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Speaker 1: This is the Meeater podcast coming at you shirtless, severely,

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Speaker 1: bug bitten, and in my case, underwear listeningcast, you can't

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Speaker 1: predict anything. The meat Eater podcast is brought to you

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Speaker 1: by First Light. Whether you're checking trail cams, hanging deer stands,

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Speaker 1: first light dot com, f I R S T L

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Speaker 1: I t E dot com. Hey guys, if you like

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Speaker 1: watching the podcasts from the Meteater podcast Network on YouTube,

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Speaker 1: you need to get your little butt over to the

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Speaker 1: meat Eater Podcast Network, which is a whole new channel

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Speaker 1: on YouTube different from the normal me Eater YouTube channel.

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Speaker 1: You need to take action here. Go to the meat

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Speaker 1: Eater podcas Cast network on YouTube and subscribe. Keep your

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Speaker 1: subscription to the other thing. You'll be subscribed to both

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Speaker 1: and you'll get all of our podcast videos there. Going forward,

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Speaker 1: they will not be where they used to live. Go

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Speaker 1: to the new place. Thank you, Brody. They're gonna do.

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Speaker 1: We've talked about this in the past. It's looking more

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Speaker 1: and more likely that Colorado will have a wolverine reintroduction.

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Speaker 2: It's in the works for sure. At the same time,

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Speaker 2: this whole ESA thing is going on. Colorado has approved

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Speaker 2: a reintroduction. I don't think it's gonna happen overnight, but

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Speaker 2: it's the plans are in the works. They got to

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Speaker 2: go through some hoops to get it done. And like

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Speaker 2: you said, you know they belong there. It's a native species, right.

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Speaker 1: Yeah, I'd like to see it happen. I don't, like,

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Speaker 1: I'm not a fan of who's doing it, but i'd

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Speaker 1: like to see it happen. Look, if someone you don't

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Speaker 1: like give you five hundred bucks is still five hundred bucks.

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Speaker 2: So how's that fall online with your uh, with your

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Speaker 2: feelings on them being listed.

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Speaker 1: I don't think that they I just don't see that

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Speaker 1: they should have been listed.

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Speaker 2: Here because there's never a lot of them in the

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Speaker 2: first place.

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Speaker 1: Yeah, it's like that, there's just not a lot of

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Speaker 1: historic data of what they were going on. They're largely

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Speaker 1: going on some you know, they're largely going on some

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Speaker 1: findings from BC extrapolating that that will happen here. It's

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Speaker 1: like a future it's like a future listing. It's like, well,

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Speaker 1: I could see there being problems in the future based

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Speaker 1: on gut Therefore, and then I just I also know

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Speaker 1: how to be leveraged, Like I already know how to

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Speaker 1: be leveraged. Yeah, well I think it's it's a I

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Speaker 1: think it's a proxy fight.

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Speaker 2: Yeah, And that leverage is the same concern I have,

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Speaker 2: Like I'm all for the reintroduction in Colorado.

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Speaker 3: Where are they pulling wolverines from? Like where did they

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Speaker 3: so robust?

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Speaker 4: Right?

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Speaker 3: Because it can't be a penri.

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Speaker 1: They probably haven't even thought about that.

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Speaker 2: Yeah, I don't think they've gotten that far. They didn't

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Speaker 2: put a lot of thought into the wolf reintruction.

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Speaker 1: But they eventually got them.

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Speaker 2: Yeah, they got them.

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Speaker 1: They'll get them.

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Speaker 2: But the leverage you're worried about is the same leverage

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Speaker 2: I'm worried about with an administration like the Polis administration,

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Speaker 2: like leveraging that against hunting, against trapping, being like, oh,

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Speaker 2: this area is closed now, you can't go in there.

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Speaker 3: It's a refuge for an endangered species, which means we're

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Speaker 3: going to prohibit uh, human travel or whatever, trapping or

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Speaker 3: anything that could conceivably harm that species.

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Speaker 2: Yeah, I mean that administration has made it clear that

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Speaker 2: that's their angle.

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Speaker 1: So yeah, I think it'll be It's like I fear

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Speaker 1: that it'll become a proxy thing where they're they're like,

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Speaker 1: what's happening here is they're kind of talking about wolverines,

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Speaker 1: but they're kind of not Yeah, they're talking about backcountry

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Speaker 1: travel yep, right to talk about snowmobile use trapping restrictions.

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Speaker 2: Yeah, I mean it's kind of like, like you've talked

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Speaker 2: about it before, the Lynx thing here, Like there's links

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Speaker 2: up in northwestern Montana, but down here in southwestern Montana

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Speaker 2: where there's not really like there's this low elevation habitat

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Speaker 2: that's like potential links habitat where you can't trap bobcats.

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Speaker 2: Like I could see some version of that happening down

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Speaker 2: in Colorado.

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Speaker 4: I don't know.

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Speaker 1: Yeah, they drew it with a they drew the lines.

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Speaker 1: What's the thing I'm looking for? Like, uh, not surgically right,

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Speaker 1: like the Lynx recovery area including a lot of stuff

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Speaker 1: that never had, never has had, and never will have

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Speaker 1: a links But I think there's probably there's work on

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Speaker 1: that being done. I don't know if it'll be applied right, But.

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Speaker 3: For the wolverines are like those boundary lines of wolverine habitat, right,

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Speaker 3: it should be like pretty close proximity to like permanent snowfields,

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Speaker 3: glacial areas.

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Speaker 1: A convenience store, and Wahhington State downtown.

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Speaker 3: You know, yeah, yeah.

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Speaker 1: What spurred a lot is I recently got a trail

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Speaker 1: cam photo of a I got a trail camp photo

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Speaker 1: of a wolverine, which is sweet. You haven't seen that, No, No,

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Speaker 1: I got a magic I got. I got a camera

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Speaker 1: hanging on one tree. Put a set right there by

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Speaker 1: the camera. I got a camera hanging on a tree.

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Speaker 1: And on that camera, I've gotten gray wolves, Kyo, red fox, bobcat,

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Speaker 1: mountain lion, black bear, now wolverine, Martin, longtail weasel, A

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Speaker 1: lot of predators. Man, I wait, I don't know. I'm

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Speaker 1: waiting for a grizzly and I'm waiting for a grizzly

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Speaker 1: and linkstone.

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Speaker 3: What's amazing?

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Speaker 1: All all the same freaking tree.

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Speaker 5: That's really cool.

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Speaker 3: They like that tree?

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Speaker 1: Yea, I had that, and that wolverine came through. So

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Speaker 1: I posted that picture and generated a lot of discussion.

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Speaker 1: I posted a picture and used that occasion to gripe

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Speaker 1: about use that occasion to gripe about the move to

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Speaker 1: threatened and how the State of Montana is suing against it.

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Speaker 1: And then and then you know, people guy wrote A

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Speaker 1: guy wrote in what I thought was gonna be a

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Speaker 1: well A guy wrote in where he starts out pretty

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Speaker 1: good attacking my position, but then he lost all credibility

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Speaker 1: with me because in the end he uses discreete population

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Speaker 1: segment when in fact it's a distinct population segment. And

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Speaker 1: I'm like, this guy, have andy what he's talking about.

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Speaker 1: He even capitalized it, so he doesn't know what a

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Speaker 1: DPS is.

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Speaker 3: So change your email before you ran back in it was.

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Speaker 1: Out the door with what he thinks. No, a lot

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Speaker 1: of people are griping about that, but I'm not giving

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Speaker 1: an inch, dude. I'm not giving an inch on it.

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Speaker 2: Stick to your guns man, like.

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Speaker 1: I don't uh. I'm a big time wilderness advocate, big

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Speaker 1: time yep, I pointed out in this thing like I

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Speaker 1: have come out all the time, like you know, continued

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Speaker 1: protections for anwar in opposition to Ambler Road. We just

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Speaker 1: did a podcast celebrating the heal the wilderness area and

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Speaker 1: the creation of the Wilderness system, which we've done a

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Speaker 1: bunch of times, and it's like, don't come at me

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Speaker 1: about it from that angle. In this case, I just

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Speaker 1: think I think the wolverine thing is bullshit.

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Speaker 3: Well, obviously we have a big issue with wildlife populations.

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Speaker 3: Right when we talk about scientific management, which is a

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Speaker 3: conversation we have all the time, right, it's like it

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Speaker 3: can be used for good and bad. From my perspective,

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Speaker 3: where it's like, well, we don't know how many animals

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Speaker 3: there are, so we need to figure that out, but

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Speaker 3: then we can set our regulations. It's like, but we

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Speaker 3: never do know how many animals there are, Like we never,

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Speaker 3: we never will.

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Speaker 1: Yeah. When they started doing the population work on wolverines

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Speaker 1: and and when it started the population work on wolverines

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Speaker 1: in Idaho, Montana wholming, the biggest takeaway was Jesus wolvernes

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Speaker 1: all over the place, and al a sudden out of

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Speaker 1: that came this. I just don't I think it's I

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Speaker 1: don't think it's a good use of time.

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Speaker 6: Well, and there's there's always a focus on did it exists?

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Speaker 1: I haven't introduced you yet.

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Speaker 5: I'm just gonna jump in because.

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Speaker 1: We're you're gonna talk for two hours.

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Speaker 6: I didn't know we had such formal rules here.

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Speaker 1: Please just started.

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Speaker 5: There's always this.

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Speaker 6: Focus on what where had it existed in there? And

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Speaker 6: there's usually little focus on what what did it perform

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Speaker 6: for the ecosystem? What good does it do back to

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Speaker 6: the ecosystem? And I think that's where the narrative needs

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Speaker 6: to be going, not historically where did it range? And

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Speaker 6: because we're usually taking snapshots that could be yeah, completely

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Speaker 6: out of context for why the animals were pushed into

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Speaker 6: a certain area. But we need to be focused on

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Speaker 6: how do we bring species back into ecosystems that perform

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Speaker 6: specific functions to improve biodiversity, to improve ecosystem health, and

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Speaker 6: be less focused on did it exist there? One day

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Speaker 6: two hundred and fifty years ago.

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Speaker 7: Mwown somebody up in Lewistown, Montana one day.

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Speaker 3: Yeah, convenience store in Washington. Right, somebody's like, oh, look

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Speaker 3: look at the data.

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Speaker 5: I mean it arranged in the dairy aisle. So we

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Speaker 5: got to put it back. That would be a daytime?

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Speaker 5: Is that?

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Speaker 1: Ladies, gentlemen you here, you just heard the voice of

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Speaker 1: Matt James from Colossal Laboratories and Biosciences Company. This don't

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Speaker 1: I don't want to. I don't want to trivialize, Okay,

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Speaker 1: I don't. I'm going to titillate people without trivializing what

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Speaker 1: you do, okay.

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Speaker 5: Should be interesting.

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Speaker 1: This is this is this is the company, These are these,

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Speaker 1: these are the people leading the charge, uh with you know,

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Speaker 1: the most likely path forward on this idea which you

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Speaker 1: discussed before, cloning a wooly mammoth, of resurrecting the Tasmanian tiger,

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Speaker 1: of perhaps one day putting Dodo birds back on the landscape.

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Speaker 6: What was their island, Mauritius, Mauritius.

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Speaker 1: So we're going to talk about de extinction. And again

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Speaker 1: when I said, don't want to trivialize it, because we're

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Speaker 1: also going to talk about preventing extinction exactly. So a

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Speaker 1: lot of emphasis in this world gets put on in

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Speaker 1: the news. It always gets like cloning a mammoth, cloning

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Speaker 1: a man with cloning a mammoth. But out of that

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Speaker 1: work and it's almost become shorthand for a collection of

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Speaker 1: it's become shorthand for like this, a collection of technological

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Speaker 1: advancements that are applicable around biodiversity and applicable around preventing extinction.

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Speaker 1: And then and then if need to be de extinction exactly.

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Speaker 6: The extinction is sort of the intersection of this amazing

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Speaker 6: set of technologies that are all emerging at a similar time,

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Speaker 6: and we sit at that intersection today, which has given

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Speaker 6: us the ability to not exactly clone a wily mammoth.

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Speaker 6: We know we cannot do that. I think you had

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Speaker 6: Best Shapiro on years ago, and she talked about this

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Speaker 6: problem exactly, but to be able to engineer genomes to

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Speaker 6: begin to mirror extinct species and bring that species back

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Speaker 6: in a way that is as representative of the extinct

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Speaker 6: animal as it could be, and what.

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Speaker 1: We talked about last night. Maybe I'm gonna have you

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Speaker 1: start with this real quick. This is not going to

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Speaker 1: be the focus of our conversation. But let's say a

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Speaker 1: fella had a once in a lifetime hunting dog.

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Speaker 5: Let's say that.

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Speaker 1: Okay, let's say this Yanni has a beloved dog and

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Speaker 1: it fell off a cliff recently.

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Speaker 6: It's fine, that's a real story, that's true. I'm sorry.

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Speaker 1: Let's say that Yannie's dog had fallen off that cliff

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Speaker 1: and wasn't okay, can you walk through, how quickly walked

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Speaker 1: through how he might wind up with in the It's possible, now,

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Speaker 1: it's expensive, but possible. How he might wind up with

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Speaker 1: that dog all over again?

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Speaker 6: Well, I mean this kind of goes back to the

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Speaker 6: late nineties when we talked about Dolly the Sheep and cloning. Right,

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Speaker 6: this is just basic cloning technology and the extension is

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Speaker 6: an advancement thereof. But so for this example, we're really

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Speaker 6: talking about cloning. So, whether you had a living dog

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Speaker 6: or a dog that you know, unfortunately just passed away,

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Speaker 6: you fresh dead, yeah, unfortunately, I hate to say it

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Speaker 6: that way, but you need a fresh dead animal or

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Speaker 6: a living animal, and you can extract living cells either

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Speaker 6: from skin tissue, where there's even some novel technologies that

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Speaker 6: might include being able to do this from blood. And

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Speaker 6: what you do is you take those cells or those

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Speaker 6: tissues and you put them into a petri dish essentially, right,

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Speaker 6: You're going to culture this and you find out what

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Speaker 6: are the culture conditions so that we can begin to

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Speaker 6: take that one tissue and proliferate into this living cell line.

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Speaker 6: And then we go and select very specific cells. We're

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Speaker 6: going to look for things like epithelial cells, and we

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Speaker 6: can make something called the fiber blast line. You have

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Speaker 6: that we just freeze it, you put it on liquid nitrogen.

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Speaker 6: It will live forever in a biobank.

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Speaker 5: Excuse me, and.

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Speaker 1: So Mingus is in a biobank.

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Speaker 6: Now Migus is on ice in a biobank, and one

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Speaker 6: day you say, you know, I really want to see

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Speaker 6: Mingus again. We have the ability to be able to

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Speaker 6: go back to Mingus, take his cells, put them into

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Speaker 6: the o site or the egg of a dog, and

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Speaker 6: fertilize an embryo culture that embryo in vitro and then

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Speaker 6: eventually transferred into a surrogate dog.

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Speaker 5: That surrogate would just state sixty.

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Speaker 6: Five days later, you know, little day zero, Mingus is

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Speaker 6: born and it is an exact living replica of the

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Speaker 6: dog or whatever animal you were looking for. Now, obviously there's.

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Speaker 3: There's with a crazy blood lust.

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Speaker 6: Right, There's one thing that I think is always important

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Speaker 6: with cloning is we have to talk about nature versus nurture.

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Speaker 5: Right, your dog.

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Speaker 6: Might not end up being you know, Mingus two dot

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Speaker 6: oh might not be Mgus one dot oh because the

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Speaker 6: way you raised the two might vary, and that plays

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Speaker 6: a big role, especially in hunting dogs. As you guys

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Speaker 6: know well better than I do, that that training that

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Speaker 6: happens really early on, that sort of life experience is

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Speaker 6: as important as genetics often.

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Speaker 3: Well dog wise, right, like, the way I was able

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Speaker 3: to train a dog ten years ago is a lot

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Speaker 3: different than the way I was able to train a

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Speaker 3: dog two years ago. So like that may be changed

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Speaker 3: because I changed, Am I improved as a trainer? Change?

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Speaker 5: Right?

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Speaker 3: No, I'm way busier now, you're actually way way worse.

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Speaker 1: Yeah that on that thing, like uh, the nature versus

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Speaker 1: nurture thing, but on this idea that pretty soon you

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Speaker 1: would be able to just get your you know, get

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Speaker 1: your best hunting dogs cloned, and instead of just going

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Speaker 1: back to the same sire, the same bitch and getting

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Speaker 1: another dog out of that litter, you're gonna wind up

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Speaker 1: with something closer, right.

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Speaker 6: You're gonna be because right every time you breed, you're

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Speaker 6: sort of shuffling genetics, and you know, the sire and

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Speaker 6: the bitches DNA will mix and you'll get a different

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Speaker 6: you know, set of phenotypes. Then you might have just

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Speaker 6: from the original, just like you might have siblings that

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Speaker 6: are not exactly the same as you.

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Speaker 5: It's because it was.

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Speaker 6: A reshuffling of the genomic information by cloning, and you're

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Speaker 6: actually taking that full genome and just doing it again.

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Speaker 1: Like how okay, how much would it look? Like? How

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Speaker 1: much would mingus two point zero look like mingos are.

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Speaker 5: The spots in the same place, So yeah, if it's

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Speaker 5: a spotted dog.

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Speaker 6: So this is a great question because there are several

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Speaker 6: things that control the way that our genes are expressed

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Speaker 6: into phenotypes.

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Speaker 5: Right.

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Speaker 6: So one of them is obviously the genetics are what

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Speaker 6: are the genetics telling the cells to make? But the

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Speaker 6: other is a is a process called epigenetics. So basically,

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Speaker 6: what are the environmental forces and around the expression of

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Speaker 6: those genes, there's regulatory pathways. Maybe you know, say you

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Speaker 6: were supposed to be six foot four, but you were

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Speaker 6: undernourished as a child, You're not going to grow to

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Speaker 6: be six foot four. That's an epigenetic effect, right. So

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Speaker 6: you could clone three minguses right now and each of

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Speaker 6: them would show up and look very very similar, but

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Speaker 6: those those spots might end up in slightly different sizes

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Speaker 6: or areas, and and sometimes you see that drift, you know,

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Speaker 6: there's uh, they've been cloning in race and not racehorses, sorry,

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Speaker 6: but like polo horses and dressage and horses like that.

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Speaker 6: And you can go into a barn and you can see,

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Speaker 6: you know a lot of these sort of brown horses

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Speaker 6: with a nice white spot on their on their face,

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Speaker 6: and it's slightly different on each one. It's the trickiest

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Speaker 6: thing you've ever seen. Yeah, but from afar they are

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Speaker 6: identical animals.

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Speaker 1: How much do you think you capture? It's it's let's

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Speaker 1: say you take Mngus okay, and you give Mingus a stimuli, okay,

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Speaker 1: Like like Mingus is And I don't know if it's

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Speaker 1: true or not, but Mingus is the sort of do

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Speaker 1: that that if he gets up on the table okay

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Speaker 1: and eats leftovers off the table when you're you know,

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Speaker 1: out of the room. He's the kind of dog that

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Speaker 1: man you tell him one time that ain't good, he

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Speaker 1: ain't gonna do it again, right, Like, if that's a

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Speaker 1: response to stimuli, what would you expect to see about

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Speaker 1: the cloned dog's response to stimuli?

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Speaker 6: Well, it just depends on how it was raised. I

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Speaker 6: would expect you know that that's really operant conditioning, right

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Speaker 6: when we talk about sort of how can you uh

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Speaker 6: show a stimuli and then get a required behavior and

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Speaker 6: provide a consequence. Sometimes it's positive, like you fed the dog,

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Speaker 6: you know, you gave him a treat because they did

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Speaker 6: what you wanted. And other times to maybe yelled at

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Speaker 6: the dog and the dog ran off, so negative conditioning there, right.

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Speaker 6: If they were raised the same way, I bet it'd

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Speaker 6: be identical. But if one was raised by a really

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Speaker 6: great dog trainer, in the other by somebody who just

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Speaker 6: let his dog feet off the table, those two manuses

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Speaker 6: would probably behave very different directions.

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Speaker 2: Is there another version of this where you can like

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Speaker 2: put add ons into mingus two point.

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Speaker 5: Oh, Like, let's say, are getting into what we're doing?

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Speaker 2: Yeah, strong, Yeah, we're.

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Speaker 6: Not enhancing that. You know, we would call those like

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Speaker 6: genetic enhancements or something. We're not really doing that for

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Speaker 6: dogs or for things. We're focused on the conservation side.

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Speaker 6: But you know, to that point, yes, you could say

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Speaker 6: we want to confer a specific disease resistance to this animal. Right,

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Speaker 6: Distemper in dogs is an issue and they found you know.

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Speaker 5: Like with wolves.

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Speaker 6: If you see a black wolf, that's actually a sign

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Speaker 6: that there's been dogs that have integressed into that dog's

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Speaker 6: genetic line. But it also is closely correlated with a

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Speaker 6: resistance to distemper, which dogs stand.

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Speaker 1: Is that right?

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Speaker 6: Yeah, so if you see a black wolf, now it

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Speaker 6: has to be a header. As I guess you're.

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Speaker 1: Looking at old dog DNA.

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Speaker 5: You're looking at old dog dna. Yeah, wolves did not

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Speaker 5: evolve the black yeah.

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Speaker 3: Uh.

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Speaker 6: And but it also is highly correlated with distemper resistance.

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Speaker 6: So you could identify that gene and finding that doesn't

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Speaker 6: have it and using genetic editing tools, you know, the

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Speaker 6: most famous being crisper. You could drop that in there

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Speaker 6: and then you know reasonably when the doug's born, it

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Speaker 6: will be resistant to distemper.

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Speaker 3: All right, can can we move on from the pet project? Oh?

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Speaker 1: No, that was that was a warm Yeah. We're gonna

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Speaker 1: do a couple of things that we're gonna get into that.

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Speaker 1: We're gonna get into all the big all the big

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Speaker 1: crazy stuff.

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Speaker 3: Yeah, that's like your boutique making money on the side

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Speaker 3: spin off.

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Speaker 6: We're not even doing it, but it's I think it's

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Speaker 6: an easy example for people to understand.

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Speaker 1: Okay, let's close that conversation out with with this. When

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Speaker 1: you crystal ball it, do you picture in ten years,

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Speaker 1: do you picture that becoming kind of how we're producing

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Speaker 1: hunting dogs, how we're producing specialty dogs, how we're producing

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Speaker 1: drug sniffing dogs. Where you have these like you know,

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Speaker 1: one and one hundred attributes.

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Speaker 6: Yeah, I think, you know, maybe ten years or too soon,

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Speaker 6: just because there's some social acceptance. But in the working

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Speaker 6: dog class, especially honey dogs and you know, say police dogs, Yeah, absolutely.

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Speaker 1: Like the military is like, no, I want that. Why

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Speaker 1: would you want a bunch of those? Yeah? If this

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Speaker 1: is a business, I don't want to go through thousands

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Speaker 1: of dogs to find that exactly.

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Speaker 6: You know, if this is a business, fore you're gonna

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Speaker 6: find a way how can we most efficiently produce that,

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Speaker 6: you know, reliably reproduce that phenotype. Absolutely, And the science

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Speaker 6: is there today and it will just in ten your

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Speaker 6: time be so scalable and cheaper that I think it'll

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Speaker 6: be widely accepted.

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Speaker 1: I asked you yesterday to throw me a ballpark on

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Speaker 1: what this Mingus project? Are you comfortable doing this?

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Speaker 5: Sure?

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Speaker 1: Yeah, I said, like give me a ballpark. Like Yanni

400
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Speaker 1: wants a new Mingus. What's he looking at? If you

401
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Speaker 1: just put at fair market.

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Speaker 6: You know, seventy five K I think just because you know,

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Speaker 6: and that's a number I just kind of pulled out

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Speaker 6: a roundabout number when we were talking about Now you're.

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Speaker 1: Talking about cost. That's that's a cost that's not retail markup.

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Speaker 5: No, because there's there's just so many. Yeah, there are so.

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Speaker 3: Many retail markum Sky's the limit. Yeah, I mean just

408
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Speaker 3: looking at the duck hunting world, like what guys will

409
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Speaker 3: pay for a finished Labrador Retriever or a German short

410
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Speaker 3: hair pointer that somebody else has gone through the raising

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Speaker 3: of with a good background, And that good background typically

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Speaker 3: just means everybody thinks that the dogs coming out of

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Speaker 3: this candel are the best.

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Speaker 1: Yep.

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Speaker 3: I mean you can put whatever price tag you want,

416
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Speaker 3: but what are some numbers you heard that people are

417
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Speaker 3: paying for them? Basically anything under a quarter of a million? Wow,

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Speaker 3: for the right person.

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Speaker 1: Yeah, man, I'm in an awkward position. Oh great, Yeah,

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Speaker 1: I want to clarify this is not what you do. Correct,

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Speaker 1: it's not what your company does.

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Speaker 6: But I'm starting to get an idea it's.

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Speaker 1: Your company does. I like layout, like, just take a

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Speaker 1: wild ass guess. Take a wild ass guess. Let's put

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Speaker 1: it into this case, like the military. You know they

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Speaker 1: have dogs they use in combat operations whatever, and they

427
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Speaker 1: want to order like a whole bunch of these dogs.

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Speaker 6: Uh Like what would that be? Wild ass guests? I

429
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Speaker 6: mean you just think you don't discoverment spending. I think

430
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Speaker 6: you could go north of a million or two million

431
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Speaker 6: on them the right animal, right, Yeah.

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Speaker 3: Think of the falconry and racing pigeon world like sultans

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Speaker 3: of Like, yeah, we're into we're into money than like

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Speaker 3: I mean, we're dancing around races.

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Speaker 1: Let's we're gonna talk about what mad actually does.

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Speaker 3: What everything before just now, that's just gonna be the

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Speaker 3: prices for animals.

438
00:22:48,160 --> 00:22:52,879
Speaker 1: Okay, because what they're actually doing is fascinating. We're go

439
00:22:53,000 --> 00:22:54,639
Speaker 1: getting what they're actually doing in just one in just

440
00:22:54,680 --> 00:22:56,280
Speaker 1: one second, I was just little. That was just a

441
00:22:56,320 --> 00:23:08,560
Speaker 1: little warm up. The kids podcast, we keep talking about,

442
00:23:08,600 --> 00:23:12,640
Speaker 1: starts July fifth, right on this podcast feed. We've said

443
00:23:12,680 --> 00:23:14,119
Speaker 1: it a bunch of times. How many are we making?

444
00:23:14,280 --> 00:23:14,560
Speaker 4: Five?

445
00:23:14,640 --> 00:23:19,440
Speaker 1: We're making five kids podcasts. Whether we make number six

446
00:23:19,520 --> 00:23:21,880
Speaker 1: depends on if your kids like it. Yeah, I can't

447
00:23:21,880 --> 00:23:24,760
Speaker 1: say any plane or net. Each episode of the kids

448
00:23:24,800 --> 00:23:27,040
Speaker 1: podcast goes like this, They're quick, how long are they?

449
00:23:27,040 --> 00:23:28,359
Speaker 1: What are they? Where are they coming to? Net? Phil

450
00:23:28,400 --> 00:23:32,240
Speaker 1: twenty fifteen to twenty Okay, it's a three x structure.

451
00:23:33,040 --> 00:23:36,400
Speaker 1: There's why it's the way it is, where we explain

452
00:23:36,640 --> 00:23:41,760
Speaker 1: why something is the way it is. It could be

453
00:23:42,200 --> 00:23:44,960
Speaker 1: Why are teddy bears called teddy bears? It could be

454
00:23:46,920 --> 00:23:49,959
Speaker 1: what is an anadamous fish? It could be when you

455
00:23:50,000 --> 00:23:55,560
Speaker 1: say nocturnal, what's the opposite? And is there a middle ground?

456
00:23:57,440 --> 00:23:59,439
Speaker 3: I like it asking the question.

457
00:23:59,560 --> 00:24:06,159
Speaker 1: Yeah, there is. It's called crepuscular. Okay. Other Wise the

458
00:24:06,160 --> 00:24:09,480
Speaker 1: way it is is that we're doing Oh what exactly

459
00:24:09,520 --> 00:24:11,840
Speaker 1: did Daniel Boone and Davy Crockett do for a living?

460
00:24:13,000 --> 00:24:15,439
Speaker 1: Why it's the way it is? What exactly were they

461
00:24:15,520 --> 00:24:17,720
Speaker 1: up to? Why does everybody know about those guys? What

462
00:24:17,760 --> 00:24:20,960
Speaker 1: did they do for a living? Can you think of more?

463
00:24:21,000 --> 00:24:22,680
Speaker 1: Why it's the way it is? We just do them all.

464
00:24:23,040 --> 00:24:24,680
Speaker 1: I think you just listed all of them. Okay, So

465
00:24:24,800 --> 00:24:27,639
Speaker 1: why it's the way it is? I host Why it

466
00:24:27,640 --> 00:24:31,560
Speaker 1: is the way it is? I tell your kid, why

467
00:24:31,680 --> 00:24:34,520
Speaker 1: is the way it is? What's my credential? I've been

468
00:24:34,520 --> 00:24:36,199
Speaker 1: telling my kids why is the way it is? For

469
00:24:36,200 --> 00:24:41,680
Speaker 1: fourteen years and everyone else? So that's why I took

470
00:24:41,800 --> 00:24:46,200
Speaker 1: That's why that's my job. And then there's Guess that Critter.

471
00:24:46,280 --> 00:24:49,880
Speaker 1: Guess that Critter, which Krinn works on, but it's hosted

472
00:24:49,880 --> 00:24:54,000
Speaker 1: by my lovely wife who hosts. She just she does

473
00:24:54,040 --> 00:24:57,840
Speaker 1: the read and guess that critter where we do wild

474
00:24:57,960 --> 00:25:01,000
Speaker 1: we come up. We use animals to have the craziest vocalizations,

475
00:25:01,440 --> 00:25:05,520
Speaker 1: the most varied, craziest vocalizations, and we play vocalizations and

476
00:25:05,520 --> 00:25:11,040
Speaker 1: then we start providing a bed of clues. Uh. The

477
00:25:11,119 --> 00:25:13,000
Speaker 1: earlier kid gets it. The smarter kid is.

478
00:25:16,560 --> 00:25:21,000
Speaker 3: You'll be able to take that score to your Montsori.

479
00:25:20,560 --> 00:25:24,120
Speaker 1: School and you'll also know whether you want to pull

480
00:25:24,160 --> 00:25:25,520
Speaker 1: blood from that kid and send it to me.

481
00:25:29,200 --> 00:25:31,000
Speaker 4: Uh.

482
00:25:31,760 --> 00:25:35,880
Speaker 1: Then the final thing is kids trivia, and we bring

483
00:25:35,880 --> 00:25:42,640
Speaker 1: in a bunch of actual live kids. They record trivia, not.

484
00:25:43,520 --> 00:25:45,440
Speaker 8: Tell us heavily.

485
00:25:46,040 --> 00:25:50,080
Speaker 1: Heavily staff familiar and some neighbors, straight neighborhood kids we've

486
00:25:50,080 --> 00:25:53,399
Speaker 1: brought in. We brought in my primary care providers kids.

487
00:25:53,440 --> 00:25:57,359
Speaker 1: Didn't we just bringing some stray kids. They played trivia,

488
00:25:57,359 --> 00:26:01,159
Speaker 1: but they play trivia this way, you know, keeping hollering

489
00:26:01,400 --> 00:26:03,960
Speaker 1: kids these days, there's no winners and losers. They're all winners.

490
00:26:04,280 --> 00:26:06,160
Speaker 1: So what the kids do is they build a pot

491
00:26:06,200 --> 00:26:09,359
Speaker 1: of money for conservation. Meaning it's our normal, it's a

492
00:26:09,359 --> 00:26:12,080
Speaker 1: trivia show for kids. But every time any of the

493
00:26:12,160 --> 00:26:16,440
Speaker 1: kids gets to like every right answer generates more revenue

494
00:26:16,560 --> 00:26:19,720
Speaker 1: into the pot, which goes to a conservation organization that

495
00:26:19,840 --> 00:26:23,320
Speaker 1: that's a kid's focused conservation group where kids focus charity

496
00:26:23,800 --> 00:26:26,199
Speaker 1: and so they they're building the pot. Meaning when you

497
00:26:26,240 --> 00:26:28,199
Speaker 1: ask all ten them a question, it's not that some

498
00:26:28,280 --> 00:26:32,280
Speaker 1: of them win and lose. It's that the right answers

499
00:26:32,400 --> 00:26:35,120
Speaker 1: build a pot of money. So their cooperative effort.

500
00:26:34,840 --> 00:26:37,760
Speaker 5: There are weak links in the chain that I'm sure.

501
00:26:40,040 --> 00:26:46,920
Speaker 8: Well in terms of the nature versus nurture host Spencer

502
00:26:47,600 --> 00:26:56,000
Speaker 8: Newharth definitely has found some personality similarities between uh are

503
00:26:56,000 --> 00:26:58,880
Speaker 8: our colleagues and their children, and he chooses to point

504
00:26:58,880 --> 00:27:01,800
Speaker 8: them out each time, like like these.

505
00:27:01,760 --> 00:27:03,600
Speaker 1: Kids just quietly have the right answer.

506
00:27:04,560 --> 00:27:09,440
Speaker 8: Yeah, I mean he definitely. He definitely picked on Mabel,

507
00:27:09,720 --> 00:27:13,240
Speaker 8: one of Yanni's daughters, for having a similar trait of

508
00:27:14,640 --> 00:27:15,800
Speaker 8: seeing if anyone, but that was.

509
00:27:15,800 --> 00:27:19,000
Speaker 9: Only because Mabel called him out, and I think that

510
00:27:19,080 --> 00:27:20,080
Speaker 9: he was embarrassed by.

511
00:27:22,080 --> 00:27:26,680
Speaker 3: The video component is there's a tube that shoots out

512
00:27:26,680 --> 00:27:30,520
Speaker 3: a marshmallow to the person with the right answer, And

513
00:27:30,560 --> 00:27:32,679
Speaker 3: that's where it really cranks up visually.

514
00:27:35,480 --> 00:27:38,640
Speaker 9: You don't feel like you know us well already from

515
00:27:38,680 --> 00:27:41,360
Speaker 9: listening to us for hours every week. Now you'll you'll

516
00:27:41,359 --> 00:27:44,000
Speaker 9: get like a another layer of who we are because

517
00:27:44,000 --> 00:27:46,560
Speaker 9: you're going to get to like study who are kids are?

518
00:27:46,600 --> 00:27:49,240
Speaker 5: And those of us without children will remain mysterious.

519
00:27:49,280 --> 00:27:54,760
Speaker 3: That's right, which was the point the whole time.

520
00:27:55,119 --> 00:27:59,679
Speaker 1: June twenty seventh, tune in on YouTube for our latest experiment.

521
00:28:00,840 --> 00:28:02,360
Speaker 1: Not latest, We don't do that many. Yeah, I guess

522
00:28:02,359 --> 00:28:05,280
Speaker 1: we've done a few experiments. Yesterda two days ago we

523
00:28:05,280 --> 00:28:08,640
Speaker 1: went out and made bullboats. So we went and got

524
00:28:09,520 --> 00:28:12,280
Speaker 1: a bull boat, as you know, or maybe you don't,

525
00:28:13,520 --> 00:28:17,480
Speaker 1: is a temporary use water craft that can be made

526
00:28:17,680 --> 00:28:20,960
Speaker 1: using nothing but the hide off of a buffalo. It's

527
00:28:21,000 --> 00:28:22,840
Speaker 1: called a bullboat because you need a pretty good sized

528
00:28:22,920 --> 00:28:27,399
Speaker 1: critter to make it. We used a couple thousand pound

529
00:28:28,000 --> 00:28:30,760
Speaker 1: roughly thousand pound bulls, I mean a three year old

530
00:28:31,119 --> 00:28:37,120
Speaker 1: three year olds. We have a friend at North Bridger Bison,

531
00:28:38,080 --> 00:28:41,520
Speaker 1: Matt Skogland, North Bridger Bison, who does he does all?

532
00:28:43,160 --> 00:28:47,200
Speaker 1: He has a bison ranch. He's explaining me before His

533
00:28:47,600 --> 00:28:49,680
Speaker 1: animals are born on his ranch and they die on

534
00:28:49,720 --> 00:28:54,200
Speaker 1: his ranch, all grass fed, field harvested. And what you

535
00:28:54,280 --> 00:28:56,440
Speaker 1: do is when you want to buy from him, you

536
00:28:56,440 --> 00:28:59,840
Speaker 1: buy the animal, right, it's custom slaughter. You buy the animal,

537
00:29:00,080 --> 00:29:01,720
Speaker 1: buying the meat on the animal. You don't go on

538
00:29:01,760 --> 00:29:03,840
Speaker 1: a website and buy a cut of this, a cut

539
00:29:03,880 --> 00:29:06,280
Speaker 1: of that. You go in and buy a portion of

540
00:29:06,440 --> 00:29:09,360
Speaker 1: percentage of an animal that's currently living on his ranch.

541
00:29:09,720 --> 00:29:14,320
Speaker 1: He field harvests the animal. It's custom cut to your specifications. Anyhow,

542
00:29:15,440 --> 00:29:18,000
Speaker 1: we got hides from him and made boats, and we

543
00:29:18,040 --> 00:29:20,520
Speaker 1: made boats using nothing but native materials. So we went

544
00:29:20,520 --> 00:29:26,880
Speaker 1: into a willow patch and used willow bark, which I

545
00:29:26,880 --> 00:29:30,800
Speaker 1: didn't love, used willow bark, braided buffalo hair, which I

546
00:29:30,840 --> 00:29:36,520
Speaker 1: didn't love, and cuts of raw hide thong not thongs

547
00:29:37,760 --> 00:29:41,400
Speaker 1: of strips of strips of yeah, strips of raw hide

548
00:29:41,400 --> 00:29:50,400
Speaker 1: for rope. So willows, willow bark, buffalo hair, buffalo strips

549
00:29:50,400 --> 00:29:55,160
Speaker 1: of buffalo hide as rope and crafted bull boats.

550
00:29:55,840 --> 00:29:58,160
Speaker 3: I think it's important to point out too, and raised

551
00:29:58,200 --> 00:30:03,760
Speaker 3: them are raw hide in this context means it is

552
00:30:03,800 --> 00:30:07,320
Speaker 3: a fresh hide, not like your raw hide dog juice.

553
00:30:07,720 --> 00:30:10,520
Speaker 3: It's the same thing, it's just at a different stage.

554
00:30:10,120 --> 00:30:17,720
Speaker 1: Of This was fresh, green, slicker and snot wet, hard

555
00:30:17,720 --> 00:30:18,600
Speaker 1: to work with hide.

556
00:30:19,200 --> 00:30:22,720
Speaker 3: I was actually very impressed with the bark because when

557
00:30:22,960 --> 00:30:27,040
Speaker 3: if the stuff that dried, when it was tied and wrapped, it.

558
00:30:28,560 --> 00:30:31,320
Speaker 1: Tough. It was real tough, braided hair is a bitch.

559
00:30:32,960 --> 00:30:34,800
Speaker 1: If you got like a dog with long hair, try

560
00:30:34,800 --> 00:30:37,240
Speaker 1: to tie her hair in a knot like try to

561
00:30:37,240 --> 00:30:40,400
Speaker 1: throw a granny into your daughter's hair. He kars hair.

562
00:30:41,440 --> 00:30:45,520
Speaker 1: It doesn't doesn't, it doesn't hold it out. So I

563
00:30:45,560 --> 00:30:47,440
Speaker 1: braided all I took all my time braiding all this

564
00:30:47,520 --> 00:30:49,320
Speaker 1: hair up, giving myself an arth You want to talk

565
00:30:49,360 --> 00:30:53,360
Speaker 1: about an arthritick egg braiden big along strands of hair

566
00:30:53,400 --> 00:30:55,120
Speaker 1: together and then you go throw a granny in It

567
00:30:55,400 --> 00:30:58,920
Speaker 1: just unravels in front of your eyes. But but there's

568
00:30:58,920 --> 00:31:00,720
Speaker 1: a thing I read. But if you the picture, you

569
00:31:00,760 --> 00:31:02,800
Speaker 1: take a picture, you take a deer hide, just a

570
00:31:02,840 --> 00:31:05,280
Speaker 1: few listeners out there, take a deer hide and start

571
00:31:06,200 --> 00:31:08,360
Speaker 1: so lay the deer hide out. Ideally you'd scrape the

572
00:31:08,360 --> 00:31:10,720
Speaker 1: hair off, lay the deer hide out, and start a

573
00:31:10,840 --> 00:31:13,520
Speaker 1: cut in and start cutting a quarter inch thick strap

574
00:31:15,360 --> 00:31:18,680
Speaker 1: parallel to the edge. And imagine you go in concentric circles,

575
00:31:19,640 --> 00:31:26,240
Speaker 1: take one hundred go around, keep going quarter inch all

576
00:31:26,320 --> 00:31:29,920
Speaker 1: the whole periphery, and then come in and do concentric circles.

577
00:31:30,040 --> 00:31:32,239
Speaker 1: You gonna you could stretch that. I'm gonna go out

578
00:31:32,240 --> 00:31:33,560
Speaker 1: on a limb and say it go to the moon.

579
00:31:35,720 --> 00:31:38,000
Speaker 9: Remember We had a guy right in and said that

580
00:31:38,360 --> 00:31:42,160
Speaker 9: he used to do that with squirrel leather. And he

581
00:31:42,280 --> 00:31:44,600
Speaker 9: said that you use that for shoe laces and it

582
00:31:44,640 --> 00:31:45,840
Speaker 9: would outlast the boots.

583
00:31:46,600 --> 00:31:48,520
Speaker 3: No way.

584
00:31:48,720 --> 00:31:51,880
Speaker 1: He did take a squirrel hide and make leather laces

585
00:31:51,920 --> 00:31:54,080
Speaker 1: out of squirrel hide. And I'll tell you what, anybody's

586
00:31:54,120 --> 00:31:57,000
Speaker 1: ever try to clean a squirrel will.

587
00:31:57,640 --> 00:31:58,920
Speaker 3: In that's right up your eye.

588
00:32:00,480 --> 00:32:03,160
Speaker 2: Leave the hair on there al or shoes.

589
00:32:03,280 --> 00:32:05,440
Speaker 1: Made me a couple of thin pieces for dental floss.

590
00:32:05,440 --> 00:32:08,360
Speaker 1: Bro because what I've been using lately is not work

591
00:32:08,520 --> 00:32:09,600
Speaker 1: that popcorn yesterday?

592
00:32:09,640 --> 00:32:11,560
Speaker 2: Would you leave the hair on for the dental floss

593
00:32:11,560 --> 00:32:13,480
Speaker 2: to get a little It's.

594
00:32:13,400 --> 00:32:15,480
Speaker 5: A brush, brush and floss at the same time.

595
00:32:15,600 --> 00:32:17,880
Speaker 1: And we raised them. We raised them. It wasn't like

596
00:32:18,440 --> 00:32:19,160
Speaker 1: we raised them.

597
00:32:19,960 --> 00:32:24,760
Speaker 3: I Uh, people got to watch.

598
00:32:25,000 --> 00:32:25,640
Speaker 1: You gotta watch.

599
00:32:26,160 --> 00:32:29,120
Speaker 3: But this comes out after the don't get it all

600
00:32:29,160 --> 00:32:31,680
Speaker 3: the way. Yeah, this comes after the deal. But people

601
00:32:31,680 --> 00:32:34,520
Speaker 3: still need to need to watch. But it was it

602
00:32:34,600 --> 00:32:37,800
Speaker 3: was a group learning effort with a race at the end.

603
00:32:38,320 --> 00:32:40,360
Speaker 1: How's that highlight of my day? Is? All day I

604
00:32:40,440 --> 00:32:42,480
Speaker 1: kept think we're gonna find morels because where we were

605
00:32:42,680 --> 00:32:45,600
Speaker 1: I walked around a lot looking, well, here's what happened

606
00:32:45,600 --> 00:32:47,560
Speaker 1: to me on the way out. On the way I'm

607
00:32:47,560 --> 00:32:49,480
Speaker 1: sitting in the back of a truck. I look over

608
00:32:49,640 --> 00:32:54,960
Speaker 1: just plain as day is a morele it grew wild. No,

609
00:32:54,960 --> 00:32:58,040
Speaker 1: we hadn't gone in that driven by. Yeah, Chili thought

610
00:32:58,080 --> 00:33:03,520
Speaker 1: someone fell out and got hit. Stop stop, he jumps out.

611
00:33:03,600 --> 00:33:05,640
Speaker 1: He thought someone got rolled over. Like there's a morale.

612
00:33:06,200 --> 00:33:07,640
Speaker 1: He's like, oh my god, you guys give me a

613
00:33:07,680 --> 00:33:12,720
Speaker 1: heart attack. We'll talk about breeding meal deer later. Oh,

614
00:33:13,440 --> 00:33:15,800
Speaker 1: we use one thousand pound animals. And then in the

615
00:33:15,920 --> 00:33:18,760
Speaker 1: historic record people talk about a bull boat that's eight

616
00:33:19,040 --> 00:33:23,640
Speaker 1: feet in diameter. But Matt Skoglan was talking about, you know,

617
00:33:23,720 --> 00:33:27,280
Speaker 1: if you really let him go. We were using hides

618
00:33:27,280 --> 00:33:31,239
Speaker 1: off three year old animals. You know, if you let

619
00:33:31,320 --> 00:33:33,240
Speaker 1: them go, you could get a you know, there's such

620
00:33:33,280 --> 00:33:36,640
Speaker 1: a thing as a close to a one ton bowl.

621
00:33:37,000 --> 00:33:37,200
Speaker 4: Yeah.

622
00:33:37,200 --> 00:33:41,360
Speaker 3: If you look at like old beef balls, old beef

623
00:33:41,360 --> 00:33:45,040
Speaker 3: balls get to a point that they can't really be managers.

624
00:33:45,040 --> 00:33:48,120
Speaker 3: They can't. They get so big and dangerous that they

625
00:33:48,200 --> 00:33:49,600
Speaker 3: kind of just do what they want. So if you

626
00:33:49,640 --> 00:33:54,040
Speaker 3: see an old beef bawl out there on the range,

627
00:33:54,560 --> 00:33:59,040
Speaker 3: they just they do They just get bigger and bigger, sorry.

628
00:33:58,840 --> 00:33:59,880
Speaker 1: Magic are around.

629
00:34:00,680 --> 00:34:05,240
Speaker 3: Yeah, the muscle bulk and everything is next get enormous

630
00:34:05,320 --> 00:34:06,200
Speaker 3: and yeah.

631
00:34:06,960 --> 00:34:09,520
Speaker 1: Uh. The last thing I'll point out is my boat,

632
00:34:09,800 --> 00:34:15,520
Speaker 1: my personal vessel was Uh no, in fact, it's no,

633
00:34:16,800 --> 00:34:19,680
Speaker 1: it's got all it's I meant to grab some of

634
00:34:19,680 --> 00:34:22,719
Speaker 1: that hide for a thing I want to make, and

635
00:34:22,800 --> 00:34:27,000
Speaker 1: I had some, Matt and uh, Matt and uh Brady

636
00:34:27,040 --> 00:34:29,239
Speaker 1: go back out and they cut a chunk of hide

637
00:34:29,320 --> 00:34:31,279
Speaker 1: off the boat. So as you find laying on the bank,

638
00:34:31,320 --> 00:34:33,880
Speaker 1: it's got a hole in it now, But no, I'm

639
00:34:33,920 --> 00:34:35,760
Speaker 1: still sitting there right. It's just sitting in a willow

640
00:34:35,800 --> 00:34:38,399
Speaker 1: patch right now, like it would be back in the day.

641
00:34:38,440 --> 00:34:41,840
Speaker 1: Apparently with a hole in it. Oh, it was so

642
00:34:41,960 --> 00:34:43,560
Speaker 1: stable you could cast a fly route out of it

643
00:34:43,600 --> 00:34:51,600
Speaker 1: floating down the river. Worked very well. All right, Matt, Uh,

644
00:34:51,719 --> 00:34:54,239
Speaker 1: let's let's dig into Colossal biosciences. Talk about how you

645
00:34:54,239 --> 00:34:57,000
Speaker 1: got started in Zoo. You were you manage Zoo's.

646
00:34:57,760 --> 00:35:00,000
Speaker 6: Yeah, so I before walk us through the career real quick,

647
00:35:00,040 --> 00:35:04,960
Speaker 6: before Colossal started, I was. I had studied biology and chemistry, ecology.

648
00:35:04,960 --> 00:35:06,920
Speaker 6: I went I went to a master's program in South

649
00:35:06,920 --> 00:35:11,040
Speaker 6: Carolina studying wetland ecology, and when I finished up there,

650
00:35:11,080 --> 00:35:14,279
Speaker 6: I sort of realized what about wetland ecology so specifically,

651
00:35:14,320 --> 00:35:16,160
Speaker 6: so it was sort of marine and wetland ecology.

652
00:35:16,160 --> 00:35:17,200
Speaker 5: I was more on the marine side.

653
00:35:17,200 --> 00:35:20,360
Speaker 6: So I was studying sea turtle nesting in South Carolina

654
00:35:20,400 --> 00:35:25,400
Speaker 6: in Atistowe Beach of sea turtle those are loggerheads. Yeah,

655
00:35:25,440 --> 00:35:27,759
Speaker 6: and uh it was great. You know, as a twenty

656
00:35:27,800 --> 00:35:30,080
Speaker 6: two year old grad student. I was living on a

657
00:35:30,080 --> 00:35:31,920
Speaker 6: beach for a week or two in a tent with

658
00:35:31,960 --> 00:35:34,760
Speaker 6: my one hundred and forty pound Saint Bernard, and uh,

659
00:35:35,080 --> 00:35:37,520
Speaker 6: you know, just trying to walk the beach every morning

660
00:35:37,560 --> 00:35:39,800
Speaker 6: and see where sea turtles were crawling, mark their nests,

661
00:35:39,800 --> 00:35:42,640
Speaker 6: and study basically thermal dynamics.

662
00:35:42,840 --> 00:35:44,920
Speaker 3: Well, you painted a very sandy tent picture.

663
00:35:45,000 --> 00:35:49,879
Speaker 6: Ye came humid, slobbery, and then there was a dog,

664
00:35:49,960 --> 00:35:50,160
Speaker 6: you know.

665
00:35:52,560 --> 00:35:53,680
Speaker 5: But it was great. I loved it.

666
00:35:53,719 --> 00:35:55,960
Speaker 6: But I realized quickly that most of the people in

667
00:35:56,239 --> 00:35:58,560
Speaker 6: my sort of path, we're going to work for DNR

668
00:35:58,719 --> 00:36:01,279
Speaker 6: fishing game or something like that. And as you know,

669
00:36:01,320 --> 00:36:02,879
Speaker 6: when I was a kid, that was appealing. But by

670
00:36:02,880 --> 00:36:04,640
Speaker 6: that point I thought, well, you know, I want to

671
00:36:04,640 --> 00:36:07,800
Speaker 6: do something a little bit more that I own, that

672
00:36:07,160 --> 00:36:10,800
Speaker 6: I that I can manage and literally took a runner

673
00:36:10,880 --> 00:36:14,040
Speaker 6: on a Craigslist ad and move up and moved to Miami,

674
00:36:14,040 --> 00:36:19,319
Speaker 6: Florida and started working with bottlenosed dolphins and California sea

675
00:36:19,320 --> 00:36:22,759
Speaker 6: lions and working and studying animal behavior. And so I

676
00:36:22,800 --> 00:36:25,800
Speaker 6: started doing that, and that eventually led to a job

677
00:36:25,920 --> 00:36:28,960
Speaker 6: working with elephants in Tampa, Florida, trying to help change

678
00:36:29,000 --> 00:36:31,239
Speaker 6: the way that we manage elephants in human care. Right

679
00:36:31,320 --> 00:36:34,360
Speaker 6: because we look at the wild, we understand that a

680
00:36:34,360 --> 00:36:37,320
Speaker 6: lot of these species are facing some level of extinction,

681
00:36:37,600 --> 00:36:39,759
Speaker 6: and elephants have had a massive decline over the last

682
00:36:39,840 --> 00:36:42,920
Speaker 6: hundred years. So one of the solutions to prevent extinction

683
00:36:43,040 --> 00:36:45,880
Speaker 6: is to create captive breeding populations. And so if you're

684
00:36:45,880 --> 00:36:48,280
Speaker 6: going to create a captive breeding population, you need to

685
00:36:48,320 --> 00:36:50,200
Speaker 6: figure out how do you manage these animals, how do

686
00:36:50,200 --> 00:36:51,759
Speaker 6: you take care of them? And so I sort of

687
00:36:51,760 --> 00:36:55,440
Speaker 6: had a job doing that at a zoo and we

688
00:36:55,440 --> 00:36:57,759
Speaker 6: were focused on that for years, and I just sort

689
00:36:57,760 --> 00:36:59,560
Speaker 6: of worked my way up through the zoo system and

690
00:37:00,120 --> 00:37:02,360
Speaker 6: managing animal care and conservation at Ze's in Miami and

691
00:37:02,400 --> 00:37:05,759
Speaker 6: then most recently in Dallas, Texas. And about that time

692
00:37:05,840 --> 00:37:08,719
Speaker 6: has when that's you know, I started there in twenty

693
00:37:08,760 --> 00:37:10,960
Speaker 6: eighteen in Dallas, and by twenty twenty, COVID hit and

694
00:37:11,360 --> 00:37:14,960
Speaker 6: sort of made you really sort of start to question everything.

695
00:37:15,000 --> 00:37:16,759
Speaker 6: You know, you're locked at your house, You're you're wondering

696
00:37:16,800 --> 00:37:19,000
Speaker 6: what's happening, You're trying to really had a lot of

697
00:37:19,040 --> 00:37:22,120
Speaker 6: self reflection in twenty twenty, and for me, I realize,

698
00:37:22,760 --> 00:37:24,640
Speaker 6: you know, it's one thing to sort of put your

699
00:37:24,640 --> 00:37:27,160
Speaker 6: finger in the in the dam and try to prevent

700
00:37:27,200 --> 00:37:30,239
Speaker 6: a leak of a species extinction. It's another thing to

701
00:37:30,280 --> 00:37:32,799
Speaker 6: try to refill that well. And so I was really

702
00:37:32,840 --> 00:37:36,080
Speaker 6: looking for ways that I could personally be more impactful

703
00:37:36,800 --> 00:37:39,479
Speaker 6: to the biodiversity crisis. And about that time, my phone

704
00:37:39,560 --> 00:37:42,560
Speaker 6: rang and this lunatic Ben Lamb, who's our ce, who's

705
00:37:42,600 --> 00:37:46,640
Speaker 6: absolute genius, you know, serial entrepreneur, tons of success. He

706
00:37:47,000 --> 00:37:51,120
Speaker 6: met a He met an amazing guy named George Church

707
00:37:51,160 --> 00:37:54,600
Speaker 6: who worked at Harvard Medical School as and he runs

708
00:37:54,600 --> 00:37:58,520
Speaker 6: the genetics lab there, really famous for creating, you know,

709
00:37:58,560 --> 00:38:01,800
Speaker 6: next generation genomic sequence technologies. An he's sort of a

710
00:38:01,880 --> 00:38:05,600
Speaker 6: legend in the genetics world, and they they've had this

711
00:38:05,680 --> 00:38:08,560
Speaker 6: George has had this idea around restoring Willie mammoths to

712
00:38:08,600 --> 00:38:12,160
Speaker 6: the Arctic for years and ben Is, being the business

713
00:38:12,160 --> 00:38:14,280
Speaker 6: minded one, was sort of able to formulate a business

714
00:38:14,320 --> 00:38:14,960
Speaker 6: plan around that.

715
00:38:15,000 --> 00:38:16,760
Speaker 5: And twenty twenty one.

716
00:38:16,680 --> 00:38:19,640
Speaker 6: Colossal Bioscience is launched and they called me to come

717
00:38:19,640 --> 00:38:21,960
Speaker 6: on and help with animal care, animal management, welfare, and

718
00:38:22,040 --> 00:38:25,840
Speaker 6: wildlife conservation. It was the pitch, like the mammoth project,

719
00:38:25,960 --> 00:38:27,719
Speaker 6: that was it at that point. That's all we had,

720
00:38:27,880 --> 00:38:30,200
Speaker 6: just make a mammoth. Yeah, we need If we were

721
00:38:30,239 --> 00:38:31,879
Speaker 6: to make a mammoth, how do you do that? Well,

722
00:38:31,920 --> 00:38:35,080
Speaker 6: there's a lot of work that requires, you know, before

723
00:38:35,160 --> 00:38:38,359
Speaker 6: the mammoth is restored, and then tons of work after

724
00:38:38,400 --> 00:38:39,080
Speaker 6: the mammoths restored.

725
00:38:39,120 --> 00:38:40,000
Speaker 5: How do you take care of them?

726
00:38:40,120 --> 00:38:43,239
Speaker 6: How do you eventually create sustainable populations that could go

727
00:38:43,280 --> 00:38:48,360
Speaker 6: back into the Arctic somewhere, And all of those require

728
00:38:48,400 --> 00:38:51,759
Speaker 6: different skills in animal management with care and welfare, but

729
00:38:51,800 --> 00:38:54,080
Speaker 6: also you know, conservation planning. How do you go and

730
00:38:54,120 --> 00:38:56,560
Speaker 6: prepare an ecosystem for species that hasn't existed in four

731
00:38:56,600 --> 00:38:58,520
Speaker 6: thousand years? How do you go and figure out how

732
00:38:58,520 --> 00:39:02,440
Speaker 6: to do this ethically legally, right, you know, hand in

733
00:39:02,440 --> 00:39:04,920
Speaker 6: hand with regulators, things like that. So it's been my

734
00:39:05,000 --> 00:39:06,560
Speaker 6: last two and a half years it's just really been

735
00:39:06,560 --> 00:39:09,040
Speaker 6: off to the races. And meanwhile to that, we've quickly

736
00:39:09,040 --> 00:39:12,680
Speaker 6: expanded from Willie mammos to also Tasmani tigers who went

737
00:39:12,760 --> 00:39:16,000
Speaker 6: extinct off the island at Tasmania in nineteen thirty six,

738
00:39:16,280 --> 00:39:17,960
Speaker 6: and the Dodo, which is sort of, you know, the

739
00:39:17,960 --> 00:39:21,279
Speaker 6: world's most iconic extinction event in sixteen hundreds. The Dodo

740
00:39:22,680 --> 00:39:25,120
Speaker 6: was discovered in eighty years later was extinct due to

741
00:39:25,239 --> 00:39:29,800
Speaker 6: Dutch sailors that were introducing predators and invasive species into Mauritius.

742
00:39:30,640 --> 00:39:33,920
Speaker 6: So all of those have different levels of challenges on

743
00:39:33,960 --> 00:39:36,640
Speaker 6: the the extinction side, and then I have a lot

744
00:39:36,640 --> 00:39:39,359
Speaker 6: of challenges on the conservation side for how do we

745
00:39:39,600 --> 00:39:43,360
Speaker 6: prepare habitats and do a lot of that that prep work.

746
00:39:43,200 --> 00:39:46,040
Speaker 3: Ahead, but also on the why side, Right, Yeah, it's

747
00:39:46,040 --> 00:39:47,799
Speaker 3: like that's a big one. You're not just doing it

748
00:39:48,040 --> 00:39:48,600
Speaker 3: because you can.

749
00:39:48,760 --> 00:39:52,120
Speaker 6: It's not enough school now the right we're facing this

750
00:39:52,480 --> 00:39:55,560
Speaker 6: enormous biodiversity crisis and we're missing species. I think the

751
00:39:55,640 --> 00:39:59,360
Speaker 6: Tasmani tigers such a great example of this. And sitting

752
00:39:59,360 --> 00:40:02,400
Speaker 6: here in Montana, you know, on the doorstuff Yellowstone, you

753
00:40:02,400 --> 00:40:05,240
Speaker 6: could sort of draw some parallels to to wolf recovery

754
00:40:05,239 --> 00:40:08,279
Speaker 6: and Yellowstone. The loss of an apex predator led to

755
00:40:08,520 --> 00:40:11,840
Speaker 6: you know, certain imbalances in Tasmania, things like wildlife disease

756
00:40:11,880 --> 00:40:15,359
Speaker 6: are running rampant today, things like like predator or sorry

757
00:40:15,360 --> 00:40:19,279
Speaker 6: prey population overpopulation is happening, and you know there's you know,

758
00:40:19,600 --> 00:40:25,239
Speaker 6: wallabies and brush tail possums in Tasmania aren't really fun

759
00:40:25,280 --> 00:40:29,799
Speaker 6: to hunt, so nobody's really regulating those populations, and so

760
00:40:29,880 --> 00:40:32,120
Speaker 6: they need this predator that can come in and provide

761
00:40:32,200 --> 00:40:36,320
Speaker 6: ecosystem stability. It can help remove sick and injured animals

762
00:40:36,320 --> 00:40:36,880
Speaker 6: that might.

763
00:40:36,680 --> 00:40:37,960
Speaker 5: Be spreading wildlife disease.

764
00:40:38,040 --> 00:40:41,000
Speaker 6: Like if you've ever heard of Tasmani devils are on

765
00:40:41,040 --> 00:40:44,160
Speaker 6: the brink of extinction because of this facial tumor disease.

766
00:40:44,520 --> 00:40:47,960
Speaker 6: It's literally a contagious cancer. So when they bite each other,

767
00:40:47,960 --> 00:40:50,839
Speaker 6: which is very much in their social network is how

768
00:40:50,840 --> 00:40:56,120
Speaker 6: they communicate, they spread this contagious cancer that ends up

769
00:40:56,440 --> 00:40:58,640
Speaker 6: creating these massive tumors in their face and they eventually

770
00:40:58,680 --> 00:41:02,520
Speaker 6: starve to death and die. That would have with the

771
00:41:02,600 --> 00:41:05,520
Speaker 6: right predator present, would as that animal got sick, it

772
00:41:05,520 --> 00:41:07,360
Speaker 6: would have been predated and would not have had the

773
00:41:07,480 --> 00:41:10,480
Speaker 6: chance to pass on that disease. And so you know,

774
00:41:10,560 --> 00:41:13,560
Speaker 6: finding solutions nature based solutions for how we can restore

775
00:41:13,640 --> 00:41:16,640
Speaker 6: ecosystems is really the focus of what the company's doing,

776
00:41:16,920 --> 00:41:18,640
Speaker 6: and we're doing it in a really fun, flashy way

777
00:41:18,640 --> 00:41:21,160
Speaker 6: like Willie Mammoths, Like what we came out of the

778
00:41:21,560 --> 00:41:23,640
Speaker 6: gate so hot and got a lot of attention, is

779
00:41:23,680 --> 00:41:26,760
Speaker 6: really fun. But I think now you know, I'm running

780
00:41:26,760 --> 00:41:29,160
Speaker 6: around trying to help spread the word on really here's

781
00:41:29,200 --> 00:41:32,600
Speaker 6: the why, because sometimes the what is so distracting that

782
00:41:32,600 --> 00:41:34,480
Speaker 6: that we don't get to the why and and and

783
00:41:34,560 --> 00:41:36,920
Speaker 6: that's that's been a great part of the last two

784
00:41:36,920 --> 00:41:37,520
Speaker 6: and a half years.

785
00:41:37,600 --> 00:41:39,160
Speaker 1: So I feel like in the case of the mammoth,

786
00:41:39,239 --> 00:41:43,040
Speaker 1: the why is an after effect, like the why is

787
00:41:43,080 --> 00:41:46,279
Speaker 1: searching for a why after the inception of the idea. Well,

788
00:41:46,320 --> 00:41:48,000
Speaker 1: there's I don't think that, Like, I don't think it's

789
00:41:48,080 --> 00:41:52,800
Speaker 1: fair to say that. I mean, let's be frank. I

790
00:41:52,880 --> 00:41:55,719
Speaker 1: mean the race to do a mammoth is because it

791
00:41:55,840 --> 00:41:57,160
Speaker 1: be super cool to make a mammoth.

792
00:41:58,000 --> 00:41:59,960
Speaker 6: I think it's sort of yeah, there's sort of two

793
00:42:00,120 --> 00:42:02,040
Speaker 6: fronts to that, or you know, the first one is

794
00:42:02,080 --> 00:42:05,440
Speaker 6: that moonshot idea of this really amazing attractive project that's

795
00:42:05,440 --> 00:42:07,759
Speaker 6: brought tons of investment right in three years we've raised

796
00:42:07,760 --> 00:42:10,759
Speaker 6: two hundred twenty five million dollars for conservation technology in

797
00:42:10,800 --> 00:42:11,719
Speaker 6: my fifteen years.

798
00:42:11,719 --> 00:42:14,320
Speaker 5: Prior we probably raised five million dollars.

799
00:42:14,320 --> 00:42:17,120
Speaker 6: You know, So the scale has been really helpful because

800
00:42:17,120 --> 00:42:20,320
Speaker 6: of the moonshot aspect, and then also along the way

801
00:42:20,520 --> 00:42:24,279
Speaker 6: of this amazing project, we're developing technologies and innovations that

802
00:42:24,360 --> 00:42:28,239
Speaker 6: are applicable every single day to currently imperiled species, and

803
00:42:28,280 --> 00:42:31,200
Speaker 6: so it really becomes this engine of innovation and investment

804
00:42:31,239 --> 00:42:34,400
Speaker 6: for in danger speceis conservation. The other side is there

805
00:42:34,520 --> 00:42:38,400
Speaker 6: is really strong evidence that shows that restoring megavertebrates to

806
00:42:38,520 --> 00:42:41,840
Speaker 6: some of these areas in the Arctic, like what's happening

807
00:42:42,360 --> 00:42:46,000
Speaker 6: in Siberia at Plesising Park, is using mega vertebrates to

808
00:42:46,080 --> 00:42:49,560
Speaker 6: try to re engineer an ecosystem and an ecosystem that's

809
00:42:49,600 --> 00:42:53,080
Speaker 6: better at insulating permafrost. And so that's sort of the

810
00:42:53,080 --> 00:42:55,799
Speaker 6: big idea. The scale in which to make, you know,

811
00:42:56,480 --> 00:42:58,359
Speaker 6: for that to happen in the Arctic and be this

812
00:42:58,520 --> 00:43:01,520
Speaker 6: massive global solution to climb change would be you know,

813
00:43:01,680 --> 00:43:04,840
Speaker 6: really untenable. But but I think that's the idea is

814
00:43:04,880 --> 00:43:07,680
Speaker 6: that we can find you know, targeted areas where we

815
00:43:07,719 --> 00:43:09,080
Speaker 6: can help impact those things.

816
00:43:09,800 --> 00:43:13,279
Speaker 1: Uh, you laid out how you'd make a mingus. Yeah,

817
00:43:14,000 --> 00:43:16,760
Speaker 1: completely different path on a mammoth.

818
00:43:17,080 --> 00:43:20,920
Speaker 6: Cloning as compared to the extinction is easy, right, And

819
00:43:20,960 --> 00:43:22,520
Speaker 6: I think that's why a lot of people came out

820
00:43:22,560 --> 00:43:24,000
Speaker 6: of the gates with the mammoth. Idea was always that

821
00:43:24,040 --> 00:43:26,239
Speaker 6: we should clone it. And you know, same same, same

822
00:43:26,239 --> 00:43:27,480
Speaker 6: idea with the mangus example.

823
00:43:27,520 --> 00:43:31,160
Speaker 3: But because we have mammoth flesh and DNA.

824
00:43:30,920 --> 00:43:33,880
Speaker 6: And exactly, but we don't have living flesh and DNA,

825
00:43:33,960 --> 00:43:35,799
Speaker 6: and you can't clone a dead cell.

826
00:43:36,480 --> 00:43:38,600
Speaker 5: You just can't. That's the unfortunate reality.

827
00:43:38,760 --> 00:43:41,400
Speaker 6: But what we can do is we can use genetic

828
00:43:41,520 --> 00:43:46,200
Speaker 6: editing and engineering tools to basically replicate. So the process

829
00:43:46,239 --> 00:43:50,239
Speaker 6: for the extinction sort of starts with palaeogenomics. So what

830
00:43:50,360 --> 00:43:52,920
Speaker 6: best Shapiro probably talked about on her when she when

831
00:43:52,960 --> 00:43:53,919
Speaker 6: she appeared years ago.

832
00:43:54,160 --> 00:43:59,360
Speaker 1: I got to interrupt you from it because as you

833
00:43:59,400 --> 00:44:02,200
Speaker 1: do this, keep this in mind. We're talking about what's that,

834
00:44:02,280 --> 00:44:04,960
Speaker 1: what's that marine mammal, the very small sea of Cortes,

835
00:44:05,040 --> 00:44:09,440
Speaker 1: the wikida. Yeah, okay, it's headed to extinction, correct, But

836
00:44:09,680 --> 00:44:13,360
Speaker 1: you guys are devising a plan by which you'll capture

837
00:44:13,920 --> 00:44:19,920
Speaker 1: living tissue of things you could capture living tissue of things,

838
00:44:21,040 --> 00:44:24,400
Speaker 1: and down the road de extinction would be entirely different

839
00:44:24,440 --> 00:44:28,279
Speaker 1: because you'd have captured living tissue in the biobank. Yeah,

840
00:44:28,440 --> 00:44:32,800
Speaker 1: so let's yeah, so let's and talking about de extinction.

841
00:44:32,880 --> 00:44:35,799
Speaker 1: There's cases where you could take a different path to

842
00:44:35,920 --> 00:44:39,320
Speaker 1: de extinction if you had the foresight to capture living

843
00:44:39,360 --> 00:44:45,440
Speaker 1: tissue of white rhinos whatever, right, it'd be different. So

844
00:44:45,560 --> 00:44:48,840
Speaker 1: we're talking right now about soft where there's no without

845
00:44:48,840 --> 00:44:53,040
Speaker 1: a time machine, there's no way to capture living tissue.

846
00:44:52,760 --> 00:44:55,680
Speaker 6: Exactly with living tissue in biobank. So one of our

847
00:44:55,719 --> 00:44:59,080
Speaker 6: biggest focuses right now is to improve biobanking throughout the world.

848
00:44:59,120 --> 00:45:00,320
Speaker 6: So that means we want to go go out and

849
00:45:00,360 --> 00:45:04,200
Speaker 6: collect living tissues of critically endangered species. We want to

850
00:45:04,239 --> 00:45:06,879
Speaker 6: create cell lines of those in freezoes down and that

851
00:45:07,120 --> 00:45:11,240
Speaker 6: is sort of the assurance insurance POPU policy against extinction

852
00:45:11,320 --> 00:45:12,800
Speaker 6: in the future, because that gives us an ability to

853
00:45:12,840 --> 00:45:14,960
Speaker 6: go back and do cloning, which is much easier than

854
00:45:15,000 --> 00:45:18,279
Speaker 6: this the extinction pathway. So a great example of just

855
00:45:18,400 --> 00:45:20,880
Speaker 6: that is what's happening with northern white rhinos. I'm not

856
00:45:20,880 --> 00:45:24,239
Speaker 6: sure if you're familiar, but northern white rhinos are, you know,

857
00:45:24,320 --> 00:45:29,680
Speaker 6: native to East Africa sort of Uganda car DRC area.

858
00:45:30,000 --> 00:45:33,120
Speaker 6: And you know, back in nineteen hundred they're about two

859
00:45:33,120 --> 00:45:35,120
Speaker 6: thousand and three thousand of them in the world. By

860
00:45:35,160 --> 00:45:37,839
Speaker 6: the sixties at number was pretty stable, and by nineteen

861
00:45:37,880 --> 00:45:40,200
Speaker 6: seventy five they were only five hundred of them. In

862
00:45:40,320 --> 00:45:42,279
Speaker 6: two thousand and eight, the last ones went extinct in

863
00:45:42,280 --> 00:45:47,360
Speaker 6: Groamba National Park, but luckily there were a few left

864
00:45:47,400 --> 00:45:50,440
Speaker 6: in human care. So there's this amazing zoo in the

865
00:45:50,440 --> 00:45:54,520
Speaker 6: Czech Republic that had had four animals. They sent them

866
00:45:54,520 --> 00:45:56,719
Speaker 6: to Kenya in this last ditch attempt to try to

867
00:45:56,719 --> 00:46:00,200
Speaker 6: breed the last remaining Northern white rhinos, and unfortunately it

868
00:46:00,200 --> 00:46:02,799
Speaker 6: turns out, whether because there was the genetics of those

869
00:46:02,800 --> 00:46:05,200
Speaker 6: animals were bad or they were too far down the path,

870
00:46:05,880 --> 00:46:08,160
Speaker 6: they weren't able to breed. So now there is this

871
00:46:08,200 --> 00:46:12,440
Speaker 6: effort using all those biobanked Northern white rhino tissues to

872
00:46:12,480 --> 00:46:15,399
Speaker 6: create embryos and then use Southern white surrogates to make

873
00:46:15,480 --> 00:46:18,919
Speaker 6: more Northern white rhinosp And actually just this last month

874
00:46:19,000 --> 00:46:22,839
Speaker 6: we announced so we're part of this international consortium called

875
00:46:22,840 --> 00:46:26,200
Speaker 6: Biorescue that's leading this charge. Last month we announced the

876
00:46:26,280 --> 00:46:29,360
Speaker 6: first ever successful in vitro fertilization of a rhino species.

877
00:46:29,400 --> 00:46:31,360
Speaker 6: So this was a Southern white embryo into a Southern

878
00:46:31,360 --> 00:46:34,000
Speaker 6: white female. But that was the sort of proof point

879
00:46:34,040 --> 00:46:35,640
Speaker 6: we needed to say, Okay, now we can use the

880
00:46:35,640 --> 00:46:38,000
Speaker 6: really valuable tissues. So the next step is we're going

881
00:46:38,040 --> 00:46:40,360
Speaker 6: to put Northern white embryos into Southern white females and

882
00:46:40,440 --> 00:46:42,920
Speaker 6: make more Northern white phinos. So that's sort of the conservation.

883
00:46:43,600 --> 00:46:54,960
Speaker 1: That's the Mingus model, that's the Megus model. Now let's

884
00:46:54,960 --> 00:46:57,000
Speaker 1: talk about the model of shit that died ten thousand

885
00:46:57,080 --> 00:46:57,480
Speaker 1: years ago.

886
00:46:57,560 --> 00:47:01,160
Speaker 6: Well, even unfortunately things like nineteen thirty six when extinct, right,

887
00:47:01,280 --> 00:47:03,360
Speaker 6: we don't have living tissues of that. There were no

888
00:47:03,400 --> 00:47:05,960
Speaker 6: biobanks back there. So what we do there is we

889
00:47:06,000 --> 00:47:08,080
Speaker 6: go and find the extinct species, whether it's a mammoth

890
00:47:08,160 --> 00:47:12,360
Speaker 6: or a thiglyasine or dodo, and we use high quality

891
00:47:12,400 --> 00:47:14,799
Speaker 6: the highest quality reference genome thi scene is a tas

892
00:47:14,840 --> 00:47:18,719
Speaker 6: Madie entire tesmany tiger, yes, sorry. And what we do

893
00:47:18,840 --> 00:47:22,040
Speaker 6: is we sequence the genome of this lost species and

894
00:47:22,080 --> 00:47:25,239
Speaker 6: then we use, you know, some comparative analysis to under

895
00:47:25,680 --> 00:47:29,279
Speaker 6: try to determine who's the current closest living.

896
00:47:29,040 --> 00:47:30,280
Speaker 5: Relative to that species.

897
00:47:30,320 --> 00:47:32,680
Speaker 6: So in the case of the Tasmanian tiger, that's this

898
00:47:32,719 --> 00:47:35,480
Speaker 6: little mouse art mouse sized marstupile called the fat tail

899
00:47:35,520 --> 00:47:37,360
Speaker 6: dinnert or in the case of a mammoth, that's an

900
00:47:37,400 --> 00:47:38,399
Speaker 6: Asian elephant or the.

901
00:47:38,360 --> 00:47:42,320
Speaker 5: Dodo with the nick of our pigeon. Really yeah, yeah.

902
00:47:42,440 --> 00:47:44,279
Speaker 6: So what we can do then is we take that

903
00:47:44,320 --> 00:47:48,919
Speaker 6: genome of the living animal. We design editing targets as

904
00:47:49,680 --> 00:47:51,920
Speaker 6: using the genomic analysis tool, so you sort of lay

905
00:47:51,920 --> 00:47:53,880
Speaker 6: them over each other, see where is one genome different

906
00:47:53,920 --> 00:47:56,200
Speaker 6: than the other, and we create editing tools to begin

907
00:47:56,280 --> 00:48:00,760
Speaker 6: to edit the living species into the loss speed different.

908
00:48:00,920 --> 00:48:03,360
Speaker 1: I don't know how you express it. What percent different

909
00:48:05,000 --> 00:48:09,240
Speaker 1: is a wooly mammoth from an Indian elephant?

910
00:48:09,880 --> 00:48:13,160
Speaker 6: This is this is a really common question, is really

911
00:48:13,320 --> 00:48:16,360
Speaker 6: challenging to answer because you and I are both human

912
00:48:16,719 --> 00:48:19,759
Speaker 6: and our genomic difference is somewhere around ninety nine point

913
00:48:19,840 --> 00:48:25,120
Speaker 6: eight percent, right or similar similarity. We are about ninety

914
00:48:25,160 --> 00:48:28,520
Speaker 6: nine point six percent related to a chimpanzee an Asian elephant.

915
00:48:28,520 --> 00:48:30,800
Speaker 1: I heard someone say we're about seventy seven percent related

916
00:48:30,840 --> 00:48:31,400
Speaker 1: to a carrot.

917
00:48:31,719 --> 00:48:34,520
Speaker 5: Yeah, exactly, Because there's a lot of stuff in there.

918
00:48:34,800 --> 00:48:37,080
Speaker 6: We have a lot a lot of Neanderthal in our

919
00:48:37,120 --> 00:48:40,360
Speaker 6: genome as well, right, because we all have these common

920
00:48:40,640 --> 00:48:43,520
Speaker 6: genes that might be responsible for the basis of life.

921
00:48:43,880 --> 00:48:46,399
Speaker 6: But a wooly mammoth to an Asian elephant is ninety

922
00:48:46,480 --> 00:48:48,640
Speaker 6: nine point six percent similar. So there's only a point

923
00:48:48,680 --> 00:48:50,239
Speaker 6: four percent difference between the two.

924
00:48:50,880 --> 00:48:53,200
Speaker 1: Okay, what about the what about the thile a scene

925
00:48:53,200 --> 00:48:54,080
Speaker 1: to the mouse.

926
00:48:54,480 --> 00:48:57,080
Speaker 6: To that that one is mouse, but to the yeah,

927
00:48:57,080 --> 00:48:59,400
Speaker 6: to the fat tail dinner, that one, I can't recall

928
00:48:59,400 --> 00:49:01,800
Speaker 6: the exact person, but it is much more distantly related.

929
00:49:01,800 --> 00:49:03,120
Speaker 1: So it's not in the ninety nine.

930
00:49:03,200 --> 00:49:05,520
Speaker 6: It's not in the ninety nine now, So when we

931
00:49:05,560 --> 00:49:09,080
Speaker 6: talk about editing for for willy mammoths, we're really looking at,

932
00:49:09,400 --> 00:49:12,640
Speaker 6: you know, several hundred edits, which really, in the grand

933
00:49:12,640 --> 00:49:14,400
Speaker 6: scheme of things, is not massive.

934
00:49:14,520 --> 00:49:19,320
Speaker 1: And then okay, let's take this Indian elephant in the mammoth.

935
00:49:20,600 --> 00:49:23,400
Speaker 1: If you just took a someone who's somewhat well informed

936
00:49:23,440 --> 00:49:26,600
Speaker 1: about animals and laid the two of them out, they're

937
00:49:26,640 --> 00:49:28,719
Speaker 1: a look and they're going to point to probably the

938
00:49:28,719 --> 00:49:29,479
Speaker 1: size of the ear.

939
00:49:29,719 --> 00:49:33,880
Speaker 6: Yeah, smaller ears on a mammoth, toss length, big curved

940
00:49:33,920 --> 00:49:36,720
Speaker 6: tusk on a on a mammoth as well.

941
00:49:36,640 --> 00:49:39,560
Speaker 1: The pellage, the hair very hairy. What else are they seeing?

942
00:49:39,600 --> 00:49:42,000
Speaker 6: They have a brown fat, so they need to have

943
00:49:42,040 --> 00:49:43,760
Speaker 6: these sort of cold tolerant feed up types.

944
00:49:44,160 --> 00:49:45,000
Speaker 5: They lived in a much.

945
00:49:44,880 --> 00:49:45,960
Speaker 1: Colder I got cut into.

946
00:49:46,760 --> 00:49:48,920
Speaker 6: Yeah, so there's this brown added post layer that you

947
00:49:48,920 --> 00:49:50,719
Speaker 6: put in in sort of like if you thought about

948
00:49:50,719 --> 00:49:53,880
Speaker 6: blubberd would be similar to that. And then there's also

949
00:49:54,040 --> 00:49:57,279
Speaker 6: things like, you know, physiological changes that you need. So

950
00:49:57,320 --> 00:49:58,680
Speaker 6: one of the things that you have to do to

951
00:49:59,000 --> 00:50:01,560
Speaker 6: live in extreme old temperatures you have to be much

952
00:50:01,560 --> 00:50:05,040
Speaker 6: better at oxygen transfer, so you need to target things

953
00:50:05,040 --> 00:50:08,080
Speaker 6: that provide those adaptations. Then we have all those targeted

954
00:50:08,120 --> 00:50:11,040
Speaker 6: and the edits are happening today in a lab. Meanwhile

955
00:50:11,080 --> 00:50:13,040
Speaker 6: to that, we're doing all the reproductive sides. So when

956
00:50:13,040 --> 00:50:16,399
Speaker 6: the moment we have our edited mammoth cells, we'll pull

957
00:50:16,440 --> 00:50:18,239
Speaker 6: the nucleus out of that and we'll put it into

958
00:50:18,280 --> 00:50:21,520
Speaker 6: that into the egg of an Asian elephant. That Asian

959
00:50:21,520 --> 00:50:25,280
Speaker 6: elephant egg then is fertilized and becomes a wooly mammoth embryo,

960
00:50:25,840 --> 00:50:28,759
Speaker 6: and then from there you use artificial reproduction, not too

961
00:50:28,800 --> 00:50:34,480
Speaker 6: dissimilar to things like IVF and artificial and artificial insemination.

962
00:50:34,640 --> 00:50:37,000
Speaker 6: Those are the basest basic tools that we start, and

963
00:50:37,040 --> 00:50:39,720
Speaker 6: then we go to somatic cell nuclear transfer, which is cloning,

964
00:50:40,280 --> 00:50:44,480
Speaker 6: and we clone that embryo and transfer it into an

965
00:50:44,520 --> 00:50:47,520
Speaker 6: Asian elephant, or when you really want to get to

966
00:50:47,600 --> 00:50:51,160
Speaker 6: the real sci fi stuff, that we're doing an artificial womb.

967
00:50:51,200 --> 00:50:54,080
Speaker 6: So we're building technologies to develop artificial wombs for these

968
00:50:54,120 --> 00:50:56,520
Speaker 6: species as well, because if you're ever going to scale

969
00:50:56,520 --> 00:50:59,359
Speaker 6: a population, you'll always be most limited by how many

970
00:50:59,360 --> 00:51:01,680
Speaker 6: females are in that population. So if we wanted to

971
00:51:01,719 --> 00:51:05,080
Speaker 6: make five hundred Northern white rhinos, we would need five

972
00:51:05,200 --> 00:51:09,360
Speaker 6: hundred Southern white rhino females. But if we had artificial bombs,

973
00:51:09,360 --> 00:51:10,360
Speaker 6: the sky's the limit.

974
00:51:12,800 --> 00:51:16,440
Speaker 3: With his diagram, Well, I got asked to and I

975
00:51:16,480 --> 00:51:19,920
Speaker 3: can see this argument coming from a guy who's sitting

976
00:51:20,000 --> 00:51:26,000
Speaker 3: immediately to my life pushback because it's not the same, right, Oh,

977
00:51:26,080 --> 00:51:29,040
Speaker 3: you want to de extinction, Well the animal is not

978
00:51:29,040 --> 00:51:29,359
Speaker 3: the same.

979
00:51:29,400 --> 00:51:31,120
Speaker 1: Well you'd be able to be like, that's what it

980
00:51:31,239 --> 00:51:31,799
Speaker 1: looked like.

981
00:51:32,320 --> 00:51:36,520
Speaker 6: Right, But it's not it, right absolutely, But I guess

982
00:51:36,239 --> 00:51:40,279
Speaker 6: my question would be, you know, let's talk about pumas

983
00:51:40,400 --> 00:51:43,840
Speaker 6: are a good example. Yep, right, what makes a puma, puma.

984
00:51:43,920 --> 00:51:45,640
Speaker 1: We'll talk about the Florida pan a Florida panther.

985
00:51:45,680 --> 00:51:47,360
Speaker 6: If I go to if I go to South Florida

986
00:51:47,400 --> 00:51:49,719
Speaker 6: and I find a Florida panther, where I come up

987
00:51:49,719 --> 00:51:53,200
Speaker 6: here and I find a cougar, they're the same species,

988
00:51:53,960 --> 00:51:55,640
Speaker 6: but they are completely different.

989
00:51:55,840 --> 00:51:58,600
Speaker 1: Well, were well because.

990
00:51:59,520 --> 00:52:01,840
Speaker 3: Because they well, okay, is this supplement.

991
00:52:02,080 --> 00:52:05,680
Speaker 1: I'm glad you brought this up. Yeah, the Florida panther,

992
00:52:05,960 --> 00:52:07,680
Speaker 1: they got down to less.

993
00:52:07,440 --> 00:52:11,160
Speaker 6: Than fifty and they had extreme genetic bottlenecking issues.

994
00:52:11,120 --> 00:52:14,640
Speaker 1: And some folks said, well, let's bring in some other ones.

995
00:52:15,480 --> 00:52:19,640
Speaker 1: And the argument was, well, no, because we're gonna lose

996
00:52:19,719 --> 00:52:24,000
Speaker 1: that little special something that makes them the Florida panther.

997
00:52:24,200 --> 00:52:26,359
Speaker 1: And it says, you know, what you're gonna lose is

998
00:52:26,600 --> 00:52:30,880
Speaker 1: the whole thing. Right, you can hang on to something

999
00:52:32,080 --> 00:52:35,920
Speaker 1: by bringing in new animals, but if you take the

1000
00:52:36,000 --> 00:52:38,800
Speaker 1: path of you know, if you take your current path,

1001
00:52:39,000 --> 00:52:40,320
Speaker 1: they're just gonna blink out and be on.

1002
00:52:40,480 --> 00:52:42,399
Speaker 6: And it's one of my favorite examples because I think

1003
00:52:42,400 --> 00:52:44,359
Speaker 6: conservation for a long time has stood in its own

1004
00:52:44,360 --> 00:52:46,799
Speaker 6: way with this idea of perfection ahead of good. Right,

1005
00:52:46,920 --> 00:52:48,040
Speaker 6: this whole perfection is.

1006
00:52:48,040 --> 00:52:48,759
Speaker 5: The enemy of good.

1007
00:52:48,920 --> 00:52:52,120
Speaker 6: They're the idealism that we should have exactly what was

1008
00:52:52,160 --> 00:52:55,359
Speaker 6: represented in that range, which is a false narrative because

1009
00:52:55,360 --> 00:52:58,680
Speaker 6: we don't even know truly we can guess really well.

1010
00:52:59,360 --> 00:53:02,360
Speaker 6: But when I think the Florida Panther Genetic Rescue Project

1011
00:53:02,440 --> 00:53:04,400
Speaker 6: is an amazing example that you don't have to have

1012
00:53:04,520 --> 00:53:07,520
Speaker 6: exactly the same thing. You need very specific phenotypes that

1013
00:53:07,560 --> 00:53:10,960
Speaker 6: make that help it perform that ecosystem function that helps

1014
00:53:11,000 --> 00:53:14,000
Speaker 6: improve the health of the ecosystem and helps restore population,

1015
00:53:14,360 --> 00:53:17,040
Speaker 6: and then the environmental factors that still exist in these

1016
00:53:17,120 --> 00:53:20,319
Speaker 6: ranges will push that animal back into more of what

1017
00:53:20,520 --> 00:53:23,120
Speaker 6: you might consider one hundred percent of pure of that species.

1018
00:53:23,200 --> 00:53:26,520
Speaker 1: Yeah. And in the meanwhile, it's eating what they ate. Yep,

1019
00:53:26,640 --> 00:53:27,280
Speaker 1: it's using.

1020
00:53:27,760 --> 00:53:28,839
Speaker 3: Going to do the same job.

1021
00:53:28,920 --> 00:53:31,080
Speaker 2: Well, isn't that true that like the bison you guys

1022
00:53:31,080 --> 00:53:33,720
Speaker 2: were work the hides you were working on those bison

1023
00:53:33,760 --> 00:53:36,600
Speaker 2: aren't one?

1024
00:53:36,840 --> 00:53:40,640
Speaker 1: Yeah? Right, Like that's a case where was the expression

1025
00:53:40,640 --> 00:53:43,279
Speaker 1: you used? Perfection is the idea of good? Yeah, that

1026
00:53:43,320 --> 00:53:47,360
Speaker 1: whole discussion about I think this whole discussion about cattle

1027
00:53:47,400 --> 00:53:51,360
Speaker 1: intro aggression into bison as being where it becomes like

1028
00:53:51,400 --> 00:53:54,960
Speaker 1: an obstacle to bison restoration. I think it's such a distraction.

1029
00:53:55,000 --> 00:53:57,320
Speaker 1: It is, and you can line up a thousand humans

1030
00:53:57,320 --> 00:54:01,200
Speaker 1: and be like, what is that animal buffalo? You're like, Nope, yeah,

1031
00:54:02,800 --> 00:54:05,840
Speaker 1: it's a it's zero point two cattle. You know.

1032
00:54:05,960 --> 00:54:09,360
Speaker 6: It's in our chief science officer, Beth Shapiro, who you know,

1033
00:54:10,440 --> 00:54:14,440
Speaker 6: she has for a long time studied bison genetics and

1034
00:54:14,480 --> 00:54:16,920
Speaker 6: she's got this amazing grad student Jonas, who they are

1035
00:54:17,200 --> 00:54:20,360
Speaker 6: just published a paper that shows the cattle integression narrative

1036
00:54:20,440 --> 00:54:23,080
Speaker 6: is completely false. If you go back historically and you

1037
00:54:23,120 --> 00:54:26,520
Speaker 6: look at bison before the presence of domestic cattle, they

1038
00:54:26,560 --> 00:54:29,080
Speaker 6: had the same level of representation of what we think

1039
00:54:29,120 --> 00:54:31,600
Speaker 6: today is cattle in them, but it's just because it's

1040
00:54:31,600 --> 00:54:35,600
Speaker 6: a they evolved from a similar release. Yeah, so there

1041
00:54:35,719 --> 00:54:39,480
Speaker 6: is actually very good evidence to suggest that Bfalow is

1042
00:54:40,160 --> 00:54:40,960
Speaker 6: kind of bs.

1043
00:54:41,719 --> 00:54:43,160
Speaker 1: Yeah, I've talked to her about that.

1044
00:54:43,239 --> 00:54:47,160
Speaker 6: Yeah, because there's actually a reproductive block for future generations

1045
00:54:47,200 --> 00:54:51,200
Speaker 6: once you hybridize the two species. So it's really interesting.

1046
00:54:51,239 --> 00:54:55,080
Speaker 6: We don't fully understand it, but Jonas's research shows that

1047
00:54:55,200 --> 00:54:57,560
Speaker 6: if you go back in time, you can see that

1048
00:54:57,600 --> 00:55:00,680
Speaker 6: the same representation at cattle in their genome that you today.

1049
00:55:00,480 --> 00:55:03,200
Speaker 2: With from like the base of the exactly tree.

1050
00:55:03,280 --> 00:55:05,360
Speaker 6: Yeah, they sort of evolved from a similar ancestor, so

1051
00:55:05,400 --> 00:55:06,680
Speaker 6: they'd have similar DNA.

1052
00:55:07,280 --> 00:55:10,000
Speaker 1: Yeah, I guess to be similar with how you know,

1053
00:55:11,800 --> 00:55:16,000
Speaker 1: all everybody of Western European descent has some trace element

1054
00:55:16,160 --> 00:55:18,120
Speaker 1: of Neanderthal exactly.

1055
00:55:19,080 --> 00:55:21,640
Speaker 6: But that doesn't mean we hybridized with neanderthalogists, we had

1056
00:55:21,640 --> 00:55:22,560
Speaker 6: a common answer.

1057
00:55:22,280 --> 00:55:23,640
Speaker 1: So it doesn't mean we're still doing it.

1058
00:55:23,880 --> 00:55:26,400
Speaker 5: Yeah, I've seen a few examples.

1059
00:55:27,320 --> 00:55:29,840
Speaker 1: So let's talk about that. Though, I want to go

1060
00:55:29,880 --> 00:55:32,919
Speaker 1: back to this, the set of the steps you do.

1061
00:55:35,320 --> 00:55:38,960
Speaker 1: The most obvious question is, uh, what's your what's your guess?

1062
00:55:39,080 --> 00:55:40,719
Speaker 1: When does this thing hit? When does the first one

1063
00:55:40,800 --> 00:55:41,320
Speaker 1: hit the ground?

1064
00:55:41,360 --> 00:55:43,720
Speaker 6: Science is so hard and I hate to put pressure

1065
00:55:43,719 --> 00:55:45,480
Speaker 6: on our scientists, and but I can because I'm not

1066
00:55:45,520 --> 00:55:47,400
Speaker 6: in the lab doing this, right, I'm just the stupid

1067
00:55:47,480 --> 00:55:50,239
Speaker 6: animal guy that talks about this stuff. Uh, you know,

1068
00:55:50,239 --> 00:55:53,520
Speaker 6: we're really moving forward quickly. We just had this amazing

1069
00:55:53,520 --> 00:55:56,160
Speaker 6: announcement that we've been the first people to ever achieve

1070
00:55:56,239 --> 00:55:59,399
Speaker 6: this plary ponent stem cell line of elephants that's never

1071
00:55:59,400 --> 00:56:01,359
Speaker 6: been done, which is sort of an integral step along

1072
00:56:01,400 --> 00:56:05,560
Speaker 6: the way. So we're looking, you know, twenty twenty eight

1073
00:56:05,640 --> 00:56:08,080
Speaker 6: is what we're targeting right now. I would say we

1074
00:56:08,200 --> 00:56:11,239
Speaker 6: have to also acknowledge that there's two year gestation for

1075
00:56:11,280 --> 00:56:13,320
Speaker 6: these so you know, I would always put plus or

1076
00:56:13,400 --> 00:56:16,160
Speaker 6: minuses on these things. But we're you know, I think

1077
00:56:16,200 --> 00:56:18,799
Speaker 6: this is much sooner than people expect. There's so many

1078
00:56:18,880 --> 00:56:22,040
Speaker 6: challenges ahead that you know, one step could could delay us.

1079
00:56:22,080 --> 00:56:25,400
Speaker 6: But that's the course so far. That's what we painted

1080
00:56:25,400 --> 00:56:26,240
Speaker 6: and we're on target.

1081
00:56:26,680 --> 00:56:32,640
Speaker 1: And when it does, sorry Brodie, real quick, is it

1082
00:56:32,680 --> 00:56:34,840
Speaker 1: a multi step process or does the first one that

1083
00:56:34,920 --> 00:56:36,879
Speaker 1: hit the ground be like, that's what you're aiming for?

1084
00:56:37,239 --> 00:56:40,560
Speaker 6: We don't, I would I would say we're always going

1085
00:56:40,640 --> 00:56:44,400
Speaker 6: to be improving, right, It's not that this is an

1086
00:56:44,480 --> 00:56:47,359
Speaker 6: iterative process that requires multiple steps, but it is likely

1087
00:56:47,400 --> 00:56:52,399
Speaker 6: that you learn something that changes the next sequence of events. Right,

1088
00:56:52,480 --> 00:56:55,040
Speaker 6: So as we see the first one, we say, oh, actually,

1089
00:56:55,920 --> 00:56:58,120
Speaker 6: you know, maybe this phenotype needed to be tweaked, or

1090
00:56:58,120 --> 00:56:59,880
Speaker 6: maybe we have a better understanding of what we call

1091
00:57:00,000 --> 00:57:03,479
Speaker 6: genotype of phenotype relationships, and then that would that would

1092
00:57:03,480 --> 00:57:05,680
Speaker 6: inform a different type of editing strategy.

1093
00:57:06,960 --> 00:57:07,720
Speaker 3: Who do you guys?

1094
00:57:09,080 --> 00:57:13,879
Speaker 2: You guys answer to as far as like legality, I mean,

1095
00:57:13,920 --> 00:57:17,600
Speaker 2: there's like obviously like ethical and moral questions that some

1096
00:57:17,640 --> 00:57:20,200
Speaker 2: people are going to have about this whole thing, but like,

1097
00:57:20,320 --> 00:57:24,760
Speaker 2: where's the where's the oversight, like, because you guys are

1098
00:57:24,800 --> 00:57:28,160
Speaker 2: like international, right, like or is it just us?

1099
00:57:28,360 --> 00:57:28,440
Speaker 1: No?

1100
00:57:28,560 --> 00:57:31,240
Speaker 6: Well, the operation is US base. We also have some

1101
00:57:31,320 --> 00:57:34,000
Speaker 6: partners in Australia, so there's some of that as well.

1102
00:57:34,040 --> 00:57:40,040
Speaker 6: But uh, it's with anything, especially in the US regulatory environment,

1103
00:57:40,160 --> 00:57:42,920
Speaker 6: it's a mess, right, It's there's there's so many competing

1104
00:57:42,960 --> 00:57:47,760
Speaker 6: forces for jurisdictional power that we don't really have all

1105
00:57:47,800 --> 00:57:50,400
Speaker 6: the answers yet. What we are doing today is we're

1106
00:57:50,440 --> 00:57:53,360
Speaker 6: working to help support the ic N if you're familiar

1107
00:57:53,360 --> 00:57:56,160
Speaker 6: with to the right, So we're supporting the ic N

1108
00:57:56,200 --> 00:58:00,480
Speaker 6: Species Survival Commission to really start to drive forward policy

1109
00:58:00,520 --> 00:58:03,000
Speaker 6: statements and really begin to build that roadmap. So we

1110
00:58:03,040 --> 00:58:05,200
Speaker 6: want to help facilitate those things, but in a third

1111
00:58:05,240 --> 00:58:08,680
Speaker 6: party independent fashion, so that these groups can help say

1112
00:58:08,800 --> 00:58:12,120
Speaker 6: this is the exact pathway that has legal, regulatory and

1113
00:58:12,160 --> 00:58:15,480
Speaker 6: ethical considerations already baked into it, and then that's sort

1114
00:58:15,520 --> 00:58:18,240
Speaker 6: of the gold standard that most governments are looking to

1115
00:58:18,240 --> 00:58:21,600
Speaker 6: to help inform their domestic regulation. Here in the US,

1116
00:58:21,640 --> 00:58:25,280
Speaker 6: we're certainly subjected to things like USDA, which and APHIS,

1117
00:58:25,280 --> 00:58:29,919
Speaker 6: which has oversight over animals and human care, especially mammals, right,

1118
00:58:29,960 --> 00:58:32,400
Speaker 6: and then US fish and wildlife because we're talking about

1119
00:58:32,440 --> 00:58:35,560
Speaker 6: endangered species. Some siety is listed some of USA listed species.

1120
00:58:36,600 --> 00:58:39,840
Speaker 6: And then we have things like FDA when you're intentionally

1121
00:58:39,880 --> 00:58:44,160
Speaker 6: altering the genome of an animal, technically there are aspects

1122
00:58:44,160 --> 00:58:47,200
Speaker 6: of that that could fall under FDA jurisdiction. But what's

1123
00:58:47,240 --> 00:58:49,880
Speaker 6: really interesting is there's groups that have been going through

1124
00:58:49,920 --> 00:58:52,760
Speaker 6: this same process on the AG site already, So there

1125
00:58:52,800 --> 00:58:56,000
Speaker 6: are some guardrails in place if we just want to

1126
00:58:56,040 --> 00:58:59,480
Speaker 6: be the subject matter expert to provide responsible regulation and

1127
00:58:59,520 --> 00:59:02,360
Speaker 6: move forward to yeather. But I think uh Awkway advantage

1128
00:59:02,400 --> 00:59:05,080
Speaker 6: salmon if you had had you guys ever seen that

1129
00:59:05,080 --> 00:59:08,120
Speaker 6: the genetically engineered line of salmon that are meant to

1130
00:59:08,160 --> 00:59:13,000
Speaker 6: be healthier in farm raise scenarios. They were given genetic

1131
00:59:13,160 --> 00:59:15,919
Speaker 6: editing tools to essentially help them heal faster because there's

1132
00:59:15,960 --> 00:59:20,240
Speaker 6: so much trauma in farm farm raise fishing. And that

1133
00:59:20,360 --> 00:59:21,840
Speaker 6: took twenty years to get approved.

1134
00:59:22,960 --> 00:59:25,520
Speaker 1: So and is it is it approved for human consumption?

1135
00:59:25,920 --> 00:59:28,360
Speaker 6: It's just last year it received a thumbs up.

1136
00:59:28,800 --> 00:59:29,360
Speaker 5: Really yeah?

1137
00:59:29,480 --> 00:59:30,680
Speaker 1: Is that off Atlantic salmon?

1138
00:59:31,480 --> 00:59:33,760
Speaker 6: I actually don't know which salmon. They based it on

1139
00:59:34,280 --> 00:59:35,960
Speaker 6: it's got to be it, Yeah, I would think.

1140
00:59:36,000 --> 00:59:39,720
Speaker 1: So all right, let me ask you this. This is

1141
00:59:39,720 --> 00:59:45,880
Speaker 1: the thing we've talked about in private conversation. We've discussed this.

1142
00:59:48,960 --> 00:59:54,240
Speaker 1: Why if you look at why the mammoth and why

1143
00:59:55,000 --> 00:59:59,320
Speaker 1: the Philo scene, what the Thilo scene, you could kind

1144
00:59:59,320 --> 01:00:02,160
Speaker 1: of look and be like one, it just happened. It

1145
01:00:02,400 --> 01:00:07,760
Speaker 1: just went extinct. Some people argue, not entirely crazy. People

1146
01:00:08,640 --> 01:00:11,880
Speaker 1: argue that it didn't go extinct. True, and it did

1147
01:00:11,880 --> 01:00:14,960
Speaker 1: for a while, have a Lazarus. It was regarded as

1148
01:00:14,960 --> 01:00:19,880
Speaker 1: a Lazarus species, referencing Lazarus from the Bible, where it

1149
01:00:19,920 --> 01:00:21,720
Speaker 1: was like they thought they were gone and they weren't.

1150
01:00:22,080 --> 01:00:25,240
Speaker 1: Another really famous Lazarus species of the blackfooted ferret. It

1151
01:00:25,320 --> 01:00:27,440
Speaker 1: was people thought they were gone, but they weren't so

1152
01:00:27,560 --> 01:00:30,720
Speaker 1: used to it's so fresh, there's people thinking that one

1153
01:00:30,800 --> 01:00:34,080
Speaker 1: might turn up. Okay, So here you have like an

1154
01:00:34,120 --> 01:00:38,400
Speaker 1: ecosystem that's ready to receive it. You have you can

1155
01:00:38,480 --> 01:00:46,120
Speaker 1: point to why it went extinct. The prey base is there, right,

1156
01:00:46,720 --> 01:00:49,000
Speaker 1: so you could you could put it back and it's

1157
01:00:49,520 --> 01:00:51,440
Speaker 1: and it's like it's it just it just wound up

1158
01:00:51,480 --> 01:00:56,600
Speaker 1: missing a beat like that to me, seems so constructive.

1159
01:00:57,480 --> 01:01:01,880
Speaker 1: It would be so it would enjoy such book support. Well,

1160
01:01:01,880 --> 01:01:06,760
Speaker 1: the Mammoth's like there's some argument that this ship has sailed.

1161
01:01:07,360 --> 01:01:10,560
Speaker 7: It's like, uh, it's like Brooks and shash Ank redemption.

1162
01:01:11,240 --> 01:01:14,200
Speaker 7: The world just got so damn fast.

1163
01:01:14,320 --> 01:01:16,520
Speaker 1: It was like Clay at the end of the live tour. Yeah,

1164
01:01:17,960 --> 01:01:20,240
Speaker 1: He's like, you know, I was gone with the world

1165
01:01:20,360 --> 01:01:25,640
Speaker 1: kept going. He couldn't reintegrate. Uh yeah. So like you

1166
01:01:25,680 --> 01:01:28,520
Speaker 1: know when when they were around, like have you seen

1167
01:01:28,520 --> 01:01:30,360
Speaker 1: all this stuff that's come out of that where they

1168
01:01:30,400 --> 01:01:32,920
Speaker 1: were able to look at stable isotopes and the mammoth

1169
01:01:33,040 --> 01:01:36,840
Speaker 1: tusk and he realized how much this, I mean, how

1170
01:01:36,880 --> 01:01:39,520
Speaker 1: much this mammoth in Alaska is moving during its lifetime.

1171
01:01:39,720 --> 01:01:42,160
Speaker 1: I mean some bitches like in the Yukon he's south

1172
01:01:42,200 --> 01:01:44,040
Speaker 1: of the Brooks Range. He's north of the Brooks Range.

1173
01:01:44,040 --> 01:01:47,560
Speaker 1: He basically traveled the length of California in a life

1174
01:01:47,600 --> 01:01:51,439
Speaker 1: that was he died at what twenty twenty years old

1175
01:01:51,480 --> 01:01:56,480
Speaker 1: or something like that. So it's like that ain't there anymore,

1176
01:01:57,600 --> 01:01:58,720
Speaker 1: do you know what I mean? So, how do you

1177
01:01:58,760 --> 01:02:01,360
Speaker 1: begin dealing with that? Like, how do you begin dealing

1178
01:02:01,400 --> 01:02:03,920
Speaker 1: with that? You want up with the sort of world's

1179
01:02:03,920 --> 01:02:05,000
Speaker 1: most lonely animal.

1180
01:02:06,160 --> 01:02:07,800
Speaker 6: Well, hopefully it won't be lonely because they'll be in

1181
01:02:07,800 --> 01:02:08,400
Speaker 6: a population.

1182
01:02:08,520 --> 01:02:08,640
Speaker 5: Right.

1183
01:02:08,720 --> 01:02:10,720
Speaker 6: This is not a one off novelty where you just

1184
01:02:10,760 --> 01:02:13,480
Speaker 6: have one of these. The focus is really create sustainable

1185
01:02:13,480 --> 01:02:17,360
Speaker 6: populations with the idea of re engineering what today is

1186
01:02:17,400 --> 01:02:20,720
Speaker 6: a tundry ecosystem that doesn't support a lot of biodiversity

1187
01:02:20,760 --> 01:02:24,560
Speaker 6: your life. Looking at what the Zimovs achieved with Plessing

1188
01:02:24,640 --> 01:02:28,080
Speaker 6: Park where they rewilded you know, large vertebrates like muskox

1189
01:02:28,160 --> 01:02:31,240
Speaker 6: and wild horses and even bisen.

1190
01:02:31,440 --> 01:02:32,640
Speaker 1: How many acres is that?

1191
01:02:32,720 --> 01:02:33,240
Speaker 5: It's small?

1192
01:02:33,880 --> 01:02:35,200
Speaker 6: I don't want to give you the wrong number, but

1193
01:02:35,200 --> 01:02:38,160
Speaker 6: it's not. It's not massive, something like eighty or eight

1194
01:02:38,280 --> 01:02:39,560
Speaker 6: hundred hector or something like that.

1195
01:02:40,360 --> 01:02:42,600
Speaker 2: How do you get around the argument though, that the

1196
01:02:42,680 --> 01:02:45,240
Speaker 2: animals that are on the tundra now are the ones

1197
01:02:45,280 --> 01:02:46,400
Speaker 2: that belong there now?

1198
01:02:47,200 --> 01:02:50,360
Speaker 6: Well, I think what we're what we find is that

1199
01:02:50,480 --> 01:02:52,360
Speaker 6: and this is there's a lot of evidence that shows

1200
01:02:52,400 --> 01:02:54,880
Speaker 6: us in West Africa forest elephants, is that the presence

1201
01:02:54,920 --> 01:02:59,160
Speaker 6: of a large mammal like that of Probsidian actually opens

1202
01:02:59,240 --> 01:03:02,880
Speaker 6: up moreological niches. So it's not really displacing species, it's

1203
01:03:02,880 --> 01:03:06,360
Speaker 6: creating more niches to bring more biodiversity. The Mamma step

1204
01:03:06,560 --> 01:03:09,920
Speaker 6: grassland ecosystem that existed four thousand years ago was as

1205
01:03:09,920 --> 01:03:14,160
Speaker 6: biodiverse as the African savannah, and today it is, you know,

1206
01:03:14,440 --> 01:03:15,720
Speaker 6: sort of a Martian landscape.

1207
01:03:15,760 --> 01:03:16,880
Speaker 5: Right, It's really bare.

1208
01:03:16,920 --> 01:03:21,000
Speaker 6: And so this idea that we could create more habital,

1209
01:03:21,760 --> 01:03:28,320
Speaker 6: habitable ecosystem for more biodiversity is really compelling in a

1210
01:03:28,480 --> 01:03:32,040
Speaker 6: time when we're facing the world's largest biodiversity crisis. We

1211
01:03:32,040 --> 01:03:34,920
Speaker 6: talk about climate change all the time, and people can

1212
01:03:34,960 --> 01:03:37,200
Speaker 6: debate that to their blue in the face. What you

1213
01:03:37,240 --> 01:03:40,920
Speaker 6: can't debate is that the extinction rates we see across

1214
01:03:40,920 --> 01:03:43,880
Speaker 6: the world are only accelerating. You know, by twenty fifty

1215
01:03:43,880 --> 01:03:45,520
Speaker 6: there are some people that estimate we could lose up

1216
01:03:45,520 --> 01:03:48,280
Speaker 6: to fifty percent of all mammal species. Right, we need

1217
01:03:48,320 --> 01:03:51,080
Speaker 6: to find solutions. We need to begin to say how

1218
01:03:51,080 --> 01:03:54,600
Speaker 6: can we support nature to be more resilient because nature,

1219
01:03:54,720 --> 01:03:57,960
Speaker 6: given time, space opportunity, will evolve and it's showing us

1220
01:03:58,040 --> 01:04:00,320
Speaker 6: that that's why we have the amazing ecosis since we

1221
01:04:00,360 --> 01:04:02,160
Speaker 6: have today, That's why we have yellows in National Park.

1222
01:04:02,240 --> 01:04:02,400
Speaker 5: Right.

1223
01:04:02,800 --> 01:04:06,080
Speaker 6: His nature has provided something amazing. But when we continue

1224
01:04:06,080 --> 01:04:09,200
Speaker 6: to layer pressure upon pressure upon pressure. We're really paining

1225
01:04:09,280 --> 01:04:11,800
Speaker 6: nature into a corner in a place where now it

1226
01:04:11,840 --> 01:04:15,560
Speaker 6: cannot respond fasten us. Evolution cannot keep up, and so

1227
01:04:15,600 --> 01:04:18,200
Speaker 6: what we're looking to do is to provide engineering solutions

1228
01:04:18,240 --> 01:04:20,920
Speaker 6: to accelerate evolution, to provide nature a chance to keep

1229
01:04:20,960 --> 01:04:24,120
Speaker 6: up with humanity, which is really difficult. But you know,

1230
01:04:24,440 --> 01:04:27,960
Speaker 6: I think restoring ecosystems is the start of that. Removing

1231
01:04:27,960 --> 01:04:32,880
Speaker 6: evasive predators, right, We're using technologies like genetic biocontrols to

1232
01:04:32,920 --> 01:04:36,080
Speaker 6: remove an invasive predator from say Mauritius, so that it

1233
01:04:36,120 --> 01:04:39,960
Speaker 6: can prepare prepare an ecosystem for the Dodo is amazing.

1234
01:04:39,960 --> 01:04:42,320
Speaker 6: I think everybody agreed that rats, cats and monkeys don't

1235
01:04:42,320 --> 01:04:43,560
Speaker 6: belong on mauritious and.

1236
01:04:43,520 --> 01:04:47,360
Speaker 3: A genetic biocontrol would be making everybody mail.

1237
01:04:47,800 --> 01:04:50,000
Speaker 6: Yeah, that would be one form of a genetic biocontrol.

1238
01:04:50,040 --> 01:04:52,680
Speaker 6: Gene drives is another form, right, So we sort of

1239
01:04:52,720 --> 01:04:56,000
Speaker 6: have these multiple ways that you can create a deleterious

1240
01:04:56,040 --> 01:04:58,600
Speaker 6: allele within an animal's genome but also give them a

1241
01:04:58,600 --> 01:05:01,600
Speaker 6: biological fitness advantage. They go into an ecosystem, they spread

1242
01:05:01,600 --> 01:05:05,200
Speaker 6: that allele that gene throughout the population, and that helps

1243
01:05:05,200 --> 01:05:08,240
Speaker 6: suppress the population or in some case completely exterminate it.

1244
01:05:09,200 --> 01:05:12,080
Speaker 6: So you know, there are these amazing opportunities, they're just

1245
01:05:12,400 --> 01:05:15,800
Speaker 6: emerging technologies that don't have the regulatory guardrails yet, that

1246
01:05:15,840 --> 01:05:18,600
Speaker 6: don't have the social understanding to really support those And

1247
01:05:18,640 --> 01:05:20,320
Speaker 6: so that's one of the things is we want to

1248
01:05:20,360 --> 01:05:23,880
Speaker 6: help socialize those ideas and help bring these debates to

1249
01:05:23,920 --> 01:05:27,840
Speaker 6: the forefront, because for us, it's important that people that

1250
01:05:27,920 --> 01:05:29,480
Speaker 6: we acknowledge we don't have all the answers.

1251
01:05:29,520 --> 01:05:31,120
Speaker 5: We have some amazingly.

1252
01:05:30,560 --> 01:05:33,760
Speaker 6: Powerful tools, but we need to have debates about these

1253
01:05:33,760 --> 01:05:36,200
Speaker 6: things because the fact of the matter is the status

1254
01:05:36,280 --> 01:05:39,560
Speaker 6: quo is losing. We're falling behind every year, and we

1255
01:05:39,640 --> 01:05:42,600
Speaker 6: need to do something maybe a little more drastic, and

1256
01:05:42,640 --> 01:05:44,360
Speaker 6: that's what Colossal's providing right now.

1257
01:05:45,120 --> 01:05:47,520
Speaker 3: So with the case of the mammoth, like the road map, right,

1258
01:05:47,560 --> 01:05:50,800
Speaker 3: so Steve just talked about this one individual that enjoyed

1259
01:05:50,840 --> 01:05:55,080
Speaker 3: this giant historic range is just not going to have

1260
01:05:55,240 --> 01:05:58,560
Speaker 3: those types of freedoms, so you would try to find

1261
01:05:58,600 --> 01:06:02,680
Speaker 3: a suitable habitat with a lot of controls, right exactly.

1262
01:06:02,960 --> 01:06:06,480
Speaker 3: And also that first mammoth is going to be uh,

1263
01:06:07,320 --> 01:06:09,880
Speaker 3: pretty valuable. I'm gonna have quite the price tag attached

1264
01:06:09,880 --> 01:06:10,480
Speaker 3: to it, right.

1265
01:06:10,760 --> 01:06:12,040
Speaker 1: You know, I think what they ought to do, and

1266
01:06:12,080 --> 01:06:14,919
Speaker 1: I've said this, we need to make nice with Russia again.

1267
01:06:16,560 --> 01:06:18,560
Speaker 1: I'm not saying I'm not talking about I'm not waiting

1268
01:06:18,600 --> 01:06:21,080
Speaker 1: into geopolitics. Let's say there's a world in which we

1269
01:06:21,120 --> 01:06:23,800
Speaker 1: made nice with Russia again and we went to Wrangle Island,

1270
01:06:25,120 --> 01:06:28,520
Speaker 1: which was the last place they existed. They didn't blink

1271
01:06:28,520 --> 01:06:30,080
Speaker 1: out till four thousand years ago.

1272
01:06:30,080 --> 01:06:32,800
Speaker 6: On Wrangle Island, the Great Pyramids of Gaza were under

1273
01:06:32,800 --> 01:06:35,000
Speaker 6: construction when the will of Mammoth went extinct. Like, I

1274
01:06:35,000 --> 01:06:37,840
Speaker 6: think that a lot of people don't have that context

1275
01:06:37,840 --> 01:06:39,560
Speaker 6: at time, right, They feel like this is such an

1276
01:06:39,560 --> 01:06:42,760
Speaker 6: ancient thing, you know, No, the Egyptians were a highly

1277
01:06:42,760 --> 01:06:46,360
Speaker 6: civilized group at the same time that Mammot swalk this earth.

1278
01:06:46,560 --> 01:06:51,200
Speaker 1: Remember Trump was some about buying Iceland. No, He's like,

1279
01:06:51,200 --> 01:06:53,920
Speaker 1: well buy Greenland, yeah, which people tease him about. But

1280
01:06:53,920 --> 01:06:56,439
Speaker 1: I thought I was like, that's a good idea. Maybe

1281
01:06:56,440 --> 01:06:57,560
Speaker 1: we can buy Wrangle Island.

1282
01:06:58,200 --> 01:07:00,840
Speaker 3: Absolutely, but yeah, like a situation like that, right, it's

1283
01:07:00,840 --> 01:07:01,760
Speaker 3: got its own fence.

1284
01:07:03,320 --> 01:07:05,440
Speaker 6: I think that's how you pilot these things, right, These

1285
01:07:06,280 --> 01:07:10,000
Speaker 6: have to be this a very thoughtful, stagegated process of rewilding.

1286
01:07:10,320 --> 01:07:13,400
Speaker 6: You cannot just make a lily mammoth and say godspeed.

1287
01:07:14,640 --> 01:07:16,920
Speaker 1: It's similar happened to that thing.

1288
01:07:17,000 --> 01:07:19,000
Speaker 6: No, we have to talk about, like, you know where,

1289
01:07:19,120 --> 01:07:23,400
Speaker 6: how does it start in a highly managed situation with caretakers,

1290
01:07:23,800 --> 01:07:27,160
Speaker 6: and then generationally that that level of care is decreased

1291
01:07:27,200 --> 01:07:30,040
Speaker 6: and that ecosystems are broader and broader, and eventually we'll

1292
01:07:30,040 --> 01:07:31,520
Speaker 6: get to a point of what we would call a

1293
01:07:31,560 --> 01:07:34,760
Speaker 6: soft release, which is sort of this vast ecosystems probably

1294
01:07:34,840 --> 01:07:38,440
Speaker 6: fenced or has some sort of physical barrier that allows

1295
01:07:38,520 --> 01:07:41,840
Speaker 6: us to say, okay, here is the experimental condition that

1296
01:07:41,880 --> 01:07:44,720
Speaker 6: people need to understand what's happening, and then one day

1297
01:07:44,760 --> 01:07:48,240
Speaker 6: you would open that gate and truly rewild and then.

1298
01:07:48,200 --> 01:07:51,400
Speaker 3: Just a crazy amount of consistent data on what's happening

1299
01:07:51,400 --> 01:07:53,440
Speaker 3: to the landscape because.

1300
01:07:53,040 --> 01:07:56,840
Speaker 6: Of And that's so exciting is there's all these sort

1301
01:07:56,840 --> 01:07:59,960
Speaker 6: of things that have to happen in ten twenty third

1302
01:08:00,280 --> 01:08:03,120
Speaker 6: years for this to happen, and today we're building technologies

1303
01:08:03,120 --> 01:08:04,480
Speaker 6: to answer those questions.

1304
01:08:04,480 --> 01:08:07,960
Speaker 1: So, and you also have the eis with the the

1305
01:08:08,040 --> 01:08:09,200
Speaker 1: environmental impact statement.

1306
01:08:09,280 --> 01:08:11,400
Speaker 5: Oh yeah, that's why we should do rub it.

1307
01:08:11,560 --> 01:08:17,080
Speaker 1: Yeah, well, yeah, it's like doing an environmental impact statement

1308
01:08:17,160 --> 01:08:19,559
Speaker 1: on it is going to be arduous.

1309
01:08:19,400 --> 01:08:22,880
Speaker 6: Absolutely, But I think there's a lot of opportunity in

1310
01:08:23,360 --> 01:08:27,559
Speaker 6: many of these efforts because there's emerging economies around conservation

1311
01:08:27,640 --> 01:08:30,720
Speaker 6: that help drive and support, you know, sustained effort. If

1312
01:08:30,760 --> 01:08:33,559
Speaker 6: you were able to improve biodiversity in area that currently

1313
01:08:33,640 --> 01:08:36,719
Speaker 6: has a low baseline of diversity, and you could create

1314
01:08:36,760 --> 01:08:40,200
Speaker 6: this African savannah like diversity in the Arctic, you could

1315
01:08:40,840 --> 01:08:44,360
Speaker 6: you know, eventually begin to apply for things like biodiversity

1316
01:08:44,400 --> 01:08:48,599
Speaker 6: and carbon credits. That becomes sustainable ways to protect nature,

1317
01:08:48,840 --> 01:08:52,840
Speaker 6: and it's investing in the preservation restoration in nature rather

1318
01:08:52,880 --> 01:08:55,759
Speaker 6: than extracting resources from nature.

1319
01:09:04,160 --> 01:09:09,600
Speaker 1: Let's let's take another example and and talk about the

1320
01:09:09,600 --> 01:09:13,080
Speaker 1: the Ivory built woodpecker. Yeah, okay, the Ivy built woodpecker

1321
01:09:13,320 --> 01:09:14,000
Speaker 1: went extinct.

1322
01:09:14,080 --> 01:09:15,360
Speaker 6: Maybe another Lasar instagrat.

1323
01:09:15,360 --> 01:09:17,759
Speaker 1: I'm talking to your Yeah, it's.

1324
01:09:17,680 --> 01:09:20,960
Speaker 5: Gone something everybody this season in c I.

1325
01:09:20,880 --> 01:09:24,320
Speaker 6: Think that's for Louisiana, right, that was the last one

1326
01:09:24,320 --> 01:09:26,960
Speaker 6: always affiliated woodpecker.

1327
01:09:27,200 --> 01:09:31,320
Speaker 1: Yeah, there's the thing of Ivory built woodpecker. People see it.

1328
01:09:31,320 --> 01:09:34,360
Speaker 1: It's affiliated pilated woodpecker. And then I went and held

1329
01:09:34,360 --> 01:09:40,400
Speaker 1: the Ivory build woodpecker. Remember at Cornell, who's there you guys. Yeah,

1330
01:09:40,439 --> 01:09:42,400
Speaker 1: but I felt I used to kind of like, in

1331
01:09:42,479 --> 01:09:46,400
Speaker 1: my mind tease people who screwed mixed them up. And

1332
01:09:46,439 --> 01:09:48,599
Speaker 1: when I held it, I'm like, Okay, I'm never gonna

1333
01:09:48,600 --> 01:09:50,040
Speaker 1: tease anyone again for mixing.

1334
01:09:49,960 --> 01:09:51,639
Speaker 2: Not blurry bigfoot footage.

1335
01:09:51,680 --> 01:09:55,680
Speaker 1: No, it's just like not. When I picked up the

1336
01:09:55,720 --> 01:09:57,680
Speaker 1: Ivy built woodpecker, I was thinking i'd be picking up

1337
01:09:57,720 --> 01:10:01,360
Speaker 1: like a like a do you know what I mean,

1338
01:10:01,439 --> 01:10:04,080
Speaker 1: like like, and it was just it was kind of like, oh,

1339
01:10:04,680 --> 01:10:08,040
Speaker 1: it's a delicate Yeah, it's got a different bill, but

1340
01:10:08,080 --> 01:10:10,599
Speaker 1: I mean it's like it's it's not this. I just

1341
01:10:10,640 --> 01:10:12,920
Speaker 1: in my mind I had them just enormous, you know,

1342
01:10:12,960 --> 01:10:16,160
Speaker 1: I had them like like a I don't know, man,

1343
01:10:16,200 --> 01:10:18,839
Speaker 1: I just pictured him like giants and you see appiliated woodpecker.

1344
01:10:18,880 --> 01:10:21,000
Speaker 1: It's a good sized bird, but it's not that. And

1345
01:10:21,040 --> 01:10:22,840
Speaker 1: then I held one and I'm like, okay, I see

1346
01:10:22,880 --> 01:10:24,439
Speaker 1: it now, I see how you screwed this up. Like

1347
01:10:24,640 --> 01:10:27,400
Speaker 1: I wasn't. I was under no discredit to the Ivy

1348
01:10:27,439 --> 01:10:29,800
Speaker 1: built woodpecker. What I'm trying to say is I was

1349
01:10:29,920 --> 01:10:34,080
Speaker 1: underwhelmed by his size and felt sympathetic toward people that

1350
01:10:34,240 --> 01:10:37,519
Speaker 1: screwed up when they see appiliated woodpecker. But point being,

1351
01:10:37,560 --> 01:10:41,879
Speaker 1: it went it went extinct during for many of you listening,

1352
01:10:42,280 --> 01:10:47,120
Speaker 1: It's true of me, it went stinc extinct during your parents' lifetime.

1353
01:10:48,320 --> 01:10:50,400
Speaker 1: We know we could, someone could take you out and

1354
01:10:50,439 --> 01:10:55,560
Speaker 1: show you the tree where they were last known to exist.

1355
01:10:55,800 --> 01:11:00,920
Speaker 1: The singer you heard of, singer sewing Machines YEP. Singer

1356
01:11:01,439 --> 01:11:04,639
Speaker 1: had a forest that they held, a forest it had

1357
01:11:04,640 --> 01:11:09,639
Speaker 1: ivybuild woodpeckers on it. They went to do a timber cut.

1358
01:11:10,160 --> 01:11:13,080
Speaker 1: People begged them not to. They did the timber cut.

1359
01:11:13,160 --> 01:11:16,919
Speaker 1: They actually cut a tree that ivybuild woodpeckers were using.

1360
01:11:17,560 --> 01:11:20,800
Speaker 1: They saw them fly out as the tree was I'm

1361
01:11:20,840 --> 01:11:26,120
Speaker 1: not joking, and then they were extinct. The biggest problem

1362
01:11:26,160 --> 01:11:29,679
Speaker 1: they have is just needing large old girl trees with cavities.

1363
01:11:30,040 --> 01:11:32,240
Speaker 6: Yeah, and it's a really challenging one because it is

1364
01:11:32,280 --> 01:11:34,080
Speaker 6: a reliant on that old growth hardwood.

1365
01:11:34,520 --> 01:11:37,479
Speaker 1: And I brought it up to you being like, let's

1366
01:11:38,080 --> 01:11:40,680
Speaker 1: focus on that, and you talked about how birds are

1367
01:11:40,760 --> 01:11:41,479
Speaker 1: pain in the ass.

1368
01:11:41,560 --> 01:11:42,880
Speaker 5: Yeah, birds are really.

1369
01:11:42,640 --> 01:11:44,799
Speaker 1: Why is that? Why are birds of pain in the ass.

1370
01:11:44,840 --> 01:11:47,320
Speaker 6: Obviously we're focusing on birds because we have this DODO

1371
01:11:47,400 --> 01:11:53,080
Speaker 6: project right forty pound flightless pigeon essentially from Murcius. What's

1372
01:11:53,080 --> 01:11:55,559
Speaker 6: amazing about that is it's also this sort of engine

1373
01:11:55,600 --> 01:11:59,679
Speaker 6: that's driving an investment into avian conservation science that that

1374
01:11:59,680 --> 01:12:02,360
Speaker 6: that hasn't really been there so far. In the late

1375
01:12:02,439 --> 01:12:04,800
Speaker 6: nineties we figured out cloning with Dolly the sheep, and

1376
01:12:04,840 --> 01:12:09,120
Speaker 6: now we've improved it vastly in mammals. But mammal reproduction

1377
01:12:09,200 --> 01:12:11,920
Speaker 6: is very different as you could would imagine from avian reproduction.

1378
01:12:12,920 --> 01:12:17,599
Speaker 6: So typically we would, like like I mentioned with mammalian cloning,

1379
01:12:17,640 --> 01:12:20,080
Speaker 6: we would take a skin cell and pull the nucleus

1380
01:12:20,080 --> 01:12:21,559
Speaker 6: out and put it into an egg. Well, you can't

1381
01:12:21,560 --> 01:12:23,800
Speaker 6: just drop a nucleus into a bird egg because it's

1382
01:12:23,800 --> 01:12:25,160
Speaker 6: a calcified egg and.

1383
01:12:25,080 --> 01:12:27,200
Speaker 5: You need to fertilize it while it's still in the body.

1384
01:12:28,040 --> 01:12:29,120
Speaker 5: So what you can do.

1385
01:12:30,080 --> 01:12:33,720
Speaker 6: What you can do is when you have, say in

1386
01:12:33,800 --> 01:12:37,599
Speaker 6: the case of the Dodo and Nicobar pigeon egg, that

1387
01:12:37,720 --> 01:12:40,160
Speaker 6: is you know, within about three days of fertilization, so

1388
01:12:40,520 --> 01:12:44,400
Speaker 6: early incubation stage, we can actually window the egg and

1389
01:12:44,800 --> 01:12:47,800
Speaker 6: really using really small tools, you can pull a couple

1390
01:12:47,800 --> 01:12:50,160
Speaker 6: of micro leaders of blood out. And what's really unique

1391
01:12:50,160 --> 01:12:57,680
Speaker 6: about avian reproduction and development is that they're sorts the

1392
01:12:57,840 --> 01:13:01,400
Speaker 6: cells that pre date sperm and egg on primordi oalderam cells.

1393
01:13:01,760 --> 01:13:04,680
Speaker 6: They're floating around freely in the in the bloodstream, and

1394
01:13:04,720 --> 01:13:06,960
Speaker 6: then they migrate to the gonads and that's where they

1395
01:13:06,960 --> 01:13:11,280
Speaker 6: begin to make you know, adult sperm and egg. While

1396
01:13:11,280 --> 01:13:15,160
Speaker 6: they're still floating within the within the bloodstream, we can

1397
01:13:15,200 --> 01:13:18,280
Speaker 6: pull those microleader to a blood out and culture those

1398
01:13:18,479 --> 01:13:20,920
Speaker 6: we call PGCs primarial dram cells, and.

1399
01:13:20,920 --> 01:13:21,840
Speaker 5: Use those to edit.

1400
01:13:22,760 --> 01:13:26,280
Speaker 6: And then we take those edited PGCs that are now

1401
01:13:26,360 --> 01:13:30,800
Speaker 6: not making chicken or pigeon, they're making Dodo sperm and egg,

1402
01:13:31,120 --> 01:13:35,280
Speaker 6: and put them back into the surrogate egg of a

1403
01:13:35,400 --> 01:13:39,000
Speaker 6: of a sterilized like say chicken or pigeon line. And

1404
01:13:39,040 --> 01:13:41,560
Speaker 6: then there those cells will migrate into their gonads and

1405
01:13:41,600 --> 01:13:45,160
Speaker 6: suddenly have this nicobar pigeon that's actually creating Dodo sperm

1406
01:13:45,360 --> 01:13:48,840
Speaker 6: or egg. The two pigeons will mate and they'll make

1407
01:13:48,880 --> 01:13:49,280
Speaker 6: a Dodo.

1408
01:13:49,880 --> 01:13:51,519
Speaker 3: Oh my goodness, how are they making it?

1409
01:13:52,080 --> 01:13:53,920
Speaker 5: Yeah?

1410
01:13:54,080 --> 01:13:55,080
Speaker 1: I was picturing the vent.

1411
01:13:56,040 --> 01:13:57,400
Speaker 6: So this is why, you know, one of one of

1412
01:13:57,400 --> 01:13:59,759
Speaker 6: the things we talk about is, you know, pigeons, probably

1413
01:14:00,200 --> 01:14:03,599
Speaker 6: our pigeons will be the genomic donner. The actual animal

1414
01:14:03,640 --> 01:14:06,840
Speaker 6: serga would be a large hen chicken. Yeah, it's not

1415
01:14:06,880 --> 01:14:10,120
Speaker 6: even that big. I mean there are there are domestic

1416
01:14:10,360 --> 01:14:13,720
Speaker 6: breeds of chickens way too. Yeah, you don't need that

1417
01:14:13,800 --> 01:14:16,400
Speaker 6: big now, So so we could so we could use

1418
01:14:16,400 --> 01:14:17,240
Speaker 6: it that chicken.

1419
01:14:16,960 --> 01:14:19,920
Speaker 1: Line, domestic chicken that could handle a egg like that. Uh.

1420
01:14:20,479 --> 01:14:23,200
Speaker 3: It just dawned on me that you have got to

1421
01:14:23,200 --> 01:14:29,479
Speaker 3: be spending as much time, if not more, on eradicating species, Yeah,

1422
01:14:29,520 --> 01:14:33,000
Speaker 3: as opposed to creating. Because I think of the big

1423
01:14:33,040 --> 01:14:35,640
Speaker 3: island of Hawaii. You're gonna have to get rid of

1424
01:14:36,439 --> 01:14:39,960
Speaker 3: introduced mongoose. You're gonna have to get which they've proven

1425
01:14:40,000 --> 01:14:44,120
Speaker 3: that they can't. Right, You're gonna have to get rid

1426
01:14:44,160 --> 01:14:47,320
Speaker 3: of mosquitoes, right, You're gonna have to get rid rid

1427
01:14:47,360 --> 01:14:50,599
Speaker 3: of snakes. You're gonna have to get rid of feral cats,

1428
01:14:50,800 --> 01:14:55,120
Speaker 3: which people are gonna love my crowd is at least.

1429
01:14:55,520 --> 01:14:57,800
Speaker 3: I mean, all of that has got to get done

1430
01:14:58,680 --> 01:15:04,639
Speaker 3: before you put this new experimental species back on the ground.

1431
01:15:04,720 --> 01:15:04,920
Speaker 6: Right.

1432
01:15:04,960 --> 01:15:08,880
Speaker 1: Well, they're developing tools that As they're developing tools, it

1433
01:15:08,920 --> 01:15:11,679
Speaker 1: could be helpful for that, right, Yeah, which are also

1434
01:15:11,800 --> 01:15:14,720
Speaker 1: subject to all kinds of scrutiny biocontrols.

1435
01:15:14,880 --> 01:15:18,840
Speaker 6: Yeah, you know, and I would say we regionally are

1436
01:15:18,880 --> 01:15:22,519
Speaker 6: targeted eradications. Right, just to be clear, you know, we

1437
01:15:22,560 --> 01:15:26,160
Speaker 6: don't want to just make all any mangoo species but

1438
01:15:26,320 --> 01:15:27,400
Speaker 6: poof off the face of the earth.

1439
01:15:27,479 --> 01:15:28,959
Speaker 5: Right, it needs to be in Hawaii.

1440
01:15:29,000 --> 01:15:33,120
Speaker 6: And so the habitat remediation work that has to occurb

1441
01:15:33,240 --> 01:15:37,800
Speaker 6: ahead of rewilding your species reintroduction is as important as

1442
01:15:37,840 --> 01:15:40,439
Speaker 6: the extinction. And that's why you know, we have such

1443
01:15:40,439 --> 01:15:43,479
Speaker 6: a large conservation focus of the company. That's why a

1444
01:15:43,520 --> 01:15:46,200
Speaker 6: big part of the job that me and my team

1445
01:15:46,200 --> 01:15:50,040
Speaker 6: have been tasked with is is going in forming partnerships

1446
01:15:50,040 --> 01:15:54,519
Speaker 6: with local stakeholders, local NGOs and governments and international NGOs

1447
01:15:54,640 --> 01:15:57,559
Speaker 6: so we can begin to pair habitats. You know, in

1448
01:15:57,600 --> 01:15:59,760
Speaker 6: a three weeks time, I'm jumping on a plane and

1449
01:15:59,760 --> 01:16:01,920
Speaker 6: flaming into Mauritius. I'm going to go there to meet

1450
01:16:01,960 --> 01:16:04,559
Speaker 6: with our partners at Marsian Wildlife Foundation to talk just

1451
01:16:04,600 --> 01:16:07,439
Speaker 6: about this. What are the islands around surrounding Mauritius that

1452
01:16:07,479 --> 01:16:11,759
Speaker 6: currently have invasive species that we would need to remove.

1453
01:16:11,960 --> 01:16:14,719
Speaker 6: And it's not just animals, it's also plants. Plant invasives

1454
01:16:14,720 --> 01:16:16,799
Speaker 6: are as bad as you you know, you could imagine.

1455
01:16:16,880 --> 01:16:19,799
Speaker 1: I mean, in order to begin grooming the landscape for dodos.

1456
01:16:19,880 --> 01:16:20,639
Speaker 5: Yeah, you can't.

1457
01:16:20,680 --> 01:16:22,680
Speaker 6: There's no sense in putting a dodo, which is a

1458
01:16:22,680 --> 01:16:25,360
Speaker 6: ground dwelling, ground nesting bird, in a place that the

1459
01:16:25,400 --> 01:16:28,519
Speaker 6: macaque was it, which was introduced by the Dutch. Is

1460
01:16:28,600 --> 01:16:30,559
Speaker 6: that monkey is still present where it's going to raid

1461
01:16:30,560 --> 01:16:32,920
Speaker 6: the nests and eat the eggs. We need to remove

1462
01:16:32,960 --> 01:16:35,639
Speaker 6: the macacus before we introduce the dodo. So those are

1463
01:16:35,720 --> 01:16:38,639
Speaker 6: sort of the issues. But also the dodo had specific

1464
01:16:38,680 --> 01:16:42,439
Speaker 6: dietary requirements and native plants are important, but you know,

1465
01:16:42,520 --> 01:16:44,960
Speaker 6: there's been a lot of introduced plant life there, so

1466
01:16:45,000 --> 01:16:47,080
Speaker 6: we have to also work with the amazing work that

1467
01:16:47,160 --> 01:16:49,400
Speaker 6: Marcian Wildlife Foundation has been doing to date. We're just

1468
01:16:49,560 --> 01:16:52,320
Speaker 6: trying to provide more tools, more funding, more more resources

1469
01:16:52,320 --> 01:16:55,479
Speaker 6: so that we can really make a difference before our doto,

1470
01:16:55,520 --> 01:16:56,920
Speaker 6: because the worst thing we could do is sit there

1471
01:16:56,920 --> 01:16:58,800
Speaker 6: with the dodo and not have a place to put

1472
01:16:58,800 --> 01:17:00,680
Speaker 6: it right. Then that's a that's as much of a

1473
01:17:00,680 --> 01:17:02,320
Speaker 6: failure as missing the target altogether.

1474
01:17:02,439 --> 01:17:05,840
Speaker 7: Well, the flip side of that is in some way

1475
01:17:05,920 --> 01:17:10,080
Speaker 7: having that Dodo ready to go incentivizes that work in

1476
01:17:10,120 --> 01:17:13,160
Speaker 7: a way that there isn't currently maybe as strong an

1477
01:17:13,200 --> 01:17:15,639
Speaker 7: impetus to take those stuffs.

1478
01:17:15,880 --> 01:17:18,040
Speaker 6: Yeah, I'm happy you called that out because I think

1479
01:17:18,080 --> 01:17:21,880
Speaker 6: one of the really amazing things about the Dodo in particular,

1480
01:17:21,880 --> 01:17:25,040
Speaker 6: but all the species that we're working on, is this

1481
01:17:25,120 --> 01:17:27,880
Speaker 6: idea that they become these shining lights of inspiration and

1482
01:17:28,240 --> 01:17:32,080
Speaker 6: to really help focus efforts back into habitat remediation and

1483
01:17:32,560 --> 01:17:36,559
Speaker 6: invasive removals and things like that. So you know, people say, well,

1484
01:17:36,560 --> 01:17:39,519
Speaker 6: what ecosystem function did the dodo provide? Well, it's not

1485
01:17:39,600 --> 01:17:42,639
Speaker 6: as critical as say an apex predator like the Tasmani tiger,

1486
01:17:42,800 --> 01:17:46,439
Speaker 6: but it does bring interest to a biodiversity hotspot to

1487
01:17:46,520 --> 01:17:50,840
Speaker 6: help bring funding, to help bring attention to repairing those

1488
01:17:50,880 --> 01:17:54,360
Speaker 6: ecosystems and preparing and preparing them for a Dodo means

1489
01:17:54,360 --> 01:17:58,320
Speaker 6: also improving life for so many other endemic species of

1490
01:17:58,360 --> 01:17:59,360
Speaker 6: the island immercies.

1491
01:17:59,720 --> 01:18:02,760
Speaker 3: Well, I mean just think of the eco tourism dollars right, Like,

1492
01:18:02,800 --> 01:18:05,800
Speaker 3: so there's incentive there, but there's also going to be

1493
01:18:05,840 --> 01:18:09,759
Speaker 3: the battle of like, uh, we can't build a hotel

1494
01:18:09,840 --> 01:18:10,200
Speaker 3: right there.

1495
01:18:11,080 --> 01:18:15,840
Speaker 1: Yeah, what's funny about the eco tourism aspect of it is, uh,

1496
01:18:16,200 --> 01:18:20,080
Speaker 1: you know, kids trip out about dinosaurs. They were so drastic.

1497
01:18:20,160 --> 01:18:23,160
Speaker 1: Part well, yeah, but you'd be like, but but you

1498
01:18:23,200 --> 01:18:26,640
Speaker 1: know what, man, the biggest animal to ever exist on

1499
01:18:26,720 --> 01:18:30,800
Speaker 1: Earth exists right now, ye, And why are you not

1500
01:18:30,880 --> 01:18:33,760
Speaker 1: eager to go look at that? It's there right now?

1501
01:18:33,800 --> 01:18:37,240
Speaker 1: Because it's the animal to ever exist on Earth is

1502
01:18:37,240 --> 01:18:39,000
Speaker 1: alive right now. And everyone wants to tell me how

1503
01:18:39,040 --> 01:18:42,720
Speaker 1: big dinosaurs were as that not as big as a

1504
01:18:42,760 --> 01:18:43,320
Speaker 1: blue whale?

1505
01:18:43,920 --> 01:18:48,160
Speaker 2: Right, Yeah, you've kind of gotten at this a little bit.

1506
01:18:48,240 --> 01:18:55,160
Speaker 2: But why why instead of Tasmanian tigers and dodos, instead

1507
01:18:55,160 --> 01:18:58,440
Speaker 2: of making them, why not make a bunch of California

1508
01:18:58,439 --> 01:19:03,840
Speaker 2: condors and Siberian tiger like now to help them? Now

1509
01:19:04,200 --> 01:19:06,599
Speaker 2: you know, obviously it's not like right now, but.

1510
01:19:06,880 --> 01:19:08,920
Speaker 6: Yeah, I would say it's not an either or proposition

1511
01:19:09,000 --> 01:19:13,120
Speaker 6: for us. It is use these these really compelling case

1512
01:19:13,160 --> 01:19:16,320
Speaker 6: studies to help drive the research, drive the investment to

1513
01:19:16,360 --> 01:19:18,679
Speaker 6: be able to apply it immediately to California condor.

1514
01:19:18,960 --> 01:19:20,800
Speaker 5: We've been meeting with, you know, we have.

1515
01:19:21,160 --> 01:19:23,000
Speaker 6: We'll be making this big announcement about some of our

1516
01:19:23,000 --> 01:19:25,479
Speaker 6: focus on North American species coming up here probably about

1517
01:19:25,479 --> 01:19:27,720
Speaker 6: the time this podcast drops. And one of those is

1518
01:19:27,760 --> 01:19:30,439
Speaker 6: also to work with Native American tribes and work in

1519
01:19:30,520 --> 01:19:34,439
Speaker 6: Indian country where they're already doing amazing conservation and and

1520
01:19:34,479 --> 01:19:37,400
Speaker 6: what's happening with California condor, and now there's reintroduction efforts

1521
01:19:37,400 --> 01:19:40,280
Speaker 6: that are being focused on in Idaho and as person,

1522
01:19:40,280 --> 01:19:43,080
Speaker 6: and I think that's where we want to begin to focus.

1523
01:19:43,120 --> 01:19:45,280
Speaker 5: So we have these toolkits.

1524
01:19:45,000 --> 01:19:47,679
Speaker 6: And there are already amazing groups working on California condor.

1525
01:19:47,720 --> 01:19:50,360
Speaker 6: There's so much attention on tigers, right, we can focus

1526
01:19:50,439 --> 01:19:53,040
Speaker 6: other places that great tools that then begin to bleed

1527
01:19:53,080 --> 01:19:55,479
Speaker 6: over and can be optimized back to those other species.

1528
01:19:55,720 --> 01:19:58,320
Speaker 6: So we're creating open source tools that are free to

1529
01:19:58,360 --> 01:20:01,960
Speaker 6: the conservation world. As we unlocked primordial germs, hell derivation

1530
01:20:02,040 --> 01:20:04,599
Speaker 6: and editing, we'll just give that to the California contour

1531
01:20:04,720 --> 01:20:07,360
Speaker 6: people or will help support it ourselves.

1532
01:20:07,720 --> 01:20:10,880
Speaker 1: When I'm having when when I'm talking about with with

1533
01:20:11,120 --> 01:20:17,840
Speaker 1: friends about colossal uh, I never use this term, but

1534
01:20:18,439 --> 01:20:24,400
Speaker 1: in explaining it immediately everybody says, oh, Jurrassic Park. Yeah.

1535
01:20:24,479 --> 01:20:26,439
Speaker 6: The fact that we're an hour into this and this

1536
01:20:26,479 --> 01:20:27,920
Speaker 6: is the first time it came up might be a

1537
01:20:28,000 --> 01:20:28,760
Speaker 6: world I've.

1538
01:20:30,360 --> 01:20:32,400
Speaker 1: Been holding my tongue and I'm not bringing it up

1539
01:20:32,439 --> 01:20:34,400
Speaker 1: to have that conversation, but I am bringing up to

1540
01:20:34,400 --> 01:20:40,640
Speaker 1: do this. We We talked about mingus. Oh, did you

1541
01:20:40,640 --> 01:20:42,800
Speaker 1: want to say more about holding your tongue? No, No,

1542
01:20:42,840 --> 01:20:44,679
Speaker 1: I I just been wanting to say that word.

1543
01:20:44,840 --> 01:20:47,080
Speaker 3: I can Trassic park.

1544
01:20:47,120 --> 01:20:50,920
Speaker 1: Well, I'm gonna all right. Please please If you don't

1545
01:20:50,960 --> 01:20:53,000
Speaker 1: like my approach, no, I am not to answer it.

1546
01:20:53,080 --> 01:20:55,479
Speaker 7: I'm I'm I'm following along. I thought we were just

1547
01:20:55,479 --> 01:20:56,120
Speaker 7: going to dig in.

1548
01:20:56,640 --> 01:20:58,800
Speaker 1: No, we're going We're going right now. I'm following a

1549
01:20:58,800 --> 01:21:02,559
Speaker 1: part of it. We talked about mingus, where we go

1550
01:21:03,040 --> 01:21:06,920
Speaker 1: pluck blood from mingus. We talked about a marine mammal,

1551
01:21:06,960 --> 01:21:10,280
Speaker 1: an imperiled marine mammal, where you go and just shoot it,

1552
01:21:10,360 --> 01:21:12,400
Speaker 1: get a plug out of it, like some kind of

1553
01:21:12,439 --> 01:21:16,479
Speaker 1: little surgical thing that you fire from a blowgun or

1554
01:21:16,520 --> 01:21:19,639
Speaker 1: a drone or whatever, and get a little thing plug,

1555
01:21:19,640 --> 01:21:22,920
Speaker 1: a hide off them, and you got that so living.

1556
01:21:24,280 --> 01:21:26,920
Speaker 1: We talked about what we have when we find a

1557
01:21:27,000 --> 01:21:31,680
Speaker 1: frozen you know, come thawing out of the permafrost, A

1558
01:21:32,120 --> 01:21:35,160
Speaker 1: mammoth that may be froze within hours of death or

1559
01:21:35,200 --> 01:21:39,760
Speaker 1: within days of death, has been frozen ever since, right,

1560
01:21:39,840 --> 01:21:43,040
Speaker 1: and we get it, and you'd still see like blood

1561
01:21:43,080 --> 01:21:46,600
Speaker 1: clots where something bit it, and you see what it

1562
01:21:46,760 --> 01:21:50,479
Speaker 1: ate last and it's still got vegetation in its teeth, right,

1563
01:21:52,880 --> 01:21:55,559
Speaker 1: But what happens when we get back to the t rex?

1564
01:21:56,800 --> 01:22:01,080
Speaker 1: Like what don't you have and what is the likelihood

1565
01:22:01,080 --> 01:22:02,000
Speaker 1: you'd ever find it?

1566
01:22:02,360 --> 01:22:04,400
Speaker 6: Well, the first thing we don't have is an interest

1567
01:22:04,439 --> 01:22:05,320
Speaker 6: in dinosaurs.

1568
01:22:05,400 --> 01:22:08,720
Speaker 1: Just okay, I mean I don't mean you, I don't

1569
01:22:08,760 --> 01:22:11,640
Speaker 1: mean a collective week what would stop somebody.

1570
01:22:11,600 --> 01:22:13,760
Speaker 3: Just like a big donor comes down?

1571
01:22:14,080 --> 01:22:17,960
Speaker 1: Okay, Yeah, I just be like, yeah, human understanding of course,

1572
01:22:18,040 --> 01:22:21,200
Speaker 1: like what is not don't I know something's not there?

1573
01:22:21,240 --> 01:22:22,040
Speaker 1: But what is not there?

1574
01:22:22,040 --> 01:22:24,479
Speaker 5: We don't have DNA okay, and just don't.

1575
01:22:24,840 --> 01:22:28,160
Speaker 6: So even if you know, typically most of the dinosaur

1576
01:22:28,200 --> 01:22:30,200
Speaker 6: specimens we would uncover our fossils.

1577
01:22:30,280 --> 01:22:33,280
Speaker 5: So those are rocks that took the place.

1578
01:22:33,320 --> 01:22:36,519
Speaker 6: Of a bone, right, So there's no DNA in that rock,

1579
01:22:37,479 --> 01:22:40,120
Speaker 6: so you can't even sequence it if you were to

1580
01:22:40,200 --> 01:22:44,440
Speaker 6: find a very well preserved sixty five million year old specimen.

1581
01:22:45,080 --> 01:22:46,880
Speaker 5: Time is still an enemy UV and.

1582
01:22:46,840 --> 01:22:52,080
Speaker 6: Temperature and bacteria contamination is still an enemy to DNA integrity.

1583
01:22:52,439 --> 01:22:55,320
Speaker 6: So even if when we talk about nineteen thirty six,

1584
01:22:55,600 --> 01:22:59,000
Speaker 6: we talked about highly degraded DNA, it takes incredible amounts

1585
01:22:59,040 --> 01:23:03,040
Speaker 6: of genomic sequencing, and so much brute force to sequence

1586
01:23:03,040 --> 01:23:04,840
Speaker 6: that over and over. If you think about over time,

1587
01:23:05,240 --> 01:23:08,760
Speaker 6: DNA starts as a single strand, just as an oversimplification

1588
01:23:09,240 --> 01:23:11,639
Speaker 6: starts as a single strand over time, it just cuts

1589
01:23:11,680 --> 01:23:13,479
Speaker 6: in half once, cuts in half twice, and it just

1590
01:23:13,520 --> 01:23:14,759
Speaker 6: that process repeats.

1591
01:23:14,920 --> 01:23:16,000
Speaker 5: So you go from maybe in.

1592
01:23:16,000 --> 01:23:18,679
Speaker 6: Nineteen thirty six we had a five hundred piece puzzle

1593
01:23:18,760 --> 01:23:22,280
Speaker 6: that we had to use artificial intelligence and computational biology

1594
01:23:22,360 --> 01:23:23,920
Speaker 6: to put back in order to.

1595
01:23:23,880 --> 01:23:24,639
Speaker 5: Make that puzzle.

1596
01:23:25,160 --> 01:23:27,160
Speaker 6: If you go back sixty five million years ago, it

1597
01:23:27,200 --> 01:23:29,599
Speaker 6: might be a five trillion piece puzzle.

1598
01:23:30,080 --> 01:23:30,880
Speaker 1: You just have dust.

1599
01:23:31,080 --> 01:23:35,400
Speaker 6: Yeah, it's so hard. The other side of it is

1600
01:23:35,439 --> 01:23:37,960
Speaker 6: we don't actually have a reference gam so you'll hear

1601
01:23:38,040 --> 01:23:41,320
Speaker 6: us talk about reference genomes a lot of a living relative.

1602
01:23:41,640 --> 01:23:43,519
Speaker 6: One of the ways that we solve those puzzles when

1603
01:23:43,560 --> 01:23:46,479
Speaker 6: we have these highly degraded DNA samples is we find

1604
01:23:46,479 --> 01:23:49,479
Speaker 6: something that's closely related and we go, oh, so it's

1605
01:23:49,520 --> 01:23:50,680
Speaker 6: sort of like a cheat sheet. You know what the

1606
01:23:50,680 --> 01:23:53,000
Speaker 6: puzzle should look like. So you know, oh, well the

1607
01:23:53,040 --> 01:23:54,960
Speaker 6: green sections up here, so I'm going to put this

1608
01:23:55,000 --> 01:23:56,880
Speaker 6: over here. And that's what the AI is doing, and

1609
01:23:56,920 --> 01:24:00,240
Speaker 6: the computational biologist they're working on with dinosaur is that

1610
01:24:00,320 --> 01:24:01,719
Speaker 6: just doesn't doesn't exist.

1611
01:24:02,000 --> 01:24:06,960
Speaker 1: So this is not acknowledging that this is not your

1612
01:24:06,960 --> 01:24:08,720
Speaker 1: area of folks. I mean, this is not a thing

1613
01:24:08,760 --> 01:24:10,439
Speaker 1: that's good. This is not a problem that's going to

1614
01:24:10,479 --> 01:24:11,040
Speaker 1: be overcome.

1615
01:24:12,120 --> 01:24:13,599
Speaker 5: No, not not.

1616
01:24:13,680 --> 01:24:17,360
Speaker 7: Tried looking for dino blood in mosquitoes preserved amber and

1617
01:24:17,360 --> 01:24:19,719
Speaker 7: then using the DNA of a West African tree frog

1618
01:24:19,800 --> 01:24:20,559
Speaker 7: to splice it in.

1619
01:24:21,240 --> 01:24:22,080
Speaker 1: And what was that?

1620
01:24:22,160 --> 01:24:25,120
Speaker 6: A loosing uh you know, you give them a loosinge dependency.

1621
01:24:25,160 --> 01:24:28,679
Speaker 7: Doctor Henry Wu figured all that out under the tutelage

1622
01:24:28,720 --> 01:24:29,400
Speaker 7: of John Hammond.

1623
01:24:29,560 --> 01:24:32,320
Speaker 6: I think Beth Shapiro from our team has actually shown

1624
01:24:32,360 --> 01:24:34,440
Speaker 6: that ambers are really poor.

1625
01:24:35,800 --> 01:24:40,280
Speaker 5: To good actually looked.

1626
01:24:40,040 --> 01:24:42,120
Speaker 6: Into it, which is amazing. I think that's why she's

1627
01:24:42,160 --> 01:24:43,000
Speaker 6: so so cool.

1628
01:24:43,000 --> 01:24:45,439
Speaker 1: But so people can put that out of their minds.

1629
01:24:45,560 --> 01:24:47,120
Speaker 5: Take it out of your mind in.

1630
01:24:47,040 --> 01:24:47,720
Speaker 1: The case.

1631
01:24:49,800 --> 01:24:54,800
Speaker 3: It's you know, they're that the plight of that little

1632
01:24:54,840 --> 01:24:57,920
Speaker 3: marine mammal is tied to fishing practices.

1633
01:24:58,280 --> 01:24:59,559
Speaker 1: Well do you know about this thing?

1634
01:25:00,200 --> 01:25:00,439
Speaker 3: Yeah?

1635
01:25:00,520 --> 01:25:02,599
Speaker 1: I was so embarrassed you showed me pic. I never

1636
01:25:03,360 --> 01:25:05,680
Speaker 1: even heard of the son of a Bitch. I looked

1637
01:25:05,720 --> 01:25:07,360
Speaker 1: at the picture and I've never seen it.

1638
01:25:07,439 --> 01:25:10,120
Speaker 3: Oh, I mean, yeah, there's a lot of Yeah, that's

1639
01:25:10,160 --> 01:25:14,040
Speaker 3: what a lot of people can't say, eat, live, and breathe,

1640
01:25:14,240 --> 01:25:17,000
Speaker 3: but they live and breathe. That animal I've never heard of.

1641
01:25:17,200 --> 01:25:18,759
Speaker 3: It's clocks ticks.

1642
01:25:18,640 --> 01:25:21,599
Speaker 6: The world's most dandered mareen mammal, and it is, you know,

1643
01:25:21,720 --> 01:25:25,040
Speaker 6: like anime level charisma. Right, It's one of the cutest

1644
01:25:25,040 --> 01:25:26,920
Speaker 6: things you'll ever see in your life.

1645
01:25:28,240 --> 01:25:31,160
Speaker 3: But you know, like if if I were in your

1646
01:25:31,240 --> 01:25:34,880
Speaker 3: shoes and you're like, okay, we have it in the

1647
01:25:35,280 --> 01:25:40,200
Speaker 3: in the bank, what there's no point in bringing it

1648
01:25:40,240 --> 01:25:43,000
Speaker 3: back right now until these fishing practices change.

1649
01:25:43,040 --> 01:25:44,960
Speaker 6: No, But that's the beauty of biobanking, is the idea

1650
01:25:45,000 --> 01:25:47,720
Speaker 6: is we need to take snapshots today, what is the

1651
01:25:47,720 --> 01:25:51,040
Speaker 6: biodiversity that exists, and not just the Noah's ark of

1652
01:25:51,080 --> 01:25:51,679
Speaker 6: one by one.

1653
01:25:51,720 --> 01:25:53,280
Speaker 5: We don't need one male and one female.

1654
01:25:53,320 --> 01:25:57,040
Speaker 6: We need the largest population representation we can get. Unfortunately,

1655
01:25:57,280 --> 01:26:00,599
Speaker 6: with this species of akida, there's only thirteen. But ideally

1656
01:26:00,640 --> 01:26:03,680
Speaker 6: somebody could go out and get thirteen, all thirteen biobanked,

1657
01:26:03,680 --> 01:26:06,000
Speaker 6: and that would give us the opportunity that if in

1658
01:26:06,320 --> 01:26:09,320
Speaker 6: ten twenty one hundred, one thousand years we finally figured

1659
01:26:09,320 --> 01:26:12,519
Speaker 6: out all of the you know, socio political pressures that

1660
01:26:12,560 --> 01:26:15,880
Speaker 6: are driving the extinction of the species, then it could

1661
01:26:15,880 --> 01:26:17,160
Speaker 6: be resored, which is amazing.

1662
01:26:17,680 --> 01:26:22,680
Speaker 3: But the human the conundrum right is like if you

1663
01:26:22,800 --> 01:26:25,560
Speaker 3: have that approach of like, okay, we got on biobanked,

1664
01:26:26,400 --> 01:26:29,360
Speaker 3: these people aren't going to change, We'll wait till it changes.

1665
01:26:29,880 --> 01:26:32,479
Speaker 3: Will it change with the absence of that animal?

1666
01:26:32,840 --> 01:26:34,599
Speaker 6: I think similar to what we're talking about the DOTO,

1667
01:26:34,680 --> 01:26:37,559
Speaker 6: it actually provides an inspiration to accelerate the change and

1668
01:26:37,600 --> 01:26:40,360
Speaker 6: push you know, we talked about the moral hazard a lot,

1669
01:26:40,400 --> 01:26:42,880
Speaker 6: which is this idea that if we have a technology

1670
01:26:43,040 --> 01:26:46,680
Speaker 6: that can mean extinction is not forever, will people care

1671
01:26:46,760 --> 01:26:47,639
Speaker 6: less about extinction?

1672
01:26:47,880 --> 01:26:49,160
Speaker 1: Oh yeah, I we'll get to you later.

1673
01:26:49,439 --> 01:26:49,840
Speaker 4: Yeah yeah.

1674
01:26:49,960 --> 01:26:53,560
Speaker 6: But my argument is they're already doing that, right. The

1675
01:26:53,960 --> 01:26:57,240
Speaker 6: level of care about the biodiversity loss is shockingly low.

1676
01:26:57,680 --> 01:26:59,960
Speaker 6: So we need to figure out tools to make sure

1677
01:27:00,080 --> 01:27:03,479
Speaker 6: that we can begin to reverse extinctions because nobody else cares.

1678
01:27:03,600 --> 01:27:05,440
Speaker 5: And I know that's a.

1679
01:27:05,240 --> 01:27:08,720
Speaker 6: Very broad statement, but to be fair, the amount of

1680
01:27:08,760 --> 01:27:12,280
Speaker 6: investment that goes into conservation is just we should all

1681
01:27:12,320 --> 01:27:14,600
Speaker 6: be ashamed. You know, the Pulse And Institute did this

1682
01:27:14,680 --> 01:27:18,639
Speaker 6: amazing research study into conservation, spending a couple of years

1683
01:27:18,680 --> 01:27:22,760
Speaker 6: back and what they found is that on average, annually,

1684
01:27:22,880 --> 01:27:26,719
Speaker 6: between philanthropy and government spending on the conservation of endangered

1685
01:27:26,760 --> 01:27:29,519
Speaker 6: species the globe globally, we spend about one hundred and

1686
01:27:29,560 --> 01:27:34,040
Speaker 6: seventy five billion dollars a year. They also did an

1687
01:27:34,120 --> 01:27:36,680
Speaker 6: estimate of what would the investment take to stop the

1688
01:27:36,720 --> 01:27:40,120
Speaker 6: biodiversity crisis or reverse it, and that's nine hundred billion

1689
01:27:40,160 --> 01:27:43,120
Speaker 6: dollars a year, which really, if you think about defense

1690
01:27:43,160 --> 01:27:45,200
Speaker 6: spending or some other you know, you can find another

1691
01:27:45,240 --> 01:27:46,320
Speaker 6: way to contextualize that.

1692
01:27:46,600 --> 01:27:47,679
Speaker 5: It's not a ton of money.

1693
01:27:48,960 --> 01:27:49,200
Speaker 1: You know.

1694
01:27:49,520 --> 01:27:51,800
Speaker 6: Stefano on my team gave me this amazing quote that

1695
01:27:52,080 --> 01:27:54,320
Speaker 6: every year the globe spends four hundred and eighty billion

1696
01:27:54,360 --> 01:27:55,240
Speaker 6: dollars on soda.

1697
01:27:57,360 --> 01:27:58,400
Speaker 3: What would you rather have?

1698
01:27:58,920 --> 01:28:02,240
Speaker 6: Yeah, that's that's not that's not to acknowledge maybe all

1699
01:28:02,240 --> 01:28:06,120
Speaker 6: the downstream health care cost right and things like that.

1700
01:28:06,160 --> 01:28:09,280
Speaker 6: So it just shows you that unfortunately, the level of

1701
01:28:09,280 --> 01:28:11,240
Speaker 6: interest and investment is so low today that I don't

1702
01:28:11,280 --> 01:28:13,599
Speaker 6: think the moral hazard is a real value, valid valid

1703
01:28:13,680 --> 01:28:16,160
Speaker 6: argument because people do not care enough today.

1704
01:28:16,680 --> 01:28:19,479
Speaker 2: If you had, I was gonna say, if you want

1705
01:28:19,479 --> 01:28:22,360
Speaker 2: to get hunters interested, you need to look into the

1706
01:28:22,400 --> 01:28:24,639
Speaker 2: Irish Elk put that on your list.

1707
01:28:25,160 --> 01:28:27,879
Speaker 1: So I've got to get bod get behind that one.

1708
01:28:28,600 --> 01:28:30,080
Speaker 1: I've got just to get a look at one.

1709
01:28:30,160 --> 01:28:34,080
Speaker 6: I've got this dream list going and yeah, if you

1710
01:28:34,120 --> 01:28:36,720
Speaker 6: could do anything in the world for me, it's not dinosaurs,

1711
01:28:36,760 --> 01:28:39,280
Speaker 6: it is it's ungulates. That's where I found my passion

1712
01:28:39,720 --> 01:28:42,840
Speaker 6: for for conservation, primarily in Africa. But you know Irish

1713
01:28:42,880 --> 01:28:45,320
Speaker 6: elk Is, you know you look at a twelve foot

1714
01:28:45,479 --> 01:28:49,439
Speaker 6: span of vantler, right, like just insane, so tall and

1715
01:28:49,479 --> 01:28:52,000
Speaker 6: so big that when the force started growing and they

1716
01:28:52,120 --> 01:28:53,880
Speaker 6: they that's what was pushing them out of their habite

1717
01:28:53,880 --> 01:28:57,360
Speaker 6: because they couldn't even fit between trees, like just an amazing.

1718
01:28:57,000 --> 01:28:58,679
Speaker 3: The shed hunting world would just poof.

1719
01:28:58,720 --> 01:29:13,519
Speaker 1: They let me hit you with the one here, uh,

1720
01:29:13,880 --> 01:29:16,679
Speaker 1: because we would Brody mentioned like, why not go focus

1721
01:29:16,720 --> 01:29:21,840
Speaker 1: on Siberian tigers? Okay, so let's talk about Siberian tigers

1722
01:29:21,840 --> 01:29:26,839
Speaker 1: from it. How many are there? Roughly less than a thousand?

1723
01:29:26,880 --> 01:29:28,519
Speaker 5: Correct, Yeah, it's easily.

1724
01:29:29,360 --> 01:29:38,240
Speaker 1: So let's say you did cultivate a population and you

1725
01:29:38,320 --> 01:29:40,160
Speaker 1: and you worked up where you got a dozen of

1726
01:29:40,160 --> 01:29:46,080
Speaker 1: them cloned Siberian tigers. Could you ever get so comfortable

1727
01:29:46,960 --> 01:29:52,519
Speaker 1: with what you'd created that you would not as that

1728
01:29:52,760 --> 01:29:58,479
Speaker 1: you would cut them loose and let them integrate into

1729
01:29:58,479 --> 01:30:03,240
Speaker 1: that population in breeding. Yes, you could. You could get

1730
01:30:03,280 --> 01:30:05,840
Speaker 1: so you could get comfortable that you weren't having some

1731
01:30:05,960 --> 01:30:10,639
Speaker 1: reticence that like, dude, I don't know, maybe there's something

1732
01:30:10,680 --> 01:30:13,080
Speaker 1: I'm not seeing and this is going to be the

1733
01:30:13,640 --> 01:30:14,880
Speaker 1: final death knell.

1734
01:30:15,160 --> 01:30:18,400
Speaker 7: And relatedly, are you able to fiddle around enough that

1735
01:30:18,439 --> 01:30:21,639
Speaker 7: you don't have concerns about genetic bottlenecks if you're bringing

1736
01:30:21,720 --> 01:30:24,400
Speaker 7: twelve tigers out of a lab, like you're going in

1737
01:30:24,400 --> 01:30:27,120
Speaker 7: there and kind of buzzing around the edges.

1738
01:30:27,160 --> 01:30:29,599
Speaker 1: Yeah, because if they're all gone, you know, you talked

1739
01:30:29,600 --> 01:30:32,479
Speaker 1: about like like de extinction. If they're all gone, there

1740
01:30:32,560 --> 01:30:35,840
Speaker 1: becomes like a what's to lose? Like, you know, if

1741
01:30:36,120 --> 01:30:38,840
Speaker 1: if you do the dodo and you want to find

1742
01:30:38,840 --> 01:30:40,880
Speaker 1: in appropriate habitat, you do all the work, you put

1743
01:30:40,920 --> 01:30:43,320
Speaker 1: dodos out and yeah, like there's a thing you hadn't

1744
01:30:43,320 --> 01:30:45,719
Speaker 1: thought of which is totally possible, and it didn't work,

1745
01:30:45,960 --> 01:30:49,080
Speaker 1: you'd be like, oh, we didn't have them before, we

1746
01:30:49,120 --> 01:30:51,400
Speaker 1: don't have them now, what can we try? But in

1747
01:30:51,439 --> 01:30:53,880
Speaker 1: the case, it's like with this question about the Siberian tiger,

1748
01:30:54,080 --> 01:30:57,479
Speaker 1: it's like, well, what's to lose. Is we don't know

1749
01:30:57,600 --> 01:31:02,479
Speaker 1: yet that there remains a chain ants, so by helping it,

1750
01:31:02,520 --> 01:31:03,479
Speaker 1: what's the risk.

1751
01:31:03,320 --> 01:31:06,160
Speaker 6: Of Yeah, and I think that risk has to be

1752
01:31:06,160 --> 01:31:08,479
Speaker 6: put in context of what is the current risk of extinction?

1753
01:31:08,640 --> 01:31:08,840
Speaker 1: Right?

1754
01:31:09,040 --> 01:31:11,360
Speaker 6: Just because it is still present doesn't mean it will

1755
01:31:11,400 --> 01:31:13,400
Speaker 6: be president in your time. So I think that is

1756
01:31:13,439 --> 01:31:17,040
Speaker 6: an important comparison. But not only am I comfortable with it,

1757
01:31:17,080 --> 01:31:18,760
Speaker 6: I mean that's my dream, That's why I work here.

1758
01:31:18,800 --> 01:31:20,080
Speaker 5: I want to go and find.

1759
01:31:19,800 --> 01:31:22,240
Speaker 6: These amazing programs where we can go make a difference

1760
01:31:22,439 --> 01:31:25,240
Speaker 6: in that way. But it's also important to note that

1761
01:31:25,240 --> 01:31:28,040
Speaker 6: that you know, this is such a thoughtful and long

1762
01:31:28,680 --> 01:31:31,600
Speaker 6: process that it's not just like I said earlier, you

1763
01:31:31,640 --> 01:31:33,519
Speaker 6: don't just make them and let them lose. We'd have

1764
01:31:33,600 --> 01:31:39,280
Speaker 6: to work in concert with NGOs, with government agencies to

1765
01:31:39,360 --> 01:31:43,160
Speaker 6: figure out how can we build a reintroduction program that

1766
01:31:43,280 --> 01:31:46,719
Speaker 6: allows us to answer all these sort of risk mitigation

1767
01:31:46,840 --> 01:31:49,760
Speaker 6: questions before we get to that release point. But yes,

1768
01:31:49,800 --> 01:31:53,040
Speaker 6: one hundred percent, my goal in life is that before

1769
01:31:53,120 --> 01:31:56,080
Speaker 6: I die, I want to see an endangered species saved

1770
01:31:56,120 --> 01:31:57,080
Speaker 6: by this technology.

1771
01:31:57,280 --> 01:32:01,400
Speaker 1: Not save, not de extinct, but preventing extinction.

1772
01:32:01,439 --> 01:32:03,680
Speaker 6: No, I mean for us, it's both you know, we

1773
01:32:04,040 --> 01:32:07,320
Speaker 6: view the extinction as a conservation tool and I think

1774
01:32:07,400 --> 01:32:09,439
Speaker 6: you know, I can see ways that we can fix

1775
01:32:09,479 --> 01:32:12,320
Speaker 6: habitats using the extinction from lost species, and that we

1776
01:32:12,360 --> 01:32:15,200
Speaker 6: can save currently imperiled populations of animals.

1777
01:32:15,640 --> 01:32:18,920
Speaker 1: Knowing what you now know, did they do the right

1778
01:32:19,000 --> 01:32:23,280
Speaker 1: thing on the Florida panther or like we had current technologies,

1779
01:32:24,240 --> 01:32:27,160
Speaker 1: would you have approached the Florida panther question differently?

1780
01:32:27,840 --> 01:32:30,640
Speaker 6: I mean, using today's tools, we could have done it

1781
01:32:30,680 --> 01:32:32,760
Speaker 6: differently and you wouldn't need to go to Texas to

1782
01:32:32,800 --> 01:32:37,280
Speaker 6: get more expensively. And this is an amazing toolkit we're building.

1783
01:32:37,280 --> 01:32:39,400
Speaker 6: And this goes back to that northern white rhino example.

1784
01:32:39,840 --> 01:32:42,240
Speaker 6: Is one of the things we're doing. And this should

1785
01:32:42,240 --> 01:32:45,080
Speaker 6: be right up Hunter's Alleys right is we're going back

1786
01:32:45,120 --> 01:32:48,200
Speaker 6: into people's private collections. We're going back into museum collections

1787
01:32:48,200 --> 01:32:51,400
Speaker 6: and understanding if you hunted a northern white rhino in

1788
01:32:51,439 --> 01:32:54,519
Speaker 6: the fifties, sixties, eighties, whatever it was, and you have

1789
01:32:54,640 --> 01:32:57,400
Speaker 6: this specimen, we want to sequence it. We want to

1790
01:32:57,439 --> 01:32:59,479
Speaker 6: go in and we want to figure out what was

1791
01:32:59,479 --> 01:33:02,519
Speaker 6: the genetic diversity representative of this species before it became

1792
01:33:02,560 --> 01:33:07,000
Speaker 6: extremely bottlenecked, functionally extinct and now we have twelve lines

1793
01:33:07,040 --> 01:33:10,439
Speaker 6: of Northern white rhinos, so essentially you only have twelve

1794
01:33:10,439 --> 01:33:11,560
Speaker 6: founders for the population.

1795
01:33:12,439 --> 01:33:13,560
Speaker 5: When we talk about.

1796
01:33:13,320 --> 01:33:15,920
Speaker 6: Florida panther, it was a a couple hundred and they

1797
01:33:15,920 --> 01:33:19,240
Speaker 6: were so inbred, so it tells you that there's a

1798
01:33:19,280 --> 01:33:21,320
Speaker 6: really low level. But what we can do is take

1799
01:33:21,360 --> 01:33:23,200
Speaker 6: those twelve lines and leave them sort of what we

1800
01:33:23,280 --> 01:33:26,639
Speaker 6: call wild type, and then start to use the genetic

1801
01:33:26,680 --> 01:33:30,639
Speaker 6: diversity information we found from those samples and edit that

1802
01:33:30,720 --> 01:33:34,439
Speaker 6: diversity back in, so we're actually artificially building more founder

1803
01:33:34,520 --> 01:33:37,679
Speaker 6: representation into the population. So that's what's happening right now

1804
01:33:37,720 --> 01:33:40,000
Speaker 6: for us with Northern white rhino. That's our key role

1805
01:33:40,000 --> 01:33:42,760
Speaker 6: in that project. We're going to Mauritius to talk about

1806
01:33:42,800 --> 01:33:46,000
Speaker 6: doing this with pink pigeons, which were a highly bottlenecked

1807
01:33:46,400 --> 01:33:49,439
Speaker 6: population that went extinct in the wild, and now we're

1808
01:33:49,439 --> 01:33:51,640
Speaker 6: looking at where else could we apply that. So for

1809
01:33:51,720 --> 01:33:54,479
Speaker 6: the Florida panther question, we could have done the same thing,

1810
01:33:55,080 --> 01:33:57,800
Speaker 6: or we could just go into the western cougar and

1811
01:33:57,880 --> 01:34:01,360
Speaker 6: identify what parts of of the genome would be most

1812
01:34:01,360 --> 01:34:05,439
Speaker 6: impactful back So without taking all of the Western cougar

1813
01:34:05,479 --> 01:34:07,640
Speaker 6: and mixing it in, you could take pieces of it

1814
01:34:07,680 --> 01:34:10,160
Speaker 6: and be more deliberate or intentional about what you want

1815
01:34:10,200 --> 01:34:14,320
Speaker 6: to do. Obviously that's more high tech and science y,

1816
01:34:14,560 --> 01:34:17,519
Speaker 6: so it becomes more expensive than just translocating western cougars,

1817
01:34:17,520 --> 01:34:20,080
Speaker 6: but it is a way to sort of, I think,

1818
01:34:20,120 --> 01:34:23,880
Speaker 6: answer some of the concerns about are you diluting an

1819
01:34:23,960 --> 01:34:25,960
Speaker 6: endemic subpopulation.

1820
01:34:26,640 --> 01:34:33,200
Speaker 3: And is there any temptation to alter these gene sequences,

1821
01:34:33,240 --> 01:34:37,840
Speaker 3: like to find these like Jurassic Park type ways of being, Like, oh,

1822
01:34:38,000 --> 01:34:42,160
Speaker 3: instead of like eradicating all the rats, can we make

1823
01:34:42,240 --> 01:34:47,640
Speaker 3: it so that ground nesting bird doesn't smell. Yeah, like

1824
01:34:47,760 --> 01:34:50,839
Speaker 3: to where the rats don't even see the nest because

1825
01:34:50,880 --> 01:34:51,519
Speaker 3: they can't.

1826
01:34:51,640 --> 01:34:55,559
Speaker 6: So we just announced this amazing project a couple weeks ago,

1827
01:34:55,560 --> 01:34:59,040
Speaker 6: I think. And so there's this A species in Australia

1828
01:34:59,040 --> 01:35:01,880
Speaker 6: comes from the Northern Ratory of Australia called the Northern

1829
01:35:01,960 --> 01:35:05,280
Speaker 6: quall quoll. It's a dazzy year it so it's closely

1830
01:35:05,320 --> 01:35:09,960
Speaker 6: related to Tasmanian devils. Years and years ago, cane toads

1831
01:35:10,160 --> 01:35:14,400
Speaker 6: marine toads were introduced to Australia as some attempt to

1832
01:35:14,400 --> 01:35:16,880
Speaker 6: control other invasives and just became an invasive in and

1833
01:35:16,920 --> 01:35:23,760
Speaker 6: of themselves, right, cane toads excrete buffotoxin boufotoxin. You know,

1834
01:35:23,960 --> 01:35:26,840
Speaker 6: so these are animals native to South America. Boufotoxin is

1835
01:35:27,400 --> 01:35:30,360
Speaker 6: a neurotoxin that kills animals that do not have a

1836
01:35:30,479 --> 01:35:32,719
Speaker 6: resistance to it. So when the cane toad was introduced

1837
01:35:32,760 --> 01:35:36,040
Speaker 6: to Australia, it really impacted the coal because it's a

1838
01:35:36,240 --> 01:35:40,799
Speaker 6: perfect size and sort of niche for the coal to predate,

1839
01:35:41,200 --> 01:35:44,080
Speaker 6: and when the qualls predate on them, they eventually die,

1840
01:35:44,360 --> 01:35:46,519
Speaker 6: and so it's really impacting the population. So what we're

1841
01:35:46,520 --> 01:35:49,840
Speaker 6: doing sort of in that same light is we've identified

1842
01:35:50,160 --> 01:35:54,120
Speaker 6: that animals that co evolved with the buffotad marine toad

1843
01:35:54,280 --> 01:35:59,920
Speaker 6: in South America actually have this natural resistance to that toxin.

1844
01:36:00,360 --> 01:36:01,880
Speaker 6: And as it turns out, it's a very simple that

1845
01:36:01,920 --> 01:36:05,479
Speaker 6: it's like one base pair change. So we're we just

1846
01:36:05,479 --> 01:36:08,000
Speaker 6: announced that we are going and making that change in

1847
01:36:08,479 --> 01:36:12,280
Speaker 6: northern coal lines so that we can release those genetically

1848
01:36:12,400 --> 01:36:15,160
Speaker 6: edited quill back into the Northern territory. And that that's

1849
01:36:15,200 --> 01:36:17,160
Speaker 6: amazing because it does two things. It saves the northern

1850
01:36:17,200 --> 01:36:21,080
Speaker 6: qual from this imminent extinction, which almost certain extinction, and

1851
01:36:21,120 --> 01:36:24,719
Speaker 6: they can start those kill down there. A nature based

1852
01:36:24,720 --> 01:36:27,160
Speaker 6: way to remove an invasive space. So it's you know,

1853
01:36:27,280 --> 01:36:29,040
Speaker 6: it's so exciting, and I think that is so to

1854
01:36:29,080 --> 01:36:31,360
Speaker 6: your question, yeah, we want to continue to find solutions

1855
01:36:31,360 --> 01:36:31,679
Speaker 6: like that.

1856
01:36:31,920 --> 01:36:36,760
Speaker 1: Wow, are there regulatory hurdles on that one?

1857
01:36:37,360 --> 01:36:38,559
Speaker 3: People got to be freaking out.

1858
01:36:38,680 --> 01:36:41,160
Speaker 6: I mean we talk about there's a big fear about

1859
01:36:41,200 --> 01:36:45,400
Speaker 6: genetically modified organistness, right, and I think there is also.

1860
01:36:45,640 --> 01:36:48,160
Speaker 1: A I got news for everybody, you're eating them?

1861
01:36:48,200 --> 01:36:48,799
Speaker 5: Yeah, exactly.

1862
01:36:48,880 --> 01:36:50,160
Speaker 6: That was going to be what I was gonna say,

1863
01:36:50,200 --> 01:36:55,120
Speaker 6: is I think anybody vacation and like Florida, right, and

1864
01:36:55,160 --> 01:36:58,040
Speaker 6: it's like you see helicopters spray and stuff everywhere.

1865
01:36:58,280 --> 01:36:59,599
Speaker 5: Yeah, chemicals are much worse.

1866
01:36:59,640 --> 01:37:01,360
Speaker 3: So yeah, right, and you're like, do you want that

1867
01:37:01,880 --> 01:37:07,600
Speaker 3: or do you want Well, that's three choices. Get absolutely

1868
01:37:07,640 --> 01:37:12,920
Speaker 3: eaten live by mosquitoes, have them aerial sprayed everywhere, or

1869
01:37:13,400 --> 01:37:16,720
Speaker 3: you can have a genetically modified mosquito in there that

1870
01:37:17,880 --> 01:37:20,960
Speaker 3: makes everybody uh male right, yep, males don't.

1871
01:37:21,400 --> 01:37:22,559
Speaker 5: Yeah, that would be one way to do it.

1872
01:37:22,600 --> 01:37:24,800
Speaker 6: But you know, I think to your point, there's an

1873
01:37:24,840 --> 01:37:28,280
Speaker 6: unwillingness to acknowledge that we have been domesticating our dogs,

1874
01:37:28,320 --> 01:37:32,479
Speaker 6: We've been domesticating our agriculture crops for tens of thousands

1875
01:37:32,520 --> 01:37:34,800
Speaker 6: of years, right, Like, that's sort of what we've done.

1876
01:37:35,200 --> 01:37:38,640
Speaker 6: That tomato that you eat every day isn't representative of

1877
01:37:38,680 --> 01:37:40,920
Speaker 6: what a tomato really is. That's what we've made it.

1878
01:37:41,280 --> 01:37:44,639
Speaker 6: But we did it through traditionally, through you know, artificial selection,

1879
01:37:44,880 --> 01:37:46,840
Speaker 6: back breeding, cross breeding, things like you know, sort of

1880
01:37:46,840 --> 01:37:49,839
Speaker 6: that Mendelian idea of genetics. If we like this phoenotype

1881
01:37:49,840 --> 01:37:50,960
Speaker 6: in this one, we're going to breed them and see

1882
01:37:50,960 --> 01:37:53,040
Speaker 6: what happens. We're doing the same thing. We're trying to

1883
01:37:53,080 --> 01:37:56,360
Speaker 6: get this gene from that target that we like, but

1884
01:37:56,400 --> 01:37:58,200
Speaker 6: we're just going to do it in an accelerated way

1885
01:37:58,240 --> 01:37:59,640
Speaker 6: in a lab. So we're still going to pull the

1886
01:37:59,680 --> 01:38:01,400
Speaker 6: same gen and put it in there as you would

1887
01:38:01,760 --> 01:38:04,479
Speaker 6: might achieve through selective breeding, but we're going to do

1888
01:38:04,520 --> 01:38:11,360
Speaker 6: it much faster and with fewer maybe unintended consequences.

1889
01:38:11,439 --> 01:38:16,080
Speaker 7: And isn't there an example of a species of zebra

1890
01:38:16,520 --> 01:38:20,719
Speaker 7: that they the quaga, that they brought back by doing

1891
01:38:20,760 --> 01:38:23,519
Speaker 7: sort of the Mendelian you pick out.

1892
01:38:23,439 --> 01:38:25,080
Speaker 5: There there's two efforts underway.

1893
01:38:25,120 --> 01:38:29,679
Speaker 6: So the quaga, which is is a closely related zebra

1894
01:38:29,760 --> 01:38:32,799
Speaker 6: and sort of it's very phenotypically different, has no stripes,

1895
01:38:32,840 --> 01:38:36,320
Speaker 6: it's like more brown, it's about it and the ROC

1896
01:38:36,439 --> 01:38:39,040
Speaker 6: from Europe. Right, there are two efforts to use back

1897
01:38:39,080 --> 01:38:42,280
Speaker 6: breeding to do that, and they're making headway, and they

1898
01:38:42,320 --> 01:38:46,280
Speaker 6: can do so with much less fanfare and and maybe

1899
01:38:46,280 --> 01:38:49,640
Speaker 6: criticism because people are really comfortable with breeding.

1900
01:38:49,360 --> 01:38:51,760
Speaker 7: Because it looks like what people were doing, yeah, tens

1901
01:38:51,840 --> 01:38:52,720
Speaker 7: of thousands of years ago.

1902
01:38:52,720 --> 01:38:54,840
Speaker 6: But the process, when you really get down to it,

1903
01:38:54,880 --> 01:38:57,200
Speaker 6: if you really want to oversimplify, is essentially the same.

1904
01:38:57,240 --> 01:39:01,360
Speaker 6: You're targeting very specific phenotypes in instead, we're figuring out

1905
01:39:01,360 --> 01:39:04,599
Speaker 6: what gene makes a phenotype and then we're trying to

1906
01:39:04,960 --> 01:39:07,400
Speaker 6: get that to be expressed in our line of interest,

1907
01:39:07,439 --> 01:39:09,839
Speaker 6: so we can do it much faster, and.

1908
01:39:09,720 --> 01:39:10,920
Speaker 5: I think that's much intention more.

1909
01:39:11,120 --> 01:39:14,000
Speaker 2: Probably what scares people though, like without leaning too far

1910
01:39:14,040 --> 01:39:17,519
Speaker 2: into like the paranoia and conspiracy theory thing, like it's like,

1911
01:39:18,479 --> 01:39:23,200
Speaker 2: who's making sure they're not going too far with this, right, yeah.

1912
01:39:23,040 --> 01:39:25,400
Speaker 3: Or in the case of the tiger, right, and it's

1913
01:39:25,400 --> 01:39:28,080
Speaker 3: like somebody in labs like, but we want them a

1914
01:39:28,080 --> 01:39:30,400
Speaker 3: little more pissed off.

1915
01:39:30,760 --> 01:39:32,800
Speaker 6: But I think that's why, you know, we invite the

1916
01:39:32,840 --> 01:39:36,280
Speaker 6: regulatory environment. We want to be the subject matter expert

1917
01:39:36,280 --> 01:39:39,760
Speaker 6: that builds those guardrails, because frankly, there are very few

1918
01:39:39,760 --> 01:39:42,000
Speaker 6: people in the world that understand the true power of

1919
01:39:42,000 --> 01:39:43,439
Speaker 6: this technology more than.

1920
01:39:43,320 --> 01:39:44,919
Speaker 5: The people at Colossal.

1921
01:39:45,240 --> 01:39:47,360
Speaker 6: So we need to sit down with the world leading

1922
01:39:47,520 --> 01:39:51,160
Speaker 6: experts in ethics and regulation to say, this is how

1923
01:39:51,200 --> 01:39:53,160
Speaker 6: we think we can use this, and here's how we

1924
01:39:53,200 --> 01:39:55,719
Speaker 6: think it could probably go wrong, right, and let's build

1925
01:39:55,720 --> 01:39:59,439
Speaker 6: a guardrail that keeps us on this path. Because when

1926
01:39:59,439 --> 01:40:01,840
Speaker 6: we have this first breakthrough, when we blow all your

1927
01:40:01,880 --> 01:40:04,639
Speaker 6: minds with this first restored spaces from extinction, we won't

1928
01:40:04,640 --> 01:40:05,799
Speaker 6: be the only show anymore.

1929
01:40:06,120 --> 01:40:08,479
Speaker 5: And then Pandora's box is wide open.

1930
01:40:08,560 --> 01:40:11,080
Speaker 6: And luckily we'll be light years ahead of it and

1931
01:40:11,080 --> 01:40:13,599
Speaker 6: anybody else. But somebody else can start to work from

1932
01:40:13,640 --> 01:40:14,880
Speaker 6: the same foundation that we built.

1933
01:40:15,040 --> 01:40:15,439
Speaker 4: Mm hmm.

1934
01:40:16,080 --> 01:40:18,800
Speaker 6: So we need responsible regulation and I want it for me.

1935
01:40:18,960 --> 01:40:20,720
Speaker 6: The only way I could ever achieve my dream of

1936
01:40:20,720 --> 01:40:24,200
Speaker 6: putting a restored spaces back into the wild or preventing

1937
01:40:24,200 --> 01:40:27,240
Speaker 6: an extinction is to have really strong regulation that invites

1938
01:40:27,280 --> 01:40:28,120
Speaker 6: that type of work.

1939
01:40:28,400 --> 01:40:32,400
Speaker 1: Yeah, you're a You're in an interesting position of when

1940
01:40:32,439 --> 01:40:37,080
Speaker 1: it comes to policy and legislation, you're in the interesting

1941
01:40:37,120 --> 01:40:39,880
Speaker 1: position of needing to point out what it is.

1942
01:40:40,080 --> 01:40:42,040
Speaker 5: Yeah, like you'd be like, like.

1943
01:40:42,200 --> 01:40:43,880
Speaker 1: Hear me out. I'm gonna tell you about a thing

1944
01:40:45,000 --> 01:40:47,479
Speaker 1: we're figuring out how to do that you're probably not

1945
01:40:47,560 --> 01:40:49,599
Speaker 1: aware of. And then I'm gonna tell you some things

1946
01:40:49,600 --> 01:40:52,519
Speaker 1: that you might want to do in order to get

1947
01:40:52,560 --> 01:40:54,759
Speaker 1: your hands around the thing. I'm gonna tell you exactly.

1948
01:40:54,920 --> 01:40:57,240
Speaker 6: Yeah, And that's why you've said I don't if if

1949
01:40:57,240 --> 01:40:58,960
Speaker 6: you've looked into us a bit, you know, one of

1950
01:40:58,960 --> 01:41:01,559
Speaker 6: the one of the groups that invested in Colossal Is

1951
01:41:02,400 --> 01:41:05,120
Speaker 6: is the venture capital Alarm of the intelligence community here

1952
01:41:05,120 --> 01:41:07,200
Speaker 6: in the US, because they want to understand more of

1953
01:41:07,240 --> 01:41:09,320
Speaker 6: that so we we can work in concert and show

1954
01:41:09,320 --> 01:41:13,040
Speaker 6: them sort of what are the capabilities of today and

1955
01:41:13,040 --> 01:41:14,920
Speaker 6: and so that's why they've invested in US, because they

1956
01:41:14,960 --> 01:41:17,479
Speaker 6: understand that it's also important to national security that the

1957
01:41:17,560 --> 01:41:20,880
Speaker 6: United States leads this effort. If we're not doing it,

1958
01:41:20,880 --> 01:41:22,920
Speaker 6: somebody else is doing it, we better be the best

1959
01:41:22,920 --> 01:41:23,200
Speaker 6: at it.

1960
01:41:23,880 --> 01:41:25,880
Speaker 3: You may put a chimp into outer space, but you

1961
01:41:25,880 --> 01:41:27,240
Speaker 3: haven't put a colossal.

1962
01:41:28,000 --> 01:41:32,360
Speaker 1: Because if our enemies come out with a psychic war elephant, right,

1963
01:41:33,080 --> 01:41:34,439
Speaker 1: they're gonna look at you and be like, well, how

1964
01:41:34,479 --> 01:41:37,240
Speaker 1: come out of that a psychic war elephant? You know

1965
01:41:37,280 --> 01:41:38,519
Speaker 1: what you know what you know, you'll be you'll be

1966
01:41:38,880 --> 01:41:41,360
Speaker 1: pleased to know. I just thought of how to tackle

1967
01:41:41,360 --> 01:41:42,200
Speaker 1: the dinosaur deal.

1968
01:41:42,520 --> 01:41:43,720
Speaker 5: Oh great, let's hear it.

1969
01:41:43,920 --> 01:41:48,960
Speaker 1: Check it out. Everybody now knows that, like, uh, you know, birds,

1970
01:41:49,880 --> 01:41:52,240
Speaker 1: people are like, well, dinosaurs didn't really go away because

1971
01:41:52,280 --> 01:41:56,160
Speaker 1: some of them became birds. Somewhere deep in that bird's

1972
01:41:56,240 --> 01:42:04,559
Speaker 1: blood I mean, yeah, turkey, Maybe a crane somewhere deep

1973
01:42:04,600 --> 01:42:08,360
Speaker 1: in that turkey is probably the secret of what you're

1974
01:42:08,360 --> 01:42:10,160
Speaker 1: looking for. Deep in his blood.

1975
01:42:10,160 --> 01:42:14,320
Speaker 7: All of Steve's best ideas begin with everybody knows X,

1976
01:42:14,720 --> 01:42:18,040
Speaker 7: but deep down in his blood, I mean the blood

1977
01:42:18,080 --> 01:42:20,600
Speaker 7: in the middle of his heart.

1978
01:42:20,040 --> 01:42:21,439
Speaker 6: And we might have just been looking at the wrong

1979
01:42:21,720 --> 01:42:25,200
Speaker 6: part of the aim is probably some clue. Have you

1980
01:42:25,240 --> 01:42:28,599
Speaker 6: seen a watson? Watson, Watson. It's a South American beard

1981
01:42:28,640 --> 01:42:30,160
Speaker 6: that looks like a tiny velociraptor.

1982
01:42:31,000 --> 01:42:32,800
Speaker 1: That might even better than a crane.

1983
01:42:32,840 --> 01:42:34,960
Speaker 6: Yeah, that might be where it's there. They're terrifying looking.

1984
01:42:35,000 --> 01:42:36,799
Speaker 6: They have little claws on their wings.

1985
01:42:36,840 --> 01:42:37,200
Speaker 1: Well they do.

1986
01:42:38,120 --> 01:42:40,559
Speaker 9: I like the fact that nature has sort of put

1987
01:42:40,640 --> 01:42:45,280
Speaker 9: up a roadblock according to you, that is going to

1988
01:42:45,360 --> 01:42:48,799
Speaker 9: hopefully prevent us from doing what you're talking about.

1989
01:42:49,479 --> 01:42:51,080
Speaker 1: Too far back, too far back.

1990
01:42:51,320 --> 01:42:54,880
Speaker 9: Yeah, or that its just and to me in a way,

1991
01:42:55,479 --> 01:42:57,120
Speaker 9: like I've said this for a long time, I get

1992
01:42:57,160 --> 01:42:59,360
Speaker 9: a lot of like frowned and like weird looks, and

1993
01:42:59,400 --> 01:43:03,280
Speaker 9: I say it, But extinction if it happened way back then,

1994
01:43:04,240 --> 01:43:05,880
Speaker 9: we lost all these species.

1995
01:43:05,960 --> 01:43:07,120
Speaker 3: It was a crazy place.

1996
01:43:07,160 --> 01:43:09,680
Speaker 9: It was a very diverse world, and then all of

1997
01:43:09,680 --> 01:43:12,799
Speaker 9: a sudden, like something hits the Earth and it changes,

1998
01:43:12,880 --> 01:43:16,120
Speaker 9: all the shit goes wrong. It would lose everything. But

1999
01:43:16,160 --> 01:43:18,920
Speaker 9: look right now or one hundred years ago. Wow, we

2000
01:43:19,000 --> 01:43:22,439
Speaker 9: have another very diverse, cool place. And there's nothing to

2001
01:43:22,479 --> 01:43:24,800
Speaker 9: say that as bad as we fuck it up in

2002
01:43:24,840 --> 01:43:27,160
Speaker 9: the next five hundred to one thousand years and we

2003
01:43:27,240 --> 01:43:30,360
Speaker 9: are gone that ten thousand years after that, it won't

2004
01:43:30,400 --> 01:43:31,559
Speaker 9: be another beautiful place.

2005
01:43:31,720 --> 01:43:36,000
Speaker 1: I look forward to us all being gone, humans all gone,

2006
01:43:36,280 --> 01:43:39,639
Speaker 1: and then let millions of years go by and then

2007
01:43:39,720 --> 01:43:44,639
Speaker 1: come back and look it'll be cool, like good lord.

2008
01:43:44,800 --> 01:43:46,840
Speaker 5: Yeah, I'm certain that they're.

2009
01:43:46,720 --> 01:43:49,320
Speaker 2: Gonna put in the bio bank so you can come.

2010
01:43:49,200 --> 01:43:52,080
Speaker 6: Back, come back, Ted Williams, just your head, yeah, yeah,

2011
01:43:52,120 --> 01:43:55,920
Speaker 6: Ted Williams style. I'm certain that in you know, nature

2012
01:43:56,040 --> 01:43:58,439
Speaker 6: and Earth will survive. It just won't be the nature

2013
01:43:58,479 --> 01:44:01,720
Speaker 6: of Earth that we know. And we're pretty attached to right,

2014
01:44:01,800 --> 01:44:04,000
Speaker 6: so it'd be nice. I think you're a little optimistic

2015
01:44:04,040 --> 01:44:06,160
Speaker 6: to think that civilization will last.

2016
01:44:06,040 --> 01:44:07,320
Speaker 5: Five hundred or thousand years.

2017
01:44:07,320 --> 01:44:10,240
Speaker 6: So at this rate that we're that we're we're chasing

2018
01:44:10,280 --> 01:44:14,000
Speaker 6: down biodiversity loss. You know, people think that biodiversity loss

2019
01:44:14,040 --> 01:44:16,360
Speaker 6: is only about, you know, the intrinsic value of nature.

2020
01:44:16,800 --> 01:44:19,839
Speaker 6: It's important to your food security, your health, you know, everything.

2021
01:44:19,920 --> 01:44:24,360
Speaker 6: Without a balance in nature, humanity will not thrive. That's

2022
01:44:24,400 --> 01:44:26,600
Speaker 6: why we have people looking at figuring out how to

2023
01:44:26,600 --> 01:44:27,080
Speaker 6: go to Mars.

2024
01:44:27,240 --> 01:44:30,760
Speaker 1: Yeah, I think that, I mean just our increasing understanding

2025
01:44:30,880 --> 01:44:37,640
Speaker 1: of the microbial structure of soil. Yeah, Like, I don't know.

2026
01:44:37,640 --> 01:44:40,120
Speaker 1: We talked about Aldo Leopold the other day, his idea

2027
01:44:40,160 --> 01:44:46,320
Speaker 1: of of someone that doesn't really understand a watch looking

2028
01:44:46,400 --> 01:44:49,880
Speaker 1: at a disassembled watch and being like, I don't see

2029
01:44:49,880 --> 01:44:55,080
Speaker 1: what good this part is, right, it's not obvious you

2030
01:44:55,080 --> 01:44:57,400
Speaker 1: know that part does, and flick it out.

2031
01:44:57,479 --> 01:45:00,240
Speaker 10: And then later be like, god, damn it that I

2032
01:45:00,240 --> 01:45:03,479
Speaker 10: think that's the part that does the And we do

2033
01:45:03,560 --> 01:45:06,120
Speaker 10: that every day when we say, you know, you know,

2034
01:45:06,880 --> 01:45:09,559
Speaker 10: commercial fishing is over fishing our seas and we're seeing

2035
01:45:09,600 --> 01:45:12,439
Speaker 10: different you know, sizes of fish or different populations of

2036
01:45:12,439 --> 01:45:14,799
Speaker 10: fish out there just because of industrialized fishing.

2037
01:45:15,680 --> 01:45:18,840
Speaker 6: You know, we talk about when we are even doing

2038
01:45:19,040 --> 01:45:22,720
Speaker 6: you know, development for human housing, we're just digging up

2039
01:45:22,920 --> 01:45:24,920
Speaker 6: pieces of land that we got well, nothing that we

2040
01:45:24,960 --> 01:45:26,519
Speaker 6: know of today was important there.

2041
01:45:26,880 --> 01:45:27,000
Speaker 1: You know.

2042
01:45:27,040 --> 01:45:30,439
Speaker 6: A great example to that was there's this this small

2043
01:45:30,439 --> 01:45:34,000
Speaker 6: lizard from Australia again in Victoria called the Victoria and

2044
01:45:34,000 --> 01:45:36,639
Speaker 6: Grassland early Dragon, and it went extinct in nineteen sixty

2045
01:45:36,720 --> 01:45:39,800
Speaker 6: nine and never seen again. And then they were one

2046
01:45:39,840 --> 01:45:43,879
Speaker 6: guy was digging up some housing some land in Victoria

2047
01:45:44,160 --> 01:45:46,040
Speaker 6: to put up a housing development, had to do an

2048
01:45:46,040 --> 01:45:49,920
Speaker 6: ecological survey and they discovered the Victorian Grassland early Dragon

2049
01:45:50,600 --> 01:45:50,960
Speaker 6: while they.

2050
01:45:50,880 --> 01:45:56,080
Speaker 7: Were destroying its What's great about that is our partners

2051
01:45:56,120 --> 01:45:58,439
Speaker 7: at Zoos Victoria and in Australia called us and they said,

2052
01:45:58,479 --> 01:46:01,880
Speaker 7: you know, unfortunately the Australian economy is not strong right

2053
01:46:01,920 --> 01:46:05,840
Speaker 7: now with all the stagnations stagflation issues down there, and

2054
01:46:06,000 --> 01:46:08,200
Speaker 7: they said, unfortunately, there's no money to save this animal.

2055
01:46:08,200 --> 01:46:10,680
Speaker 6: We ended up fight, Yeah, we ended up funding it.

2056
01:46:10,960 --> 01:46:13,719
Speaker 6: We ended up supporting all the genetics and genemic research

2057
01:46:13,720 --> 01:46:15,960
Speaker 6: and Zoos Victoria has done an amazing job, maybe one

2058
01:46:15,960 --> 01:46:18,040
Speaker 6: of the best species recovery stories I've ever heard of.

2059
01:46:18,240 --> 01:46:20,800
Speaker 6: They're the most prepared. They thought, one day, somebody's gonna

2060
01:46:20,800 --> 01:46:22,799
Speaker 6: find this lizard. So they went and found a closely

2061
01:46:22,920 --> 01:46:27,200
Speaker 6: related lizard and perfected its husbandry. In the first year

2062
01:46:27,240 --> 01:46:30,400
Speaker 6: that we put that animal at Ze's Victoria, they laid

2063
01:46:30,400 --> 01:46:32,479
Speaker 6: eggs and now there's we went. Yeah, we went from

2064
01:46:32,520 --> 01:46:35,240
Speaker 6: sixteen animals to about seventy or so.

2065
01:46:35,920 --> 01:46:36,240
Speaker 1: Yeah.

2066
01:46:36,240 --> 01:46:40,160
Speaker 6: So, I mean just amazing, right, absolutely incredible story. And

2067
01:46:40,400 --> 01:46:42,320
Speaker 6: I think that's just goes to show you that, you know,

2068
01:46:43,000 --> 01:46:45,559
Speaker 6: just because things aren't obvious, you know, there's a lot

2069
01:46:45,600 --> 01:46:47,439
Speaker 6: to nature that we don't understand or that we just

2070
01:46:47,520 --> 01:46:50,240
Speaker 6: that that you kind of miss and couldn't have these

2071
01:46:50,680 --> 01:46:52,480
Speaker 6: insane ripple effects.

2072
01:46:53,360 --> 01:46:56,920
Speaker 1: Well that was great, Thank you for coming on.

2073
01:46:57,080 --> 01:46:57,760
Speaker 5: Thanks for having me.

2074
01:46:57,800 --> 01:46:59,519
Speaker 6: I mean, this is uh you got a lot of

2075
01:46:59,560 --> 01:47:03,040
Speaker 6: fans that lass uh yeah, yeah, I'd be remiss if

2076
01:47:03,080 --> 01:47:04,920
Speaker 6: I didn't give shout out to our head of animal husbandry,

2077
01:47:04,920 --> 01:47:07,080
Speaker 6: Steve Metzler. He's the biggest fan of you guys, so

2078
01:47:07,720 --> 01:47:09,920
Speaker 6: he was jealousy couldn't be here. But we really appreciate

2079
01:47:09,960 --> 01:47:12,840
Speaker 6: the audience with you and and uh and and and

2080
01:47:12,880 --> 01:47:14,240
Speaker 6: getting to share a little bit of what we do.

2081
01:47:14,280 --> 01:47:16,519
Speaker 6: We hope we have some exciting updates for you coming up.

2082
01:47:16,680 --> 01:47:18,559
Speaker 1: Yeah, I want to. I want to make my final

2083
01:47:18,600 --> 01:47:21,320
Speaker 1: clarification here. Like we had we we joked a little

2084
01:47:21,320 --> 01:47:25,360
Speaker 1: bit and had some lass about things, right, But I

2085
01:47:25,360 --> 01:47:28,760
Speaker 1: I do think that when we had dinner last night,

2086
01:47:29,320 --> 01:47:32,760
Speaker 1: we talked about that I used to had this, I

2087
01:47:32,800 --> 01:47:36,759
Speaker 1: had the wrong idea that I always saw people justified

2088
01:47:36,760 --> 01:47:41,519
Speaker 1: the space race by pointing to Teflon, you know, and

2089
01:47:41,600 --> 01:47:43,760
Speaker 1: I was and then someone pointed out tough On didn't

2090
01:47:43,760 --> 01:47:46,880
Speaker 1: come from I thought it came from our efforts to

2091
01:47:46,920 --> 01:47:48,720
Speaker 1: land on the movie. Either way, I was bringing up

2092
01:47:48,720 --> 01:47:52,200
Speaker 1: this idea that you chase a thing, right, and and

2093
01:47:52,520 --> 01:47:55,160
Speaker 1: and and and maybe it's not clear why the why

2094
01:47:55,920 --> 01:47:58,000
Speaker 1: we have this desire at the time me this desire

2095
01:47:58,040 --> 01:48:00,160
Speaker 1: to go to the moon, right, it's kind of what

2096
01:48:00,240 --> 01:48:02,200
Speaker 1: are you gonna do when you get there? And it's

2097
01:48:02,200 --> 01:48:05,439
Speaker 1: an open question, but it leads you down this path,

2098
01:48:05,560 --> 01:48:08,840
Speaker 1: and for us, it led down this path of set

2099
01:48:08,920 --> 01:48:14,960
Speaker 1: you know, eventually, satellite technology, internet whatever. It opens up

2100
01:48:15,000 --> 01:48:19,400
Speaker 1: all these things. And I do really appreciate in the

2101
01:48:19,439 --> 01:48:24,400
Speaker 1: conversations that we've had, I do really appreciate that there's

2102
01:48:24,439 --> 01:48:27,280
Speaker 1: this kind of like North Star idea that's very arresting

2103
01:48:28,120 --> 01:48:31,519
Speaker 1: about like that we would make a mammoth, right, we

2104
01:48:31,520 --> 01:48:34,439
Speaker 1: would de extinct a mammoth, And I appreciate that for

2105
01:48:34,560 --> 01:48:43,200
Speaker 1: its It's it's like lunar shot appeal, right, But the

2106
01:48:43,240 --> 01:48:45,840
Speaker 1: way in which that, like looking at that north Star,

2107
01:48:46,000 --> 01:48:49,599
Speaker 1: the way in which that has created and will continue

2108
01:48:49,640 --> 01:48:55,240
Speaker 1: to create strategies and technologies that would be like applicable

2109
01:48:55,320 --> 01:49:00,799
Speaker 1: to real world current problems is like it's noteworthy.

2110
01:49:01,000 --> 01:49:02,360
Speaker 5: Yep, I agree.

2111
01:49:02,479 --> 01:49:08,280
Speaker 1: I'm like, I'm supportive. I'm supportive of the pursuit mostly

2112
01:49:09,040 --> 01:49:11,080
Speaker 1: as much as I'd love to see a mammoth. I'm

2113
01:49:11,120 --> 01:49:14,360
Speaker 1: supportive of the pursuit because of the all the implications

2114
01:49:14,400 --> 01:49:16,439
Speaker 1: that you discussed about ways in which you can be

2115
01:49:16,520 --> 01:49:22,800
Speaker 1: currently currently helpful on real problems of species blinking out.

2116
01:49:23,200 --> 01:49:26,040
Speaker 6: You know, absolutely the journey is as important as a

2117
01:49:26,120 --> 01:49:28,240
Speaker 6: destination in this case, right we are. We are doing

2118
01:49:28,280 --> 01:49:31,280
Speaker 6: amazing things along the way. If we ever get to

2119
01:49:31,320 --> 01:49:33,719
Speaker 6: the point where we've had so much success that your

2120
01:49:33,800 --> 01:49:37,040
Speaker 6: concerns about the destination come into play, We've hit such

2121
01:49:37,040 --> 01:49:39,439
Speaker 6: a home run that we have made such a difference

2122
01:49:39,520 --> 01:49:42,280
Speaker 6: to the natural world that I think people really understand,

2123
01:49:42,439 --> 01:49:43,480
Speaker 6: you know, in retrospect.

2124
01:49:43,760 --> 01:49:45,760
Speaker 5: Why this pursuit is so important.

2125
01:49:47,479 --> 01:49:50,400
Speaker 1: When it comes time to find out the regulatory structure

2126
01:49:50,439 --> 01:49:54,760
Speaker 1: on mammoth haunts. I would appreciate if you guys can

2127
01:49:54,920 --> 01:49:55,400
Speaker 1: talk to us.

2128
01:49:55,720 --> 01:49:56,920
Speaker 3: Yeah, definitely hope.

2129
01:50:00,040 --> 01:50:02,640
Speaker 5: Hunter's orange necessary.

2130
01:50:03,160 --> 01:50:07,160
Speaker 1: All right, Matt James, some colossal biosciences. Thanks for coming out, man,

2131
01:50:07,200 --> 01:50:07,800
Speaker 1: Thank you so much.

2132
01:50:07,800 --> 01:50:08,559
Speaker 5: Guys, appreciate it.

2133
01:50:08,640 --> 01:50:08,960
Speaker 1: Thank you.

2134
01:50:18,800 --> 01:50:26,000
Speaker 4: It's a fresh instead of eyed. We'll always find more.

2135
01:50:26,920 --> 01:50:33,800
Speaker 11: Be crawl down in the car for them on your

2136
01:50:34,000 --> 01:50:46,240
Speaker 11: hands and knelt on my being the worm to tell you.

2137
01:50:45,320 --> 01:50:52,080
Speaker 4: You don't wrong. But come on, baby, last, not tonight.

2138
01:50:53,600 --> 01:51:00,280
Speaker 4: So listen to my song. Honey, I a hot pos

2139
01:51:00,400 --> 01:51:02,719
Speaker 4: Sam the pot with you.

2140
01:51:04,560 --> 01:51:11,400
Speaker 11: There's nothing that I can do, so feed the flame, Honey.

2141
01:51:11,040 --> 01:51:57,400
Speaker 4: I love you. I'm your pusson the hot line, my

2142
01:51:57,560 --> 01:52:01,240
Speaker 4: how phossum o you.

2143
01:52:03,320 --> 01:52:10,200
Speaker 11: There's nothing el that I can do, Sophia the Flame, Honey.

2144
01:52:09,840 --> 01:52:13,160
Speaker 2: I love you.

2145
01:52:13,160 --> 01:52:18,759
Speaker 4: You're Pusson. Oh wow, Pusson.

2146
01:52:19,920 --> 01:52:23,799
Speaker 11: You don't believe my honey, I'm You're person