interesting getting his perspective, uh, on what, on what's going on there. And he tracks all the major companies, say, be the, be the ones that make the machines or make the components, um, go into them, and then what they're being used for.

Um, so Olivier would be on, um, you know, for, uh, quite regularly. The other person I'd highlight is Brad Shiman, who is our practice lead for data and analytics. And as we know, AI is nothing without data.

And so he's, um, yeah, he's been like me. He's a, you know, a veteran analyst, been around a long time, um, and he's really digs into, um, you know, how data is being used, how pipelines are built, um, how it's, how processing happens, um, and then the analytics, um, that, that, that happens as a result of that. And he's, you, he's deeply technical and he, but he very good at under, you know, expressing, uh, how these things are used in, in, in enterprises.

And, you know, we're utilizing ai, um, title, um, fits in very well. Yeah. So with, with regard to Brad, I gotta say, um, I'm really thrilled to have him around because he was deeply involved in the development of the Futurum Signal, uh, which is our new, um, uh, analyst report that we're doing.

He also is one of the go-to guys for me, internal with the company when I really need, uh, I'm not really a practitioner voice because he's not really a practitioner anymore. I mean, he's, he's really an analyst, but, uh, he understands those, the way that people think, the way that people use these tools. Mm-hmm.

Yeah, he does. He's, I mean, for, for our work in Signal, he's, uh, probably spent more time in, uh, writing Python. He has writing words in his, his analyst reports in the last, uh, couple of months.

So yeah, he, he, he knows how to get his hands dirty, um, with his stuff. And you say, I understand it from, from, from the, uh, the user's and the practitioner's perspective, and He's really doing it too. Yeah.

Which is, which is great. 'cause a lot of us, to be honest, um, you know, it's been a little while since I've been in a ice cold data center, uh, plugging in cables. But, uh, you know, I, I do, uh, actually, when it comes to ai, I do actually get my hands dirty on this stuff too.

And I've been building my own, uh, agentic pipelines and working with various things, uh, to try to keep myself fresh. Um, so those are the folks that we're gonna be joining us. Now.

Most episodes are gonna have two of us, or three of us, uh, depending on who's available, depending on who has, uh, news of the week, who has experienced something, because of course, with Futureum, another nice thing is that we have enough people here that we attend most of the major industry events. Mm-hmm. Um, this week, uh, when we're recording this last week, when you're hearing this, uh, we attended, uh, GTC in, uh, Washington, DC we attended, of course, AI Field Day.

Um, what other major events are there, uh, that you're gonna be attending in the AI space that we might, uh, see some news from? Well, I've been at Adobe Max in Los Angeles this, this week. So many people may not think of Adobe as an AI company, but they, um, they're very much at the forefront.

If you think about the kind of two, um, uh, realms where AI has had a direct effect on people's jobs. One is creativity, creative professionals, the other one is coders. And so, you know, this is one, you know, I look, I always look at Adobe for that, for that creative professional stuff, other things on the horizon.

Um, Microsoft Ignite is in two or three weeks time, uh, in San Francisco. Um, and then the, you know, the one sort of anchors the, the, the, the, the end of the year is AWS reinvent in Vegas. And, um, we will be representing, I'll be both of those personally, and there'll be others, uh, other colleagues at those.

And then we, yeah, we go to all the, all the big, um, all the hyperscale. So Google's event, which is in, usually in April. Um, and say Microsoft and a s and then NVIDIA's GTCs.

There used to only be one, um, post COVID. There was only one immediately. And then now there's spawning, you know, multiple GTCs.

I was the one in Paris. I was a co-host of the pregame show there. Mm-hmm.

Um, and then obviously we've had Washington, um, and there's always, um, announcements going on there. And I was watching, um, Jenssen's keynote from the Washington, um, uh, GTC. And he's, you know, it's amazing when you hear some keynotes and you hear his and his is, you know, always about, you know, we're not, we, you know, he is announcing products and launching products, but also, yeah, we're gonna change the world, and this is how he's gonna change over the next five to 10 years.

I mean, he's obviously a big guy for visions, um, and, uh, he has, uh, obviously been, you know, a visionary in, in, in that space and how he's propelled his company forward. But yeah, we'll be, um, represented at every, uh, every, every major conference you can think of. Yeah.

And, and as you mentioned, I mean, AI is, is everywhere. Uh, I was at NetApp Insight a couple of weeks ago. Um, most of the topic was ai, we're gonna go to CubeCon.

Mm-hmm. I'm sure that most of that conversation is gonna be at least AI adjacent. Mm-hmm.

Um, let's talk a little bit about the companies. Of course, you mentioned Nvidia, they are the big green, uh, 500 pound gorilla of the AI industry, a $5 trillion company as of this week, right? Yeah, Yeah.

The first time. And I mean, it was only, I can't remember, it was only a few, couple of months ago when there were 4 trillion, and we thought that was, uh, amazing. They grow up So fast.

They do. They do. It's, um, yeah, it's a bit of a, you know, 35 years old, uh, um, overnight success story.

Um, but yeah, that's, that's the main one. Also this week, I guess we've seen, um, you know, just recently the results from Amazon, um, Microsoft and Google, and I guess what, uh, people were looking for. There were signs, um, of a couple of things.

You know, the cloud revenue growth, um, and then the CapEx investments and on the cloud revenue growth, they all delivered. I mean, some of them Google kind of, there was, you know, not surge past expectation, but certainly went past them. Um, and the others were, you know, certainly, you know, showed strong growth, um, which is, um, there's a lot of people out there looking for the stumbles on these, on these companies, and they, they certainly didn't do that.

And, um, and so it's, it's really indicative of, you know, what is driving that, that's enterprises paying for cloud. So they are, and why are they doing it is largely driven by ai. Yeah.

And so this down, this could be down at the, the compute level, the storage level, but also further up the, up the chain. They all all have, uh, you know, big tool stacks and increasingly have applications as well. Um, and so the thing that's really indicative of, um, you know, where enterprises are spending their money, so this is not the, the tech industry spending money on the tech industry.

This is, yeah. Manufacturing, banking, insurance, healthcare, spending money with, with, um, with cloud providers. Yeah.

And the, well, I, Let me jump in on that. Yeah. Because, um, I, well, first off, I'm gonna, I'm gonna play the skeptic mm-hmm.

Uh, on this, on this show, uh, because somebody needs to, because there's a lot of breathless pronouncements about AI here. Uh, I think you're a hundred percent right about those, uh, major, uh, cloud providers. They, they reported better, uh, you know, a continuing upward trajectory in revenue.

They reported, uh, greater CapEx spending, uh, growth in CapEx spending. In fact, somebody was just sharing, uh, I love this. I, this, uh, Google now spends more money on servers than the entire industry spent on servers in 2009.

And that is wild. And also indicative of the strength of this industry that we're in, that, uh, these companies have become so huge that they're bigger than the whole industry, not so long ago. But that being said, um, and, and of course we should probably mention Oracle mm-hmm.

As well as another big, um, uh, beneficiary of the cloud, uh, boom. Uh, they certainly have been really capitalizing in AI especially, but I think we should turn and, and think as well about some of the companies that aren't cloud providers, because most of the revenue that those companies are, are, uh, reporting is cloud revenue as opposed to AI revenue. Yeah.

Now, certainly there is a lot of AI revenue, but I'm wondering, um, also just today we saw a substantial price, uh, you know, market, wall Street stumble for meta, uh, meta reported, um, strong ish revenue. They reported, um, increased investment, and yet their, uh, share price stumbled. And I think that that's because, uh, really people are looking at that and saying kind of, where's the AI revenue for somebody like Meta as opposed to somebody like Google?

How do you feel about that? I think Meta is a completely different kind of company to, to the other three completely different. I mean, yeah, it's a social media company with the driven by advertising.

I mean, if you take Google as a contrast, uh, and even Amazon, Amazon has a humma humongous advertising business, but it has the other businesses as well, obviously the retail business and AWS and Google. Google has obviously is search driven ad business. And you know, that's that kind of, you know, it can enable it to, to grow its cloud business, enable it to fund, to, uh, fund it in his early days, um, before it got up and running has its own kind of flywheel effect.

And I think Matter is, is an interesting one, but I, I kind of look at them, you know, quite differently. And they've got, they've got obviously the advertising, um, revenue to, to fund the CapEx, but that is their business. That's, that is their only business.

And so it said, there's no other, they, they're not an enterprise play. They don't have, you can't buy compute services from Meta. Uh, maybe you should be able to, maybe they should have done that.

Um, but they haven't done that, and they maybe too late. Um, and not no, no evidence they're gonna either. Yeah.

So, well, it's, It's interesting, isn't it, in, in an alternate universe, we could be saying, well, of course people buy compute services from meta, if only Google had offered, uh, their infrastructure for, uh, for use as a service. You know, because they really did start off from the same starting point, and one went right, and one went left, and look where they are now. Yeah.

And you mentioned Oracles, I think that's the opposite example where you have a company, um, that is obviously a traditional software company, and also they have hardware. They bought some microsystems many, many years ago. Um, and that was a good job for them, it looks like now.

Um, but they're not, they don't have an advertising business, so they are, so they, this is, this is where they are under, you know, arguably more financial pressure because they haven't got this kind of comfort blanket of, of advertising revenue over which, so they, you know, they've gotta borrow money. Um, and, you know, their, their CapEx spendings obviously huge compared to the, um, the amount of, you know, cash flow they generate. Um, which is an interesting contrast.

Lemme say it's transforming their business at the moment. I mean, let's see where they are in a couple of years. Um, compare compared to the other.

'cause obviously they're investing it, they have to have that to pay off, um, in Yeah. Within a, you know, couple of years because they haven't got that other revenue stream and they're obviously in a, you know, a lower margin, um, you know, business to a certain extent. Yeah.

Well, and I, and I do wanna clarify for the listeners, we're not intending this to be a financial show. This is not, that's not what, what what we are, what we are trying to see here is essentially that core question that comes right down to the name of the podcast utilizing ai. How are companies utilizing, how are they making practical use of AI to accomplish the goals of their business?

Hmm. And these companies that we've just been talking about are the biggest players in the world when it comes to utilizing ai. Yeah.

Essentially, they are buying hardware. They are pouring resources into, uh, software development, into data science, into building AI models. They are doing more, uh, again, if you, if you think about what I said about Google and, and their CapEx, uh, Google probably spends more on, uh, basic research in AI than the entire world did in 2009 as well.

Hmm. You know, they are absolutely trying to find the revenue stream there. And that's, I think, the core question for everybody, whether they are a finance company, healthcare company, energy company, uh, you know, whatever it is.

They're also having the same, asking the same questions that Google is asking, that Meta is asking, that Oracle is asking, like, how does this technology, how does this obviously transformative technology, uh, how does it help my business? How do I make practical use of it? And how do I, uh, ultimately get revenue from this instead of pouring revenue into it?

Into it? Yeah. So talk to me a little bit about that.

Um, how are, um, companies and other industries utilizing AI and how can we take lessons from these big juggernauts? Yeah. The way I look at it for, for enterprises and the use, they, they're, they've, they've got this tension, they've got this, um, there's FOMO on one hand, which is like, we hear about all these great things, including the hyperscalers.

Yeah. But you might be a bank, so you don't, you're not in the same business, but you are, you do have that fear of missing out. I don't wanna turn into the, you know, the blockbuster video of this whole scenario.

Um, but you have a business to run every day and, you know, 24 hours a day. And so there's a, that there is that tension. So what they've done, um, what they've gone for is, is the low hanging fruit.

They did exactly the same thing in the, in the kind of prior age of enterprise machine learning. So 2016 to 19 period. Um, and that's go after the horizontal problems, the customer service automation, um, those, those kind of, that kind of, um, is, is the, is the initial, the initial, um, area where they're looking to, to automate processes.

Um, and then they sort of work on more complex, um, processes as they go along. The challenge organizations have had, and the ones we speak to, and the ones we surveys, we do a lot of, a lot of surveys at Futurum is, um, is that the, you know, they were investing in it, say in that kind of 10 years ago period. Um, then you, Chad, GBT happened almost three years ago now.

Um, but that feels like a very long time ago. And then suddenly, you know, really at the beginning of this year, um, they were told, hang on, generative AI is important, but Agen AI is the next thing. And you've gotta invest in that.

And obviously, they're all dependent on one another. AgTech is very much driven by generative ai. And so I think there is a kind of, there is a, yeah, there's some skepticism as to, you know, where should I be placing my bets?

Um, but I think you, what they, they they're looking at is, are those kind of use cases. I'm glad we've called the podcast utilizing, um, AI for that reason, um, that are, that are horizontal. And then what will happen, um, and we're already seeing at a certain extent, is it will go vertical very quickly.

Mm-hmm. So if you're an insurance business, um, you know, you will have, there'll be certain workflows in your, in your business that you will automate using agents. Um, and that's completely different than if you're a company that, you know, runs hotels or makes cars, because it's all driven by data.

And so, you know, your, if you're a car company, your data set is completely different than than a hotel company's data set. Um, and your processes are gonna be different once you get beyond those, those kind of, um, you know, sort of standard kind of back office and some, some front office, um, processes. So I think it's, it's, it's important for companies not to try and compare themselves, you know, to, to Google and Microsoft and AWS to, to a certain extent, unless you are literally trying to be them, um, and focus more on, um, you know, how can, how can we, we automate processes.

After all, as I like to say, the history of the software industry is the history of automating human processes and has been for 60, 50, 60 years. And now we're at the stage, though, with ai, um, that it can automate far more complex processes. And now it has the ability to quote, understand unstructured data.

Obviously it doesn't literally understand, but it acts as if it does. Um, you can bring in natural language, um, both as the input and, and use it as an, as an interface, which is, that was basically impossible three years ago at any scale. Um, there's always been NLP around, um, but it's been incredibly difficult to use.

Um, and so, you know, the, the advent of LLMs kind of dealt with that issue to a certain extent. And now we're kind of looking at more specialized models, smaller models, uh, and and things like that to, to get down to, you know, very specific industries and then even companies Yeah. Automated like that.

Yeah, Absolutely. And, and, and I think that, um, this term, agentic ai, which we've been talking about quite a lot, is very interesting as well, because, um, on the one hand it has sort of a functional description, which is what we've been using on the, uh, sort of the, the, the, the parent of this podcast called Utilizing Tech, where we, uh, we have been talking about AgTech AI this season. com.

Uh, on that, in that discussion, we've talked about exactly what you've said, which is that, um, AI agents are essentially designed to replace people or replace the work of people or augment people. Companies are seeing that as a way that they can get some return on investment or take advantage of the potential of this technology. And so, I, I wanna talk about another thing here, and that's that, um, Futurum recently announced, uh, uh, agentic AI platforms, um, uh, report, uh, showing kind of who's, who's doing especially well, uh, as a trusted enterprise partner for AG Agentic AI is the, is first off, is that a, an adequate way to describe the topic of this report?

Um, yeah, I, who's doing well? Who's offering the most comprehensive platforms at the moment? Um, and you know, we, we, we will re revisit this multiple times a year.

I think there's definitely a, um, there's a, there's a challenge, there's a battle in the industry, if you like, for who would be a plat. You know, everybody wants to be a platform vendor because that's, you know, incredibly lucrative, sticky, all the other words. Um, you, you think of, um, versus, you know, being a provider of a very specific agent that has to go and run on another company's platforms, but they can't all be platform vendors.

We don't need, um, that many. Um, but so they will shake out. But obviously we had in, you know, we had, you know, um, Salesforce and Microsoft, um, and IBM and others, uh, in our, in our signal, um, when we're looking there in ServiceNow and SAP, so that you're looking at a mixture of, um, large application software companies like SAP and, and ServiceNow, the cloud providers who, you know, already kind of cloud platforms.

And then you have other specialists, uh, like companies like Glean that have kind of come out of a, a search background and NLP background, um, and have, you know, quickly identified not only specific problems with the organizations, but who the buyer is of the software that solves those problems. Mm-hmm. And like UiPath, which is, um, a champion of robotic process automation, which, um, I'm not saying RPA is dead, but it's certainly, um, we, the organ, the industry's rapidly moved on from it that was using scripts to automate things so ass an automation play.

Um, but now if you can use agents that can actually, you know, do the, the automation themselves, rather than being told exactly what to do each time, then you are into a whole different scale. com/help, and how agentic that actually is. Mm-hmm.

And it's amazing how not that agentic a lot of it is, and what I mean is it's, it's still using Gen ai, but it's using, you know, that somebody has to prompt, um, for it to then give you an answer versus it giving you an answer. You know, so, and, and dealing. And so there's a long way, long, long way to go.

Um, you know, if we think we're at the early, still early in gen ai, we're incredibly early ingen ai, like if we think of Scur, we're in the bottom of the, the, the flat bit at the bottom. Um, but you don't wanna miss it when it, when it, when it jumps up. So it's, it's, it's incredibly early.

We are trying to sort out the wheat from the chaff. That's our job as analysts. Mm-hmm.

Um, and we're pretty good at it. So a lot, a lot, lot of us, like, you know, I've been looking at AI for 25, 26 years, have kind of seen all the waves and we can kind of spot what's real and what's not. And that's the kind of service we provide to the, uh, to the future and client base.

And we will continue to do that. And of course, the, the, to me, the interesting thing about the signal also is that we are trying to, uh, really differentiate this because of the speed at which we can process this data thanks to yes, agentic ai. Mm-hmm.

So we are literally using these tools to help us accelerate our own understanding of the agentic AI market and the rest of the markets that we cover. So there will be signal reports in more, uh, well, there have already been in other areas, and there will be more in other areas. And all of those will be kept much more up to date, much more, uh, fresh and responsive to the news and developments in the industry thanks to the use of Agent ai.

So we are literally using this technology at the same time that we're evaluating it. Yeah. Using the technology to produce the reports about the evaluating the technology is kind of game very meta.

Yes, It is. Uh, apologies to meta the company. Yeah.

Small m Um, and, and so of course we just had AI Field Day, um, we talked to some companies there. Uh, which ones stood out to you? And, um, which ones do you think are relevant to the audience here?

Well, I'm, obviously I was only one, one of the two days. So, um, I did hear very good things about HP though on the, on the, on the previous day. Um, the, The, yeah, they had a real nice, um, very partner centric and, um, very sort of trusted enterprise provider messaging, which I think is really the right way to go about this with the, uh, enterprise Yeah.

And For what they offer as a, as a company. I think that makes a lot of sense. I guess, um, you know, today, you know, we, I've, you know, when we're recording this, um, yeah, I guess the one that stood out to me was Articulate, um, which was originally a spin out from Intel.

Um, and that's a really interesting, um, company that is putting agents to work without actually shouting from the rooftops. We're an agent platform, but they are, um, and they've, they've done a really interesting, interesting, um, job of going after domain specific models, um, and domain specific agents, um, in sometimes in quite sensitive industries, um, that don't like a shout about it. Um, but also, you know, and deploying it on the cloud, on prem, in air gap, completely air gap scenarios.

Um, so they were doing some really interesting stuff. And we also heard, um, really interesting stuff from, from Digitate in the, in the kind of, um, IT service management space and IT support, um, and from Nutanix, which is, you know, one of the kind of fundamental data layer providers. Mm-hmm.

Um, and although, you know, they didn't talk to us too much about the agent stuff, they were different focus. What they are focused on is obviously enabling companies to build those data pipelines that you need. 'cause very few companies are out there training models, um, but they still need to, you know, build pipelines for, for analytics purposes or data science purposes.

Plus they are gonna do fine tuning. Mm-hmm. So, yeah, it was really interesting, you know, going, going, digging really deep.

I speak to a lot of vendors all the time, but then you go, kind of go much deeper in, in field day scenario. Yeah, Absolutely. And, and, uh, I'll mention the other companies as well.

Um, you know, speaking of data, we talked to Haiku. Uh, they are experts at, uh, basically protecting data anywhere, um, across SaaS environments, and they're bringing that, uh, experience and capability to ai. Mm-hmm.

Which is great. Uh, we also talked to Fortinet about their 40 AI approach, uh, which is more of a suite of products that, um, uh, really kind of brings to bear that sort of enterprise understanding of, of security, uh, risks and tries to solve some of those for ai. So if you're interested in that, check out the Tech Field Day website.

Uh, we are posting the recordings of these sessions, basically as you're hearing this. And, uh, those will all be online at YouTube slash Tech Field day and streaming on the Techstrong, uh, website as well. So this is the sort of conversation we're gonna have every week here on utilizing ai.

Uh, we will be, uh, talking about what's going on this week. We'll be talking about what's top of mind, and we'll be talking also about the, the major topics, the major themes and trends in the industry. And, uh, we're specifically not going to set a, uh, topic until the week of the episode because we want it to be, uh, reacting to everything that's happening.

This is a very fast moving industry. There are new announcements all the time. We didn't even get to some of the announcements.

I mean, uh, Nvidia, uh, they, they, they announced Vera Rubin, uh, we didn't even mention that. Mm-hmm. Um, you know, it's, it's wild everything that's happening here, uh, and how quickly it's happening.

So, uh, our commitment is we're gonna have this, uh, podcast be it is gonna be live every Wednesday. Um, so please do subscribe, find utilizing AI in your favorite podcast application, and we will have a new episode for you. We will be, uh, covering what's going on in enterprise it.

And again, our focus is on practical use cases. So this is not an opportunity for us to, you know, uh, talk about finance. This is not an opportunity for us to talk about speeds and feeds or, uh, to complain about what's wrong with ai.

And you know, how, how it's affecting, you know? Yes, it, it does. And yes, we will talk about that, but it's not a chat show.

This is basically what you need to know this week about utilizing enter AI in the enterprise. That's our commitment to you. So thank you, Nick, for joining me for this first episode of utilizing ai.

Uh, we are recording this, as I said here at AI Field Day, and it's been great having you join us at AI Field Day and having the other Futurum folks be involved in the Tech Field Day events. Um, as we wrap up the discussion, uh, a little call to action here, where can people connect with you? Where can they find out more about this and continue some of these conversations?

com, and you can find me. Um, I'm on Twitter x Nick patients, um, I'm on Blue Sky and, uh, and obviously LinkedIn. com will be the, the main Place.

And as for me, uh, most of what I do gets published on the Textron side. So you'll see me on the Textron Gang pretty much every Tuesday. it, uh, the rest of their sites as well.

com, um, and of course, on the tech field, a podcast, uh, as well. And, uh, you can find me on social, um, at s FoST, um, and on LinkedIn. So thank you very much for listening to this episode of utilizing ai.

If you enjoyed this discussion, please do subscribe. Uh, again, you can subscribe on YouTube or you can subscribe in your favorite podcast application. Just search for utilizing ai.

Uh, we would also love to hear from you again, this is the very first episode. If you have a, a suggestion on where we would like to take this, uh, you know, please do get in touch. For show notes and more episode, head to Textron ai, uh, click podcast in the menus there.

Uh, you will also find this on the utilizing AI channel and the, uh, Textron uh, TV app. Thanks for listening, and we will catch you next week.