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Righto buddy miners, welcome to 
another bloody JD and LEGC 

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spectacular brought to you by 
Axis Mining Technology, the 

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trusted advisor for Drill Isle 
survey instrumentation and their

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best people to talk to on the 
phone about it 'cause there's a 

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guru on the end of the line 
every single time. 

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Love your work Axis. 
Oh, that's it. 

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Nice. 
So this was a bit of a little 

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pre digger's amble that you too 
kindly did while I went to a 

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golf day. 
Thank you very much by the way, 

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I was doing some DD out there. 
BDD. 

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DDDDD. 
Who we got? 

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So we've got John Ronsky here 
today and we've also got Ahmed 

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to help us navigate the 
conversation. 

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John is a super switched on 
geoscientist and Ahmed helped us

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kind of get through that more 
technical part of the 

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conversation. 
I'd listen to John on a few 

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podcasts he'd done in the past 
and I thought the ideas he had 

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were absolutely fascinating. 
This is a guy with a couple 

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decades at at Western mining few
years in there at BHB. 

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Then he's been running his own 
bit. 

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He's been teaching out of out of
UWA for quite some time. 

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And he's, he's got a few 
different talking points that I 

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find absolutely fascinating in 
and around our kind of home 

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ground of talking about the 
funding of mining companies, 

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getting exploration projects 
online. 

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And we're going to talk through 
things like the. 

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Search spaces. 
Search spaces, that's one of 

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these sort of big features about
how companies go about 

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exploration. 
He's got models and you know, a 

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lot of it kind of ties in with 
what BHB Explorer has kind of 

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done, although this is a concept
model exactly. 

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He'd come up with this concept a
good sort of decade ago now. 

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So I think with that, we'll 
we'll rip into it. 

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Right now, good stuff. 
Here we go. 

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All right, money miners, we've 
got a we've got a special chat 

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here with John Ronski, Ahmad 
Ali, a bit of a different line 

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up today, but we're pretty 
excited to to get into this. 

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John, you've, you've spoken a 
lot in, in over your career 

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about a topic that's sort of 
near and dear to our heart. 

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But the way I want to kind of 
segue into this is that that 

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crossover between business and 
the science of exploration 

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discovery. 
And you've spoken about four 

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rules for exploration companies 
in the past. 

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And that kind of leads us into 
talking about search spaces and,

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and the funding model for, for 
juniors out there. 

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And I want to start by hearing 
about search spaces these these 

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four rules that you have for 
exploration companies out there 

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and then kind of go from there. 
OK. 

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Well, the first rule is decide 
what you're looking for, because

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you've got to focus on something
that's going to make a 

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difference to you as a business.
And if you're BHP, that's one 

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thing. 
If you're a, a, a junior, you 

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know, trying to break into the 
industry, that's another thing. 

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So you have to consider the 
thresholds, you have to 

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consider, you know, the, the 
capital, you have to consider 

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the risk that you you can take. 
So for example, if you're a BHP,

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you have to be looking for a 
very, very large deposit, 

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something that can replace an 
Escondido or an Olympic dam. 

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So yeah, we in life have this 
sort of risk reward 

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relationship. 
So if you want something that 

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has a very, very high reward, 
you have to be taking a high 

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risk. 
So if you're genuinely in the 

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game to find one of those 
deposits, it influences your 

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strategy. 
So that's the starting point. 

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You've got to decide what you're
looking for and, and what's 

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going to make a difference. 
The second point is you have to 

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identify a valid search space 
where that could be. 

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You know, it's no good saying, 
well, I want to find this giant 

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deposit, but it has to be within
50 kilometres of my existing 

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infrastructure. 
And I don't want it to be too 

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deep or whatever because that 
may well be a search space that 

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doesn't exist. 
So when we talk about the 

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concept of search space, what 
we're really saying is the 

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search space is the intersection
between what we know 

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geologically about what's going 
to control the location of a 

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deposit in space and what we 
know about the economic 

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environment. 
And critically, the history of 

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every bit of exploration that's 
gone on before. 

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Because if someone else has 
already sterilised that search 

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base, it doesn't matter how 
smart your geology is, it 

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doesn't matter how smart your 
detection technology is. 

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We already know it's not there. 
It's a very, I mean, in some 

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ways exploration is very 
Bayesian approach. 

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You know, you start off with I 
don't know, and you collect more

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data and each bit of new data, 
you know, reinforces a story. 

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Either it is perspective or it 
isn't perspective. 

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And of course the big challenge 
with the search base idea is 

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that we find our biggest 
deposits where we have the lease

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data. 
Really, really important 

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concept. 
Kind of an obvious concept, but 

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I restate it now because in the 
era we currently live in where 

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we hear a lot of stuff about big
data and AI, and the idea is, 

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well, actually we've got lots of
data. 

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All we need to do is analyse it 
in a smart way and we'll find 

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the deposits. 
I fundamentally disagree with 

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because we don't find deposits 
where we have a lot of data. 

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We find deposits in volumes 
where we don't have any data or 

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very, very limited data. 
So that's that's a search based 

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concept. 
And I think just to interject 

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here, I think one of the other 
important things about search 

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space is that they can change 
over time as well. 

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Yeah. 
So, so lithium will be one, 

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right, where people discovered, 
you know, tin deposits before, 

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but lithium was obviously not 
invoked then. 

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So no one actually did anything.
So yeah. 

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So one of the things I think 
here is that, yeah, like to 

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John's comment that you often 
find these things where there's 

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no data. 
Well, it has to be data that's 

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relevant to what, what the 
problem you're trying to solve 

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as well is that they, they could
be actually data rich areas, but

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it's just that we haven't looked
for the specific thing like 

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lithium in that data set and 
hence we might have overlooked 

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it. 
So yes, so the concept of search

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space is, is like, you know, 
it's not just a physical space 

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that you will kind of look for. 
It's also a philosophical kind 

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of space and like, well, you 
know, like how do your ideas 

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evolve over time? 
How does the technology change? 

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You know, technology can have a 
fundamental effect on how you 

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find things. 
You know, the detection limit of

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a certain technique gets lower 
all of a sudden, you know, like 

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you can, you can review that 
data differently. 

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So I often find that search 
space becomes this concept where

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people think it's physical. 
They go, oh, yeah, like I'm 

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going to go physically out to 
the edge of the world because no

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one's explored there. 
Well actually search spaces can 

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exist in well explored terrains 
as well. 

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It's just that you have changed 
the the parameters of what you 

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are looking for, hence you've 
opened opened up a new search 

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space in that sense. 
Yeah, No, 100%, Ahmad, search 

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space is, is, it's an abstract 
parameter space. 

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I mean, I didn't want to become 
too technical about it, but 

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there's a number of different 
parameters that will govern 

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whether a search space exists, 
you know, including all the ones

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that you talked about that, you 
know, the commercial regime in a

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country is an important part of 
that search space. 

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But just to to pick up a point 
about different commodities 

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actually now before I do that, 
two points about search space. 

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One, the reason why we coined 
the term search space rather 

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than the other concept of 
exploration maturity, which you 

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often hear people talk about 
exploration maturity, is we felt

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like maturity seemed to relate 
to just how much work had gone 

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on in a particular area. 
And if that work had not been 

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been effective for the 
particular search base that we 

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were interested in, it was 
irrelevant. 

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So yeah, some textbook examples 
from the history of exploration 

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WA, the Cambalda nickel deposit 
was discovered in January 1966. 

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And up to that point within the 
Yogan Craton of WA, no one knew 

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anything about the presence of 
nickel. 

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In fact, no one knew that these 
commodit rocks could host 

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nickel. 
And the world expert said, I 

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know you don't find nickel in 
those rocks because you found 

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nickel in places like Sudbury. 
So that instant that created a 

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new search space. 
Now that that result, that drill

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hole was basically right in the 
middle of the Red Hill gold 

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mining area. 
So it was right in the middle of

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the of a almost on. 
You know, some of those samples 

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of nickel were first found on 
the dumps of old gold mines. 

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And of course the Kalgoorlie had
been at that point for 70 years,

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a major gold mining centre. 
But that reset the search space 

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and the more the most recent 
sort of reset of search space 

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we've had has been the lithium 
boom. 

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So, you know, if we're in a 
world where we're looking for 

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the traditional commodities of 
gold and copper, which have been

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the two most important ones 
we've explored for for a long 

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time, it's a pretty reasonable 
assumption globally to say that 

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not many of these deposits are 
going to be sticking out of the 

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ground with an obvious surface 
expression, right. 

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This wasn't true of lithium 10 
years ago because people hadn't 

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focused on that. 
So you could still go to places 

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like Pill and Gore and say, oh, 
there's a big outcropping Ridge 

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of pegmatite. 
OK, fantastic. 

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Because the search space for 
lithium was much less mature 

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than, say, the search space for 
gold. 

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I mean, people have been looking
for gold around the world for a 

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very long time. 
So you know most of the surface 

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with and you know, one of the 
things to understand about 

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search space is the technologies
we have for exploring things at 

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the surface are vastly more 
effective and cost, you know, 

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cheaper than technologies for 
exploring below the subsurface, 

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even like only a few metres if 
it's concealed. 

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So this sort of. 
Concept it, you know, we're 

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getting right into the the 
geology here, but we come at it 

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from an investment lens 
predominantly on on the show 

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here. 
Is this a concept you think is 

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is widely held in the in the 
geological community? 

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Look, I thinking, I think 
increasingly so and it is 

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actually very relevant to 
investment because if we look at

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the the opportunities for 
investment in say the 

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greenfields exploration space, 
to me the valid search base 

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criteria is a really important 
philtre that would probably in 

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my opinion separate about 20% of
the companies that actually have

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a chance and 80% that probably 
don't. 

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So going to an area where there 
might have been lots of sniffs 

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of mineralization, lots of drill
holes, but no actual discovery 

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and going back to those areas 
without coming up with some new 

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search based concept is not 
going to be successful. 

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But often times, you know, 
investors who don't see things 

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through that lens will put money
into those sort of 

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opportunities, right? 
So I actually think that the 

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search based concept, well our 
teachers course, senior 

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exploration management and one 
of the things I say is the one 

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concept that I'd like you to 
take away from this course more 

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than anything else is the 
concept of the search space. 

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Why? 
Because it's the central concept

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that links the scientific things
that we do in this business with

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the business outcomes, with the 
commercial outcomes. 

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If you don't understand search 
space, you really don't have the

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key central concept to 
understand how mineral 

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exploration delivers value to 
investors. 

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And I, and I think that concept 
about, you know, like why it's 

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important is, yeah, like maybe 
from, if you're investing in a 

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consumer product or something 
like that, I think it's slightly

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different in that, yeah, like 
you can always grow your 

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consumer market in a different 
way. 

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You know, you can sell shoes, 
but you can sell clothes at the 

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same time, or you can sell hats.
You know, there's always 

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something that you can add. 
Whereas I think in, in, in 

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mineral exploration, you know, 
one of the key aspects of why 

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search space is important is 
because they're kind of 

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exhaustive. 
Like once someone has explored 

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an area, it it kind of gets 
removed. 

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It's a non renewable kind of 
yeah. 

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So, so once someone has found 
something there and they've 

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mined it, that search space is 
effectively kind of dead now. 

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Or in order to grow that search 
space, if you want to go deeper 

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or something like that, there's 
an economic parameter that comes

227
00:12:01,120 --> 00:12:01,920
in. 
It's not going to be more 

228
00:12:01,920 --> 00:12:02,960
expensive. 
Yeah. 

229
00:12:02,960 --> 00:12:07,400
It's going to be harder to find 
as a search space matures, you 

230
00:12:07,400 --> 00:12:09,480
know, like the easier things 
should be found first and the 

231
00:12:09,480 --> 00:12:12,080
harder things now will be, will 
be the ones that you'll be 

232
00:12:12,080 --> 00:12:14,200
looking for. 
And there's a pretty startling 

233
00:12:14,200 --> 00:12:16,520
fact, though, that flies in the 
face of that which you said in a

234
00:12:16,520 --> 00:12:20,640
previous interview, John, that 
roughly 80% of money going into 

235
00:12:20,640 --> 00:12:24,360
the ground is spent on depleted 
search spaces. 

236
00:12:24,720 --> 00:12:30,720
Why is this still the case? 
Because the perception of, I 

237
00:12:30,720 --> 00:12:32,960
think it's an incorrect 
perception of risk, right. 

238
00:12:33,520 --> 00:12:39,240
And let me just tell it from the
perspective if I'm a some sort 

239
00:12:39,240 --> 00:12:43,200
of executive in some large 
mining company and I can have a 

240
00:12:43,200 --> 00:12:46,600
programme where I'm going to go 
out into areas with no known 

241
00:12:46,600 --> 00:12:49,800
mineralisation and it might be 
several years before I can 

242
00:12:49,800 --> 00:12:51,920
return a result. 
But that might be what I need to

243
00:12:51,920 --> 00:12:54,120
do to make the discovery this 
company needs. 

244
00:12:54,400 --> 00:12:57,680
Or I can do joint ventures on 
half a dozen projects where 

245
00:12:57,680 --> 00:12:59,720
there's quite a lot of known 
mineralisation. 

246
00:13:00,040 --> 00:13:02,280
And I know that I'll be able to 
report every quarter. 

247
00:13:02,280 --> 00:13:04,400
I've got this drill hole 
intersection and I've got this 

248
00:13:04,400 --> 00:13:07,240
drill hole intersection. 
Which option is lower risk for 

249
00:13:07,240 --> 00:13:09,160
me professionally and 
personally, right. 

250
00:13:09,960 --> 00:13:13,120
And which option is lower risk 
or higher risk for the company? 

251
00:13:13,120 --> 00:13:15,080
They're not the same. 
And. 

252
00:13:15,960 --> 00:13:18,600
So just hang on a minute there. 
We're talking about risk and 

253
00:13:18,760 --> 00:13:20,760
reward. 
And there's one company that 

254
00:13:20,760 --> 00:13:23,440
popped into my mind and that's 
MMS guys. 

255
00:13:23,440 --> 00:13:26,960
Well, that like, well, in terms 
of risk reward, like no risk, 

256
00:13:27,360 --> 00:13:29,520
shit loads of reward. 
That's it. 

257
00:13:29,520 --> 00:13:31,720
They take the risk off your 
hands. 

258
00:13:31,800 --> 00:13:34,280
Yeah, they are the mining 
company, trusted mining 

259
00:13:34,280 --> 00:13:36,960
contractor out there. 
And all I've made, all JD all 

260
00:13:36,960 --> 00:13:40,200
think MMS are that good that 
they probably don't even have 

261
00:13:40,200 --> 00:13:42,280
risk either. 
I think you're right. 

262
00:13:42,840 --> 00:13:44,560
Yeah, absolutely. 
And yet, you know what else 

263
00:13:44,560 --> 00:13:47,920
stands out about MMS guys? 
Bloody tailored service. 

264
00:13:47,920 --> 00:13:51,840
They do they, you know, you've 
got any problem, you just give 

265
00:13:51,840 --> 00:13:54,200
Josh a buzz, they will sort it 
out for you. 

266
00:13:54,200 --> 00:13:57,600
I mean, we're talking about mine
site support, drill and busting 

267
00:13:57,600 --> 00:13:59,760
services, contract mining 
services. 

268
00:13:59,760 --> 00:14:01,600
Obviously there's a few good 
examples out there. 

269
00:14:01,600 --> 00:14:05,160
Just Josh, it will talk you 
through them dry and wet. 

270
00:14:05,160 --> 00:14:08,240
Hire anything else you want. 
And the tech, the Technical 

271
00:14:08,240 --> 00:14:09,600
Support. 
Technical. 

272
00:14:09,600 --> 00:14:11,840
Evaluate the pit mate, don't 
body. 

273
00:14:11,840 --> 00:14:13,800
Try and figure out how to mine 
it yourself. 

274
00:14:13,800 --> 00:14:15,760
Get the miners to figure it out 
for you. 

275
00:14:15,760 --> 00:14:19,760
You're just moving dirt. 
Love your work MMS, get on to 

276
00:14:19,760 --> 00:14:22,160
them this good. 
This is going to be how mining 

277
00:14:22,160 --> 00:14:24,880
contracting is in the future. 
Pioneering. 

278
00:14:25,560 --> 00:14:26,040
Here we go. 
Good. 

279
00:14:26,200 --> 00:14:28,560
Work MMS. 
We better get back to you, Jan. 

280
00:14:29,040 --> 00:14:33,400
I think that the reality is 
that, you know, particularly if 

281
00:14:33,400 --> 00:14:38,400
you're going to fund expiration 
from, you know, the risk capital

282
00:14:38,400 --> 00:14:42,480
market with a fairly sort of 
volatile, fairly volatile source

283
00:14:42,480 --> 00:14:46,880
of capital, you, you, you need 
to provide that excitement. 

284
00:14:47,000 --> 00:14:49,800
Yeah, the idea of you've given 
me your money and I'll report 

285
00:14:49,800 --> 00:14:51,920
back to you in two years time 
when I finish this programme. 

286
00:14:52,040 --> 00:14:55,120
Who invests in that, right. 
So that, so that's sort of the 

287
00:14:55,120 --> 00:14:58,200
tension that that that goes on, 
I think. 

288
00:14:58,200 --> 00:15:00,280
I mean, effectively it's like, 
you know, people will do what's 

289
00:15:00,280 --> 00:15:03,960
expedient, either commercially 
or, you know, from a point of 

290
00:15:03,960 --> 00:15:06,160
view of releasing stuff to the 
market or investor. 

291
00:15:06,440 --> 00:15:09,960
Then I think what would be the 
harder thing to do, which is 

292
00:15:10,080 --> 00:15:11,520
exactly what John's kind of 
talking about. 

293
00:15:11,520 --> 00:15:13,320
Like, yeah, it would be harder 
to go and say we're going to 

294
00:15:13,320 --> 00:15:16,400
raise money and for three years 
we probably won't release a 

295
00:15:16,400 --> 00:15:19,680
single announcement. 
But after that, we'll know, you 

296
00:15:19,680 --> 00:15:21,320
know, people will go. 
I'm out of here. 

297
00:15:21,600 --> 00:15:24,520
Yeah, because there's a couple 
questions I wanted to ask about 

298
00:15:24,520 --> 00:15:28,680
that because there's the the 
concept of the search pace makes

299
00:15:28,680 --> 00:15:32,400
so much sense, right? 
It's it's, it's so logical, but 

300
00:15:32,400 --> 00:15:38,120
actually practically getting 
people in companies to do it is 

301
00:15:38,120 --> 00:15:41,480
such another challenge, right? 
You know, the business element 

302
00:15:41,480 --> 00:15:45,920
comes in people, there's a 
resistance against change. 

303
00:15:47,320 --> 00:15:51,920
And I think the other thing 
which was actually touched on, 

304
00:15:51,920 --> 00:15:55,360
you know, in a great Live Wire 
article earlier this week about 

305
00:15:55,560 --> 00:15:58,000
people are scared to go to risky
jurisdictions. 

306
00:15:58,000 --> 00:16:02,000
And it's often the pressure from
the public markets and, you 

307
00:16:02,000 --> 00:16:07,360
know, public money to it's like,
why, why should I go pursue this

308
00:16:08,000 --> 00:16:12,680
risky, as you know, or good 
asset in a risky jurisdiction 

309
00:16:12,680 --> 00:16:15,560
here where I can just do 
something safe and easy, you 

310
00:16:15,560 --> 00:16:19,720
know, over here. 
And it sort of talked about how 

311
00:16:19,720 --> 00:16:22,680
there's this particular article 
talked about how there's a 

312
00:16:22,680 --> 00:16:26,440
tussle between, oh, we need more
copper, although there's copper 

313
00:16:26,440 --> 00:16:29,840
over here or it's too risky. 
So it's the site. 

314
00:16:31,160 --> 00:16:32,840
How do you breach that? 
I guess I. 

315
00:16:32,840 --> 00:16:34,640
Mean I think one of the most 
overused terms of mineral 

316
00:16:34,640 --> 00:16:36,760
exploration is risk. 
I think. 

317
00:16:37,400 --> 00:16:38,800
Yeah. 
Like when everyone says risk, I 

318
00:16:38,800 --> 00:16:40,960
always like to ask the question 
like, what risk are you actually

319
00:16:40,960 --> 00:16:44,240
talking about here, Right. 
That I mean, like fundamentally 

320
00:16:44,240 --> 00:16:47,600
mineral exploration is not a 
risky business, like financially

321
00:16:47,600 --> 00:16:49,680
risky because you only lose the 
money you put in. 

322
00:16:50,360 --> 00:16:53,160
So you know exactly how much 
you're going to lose at any 

323
00:16:53,160 --> 00:16:55,280
point. 
But now is there other risk in 

324
00:16:55,280 --> 00:16:56,800
exploration? 
Yeah, there's technical risk 

325
00:16:56,800 --> 00:16:58,880
that could be jurisdictional 
risk because you're going in a 

326
00:16:58,880 --> 00:17:01,040
new country and you don't know 
how to work there or anything 

327
00:17:01,040 --> 00:17:01,640
like that. 
It's. 

328
00:17:01,640 --> 00:17:05,720
Career risk, that's the. 
Big one, and I think that's, you

329
00:17:05,720 --> 00:17:09,599
know, like to your comment in 
that, you know, like why people,

330
00:17:10,839 --> 00:17:13,359
you know, like why people are 
pushed by investors to behave a 

331
00:17:13,359 --> 00:17:17,160
certain way is because if I 
think if overall the investment 

332
00:17:17,160 --> 00:17:22,040
crowd maybe doesn't want to take
the long term risk of actually 

333
00:17:22,040 --> 00:17:25,040
finding something or, you know, 
'cause mineral exploration in a 

334
00:17:25,040 --> 00:17:28,880
lot of sense in, in a new search
space is a learning kind of 

335
00:17:28,880 --> 00:17:30,920
exercise. 
And so, you know, so our 

336
00:17:30,920 --> 00:17:34,160
investors, you know, like how 
many investors are there that 

337
00:17:34,160 --> 00:17:36,800
would fund companies to learn 
for a couple of years before 

338
00:17:36,800 --> 00:17:39,200
they actually do it? 
I'm not sure there's a lot of 

339
00:17:39,200 --> 00:17:42,000
them, right? 
Absolutely, and what a good 

340
00:17:42,000 --> 00:17:46,720
exploration company should do is
explore a project and then say, 

341
00:17:46,720 --> 00:17:49,560
you know what, it's not here. 
I'm moving on. 

342
00:17:50,080 --> 00:17:52,960
Market often though wants to see
people persist. 

343
00:17:52,960 --> 00:17:56,240
They say, well, you raise the 
money for, you know, to to do 

344
00:17:56,240 --> 00:17:57,760
this, that's what you have to 
spend the money on. 

345
00:17:57,760 --> 00:18:00,800
Even to the point the ASX says, 
well, you basically got to show 

346
00:18:00,800 --> 00:18:02,760
the first two years what you're 
going to spend the money on. 

347
00:18:02,960 --> 00:18:06,120
So if you have a concept, you 
raise the money and in six 

348
00:18:06,120 --> 00:18:07,240
months you've done the work and 
gone. 

349
00:18:07,240 --> 00:18:08,840
There's nothing there 
technically. 

350
00:18:08,840 --> 00:18:10,840
You still have to spend. 
That's right. 

351
00:18:11,080 --> 00:18:13,200
You know, and so some of these 
things are perhaps well 

352
00:18:13,200 --> 00:18:15,000
intentioned but naive. 
Yeah. 

353
00:18:15,720 --> 00:18:20,840
Look, the, the, the reality is 
that the beauty about expiration

354
00:18:21,240 --> 00:18:25,200
is you only ever have to commit 
funds up to a critical decision 

355
00:18:25,200 --> 00:18:29,480
point. 
So if you manage that well, you 

356
00:18:29,480 --> 00:18:32,560
can be very effective with, with
your use of funds. 

357
00:18:32,560 --> 00:18:36,000
And it has the advantage that, 
you know, particularly if you're

358
00:18:36,000 --> 00:18:38,960
in a sort of larger mining 
company is it is actually 

359
00:18:38,960 --> 00:18:41,040
discretionary. 
You don't have to spend the 

360
00:18:41,040 --> 00:18:45,480
money and as opposed to doing a 
very large, you know, billion 

361
00:18:45,480 --> 00:18:47,960
dollar transaction, it either 
fails or it doesn't. 

362
00:18:48,320 --> 00:18:51,360
Yeah. 
And and the, the consequences of

363
00:18:51,360 --> 00:18:55,720
that, I, I think it's really 
important just on this, I 

364
00:18:55,720 --> 00:18:59,440
totally agree with Ahmad. 
The concept of risk is used, 

365
00:18:59,880 --> 00:19:02,480
it's a very overused word and 
it's used in a number of 

366
00:19:02,480 --> 00:19:05,160
different contexts. 
So there's probably about 10 

367
00:19:05,160 --> 00:19:08,480
definitions of risk that are 
used in the mining and mineral 

368
00:19:08,480 --> 00:19:10,320
exploration industry. 
And they're all different. 

369
00:19:10,640 --> 00:19:13,720
But often people will have 
conversations not realising that

370
00:19:14,080 --> 00:19:17,560
I'm using definition risk 7 and 
they're using definition risk 

371
00:19:17,560 --> 00:19:18,680
three. 
Yeah. 

372
00:19:18,720 --> 00:19:20,880
So this is this is part. 
Of the problem and you can kind 

373
00:19:20,880 --> 00:19:24,080
of manifest that like, you know,
like say in a, in a group, like,

374
00:19:24,080 --> 00:19:26,120
yeah, in a mineral exploration 
company, you might have someone 

375
00:19:26,120 --> 00:19:28,920
that's operational, someone 
that's BD commercial and someone

376
00:19:28,920 --> 00:19:31,040
that's a geologist. 
Now, they may all use the term 

377
00:19:31,040 --> 00:19:33,120
risk, but in fact, they're 
actually all talking about 

378
00:19:33,120 --> 00:19:34,880
completely different types of 
risk. 

379
00:19:35,440 --> 00:19:38,240
So even in one conversation, 
people will just say, well, you 

380
00:19:38,240 --> 00:19:40,400
know, is it risky from a 
geologist point of view? 

381
00:19:40,400 --> 00:19:42,880
He's, you know, they're asking a
completely different question 

382
00:19:42,880 --> 00:19:44,640
than what the commercial person 
might be asking. 

383
00:19:44,920 --> 00:19:48,640
So, you know, let me just use 
that as one example to sort of 

384
00:19:48,640 --> 00:19:53,960
illustrate that many people will
say Greenfield's exploration is 

385
00:19:53,960 --> 00:19:56,760
more risky than Brownfield's 
exploration as an axiom. 

386
00:19:56,760 --> 00:20:00,160
You know, no one debates it. 
But actually it's something that

387
00:20:00,160 --> 00:20:03,800
should be debated because if you
say I'm going to define risk as 

388
00:20:03,800 --> 00:20:07,640
the probability of an economic 
return on my investment, there's

389
00:20:07,640 --> 00:20:09,920
quite a lot of evidence to say 
that's not the case. 

390
00:20:10,760 --> 00:20:13,800
A few years ago, Mike Christie, 
who's the boss of exploration 

391
00:20:13,800 --> 00:20:16,320
for First Quantum. 
Just did a very simple study, 

392
00:20:16,440 --> 00:20:18,600
looked at all the copper mines 
that had been found over a 

393
00:20:18,600 --> 00:20:21,080
period of time and looked at 
whether they were greenfields 

394
00:20:21,080 --> 00:20:23,960
discoveries or brownfields 
discoveries. 

395
00:20:23,960 --> 00:20:26,480
And remember that probably 70 or
80% of the dollars went into 

396
00:20:26,480 --> 00:20:30,520
brownfields and found 
greenfields found by far away 

397
00:20:30,600 --> 00:20:34,800
more copper, right? 
So is it more risky because 

398
00:20:34,800 --> 00:20:40,760
people confuse risk with the, 
the probability of an individual

399
00:20:40,760 --> 00:20:44,360
opportunity being successful, 
whereas risk from an investment 

400
00:20:44,360 --> 00:20:47,480
perspective is a portfolio level
concept, right? 

401
00:20:47,480 --> 00:20:50,560
Because you're not just 
targeting 1 greenfields project 

402
00:20:50,560 --> 00:20:52,080
and continuing to do that 
forever. 

403
00:20:52,360 --> 00:20:57,480
So that and they often confuse 
the the the risk profile of 

404
00:20:58,200 --> 00:21:01,600
high, high profile, very 
successful periods of 

405
00:21:01,600 --> 00:21:05,640
brownfields exploration with the
overall profile of the 

406
00:21:05,640 --> 00:21:09,080
greenfields exploration history.
Yet we know that in in most 

407
00:21:09,080 --> 00:21:11,960
situations, periods of 
successful brownfields 

408
00:21:11,960 --> 00:21:14,520
ultimately then replaced by 
periods of unsuccessful. 

409
00:21:14,680 --> 00:21:16,240
Why? 
Because you're depleting the 

410
00:21:16,240 --> 00:21:18,680
search space. 
That that flies massively, I 

411
00:21:18,680 --> 00:21:21,400
think in the in the face of a 
commonly held view. 

412
00:21:21,400 --> 00:21:25,000
The brownfields is how you how 
you yield better results. 

413
00:21:25,000 --> 00:21:26,160
What? 
Why do you think that is the 

414
00:21:26,640 --> 00:21:30,840
commonly held view? 
There's a period of time where 

415
00:21:30,840 --> 00:21:33,680
that really works. 
So if I've made a Greenfields 

416
00:21:33,680 --> 00:21:37,920
discovery in a new terrain, 
right, and I don't know much 

417
00:21:37,920 --> 00:21:42,160
about it, it makes sense for a 
period of time to focus all my 

418
00:21:42,160 --> 00:21:46,920
resources there and find all 
those additional deposits 

419
00:21:46,920 --> 00:21:49,800
because that's the sort of 
embedded option value really 

420
00:21:50,000 --> 00:21:52,320
that relates to the original 
greenfields discovery. 

421
00:21:52,520 --> 00:21:55,880
So what you're really doing is, 
is just optimising the value of 

422
00:21:55,880 --> 00:21:57,800
the original greenfields 
discovery, because when we make 

423
00:21:57,800 --> 00:22:01,160
our first discovery, 
particularly in a, in a new 

424
00:22:01,160 --> 00:22:03,920
terrain, there's often a lot 
more to be found and that, and 

425
00:22:03,920 --> 00:22:07,120
that's why there's a real value 
to making those discoveries. 

426
00:22:07,440 --> 00:22:11,960
But at some point, what happens?
And in most companies, in most 

427
00:22:12,120 --> 00:22:16,160
situations, money continues to 
get spent beyond the point where

428
00:22:16,560 --> 00:22:19,240
it's best to stop spending it 
there and spend it somewhere 

429
00:22:19,240 --> 00:22:21,840
else, right? 
And does that sort of analysis 

430
00:22:21,840 --> 00:22:25,080
take take into account the fact 
that you have economic 

431
00:22:25,080 --> 00:22:28,560
advantages from discovering 
copper or whatever you might be 

432
00:22:28,560 --> 00:22:32,440
looking forgiven the the sort of
latent infrastructure in and? 

433
00:22:32,440 --> 00:22:35,480
Around absolutely and that and 
that's so in, in the brownfields

434
00:22:35,480 --> 00:22:39,360
environment for those reasons 
your success threshold is a lot 

435
00:22:39,480 --> 00:22:42,840
lower right. 
But at the same time what you 

436
00:22:42,880 --> 00:22:46,240
are doing is ultimately only 
incrementally supporting that 

437
00:22:46,240 --> 00:22:50,240
existing operation. 
So that's fine, but what you're 

438
00:22:50,240 --> 00:22:52,320
not doing is investing in 
finding the next one. 

439
00:22:52,560 --> 00:22:54,920
Yeah. 
And to to sort of beat this out,

440
00:22:54,920 --> 00:22:58,360
you've you've spoken about 
advanced projects with with a 

441
00:22:58,360 --> 00:23:01,480
bit of disdain and you've 
highlighted two types of risks, 

442
00:23:01,480 --> 00:23:05,240
you know, high risk type 
projects and no hope projects. 

443
00:23:06,400 --> 00:23:09,240
I loved how you sort of, you 
know, put forth that that 

444
00:23:09,240 --> 00:23:11,320
concept. 
Can you kind of expand on that 

445
00:23:11,320 --> 00:23:14,600
because it's a, it's a topic 
that comes up a lot on the show 

446
00:23:14,600 --> 00:23:17,520
and you see the headlines, 
advanced exploration project or 

447
00:23:17,760 --> 00:23:20,600
you know, yadda, yadda, yadda. 
And money just continually gets 

448
00:23:20,600 --> 00:23:23,520
sunk into it. 
People know about it and they 

449
00:23:23,520 --> 00:23:25,680
think, oh, maybe in a slightly 
better environment cause the 

450
00:23:26,200 --> 00:23:27,840
yeah, the commodity price has 
gone up. 

451
00:23:28,040 --> 00:23:30,680
You know, never mind the fact 
that inflation has ripped 

452
00:23:30,680 --> 00:23:32,640
through in that. 
Well, I think that's exactly 

453
00:23:32,680 --> 00:23:34,720
right, Jonas. 
So, you know, we have these 

454
00:23:34,720 --> 00:23:39,080
projects and I it, it didn't, it
didn't make it before, but you 

455
00:23:39,080 --> 00:23:42,720
know, now the commodity price is
higher. 

456
00:23:43,280 --> 00:23:47,160
So maybe now it's economic, but 
as you say, usually costs come 

457
00:23:47,160 --> 00:23:50,320
up at the same time. 
But the other, the other issue 

458
00:23:50,320 --> 00:23:54,520
with those sort of projects is 
there's an unfor because the 

459
00:23:54,520 --> 00:23:57,960
dominant dynamic of our industry
is the price cycle, right? 

460
00:23:58,400 --> 00:24:00,720
If you think about what 
typically happens rising price 

461
00:24:00,720 --> 00:24:06,080
cycle, we dust off this dormant 
project in junior company, you 

462
00:24:06,080 --> 00:24:08,920
know, blue sky mining and then 
we go to the market, get 

463
00:24:08,920 --> 00:24:12,840
everyone excited, you know, the 
share price goes up. 

464
00:24:13,240 --> 00:24:15,880
And then if we're really 
unlucky, if the shareholders are

465
00:24:15,880 --> 00:24:17,840
really unlucky, there's a 
decision to try and develop this

466
00:24:17,840 --> 00:24:20,720
thing. 
And, and so we bring all that 

467
00:24:20,720 --> 00:24:26,480
capital in and we build the mine
just in time for the price to 

468
00:24:26,480 --> 00:24:31,280
crash and the down cycle. 
But it's also, I think one of 

469
00:24:31,280 --> 00:24:33,680
the reasons why advanced 
projects get recycled is for the

470
00:24:33,680 --> 00:24:37,880
same thing where it's easier to 
go to the market with a project 

471
00:24:37,880 --> 00:24:41,640
that, you know, like has a 
defined resource or has a study 

472
00:24:41,640 --> 00:24:44,400
or, you know, like, and, and I 
think, you know, like that's 

473
00:24:44,400 --> 00:24:47,640
kind of the argument that in 
that a part of the cycle, it's 

474
00:24:47,640 --> 00:24:49,640
much easier to go to investors 
and go, hey, we've got an 

475
00:24:49,640 --> 00:24:52,840
advanced project, you know, 
meaning it's much further along 

476
00:24:52,840 --> 00:24:55,120
the line. 
But in reality, you know, like 

477
00:24:55,120 --> 00:24:57,760
there's a reason why, you know, 
like John calls them no hope 

478
00:24:57,760 --> 00:24:59,440
projects. 
I called them stalled projects. 

479
00:24:59,440 --> 00:25:01,600
You know, there's a reason why 
that project has stalled along 

480
00:25:01,600 --> 00:25:05,720
its development line is because 
it has some fundamental flaw 

481
00:25:05,720 --> 00:25:09,040
which prevented it from going 
becoming an economically viable 

482
00:25:09,040 --> 00:25:10,880
opportunity. 
Now that might be commodity 

483
00:25:10,880 --> 00:25:13,080
price that that's OK. 
You know, like commodity price 

484
00:25:13,080 --> 00:25:14,800
goes up, all of a sudden it 
becomes economic. 

485
00:25:14,800 --> 00:25:17,040
That's totally OK. 
But other times there are some 

486
00:25:17,040 --> 00:25:19,400
fundamental flaws in these 
projects which which they 

487
00:25:19,400 --> 00:25:21,480
haven't solved. 
And people go, well, you know, 

488
00:25:21,480 --> 00:25:23,400
like price is high, we're going 
to dust this thing off. 

489
00:25:23,400 --> 00:25:25,920
And look, it's now advanced and 
it's on the development path, 

490
00:25:26,240 --> 00:25:28,480
but it's not because it has the 
exact same problems it had in 

491
00:25:28,480 --> 00:25:30,120
the last like cycle. 
No. 

492
00:25:30,240 --> 00:25:32,760
There's always a new cycle of 
investors to run through it 

493
00:25:32,760 --> 00:25:33,280
though. 
Yeah. 

494
00:25:33,280 --> 00:25:35,160
Well, yeah. 
Well, and the other thing is the

495
00:25:35,160 --> 00:25:37,640
project often changes its name. 
Yes, I was going to. 

496
00:25:37,640 --> 00:25:40,120
Mention the company as well. 
Because you kind of hope the 

497
00:25:40,120 --> 00:25:43,400
next batch of young investors 
don't even remember that. 

498
00:25:43,520 --> 00:25:45,040
Oh, this is exciting. 
Yeah. 

499
00:25:45,920 --> 00:25:48,400
And John just linked into that 
as well. 

500
00:25:49,080 --> 00:25:52,800
You talk a lot about behavioural
psychology as well that probably

501
00:25:52,800 --> 00:25:59,240
influences these these biases 
companies and investors and that

502
00:25:59,240 --> 00:26:01,960
they have. 
What's your thoughts on that? 

503
00:26:02,480 --> 00:26:06,520
Well, you know, I'm a, I'm a big
fan of the Kahneman work, the 

504
00:26:06,680 --> 00:26:09,360
the behavioural psychology and, 
you know, it's a key part of 

505
00:26:09,360 --> 00:26:13,640
what we teach in our, our senior
exploration management course. 

506
00:26:13,640 --> 00:26:18,280
But you know, one of the things 
that that that Kahneman looks at

507
00:26:18,280 --> 00:26:22,480
is how people make decisions in 
the gain frame and in the loss 

508
00:26:22,480 --> 00:26:24,360
frame. 
And they make decisions based on

509
00:26:24,640 --> 00:26:29,000
whether there is a high degree 
of certainty with the outcome 

510
00:26:29,000 --> 00:26:32,040
and there's a risk that you 
won't get it or there's really 

511
00:26:32,040 --> 00:26:34,200
not much chance. 
And you see different 

512
00:26:34,200 --> 00:26:36,000
behaviours. 
So in some of those quadrants 

513
00:26:36,400 --> 00:26:40,120
you see risk seeking behaviour. 
So, you know, people buy lottery

514
00:26:40,120 --> 00:26:44,280
tickets because not much chance,
but but also it's, it doesn't 

515
00:26:44,280 --> 00:26:46,520
cost much to play. 
And I think that's sort of the 

516
00:26:46,520 --> 00:26:49,680
rationale between, you know, 
investing in like junior 

517
00:26:49,680 --> 00:26:53,320
companies or whatever. 
On the other hand, you know, we,

518
00:26:53,320 --> 00:26:57,040
we also see this behaviour where
it's a relatively high certainty

519
00:26:57,040 --> 00:27:00,520
loss frame. 
For example, a mine is running 

520
00:27:00,520 --> 00:27:03,600
out of ore and it's often that's
the only time management get 

521
00:27:03,600 --> 00:27:05,000
interested in funding 
exploration. 

522
00:27:05,000 --> 00:27:06,520
They should have been doing it 
for 20 years. 

523
00:27:06,880 --> 00:27:10,960
But in the lost frame, people 
will end up taking bigger risks.

524
00:27:11,320 --> 00:27:14,360
But I, I do want to say 
something about behavioural 

525
00:27:15,440 --> 00:27:20,320
psychology and you know, this 
concept of the fact that we make

526
00:27:20,320 --> 00:27:24,480
decisions in life as humans that
are not risk neutral, right? 

527
00:27:24,800 --> 00:27:28,960
So a risk neutral decision would
be, you know, I've got, you 

528
00:27:28,960 --> 00:27:36,280
know, 1% chance of getting $100 
million is equivalent to 100% 

529
00:27:36,280 --> 00:27:38,320
chance of getting $1,000,000, 
right. 

530
00:27:39,000 --> 00:27:42,520
So those are identical in a risk
neutral perspective. 

531
00:27:42,520 --> 00:27:45,560
But I think for most of us, if 
we were given that chance, I'd 

532
00:27:45,560 --> 00:27:49,520
go, you know what, I'll take the
$1,000,000 and the 1% chance of 

533
00:27:49,520 --> 00:27:52,200
getting 100 million I'm going to
leave behind. 

534
00:27:52,640 --> 00:27:59,000
So we often risk discount and 
one of the contexts that we risk

535
00:27:59,000 --> 00:28:04,440
discount in is when the actual 
probability, yeah, the value of 

536
00:28:04,440 --> 00:28:07,800
something which we can say the 
expected value is probability by

537
00:28:07,800 --> 00:28:12,040
what it might be, might be high.
But because that probability is 

538
00:28:12,040 --> 00:28:15,440
actually low, like in an early 
stage exploration project, we 

539
00:28:15,440 --> 00:28:18,560
discounted. 
So what we see is that early 

540
00:28:18,560 --> 00:28:22,520
stage exploration projects are 
often, you know, and this is the

541
00:28:22,520 --> 00:28:24,800
good ones, you've got to philtre
out the no hope ones, right? 

542
00:28:24,800 --> 00:28:31,160
But the good ones are often 
valued at at quite low values 

543
00:28:31,160 --> 00:28:33,720
compared to what AEMV would say 
they should be. 

544
00:28:33,800 --> 00:28:37,880
OK. 
So and actually after discovery,

545
00:28:37,880 --> 00:28:40,960
they're often valued higher. 
But what that means is there's a

546
00:28:40,960 --> 00:28:44,840
very interesting human 
psychology creates a very 

547
00:28:44,840 --> 00:28:48,240
interesting arbitrage 
opportunity for investors in 

548
00:28:48,240 --> 00:28:54,400
that if you have the the 
wherewithal, if you've got the 

549
00:28:54,400 --> 00:28:58,600
capital to be able to take the 
risk that a number of these 

550
00:28:58,600 --> 00:29:00,920
things are going to fail. 
But ultimately you could be 

551
00:29:00,920 --> 00:29:04,080
successful as a portfolio, 
you're going to always do better

552
00:29:04,360 --> 00:29:07,160
being on the left hand side of 
that discovery hole, right? 

553
00:29:07,440 --> 00:29:10,360
Because you're in, you're 
investing at at a much cheaper 

554
00:29:10,520 --> 00:29:13,640
price than on the other side. 
And you could just play the odds

555
00:29:13,640 --> 00:29:14,720
game to. 
Some degree, right? 

556
00:29:14,720 --> 00:29:18,360
So, so that's the logic for why,
you know, large, large companies

557
00:29:18,360 --> 00:29:20,480
with big balance sheets should 
in fact do that. 

558
00:29:21,000 --> 00:29:24,400
But this is this is I think an 
important point in that, you 

559
00:29:24,400 --> 00:29:28,200
know, like at some point in low 
probability success rates, you 

560
00:29:28,200 --> 00:29:30,920
have to play the odds at some 
point to to succeed. 

561
00:29:30,960 --> 00:29:34,360
You know, like you can't, you 
either have to pay the odds or 

562
00:29:34,360 --> 00:29:36,560
you have to play a very long 
game, right? 

563
00:29:36,560 --> 00:29:38,560
So you're so taking the bets, 
but you're taking them over a 

564
00:29:38,560 --> 00:29:41,440
long period of time. 
And I think, you know, like one 

565
00:29:41,440 --> 00:29:44,800
of the, the frustrations I think
I see is that a lot of people in

566
00:29:44,800 --> 00:29:47,040
mineral exploration are actually
doing the opposite, right? 

567
00:29:47,040 --> 00:29:50,000
That they're, they're taking 
very few bets, you know, like 

568
00:29:50,000 --> 00:29:52,840
one project and they are putting
all their hopes on that one 

569
00:29:52,840 --> 00:29:54,840
project to kind of get get to 
the line. 

570
00:29:55,080 --> 00:29:58,280
But fundamentally that project 
almost always has a low 

571
00:29:58,280 --> 00:30:01,080
probability of success, you 
know, like that that hasn't 

572
00:30:01,080 --> 00:30:03,720
really changed in that sense. 
But it's just that their 

573
00:30:03,720 --> 00:30:06,760
perception has changed about it 
because they think, and this is 

574
00:30:06,760 --> 00:30:09,840
often a problem with I guess 
technical people in the industry

575
00:30:09,840 --> 00:30:12,760
where they think that project is
the is the one, you know, they 

576
00:30:12,760 --> 00:30:14,400
have their false hope and that's
OK. 

577
00:30:14,720 --> 00:30:18,000
But commercially, you know that 
or investment wise, you know 

578
00:30:18,000 --> 00:30:20,120
that that's probably not going 
to pay out in the long run. 

579
00:30:20,640 --> 00:30:25,320
So there's this. 
This, you know, unease between 

580
00:30:25,440 --> 00:30:30,320
the the risk that companies 
outwardly express that they are 

581
00:30:30,320 --> 00:30:33,280
going to take, that they want to
take, whereas their approach is 

582
00:30:33,280 --> 00:30:35,600
actually quite timid. 
This is something you've spoken 

583
00:30:35,600 --> 00:30:37,640
about in. 
Yeah, Richard Taylor, who got 

584
00:30:37,640 --> 00:30:41,120
the Nobel Prize for economics, I
think it was in 2015. 

585
00:30:41,360 --> 00:30:42,560
Yeah. 
One of the things in his book 

586
00:30:42,560 --> 00:30:47,560
he, he, he, he calls it bold 
targets, timid choices. 

587
00:30:48,400 --> 00:30:50,440
There's a company that comes to 
mind, guys when we're talking 

588
00:30:50,440 --> 00:30:53,760
about grand objectives, but not 
timid action. 

589
00:30:53,760 --> 00:30:57,320
I'm talking about grand outcomes
and that is bloody Greenlands. 

590
00:30:57,560 --> 00:31:01,000
Great Great Grand is like sort 
of shortfall Greenlands. 

591
00:31:01,120 --> 00:31:02,360
I think, yeah. 
In in a way. 

592
00:31:02,560 --> 00:31:03,640
You're absolutely right. 
One in the. 

593
00:31:03,880 --> 00:31:05,400
Same. 
Yeah, one, one in the same. 

594
00:31:05,640 --> 00:31:07,680
And these guys, you know, you 
open up their website and they 

595
00:31:07,680 --> 00:31:09,680
got some of my favourite words 
on the whole planet. 

596
00:31:10,040 --> 00:31:12,560
Turnkey. 
Solutions and the video how 

597
00:31:12,560 --> 00:31:17,080
goods the video lie over the 
friggin damn mate sensation. 

598
00:31:17,120 --> 00:31:19,840
It just reeks of water. 
These guys bloody do it all. 

599
00:31:20,360 --> 00:31:22,960
Any any water related problem 
you've got, these guys will sort

600
00:31:22,960 --> 00:31:24,160
out. 
You want a day water? 

601
00:31:24,160 --> 00:31:25,840
An open pit? 
You want a day water an 

602
00:31:25,840 --> 00:31:28,320
underground? 
You want to transfer water 

603
00:31:28,320 --> 00:31:30,840
across your mind site? 
You want to line some ponds? 

604
00:31:31,720 --> 00:31:34,080
Want to lay some pipes? 
These guys will do it for you. 

605
00:31:34,200 --> 00:31:38,280
Mate they will even drink water 
and make you less dehydrated 

606
00:31:38,280 --> 00:31:42,440
like that is how good they are. 
Like they are absolute water 

607
00:31:42,440 --> 00:31:44,240
magicians. 
God's work the best way. 

608
00:31:44,360 --> 00:31:47,560
Absolute doing God's work. 
So my cheers Greenlands. 

609
00:31:47,560 --> 00:31:50,520
Go, Greenlands, Go. 
Australia hydration kings and. 

610
00:31:50,520 --> 00:31:55,640
Let's go back to your episode. 
And can you expand on this in 

611
00:31:55,640 --> 00:31:58,680
the, in the context of major 
mining companies out there that 

612
00:31:58,680 --> 00:32:01,960
have, you know, not just the, 
the small one asset companies, 

613
00:32:01,960 --> 00:32:04,360
but the, the majors out there 
that do have the ability to 

614
00:32:04,360 --> 00:32:07,040
have, and they do have a, a 
portfolio of assets that have 

615
00:32:07,280 --> 00:32:10,080
the capital to, to pick and 
choose how they go about it. 

616
00:32:10,520 --> 00:32:14,240
How would you sort of guide them
or tweak their their decision 

617
00:32:14,240 --> 00:32:17,400
making if if they came to you? 
Well, once again, I get the 

618
00:32:17,400 --> 00:32:18,840
point I made a little bit 
earlier, right? 

619
00:32:18,880 --> 00:32:22,360
I think it's understanding where
you want to be on the risk 

620
00:32:22,360 --> 00:32:26,000
reward curve, right? 
So there is no such thing as a 

621
00:32:26,000 --> 00:32:28,520
free lunch, right? 
We all know that if you want a 

622
00:32:28,520 --> 00:32:32,200
really big reward and you know 
the discovery of a world class 

623
00:32:32,600 --> 00:32:35,440
or deposit is a massive reward 
in terms of sort of the 

624
00:32:35,440 --> 00:32:39,280
multiples and the uplift. 
But it goes without saying that 

625
00:32:39,520 --> 00:32:41,920
the risk or and I define risk 
here in the sense of the 

626
00:32:41,920 --> 00:32:45,000
probability of that occurring is
going to be relatively low, 

627
00:32:45,080 --> 00:32:47,400
right. 
So if we think about this risk 

628
00:32:47,400 --> 00:32:51,840
reward curve, I would say that 
as a big company, work out what 

629
00:32:51,840 --> 00:32:55,640
you need to be and then work out
what that means in terms of 

630
00:32:55,640 --> 00:32:58,520
risk. 
So if you're a BHP and your 

631
00:32:58,520 --> 00:33:03,800
portfolio looks the same as, I 
don't know, an IGO or a company 

632
00:33:03,920 --> 00:33:06,400
of a 10th the size, it's 
probably telling you there's a 

633
00:33:06,400 --> 00:33:10,520
problem, right? 
But what I was getting to before

634
00:33:11,200 --> 00:33:14,480
the, the, the challenge we have 
is what economists call a 

635
00:33:14,480 --> 00:33:17,720
failure of agency, because at 
the end of the day, there is no 

636
00:33:17,880 --> 00:33:21,320
entity called BHP who's making 
decisions based on what BHP 

637
00:33:21,320 --> 00:33:23,280
needs to do. 
There's a whole lot of 

638
00:33:23,280 --> 00:33:27,600
individuals making decisions 
based on, you know, a range of 

639
00:33:27,600 --> 00:33:30,440
factors, including, you know, 
what, what, what's rational to 

640
00:33:30,440 --> 00:33:31,920
them. 
And I'm not just picking on BHP,

641
00:33:31,920 --> 00:33:33,920
but just, you know, just because
they're the largest mining 

642
00:33:33,920 --> 00:33:36,520
company in the world. 
But but that sort of logic. 

643
00:33:36,680 --> 00:33:38,880
And I think, you know, like to 
back to your question about like

644
00:33:39,120 --> 00:33:42,840
why behavioural psychology or 
economics, you know, matters in 

645
00:33:42,840 --> 00:33:45,520
this space is because, you know,
like, so yeah, like the 

646
00:33:45,520 --> 00:33:47,840
condiment of these guys have 
talked about like a number of 

647
00:33:47,840 --> 00:33:49,520
kind of heuristics that people 
use. 

648
00:33:49,840 --> 00:33:52,280
And one of the ones I think, you
know, like aside from the one 

649
00:33:52,280 --> 00:33:54,640
that John's mentioning is this 
thing called the availability 

650
00:33:54,640 --> 00:33:57,600
bias, right? 
Which is that people will answer

651
00:33:57,600 --> 00:34:00,080
the the question that they can 
instead of the one that they 

652
00:34:00,080 --> 00:34:02,760
should. 
And so so when you ask, you 

653
00:34:02,800 --> 00:34:05,760
know, like when you ask someone 
in VHP be like, you know, like 

654
00:34:05,760 --> 00:34:09,520
what do you actually need to do 
to find a world class asset? 

655
00:34:09,760 --> 00:34:12,280
Well, the answer is that they 
have to take on the commensurate

656
00:34:12,280 --> 00:34:14,159
level of risk in order to go and
do it. 

657
00:34:14,480 --> 00:34:17,199
But the way they the answer is 
by answering the question of 

658
00:34:17,199 --> 00:34:19,000
what they can do. 
And they go, well, actually 

659
00:34:19,000 --> 00:34:21,719
we'll go look around our 
existing asset for another world

660
00:34:21,719 --> 00:34:24,600
class, you know, but that's not 
like, you know, that's not the 

661
00:34:24,600 --> 00:34:26,320
question that need need to be 
answering. 

662
00:34:26,520 --> 00:34:31,440
Can incentives overcome this? 
They they, they have to be 

663
00:34:31,760 --> 00:34:36,000
longer term and and they also 
have to acknowledge that there 

664
00:34:36,000 --> 00:34:39,040
is a component of lacking here 
with with good work. 

665
00:34:39,040 --> 00:34:45,040
So, you know, it's like I said 
before, exploring a project that

666
00:34:45,040 --> 00:34:48,800
was a genuine concept and 
realising that we need to stop 

667
00:34:48,800 --> 00:34:51,600
and moving on. 
That's something that is 

668
00:34:51,600 --> 00:34:53,639
actually behaviour that we do 
want to reward. 

669
00:34:54,080 --> 00:34:56,199
Is it being rewarded I. 
I yeah, yeah. 

670
00:34:56,440 --> 00:34:58,640
And I think I mean, like the 
short answer to your question is

671
00:34:58,640 --> 00:35:00,840
yes, right. 
Because that's, we know from the

672
00:35:00,840 --> 00:35:03,160
field of behavioural economics, 
that's how you change behaviour 

673
00:35:03,160 --> 00:35:05,120
by incentivizing. 
Yeah. 

674
00:35:05,120 --> 00:35:08,480
So John mentioned Richard Haley,
he has also another thing called

675
00:35:08,480 --> 00:35:11,560
the dump principle problem or 
the asymmetrical risk problem. 

676
00:35:12,000 --> 00:35:16,160
And yeah, like so to your 
question about incentives, yes, 

677
00:35:16,160 --> 00:35:19,160
they can overcome that because 
in Taylor's example, you know, 

678
00:35:19,160 --> 00:35:22,160
he kind of expressed that he was
in a multi conglomerate kind of 

679
00:35:22,160 --> 00:35:26,880
media company and he asked the 
CEO and the CEO wanted to take a

680
00:35:26,880 --> 00:35:28,960
high level of risk. 
And then he asked all the 

681
00:35:28,960 --> 00:35:31,360
managers that sat underneath and
they didn't want to take any 

682
00:35:31,360 --> 00:35:32,400
risk at all. 
Right. 

683
00:35:32,760 --> 00:35:35,160
And the fundamentally it came 
down to that if you were a 

684
00:35:35,160 --> 00:35:37,760
manager and you took that level 
of risk and it didn't pan out, 

685
00:35:37,760 --> 00:35:39,640
you will probably lose your job.
Yeah. 

686
00:35:40,000 --> 00:35:43,240
It's fascinating, right? 
Because the the behaviour you 

687
00:35:43,240 --> 00:35:46,440
want to incentivize them for is 
to take the appropriate amount 

688
00:35:46,520 --> 00:35:48,040
of risk. 
You know, everything else. 

689
00:35:48,320 --> 00:35:49,800
Everything else staying 
constant. 

690
00:35:49,920 --> 00:35:52,400
Yeah, but but then. 
Doesn't mean they'll be at an 

691
00:35:52,400 --> 00:35:54,600
individual level. 
Successful, but you know, but 

692
00:35:54,600 --> 00:36:01,400
the outcome of taking that risk 
can can then not be career 

693
00:36:01,400 --> 00:36:03,160
detrimental to them either, 
right? 

694
00:36:03,160 --> 00:36:05,200
You can't have it both ways. 
You can't tell someone take a 

695
00:36:05,200 --> 00:36:07,600
lot of risk which is going to 
have a high degree of failure. 

696
00:36:07,720 --> 00:36:09,360
But if you fail, I'm going to 
sack you. 

697
00:36:09,400 --> 00:36:10,960
But like, that's not the right 
way to. 

698
00:36:11,160 --> 00:36:16,560
So in that Taylor example, 
right, so the C, the CEO wanted 

699
00:36:16,560 --> 00:36:18,880
to take all these projects and I
think there was something like 

700
00:36:19,760 --> 00:36:22,520
10 executives and each one of 
them was told, well, here's a 

701
00:36:22,520 --> 00:36:26,360
project that if you invest 
$1,000,000, there's a 50% chance

702
00:36:26,360 --> 00:36:28,800
it's successful and you get 
$3,000,000, right? 

703
00:36:29,280 --> 00:36:31,760
And a 50% chance you, you lose 
it all, right? 

704
00:36:32,000 --> 00:36:36,480
And the CEO said we should take 
all of those and very, very few 

705
00:36:37,400 --> 00:36:41,120
of the individuals wanted to 
because 50% is a pretty high 

706
00:36:41,120 --> 00:36:43,200
probability, right? 
One in two that you're going to 

707
00:36:43,200 --> 00:36:46,400
lose it. 
So, and, and that's said this 

708
00:36:46,400 --> 00:36:51,800
whole idea of risk discounting 
because pretty obviously 50% 

709
00:36:51,800 --> 00:36:54,640
probability that you're going to
get three times your investment 

710
00:36:54,640 --> 00:36:57,720
back is EMV positive scenario, 
right? 

711
00:36:57,960 --> 00:37:01,960
So in a risk neutral world, we 
should take all EMV positive 

712
00:37:01,960 --> 00:37:05,680
scenarios, but we don't because 
because of risk and risk is 

713
00:37:05,920 --> 00:37:08,920
ultimately an individual thing 
and it's ultimately a 

714
00:37:09,080 --> 00:37:12,920
psychological decision. 
So we, we don't just want to 

715
00:37:12,920 --> 00:37:15,960
talk about the, the issues 
around there and the problems 

716
00:37:15,960 --> 00:37:19,360
with exploration companies and 
what the industry faces at the 

717
00:37:19,360 --> 00:37:21,480
moment. 
And you know, thankfully you've,

718
00:37:21,560 --> 00:37:24,400
you've thought a lot about this,
John, and you've put forward a 

719
00:37:24,400 --> 00:37:27,600
really sort of succinct and 
interesting paper on this idea 

720
00:37:27,600 --> 00:37:32,600
of an exploration aggregator. 
And I I believe this was written

721
00:37:32,600 --> 00:37:35,520
sort of late 20/10/2016. 
Something like that. 

722
00:37:35,520 --> 00:37:38,600
I think I, I spoke about it at 
PDAC in 2016. 

723
00:37:38,720 --> 00:37:41,680
Yeah, yeah. 
So the basic idea there, it was 

724
00:37:41,680 --> 00:37:47,560
actually to thinking through 
some of these challenges and and

725
00:37:47,560 --> 00:37:51,560
feeling like as a global 
industry, we did not efficiently

726
00:37:51,560 --> 00:37:55,040
allocate capital to this really 
important task, which has only 

727
00:37:55,040 --> 00:37:57,800
become more important of 
Greenfield's exploration, right 

728
00:37:57,800 --> 00:38:01,240
and finding, finding these new 
mineral deposits. 

729
00:38:01,360 --> 00:38:04,040
And I think just to interject 
there, John, one of the, I think

730
00:38:04,640 --> 00:38:07,920
fundamental things about the 
funding is to say, yeah, there's

731
00:38:07,920 --> 00:38:10,160
two schools of thought. 
One of them says that, you know,

732
00:38:10,160 --> 00:38:12,400
we don't have enough funding. 
The other says that we actually 

733
00:38:12,400 --> 00:38:15,080
have enough funding is just 
allocated badly. 

734
00:38:15,080 --> 00:38:17,480
Yeah, like to some degree. 
And I think like you know, and I

735
00:38:17,480 --> 00:38:20,120
think that's an important point 
in your model is that it's not 

736
00:38:20,120 --> 00:38:22,960
advocating that we need massive 
amounts of in increased 

737
00:38:22,960 --> 00:38:25,200
investments, It's just that the 
investment we have could be 

738
00:38:25,200 --> 00:38:26,680
better utilised. 
Absolutely. 

739
00:38:26,680 --> 00:38:31,400
The agents around, you know, we 
may, we may need a, a bigger 

740
00:38:31,400 --> 00:38:35,320
global quantum, but to do that, 
we need to demonstrate the 

741
00:38:35,320 --> 00:38:38,800
results. 
And you know, you can sit down 

742
00:38:38,800 --> 00:38:42,280
and, and, and do the numbers 
where you kind of say, well, how

743
00:38:42,280 --> 00:38:44,920
many big deposits are being 
found each year? 

744
00:38:44,920 --> 00:38:47,000
And they're all like worth a 
certain amount. 

745
00:38:47,160 --> 00:38:49,440
How much are we spending as an 
industry? 

746
00:38:49,960 --> 00:38:52,520
And those numbers don't look 
that good like they they have, 

747
00:38:52,520 --> 00:38:56,040
they're, they're quite high. 
You know, it's like probably of 

748
00:38:56,040 --> 00:39:01,200
the order of 200 million US just
for any type of deposit, not a 

749
00:39:01,200 --> 00:39:03,400
not a tier one. 
And it's probably something like

750
00:39:03,680 --> 00:39:06,600
8,000,008 billion for like a, a 
tier one. 

751
00:39:07,160 --> 00:39:12,720
But the problem with all that 
sort of analysis is that a very 

752
00:39:12,720 --> 00:39:15,560
large chunk of that money, you 
know, the global exploration 

753
00:39:15,560 --> 00:39:19,360
industry spends. 
It varies of course, but you 

754
00:39:19,360 --> 00:39:22,880
know, somewhere of the order of 
10 to 15 billion US a year. 

755
00:39:23,600 --> 00:39:28,800
And a very large part of that 
money is, is not focused on 

756
00:39:28,800 --> 00:39:32,200
finding new Tier 1 deposits. 
Exactly how large, I don't know.

757
00:39:32,200 --> 00:39:34,520
If I had to guess, I'd say 
probably close to 90%. 

758
00:39:34,840 --> 00:39:37,680
Now some of that's for good 
reason in that the money's been 

759
00:39:37,680 --> 00:39:41,560
allocated to, you know, around 
existing operations and so on. 

760
00:39:41,840 --> 00:39:44,600
Some of it for less good reason.
It's being allocated because to 

761
00:39:44,600 --> 00:39:48,680
projects where there is an 
opportunity to raise capital or 

762
00:39:48,800 --> 00:39:51,520
some of it is because there is 
an ecosystem in our industry and

763
00:39:52,000 --> 00:39:54,280
below the level of tier ones, 
you can, you know, there, 

764
00:39:54,280 --> 00:39:57,080
there's viable companies finding
smaller stuff, but that doesn't 

765
00:39:57,080 --> 00:40:00,840
really solve sort of global 
problems and it it's not got 

766
00:40:00,840 --> 00:40:03,800
that sort of tier one type value
creation. 

767
00:40:04,120 --> 00:40:11,280
So I guess my concept would be 
being selective, right? 

768
00:40:11,280 --> 00:40:13,280
So part of the exploration 
aggregator model. 

769
00:40:13,280 --> 00:40:18,960
The the first point is that you 
you need the skill set in the 

770
00:40:18,960 --> 00:40:21,160
aggregator to make sure that 
the. 

771
00:40:21,960 --> 00:40:24,920
The gating process is that the 
only thing that ever gets funded

772
00:40:25,240 --> 00:40:28,960
are those projects that have the
genuine opportunity to find the 

773
00:40:28,960 --> 00:40:32,120
tier one, right? 
So that's the first thing. 

774
00:40:32,120 --> 00:40:33,720
So you improve the odds, 
essentially. 

775
00:40:33,760 --> 00:40:35,840
Oh absolutely You're not. 
You're not spending money on 

776
00:40:35,840 --> 00:40:39,480
things you know are have no hope
of ever getting. 

777
00:40:39,480 --> 00:40:43,640
Anywhere so, so just to be very 
clear, I, I, you know, you, you 

778
00:40:43,640 --> 00:40:45,120
obviously want to apply your 
best science. 

779
00:40:45,120 --> 00:40:47,360
And if you do that, you know, 
some projects might be better 

780
00:40:47,360 --> 00:40:50,720
than others, But the reality is 
that I'm, you know, I'm not, I'm

781
00:40:50,720 --> 00:40:54,080
not saying you can be too, too 
sophisticated at that early 

782
00:40:54,080 --> 00:40:58,280
stage in saying, well, this 
one's maybe a 1% probability, 

783
00:40:58,280 --> 00:41:01,080
this one's a 1 1/2 percent 
probability or whatever it is. 

784
00:41:01,320 --> 00:41:05,360
But what I'm saying is you want 
to cut out anything that's a 0% 

785
00:41:05,360 --> 00:41:07,920
probability, right? 
So that, that, that's, that's 

786
00:41:07,920 --> 00:41:10,160
the key point. 
You, you want to, you want to 

787
00:41:10,160 --> 00:41:12,960
reduce it to those things that 
have, you know, a genuine 

788
00:41:12,960 --> 00:41:14,320
chance. 
That's the first Philtre. 

789
00:41:15,040 --> 00:41:18,880
The, the 2nd philtre is it has 
to be managed as a portfolio. 

790
00:41:19,440 --> 00:41:23,840
And you, you, you need that 
capital pool that yeah, there's 

791
00:41:23,840 --> 00:41:26,680
concept of, of gamblers ruin. 
So even if something is EMV 

792
00:41:26,720 --> 00:41:29,720
positive, right, you might go 
broke before you get there. 

793
00:41:30,320 --> 00:41:32,960
And your ability to avoid 
gamblers ruin is a function of 

794
00:41:32,960 --> 00:41:35,720
your pool of capital. 
So you need a pool of capital to

795
00:41:35,720 --> 00:41:38,720
be able to manage this as a 
portfolio. 

796
00:41:39,080 --> 00:41:41,680
And your bet sizes, right? 
That's right, That's right. 

797
00:41:42,040 --> 00:41:45,640
And the, but the absolutely 
critical thing about bet size is

798
00:41:46,800 --> 00:41:50,040
you've got to manage all your 
projects with decision point 

799
00:41:50,040 --> 00:41:52,640
planning, right? 
So this is, this is getting into

800
00:41:52,640 --> 00:41:56,400
the not the micro, but a really 
fundamental concept. 

801
00:41:56,680 --> 00:41:59,600
It's not like I've got this 
exploration project and I'm 

802
00:41:59,600 --> 00:42:03,120
going to spend 20 million or 30 
million on it's like I've got 

803
00:42:03,120 --> 00:42:05,720
this exploration project. 
It could be the next Escondida, 

804
00:42:06,040 --> 00:42:10,440
but after I've spent, I don't 
know, two or three million doing

805
00:42:10,440 --> 00:42:13,720
these drill holes, I will know 
whether an Escondida is there or

806
00:42:13,720 --> 00:42:15,440
not. 
Now, if I'm unsuccessful, it 

807
00:42:15,440 --> 00:42:18,040
still could be something small. 
Yeah, but I know it's not the 

808
00:42:18,040 --> 00:42:19,000
big one. 
Yeah, right. 

809
00:42:19,000 --> 00:42:20,600
That's right. 
So and that's your decision to 

810
00:42:20,600 --> 00:42:21,880
kind of walk, right? 
That's right. 

811
00:42:21,880 --> 00:42:24,600
You know, if you're not going to
get that pay off, yeah, then 

812
00:42:24,600 --> 00:42:27,240
you're not, you know, committing
funds just for the sake of 

813
00:42:27,400 --> 00:42:30,240
because that's the only project 
you have or, or whatever other 

814
00:42:30,240 --> 00:42:33,960
kind of metric that comes in. 
And the, the sort of the third 

815
00:42:33,960 --> 00:42:37,480
aspect and why I call it the 
aggregator is, is I think, you 

816
00:42:37,480 --> 00:42:39,520
know, one of the things we 
learned from the history of the 

817
00:42:39,520 --> 00:42:43,280
exploration industry is it's 
very hard to do things as a big 

818
00:42:43,520 --> 00:42:47,080
sort of global conglomerate 
because there is a real value in

819
00:42:47,080 --> 00:42:51,760
being close to the ground, you 
know, close to the, the local 

820
00:42:51,760 --> 00:42:53,720
people, close to the local 
geology. 

821
00:42:54,440 --> 00:42:56,960
And you know, I remember a few 
years ago there was a study on 

822
00:42:56,960 --> 00:43:00,080
gold exploration which showed 
the most successful explorers 

823
00:43:00,080 --> 00:43:02,400
were the ones that were focused 
in a particular region. 

824
00:43:02,560 --> 00:43:04,800
Makes a lot of sense, right? 
And the reason why it makes a 

825
00:43:04,800 --> 00:43:07,280
lot of sense, and I'll, I'll 
come to this in a minute, is the

826
00:43:07,280 --> 00:43:11,240
learning curve, right? 
But how can you simultaneously 

827
00:43:11,240 --> 00:43:16,240
have a big global portfolio, but
also have, let's call it local 

828
00:43:16,240 --> 00:43:18,760
expertise, local skill set, 
local learning? 

829
00:43:19,000 --> 00:43:22,720
Well, you've got to support a 
diversity of organisations. 

830
00:43:23,160 --> 00:43:26,680
So you know, whatever this sort 
of overarching source of capital

831
00:43:26,680 --> 00:43:28,320
is. 
And I think the BHP explore 

832
00:43:28,320 --> 00:43:31,240
model is, is, is sort of one 
model globally, which is kind of

833
00:43:31,240 --> 00:43:36,240
trying to do this at the moment.
And it, it, it seeks, you know, 

834
00:43:36,240 --> 00:43:38,560
high quality opportunities from 
around the world. 

835
00:43:38,560 --> 00:43:41,680
Whether it's got the critical 
mass it needs yet, I, I don't 

836
00:43:41,680 --> 00:43:43,040
know. 
But I think it's it, you know, 

837
00:43:43,040 --> 00:43:46,080
it's a very good step in, in the
right direction. 

838
00:43:46,520 --> 00:43:49,720
But you need to be able to 
support a diversity of groups 

839
00:43:49,720 --> 00:43:52,760
that have that local expertise, 
that local knowledge, so they 

840
00:43:52,760 --> 00:43:56,960
can be effective. 
And then fundamentally, there 

841
00:43:56,960 --> 00:44:00,600
needs to be a commercial 
framework, which is win win, 

842
00:44:00,800 --> 00:44:04,200
right? 
So the larger corporation 

843
00:44:04,360 --> 00:44:07,560
obviously ultimately wants 
continuity of its business by 

844
00:44:07,560 --> 00:44:11,520
getting access to these things. 
But it has to be has to be 

845
00:44:11,520 --> 00:44:14,880
prepared to give enough away. 
Because you think about why 

846
00:44:14,880 --> 00:44:17,960
someone invests in a junior 
exploration company doing 

847
00:44:17,960 --> 00:44:22,520
exploration, it's not for like a
50% return on their money, 100%.

848
00:44:22,520 --> 00:44:26,680
It's the, the, the small, but 
non 0 probability of a very, 

849
00:44:26,680 --> 00:44:29,400
very large return. 
So it's very important that 

850
00:44:29,400 --> 00:44:34,680
that's not not capped. 
So but just what just just 

851
00:44:34,680 --> 00:44:39,760
sorry, I'm learning because one 
of the things about exploration 

852
00:44:39,760 --> 00:44:43,800
is that if you look at sort of 
average success rates, it 

853
00:44:43,800 --> 00:44:47,600
doesn't look economic, right? 
But if you think about one of 

854
00:44:47,600 --> 00:44:50,720
these curves of I'm going to 
explore 100 projects and it's 

855
00:44:50,720 --> 00:44:56,360
going to cost me X and what's 
the MPV of my programme, what 

856
00:44:56,360 --> 00:45:00,080
those models imply is the 
probability of success of your 

857
00:45:00,080 --> 00:45:02,840
100th project is the same as 
your first project. 

858
00:45:03,360 --> 00:45:05,720
And what that implies is that 
you haven't learned anything. 

859
00:45:06,200 --> 00:45:10,800
And in real life, if we're doing
exploration, well, we're 

860
00:45:10,800 --> 00:45:13,640
exploring an area, we're 
unsuccessful, but that 

861
00:45:13,640 --> 00:45:17,360
information is fed back into the
next set of targets we drill and

862
00:45:17,360 --> 00:45:20,320
the next set and we improve that
probability of success. 

863
00:45:20,560 --> 00:45:25,200
So that the learning theme, that
that's the key, that that's the 

864
00:45:25,200 --> 00:45:30,400
key juice that that drives this 
and why, you know, persisting in

865
00:45:30,400 --> 00:45:33,840
local areas or persisting around
a particular commodity type is 

866
00:45:33,840 --> 00:45:36,200
so critical. 
And I think this is, you know, 

867
00:45:36,200 --> 00:45:38,440
like this last point about the 
learning curve is I think when 

868
00:45:38,440 --> 00:45:42,040
we look at companies that were 
really good explorers, that's I 

869
00:45:42,040 --> 00:45:44,480
think one of the, you know, like
in the, in the stuff that we did

870
00:45:44,480 --> 00:45:46,600
in our podcast, that's one of 
the themes that kind of comes 

871
00:45:46,600 --> 00:45:51,680
out is that actually they kept 
a, a group of people together 

872
00:45:51,680 --> 00:45:54,280
for enough time so that the 
learning could kind of bounce 

873
00:45:54,280 --> 00:45:57,600
around between them to a point. 
And that, and that's kind of a, 

874
00:45:57,800 --> 00:45:59,800
and it's not a nebulous concept.
Like, you know, if you think 

875
00:45:59,800 --> 00:46:01,920
about sports teams, you know, 
like the teams that are really 

876
00:46:01,920 --> 00:46:05,640
good, you know, they tend to 
have in an organisational 

877
00:46:05,640 --> 00:46:10,240
culture or, you know, like the 
organisation is set up a certain

878
00:46:10,240 --> 00:46:13,680
way, whether that that learning 
feedback loop is kind of getting

879
00:46:13,760 --> 00:46:15,400
passed around. 
You know, like if they're 

880
00:46:15,400 --> 00:46:17,800
drafting players, you know, they
learn from the mistakes that 

881
00:46:17,800 --> 00:46:19,360
they've made. 
So they're not making the same 

882
00:46:19,360 --> 00:46:21,000
dumb mistakes the same time 
again. 

883
00:46:21,320 --> 00:46:24,280
Whereas organisations, yeah, 
like in sports organisations are

884
00:46:24,280 --> 00:46:27,920
really easy to look at when they
go through this period of, you 

885
00:46:27,920 --> 00:46:30,280
know, like the board is cleared 
out, all the executives are 

886
00:46:30,280 --> 00:46:32,080
cleared out, the coaches sacked,
all of that stuff. 

887
00:46:32,280 --> 00:46:37,240
You can see that they don't have
great like success rate in that.

888
00:46:37,320 --> 00:46:38,840
And you can think about, you 
know, if you're a basketball 

889
00:46:38,840 --> 00:46:41,040
fan, you think about the San 
Antonio Spurs or something like 

890
00:46:41,040 --> 00:46:43,440
that, you know, a massively 
successful organisation for a 

891
00:46:43,440 --> 00:46:45,520
long, long time. 
And they've basically kept the 

892
00:46:45,520 --> 00:46:48,120
same people there for for a 
large period. 

893
00:46:48,120 --> 00:46:50,960
And that's kind of like the 
learning curve model is that if 

894
00:46:50,960 --> 00:46:53,320
you can keep them around without
having to sack them every like 

895
00:46:53,320 --> 00:46:55,800
three or four years, then you 
know, like that's kind of the, 

896
00:46:55,800 --> 00:46:58,040
the, the critical mass you want 
to build, I think. 

897
00:46:58,040 --> 00:47:00,800
The Chicago Bulls might be a a 
slightly better example there as

898
00:47:00,840 --> 00:47:02,800
well. 
And you can sort of see there's 

899
00:47:02,840 --> 00:47:06,000
a, a long teething period and 
then eventually, you know, the, 

900
00:47:06,080 --> 00:47:08,640
the flywheel starts humming and 
you get championship. 

901
00:47:08,640 --> 00:47:10,880
After that, and I think that, 
and then that's kind of the 

902
00:47:10,880 --> 00:47:13,840
concept is that, you know, like 
you like exactly the point you 

903
00:47:13,840 --> 00:47:16,480
made is that there are there is 
a period of lean years because 

904
00:47:16,480 --> 00:47:17,920
you you're still figuring it 
out. 

905
00:47:17,920 --> 00:47:20,120
You know, like in a sports 
organisation, you're figuring 

906
00:47:20,120 --> 00:47:21,960
out your drafting strategy and 
all these things. 

907
00:47:22,400 --> 00:47:24,600
And in middle exploration, I 
think when you go into a new 

908
00:47:24,600 --> 00:47:27,640
area, you're still figuring this
thing, these things out, right? 

909
00:47:27,640 --> 00:47:30,880
You're figuring out which areas 
you can really work in, the type

910
00:47:30,880 --> 00:47:33,840
of techniques that work best, 
you know, like how effective you

911
00:47:33,840 --> 00:47:36,320
can be from a dollar point of 
view in exploring in certain 

912
00:47:36,320 --> 00:47:38,680
areas. 
And so there's this, you know, 

913
00:47:38,680 --> 00:47:42,040
basically flat line kind of 
payoff period. 

914
00:47:42,280 --> 00:47:44,840
But then when you get to that 
point, it's kind of like the 

915
00:47:44,960 --> 00:47:47,640
Chicago Bulls model is that the 
success comes really quickly 

916
00:47:47,640 --> 00:47:49,800
after that because you've now 
amalgamated. 

917
00:47:49,960 --> 00:47:52,840
And if I can just sort of make 
one technical point about 

918
00:47:52,840 --> 00:47:56,280
learning, the most important 
thing to learn is what is a 

919
00:47:56,280 --> 00:48:00,880
false positive, right? 
Because mineral expiration, it's

920
00:48:00,880 --> 00:48:04,080
a low base rate environment, 
which means that the targets 

921
00:48:04,080 --> 00:48:07,480
that we test very rarely have 
what we're looking for, which is

922
00:48:07,480 --> 00:48:11,760
an economic or deposit. 
And simple, you know, Bayesian 

923
00:48:12,040 --> 00:48:15,640
probability tells you that in 
that environment, the key factor

924
00:48:15,640 --> 00:48:18,480
if I'm looking at an anomaly and
deciding whether it's associated

925
00:48:18,480 --> 00:48:21,720
with an ore body or not is the 
false positive rate of that 

926
00:48:21,720 --> 00:48:23,680
anomaly. 
In other words, how easy is it 

927
00:48:23,680 --> 00:48:26,040
to create the same anomaly 
that's not an ore body? 

928
00:48:26,560 --> 00:48:29,320
And that has some really 
important consequences. 

929
00:48:29,520 --> 00:48:32,640
So I like to say that, you know,
when my daughter was 10, I 

930
00:48:32,640 --> 00:48:36,600
taught her how to assess ASX 
releases of exploration 

931
00:48:36,600 --> 00:48:38,120
companies. 
Very, very simple method. 

932
00:48:38,480 --> 00:48:42,200
So go to the page where they 
have a plot of all their targets

933
00:48:42,520 --> 00:48:44,760
and count them up. 
And if there's more than three, 

934
00:48:44,760 --> 00:48:50,600
they're no good. 
And the reason is all bodies are

935
00:48:50,600 --> 00:48:53,080
rare. 
So if we're going to say this is

936
00:48:53,120 --> 00:48:55,720
this is the signature, I've got 
a geochemical anomaly or a 

937
00:48:55,720 --> 00:49:00,120
geophysical anomaly, you know, 
it needs to really stand out to 

938
00:49:00,120 --> 00:49:03,040
have a high probability. 
If we've got a lot of targets by

939
00:49:03,040 --> 00:49:06,160
definition, and it's a 
fundamental output of Bayesian 

940
00:49:06,160 --> 00:49:09,120
analysis, the targets are not 
very good. 

941
00:49:09,360 --> 00:49:12,360
And yet you still get people 
saying, well, we've got lots and

942
00:49:12,360 --> 00:49:14,280
lots of targets. 
That's that's a good thing. 

943
00:49:14,320 --> 00:49:16,440
Particularly like geophysics, 
like, yeah, this is a classic 

944
00:49:16,440 --> 00:49:19,160
one where they go, we've got 50 
anomalies and you go, I think 

945
00:49:19,160 --> 00:49:20,560
you've missed the definition of 
anomaly. 

946
00:49:20,680 --> 00:49:22,200
Anomaly, yeah. 
That's good. 

947
00:49:22,200 --> 00:49:25,640
Well, I, I, the, the heuristic I
have is, I like to say that 

948
00:49:25,800 --> 00:49:28,400
green and yellow are not your 
friends. 

949
00:49:29,240 --> 00:49:32,240
And by that I mean, you know, if
you've got your map and you're 

950
00:49:32,240 --> 00:49:35,480
using a typical sort of spectral
stretch, you want to have the 

951
00:49:35,480 --> 00:49:38,200
big red and white dot on a blue 
background, then you've got a 

952
00:49:38,200 --> 00:49:40,800
good a good anomaly if you've 
got lots of green and yellow in 

953
00:49:40,800 --> 00:49:42,720
that map. 
Yeah, that's fine. 

954
00:49:44,040 --> 00:49:46,200
One comment I wanted to make 
about John's like you know, like

955
00:49:46,200 --> 00:49:48,280
model about the aggregator 
because you know, we kind of had

956
00:49:48,280 --> 00:49:49,600
this discussion a couple of 
times. 

957
00:49:49,880 --> 00:49:53,720
And I think one of the the 
fundamental things why you would

958
00:49:53,720 --> 00:49:57,080
want an aggregated model is if 
you start off with the premise 

959
00:49:57,080 --> 00:50:00,200
that every dollar being spent in
exploration is not the same, 

960
00:50:00,560 --> 00:50:02,920
then you can see that there are 
people that are spending dollars

961
00:50:02,920 --> 00:50:04,880
effectively and they're people 
that are spending in 

962
00:50:04,960 --> 00:50:07,800
ineffectively. 
And so, you know, like what you 

963
00:50:07,800 --> 00:50:10,120
want to start off with. 
So if you start off with that as

964
00:50:10,120 --> 00:50:13,160
your premise, you can say that 
they are some agents. 

965
00:50:13,160 --> 00:50:16,240
And you know, John said 90%, you
know, Rick has his own kind of 

966
00:50:16,240 --> 00:50:18,640
the Rick rule has his own 
percentage of how many companies

967
00:50:18,640 --> 00:50:21,280
are lifestyle companies and not 
really wanting to find things, 

968
00:50:21,880 --> 00:50:23,280
right. 
And so I think that's always the

969
00:50:23,280 --> 00:50:27,520
premise that when people say 
this, you know, like we take the

970
00:50:27,520 --> 00:50:31,080
total expended in mineral 
exploration worldwide and we say

971
00:50:31,080 --> 00:50:32,640
this is the amount of metal that
we found. 

972
00:50:33,080 --> 00:50:35,440
You know, like the the basic 
assumption you're making is that

973
00:50:35,440 --> 00:50:36,960
every dollar being spent is the 
same. 

974
00:50:37,320 --> 00:50:40,920
Now if you change that around to
actually looking at companies 

975
00:50:40,920 --> 00:50:44,200
that spent effective dollars and
ineffective dollars, that rate 

976
00:50:44,200 --> 00:50:46,720
of return would be much better. 
100% right, Yeah. 

977
00:50:47,040 --> 00:50:49,720
And and again to to my sports 
analogy is actually the same 

978
00:50:49,720 --> 00:50:51,680
right at the start of the 
season, you have X number of 

979
00:50:51,680 --> 00:50:54,440
teams, but you know that there's
only a handful that are 

980
00:50:54,440 --> 00:50:56,240
legitimately going to be at the 
top of the table. 

981
00:50:56,240 --> 00:50:58,440
And the others are just making 
kind of numbers up, right, 

982
00:50:58,440 --> 00:50:59,840
because they're they're not good
enough. 

983
00:51:00,000 --> 00:51:01,600
Yeah. 
And I think it's the same in in 

984
00:51:01,600 --> 00:51:03,960
middle exploration. 
Oh, I was just going to say just

985
00:51:03,960 --> 00:51:06,880
sort of on that theme as well. 
Do you think that that the 

986
00:51:06,880 --> 00:51:14,040
nature of the exploration sort 
of aggregator and the these sort

987
00:51:14,040 --> 00:51:18,720
of behavioural economics that we
sort of say heuristics, we sort 

988
00:51:18,720 --> 00:51:23,880
of say, do you think it makes it
sort of a more suitable in a 

989
00:51:23,880 --> 00:51:27,000
sort of private capital market 
as opposed to public look, I 

990
00:51:27,040 --> 00:51:28,000
think. 
Naturally, yeah. 

991
00:51:28,480 --> 00:51:32,440
I think there is a natural 
tendency for that to be so, 

992
00:51:32,480 --> 00:51:34,440
yeah. 
Well, like long term patient 

993
00:51:34,440 --> 00:51:37,280
capital because it's just the 
public markets just I don't 

994
00:51:37,280 --> 00:51:39,520
think could could cope with 
something like this even though 

995
00:51:39,520 --> 00:51:42,240
it makes. 
Well, the public markets could 

996
00:51:42,240 --> 00:51:45,800
invest in the in the in the 
aggregator in the same way 

997
00:51:45,800 --> 00:51:48,680
people invest in sort of 
Berkshire Hathaway, for example,

998
00:51:48,720 --> 00:51:51,160
if it was successful, but they 
probably wouldn't do it until it

999
00:51:51,480 --> 00:51:53,960
had demonstrated some success. 
Yeah, I think those investors 

1000
00:51:53,960 --> 00:51:55,520
are few and far between. 
Yeah. 

1001
00:51:55,920 --> 00:51:58,720
But you can see, sorry, the 
yeah, you can see that in I 

1002
00:51:58,720 --> 00:52:01,520
guess other industries. 
I think the VC world, you know, 

1003
00:52:01,520 --> 00:52:04,920
like they there is very little 
involvement in in kind of the 

1004
00:52:04,920 --> 00:52:08,320
startup world, the VC driven 
startup world from public 

1005
00:52:08,440 --> 00:52:10,320
entities, right. 
Like they're often the, you 

1006
00:52:10,320 --> 00:52:12,200
know, they're never come in in 
the early money, but they're 

1007
00:52:12,200 --> 00:52:15,600
happy to come in in like, you 
know, series BC whatever after 

1008
00:52:15,600 --> 00:52:18,000
that. 
But yeah, that I think, I think 

1009
00:52:18,000 --> 00:52:19,560
that is a fundamental kind of 
constraint. 

1010
00:52:20,080 --> 00:52:23,120
I want to just really tie this 
into a real world example 

1011
00:52:23,120 --> 00:52:25,760
because you've, you've put all 
this, this work in, but what 

1012
00:52:25,760 --> 00:52:29,080
we've seen since this paper come
out is like you say, BHP 

1013
00:52:29,080 --> 00:52:32,560
explores programme and you know 
it, it, it is remarkable to me 

1014
00:52:32,560 --> 00:52:36,320
at at every turn in incentives 
are just in your face and you, 

1015
00:52:36,360 --> 00:52:39,240
you highlight there that you 
need to incentivize the, the 

1016
00:52:39,240 --> 00:52:41,760
smaller company, whether that be
the people, everyone at every 

1017
00:52:41,760 --> 00:52:46,040
stage needs to be incentivized 
by the ultimate outcome. 

1018
00:52:47,120 --> 00:52:50,080
Now BHB explore has actually 
started to do this. 

1019
00:52:50,080 --> 00:52:53,080
They've had a couple schools now
or groups of. 

1020
00:52:53,400 --> 00:52:55,560
Cohorts, I think they call. 
Them cohorts that that's the 

1021
00:52:55,560 --> 00:52:57,640
one. 
And I mean in your model you put

1022
00:52:57,640 --> 00:53:00,120
forward the example that it can 
be a major mining company, it 

1023
00:53:00,120 --> 00:53:03,840
could be a direct agent, it 
could be a specialist third 

1024
00:53:03,840 --> 00:53:08,920
party. 
Do you think a a BHB is the the 

1025
00:53:08,920 --> 00:53:12,640
best type of company to do this?
And given that they've now put 

1026
00:53:12,640 --> 00:53:15,640
this into practise, where would 
you sort of guide them on 

1027
00:53:15,960 --> 00:53:17,680
improving what they've? 
Done well, first of all, I think

1028
00:53:17,680 --> 00:53:21,320
it's great that they're doing it
because I, I think they need to 

1029
00:53:21,320 --> 00:53:22,960
do it. 
And one of the reasons they need

1030
00:53:22,960 --> 00:53:25,560
to do it is I actually don't 
think we have a globally 

1031
00:53:25,560 --> 00:53:28,800
successful model. 
And I've worked in, in large 

1032
00:53:28,800 --> 00:53:31,640
global companies have tried to 
do global exploration. 

1033
00:53:31,800 --> 00:53:35,720
It's very difficult to do as as 
one company there are there, you

1034
00:53:35,720 --> 00:53:37,480
know, there's a lot of 
overheads, there's an increasing

1035
00:53:37,480 --> 00:53:40,960
amount of internal friction that
prevents that being done. 

1036
00:53:40,960 --> 00:53:43,000
So. 
Just the also just the level of 

1037
00:53:43,000 --> 00:53:46,200
organisational complexity you 
need to work in, you know, 

1038
00:53:46,200 --> 00:53:49,320
Australia at the same time work 
in the high Andies, you know, 

1039
00:53:49,320 --> 00:53:51,400
like it's just not like it's a 
complicated. 

1040
00:53:51,400 --> 00:53:54,960
Exercise, yeah, yeah. 
So, so I, I, and I don't, I 

1041
00:53:54,960 --> 00:53:57,440
don't think, you know, and if 
you think about the history of 

1042
00:53:57,440 --> 00:54:02,720
our industry, you know, when I 
started, unfortunately over 40 

1043
00:54:02,720 --> 00:54:06,200
years ago now, but we didn't 
really have this concept of 

1044
00:54:06,200 --> 00:54:08,480
people exploring globally. 
You know, there was only four or

1045
00:54:08,480 --> 00:54:10,280
five countries in the Western 
world. 

1046
00:54:10,280 --> 00:54:12,080
People would mostly explore in 
any way. 

1047
00:54:12,360 --> 00:54:14,000
And if you're in Australia, you 
explored there. 

1048
00:54:14,000 --> 00:54:15,360
If you're in America, you 
explore there. 

1049
00:54:15,400 --> 00:54:18,480
And it was only really after the
end of the Cold War and we had 

1050
00:54:18,480 --> 00:54:23,040
this big era of globalisation 
that we started to try and think

1051
00:54:23,040 --> 00:54:25,400
about exploring globally. 
And I think at one point in the 

1052
00:54:25,400 --> 00:54:28,440
late 90s, BHP, for example, in 
48 countries, right? 

1053
00:54:29,160 --> 00:54:34,000
And that's 48 officers, 48, you 
know, groups of people now that 

1054
00:54:34,000 --> 00:54:36,360
didn't last that long. 
Western mining we're in about 

1055
00:54:36,360 --> 00:54:39,000
25. 
It's, it's not really 

1056
00:54:39,080 --> 00:54:41,760
sustainable. 
And I just think it's too 

1057
00:54:41,760 --> 00:54:45,120
difficult with, with time zones 
with as Ahmad says, internal 

1058
00:54:45,120 --> 00:54:50,000
complexities, all the, the, the 
constraints, particularly around

1059
00:54:51,200 --> 00:54:53,120
licence to operate issues and so
on. 

1060
00:54:53,480 --> 00:54:58,520
So a model like Explorer is 
probably what is what is 

1061
00:54:58,520 --> 00:55:02,200
required. 
But there there's a few key 

1062
00:55:02,200 --> 00:55:04,520
aspects that are required to 
make that model work. 

1063
00:55:04,760 --> 00:55:09,040
One, you need really, really 
good experienced technical 

1064
00:55:09,040 --> 00:55:12,560
people who are providing that 
philtre, right. 

1065
00:55:12,880 --> 00:55:17,240
So you know, you need people who
really have been in the industry

1066
00:55:17,440 --> 00:55:19,640
for many, yeah, this is an 
industry where it actually 

1067
00:55:19,640 --> 00:55:21,280
matters. 
Experience matters, the right 

1068
00:55:21,280 --> 00:55:24,000
sort of experience, but it 
actually is important. 

1069
00:55:24,000 --> 00:55:26,480
So it needs to be guided by 
that. 

1070
00:55:27,120 --> 00:55:31,560
Secondly, the commercial 
frameworks need to be such that 

1071
00:55:31,760 --> 00:55:35,040
people want to bring their best 
projects in, not just the 

1072
00:55:35,040 --> 00:55:38,480
projects they don't think could 
get funded in the risk capital 

1073
00:55:38,480 --> 00:55:40,920
market, right? 
So, you know, to me, that's the 

1074
00:55:40,920 --> 00:55:45,080
test of a model like Explore. 
Are people bringing a project in

1075
00:55:45,080 --> 00:55:47,640
because it's their core project,
it's the one they really believe

1076
00:55:47,640 --> 00:55:50,800
in, or are they bringing it in 
because it's not their core 

1077
00:55:50,800 --> 00:55:53,080
project, they're kind of 
interested in it and they think 

1078
00:55:53,080 --> 00:55:55,840
this is an alternative Ave for 
funding. 

1079
00:55:56,240 --> 00:55:59,320
And that gets back to you know, 
you know, and I'm not not 

1080
00:55:59,320 --> 00:56:02,280
familiar with any of those sort 
of details of those commercial 

1081
00:56:02,280 --> 00:56:05,720
agreements, but but 
fundamentally that gets back to 

1082
00:56:05,720 --> 00:56:08,080
that attractiveness. 
And of course like everything in

1083
00:56:08,080 --> 00:56:09,680
life, branding and marketing, 
right. 

1084
00:56:10,360 --> 00:56:13,880
So if you have successes and 
this is a successful model and 

1085
00:56:15,520 --> 00:56:19,680
to be a successful model it has 
to be successful for BHP and 

1086
00:56:19,680 --> 00:56:23,920
it's shareholders, but also 
successful for individual 

1087
00:56:23,920 --> 00:56:28,880
companies within that, you know,
So by being part of the scheme, 

1088
00:56:28,880 --> 00:56:31,920
companies have to be at least 
not worse off, maybe a bit 

1089
00:56:31,920 --> 00:56:35,080
better off just by being in it. 
And then of course, not all of 

1090
00:56:35,080 --> 00:56:37,360
them are going to be successful,
but if they are successful, 

1091
00:56:37,600 --> 00:56:40,080
they're going to have have to be
seen to have benefited 

1092
00:56:40,080 --> 00:56:44,200
significantly from that success 
as opposed to the default 

1093
00:56:44,200 --> 00:56:46,920
alternative which is raising 
capital on the risk capital 

1094
00:56:46,920 --> 00:56:48,880
market, the public markets and 
so on. 

1095
00:56:50,200 --> 00:56:51,840
I think I think to your 
question, like, you know, 

1096
00:56:51,840 --> 00:56:54,800
whether it could be done most 
effectively the major mining 

1097
00:56:54,800 --> 00:56:58,160
company or or not. 
You know, like if you take the 

1098
00:56:58,160 --> 00:57:01,440
example out of out of mining 
into other industries, you know,

1099
00:57:01,440 --> 00:57:04,240
like say like AVC that does it, 
you know, accelerate a programme

1100
00:57:04,240 --> 00:57:06,080
or something like that. 
You know, I think the one 

1101
00:57:06,080 --> 00:57:08,640
fundamental difference is that 
the VC doesn't have a vested 

1102
00:57:08,640 --> 00:57:12,640
interest in the entity that's 
being produced by the startup or

1103
00:57:12,640 --> 00:57:14,520
the product that's being 
produced by the startup. 

1104
00:57:14,880 --> 00:57:18,280
Whereas I think in BHP that you 
know, like that's where I think 

1105
00:57:18,280 --> 00:57:22,600
you have to have a really sound 
commercial model because ABHP is

1106
00:57:22,600 --> 00:57:25,360
kind of facilitating the 
accelerator programme, you know,

1107
00:57:25,360 --> 00:57:28,280
call it whatever. 
But then at the end, they're 

1108
00:57:28,280 --> 00:57:31,200
also the customer that wants to 
kind of get right. 

1109
00:57:31,200 --> 00:57:33,160
And I'm and I think they're. 
Existential for them. 

1110
00:57:33,160 --> 00:57:35,880
Isn't it really ultimately that 
this programme is successful? 

1111
00:57:35,880 --> 00:57:37,760
That's a. 
That is a pretty pretty 

1112
00:57:37,760 --> 00:57:40,160
important distinction. 
So I think they have to navigate

1113
00:57:40,160 --> 00:57:43,440
that internally as well as the 
the companies that are coming to

1114
00:57:43,440 --> 00:57:47,040
them in a, in a, in a different 
way I think than a standard kind

1115
00:57:47,040 --> 00:57:49,640
of accelerator model where, you 
know, VCs are just coming in as 

1116
00:57:49,640 --> 00:57:51,800
an investor. 
And then they, you know, like 

1117
00:57:51,800 --> 00:57:54,680
they want to help the company 
get somewhere, but they don't 

1118
00:57:54,680 --> 00:57:57,560
have a vested interest in that, 
in that product or that outcome 

1119
00:57:57,560 --> 00:57:59,840
of that of that company. 
I think that's a very good 

1120
00:57:59,840 --> 00:58:02,200
point. 
So that, I think is a challenge 

1121
00:58:02,200 --> 00:58:05,480
of how you do it internally. 
But, you know, like, to be 

1122
00:58:05,480 --> 00:58:07,640
honest, the best agents we 
currently have in the industry 

1123
00:58:07,640 --> 00:58:10,080
to do that I think are probably 
major mining companies, yeah. 

1124
00:58:10,400 --> 00:58:13,320
Well, I think they're the ones 
with the most skin in the game, 

1125
00:58:13,320 --> 00:58:14,000
right? 
Yeah. 

1126
00:58:14,000 --> 00:58:17,200
So if you analyse, you know, and
I've done this thought process 

1127
00:58:17,200 --> 00:58:19,600
of sort of analysing, who cares,
right? 

1128
00:58:19,640 --> 00:58:22,200
Ultimately, who cares that 
there's not efficient allocation

1129
00:58:22,200 --> 00:58:25,120
of capital to global greenfields
exploration? 

1130
00:58:25,440 --> 00:58:27,960
Well, the the biggest 
stakeholders are these large 

1131
00:58:28,040 --> 00:58:30,320
multi generational mining 
companies, right? 

1132
00:58:30,760 --> 00:58:33,160
And then that's just like, you 
know, like if like in the space 

1133
00:58:33,160 --> 00:58:35,520
of exploration, if you're a 
major mining company and there's

1134
00:58:35,520 --> 00:58:39,240
not an effective allocation of 
capital to make new discoveries,

1135
00:58:39,560 --> 00:58:41,720
then you know, like at some 
point your business is going to 

1136
00:58:41,720 --> 00:58:43,880
struggle because it's going to 
have to buy things at a higher 

1137
00:58:43,880 --> 00:58:47,880
and higher premium to add to 
your, your reserve base or your 

1138
00:58:47,880 --> 00:58:49,920
business base. 
But at some point, they just 

1139
00:58:49,920 --> 00:58:53,520
won't be the assets that can 
generate the metal, correct, at 

1140
00:58:53,520 --> 00:58:56,480
a cost that makes sense. 
So I suppose just thinking 

1141
00:58:56,560 --> 00:58:59,800
through that one step further, 
at some point it becomes 

1142
00:58:59,800 --> 00:59:02,800
societal or a, or a, or a 
governmental issue. 

1143
00:59:02,800 --> 00:59:06,440
And of course, that's something 
that's changed in my career 

1144
00:59:06,440 --> 00:59:10,120
because it's only been in the 
last half a decade or so that 

1145
00:59:10,120 --> 00:59:14,960
we've started to see a serious 
involvement at a global level in

1146
00:59:14,960 --> 00:59:17,720
terms of governments and people 
thinking about minerals. 

1147
00:59:17,720 --> 00:59:20,480
Because, you know, for most of 
my career, minerals and mining 

1148
00:59:20,480 --> 00:59:23,480
was, was to be honest, looked 
down on and, and seen as somehow

1149
00:59:23,480 --> 00:59:26,240
inferior to technology and all, 
all these other things. 

1150
00:59:26,720 --> 00:59:28,560
And it's just something you took
for granted. 

1151
00:59:28,560 --> 00:59:31,080
And now we know that we're in a 
world where we can't do that. 

1152
00:59:31,720 --> 00:59:33,640
There's no interest like self 
interest, right? 

1153
00:59:33,960 --> 00:59:37,760
That's the companies get on it. 
There's this concept I, I read 

1154
00:59:37,760 --> 00:59:41,600
about, I hear about a lot of 
these companies from, you know, 

1155
00:59:42,240 --> 00:59:44,800
you know, from back in the day 
that were really technically 

1156
00:59:44,800 --> 00:59:48,240
focused, that had great cultures
and everything and Western 

1157
00:59:48,240 --> 00:59:50,880
mining comes to mind and there's
a few others. 

1158
00:59:51,160 --> 00:59:54,840
Do you think this is a rose 
tinted view on the past or was 

1159
00:59:54,840 --> 00:59:57,520
there something distinctly 
different about how they 

1160
00:59:57,520 --> 01:00:01,200
operated? 
I think first of all that there.

1161
01:00:02,360 --> 01:00:05,200
I mean, some of it is obviously,
you know, there was always those

1162
01:00:05,200 --> 01:00:07,160
raised tinted glasses, but I 
think there's some real 

1163
01:00:07,160 --> 01:00:08,880
substance to it. 
But I think you've also got to 

1164
01:00:08,880 --> 01:00:11,960
see it in in context, right. 
So one of the things that 

1165
01:00:11,960 --> 01:00:15,400
Western mining did, for example,
very concrete thing that I don't

1166
01:00:15,400 --> 01:00:18,800
think any organisation does on 
the same scale today is its 

1167
01:00:18,800 --> 01:00:20,040
study leave scheme. 
Yeah. 

1168
01:00:20,120 --> 01:00:23,760
So it would provide, and pretty 
much any, any talented 

1169
01:00:24,520 --> 01:00:27,800
geoscientist would get funded 
for half salary for a year to go

1170
01:00:27,800 --> 01:00:29,760
and do a master's. 
And then in the end, yeah, I 

1171
01:00:29,760 --> 01:00:32,480
mean, I, I got funded to a PhD, 
for example, I never would have 

1172
01:00:32,480 --> 01:00:35,720
been able to do it otherwise. 
So I was a beneficiary of that. 

1173
01:00:36,040 --> 01:00:40,400
So there was that very, very 
significant investment in 

1174
01:00:40,400 --> 01:00:42,920
development. 
It's one of the reasons why, you

1175
01:00:42,920 --> 01:00:45,480
know, people used to talk about 
Western mining as the university

1176
01:00:45,480 --> 01:00:49,160
to the industry because it did 
that and it probably did that a 

1177
01:00:49,160 --> 01:00:53,000
lot more than other companies, 
but but that was a more common 

1178
01:00:53,000 --> 01:00:55,000
thing. 
But they held on to the people. 

1179
01:00:55,200 --> 01:00:58,080
Yeah, correct. 
So, so there's a couple aspects 

1180
01:00:58,080 --> 01:01:00,600
about that. 
One, it was a world where the 

1181
01:01:00,600 --> 01:01:03,320
culture was more like, I've 
joined this company and I'll 

1182
01:01:03,320 --> 01:01:06,440
work for them, you know, for a 
long time to retirement that, 

1183
01:01:06,680 --> 01:01:10,480
that was a different world to, 
to, to, to what we have today. 

1184
01:01:11,400 --> 01:01:14,760
But the flip side of it is when 
you invest in your people, 

1185
01:01:14,800 --> 01:01:16,520
you're more likely to keep them 
anyway. 

1186
01:01:16,520 --> 01:01:21,400
So I, I do feel that it's 
interesting that companies 

1187
01:01:21,400 --> 01:01:26,040
today, which are, you know, plus
10 times the sort of market cap 

1188
01:01:26,040 --> 01:01:30,360
of what Western mining ever was,
don't invest in, in this sort of

1189
01:01:30,360 --> 01:01:31,880
training. 
I mean, if they do it, they do 

1190
01:01:31,880 --> 01:01:35,640
it very, very sporadically. 
But one of their pillars is 

1191
01:01:35,640 --> 01:01:38,240
people is our biggest resource, 
John, But yeah. 

1192
01:01:38,280 --> 01:01:40,440
Yeah, I know they're. 
Far more profitable than than 

1193
01:01:40,440 --> 01:01:41,640
Western. 
Yeah, yeah. 

1194
01:01:42,000 --> 01:01:44,120
I mean, I can only give my 
example, you know, like I 

1195
01:01:44,120 --> 01:01:47,160
remember going into, you know, 
like my career corresponded with

1196
01:01:47,160 --> 01:01:49,640
the end of WMC and the start of 
it being in BHP. 

1197
01:01:49,800 --> 01:01:51,840
And I remember going into a 
group where there was, you know,

1198
01:01:51,840 --> 01:01:54,480
like eight of us. 
And I think all of them were ex 

1199
01:01:54,480 --> 01:01:58,160
WMC people and all of them had 
been there 15 plus years, right.

1200
01:01:58,160 --> 01:02:01,160
Like I, I don't think I've ever 
walked into a group now where 

1201
01:02:01,160 --> 01:02:06,120
you could get that level of of 
kind of longevity in, in the 

1202
01:02:06,120 --> 01:02:08,240
company, right. 
But but to your point, you know,

1203
01:02:08,240 --> 01:02:10,520
like we're talking about that 
learning curve kind of kind of 

1204
01:02:10,520 --> 01:02:13,160
model, you know, like I think 
that was a great thing that they

1205
01:02:13,160 --> 01:02:16,880
could a, allow people to get 
better to like train them, but 

1206
01:02:16,880 --> 01:02:19,680
also just keep them for a long, 
long time in in that sense. 

1207
01:02:19,680 --> 01:02:23,240
And then that IP stays in the 
business, yeah, because 

1208
01:02:23,280 --> 01:02:26,640
otherwise that learning curve, 
as we sort of discussed before, 

1209
01:02:28,040 --> 01:02:30,440
yeah, obviously there's, you 
know, the physical and the data 

1210
01:02:30,440 --> 01:02:33,880
and all that, but the IP that 
sits up here is now gone over 

1211
01:02:33,880 --> 01:02:36,520
there and over there and it just
stalls that whole. 

1212
01:02:36,520 --> 01:02:40,160
Process so one of the unusual 
aspects of that western mining 

1213
01:02:40,160 --> 01:02:42,360
system was the concept of the 
guilds. 

1214
01:02:42,360 --> 01:02:43,960
The geoscientists were in a 
Guild. 

1215
01:02:43,960 --> 01:02:47,240
So I might be working as a mine 
geologist of a particular mine 

1216
01:02:47,480 --> 01:02:50,320
or I might be working as an 
exploration geologist somewhere.

1217
01:02:50,600 --> 01:02:53,840
But there was the idea that 
someone was looking at the whole

1218
01:02:53,840 --> 01:02:57,520
group of geoscientists and 
actually making decisions like 

1219
01:02:57,800 --> 01:03:00,720
we're going to send him to a 
mind for two years to get this 

1220
01:03:01,320 --> 01:03:04,720
experience or they're going on 
study leave or they're going to 

1221
01:03:04,720 --> 01:03:08,200
exploration. 
So the discipline was managed 

1222
01:03:08,400 --> 01:03:11,200
holistically. 
And you know, what we saw 

1223
01:03:11,200 --> 01:03:15,200
changing in the 90s with the 
rise of HR culture and and 

1224
01:03:15,200 --> 01:03:17,720
direct sort of, you know, 
management control that I mean 

1225
01:03:17,720 --> 01:03:22,240
that was seen as and a 
necrotistic archaic and maybe a 

1226
01:03:22,760 --> 01:03:24,440
challenge to. 
And a cost item. 

1227
01:03:25,320 --> 01:03:28,400
Yeah, and a challenge to to sort
of management authority. 

1228
01:03:28,400 --> 01:03:30,800
And so all that got got 
dismantled. 

1229
01:03:31,240 --> 01:03:34,680
And I don't think in large 
organisations there's much 

1230
01:03:34,680 --> 01:03:38,000
discussion that goes on of, you 
know, here's my org chart of the

1231
01:03:38,000 --> 01:03:40,360
300 geologists I have in this 
organisation. 

1232
01:03:40,360 --> 01:03:43,480
And this is how, you know, 
we're, we're going to these, we 

1233
01:03:43,480 --> 01:03:45,560
think these are the talent, 
these are the ones we have to do

1234
01:03:45,560 --> 01:03:47,320
it. 
It's very much individuals 

1235
01:03:47,320 --> 01:03:50,520
fighting their way through 
whatever silos that exist, 

1236
01:03:50,520 --> 01:03:54,000
whether it's at an operation or 
in an exploration group. 

1237
01:03:55,240 --> 01:03:57,920
It's amazing because, you know, 
there are other industries that 

1238
01:03:57,920 --> 01:04:00,760
that try and do this, but what 
they do is just make your pay 

1239
01:04:00,760 --> 01:04:03,520
vest way down the track and they
try and lock you in. 

1240
01:04:03,520 --> 01:04:06,000
So the fact that Western mining 
could could do this without 

1241
01:04:06,000 --> 01:04:08,760
just, you know, essentially 
holding your pay from you. 

1242
01:04:08,760 --> 01:04:09,960
Yeah. 
Yeah, that's why. 

1243
01:04:09,960 --> 01:04:12,960
And it's also like, you know, to
your common alley about like the

1244
01:04:12,960 --> 01:04:15,480
IP and like there's there's this
great book and I can't remember 

1245
01:04:15,480 --> 01:04:17,560
the author's name. 
It's called where good ideas 

1246
01:04:17,560 --> 01:04:18,680
come from. 
All right. 

1247
01:04:18,680 --> 01:04:21,320
And then, and then in the book 
they talk about that if you look

1248
01:04:21,320 --> 01:04:25,480
at kind of like the stream of 
innovation over the last 100 

1249
01:04:25,480 --> 01:04:28,800
years, you know, like it often 
develops with this, you know, 

1250
01:04:28,800 --> 01:04:32,000
like one person has one piece of
the puzzle and this other person

1251
01:04:32,000 --> 01:04:33,040
has the other piece of the 
puzzle. 

1252
01:04:33,200 --> 01:04:36,480
What you need is that 
connectedness between those 

1253
01:04:36,480 --> 01:04:39,480
ideas to kind of come together 
and, and become something, you 

1254
01:04:39,480 --> 01:04:42,280
know, so, so my like view on 
this is like, you know, like the

1255
01:04:42,280 --> 01:04:46,560
reason why I think organisations
like WMC and like CRA was 

1256
01:04:46,560 --> 01:04:49,280
another one that that was I 
think successful is because 

1257
01:04:49,560 --> 01:04:52,400
they, they had this right, that 
they kept that IP kind of 

1258
01:04:52,400 --> 01:04:55,160
bouncing around and hitting each
other in, in, in that same 

1259
01:04:55,160 --> 01:04:58,280
organisation. 
Now I think, you know, we, we 

1260
01:04:58,280 --> 01:05:00,840
may have still the same number 
of geologists, but now they're 

1261
01:05:00,840 --> 01:05:02,880
spread out over, you know, 1000 
companies. 

1262
01:05:03,160 --> 01:05:05,880
So I think that 
interconnectedness of ideas 

1263
01:05:05,880 --> 01:05:10,280
probably is not as efficient as 
it could be when it's in one 

1264
01:05:10,280 --> 01:05:13,720
organisation and it's being 
managed, like the talent is 

1265
01:05:13,720 --> 01:05:16,640
being managed holistically in 
that sense, you know. 

1266
01:05:16,640 --> 01:05:19,360
So I think that's kind of the 
challenge of why, you know, like

1267
01:05:19,360 --> 01:05:22,520
we sometimes struggle to kind of
progress along with ideas in 

1268
01:05:22,520 --> 01:05:25,040
some way as well. 
John, the the last thing I want 

1269
01:05:25,040 --> 01:05:27,160
to hear from you and you've, 
you've touched on this earlier, 

1270
01:05:27,160 --> 01:05:31,800
but AI, machine learning, all 
these things are clearly the, 

1271
01:05:31,880 --> 01:05:34,840
the buzzword of the last three 
years. 

1272
01:05:34,880 --> 01:05:38,920
Now I want to hear from you, 
given your, your sort of deep 

1273
01:05:38,920 --> 01:05:41,520
technical experience here and 
you, you've spoken about it in 

1274
01:05:41,520 --> 01:05:44,680
the, in the sense of big data 
and these sorts of things and 

1275
01:05:45,160 --> 01:05:46,880
search spaces. 
And we're going, we should be 

1276
01:05:46,880 --> 01:05:48,720
going to places that don't have 
the data. 

1277
01:05:49,200 --> 01:05:53,600
But what do you think will be 
the implications from this sort 

1278
01:05:53,600 --> 01:05:57,160
of wave of investment in AI 
specific to the the mineral 

1279
01:05:57,160 --> 01:06:00,320
exploration field? 
Look, this should have been the 

1280
01:06:00,320 --> 01:06:01,360
last thing we should have talked
about. 

1281
01:06:01,360 --> 01:06:02,800
This should be the first thing 
we should have talked about 

1282
01:06:02,800 --> 01:06:05,200
that. 
Look, my, my opinion is 

1283
01:06:05,200 --> 01:06:08,120
extremely limited will be the, 
the impact. 

1284
01:06:08,120 --> 01:06:13,160
And I, I, I say this both on the
basis of empirical experience. 

1285
01:06:14,600 --> 01:06:17,480
You know, we talked about the 
last three years there, there've

1286
01:06:17,480 --> 01:06:20,680
been people, very, very smart 
people way ahead of the curve 

1287
01:06:20,680 --> 01:06:24,600
doing this over a decade ago, 
spent probably $100 million 

1288
01:06:24,600 --> 01:06:26,440
without any success. 
And not because they weren't 

1289
01:06:26,440 --> 01:06:29,800
very smart and not because they 
didn't have the best technology.

1290
01:06:30,880 --> 01:06:33,320
So that's sort of the empirical 
experience. 

1291
01:06:33,920 --> 01:06:40,120
The the conceptual reason is 
that I think the critical thing 

1292
01:06:40,120 --> 01:06:43,680
that we need to understand is 
what defines a big data 

1293
01:06:43,680 --> 01:06:47,720
environment, meaning, you know, 
big data as in a set of a 

1294
01:06:47,720 --> 01:06:50,240
problem set that is amenable to 
AI. 

1295
01:06:50,680 --> 01:06:54,280
And in my opinion, where people 
get confused is I think it's a 

1296
01:06:54,280 --> 01:06:57,240
big data environment if the 
available data can be measured 

1297
01:06:57,240 --> 01:07:01,600
in the terabytes. 
But if that available data does 

1298
01:07:01,600 --> 01:07:07,560
not very well represent the 
parameter space of interest, I I

1299
01:07:07,560 --> 01:07:08,880
think you've got a problem, 
right. 

1300
01:07:08,960 --> 01:07:13,280
Yeah, because our parameter 
space of interest I think is a 

1301
01:07:13,280 --> 01:07:17,880
poor data environment. 
So conceptually, I don't think 

1302
01:07:18,240 --> 01:07:21,880
AI can ever do very well at 
targeting in these poor data 

1303
01:07:21,880 --> 01:07:25,520
environments. 
In principle, what it should be 

1304
01:07:25,520 --> 01:07:30,600
able to do is help us learn in 
our data rich environments and 

1305
01:07:30,600 --> 01:07:34,520
extract patterns from that. 
So in principle, I accept that 

1306
01:07:34,520 --> 01:07:37,280
as a possibility. 
But I have to say I haven't yet 

1307
01:07:37,280 --> 01:07:40,000
seen any good examples. 
And you know, some of the 

1308
01:07:40,000 --> 01:07:42,640
companies I'm involved with have
invested in, in some of this. 

1309
01:07:42,640 --> 01:07:45,040
And to be honest, we've been 
disappointed with the examples. 

1310
01:07:45,040 --> 01:07:51,080
But I'm not an AI specialist so 
I I don't know exactly why these

1311
01:07:51,080 --> 01:07:56,200
things have not worked but but 
my just lived experience so far 

1312
01:07:56,480 --> 01:08:00,160
is I haven't seen anything that 
that's added value. 

1313
01:08:01,040 --> 01:08:04,040
And I think to like to the 
comment about like why I think 

1314
01:08:04,040 --> 01:08:05,960
it's somewhat struggle. 
I mean, John and I've talked 

1315
01:08:05,960 --> 01:08:09,320
about this a fair bit where, you
know, like we get approaches by 

1316
01:08:09,320 --> 01:08:12,240
people trying to come in and you
know, like apply and more AI 

1317
01:08:12,240 --> 01:08:15,400
machine learning approach. 
And I think one of the, the, the

1318
01:08:15,400 --> 01:08:18,200
fundamental issues I think comes
from is that, you know, like, 

1319
01:08:18,479 --> 01:08:20,880
like John said, in mineral 
exploration, we are very data 

1320
01:08:20,880 --> 01:08:23,720
poor environment. 
You know, like we collect data, 

1321
01:08:23,720 --> 01:08:28,040
but we collected in, you know, 
select areas quite well, but we 

1322
01:08:28,040 --> 01:08:30,720
don't like, we rarely collect 
holistic data. 

1323
01:08:30,720 --> 01:08:33,479
You know, the data resolutions 
are always quite different in 

1324
01:08:33,479 --> 01:08:36,160
different parts of what we are 
trying to solve, unless it's a 

1325
01:08:36,160 --> 01:08:38,399
very small area, then you know, 
like maybe someone flies a 

1326
01:08:38,399 --> 01:08:40,160
geophysics survey or something 
like that at the same 

1327
01:08:40,160 --> 01:08:43,200
resolution. 
So there's two kind of problems.

1328
01:08:43,200 --> 01:08:47,720
One is that we are a data poor 
environment and B, we, we have 

1329
01:08:47,720 --> 01:08:50,359
this, I think changing rate of 
false positives, right? 

1330
01:08:50,359 --> 01:08:53,279
Like once you, you have to have 
a certain level of testing to 

1331
01:08:53,279 --> 01:08:56,359
figure out whether the anomalies
that you've identified are 

1332
01:08:56,359 --> 01:08:59,000
appropriate or not. 
And so, and machine learning 

1333
01:08:59,000 --> 01:09:02,560
works really well when you have 
a large base rate of, of a 

1334
01:09:02,560 --> 01:09:05,120
training data set. 
You know, we don't always have 

1335
01:09:05,120 --> 01:09:07,200
that, you know, we're always 
tired to build this as we kind 

1336
01:09:07,200 --> 01:09:10,040
of go along. 
But one of the fundamental 

1337
01:09:10,040 --> 01:09:12,800
reasons, you know, like, like 
I've been guilty of applying a 

1338
01:09:12,800 --> 01:09:16,040
lot of AI in in, you know, 
expression with limited success.

1339
01:09:16,359 --> 01:09:19,840
And one of the issues I think I 
find with it is that, yeah, like

1340
01:09:19,960 --> 01:09:21,880
AI machine learning, I think 
mineral exploration will be 

1341
01:09:21,880 --> 01:09:25,160
really good at interrogating the
data sets when we have them. 

1342
01:09:25,479 --> 01:09:27,920
But often the challenge in 
mineral exploration is 

1343
01:09:28,080 --> 01:09:31,439
identifying where you should go 
collect data sets. 

1344
01:09:31,800 --> 01:09:34,720
And I don't think that is a 
question that will be best 

1345
01:09:34,720 --> 01:09:38,760
answered by machine learning. 
Unless we just accept that we're

1346
01:09:38,760 --> 01:09:41,319
going to spend millions of 
dollars collecting data sets 

1347
01:09:41,319 --> 01:09:44,960
everywhere at a set resolution, 
you know, like how we want to do

1348
01:09:44,960 --> 01:09:49,000
it, then I think, yeah, maybe we
can take our intellectual 

1349
01:09:49,000 --> 01:09:51,600
insights of what's an anomaly 
and what's not an anomaly and 

1350
01:09:51,600 --> 01:09:54,560
model it into a a, you know, ML 
model. 

1351
01:09:54,560 --> 01:09:55,840
And then you can go and look for
that. 

1352
01:09:56,160 --> 01:09:58,040
But I don't think we're there 
yet, right? 

1353
01:09:58,040 --> 01:10:00,080
Like we just don't have the 
amount of data. 

1354
01:10:00,400 --> 01:10:02,840
Look, I think the the issue of 
data is an important one. 

1355
01:10:02,840 --> 01:10:07,000
And I've had a number of of, of 
conversations, you know, the 

1356
01:10:07,080 --> 01:10:10,640
government agencies who want to 
improve their prospectivity. 

1357
01:10:10,640 --> 01:10:13,000
And it's like, well, should we 
invest in all this AI? 

1358
01:10:13,520 --> 01:10:15,800
And you say, well, don't do 
that. 

1359
01:10:15,880 --> 01:10:18,480
Invest in getting your 
fundamental data right. 

1360
01:10:18,680 --> 01:10:22,080
So for example, if you're 
dealing with an area that 

1361
01:10:22,080 --> 01:10:25,680
doesn't have, say, something 
like one kilometre grid gravity,

1362
01:10:25,960 --> 01:10:27,720
you can't do best practise 
targeting. 

1363
01:10:28,160 --> 01:10:32,760
So to me it's, it's kind of sort
of irrelevant whether you're 

1364
01:10:32,760 --> 01:10:36,000
developing your best AI to look 
at the magnetics and all the 

1365
01:10:36,000 --> 01:10:38,720
other datas you have when you're
missing a key data set. 

1366
01:10:39,200 --> 01:10:43,680
So I have a very, very strong 
bias to saying if you've got an 

1367
01:10:44,440 --> 01:10:47,880
increment of capital that you 
want to invest in moving a 

1368
01:10:47,880 --> 01:10:50,320
problem forward, collect that 
data. 

1369
01:10:50,560 --> 01:10:52,480
And yeah, we started this 
conversation. 

1370
01:10:52,480 --> 01:10:54,840
Jonas, you asked me about my 4 
rules and I only really got to 

1371
01:10:54,840 --> 01:10:56,600
rule 2. 
Yeah, I was just about to say 

1372
01:10:56,680 --> 01:10:59,440
#3. 
Rule 3 was collect your own 

1373
01:10:59,440 --> 01:11:02,080
primary data in the search space
of interest. 

1374
01:11:02,360 --> 01:11:05,840
And to Amad's point that he was 
just articulating, working out 

1375
01:11:05,840 --> 01:11:07,840
what that search base of 
interest is, is also an 

1376
01:11:07,840 --> 01:11:11,160
intellectual process and in fact
a key value creating process. 

1377
01:11:11,400 --> 01:11:14,600
But once you've done that, go 
and collect your your own own 

1378
01:11:14,720 --> 01:11:17,280
primary data. 
And rule 4, of course, something

1379
01:11:17,280 --> 01:11:20,400
we've touched on again and again
is learning from, test those 

1380
01:11:20,400 --> 01:11:22,960
targets and learn, learn from 
that. 

1381
01:11:23,320 --> 01:11:29,280
So I will any day of the week, 
say in most situations, you'd be

1382
01:11:29,280 --> 01:11:33,080
better off investing in 
collecting primary data. 

1383
01:11:33,080 --> 01:11:36,280
It has to be a primary data set 
that really helps you with what 

1384
01:11:36,280 --> 01:11:38,520
you're doing. 
Things like gravity are good 

1385
01:11:38,520 --> 01:11:41,000
because it goes to the 
fundamental architecture of the 

1386
01:11:41,000 --> 01:11:43,400
crust, which is which is always 
important. 

1387
01:11:44,080 --> 01:11:47,360
But you know, just coming back 
to, I think an interesting 

1388
01:11:47,360 --> 01:11:51,840
analogy when we think about 
domains where, you know, AI, 

1389
01:11:51,840 --> 01:11:54,800
deep learning or all of these 
things can work and they aren't,

1390
01:11:54,800 --> 01:11:57,920
is the comparison between 
weather forecasting over the 

1391
01:11:57,920 --> 01:12:01,040
last few decades and earthquake 
forecasting, right. 

1392
01:12:01,440 --> 01:12:04,480
So these are both very, very 
complex, non linear systems. 

1393
01:12:04,480 --> 01:12:07,160
You know, weather forecasting is
a classic chaotic, you know, the

1394
01:12:07,160 --> 01:12:11,680
butterfly flaps its wings and 
you know, the typhoon in in, or 

1395
01:12:11,680 --> 01:12:15,280
the tornado in Texas, whatever. 
But we've actually got a lot 

1396
01:12:15,280 --> 01:12:18,000
better with weather forecasting.
Weather forecasts are quite 

1397
01:12:18,120 --> 01:12:20,440
reasonable now. 
And that's through, you know, 

1398
01:12:20,440 --> 01:12:24,000
massive computing power and 
making all these models and, and

1399
01:12:24,000 --> 01:12:26,800
doing all this. 
On the other hand, earthquake 

1400
01:12:26,800 --> 01:12:28,880
forecasting is still really 
poor. 

1401
01:12:29,200 --> 01:12:33,360
And we had a big earthquake in 
Christchurch going back a few 

1402
01:12:33,360 --> 01:12:37,000
years ago. 
Devastating it was on a fault 

1403
01:12:37,000 --> 01:12:39,440
that wasn't even recognised. 
It wasn't even in the model, 

1404
01:12:39,480 --> 01:12:42,080
right. 
So with weather forecasting, we 

1405
01:12:42,080 --> 01:12:45,480
now through satellites and 
whatever, we have a pretty good 

1406
01:12:45,480 --> 01:12:49,120
characterization of our system, 
IE the atmosphere and the ocean 

1407
01:12:49,120 --> 01:12:51,360
atmosphere or the land 
atmosphere interface. 

1408
01:12:51,560 --> 01:12:53,960
So, so we've got a pretty and 
we'll get better, but we've got 

1409
01:12:53,960 --> 01:12:56,400
a pretty good model for it. 
When it comes to something like 

1410
01:12:56,400 --> 01:13:02,560
earthquake forecasting, we have 
a very poor model of the 

1411
01:13:02,560 --> 01:13:05,080
relevant search base, which is 
the rock mass underneath us. 

1412
01:13:05,560 --> 01:13:07,520
And then you think about mineral
deposits, it's not just 

1413
01:13:07,520 --> 01:13:10,160
forecasting 1 earthquake, it's 
forecasting a bunch of 

1414
01:13:10,160 --> 01:13:12,840
earthquakes that happened 2 1/2 
billion years ago, right, so. 

1415
01:13:13,440 --> 01:13:15,480
And the time interaction and all
these type of things. 

1416
01:13:15,680 --> 01:13:18,560
And so I think this is kind of 
the the concept like, yeah, like

1417
01:13:18,560 --> 01:13:23,440
I think machine learning solves 
computationally heavy tasks. 

1418
01:13:23,440 --> 01:13:25,520
Like, you know, that's where 
it's got to, you know, we're not

1419
01:13:25,520 --> 01:13:29,160
at a point now where the true 
artificial intelligence that, 

1420
01:13:29,160 --> 01:13:31,200
you know, we've created 
something that that that can 

1421
01:13:31,200 --> 01:13:33,240
kind of come in and, and solve 
that problem. 

1422
01:13:33,440 --> 01:13:35,520
And so the domains where it's 
really struggled is where you 

1423
01:13:35,520 --> 01:13:37,880
actually need that. 
The answer is in the 

1424
01:13:37,880 --> 01:13:42,080
intelligence of how you 
contextualise data and review it

1425
01:13:42,080 --> 01:13:44,520
and do that. 
And humans are still, I think, 

1426
01:13:44,520 --> 01:13:47,400
far better at it, you know, than
than any computer we have 

1427
01:13:47,400 --> 01:13:50,840
currently. 
I just had one final question 

1428
01:13:51,400 --> 01:13:54,160
reflecting on sort of what we've
discussed today. 

1429
01:13:54,720 --> 01:13:57,520
Do you think there is really a 
case for a single asset 

1430
01:13:57,520 --> 01:14:01,400
exploration company? 
That's a good question. 

1431
01:14:01,920 --> 01:14:04,320
A Greenfield's expiration. 
No, no, I don't. 

1432
01:14:04,360 --> 01:14:06,680
But I think that pretty much you
have to. 

1433
01:14:07,520 --> 01:14:11,640
I mean, one of the issues here 
relates to the quantum of 

1434
01:14:11,640 --> 01:14:15,000
capital like that can be raised.
And I don't know whether any of 

1435
01:14:15,000 --> 01:14:17,080
you guys have heard of Mike 
Etheridge. 

1436
01:14:17,080 --> 01:14:19,680
He was a big leader of our 
industry about 20 years ago. 

1437
01:14:20,400 --> 01:14:24,680
He wrote some pretty influential
stuff and he was the first guy 

1438
01:14:24,680 --> 01:14:28,040
to really sit down and try and 
provide some quantitative 

1439
01:14:28,520 --> 01:14:31,800
analysis around exploration. 
And he actually published a 

1440
01:14:31,800 --> 01:14:36,120
paper, I think it was about 
early 2000s, where he bemoaned 

1441
01:14:36,120 --> 01:14:39,720
the fact that when you looked at
the dynamics of the industry, 

1442
01:14:39,720 --> 01:14:43,160
the typical IPO raise was 4 or 
5,000,000 bucks. 

1443
01:14:43,160 --> 01:14:46,120
And that was pathetic. 
Of course, it's still about four

1444
01:14:46,120 --> 01:14:47,360
or five billion, correct? 
Yeah. 

1445
01:14:47,480 --> 01:14:51,040
And that four or 5 billion bucks
is now worth about half as much 

1446
01:14:51,040 --> 01:14:53,560
as what it was. 
That's how when ASX costs have 

1447
01:14:53,560 --> 01:14:57,520
only gone up. 
Yeah, and ASX costs, heritage 

1448
01:14:57,520 --> 01:15:03,200
costs, ground costs. 
So, you know, the, the reality 

1449
01:15:03,200 --> 01:15:07,360
is that you know, companies, you
know, they float, they raise 

1450
01:15:07,360 --> 01:15:09,000
money. 
This is my project, right? 

1451
01:15:09,440 --> 01:15:12,360
And I suppose that's what the 
investors are investing in. 

1452
01:15:12,760 --> 01:15:16,920
But realistically, what you are 
always investing in is a team 

1453
01:15:17,640 --> 01:15:21,160
that hopefully will explore that
project. 

1454
01:15:21,600 --> 01:15:25,480
And if that fails, if you're 
not, which it probably will if 

1455
01:15:25,480 --> 01:15:28,040
you're not very lucky, it will 
then get the next project and 

1456
01:15:28,040 --> 01:15:29,880
the next project and the next 
project right. 

1457
01:15:30,840 --> 01:15:33,360
I think that's the the perfect 
spot to leave the conversation. 

1458
01:15:33,400 --> 01:15:35,200
Thanks a lot for your time, John
and Ahmad. 

1459
01:15:35,200 --> 01:15:36,680
This has been a fascinating 
conversation. 

1460
01:15:36,720 --> 01:15:37,720
Appreciate it. 
Thanks a lot. 

1461
01:15:37,920 --> 01:15:39,160
I love this stuff. 
Cheers. 

1462
01:15:39,520 --> 01:15:42,920
Alrighty, thank you very much 
Ahmed Ali and John Ronsky. 

1463
01:15:42,920 --> 01:15:46,120
I was a great chat and. 
Thank you to you too for you 

1464
01:15:46,120 --> 01:15:48,440
smashed it out. 
No, I loved it lots. 

1465
01:15:48,440 --> 01:15:52,240
And yeah, no, there's certainly 
sometimes it's easy to forget 

1466
01:15:52,240 --> 01:15:55,640
all the, the heuristics and 
biases we have as a, you know, 

1467
01:15:55,640 --> 01:15:57,200
investors and mining companies 
have. 

1468
01:15:57,200 --> 01:16:00,440
So that was, that was a really 
interesting pace that I, I loved

1469
01:16:00,440 --> 01:16:02,320
about that chat. 
Absolutely fascinating. 

1470
01:16:02,320 --> 01:16:03,560
We got a couple other people to 
thank. 

1471
01:16:03,560 --> 01:16:04,920
Oh. 
I love to think of those people.

1472
01:16:05,240 --> 01:16:08,600
Access mining technology MMS we 
had in the show. 

1473
01:16:08,600 --> 01:16:10,320
We also had greenlands in the 
show. 

1474
01:16:10,320 --> 01:16:14,160
Give them a buzz verify smack 
power and technology, DSI 

1475
01:16:14,160 --> 01:16:19,280
underground, Silverstone CRE 
insurance K drill and use spark.

1476
01:16:19,280 --> 01:16:21,280
Use it. 
Get on to Spark. 

1477
01:16:22,880 --> 01:16:24,000
Have a good weekend, money 
miners. 

1478
01:16:26,160 --> 01:16:28,720
Information contained in this 
episode of Money of Mine is of 

1479
01:16:28,720 --> 01:16:30,760
general nature only and does not
take into account the 

1480
01:16:30,760 --> 01:16:34,400
objectives, financial situation 
or needs of any particular 

1481
01:16:34,400 --> 01:16:36,440
person. 
Before making any investment 

1482
01:16:36,440 --> 01:16:39,480
decision, you should consult 
with your financial advisor and 

1483
01:16:39,480 --> 01:16:42,640
consider how appropriate the 
advice is to your objectives, 

1484
01:16:42,840 --> 01:16:44,840
financial situation and needs.