Fixing Exploration Funding with Jon Hronsky

Righto buddy miners, welcome to another bloody JD and LEGC spectacular brought to you by Axis Mining Technology, the trusted advisor for Drill Isle survey instrumentation and their best people to talk to on the phone about it 'cause there's a guru on the end of the line every single time. Love your work Axis. Oh, that's it. Nice. So this was a bit of a little pre digger's amble that you too kindly did while I went to a golf day. Thank you very much by the way,

I was doing some DD out there. BDD. DDDDD. Who we got? So we've got John Ronsky here today and we've also got Ahmed to help us navigate the conversation. John is a super switched on geoscientist and Ahmed helped us kind of get through that more technical part of the conversation. I'd listen to John on a few podcasts he'd done in the past and I thought the ideas he had were absolutely fascinating. This is a guy with a couple decades at at Western mining few years in there at BHB.

Then he's been running his own bit. He's been teaching out of out of UWA for quite some time. And he's, he's got a few different talking points that I find absolutely fascinating in and around our kind of home ground of talking about the funding of mining companies, getting exploration projects online. And we're going to talk through things like the. Search spaces. Search spaces, that's one of these sort of big features about how companies go about

exploration. He's got models and you know, a lot of it kind of ties in with what BHB Explorer has kind of done, although this is a concept model exactly. He'd come up with this concept a good sort of decade ago now. So I think with that, we'll we'll rip into it. Right now, good stuff. Here we go. All right, money miners, we've got a we've got a special chat here with John Ronski, Ahmad Ali, a bit of a different line up today, but we're pretty excited to to get into this.

John, you've, you've spoken a lot in, in over your career about a topic that's sort of near and dear to our heart. But the way I want to kind of segue into this is that that crossover between business and the science of exploration discovery. And you've spoken about four rules for exploration companies in the past. And that kind of leads us into talking about search spaces and, and the funding model for, for juniors out there.

And I want to start by hearing about search spaces these these four rules that you have for exploration companies out there and then kind of go from there. OK. Well, the first rule is decide what you're looking for, because you've got to focus on something that's going to make a difference to you as a business. And if you're BHP, that's one thing. If you're a, a, a junior, you know, trying to break into the industry, that's another thing.

So you have to consider the thresholds, you have to consider, you know, the, the capital, you have to consider the risk that you you can take. So for example, if you're a BHP, you have to be looking for a very, very large deposit, something that can replace an Escondido or an Olympic dam. So yeah, we in life have this sort of risk reward relationship. So if you want something that has a very, very high reward, you have to be taking a high

risk. So if you're genuinely in the game to find one of those deposits, it influences your strategy. So that's the starting point. You've got to decide what you're looking for and, and what's going to make a difference. The second point is you have to identify a valid search space where that could be. You know, it's no good saying, well, I want to find this giant deposit, but it has to be within 50 kilometres of my existing

infrastructure. And I don't want it to be too deep or whatever because that may well be a search space that doesn't exist. So when we talk about the concept of search space, what we're really saying is the search space is the intersection between what we know geologically about what's going to control the location of a deposit in space and what we know about the economic environment. And critically, the history of every bit of exploration that's gone on before.

Because if someone else has already sterilised that search base, it doesn't matter how smart your geology is, it doesn't matter how smart your detection technology is. We already know it's not there. It's a very, I mean, in some ways exploration is very Bayesian approach. You know, you start off with I don't know, and you collect more data and each bit of new data, you know, reinforces a story. Either it is perspective or it isn't perspective.

And of course the big challenge with the search base idea is that we find our biggest deposits where we have the lease data. Really, really important concept. Kind of an obvious concept, but I restate it now because in the era we currently live in where we hear a lot of stuff about big data and AI, and the idea is, well, actually we've got lots of data. All we need to do is analyse it in a smart way and we'll find

the deposits. I fundamentally disagree with because we don't find deposits where we have a lot of data. We find deposits in volumes where we don't have any data or very, very limited data. So that's that's a search based concept. And I think just to interject here, I think one of the other important things about search space is that they can change over time as well.

Yeah. So, so lithium will be one, right, where people discovered, you know, tin deposits before, but lithium was obviously not invoked then. So no one actually did anything. So yeah. So one of the things I think here is that, yeah, like to John's comment that you often find these things where there's

no data. Well, it has to be data that's relevant to what, what the problem you're trying to solve as well is that they, they could be actually data rich areas, but it's just that we haven't looked for the specific thing like lithium in that data set and hence we might have overlooked it. So yes, so the concept of search space is, is like, you know, it's not just a physical space

that you will kind of look for. It's also a philosophical kind of space and like, well, you know, like how do your ideas evolve over time? How does the technology change? You know, technology can have a fundamental effect on how you find things. You know, the detection limit of a certain technique gets lower all of a sudden, you know, like you can, you can review that data differently. So I often find that search space becomes this concept where

people think it's physical. They go, oh, yeah, like I'm going to go physically out to the edge of the world because no one's explored there. Well actually search spaces can exist in well explored terrains as well. It's just that you have changed the the parameters of what you are looking for, hence you've opened opened up a new search space in that sense. Yeah, No, 100%, Ahmad, search space is, is, it's an abstract parameter space.

I mean, I didn't want to become too technical about it, but there's a number of different parameters that will govern whether a search space exists, you know, including all the ones that you talked about that, you know, the commercial regime in a country is an important part of that search space. But just to to pick up a point about different commodities actually now before I do that, two points about search space.

One, the reason why we coined the term search space rather than the other concept of exploration maturity, which you often hear people talk about exploration maturity, is we felt like maturity seemed to relate to just how much work had gone on in a particular area. And if that work had not been been effective for the particular search base that we were interested in, it was irrelevant.

So yeah, some textbook examples from the history of exploration WA, the Cambalda nickel deposit was discovered in January 1966. And up to that point within the Yogan Craton of WA, no one knew anything about the presence of nickel. In fact, no one knew that these commodit rocks could host nickel. And the world expert said, I know you don't find nickel in those rocks because you found nickel in places like Sudbury. So that instant that created a

new search space. Now that that result, that drill hole was basically right in the middle of the Red Hill gold mining area. So it was right in the middle of the of a almost on. You know, some of those samples of nickel were first found on the dumps of old gold mines. And of course the Kalgoorlie had been at that point for 70 years, a major gold mining centre. But that reset the search space and the more the most recent sort of reset of search space we've had has been the lithium boom.

So, you know, if we're in a world where we're looking for the traditional commodities of gold and copper, which have been the two most important ones we've explored for for a long time, it's a pretty reasonable assumption globally to say that not many of these deposits are going to be sticking out of the ground with an obvious surface expression, right. This wasn't true of lithium 10 years ago because people hadn't

focused on that. So you could still go to places like Pill and Gore and say, oh, there's a big outcropping Ridge of pegmatite. OK, fantastic. Because the search space for lithium was much less mature than, say, the search space for gold. I mean, people have been looking for gold around the world for a

very long time. So you know most of the surface with and you know, one of the things to understand about search space is the technologies we have for exploring things at the surface are vastly more effective and cost, you know, cheaper than technologies for exploring below the subsurface, even like only a few metres if it's concealed.

So this sort of. Concept it, you know, we're getting right into the the geology here, but we come at it from an investment lens predominantly on on the show here. Is this a concept you think is is widely held in the in the geological community?

Look, I thinking, I think increasingly so and it is actually very relevant to investment because if we look at the the opportunities for investment in say the greenfields exploration space, to me the valid search base criteria is a really important philtre that would probably in my opinion separate about 20% of the companies that actually have a chance and 80% that probably don't.

So going to an area where there might have been lots of sniffs of mineralization, lots of drill holes, but no actual discovery and going back to those areas without coming up with some new search based concept is not going to be successful. But often times, you know, investors who don't see things through that lens will put money into those sort of

opportunities, right? So I actually think that the search based concept, well our teachers course, senior exploration management and one of the things I say is the one concept that I'd like you to take away from this course more than anything else is the concept of the search space. Why? Because it's the central concept that links the scientific things that we do in this business with the business outcomes, with the commercial outcomes.

If you don't understand search space, you really don't have the key central concept to understand how mineral exploration delivers value to investors. And I, and I think that concept about, you know, like why it's important is, yeah, like maybe from, if you're investing in a consumer product or something like that, I think it's slightly different in that, yeah, like you can always grow your consumer market in a different way. You know, you can sell shoes, but you can sell clothes at the

same time, or you can sell hats. You know, there's always something that you can add. Whereas I think in, in, in mineral exploration, you know, one of the key aspects of why search space is important is because they're kind of exhaustive. Like once someone has explored an area, it it kind of gets removed. It's a non renewable kind of yeah. So, so once someone has found something there and they've mined it, that search space is effectively kind of dead now.

Or in order to grow that search space, if you want to go deeper or something like that, there's an economic parameter that comes in. It's not going to be more expensive. Yeah. It's going to be harder to find as a search space matures, you know, like the easier things should be found first and the harder things now will be, will be the ones that you'll be

looking for. And there's a pretty startling fact, though, that flies in the face of that which you said in a previous interview, John, that roughly 80% of money going into the ground is spent on depleted search spaces. Why is this still the case? Because the perception of, I think it's an incorrect perception of risk, right.

And let me just tell it from the perspective if I'm a some sort of executive in some large mining company and I can have a programme where I'm going to go out into areas with no known mineralisation and it might be several years before I can return a result. But that might be what I need to do to make the discovery this company needs. Or I can do joint ventures on half a dozen projects where there's quite a lot of known mineralisation.

And I know that I'll be able to report every quarter. I've got this drill hole intersection and I've got this drill hole intersection. Which option is lower risk for me professionally and personally, right. And which option is lower risk or higher risk for the company? They're not the same. And. So just hang on a minute there. We're talking about risk and reward. And there's one company that popped into my mind and that's MMS guys.

Well, that like, well, in terms of risk reward, like no risk, shit loads of reward. That's it. They take the risk off your hands. Yeah, they are the mining company, trusted mining contractor out there. And all I've made, all JD all think MMS are that good that they probably don't even have risk either. I think you're right. Yeah, absolutely. And yet, you know what else stands out about MMS guys? Bloody tailored service.

They do they, you know, you've got any problem, you just give Josh a buzz, they will sort it out for you. I mean, we're talking about mine site support, drill and busting services, contract mining services. Obviously there's a few good examples out there. Just Josh, it will talk you through them dry and wet. Hire anything else you want. And the tech, the Technical Support. Technical. Evaluate the pit mate, don't body. Try and figure out how to mine it yourself.

Get the miners to figure it out for you. You're just moving dirt. Love your work MMS, get on to them this good. This is going to be how mining contracting is in the future. Pioneering. Here we go. Good. Work MMS. We better get back to you, Jan. I think that the reality is that, you know, particularly if you're going to fund expiration from, you know, the risk capital market with a fairly sort of volatile, fairly volatile source of capital, you, you, you need to provide that excitement.

Yeah, the idea of you've given me your money and I'll report back to you in two years time when I finish this programme. Who invests in that, right. So that, so that's sort of the tension that that that goes on, I think. I mean, effectively it's like, you know, people will do what's expedient, either commercially or, you know, from a point of view of releasing stuff to the market or investor.

Then I think what would be the harder thing to do, which is exactly what John's kind of talking about. Like, yeah, it would be harder to go and say we're going to raise money and for three years we probably won't release a single announcement. But after that, we'll know, you know, people will go. I'm out of here. Yeah, because there's a couple questions I wanted to ask about that because there's the the concept of the search pace makes

so much sense, right? It's it's, it's so logical, but actually practically getting people in companies to do it is such another challenge, right? You know, the business element comes in people, there's a resistance against change. And I think the other thing which was actually touched on, you know, in a great Live Wire article earlier this week about people are scared to go to risky jurisdictions.

And it's often the pressure from the public markets and, you know, public money to it's like, why, why should I go pursue this risky, as you know, or good asset in a risky jurisdiction here where I can just do something safe and easy, you know, over here. And it sort of talked about how there's this particular article talked about how there's a tussle between, oh, we need more copper, although there's copper over here or it's too risky. So it's the site.

How do you breach that? I guess I. Mean I think one of the most overused terms of mineral exploration is risk. I think. Yeah. Like when everyone says risk, I always like to ask the question like, what risk are you actually talking about here, Right. That I mean, like fundamentally mineral exploration is not a risky business, like financially risky because you only lose the money you put in. So you know exactly how much you're going to lose at any point. But now is there other risk in

exploration? Yeah, there's technical risk that could be jurisdictional risk because you're going in a new country and you don't know how to work there or anything like that. It's.

Career risk, that's the. Big one, and I think that's, you know, like to your comment in that, you know, like why people, you know, like why people are pushed by investors to behave a certain way is because if I think if overall the investment crowd maybe doesn't want to take the long term risk of actually finding something or, you know, 'cause mineral exploration in a lot of sense in, in a new search space is a learning kind of

exercise. And so, you know, so our investors, you know, like how many investors are there that would fund companies to learn for a couple of years before they actually do it? I'm not sure there's a lot of them, right? Absolutely, and what a good exploration company should do is explore a project and then say, you know what, it's not here. I'm moving on. Market often though wants to see people persist.

They say, well, you raise the money for, you know, to to do this, that's what you have to spend the money on. Even to the point the ASX says, well, you basically got to show the first two years what you're going to spend the money on. So if you have a concept, you raise the money and in six months you've done the work and gone. There's nothing there technically. You still have to spend. That's right. You know, and so some of these things are perhaps well

intentioned but naive. Yeah. Look, the, the, the reality is that the beauty about expiration is you only ever have to commit funds up to a critical decision point. So if you manage that well, you can be very effective with, with your use of funds. And it has the advantage that, you know, particularly if you're in a sort of larger mining company is it is actually

discretionary. You don't have to spend the money and as opposed to doing a very large, you know, billion dollar transaction, it either fails or it doesn't. Yeah. And and the, the consequences of that, I, I think it's really important just on this, I totally agree with Ahmad. The concept of risk is used, it's a very overused word and it's used in a number of different contexts. So there's probably about 10 definitions of risk that are used in the mining and mineral

exploration industry. And they're all different. But often people will have conversations not realising that I'm using definition risk 7 and they're using definition risk three. Yeah. So this is this is part. Of the problem and you can kind of manifest that like, you know, like say in a, in a group, like, yeah, in a mineral exploration company, you might have someone that's operational, someone that's BD commercial and someone

that's a geologist. Now, they may all use the term risk, but in fact, they're actually all talking about completely different types of risk. So even in one conversation, people will just say, well, you know, is it risky from a geologist point of view? He's, you know, they're asking a completely different question than what the commercial person might be asking.

So, you know, let me just use that as one example to sort of illustrate that many people will say Greenfield's exploration is more risky than Brownfield's exploration as an axiom. You know, no one debates it. But actually it's something that should be debated because if you say I'm going to define risk as the probability of an economic return on my investment, there's quite a lot of evidence to say that's not the case.

A few years ago, Mike Christie, who's the boss of exploration for First Quantum. Just did a very simple study, looked at all the copper mines that had been found over a period of time and looked at whether they were greenfields discoveries or brownfields discoveries. And remember that probably 70 or 80% of the dollars went into brownfields and found greenfields found by far away

more copper, right? So is it more risky because people confuse risk with the, the probability of an individual opportunity being successful, whereas risk from an investment perspective is a portfolio level concept, right? Because you're not just targeting 1 greenfields project and continuing to do that forever. So that and they often confuse the the the risk profile of high, high profile, very successful periods of brownfields exploration with the overall profile of the

greenfields exploration history. Yet we know that in in most situations, periods of successful brownfields ultimately then replaced by periods of unsuccessful. Why? Because you're depleting the search space. That that flies massively, I think in the in the face of a commonly held view. The brownfields is how you how you yield better results. What? Why do you think that is the commonly held view? There's a period of time where

that really works. So if I've made a Greenfields discovery in a new terrain, right, and I don't know much about it, it makes sense for a period of time to focus all my resources there and find all those additional deposits because that's the sort of embedded option value really that relates to the original greenfields discovery.

So what you're really doing is, is just optimising the value of the original greenfields discovery, because when we make our first discovery, particularly in a, in a new terrain, there's often a lot more to be found and that, and that's why there's a real value to making those discoveries. But at some point, what happens? And in most companies, in most situations, money continues to get spent beyond the point where it's best to stop spending it there and spend it somewhere

else, right? And does that sort of analysis take take into account the fact that you have economic advantages from discovering copper or whatever you might be looking forgiven the the sort of latent infrastructure in and? Around absolutely and that and that's so in, in the brownfields environment for those reasons your success threshold is a lot lower right. But at the same time what you are doing is ultimately only incrementally supporting that

existing operation. So that's fine, but what you're not doing is investing in finding the next one. Yeah. And to to sort of beat this out, you've you've spoken about advanced projects with with a bit of disdain and you've highlighted two types of risks, you know, high risk type projects and no hope projects. I loved how you sort of, you know, put forth that that

concept. Can you kind of expand on that because it's a, it's a topic that comes up a lot on the show and you see the headlines, advanced exploration project or you know, yadda, yadda, yadda. And money just continually gets sunk into it. People know about it and they think, oh, maybe in a slightly better environment cause the yeah, the commodity price has gone up. You know, never mind the fact that inflation has ripped

through in that. Well, I think that's exactly right, Jonas. So, you know, we have these projects and I it, it didn't, it didn't make it before, but you know, now the commodity price is higher. So maybe now it's economic, but as you say, usually costs come up at the same time. But the other, the other issue with those sort of projects is there's an unfor because the dominant dynamic of our industry is the price cycle, right?

If you think about what typically happens rising price cycle, we dust off this dormant project in junior company, you know, blue sky mining and then we go to the market, get everyone excited, you know, the share price goes up. And then if we're really unlucky, if the shareholders are really unlucky, there's a decision to try and develop this thing. And, and so we bring all that capital in and we build the mine just in time for the price to

crash and the down cycle. But it's also, I think one of the reasons why advanced projects get recycled is for the same thing where it's easier to go to the market with a project that, you know, like has a defined resource or has a study or, you know, like, and, and I think, you know, like that's kind of the argument that in that a part of the cycle, it's much easier to go to investors and go, hey, we've got an advanced project, you know, meaning it's much further along

the line. But in reality, you know, like there's a reason why, you know, like John calls them no hope projects. I called them stalled projects. You know, there's a reason why that project has stalled along its development line is because it has some fundamental flaw which prevented it from going becoming an economically viable opportunity. Now that might be commodity price that that's OK. You know, like commodity price goes up, all of a sudden it becomes economic.

That's totally OK. But other times there are some fundamental flaws in these projects which which they haven't solved. And people go, well, you know, like price is high, we're going to dust this thing off. And look, it's now advanced and it's on the development path, but it's not because it has the exact same problems it had in the last like cycle. No. There's always a new cycle of investors to run through it though. Yeah. Well, yeah. Well, and the other thing is the

project often changes its name. Yes, I was going to. Mention the company as well. Because you kind of hope the next batch of young investors don't even remember that. Oh, this is exciting. Yeah. And John just linked into that as well. You talk a lot about behavioural psychology as well that probably influences these these biases companies and investors and that they have. What's your thoughts on that?

Well, you know, I'm a, I'm a big fan of the Kahneman work, the the behavioural psychology and, you know, it's a key part of what we teach in our, our senior exploration management course. But you know, one of the things that that that Kahneman looks at is how people make decisions in the gain frame and in the loss frame. And they make decisions based on whether there is a high degree of certainty with the outcome and there's a risk that you won't get it or there's really

not much chance. And you see different behaviours. So in some of those quadrants you see risk seeking behaviour. So, you know, people buy lottery tickets because not much chance, but but also it's, it doesn't cost much to play. And I think that's sort of the rationale between, you know, investing in like junior companies or whatever. On the other hand, you know, we, we also see this behaviour where it's a relatively high certainty

loss frame. For example, a mine is running out of ore and it's often that's the only time management get interested in funding exploration. They should have been doing it for 20 years. But in the lost frame, people will end up taking bigger risks. But I, I do want to say something about behavioural psychology and you know, this concept of the fact that we make decisions in life as humans that are not risk neutral, right?

So a risk neutral decision would be, you know, I've got, you know, 1% chance of getting $100 million is equivalent to 100% chance of getting $1,000,000, right. So those are identical in a risk neutral perspective. But I think for most of us, if we were given that chance, I'd go, you know what, I'll take the $1,000,000 and the 1% chance of getting 100 million I'm going to leave behind.

So we often risk discount and one of the contexts that we risk discount in is when the actual probability, yeah, the value of something which we can say the expected value is probability by what it might be, might be high. But because that probability is actually low, like in an early stage exploration project, we discounted. So what we see is that early stage exploration projects are often, you know, and this is the good ones, you've got to philtre out the no hope ones, right?

But the good ones are often valued at at quite low values compared to what AEMV would say they should be. OK. So and actually after discovery, they're often valued higher. But what that means is there's a very interesting human psychology creates a very interesting arbitrage opportunity for investors in that if you have the the wherewithal, if you've got the capital to be able to take the risk that a number of these

things are going to fail. But ultimately you could be successful as a portfolio, you're going to always do better being on the left hand side of that discovery hole, right? Because you're in, you're investing at at a much cheaper price than on the other side. And you could just play the odds game to. Some degree, right? So, so that's the logic for why, you know, large, large companies with big balance sheets should in fact do that.

But this is this is I think an important point in that, you know, like at some point in low probability success rates, you have to play the odds at some point to to succeed. You know, like you can't, you either have to pay the odds or you have to play a very long game, right? So you're so taking the bets, but you're taking them over a

long period of time. And I think, you know, like one of the, the frustrations I think I see is that a lot of people in mineral exploration are actually doing the opposite, right? That they're, they're taking very few bets, you know, like one project and they are putting all their hopes on that one project to kind of get get to the line. But fundamentally that project almost always has a low probability of success, you know, like that that hasn't

really changed in that sense. But it's just that their perception has changed about it because they think, and this is often a problem with I guess technical people in the industry where they think that project is the is the one, you know, they have their false hope and that's OK. But commercially, you know that or investment wise, you know that that's probably not going to pay out in the long run.

So there's this. This, you know, unease between the the risk that companies outwardly express that they are going to take, that they want to take, whereas their approach is actually quite timid. This is something you've spoken about in. Yeah, Richard Taylor, who got the Nobel Prize for economics, I think it was in 2015. Yeah. One of the things in his book he, he, he, he calls it bold targets, timid choices.

There's a company that comes to mind, guys when we're talking about grand objectives, but not timid action. I'm talking about grand outcomes and that is bloody Greenlands. Great Great Grand is like sort of shortfall Greenlands. I think, yeah. In in a way. You're absolutely right. One in the. Same. Yeah, one, one in the same. And these guys, you know, you open up their website and they got some of my favourite words on the whole planet.

Turnkey. Solutions and the video how goods the video lie over the friggin damn mate sensation. It just reeks of water. These guys bloody do it all. Any any water related problem you've got, these guys will sort out. You want a day water? An open pit? You want a day water an underground? You want to transfer water across your mind site? You want to line some ponds? Want to lay some pipes? These guys will do it for you. Mate they will even drink water and make you less dehydrated

like that is how good they are. Like they are absolute water magicians. God's work the best way. Absolute doing God's work. So my cheers Greenlands. Go, Greenlands, Go. Australia hydration kings and.

Let's go back to your episode. And can you expand on this in the, in the context of major mining companies out there that have, you know, not just the, the small one asset companies, but the, the majors out there that do have the ability to have, and they do have a, a portfolio of assets that have the capital to, to pick and choose how they go about it. How would you sort of guide them or tweak their their decision

making if if they came to you? Well, once again, I get the point I made a little bit earlier, right? I think it's understanding where you want to be on the risk reward curve, right? So there is no such thing as a free lunch, right? We all know that if you want a really big reward and you know the discovery of a world class or deposit is a massive reward in terms of sort of the

multiples and the uplift. But it goes without saying that the risk or and I define risk here in the sense of the probability of that occurring is going to be relatively low, right. So if we think about this risk reward curve, I would say that as a big company, work out what you need to be and then work out what that means in terms of risk. So if you're a BHP and your portfolio looks the same as, I don't know, an IGO or a company of a 10th the size, it's probably telling you there's a

problem, right? But what I was getting to before the, the, the challenge we have is what economists call a failure of agency, because at the end of the day, there is no entity called BHP who's making decisions based on what BHP needs to do. There's a whole lot of individuals making decisions based on, you know, a range of factors, including, you know, what, what, what's rational to them. And I'm not just picking on BHP, but just, you know, just because they're the largest mining

company in the world. But but that sort of logic. And I think, you know, like to back to your question about like why behavioural psychology or economics, you know, matters in this space is because, you know, like, so yeah, like the condiment of these guys have talked about like a number of kind of heuristics that people use. And one of the ones I think, you know, like aside from the one that John's mentioning is this thing called the availability

bias, right? Which is that people will answer the the question that they can instead of the one that they should. And so so when you ask, you know, like when you ask someone in VHP be like, you know, like what do you actually need to do to find a world class asset? Well, the answer is that they have to take on the commensurate level of risk in order to go and do it.

But the way they the answer is by answering the question of what they can do. And they go, well, actually we'll go look around our existing asset for another world class, you know, but that's not like, you know, that's not the question that need need to be answering. Can incentives overcome this? They they, they have to be longer term and and they also have to acknowledge that there is a component of lacking here with with good work.

So, you know, it's like I said before, exploring a project that was a genuine concept and realising that we need to stop and moving on. That's something that is actually behaviour that we do want to reward. Is it being rewarded I. I yeah, yeah. And I think I mean, like the short answer to your question is yes, right. Because that's, we know from the field of behavioural economics, that's how you change behaviour

by incentivizing. Yeah. So John mentioned Richard Haley, he has also another thing called the dump principle problem or the asymmetrical risk problem. And yeah, like so to your question about incentives, yes, they can overcome that because in Taylor's example, you know, he kind of expressed that he was in a multi conglomerate kind of media company and he asked the CEO and the CEO wanted to take a

high level of risk. And then he asked all the managers that sat underneath and they didn't want to take any risk at all. Right. And the fundamentally it came down to that if you were a manager and you took that level of risk and it didn't pan out, you will probably lose your job. Yeah. It's fascinating, right? Because the the behaviour you want to incentivize them for is to take the appropriate amount of risk. You know, everything else. Everything else staying constant.

Yeah, but but then. Doesn't mean they'll be at an individual level. Successful, but you know, but the outcome of taking that risk can can then not be career detrimental to them either, right? You can't have it both ways. You can't tell someone take a lot of risk which is going to have a high degree of failure. But if you fail, I'm going to sack you. But like, that's not the right way to.

So in that Taylor example, right, so the C, the CEO wanted to take all these projects and I think there was something like 10 executives and each one of them was told, well, here's a project that if you invest $1,000,000, there's a 50% chance it's successful and you get $3,000,000, right? And a 50% chance you, you lose it all, right? And the CEO said we should take all of those and very, very few of the individuals wanted to because 50% is a pretty high

probability, right? One in two that you're going to lose it. So, and, and that's said this whole idea of risk discounting because pretty obviously 50% probability that you're going to get three times your investment back is EMV positive scenario, right? So in a risk neutral world, we should take all EMV positive scenarios, but we don't because because of risk and risk is ultimately an individual thing and it's ultimately a

psychological decision. So we, we don't just want to talk about the, the issues around there and the problems with exploration companies and what the industry faces at the moment. And you know, thankfully you've, you've thought a lot about this, John, and you've put forward a really sort of succinct and interesting paper on this idea of an exploration aggregator. And I I believe this was written sort of late 20/10/2016. Something like that. I think I, I spoke about it at PDAC in 2016.

Yeah, yeah. So the basic idea there, it was actually to thinking through some of these challenges and and feeling like as a global industry, we did not efficiently allocate capital to this really important task, which has only become more important of Greenfield's exploration, right and finding, finding these new mineral deposits. And I think just to interject there, John, one of the, I think fundamental things about the funding is to say, yeah, there's

two schools of thought. One of them says that, you know, we don't have enough funding. The other says that we actually have enough funding is just allocated badly. Yeah, like to some degree. And I think like you know, and I think that's an important point in your model is that it's not advocating that we need massive amounts of in increased investments, It's just that the investment we have could be better utilised. Absolutely.

The agents around, you know, we may, we may need a, a bigger global quantum, but to do that, we need to demonstrate the results. And you know, you can sit down and, and, and do the numbers where you kind of say, well, how many big deposits are being found each year? And they're all like worth a certain amount. How much are we spending as an industry? And those numbers don't look that good like they they have,

they're, they're quite high. You know, it's like probably of the order of 200 million US just for any type of deposit, not a not a tier one. And it's probably something like 8,000,008 billion for like a, a tier one. But the problem with all that sort of analysis is that a very large chunk of that money, you know, the global exploration industry spends. It varies of course, but you know, somewhere of the order of 10 to 15 billion US a year.

And a very large part of that money is, is not focused on finding new Tier 1 deposits. Exactly how large, I don't know. If I had to guess, I'd say probably close to 90%. Now some of that's for good reason in that the money's been allocated to, you know, around existing operations and so on.

Some of it for less good reason. It's being allocated because to projects where there is an opportunity to raise capital or some of it is because there is an ecosystem in our industry and below the level of tier ones, you can, you know, there, there's viable companies finding smaller stuff, but that doesn't really solve sort of global problems and it it's not got that sort of tier one type value creation. So I guess my concept would be being selective, right?

So part of the exploration aggregator model. The the first point is that you you need the skill set in the aggregator to make sure that the. The gating process is that the only thing that ever gets funded are those projects that have the genuine opportunity to find the tier one, right? So that's the first thing. So you improve the odds, essentially. Oh absolutely You're not. You're not spending money on things you know are have no hope of ever getting.

Anywhere so, so just to be very clear, I, I, you know, you, you obviously want to apply your best science. And if you do that, you know, some projects might be better than others, But the reality is that I'm, you know, I'm not, I'm not saying you can be too, too sophisticated at that early stage in saying, well, this one's maybe a 1% probability, this one's a 1 1/2 percent probability or whatever it is. But what I'm saying is you want to cut out anything that's a 0%

probability, right? So that, that, that's, that's the key point. You, you want to, you want to reduce it to those things that have, you know, a genuine chance. That's the first Philtre. The, the 2nd philtre is it has to be managed as a portfolio. And you, you, you need that capital pool that yeah, there's concept of, of gamblers ruin. So even if something is EMV positive, right, you might go broke before you get there. And your ability to avoid gamblers ruin is a function of

your pool of capital. So you need a pool of capital to be able to manage this as a portfolio. And your bet sizes, right? That's right, That's right. And the, but the absolutely critical thing about bet size is you've got to manage all your projects with decision point planning, right? So this is, this is getting into the not the micro, but a really fundamental concept. It's not like I've got this exploration project and I'm going to spend 20 million or 30 million on it's like I've got

this exploration project. It could be the next Escondida, but after I've spent, I don't know, two or three million doing these drill holes, I will know whether an Escondida is there or not. Now, if I'm unsuccessful, it still could be something small. Yeah, but I know it's not the big one. Yeah, right. That's right. So and that's your decision to kind of walk, right? That's right.

You know, if you're not going to get that pay off, yeah, then you're not, you know, committing funds just for the sake of because that's the only project you have or, or whatever other kind of metric that comes in. And the, the sort of the third aspect and why I call it the aggregator is, is I think, you know, one of the things we learned from the history of the exploration industry is it's very hard to do things as a big sort of global conglomerate because there is a real value in

being close to the ground, you know, close to the, the local people, close to the local geology. And you know, I remember a few years ago there was a study on gold exploration which showed the most successful explorers were the ones that were focused in a particular region. Makes a lot of sense, right? And the reason why it makes a lot of sense, and I'll, I'll come to this in a minute, is the

learning curve, right? But how can you simultaneously have a big global portfolio, but also have, let's call it local expertise, local skill set, local learning? Well, you've got to support a diversity of organisations. So you know, whatever this sort of overarching source of capital is. And I think the BHP explore model is, is, is sort of one model globally, which is kind of trying to do this at the moment. And it, it, it seeks, you know, high quality opportunities from around the world.

Whether it's got the critical mass it needs yet, I, I don't know. But I think it's it, you know, it's a very good step in, in the right direction. But you need to be able to support a diversity of groups that have that local expertise, that local knowledge, so they can be effective. And then fundamentally, there needs to be a commercial framework, which is win win, right? So the larger corporation obviously ultimately wants continuity of its business by

getting access to these things. But it has to be has to be prepared to give enough away. Because you think about why someone invests in a junior exploration company doing exploration, it's not for like a 50% return on their money, 100%. It's the, the, the small, but non 0 probability of a very, very large return. So it's very important that

that's not not capped. So but just what just just sorry, I'm learning because one of the things about exploration is that if you look at sort of average success rates, it doesn't look economic, right? But if you think about one of these curves of I'm going to explore 100 projects and it's going to cost me X and what's the MPV of my programme, what those models imply is the probability of success of your 100th project is the same as your first project.

And what that implies is that you haven't learned anything. And in real life, if we're doing exploration, well, we're exploring an area, we're unsuccessful, but that information is fed back into the next set of targets we drill and the next set and we improve that probability of success. So that the learning theme, that that's the key, that that's the key juice that that drives this and why, you know, persisting in local areas or persisting around a particular commodity type is

so critical. And I think this is, you know, like this last point about the learning curve is I think when we look at companies that were really good explorers, that's I think one of the, you know, like in the, in the stuff that we did in our podcast, that's one of the themes that kind of comes out is that actually they kept a, a group of people together for enough time so that the learning could kind of bounce around between them to a point. And that, and that's kind of a,

and it's not a nebulous concept. Like, you know, if you think about sports teams, you know, like the teams that are really good, you know, they tend to have in an organisational culture or, you know, like the organisation is set up a certain way, whether that that learning feedback loop is kind of getting passed around. You know, like if they're drafting players, you know, they learn from the mistakes that they've made. So they're not making the same dumb mistakes the same time again.

Whereas organisations, yeah, like in sports organisations are really easy to look at when they go through this period of, you know, like the board is cleared out, all the executives are cleared out, the coaches sacked, all of that stuff. You can see that they don't have great like success rate in that. And you can think about, you know, if you're a basketball fan, you think about the San Antonio Spurs or something like that, you know, a massively successful organisation for a

long, long time. And they've basically kept the same people there for for a large period. And that's kind of like the learning curve model is that if you can keep them around without having to sack them every like three or four years, then you know, like that's kind of the, the, the critical mass you want to build, I think. The Chicago Bulls might be a a slightly better example there as

well. And you can sort of see there's a, a long teething period and then eventually, you know, the, the flywheel starts humming and you get championship. After that, and I think that, and then that's kind of the concept is that, you know, like you like exactly the point you made is that there are there is a period of lean years because you you're still figuring it out. You know, like in a sports organisation, you're figuring out your drafting strategy and all these things.

And in middle exploration, I think when you go into a new area, you're still figuring this thing, these things out, right? You're figuring out which areas you can really work in, the type of techniques that work best, you know, like how effective you can be from a dollar point of view in exploring in certain areas. And so there's this, you know, basically flat line kind of payoff period.

But then when you get to that point, it's kind of like the Chicago Bulls model is that the success comes really quickly after that because you've now amalgamated. And if I can just sort of make one technical point about learning, the most important thing to learn is what is a false positive, right? Because mineral expiration, it's a low base rate environment, which means that the targets that we test very rarely have what we're looking for, which is

an economic or deposit. And simple, you know, Bayesian probability tells you that in that environment, the key factor if I'm looking at an anomaly and deciding whether it's associated with an ore body or not is the false positive rate of that anomaly. In other words, how easy is it to create the same anomaly that's not an ore body? And that has some really important consequences.

So I like to say that, you know, when my daughter was 10, I taught her how to assess ASX releases of exploration companies. Very, very simple method. So go to the page where they have a plot of all their targets and count them up. And if there's more than three, they're no good. And the reason is all bodies are rare. So if we're going to say this is this is the signature, I've got a geochemical anomaly or a geophysical anomaly, you know, it needs to really stand out to

have a high probability. If we've got a lot of targets by definition, and it's a fundamental output of Bayesian analysis, the targets are not very good. And yet you still get people saying, well, we've got lots and lots of targets. That's that's a good thing. Particularly like geophysics, like, yeah, this is a classic one where they go, we've got 50 anomalies and you go, I think you've missed the definition of anomaly. Anomaly, yeah. That's good.

Well, I, I, the, the heuristic I have is, I like to say that green and yellow are not your friends. And by that I mean, you know, if you've got your map and you're using a typical sort of spectral stretch, you want to have the big red and white dot on a blue background, then you've got a good a good anomaly if you've got lots of green and yellow in that map. Yeah, that's fine.

One comment I wanted to make about John's like you know, like model about the aggregator because you know, we kind of had this discussion a couple of times. And I think one of the the fundamental things why you would want an aggregated model is if you start off with the premise that every dollar being spent in exploration is not the same, then you can see that there are people that are spending dollars effectively and they're people that are spending in

ineffectively. And so, you know, like what you want to start off with. So if you start off with that as your premise, you can say that they are some agents. And you know, John said 90%, you know, Rick has his own kind of the Rick rule has his own percentage of how many companies are lifestyle companies and not really wanting to find things,

right. And so I think that's always the premise that when people say this, you know, like we take the total expended in mineral exploration worldwide and we say this is the amount of metal that we found. You know, like the the basic assumption you're making is that every dollar being spent is the same. Now if you change that around to actually looking at companies that spent effective dollars and ineffective dollars, that rate of return would be much better. 100% right, Yeah.

And and again to to my sports analogy is actually the same right at the start of the season, you have X number of teams, but you know that there's only a handful that are legitimately going to be at the top of the table. And the others are just making kind of numbers up, right, because they're they're not good enough. Yeah. And I think it's the same in in middle exploration. Oh, I was just going to say just

sort of on that theme as well. Do you think that that the nature of the exploration sort of aggregator and the these sort of behavioural economics that we sort of say heuristics, we sort of say, do you think it makes it sort of a more suitable in a sort of private capital market as opposed to public look, I think. Naturally, yeah. I think there is a natural tendency for that to be so,

yeah. Well, like long term patient capital because it's just the public markets just I don't think could could cope with something like this even though it makes. Well, the public markets could invest in the in the in the aggregator in the same way people invest in sort of Berkshire Hathaway, for example, if it was successful, but they probably wouldn't do it until it had demonstrated some success. Yeah, I think those investors are few and far between. Yeah.

But you can see, sorry, the yeah, you can see that in I guess other industries. I think the VC world, you know, like they there is very little involvement in in kind of the startup world, the VC driven startup world from public entities, right. Like they're often the, you know, they're never come in in the early money, but they're happy to come in in like, you know, series BC whatever after that. But yeah, that I think, I think that is a fundamental kind of constraint.

I want to just really tie this into a real world example because you've, you've put all this, this work in, but what we've seen since this paper come out is like you say, BHP explores programme and you know it, it, it is remarkable to me at at every turn in incentives are just in your face and you, you highlight there that you need to incentivize the, the smaller company, whether that be the people, everyone at every stage needs to be incentivized by the ultimate outcome.

Now BHB explore has actually started to do this. They've had a couple schools now or groups of. Cohorts, I think they call. Them cohorts that that's the one. And I mean in your model you put forward the example that it can be a major mining company, it could be a direct agent, it could be a specialist third party. Do you think a a BHB is the the best type of company to do this? And given that they've now put this into practise, where would you sort of guide them on

improving what they've? Done well, first of all, I think it's great that they're doing it because I, I think they need to do it. And one of the reasons they need to do it is I actually don't think we have a globally successful model. And I've worked in, in large global companies have tried to do global exploration.

It's very difficult to do as as one company there are there, you know, there's a lot of overheads, there's an increasing amount of internal friction that prevents that being done. So. Just the also just the level of organisational complexity you need to work in, you know, Australia at the same time work in the high Andies, you know, like it's just not like it's a complicated.

Exercise, yeah, yeah. So, so I, I, and I don't, I don't think, you know, and if you think about the history of our industry, you know, when I started, unfortunately over 40 years ago now, but we didn't really have this concept of people exploring globally. You know, there was only four or five countries in the Western world. People would mostly explore in any way. And if you're in Australia, you explored there. If you're in America, you explore there.

And it was only really after the end of the Cold War and we had this big era of globalisation that we started to try and think about exploring globally. And I think at one point in the late 90s, BHP, for example, in 48 countries, right? And that's 48 officers, 48, you know, groups of people now that didn't last that long. Western mining we're in about 25. It's, it's not really

sustainable. And I just think it's too difficult with, with time zones with as Ahmad says, internal complexities, all the, the, the constraints, particularly around licence to operate issues and so on. So a model like Explorer is probably what is what is required. But there there's a few key aspects that are required to make that model work. One, you need really, really good experienced technical people who are providing that philtre, right.

So you know, you need people who really have been in the industry for many, yeah, this is an industry where it actually matters. Experience matters, the right sort of experience, but it actually is important. So it needs to be guided by that. Secondly, the commercial frameworks need to be such that people want to bring their best projects in, not just the projects they don't think could get funded in the risk capital

market, right? So, you know, to me, that's the test of a model like Explore. Are people bringing a project in because it's their core project, it's the one they really believe in, or are they bringing it in because it's not their core project, they're kind of interested in it and they think this is an alternative Ave for funding.

And that gets back to you know, you know, and I'm not not familiar with any of those sort of details of those commercial agreements, but but fundamentally that gets back to that attractiveness. And of course like everything in life, branding and marketing, right.

So if you have successes and this is a successful model and to be a successful model it has to be successful for BHP and it's shareholders, but also successful for individual companies within that, you know, So by being part of the scheme, companies have to be at least not worse off, maybe a bit better off just by being in it. And then of course, not all of them are going to be successful, but if they are successful, they're going to have have to be seen to have benefited

significantly from that success as opposed to the default alternative which is raising capital on the risk capital market, the public markets and so on. I think I think to your question, like, you know, whether it could be done most effectively the major mining company or or not. You know, like if you take the example out of out of mining into other industries, you know, like say like AVC that does it, you know, accelerate a programme

or something like that. You know, I think the one fundamental difference is that the VC doesn't have a vested interest in the entity that's being produced by the startup or the product that's being produced by the startup. Whereas I think in BHP that you know, like that's where I think you have to have a really sound commercial model because ABHP is kind of facilitating the accelerator programme, you know,

call it whatever. But then at the end, they're also the customer that wants to kind of get right. And I'm and I think they're. Existential for them. Isn't it really ultimately that this programme is successful? That's a. That is a pretty pretty

important distinction. So I think they have to navigate that internally as well as the the companies that are coming to them in a, in a, in a different way I think than a standard kind of accelerator model where, you know, VCs are just coming in as an investor. And then they, you know, like they want to help the company get somewhere, but they don't have a vested interest in that, in that product or that outcome of that of that company. I think that's a very good

point. So that, I think is a challenge of how you do it internally. But, you know, like, to be honest, the best agents we currently have in the industry to do that I think are probably major mining companies, yeah. Well, I think they're the ones with the most skin in the game, right? Yeah. So if you analyse, you know, and I've done this thought process of sort of analysing, who cares, right?

Ultimately, who cares that there's not efficient allocation of capital to global greenfields exploration? Well, the the biggest stakeholders are these large multi generational mining companies, right?

And then that's just like, you know, like if like in the space of exploration, if you're a major mining company and there's not an effective allocation of capital to make new discoveries, then you know, like at some point your business is going to struggle because it's going to have to buy things at a higher and higher premium to add to your, your reserve base or your business base. But at some point, they just won't be the assets that can generate the metal, correct, at

a cost that makes sense. So I suppose just thinking through that one step further, at some point it becomes societal or a, or a, or a governmental issue. And of course, that's something that's changed in my career because it's only been in the last half a decade or so that we've started to see a serious involvement at a global level in terms of governments and people thinking about minerals.

Because, you know, for most of my career, minerals and mining was, was to be honest, looked down on and, and seen as somehow inferior to technology and all, all these other things. And it's just something you took for granted. And now we know that we're in a world where we can't do that. There's no interest like self interest, right?

That's the companies get on it. There's this concept I, I read about, I hear about a lot of these companies from, you know, you know, from back in the day that were really technically focused, that had great cultures and everything and Western mining comes to mind and there's a few others. Do you think this is a rose tinted view on the past or was there something distinctly different about how they operated? I think first of all that there.

I mean, some of it is obviously, you know, there was always those raised tinted glasses, but I think there's some real substance to it. But I think you've also got to see it in in context, right. So one of the things that Western mining did, for example, very concrete thing that I don't think any organisation does on the same scale today is its study leave scheme. Yeah. So it would provide, and pretty much any, any talented geoscientist would get funded for half salary for a year to go

and do a master's. And then in the end, yeah, I mean, I, I got funded to a PhD, for example, I never would have been able to do it otherwise. So I was a beneficiary of that. So there was that very, very significant investment in development. It's one of the reasons why, you know, people used to talk about Western mining as the university to the industry because it did that and it probably did that a lot more than other companies, but but that was a more common

thing. But they held on to the people. Yeah, correct. So, so there's a couple aspects about that. One, it was a world where the culture was more like, I've joined this company and I'll work for them, you know, for a long time to retirement that, that was a different world to, to, to, to what we have today. But the flip side of it is when you invest in your people, you're more likely to keep them anyway.

So I, I do feel that it's interesting that companies today, which are, you know, plus 10 times the sort of market cap of what Western mining ever was, don't invest in, in this sort of training. I mean, if they do it, they do it very, very sporadically. But one of their pillars is people is our biggest resource, John, But yeah. Yeah, I know they're. Far more profitable than than Western. Yeah, yeah.

I mean, I can only give my example, you know, like I remember going into, you know, like my career corresponded with the end of WMC and the start of it being in BHP. And I remember going into a group where there was, you know, like eight of us. And I think all of them were ex WMC people and all of them had been there 15 plus years, right. Like I, I don't think I've ever walked into a group now where you could get that level of of kind of longevity in, in the

company, right. But but to your point, you know, like we're talking about that learning curve kind of kind of model, you know, like I think that was a great thing that they could a, allow people to get better to like train them, but also just keep them for a long, long time in in that sense.

And then that IP stays in the business, yeah, because otherwise that learning curve, as we sort of discussed before, yeah, obviously there's, you know, the physical and the data and all that, but the IP that sits up here is now gone over there and over there and it just stalls that whole. Process so one of the unusual aspects of that western mining system was the concept of the guilds. The geoscientists were in a Guild.

So I might be working as a mine geologist of a particular mine or I might be working as an exploration geologist somewhere. But there was the idea that someone was looking at the whole group of geoscientists and actually making decisions like we're going to send him to a mind for two years to get this experience or they're going on study leave or they're going to exploration. So the discipline was managed

holistically. And you know, what we saw changing in the 90s with the rise of HR culture and and direct sort of, you know, management control that I mean that was seen as and a necrotistic archaic and maybe a challenge to. And a cost item. Yeah, and a challenge to to sort of management authority. And so all that got got dismantled.

And I don't think in large organisations there's much discussion that goes on of, you know, here's my org chart of the 300 geologists I have in this organisation. And this is how, you know, we're, we're going to these, we think these are the talent, these are the ones we have to do it. It's very much individuals fighting their way through whatever silos that exist, whether it's at an operation or in an exploration group.

It's amazing because, you know, there are other industries that that try and do this, but what they do is just make your pay vest way down the track and they try and lock you in. So the fact that Western mining could could do this without just, you know, essentially holding your pay from you. Yeah. Yeah, that's why. And it's also like, you know, to your common alley about like the IP and like there's there's this great book and I can't remember

the author's name. It's called where good ideas come from. All right. And then, and then in the book they talk about that if you look at kind of like the stream of innovation over the last 100 years, you know, like it often develops with this, you know, like one person has one piece of the puzzle and this other person has the other piece of the puzzle.

What you need is that connectedness between those ideas to kind of come together and, and become something, you know, so, so my like view on this is like, you know, like the reason why I think organisations like WMC and like CRA was another one that that was I think successful is because they, they had this right, that they kept that IP kind of bouncing around and hitting each other in, in, in that same

organisation. Now I think, you know, we, we may have still the same number of geologists, but now they're spread out over, you know, 1000 companies. So I think that interconnectedness of ideas probably is not as efficient as it could be when it's in one organisation and it's being managed, like the talent is being managed holistically in that sense, you know. So I think that's kind of the challenge of why, you know, like we sometimes struggle to kind of progress along with ideas in

some way as well. John, the the last thing I want to hear from you and you've, you've touched on this earlier, but AI, machine learning, all these things are clearly the, the buzzword of the last three years. Now I want to hear from you, given your, your sort of deep technical experience here and you, you've spoken about it in the, in the sense of big data and these sorts of things and search spaces. And we're going, we should be going to places that don't have the data.

But what do you think will be the implications from this sort of wave of investment in AI specific to the the mineral exploration field? Look, this should have been the last thing we should have talked about. This should be the first thing we should have talked about that. Look, my, my opinion is extremely limited will be the, the impact. And I, I, I say this both on the basis of empirical experience.

You know, we talked about the last three years there, there've been people, very, very smart people way ahead of the curve doing this over a decade ago, spent probably $100 million without any success. And not because they weren't very smart and not because they didn't have the best technology. So that's sort of the empirical experience.

The the conceptual reason is that I think the critical thing that we need to understand is what defines a big data environment, meaning, you know, big data as in a set of a problem set that is amenable to AI. And in my opinion, where people get confused is I think it's a big data environment if the available data can be measured in the terabytes. But if that available data does not very well represent the parameter space of interest, I I think you've got a problem, right.

Yeah, because our parameter space of interest I think is a poor data environment. So conceptually, I don't think AI can ever do very well at targeting in these poor data environments. In principle, what it should be able to do is help us learn in our data rich environments and extract patterns from that. So in principle, I accept that as a possibility. But I have to say I haven't yet

seen any good examples. And you know, some of the companies I'm involved with have invested in, in some of this. And to be honest, we've been disappointed with the examples. But I'm not an AI specialist so I I don't know exactly why these things have not worked but but my just lived experience so far is I haven't seen anything that that's added value. And I think to like to the comment about like why I think

it's somewhat struggle. I mean, John and I've talked about this a fair bit where, you know, like we get approaches by people trying to come in and you know, like apply and more AI machine learning approach. And I think one of the, the, the fundamental issues I think comes from is that, you know, like, like John said, in mineral exploration, we are very data

poor environment. You know, like we collect data, but we collected in, you know, select areas quite well, but we don't like, we rarely collect holistic data. You know, the data resolutions are always quite different in different parts of what we are trying to solve, unless it's a very small area, then you know, like maybe someone flies a geophysics survey or something like that at the same resolution. So there's two kind of problems.

One is that we are a data poor environment and B, we, we have this, I think changing rate of false positives, right? Like once you, you have to have a certain level of testing to figure out whether the anomalies that you've identified are appropriate or not. And so, and machine learning works really well when you have a large base rate of, of a training data set. You know, we don't always have that, you know, we're always tired to build this as we kind

of go along. But one of the fundamental reasons, you know, like, like I've been guilty of applying a lot of AI in in, you know, expression with limited success. And one of the issues I think I find with it is that, yeah, like AI machine learning, I think mineral exploration will be really good at interrogating the data sets when we have them. But often the challenge in mineral exploration is identifying where you should go collect data sets.

And I don't think that is a question that will be best answered by machine learning. Unless we just accept that we're going to spend millions of dollars collecting data sets everywhere at a set resolution, you know, like how we want to do it, then I think, yeah, maybe we can take our intellectual insights of what's an anomaly and what's not an anomaly and model it into a a, you know, ML model. And then you can go and look for that. But I don't think we're there yet, right?

Like we just don't have the amount of data. Look, I think the the issue of data is an important one. And I've had a number of of, of conversations, you know, the government agencies who want to improve their prospectivity. And it's like, well, should we invest in all this AI? And you say, well, don't do that. Invest in getting your fundamental data right.

So for example, if you're dealing with an area that doesn't have, say, something like one kilometre grid gravity, you can't do best practise targeting. So to me it's, it's kind of sort of irrelevant whether you're developing your best AI to look at the magnetics and all the other datas you have when you're missing a key data set. So I have a very, very strong bias to saying if you've got an increment of capital that you want to invest in moving a problem forward, collect that data.

And yeah, we started this conversation. Jonas, you asked me about my 4 rules and I only really got to rule 2. Yeah, I was just about to say #3. Rule 3 was collect your own primary data in the search space of interest. And to Amad's point that he was just articulating, working out what that search base of interest is, is also an intellectual process and in fact a key value creating process. But once you've done that, go and collect your your own own

primary data. And rule 4, of course, something we've touched on again and again is learning from, test those targets and learn, learn from that. So I will any day of the week, say in most situations, you'd be better off investing in collecting primary data. It has to be a primary data set that really helps you with what you're doing. Things like gravity are good because it goes to the fundamental architecture of the crust, which is which is always important.

But you know, just coming back to, I think an interesting analogy when we think about domains where, you know, AI, deep learning or all of these things can work and they aren't, is the comparison between weather forecasting over the last few decades and earthquake forecasting, right. So these are both very, very complex, non linear systems. You know, weather forecasting is a classic chaotic, you know, the butterfly flaps its wings and you know, the typhoon in in, or

the tornado in Texas, whatever. But we've actually got a lot better with weather forecasting. Weather forecasts are quite reasonable now. And that's through, you know, massive computing power and making all these models and, and doing all this. On the other hand, earthquake forecasting is still really poor. And we had a big earthquake in Christchurch going back a few years ago. Devastating it was on a fault that wasn't even recognised. It wasn't even in the model,

right. So with weather forecasting, we now through satellites and whatever, we have a pretty good characterization of our system, IE the atmosphere and the ocean atmosphere or the land atmosphere interface. So, so we've got a pretty and we'll get better, but we've got a pretty good model for it. When it comes to something like earthquake forecasting, we have a very poor model of the relevant search base, which is the rock mass underneath us.

And then you think about mineral deposits, it's not just forecasting 1 earthquake, it's forecasting a bunch of earthquakes that happened 2 1/2 billion years ago, right, so. And the time interaction and all these type of things. And so I think this is kind of the the concept like, yeah, like I think machine learning solves computationally heavy tasks.

Like, you know, that's where it's got to, you know, we're not at a point now where the true artificial intelligence that, you know, we've created something that that that can kind of come in and, and solve that problem. And so the domains where it's really struggled is where you actually need that. The answer is in the intelligence of how you contextualise data and review it and do that. And humans are still, I think, far better at it, you know, than than any computer we have

currently. I just had one final question reflecting on sort of what we've discussed today. Do you think there is really a case for a single asset exploration company? That's a good question. A Greenfield's expiration. No, no, I don't. But I think that pretty much you have to. I mean, one of the issues here relates to the quantum of capital like that can be raised. And I don't know whether any of you guys have heard of Mike Etheridge. He was a big leader of our industry about 20 years ago.

He wrote some pretty influential stuff and he was the first guy to really sit down and try and provide some quantitative analysis around exploration. And he actually published a paper, I think it was about early 2000s, where he bemoaned the fact that when you looked at the dynamics of the industry, the typical IPO raise was 4 or 5,000,000 bucks. And that was pathetic. Of course, it's still about four

or five billion, correct? Yeah. And that four or 5 billion bucks is now worth about half as much as what it was. That's how when ASX costs have only gone up. Yeah, and ASX costs, heritage costs, ground costs. So, you know, the, the reality is that you know, companies, you know, they float, they raise money. This is my project, right? And I suppose that's what the investors are investing in.

But realistically, what you are always investing in is a team that hopefully will explore that project. And if that fails, if you're not, which it probably will if you're not very lucky, it will then get the next project and the next project and the next project right. I think that's the the perfect spot to leave the conversation. Thanks a lot for your time, John and Ahmad. This has been a fascinating conversation. Appreciate it. Thanks a lot. I love this stuff. Cheers.

Alrighty, thank you very much Ahmed Ali and John Ronsky. I was a great chat and. Thank you to you too for you smashed it out. No, I loved it lots. And yeah, no, there's certainly sometimes it's easy to forget all the, the heuristics and biases we have as a, you know, investors and mining companies have. So that was, that was a really interesting pace that I, I loved about that chat. Absolutely fascinating. We got a couple other people to thank. Oh. I love to think of those people.

Access mining technology MMS we had in the show. We also had greenlands in the show. Give them a buzz verify smack power and technology, DSI underground, Silverstone CRE insurance K drill and use spark. Use it. Get on to Spark. Have a good weekend, money miners. Information contained in this episode of Money of Mine is of general nature only and does not take into account the objectives, financial situation or needs of any particular

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