Tech, Talent, and Transformation: Exploring AI's Impact on Startups (Episode 206...

Transcript

Jeff Bullas

00:00:03 - 00:00:36

Hi, everyone and welcome to the Jeff Bullas show today I have with me, Adam Danyleyko. Now, Adam is a dedicated advocate for the start up community with a background steeped in fostering growth and innovation. He is the Product Owner for startups at Amii, the Alberta Machine Intelligence Institute. He brings a wealth of knowledge and experience to the table. He has over four years of diverse experience in roles and hr business partner in Alberta Energy to policy analyst in economic development and trade. Adam honed his skills in community building and policy development

Jeff Bullas

00:00:36 - 00:01:22

and Amii by the way, is a not for profit organization that helps start-ups in Canada and he works for the Machine Intelligence Units or focusing on AI to help start-ups. His passion for nurturing start-ups ignited during his tenure at start-up Edmonton where he played a pivotal role in expanding post-secondary programming and leading the community team. Adams journey's support in power start up founders is underscored by his commitment to seeing others thrive with a Bachelor of Commerce and HI Management from the University of Alberta School of Business. He possesses the ideal blend of economic knowledge and practical experience to guide start-ups on their journey. His expertise in start ups, the AI advantage for start-ups, student entrepreneurship and ecosystem building, making

Jeff Bullas

00:01:22 - 00:01:30

the person to talk about AI for start ups in Canada. Thank you, Adam for being on the show. It's an absolute blast to have you here.

Adam Danyleyko

00:01:31 - 00:01:34

Yeah, thanks so much for having me, Jeff. I really appreciate it.

Jeff Bullas

00:01:34 - 00:02:00

So we're gonna have a lot of chats about AI today and why it's important for start ups to do it from day one, which I think was, you know, one of the areas we're going to explore. So tell us a little bit about your journey from hr and maybe tell us why you actually did a degree in hr what, what is there a curiosity there that became compelling? Tell us about how you got even to hr

Adam Danyleyko

00:02:02 - 00:02:34

Yeah, so when I started university, I actually thought I wanted to be an accountant. So I've been all over the place, I thought I wanted to be an accountant. Took a, took the, you know, kind of on 100 level accounting realized it was not for me, I was definitely more interested in the people side of things and I, so I transitioned over to an hr degree, worked as an hr business partner for the government of Alberta here in Edmonton for a few years. I really enjoyed a lot of, again, the people side of, of that role. But I, I didn't really love

Adam Danyleyko

00:02:34 - 00:02:59

the repetitiveness of the role. So I found it very, like, it always felt like I was treading water. Like I would have three recruitments on the go. I have classifications on the go. And for me, I really realized that I like more project based work where you can build up to something and have you know, your big day and then have a retrospective celebration and then move on to the next project. And so

Adam Danyleyko

00:03:00 - 00:03:29

that's kind of when I moved out of hr into kind of hr adjacent role, I guess you could say at first where I did, I ran a cross government internship program and a course program at the government. And then I moved over to start up Edmonton. So taking a lot of that student engagement work that I had been doing at the my last role at the government and applying it to the start up ecosystem to support the start up companies here at Edmonton, engage with students. And so that, that's really how I

Adam Danyleyko

00:03:29 - 00:03:59

transitioned out of hr And now I was outside of Edmonton for about four years in a variety of different roles and had many different responsibilities, but really built out a, a passion and a love for start up and for supporting founders. And then when this role at A E came up to continue supporting start up but to broaden my scope from just the city of Edmonton to all of Alberta, Canada and beyond. , it was definitely something that I had to jp at. So I've been in this role now for three years and really, really loving every day of it.

Jeff Bullas

00:04:01 - 00:04:56

Yeah, it's, it's very interesting that, you said you're interested in accounting. , I had that same interest in accounting cos I thought accountants made money but all they do is really count money. , and I, I, and I did spreadsheets. , and, I did, I did accounting. I did an accounting degree for one year and realized, that I would just, it really didn't suit me. For me it's more about people than spreadsheets. And in fact, our, our accounting main accounting professor, it was so boring that one day just in protest the student has brought PLL to class and actually put them down on the desk and he was really, really upset. I don't know why. But anyway, it was so boring. He put us to sleep. , and for me, my brother did accounting. I didn't, and,

Jeff Bullas

00:04:56 - 00:05:00

the rest is history. But anyway, so accounting, I totally get it.

Adam Danyleyko

00:05:01 - 00:05:07

Yeah. I mean, I think you last a little longer than I did if I'm being honest, if I'm being honest in there.

Jeff Bullas

00:05:08 - 00:05:19

Well, yeah, it, luckily I transitioned into a teaching degree, which is more about people. , but it's hard to know when you're younger, what you really want to do, isn't it?

Adam Danyleyko

00:05:21 - 00:05:54

Yeah, totally. I mean, it's hard when you don't have a lot of lived experience or, you know, even just work experience to know what you wanna do. It, it's definitely an interesting that especially, I mean, I feel like in North AmericAIt's a little bit more common for people to, you know, young people to go straight from high school right into university. , as opposed to, in Europe. And I think it's a little bit more common in Australia too. Correct me if I'm wrong, but to take more of a gap year and get some lived experience that's more common outside of North America than, than it is here. ,

Adam Danyleyko

00:05:54 - 00:06:04

I think that's probably a good idea to take some time live some live a little bit of life. See what you like, see what you don't like and then figure out what you really want to do for the rest of your

Jeff Bullas

00:06:04 - 00:06:59

life. Yeah. Gap year is becoming really, almost part of the course of doing the courses, you know? So the reality is that if you hadn't had life experience, how do you know what you're gonna find? Interesting? What are you good at? You don't, you might have been good at spelling and mental arithmetic, you know. , but you know, who you really got to go and get some life experience. So, I think the challenge in education is, is how do we get young people to make informed choices on what they're going to do in life? And the reality is that the world's changing so quickly that it's hard to know, what role you will play and actually what roles you will play because you used to, you used to have a career for life. You know,

Jeff Bullas

00:07:00 - 00:07:44

now it's like how many careers will I have in my life? And that's really interesting. And, and I think as you grow older, you actually change and you find things that interest you. And I think there's two words that interest me at the moment, which together I think help in this discussion is what are you curious about? And I tend to ask my friends about that and I go, I'm curious about a lot of things, but then the other question after that is, but what is compelling that actually calls you? And that's because out of that compelling comes drive and energy.

Jeff Bullas

00:07:45 - 00:08:26

But you gotta be curious first and that's really, and, and just to observe what you're curious about is quite often not considered. So, and when we're kids, we actually follow our curiosity all the time where we play as we grow up, we're told to be serious. because you're now an adult and we forget to play and explore. But anyway, I digress. So anyway, so, so you you moved from, hr now you're into start-ups. You must see a lot of interesting you're seeing basically almost a, a landscape of start ups, aren't you?

Adam Danyleyko

00:08:27 - 00:08:38

Yeah, we've worked like this year. So this, this past year my team supported over 100 start ups to 100 different start ups that we've worked with from all across Canada. Yeah. Yeah.

Jeff Bullas

00:08:39 - 00:08:54

So, out of these start ups is there sort of like some categories or areas that seem that start ups seem to be leaning into more than others? So you know, what's the beat of the street? The trends that you're noticing out of those 100?

Adam Danyleyko

00:08:56 - 00:09:39

Yeah, it's really interesting. So they're, to be honest, they're all over the place. I'd say every their start ups applying their work and focus to some of the world's biggest challenges and really covering all different verticals of our economy. So everything from, we're seeing a lot in the supply chain space, which has been something that has become more and more top of mind, I guess you could say since the pandemic and a lot of the supply chain challenges that were being faced during the pandemic and are are still being faced a lot in the health space. I think health is health and wellness is a, is a huge area that a lot of start ups are looking at.

Adam Danyleyko

00:09:39 - 00:10:06

and a lot of companies in general are looking at. whereas we, you know, in Alberta here, we were a very energy focussed economy. So we have a lot of oil and gas and energy production in our province. And so naturally with that, there's a lot of start up focus on on energy whether it's the generation transmission storage, use of energy that, that's a huge focus or reduc

Adam Danyleyko

00:10:06 - 00:10:33

and of, of energy usage is, is a big focus. So yeah, lots of, lots of big focus. We, we're also we're on the prairies and so in the prairies here in Canada too, we, we have oil and we have farming. So, Agrotech and Agro food is a, is a huge industry here as well. And we're seeing lots of start ups popping up in that space on how to make farming better, more efficient, more productive. Lots in those kind of spaces.

Jeff Bullas

00:10:34 - 00:10:53

Yes, it's, it's applying technology to actually be more productive, isn't it that, is certainly as technology has emerged, you know, and become much more visible since the post, I suppose the eighties, everyone ended up with a computer on their desk, everyone has a computer at home now. And then we have the rise

Adam Danyleyko

00:10:53 - 00:10:54

of no one has one in their pocket.

Jeff Bullas

00:10:55 - 00:11:44

We do, we have one in our pocket where we actually can share our consciousness with the planet that's then put into the social media platforms and beyond website. So, II, I certainly think that we're seeing we're almost emerging and then what I call a super conscious. In other words, hanity's intelligence, creativity is put into the cloud, the web. Now we've got so much noise trying to make sense of that is as hans. We are actually, you know, trends spotters, we try and we do pattern recognition but there is so much noise now globally. Is that how do you make sense of all that noise and data? And this is where AI steps in, isn't it? So it's, it's basically datAIs the new oil.

Adam Danyleyko

00:11:45 - 00:12:01

Yeah, I've heard that that's definitely something that that we hear a lot for sure. And we talk about here having the right data to answer the questions that you wanna answer is definitely important. Yeah. Yeah.

Jeff Bullas

00:12:01 - 00:12:35

So let's talk about AI and start ups and you with that and how you end up? OK. So interest of start ups hiring for start-ups maybe. But then you've, you're in this, you know, nonprofit for Canadian government or your region and you're now heading up the AI part to help start ups? How did you did this happen naturally? But was it your idea? Was it? Whose idea was it to actually lean into AI for start ups as a division, which is what you're doing, isn't it?

Adam Danyleyko

00:12:36 - 00:13:16

Yeah. So our whole organization is focused on AI. So our mission as A, as a not for profit is AI for good and for all, and so we work with all types of companies to support them in their AI development. specifically, my team supports the start ups. So tech start ups building rapidly available software solutions. And so when I, before I was on the team, there wasn't really start up a dedicated start up program. And so my task when I was hired was to figure out what we should be doing in order to support start ups on their AI journeys. And so really spent

Adam Danyleyko

00:13:16 - 00:13:53

a good year, I approached it like I was a start up. So I had a, a scientist on my team at the time, we approached it, like we were starting a start up, we met with a ton of different start-ups who had were at all different stages of their AI journey. So some that were really well versed in AI added in their product already, some that had tried and, and stopped or failed, some that hadn't tried yet, some that were brand new companies, some that have been around for 10 years to really see what, where the, the lay of the land was and what the, the op options already were for start ups when it came to AI where those roadblocks were.

Adam Danyleyko

00:13:53 - 00:14:39

And then we started. So we, we did our customer discovery, then we started rapid prototyping. So we started building different products, programs to support start ups and we would double down on what was working, we would kill what wasn't working. And over the course of that first year, we really built out two major programs specifically for start ups to help them. at the early stages identify where AI can be applied to their business and then prioritize that, that, that list of options in order to know where to start. And then we also built out a CTO coaching program for start ups that have deployed AI. So these are already AI companies to provide them ongoing support and resources in a more ongoing basis once they already have AI in their products.

Jeff Bullas

00:14:40 - 00:14:44

OK. So CTO, you mean chief Technical Officer, is that correct?

Adam Danyleyko

00:14:44 - 00:14:45

Yeah, exactly.

Jeff Bullas

00:14:45 - 00:15:04

Yeah. So you're basically trying to provide support to the Chief technical officers to help them. I identify, I suppose how I could be used for increased productivity and how it could be woven into existing products for new products.

Adam Danyleyko

00:15:05 - 00:15:34

Yeah. So these co these these are start ups that already have expertise in AI in some way. So they've already built some sort of an AI technology that they're leveraging in, in their product that's already in market. And so our program provides the, the main piece would be coaching. So we have machine learning scientists on my team. That coach have coaching sessions with our member companies to provide them an outside

Adam Danyleyko

00:15:34 - 00:16:03

opinion. A second set of eyes on how to improve their existing product and their existing use of AI or sometimes they're looking at a new way or a new tool or a new product that they want to build and we can provide them insight and advice into that aspect of their business as well. So we're really acting as an advisor as an outside third party set of eyes to provide support and advice in their, in their operations. So when we looked at the

Adam Danyleyko

00:16:03 - 00:16:32

in that customer discovery, we really realized, at least here in AlbertAIn Canada, there is a lot of supports for the business side of start ups. So most accelerators and you know, accelerators incubators, they're really focused in on the business side. So a ton of CEO supports, but there was a severe lack of technical supports on the technology side. And so that's really what our specialty is, is AI tech.

Adam Danyleyko

00:16:32 - 00:17:06

And so instead of reinventing the wheel and building something that already exists out there. On the business side, we f we decided to focus in on the technical side where our expertise was and provide those technical leaders at start ups coaching. We do expert sessions where we bring in either some of our research fellows or industry industry experts in AI machine learning to have sessions with them. We've had recruitment supports, we do peer networking. So it's, it's a whole fulsome program to support those technical leaders at start ups from across Canada.

Jeff Bullas

00:17:07 - 00:17:35

So with that, do you have, you had trouble resourcing the expertise you need in terms of, you know, are AI experts thin on the ground or is everyone learning as they go? In other words, they've got basic technical skills, but AI can do a lot of the technical skills anyway. So what resources do you need to help those CTO S that you've brought into the fold into the team to help the CTO S?

Adam Danyleyko

00:17:36 - 00:18:17

Yeah, that's a really good question. So predominantly the technical individuals that we're hiring are machine learning scientists. And so we have, we have quite a few machine learning, scientists and scientists in general on our team. We're very science heavy organization. And so these are often individuals with either a master's or a phd in AI and machine learning are, and so they ha they have experience often industry experience on top of that as well. So they have a, a wealth of knowledge that they can draw upon when they're working with our clients. It's as a research institute, we have

Adam Danyleyko

00:18:17 - 00:19:03

very good line of sight into the talent pool. So we're affiliated pretty strongly with the University of Alberta here in Edmonton. So we've, we fund the University of Alberta and we fund researchers there in order to who are doing fundamental research, those researchers are professors who have students, you know, grad students, phd S postdocs that are working with them. So we have, we, we support that talent pipeline of individuals. It's a few that I think it's three, between three and 500 students in, in the grad phd and postdocs that work underneath our fellows that we support. So we're, we're very lucky in that way that we can tap into that network pretty, pretty well. And then we also work to support a lot of the companies we work with to help them tap into that as well because

Adam Danyleyko

00:19:03 - 00:19:27

machine learning talent, like people who are experts in the types of things that we need them to be in and that the companies we work with, need them to be in. They're one of the most in demand skill sets in the entire world right now. And so it's a very competitive for that talent. So we're, we're very lucky that we have access into that. And we, we leverage that in order for a lot of the companies that we work with as well.

Jeff Bullas

00:19:28 - 00:19:35

Yeah. So what's the, so you've been doing this for, how long? Now, how long have you been working for a for Amii?

Adam Danyleyko

00:19:36 - 00:19:39

just coming up in a month? It'll be three years.

Jeff Bullas

00:19:40 - 00:19:48

Well, OK, so you've seen the rise of chat GP. T in, 2022 in the middle of that, haven't you?

Adam Danyleyko

00:19:49 - 00:20:36

Yeah, it's, it was, it was pretty crazy. , a lot of our conversations have shifted over the past year and a half, I guess, which is, you know, great. We're, we're having a lot more people, I guess today are aware of a, I as a tool that can be used. , and so it's, it's, you know, oftentimes makes some conversations a lot easier and that people have, we're not starting from scratch and explaining what AI is. But it also creates some unique challenges because a lot of people are, a lot of people want to look at a tool like chat GP T and, and come to us and say, OK, how can I use chat GP T to do X task or I want to use? How can I use chat GP T in my business? And

Adam Danyleyko

00:20:37 - 00:21:14

that's a, that's a fair question to ask. But when we're approaching problem solving and, and working through problems with our clients, we really like to start with the problem. So what, what are you trying to do? What are you trying to solve? And then we find the right tool to solve that problem. Whereas if you're saying I have chat GP T, what do I do with it? You're really starting with a solution and then looking at your business and trying to find a problem that it can solve. So it's a little bit backwards. But I'd rather more people know about AI than, than not. And it definitely makes it's definitely good, good conversation starter in a lot of

Jeff Bullas

00:21:14 - 00:22:11

ways. Again. Exactly. For me watching it and looking at the history of technology, it becomes apparent that once you give a technology a easy han interface, then that's when it becomes globally accepted. And that's what happened with, you know, the search, that's what happened with browsers. Browsers were given an easy, you know, Netscape arising out of mosaic. Back in the nineties, then we saw, you know, the search engines, you know, Google arise out of that, you know, type in, you know, your search query chat GP T gave basically the black box of AI gave it a han face interface so that it could be used by the world and the average Joe and that's where it exploded. And for me, I was just,

Jeff Bullas

00:22:12 - 00:22:50

I started playing with it about about four weeks after it came out and I went, wow. And I said to the team, my team, I said we're gonna lean into this. But it's the velocity is for me is what's mind blowing. I've seen the rise of PC SI mm My first career in tech was in sales and marketing when the PC industry took off in the mid eighties. You know, when Apple and IBM were duking it out and then rise of Microsoft and so on. So, but the velocity of AI and Chat G BT is mind blowing, isn't it?

Adam Danyleyko

00:22:53 - 00:23:30

Yeah, it's, it's definitely, is a very unique, unique case. I think when it comes to a technology that almost instantly become so ubiquitous around the world, it's not, and it's not something that I've, I don't think I've seen happen, I guess maybe when the iphone first came out, it would have been a similar instant, like, you know, maybe I don't even think iphone was, is as instantaneous as, as chat GP T because you can access this technology on any device anywhere. All right. So, and it, right now you can access it for free, which is, which is, which is even better. Yeah, it's really cool to see and really democratizing a lot of tasks that

Adam Danyleyko

00:23:31 - 00:23:44

in the past warrant are making things a lot easier, freeing up a lot of productivity time for people too. If you know how to use the tool, those types of tools properly, they can make you a lot more productive, which is, which is pretty incredible.

Jeff Bullas

00:23:45 - 00:24:38

Yeah. I'm fascinated by what I see the competitiveness emerging, especially amongst the bigger players in that. Chat EPT is certainly leading han. It's, it's the most visible and most conscious tool. Now we've got Google, you know, brought out barred. Now we've got, you know, and then we've got pla like Elon Musk are trying to get into it and NVIDIA are now getting into it as well. I saw recently announced that they're actually creating their own, chat G BT version because they own the hardware so they understand machine learning. So now, so my feeling is that I think, you can't discount Google. , but I wouldn't be surprised that Chat G BT has already won the race in terms of being the go to tool for generative AI, what do you think?

Adam Danyleyko

00:24:40 - 00:25:09

Yeah, it'll be interesting. I, I'm not too sure. I know Google announced Gemini fairly recently, which is I, I my understanding is it's the next iteration of Bard. So on that multimodal learning system. And so that'll be, that'll be really cool to see at the end of the day. It's, I don't know if there's gonna be AAA winner per se. I mean, there's lots of tools available out there and I think what will be interesting is how the tools

Adam Danyleyko

00:25:10 - 00:25:58

are integrated into other, other ways and how they're used to in, in kind of the backbone of, of different things. So pretty soon, if not already, you'd be able to build a company like one person using GP T for GT five, whatever it ends up being in the near future. We'll be able to build an app using GP T that runs on GP T and so it'll be for start up. I think it's gonna be fascinating to see what that, what that looks like going forward and how the start up landscape changes. How would that will mean for investment and investors over time? Are, are, are those companies going to be investment eligible? Not eligible? But will investors want to invest in companies that are one or two people? running them in that kind of way?

Adam Danyleyko

00:25:59 - 00:26:12

I think it's gonna be fascinating to see how these types of tools are gonna change. Not only our, our day to day lives and our own individual productivity, but the the landscape for start ups around the world. I think it's gonna be fascinating over the next 1 to 2 years.

Jeff Bullas

00:26:12 - 00:26:43

Yeah, it's it is, I am really curious about this amplification and extension of our hanity with the AI tools which can do a whole range of things, solve a lot of problems. I read a book recently called The Next Wave by Mustafa Sofi, the founder and CEO of Deep Mind that got bought by Google for nearly a billion dollars. And I said to, I said to my team, I said really what I think is going to happen is that

Jeff Bullas

00:26:44 - 00:27:25

within a few years, I don't know how long those few are, but we will see billion dollar companies run by five or six people because they've got the tools to amplify them. That's and what will that do to start ups, well, you gotta start thinking in different ways. And Mustafa actually said that he believed one of the models at the moment we're using a hate, you know, chat GP T and generative AI to actually do research, find information, organize it. Do the writing for you, for example, create images for you, do the marketing funnels, you know, copy. And the list goes on, he says that one of the models he think is going to happen is that

Jeff Bullas

00:27:25 - 00:28:10

eventually AI will be able to do, not only the thinking and do the research, but actually do the functioning, the doing. And he says one model that I think is going to be interesting to watch is it could be applied to templated models such as, you know F BT fulfillment by Amazon FB A sorry fulfillment by Amazon type business models where you find A AI will do the product research, it'll do the marketing program, it'll come up with the idea, it'll then source the product, it will then actually then use Amazon to do the delivery and then actually then the payment. So he says that technology isn't there yet, but he sees the potential within a more templated models for AI to actually scale a business quickly.

Jeff Bullas

00:28:10 - 00:28:22

and do it from start to to actual delivery of the product eventually aided by logistics and talked about logistics are actually a big or fulfillment for you in Canada as well.

Jeff Bullas

00:28:27 - 00:28:30

So we've frozen a little bit here

Adam Danyleyko

00:28:31 - 00:28:31

I asked

Jeff Bullas

00:28:31 - 00:29:24

you. Yeah. Yeah so. Ok we're back. Alright. Stream was frozen so I was I don't know where we got up to but we're talking about the fact that within a few years we're going to have businesses that we run by a few people and it could generate like they performed by Amazon stores can be turnover of 200 million. But AI and Chat G BT are actually gonna end up producing the actual technology to do everything from start to finish, ideation, source product, write a marketing plan, get it in, you know, get it delivered, get the money in. So, and that's what my staff has said that he believed that sort of business model could certainly happen within a few years. It's not there now. But , so what do you think about that? Like you just mentioned the idea that

Jeff Bullas

00:29:24 - 00:29:37

people can start a business, a start up. It's only one or two people or three or four people. But cos generative AI and could actually scale our hanity right through the business chain, right from start to finish. What do you think?

Adam Danyleyko

00:29:38 - 00:30:19

Yeah, I mean, I think that's definitely possible. I think it, when a, anytime you're looking at a company or a start up something really important to think about as a founder is, what's your moat? So what is, what is your, what is, separates you from other people? What makes you unique? What makes your company unique? And I think when like the down, like the upside to having a company like that is, you know, a company that's run on G BT is you can, again, like you said, you can get something up and running with very limited people, very limited overhead to get it going. I think a huge risk of those types of businesses though are,

Adam Danyleyko

00:30:20 - 00:31:08

there's not a lot of moat. So what happens if you build a company around the tool and then open AI releases that tool themselves? Your company no longer exists. So like, because now you're competing directly with open AI or what happens when the, when you're, when you're, your whole company is 100% reliant on another company's existence that feels very risky to me. So what happened? Like we, we just saw a couple of months ago open, I almost didn't exist anymore. There was like a, you know, a company that had gone from obscurity. Nobody really knew about it to one of the most well known companies in the entire world to almost not existing in less than a year and they were able to recover through that. But it, it just shows that all of these companies,

Adam Danyleyko

00:31:09 - 00:31:34

they're, they're, they're companies, they run by people at the end of the day, at least for now. And they're, they're open to the, the ups and downs and the pitfalls of any other company. And so when you, like I said, when you're 100% reliant on someone else being in business, one other company being in business and, and maintaining the product in the way that you need it to work for your business. That feels very risky to me. And so that would be my, my

Adam Danyleyko

00:31:34 - 00:32:00

kind of caveat there is you can, there's lots of upside. There's definitely some downside when you're putting all your eggs in one basket like that though. So it's gonna be very interesting, I think, to see how, how this all shakes out and what the next few years looks like. And I think there's gonna be a lot of amazing companies that get built. There's probably gonna be a lot of companies that raise a ton of money or make a ton of money and then disappear, or then

Adam Danyleyko

00:32:00 - 00:32:39

open AI or Google or Microsoft or whoever creates the same tool that they're building right now. And then a lot of those companies might disappear overnight. So I think it's gonna be a very, maybe tultuous is the right word to for the next few years I can, if I had a crystal ball and predicted, I would say there's gonna be a lot of, a lot of uncertainty in the waters over the next couple of years when it comes to start ups. But there's lots of opportunities and I think if you're building a company it has good f good fundamentals. You really understand your customer and the problem your customer is facing and then you build a product that is really working to solve that problem for your customer.

Adam Danyleyko

00:32:39 - 00:32:49

So, those are the companies I think that are going to succeed. So that's, that's really what I, I, those are the ones that I tend to gravitate gravitate to, and the ones that I've seen succeed so far.

Jeff Bullas

00:32:50 - 00:33:31

Yeah. Yeah, it's, and you can build an app quite quickly now with generative, you know, AI, chat G BT. And we've seen that happen with the opening in, I think it was January 10 after, open A, I announced their developer, I suppose final development program for people to create, generate specific niche apps under the banner of the generic chat GP T app. , and what blew me away is within three months. I think it was when they launched on January 10th this year, they opened the GP T Store with 3 million apps.

Adam Danyleyko

00:33:31 - 00:33:42

Yeah. Yeah. But how long, I wonder how long it would be interesting to look back and see how long it took Apple to hit a million apps in their app store. I didn't open with a million apps.

Jeff Bullas

00:33:42 - 00:33:46

I can tell you exactly how long it took. , five years.

Adam Danyleyko

00:33:47 - 00:33:54

Yeah, five years to hit a million and open AI hit three in a month,

Jeff Bullas

00:33:54 - 00:34:34

three months from actually opened the store with 3 million. I wrote an article recently about that because I was fascinated by this velocity. The only thing is I started looking at some of the apps in the store. I'm just looking at the top trending apps, the 10 top trending apps going to write about that soon, that's actually written. But what I'm starting to notice is, there's a phrase that used to be, there's an app for that. I think what I'm noticing is with the chat G petite store is we're gonna end up with a lot of crap apps As in Yeah, for

Adam Danyleyko

00:34:34 - 00:34:36

sure.

Jeff Bullas

00:34:36 - 00:35:21

A and what I mean by crap apps means they don't do much more than Chat G BT. They've just been given another name and they don't do much. So I think there's a thing called quality versus quantity, I think at the moment, There is, I'm sure there is quality in amongst all that quantity, but the issue is sifting through that is going to be a minefield and that raises a question for me. Based upon what you guys are doing is you're dealing with start ups, you identify a problem, then you go looking for the tool to solve that, an AI tool. How do you guys do that? Because the AI tool landscape is now vast,

Jeff Bullas

00:35:22 - 00:35:40

not necessarily deep but vast So how do you identify the tools? Do you have preferred tools that you recommend? Tell us about that because that's an issue I believe that we all face in the rise of AI apps is that trying to find good tools amongst all the noise?

Adam Danyleyko

00:35:41 - 00:36:25

Yeah. So when we're working with a client, kind of my team would help them at the early stages of seeing where those opportunities within their business are. Then we have other across our other teams, we can scope out a specific use case. And we do a lot of research in those, those projects to help them. We do literature reviews, tech reviews. So we're, we're doing research, we have scientists that are out there doing research and identifying the right, the right approach, the right tool for, for them. And we like to look at we get them, we look at should they buy a solution? Is there an off the shelf solution? They should buy. Is there a something that they need to build or is it something that they can partner

Adam Danyleyko

00:36:25 - 00:37:01

on? So those are typically the three avenues that we look at? And then because sometimes it's actually you have to build the solution yourself, that's, you know, this has never been done before. You have to go out and, and build the model, build the solution yourself. But there's, you know, if you're looking at, at having a a root optimization aspect to a tool you probably don't need to build that yourself. There's, you know, Google. Google has an incredible tools around that. Amazon would have great tools around that. So there's tools out there that already exist with that. So we don't want our, our clients wasting time energy and resources on

Adam Danyleyko

00:37:01 - 00:37:12

building something that they can buy or partner on pretty, pretty seamlessly. And then, but when it is appropriate for them to build their own, then we help them with that as well.

Jeff Bullas

00:37:12 - 00:37:21

Yeah. So how do you find those apps? Is it basically, do you have you created like your own library resources that you become your go tos?

Adam Danyleyko

00:37:24 - 00:38:06

Yeah, I mean, we, we definitely have tools that, that we, we've worked with and that we, we know work well. a lot of times though what, what we're not necessarily looking at the same types of tools that a conser would be looking at. So we're looking at what types of, of models are in the background. So these aren't all these wouldn't really be considered like conser facing products that we're looking at. So like we, we're looking for mo like AI models that would be able to do a specific task or, or help support in collaboration with other tools to deliver the tasks that our clients are looking for. And so it's not the, it's not,

Adam Danyleyko

00:38:07 - 00:38:37

we're not necessarily looking at like the open AI APP store in the same way that you or I might look for if we had a specific task that we wanted to solve. Our scientists oftentimes too are a lot of times we're, we're building those models for our clients and with our clients. So they're actually, you know, in writing code, training that code and those models on, on our client's datAIn order to achieve the results that they're looking for, whether that's cla a classification system using, looking at computer vision or natural language processing

Adam Danyleyko

00:38:37 - 00:38:59

or making a prediction. So whether they're looking to make a projection about the future to produce some sort of an output to prevent something from happening, promote a specific area or personalize something. Those are the five pieces of AI that we look at. we work to build that out or to find the right option for our clients.

Jeff Bullas

00:38:59 - 00:39:06

So just, just go a little deeper on something you mentioned about the five PS of AI. Could you list them again slowly and

Adam Danyleyko

00:39:06 - 00:39:25

yeah, yeah. So I guess five PS in terms of how AI provides business value. So it's project produce prevent, promote and personalize. Those are the, the five ways that we, we look at how AI can provide business value.

Jeff Bullas

00:39:27 - 00:39:40

So you got project produce, prevent, promote, promote and personal. Is that a model that you guys developed?

Adam Danyleyko

00:39:42 - 00:40:03

I don't think this is our, in, like the words that, you know, that we've, specifically pulled together. I, I, my understanding is that they're, there are more common, understanding of, of business, value for AI, as opposed to something that we've specifically pulled together. But to be honest, I'm not 100% sure.

Jeff Bullas

00:40:04 - 00:40:08

All right. That's fine. , so

Jeff Bullas

00:40:10 - 00:40:23

are you seeing some really positive results from start ups that are using AI in their day to day, either producing a product or using it to be more productive?

Adam Danyleyko

00:40:24 - 00:40:49

Yeah. Yeah. A lot of I mean, a lot of our, our clients are leveraging tools for their own individual productivity like chat GP T and different tools like that. That's not so much what we focus on. We're focusing more on how can they build AI into their product. And so, and to, to improve their product. And so a lot of the start ups that we work with when,

Adam Danyleyko

00:40:49 - 00:41:17

when they are looking at how AI can help them. It's, it's oftentimes when they're at an inflection point and they're about to start scaling. So they need to scale very rapidly in the near future geographically or in terms of the nber of customers or in some way, they're going to be scaling rapidly. And a lot of their manual processes that worked when they were this big are going to break down entirely when they're this big. And so that's where a lot of AI models are able to really support them is in that scaling.

Adam Danyleyko

00:41:18 - 00:41:48

And so we've seen a lot of, a lot of the start ups that we've worked with, leverage AI in order to scale a lot more rapidly than they'd be able to and a lot more affordably, than if they had to scale by scaling up their manual processes. So, like if you, if you would imagine, like if you were scheduling, I don't know, for example, garbage pickup and you had a per, you know, when you only have five trucks, you can,

Adam Danyleyko

00:41:48 - 00:42:14

you can just have a person that works in an office and does the scheduling for those five trucks every day. But when you're starting to expand to different cities and now you have, you know, 5000 trucks across North America. Well, now, in order to, to do that scheduling, you either need to hire hundreds of people or you'd have to build some sort of an AI system to help manage that. And so that's, that's oftentimes where a lot of the companies that we see are having the most success,

Jeff Bullas

00:42:15 - 00:42:20

right? So the scaling more productive, doing more with less. Yeah.

Adam Danyleyko

00:42:20 - 00:42:21

Yeah. Yeah, for

Jeff Bullas

00:42:21 - 00:43:15

sure. Yeah. So, in terms of, I, I suppose building tools, the, the other question I have is we're seeing a lot of tools being built by emerging start ups. So you've got the new start ups building tools. and they're taking on the big guys that already have the resources to build the same tools. So you got something, for example, like I'm gonna do you know, Canberra, it's an Australian company. It's maybe got three or 4000 staff. Now it does images makes it easy for people to do. You know what Adobe made difficult with Photoshop, for example. So Canberra basically became a competitor to Adobe to actually make it easy and democratized design. Instead of having some, you know, designer that worked out the complexities of how to use Adobe Photoshop

Jeff Bullas

00:43:15 - 00:44:00

and democratized design almost effectively for, you know, graphics for business, you know, images. Now it's moving video, now it's adding AI to its images and so on, then you've got to start going, I'm gonna do the same thing. Except they have the resources. So there's this battle between the start ups with an idea about producing a tool that solves the problem versus an existing larger company that has the resources to actually add it quickly to their already their ecosystem and their, their, their conser base. How do you see that playing out? Like is there going to be the rise of some start ups that will overwhelm the existing players or do you think the existing players have the incbents

Jeff Bullas

00:44:01 - 00:44:12

have a much better way of actually fighting off those start ups that are trying to take their territory. So start up is the incbent.

Adam Danyleyko

00:44:12 - 00:44:38

I think you know, very short answer would be, I think it depends. I think that it's really going to depend on the situation. So in some cases, having that legacy and having the resources to back up a company. well, in certain situations allow them to succeed and allow the legacy companies to succeed. In some cases, having the,

Adam Danyleyko

00:44:39 - 00:45:05

you know, diamonds are, they say diamonds are made under pressure, right? So when you have limited resources, you have all these constraints on you oftentimes, that's when you see some of the most innovation taking place. So sometimes that the constraint of less resources allows start ups to actually be more creative and more innovative than a large company might have. also like a lot of the companies now that we think of as these big, you know, that not just we think of that are these big industry players,

Adam Danyleyko

00:45:05 - 00:45:33

the Metas, the Googles, the Ubers, the, you know, name whatever company they were all start ups not too long ago. And so it might have been 10 years ago, it might have been 20 years ago, they were the start ups of, of that time. So for sure there's gonna be new companies that, that come out of, you know, seemingly nowhere and take over giant chunks of market share. They might those companies might get knocked out of first place at some point. But there's also a lot to be said about having the resources

Adam Danyleyko

00:45:33 - 00:46:01

is behind something as well. So I think it's, it's really gonna be dependent on how the large companies can stay innovative and stay at the, the front, the forefront of a lot of these areas. But it's also how can start ups take advantage of the constraints that they're under in order to be even more innovative. I think that that's really where that's gonna con continue to happen. We've, we've most innovations, a lot of innovations over the past 20 to 50 years

Adam Danyleyko

00:46:01 - 00:46:25

have come out of start ups and they've either then been, you know, grown that start up into a large company or they've been acquired by a large company or the technology has been licensed or whatnot. But a lot of innovation is still have most innovation in my mind is actually still happening at the start up phase and in, in start ups. So it's gonna, it's gonna continue to drive innovation and economic development around the world. Yeah,

Jeff Bullas

00:46:25 - 00:47:08

I, I would very much agree and you only have to look at , one example is Uber, which took on the incbent taxi industry globally. because the problem was they tried to smon a taxi in Paris on a cold night and they just couldn't get one, they drive past, they're already full. They said there must be a better way to solve this problem. And we all remember being late night in the sea trying to catch a cab and they just keep driving past, and in a cold climate like Canada, I think that's really important versus Australia where, you know, we don't have your snow but, and Paris gets cold at night. So during winter, Uber basically

Jeff Bullas

00:47:09 - 00:47:49

went in, created, solved a problem and the taxi industries are very, very slow to respond. They thought their moat was, they're protected by bureaucracy, government regulations. But Uber actually broke a lot of rules along the way to do that, like ignored them until it had a position where it actually now is you go to for a, for a car ride to somewhere else and it does do a lot better than the taxi industry. but the taxi has got better. So the incbent gets lazy and feel safe behind what it sees as a moat that sometimes can be jped by the start up, can't it? So Uber is a perfect example of that.

Adam Danyleyko

00:47:51 - 00:48:30

Yeah, 100%. So I, I, yeah, completely agree. I think it'll be very interesting to see how, how, how the next few years shakes out. I think, you know, it's gonna be the same thing that I mentioned earlier. I think it'll be a little tultuous over the next few years to see how these different industry players work. And you know, the nice thing about AI and you know, going now and into the next few years is it's democratizing so much of these skills and that used to be very expensive to acquire, they're becoming a lot more affordable or a lot. Sometimes you don't have to pay for them at all or you're able to do things like you were talking about with that that

Adam Danyleyko

00:48:30 - 00:48:50

Adobe competitor being able to democratize design. But now you're able to democratize so many different tasks to bring the barriers of entry down for so many of these start ups that they're able to legitimately compete with large companies and incbents at a rate that I don't think we've ever seen before. So it's gonna be, it's gonna be very interesting to see how it all shakes out.

Jeff Bullas

00:48:50 - 00:49:28

Yeah. And it was I read this morning actually New York Times about what are the skills that AI doesn't have? What does hans, hans have that AI doesn't have? And we're talking about the fact that AI now generative AI can actually, at the moment we're starting to do 90% of the really difficult technical tasks which used to be promote to stop people getting stiff done. So actually AI is now generating code. It's right. It's creating websites. So that's the high technical skills that are actually being done by generative AI and AI itself versus soft skills.

Jeff Bullas

00:49:29 - 00:50:26

So, I think, and I agree, I think the rise of the importance of soft skills, communication skills that can't be replicated by AI at the moment. But I think communication are going to become even more valued because the tech stuff can be done by machine intelligence, right? So it's really fascinating to watch this, but the pace of it is what blows me away. Yeah. So for me, I almost, well, I feel overwhelmed in this space and I'm, I live and work and breathe in this space. The average Joe or Jane would struggle would even be struggling more. So we're having more and more conversations around the dinner tables about the importance of AI and where it's taking hanity. So,

Jeff Bullas

00:50:27 - 00:51:04

but then there's, you know, the one you mentioned in the five ps was prevent. and the other one that's a big question for AI is the containment of AI things that we AI should not be doing. And we're seeing that, for example, in deep fakes. In other words, people basically copying other people. And there was an example recently of someone, a look that did a deep fake of their CFO asking someone to move $23 million and they did it, they thought that was the person, it was a deep fake of the person.

Jeff Bullas

00:51:06 - 00:51:24

So where do you see some of the issues? And you're observing it in this whole landscape of start-ups. What are some of the big issues and maybe s this up to finish off. What are the, both the issues and the opportunities you think that AI brings to start ups?

Adam Danyleyko

00:51:26 - 00:51:57

Yeah. But, so I guess like maybe to kind of touch a little bit on what you just said too is our mission here at AM E is AI for good and for all. So we, we take that very seriously. And we work very hard Even in our, before we're getting into a contracting phase to make sure that when we're working with a client, they're aligned and the project is aligned with that mission. So we, we say no to projects that aren't aligned with that mission. Because we, we don't think that

Adam Danyleyko

00:51:58 - 00:52:27

AI should be used for everything. There's, there's lots of stuff that, that it shouldn't be used for. It's a tool but like any tool, the tools can be used for good things and used for bad things. You can use a hammer for a lot of different things, but a hammer is just a tool so that the hammer itself isn't inherently good or bad. It's what we choose to use that hammer to do that is good or bad. And so it's the same with AIAI is just a tool that we are able to leverage when it comes to start ups. It's

Adam Danyleyko

00:52:29 - 00:52:58

I think, like I said earlier, like when it comes to how start-ups can leverage AI, it's how can they, how can they improve their business processes? How can they scale and reduce the the need for manual processes within their product as much as possible or not as much as possible in order to scale effectively. I think it is a big opportunity for start up that we see often at the product level, at the individual contributor level. There's lots of AI tools like chat,

Adam Danyleyko

00:52:58 - 00:53:27

I mean, I use chat GP T in my, it's al it's always open on my browser. I'm using it for different tasks throughout my day to make my life and my my job easier and to make myself more productive. I think every like most people, if not, everybody should be using tools like that to help make them individually more productive when they're looking at how can they build it into their product and how can they leverage it in their product? You know, like I said, those, those five PS of AI are the ways that we're seeing companies use it. So are they projecting future

Adam Danyleyko

00:53:27 - 00:53:56

sales of projecting future sales demand for maybe for their product or for other products? Are they producing something? So, is generative, using generative AI, are they producing some sort of content within that for their client, are they preventing injuries by using computer vision to look at or monitor safety situations on a job site or to prevent oil spills or identify those oil spills when they happen? Are they promoting or they, are they able to

Adam Danyleyko

00:53:56 - 00:54:19

look out and better individualized promotion and get messaging out that they want to get out to more people or the right message to the right people and personalizing experiences as well. So those are the ways that that start ups really should be thinking about AI and we help start ups through our, our programming to look at their business and identify those areas that

Adam Danyleyko

00:54:19 - 00:54:43

AI can be applied to and help them prioritize that so that they know where to start, how they can start approaching AI start thinking about it within their business and then we can support their whole journey all the way through scoping out a problem, building it out, finding talent to support them as well and then coaching them once they have it built out. So when it comes to start ups, we can help along the whole AI adoption process for them.

Jeff Bullas

00:54:44 - 00:55:34

Yeah I think in sming up what you've said is that you want to make sure that AI and it's the mission statement of, of the, of Amii, isn't it? In other words, it's for the good of people. In other words, if it doesn't fit within it being good then it's not going to be. , well, you won't allow it and you won't get involved. A and this is where, so that's one is that it's basically making sure that we're using technology for good and AI for good. And what's really good to see is that we're having conversations about this, like the EU is about to launch essentially policies for containment of AI or make sure it is for the good. which is a conversation we should have had about social media about 15 years ago.

Adam Danyleyko

00:55:35 - 00:55:50

Yeah, it's definitely. Yeah. Yeah, I, I don't, I don't know if anybody could have guessed 15 years ago what social media would have turned into today, but it would have been good to have more conversations back then for sure.

Jeff Bullas

00:55:50 - 00:56:22

Yeah. and look for me, social media has given me a voice to the world that I never would have had. So for me, it's really interesting. I was involved in a world youth for event about five years ago, four or five years ago. There was a round table hosted by the president of Egypt and it was the forces of social media and the against social media. And for me, I was on the fore side, we all had three minutes. But what was fascinating. It was a Naha moment, I suppose, a tipping point for me to understand that

Jeff Bullas

00:56:23 - 00:57:11

we need to be very aware of social being, social media's being abused rather than used properly. It's being used for good and for bad disinformation is basically starting to tear democracies apart. Disinformation. So, yeah, I, I think we're having this conversation early on with AI which is really, really important and it doesn't mean you're gonna stop the bad actors, bad governments using it to, you know, control people. But anyway, it's, but the velocity as I said before is really what blows me away is that we're trying to ride a bucking racing, you know, Bronco, that's just out of the gate. But we're getting in early, which is really good. So,

Jeff Bullas

00:57:12 - 00:57:56

anything else you'd like to contribute up some of the insights just before we wrap up? Like what you've learned along the way that you think are important for start ups to consider, especially with AI. That's the first question. The other question that you want, what I want you to answer in the best way you can is what brings Adam real deep joy in what you do. And in fact, if you had all the money in the world, what would Adam do? But that's the last we wrap it up and let you sort of like circulate a little bit percolate. These are good questions. Yeah. So nber one, so what are some of the things you'd say to start ups in their journey of starting to use AI and apply it.

Adam Danyleyko

00:57:57 - 00:58:22

Yeah. So I think first thing would be start thinking about it early. So I like, I like to say start ups should be thinking about AI from day one, whether or not they're building an AI product. O oftentimes I work, we see a lot of start up that come in that want to start building out an AI model and that, that's fantastic. That's what we're here to help. And then we, we ask them, OK, what data do you have?

Jeff Bullas

00:58:22 - 00:58:59

To help build that, that you need to train your model on data. And they have, they, you know, they've been having a, they've had an app or they've had a product for years and they, they haven't collected any data on how customers are using their app or whatever they need to do. So then they have to start collecting that data before they can build their model to be trained on said data. So you can start collecting data early with and even better if you have an idea of what the potential future AI model could look like. So, you know, what data you would need to be collecting along the way, it's gonna make your life so much easier when you actually want to start building that tool.

Jeff Bullas

00:58:59 - 00:59:36

So that'd be the first thing. Second thing is start with the problem and then find the right solution to that problem rather than starting with a solution and trying to find a problem that it fixes. So that would be my other big piece of advice for start ups when it comes to me and what really drives me, It's really what it comes down to is helping people. So I, I love supporting people and really building the community around me. And so whether that was during my time with the governor of Alberta, supporting the people of Alberta and the people of the province that I live in or

Jeff Bullas

00:59:36 - 00:59:57

at start up Edmonton, supporting our city and the entrepreneurs in our city to now, you know, I have my team that I work with every day here at AM E but also to our community of start up that we work with and support all across the country. And so that's really what brings me joy and brings me happiness. And whether I, if I had, you know, all the

Jeff Bullas

00:59:57 - 01:00:18

in the world, I'm sure I would still be doing something every day to help people to help them achieve their goals and to help them may be the best that they can be. So that's really what I try and do every day here, whether it's internally with my team or whether it's with the start ups that I work with. So that, that's really what drives me and motivates me at the end of the day.

Adam Danyleyko

01:00:19 - 01:01:05

Thank you very much for sharing that. And you've actually with what brings you joy is community and obviously relationships and bringing value to those. And the, the science actually says that's what brings people happiness the most, which is relationships and the 87 year old Harvard study reveals that the people that are happiest are the ones that actually had quality han relationships and that's what brought them joy. And you're actually doing that. So trying. So, Adam, thank you very much for sharing your insights. It's been absolutely fascinating. I loved our conversation and it was great and look forward to maybe bping into you on the other side of the world sometime. And

Adam Danyleyko

01:01:06 - 01:01:24

yep. So thank you very much. It's been a blast and I've learned a lot which is always brings me joy. I love learning. I'm curious but building relationships. this is, you know, and every, every relationship starts with a conversation. So thank you for having a conversation.

Jeff Bullas

01:01:25 - 01:01:29

Yeah. Thanks so much for having me. It was, it was my pleasure being here. Really. Appreciate it.

Adam Danyleyko

01:01:30 - 01:01:30

Thanks Adam.