Speaker: 00:00:00

This is Conservation and Science podcast, where we take a deep dive

into topics of ecology, conservation and human wildlife interactions.

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I'm telling me, Serafinski and I always try to bring you diverse

perspectives of an environmental story that I cover.

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And that means that sometimes you might hear voices

or that are opposing ends of environmental debate,

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and that is fine, because what we need, we need more dialog

and understanding and less fighting and division, in other words.

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I want you to listen to people you may have not listened to otherwise.

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And today our guest is scientist, adventure enterpreneur.

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And all those things is one man: Bert terHart. Bert,

welcome to the show. It's great to be here.

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I'm really excited to speak with you.

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We've, I remember answering one of the questions

and one of the questions you originally put to me

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say, I'm not exactly sure how all this

AI and science or business stuff translates.

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And it's like, okay, well, I've done some other things, so that was

pretty cool. I had fun writing that. So this is going to be great.

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Excellent.

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Listen, you are you are you, you must say like you wear many hats.

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You're a fellow of the Royal Canadian Geographical Society,

explorer in residence for the BC Historical Society.

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You're a trained research scientist.

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You are CEO and lead brain dot AI.

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You founder of a Canadian interactive waterway inter initiative.

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Like, how do you think about yourself?

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How do you like you think about yourself as an adventurer,

as an entrepreneur, as a scientist?

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Like what?

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How do you think about yourself? Well, if I had to

if I had to say when I think about myself, I think about this.

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I think primarily about the thing I'm most passionate about,

and that is science.

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So my perspective on everything is, is, scientific perspective.

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I'm I'm formally trained as a scientist.

I have probably went to many degrees,

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but you know, that that said, everything I've ever done,

including all the all

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that the crazy stuff for the ArcGIS or the BC Historical Society

has always been with other, an historical context that relates to,

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how the place that we live has come to be, or it's

from a scientific perspective, which is what kind of ecosystem am I?

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Am I traveling through and and what can I do

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to contribute to the global knowledge base,

as it pertains to, to my passions as I move through that ecosystem?

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So that's paddling across Canada, sailing across an ocean,

going out to Aleutian Islands, going into the Bering Sea.

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So there's always an opportunity for me to do,

to do some kind of formal science as, as, as a citizen.

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So if you ask me what I am, I'm a I'm a science guy, like Bill

Nye the Science guy.

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So how about that.

So that exit that's that's clarified that clarifies that thing.

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And so that was my,

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my like thing that I was wondering, like you circumnavigate the globe

and and the solo on the, on the sailing yacht, which is like wow man.

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I remember when I was a kid, I was, reading a book

about a Polish explorer who to circumnavigate the globe solo.

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And yes, cool. I think Henrik Pascua was his name.

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And and I was just like, man, this is like so I have like, I read that

book, like, what is happening on the boat, like what can happen now?

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Tell me like,

and you can, you know, I'm always ask you this open question.

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So you may say, like how what motivated you to do this?

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But, what I'm particularly curious is like, have you like,

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while you're doing this, you then kind of your sciencey brain kicked in

and you were connecting those things,

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or was it on the from the very get go

that this is going to be like a some sort of like a scientific endeavor?

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Yeah.

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Well, as soon as I decided I was going to make that,

I was going to do the, the

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this trip around the world, I went to some of my old, science contacts,

some of the, you know, some people on my PhD committee,

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some other scientists I knew I knew who were that

I had followed by by following their, their, their research,

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doing things that I was interested in.

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And then I, I did some things that were

that was well outside my, my normal, I guess, training.

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So, I went to the instead of ocean sciences here in British Columbia.

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I went to the University of Hawaii and then I went to another,

another university where I got hold of someone who was doing micro

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microplastics, in the ocean.

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So with the interest of ocean sciences, they have a very large program

that, that that involves GPS tracked current drugs.

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So you throw in these,

you throw these current drugs into the ocean, they're tracked by GPS.

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And we have they had very good resolution in the North Pacific,

but virtually none in the Southern Ocean.

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So I took a bunch of these current drugs with the

when I so I contacted the guy who's in charge of that study

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who happened to be on my old committee, and I said, hey,

this is what I'm doing,

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and how would I put some of these current drugs

in a place that you would never, ever, ever be able to get them in?

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Because it's very science is unbelievably expensive.

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You have to put people, equipment,

resources, time and energy into places that are typically very far away.

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So if you're going to the you know, for me it's going into the Arctic

or the Aleutian Islands or going,

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you know, all the way in the Southern Ocean.

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So I said, give me some of these drugs and I'll happily

plop them in the ocean as I go around, you know, five great capes.

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So that was that was that.

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And I contacted a guy, out of the University of Hawaii

who was doing micro and macro plastic surveys.

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And I said, look, I'm going around the world

and I'm willing to spend an hour a day

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looking out, out on the boat for microplastics, things

that you can actually see with the naked eye.

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So he said, sure. So that's what I did. I spent it when it was possible.

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I spent an hour outside the boat looking for,

chunks of plastic floating in the ocean.

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And of course, no one throws over microplastics.

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They throw over microplastics, you know, a bottle or something

like that, or a or a fish crate, and then it degrades, of course.

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So, and if you stare out at the same piece of thing,

whether it's water or grass or forest,

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pretty soon

you have a very, very good idea of what doesn't belong there.

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So you get very good at at identifying things

at that, that are floating. Obviously that shouldn't be there.

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And then I, I contacted another scientist who was doing microplastics,

and that meant doing plankton trawls behind the boat and then basically,

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isolating those samples, ensuring that they were stable and, and,

and carrying them with me around the world until I got back.

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Well, that that that proved to be too difficult.

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And that proved to be too hard because I had lots of other things

to do on the boat, like, you know, beyond just staying alive.

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So yes, sailing actually, so that that proved to be a bit too much.

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But the other thing I did was,

I tried to, do bird counts of albatross.

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Albatross?

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In the Southern Ocean, there's the population is basically,

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at at the near catastrophic levels

because of the overfishing of their primary food source, which is squid.

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And they were live in the Southern Ocean.

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And that part of the world is virtually unpublished

because no one gets there.

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So if you happen to be sailing around there and you're

actually out there counting birds, that's incredibly valuable.

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So so that's that was, I as soon as I decided I was going to sail

around the world, I decided I was going to do it first.

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I was going to engage in things that I'm passionate about.

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This is this is fantastic, story.

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And this is fantastic

that you were willing to do that, to do those things.

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And, look, we're going to come back to

many things that you already mentioned.

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But I just want to say, like right on the get go, you know what

you're we're looking at, you know, how the things supposed to look like

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I'm curious like in general like how they were looking like,

so what what were the changes that you seen?

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What was the,

you know, like a out of place or alarming things that you saw?

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Well, I guess the first thing that I would say that that was,

that was most alarming was running into the

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to the Chinese industrialized fishing fleet.

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Offshore.

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And I was, as I went by the Falkland Islands, which is,

you know, between Cape Horn, in between South America and South Africa.

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I was warned by the, by the, by the people who can, by Falklands

people and Falklands that and the British who,

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who actually managed that, that particular part of the world

in terms of the in terms of fisheries and their coastal fisheries

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up to 200 miles offshore, they said you have to watch out

for the Chinese industrialized commercial fishing fleet.

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They're fishing illegally. They're not supposed

they're fishing in a place where where they're not supposed to be.

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They have everything turned off, all the AIS,

everything. They're basically black.

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And if you run into them and they they'll well, basically,

if they run you over, they couldn't care less.

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So I ran into them twice.

It was probably I mean, you don't see very many ships at all.

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And, suddenly as I'm sailing in the middle of the night,

I get this warning on AIS,

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the automatic identification system that every then I had on board

just to just to keep me from doing that sort of thing.

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And the thing just lights up and I.

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And there's nothing on the horizon.

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There's no lights at all outside.

Which is strange because this is AIS is line of sight.

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And, suddenly as I'm looking out on the horizon,

I see that the light of

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of basically 1000ft, packer,

which is the thing that stays at sea 365 days a year.

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All it does is process the the catch of all these other sort of,

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satellite vessels, these other boats that are going out and fishing,

and they come back to this giant thing like an aircraft carrier.

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It's huge processes of fish. And then these other boats come

and take it back to market and take it away.

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So this giant thing lights up

and I get on the radio and say, you know what's going on? Who are you?

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You know, which which way should I go? Because, a vessel at sea

that's fishing has the right of way.

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So I don't have the right away.

I have to get out of this guy's way. And there's the. The English is.

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Well, there's no reason to expect that the people are speaking English.

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But it was the English was was almost incomprehensible.

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And it was just it was just go behind, go behind.

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And then suddenly in front of me, there's like a chain of boats

every all the lights turn on at once, and I see the big one,

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and I'm supposed to go behind this thing,

and then all the lights turn off again.

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So it's it, it's

it contravenes everything that's supposed to happen at sea.

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So, and I was warned about it because if you these guys are,

if you run into them, then you'll never be seen again.

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Let's go to bit the boats. I might as a small boat.

They would hit me and I would I be the only person that knew.

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And, what they're fishing for primarily is,

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Well, there's fishing for all kinds of things, but they fish for squid,

and squid is what albatross eat, and they're just.

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They're just raping it.

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I mean, it's it's shocking.

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It's shocking

how much, how much that they, they can that they can process.

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So actually, you know, when I was a graduate student,

this is a long time ago now, this was like the late 80s.

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There was a not

there was enough fishing net in the water to go from Vancouver to Tokyo.

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That's how much that's how much gillnet was in the water at any at

any day, any any given day of the, of the, of the week, month or year.

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And of course, they're fishing for a particular fish,

but the bycatch is everything else.

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It's dolphin and it's, it's, it's whales and it's,

it's sharks and it's turtles, you know, and it's salmon.

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Because we were concerned about salmon fishing at the time, there was

return migration routes of sockeye salmon and it's it really is.

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It is absolutely. It's worse than you think.

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And, there's no real incentive to do anything about it because,

these are peat that they're fishing in, in international waters,

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but they're fishing illegally,

which, which might be bycatch or maybe not,

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or or maybe they're fishing very close to, to say, the Falkland Islands

with other fishing very close to any place that there's banks.

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So, and the banks are typically near, near continental coasts. So it's

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yeah, that's, it's way worse than you think.

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So it's fishing.

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So it's fishing once again, I don't want to sound like a guy

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who's picking out picking on the fishing or fishing industry once again,

but they they're probably the worst.

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Yeah, they're the worst moments.

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I mean, if you think of if you think everyone, I think it knows

the a bit of the saga that that had to go on with whaling.

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But there was, you know, whaling was outlawed.

And then there's, there's people still fish.

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There was people

still fishing illegally for whales for a very long time.

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And the, you know,

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the international community has to wield a very large club before it,

before those particular countries who are doing those things stop.

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And most of you know, the 80% number is huge because,

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firstly, we don't eat that much fish compared to other countries

who who eat an enormous amount of fish.

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Like there's some shocking statistic.

So I was in the Aleutian Islands, for example, on Kodiak.

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I was actually at the time doing

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helping UBC Forestry University, British Columbia Forestry,

doing genetic distribution of Sitka spruce, which is really cool.

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Sitka spruce is is an invasive species. Actually.

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It travels from California all the way up,

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you know, through the northwest and then down in the Alaskan

panhandle and ends at the first of the Aleutian Islands.

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So there is a couple PhD students and a technician who were

who were doing trickery.

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They were coring

to, to, to test, you know, where do these trees come from?

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How did they jump? Basically from the mainland to Kodiak.

It was very cool. It was very fun.

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But we ended up in Kodiak Island, you know, getting science,

getting scientific stuff on board equipment and whatnot and people.

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And there's, there's a fish processing plant there

that processes 3 million pounds of sockeye, natural sockeye a year.

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It runs on the fish oil that it produces is completely self-sustaining,

which sounds wonderful, except all that fish goes to dog food.

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Well, this.

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So there's no winning, right?

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There just seems to be no winning.

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Exactly.

You just shake your head. Oh, they're finally doing something good.

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But then it's like, you're kidding me, right? Dog food.

Is that right? Is that what we're doing?

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Is that why we're going to burn through, you know, 3 million pounds?

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So there's but okay, so that's that's kind of the that the dark side

that let me give you a brighter story.

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So there is a very yeah, there is

there is a very good young scientist who had a very good idea.

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And in the Southern Ocean albatross,

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these were the great albatross, the 12ft wingspan, you know, these birds

that flap their wings literally once every half hour spend.

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They're almost there.

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And while they spend it, they spend two years at sea and then go back

to the place that they were, that they were hatched and then mate.

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And then they go back to sea.

So they travel enormous distances and cover enormous,

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areas.

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So what this guy did was

he strapped a magnetometer and a GPS tracker to an albatross,

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and, they captured like a they captured,

I think, something like 160 albatross.

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And they,

they put this equipment on them, and then they turned them loose.

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And every time the magnetometer goes off, it has to be near a ship.

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And albatross love finding ships

because there's, you know, there's usually something good to eat.

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And if there's not something good to eat, they, they're just

they're just tremendous company

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because, every time I stopped in the Southern Ocean

when I was becalmed,

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I was just surrounded by these albatross,

which is which is how I was able to count.

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But, so with this, I figured that if there's if the magnetometer

goes off, it's a ship, and if it's a ship, it has to have an air signal.

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And if there's no AI signal,

they're there illegally and therefore probably fishing.

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So, these albatross over the course of a year, covers

something like 46,000,000mi² of the Southern Ocean flying everywhere.

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And the data he got was, was a part of this study that that says

80% of the fishing catches illegal was part of that study.

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A small part, but it was, it was science on a shoestring at its best.

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And the data that that they got was invaluable

because it's otherwise there's no way to know.

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And you, you can't just say, well, we're going to do it remotely

because that costs an incredible pile of money to get satellite

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time to go back and, you know, stare at the Southern Ocean

where there's nothing but nothing but nothing.

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But to get albatross to do it was brilliant.

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And, the data they got about, you know, where boats should be

and shouldn't be, the people that were there, that should be

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and shouldn't be, and what they were doing if it was illegal

or illegal was, was was again, like I say, very valuable.

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So there's, there's lots of room.

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There's lots of

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room for, for people who, who like to do science at a shoestring

and come up with a good idea because there's lots of data.

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If everybody needs data and, the places where data is, is needed

is everywhere that you can imagine

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because the ecosystem is, as I'm sure you, you would

agree, is under attack just about everywhere, everywhere we step.

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Yes. That's that's that's it. Unfortunate. True.

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Whether whether the whether the attack is, you know, intentional

or unintentional, it's it's under pressure one way or another.

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This is fantastic story I love it.

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The albatross who are just like, know it, unknowingly

snooping on the on the illegal fishing.

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This is this is absolutely brilliant.

But I just want to quickly touch on one other thing that you mentioned.

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You mentioned microplastic.

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Yeah, we hear about microplastic everywhere.

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Like everybody knows about microplastic. It's everywhere.

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But it probably is the first time I heard about microplastic.

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So could you like, explain it laid out to our listeners,

the issue of microplastic,

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what what part of the whole plastic pollution it is

and whether, you know, what are the science related to microplastic?

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Well, there's there's two sources of, of of microplastic in the oceans.

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There's there's microplastic

that ends up in the ocean as a result of river runoff.

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So, and river runoff, you can assume,

is coming from industrialized areas because most of the coast is is

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industrialized in most of the world, and all the microplastic

is not coming from places like, you know, places like the Antarctic

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where there's no industrialization, there's no runoff, and there's

and there's and there's no big plastics to turn into little plastics.

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So obviously, microplastics are plastics at one time that were large,

that are now small.

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So there's one source which is river runoff.

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The other source is people throw stuff into the ocean. Plastics

and it degrades.

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It degrades as a result of UV radiation.

And of course, it's constantly being washed by the ocean.

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So the ocean is basically it's, it's salty.

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So, and it's water.

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So it's, it's a very good asset, actually.

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It's very it's very good bleach,

which is why wood gets bleach, which is, you know,

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you throw something in the, in salt water and ends up getting bleach.

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So there's the fact that the, the, whatever you put into the ocean

is, is attacked chemically.

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And then and then it's, it's a, it's attacked,

radiological by UV radiation.

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So the source of the source of microplastic

that comes in the ocean beyond river runoff is from ships,

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ships at sea or, or industrialization

where people are throwing big chunks of plastic into the ocean.

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And it's a massive problem because at any one time there's 60,000

container ships at sea, 60,000, and they're concentrated on the,

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on the on the shipping routes, the ship, they're not spread out

over the oceans equally, they're spread out over the shipping routes.

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So on the shipping routes or shipping lanes,

there's at least 60,000 container ships. There's the cruise ships.

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Then there's everything,

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and there's all the fishermen who are fishing,

not necessarily in the shipping routes, but in their own specific areas.

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So and the places in those places that are shipping routes

or people are fishing,

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there's large ships throwing over large chunks of plastic

and there's there's certainly isn't.

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There's international law about what you shouldn't,

but you shouldn't, should not throw over the side.

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But there's virtually no there's regulation, but there's no enforcement.

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So of course, the tendency is for these ships

to throw stuff over the side.

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And the amount of stuff that gets thrown over

the side of ships would would shock you.

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There's places like, for example, up in Haida Gwaii.

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I'm not sure if you know where that is, but it's a World Heritage Site

that Unesco World Heritage Site off the coast of British Columbia,

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and there's no industrialization there at all.

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It's all been turned off, and the only place that it ends up

there is plastic that washes up on the beaches

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between is exposed to the North Pacific.

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So, as a volunteer, we would go there or I would go there

whenever I was in Haida Gwaii, and we would pick plastics up

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off the beach as, as part of a Canadian government.

Paid for initiative.

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And every year we could take we could take anywhere from 2000 to 4000

pounds of plastic off the beach in this one little tiny island group.

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And it's all it's giant jugs of what used to be oil people, fishermen

changing oil at sea.

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There's there's fish crates. There's there's there's net

that goes on for miles and there's tons of it.

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There's absolutely tons of it. And if it doesn't end up on the beach,

it just continually circulating around the world.

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And, and, you know, the, the oceanic gyres like the Gulf Stream

or the curiosity or the or the goolies or the South Pole,

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whatever, there's all these, these currents,

and they just sit there and,

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you know, rotate around the world's oceans and they turn big plastics

through sunlight and chemical reaction in the ocean into little plastic.

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So there's these two sources, runoff and then big plastics

turning into little plastics by, by people throwing things off ships.

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And it's a problem.

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It's it's tons and tons and tons, thousands and thousands and thousands

of metric tons of plastic being tossed off ships every year.

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What's your what's your take on the this initiative

or this is a company, ocean cleanup because,

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some, some even in the scientific circles are, criticizing them,

some other people thinking this is the best thing ever.

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What's your take on ocean cleanup? Well,

I think the balance is somewhere in between the two.

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I think the the the this notion that there's a giant sea of,

of plastic floating in the ocean the size of Texas is a fallacy.

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It doesn't exist.

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So if you if you if you create a problem, if you create a solution

to fix up the giant, you know, floating island of plastic,

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then the problem doesn't exist. I'm not exactly sure what you're fixing.

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So, so, but, but, but the idea that there has to be some way for us to,

Well, I hate to use the word vacuum because that

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that would then imply that there's, there's a concentration of it,

but there has to be, some way for us to deal with the plastics.

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That's that's,

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that gets tossed over the side.

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And, and sadly, even though there's a tremendous, there's, there's,

there's thousands of metric tons of plastic being tossed over the side.

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The oceans are very, very, very large, large beyond imagining.

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So even if you only see, let's say that you see, you know, one

chunk of plastic every half a square mile or half a square mile,

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if you imagine, you know, you're sitting in a place

that's that's 500km or 500m by 500m or, well, half a mile.

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Yeah. It sorry, 1.6 or say 800m. Right.

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And there's one piece of plastic in this 800m by 800m square.

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That's you'd be it almost never see that.

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But the ocean is gazillions. Well, that's an exaggeration.

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But you can imagine the ocean is is way larger

than, you know, one chunk.

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That's that's it's millions and millions of square miles.

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So there's one piece of plastic in an 800 meter

square ends up being a mountain of plastic.

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So the problem the problem is that how do you actually, you know,

use ocean cleanup to go around and find all those, those pieces.

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It's pretty hard.

I think that's I think that's that's part of the problem.

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I think the problem I think the solution, well,

we don't know everything that there is to know about microplate six.

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There's you know, I've heard there's some other research that says

that would say that though, the maybe the problem is as bad as it it is

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or we think it is. I'm not sure I'm convinced by that. At all.

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But I think I think the future is, is getting up,

you know, using some sort of material that's plastic esque

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that doesn't that that degrades or becomes completely soluble in ways

that, that don't harm the environment.

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I mean, that's that's a big ask.

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I wouldn't know where to start with that problem, but,

it's way easier to

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I would think you're not going to convince people

to stop throwing stuff over the side.

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I don't I think that's just going to be too hard,

especially without advancement.

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Yeah, without I mean, that's that's the problem, right? Yeah.

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Every time we speak, every time we speak about the laws

and this and that, any environmental

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like whether it's like Europe here

locally, Ireland or in the US or in Canada is always the same thing.

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Like we have plenty of laws, we don't need more law,

we just need the enforcement of existing law.

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And I guess that's the that's

the problem that everyone comes in is like, oh, we need a new law.

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It's like, no, like it's not needed.

You just need to enforce what's already there, right?

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Yeah, yeah. You need you need enforcement.

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And enforcement implies incentive,

which is well, basically a disincentive.

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So you need a better incentive structure

to actually get people to change behaviors.

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And, that the incentive and I think this is a behavior

that because people have been throwing stuff away for,

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for tens of thousands of years, I live on a small island.

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First Nations

people have been here for maybe two, 3000, maybe five, who knows?

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Probably more closer to 5000 years.

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And they've been throwing stuff away for,

for for very long, for a very long time.

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Everywhere you look basically it's a midden amidships.

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Where I live, a midden is nothing more than a

that then an old garbage heap.

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But what they threw away

were, were seashells, you know, crushed seashells.

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So that doesn't hurt the environment at all.

But it's still people throwing stuff away.

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So I think to to get people to change that behavior would be very hard.

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I think you need I think you need to incentivize that by getting them

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to incentivize that, by coming up with it with a plastic

that's that's slightly different than what we're using right now.

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We don't need to have I don't need to have a plastic bottle

that lasts, you know, for 200 years.

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I need a plastic bottle that lasts for two hours. Right.

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I'm going to drink it and then and then do something else with it.

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So. And I have the you know, speaking about sailing is the same problem

because we people started making, fiberglass sailboats

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with no idea how long a fiberglass sailboat would last.

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And it turns out that a fiberglass sailboat,

the hull of it is going to last for 300 years, of course,

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but the rest of it is no longer functioning because everything else is,

you know, the the hull remains, but everything else is gone.

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But what do you do with it?

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What do you do with these fiberglass

hulls built in the 60s, late 60s and early 70s that nobody wants anymore

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and are just now

floating and clogging up, you know, harbors and anchorages everywhere,

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and they're taking them when they can, turning them into smaller

bits of plastic and putting them into a landfill.

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But it's a problem.

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And no one building sailboats,

you know, 50, 60, 70 years ago was thinking that

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that the boat that they built, the only way to get rid of it is

to turn it into smaller chunks of sailboat and put them in a landfill.

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So we, you know, so we need, we need, we need to deal with,

with the fact that plastics are basically these forever

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and not just forever chemicals.

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They're forever bits, you know, big things turning into smaller things

so that that that's to me that's

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I it's a problem

that's I don't have any chemical, engineering, expertise at all.

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But we're going to have to fix that problem.

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We're going to have to fix it really quick

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because as the third World, I hate to use the world third world,

but as other countries industrialize and become,

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become more like us in the, in, in, in terms of, you know, how we,

how we consume things in the West, the problem is going to explode.

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It's bad enough as it is now, but it's going to explode.

That's a that's a huge problem. That's a huge problem. Right?

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And we're not going to get into this, but I, you know, you know, like

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then because then those people who are rightfully so say, yeah, oh,

you already done all that and now you're telling us we can.

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Yeah. Exactly.

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Yeah. So like this is like material for another for another podcast.

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But I just on the plastic,

I just want to stay on the plastic for a second because here

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it is, is very interesting and something that I hear a lot.

And surely our listeners will be interested.

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Is that something that you can confirm that the majority

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of the plastic out there in the sea are actually fishing gear,

like a ghost nets or some abandoned fishing gear?

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Well, I wouldn't say the majority of it, but I would say certainly

a very, very large piece of it, because nets are, you know, nets.

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What do you do with that?

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What do you do with, you know, with, with, with with a gill net

that gets destroyed when a whale gets in it or whatever

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the case might be, it's way easier to cut it off

and and let it go away than it is to fix it.

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And and of course, the financial incentive to fixing

it is very, very low because firstly, it's expensive.

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It would take forever and then the boat isn't fishing.

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So the incentive to just to get to use something new right off the bat

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is, is out of this world for those countries

and those people in those companies that are, that are fishing

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where whether a boat at sea is very, very expensive to run it,

it costs an enormous amount of money.

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And of course, these boats aren't going to be out there

unless they're making money.

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So the incentive to to just to not repair anything,

but just to fix it, just to get a part replace it is really, really

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the incentive for that is really strong.

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Like think of your own car.

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No one fixes a car anymore. They replace parts

so what do you do with the old part?

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You just throw it away like it back in the day,

like when my grandfather was at sea.

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He was a ship's engineer.

They made everything. They had a machine shop on board.

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When something broke, they made a new one.

They made it from a chunk of metal.

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And if they couldn't fix the new one by replacing bearings or re boring,

whatever the case may be, they just made one on the spot.

365

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Well we don't, we don't fix things like that

anymore. Cars are basically throwaway things for us.

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They get recycled, which means they're turned into,

you know, they're flattened somewhere and they end up.

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I would think of tires like,

we have a huge problem because we just throw stuff away.

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And of course that happens at sea.

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And it's they just they just throw everything away and replace it.

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The problem you're touching on this, it's huge

because like what I heard, like it's maybe not totally related to

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the subject of the podcast.

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What I heard is like,

some had an idea that they can reuse, recycle the old, tires.

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And that's what they, making this, this ground in the kindergarten.

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So it's kind of like a soft and and then kids when they throw

and then it turns out like, oh, there's a small problem,

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but there is like a good, good peer

reviewed size that that might cause cancer in kids because it's like,

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like it's it's just like it's like we creating the mass

mass of this toxic waste. It's like, where are you?

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Where do you go from there? It's

it's just, it's just sort of desperate.

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But tell me when you were out of the sea, have you noticed it a lot?

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Because you said, like, oh, you would notice this, this plastic.

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But I remember a couple of years ago,

I was, watching, Volvo Ocean Race.

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And they had also this program, kind of like a raising awareness of

people because obviously there's like a lot of eyes on the on the event.

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And I remember this footage, people,

you know, they're they're showing from the bowl.

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They were like literally sailing through plastic in some places.

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So where was that like that most of the time for you

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or was it like that in certain areas

like what's your what's your assessment based on being out there?

386

00:30:46,480 --> 00:30:49,320

I never saw any of that ever.

387

00:30:49,320 --> 00:30:54,840

And I sailed through those areas where those were

where they're supposed where it was, where that was alleged to be.

388

00:30:54,840 --> 00:30:57,560

But the Volvo Ocean Race, it's a stage race.

389

00:30:57,560 --> 00:31:02,640

So they go they go in stages from one, from one

basically continent and place to another.

390

00:31:02,640 --> 00:31:08,600

So they're they're approaching very large cities

like Shanghai, Rio de Janeiro, Melbourne.

391

00:31:08,600 --> 00:31:14,760

So as you approach those places where there's a lot of ships

and like a lot of commercial ship traffic, a lot of fishing traffic,

392

00:31:14,760 --> 00:31:15,720

because they're there.

393

00:31:15,720 --> 00:31:20,880

All the fish are concentrated on coastlines

along the continental shelf, primarily.

394

00:31:20,880 --> 00:31:26,320

Well, I shouldn't say that primarily,

but certainly the fishing is, is is more most productive,

395

00:31:26,320 --> 00:31:29,800

anywhere on the continental shelf in the continental break.

396

00:31:29,800 --> 00:31:34,880

But I was never I was not

I was not near anywhere. Those places I crossed shipping lanes.

397

00:31:34,880 --> 00:31:39,040

And when I crossed shipping lanes,

then there would be an, an increase in microplastics.

398

00:31:39,040 --> 00:31:41,320

I could actually see some and start counting.

399

00:31:41,320 --> 00:31:49,600

But it was always where there was, where there like, for example, there

one of the ships I saw was, was a fishing was a fishing boat.

400

00:31:49,600 --> 00:31:53,160

They were fishing for black marlin out of Spain,

actually fishing out of Mexico

401

00:31:54,240 --> 00:31:56,280

because they had out fish, the Atlantic Ocean.

402

00:31:56,280 --> 00:31:57,520

And we're now in the Pacific.

403

00:31:57,520 --> 00:32:01,920

They actually have to go that far to, you know, to to continue to catch,

to make it profitable, to catch black marlin.

404

00:32:01,920 --> 00:32:04,080

Don't leave it, don't even start started.

405

00:32:04,080 --> 00:32:11,000

So yeah, I, so, so as I, I see the I see this boats fishing properly.

406

00:32:11,000 --> 00:32:13,280

I call them on the radio because I like some of that talk to.

407

00:32:13,280 --> 00:32:18,760

I talk to them and sure enough, sure enough

I come across a piece of plastic.

408

00:32:18,760 --> 00:32:20,640

It I forget what, what exactly it was.

409

00:32:20,640 --> 00:32:27,000

It was a water bottle or something, but it was something thrown

overboard by that ship because I was in that immediate vicinity.

410

00:32:27,360 --> 00:32:31,400

So that's one ship in one place.

So imagine a bunch of ships are going into the same place.

411

00:32:31,400 --> 00:32:36,320

You find that stuff,

it's like it's like sailing in to Ketchikan in Alaska.

412

00:32:36,320 --> 00:32:38,680

Ketchikan is where you have to clear the customs.

413

00:32:38,680 --> 00:32:44,720

In Alaska, if you go from Canada going north,

and at any one time during the summer, there'll be this will be

414

00:32:44,720 --> 00:32:50,800

I shouldn't say that, but there can be up to five of these 1000

or 1200 foot cruise ships in this little tiny harbor,

415

00:32:50,800 --> 00:32:53,160

and they have to go in and come out in the same place.

416

00:32:53,160 --> 00:32:56,520

And there's laws, of course,

but what you can't or cannot do in coastal waters.

417

00:32:56,520 --> 00:32:59,640

But as soon as you get three miles away from those places,

418

00:32:59,640 --> 00:33:05,360

then suddenly the rules change and you can tell that you're suddenly

in that place where the rules are changing.

419

00:33:05,360 --> 00:33:08,880

So the if for the Volvo Ocean Race,

they would have been going through areas

420

00:33:08,880 --> 00:33:13,240

where there would be a concentration of ships

and a concentration of people, so they would see something like that.

421

00:33:13,240 --> 00:33:17,360

But I never saw something like that

just because I wasn't in those places.

422

00:33:17,360 --> 00:33:23,960

But it I mean, I know that I follow the race,

I know that I think I have a think I remember as well the footage

423

00:33:23,960 --> 00:33:28,560

because it was very interesting to me,

not just the sailing, but what they were doing in terms of science.

424

00:33:28,560 --> 00:33:31,600

And that's a really good example of citizen science.

Like anyone can do that.

425

00:33:31,600 --> 00:33:33,840

Anyone that's passionate about something,

426

00:33:33,840 --> 00:33:39,840

there's there's a scientist who spent their lifetime who has spent his

or her life studying that thing that you're interested in as well.

427

00:33:40,000 --> 00:33:41,760

But they've done it professionally.

428

00:33:41,760 --> 00:33:44,920

And so they the example I use are is surfers are surfers everywhere.

429

00:33:44,920 --> 00:33:52,160

People love to surf all around the world, and scientists

are very interested in how materials are transported down coastlines.

430

00:33:52,440 --> 00:33:54,360

It's called literal transport.

431

00:33:54,360 --> 00:33:59,840

And, it has a it has a very

it has a huge impact on how industrial waste comes out of a river

432

00:33:59,840 --> 00:34:05,760

and then ends up being, you know, spread along the coast

because there's there's physical processes that govern that.

433

00:34:05,760 --> 00:34:08,120

And, and people spend a lifetime studying it.

434

00:34:08,120 --> 00:34:14,120

But one of the, one of the things littoral transport is affected

primarily by waves and beyond currents.

435

00:34:14,120 --> 00:34:18,520

Currents are generally offshore, but by waves hitting the beach,

which is what surfers love.

436

00:34:18,520 --> 00:34:23,520

Surfers are very good at saying, you know how big the waves are,

and they're there almost all the time

437

00:34:23,520 --> 00:34:25,520

and there's a scientist or there's, there's, there's

438

00:34:25,520 --> 00:34:31,680

there's probably a thousand scientists, at least in the world

who've spent there, spent their whole career studying literal transport.

439

00:34:32,400 --> 00:34:39,240

So if you go surfing, you can you can say, well, the waves today

were 6ft or 8ft or, you know, breaking 100m offshore or 200m offshore.

440

00:34:39,720 --> 00:34:44,400

That's incredible.

That's incredibly valuable to someone who's studying lateral transport.

441

00:34:44,400 --> 00:34:47,880

So there's a way to combine something you're passionate about.

And surfers tend to be very passionate.

442

00:34:47,880 --> 00:34:53,400

They go out and you know, the weather's horrible.

They're out there all the time and they're at all times of the year.

443

00:34:53,400 --> 00:34:59,560

And then that's they're just literally looking at the data

that the scientists are just craving and absolutely need.

444

00:35:00,120 --> 00:35:00,960

So there's two ways.

445

00:35:00,960 --> 00:35:04,320

There's always a way to combine things that you're that you're crazy,

446

00:35:04,320 --> 00:35:08,400

that you're crazy in love with with with a scientist

who's crazy in love with the same sort of thing.

447

00:35:08,400 --> 00:35:14,440

And, and listen, we're going to come back to the citizen science

because, you know, we talk about this as well.

448

00:35:14,440 --> 00:35:20,440

Like, for example, anglers and even like in Ireland like,

you know, Fisheries Ireland, they have it like an app,

449

00:35:21,480 --> 00:35:26,280

like you said, anglers that are out there, there,

you know, rain or good in bad weather.

450

00:35:26,280 --> 00:35:31,800

And they just data that they gather or tagging fish and so on.

451

00:35:31,800 --> 00:35:33,960

It's just it's just incredible.

452

00:35:33,960 --> 00:35:37,320

Listen, but I just want to switch gears for a second.

453

00:35:37,320 --> 00:35:42,200

To something that is dear to my heart and which is a policymaking.

454

00:35:42,200 --> 00:35:47,600

And you spoke about the policymaking,

the impacts of policymaking, but of poor policymaking.

455

00:35:47,600 --> 00:35:53,880

And I, I am, you know, question as I'm asking to to various guests

and I'm pondering myself,

456

00:35:54,320 --> 00:36:04,120

you know, how how to connect or how to make the policymakers

making this making, you know, quote unquote good decision.

457

00:36:04,120 --> 00:36:07,520

Right. And this is already loaded because like, what is good decision?

458

00:36:07,520 --> 00:36:13,600

And this is like a story that I shared on on one of the episodes

when like one of the scientific conferences, I was sitting,

459

00:36:14,000 --> 00:36:18,560

next to a policymaker person who is who is a policymaker.

460

00:36:18,560 --> 00:36:22,840

And, you know, after a few glasses of wine, the,

you know, conversations open up.

461

00:36:22,840 --> 00:36:24,600

And I was just like, My God,

462

00:36:25,600 --> 00:36:25,960

right.

463

00:36:25,960 --> 00:36:28,240

And and that was on the scientific conference.

464

00:36:28,240 --> 00:36:34,080

So, so that person was there to listen to scientists,

what they're saying. Right.

465

00:36:34,080 --> 00:36:39,200

But but the takeaway was like essentially like all those scientists,

they don't know how to make it odds. It's just. Right.

466

00:36:39,200 --> 00:36:45,680

So so you can, you know, again, it's a very open question

that no, not even say it's a question.

467

00:36:45,680 --> 00:36:47,120

It's a discussion point.

468

00:36:47,120 --> 00:36:54,120

But I am curious from your experience, you know, like,

what are the best ways to talk to policymakers

469

00:36:54,480 --> 00:36:58,560

to incentivize them to, to make it right decisions?

470

00:36:58,560 --> 00:37:05,520

Or maybe it's not about policymakers, maybe it's about their,

you know, their bosses, but because inside, you know, my take on this,

471

00:37:06,320 --> 00:37:09,960

and you may correct me if I'm wrong, is like the policymaker

that they don't care about science.

472

00:37:09,960 --> 00:37:16,040

They they need to you they do the service to their boss,

and their boss needs to be elected in four years.

473

00:37:16,240 --> 00:37:16,760

Yeah.

474

00:37:16,760 --> 00:37:23,000

And that's and just you

there's it is impossible to make a good environmental policy

475

00:37:23,280 --> 00:37:27,440

because like you mentioned, environmental policy

in a state of affairs that we have right now,

476

00:37:27,440 --> 00:37:33,760

usually not going to be popular

and it's going to be it's going to be inconvenient.

477

00:37:33,760 --> 00:37:42,160

And no politician wants to do inconvenient things because they know

the next four years they out how to how to even approach this problem.

478

00:37:42,360 --> 00:37:50,120

Well, I think that, you know, fundamentally there's I look at it very,

very simply, there's two things that policy revolves around.

479

00:37:50,640 --> 00:37:55,880

One is something that sounds good

and one is the other is something that does good.

480

00:37:55,880 --> 00:37:58,680

And they're wildly they can be wildly different things.

481

00:37:58,680 --> 00:38:04,640

And it turns out that politicians are very good at in general,

they they like to sound good because that's easy.

482

00:38:04,640 --> 00:38:10,000

It's the easy path,

but they very rarely want to do good, because doing good is hard.

483

00:38:10,000 --> 00:38:17,240

It's hard to, to, to, to disincentivize, you know, behaviors

that are hardwired or disincentivize behaviors that are,

484

00:38:17,520 --> 00:38:19,200

that are financially rewarding.

485

00:38:19,200 --> 00:38:23,280

So you have to like I it's it's my responsibility.

486

00:38:23,280 --> 00:38:29,280

I view it as my responsibility to my responsibility

to engage with good policy

487

00:38:29,440 --> 00:38:35,520

and then, not just engage with it, but amplify those policies

in any way that I can, which is to bring awareness,

488

00:38:35,880 --> 00:38:41,880

bring people's awareness to things that that just don't,

that aren't doing good at all.

489

00:38:42,440 --> 00:38:50,800

And they're all around us like we we hear politicians or policymakers

sounding good all the time, and we don't.

490

00:38:50,800 --> 00:38:55,440

It's not rocket science to figure out

if that's actually doing good, sounding good and doing good

491

00:38:55,440 --> 00:39:01,680

like we're if if we weren't able to differentiate as a species

between those two things, there would be no humans working on the planet

492

00:39:02,240 --> 00:39:08,640

because we if you're embedded in nature, are truly embedded in nature,

then you nature is unforgiving.

493

00:39:09,080 --> 00:39:12,960

It will not. It doesn't tolerate in any way, shape or form bad policy.

494

00:39:12,960 --> 00:39:20,000

I cannot decide that I'm going to go sleep naked in the forest,

you know, for a week, because in two days I'll be dead, right?

495

00:39:20,000 --> 00:39:21,560

That's just bad policy.

496

00:39:21,560 --> 00:39:26,240

It sounds good. I'm meant to go out and hug trees for the next,

you know, seven days straight, naked.

497

00:39:26,240 --> 00:39:29,040

But it doesn't do any good, doesn't do me any good.

498

00:39:29,040 --> 00:39:32,040

And it certainly doesn't do the tree any good and bad policy.

499

00:39:32,040 --> 00:39:41,040

You can also engage with with bad policy badly, which would be,

for example, throwing paint on a Van Gogh painting that it's you're

500

00:39:41,920 --> 00:39:47,480

you're engaging with a bad policy in a way that doesn't make any sense,

because you're not you're not bringing awareness to the policy.

501

00:39:47,480 --> 00:39:52,800

You're just bringing awareness to yourself.

So I don't like that kind of activism because it doesn't do any good.

502

00:39:52,800 --> 00:39:54,120

It only turns people away.

503

00:39:55,280 --> 00:39:57,760

It certainly turns people away who might be sitting on the fence.

504

00:39:57,760 --> 00:40:02,600

And the vast majority of people are sitting on the fence

because they don't exactly know.

505

00:40:02,600 --> 00:40:05,840

Or maybe they're I shouldn't say they don't know.

I think that's unfair.

506

00:40:05,840 --> 00:40:08,080

I think that they just they just they haven't been

507

00:40:08,080 --> 00:40:14,080

they haven't been given enough information to say,

okay, this is sounding good, but it's not doing any good.

508

00:40:14,280 --> 00:40:18,880

So when you when you find and you can't, you can't solve every problem.

509

00:40:18,880 --> 00:40:21,720

But you can

you can be engaged in those things that you're passionate about.

510

00:40:21,720 --> 00:40:26,360

So I, I'm, I'm engaged. I love I love the water.

511

00:40:26,360 --> 00:40:30,120

I've been I mean that's been my formal

512

00:40:30,120 --> 00:40:36,560

that's, that's, that's consumed me formally

and informally because I'm and I'm an oceanographer by training.

513

00:40:37,360 --> 00:40:41,400

I, you know, paddle a canoe sailboat.

I'm always on the water doing something.

514

00:40:41,400 --> 00:40:47,880

So I'm, I'm constantly looking at policy

that and try to engage with with policy that does good.

515

00:40:47,880 --> 00:40:56,280

So as an example, this summer I'm supposed to be paddling through,

a lot of Canadian wilderness with, First Nations person

516

00:40:56,280 --> 00:41:05,600

and an, an actual PhD hydrologist

to study the impacts of dams on, on, on downstream ecosystems.

517

00:41:05,840 --> 00:41:10,120

So this first Nations guy been living

he's been living there for generations.

518

00:41:10,120 --> 00:41:15,720

And there's generational knowledge that he knows

because he lives off the land and relies on the water

519

00:41:15,720 --> 00:41:19,640

for not just transport,

but for food and for everything else you can imagine.

520

00:41:19,640 --> 00:41:25,360

And there's a hydrologist who actually knows, you know,

something or two about dams and how they work and what they're doing,

521

00:41:25,360 --> 00:41:27,120

what they're trying to achieve.

522

00:41:27,120 --> 00:41:34,120

So they're paddling a great big chunk of the Canadian wilderness,

taking data, you know, making observational data as citizen scientists,

523

00:41:34,120 --> 00:41:41,280

one when one formally no one formally trained as a scientist

or when citizen scientist to try to get an understanding of what really

524

00:41:41,560 --> 00:41:43,240

of what the policy is

525

00:41:43,240 --> 00:41:50,240

and the impacts of that policy by Canadian government on, you know,

closing the dam and opening the dams to, to generate electricity.

526

00:41:51,000 --> 00:41:58,640

So there's good and bad policy about about about how that process,

about how they do that because they have to generate electricity.

527

00:41:58,640 --> 00:42:05,560

Do they let and there's, there's,

if you do it poorly, then you're basically just, you know, flooding,

528

00:42:06,000 --> 00:42:10,400

everything downstream,

you know, three times or twice a day and destroying everything.

529

00:42:10,400 --> 00:42:12,880

Or you can come up with a more measured approach.

530

00:42:12,880 --> 00:42:16,480

So they're engaging in something that does good

531

00:42:17,760 --> 00:42:21,800

around a policy that doesn't sound good.

532

00:42:21,800 --> 00:42:29,240

So it's a perfect example of of what you can do,

and in a very focused way, because you can't be involved in everything.

533

00:42:29,240 --> 00:42:33,120

It's just there's just too much.

But there will be something that you're passionate about.

534

00:42:33,120 --> 00:42:39,960

There will be policy around that, like fishing, for example,

and you and or surfing or whatever the case might be.

535

00:42:39,960 --> 00:42:43,320

And you can find out what the policies are surrounding that, that are,

536

00:42:43,320 --> 00:42:49,960

that are affecting you personally because it's something

that you're engaged in and then choose to engage, with those policies.

537

00:42:49,960 --> 00:42:52,560

And if it's bad policy, all you can do is make your voice heard.

538

00:42:52,560 --> 00:42:56,800

You can make you can make your voice

heard like you're doing on a podcast here, like we're doing you can

539

00:42:56,800 --> 00:43:02,720

you can write to people who are voting and say, oh, how unhappy you are,

because that's still incredibly powerful.

540

00:43:02,720 --> 00:43:08,560

There's, there's there's nothing more powerful than a politician

getting a letter from a, from a constituent

541

00:43:08,560 --> 00:43:10,960

who excoriates them for being a jackass

542

00:43:12,080 --> 00:43:14,200

and calls them out like, you voted for this.

543

00:43:14,200 --> 00:43:15,080

It's ridiculous.

544

00:43:15,080 --> 00:43:17,960

Why did you do that? Like, why are you selling out?

545

00:43:17,960 --> 00:43:21,200

And I mean it, that's way more effective.

546

00:43:21,200 --> 00:43:28,160

And you can don't just send a letter to that one person, you send it to

everybody on that list of, you know, the person up and down the chain,

547

00:43:28,440 --> 00:43:32,040

and then people become accountable for what comes out of their mouth

and what they're doing.

548

00:43:32,040 --> 00:43:39,480

And that's the only way that I know that I know of to, to engage,

you know, formally as a citizen scientists

549

00:43:39,480 --> 00:43:46,040

and then formally as a constituent and then inform me, like,

like we're doing here around policies that that, that you disagree with.

550

00:43:46,280 --> 00:43:50,040

That's a good point to engage in a positive way.

551

00:43:50,040 --> 00:43:54,600

And, and we said it many times on the, on this podcast,

like write to your politicians,

552

00:43:54,600 --> 00:44:00,880

you know, you send a letter or send an email

like just do something but just, you know, like, excuse me.

553

00:44:00,880 --> 00:44:01,320

My word.

554

00:44:01,320 --> 00:44:03,720

Bitching on social media doesn't cut it.

555

00:44:03,720 --> 00:44:08,200

It's it's it's it's you used to be to take it one step further.

556

00:44:08,200 --> 00:44:12,280

But listen, I have a question for you. You're an entrepreneur as well.

557

00:44:12,280 --> 00:44:16,320

Lead brain, don't I, tell me,

558

00:44:17,840 --> 00:44:20,240

how do you navigate,

559

00:44:20,240 --> 00:44:29,080

the the the complex landscape between, you know, being under preneur

and and doing business and using technology.

560

00:44:29,080 --> 00:44:35,040

And on the other hand, we all heard about, like,

how the all those technologies are affecting their environment.

561

00:44:35,040 --> 00:44:42,240

And, you know, especially with, I know, massive data centers,

there's a water park cooling the power for powering all that think

562

00:44:42,920 --> 00:44:45,360

tell me like what's your what's your take.

563

00:44:45,360 --> 00:44:51,840

Because, you know, it's a little bit counterintuitive

if you're coming from this environmental angle.

564

00:44:51,840 --> 00:44:57,160

And, and here's you're you're doing like a business here,

which is obviously like everybody needs to live and do their business.

565

00:44:57,160 --> 00:44:58,680

So that's a genuine question.

566

00:44:58,680 --> 00:45:06,240

How you navigate that landscape both in a, in a,

you know, practical matters and also in your, in your mind.

567

00:45:06,480 --> 00:45:08,120

Well, I think,

568

00:45:09,360 --> 00:45:10,760

let me take one step backwards.

569

00:45:10,760 --> 00:45:16,760

And we're talking about AI,

but it takes 5000l of water to make a pair of jeans.

570

00:45:17,520 --> 00:45:18,880

Think about that.

571

00:45:18,880 --> 00:45:20,600

I mean, in, in Canada we have some of that.

572

00:45:20,600 --> 00:45:24,400

We have the largest, probably the largest reserve of freshwater.

573

00:45:24,400 --> 00:45:29,120

But first, lots of First Nations

people live in this country without without access to,

574

00:45:29,120 --> 00:45:31,800

to clean potable water, as you and I would have access to it.

575

00:45:31,800 --> 00:45:33,240

Sure, they can drink water out of the lake

576

00:45:33,240 --> 00:45:39,240

or the river, but most neither you nor I would generally,

you know, go down to the lake and get a bucket of water.

577

00:45:39,360 --> 00:45:47,320

So this, this, this idea of, of, of extraordinary resource

usage is, is all around us.

578

00:45:47,320 --> 00:45:54,320

It's not just in AI, it's literally in the pants that you wear,

like 5000l of water to make a pair of jeans seems seems excessive.

579

00:45:54,320 --> 00:45:56,160

Not to mention the fact that ships

580

00:45:56,160 --> 00:46:02,600

are traveling around the world because a pair of jeans is assembled

in one place, but all the bits and pieces come from everywhere else.

581

00:46:02,880 --> 00:46:07,720

And then it comes on on a giant ship

fueled by some of the worst diesel fuel for steel.

582

00:46:07,720 --> 00:46:09,440

You know, fuel you can imagine.

583

00:46:09,440 --> 00:46:15,840

So I, I heard I heard that the some,

some of the factories are not built in

584

00:46:15,840 --> 00:46:20,160

certain areas because water is too bad

and that water is a drinking water.

585

00:46:20,160 --> 00:46:24,840

But the industrial factories

and stuff need the better, better quality of the water.

586

00:46:24,840 --> 00:46:28,680

The other one was the to make like a, like a chips, the amount of like,

587

00:46:29,920 --> 00:46:36,320

thousands upon tens of thousands of cubic liters of water

every second using those things.

588

00:46:36,320 --> 00:46:42,120

It's just madness. It's, it's it's crazy. Like it's crazy talk like the

the cloud.

589

00:46:42,120 --> 00:46:42,680

The cloud.

590

00:46:42,680 --> 00:46:48,680

This is about a year and a half ago

now, the cloud at that time, you used more electricity than Japan.

591

00:46:48,720 --> 00:46:53,320

So, so, so how do you square those kinds of things?

592

00:46:53,320 --> 00:47:00,640

We have enormous problems and large language models, speaking

specifically of AI are able to solve very, very complex problems.

593

00:47:00,640 --> 00:47:05,120

So if you think of the think of a protein

and think of think of the drugs.

594

00:47:05,120 --> 00:47:07,520

Drugs are very expensive to make there.

595

00:47:07,520 --> 00:47:14,280

And and it it involves an incredible expenditure of time, energy

and money and time.

596

00:47:14,280 --> 00:47:18,560

Energy and money translates into enormous resource usage.

597

00:47:18,560 --> 00:47:21,360

Like I'm talking about electricity and heating

and all those kinds of things.

598

00:47:21,360 --> 00:47:24,720

But but proteins are very complicated.

599

00:47:24,720 --> 00:47:31,560

And there's about a billion different ways, at least for, for a protein

to, to wrap itself into a shape and it's basically a key.

600

00:47:31,800 --> 00:47:36,000

And a drug basically is a mat is, is is a synthetic. It's a synthetic.

601

00:47:36,000 --> 00:47:38,920

So think of the protein natural as a lock.

602

00:47:38,920 --> 00:47:43,600

And a drug basically is a key to the lock.

So they have to match perfectly.

603

00:47:43,600 --> 00:47:49,480

And that's that's very simplistically, sort of how, how that works.

604

00:47:49,480 --> 00:47:56,400

But it's almost impossible for a human to come up with the billions

and billions of combinations to that particular lock.

605

00:47:57,000 --> 00:47:58,920

I does it in an hour.

606

00:47:58,920 --> 00:48:05,520

So we will see advances in, in, in technologies

that have to deal with chronic degenerative diseases

607

00:48:05,840 --> 00:48:13,080

like cancer, like Alzheimer's, that are drug related, that

we would have taken basically decades, if not centuries to solve that.

608

00:48:13,080 --> 00:48:20,280

I can do, in, in, in an unbelievably short amount of time because

it can just, you know, create all these, these, these combinations.

609

00:48:20,320 --> 00:48:24,120

It basically in a heartbeat. So there's tremendous upside.

610

00:48:24,120 --> 00:48:27,680

And if you look at, okay,

you have to have a huge data center to read it.

611

00:48:27,680 --> 00:48:37,240

But imagine it takes you ten years of, of of a 500 people in a,

in a, in a building that have to live, work, feed to do the whole thing.

612

00:48:37,440 --> 00:48:44,880

Think of the cost of that to, to to come up with one drug

as opposed to an hour of AI doing it to come up with the combination.

613

00:48:44,880 --> 00:48:49,880

And I'm sort of just scrubbing off all the other bits and pieces

that go into getting a drug into market,

614

00:48:49,880 --> 00:48:55,520

but just discovering what might work, you know, you think of them,

think of the poor white mice you have to kill in the lab.

615

00:48:55,520 --> 00:48:56,640

Right.

616

00:48:56,640 --> 00:49:00,920

So there's that's the other side of the coin, right?

There's this tremendous amount of energy we're using.

617

00:49:00,920 --> 00:49:05,320

But then if you spread that out over, say, 5 or 10 years,

what it would take to make a drug,

618

00:49:05,320 --> 00:49:09,440

then suddenly the equation seems to be a little bit more balanced.

619

00:49:09,440 --> 00:49:13,480

So in terms of for me how I so that's one way I look at it.

620

00:49:13,480 --> 00:49:16,800

Basically resource usage across on, on a big scale.

621

00:49:16,800 --> 00:49:22,120

Because if I'm going to talk about how much it costs

to run a data center, then I'm going to then okay, let's talk about

622

00:49:22,120 --> 00:49:29,040

let's talk about producing, you know, 500,000 pairs of jeans in a month,

how much, you know, what kind of energy goes into that.

623

00:49:29,040 --> 00:49:31,680

But we wear jeans all the time and don't think anything of it.

624

00:49:31,680 --> 00:49:37,200

So I look at it from that's from firstly from that scale,

but on a smaller scale as it pertains to me.

625

00:49:37,200 --> 00:49:41,400

My father was a small businessman. He and I grew up in a small town.

626

00:49:41,400 --> 00:49:43,320

Small businesses, really hard.

627

00:49:43,320 --> 00:49:46,080

Small business lies at the heart of basically innovation.

628

00:49:46,080 --> 00:49:50,160

It lies at the heart of people being employed.

It lies at the heart of of every economy.

629

00:49:50,160 --> 00:49:54,120

Because without small business, like 90% of businesses, basically.

630

00:49:54,120 --> 00:49:57,600

Well, I shouldn't say 90%,

but certainly the majority of business is small business

631

00:49:58,880 --> 00:50:00,600

and they struggle with basically the same thing.

632

00:50:00,600 --> 00:50:03,760

And what I have been able to do is relieve some of those problems,

633

00:50:03,760 --> 00:50:10,080

like for example, when when you buy something today, you go online

and ask the question, you know, who should I give my money to?

634

00:50:10,840 --> 00:50:16,880

We used to go into, you know, the hardware store

and ask a guy, you know, what kind of washing machine should I buy?

635

00:50:16,920 --> 00:50:18,480

But we don't do that anymore.

636

00:50:18,480 --> 00:50:20,080

That happens online,

637

00:50:20,080 --> 00:50:25,880

and it happens in the context of a small A because most most businesses,

small business, it happens in the context of small business.

638

00:50:25,880 --> 00:50:32,400

So if you can if I can in some way, shape or form

help those small business people or small business persons

639

00:50:33,000 --> 00:50:38,120

get in the conversation when their customers are saying,

who do I buy from? Then I think I've done something good.

640

00:50:38,120 --> 00:50:44,160

So and I use and we can use AI to,

to make sure that, the footprint of that business is large enough

641

00:50:44,160 --> 00:50:48,120

that they can be found online because it's a, it's a

the playing field is not level.

642

00:50:48,120 --> 00:50:48,480

You don't

643

00:50:48,480 --> 00:50:50,640

you can be really, really good at what you do, but you could

644

00:50:50,640 --> 00:50:54,600

that doesn't mean that necessarily you're going to be found on YouTube

where you're going to be found on Instagram

645

00:50:54,600 --> 00:50:59,840

or LinkedIn or Google or whatever search engine,

you know, whatever search algorithm you have to be engaged with.

646

00:50:59,840 --> 00:51:06,840

So being good at being good at your job and actually being found

online are two different things, but all your customers are online.

647

00:51:06,840 --> 00:51:11,200

So you've got to square those two things.

And AI is a is a really, really good way to do it.

648

00:51:11,200 --> 00:51:14,680

You spoke with entrepreneurs.

That was you're in there. Partner yourself.

649

00:51:14,680 --> 00:51:19,200

Like in your experience what is their most convinced?

650

00:51:19,200 --> 00:51:21,400

Like what is the way to convince

651

00:51:22,360 --> 00:51:23,760

decision makers in the

652

00:51:23,760 --> 00:51:29,760

businesses to make like environmentally conscious decisions?

653

00:51:30,080 --> 00:51:32,680

What is like, but you know, how to talk to them?

654

00:51:32,680 --> 00:51:37,720

Well, I think the most important thing

is like every business person is concerned with culture.

655

00:51:37,720 --> 00:51:42,320

So if you have a culture in your business

that's dysfunctional, the business itself is dysfunctional.

656

00:51:42,320 --> 00:51:45,680

And if the business is is dysfunctional, you never going to make it.

657

00:51:45,680 --> 00:51:50,680

So. In this day and age, you have to be a well,

I shouldn't say in this day and age it's always been that way.

658

00:51:50,680 --> 00:51:54,480

If you want to attract really good people to come work with you,

then you have to have a really

659

00:51:54,480 --> 00:51:57,800

there has to be a reason for them

to come work with you beyond just paying,

660

00:51:57,800 --> 00:52:03,760

because people don't just respond to money,

they respond to things that are well outside just getting paid.

661

00:52:03,760 --> 00:52:11,280

Because after after our basic needs are met basically, and all are

primarily in the culture that we live in, all our needs are met.

662

00:52:11,320 --> 00:52:14,280

We live like kings, basically compared to the rest of the world.

663

00:52:14,280 --> 00:52:16,000

Certainly in a historical context.

664

00:52:16,000 --> 00:52:20,880

So it's hard to say that,

you know, in general that our needs aren't, aren't being met.

665

00:52:20,880 --> 00:52:23,640

But beyond that, there's other things that humans respond to.

666

00:52:23,640 --> 00:52:29,760

Like,

we have a people respond, to the to things, then of course, of course,

667

00:52:29,800 --> 00:52:35,800

that they're passionate about, but they respond to things

that they are morally that they feel morally aligned with.

668

00:52:36,360 --> 00:52:42,240

So they respond to, you know, things that are pointed up

as appointed as opposed to pointed down.

669

00:52:42,240 --> 00:52:46,440

So if your culture in your business is pointed

up, you're doing good things in the community, you're doing

670

00:52:46,440 --> 00:52:52,840

good things when it comes to, stewardship in the environment,

it means that you're engaged in volunteering and those kinds of things.

671

00:52:52,840 --> 00:52:56,440

And that draws people beyond, beyond

just the fact that you're paying them.

672

00:52:56,440 --> 00:53:02,000

So for entrepreneurs, I would say focus on the culture in your business

and make sure that the culture that you're that

673

00:53:02,000 --> 00:53:06,280

you're what you're actually cultivating

is good stewardship for the environment.

674

00:53:06,280 --> 00:53:12,280

And, you know, even if you're even if you're doing something

like making jeans, that doesn't mean you can't be planting trees.

675

00:53:12,520 --> 00:53:18,640

That doesn't mean that you can't be, that you can't be engaged

in providing clean water to to those to those communities

676

00:53:18,640 --> 00:53:20,680

that don't necessarily have access to it.

677

00:53:20,680 --> 00:53:31,520

That doesn't it doesn't mean that you can't be out in in your community

ensuring that people have access to, to good, safe food, safe being.

678

00:53:31,520 --> 00:53:34,760

It's not full of it's not laden with, you know, with, with chemicals.

679

00:53:34,760 --> 00:53:38,160

And of course, that's a huge problem in the culture that we live in.

680

00:53:38,160 --> 00:53:44,160

You can be in to that's that's this stewardship

and the and the ecosystem that you're actually in.

681

00:53:44,200 --> 00:53:49,160

You can but you can also be engaged

and in volunteering like there's nothing there's nothing more powerful.

682

00:53:49,160 --> 00:53:56,160

There's nothing, nothing that gets people working for you more excited

than then volunteering in the community in a way that they themselves

683

00:53:56,160 --> 00:53:59,960

think is important. So simply ask the people that are working for you

what is it you'd like to do in the community?

684

00:53:59,960 --> 00:54:05,120

What would make you feel good about about yourself today?

And you'll get fantastic ideas.

685

00:54:05,120 --> 00:54:09,360

And the companies that do those sorts of things are wildly successful

because people want to work.

686

00:54:09,360 --> 00:54:10,680

They're they're excited.

687

00:54:10,680 --> 00:54:15,600

They think that they're they think they're doing something really good,

not just for themselves but for other people.

688

00:54:15,600 --> 00:54:16,880

And that's incredibly motivating.

689

00:54:16,880 --> 00:54:24,560

So you can you can incentivize your, your workforce,

not just by paying them, but by, by creating a, a culture that's engaged

690

00:54:24,920 --> 00:54:31,440

with good policy that does good and that can start

that can start locally, that can start exactly where you are.

691

00:54:31,880 --> 00:54:35,280

And then then of course, you'll have a voice if you do that,

and you can use that voice

692

00:54:35,280 --> 00:54:41,280

then to, to lever the people who are supposed

to be making policy decisions by writing to them as a group,

693

00:54:41,480 --> 00:54:45,760

saying, okay, here, there's a letter here

that's signed by everybody that works for us,

694

00:54:45,760 --> 00:54:50,080

and we're unhappy about what you're doing

because we think what you're doing sounds good but isn't doing any good.

695

00:54:50,080 --> 00:54:54,840

And here's why. And you should probably rethink that. That's a

that's a very good answer.

696

00:54:54,840 --> 00:55:00,960

And that actually answered my other question that I had,

because sometimes you have those, you know,

697

00:55:01,080 --> 00:55:05,040

but you have those initiatives that are sounds good,

like I'm going to use your words.

698

00:55:05,040 --> 00:55:07,600

They sounds good, but they are not doing any good.

699

00:55:07,600 --> 00:55:09,880

And, you know, like I also like I'm wondering,

700

00:55:09,880 --> 00:55:15,880

like how to engage with those things

because on the other hand, you know, like I my day job isn't it.

701

00:55:15,960 --> 00:55:17,520

It isn't a tech.

702

00:55:17,520 --> 00:55:21,600

And I, for example,

listen about the authors who are just boasting where like,

703

00:55:21,600 --> 00:55:27,920

oh, you know, we this many percent powered by renewable energy and we,

you know, do all those things.

704

00:55:27,920 --> 00:55:33,960

And this is like it sounds like it is pointing up and people say,

oh, this is great, right?

705

00:55:34,240 --> 00:55:38,600

But then you are approaching that from the environmental perspective.

And it's like, okay, so how does it work?

706

00:55:38,600 --> 00:55:46,080

Is that through subsidy companies, the subsidy companies are be buying

peat bog, which is carbon sink and should be left alone.

707

00:55:46,280 --> 00:55:49,960

And they're building big frickin, wind farms

708

00:55:49,960 --> 00:55:57,040

on those peat bogs, and they're becoming net carbon emitters

because of the service roads needed to build those things.

709

00:55:57,040 --> 00:56:00,560

And so on and so forth and all that is.

710

00:56:00,560 --> 00:56:08,160

So you can then say from the stage that like, oh,

we like this, this many percent, you know, renewable energy.

711

00:56:08,160 --> 00:56:13,040

But the damage you've done to the environment to say this. So, you know,

we call it greenwashing.

712

00:56:13,040 --> 00:56:15,600

And so this is one part that I'm saying.

713

00:56:15,600 --> 00:56:21,600

But then there's another angle that I was like,

well, they gotta start somewhere

714

00:56:22,680 --> 00:56:28,120

for like for so many decades that was not even in the picture.

715

00:56:28,120 --> 00:56:33,440

So now this is in the picture. Is it not good

that this is in the picture because they got gotta start somewhere.

716

00:56:33,440 --> 00:56:35,320

You know, I, I don't know if you have that.

717

00:56:35,320 --> 00:56:40,200

I'm sure you have some comments on this,

but I'm just wondering this, you know, like how to engage with this.

718

00:56:40,200 --> 00:56:46,560

Like on one hand call them out on just blatant greenwashing

and then on the other hand, like,

719

00:56:46,760 --> 00:56:53,560

well, maybe actually the more productive approach is just as support

or like engage positively with this

720

00:56:53,920 --> 00:56:57,680

because this is a start

with might be a start of something actually positive.

721

00:56:57,680 --> 00:57:02,880

Yeah, I think that's exactly the way to look at it is still the

with the ways to look at it that they're on, they're on the path.

722

00:57:02,880 --> 00:57:04,400

At least they're pointed up.

723

00:57:04,400 --> 00:57:10,080

So firstly they have to invest money

and the infrastructure into into making a change.

724

00:57:10,080 --> 00:57:11,800

And, and that's a very big deal right.

725

00:57:11,800 --> 00:57:16,840

Because you know, big companies

are you know, imagine Amazon has to somehow change direction. Right.

726

00:57:16,840 --> 00:57:23,280

Or they think of the things that machinations of, of a company

that big that has to that has to move

727

00:57:23,760 --> 00:57:27,280

because the inertia behind it is, is, is, is, is enormous.

728

00:57:27,280 --> 00:57:33,600

So once they start to move like that's the hard

part is getting them to move then now the problem is to accelerate that.

729

00:57:33,800 --> 00:57:34,600

So okay, okay.

730

00:57:34,600 --> 00:57:37,360

You've, you've you've moved in in a positive direction.

731

00:57:37,360 --> 00:57:40,920

But that isn't enough. Right. Because wind farms aren't the answer.

732

00:57:40,920 --> 00:57:44,480

Solar isn't the answer.

The energy density is just not enough to power the,

733

00:57:45,480 --> 00:57:50,680

the demand that we have for for energy,

the demand that we have for energy is going up exponentially.

734

00:57:50,680 --> 00:57:54,120

And we need we need very, very, very we need very, very,

735

00:57:54,120 --> 00:58:00,120

power dense solutions to providing the energy

that we're going to that with, that we're going to need.

736

00:58:00,880 --> 00:58:06,120

And, solar and wind

is, is, is basically gets everybody moving in the right direction.

737

00:58:06,120 --> 00:58:08,240

But it's not the solution.

738

00:58:08,240 --> 00:58:11,040

There isn't, you know, the solution to power

739

00:58:11,040 --> 00:58:17,040

the cloud, for example, is not to cover the a landmass

the size of the United States with with windmills.

740

00:58:17,520 --> 00:58:20,440

That's that's not a good solution.

741

00:58:20,440 --> 00:58:21,920

It is a solution.

742

00:58:21,920 --> 00:58:23,280

But it's not a good solution.

743

00:58:23,280 --> 00:58:29,560

It sounds good, like you say, because it's green,

but it doesn't doesn't do good, but it's moving in the right direction.

744

00:58:29,560 --> 00:58:35,440

So once once the change happens and then the responsibility

is to accelerate that and ask some what's next?

745

00:58:35,440 --> 00:58:36,960

What's next, what's next.

746

00:58:36,960 --> 00:58:42,840

Because clearly, clearly this is now taking something in your case,

something that was carbon neutral, that was a carbon sink to now

747

00:58:42,840 --> 00:58:46,440

that's it's not no longer carbon neutral. It's carbon positive.

748

00:58:46,440 --> 00:58:48,600

It's it's emitter. It's a carbon emitter. Right.

749

00:58:48,600 --> 00:58:51,720

So it's not it's not taking such scrubbing carbon.

750

00:58:51,720 --> 00:58:55,000

It's actually it's like dumping it producing it.

751

00:58:55,000 --> 00:58:58,720

So you need to accelerate that change

because now they're moving in the right direction.

752

00:58:58,720 --> 00:59:01,680

And the hard part is actually to get the moving

which is why they're celebrating.

753

00:59:01,680 --> 00:59:05,280

Look at us. You know, we've made this big change okay. That's great.

754

00:59:05,280 --> 00:59:09,200

It isn't enough. Like you got to go just a little bit farther,

but you're moving in the right direction.

755

00:59:09,200 --> 00:59:12,480

They need to be celebrated in that regard for making that change.

756

00:59:12,480 --> 00:59:17,280

But then they you can't take that.

You can't take your foot off the gas and let them off the hook.

757

00:59:17,280 --> 00:59:23,880

Well, maybe letting them off the hook is not the right way to say it,

but you just can't take your foot off the gas to to to encourage them

758

00:59:23,880 --> 00:59:30,520

to continue down that path in an accelerating manner,

to keep up with it, with the demands that they're actually,

759

00:59:30,520 --> 00:59:34,160

with the demands that their own industry,

their own companies are going to be creating.

760

00:59:34,160 --> 00:59:35,160

Yeah, thanks for that.

761

00:59:35,160 --> 00:59:36,440

This is this is a good point.

762

00:59:36,440 --> 00:59:40,560

And, you know,

like we always like the message in this podcast is always, like I said

763

00:59:40,560 --> 00:59:47,640

at the top of the show, just engage in the positive way and the and the

and the mutual understanding, rather than, than fighting.

764

00:59:47,760 --> 00:59:54,240

Are you like overall are you an optimist into,

you know, like if you look at your crystal ball and you look, you know,

765

00:59:54,320 --> 00:59:58,640

what's going to happen to the environment

in the next ten, 20, 50, maybe 100 years.

766

00:59:58,640 --> 00:59:59,560

What do you see?

767

00:59:59,560 --> 01:00:01,080

Are you a do you see the good picture?

768

01:00:01,080 --> 01:00:05,600

You see a bad picture?

Do you think we are just as good as done or do we have a chance?

769

01:00:05,600 --> 01:00:07,920

Oh, I think I'm very positive to be.

770

01:00:07,920 --> 01:00:12,760

To be frank, the humans are very, very good at adapting,

but we're terrible at mitigating.

771

01:00:12,760 --> 01:00:20,200

So one of the ways to to differentiate good and bad policy is to

is understand the difference between mitigation and adaptation.

772

01:00:20,680 --> 01:00:23,280

And we have, like, you know, First Nations here.

773

01:00:23,280 --> 01:00:25,840

I mentioned them a couple times in this country

because we live quite close

774

01:00:25,840 --> 01:00:31,840

to Aboriginal peoples in terms of, proximity, but one

but then in terms of temporal, temporal.

775

01:00:32,440 --> 01:00:37,800

Basically you have pre-industrial age cultures,

you know, clashing with industrial age cultures and that that's,

776

01:00:37,800 --> 01:00:42,480

you know, whenever there's whenever there's a boundary,

you obviously have friction. That's where everything happens.

777

01:00:42,480 --> 01:00:49,080

So they have a this marvelous history of,

that goes back 10,000 years of, of adapting.

778

01:00:49,400 --> 01:00:54,160

So think of people living, the Inuit people living in Greenland

or all across in the Arctic,

779

01:00:54,160 --> 01:01:00,920

all the Arctic from,

you know, Russia, all around Canada, you know, Denmark, Iceland, maybe.

780

01:01:00,920 --> 01:01:03,160

That's certainly Iceland, I suppose.

781

01:01:03,160 --> 01:01:06,600

And the people that have been living

there have adapted to that environment.

782

01:01:06,600 --> 01:01:11,280

It's probably one of the harshest environments in the world to live in,

but they're beautifully adapted to living there.

783

01:01:11,280 --> 01:01:15,440

And they did it with tools that you and I wouldn't

look at a tool like a thorn.

784

01:01:15,440 --> 01:01:19,440

Can you imagine sewing deer clothing with a thorn?

785

01:01:19,440 --> 01:01:25,080

And you're sewing through seal hide in moose

hide and al-Qaida and caribou and wolf and everything under the sun.

786

01:01:25,080 --> 01:01:27,080

But their clothing is unbelievably good.

787

01:01:27,080 --> 01:01:33,000

It's it's so they're they're they're really good

at we're really good at adaptation. Look at the Dutch people

788

01:01:34,200 --> 01:01:36,440

building, you know, building their I can there.

789

01:01:36,440 --> 01:01:40,920

No one has. There's no one out there telling the North Sea

to stop rising like that's happening.

790

01:01:40,920 --> 01:01:48,360

They're not going to mitigate, you know, rainfall into the ocean by,

by by seeding clouds or whatever the case, they are seeding clouds.

791

01:01:48,360 --> 01:01:49,960

I suppose. It's such a word.

792

01:01:49,960 --> 01:01:54,040

They're going it's going to build, they're going to raise the dike

a little bit, which is mitigation, rising sea levels.

793

01:01:54,040 --> 01:01:57,840

Who knows why we're not going to worry about that.

We're going to raise the dike.

794

01:01:57,840 --> 01:01:59,480

So we're good at mitigating.

795

01:01:59,480 --> 01:02:05,480

So one way to to to differentiate

policy is mitigation versus adaptation.

796

01:02:05,560 --> 01:02:11,720

But as we go forward where our ability to mitigate improves,

it improves with with with technology.

797

01:02:12,040 --> 01:02:15,400

So you can feed large language models, very complex problems.

798

01:02:15,400 --> 01:02:21,720

And they'll come up with really good answers in ways that, that

we couldn't imagine and at a, at a pace at which we couldn't imagine.

799

01:02:22,080 --> 01:02:22,920

So I think we'll see.

800

01:02:22,920 --> 01:02:24,280

I solve problems that we

801

01:02:24,280 --> 01:02:30,760

that we would not be able to solve ourselves in the future,

not all good, of course, because there's always two sides to every coin.

802

01:02:31,240 --> 01:02:38,320

But I think that our ability to mitigate is going to it's going to,

it's going to outpace our,

803

01:02:38,760 --> 01:02:42,120

by a very large margin, our ability to destroy things.

804

01:02:42,120 --> 01:02:47,000

So so let me give you an example.

Let's talk about, very briefly, industrial agriculture.

805

01:02:47,000 --> 01:02:50,880

One of the ways that we're able to feed

the world is because we've become very, very good

806

01:02:50,880 --> 01:02:56,880

at producing,

at producing on a set piece of land, at increasing production.

807

01:02:57,280 --> 01:03:05,520

Now, the problem with that is that we've been using, you know, we've

been using fossil based fossil, fossil based fertilizers to do that.

808

01:03:06,240 --> 01:03:08,200

I can solve that problem for us.

809

01:03:08,200 --> 01:03:10,400

It'll solve the problem of of us,

810

01:03:10,400 --> 01:03:16,800

being able to increase industrial production, food production,

which will which we'll have to do if we're going to feed the world.

811

01:03:16,800 --> 01:03:21,120

But we can do that in a way

that's not nearly so damaging to the environment.

812

01:03:21,120 --> 01:03:23,960

One of the ways that one of the ways that happens here in Canada,

813

01:03:23,960 --> 01:03:31,280

in a, in a sort of simplistic way, is that everything

that's that's every every piece of farming equipment has a GPS on it.

814

01:03:31,960 --> 01:03:32,880

And that G.P.S.

815

01:03:32,880 --> 01:03:40,040

tracker tells that, that tells that farmer exactly how much seeds

should, should be going into this part, into this part of his

816

01:03:40,400 --> 01:03:44,400

part of his field, because it knows what the moisture content is,

because it's being measured.

817

01:03:44,400 --> 01:03:48,960

It knows that this part of the field

needs a little bit more fertilizer than the the other part of the field.

818

01:03:48,960 --> 01:03:49,520

It knows.

819

01:03:49,520 --> 01:03:54,960

It knows historically what the yield was last year, in the year

before that, in the year before that, and that likely that's going to

820

01:03:54,960 --> 01:03:58,080

maybe that trend is going to continue

or it's going to do something else.

821

01:03:58,080 --> 01:04:01,240

So that's an incredible amount of data on a tractor.

822

01:04:01,240 --> 01:04:06,160

And that tractors being every, every meter that tractor moves across

that field is being tracked.

823

01:04:06,160 --> 01:04:14,960

So there's a, a way to think of simplistic AI helping that farmer

be far more efficient in the use of fertilizers and chemicals, be

824

01:04:14,960 --> 01:04:22,320

far more efficient in the use of seeds, be far more efficient in the use

of fuels, everything to increase yield, which is incredibly important.

825

01:04:22,560 --> 01:04:27,240

So I think yields on in North America have increased

almost tenfold over the last.

826

01:04:27,240 --> 01:04:33,840

Well, I mean, ever since they've been farming industrially,

which is a massive increase, like ten times the amount of

827

01:04:34,280 --> 01:04:38,400

if you can produce ten times

the amount of fuel over the same piece of ground, then that's a big win.

828

01:04:38,400 --> 01:04:40,680

And if you can increase that again,

829

01:04:40,680 --> 01:04:46,920

and there's no reason to think that that can't happen because you can be

far more efficient and you can be far better at what you're doing.

830

01:04:46,920 --> 01:04:51,480

So if you can increase that again

but but reduce the environmental impact, that's a huge win.

831

01:04:51,480 --> 01:04:53,600

And so I'm optimistic about things like that.

832

01:04:53,600 --> 01:05:01,000

I'm optimistic about about using large language models

to to come up with better policies around fishing.

833

01:05:01,000 --> 01:05:04,760

So I'm a I love to fish, love to fly fish actually. So

834

01:05:06,000 --> 01:05:11,400

and I don't think I don't remember the last time ever

I've eaten a fish I've ever caught because, anyway.

835

01:05:11,400 --> 01:05:13,160

But I love to fish, so I'm.

836

01:05:13,160 --> 01:05:19,200

I'm always on the river, and I that one thing that drives me

crazy are, is the lack of enforcement like you were describing.

837

01:05:19,280 --> 01:05:25,840

For people who are fishing, there's lack of enforcement, but there's a

there's a fisherman, by and large, tend to be at least there.

838

01:05:25,840 --> 01:05:30,080

At least it's a vocal voice

because people that like fly fishermen are they're

839

01:05:30,080 --> 01:05:38,760

they're making huge strides and turning rivers into catch and release

only they're making huge strides into helping, fish come back to,

840

01:05:38,760 --> 01:05:46,200

fish populations to increase by encouraging governments to create waters

that are controlled or classified, which which reduces impact.

841

01:05:47,200 --> 01:05:53,280

And I can help with that because it can it

can it can take a large amount of data and then and then feed it

842

01:05:53,280 --> 01:06:00,520

into basically a global knowledge base to come up with better decisions

on how best to, to manage or to classify or to control access.

843

01:06:00,520 --> 01:06:04,040

So I'm, I'm optimistic almost across the scale.

844

01:06:04,040 --> 01:06:06,920

But that doesn't mean that we're not going to have big problems.

845

01:06:06,920 --> 01:06:12,360

We will have big problems, but we have we'll be able to wield

bigger and bigger hammers, as it were, to solve those problems.

846

01:06:12,360 --> 01:06:16,680

Well, thank you for that. And we need we need, positive messages, folks.

847

01:06:16,680 --> 01:06:25,320

Links to birds, personal website to website describing his adventures

as well as his business are in the description of this show.

848

01:06:25,640 --> 01:06:28,440

So go in there and continue exploring.

849

01:06:28,440 --> 01:06:33,640

Bert,

would you leave us and our listeners with that final message, like how?

850

01:06:33,640 --> 01:06:34,960

Like if you would like to

851

01:06:36,080 --> 01:06:37,920

leave us, like with one

852

01:06:37,920 --> 01:06:44,400

advice, you know, how to engage with the environment, with the policy,

how to engage in a positive way

853

01:06:44,800 --> 01:06:50,800

that would make that brighter future that you describe a reality.

854

01:06:50,920 --> 01:06:52,440

What would that advice be?

855

01:06:52,440 --> 01:06:57,080

I've never been successful at anything in my life

that I didn't have to persist at.

856

01:06:57,080 --> 01:07:01,120

So if you want to make if you want to be successful in business,

you have to persist.

857

01:07:01,120 --> 01:07:03,720

You want to climb a mountain, you have to persist.

You want to sail around the world.

858

01:07:03,720 --> 01:07:06,960

You got to persist, paddle across a continent. You got to persist.

859

01:07:06,960 --> 01:07:09,520

You got to think of, think of the strides that people made.

860

01:07:09,520 --> 01:07:16,480

Greenpeace in particular,

I suppose, maybe, I mean, well, I would say Greenpeace in terms of,

861

01:07:16,480 --> 01:07:23,080

killing, literally killing the international,

whale fishery like, that didn't happen overnight.

862

01:07:23,080 --> 01:07:29,080

There wasn't one person with a sign, you know, in front of some

parliament building somewhere saying you know, stop killing whales.

863

01:07:29,400 --> 01:07:32,520

That took, took, you know, at least two decades.

864

01:07:33,600 --> 01:07:36,200

I'm not saying everything that you're going to do

is going to take two decades.

865

01:07:36,200 --> 01:07:40,880

What I'm saying is that if you find something

that that you're passionate about, you will have to persist.

866

01:07:40,880 --> 01:07:42,600

If you want to make a long life, think of it.

867

01:07:42,600 --> 01:07:47,480

If you want to make a long term change, then you're going to

then you're going to have to engage over the long term.

868

01:07:47,480 --> 01:07:48,920

So we have big problems.

869

01:07:48,920 --> 01:07:57,360

They're all solvable if we're willing to persist in pursuing

good solutions, solutions that don't just sound weird but do good.

870

01:07:57,680 --> 01:08:03,840

So when you when you I would say to those people who are listening,

who are legitimately concerned and want to do something,

871

01:08:03,840 --> 01:08:06,240

then understand that you're this is a long game.

872

01:08:06,240 --> 01:08:10,800

This isn't this isn't nothing that nothing that we've talked about

is going to change overnight.

873

01:08:10,800 --> 01:08:15,560

That's not a bad thing in any way, in any way, shape or form,

because we all

874

01:08:15,560 --> 01:08:18,920

because we live in a pretty good space, by and large, in this country.

875

01:08:18,920 --> 01:08:23,280

And those things have come about

because people have been playing the long game to make things good.

876

01:08:23,280 --> 01:08:26,160

And now we have to play the long things to make things better.

877

01:08:26,160 --> 01:08:31,040

It's as simple as that. So simply persist. That's all it takes.

You don't have to be smart. You don't get to be good.

878

01:08:31,040 --> 01:08:34,920

You don't have to be rich.

You just have to be willing to persist that desire.

879

01:08:34,920 --> 01:08:38,280

These are words of wisdom. Thank you so much. It's been pleasure.

880

01:08:38,280 --> 01:08:39,440

Yeah, it's been great timing.

881

01:08:39,440 --> 01:08:44,720

I, like I said, I knew I knew we'd have fun doing it,

even though maybe some of the news is not as necessarily good.

882

01:08:44,720 --> 01:08:47,000

But it doesn't mean this isn't a good thing to talk about.