2809: Rackspace and AI: Crafting the Next Wave of Digital Transformation

[00:00:00] How should companies navigate the accelerating pace of technological change and harness the power of emerging technologies to stay ahead? Well, today on Tech Talks Daily Podcast, I'm very excited to welcome back a familiar voice and one of my favorite guests.

[00:00:18] I am, of course, talking about Jeff DeVerta, CTO at Rackspace Technology for his third appearance on the show. Now, Rackspace Technology is a leader recognized by Gartner Magic Quantrant and they play a pivotal role in propelling businesses forward by managing apps, data, security and multiple

[00:00:37] clouds throughout every phase of their digital transformational journey. But today, we're going to explore the changing face of digital transformation with a very special focus on the explosion of generative AI and its significant impact on industries and IT infrastructure modernization. Because yes, it is a buzzword.

[00:00:59] We've all seen the headlines and experimented with it, but this is where things are ramping up. The cool stuff is starting to appear. The solving of real problems is happening. So from driving efficiency in healthcare and government to fostering a culture of curiosity

[00:01:15] and continuous learning, all this stuff is equally as important as generative AI itself. So Jeff is going to share his insights on the opportunities and the challenges that lie ahead as we delve into the transformative power of AI and ultimately what it means for

[00:01:31] businesses and individuals alike in the evolving digital landscape. It's going to impact every single one of us, but I think Jeff's enthusiasm and passion for this topic will ensure that you look to the future more hopeful than fearful.

[00:01:46] Before we get today's guest on though, I need to give a quick shout out and a thank you to the sponsors of Tech Talks Daily this month. They are Kiteworks and in a digital age where the landscape of remote work is ever expanding,

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[00:02:48] But now it's time to get on with the show and invite today's guest on. So buckle up and hold on tight as I beam your ears all the way to Dallas, Texas, where Jeff has taken time off the show floor to have a conversation with me today.

[00:03:02] So a massive warm welcome back to the show, Jeff, for your hat trick of appearances. But for anyone that missed out on the chats, can you just remind everyone listening with a little bit of who you are and what you do? Neil, I'm so glad to be back.

[00:03:14] We made the joke earlier. It doesn't matter who you invite from Rackspace. I'm showing up because I like to hang out with you. My official title at Rackspace here is the chief technology evangelist, which is one

[00:03:25] of my favorite things to do because it means I get to do three things. I get to work inside of the office of the CTO for Mr. Srini Kaushik. And then so I get to help a strategy and all of that fun stuff about where we're going

[00:03:38] with technology. I also get to help talk to customers and help them with their journey. And then, of course, I spend a fair amount of time on stages all around the world getting

[00:03:48] to talk about technology and the things that are going on in the areas, of course, where Rackspace can help from time to time. Started my career in technology way long time ago in the Microsoft collaboration space, then really got into enterprise architecture.

[00:04:05] And that's really the road that took me to where I am today. It's a pleasure to have you back on this. So much I want to talk with you about. And of course, as it is a tech podcast, we've got to mention AI straight up.

[00:04:16] And you were talking about you speak on different stages. I go to so many different tech conferences and last year in particular, it seemed that every CEO was intent on telling everyone, hey, AI is not new. We've been doing this for years.

[00:04:27] But a lot did seem to be jumping on the bandwagon. And so much has changed since we spoke. I think it was 2021 where nobody was talking about Gen AI or AI or not too much back then.

[00:04:38] So what do you make of this Gen AI trend as it continues to march forward and dominate just about every conversation on and off the show for us? Yeah, it's you can't go to any conference.

[00:04:49] You can't go to any event and not hear the dreaded acronym, the wonderful acronym AI. It's in everything. You know, I'm walking down the aisle in the grocery store waiting for somebody, a food product to say no with AI. But it's everywhere. But you know, it's interesting.

[00:05:06] You're right. AI is not new. You know, folks are saying that they've been doing it for years. And the reality is, is they have. You know, when we get into all of the things that are happening in that space, you know,

[00:05:19] the whole thought and initial thought around this started in what, 1947? So yeah, this has been something that's been in the slow cooker for a long time. It's been in the slow cooker for a lot of reasons all of us here in tech know, whether

[00:05:33] it's a dearth of data, a lack of ability to compute. The advent of the GPU course was massive, but it wasn't really until, you know, we saw the transformers come along and not the movie that really brought AI into the forefront

[00:05:52] because that's when it became tangible to the layman, to folks who could open up starting last November, a year ago, November, you know, a chat GPT. We all wake up, you know, January 1st with our hangovers and we can magically spell chat GPT.

[00:06:07] And, and, and last year was all about the air of people, you know, everybody going in and you know, what should I have for dinner or tell me a funny joke or, you know, the experimentation let's see what it does sometimes on point, sometimes not on point.

[00:06:20] But I tell you with all the transformation that happened last year, we have reached a point of, I think inflection. I really hope we never go back from it is an exciting time to be in technology.

[00:06:33] And Neil, the main reason for this, and this has been a message of mine for the past six months or so on stages is that AI is finally that workload. That's going to get people to transform their infrastructure, to be more modern, to be more cloudy.

[00:06:49] I don't necessarily mean going to the cloud, but to be more cloudy, to be more nimble. They're going to do the work so that they can adopt AI because it does. They still have to do the work. You can't not do the work.

[00:06:59] Those technical debts have to be paid at some point. Absolutely. And I think last year, as you said, it was all about experimentation and a lot of people compared it to the iPhone moment, but I would say it was more like the app store moment,

[00:07:12] you know, where those first year or so, I think every app that came out was a bit of a gimmick. It was an experiment where developers were seeing how far they could push it. You could turn your phone into an instrument, a pint of beer or a chainsaw.

[00:07:24] And now we're getting to the cool bit right now. We know how it all works. We know its limitations. We know how it's going to improve this year. How can we start solving real world problems here?

[00:07:34] So on that side of things, what are the most exciting new trends that you're observing with Gen AI workloads and how are they shaping the future of business technology, do you think?

[00:07:45] You know, I've heard a lot of folks talk about how it's like that iPhone moment, and I love your app store alignment as well, but I wonder if it isn't even just a backtrack for one second.

[00:07:56] It's more like the mainframe to client server or to the PC world, because we go from a point where here is this technology only meant for the big players, the universities, the massive organizations, people who could have a mainframe.

[00:08:10] Now everybody gets a computer in their house and now they can start to do things, whether that's entertainment or whether that's productivity. I feel like AI maybe falls more in line there or even the internet moment.

[00:08:22] And boy, gosh, Microsoft is not going to miss this one, are they? They're all over that, aren't they? And I think that really was what will draw me into you asked what I'm excited about.

[00:08:31] It's the co-pilot world, whether we're going to call it co-pilot or whether we're going to call it Bard or whoever's favorite nomenclature. I think it's that, and it's where I'm living. I think it's why I'm the most excited about it is it's how does it help individuals personally

[00:08:48] and corporately do more? And that's where I find the most transformation happening right now. Because we could talk about some amazing things that are how much just read a credible article on esophageal cancers and how this is actually helping people live longer.

[00:09:04] Because of course, through vision capabilities, they're able to look at these regular scans and get early detection of esophageal cancer. Because if somebody gets a regular diagnosis of esophageal cancer through a regular throat scan, they have a not quite 20% chance of survival within four years.

[00:09:25] That's a dismal number, but that goes exponentially better if they get early detection. And what's causing the early detection, of course, is AI being able to look at scans and see those early, early precursors. So there's all sorts of incredible examples like that that are having significant impact.

[00:09:43] Here's another one, Neil. I like to find the non-technical implications of how we're using technology. Here's another one I read about this week. And it is where they're using AI to help curb overfishing of the world's oceans. Really? Isn't that interesting?

[00:09:58] So a phrase I use a lot is AI is so good in some ways because it's using machine learning and machines to go and look. I used to say, find a needle in a haystack. Now I say finding a needle in a needle stack.

[00:10:13] And so when you look at all the data, well, what data are these companies using? There's this one whose name I forget off the top of my head. But they're looking at transponder data for ships. They're looking at cell phone records.

[00:10:23] They're looking at like 10 other data sources, public referenceable data sources. And they are collating this massive amount of data. And they're saying, are these individuals, are these ships, are these other things happening?

[00:10:36] Are they parking in one area far too long and not have a permit to fish in that area? And if that's the case, they're alerting authorities and authorities go out. So AI helping curb overfishing of the world's oceans, solving problems like esophageal, early detection of esophageal cancer.

[00:10:54] And so these are some really interesting things. But Neil, what would you do if you got three hours added to your 24 hour day? What would you do? Yeah, oh man, I've got all kinds of mischief, let me tell you. I know. Let's keep it productive.

[00:11:09] Let's keep it productive, Neil. What if you got three hours into your eight hour or 10 hour work day? And I was just talking to a woman named Reagan Avon. She's just a brilliant woman out of Columbus, Ohio in this space.

[00:11:23] And she's saying, it's not just what if you could get that, but what if every organization could get, every individual could get one, two or three hours of productivity back in their day?

[00:11:34] And not to the point where then CEOs are going, oh good, we can fire some people. Oh, they're going to say, what can we do with that time? These people know our business, they know our customers, they know our processes.

[00:11:44] How can we put them on stuff that has real value and let the machines do the machine stuff? This is the kind of stuff that gets me super excited about AI. Yeah, and it's already transformed my workflow with this podcast.

[00:11:55] And one of the reasons I could get 30 episodes out, I mean, attached to this call at the moment is a service called Fathom, which will not only transcribe the call, but it will also give key takeaways, key points, things that we talked about, and then create a little

[00:12:08] summary. And I could put that into chat GPT, it will help me create the episode description, maybe do the intro outro. There's just so many different elements, it just saves me time and it slows marginal gains.

[00:12:20] If you were to save, I don't know, 40 minutes a day over a year, you've certainly saved so much time, haven't you? Well, yeah. And so it's not even just about save time, but how much has your work product, how much

[00:12:30] of those descriptions become more engaging maybe, or they found that needle in the needle stack of the words that we say. I mean, they're going to have to look hard to find something with me, but they're going to find something in there.

[00:12:41] They're going to collate it, it's going to collate it into some words that are engaging, attractive, it's going to get more listeners, you're going to be more popular. So it's not just about how do we get time back, but how do we make that core product even better?

[00:12:55] Yeah. And you mentioned a few months ago, that great mainframe example, and it's very similar to when SAS first came out, you know, there's a lot of this technology was just for the Fortune 100, Fortune 500 companies. But now anybody can have any kind of technology in their living room.

[00:13:12] We've got the SAS tools, you've got ChatGPT. There's also a great community, I don't know if you've seen this, where they built businesses from scratch from a ChatGPT prompt. And I think there's a Telegram group.

[00:13:24] So they pretty much said, I've got this idea, how can I make this into a business? What do I need to sell? OK, you want to sell T-shirts? What do I put on these T-shirts? This is what you should put on them. Now I need a website.

[00:13:35] This is how you build a website. Now I need to market it. This is how you market it. And they've built an entire business and some six figure salaries that these people have built just starting from a few prompts. It's just breathtaking. That's incredible.

[00:13:49] I'm going to need to look that one up. I'm already I'm taking notes here, the things you're teaching me today. So Fathom is on that list and I got an open Telegram and go find this group. That sounds fascinating.

[00:13:58] And also, if we look at how it's leveling the playing field and creating so many opportunities here, how do you see generative AI maybe revolutionizing entire industries in the coming years? It feels like so many opportunities, so much up for grabs.

[00:14:14] But how do you see that taking shape? Well, you can look at. So let's take let's take call centers, for instance, I think that's a really good example. You know, right now you can still hear and you can find in in some some some natural language conversations.

[00:14:33] You can every now and again you can hear the mistake that an AI will make in making it sound like you're listening to a narrator tell a story or something. I was listening to one last night where I went to bed and and I thought, well, this

[00:14:44] guy's got really good voice is engaging, whatever. And then he said, character, oh, character. Oh, you're an AI, aren't you? But if you when you think about a call center, businesses that are either call centers or

[00:14:55] divisions within an organization, you know, that is an area that right now there is such massive transformation that's happening. Sentiment analysis live in a call that's happening. Amazing being able to see, you know, they're putting smiley faces or frowny faces and

[00:15:11] look at imagine what the dashboard is for the manager who's just looking at a screen of their agents and smiley faces or sad faces, being able to click into and see what's going on in those areas or better yet, listening to the conversation with a live person on

[00:15:24] the on the agent side with the customer and bringing up live help for the agent based on the conversation. Again, making us better, making that answers accurate and and and more better. Sorry to use the proper English there.

[00:15:39] And but then, you know, at some point that agent's going to that live live air quotes for those of you at home, live agent goes away and it becomes an AI chat bot that is literally just having a conversation.

[00:15:53] I think we're going to see some massive transformation there. We already see it a little bit in text form that's fronting some of these calls. So you start and you give it some core information. If you can't help, you get along to the last person.

[00:16:04] So I think that's going to be interesting. I I think I like to look at ways for AI making impacts in existing organization or industries to make them better at what they do and not just really replace, because I think that's where that core value comes in.

[00:16:19] Already gave a health care example. I think this is ripe for government. Imagine the judge who's listening to the plaintiff and the other person. I don't remember all the names. I'm not a legal a legal or a speaker.

[00:16:34] But but being able to as they think about the the case that's been presented to them to be able to then ask a legal generative bot to be able to ask about all the case law that

[00:16:48] exists around what's being asked and compare what they want to say against, you know, a couple of hundred or in your case, I mean, with given your accent, a couple of thousand years worth of of of case law that exists to be compared to.

[00:17:01] And I think about how it's going to go through every one of these industries and make such massive impact in the quality and quantity of what they're able to produce. And a topic we've got to talk about, of course, we're both excited about the future and

[00:17:15] what it can bring. But also the days of getting a leaving school, getting a job and doing that same job for the rest of your life are long gone. And there's a lot of talk and fear about people losing careers, losing jobs, etc..

[00:17:27] So as generative AI reshapes the business landscape, begins to automate those mundane, repetitive tasks. Yeah, we all need to almost adopt a sense of continuous learning. So what key skills and competences do you think workforces and employees and listeners

[00:17:43] should be listening and a little bit fearful of the future? What kind of skills should they be developing and how important are reskilling and upskilling in this context too? And what responsibilities do employers have on helping people ensure that they're not getting left behind?

[00:17:58] Yeah. So for those of you at home, you need to know how well prepared Neil is and he sends a lot of these questions out ahead of time. So be prepared and sound like I'm smart. And quite honestly, it's helped to see the thoughts behind it.

[00:18:10] But I'm going to read my one answer for this that I wrote down. It was really just one word and that is curiosity. I think that if individuals can adopt an attitude of curiosity and not fear around

[00:18:24] technology and how it can help them be better and make their organizations be better, then that's going to lead to a mindset of continuous learning. I could not agree more with you that that, you know, gone are the days when when you

[00:18:39] have one one job or one career for your whole lifetime of work that's gone and gone are the days where you have a distinct time of learning your university years and then you go off and do the work. So you have to be learning every single day.

[00:18:53] Too much is changing every single day. And your employers, whether they know it or not, they have to have you looking around the corner and thinking, how can in your piece of that organization and the piece of work that you do, you've got to do it well.

[00:19:09] But how could you do it better? How could technology help? The landscape is and the rules have changed between the IT departments inside of organizations and the air quotes again, for those of you at home, then the business, you know, that everybody is a technologist.

[00:19:23] If you are not well versed in technology, you must be if you're listening to us here. But if you're not or you know people who aren't, encourage them and have them start listening to this podcast.

[00:19:32] It's a great one to be aware of what's happening and changing inside of the world of tech. And then also gone are the days when you have to look to your your your organization

[00:19:42] to set that stage or that standard and the ability for you to go to the yearly training, go to this conference, go to that conference. You need to be reading. You need to be listening. You need to set time aside. You know what else you need to do?

[00:19:56] You need to open up chat GPT or my favorite. I really do like being chat. So being dot com slash chat, it's their implementation of of chat GPT. I'd like to debate that, which is better. And and ask ask them these questions.

[00:20:11] Hey, what changed in technology this week? What are you chat GPT excited about? A.I. What are you chat GPT? What have you seen? Have you seen technology impact? What interest are you in at home? Are you in finance?

[00:20:23] Are you in health care? Are you in whatever it is? And ask those questions. It will get and that's the beauty of it. You could go to Google and ask the question, but you're going to get a thousand answers. You have to collate those things.

[00:20:33] You have to figure out what it all means and then form an opinion. Or you can use a generative chat model like Bing chat, which has live access to the Internet and be able to ask those questions.

[00:20:44] Have it summarize what you would have to do, but it gives you all the hyperlinks to it as well to all of its sites, all those sources. And you can go read all that source material for the things that are interesting.

[00:20:53] So these are these are just a few of my little hints. But it starts with being curious. You have to be curious. Yeah. And in nearly 3000 interviews on this podcast, that word curious is possibly the one that's mentioned more than anything. It is so important.

[00:21:07] And the difference between success and unsuccessful, unsuccessful people sometimes as well, just being open to things. And on the flip side, though, for business leaders that are listening in terms of things like talent acquisition, what shifts are you anticipating as companies increasingly adopt

[00:21:22] generative AI? How should organizations maybe adapt their hiring strategies to attract the right talent for these new tech paradigms that we're we're embarking on here? Neil, I think it starts with with how they're managing their organization today.

[00:21:37] And if they just put that thought that we started with in the back of their head, what if every employee in my organization got one extra day, one extra hour of productivity every single day? How could first of all, how can you enable it?

[00:21:50] Technology is going to do that. Second, what would you encourage them to do with that time? Don't try to fire one in eight people. But how do you take and give all of them? You're getting more out of your people and you don't have to pay them more.

[00:22:01] What could be better to make it better? And then you need to build a program around that for how you tell the world that you've done that. Don't give them your trade secrets. There's something super special about every single organization that is unique to them.

[00:22:13] We call it intellectual property. You don't have to give it away, but you can absolutely brag that you got what you have 10,000 people, 5,000 people who work for your organization. You got 5,000 hours a day of productivity back every single day. Now, here's what we're doing with it.

[00:22:28] This is what we've done. That's the kind of stuff that is going to attract the right people who are going to be able to come in and really do some amazing stuff with those extra hours that you're going to

[00:22:38] be able to generate, because they're going to see that you're not afraid to look around the corner about how things could be done better or different and that you're not afraid to empower your people to try things that may feel a little bit scary.

[00:22:51] Now, I'm not saying if you're in retail, how do you turn the entire everything over to A.I.? We're not saying that. Start careful. It's just like in the beginning of cloud transformation. When you think about, hey, we're going to move out to our favorite cloud.

[00:23:03] You don't go move that one thing that pays the bills first. You go find some small project, some small thing that if it fell over for a day and a half or two days, the business doesn't die. So you start small. You build from there.

[00:23:17] You make sure you have the right governance in place before you do these things. You don't want to put all your secret super secret contracts out in a public database somewhere, you know, generative thing that that the world is going to then have access to.

[00:23:28] So there's there's all sorts of baby steps and careful things you need to do. We can talk about that. But I think the way you attract the right talent is, first of all, start to execute utilizing these new technologies.

[00:23:39] You start to get the benefits from it and you develop an amazing story around it. And as you start to then go and hire people, you start to make this the other thought I had.

[00:23:48] You start to make that curiosity or the things that come from it a non-functional use of development term, a non-functional requirement of these functional people.

[00:23:59] Just like, you know, the old days when you would if you need an accountant, you would say I need for your degree in this type of finance and all the other things that you would want from an accountant person.

[00:24:08] But you'd also want to have that plays well with others type of a capability. Well, I would put curiosity. I would put technology proven ability to do incredible things with technology as part of those non-functional requirements, those nice to have.

[00:24:24] And before you came on the podcast today, I had an email from a list that is named Simon. He was incredibly passionate about this space as me and you are and excited about the possibilities that generative AI can offer.

[00:24:35] But he was saying he listens to all this stuff online. He reads it online. He gets blown away by the opportunities. But then he goes into the workplace and they flat out banned it straight away and said, no, we don't want to. We were concerned about two things.

[00:24:47] One is the company data that could be teaching these machine learning models and also the potential regulation. They just terrified of it and just flat out banned it. So what are the most significant strategic opportunities and challenges that you're seeing businesses face with the adoption of generative AI?

[00:25:06] And what's the best way of navigating issues like this? Because there's a certain amount of fear around this kind of change at the same time, isn't that? Yeah, well, and then some of those concerns are super valid.

[00:25:18] I mean, you don't want to take and put your secret sauce out in chat GPT public for the world to see. But by the way, if you go into the API and you have the right contract with them, you can be in a private instance.

[00:25:30] By the way, you can contract and use Google or AWS or Azure in a private instance with their cognitive services and do that stuff. But all of it starts with an appropriate governance plan.

[00:25:41] That's a top down governance plan that include that is built by a governance committee that has representation from all aspects of the organization. Now, it takes effort to get some of these companies to start down that road.

[00:25:54] So in some cases, it's up to Sam to be that thought leader, find other like minded people who see the value and want to help be that champion for how to do it safely.

[00:26:04] And and hopefully get the company starting to move in a direction where they will put the right guardrails in place.

[00:26:11] You know, over at Rackspace, that company where I get to work, we've got a program in place and we actually have companies who want us to come in and help them with AI. We make them take a little test first.

[00:26:21] And that is their ability, their organizational propensity to be able to adopt the technology because we don't want to drop a science project off on their front door and have it just flounder or have somebody slam the door on it.

[00:26:32] If IT builds this thing and, you know, and the sea levels turn it off. So it's a very valid thing to do now. You invest some time. And if the company still slams the door, you know, a slam door is a very closed minded way to do things.

[00:26:46] You know, maybe Sam needs to find another place. Maybe Sam needs to find a company that's more willing. But I would say that if their organization isn't doing anything yet, they're going to realize that if they don't, they will be left behind.

[00:26:58] The old adage, it's old adage, it's not a year old yet, but that if that AI is not going to take away your job, but the person who uses AI is going to take your job.

[00:27:06] The company that uses AI is going to outpace the one that does it.

[00:27:10] Companies are going to realize that Sam's in a great position to help be that thought leader inside of his organization, to help them turn that corner and maybe be the new AI chief for the organization at some point.

[00:27:21] 100 percent with you on that, and I hope Sam gets to listen to your response there. And also with that growing capabilities of generative AI, the other big topic, of course, is ethical considerations and AI governance.

[00:27:33] You hinted on a few of them there, but anything else that they should be doing to ensure responsible use? Yeah, so I'm so glad you used the R word responsible. AI has to be used responsibly.

[00:27:45] We used a simple example of we don't want to take the core data and put it out in a public database where the world can see it. That's a bad, that's a bad day. But absolutely.

[00:27:55] First of all, when we think responsibility, we break that down into three primary areas here at Rackspace. So it starts with, it starts with, we like to say symbiotic. We love alliteration around here. You can hear some more S words showing up.

[00:28:08] But symbiotic meaning, AI is not here to replace you or your organization. AI is here to make people better. And AI is at its best when it makes people the best that they can be. Let machines go do the drudgery.

[00:28:21] Let people take the credit for it and cite it appropriately and do better work. So we want them to be, we want it to be symbiotic. We want it to be secure. AI is nothing if it doesn't have data.

[00:28:35] And when we start bringing lots of data sources together, it creates an attack surface. So we want to make sure that that content is safe and secure. And then the last is sustainable. I mentioned the example before, of course, sustainable from the green perspective.

[00:28:48] AI is very power hungry. And so we have to make sure that we're building solutions that are good for the world. But the second piece on sustainability is we want to make sure that these solutions are sustainable as well.

[00:29:00] Meaning it's not a science project that is, that's a set and forget. AI is not a set and forget. AI is a set and continue to do refinement in the training and all sorts of other things. So there's a lot that has to happen there.

[00:29:13] So, and then we also want to make sure that we're eliminating bias. That has to be an opinion, a viewpoint going in, a non-functional requirement. One of the pieces on the ethical side that we want to make sure are considered as well.

[00:29:30] And there's also a lot of excitement online building at the moment for the potential of chat GPT five when it eventually comes out. Probably won't be till towards the end of the year, but looking at this year and beyond, what excites you about the future of this tech?

[00:29:45] So I love those tangible examples I gave earlier, you know, esophageal cancer, solving problems with overfishing of the oceans. Those are some really interesting ones. And these are very, very big and grandiose.

[00:30:01] But what gets me the most excited, Neil, is you and I have been talking about this stuff for a while now, and we've been playing with the technology for a while now. Transparency.

[00:30:11] It's just in the past couple of months that it is part of my every single day. I'm utilizing it every single day to help do things.

[00:30:19] And I'm excited for the world to make it part of their every single day and get an hour, two hours, three hours of productivity. And the productivity that you're that you're engaged in is of a higher quality. I think that's the moonshot for twenty twenty four.

[00:30:34] And when we're looking at what can we do better, we can work smart, not harder, etc. But there is that pressure of continuous learning, which we've already mentioned.

[00:30:42] So I've got to ask you, as someone that's curious and passionate about this space, how or where do you self educate? Oh, that's a good question. So I there's lots of ways to say, you know, eat your own dog for drink your own champagne.

[00:30:57] I do what I've just mentioned before I go into a conversation. I am opening bing dot com slash chat and I'm asking what's new this week. Tell me about this specific industry.

[00:31:06] If I'm going to have a conversation about an individual who's a public figure, I'm going to start here to collate lots of information together.

[00:31:13] I spend a lot of time reading white papers and research that's coming out because I like I think that's a great precursor of what's coming. I am also engaged on Azure's my technology for the year, by the way.

[00:31:24] So I am engaged in Azure training around, you know, architecture as well as their A.I. piece, because I like to know what's happening underneath the hood. And a lot of Google stuff last year this year is going to be that. So I am doing formal training.

[00:31:37] It's all self-paced and I'm doing it online. So it's it's a smattering of all the things. You know, it's I like to think of it as a nice brick wall. You know, you've got your big bricks that are in there.

[00:31:45] Those are my Azure courses, trainings I had to go get certified for. And then there's all the mortar that holds it together. And that's the daily things, the articles I'm reading, the snippets that's coming across the research papers that I'm seeing as well.

[00:31:58] Well, your passion for this really shines through in our conversation today. So if anybody wants to continue to follow you, contact you or your team or just find out more information about what you're doing at Rackspace. Where do you like to point everyone listening?

[00:32:11] Yeah, best place to find me is over on LinkedIn. There is some content on YouTube, but LinkedIn is where I'm most active. I have a weekly live stream that I do on Tuesday mornings at 830 Central Time. Make sure that you listen to Neil's show first.

[00:32:24] I'm not trying to take things away from Neil, but you're welcome to come listen to that at any point or be a part of that conversation because we do do it live at 830 a.m. Central. If you follow me on LinkedIn, of course, my name is Jeff Diverter.

[00:32:35] So I'm just LinkedIn. It's my first name, the character J and then Diverter. You'll find me there. There's not a lot of Jeff Diverters running around LinkedIn. So pretty easy to find. Well, there's plenty of room for us both out there.

[00:32:46] So I will gladly add links to everything that you just mentioned so people can find you and listen to you, too. I'm sure there'll be a lot of people tuning in to that. And if folks are interested about how they get started as an organization

[00:32:58] or Sam wants to, you know, get us involved, you know, they can always go to FAIR. That's our offering at Rackspace. That's an acronym for Foundry for AI at Rackspace. So FAIR.rackspace.com. And you can learn about that process and that that little quiz I mentioned

[00:33:12] about a business's propensity for learning AI or their organization ready for AI. It's a free thing you can do right on the website. So anybody's welcome to go do that. Oh, awesome. I'll make sure links to that too.

[00:33:23] And we thank you so much there from Trends in Generative AI. We're like five minutes in, right? Five minutes. So much positive stuff and covering the ethical consideration, AI governance and responsible AI, but balancing opportunities and challenges in equal measure.

[00:33:39] A pleasure as always, just because this is your hat trick of appearances. This isn't it for you, though. I hope to get you back on later in the year. We'll see how things are going, especially as maybe ChatGPT5 comes out.

[00:33:49] But more than anything, just thanks for joining me today. Happy to. Maybe a midyear check in. We can see how our predictions are holding up. I want to extend a heartfelt thank you to Jeff DeVere, a CTO at Rackspace Technology, for joining me once again on this podcast.

[00:34:01] He's officially my spirit animal. I can't thank him enough. It's his passion and enthusiasm. And coming on here, sharing his expert insights into the dynamic world of digital transformation and generative AI. I think it really shines through. And I think we are reaching that inflection point,

[00:34:19] a potential for AI to revolutionise industries, but also for hammering home the point today, the culture of curiosity and continuous learning. This has undoubtedly shed light on the pathways that businesses can navigate through the complexities of modernisation and innovation. But it's not just about the technology.

[00:34:38] It's about the people. It's about the culture. And I think it's clear that the journey towards harnessing AI responsibly and as Jeff said there, that R word is so important, responsibly and effectively. It can be both exciting and challenging, but they are endless opportunities

[00:34:54] for growth, efficiency and innovation. So as we look ahead, I think the conversation around AI and all its implications and its integration into our daily operations, as that continues to evolve, the key takeaways from today's discussion with Jeff remind me that the importance of starting small,

[00:35:14] focusing on empowering employees and ensuring that the principles of responsible AI guide those strategies, whether you're in early stages of adoption or looking to scale your initiatives. I think there's something for everyone to learn and apply from that. And hopefully Sam's listening to the podcast as well.

[00:35:30] Hopefully he will get back to me and he's taken something away from this conversation, but over to you. What steps will you take to embrace AI in a way that is secure, sustainable and symbiotic with your workforce? As always, share your thoughts.

[00:35:45] Join the conversation as we continue to explore the limitless possibilities of technology together by simply emailing me techblogwriteroutlook.com Twitter, LinkedIn, Instagram, just at Neil C Hughes. But that's it for today. So stay curious, keep learning. And until next time, let's keep pushing these boundaries

[00:36:04] and exploring the art of the possible. And I also cordially invite you to join me in doing it all again tomorrow with another guest. So hopefully I'll see you there.