Adam Torres and Adam Danyleyko discuss Amii.
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Show Notes:
“AI for Good and For All” is one of Amii’s mission statements. In this episode, Adam Torres and Adam Danyleyko, Product Owner – Startups at Amii (Alberta Machine Intelligence Institute), explore Amii along with its upcoming Upper Bound conference which is the largest AI conference in Canada.
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About Adam Danyleyko
Adam is passionate about supporting startup founders build & grow their businesses. As the Product Owner of Startups at Amii, his team is building programming to help startups explore, build, and deploy ML & AI Technologies. Adam got into the tech ecosystem through my time at Startup Edmonton where he was the Community Program Manager and oversaw a variety of different programs over my time including on-campus student engagement, Talent Program, Student Developers Conference, space & member management, and supported all other aspects of Startup Edmonton’s programming including Edmonton Startup Week.
He also has experience in a variety of roles within the Government of Alberta, where he worked for 4.5 years before coming to Startup Edmonton. His most recent role was with the Alberta Public Service Commission where he ran a cross-government Policy Internship Program and the popular Policy Essentials course program. He is a graduate of the University of Alberta School of Business and have a Bachelor of Commerce in HR Management. Outside of the office, he coach case competition teams and has served as Chair of the Board of Directors for JDC West Business Competition, an organization he has been involved with since 2012. He loves drinking local craft beer, spending time in the mountains, and discussing theories on A Song of Ice & Fire, Star Wars, Marvel, and a variety of other Sci-Fi & Fantasy stories.
About Alberta Machine Intelligence Institute (Amii)
Amii grows machine intelligence capacity and capabilities in Alberta. Originally formed in 2002, the Alberta Machine Intelligence Institute (Amii) explores the frontiers of scientific knowledge and drives business adoption in the fields of machine learning & artificial intelligence, together called machine intelligence. Through world-class research, development and education, our team of experts, including over 120 staff and students, work to advance academic understanding at the University of Alberta and other affiliated institutions and to leverage world-leading academic talent and expertise to grow Alberta’s machine intelligence literacy and build AI and machine learning capabilities in business – from early adoption to advanced research and development. Amii is home to some of the world’s brightest minds in machine intelligence.
Full Unedited Transcript
Hey, I’d like to welcome you to another episode of mission matters. My name is Adam Torres. And if you’d like to apply to be a guest in the show, just head on over to mission matters. com and click on, be our guest to apply. All right. So did I have Adam Danny Laco on the line and he’s a product owner over at and startups at Amy also known as the Alberta machine intelligence Institute.
Adam, welcome to the show. Yeah. Thanks so much for having me really excited to be here. Adam, we got, I almost said Amy and it’s not Amy. Amy’s the, Amy’s the, is the Alberta machine intelligence is too. All right, Adam, I gotta love another Adam on this show. So excited about, about today’s topic. So we’re going to talk about how AI optimize processes and how I can optimize processes and also enhance customer experiences in businesses.
And also we definitely got to talk about, I think you got the, the Third annual conference coming up for upper bound, which is your which is a big AI conference. So we’re going to get into that as well, but Adam, I think you already know the drill and so does my long time listeners. We’re going to start this episode the way that we start them all with what we like to call our mission matters minute.
So Adam at mission matters, our aim and our goal is to amplify stories for entrepreneurs, executives, and experts. That’s our mission. Adam, what mission matters to you? Yeah, so at Amy, our mission is AI for good and for all, and my team, the startups team at Amy directly supports that mission by helping and supporting tech startups across Canada and beyond to explore, build and commercialize AI and machine learning technologies, and we help those startups do that in order to help them solve some of the world’s biggest challenges, and so, for example, one of the companies that we’ve worked with is a company called Google.
Echo, and they’ve developed a system to diagnose of a variety of different conditions using machine learning and ultrasound images. And one of their first products in the market is detecting infant hip dysplasia. And so they’re able to use AI and machine learning to help save thousands of people. Pain and suffering later in life.
Cause if they’re able to diagnose it when it’s a baby and they’re able to treat it and stop that person from having conditions like osteoarthritis later in life. So it’s these kinds of challenges that I’m really passionate about and what really mattered to me. It’s amazing. Love bringing mission based individuals on the show to share, you know, why they do what they do, how they’re doing and really what we can all learn from that so that we can all make a difference there.
So great having you on. And I guess, First thing first, man, tell me about this conference. So upper bound, like, like tell me about how all that came about. Yeah. Awesome. So this is our, like you mentioned earlier, this is our third annual upper bound conference coming up. We actually host it in person in Edmonton, Alberta, in Canada from May 21st to the 24th.
And so it’s, it’s very interesting in terms of your traditional AI conference. So a lot of AI conferences, either are. Really academic focused or really industry focused. Ours is actually a blend of both. So we have some really deep AI academic sessions led by our researchers, and these are world leading researchers in AI machine learning.
But then we also have industry sessions where we can bring industry together. I’m leading. A whole track of sessions on startups. We’re leading a track on adventure and AI. And so being able to bridge the gap between academics, early career professionals, startups, industry and bring everybody together into one conference.
It’s a pretty special place. Now, I know that you mentioned this is the third annual conference. Is this, have you been to the conferences in the past? Were you with Amy back then? Or is this your first conference? Like, give me a feel for what you’re excited about. Yeah, totally. So this is, I’ve been at all of them, so we, this will be my third one as well.
Yeah. And so, the first one was actually, it wasn’t even called upper bound in the year one. It was called AI week and it was a celebration of of 25 years of AI in Alberta. And so that was what kind of kicked it off. And then last year we re rebranded it into our annual conference upper bound.
And last year we launched with a couple sessions around AI and startups and this, and they were very popular and very well attended. So this year we, we. We’ve expanded it a lot. We have, I think, close to 10 different sessions on AI and startups. We have, we added a venture track but there, there are tracks.
I think there’s over 20 different tracks of topics and sessions across the conference. So in basically anything AI and insert topic here, AI and bio, AI and health, AI and law, AI and in everything. So there’s a ton of different tracks, which will be very interesting to attend. What is, what is like the attendance?
Like, like how many people attend this conference roughly? Yeah. So yeah we’re projecting over 5, 000 attendees this year. That’s massive. Yeah. It’s a, it’s a big deal. Yeah. So around 5, 000 attendees coming to Edmonton, we host a, we’re, we’re, I think we’re projecting over a thousand talent bursaries as well.
So this is where people have been able to apply from around the world. To come to the conference and if they receive a talent bursary, then, or if they, if they’re selected for a talent bursary, then they actually get reimbursed for their flights and hotels and things like that to come to the conference as well.
So last year we had people from over 50 different countries around the world come to Edmonton for the conference on one of those talent bursaries. So I definitely think it’s, it’s Canada’s biggest AI conference and in one of the bigger AI conferences in the world, for sure. What do you think draws people to it?
Like, what do you think other than to hang out with you and you know, like, what, what do you think draws people to the conference? I mean, obviously I’m the number one draw. No, I’m just kidding. I think it’s that real mix of academic and industry focused for the conference. So at Amy, we have some of the world’s leading researchers in AI and machine learning that, that we, that are part of.
Part of our research group here in Edmonton at the University of Alberta and at some other institutions across Canada. I think being able to come and interact and hear from the world leading researchers in AI and machine learning is definitely something that people are coming and haven’t coming for and will continue to come for.
And so a lot of those attend, attendees, it’s a really good mix. Early career AI professionals, people who are doing their master’s PhD postdoctoral studies in AI machine learning from around the world, local business leaders from here in Edmonton as well as people from around the world that are interested in AI machine learning.
How many speakers, like you mentioned a bunch of breakout sessions and others. So I’m guessing there’s going to be a lot of different speakers. Like how many roughly would you say? Cause that’s a massive, a massive conference. Yeah, I, if I remember correctly, it’s over 200 speakers and over 150 sessions across the four days.
So it is jam packed. We have multiple stages multiple main stages that’ll be happening concurrently. There’ll be different break sessions happening in breakout rooms. Yeah, multiple different venues taking place. It’s we kind of take over the city for the week. It’s, it’s quite the experience.
Oh, that, that’s absolutely amazing. And, and the dates, I don’t know if I, if you said the dates, the dates May 21st to the 24th. 2024 Yeah. Hosted here in Edmonton, Alberta. That’s awesome. And we’ll put, and we’ll put more information in the, in the show notes about the conferences Yeah. As well in the, and Oh, while, while we’re at, while we’re talking about website again the website for that is upper bound, U-P-P-E-R-B-O-U-N d.ai and tickets right now.
Our 40 percent off. So there’s a, an early bird discount, 40 percent off tickets available. All right, man, I mean, when you know, you’re going, it’s been not only in terms of percentage on ticket, but the sooner you buy your plane ticket normally works out for you too. So all good. Totally. 100%. So let’s go further.
I mean you know, based off our discussion so far, I think it’s, it’s I think the audience understands that Amy’s is a big deal when it comes to AI. And in this space, especially in Canada and worldwide, you mentioned over 50, you know people are represented from over 50 countries from the in the last conference.
But that being said, let’s take maybe a step back. I don’t want to get ahead of myself here. And just tell us a little bit more about Amy overall. Yeah, so we’re a research institute, like I said, based in Edmonton, Alberta in Canada, and we’re one of three centers of excellence for AI research in Canada as part of the pan Canadian AI strategy.
So we do 2 major things. We fund fundamental research and AI machine learning, and then we work with industry to help translate that research into industry adoption. And so my team is 1 of 1 of the product teams here at Amy that specifically focuses in on supporting tech startups. As they explore, build and commercialize AI machine learning.
But we work with all types of companies from, you know, small mom and pops, SMEs, startups, national, multinational corporations governments, not for profits, any, any kind of organization you can imagine we, we can work with and support you know, Along their AI journey. Wow. That’s interesting. And so like, what are the types of of like, of companies that are, that you typically work with?
Like, give us a feel for that. Yeah. So specifically on, on my side, on the startup side, we, we work with I guess two major types of companies. The first is startups that have a product in a market that’s not using AI, but they want to see how it can be applied to their business. So we can help them look at their business, see where those opportunities are, evaluate those.
Think about how they could be solved by a I machine learning. So that’s kind of the 1st type of company. The 2nd type is companies and startups that are already a I companies. They already have machine learning deployed in their product. It’s in their customers hands on. And for those ones, we provide more of a longer term coaching program for them, where we bring in their CTOs and their technical leads provide ongoing coaching over the course of a year.
Really Really providing a lot of value to them that way. And then in between that, those are kind of like the opposite ends of the spectrum in terms of the AI adoption. We have programs across our team to help companies scope out a specific problem, build them a roadmap, source talent, and actually build out a solution for them.
And then, like I said, coach them once it’s already deployed. And so one of the things that you’re known for, and you mentioned it in our conversations is AI for good and for all, like, what does that mean for you in the mission? Yeah. So it really means that we’re really careful about. The type of work that we do, the type of companies that we work with AI and machine learning.
It’s a tool. It can be a very powerful tool. But like any tool, tools can be used for good and tools can be used for bad. And we, we really take a lot of care to making sure that the companies and the projects that we’re working on are contributing to the benefit of society. And we’re very careful to.
In our, you know, in everything from our contracting phase, selecting which kind of projects we want to work on and are able to work on all the way through to how we build out a project, how we’re taking into consideration things like bias and fairness in the systems that we’re building, how we’re keeping track over the data.
So we use data sheets for our data sets so that everybody. Whether on our team or our client after we’re done working with them really knows exactly where the data came from. What’s going on with the data? How it’s been processed. And then also kind of post being able to turn over to our clients understanding of, what was the impact of the algorithms that we’re using? We use algorithmic assessment tools, the data sheets for data sets, really giving them all the information that we can to make sure that once we’re done working with them, they’re able to maintain that positivity within the products and the services we’re building.
Yeah. And now you I don’t want to, I don’t want to assume that this is obvious because you live this day in and day out. Some of the people that watch this, they’re not living and breathing AI. It’s still kind of like a buzzword. They hear it. How does it help my business? How does it not? Why is what you just now said, like, why does that matter?
Like to be so thoughtful and so careful, like, why does that matter? I know that’s a big question, but that’s how we get in the weeds. You know, why does that matter? So I think that there, you could kind of answer that from a couple of different perspectives. Number one, there’s the, I guess, moral and ethical stance on looking at how.
Do the tools and products that we that we make here, but that anybody makes, how do they impact people? Yeah. So I think that that’s a really important thing to think about just from a moral ethical stance. There’s also companies, there’s a risk that companies face when they’re building AI. And so being able to understand the impact that they’re having and what risks come with that what benefits and what risks there’s you know, Legal and, and reasons as to why we.
Companies should be caring about it. The trust that companies have from their customers and their users, being able to, to build that and not damage that. I think depending on how you’re looking at it, it’s important from all these different perspectives to really make sure that what you’re doing specifically.
Across anything you’re doing in business, but specifically in AI that you’re taking into consideration bias, fairness, equity, these different, really important principles. And that’s why it’s such an important piece of the work that we do. That’s great. You, you know, I couldn’t let you off the line without talking about generative AI.
I mean, that’s been, that’s. In the news. That’s what we’re talking about. Every new update we get, like, this is like, this is the new what we’re talking about just overall. So generative AI, like where’s your stance on that? Like in where we’re at. Yeah, it’s, it’s really cool. I mean, it’s been The last, what is it?
Like 15, 16 months. It’s been every conversation. There’s been lots of conversations here about it. I think every company we’ve, we’ve worked with over the past year and a half is, has been chatting about it. I think it’s amazing. It’s, it’s definitely a product, you know, chat GPT is a productivity tool that I use to make myself more productive.
And in my role I think it’s something that. You know, most people should be using in, in some way. But it’s anytime there’s a new technology, it’s really easy for society, for, for people to fall into the trap of this new tool will solve all of my problems and it, it, it won’t, it is a really good tool and it’s really good at specific things.
But it’s not the be all end all, and there’s a lot of other tools and other ways of thinking that I think are. That we, we need to not fall into the trap of thinking that generative AI or chat GPT is going to solve everything. Yeah, it’s. It’s great, but we need to kind of also temper expectations with it.
So you have a much different vantage point than most specifically in working with so many startups, right? Especially on the product side and, and especially for companies that maybe haven’t used much AI or just started. about or testing the waters on how it can improve their business. And I know this is going to be different for every company size, a company industry or otherwise, but in general, let’s generalize a little bit here, what should people, what should companies be thinking as they start to kind of get into those AI waters?
Like what should, how should they be approaching that topic? Yeah. I think number one. Thinking about it early is going to be really good. So thinking about it before you want, before you need a solution built. Thinking about it early, because when it comes to a normal software development, you can build a tool and then deploy it when it comes to AI.
Oftentimes, what you need is is a ton of data to even train your system on. So even if you can build a system, if you don’t have the historical data that you need to train the system on, you have to start collecting that. So I like to tell companies to Start thinking about what you want to build and then collecting the appropriate data as early as possible and collecting the appropriate data is important.
You don’t need to be collecting everything, but collecting the things that you will actually need in the system to get you the answers that you’re looking for and to answer the questions you’re asking the system. That’s really important. Starting early, starting before you need it, and then building over time, starting with, we like to always make sure that all the projects we’re working on are providing business value to our clients.
And so we get them to think about what is the value of the system that they’re building? What is like, what is internally the value? What’s the value to their customers? What are the risks associated with it? And really helping them identify what are those low hanging fruit to start with, get some wins under your belt.
Get your team used to. Working in this space and then build up from there. It’s kind of like that. The Rome wasn’t built in a day kind of philosophy. And I think that really fits here is you’re not going to start by building the Coliseum, you’re going to start by building something small and building your way up.
Can you give an example and it doesn’t, you don’t have to drop any company names if you don’t want to, no big deal. But in general, can you give an example of maybe a company that’s kind of gone through that process, whether it’s again, from the product side, like they develop something, they had to, you know, they trained it, they, they implemented it and what their end goal was just to shed a little bit of light for those that are out there kind of still trying to wrap their head around this.
Yeah, of course. It’s. Oh, a company that we have worked with, they’re out of Calgary, which is a city just a few hours away from us is this company called Routique. And so they do a lot of logistics and supply chain work. And we did a project with them. It was a big year plus long project around the future of warehousing.
And so being able to look at how products move within a warehouse, how to make sure that before, before you move on, how fun was that for you to even get to play with that, that subject, the future of warehousing, man, that’s, that’s an interview in itself, but that must’ve been a lot of fun. Yeah, it’s they’re doing some really cool stuff.
And, and so I think that’s a really, really cool use case. They, that project had multiple different use cases on it, but one of them was, was looking at that and how products move, how to best pack trucks to make shipping more efficient. Wow different things like that. So you’re able to, you know, we started working with them a few years before they’ve been doing some more basic AI stuff over the last 20 years in terms of delivery management and route optimization.
And then we’ve been working with them quite a bit over the last couple of years to help them really level up their AI game and expand their AI team quite a bit. Which has been awesome. They’re, they’re doing some really cool things. And they’re really leveraging the tools in order to, to make their processes more efficient.
Cause I think a lot of startups in particular, you’re, when you’re able to start and your, your scope is this big. You can run on manual processes for a lot of things. And then once you start seeing that hockey stick growth and you’re looking to expand and grow, whether that is geographically to more types of products, more customers, your manual processes really start breaking down and you either need to go from, Oh, I had, I had one person who was scheduling drivers in this area when I was only doing my neighborhood or my city.
But now if I’m going all across Canada or all across you know, California or all across North America. You’re going to have, if you need one person to do your city now, you’re going to be having to hire thousands of people across the country to do that. And that’s often not feasible for a lot of startups.
And so that’s when, when they’re starting to expand and really scale their operations is when we see a lot of startups really be able to take best advantage of these types of technologies. Thank you for sharing that. That’s a great, that’s a great use case in here. And that, that even gets me thinking about this.
And it’s like, cause sometimes I feel like we keep the AI discussion like too in the sky or too futuristic. But when you kind of marry it with something like, Hey, we’re trying to figure out logistics and warehouses, right. And how to do things more efficiently, I feel like then people can wrap their head around it more and they’re like, Oh, like, this is like, you know, You know, once upon a time, the discussion was all about just in time, right?
Production and like changing all of these things are like, you know, and distribution logistics. And so it’s still, you know, that’s still a part of the discussion and a big part of all of this in terms of what we use, the use case you just gave. But I just mean like now adding the AI component, it just. It just adds, in my opinion, the potential to to make things more efficient, to make them better.
And I don’t, I don’t know what it leads to, but I think it leads to something interesting is the way I see it. Yeah. Yeah. Another really cool company based in Edmonton here. That’s really focused in on actually improving safety is a company called Sam desk. And so they use AI to, and social media often.
I think they’re the biggest platform they leverage is Twitter. And so they’re able to actually detect when critical events are taking place around the world using the power of natural language processing, machine learning and social media. And so they’re able to detect events like active shooters and you know natural disasters and things like that faster than the police are able to detect it.
So they’re, they’re able to then. Detect something that’s happening and then notify their clients. So if they’re, if they have some of their clients or whether it’s governments or like even like grocery delivery companies, like those types of services where you can have someone go and pick up your groceries for you.
If they’re able to notify those, their clients about an active shooter situation at a, at a shopping center, then that company can redirect its drivers away from that, potentially saving lives by not sending somebody to, into a dangerous area. Man, that’s so next level. Like that’s great like that.
And so for your role as, as in product and, and, and, and working on these scenarios, like one day you could be talking about like saving lives. The next day could be warehouses. The next day could be like, how fun is it to be in the intersection of that? Yeah, it’s pretty cool. We we have a lot of amazing companies in our network doing amazing things.
Like I said, at the start, solving some of the world’s biggest problems and challenges. There’s, there’s no such thing as a dull day. Here we get to work with some amazing people and amazing founders from across the country. It’s amazing Adam. Well, hey, I just want to say it’s been great having you on the show and providing new insight and angles for me personally, as I learned through and navigate.
I’m not in AI day to day. I mean, I do interviews about it very often, but But I’m not in it day to day, so I love to see, you know, smart, intelligent people like yourself and all the people are really over at Amy. I know it takes a team to do this, but really helping to advance AI overall in industry and for society and again, AI for good and for all, which is your tagline.
So thank you for coming on the show. I do want you to leave that website again for upper bound. And also if people just want to follow Amy or even follow your work, like how do people connect? Yeah. Awesome. So upper bound. ai is the website for our conference. Like I said earlier, 40 percent off tickets until the end of March, I believe.
And then to follow our work, check out what we’re doing here. Reach out to our team. You can go to amy. ca. And so it’s amii. ca. We have all of our different programs listed on there. We have an intake form. So if you’re interested in working with us and how we can support your company you can fill out the intake form and then our team will reach out to you and set up a chat.
Fantastic. And for everybody watching this we’ll put the link in the show notes, all that other good stuff. So you can go over and and check it out. And speaking of the audience, if this is your first time with mission matters we’re all about bringing out entrepreneurs, executives, and experts and having them share their mission, the reason behind their mission.
You know why they do what they do. So if you haven’t hit that subscribe button yet, that this is your invitation. Hit that subscribe button because we have many more mission based individuals coming up on the line and we don’t want you to miss a thing. Adam, again, thank you so much for coming on this show and appreciate you coming on.
Yeah. Thanks so much for having me. It was awesome chatting.