#220 [Radar Recap] Building Tomorrow's Workforce, Today: Scaling Internal AI Academies

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Welcome back everyone. This is Richie. Let's kick things off. So taking advantage of AI isn't as simple as just buying a new tool. You also need your employees to understand how to use those tools. And also you need to make sure they understand AI itself. That is, it is essential to have some sort of upskilling or reskilling program just to make sure that everyone is up to date and seeing oh well, we need an AI training program is very easy. The trickier thing to do is actually running such a program. And I have to say I have a lot of respect for learning development professionals because getting the right training to the right employees and and keeping the learners engaged while they have their day job competing for their attention is really no mean feat. There are many devils in the details and bad training is just a waste of time for everyone involved. So helping steer the path to training success are three learning development experts. So, first of all, we have Mike Baylor. He is the Chief Digital and AI Officer at Lockheed Martin. Mike is responsible for the innovation and delivery of digital and AI technologies across the Lockheed Martin Corporation. He's got over 23 years of experience leading data teams and he's got expertise in digital transformation, infrastructure development and execution. Some career highlights include launching a commercial business comprised of machine learning and analytics technologies for government, commercial and international customers, pioneering innovative systems engineering to integrate the data for large complex systems, and supporting satellite operations for NASA. Satellites are definitely very cool. Next up, we have Carol Ann Diskin. Carol Ann is a Senior Technical Program Manager at Dropbox, where she spearheads technical learning initiatives for skill development. She's dedicated to cultivating a culture of continuous learning within Dropbox. And Caroline also serves as co leader of the AI Learn program in collaboration with with the Dropbox Learning and Organizational Development team. And third up, we have Dr. Alta Marauno Rayo, who is the Chief Data scientist and responsible AI official of the U.S. department of State. She was spearheading initiatives in artificial intelligence and data science. Previously, she was a senior mathematical statistician in the Department of Labor, where she significantly impacted the field. At the Chief Evaluation Office, her work focused on the statistical and AI and machine learning methodologies, behavioral economics and human centered design. Gio was also a director of the Ministry of Foreign affairs in Nicaragua, an academic at Carnegie Mellon University, Vanderbilt University, and the University of Texas in Austin, and it's a celebrated Fulbright and National Science foundation scholar. So we've got three expert speakers, all from very different organizations. So I'm very excited about how this conversation is going to lie. So, first of all, we need some motivation. Can you talk me through why did you decide that your colleagues needed AI training? Gio, do you want to go first?

Happy to. And hello, everyone. So at the Department of State, we feel, and actually we see that the written word is our currency. So this means that we have massive amounts of unstructured data that benefit hugely from AI tools and specifically from generative AI tool. And since AI is not going away, generative AI is here to stay. We feel that our workforce needs to be trained and ready to use these tools and discern, be able to understand what are the promises and also the limitations of these tools. So, similar to data, AI can be very intimidating for some people. So we're trying to make sure that training helps both with their understanding of the tools, of the promises and limitations, but also making sure that they build the levels of comfort that are necessary to be able to start with, let's say, a generative AI interface and then move on to more complex text tools.

That's pretty cool. I like that you mentioned unstructured data, because traditionally you think of data as being like numbers, and actually now it's like any text you've got that's fair game as data. And I also like that you mentioned building confidence as well. So you start with the simple stuff and then gradually get more advanced. Carol Anne, do you want to talk me through what the motivation was for having AI training at Dropbox?

So I suppose very similar to jio. You know, we recognize that AI is transforming every industry, including our own. So to stay competitive and innovative, it was essential that our workforce as well develop the structure, strong understanding of AI principles, concepts and applications. So providing AI training courses that ensures that our team is well equipped to leverage AI technologies effectively and safely, which ultimately we want to drive better decision making, improving internal processes, and then delivering, you know, superior products and services, both internally to our teams and externally to our customers. So really, the motivation is behind making sure we're staying up to date with industry trends and making sure that we're really staying competitive and innovative.

That's cool.

I like that. At the end of the day, it's not just about the technology, it's about making sure that it supports the business in some way. So you want to stay competitive, you want to stay innovative, you want to help your customers somehow. That's very cool. So moving, starting from motivations to goals, were there any specific objectives you had in your training programs? Mike, do you want to take this? Yeah.

The overall goals for our training programs, you know, our main goals were to really empower the Lockheed Martin employees in every area, be it finance or engineering or manufacturing. So we provide guidance on topics generative AI and also third party AI suppliers. As you all know, there's billions of dollars being pumped into artificial intelligence, especially generative types of technologies. There's a lot of salesmanship going on there. So being able to sort through kind of who's who in the zoo, so to speak, from AI suppliers perspective is really important for a large company of over 100,000 people overall, like tool suites that we have, reusable software packages and training courses especially. So all of this designed to teach people what AI is and also what it is and how to apply it to the problems that they face.

I think that last point is very important that you need to know what AI isn't. I think with the amount of hype that's been around AI recently, it's like think, oh well, yeah, ChatGPT can do absolutely anything and it can't. And so knowing what's not possible is going to help stop you going down some silly dead ends. So I'd love to talk a bit about who needs AI training. So I know you've mentioned a few of the teams each in terms of like who gets AI training. I want to go into that in a bit more depth. Gio, do you want to talk me through, like, who needs AI training?

Yeah. So in a word, everyone, everyone in the State department needs AI training. And let me start with some stats. So the goal for our office is to make sure that every single person in the State Department at all levels gets training. And over the past three years we have delivered the partners, they has delivered over 81,000 person hours of training in data and AI. My office specifically sponsors six courses through a training shop, the Foreign Service Institute. We target those courses on people that self identify as consumers and developers of AI and data. So these people self select. So we're ready to go into the Technical weeds on these specific courses. But in addition to that, we also incorporated data and AI training into what we call tradecraft courses, which are courses that are required. So this is not the self select group, this is not the group that self selects. But every single person that's a foreign service officer must go through the tradecraft courses. And it was a very big deal for us to include data and AI in these courses. And it's important because as they go through these courses they can check a box and say I've taken AI and data course. This goes through towards their promotion file. Another thing that we're super excited in is that we also have courses for ambassadors and deputy Chief of missions. So this is also huge so that an ambassador can understand what tools are out there and how they can leverage that for mission critical tasks. In addition to the three sorts of levels of courses that we have, we're also creating new emerging technology training sessions with senior leaders. We also offer online self paced training for employees who requested through Data Camp. We also have office hours on a monthly basis on data topics and AI. And we started something that's pretty cool that I really like and it's called the Post Data program and it's basically a framework to strengthen post data and AI capacity in our embassies around the world.

That's pretty amazing. I love that you kind of start with everyone needs some kind of training, but it's different types of training for different people. So if you're a leader, you have very different requirements to someone with a technical job or, or maybe just someone who's only sort of more casually involved in data and AI. That's very, very cool stuff. Mike, do you want to talk me through who you think needs AI training?

Double click on what Gio was saying. I think I talk about AI, especially generative, that there won't be a corner of the corporation, Lockheed Martin that won't have AI touch it one way or another in the next five, 10 years. So everyone at the corporation needs to have access to the trainings. Some may be more useful to specific groups. Same thing we're doing here where we have a generative AI for business leaders. So this is designed to especially be useful for those types. But anyone can take the training and we have different training for those who want to develop skills and artificial intelligence, machine learning and the doers to build and that would be obviously different trainings as well. But anyone at the corporation that is willing to put, put time in to do this can do it. And we've seen a Lot of success as that. So I think that's absolutely key. Just to democratize it and make it available to everyone.

That's cool. And again, I like that it goes right up to sort of senior level. Like only management needs training on this. All right, Carol Anne, can you talk me through who needs AI training at Dropbox?

Yeah, I mean, not to continue the trend here, but to reiterate, I guess what Gio and Mike are saying, you know, it does start from the top down really. You know, from our senior leadership driving that, you know, empowering our teams to expand our skill sets and our knowledge set within the AI and ML space. You know, whether that's through online training or, you know, internal boot camps that we have created and designed with some of our experts within the machine learning team. You know, these are really hands on approaches to applying AI and ML in your daily work, which we think is really important as well. Because although learning certainly, you know, your theoretical online courses are super important, applying that knowledge also in your work is extremely important as well. And really getting used to working with AI in your day to day also makes you feel more empowered and just more, I suppose, able to get more proficient and become more of an expert in your role and then you can spread that, you can become that person within your team to empower the rest of your team also and everyone else around you, you know, on a cross functional basis. So we really encourage everyone, as Mike said, from finance to our technical folks as well, to really dive in, start somewhere. You know, it doesn't matter where you start, it's just really start somewhere.

That's very cool. I like that we've had revotes for absolutely everyone needs some form of AI training. So that's very cool. And I also love that you mentioned it being an empowering experience because you, you need to understand this and you need to feel confident to be able to make use of these technologies. All right, so let's go back to the beginning because I think a lot of organizations are just getting started with these training programs. So I'd like to know a bit more about like how these programs were set up. So to begin with, like who is responsible for setting up the AI training program? Gio, if you want to go first.

This time, our chief data and artificial intelligence officer, Dr. Matthew Gravis. He oversees all data and AI training initiatives. So within our shop, within our office, the center for analytics, we have a dedicated team that focuses exclusively on communications culture and training. And we obsess about how to enhance training, targeted training, across the department. The way that we do that is by partnering, working together very closely with the training shop, the Foreign Service Institute, so that we can harness and leverage all of their expertise or all of their know how so that we can make training intuitive to different levels of employees and for the right kind of material that they need to better improve and increase efficiencies in their job.

That's interesting that it came from Mike. He's very senior, he's C suite. And so it's come from the top down, sort of figuring out what. Because everyone needs to know this, it has to come from management. And then we'll figure out what is needed for each of the individual departments or teams. Is it the same thing? Lockheed Martin Mike So we have the.

Philosophy of, you know, build once you know, use many. And within Lockheed Martin we have a centralized approach where we can build common training and all the technology to which then we can disperse across the corporation. And within my organization and the CDAO we have this Lockheed AI center, we call it the lake. We have to have an acronym for everything, so we call it the Lake. And within that I have a directorate called Foundations. And within that Foundational directorate. It's about providing foundational AI capabilities to the entire corporation. This includes training. So they produce and hosted end user tailored training courses. But they've also produced an AI ML fundamentals program that once completed enables employees to transition to a real AIML machine learning engineer job code which we've. That's also a key thing that we have within the corporation. We have a job code for it and a pathway to growth. And we find a lot of those individuals that are currently employed and working in my organization came from that, which is fantastic.

That's very cool. I love that it's linked to actual career structure. So you can get a promotion or you can change your roll to something that is technically focused. If you complete the training that feels like very good motivation. And actually motivation is always one of the tricky things. So I'm wondering how you go about promoting the program internally just to make sure everyone is aware that training is available. Carol Ann, do you want to take this?

I suppose we look at it in a multifaceted way really to promote our AI Learn program internally. You know, it includes internal communications, so announcements through company wide emails, newsletters, Slack channels. Leadership endorsements is key here as well. Endorsements and encouragement from senior leaders who emphasize the importance and benefits of AI training. We have interactive sessions, we host external speakers in thought leaders and AI experts who come in and talk to us about industry trends and what's really going on in the AI landscape, which is really important as well. We also have incentives, which is really cool. So offering awards and recognition for participation and completion of courses. They could be certificates, badges, swag. Who doesn't love swag? And of course, internal shout outs and really just sharing stories, you know, our success stories, and who's really shouting about what they're learning. Within Dropbox, we love to hear about those kind of stories and promote them. So really giving folks a voice as well, whether they're just starting at a foundational level or they're AI experts. I think it's important to have that range of voice. But yeah, that's how we try and cover all of the promotional area of the training.

That's very cool. I like that. A lot of this feels very easily replicable by most organizations. It's like sending messages via email or Slack or whatever. It's like, well, these are standard ways of communicating. But then on top of that, you've got things like leadership, making commentary, and then you've got swag. I'd love to hear more about that. Like, what kind of swag do you give to people for doing training?

Oh, lots of. Lots of different swag. We have beautiful notebooks, we have all different types of, like beautiful coffee cups all labeled up. So, yeah, there's great stuff going on.

Okay, nice. Once you promote it so people are aware that the training is happening, the next tricky thing is just making sure that people stay engaged in the training. Quite often people start and then work priorities come up and they get distracted and get that the training is there. So how do you keep people engaged? Gio, do you want to talk us through this?

Yeah. So this is one of my favorite things, inspiring or igniting creativity. So we do that by making sure that we go beyond the theory and we actually show them how AI is done, like in the wild, how generative AI is actually enhancing efficiency. So our AI use cases really go beyond just saying what could really be to showing what has been. So we demo things all of the time. And currently we are in the process of developing an internal chatbot that can safely and securely process department data. And we're in the beta testing phase and we want to make sure that people understand the chatbot, demo it, have them play with it. So that inspires new ways of thinking or creativity. About what other use cases could we have envision and how can we use this chatbot for another set of things that I haven't thought about or anybody else in the developing team haven't thought about. So we're really trying to ignite that creativity, inspire those new AI use cases by showing them what it is that AI could do for them right now.

I love that. Yeah. Just being able to see some examples of this is a cool thing you can do is pretty inspiring because sometimes it's quite difficult for people to imagine, oh, well, is this something that's possible? But when you see it, it's definitely very motivating, actually. This is such interesting stuff. Mike, do you have any more opinions on how you keep people engaged?

Yeah, I mean, it's really about focusing on what the detail that the learner needs. If they're like an engineer looking to develop AI themselves, or the focus on an algorithm section or AI libraries or ML ops pipelines, what they need. If their manager needs to develop a better intuition of where to invest in AI, then we focus on teaching them how to identify opportunities for AI application. But it's definitely given the breadth of AI and all the different opportunities you have, you have to have really a mixed bag of approaches to get to the learners and make it a value for them.

Excellent. So just really making sure that the right people are learning the right things and it's appropriate to whatever their job goals are. All right. So quite often we find when you've got a training program, some people are kind of, okay, they go through the program and it's fine, but other people get really enthusiastic about it and they start championing this program. So I'd love to know about how do you identify these champions, and how do you make use of them to get other people more enthusiastic?

Yeah.

Caroline, do you want to talk me through? Like, who are your champions of learning about AI?

Yeah, we have many champions from all across the company, which I think is wonderful.

So.

So I suppose these champions really we engage very deeply with, because these are the folks that really will do the promotion for you without any effort, really, to be honest, because they're so passionate and so driven about learning and about these new technologies and these new skill sets. So, for example, we had an onboarding session with datacamp, and we had some of our Data Camp champions come on board who are topping our leaderboards month after month. So these guys were able to come on board and really talk to the audience who were, you know, on the fence maybe about taking some courses or weren't really sure how to engage or where to engage, where to start, even. So they provided the foundational kind of story of how they began, you know, all about how you can earn your experience points and talked about the variety of content as well that's out there. Also, we have some really great AI and ML experts within Dropbox who are just excellent teachers. You know, they're excellent instructors, they're excellent mentors and really effortlessly deliver boot camps to such a high standard. You know, we've had serious success with some of these boot camps that we've delivered internally and by word of mouth. Then word travels, people get really interested. We have multiple signups for our next one, et cetera. So champions are so important and like I said, they come from all different teams, all different organizations within Dropbox. It's wonderful. And we want to empower them to keep driving that, you know, learning, I suppose, passion all across the company.

That's brilliant. I love that you've got people who are like maybe a bit technical already or they're good at teaching and they've started mentoring other people within the organization. That's very cool. Mike, do you want to talk through. Have you made a use of champions at your organization in any way?

Yeah, and at Lockheed we have a of lot, a lot of engineers. So we're high on like the nerd scale of these types of new technologies. So there's a lot of internal advocacy. We've have our overall AIML ops capability where we have thousands of individuals using this and you know, we have training boot camps and various virtual conferences to which we can get people exposed to the technology and get them, you know, rolled in there. But honestly, you know, it's been a blessing that we haven't had to do a ton of internal promotion, although we do. And a lot of it's been through word of mouth and talking about what they have done going back to evangelizing. Well, I did it for this use case and someone else picks up on that. Well, I can use that too, or apply it in this way and that sort of thing. So there's an organic nature to it that's been very successful with. But I think over time you're going to get past the early adopters and then what we're focused on now is how to get the rest of the corporation and others involved that maybe won't be as excited to get engaged in kind of the AI revolution that we're all taking part in. That's going to be a key element moving forward.

That's very cool. When word of mouth actually works, it's like, well, as a manager you don't have to do things like all the employees or all the people who are taking this training, there's like, they're sharing stuff, they're promoting things just because they love it and. Yeah, makes your life easier, I'm sure. All right, so I'd love to talk about success stories because, I mean, this is why we're here, right? Is to have some kind of success with the training program. So I guess, are there any new projects that you've been able to take on or have you seen some kind of benefit from having AI training? Gio, you've not spoken for a while. It must be your turn.

We have this very cool program that's called the Post Data program, which basically we bring data and AI to embassies and posts around the world. And that program has been incredibly successful. And it actually sponsored, spearheaded like a grassroots movement with five initial posts that have launched the program. So Mexico City, Tegucigalpa, Tashcan, Jetta, Jakarta. These were really successful programs that were able to find problems underground and find or match those problems to sustainable solutions. And we've seen incredible successes. So let me just give you a stat because I'm a nerd, a self identified data nerd. So let me give you a stat. So our embassy in Tegucigalpa is able to use AI to save 50% of their staff time writing cables, which are basically field reports. So while folks do spend time fact checking, because of course we all know about the limits of generative AI and the dangers of hallucinations or confabulations, they still are able to save 50% of the time. That's significant. And that's less face to screen time and more face to face time for them.

That is so cool because normally when we talk about a big productivity boost, it's like, oh, we can do something 10% faster. And just being able to cut that time for writing reports in half, that's a massive win. I'm sure nobody like, well, maybe one or two people really love writing reports. I can't think there's like many people like really excited about like writing these sort of regular cables and just being able to cut down that time to sound very cool. All right, so I'd also like to talk about the impact on people's careers. So Mike, before you mentioned how this was tied to promotion. So you complete the training and then there's a possibility to get into one of the more technical roles. Can you talk me through just how that works?

Yeah, absolutely. And I love this approach because, you know, we lay out the various trainings and there's different Job codes and there's you know, obviously data related job codes and analytics, artificial intelligence, machine learning, data engineering. So we have these job codes set up and as the universities are a little bit slow to get the curriculum to have these students pumped out of the university system, but what a great opportunity for our workforce to upskill, right? So we have specific training for each one of those and an individual that thinks, well, I've heard about this AI technology, I think it's a huge future in this and it's going to help my career. So then they'll gravitate over, see, wow, there's free training for use. All I need to do is invest in my time, right? And then they, and it's not easy, right? So you have to learn, you have to do a lot of work and put time in. It's like taking a college course. But at the end of it they have all these skills and when they approach someone like myself or someone say I went through this on my own, on my own time, you know, as you know, having an employee that wants to do the job is half the battle. So they come in that I've invest, they've invested their time and effort because you're going to, honestly, I feel like you get really good engagement and employees as an artifact of that versus you know, a mandated type style training type of thing. So with that, you know, we love to inner source and promote our employees from within into these areas. Because as we all know, when you build any real application, whether it's artificial intelligence or the data or analytics, half of it's the technology piece, the other half is the domain. So you have to understand the domain. And a lot of all our employees typically come with the domain side so they learn the tech and then they're in a great position to be very successful.

That is a very important point is just if you've got domain knowledge and then you can use the technology as well, it's a fairly rare combination and it's incredibly powerful. So having that ability to do internal promotions must be a big boost for your organization. So there's a load of great audience questions. So I've got one more question for each of you, which is just what's your final advice for organizations that want to set up an AI training program? Yeah, Carol Ann, what's your golden nugget of wisdom?

I say go for it. No, I really think you'll never look back, right? AI is going nowhere. It's only going to become more transformative. It's only going to become more Innovative. So I really think even if you haven't started yet, there's time. Just start at the foundational, the fundamental side of AI. Really get your workforce, your teams excited about it. Start doing demos, show and tell, start bringing in some AI experts to chat about the landscape. I would really just start at the foundational levels and start building from there. AI is just transformative and we don't even know what the potential is yet. Right. So I think really just getting folks excited and starting from the ground up is the best thing to do. And obviously getting buy in as well from senior leadership I think is key because we want to drive that from the top down, which really, you know, resonates with your workforce then if that happens. So I'm excited for all of what's going to come in the future with AI.

Brilliant, Howie. Just go for it and stay excited. There's some wonderful goals there. Gio, what's your final advice?

I have a three ingredient recipe. So make it intuitive and accessible. That's ingredient number one. Ingredient number two, cast a wide net and make sure that even those people that are non technical get to have a little bit of fun. Then that third ingredient is reach for the sky. Go for making sure that everyone has a solid foundational understanding of what data is and what the AI is, but also for them to be able to have that comfort level that is going to allow them to incorporate additional knowledge on emergent technology. Because we're just starting and this is going to get even more exciting and more fun as time progresses. So that's my three ingredient recipe.

That's making a delicious AI training cake there. Nice stuff. And I love that we're back to everyone needs some form of training. All right, Mike, what's your final advice?

Yeah, I'd say just overall a lot of times training and these big activities gets put on the back burner, but you need to make it a top priority. We've seen return on investment by training our engineers, but also our business leaders with the benefits and appropriate applications of AI. I think it can be easy for us, Lockheed, to write off the non engineer types but really that's where a lot of the value is and what I tell people like that are do this for a living. Yeah, we have a lot of really great ideas but the best ideas are going to come from people like buried within the organization that aren't AI experts that get plugged in. That's where the really good ideas are going to come from and we need to have that kind of culture that's Brilliant.

I love it. Yeah. Again, everyone needs some kind of training because it's going to be those people with the domain knowledge that are going to come up with the good ideas. All right, we've got a load of great questions from the audience, so I'm going to switch over to those. So this question is, what should I focus on while giving my team AI training for the first time? Yeah. So we talked about a lot of different ideas for AI training. Where should you focus your efforts?

So the first thing that I would focus on is making sure that we have intuitive, plain language definitions for what data is. So text is data, numbers are data, everything is data. And then also not getting too much in the weeds, but actually showing and telling by showing people what tools are out there and what are some of the promises and some of the limitations of those. So starting small, so AI one on one would be really helpful. And I think that you all at datacamp have great resources to get that started.

All right, so, yeah, you got to figure out what's important in order to work out what you should focus your attentions on. Okay, so they've got another question on internal academies. So I guess this is something that a lot of larger organizations have. You've got some kind of training academy set up. So the question is, how can you balance training costs with achieving ROI efficiently for businesses? Yeah. So obviously there's a cost to training, but hopefully you're going to get some kind of benefit. Do you want to talk me through how you go about.

Right.

Reconciling the two? Like maybe how do you measure the return on investment and how do you know that the training program works? Mike, do you want to take this? You were mentioning ROI before.

Yeah, sure. And this is a good question because they're going to ask, well, what's the. So what, what's the value that are the training cost? But the way that we looked at it was we looked at the corporation as a whole and it's because a lot of, when you start out doing AI, a lot of times it's just for the, you know, AIML engineers, the very high, high level AI developers. But we look holistically at the corporation and then we show. Okay, out of that, let's segment out who needs to get what type of training and upskilling and then per, like almost at the individual level, what value you're going to get out of that Persona or that person. So the way it was a ramp that I ended up building and it showed 80,000 people on one side of the ramp and 5,000 on the other. The 5,000 are the high end, you know, machine learning engineers that are going to be developing capabilities. Yes, we need that, we need to promote that, we need to do that. But we also need to upskill into basic gen AI or like rag techniques or other things that can just do. And then here's the thing, each one of those people might not be a huge percentage of value on the high end of the ramp with the 80,000 people per person, but in aggregate the value is going to potentially exceed the 2,000 people that are hardcore AIML engineers when you look at the overall holistic value. So doing things like that and articulating that is sort of up the chain to executives. Justify the expense is really important because you can't get there without training.

Okay, yeah. So you're looking at what's the different amount of value add for different kinds of employees and then you can do some sort of aggregate over, like over job roles or over positions or something like that. Interesting.

Yeah.

Okay, cool. All right, I think we've got time for another question. So next one is to some extent we're responsible to take advantage of learning resources for upskilling. How can we establish the most important paths to upskill? Yes, there's a lot of different ways of doing AI training. How do you go about finding what's most appropriate? Caroline, do you want to take us?

I think there's so many different ways to deliver training and everybody is different. So learning is subjective to so many different people. Some people are very hands on and just want to get straight in there and start applying what they're learning. Some people are more. I'd like to watch some videos, I'd like to take it in at my own self paced, steady pace. And then other people, you know, are a combination of that. So blended learning for me I think is, is a wonderful way of delivering training. I think you're giving folks the option of which modality they prefer. And I also think we're being inclusive there, we're inviting people in. I also think having a mix of internal trainings. So what's your company doing in the AI and ML space versus external training like Data Camp and other learning platforms or talks or webinars, et cetera, they're all wonderful as well. So having a combination of different modalities, as I said, is really, I think for us it works. I would encourage it because again, I think people have different ways of learning and you just, you want to make sure that people are excited about it. As I mentioned before and meet people where they're at. It doesn't have to be a five hour training course. Bite sized chunks. Bring people in slowly and encourage them to keep learning. That's what I would really say. Just mix it up. Make sure there's a way for everybody to be included.

Absolutely. A lot of that makes sense that you need to know, like what stage people are at before they begin learning because there's no point like giving them stuff that's too easy or too hard and then figure out what mode of learning they prefer and how much time do they have. Lots of things to consider is basically know your audience, I suppose. All right with that. We are at time. It's so exciting. I wish we could talk for longer. There's so much exciting stuff we haven't covered. But anyway, that was absolutely brilliant. I really enjoyed that. So, yeah. Thank you, Gio. Thank you, Caroline. Thank you, Mike. Thank you to everyone who asked a question. So thank you once again to all our speakers. Cheers.

Bye.

Thank you.