2900: Transforming Grab-and-Go: The Role of AI and IoT in Modern Retail

[00:00:00] As you know, every day I try and get every single person listening to this podcast thinking

[00:00:06] differently about how we're all surrounded by technology just about everywhere we look

[00:00:11] and in sometimes areas that we don't associate with technology too.

[00:00:16] And today I want to discuss how the fusion of IoT, AI and smart vending technology is

[00:00:24] redefining the convenience of grab and go food shopping.

[00:00:28] Because today I'm joined by Aslak De Silva, he is CEO of Cellfly Store and I invited him

[00:00:34] on here to explore the innovative ways that his company is leveraging a variety of technologies

[00:00:40] to transform the retail landscape.

[00:00:42] And also how their intelligent vending machines are not just vending products, they're predicting

[00:00:48] consumer demand, optimising operations and offering around the clock service without

[00:00:54] increasing overhead costs.

[00:00:57] So I want to learn more about that, how it's utilising real-time data and AI to boost sales

[00:01:03] significantly, manage inventory more efficiently and even influence consumer behaviour with

[00:01:09] dynamic pricing.

[00:01:12] And if we've got time, also learn more about his vision for a future where hyperlocal half-mile

[00:01:17] stores become commonplace, seamlessly serving the immediate needs of a community through

[00:01:23] automated data-driven solutions.

[00:01:26] So buckle up and hold on tight as I beam your ears all the way to Finland as we uncover

[00:01:32] the technical and business insights that are setting this company apart in the smart vending

[00:01:37] market.

[00:01:38] So a massive warm welcome to the show.

[00:01:42] Can you tell everyone listening a little about who you are and what you do?

[00:01:46] Yeah, hi Neil.

[00:01:47] Thanks for having me.

[00:01:48] My name is Aslak De Silva.

[00:01:49] I'm the CEO of Selfie Store.

[00:01:52] We drive with intelligent vending machines which are pretty cool.

[00:01:56] We'll get to talk about those more.

[00:01:57] I live in Finland.

[00:01:59] So yeah, maybe that's a short story of me.

[00:02:02] Fantastic.

[00:02:03] Sounds incredibly cool.

[00:02:05] And I'm supposed to set the scene for our conversation today.

[00:02:08] Can you start by explaining how Selfie Store's smart vending machines differ from, let's

[00:02:13] say, traditional vending machines that we've all seen in airports and gyms and everywhere

[00:02:17] we go?

[00:02:18] And also the role of technology.

[00:02:20] What key technologies are you employing to enhance this grab-and-go shopping experience?

[00:02:25] So of course, vending machines have been there for ages.

[00:02:28] I mean, the basic technology is maybe a couple of hundred years old.

[00:02:33] And so the purpose is that everybody can serve themselves and then the goods that they need

[00:02:38] are brought to them.

[00:02:40] Maybe 100, 150 years ago, we were looking at newspapers or tobacco or whatever that was.

[00:02:47] And the technology was pretty static until I think in the later years now when we have

[00:02:52] all other technological advancements.

[00:02:55] But basically, vending machines have been very much and are still very labor-oriented

[00:03:00] and labor-focused.

[00:03:02] Somebody has to carry the goods there.

[00:03:04] Somebody has to buy the goods.

[00:03:05] So basically, the only thing that happens there automatically is maybe the purchasing.

[00:03:10] And if you look at the old ones, when you had maybe coins or cash and you put in there

[00:03:14] and put a code in, and then it would drop you something.

[00:03:16] In some cases, it didn't drop unless you hit the machine, and then you got your goods out

[00:03:20] of the slot.

[00:03:22] But today when we're talking about...

[00:03:24] So of course, there are many different technologies involved.

[00:03:27] And with Selfie Store, we work with RFID, which is then radio frequency signals in

[00:03:33] the items.

[00:03:34] We put a sticker or the merchants who are operating with our machines put a sticker.

[00:03:40] And within that sticker, you can code a lot of information in it.

[00:03:43] You can put that, for instance, who put the item in, when.

[00:03:47] You can put the expire date of the product that you're going to put in.

[00:03:50] So if it's a fresh food or something.

[00:03:52] And with that, then the data is transferred to the computer or the unit inside.

[00:03:57] And then it knows exactly which items are in, who put them there.

[00:04:01] It will have telemetry for monitoring the temperature of the cabinets and all these

[00:04:06] things.

[00:04:07] And then this becomes data, of course, in the end.

[00:04:10] And then you can utilize the data for many things.

[00:04:13] But maybe what is then the intelligent part of it is then that you can actually have different

[00:04:18] kind of API connections to other sources as well, where you can use, for instance, weather

[00:04:23] data to predict what's going to be sold or then just collect the historical data and

[00:04:28] compare that, wait a minute, was there a traffic jam at that time and how did that impact

[00:04:32] the sales?

[00:04:33] And with these kind of different data pools, then you start talking about intelligent vending

[00:04:39] when you have this, you can end with the AI or with humans as well to just analyze the

[00:04:44] kind of data and make some conclusions out of it.

[00:04:46] So does that make sense?

[00:04:49] It really does.

[00:04:50] And one of the things, the first thing that put you on my radar was when I was reading

[00:04:53] online how you leveraged some of the latest developments in IoT to create this completely

[00:04:59] new way of serving customers.

[00:05:01] But not only that, of course, you also have AI at the core of Selfie Store's operations.

[00:05:07] So just to bring that to life, how do these intelligent systems using AI and how do they

[00:05:12] predict demand and what impact has it had on consumer buying behaviors?

[00:05:17] Yeah, that's a really good question and probably interesting for people to hear.

[00:05:21] So as you were mentioning, IoT is in the core.

[00:05:24] So all the data goes into the cloud and then within the cloud, then you can collect data

[00:05:30] from different Selfie Stores around there.

[00:05:32] So we have now customers in more than 20 countries in Europe and plenty of locations.

[00:05:38] So we collect all the real-time data and then the AI can work with that.

[00:05:42] A couple of examples that I could share what AI can do is then that in a normal case that

[00:05:46] if you had a vending machine, so you might be wondering that should I sell maybe Coke

[00:05:51] Zero or Pepsi Max?

[00:05:53] Those are popular items, but often you sell one of them.

[00:05:56] You don't have both, but you don't know which one to go for.

[00:06:00] But here now with the data that we have and with AI, so basically we can ask the question

[00:06:04] that what should you sell because this location is let's say it's in a hospital and the temperature

[00:06:08] is like this and that.

[00:06:09] So comparing the data from other Selfie Stores, so then it will be able to tell you actually

[00:06:15] that yeah, maybe you should go to this direction.

[00:06:18] With cool stuff with AI is that it's not saying actually that which one should you go because

[00:06:22] then what we found out is that it would say that actually you should have them both.

[00:06:26] And if you have them both, so based on the data that we had from history, so it would

[00:06:30] actually increase the sales of other products inside the cabinet by 43%.

[00:06:35] So then you know that, okay, I shouldn't ask that which one should I have?

[00:06:39] I should have them both and then actually increase the sales of other items in the

[00:06:42] cabinet.

[00:06:43] So this way is a kind of a clear example of what you can work with AI and data and pick

[00:06:49] up these things.

[00:06:50] It can be anything of what kind of bundle deals we should have, what kind of discounts

[00:06:55] work well or what kind of maybe a women's day is coming up.

[00:07:00] So how should the assortment change for that specific day?

[00:07:04] So anything like that.

[00:07:05] So then AI is a very useful tool for us to find out from a big bunch of data, a data

[00:07:09] pool there and have these predictions that, okay, what should you do to sell more?

[00:07:14] And one of the things I try and do on this podcast every day is getting people thinking

[00:07:18] differently about technology and how it impacts places that they don't automatically associate

[00:07:23] with technology.

[00:07:24] And I would say a vending machine, for example, is a perfect example of that.

[00:07:29] And another thing that stands out is that ability of your technology to provide real

[00:07:33] time data on sales.

[00:07:35] So important now, but also inventory and customer behaviors, et cetera.

[00:07:40] So again, to bring that to life, are you able to share how that level of insight is

[00:07:44] improving or maybe even transforming the way that merchants manage their operations?

[00:07:50] Yeah, I think the funny thing which always with this great technology and tools is that

[00:07:55] you still need somebody to say that, yeah, I will follow the opinions of the AI as an

[00:07:59] example.

[00:08:01] Even if you predict what's going to be sold, so then somebody has to do for that goal for

[00:08:05] it.

[00:08:06] Year on year when we look at the sales differences, on average, selfish stores out there sell

[00:08:10] now more than 30% more than a year ago.

[00:08:14] So I think that's a kind of a proof case of the changes there.

[00:08:18] But not all work with the kind of things and many of our customers, which is fine.

[00:08:22] Of course they can make their own decisions.

[00:08:24] So they sell whatever they want.

[00:08:26] But what we've been seeing here is that I'm maybe using an example from marketing and

[00:08:30] kind of this A-B testing and multivariate testing.

[00:08:34] So these can be speed up quite quickly.

[00:08:36] And I think one of the biggest questions is that how do you use dynamic pricing?

[00:08:40] So I think these kind of dynamic pricing examples from travel industry or even e-commerce, so

[00:08:45] here you can make a big buck in a quick time.

[00:08:48] So for instance, if the weather gets super hot, I'm sure the UK as well, some days it

[00:08:53] does get that in London at least.

[00:08:56] And then you see the demand of beverages going up.

[00:08:59] So we humans are quite slow to react to that.

[00:09:01] But then you can automate lots of things in this, that let's say that the beverage is

[00:09:05] unusual, the sales is peaking up.

[00:09:07] Normally you sell two per hour, now you're selling five per an hour.

[00:09:10] So you should change the price and then you can automate these things with AI quite quickly

[00:09:14] to kind of work better.

[00:09:16] And in that moment, you make a lot more money than you would normally do.

[00:09:21] And then actually customers are also happier because when you are in need, so you're happy

[00:09:25] to pay more as long as you get the product that you want, which is then a funny thing

[00:09:29] to think.

[00:09:30] But I think it's more like that you are happy to pay if you get something and the most disappointing

[00:09:34] for a consumer is that there's no inventory.

[00:09:37] And at the same time, then our machine would send that, hey, the sales of these beverages

[00:09:41] are going high.

[00:09:42] So there's kind of push notification for the merchant that, hey, you should stock up quickly.

[00:09:46] It seems that now you're doing well.

[00:09:48] And then with our system is quite easy that, okay, let's say that you had said there are

[00:09:51] some sandwiches that are not going to sell you at the same time while you refill with

[00:09:56] new beverages, you just take out the sandwiches and that is done in mere seconds, maybe 30

[00:10:01] seconds, you're done your refill and taking out some items.

[00:10:04] And then you're good to go to sell with new consumers and make more money.

[00:10:07] So I think those kinds of individual moments and being able to be more proactive in those

[00:10:12] are the best cases to make more money.

[00:10:14] And it can be anything that in a normal day, you make a hundred euros, but on that day,

[00:10:19] you make 500 euros, a thousand euros.

[00:10:21] We do see this at events as an example that a lot more money is made on those events

[00:10:27] when you can predict what's going to be sold in the next hour or so.

[00:10:32] And obviously you're based in Finland, I'm based here in the UK.

[00:10:35] We'll have people listening in 165 countries or something like that, I think.

[00:10:40] Which markets do you serve?

[00:10:41] I think I read online something like 20 plus countries, is that right?

[00:10:45] Yeah, at the moment we are in Europe.

[00:10:47] So anything from Finland to Spain, even to actually Malta and Canary Islands.

[00:10:52] But of course we are working towards other markets.

[00:10:55] So we are now entering the US market and the North American and testing out.

[00:11:00] I know that the competition is hard, but we'll see how we do there.

[00:11:04] Why aren't we serving other markets yet is based on the certification processes.

[00:11:07] So when we work with RFID, so when they're radio signals as an example, so different

[00:11:13] regions in the world have different frequencies allowed and so on.

[00:11:17] Plus then of course components are different for when we talk about even freezer

[00:11:22] and frozen temperature and products that we are manufacturing and operating with.

[00:11:27] So then you need some local specifications that actually is pretty dreadful to kind of

[00:11:32] comply with.

[00:11:33] So that's why we've been focusing in Europe for the time being.

[00:11:36] But of course, in the future, also working with other locations and areas in Europe.

[00:11:41] Fantastic.

[00:11:42] And we do have a lot of people listening in the US, so it'd be great to hear if anyone

[00:11:46] gets in touch with you about that.

[00:11:47] And back to the retailers themselves, I think extending service hours, no matter where

[00:11:53] people are located in the world, it's crucial for so many businesses.

[00:11:56] So how do your solutions enable merchants to offer that round the clock service without

[00:12:02] increasing overhead costs?

[00:12:04] Anything you can share around how you do that too?

[00:12:06] Basically what we try to do is that the vending machines or the cabinets are as easy to use

[00:12:13] as your home fridge would be.

[00:12:14] Of course, here you need to open it with your credit card or Apple Pay or something.

[00:12:19] So they look nice and are easy to use and you open the door and then you can hold the

[00:12:24] items in your hand, pick how many you want, and then when you close the door, so then

[00:12:28] the purchasing is done.

[00:12:29] So quick and easy to use.

[00:12:31] Here if somebody wants to operate with 24 sevens, you can do that.

[00:12:36] You can just leave the cabinet there, it will do its business.

[00:12:39] If something has run out, so of course then it's not available, but the other items are

[00:12:42] there.

[00:12:43] And in cases that if you want these push notifications to show that, okay, some items

[00:12:47] are going to run low or are finished, so then you get that information.

[00:12:51] But there I think the most advantage comes from the predictive planning of refills and

[00:12:57] what products are going to be sold.

[00:12:58] It can be anything related to, like I said, to the temperature or the day.

[00:13:04] So the data will kind of tell you a bit like, okay, in an office as an example, that Friday

[00:13:10] afternoon is the peak day, peak hours.

[00:13:12] But Saturday, Sunday, there's not so many traffic there or not so many people there

[00:13:17] around.

[00:13:17] So of course, and that day doesn't make sense to refill it, or unless you want to refill

[00:13:22] it so that it's full on Monday.

[00:13:23] And so we have hotels working a lot with data that when people come in, are they more like

[00:13:29] families or business travelers?

[00:13:31] And then you change the assortment based on that.

[00:13:33] And then you can again predict the sales a bit and how much of each item should you have

[00:13:38] there to be able to serve the consumers when they come.

[00:13:40] And then of course, the best is the quickness of the turnaround of your stock so that you

[00:13:46] can then refill, but so that it's never empty, but never keep like expiring products inside.

[00:13:51] So I think it comes to that all in all that you've just kind of work with the data, with

[00:13:56] the predictive sales of the upcoming items and so on, and then you're covered with that.

[00:14:03] And as someone right in the heart of this space, how do you see intelligent vending

[00:14:07] machines and other similar technologies?

[00:14:09] How do you see all this combining and influencing maybe traditional retail models?

[00:14:14] Are you noticing any changes here?

[00:14:17] Yeah, I don't know if it's more of my dream and reality, but I do see this like a lot

[00:14:22] of time we talk about last mile delivery being the most expensive one.

[00:14:26] I do see this kind of more half mile stores coming with intelligent vending, where again,

[00:14:34] what is sold where is more depending on the data that's collected from that source.

[00:14:38] And then the assortment is based on the needs by the consumers nearby.

[00:14:43] And that will change the game.

[00:14:44] That can mean anything from holiday resorts that are very remote, that you will have services

[00:14:50] in those places where you don't normally have.

[00:14:52] It could be next to a hiking route or on top of the mountain, or just when you come late

[00:14:58] to the hotel where nobody's there, so you are served.

[00:15:01] But it also could mean that basically restaurants that are very popular have more of these kind

[00:15:06] of pop up shops for you to go and serve yourself, which are then not exactly where the restaurant

[00:15:12] is, but maybe two miles away from them.

[00:15:14] But then for the consumer, it makes sense because then ordering in might make sense,

[00:15:18] but then the restaurant is losing a lot of money and it takes time and you're waiting,

[00:15:22] whereas you can then serve yourself maybe halfway to the restaurant and these things.

[00:15:27] So I do see these things happening, especially if you think of the development of robotics

[00:15:32] for the refilling.

[00:15:34] So I think that's going to kind of change the game a lot, because then you don't need

[00:15:38] to have these kind of big warehouses or big marketplaces, which is logistically smart

[00:15:43] when the logistical costs go low, but with robotics development.

[00:15:48] So I should see these kind of half mile stores, which are closer to the consumers, but with

[00:15:53] maybe automated refills or automated transportation then where the cost of the transportation is

[00:15:59] not that relevant anymore.

[00:16:02] So that will change the game.

[00:16:03] When will that happen?

[00:16:04] I don't know.

[00:16:05] Do you see the same or how does that sound to you?

[00:16:07] Richard Pinchott Yeah, no, it's very similar.

[00:16:10] And one of the things that I think might hold people back, I suppose, is some of the perceived

[00:16:16] challenges.

[00:16:17] I'm curious from your side, right in the eye of the storm again, what kind of challenges

[00:16:22] have you faced when integrating complex technologies like IoT, like AI into consumer facing products?

[00:16:30] Because I think in traditional sectors, there's a certain amount of nervousness or maybe even

[00:16:36] anxious about integrating technologies like this and just putting it out there and letting

[00:16:40] it run itself.

[00:16:42] Are you seeing that too or not?

[00:16:44] Or what kind of challenges have you come across?

[00:16:46] Yeah, I think our approach for consumers is to keep it as simple as possible.

[00:16:52] So that's what I'm talking about this kind of as easy to use as your home fridge would

[00:16:56] be.

[00:16:56] It's just kind of figure it out how to open it and you pull the door open, pick the items

[00:17:01] and close it.

[00:17:02] Then that's it for the consumer.

[00:17:04] It's more related then to the payment methods that can you use your Apple Pay or do you

[00:17:09] have an app or how to pay?

[00:17:11] So as long as it's simple for the consumer, everything works well.

[00:17:14] But then of course, inside the hood, then you have all this tech and then the cloud

[00:17:19] based systems and AI.

[00:17:20] So I think that might be then frightening for many and then for the operators and the merchants

[00:17:25] there.

[00:17:25] So how to use that and are they comfortable with that?

[00:17:28] Do they trust even that kind of predictive refill plan that we should do this?

[00:17:33] So I think that's a bigger challenge for us.

[00:17:35] And we do see lots of things there.

[00:17:37] But we do see lots of companies like really happy about it because they can then use their

[00:17:42] existing ERP systems, inventory management and everything is automated based on that.

[00:17:46] So they can even do their own API connections and work with whatever they want.

[00:17:52] So they are super happy about it.

[00:17:54] I think traditionally vending machines haven't been a lucrative opportunity for grocery stores

[00:18:00] or even restaurants because it's just a small scale operations.

[00:18:03] You fit a couple of hundred items per time there.

[00:18:05] So it's maybe not worth the time that you waste on operating them.

[00:18:11] But now it's changing a bit more.

[00:18:12] So I do see a bright future there for sure.

[00:18:14] And there was a quote about five or 10 years ago, right?

[00:18:18] It was the IBM leader.

[00:18:19] And she said that the last best experience that any consumer has anywhere becomes the

[00:18:24] standard expectation of what they expect to see everywhere.

[00:18:28] So there's also, I think, an element of business leaders cannot afford to ignore these advances

[00:18:35] in technology as those expectations rise, as technology increases, ignoring it means

[00:18:39] they could get left behind.

[00:18:41] So how should business leaders maybe better prepare their companies to harness the benefits

[00:18:46] of things like AI, like IoT and ultimately ensure that they stay ahead in this rapidly

[00:18:52] evolving technological landscape and don't get left behind?

[00:18:56] Yeah, really good question, Neil.

[00:18:58] I wish I had answered it well.

[00:19:00] Let's see.

[00:19:01] I was surprised when I'm not tech savvy myself, but I'm really into learning about those

[00:19:06] things.

[00:19:06] For instance, with AI and data, I was surprised that you actually need to sort the data in

[00:19:12] a proper way and first think, okay, what do you want to get out of it?

[00:19:17] For instance, what we noticed in the beginning was that it's not about the size of the bottle

[00:19:22] or can that you're selling, if it's Coke or something.

[00:19:25] You need to have different categories for them to understand.

[00:19:28] So we were asking questions that what kind of bundle deals people buy?

[00:19:32] And then if you just have the exact items that let's say you have a tuna salad and a

[00:19:38] tuna sandwich, and then you have a Coke Zero and maybe the standard Coke and so on.

[00:19:44] So you will have so many different bundle deals that it makes no sense.

[00:19:47] You just see that you have many bundle deals, but there were 100 different versions of it.

[00:19:52] So then you needed to categorize that, okay, maybe these are beverages, these are meal

[00:19:56] items.

[00:19:57] Maybe you're interested in sandwiches versus salads.

[00:20:00] And there the data starts to like, okay, the AI helps a lot after that.

[00:20:04] Or you can work quickly with data to understand that, okay, which are the beverages?

[00:20:08] And then with the proper categories, then you ask new questions.

[00:20:12] So you start building the kind of the item level categories for each items.

[00:20:17] And after that, you'll start seeing benefits.

[00:20:20] Another example that I was asking was that, okay, let's say, are sugar-free products healthy?

[00:20:25] And are people actually buying only sugar-free products when they buy something?

[00:20:30] Or is it more that they buy, again, like Pepsi Max, but they might buy a Snicker bar,

[00:20:35] which is then with sugar?

[00:20:36] So these kinds of things when you start asking, so then you need to build the data with those

[00:20:42] questions and be able to find the answers.

[00:20:44] And when you have those, after that, the AI benefits start to kind of build up.

[00:20:49] And then, of course, in order to be able to use the data, so you need this IoT systems,

[00:20:54] real-time data, you need maybe studying your cloud services that you're working with that

[00:20:59] do they actually have the capabilities already?

[00:21:02] If they do, and they have some algorithms for you, you're speeding up your process a lot.

[00:21:07] So I mean, that first for me, it was almost looking at the dictionary of what these concepts

[00:21:11] mean.

[00:21:12] And then figuring out, okay, what's the first step?

[00:21:14] What's the second step?

[00:21:15] What would benefit?

[00:21:16] What would change my mind if I found the information?

[00:21:20] And then the other part is looking at what would make my life easy?

[00:21:24] So when we started with the IoT, so telemetry of the cabinets that you don't need to literally

[00:21:29] go and see what's wrong.

[00:21:30] But you can again find out from the data that, okay, maybe the cooling unit has broken down

[00:21:35] because the temperature is now very high.

[00:21:37] So then you know when you go there to visit physically that bring up tools to fix the

[00:21:42] cooling unit or a replacement cooling unit, so on.

[00:21:45] So I think it starts from these kind of questions that what would save my time?

[00:21:49] What would benefit me?

[00:21:50] What would I want to know to change my mind?

[00:21:53] And with those approaches, then you have plenty of different technical opportunities to kind

[00:21:58] of move forward.

[00:21:59] And of course, AI being one that I think everybody should study a lot to understand what it can

[00:22:04] do because it can really change your game in many ways.

[00:22:08] And you've been on an inspiring journey and seen so many big changes in your industry.

[00:22:13] So if you were to look over your shoulder now at your career, reflecting on your past

[00:22:17] leadership roles compared to your current position, how would you say your vision of

[00:22:23] unmanned retail and smart technologies has evolved over the years?

[00:22:26] Because we've seen so many huge technological changes over the last 12 to 18 months.

[00:22:31] But what have you seen?

[00:22:33] Well, yeah, I think for me why I even wanted to go for this business was that I'm so frustrated

[00:22:39] in queuing.

[00:22:41] So I just hated that basically all the information all the time is there that I would want to

[00:22:46] go to the grocery store when there's nobody else or going to the airport as quickly as

[00:22:50] possible with no queuing and everything.

[00:22:53] So to me, that was the trick tricker to kind of go into this industry and learn how you

[00:22:58] could actually tackle the queues.

[00:23:00] So I think that's one.

[00:23:01] But I think what we are seeing is a lot about this kind of self-service development in general.

[00:23:06] And I mean, it's not only about like the traditional vending machines were more like if you're

[00:23:10] traveling in a train station, you pick up something to drink and that's it or it's just

[00:23:15] conveniently sometimes there, but you're not paying attention.

[00:23:17] But I do see now, of course, being in the industry that I see a lot more of these kind

[00:23:22] of cool solutions where anything is possible and the waiting time is very limited.

[00:23:28] Like these home deliveries in a way are also they have the waiting time similarly.

[00:23:33] So I do see these trends that we don't like to queue, we don't like to wait.

[00:23:37] So that's changing a lot and has changed a lot in the last 18 months in my mind at least.

[00:23:43] And on behalf of everyone listening, I'd be inspired by your journey.

[00:23:47] I think for a lot of people, there is a real pressure on us all to be in a state of almost

[00:23:52] continuous learning.

[00:23:54] So a question I'd love to ask to finish our conversation today is where or how do you

[00:23:58] self-educate?

[00:23:59] Any tips you can share on that?

[00:24:01] Yeah, I'm very diligent on that.

[00:24:04] I every morning when I wake up, so actually do some yoga and learn something.

[00:24:10] So I do listen to a lot of audio books and podcasts like this.

[00:24:14] I mean, these are great sources to kind of...

[00:24:17] I try to listen to one podcast episode per day, mainly tech and leadership, sometimes

[00:24:21] sales and marketing as well, but just to keep there and hear what other business leaders

[00:24:26] are talking about, what they're working with.

[00:24:28] So I think that's super important.

[00:24:30] So to me, I think if you look at 10 years back, so it was more on the news that what

[00:24:35] has happened in the world, whereas now I'm very focused on understanding what's happening

[00:24:41] in the business, not from the business side, but maybe even from the technological developments

[00:24:46] and new ideas.

[00:24:48] So every day I listen to one or even more podcast episodes to learn what's happening

[00:24:54] there from different business leaders.

[00:24:55] So that's how I keep myself as educated as I can.

[00:24:59] Well, you're such an inspiring guy.

[00:25:01] And I would imagine there'd be a lot of people listening wanting to find out more information

[00:25:05] about your work and maybe connect with you or ask your team a question.

[00:25:09] But anyone listening just wanting to find out more about you and your technology and

[00:25:12] your work, what's the best starting point for everything?

[00:25:15] Yeah, of course, if you want just to know about what we do, so our website,

[00:25:19] www.selfiestore.com is there.

[00:25:22] We are active on LinkedIn myself as well.

[00:25:25] I think I'm the only Aslak De Silva in the world.

[00:25:27] So if you find me there, it's me.

[00:25:30] I'm happy to connect with everybody and continue learning together.

[00:25:34] What's the world going to be in the future?

[00:25:36] So yeah, please find us on LinkedIn.

[00:25:38] Even Twitter works well as well or X nowadays.

[00:25:42] Well, not only are you the only Aslak De Silva in the world, I would also say you're one

[00:25:46] of the very, very few that are using IoT, machine learning and AI to offer smart vending

[00:25:52] machines that make grab and go food shopping as easy as using your home fridge.

[00:25:58] A huge achievement to pull that off.

[00:26:00] It's been absolutely fascinating hearing more about your story and how this technology

[00:26:04] has evolved.

[00:26:05] But thank you so much for sharing your story today.

[00:26:08] Thanks, Steve.

[00:26:09] It was fun to be here.

[00:26:09] Thank you so much.

[00:26:11] So as we conclude our conversation today, I think it's evident that the integration

[00:26:16] of AI and IoT and machine learning and smart vending technology, it's not just transforming

[00:26:23] how their customers shop, but also how businesses operate.

[00:26:27] We're starting to see examples now of the strategic use of real time data and predictive

[00:26:32] analytics and how that is almost paving the way for a new era of convenience and efficiency

[00:26:39] in retail.

[00:26:41] But hey, this world is not for everyone.

[00:26:42] What do you think about the rise of intelligent vending machines and their impact on your

[00:26:47] daily shopping experience?

[00:26:49] Could this technology be key to a smarter, more responsive retail environment?

[00:26:54] So this is where I invite you to share your thoughts and questions with us today.

[00:26:58] So please email me techblogwriteratwork.com, Twitter, LinkedIn, Instagram, just at Neil

[00:27:03] C. Hughes.

[00:27:04] Let me know how you see smart vending technology evolving in your community, whether that's

[00:27:09] a good thing or a bad thing.

[00:27:11] If you want to come on here and talk with me about that, we can do that too.

[00:27:15] But that's it for today.

[00:27:16] So thank you for listening as always, and hopefully you'll join me again tomorrow.

[00:27:20] But until next time, don't be a stranger.