Nathan M. Stubina: All right. Well, first of all, i'd like to welcome everyone to our Webinar here on the future of productivity. So we have a couple of guests. We have James and Glenn, Glenn and Kristen are here with me in our Nicaroo in Toronto

Nathan M. Stubina: and James. He's a senior solution architect at Amazon Web Services based in Ottawa.

Nathan M. Stubina: He's passionate about helping Canada's Federal Government use aws to deliver services to Canadians, and he's a certified Amazon Culture innovator, Speaker: I want to hear about that, and how you get certified, and we have Glenn, Glenn and Engineer and the global head of mining and minerals at Amazon Web services. Glenn comes from Sydney. Australians worked in mining for us three decades.

Nathan M. Stubina: They always tell me. Never say that. Just say two decades, because then you sound like you've got experience Three, you sound old, but

Nathan M. Stubina: Australia, Indonesia, Chile, Canada, and the Us. And he now resides in Denver, Colorado. He's focused on adoption of cloud computing a particular emphasis on industrial data, learning and enterprise system integration his expertise fans from working at several global mining companies like Php, Ab. And Caterpillar, and he's excited about how biggest drive, change and transformation in the mining and mining and minerals industry.

Nathan M. Stubina: So, as usual, uh, we invite the the participants and the people in the audience to chat amongst themselves. Uh, we'll have a few presentations. I'll ask questions and yawn. Who works with me at shares that cheryl hard set on tasks. Help me with these webinars if they see uh something interesting developing in the chat room. I'll either break in or or ask one of the speakers to to answer some questions, and sometimes we'll ask someone in the audience to ask the question directly, so,

James Kierstead (AWS): but that will kick it off and pass it over, so we'll have two people. We'll have James and Glen and James will be going first.

James Kierstead (AWS): Okay, we can see my slides.

Cheryl Hart: Yes, we can.

James Kierstead (AWS): Great. So ah, thank you. Everyone for having me here today. So by my name is James Kirsten. I'm. A solutions architect based here in Ottawa, Canada. So I've been with the ews for about four and a half, years, and in that time I've been working with the Federal Government,

James Kierstead (AWS): helping them adopt Cloud so they could drive innovation in new ways to serve Canadians.

James Kierstead (AWS): So I would preface this by explaining that at Amazon we know that there's many ways to innovate. We Don't claim that ours is the best or the only approach to innovation, or that it's perfect. So i'm always interested to hear what you know. Others are thinking and doing in the space.

James Kierstead (AWS): But we're happy to share the details about what we've adopted, and the lessons that we've learned over the years.

James Kierstead (AWS): There are many viable ways or approaches that you can take to Orient your business. You can focus on your competitors or invent new technologies or innovate around new business around business models. There's many approaches but what we've chosen to center. Our Our approach on is around obsessive customer focus.

James Kierstead (AWS): Ah, so we do hold ourselves accountable for for demonstrating a customer-centered approach, and everything we do, and one of the ways that we've done that is, through our our leadership principles. So we do have a total of sixteen leadership principles. But I'll only be touching on one or two of those those today.

James Kierstead (AWS): We also have a lot of mechanisms at Amazon. So these allow us to, you know, scale and help our leaders operate and innovate beyond their their direct line of site. And one of those hallmark mechanisms that we have that we see here is to drive this customer center of innovative thinking and execution is the looking backwards process.

James Kierstead (AWS): The outputs of this process is what we call the Pr Faq. Or the press release frequently asked questions

James Kierstead (AWS): starting from the left, like the press, release

James Kierstead (AWS): it's a one-page document. It's a narrative that describes the new product or or service, using customer-centric language. So with the press release. What we're trying to do is we're trying to leap into the future and imagine how a customer might feel about What about that product or service?

James Kierstead (AWS): What they may say about that idea? We undertake this exercise before we even start development or writing software?

James Kierstead (AWS): Um. But limiting the press released just to the one page. What that allows us to do is to make sure that the ah, the thinking is Chris, and that we, you know we described a launch of this new product.

James Kierstead (AWS): Um! In that press release. We, you know we communicate who the customer is, what the problem the customer is facing, describe the solution with the description of the most important customer benefit for benefits.

James Kierstead (AWS): We also include, like a fictional quote from that customer that records the reaction to the, to the new service or product, and this, you know, helps us put ourselves in the mind of the customer,

James Kierstead (AWS): and think about how they would describe the benefits and value around the launch of the new product or service. The second part of the of the Prf. Iq. Is the frequently asked questions. So there's two forms. There's the internal Faq. And the external Faq. The Internal Faq. Is really those questions around. You know how how we're going to price it

James Kierstead (AWS): in. What's the market that we're we're targeting? Where is the public? Faq. It' be more from the customer point of view. How what you know what's the price, and what happens if something goes wrong with it.

James Kierstead (AWS): So there's three parts to the Faq that help us refine this idea and the customer problem that solves.

James Kierstead (AWS): Ah, one of our leadership principles is a bias for action. So bias for action is Ah, you know, speed matters in business. How many of the decisions and actions that we take are are ah reversible. Ah! So they don't necessarily require. Ah! Extensive study. Ah! One of the things that we value is calculated risk taking.

James Kierstead (AWS): So when you you think about that like, how do we decide when it's appropriate to move quickly? The clue is in the description. Ah, it's whether it's reversible. So one helpful mechanism that we've developed is one way versus two way doors.

James Kierstead (AWS): One way. Doors have a significant and irrevocable consequences, and they require very deep Ah! Analysis before we undertake them. So an example would be, you know, deciding to build a fulfillment center or opening a building, a brand new Aws data center,

James Kierstead (AWS): something very capital in kind of like that. We die very deep before we make that decision. But there's other type of other types of decisions, and and these are the majority decisions where they have, they have very limited or reversible consequences. So an example might be trying some kind of tweak on on the web, on a, on a, on a website

James Kierstead (AWS): very easy to to back out of that and change direction. If that doesn't work out for us.

James Kierstead (AWS): So we see that the two-way door. Ah, you know we have enough evidence and reason to believe that going through it would be a good idea. We just just walk through it either way. We've learned valuable lessons from the exercise we teach our leaders that they should,

James Kierstead (AWS): you know, make decisions when they have seventy percent of the information. If you wait for you to do analysis, paralysis and wait until you have ninety percent of the information. You're just moving way too slow in the market.

James Kierstead (AWS): Ah, we also have this distinctly, you know Amazonian Amazonian, a way of organizing people to optimize the execution, and that is what we call our two pizza team,

James Kierstead (AWS): meaning that no team, no teams, should be big enough. They require more than two pizzas to defeat them. Smaller teams help us minimize the need for matrix communication or unnecessary meetings and bureaucracy, and it really helps us to accelerate the decision making.

James Kierstead (AWS): This concept is fundamentally around creating a little startup of of around five or ten people and providing them the right conditions and resources, so that each team has ownership and autonomy. Um, you know, to have a deep single threaded focus in one area.

James Kierstead (AWS): These decentralized and autonomous teams are empowered to develop and launch based on what they learn from their direct interactions with customers.

James Kierstead (AWS): Ah, but you also need to provide these teams with the right conditions and resources, so that each team has that ownership and autonomy and a deep, single-traded focus in one area. So a new pizza team also has the right resources embedded in them,

James Kierstead (AWS): and that would mean like that. They would have the engineering, the testing, the product management. All that would be, you know, encapsulated in that team.

James Kierstead (AWS): Ah, they have a very tight charter and a well-defined mission, and they are also on the right Kpis for their business. The result of these decentralized, autonomous teams. Are, and how they are empowered to develop and watch, based on what they learn from the interactions with the customers that are using their service.

James Kierstead (AWS): So two piece of teams. Is it really about the size? It is much about pushing the ownership and autonomy out to the out to the edge, and as demand for the product and service crows rather than expanding that team

James Kierstead (AWS): to more members. What we do is we split those teams into separate two pizza teams working on single-threated sub areas.

James Kierstead (AWS): Ah, what this two pizza team model doesn't do for the for you, though is guaranteed success. Ah, but you are our attitude is that you can't have innovation without failure. There's really two. There's two. They're really two sides of the same coin.

James Kierstead (AWS): If you're always going to succeed with experiments, then they're not really experiments, and you're not really learning anything from, you know, by taking those chances, and Amazon has a share of failures. We had the failure of our auction market. Not once, but twice.

James Kierstead (AWS): We launched Amazon uh auctions in one thousand nine hundred and ninety-nine it didn't pan out, and later we launched z shots, which for a small T uh Amazon, would let anybody set up a virtual store on Amazon to sell their products.

James Kierstead (AWS): But that idea that idea didn't pan out, either

James Kierstead (AWS): what we kept at it we made stubborn on the vision flexible flexible on the details. We believed in the long-term value that the idea would attract Ah! With customers and sellers. Ah, but we were remained flexible on the implementation, and we iterated, based on what we learned to the exercise.

James Kierstead (AWS): Now, Amazon Ah! Marketplace is a significant part of the retail business. A lot With the last year over half the the paid units were being sold to third party marketplace sellers,

James Kierstead (AWS): and we we also had the fulfillment by Amazon program that allows sellers to store their product and and warehouses to make those products eligible for for pride, shipping,

James Kierstead (AWS): And of course we had the very public. Ah, failure of the firephone. Ah! We later end up doing one hundred and seventy million dollars. Ah, right down a month old Inventory. What we learned is that building hardware is ah is hard, and yet many of the things that we have learned about building hardware and working with suppliers.

James Kierstead (AWS): Ah, help us today in our in our devices business. Some of the people that had worked on the fire. Ah! All went on to work on early versions of the Echo and Alexa. So the the the the message is, you really need to have that culture. If you work on something that fails you, should it shouldn't be punished for that failure

or for St. Of the Company?

James Kierstead (AWS): And is there any questions.

Nathan M. Stubina: So I saw Jim put a link to the the pizza Roland, in the chat room. So people want to look that up. That's great sheryl. I say you need two of those on your own. Does that mean you don't need to have team members?

Cheryl Hart: I've seen you eat two of those pizzas in one sitting. Exactly.

Cheryl Hart: Yeah, that's what I was asking what the size of the slices for a team ever, you know. So it's actually a quite funny group. We've got going on here. Everyone's saying what's the size of the pizza?

Cheryl Hart: I she is a

Cheryl Hart: I was just gonna ask. I think I think a lot of people are saying, Yeah, you know, fear of failure happens. But you know, if you have an example or something

Cheryl Hart: process that, like some, you know, there's a fair bit of money you put into some of these processes. How do you reassure that people are safe in their jobs to keep advancing and and having some failures.

James Kierstead (AWS): Well, I think a lot of it has to do with the culture that you Ah, you create, and you know we, I think we've done a pretty good. Ah, we've done very well in making sure that people feel that

James Kierstead (AWS): you're able to innovate and try new things. We have various mechanisms in place, so that if you do have an idea, you can go off and create a narrative at the Pra. That I talked about,

James Kierstead (AWS): and use that to advocate for your idea and try to build support for um, you know, experimenting with it. Um! But there's There's a recognition that Ah, if you are risk averse, and you don't try new things. Then you're going to miss those opportunities

James Kierstead (AWS): to bring new innovative ah products to the market. Nobody ever asked, you know for a Puck that you could talk to that. You could put on your your countertop. Someone had to go off and and imagine that, and then create the the Prfa queue. And then, really, you know, advocate for that.

James Kierstead (AWS): But those leadership principles that I talked about earlier are setting the right. Ah, you know tone and and expectation on. You know, every way that's that's working in. The organization is a big part and making people feel that they're they're safe that they can experiment, you know, without fear of, you know, consequences of as something doesn't work out.

Nathan M. Stubina: I see a shish. If if you want, just put put your question in the chat, and then we can break it afterwards. I see some other good questions. I was wondering on the timing on the firephone. I hope it wasn't at that time when all the plain phones were kept exploding, because that would be a terrible marketing name.

Nathan M. Stubina: Um Glenn, are you about ready, we can pass it over to you and then break in with some other, some other questions. Unless, Cheryl, unless you see something trending in the chatter.

Cheryl Hart: Well, it's just gonna say, actually neat that you're You're surrounded by a nice glass walls. One of the things that sure it's done is put an innovation room. So it's It's really cool like being able to balance that information off walls, and and you know, almost almost feel protected right. But uh done a a great job on that.

Cheryl Hart: Yeah, we called it the Incubator Room. So we that's where the all the brilliant ideas get the incubator.

Cheryl Hart: Maybe one day we'll have a session just on that. What do you think?

Jan Smit: And all of an incubator room is filtered chickens?

Cheryl Hart: Well, I know Andy Reynolds is chopping at the bit on this, So do we want to like Andy a now or later,

Cheryl Hart: and if you, if you have a Andy, if you have some questions

Andy Reynolds: well, I I guess I one that I've put in the chat. There is. Um! How do you stop the wheel from being reinvented, you know, if you have all of this uh distributed autonomy to teams to solve problems that they see. Um, How do you stop it from looking like a peanuts football game, where all of the teams go to the same place and try and solve the same problem.

James Kierstead (AWS): So that's actually a great question. And you know there is a risk of that, because with those autonomous teams there could be some overlap.

James Kierstead (AWS): But the attitude is that sometimes that overlap is desirable, as you're testing and trying out different ideas in the marketplace. No over time, you know. You'll you'll realize what works it doesn't work and those single threaded leaders They do roll up in the organization. So at some point,

James Kierstead (AWS): you know, you do have the opportunity to double down on on on one or another.

Andy Reynolds: Yeah, I guess the the follow-up question is, well, how do you share the learnings about? How do you? How do you make the

Andy Reynolds: the conclusions available? So that others don't have to go and learn them again.

James Kierstead (AWS): Yeah, just thinking through that. Like most of the you know, there's different knowledge management platforms that we use that we we we we capture a lot of that. That That information in that's available to the to the employees.

Nathan M. Stubina: So thanks, Sandy James. We'll stop sharing your screen and we'll switch over to Glen's. He has some videos to show us as well.

Glenn Kerkhoff: Okay, Thanks, Nathan.

Cheryl Hart: There you want to queue it up. Video: it's really cool one.

Cheryl Hart: I'm excited for this one. I've seen it, and I love it.

Glenn Kerkhoff: Oh, there we go!

Nathan M. Stubina: There we go. Yeah,

Glenn Kerkhoff: okay.

Jan Smit: So you sure should all be seeing a screen that says, Aws innovation in action. Correct: Yeah. Great. All right.

Glenn Kerkhoff: Okay. So yeah, thanks, Nathan, and thanks everyone for taking the time to um to join us here today, and thanks for the opportunity to come and talk with the bits and bytes. Group. Um! Just a little bit about myself and about aws and what we're doing in the industry groups.

Glenn Kerkhoff: And Nathan went through a little bit of my bio earlier in this session. But yeah, basically I've I've been in the mining and mining industry for pretty much my whole life. I'm. A mining engineer, and originally from Australia. I now live in in Denver, in Colorado,

Glenn Kerkhoff: you know. One of the questions we get a lot is, you know, what's a mining engineer doing, working at Amazon? Unlike the last thing that people expect. And

Glenn Kerkhoff: we actually have a group at Amazon that's called our worldwide specialist organization, and in that group is where we house our industry, vertical groups. And so we have an industry.

Glenn Kerkhoff: Ah! Lead! For each of the the industries in which we operate. So some of those might be like oil and gas, or manufacturing or agriculture could also be industries like, you know, financial services, healthcare media entertainment,

Glenn Kerkhoff: lots of different industries. And so I lead the group that is the mining and medals,

Glenn Kerkhoff: and and our role in that worldwide specialist organization is really to bring that industry perspective to to Amazon, to Aws and to help our customers understand and determine ways in which they can use aws to help improve productivity,

Glenn Kerkhoff: improve efficiency, improve sustainability. Basically just, you know,

Glenn Kerkhoff: create the the environment from the uh collection of data and the processing of that data into information that can be used to increase the customer's, you know, overall efficiency and improve their operations.

Glenn Kerkhoff: And so that's kind of where I said. And and really a lot of what I do is really as the go between between the technology part of aws and the industry part of the mining industry. And so that's kind of why i'm at Amazon.

Glenn Kerkhoff: So

Glenn Kerkhoff: what we're going to do now is just talk a little bit about some case studies that I wanted to present, and we're going to take a slightly different perspective than what you might think. Here we're going to talk about. Ah, Aws innovation in action. So James has just walked through very quickly. You know some of you know the ways that aws structures itself to innovate.

Glenn Kerkhoff: But what I'm going to do is talk about how some of these innovations actually have manifested themselves into different topics. But what you're not going to see. Here are the use cases specific to the mining industry.

Glenn Kerkhoff: Just talking with Nathan and Cheryl earlier. We decided to go a slightly different perspective, and look at other industries and

Glenn Kerkhoff: and look at ways that we can learn from other industries in terms of what happens in in data and analytics and machine learning, and think about ways that we can learn from other industries and apply those techniques into the mining industry.

Glenn Kerkhoff: Um, So that's where we go to go, and what I've got here is two or three videos over two videos, and if we've got time we'll do a third. That just talk about different use cases which i'm sure you'll be familiar with. So okay, So let's kick off.

Glenn Kerkhoff: So the first video I want to talk about, or the first case study. I'm sure it's one that you're all familiar with,

Glenn Kerkhoff: which is Amazon, dot com, and we like to talk about this one, because a lot of our customers are out there asking us all the time Right? How does Amazon dot com work? How does Aws support Amazon, Dot com, And what can we learn from that that we can bring into our into the mining industry, or quite frankly, into any industry. So let me just kick off with a short video. That's about one minute.

Glenn Kerkhoff: Um. And these videos, by the way, have sound normally, but they're not going to have sound on this zoom. Call um. I will be providing the links to these videos later. The sound is very cool, so maybe when you get some time you might want to revisit these and and look at them yourselves.

Glenn Kerkhoff: Um: Okay. So

Glenn Kerkhoff: let me just close a few things down here.

Glenn Kerkhoff: Okay. So you should be seeing the Amazon fulfillment logo on a building. Can everyone see that? Okay, Great?

Glenn Kerkhoff: All right. So i'll just do a little bit of commentary as we go through this.

Glenn Kerkhoff: So what you're seeing Here is an Amazon fulfillment center.

Glenn Kerkhoff: And what you're looking at here is a video coming through. Okay, this is the robotics that we use in the fulfillment center to take items into inventory and to pick items out of inventory and send them to to our customers. I'm not sure if you've seen this before.

Glenn Kerkhoff: It's really quite amazing. We We actually do public tours of our fulfillment service. And if you haven't done one, you should go online and you can book at a local fulfillment center and go and see what happens behind the scenes. And so what you'll notice here is that these robots

Glenn Kerkhoff: are actually moving the the shelves around in the warehouse. So in a typical warehouse, you think of having rows of of shelves with people walking up and down the road rose and picking different parts of the shells

Glenn Kerkhoff: in the Amazon warehouse. It's the reverse. The The shelves move around, we call them pods, and they move around and come to the, to the what we call our our picker, or it's our Amazon associate, who then takes the component to offer the pods,

Glenn Kerkhoff: and actually what I wanted to do. Let me just do this very quickly. I just want to show this video

Glenn Kerkhoff: again.

Glenn Kerkhoff: So again you can see those pods moving around. You can see all the items in the pods. It's just going to go a little bit longer this time. I want to show what the end result is here.

Glenn Kerkhoff: These are robots that are actually called tiva robots. If anyone's interested, we have tens of thousands, hundreds of thousands of these robots operating all over the world.

Cheryl Hart: So I made a very funny thing going, so i'm taking the kid a post or us post. Learn from this with Don't worry.

Glenn Kerkhoff: So um

Glenn Kerkhoff: to see where this is at. Yeah. So what you'll see now. We're coming up to about the minute mark, and so this is showing you the robots.

Glenn Kerkhoff: But what you'll see here in a moment is the is the Amazon associate picking the items off of the pod and placing them into a bin.

Glenn Kerkhoff: Okay, So here we go. So here you can see the the associate. The Todd comes in. It's all controlled by computer vision and machine learning. They pick the item off of the pod, and they will place it into a bin. And as this is happening, there is a computer visioning happening that's interpreting.

Glenn Kerkhoff: You know where the part, or whether your item is coming from, and where it's being placed. Here we have another view of some different robotics. This is actually the the inbound logistics of the items coming into a warehouse.

Glenn Kerkhoff: Okay, I'm going to stop this video. Now,

Glenn Kerkhoff: there's a lot that has happened. Someone was asking if you could buy that robot on Amazon. It does one robot stick the other robot.

Glenn Kerkhoff: Unfortunately, no, those are. Ah, robots are not for sale on Amazon, but Certainly it is the it's the it's kind of the backbone of the of how we handle the the supply chain and the logistics of getting

Glenn Kerkhoff: items to our customers, and that's a good Segue Nathan, you know, when you look at um at the at the Amazon business, you know we have, you know, over two hundred of these fulfillment centers around the globe. Each full film and center depending on the days, is moving about, could be as much as a million items

Glenn Kerkhoff: a million packages out to customers. Um. Each fulfillment center itself carries several million items, and so you've got items coming in. You've got to items going into an inventory. Then coming out of inventory, being packed and sent on to customers.

Glenn Kerkhoff: And if you think about that, you know, we're talking about hundreds of millions of items being delivered per day to our customers. And if you're a prime customer, you're getting that in two days,

Glenn Kerkhoff: and it's really quite a logistical feat, you know, and the way that this works is

Glenn Kerkhoff: is not the traditional way that people think about warehouses. It's more to do with the machine learning and the analytics of the robotics and the automation, and all of the processes that sit behind this that make this possible to get that kind of scale.

Glenn Kerkhoff: And there's some other interesting facts here. You think about like you don't see it in this video. But there's typically seventeen miles of conveyance in one of these fulfillment service. Quite often, when people are buying two things from Amazon, two different items,

Glenn Kerkhoff: those components will come, or those items will come from two different fulfillment centers in two different parts of the country, but they will still land at your door in one box in two days. In Amongst all these several million parcels being shipped around the country.

Glenn Kerkhoff: So you think about it. It's just Ah, it's just amazing how that works. And this is really the backbone of of what happens with the Amazon dot com online shopping. And this is all powered by Aws and our robotics capability,

Cheryl Hart: any ah questions on any of this,

Cheryl Hart: I think everybody's amazed here, always connecting, and

Cheryl Hart: I don't think everybody's seen the video I I mean, I haven't seen a lot of these videos, So I think it's amazing to see how much is that

the question?

Jan Smit: I would have a question, Glenn, does this mean that you are continuously optimizing your logistics pattern?

Glenn Kerkhoff: Yeah, correct. I mean, you can talk about this for a long time on this yarn. I mean. There, there's so much going on here like, if you think about inventory reconciliation, you know. Typically in a warehouse someone would walk around doing the reconciliation in accounting the number of parts.

Glenn Kerkhoff: The number of items at Amazon we do an on It's basically a continual ongoing real-time reconciliation. We are continually reconciling the goods that are going into inventory and out of infantry by a computer vision to make sure that everything adds up.

Glenn Kerkhoff: It's not very often that you see that you would see. Ah, it's something come to you that's got the wrong item in the box. You know, we really aim for a very, very high quality barrier in terms of getting the right goods to the people. And so

Glenn Kerkhoff: when you look at what we're doing here, it's not just about the technology. It's kind of revolutionizing the way you run a warehouse.

Glenn Kerkhoff: So some of the things that you know, just in terms of the techniques that are behind the scenes here, you know. Obviously, there's a lot of different senses that are going on. The robots themselves are using. They use bark barcodes on the floor as well as computer vision and radar to help them navigate through the warehouse.

Glenn Kerkhoff: There's all sorts of machine learning and artificial intelligence happening. So it's a continual learning process in terms of you know what's happening in that warehouse.

Glenn Kerkhoff: The real, amazing thing here is that in addition to what's happening in the warehouse, we're actually predicting what people will buy in the future. The only way that we can really achieve that two-day turnaround, or in some cases one day.

Glenn Kerkhoff: And ultimately we're striving for the same day delivery is we've got to be able to predict what people are buying in the future before they buy it. So this is all about our forecasting algorithms, our simulations. It's a lot of iot computer vision

Glenn Kerkhoff: a lot of high-performance compute. And you know extensive database technology that is really driving all of this

Cheryl Hart: And it's a Serbian log logging like this already in the mineral logging, when when you drill. Is there any of that kind of Ai technology connected in there yet that you're aware of?

Glenn Kerkhoff: So we. We have a number of partners that are using many of these same Aws services that are looking at, how to improve the the speed and accuracy and the whole process of logging drill call. And and certainly that's one topic,

Glenn Kerkhoff: You know. I think, that when we look at this, and this is what we talked about Nathan is is, we didn't really want to just go straight into a mining use case we wanted to show something a bit different. One

Glenn Kerkhoff: um. And so, you know, drilling and logging of drill core is just one use case. Ah, but really what I wanted to do here, and and I can get back to you with more information on this. We're going to provide some links to these videos and some contact details. We're very happy to to to Ah, follow up with some discussion on any of this.

Glenn Kerkhoff: But what you look at here is, you know you think about. You know some of the topics with cupboard here, inbound logistics, receiving, stopping, but things like tracking and location and optimization. You know, these are all types of things that we we do in the mining industry in different ways, not just in the warehouse, right? A lot of what our customers are asking us

Glenn Kerkhoff: is: Well, yeah, Amazon is doing all this stuff in their warehouse. What techniques are you using that we can apply into the mining industry so drill call logging might be one. Certainly the warehouse. Out of mine is another area, of course,

Glenn Kerkhoff: a warehouse out of my side. It's not going to be anywhere near the scale of this, but there are parts of this that could be used in a warehouse.

Glenn Kerkhoff: But my excitement about all this is really how this would apply to other things, you know, like monitoring the material movement from from rock in the ground, through drill blasts, load haul down through the crusher through the processing plan onto the customer. Things like metal balancing. Yeah, Sorry.

Nathan M. Stubina: Yeah, I just jump in. I see there's really a lot of great questions going in the chat room. So so what we usually do is we give our guests a copy of the chat room, and they're they're able to follow up with other people. And also I should point out that on the website where you went to register there's something called. Ask the expert. So if you don't get a chance today, or you're looking at this after the live viewing, Ah feel free to use the Ascii expert and then

Nathan M. Stubina: get back to Glen and James with the questions, because obviously we won't, have time to cover them all. But there's some really good good stuff going on in the Ch.

Glenn Kerkhoff: Yeah, thanks, Anthony. And you know we did have a quick Poll and Cheryl did. We got time to just bring that up real quick

Cheryl Hart: for sure we've had it. Laura's gonna pull it up for us. It's uh, And while we're doing this we need to look at the innovation.

Cheryl Hart: Yeah. So this poll here is you should be able to see it on your screen. So you know, these are a lot of the different topics that we look at

Glenn Kerkhoff: in terms of technology that could be used in mining to innovate and generate new possibilities around productivity, improvement, sustainability, things like safety. I mean, there's a lot of different areas. So we're kind of curious to get your feedback in terms of where you think there might be opportunities from your.

Glenn Kerkhoff: There's some good feedback here

Glenn Kerkhoff: right now. It looks like about a third on inventory. Oh, you know automation as well.

Nathan M. Stubina: Yeah.

Glenn Kerkhoff: And so these are good topics, right when we I mean, when we look at the industry and we all know this, you know the industry on large is going through a a transformation in itself. A lot of it was due to Covid. But we're starting to think about. How do we automate processes?

Glenn Kerkhoff: Get people off site to remote locations or remote operating centers? Getting people offside is going to improve sustainability and safety? You know there's a lot of different things going on. Robotics is a big area, I mean. Obviously, there's a lot of emphasis, a lot of um, you know,

Glenn Kerkhoff: feedback from from different oems about autonomous machinery. That's only one piece of automation the way we look at it, You know there's all sorts of automation that can happen in the processing plant in the warehouse.

Glenn Kerkhoff: Um, the value chain piece, you know. This is the one I mentioned where you know we're very interested at at aws in determining how to automate the process of tracking material through the value chains, doing things like the metal balancing and the production accounting, using things like computer vision to do stockpile volumes

Glenn Kerkhoff: to using computer vision to look at machine activity. Of course, some of the the big data topics are around collecting data to use for for maintenance and analytics. There, There's a lot of different areas that you could apply technology.

Cheryl Hart: I was just gonna say that maybe because You've shown an inventory where hostile thing I don't know if it had to be there. But I the lowest one I see in value chain. You know one of the supply chain is that we need to get production out. But you know, the futures can tell us how much product

Cheryl Hart: sectors that would be.

Cheryl Hart: Yeah, yeah, and exactly. And these are all some of those, you know, innovation topics, right? That it's like, you know. If we could do this, we we sometimes call this the art of the possible. But certainly there's a lot of technology that we can put into the whole topic of forecasting.

Glenn Kerkhoff: And customers are doing this. Now, I mean, this is what happens in the whole area of metal price predictions.

Glenn Kerkhoff: Um, you know, and what that means in terms of the demand overall, demand price, and ultimately what that would mean for a customer in terms of being able to fulfill demand. You know there's a lot of opportunity

Glenn Kerkhoff: I want to make sure we leave enough time for the next one. Is there any other questions on this topic before we jump to the next case?

Glenn Kerkhoff: Okay?

Glenn Kerkhoff: And again, more than happy to to follow up with some questions after the fact. I know there's a There's a lot going on in people's minds here. So

Glenn Kerkhoff: all right, let me. That was great audience participation. We had like three quarters of the people, and there's a few people like Cheryl and Yan and my son, who can't vot so probably at eighty percent of the audience of taking part. So, thanks to them,

next to you,

Jan Smit: I was one so like clicks. I'll do anything.

Glenn Kerkhoff: Okay, let me. Just. I've just got to jump back to

Glenn Kerkhoff: this screen here.

Glenn Kerkhoff: Okay,

one one second. Let me just uh

Glenn Kerkhoff: go here,

Glenn Kerkhoff: All right, so let's move on to another case. Study

Glenn Kerkhoff: um, and again, not from mining. But i'm sure if there's something that people are familiar with, and it really sits in the area of sports, and we at aws are doing a lot with integrating technology into different sports.

Glenn Kerkhoff: In this case we're going to talk a little bit about the formula, one racing. So if you're interested in automobile racing, this might be an interesting video. But there's more than that. There's the Nhl. There's Pga

Glenn Kerkhoff: There's the Nfl. There's a lot of different sports where aws is actually empowering the fan experience the

Glenn Kerkhoff: so like I mentioned, we're going to talk about formula one.

Glenn Kerkhoff: You should be seeing a big red stop light in the screen. All right. Good

Glenn Kerkhoff: again. This ah video clip is not going to have sounds. Um! But I would encourage you to go and watch this clip later with the sound. The sound is really ah, you know kind of what makes it a bit. Um, it is a marketing video, and again it'll be like the last one. I'm going to go through the video. It's just forty seconds,

Glenn Kerkhoff: and I just want you to watch what's happening. And then we're going to talk about what's what's really making this happen behind the scenes. It's a pretty wild clip, right? So you've got to sort of pay attention, and i'll comment a little bit as we go through this.

Glenn Kerkhoff: And so what I'd like you to do. It's going to be a mixture of You know what a fan would see in a formula, one race on the screen on their Tv screen, if you like, as well as different clips from the race itself. And you will notice, as you go through this clip, that there's all these dashboards that pop up on the sides of the screen.

Glenn Kerkhoff: And so I want you to quickly pay attention to those, if you can, and it's It's going to be a pretty quick clip here. So all right, here we go.

Glenn Kerkhoff: So you see these dashboards on the side. You'll see the at the bottom. There's a pit to the pit. Stop strategy. You've got the lap that the the race car is at You've got the cornering speed on the right hand side there.

Glenn Kerkhoff: You know Now the car's in the pit. They're looking at tire strategy. Here. Um again on the left-hand side incidents. You know what's happening back in the Piss corning speed car speed. You know lots of different data and information that's being fed back to the screen.

Glenn Kerkhoff: You get superimposed on the race itself. That's the end of that clip again. I'll send a link to you, and you should have a look at this a few times. Actually, it's a great clip.

Nathan M. Stubina: Thanks for the sounds. There, Cheryl, that that helped a lot.

Nathan M. Stubina: Room room in the chapter in there

Nathan M. Stubina: people are always asking me. You know. How do we get mining to be sexy? So I think if we turn the caviarly super pit into an F. One race I picked up my two and thirty,

Cheryl Hart: it would be awesome.

Nathan M. Stubina: You picked a great example like my my son, if I try to get him up before noon on the weekend. It's almost possible. But if there's an F one from Malaysia he has to get up at six. No problem so great example.

Glenn Kerkhoff: But i'm going to challenge the audience. You know, people are always saying, Oh, that's great for f one for that's great in a you know, an environment of the inventory or a warehouse. But you know, Think outside the box like, How could these things be applied to mining? And I guess that'll be your your point here.

Glenn Kerkhoff: Yeah,

Glenn Kerkhoff: if I could just tee it up a little bit, because we're going to ask you all again. But you know how you would see the application of this. But just to tee this up.

Glenn Kerkhoff: You know what you're seeing. Here is a formula, one race which is obviously very different to you know. Truck, shovel fleet in a in a mine,

Glenn Kerkhoff: especially the speed.

Glenn Kerkhoff: But you know the sort of information that comes back to the viewer here, and, by the way, it's not just to the viewer. It's the same information that's going to the pit crew,

Glenn Kerkhoff: except, of course, the pit view sees a different dashboard to the one we're seeing Here is things like. Well, where is the the race car, you know, placed what lap is it on? But also where is it on the track?

Glenn Kerkhoff: What's the speed of the car. What is the cornering speed of the car?

Glenn Kerkhoff: When is the predicted pit? Stop um! What's the status of the tyres? You know what type of ties Is the car actually racing on? And what is the strategy for the ties to make sure the ties are going to last through to the end of the race.

Glenn Kerkhoff: It's it's actually got feedback on the safety car and different safety incidents that are happening, and things that are happening in the pit.

Glenn Kerkhoff: And and when we look at all those sorts of topics there for a race, you know, I would contend that a lot of those same topics exist in a truck shovel fleet, albeit in a different, you know frame of speed. And so again, some of the technical concepts that we're looking at here,

Glenn Kerkhoff: you know, there's obviously a lot of data coming off of those machines is being transmitted wirelessly to the to the pick crew. The location, all sorts of analytics computer vision,

Glenn Kerkhoff: you know, real time dashboards, a lot of simulation happening behind the scene. You think about it here. The the objective is not just to get the car around the track. It's to win the race,

Glenn Kerkhoff: you know. Which means, you know, if you think about that, that's well, how can I maximize the average speed of the car over the the whole race. That's kind of what you're trying to do with a truck

Glenn Kerkhoff: right? But in our context we you know we'd be looking at temperature of oil temperature of a brakes temperature, you know. Not just position, but you know hundreds of different operating grammars

Glenn Kerkhoff: exactly, and those parameters I mean, we. We're only seeing a small sample on this screen, and what the Pick crew says, you know, and it's it's interesting if you look at all these different examples with sports. It's really about how to improve the customer of the the Fan experience a customer experience.

Glenn Kerkhoff: But of course the pit crew is looking at this from a different perspective. They're trying to win the race. And so, anyway, I think you know, just going back to the the learnings here.

Glenn Kerkhoff: There's a lot happening here when you look at a formula, one race and a typical fan that's watching this on the screen may not realize what's behind the scenes. You know what's what's happening here. But we did have another poll,

Glenn Kerkhoff: and I wanted to cheryl just to pop that one up on the formula. One: I've put a few topics in there for feedback. So, Cheryl, can you pop that?

Cheryl Hart: Maybe I could ask you a question. Yeah, one question we get all the time is, is, Does this mean that Aws is now going to go into mining, So not just helping or a service to mining. Do you think that whenever we'd ever see the day, and maybe not just aws? Specifically, you know, we get the question. You know this Tesla want to get access to the nickel, or Ford, or or whoever. So any

Nathan M. Stubina: have you thought about this or any comments?

Glenn Kerkhoff: Yeah, that's a good question. We get that question quite a lot. It's not an easy one to answer right. I guess you would never say never. I'm not sure. I mean, we're from where I sit. What Aws is doing is looking at how we can help

Glenn Kerkhoff: our customers improve their performance in mining. I'm not sure that we want to be in mining, competing.

Glenn Kerkhoff: If you look at what we're doing now, I guess if you look at Jeff Bezos, he's flying, you know rocket ships into into space. So who knows? I mean we we, you know. Amazon, got into the grocery business with whole foods, and there's a lot of different industries that we get into

Glenn Kerkhoff: so again I I would never say never. But I don't think so. I think the thing with electrification. A battery electric, you know, that puts a different spin on it, of course, because you look at Elon Muskers, you know, mention that in the media. So who knows but for now

Glenn Kerkhoff: and for the foreseeable future. What we want to do is help our customers maximize their performance, and to to improve the sustainability of mining in the industry. And so that's kind of what we're looking to do here.

Cheryl Hart: Cheryl was essentially all lunch there.

Cheryl Hart: I'm going to get it. Lori. You have it available.

Cheryl Hart: You know what Julius has a great question here.

Cheryl Hart: Okay, Julius has a Julius. Do you want to?

Cheryl Hart: Are you okay to unmute?

Julius Pretorius: Yeah, I can do that. Um, Lynn. Could you maybe discuss a little bit about the uh infrastructure and data management capabilities that you require for for week data. Um! In a previous life I played a little bit. You met at a smallish organization in Edmonton, and one of the biggest obstacles we came across was, uh,

Julius Pretorius: you know. How do you get your data from from your site uh to your central data management uh facility. And then you know, what do you do with your data? How do you? How do you make it? Um uh uh accessible to everybody in a you know format that everybody can use those sorts of things.

Glenn Kerkhoff: Yeah.

Glenn Kerkhoff: Great question, Julius. And that's a big question, so i'll just try to to jump into this at a high level, and we get asked: this: A lot is like, How do you get the data? So there's two aspects to that. Let me talk about that first.

Glenn Kerkhoff: The first one is, how do you get the data from the machine to the mine office, and we've all been in this situation where you know. Talk about wireless networks and that type of thing at the site. We are at Amazon, doing all sorts of different techniques, including things like private Fiveg

Glenn Kerkhoff: know different ways of putting data communications on cloud to collect data, big data

Glenn Kerkhoff: real time and get that into the Aws platform. If you look at, I think you probably heard about Prime Day,

Glenn Kerkhoff: which is the two days that Amazon goes, and you know, offers. It's like their main shopping day. The number of transactions that come into Aws during that time

Glenn Kerkhoff: is is billions of transactions. We're talking about an enormous number of transactions. We are no stranger to handling big data. The iot sensors In one of those warehouses we looked at thousands and thousands, tens of thousands of senses at a mine,

Glenn Kerkhoff: you know, getting that data into aws, you know that's going to require some technology capability, both in terms of hardware commons. But then also on the software side, the ability to absorb that data in a real-time fashion

Glenn Kerkhoff: there's a variety of different ways that we do that, Julius and I probably can't get into them all now. But but certainly we've got that piece covered.

Glenn Kerkhoff: But there's a second piece I wanted to mention, and that is that a lot of mines are in remote locations, and people will ask, Well, how does cloud work at? You know, up in the Arctic Circle. If I've got a diamond mine up there, and there's limited connectivity.

Glenn Kerkhoff: And so in those cases we have our what we call our hybrid edge technology, which is where we would actually install aws hardware computer hardware at your side

Glenn Kerkhoff: to operate in a standalone disconnected mode. So in effect, what we're doing there is. We're putting the Aws cloud services at your site right at the edge to collect that data and bring that into aws, and then that edge. Location then integrates back with the cloud.

Glenn Kerkhoff: Um:

Glenn Kerkhoff: Yeah. So,

Glenn Kerkhoff: Julie, I know that's a very high level. I'm more than happy. You're going to follow up on this. But does that?

Glenn Kerkhoff: Does that help a bit? Does it any follow-up questions on that?

Julius Pretorius: Thank you.

Nathan M. Stubina: I see it's tracking about fifty percent reliability.

Nathan M. Stubina: Yeah, but a quarter College and some safety and conditioning in there. Is that what you were expecting for? The

Glenn Kerkhoff: kind of yeah, I think the Reliability Angle is always the one people look at, I mean, and yeah, I mean, this is an area that is always one of the top areas. How do I increase the reliability and the availability of my equipment. You know I think best practice for availability on mobile equipment is in the

Glenn Kerkhoff: low nineties ninety-two, ninety-three. Percent If you can get to that in availability. There's a lot of mines out there that are in the seventies, and so there's some big gains that people that can be got there if you can just collect that data and use that

Glenn Kerkhoff: to increase reliability and therefore availability. And we're doing this in a lot of different areas, a lot of different industries. It's one of our key focus areas for the mining industry.

Glenn Kerkhoff: Here's a question that could be for either you or change. I like this one here so ah! And feel free to give away your secrets here. So what would be some of the greatest or most surprising partnerships that Amazon has developed. And why So we saw, you know, the the sports world, but anything come to mind, or James

Glenn Kerkhoff: Um

Glenn Kerkhoff: the one that I think about a lot is you mean in mining, Nathan? Or do you mean, anyway? Yeah,

Nathan M. Stubina: yeah, just general partnerships with you.

Glenn Kerkhoff: Yeah. Well, this we have partners, and then we, you know, and then we, you know we do. We make acquisitions. So I mentioned whole foods, i'm i'm sure everyone's heard of whole foods, and when we acquired a whole fruit, whole foods, it was like, Well, that's a little bit strange. Why is Amazon buying a grocery store, a grocery chain?

Glenn Kerkhoff: But you know the answer is because we're We're trying to revolutionize that industry, and there's a different clip which is in the links that i'll leave with you all that talks about Amazon's, what we call our just walk out technology. And i'm not sure if you've seen this. But

Glenn Kerkhoff: basically we see the grocery shopping. In the future you walk into the grocery store. You'll pick your items and you will just leave and go home. And that using computer vision and other technology. We will figure out what people have taken, and then and then charge them remotely.

Glenn Kerkhoff: So that was one That sort of came up. That was. It was quite kind of interesting. I don't know if you saw the news we just actually acquired a company called I Robot, which is the vacuum, the portable Vacuum Cleaner

Glenn Kerkhoff: company, and you know I robot. You know they've been working with aws for many years, so I guess we're getting into the vacuum business.

Glenn Kerkhoff: I think, in the mining space we have all sorts of partners that we we work with more partners than than acquisitions per se. But you know lots of system integrators, a lot of hardware components, Oems

Glenn Kerkhoff: um technology companies, a lot of the the different technologies you're using today. You know whether it's geology, mind planning, fleet management, maintenance, Brp: All those different topics of that you'd see in mining many of those different

Glenn Kerkhoff: vendors that are out. There are partners of Amazon sap is a great example of an Amazon partner putting sap on aws.

Nathan M. Stubina: Well, James James, you can jump in there. But but also I was wondering like, Besides, you know your partners. You hear of case studies where people contact you after the fact and say, Oh, we've been using. You know your services for this, even though you weren't involved with them from the start.

Glenn Kerkhoff: That's a great question, and we do see a lot of our customers experimenting themselves,

Glenn Kerkhoff: you know. So, in fact, some of the like. And this is in the mining company space. Some of the largest mining companies in the world have adopted the Amazon culture of innovation in terms of working backwards to to to innovate and come up with new ways to look at data. So we do see that

Glenn Kerkhoff: I think the the industry as a whole, though you know they're just on the the start of their cloud journey. You know. There's a lot of technology that gets in the the mining industry today. Um, we're seeing companies more and more so, wanting to integrate technologies together, merge data sets together to get new insights. And so

Glenn Kerkhoff: we see some of that. But we're expecting to see a lot more in the mining industry going forward to be off working in remote locations.

Nathan M. Stubina: Here, James, I'll ask you that. But before that, you know people

Glenn Kerkhoff: not actually not many people have dropped off, but I know at the bottom of the hour. Sometimes people do. So, you know, if if people have other commitments, that's fine. But if if you guys are okay, we'll keep going a bit. Yeah, James, did you want to jump in with anything?

Glenn Kerkhoff: I'm. Sure, I mean, you know some of the relationships are are complicated. I mean, we do have a marketplace uh marketplace service on our aws uh platform, where we have competitors and partners offer their products to that.

James Kierstead (AWS): And you know thinking about it, You know aws south of Amazon, and of course Amazon continues to use aws for its you know it's cloud services, but we have competitors of you know, Amazon, that use the platform as well.

James Kierstead (AWS): So it's all about, you know. Taking advantage of cloud computing by differentiating on another basis,

Nathan M. Stubina: it was a question, Does Aws or Amazon invest in sensors, or do you just use what's on the market for, you know? Let's say the F one case, or if if you see a need for a sensor that's not there, and someone approaches you to invest its startups or small companies.

Glenn Kerkhoff: Yeah, The answer is, yes. And in terms of you know. Do we have our own senses, or do we, partner with other companies that have census? The answer is, Yes, and yes. So a good example

Glenn Kerkhoff: very applicable to the to the mining industry is that we have a sensor called a monoton. I'm not sure if you've seen this, you can buy it from Amazon com,

Glenn Kerkhoff: and it is a hardware iot sensor with a magnetic mount that you put onto a piece of rotating equipment, and it measures vibration. The measures heat and it measures.

Glenn Kerkhoff: I'm sure if it's measuring noise. Measuring a couple of things

Glenn Kerkhoff: comes together, it comes connected to an Aws gateway device that you basically plug into your network all pre-configured,

Glenn Kerkhoff: and you can immediately start collecting data from rotating equipment and sending that into the cloud where we run the machine learning models to start to look for data discrepancies using different machine learning and different different techniques.

Glenn Kerkhoff: And so, when you look at this, this is something that we're really trying to push into to the mineral processing side specifically in the processing plant.

Glenn Kerkhoff: I think. Putting it onto a large hall track, for example, is a bit of a stretch at the moment. You know that device may not last. It's a rugged device, but you know, in the field, you know, we would partner with other companies. So we have a lot of different partners. We work with on iot senses and

Glenn Kerkhoff: computers, regularized sensors that we can integrate with.

Glenn Kerkhoff: But Certainly the monoton is something that everyone might want to have a look at. You can just go to Amazon, Com and type in Monetron, and it'll show you what that looks like.

Nathan M. Stubina: Cheryl Yacht. Anything trending that that I've missed.

Cheryl Hart: So Dennis has a has a great question. If Bass is still here, you want to ask your question.

Cheryl Hart: We're unmute

Glenn Kerkhoff: also related to uh optimizing mineralogy being fed to the plant. And I mean, we do a lot of analysis. Obviously there are probably other sensors that can be incorporated to collect more data. But is anybody using a system like that to,

Dennis Tataryn: you know, collect data before you're even feeding me, or as you're mining to be able to optimize processing.

Glenn Kerkhoff: Yeah. Great question, Dennis. And

Glenn Kerkhoff: yeah, the answer is is, Yes,

Glenn Kerkhoff: um. But I think this is an area that is still a work in progress. Right? There's a number of different companies that are out there that have sent to technology to identify minor allergy, and you know geomet, allergy, and

Glenn Kerkhoff: other properties that may be necessary to do appropriate blending to feed the plant.

Glenn Kerkhoff: But I think this is an area. That's a bit untapped, Right? We We all know that we want to be able to measure the quantities of material being extracted from the ground and said through the plant. But of course, as we all know, the the main thing is well, what is the

Glenn Kerkhoff: you know? What is the grade? What is the the geometological characteristics. What are the impurities, all of all of that type of thing? It's certainly on our radar screen to work on that. It's one of the areas we're working on. But I would say that's more of a a work in progress that's going to do to sort of evolve in stages,

Glenn Kerkhoff: integrating with things like limbs systems is something where we're looking to do as well, you know, to to basically feed into the you know the metal balancing. It's a pretty big topic, Dennis and I'm very happy to talk about it, but it's probably a thirty minute discussion.

Jan Smit: It does raise one other good point, though, And I I want to mention this that our business of aws is not to go and reinvent the wheel with technology companies that are out there offering sensors or other pieces of software. I guess we could. You know we could go, and, for example, build a

Glenn Kerkhoff: some sort of a device to do some, you know, some monitor or some metallurgical property detection from a piece of rock core, for example. But it's not really our business, and what we really want to do is work with those supplies of technology that are already doing that

Glenn Kerkhoff: to improve their products on aws and be able to expose the data that they're collecting into other parts of the business. So I want to make it clear here that we're not out as aws, We're looking to really be that partner for technology companies to improve their offerings

Glenn Kerkhoff: into the industry which would thereby improve the efficiency of the end-user customer

Nathan M. Stubina: just a piggyback on that so So there are companies like, you know, mind sense out of Vancouver that have that sensors on shovels uh. So you know, in in our context share it's context, like it's not just the nickel rate. It's Also, you know what's the acid consumers, because it might have nickel, but it might cost too much money to produce it. So if we're looking at nickel or eight straight, that we might want,

Nathan M. Stubina: you know, some some of the lumina or some of the magnesium or magnesia. You know that consume acid. So so we could follow up on that discussion at another time. But but yeah, So combining a few different sensors. Ah, besides, just you know, is there enough copper article in the order to get as well?

Glenn Kerkhoff: Yeah, Exactly. And yeah, look, there's a few companies out there I can mention. There's one called Data Rock. There's one called Course Scan. There's board which you would know, and of course there's mine sense. I mean, we're we're we're talking with all of these companies. Many of them are on aws like Data Rock,

Glenn Kerkhoff: who do interpretation of drill core core scan is another one that's doing in that same space,

Glenn Kerkhoff: you know. Mind sense is a little bit different, because it's, you know, trying to do that in a more real-time way. Motion metrics is another one that i'm sure you're familiar with. So there's a lot of different, you know, partners in the technology vendor space that are working on aws and working with aws

Glenn Kerkhoff: to help improve their offerings in this space.

Nathan M. Stubina: So we're getting close on time, so maybe i'll leave it back with you before. I thank you for joining us. But but, James, plan anything you want to leave with us in the mining area. Anything that you know, anything, any last words you'd like to in part on us.

Glenn Kerkhoff: Well, um look again. Thank you to everyone for for for joining and and Nathan and and Cheryl and And, Jan, thank you for the opportunity to speak.

Glenn Kerkhoff: You know some of these topics that we've been, you know, talking here in the last thirty minutes or So they're big topics, right. And

Glenn Kerkhoff: you know I love talking about this stuff and exploring new ways to think about how to improve operations through the use of data, collection and interpretation. It's hard to do in, you know, in in thirty minutes. But you know i'm in and around the the mining industry. You know my role is to be customer and partner-focused.

Glenn Kerkhoff: So yeah, based in in Denver, as I mentioned. But I spent a lot of time in Toronto and Vancouver and Calgary, and more than happy to follow up and have some deeper dive discussions that's part of my role. So if you want to reach out to me, You,

Glenn Kerkhoff: i'll leave you with Kristen's contact details, but i'm also on linkedin if you want to reach out to me there. But yeah, I think we're very interested in hearing what the industry is wanting to do, and where they see opportunities

Glenn Kerkhoff: to improve, and the two polls that we ran were great. I I think he gave us some good perspective, and some of it was expected, and it's good to see that we're sort of thinking, you know, aligned so. But yeah again, thank you for the opportunity to speak today,

Nathan M. Stubina: and i'll. I'll give it to James. But I just saw a great comment come up from Samantha Esqui, who I know from Saudi Arabia and Naha here from Surrey as well. Samantha's comment was, The The wheels are turning, and I presume she meant in her mind as opposed to the the truck wheels.

Nathan M. Stubina: So, James, any anything you'd like to,

James Kierstead (AWS): and how it's around.

James Kierstead (AWS): I just want to thank everybody for having me today, and, like I was saying in the presentation, that the key thing is to is the calculated risk taking you have to be

James Kierstead (AWS): to, you know, Fail on time from time to time, and learn from those. Learn from those lessons. Learn from those

Jan Smit: Yeah, I think that there's a big, deep dive here, and I think we're actually gonna have to have uh, uh, James and Glenn again. There's just uh quite a diverse to get questions. So you know to summarize it. I really like that going from a step back and kind of explain the focus for us. So you know a lot of questions on designing sensors. How do you get the the analytics? And I don't know the idea of, you know, connecting in the lens system? You know,

Cheryl Hart: to advance these uh tools that we have, and make them more productive across multiple chains. Not just in,

Cheryl Hart: you know. Is there certain ways that certain metals are going to be picked up faster with Ai than other ones, you know, like the line's definitely rolling, and things are going like, Smith said, Thank you.

Glenn Kerkhoff: Yeah. The chat room is very active. It's a great question. It's coming up. We'll leave you with a copy of them if you'd like to, you know. Follow up with some of them. A lot of the people on the call are regular, some of the people as well.

Nathan M. Stubina: So, first of all, thanks to Cheryl and young partners in crime, and putting these together, Lori and her group at smartenup institute for providing us the platform,

Nathan M. Stubina: Kristen, for joining us in setting this up, and of course, Glenn and James for our speaker. So thank you, Everyone, thanks to the audience, the hour and out of it really flew by from my side of the microphone, so I hope you enjoy it. Thanks, everyone.

Cheryl Hart: Yep. Thank you so much.

Jan Smit: Do

Samantha Espley: thank you.

Nathan M. Stubina: I'll sign off now. Thanks, everyone.

Cheryl Hart: Yes,

Jan Smit: thank you.

00:27 Jim Frey: Welcome everyone! Where are you connecting from?
00:44 Denise Pankiw: Hey Jim, from fort Saskatchewan!
01:07 Michael Lodwig: Fort Saskatchewan Also
01:37 Andy Reynolds: Coast Salish and Snuneymuxw territory (Vancouver Island)
01:42 Elizabeth Steyn: Hey, from London, Ontario
02:06 Bayar Baatar: Happy New Month, from Burlingon, Ontario!
02:14 Bayar Baatar: *Burlington
02:21 Jim Frey: Greetings. Happy to see you all!
02:35 Kristen Morgan: Hello everyone from Kelowna, BC, on the unceded lands of the Syilx nation
02:50 Sherritt Bits&Bytes: from beautiful Kelowna British Columbia!
04:52 Cheryl Hart: Awesome to have everyone here! Many great language abilities...
05:12 Andy Reynolds: OZ Minerals use this IPRFAQ approach for their innovation challenges. Very effective for building collaboration.
07:06 Jim Frey: https://www.linkedin.com/in/james-kierstead-7a692876/?originalSubdomain=ca
07:21 Bayar Baatar: what size pizza?
07:22 Cheryl Hart: Speed Kills….Many say Perfection is the devils work
08:53 Sherritt Bits&Bytes: how many slices per team member???
09:08 Jim Frey: https://www.theguardian.com/technology/2018/apr/24/the-two-pizza-rule-and-the-secret-of-amazons-success
09:20 Cheryl Hart: Are the slices even?
10:41 Jan Smit: Often, the concept that is identified is valid, even if the specific solution proposed doesn't work. Try again, if the concept is valid!
10:58 Kristen Morgan: How does Amazon capture the learning the comes from the failures of experiments?
11:31 Jim Frey: Well said Jan! Try, try again.
12:06 Andy Reynolds: How do you prevent management from trying to make it all efficient?
12:36 Jan Smit: Do you keep a database of challenges, or key concepts?
12:48 Cameron Harris: It sounds like the "Lean" is for two way doors, and "waterfall" is for one way doors. Fair summary?
12:54 Andy Reynolds: Who decides when to give up on an idea?
13:35 Jim Frey: https://www.ebay.com/itm/234507878535?chn=ps&norover=1&mkevt=1&mkrid=711-117182-37290-0&mkcid=2&itemid=234507878535&targetid=1263094003826&device=c&mktype=&googleloc=200534&poi=&campaignid=14859008593&mkgroupid=130497710760&rlsatarget=pla-1263094003826&abcId=9300678&merchantid=113584296&gclid=CjwKCAjwsMGYBhAEEiwAGUXJafjt9OPOpXeQZCj11OaoDtgWjZpTHMoeaqyUm4eH8HiOLSXsxdp6whoC7k8QAvD_BwE
14:27 Andy Reynolds: Further to Jan's question, how do you stop the wheel from being reinvented?
14:31 ASHISH PANDEY: Amazon being such a big company, I am curious to know how many small teams are there at Amazon? Is there a number? and how are the teams managed
15:58 Bayar Baatar: Ah, like A/B Test
16:14 Marilyn Spink: Great question @Andy Reynolds. Critical to make new mistakes vs. repeating mistakes of other cause we will always make mistakes.
17:40 Jim Frey: https://www.linkedin.com/in/glenn-kerkhoff-1a50843/
18:33 Cheryl Hart: Yes - Bayar
18:51 Jan Smit: A shout-out for mining engineers! The most likeable of all engineering types.
19:12 Cheryl Hart: hmmm - Jan!
19:43 Neha Singh: I like the metallurgists a lot more Jan :D
19:59 Nathan M. Stubina: Me too
20:25 Cheryl Hart: I need more convincing. :)
21:20 Neha Singh: Metallurgists are the Data Gods of the Mining Industry IMHO
21:28 Marilyn Spink: Thanks for the nod Neha!
21:42 Neha Singh:
22:42 Jan Smit: What happens if a mouse gets into such a centre?
23:10 Cheryl Hart: https://www.youtube.com/watch?v=_waZrhOZVWY
23:29 Sherritt Bits&Bytes: Can Canada and/or US Post learn from this fulfillment center?
24:16 Sherritt Bits&Bytes: Can i purchase the robot on Amazon?
25:04 Kristen Morgan: If you combined those robots with a Roomba, you'd have the cleanest warehouse on the planet!
25:33 Marilyn Spink: Believe these robots used elsewhere in advanced manufacturing & automotive industries as well as grocery delivery service warehouses - Voila & Grocery Gateway.
26:52 Jan Smit: I sometimes get different orders, placed at different times, in a single delivery - so the system is continuously reviewing the optimum logistics pattern?
27:14 Jim Frey: It's amazing what has been created!
28:45 Sherritt Bits&Bytes: It's like a real-time trading system where the reconciliation is done at the moment of trade.
29:40 Paul Nawrocki: What is the reliability of the robots and the amount of maintenance required to keep them operational?
29:42 Jan Smit: This is a vision of ultimate, real time adapting to the environment - should be translatable to a mining operation!
29:50 Julius Pretorius: Are your computer vision algorithms of a similar sophistication to those found in a Tesla? Or are they pared down?
31:51 Marilyn Spink: Any process really
32:23 Jan Smit: ….when a pump goes off-line, your plant mass balance could re-adjust in real time, for maximum maintenance of profitability
33:09 Marilyn Spink: Modelling process and tracking is key....
35:41 Sherritt Bits&Bytes: I think that value chain can be the one area of most impact for this technology.
36:05 Andy Reynolds: I answered "other" because the biggest opportunity is in business models. Amazon can embrace innovation because of the network effects it creates through its platform business model
36:26 Jan Smit: What then is the optimum role of human participation in all this?
37:19 Cheryl Hart: I love this video
37:41 Sherritt Bits&Bytes: woohoo! F1 is awesome!
37:45 Jan Smit: Are humans best for adaptability, complex tasks, dexterity.....?
38:02 Jim Frey: Did someone say SPORTS?
39:11 Cheryl Hart: zoom zoom
39:20 Jan Smit: Clearly not "full autopilot".
39:27 Kristen Morgan: I was at the Spa-Francomchamps F1 race this past weekend and it was amazing to see how heavily involved AWS was with the data, even from the fan-facing side!
41:38 Jim Frey: Place your bets please.
41:40 Kristen Morgan: As a fan, having the F1 data visible and accessible means I actually understand what's going on and how it feeds the strategy- F1 is what it is thanks to the AWS data!
42:20 Marilyn Spink: I would agree, it is all a process which needs to be tracked and trended. Performance Analytics of a mine vs. F1
42:27 Jan Smit: Very impressive, but the race car driver is effectively becoming a "brain-in-a-jar"?
42:45 Julius Pretorius: Care to discuss the infrastructure and data management capabilities that are required to implement AI approaches? To my mind that is the biggest obstacle to implementation.
43:59 Jim Frey: Good point Jan. Ricky Bobby would not go for that!
44:05 Marilyn Spink: Is collecting any data on Sustainability Metrics?
45:39 Sherritt Bits&Bytes: I worked on a tech system for BC Highways that tracked the fuel, the mileage, the speed, the time on the roads, and was an early machine learning system so the system could learn how to best assign the drivers to the most accurate areas in peak periods + so many other logistic and labour requirements, as well as the health of the trucks themselves. btw - they are still using the system today!
45:43 Marilyn Spink: Is AWS collecting in their AI including Sustainability Goals?
47:55 Glen Smith: How would you compare AWS to asset framework platforms currently used in industry?
48:17 Neha Singh: also a big component is user readiness and expectation of not knowing what is the "art of the possible"
50:04 Jan Smit: Reliability.... or focus on system adaptability/redundancy?
50:04 Marilyn Spink: Great point Neha!
50:10 Andy Reynolds: My "other" response was mining system design. It's an archaic process.
50:22 Marilyn Spink: It is all about change management.
51:27 Glen Smith: How would AWS enhance fleet management systems that are currently in use?
52:42 Dennis Tataryn: Anyone using the technology to optimize mineralogy of feed to the processing plant?
52:55 Michael Lodwig: Is AWS involved with the design and implementation of sensors and instrumentation or more on the data analytics side?
53:32 Jan Smit: Dennis - you mean, real-time, in process blending through production management?
54:07 Dennis Tataryn: Yes along those lines, or optimizing the mining plan and day to day mining operation.
55:59 Glen Smith: Sensors are what it's all about - no data collection -> no analytics
56:37 Jan Smit: Mmmmmm…… that monotron could be tied to my cat?
56:56 Julius Pretorius: Dennis, Jan, in my previous group we used computer vision for this purpose in the Pulp and Paper industry.
59:11 Neha Singh: Maybe you should come back and do another session on that topic Glenn!
01:01:38 Samantha Espley: Very, very interesting! Wheels are turning. Thank you!
01:01:57 Cheryl Hart: so much to cover - we'll have to get them on again
01:02:11 Kristen Morgan: Thank you so much for your time, such an interesting session!
01:02:12 Cheryl Hart: Thanks Samantha!
01:02:50 Robert Lopetinsky: Thank you Amazon Team
01:02:52 Sherritt Bits&Bytes: @Maryam asks this question:
01:02:55 Sherritt Bits&Bytes: Can AWS be connected to the historian data for online data analysis/
01:03:10 Neha Singh: Monitron is very interesting - Thanks Cheryl, Jan and Nathan for providing the opportunity to learn about this
01:03:46 Neha Singh: I am looking to implement a quick Monitron use case ASAP - with some of our industrial clients.
01:03:55 Jim Frey: Thank you for attending and participating today! https://sherritt.smartdirect.ca/
01:03:56 Michael Lodwig: Thank you very much for the session and discussions
01:04:13 Julius Pretorius: Thanks! Very interesting!
01:04:29 Neha Singh: Also very much in line with the #BDT2022 theme of Remote-First
01:04:29 Will van Niekerk: Very nice alternative view on things. Well presented
01:04:36 Darpan Kohli: Thank you for a great presentation!
01:04:44 Bayar Baatar: I really liked the different pizza groups possibly having overlapping goals - and that’s okay with AWS!
01:05:22 Baseer Abdul: Thanks to Sherritt for organizing this talk
01:05:30 Cheryl Hart: thanks!
01:05:35 Marilyn Spink: Thanks for organizing
01:05:35 Alyssa Carson: Thank you!