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Speaker 1: Sounds on the side. It's episode sixteen, and I gotta say,

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Speaker 1: Scary and Brody are Brody and is Scary? The Brooklyn

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Speaker 1: Boys they told me to count every single episode. They're

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Speaker 1: up to like nine hundred and ninety seven million, and

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Speaker 1: they said they count every episode.

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Speaker 2: Don't do that. It's very outdated, like the Brooklyn Boys.

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Speaker 1: Oh burn woo.

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Speaker 2: That was for Scary personally.

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Speaker 1: Should we talk about how the studio caught on fire earlier?

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Speaker 3: That The aftermath of that was probably the best thing

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Speaker 3: I've ever seen because you were laughing. Scotty was laughing,

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Speaker 3: but Scary was doing like a nervous laugh. His heart

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Speaker 3: was clearly still racing.

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Speaker 2: I don't know.

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Speaker 1: Oh wait, oh, we have this sound. He was in

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Speaker 1: here recording a commercial and he heard like pops and

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Speaker 1: clicks and it all picks up. It is all we

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Speaker 1: have the sound. Let's play it right now. Hair and

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Speaker 1: Skilled Trades Training design.

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Speaker 4: To the fuck?

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Speaker 5: Is that?

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Speaker 4: Fuck?

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Speaker 1: What the fuck is going on?

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Speaker 4: Dude? What I heard that?

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Speaker 1: Twelve fucking popping noises like something.

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Speaker 4: Cold?

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Speaker 1: Jeff cold, Jeff, I'm pluging, Jeff, Jeff, Oh my god, Okay.

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Speaker 4: Is it the candle?

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Speaker 1: No, it's it's Jeff, Jeff, Jeff, help, come down here.

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Speaker 1: The USB port is exploding in front of Gandhi's thing.

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Speaker 1: I heard that sixteen pops.

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Speaker 4: You smell it. Oh my god, the fire alarm is

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Speaker 4: gonna go on. Come down here, please record it. If

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Speaker 4: I'm recording, I'm rolling on a commercial video recorded because

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Speaker 4: again and it's smoked because when you know what happen

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Speaker 4: when he comes here.

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Speaker 5: Of course that was it because something was plugged in.

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Speaker 4: No, it's proofed out of there. I saw it. Oh

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Speaker 4: my god.

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Speaker 3: I'm still recalling recording training design to accelerate entry into

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Speaker 3: the workforce, and.

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Speaker 4: There you go.

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Speaker 1: That is scary jobs.

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Speaker 2: He's done well in a panic wi Jeff, Jeff, help, Jeff?

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Speaker 1: The fuck is that?

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Speaker 2: The fuck? Was that? The fuck?

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Speaker 1: Oh my god? Okay, anyway, I'm really excited about the

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Speaker 1: guest today, Diamond. I know you're a little iffy about

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Speaker 1: what's going on, but we have a guy coming in.

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Speaker 1: His name is Ben Lamb. He is part of a

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Speaker 1: project and a company. The company is called Colossal, and

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Speaker 1: they are doing some really cool stuff. One of the

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Speaker 1: things that they are working on is bringing back the

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Speaker 1: wooly mammoth. Sounds crazy, right.

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Speaker 2: It's very weird.

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Speaker 1: But okay, okay, there are a lot of reasons that

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Speaker 1: they say this is a good idea, and I'm fascinated

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Speaker 1: as far as why is a good idea? Why the

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Speaker 1: wooly mammoth? How are you going to do this? You know,

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Speaker 1: I'm gonna just pepper him with questions, but we got

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Speaker 1: to get in here first. I am so so excited

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Speaker 1: about this. I am with Ben Lamb, CEO of Colossal.

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Speaker 1: Did I get that right?

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Speaker 4: Yes?

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Speaker 1: Yeah, okay, And Colossal is something that I have been

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Speaker 1: interested in since I found out about Colossal, but even

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Speaker 1: before that. Your partner, doctor George Church, I met him

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Speaker 1: years and years ago when I was in Boston. The

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Speaker 1: two of you together are working on something. Actually, there's

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Speaker 1: far more than two of you. There are a lot

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Speaker 1: of you.

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Speaker 4: If it was just us, we wouldn't we would not

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Speaker 4: be very far.

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Speaker 1: A lot of people working on this project. And the

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Speaker 1: project is too bring back the wooly mammoth.

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Speaker 5: As well as bringing back other species and develop technologies

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Speaker 5: for conservations.

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Speaker 1: Okay, so why are people focused on the wooly mammoth

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Speaker 1: right now?

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Speaker 4: Then?

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Speaker 5: It's what gets the headlines right. Everybody only wants to

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Speaker 5: talk about the wooly mammoth. Like, what's been funny is

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Speaker 5: we actually have more conservation applications of our de extinction

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Speaker 5: tools and technologies for conservation than anything else. But people

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Speaker 5: are like, that's fantastic, or we're like, hey, we were

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Speaker 5: working to save the northern white rhin.

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Speaker 4: No, that's amazing about this mammoth and so and so.

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Speaker 5: Then we announced the Thiolistan or Tasmanian tiger, we announced

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Speaker 5: the dodo, and people like those are amazing, but about

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Speaker 5: this mammoth.

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Speaker 1: Okay, so it's funny you say that. Because I actually

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Speaker 1: worked in reverse. I didn't look into as much as

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Speaker 1: I should have because I wanted to talk to you

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Speaker 1: about this stuff and find out this way. But I

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Speaker 1: was like, okay, so we're going to bring back the

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Speaker 1: wily mamoth. What about the animals now that really need help?

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Speaker 1: I specifically said to Diamond, like, oh, I know the

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Speaker 1: white rhino specifically, Yeah, maybe they could work on that.

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Speaker 1: So this is great. So you're working on not just

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Speaker 1: the wooly mammoth, which we will get to it. Now,

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Speaker 1: I want to know about the other ones.

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Speaker 4: We have three d extinction projects.

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Speaker 5: The wooly mammoth, Okay, the tasmani and tiger also known

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Speaker 5: as the thylacine, and then the Dodo bird from Mauritius.

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Speaker 4: Okay, those are our three D extinction projects.

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Speaker 5: But then we have a handful of conservation projects around

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Speaker 5: the world, and all of the technologies that we build

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Speaker 5: on the path to the extinction we're giving to conservation

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Speaker 5: in the world for free. So, you know, the extinction

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Speaker 5: is a very hard problem and you have to innovate

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Speaker 5: a lot of new technologies in order to make it successful.

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Speaker 5: You have to build the entire system, so little pieces

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Speaker 5: of that can go and help species now. And so

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Speaker 5: we can't save every species, but we can be this

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Speaker 5: like R and D lab for conservation that gets the

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Speaker 5: benefit of all of our technologies for free.

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Speaker 1: So what is keeping you from saving every species?

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Speaker 5: I mean, that's just a I mean, the only way

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Speaker 5: to save every species has changed hearts and minds, right, Like,

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Speaker 5: that's that's it. And there's some natural extinction rates that occurred.

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Speaker 5: You know, if we as humans weren't massively changing the

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Speaker 5: climate and polluting the climate and also polluting the environment

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Speaker 5: and you know, filling it with plastics and everything else, right,

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Speaker 5: and so so for us you know, I think that

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Speaker 5: the more sustainable model is go focus on a couple

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Speaker 5: of keystone giant, awesome species like the mammoth and the

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Speaker 5: thialis and the dodo, and then use those technologies and

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Speaker 5: empower conservationists. Right, there's you know, twenty five different rhino

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Speaker 5: groups out there. Let's give them the latest and greatest

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Speaker 5: technologies for conservation that they don't have time or money

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Speaker 5: to or even the resources and people to build.

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Speaker 4: Why don't we just do it and then just give

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Speaker 4: them that text?

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Speaker 5: So maybe we it's us trying to empower a ton

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Speaker 5: of different conservation groups.

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Speaker 4: Around the world. You know, we're not going to be

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Speaker 4: the sole conservation group.

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Speaker 1: So what made you pick these specific species?

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Speaker 5: So I didn't have a lot of choice on the

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Speaker 5: mammoth thing. Just be honest, Like, George has been working

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Speaker 5: on it, like you mentioned.

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Speaker 1: You Yeah, well probably seven are years ago.

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Speaker 5: Yeah, several years before like we met, George had been

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Speaker 5: working on it, had been doing all the competational analysis,

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Speaker 5: been collecting mammoth genomes, doing trips to Siberia.

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Speaker 1: How does one do that?

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Speaker 5: Yeah, it's it's there's lots of expeditions involved. So like

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Speaker 5: people think of Colossal as like just a lab company,

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Speaker 5: but there's a ton of field work. So you know,

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Speaker 5: we get the Jurassic part question quite frequently as you assume.

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Speaker 4: Yeah, yeah, I'm sure.

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Speaker 5: I'm sure dinosaurs and Jurassic Bug will come up with somewhere, right.

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Speaker 5: But there's also this like weird Indiana Jones component to

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Speaker 5: it where we actually go out into the field and

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Speaker 5: find samples, and we actually go and there's this crazy

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Speaker 5: like David Attenborough nature component where we're out there doing

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Speaker 5: conservation and like inoculating and helping animals in the field.

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Speaker 1: Right, So it's you're describing my dream.

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Speaker 4: It's a weird we're hiring.

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Speaker 5: I think people think it's just a lab thing, and

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Speaker 5: it's just not. It's it's just like really interesting mix

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Speaker 5: of stuff. And so we partner with great organizations. So

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Speaker 5: I'm part of the Explorers Club. Many of our top

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Speaker 5: advisors part of the Explorers Club. It's really this network,

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Speaker 5: you know, it's not just George and I. We've got

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Speaker 5: one hundred and thirty people at Colossal. We have sixty

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Speaker 5: scientific advisors around the world, and then we fund another

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Speaker 5: thirty or forty.

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Speaker 4: Post docs in lab.

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Speaker 5: So you know, we're over two hundred people that are

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Speaker 5: kind of working towards this crazy mission.

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Speaker 2: Where are you based?

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Speaker 4: So we're based in Dallas, Texas.

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Speaker 1: Okay, yeah, when you guys decided, actually, George Church decided

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Speaker 1: a long time ago that he thought it would be

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Speaker 1: a good idea to bring back the wooly mammoth. Tell

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Speaker 1: people why.

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Speaker 5: So George had looked at George had kind of like

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Speaker 5: this two part goal. One, if you can pick a

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Speaker 5: keystone species like the mammoth that had ecological benefits while

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Speaker 5: also looking for a species that isn't well studied, like

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Speaker 5: elephants and elephant reproductive systems, you could build technologies to

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Speaker 5: help save elephants because elephants will go extinct prey on

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Speaker 5: our lifetime, but maybe in the next generation's lifetime if

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Speaker 5: we don't do anything about it. There's a deadly herpes

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Speaker 5: virus that kills twenty percent of elephants every single year

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Speaker 5: that no.

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Speaker 4: One's done anything about.

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Speaker 5: We have the tools to fix it, just no one's

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Speaker 5: anything about it because they don't money in it. Right,

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Speaker 5: we have poaching, we have human elephant conflict, you know,

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Speaker 5: especially in parts of Afroa, parts of India, and so

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Speaker 5: it's like you've got all of these issues around around

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Speaker 5: you know, elephants today. But then separately, you've got this

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Speaker 5: crazy degraded ecosystem that's pretty absent of life, right, and

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Speaker 5: that's the that's this tundra, this art heard about the

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Speaker 5: Arctic tendra. Well most people don't realize this, but go

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Speaker 5: back ten thousand years. It was actually called the mammos

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Speaker 5: step and it was full of life. It had wooly

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Speaker 5: rhinos and dire wolves and wooly mammos and.

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Speaker 4: All other diolves are not just from gaming. They're not just.

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Speaker 5: From game of thro something every Yeah, yeah, we actually, yeah,

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Speaker 5: they're they're great, and so uh there's all kinds of species, right,

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Speaker 5: and so they're they're not a mythical creature. So they

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Speaker 5: had all these different species that lived in this ecosystem.

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Speaker 5: And what we found is that a more diverse ecosystem

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Speaker 5: leads to a higher kind of nitrogen oxygen turnover, so

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Speaker 5: that actually brings in more vegetation that actually like increases

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Speaker 5: kind of what this it's called the albedo effect, which

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Speaker 5: is our sign's turn where it's light reflection back into space.

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Speaker 5: So everything that's not absorbed into photosynthesis gets reflected back

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Speaker 5: into space, so it actually cools the ground temperatures in

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Speaker 5: the winter months, keeps the permafrost frozen. Why that's so

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Speaker 5: important is because there's more carbon in the permafrost stored

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Speaker 5: than all of the atmosphere by about two to three x,

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Speaker 5: so that stuff melts. We got bigger problems than the

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Speaker 5: problems we have today in the world, and so and

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Speaker 5: so George was like, Wow, we could start to build

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Speaker 5: a keystone species that we think that people would get

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Speaker 5: excited about because they're not like a bunch of hate

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Speaker 5: groups about mammos, right, people love mammos. So you could

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Speaker 5: inspire people, you could build technologies to help elephant conservation,

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Speaker 5: and you could start to revitalize this ecosystem that's completely.

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Speaker 4: Desolate of life now.

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Speaker 5: And it required us to go beyond Harvard and have

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Speaker 5: these academic partnerships and work in collaborations with groups like

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Speaker 5: the Explorers Club to really pull this off.

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Speaker 1: How hard has this been? When you guys pitched the idea, Hey,

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Speaker 1: we're thinking about bringing back the wooly mammo so that

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Speaker 1: we can prevent climate change and at least slow it.

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Speaker 1: What is the reaction?

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Speaker 5: So, so, what's crazy is we've gotten over eighty billion

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Speaker 5: media impressions, which is stupid. We pretty much stopped, yeah,

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Speaker 5: pretty much stopped counting. And so what we found is

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Speaker 5: that in a couple of different ways, we've we've kind

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Speaker 5: of like sparked the curiosity of like the young. Right,

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Speaker 5: so we get like we like my favorite on the

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Speaker 5: worst day at Colossal, when you like open up a

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Speaker 5: letter and it's like a mom that's like, thank you

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Speaker 5: so much for doing this. My kids are like asking

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Speaker 5: me about science, right, like I was Actually I was

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Speaker 5: actually in the Maladives on vacation, sitting at breakfast on

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Speaker 5: the small island, and I literally heard this woman behind

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Speaker 5: me say, hey, that's uh, I think that's a Dodo?

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Speaker 4: Is that a Dodo?

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Speaker 5: And the kids like, no, mom, the dodos extend. This

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Speaker 5: kid's like eleven or twelve, Like the Dodo is extinct,

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Speaker 5: but there is a company that's working to bring back

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Speaker 5: the Dodo.

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Speaker 1: And I was like, did you turn around like this?

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Speaker 4: I got, I turned around and like went and talked

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Speaker 4: to him for like twenty minutes. Right.

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Speaker 5: So on one part of it is like we've gotten

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Speaker 5: kids and parents people really excited about science. We all

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Speaker 5: sat in our house for a year and a half

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Speaker 5: with this COVID right, and it's like, shouldn't we be

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Speaker 5: doing more moonshots? Shouldn't we trying to help save the planet.

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Speaker 5: Shouldn't we like help conservation. So I think people are

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Speaker 5: there's a lot of people that are excited about it.

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Speaker 5: You know, we have an attitude towards our to the

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Speaker 5: negative naysayers, to run towards them. Like Best Shapiro, who

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Speaker 5: just joined as our chief science officer, who's amazing, number

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Speaker 5: one ancient.

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Speaker 1: He said, Beth Shapiro, Yeah, okay.

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Speaker 4: Yeah, Oh did you think? I said, no, it could have.

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Speaker 1: Not like Ben, you know, don't I would not be

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Speaker 1: on board side.

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Speaker 5: I don't think he's exactly qualified for this project. So yeah,

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Speaker 5: So but Beth Shapiro, number one ancient DNA researcher in

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Speaker 5: the world. She actually wrote the book How to Clone

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Speaker 5: a Mammoth, right, and so she's awesome. She was one

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Speaker 5: of our biggest naysayers. We went to her and said,

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Speaker 5: what are we doing wrong? How could we She's like,

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Speaker 5: you're pushing your climate models too far. You really need

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Speaker 5: more data to justify how many mammoths are there, and

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Speaker 5: we need to do a peer reviewed paper. We need

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Speaker 5: to understand what can survive there now. So I'm happy

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Speaker 5: to tell you that we have a peer view paper

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Speaker 5: right now. Took her advice right, and it takes years

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Speaker 5: to get peer of view papers. To have a peer

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Speaker 5: view paper in review, we listened to her. Our second

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Speaker 5: biggest naysayer when we launched was a guy named Louva Dollin.

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Speaker 4: I'm here with Luva in New York. He just sat

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Speaker 4: on my table at the Explorers Cup.

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Speaker 5: He's a number one Mammoth researcher, and he was like,

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Speaker 5: they didn't reach out to me, Like, I'm the number

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Speaker 5: one mamoth researcher in the entire world. They didn't talk

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Speaker 5: to me. So how do these guys think they're going

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Speaker 5: to be successful? And I'm the one that knows all

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Speaker 5: the genes that make a mammoth at the Mammoth right, So.

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Speaker 1: We listen to their point.

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Speaker 5: Yeah, So we listen to that feedback and we kind

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Speaker 5: of just run towards it. We really love the informed

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Speaker 5: critics because we wouldn't be where we are today without

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Speaker 5: Louva Dollan or Best Shapiro, and those were our two

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Speaker 5: biggest critics at launch.

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Speaker 1: I love this and now they're on your side. So

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Speaker 1: if this project succeeds, I think I saw online that

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Speaker 1: you guys planned to have this going by twenty twenty seven.

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Speaker 5: People are very excited about the dates because yeah, hello, yeah,

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Speaker 5: we are.

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Speaker 4: Too right, because we work, you know, twenty four to seven.

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Speaker 5: Yeah, we have set a big, hairy, colossal goal of

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Speaker 5: twenty twenty eight for our first mammoth caves.

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Speaker 4: Ok So twenty twenty eight is our first manoth cavs.

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Speaker 5: What I will say, just for fun, is there's a

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Speaker 5: twenty two month gestation for elephants.

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Speaker 4: So that means that.

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Speaker 5: We've got to have our embryos ready by at least

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Speaker 5: late twenty twenty six in order to see that we

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Speaker 5: are on track for that. For as much as excitement

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Speaker 5: as people had on the earlier announcements, I think the

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Speaker 5: announcements we're gonna have in the latter half this year

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Speaker 5: it's gonna be weird.

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Speaker 4: It's gonna be fun. Will we come back, Yeah, I'm sure.

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Speaker 5: I'm gonna work all the time, so I'm here once

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Speaker 5: a month, Okay, Yeah, so I'm happy to come back.

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Speaker 4: Keep you guys posted.

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Speaker 5: But I don't believe the mammoth will be the first

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Speaker 5: species for that is extinct.

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Speaker 1: Do you want to say what you believe will know?

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Speaker 4: I won't say what I want it ta Yeah, it's

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Speaker 4: good qualities.

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Speaker 1: Let's talk about the actual logistics of how this is

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Speaker 1: gonna work. So you're gonna have some calves first, how

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Speaker 1: many so.

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Speaker 5: We don't know, but I mean we want if you

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Speaker 5: look at elephant herds. We work really closely with elephant

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Speaker 5: conservation groups in Botswana elephant Havens, and then say the

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Speaker 5: elephants is the largest one in Kenya, and we're actually

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Speaker 5: using ai and droves and fleer cameras and others to

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Speaker 5: train models to understand how you rewild orphaned elephant babies

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Speaker 5: back into herds. So most likely the first hurd will

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Speaker 5: be eight to ten. That's kind of like what a

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Speaker 5: normal kind of small the mid sized herd is.

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Speaker 1: But who's going to raise the baby calves and teach

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Speaker 1: them how to be big grown mammis.

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Speaker 4: Yeah, that's a great question.

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Speaker 5: So that's what So one of our partners, elephant Havens,

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Speaker 5: that's what they do with all day long with African elephants, right,

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Speaker 5: is they they look at orphaned elephants. They save orphan

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Speaker 5: elephants they help build those herd dynamics help teach these things.

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Speaker 5: What's incredible about a lot of species, especially some of

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Speaker 5: the smarter species, is you know, it takes us a

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Speaker 5: while to like walk and talk and whatnot, but there's

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Speaker 5: lots of species that come out. They know how to

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Speaker 5: eat yea, they know how to walk. They even speak

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Speaker 5: their own language, right. Like, I had this really interesting

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Speaker 5: conversation with this indigenous tribal leader about how he was

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Speaker 5: telling me how wolves in weird ways are smarter than

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Speaker 5: us because they can speak their own language from.

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Speaker 4: Day one, and they're like, we don't. We have to

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Speaker 4: learn this, and we're pretty bad at it even after

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Speaker 4: we learn it.

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Speaker 1: Right, Some people never really get a grass people.

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Speaker 4: I think some are very generoud, most people never do.

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Speaker 5: So for us, you know, working with elephant conservation groups,

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Speaker 5: understanding those models is key. Asian elephants will be the

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Speaker 5: surrogates for the first mammoth caves and so there will

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Speaker 5: be a lot of that social behavior that works together.

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Speaker 5: And some people are like, but Asian elephants are like

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Speaker 5: tropical and hot yes where yes exactly, So so we

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Speaker 5: get those questions right and so right now you know

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Speaker 5: our roles put them back into the Arctic Circle in

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Speaker 5: an area called Circle Polar North, which is actually a

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Speaker 5: little bit further. It comes down a little bit into

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Speaker 5: Lower Canada and northern United States. Right now, we are

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Speaker 5: focusing mostly on Alaska and Canada given.

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Speaker 4: All the geopolitical conflicts that we're seeing in Russia.

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Speaker 1: Yeah.

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Speaker 5: But what's interesting though, is one of our partners in

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Speaker 5: Canada has elephants on this big refuge and these are

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Speaker 5: Asian elephants, and we've been up there and we have

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Speaker 5: videos of them like rolling around in the snow. These

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Speaker 5: are not Arctic adapted, genetically modified mammoth elephants. These are

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Speaker 5: just Asian elephants, like straight out the womb, right, and

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Speaker 5: they are running around, they're breaking through the ice. They're

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Speaker 5: actually swimming in frozen lakes, and you'd be like, how

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Speaker 5: is that possible?

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Speaker 4: But most people.

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Speaker 5: Don't realize this also about mammis. During the during the

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Speaker 5: last two and a half million years, you had the Pleissistine, right,

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Speaker 5: which is like what we think of with like ice age,

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Speaker 5: and then you have the Holocen which we're in now.

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Speaker 5: But there's been these different kind of interglacial moments where

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Speaker 5: there are actually periods over the last one hundred thousand

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Speaker 5: years where mammis survived very well that were actually hotter

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Speaker 5: than today, And so mammis actually we have data that

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Speaker 5: shows that they traverse pretty far south, so they actually

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Speaker 5: were in pretty warm, temperate climates. They could survive you know,

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Speaker 5: here quite easily, but then they could go up to

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Speaker 5: negative forty so they really had that versatility.

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Speaker 4: Wow.

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Speaker 1: Yeah, so you got these They're going to be sort

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Speaker 1: of introduced into a herd of Asian elephants somewhere up north.

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Speaker 4: Yes, somewhere up north.

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Speaker 1: How long is it going to take for these calves?

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Speaker 1: Because what I read was, and again correct me if

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Speaker 1: I'm wrong, very well for you, that the DNA is

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Speaker 1: ninety nine percent Asian elephant, yeah, and one percent the mammoth.

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Speaker 4: So that yeah, so it's ninety nine point six percent.

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Speaker 1: Nine nine point six Asian elephants.

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Speaker 5: Ninety nine point six percent genetically the same as a mammoth. Uh,

404
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Speaker 5: they're actually this is this is kind of fun dinner

405
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Speaker 5: trivia feat.

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Speaker 4: Yes, they are actually closer related.

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Speaker 5: Mammas are closer related to Asian elephants than Asian elephants

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Speaker 5: are to African elephants. Okay, yeah, that when I learned

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Speaker 5: that kind of blew my mind. That was one instring fact.

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Speaker 5: The second in string fact I learned that blew my

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Speaker 5: mind is that when we were we as humanity, not colossal,

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Speaker 5: we're building the pyramids. Uh, they're a mamos running around

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Speaker 5: and that like sometimes people like group mammoths back into

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Speaker 5: like the dinosaurs.

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Speaker 4: Absolutely, they're not sixty five million years.

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Speaker 1: Right, They're not going to be the first generation of

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Speaker 1: these the calves, they're not going to be full on

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Speaker 1: wily mammos. Right, It's going to take some more generational

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Speaker 1: breeding for them to actually become full on willly mamas.

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Speaker 1: How long is that going to take?

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Speaker 4: That?

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Speaker 5: But that goes to purpose, right, Okay, so we think

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Speaker 5: of we're not trying to clone extinct species at colossal, right,

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Speaker 5: And so the way that the world currently defines de extinction,

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Speaker 5: like feid to Wikipedia, it says, either an animal that's

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Speaker 5: engineered to look like an extinct species.

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Speaker 4: Which we think is kind of dumb. Yeah, yeah, like

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Speaker 4: that's just dumb.

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Speaker 2: Yeah.

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Speaker 5: The second thing is a clone is a clone of

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Speaker 5: that extinct species. But like, you're never going to be

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Speaker 5: able to clone extinct species. I try to say never

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Speaker 5: or impossible. I currently do not see a technological path

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Speaker 5: to where you can clone dead cells and get one

435
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Speaker 5: hundred percent accuracy, because the minute we take blood out

436
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Speaker 5: of you or me or anybody, it starts to degrade

437
00:18:44,000 --> 00:18:47,120
Speaker 5: environmental factors. Right, So imagine ten thousand year old DNA.

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Speaker 4: Is pretty fragmented.

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Speaker 5: So we view de extinction at colossal differently than how

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Speaker 5: it's currently defined.

441
00:18:52,640 --> 00:18:53,920
Speaker 4: We define it more.

442
00:18:53,720 --> 00:18:57,080
Speaker 5: As rebuilding extinct species for today, So we don't ever

443
00:18:57,200 --> 00:19:00,000
Speaker 5: really care if we get to ninety nine point nine

444
00:19:00,040 --> 00:19:03,199
Speaker 5: nine nine nine percent of mammoth. If we if we

445
00:19:03,480 --> 00:19:07,800
Speaker 5: successfully genetically de extinct the core genes that drove the

446
00:19:07,800 --> 00:19:10,040
Speaker 5: phenotypes or physical attributes.

447
00:19:09,680 --> 00:19:11,720
Speaker 4: Of a mammoth, so that's now cold adaptive.

448
00:19:11,760 --> 00:19:14,200
Speaker 5: So those are things like the small ears, dom cranium,

449
00:19:14,359 --> 00:19:16,879
Speaker 5: that fat layer, the big shaggy coat that we always

450
00:19:16,880 --> 00:19:17,320
Speaker 5: think of like.

451
00:19:17,280 --> 00:19:19,560
Speaker 1: You're describing me, no no, no.

452
00:19:19,320 --> 00:19:22,480
Speaker 5: No no, the big shaggy the big shaggy coat that

453
00:19:22,480 --> 00:19:24,600
Speaker 5: we all think of, right yeah, like snuffy, yeah, exactly

454
00:19:24,640 --> 00:19:26,800
Speaker 5: when we think of stuff like if that is the

455
00:19:26,880 --> 00:19:30,520
Speaker 5: curve tuss, if we distinct those core phenotypes that have

456
00:19:30,600 --> 00:19:33,880
Speaker 5: been lost to time, then we think that's successful.

457
00:19:33,920 --> 00:19:35,440
Speaker 4: If the mammoth. Now there's other things that are like

458
00:19:35,520 --> 00:19:37,119
Speaker 4: kind of under the hood type stuff where it's like

459
00:19:37,440 --> 00:19:39,600
Speaker 4: how the nerve endings work.

460
00:19:39,680 --> 00:19:43,040
Speaker 5: So in a lot of cold adapted animals, their nerve

461
00:19:43,119 --> 00:19:45,760
Speaker 5: endings work slightly different than us, Like ours actually freeze

462
00:19:46,040 --> 00:19:49,320
Speaker 5: and they fry. They basically get fried at certain temperatures. Right,

463
00:19:49,400 --> 00:19:52,080
Speaker 5: but polar bears, caribou mammos didn't.

464
00:19:52,160 --> 00:19:52,320
Speaker 4: Right.

465
00:19:52,600 --> 00:19:55,920
Speaker 5: How they produce oxygen through hemoglobin is completely different than us.

466
00:19:56,200 --> 00:19:59,600
Speaker 5: Right because at negative forty our lungs crystallized yea and

467
00:19:59,600 --> 00:20:00,880
Speaker 5: we can't these red blood cells.

468
00:20:00,920 --> 00:20:03,320
Speaker 4: So therefore we get oxygen our bodies. Right, so we

469
00:20:03,359 --> 00:20:04,800
Speaker 4: actually suffcate. So if we.

470
00:20:04,800 --> 00:20:08,639
Speaker 5: Bring back those things, those those core genes, you know,

471
00:20:08,720 --> 00:20:12,040
Speaker 5: that does not make it one hundred percent a mammoth,

472
00:20:12,080 --> 00:20:15,440
Speaker 5: but if it meets the physical kind of look definition,

473
00:20:15,800 --> 00:20:20,080
Speaker 5: and more importantly, it meets the ecological impact definition. And

474
00:20:20,240 --> 00:20:22,840
Speaker 5: even more importantly, it is those core genes that we

475
00:20:22,920 --> 00:20:26,080
Speaker 5: have identified using you know, competitional analysis and AI and

476
00:20:26,160 --> 00:20:28,160
Speaker 5: brought those genes back that have been lost to time.

477
00:20:28,720 --> 00:20:30,800
Speaker 4: That's how we define the exchange. Now other people may

478
00:20:30,800 --> 00:20:31,760
Speaker 4: define it differently.

479
00:20:32,520 --> 00:20:34,640
Speaker 5: Now we also layer in some other stuff we want

480
00:20:34,640 --> 00:20:38,439
Speaker 5: to also enhance the animals, and we want to engineering resilience.

481
00:20:38,680 --> 00:20:40,679
Speaker 5: You know, I mentioned that herpes virus, that there's a

482
00:20:40,720 --> 00:20:44,000
Speaker 5: deadly herpes virus EEHV that we're working to eradicate. It

483
00:20:44,119 --> 00:20:46,600
Speaker 5: kills twenty percent of Asian elephants every single year, way

484
00:20:46,600 --> 00:20:49,080
Speaker 5: more than port poaching. And it's like in a Bola

485
00:20:49,160 --> 00:20:52,199
Speaker 5: level death. It's it's just fucking terrible. It's awful, but

486
00:20:52,240 --> 00:20:54,320
Speaker 5: no one's solved it yet because there's not a lot

487
00:20:54,359 --> 00:20:57,000
Speaker 5: of money in just curing elephant herpes, even though it's

488
00:20:57,200 --> 00:20:59,320
Speaker 5: a terrible disease. Well, if we're going to spend all

489
00:20:59,320 --> 00:21:02,080
Speaker 5: this effort in money to make these mammis, they are

490
00:21:02,119 --> 00:21:06,000
Speaker 5: genetically susceptible to this disease. So a purest perspective of

491
00:21:06,119 --> 00:21:08,679
Speaker 5: the extinction would say, well then you can't, you know,

492
00:21:08,800 --> 00:21:12,800
Speaker 5: engineer and resilience. But it's like why like why would

493
00:21:12,840 --> 00:21:15,119
Speaker 5: we not try to make these animals the healthiest and

494
00:21:15,160 --> 00:21:18,239
Speaker 5: the best they can for survivability, right, And so we

495
00:21:18,280 --> 00:21:21,960
Speaker 5: are engineering. We have early indications of our vaccine with

496
00:21:22,320 --> 00:21:26,159
Speaker 5: doctor Pauline at Baylor College of Medicine, and if that's successful,

497
00:21:26,280 --> 00:21:28,719
Speaker 5: then we were going to engineer that into our mammis.

498
00:21:28,760 --> 00:21:30,960
Speaker 5: And so that's why we go back to this whole

499
00:21:31,160 --> 00:21:33,920
Speaker 5: concept of the extinction should be really about you know,

500
00:21:34,320 --> 00:21:37,879
Speaker 5: rebuilding extinct species for thriving today, not just trying to

501
00:21:37,880 --> 00:21:38,840
Speaker 5: clone the past.

502
00:21:39,280 --> 00:21:41,560
Speaker 1: So you're going to have these calves, yeah, yeah, male

503
00:21:41,640 --> 00:21:42,520
Speaker 1: or female.

504
00:21:43,000 --> 00:21:44,440
Speaker 4: Probably mostly female to start.

505
00:21:44,760 --> 00:21:45,919
Speaker 1: What's the reasoning behind that?

506
00:21:46,520 --> 00:21:50,000
Speaker 5: Just because you in elephant herd dynamics you kind of

507
00:21:50,040 --> 00:21:51,520
Speaker 5: look at that males go off at.

508
00:21:51,480 --> 00:21:55,480
Speaker 4: A certain age and then they recavoc Yeah, they procreate

509
00:21:55,560 --> 00:21:56,040
Speaker 4: and whatnot.

510
00:21:56,200 --> 00:21:57,119
Speaker 1: What are they going to eat?

511
00:21:57,359 --> 00:21:58,119
Speaker 4: That's a great question.

512
00:21:58,160 --> 00:22:03,440
Speaker 5: So most mammis actually just a you know, like existing elephants.

513
00:22:03,680 --> 00:22:06,119
Speaker 5: They ate grasses, the Arctic grasses, they ate the mosses,

514
00:22:06,240 --> 00:22:08,680
Speaker 5: ate the shrubs in the trees up there. They knocked

515
00:22:08,680 --> 00:22:12,359
Speaker 5: down they actually knocked down trees. Elephants are weird about

516
00:22:12,680 --> 00:22:14,680
Speaker 5: loving knocking down trees. And I know, we like grew

517
00:22:14,720 --> 00:22:16,200
Speaker 5: up and they're like planet a tree, plant tree, and

518
00:22:16,200 --> 00:22:18,919
Speaker 5: people should totally plant trees. Colossal does not have a

519
00:22:18,960 --> 00:22:21,520
Speaker 5: position that's anti tree, clear, but.

520
00:22:23,200 --> 00:22:25,480
Speaker 4: I actually but what's.

521
00:22:25,240 --> 00:22:28,919
Speaker 5: Interesting is not all trees are created equal, and so

522
00:22:29,040 --> 00:22:33,000
Speaker 5: like for example, the tiger forests are these terrible carniferous trees.

523
00:22:33,280 --> 00:22:36,120
Speaker 5: They are like the worst carbon stores. They almost act

524
00:22:36,160 --> 00:22:39,439
Speaker 5: as like heat lightning rods that permeate the sun's radiation

525
00:22:39,840 --> 00:22:42,240
Speaker 5: down in the root structure and help increase the speed

526
00:22:42,280 --> 00:22:44,720
Speaker 5: at which the permafrost melts.

527
00:22:44,800 --> 00:22:44,960
Speaker 4: Right.

528
00:22:45,119 --> 00:22:48,440
Speaker 5: And there's actually been some really weird but amazing scientific

529
00:22:48,480 --> 00:22:51,399
Speaker 5: studies that have come out of Africa and Gobon looking

530
00:22:51,440 --> 00:22:54,840
Speaker 5: at forest elephants and how they actually love They also

531
00:22:54,880 --> 00:22:56,960
Speaker 5: love to knock down trees, but they don't knock down

532
00:22:57,040 --> 00:22:59,160
Speaker 5: the trees. They know which trees are like the most

533
00:22:59,160 --> 00:23:01,960
Speaker 5: efficient at carbon of course, and they don't they don't

534
00:23:02,000 --> 00:23:02,600
Speaker 5: knock them down.

535
00:23:02,840 --> 00:23:06,040
Speaker 4: They only knock down kind of the shittier trees. It's amazing,

536
00:23:06,359 --> 00:23:08,679
Speaker 4: that's I mean, love to watch it.

537
00:23:08,880 --> 00:23:11,800
Speaker 5: You should go down this like forest elephant carbon tree

538
00:23:11,880 --> 00:23:13,639
Speaker 5: knocking down rabbital It's the weirdest.

539
00:23:13,640 --> 00:23:15,960
Speaker 1: Well, guess what I'm doing later today. Then, So they're

540
00:23:15,960 --> 00:23:18,240
Speaker 1: gonna they're gonna have their own ecosystem. They'll be able

541
00:23:18,240 --> 00:23:20,080
Speaker 1: to survive on whatever is there. So you guys are

542
00:23:20,119 --> 00:23:23,719
Speaker 1: not going to also introduce new plants or anything like that.

543
00:23:23,840 --> 00:23:27,080
Speaker 5: But there have been studies that have shown that the

544
00:23:27,600 --> 00:23:30,480
Speaker 5: reintroduction with the removal of the tyg of forests and

545
00:23:30,520 --> 00:23:33,760
Speaker 5: the reintroduction of other coal tolerant mammals that the Arctic

546
00:23:33,800 --> 00:23:36,360
Speaker 5: grasslands come back naturally, right, And we see.

547
00:23:36,200 --> 00:23:37,159
Speaker 4: This all over the world. Right.

548
00:23:37,200 --> 00:23:40,280
Speaker 5: So we're working also in Mauritius with Mauritian Wildlife Foundation

549
00:23:40,320 --> 00:23:42,600
Speaker 5: to bring back the bring back the dodo.

550
00:23:42,880 --> 00:23:45,000
Speaker 4: And I'm totally butitch for the story because we're all

551
00:23:45,119 --> 00:23:45,720
Speaker 4: involved in it.

552
00:23:46,160 --> 00:23:52,600
Speaker 5: Basically, there was this large uh like Galopicus style tortoise that.

553
00:23:52,280 --> 00:23:55,600
Speaker 4: That they hunted to extinction, that went extinct and extinct Maurcius, right.

554
00:23:55,880 --> 00:23:59,080
Speaker 5: But what they've done recently is they've reintroduced a similar

555
00:23:59,080 --> 00:24:03,159
Speaker 5: turtle from Say, which is a neighboring island. They reintroduced

556
00:24:03,160 --> 00:24:05,560
Speaker 5: it and then all of a sudden, like they started

557
00:24:05,600 --> 00:24:07,800
Speaker 5: seeing this weird plant that no one had seen in

558
00:24:07,840 --> 00:24:08,440
Speaker 5: like fifty years.

559
00:24:08,800 --> 00:24:11,280
Speaker 4: Where's this plant coming from? This is amazing?

560
00:24:11,560 --> 00:24:14,760
Speaker 5: And what they found was there something about the the

561
00:24:14,840 --> 00:24:19,840
Speaker 5: gestational track of the tortoise that allows this like it

562
00:24:20,240 --> 00:24:24,359
Speaker 5: partly germinates in the gestational attack of the tortoise based

563
00:24:24,359 --> 00:24:27,960
Speaker 5: on this other plant that it eats. So bringing back

564
00:24:28,040 --> 00:24:31,880
Speaker 5: that tortoise has created this new plant life and new

565
00:24:31,920 --> 00:24:34,280
Speaker 5: fauna that they hadn't seen in like fifty years.

566
00:24:34,280 --> 00:24:36,400
Speaker 4: That they thought was extinct. That wasn't extinct.

567
00:24:36,400 --> 00:24:38,439
Speaker 5: It just didn't have the right system for the for

568
00:24:38,480 --> 00:24:40,879
Speaker 5: the entire ecology to work together. I do think that

569
00:24:40,920 --> 00:24:46,320
Speaker 5: we will have a more robust and more divert biodiverse ecosystem.

570
00:24:46,760 --> 00:24:49,200
Speaker 1: So this turtle, this tortoise that you were talking about,

571
00:24:49,359 --> 00:24:51,560
Speaker 1: was brought back. I didn't know that. Are there other

572
00:24:51,640 --> 00:24:56,040
Speaker 1: species that have been d have become stinct?

573
00:24:56,080 --> 00:24:59,080
Speaker 4: So that was really the extinction that was how do you.

574
00:24:59,080 --> 00:25:04,480
Speaker 1: Even say that have become what I would say resurrected, resurrected, Okay,

575
00:25:04,560 --> 00:25:07,520
Speaker 1: I think the extinction, Yeah sounds weird.

576
00:25:07,680 --> 00:25:10,440
Speaker 5: Okay, but probably should but I think it sounds weird.

577
00:25:10,560 --> 00:25:14,000
Speaker 5: So that that was just a process called rewilding. So

578
00:25:14,000 --> 00:25:15,440
Speaker 5: they were just rewilding that species.

579
00:25:15,520 --> 00:25:16,840
Speaker 4: Okay, back there from another thing.

580
00:25:16,880 --> 00:25:19,879
Speaker 5: So like something similar that's kind of more related to

581
00:25:19,880 --> 00:25:22,479
Speaker 5: the United States was Yellowstone, right, So like in nineteen

582
00:25:22,520 --> 00:25:26,120
Speaker 5: twenty five they called, you know, we as humans were

583
00:25:26,119 --> 00:25:27,000
Speaker 5: super smart, right.

584
00:25:27,119 --> 00:25:29,960
Speaker 4: And we're like, wolves are bad because we've heard.

585
00:25:29,680 --> 00:25:31,959
Speaker 5: That they like, you know, ate red riding hood and

586
00:25:32,040 --> 00:25:35,320
Speaker 5: they ate our you know, our cattle. By the way,

587
00:25:35,359 --> 00:25:37,400
Speaker 5: cattle isn't raised like that anymore. And so I don't

588
00:25:37,440 --> 00:25:39,640
Speaker 5: think a wolf even wants to go near cattle farm.

589
00:25:39,520 --> 00:25:41,280
Speaker 1: Because they're discussed disgusted by.

590
00:25:41,119 --> 00:25:44,280
Speaker 5: The Yeah, and so yeah, they like, you know, they

591
00:25:44,400 --> 00:25:47,280
Speaker 5: blew the pig's house down, Like wolves are just evil, right.

592
00:25:47,520 --> 00:25:49,720
Speaker 5: We had this mentality, and so in nineteen twenty five

593
00:25:50,400 --> 00:25:52,359
Speaker 5: in Yellowstone they're like, we have to call the wolves.

594
00:25:52,359 --> 00:25:55,840
Speaker 5: So they killed all the wolves and and then seventy

595
00:25:55,920 --> 00:25:59,080
Speaker 5: years later they reintroduced like fourteen or fifteen wolves, like

596
00:25:59,119 --> 00:26:01,760
Speaker 5: not even that many wolves, and in five years the

597
00:26:01,760 --> 00:26:05,040
Speaker 5: park completely changed. There's more by there's more plant life,

598
00:26:06,320 --> 00:26:11,280
Speaker 5: more dynamic river flow, and more more species, not less,

599
00:26:11,280 --> 00:26:14,120
Speaker 5: because there's this mentality that like, if the wolves are here,

600
00:26:14,440 --> 00:26:16,080
Speaker 5: they're going to kill all the species, so we have

601
00:26:16,119 --> 00:26:18,280
Speaker 5: to get rid of them. But what they didn't realize

602
00:26:18,320 --> 00:26:21,240
Speaker 5: is that the absence of wolves made things like the

603
00:26:21,320 --> 00:26:25,840
Speaker 5: elk and the large herbivores and bison stopped to migrate,

604
00:26:26,080 --> 00:26:29,119
Speaker 5: and then they overprocreate and they overgraze. And then with

605
00:26:29,240 --> 00:26:31,480
Speaker 5: that stop of migration, they stay in like one area

606
00:26:31,480 --> 00:26:34,000
Speaker 5: and they ate like all the stuff around, you know,

607
00:26:34,080 --> 00:26:36,320
Speaker 5: the banks of rivers, So then the beavers can build

608
00:26:36,320 --> 00:26:39,040
Speaker 5: their dams. That means the rivers and the ponds didn't

609
00:26:39,040 --> 00:26:41,520
Speaker 5: exist that or they at least were much more shallow.

610
00:26:41,560 --> 00:26:43,920
Speaker 5: That means that the temperature can work for certain types

611
00:26:43,920 --> 00:26:46,359
Speaker 5: of fish and salmon. And so there's this like entire

612
00:26:46,400 --> 00:26:50,199
Speaker 5: it's called tropic downgrading. There's entire like ripple effect of

613
00:26:50,240 --> 00:26:53,800
Speaker 5: when you remove a keystone species. And so the world

614
00:26:53,920 --> 00:26:57,639
Speaker 5: is getting better at reintroducing and kind of undoing the sins.

615
00:26:57,400 --> 00:26:57,879
Speaker 4: Of the past.

616
00:26:58,440 --> 00:27:00,639
Speaker 1: So you don't think that there's any aspect of this

617
00:27:00,720 --> 00:27:02,960
Speaker 1: that is in some ways screwing with nature by bringing

618
00:27:02,960 --> 00:27:03,600
Speaker 1: this stuff back.

619
00:27:03,720 --> 00:27:05,320
Speaker 4: I think that we have a duty to do it right.

620
00:27:05,359 --> 00:27:08,520
Speaker 5: And so like there's evidence, you know, we killed the

621
00:27:08,600 --> 00:27:12,000
Speaker 5: thylacine in nineteen thirty six was when the.

622
00:27:12,000 --> 00:27:13,120
Speaker 4: Last one went extinct.

623
00:27:13,640 --> 00:27:16,800
Speaker 5: Wow, and which ironically his name was Benjamin but the

624
00:27:17,480 --> 00:27:21,960
Speaker 5: but but the United the the government of Australia actually

625
00:27:22,000 --> 00:27:24,760
Speaker 5: put a bounty on their heads and like and like

626
00:27:24,800 --> 00:27:28,400
Speaker 5: we eradicate them for right. The Dutch introduced invasive species

627
00:27:28,440 --> 00:27:31,000
Speaker 5: and killed the dodos. Right, if you look at the

628
00:27:31,080 --> 00:27:33,399
Speaker 5: rise of early man. There's been debates on the mammis,

629
00:27:33,520 --> 00:27:35,439
Speaker 5: but if you really if you look at the rise

630
00:27:35,520 --> 00:27:39,639
Speaker 5: of early man in in in the US and in

631
00:27:40,119 --> 00:27:45,960
Speaker 5: and in Siberia, in the decline of mammas. They're exactly imverse, right,

632
00:27:46,000 --> 00:27:47,880
Speaker 5: And they didn't have to kill them, all right, they

633
00:27:47,880 --> 00:27:50,320
Speaker 5: just had to kill enough of them to send them

634
00:27:50,320 --> 00:27:51,920
Speaker 5: down this path as we as we.

635
00:27:51,880 --> 00:27:52,359
Speaker 4: Talked about it.

636
00:27:52,359 --> 00:27:55,960
Speaker 5: And so I feel like we have a responsibility if

637
00:27:55,960 --> 00:27:58,120
Speaker 5: we have the technologies, Like I feel like we play

638
00:27:58,160 --> 00:28:01,000
Speaker 5: god every day when we like eradicate these vcs or

639
00:28:01,040 --> 00:28:02,880
Speaker 5: when we like cut down the forest or.

640
00:28:02,840 --> 00:28:04,600
Speaker 4: Take medicine for ourselves.

641
00:28:05,000 --> 00:28:07,760
Speaker 5: So like, if we have these tools and technologies, why

642
00:28:07,800 --> 00:28:10,040
Speaker 5: not you know, undo some of the sins of the

643
00:28:10,080 --> 00:28:13,439
Speaker 5: past while also building technologies that can help conservation. And

644
00:28:13,480 --> 00:28:15,960
Speaker 5: so you know, that's part our core of our mission

645
00:28:15,960 --> 00:28:19,240
Speaker 5: is that everything that we develop from a the extinction

646
00:28:19,320 --> 00:28:21,680
Speaker 5: perspective in this pipeline, we just give to the world

647
00:28:21,720 --> 00:28:22,280
Speaker 5: for free.

648
00:28:22,520 --> 00:28:24,680
Speaker 1: That's incredible. So what's in it for you then? Just

649
00:28:24,680 --> 00:28:25,320
Speaker 1: saving the earth?

650
00:28:25,600 --> 00:28:27,919
Speaker 4: No, I mean they're I mean different you know, strokes

651
00:28:27,920 --> 00:28:28,520
Speaker 4: for different folks.

652
00:28:28,600 --> 00:28:31,680
Speaker 5: Right For me, you know, I think it's I built

653
00:28:31,680 --> 00:28:35,080
Speaker 5: a bunch of technology companies. I like building teams of

654
00:28:35,119 --> 00:28:36,760
Speaker 5: women and men that are much smarterer than me. So

655
00:28:36,840 --> 00:28:39,960
Speaker 5: I get I love building hard challenges. I also like

656
00:28:40,000 --> 00:28:42,480
Speaker 5: building systems because like software is mostly a system.

657
00:28:42,640 --> 00:28:43,880
Speaker 1: Is that your background mostly?

658
00:28:44,000 --> 00:28:44,280
Speaker 2: Okay?

659
00:28:44,320 --> 00:28:46,640
Speaker 5: Yeah, so technology mostly software. I did a little space

660
00:28:46,680 --> 00:28:49,240
Speaker 5: hardware stuff, so I don't have a biology background at all.

661
00:28:49,400 --> 00:28:53,000
Speaker 5: So I'm learning it as as as fast as I can.

662
00:28:53,120 --> 00:28:55,160
Speaker 1: You present it quite well. I would buy it if

663
00:28:55,200 --> 00:28:56,320
Speaker 1: you just told me, like, hey, I do have a

664
00:28:56,360 --> 00:28:57,959
Speaker 1: biology background. Yeah, I believe that.

665
00:28:58,120 --> 00:29:00,640
Speaker 5: George said that I'm one of his better students he's

666
00:29:00,680 --> 00:29:02,960
Speaker 5: never had. So I had to unpack that for a

667
00:29:02,960 --> 00:29:04,720
Speaker 5: minute because he said it really early in the morning once,

668
00:29:04,760 --> 00:29:06,200
Speaker 5: and I was like, it's a good thing.

669
00:29:06,560 --> 00:29:08,360
Speaker 1: But yeah, so so far it seems like this is

670
00:29:08,360 --> 00:29:09,400
Speaker 1: a great plan ALTA.

671
00:29:10,560 --> 00:29:12,560
Speaker 5: It's going well and there are lots of ways to

672
00:29:12,600 --> 00:29:16,120
Speaker 5: make money from it, right, and so like the system

673
00:29:16,160 --> 00:29:18,880
Speaker 5: that we are developing, not only can it help conservation

674
00:29:19,000 --> 00:29:22,280
Speaker 5: and be helpful for the extinction, but we are spinning

675
00:29:22,280 --> 00:29:25,440
Speaker 5: out tools and technologies. We have another company that is

676
00:29:25,520 --> 00:29:30,680
Speaker 5: gestated at Colossal that we announced last week called Breaking.

677
00:29:31,320 --> 00:29:32,440
Speaker 4: We're super stoked about this.

678
00:29:32,680 --> 00:29:35,000
Speaker 1: Is that the plastics? Yeah, okay, yes, tell me about that.

679
00:29:35,080 --> 00:29:35,280
Speaker 4: Yeah.

680
00:29:35,320 --> 00:29:39,240
Speaker 5: So, so we did not discover it at Colossal, was

681
00:29:39,240 --> 00:29:43,480
Speaker 5: discovered by an incredible woman named Sukanya and our partner

682
00:29:43,480 --> 00:29:47,880
Speaker 5: of BASCAR that they actually discovered it while working at

683
00:29:48,160 --> 00:29:50,400
Speaker 5: the VS Institute, which is a part of Harvard and

684
00:29:50,480 --> 00:29:54,880
Speaker 5: working with George And what's interesting is they found this

685
00:29:55,080 --> 00:29:59,280
Speaker 5: micro x thirty two through a process called bioprospecting, and

686
00:29:59,360 --> 00:30:02,680
Speaker 5: they found microbe and actually a series of microbes, but

687
00:30:02,720 --> 00:30:07,240
Speaker 5: this one microbe that eats everything, every plastic that they've

688
00:30:07,240 --> 00:30:08,760
Speaker 5: thrown at it. Right, And so if you look at

689
00:30:08,800 --> 00:30:11,719
Speaker 5: like the spectrum of plastic, it goes from like, you know,

690
00:30:12,200 --> 00:30:15,520
Speaker 5: very easy to degrade, like the super recyclable stuff to

691
00:30:15,640 --> 00:30:18,800
Speaker 5: like the industrial like military complex stuff.

692
00:30:18,520 --> 00:30:20,280
Speaker 4: That's like virtually impossible.

693
00:30:20,640 --> 00:30:22,959
Speaker 5: And it was able to degrade things that were not

694
00:30:23,080 --> 00:30:27,600
Speaker 5: possible to degrade, that would not naturally degrade, and also

695
00:30:27,880 --> 00:30:29,760
Speaker 5: things that would take about eight hundred years in twenty

696
00:30:29,800 --> 00:30:32,200
Speaker 5: two months, and all you had to do is add

697
00:30:32,200 --> 00:30:32,920
Speaker 5: salt and water.

698
00:30:33,240 --> 00:30:34,320
Speaker 4: And so what's really important.

699
00:30:34,320 --> 00:30:36,280
Speaker 5: The reason why we named the company breaking is that

700
00:30:36,320 --> 00:30:40,560
Speaker 5: it's not making microplastics, it's actually breaking the chemical bonds

701
00:30:40,600 --> 00:30:42,720
Speaker 5: of the plastic and just making dirt.

702
00:30:43,080 --> 00:30:45,160
Speaker 1: It just leaves behind carbon, actually just.

703
00:30:45,160 --> 00:30:53,960
Speaker 5: Leaves behind dirt and some and some garden. Yeah, it's crazy.

704
00:30:59,360 --> 00:31:01,720
Speaker 1: So how quickly can you guys roll out a program

705
00:31:01,800 --> 00:31:03,120
Speaker 1: to get all the crap out of the ocean, and

706
00:31:03,120 --> 00:31:04,280
Speaker 1: just so.

707
00:31:04,760 --> 00:31:07,000
Speaker 5: In any of these processes, right, especially when you start

708
00:31:07,000 --> 00:31:10,520
Speaker 5: to leverage synthetic biology and genetic engineering and directed evolution.

709
00:31:11,320 --> 00:31:13,160
Speaker 1: And so when we saw this, which all of that

710
00:31:13,160 --> 00:31:15,320
Speaker 1: sounds like something out of our horrific sci fi mana. Yeah,

711
00:31:15,640 --> 00:31:17,200
Speaker 1: directed evolution, yes, that.

712
00:31:17,240 --> 00:31:17,760
Speaker 4: Is what we do.

713
00:31:17,880 --> 00:31:20,520
Speaker 5: Yeah, but we also do that naturally, right, Like have

714
00:31:20,600 --> 00:31:22,680
Speaker 5: you seen a pug like that's directed evolution?

715
00:31:23,080 --> 00:31:24,400
Speaker 1: Like something wrong with those little things?

716
00:31:24,520 --> 00:31:26,720
Speaker 5: Yeah, exactly, But someone made a lot of decisions to

717
00:31:26,760 --> 00:31:29,920
Speaker 5: breed stuff like right, people are like, oh, genetically modified organisms.

718
00:31:30,240 --> 00:31:31,960
Speaker 5: You know, there was the whole anti GMO thing for

719
00:31:31,960 --> 00:31:34,200
Speaker 5: a long time, which we need GMOs to exist in

720
00:31:34,240 --> 00:31:36,840
Speaker 5: today's world with the number of people on this planet

721
00:31:37,120 --> 00:31:40,160
Speaker 5: and transport and all this other stuff and disease resistant

722
00:31:40,240 --> 00:31:43,440
Speaker 5: crop resistance. We can't have a situation where a massive

723
00:31:43,440 --> 00:31:45,760
Speaker 5: amount of crops fail and we're like, okay, well cool,

724
00:31:45,760 --> 00:31:47,120
Speaker 5: a third of the plant's just going to die this

725
00:31:47,240 --> 00:31:49,520
Speaker 5: year like back in the old days, right, And we

726
00:31:49,560 --> 00:31:51,960
Speaker 5: have been like breeding strains of like wheat and stuff

727
00:31:51,960 --> 00:31:53,400
Speaker 5: together for thousands of years.

728
00:31:53,400 --> 00:31:54,440
Speaker 4: So we we've just.

729
00:31:54,400 --> 00:31:58,600
Speaker 5: Been doing genetic engineering and directed evolution pretty shittily right,

730
00:31:58,680 --> 00:32:01,080
Speaker 5: So now we have better tools, we're just barter and

731
00:32:01,080 --> 00:32:03,960
Speaker 5: more efficient about it. And so so right now everything

732
00:32:04,000 --> 00:32:06,480
Speaker 5: with breakings happening in the lab, happening in contained bio

733
00:32:07,120 --> 00:32:11,200
Speaker 5: containment systems. But it lives one hundred percent on the plastic. Right,

734
00:32:11,280 --> 00:32:13,360
Speaker 5: so in the oh it got out.

735
00:32:13,200 --> 00:32:16,200
Speaker 4: In the wild, there's no those role issues, right because.

736
00:32:15,960 --> 00:32:17,960
Speaker 1: So even if it escaped, it would just go be plastic.

737
00:32:18,160 --> 00:32:19,440
Speaker 4: It wouldn't even go eat plastic.

738
00:32:19,480 --> 00:32:21,760
Speaker 5: I mean, it's not a movable thing. It wouldn't like

739
00:32:21,800 --> 00:32:24,840
Speaker 5: go find the plastic. Right, So we have engineered in

740
00:32:25,160 --> 00:32:27,400
Speaker 5: kill switches and some other things, so it only has

741
00:32:27,440 --> 00:32:28,720
Speaker 5: a certain shelf life and whatnot?

742
00:32:29,080 --> 00:32:30,560
Speaker 1: What is a kill switch for something like that?

743
00:32:30,600 --> 00:32:31,880
Speaker 4: How do you kill it?

744
00:32:31,360 --> 00:32:34,040
Speaker 5: It's a shelf life, So regardless of how successful it is,

745
00:32:34,160 --> 00:32:36,760
Speaker 5: like we engineer in sin essence.

746
00:32:37,320 --> 00:32:38,880
Speaker 1: So when they go out into the field and they

747
00:32:38,880 --> 00:32:40,880
Speaker 1: come back with these microbes, where did they find them?

748
00:32:41,600 --> 00:32:43,800
Speaker 4: So we aren't saying where we found X thirty two?

749
00:32:43,960 --> 00:32:47,400
Speaker 1: Oh okay again this is so I want to.

750
00:32:47,360 --> 00:32:49,840
Speaker 5: Say it because it's being on the bord of trustees

751
00:32:49,840 --> 00:32:51,480
Speaker 5: the Explorers Club, and also working so closely to the

752
00:32:51,560 --> 00:32:51,920
Speaker 5: words Club.

753
00:32:51,960 --> 00:32:53,800
Speaker 4: I would love at some point we will.

754
00:32:53,640 --> 00:32:58,320
Speaker 5: Tell the story of how X thirty two came to

755
00:32:58,360 --> 00:33:00,720
Speaker 5: be found, because it's an adventure in itself.

756
00:33:00,920 --> 00:33:04,480
Speaker 1: Okay, all of this is the very Indiana Jones esque

757
00:33:04,560 --> 00:33:06,880
Speaker 1: aspect of it that you were talking about. We found

758
00:33:06,880 --> 00:33:08,880
Speaker 1: a microbe. Don't tell anybody where it is. If you

759
00:33:08,960 --> 00:33:10,880
Speaker 1: tell them, all these other teams are going to descend

760
00:33:10,920 --> 00:33:13,680
Speaker 1: upon the area, take it, maybe mess up the research.

761
00:33:13,800 --> 00:33:16,200
Speaker 1: I think this is amazing. But all the things that

762
00:33:16,200 --> 00:33:18,440
Speaker 1: you've talked about so far are all good things. Yeah,

763
00:33:18,480 --> 00:33:21,360
Speaker 1: what are the downfalls? What is a possible negative impact

764
00:33:21,360 --> 00:33:24,040
Speaker 1: that bringing a wooly mammoth back could have on the planet.

765
00:33:24,080 --> 00:33:27,480
Speaker 5: Yeah, So I think you have to look at unintended

766
00:33:27,600 --> 00:33:31,600
Speaker 5: and intended consequences, right, And the rewilding process on all

767
00:33:31,640 --> 00:33:34,880
Speaker 5: these species is one that takes as much time and

768
00:33:34,880 --> 00:33:37,080
Speaker 5: I'll tell you probably even more effort in the science.

769
00:33:37,480 --> 00:33:41,920
Speaker 5: And so we launched our Tasmanian Tiger Working Group last year,

770
00:33:41,960 --> 00:33:43,320
Speaker 5: but we've been doing it for three years. We just

771
00:33:43,360 --> 00:33:46,560
Speaker 5: announced it publicly and so we're working closely with indigenous

772
00:33:46,560 --> 00:33:50,720
Speaker 5: people groups, private landowners, the public at large, local governments

773
00:33:51,640 --> 00:33:54,840
Speaker 5: and so. Like the largest industry in Tasmania is logging,

774
00:33:55,240 --> 00:33:57,880
Speaker 5: and so it's stupid to think that we're going to

775
00:33:57,880 --> 00:34:01,480
Speaker 5: reintroduce an animal that's like culturally important to Tasmania without

776
00:34:01,520 --> 00:34:02,240
Speaker 5: having their opinion.

777
00:34:02,240 --> 00:34:04,280
Speaker 4: Because they've got lots of money. You got to.

778
00:34:04,240 --> 00:34:07,080
Speaker 5: Include, You got to be inclusive, right, So we rely heavily

779
00:34:07,160 --> 00:34:09,600
Speaker 5: on these experts. We work really closely with a group

780
00:34:09,640 --> 00:34:13,000
Speaker 5: called Rewild, which is one of the top groups out

781
00:34:13,000 --> 00:34:17,200
Speaker 5: there for rewilding species back into their environments. And so

782
00:34:17,880 --> 00:34:21,360
Speaker 5: you know, it really does take a very large consortium.

783
00:34:21,440 --> 00:34:23,680
Speaker 5: And so even though we don't have mammis or dialo

784
00:34:23,719 --> 00:34:26,200
Speaker 5: scenes or dotos, now we've started all those meetings and

785
00:34:26,200 --> 00:34:28,759
Speaker 5: we have quarterly meetings with these various groups. And then

786
00:34:28,800 --> 00:34:31,800
Speaker 5: there's this other outside of kind of measuring the intended

787
00:34:31,840 --> 00:34:35,080
Speaker 5: and potential unintended consequences and trying to plan for the best,

788
00:34:35,480 --> 00:34:38,000
Speaker 5: you also need to ensure that you are taking an

789
00:34:38,000 --> 00:34:39,839
Speaker 5: account kind of the importance.

790
00:34:40,120 --> 00:34:41,640
Speaker 4: And there's a spiritual aspect.

791
00:34:41,800 --> 00:34:43,960
Speaker 5: So like if you ask the Aboriginal people in Australia

792
00:34:43,960 --> 00:34:47,359
Speaker 5: about the Thilet Center Tasbanian tiger, they'll tell you it's

793
00:34:47,760 --> 00:34:50,520
Speaker 5: core to their creation story. It's part of who they

794
00:34:50,560 --> 00:34:52,879
Speaker 5: are as a people. And their view is it's never left.

795
00:34:52,880 --> 00:34:55,640
Speaker 5: They're like, it's spirit sell here. You know, you guys

796
00:34:55,719 --> 00:35:00,880
Speaker 5: murdered it, but like you as these settlers and Tasmania

797
00:35:00,880 --> 00:35:05,680
Speaker 5: and Australian sheep farmers, but fundamentally, it's never left and

798
00:35:05,680 --> 00:35:07,799
Speaker 5: it's always been part of our creation story. So we're

799
00:35:07,800 --> 00:35:09,880
Speaker 5: not going to go out there and just like open

800
00:35:09,880 --> 00:35:12,600
Speaker 5: the gates and be like have fun, mam miss and

801
00:35:12,760 --> 00:35:15,560
Speaker 5: we'll cross our fingers and maybe this will go well, right, right.

802
00:35:15,480 --> 00:35:20,680
Speaker 1: So the natives in Tasmania, they're on board with bringing

803
00:35:20,719 --> 00:35:22,120
Speaker 1: this back in the way you guys are bringing it back.

804
00:35:22,160 --> 00:35:23,160
Speaker 4: They actually did. It's cool.

805
00:35:23,200 --> 00:35:26,120
Speaker 5: They did a poll in ABC did a poll and

806
00:35:26,160 --> 00:35:28,600
Speaker 5: it was like people excited about bringing back the Tasmanian

807
00:35:28,680 --> 00:35:30,280
Speaker 5: tiger and it was like twenty percent.

808
00:35:30,320 --> 00:35:31,479
Speaker 4: I was like, that's not good.

809
00:35:31,760 --> 00:35:33,879
Speaker 5: We've spent a lot of time, you know, because because

810
00:35:33,880 --> 00:35:35,560
Speaker 5: our job is not to persuade anyone, it's just to

811
00:35:35,680 --> 00:35:38,280
Speaker 5: educate people, like we should be when you do big bullshit,

812
00:35:38,320 --> 00:35:41,520
Speaker 5: you should be transparent about it, but you shouldn't try

813
00:35:41,520 --> 00:35:42,160
Speaker 5: to sell.

814
00:35:42,000 --> 00:35:42,480
Speaker 4: People on it.

815
00:35:42,520 --> 00:35:44,640
Speaker 5: So we just like have conversations like this, like this

816
00:35:44,680 --> 00:35:46,839
Speaker 5: is what we're doing, and when people tell us like, oh,

817
00:35:46,880 --> 00:35:48,479
Speaker 5: if you thought about this, like Oh, that's a good idea.

818
00:35:48,480 --> 00:35:50,479
Speaker 5: We should We're very open to that, right, We're open

819
00:35:50,480 --> 00:35:52,960
Speaker 5: to that criticism and feedback and so and so. With that,

820
00:35:53,280 --> 00:35:56,920
Speaker 5: we constantly are our tunear model. But then ABC redid a.

821
00:35:56,840 --> 00:35:59,880
Speaker 4: Poll and it was like seventy percent a year later.

822
00:36:00,239 --> 00:36:02,000
Speaker 1: So the question that I asked you was what are

823
00:36:02,040 --> 00:36:04,600
Speaker 1: the negatives? And the answer, a short version of the answer,

824
00:36:04,640 --> 00:36:06,440
Speaker 1: is really just we're not We don't know until we know.

825
00:36:06,719 --> 00:36:08,520
Speaker 5: We don't know until we know, right, Okay, but I

826
00:36:08,560 --> 00:36:12,520
Speaker 5: think that there's enough modeling data and if you were

827
00:36:12,520 --> 00:36:15,600
Speaker 5: inclusive in the approach, which we are, you know you

828
00:36:15,600 --> 00:36:16,520
Speaker 5: can try to hedge.

829
00:36:16,360 --> 00:36:16,960
Speaker 4: The best you can.

830
00:36:17,120 --> 00:36:20,120
Speaker 1: Okay, let's get to the Jurassic Park questions. People have

831
00:36:20,200 --> 00:36:21,680
Speaker 1: to have told you, guys, don't do this, this is

832
00:36:21,719 --> 00:36:22,240
Speaker 1: a bad idea.

833
00:36:22,520 --> 00:36:25,080
Speaker 5: Correct, Well, we've gotten we've gotten the jurass so we've

834
00:36:25,080 --> 00:36:29,400
Speaker 5: gotten We've gotten lots of Jurassic Park memes in famous

835
00:36:29,440 --> 00:36:30,399
Speaker 5: quotes and Jurassic Park.

836
00:36:30,480 --> 00:36:31,240
Speaker 4: Right, there are.

837
00:36:31,120 --> 00:36:32,640
Speaker 1: Seven movies about why we shouldn't do this.

838
00:36:32,719 --> 00:36:34,319
Speaker 4: Yes, okay, we all know who it ended, right.

839
00:36:34,360 --> 00:36:36,799
Speaker 5: I don't think the Jurassic Park was focused on conservation,

840
00:36:37,080 --> 00:36:40,320
Speaker 5: but maybe there was an underlying conservation undertone I missed,

841
00:36:40,320 --> 00:36:43,960
Speaker 5: I don't think. But also, you know, it's not possible

842
00:36:44,320 --> 00:36:47,759
Speaker 5: to de extinct A dinos where the DNA just doesn't exist, right,

843
00:36:47,800 --> 00:36:51,799
Speaker 5: So it's not possible. Amber it's massively porous. It doesn't work,

844
00:36:51,920 --> 00:36:54,319
Speaker 5: not that we've tried or anyone's tried it, but it

845
00:36:54,360 --> 00:36:57,240
Speaker 5: is not an efficient storage of DNA.

846
00:36:57,360 --> 00:36:59,320
Speaker 1: So you're telling me Jurassic Park was bunk science.

847
00:36:59,400 --> 00:37:00,640
Speaker 4: Yeah, I will tell you may now.

848
00:37:00,880 --> 00:37:03,279
Speaker 5: But here's two interesting things about dress Park, right where

849
00:37:03,280 --> 00:37:05,359
Speaker 5: I don't think Dress Park gets tough credit. Number one

850
00:37:05,880 --> 00:37:09,279
Speaker 5: is it taught the world, Like there's this thing called

851
00:37:09,280 --> 00:37:13,120
Speaker 5: genetic engineering. Little mister DNA's like speech in it. I

852
00:37:13,160 --> 00:37:16,120
Speaker 5: think inspired people. Like when I was young and saw it,

853
00:37:16,120 --> 00:37:17,520
Speaker 5: I was like, maye, maybe I should be at genes.

854
00:37:17,719 --> 00:37:19,920
Speaker 5: That's cool, right, So I think.

855
00:37:19,719 --> 00:37:22,239
Speaker 4: It really opened our eyes, as a lot of sci

856
00:37:22,239 --> 00:37:24,800
Speaker 4: fi does, to the art of the possible. So I

857
00:37:24,840 --> 00:37:26,680
Speaker 4: think it did do good stuff. Right. It's also an

858
00:37:26,800 --> 00:37:27,880
Speaker 4: entertaining movie, right.

859
00:37:27,800 --> 00:37:29,480
Speaker 1: All of them. I love all of them. We argue

860
00:37:29,480 --> 00:37:30,879
Speaker 1: about this all the time. I thought they were all great.

861
00:37:30,880 --> 00:37:33,359
Speaker 5: They're all great, I do. I think in the new one,

862
00:37:34,040 --> 00:37:36,400
Speaker 5: the one that's coming out, it's gonna be I think

863
00:37:36,440 --> 00:37:37,000
Speaker 5: it's gonna be great.

864
00:37:37,040 --> 00:37:40,040
Speaker 4: Okay, so I should know over really endorse individual people,

865
00:37:40,080 --> 00:37:40,560
Speaker 4: but I do.

866
00:37:41,000 --> 00:37:45,520
Speaker 5: I'm very very excited about the next one in the

867
00:37:45,560 --> 00:37:48,120
Speaker 5: director on it, Okay. But I will say that that

868
00:37:48,600 --> 00:37:51,359
Speaker 5: another thing that people some days to ask us is like.

869
00:37:51,480 --> 00:37:53,160
Speaker 4: Were you inspired by a Jurassic Park.

870
00:37:53,400 --> 00:37:56,680
Speaker 5: Here's a fun another fact in Michael Crichton's original book,

871
00:37:56,800 --> 00:37:58,040
Speaker 5: there's this DNA sequence.

872
00:37:58,640 --> 00:38:00,560
Speaker 4: It's like one letter off from.

873
00:38:00,480 --> 00:38:04,959
Speaker 5: George, which is like statistically basically impossible or highly highly

874
00:38:05,040 --> 00:38:07,120
Speaker 5: highly improbable. It is probably a better way to say

875
00:38:07,120 --> 00:38:10,480
Speaker 5: it is that it's like one letter off from George

876
00:38:10,560 --> 00:38:13,160
Speaker 5: Church's research that he published.

877
00:38:12,880 --> 00:38:14,520
Speaker 4: In the seventies all day because he was one of

878
00:38:14,560 --> 00:38:16,239
Speaker 4: the top guys in the World War. Did they use

879
00:38:16,239 --> 00:38:16,719
Speaker 4: his Yeah?

880
00:38:16,719 --> 00:38:18,680
Speaker 5: So, if anything, I like to think and George, and

881
00:38:18,760 --> 00:38:23,040
Speaker 5: I think that maybe George inspired Michael Crichton on genetic

882
00:38:23,120 --> 00:38:26,680
Speaker 5: engineering and sequencing genome. So we were not inspired by

883
00:38:26,800 --> 00:38:28,640
Speaker 5: drastic bark. But I do think that there was a

884
00:38:28,880 --> 00:38:31,719
Speaker 5: likelihood that you know, Michael Crichton probably he was very

885
00:38:31,760 --> 00:38:35,840
Speaker 5: smart and knew of George's work, and something that is

886
00:38:35,880 --> 00:38:38,520
Speaker 5: like ninety nine percent George's work showed up and in.

887
00:38:38,480 --> 00:38:39,240
Speaker 4: The book itself.

888
00:38:39,280 --> 00:38:43,480
Speaker 1: So is there any chance or thought of you guys

889
00:38:44,120 --> 00:38:48,080
Speaker 1: resurrecting any type of human genes that have gone extinct?

890
00:38:48,560 --> 00:38:53,640
Speaker 5: Yeah, we get the Knanderthal question. Probably like the Jurastic Parkway.

891
00:38:53,640 --> 00:38:55,520
Speaker 5: It's probably the next kind of set of those types

892
00:38:55,560 --> 00:38:55,879
Speaker 5: of questions.

893
00:38:56,000 --> 00:38:57,080
Speaker 1: Damn, I thought it was so original.

894
00:38:57,239 --> 00:38:58,399
Speaker 4: Yeah, no, it's all right, it's right.

895
00:38:58,760 --> 00:39:01,680
Speaker 5: We are not working on so Colossal has made a

896
00:39:01,680 --> 00:39:04,960
Speaker 5: mandate that we are only working on de extinction and

897
00:39:05,000 --> 00:39:09,000
Speaker 5: species preservation of existing species for conservation. We're not doing

898
00:39:09,040 --> 00:39:12,520
Speaker 5: any competition analysis on humans Neanderthal. There's many people are

899
00:39:12,840 --> 00:39:15,040
Speaker 5: that's just not us now. I do believe that some

900
00:39:15,080 --> 00:39:18,160
Speaker 5: of our genetic engineering tools in a separate company would

901
00:39:18,160 --> 00:39:21,200
Speaker 5: be used to help different disease states, just like our

902
00:39:21,239 --> 00:39:25,160
Speaker 5: competitional analysis and AI software is now being used for

903
00:39:25,280 --> 00:39:26,760
Speaker 5: drug discovery and cancer research.

904
00:39:26,960 --> 00:39:28,799
Speaker 1: I think this entire thing is amazing. Do you wake

905
00:39:28,880 --> 00:39:30,399
Speaker 1: up every day like I have the coolest.

906
00:39:30,080 --> 00:39:32,439
Speaker 4: Job around On the worst day, it's still pretty cool.

907
00:39:32,520 --> 00:39:35,000
Speaker 1: How does one become part of your explorer team? So

908
00:39:35,239 --> 00:39:35,959
Speaker 1: Explorers Club?

909
00:39:36,160 --> 00:39:39,080
Speaker 4: Yes, so the Explorers Club is here based here in

910
00:39:39,120 --> 00:39:40,000
Speaker 4: New York. It's amazing.

911
00:39:40,040 --> 00:39:42,759
Speaker 5: They have lectures every Monday, it's awesome. So anybody can

912
00:39:42,800 --> 00:39:46,399
Speaker 5: apply it just explores dot org. And then if people

913
00:39:46,400 --> 00:39:48,640
Speaker 5: want to get follow Colossal, they just go to Colossal

914
00:39:48,680 --> 00:39:52,000
Speaker 5: dot com and all of our social and we try

915
00:39:52,040 --> 00:39:56,000
Speaker 5: to be really responsive and transparent to everything from media

916
00:39:56,120 --> 00:39:57,719
Speaker 5: to social requests.

917
00:39:58,000 --> 00:40:01,200
Speaker 1: Okay, what is your criteria let people in asking for

918
00:40:01,200 --> 00:40:01,760
Speaker 1: a front.

919
00:40:01,600 --> 00:40:02,480
Speaker 4: Oh to work out.

920
00:40:02,480 --> 00:40:05,160
Speaker 1: Didn't work at Colossal, So get into the Explorers Club.

921
00:40:05,239 --> 00:40:06,560
Speaker 4: Oh so on the Explorers I got.

922
00:40:06,400 --> 00:40:07,919
Speaker 1: To start small. I mean, she has to start small.

923
00:40:08,000 --> 00:40:10,480
Speaker 5: Yeah, that your friend, your friend. Yeah, so you should

924
00:40:10,480 --> 00:40:12,400
Speaker 5: just go to some lectures. You know, you know, you

925
00:40:12,440 --> 00:40:14,840
Speaker 5: know some people now, right, So so go to some

926
00:40:14,920 --> 00:40:16,840
Speaker 5: lectures they have. They have all these cool things that

927
00:40:16,880 --> 00:40:19,440
Speaker 5: happen at the Explorers Club here in New York. And

928
00:40:19,480 --> 00:40:24,040
Speaker 5: then there's the Global Explorers Club. Uh, the Global Explorer

929
00:40:24,080 --> 00:40:27,120
Speaker 5: Summit in the Azores in Portugal, which is in June.

930
00:40:27,480 --> 00:40:29,000
Speaker 5: So if you could pull it, you should do it

931
00:40:29,000 --> 00:40:31,080
Speaker 5: because it's it's the best conference I've ever been to.

932
00:40:31,920 --> 00:40:33,920
Speaker 5: And it's just this network of incredible women and men

933
00:40:34,160 --> 00:40:36,520
Speaker 5: that are doing everything from conservation to going to the

934
00:40:36,520 --> 00:40:38,000
Speaker 5: moon to going to the bottom of the ocean. So

935
00:40:38,400 --> 00:40:41,080
Speaker 5: there's been a handful of famous first like the first

936
00:40:41,080 --> 00:40:43,360
Speaker 5: people that went to the Moon carried the explorers. Like

937
00:40:43,360 --> 00:40:44,880
Speaker 5: the first people went to the bottom of marion Is

938
00:40:44,920 --> 00:40:46,840
Speaker 5: Trench carried the exports side. The first people at the

939
00:40:46,840 --> 00:40:49,279
Speaker 5: top of Everest carried the explorers. Are the first people

940
00:40:49,440 --> 00:40:52,280
Speaker 5: go down the Amazon. From a charting perspective, obviously indigenous

941
00:40:52,280 --> 00:40:55,200
Speaker 5: people did a wait before carried the explorers flag. And

942
00:40:55,239 --> 00:40:57,960
Speaker 5: so it's a really cool organization. You can apply online.

943
00:40:58,960 --> 00:40:59,920
Speaker 1: I'm at the website right.

944
00:41:00,160 --> 00:41:03,440
Speaker 5: There is a process to get in, like you have

945
00:41:03,520 --> 00:41:06,840
Speaker 5: to have some exploration stuff, but you can just go

946
00:41:06,920 --> 00:41:09,560
Speaker 5: to the Explorers Club and every single night at the bar,

947
00:41:09,960 --> 00:41:13,360
Speaker 5: basically a new expedition, uh comes up. And I like

948
00:41:13,400 --> 00:41:16,080
Speaker 5: to say that an expedition is just an adventure with

949
00:41:16,200 --> 00:41:19,280
Speaker 5: a purpose, so you can go on on one. Everyone's

950
00:41:19,320 --> 00:41:22,080
Speaker 5: always excited for new explorers and new people to join.

951
00:41:22,360 --> 00:41:25,560
Speaker 5: Anybody can be an explorer, anybody can be a scientist

952
00:41:25,560 --> 00:41:27,440
Speaker 5: that they want to be right and then that you

953
00:41:27,560 --> 00:41:30,840
Speaker 5: just start you know there, and then you know, eventually

954
00:41:31,160 --> 00:41:32,399
Speaker 5: have some credentials and apply.

955
00:41:33,160 --> 00:41:35,720
Speaker 1: This is so cool, all right, last couple of questions about.

956
00:41:35,520 --> 00:41:37,120
Speaker 4: The manager, Yeah, whatever you want.

957
00:41:37,600 --> 00:41:38,960
Speaker 1: How do we know they're not going to have some

958
00:41:39,000 --> 00:41:40,840
Speaker 1: type of conflict with the polar bears and stuff that

959
00:41:40,840 --> 00:41:43,000
Speaker 1: they're there is that gonna is that it has to

960
00:41:43,040 --> 00:41:43,560
Speaker 1: be possible.

961
00:41:43,560 --> 00:41:44,040
Speaker 4: Weird.

962
00:41:44,520 --> 00:41:47,040
Speaker 5: These are the weird things that happened in my life

963
00:41:47,400 --> 00:41:50,399
Speaker 5: now is like I spent we had to hire a

964
00:41:50,520 --> 00:41:54,480
Speaker 5: caribou migratory pattern expert and so there's actually.

965
00:41:54,360 --> 00:41:56,000
Speaker 1: You can pressed that that's a job this.

966
00:41:56,800 --> 00:41:59,440
Speaker 5: I don't know what it pays, but I don't remember

967
00:41:59,440 --> 00:42:02,040
Speaker 5: the consultant being expensive. And we actually had to go

968
00:42:02,200 --> 00:42:04,279
Speaker 5: not just talk to the indigenous people groups, but we

969
00:42:04,320 --> 00:42:06,640
Speaker 5: had to go look at like and understand what are

970
00:42:06,719 --> 00:42:11,200
Speaker 5: migratory patterns of caribou and would any of the potential

971
00:42:11,320 --> 00:42:14,839
Speaker 5: mammoth re wilding hubs affect the caribou r I don't

972
00:42:14,840 --> 00:42:17,520
Speaker 5: have an answer yet on on on polar bears. That's

973
00:42:17,560 --> 00:42:19,080
Speaker 5: another species that just needs a lot of it.

974
00:42:19,239 --> 00:42:21,800
Speaker 1: Absolutely with the loss of ice.

975
00:42:21,760 --> 00:42:23,840
Speaker 5: Best Shapiro, It's actually done a lot of work in

976
00:42:24,239 --> 00:42:26,680
Speaker 5: polar bear genetics and the cross breeding with brown bears.

977
00:42:26,760 --> 00:42:28,000
Speaker 1: So if people want to help you out, they want

978
00:42:28,000 --> 00:42:29,640
Speaker 1: to get on board with this cause, how do they

979
00:42:29,640 --> 00:42:29,880
Speaker 1: do that?

980
00:42:29,960 --> 00:42:32,960
Speaker 5: They just go to our socials, they go to our website.

981
00:42:33,040 --> 00:42:35,040
Speaker 4: You know, we try to constantly put out content we

982
00:42:35,080 --> 00:42:37,080
Speaker 4: try to be as well.

983
00:42:37,120 --> 00:42:39,400
Speaker 5: We found though, and so we just put out so

984
00:42:39,520 --> 00:42:42,359
Speaker 5: much content just never enough, like people just want more

985
00:42:42,400 --> 00:42:44,200
Speaker 5: and more, so we're trying to do more and more.

986
00:42:44,880 --> 00:42:47,399
Speaker 5: We just announced our partnership with James Reid. I don't

987
00:42:47,400 --> 00:42:48,720
Speaker 5: know if you saw My Octopus Teacher.

988
00:42:49,080 --> 00:42:49,640
Speaker 1: I sure did.

989
00:42:49,880 --> 00:42:50,880
Speaker 4: Do you eat octopus after that?

990
00:42:50,960 --> 00:42:53,520
Speaker 1: And I don't see. Oh my god, I feel like

991
00:42:53,560 --> 00:42:56,680
Speaker 1: such an idiot. Yes, because exactly that is exactly what

992
00:42:56,719 --> 00:43:00,760
Speaker 1: happened Octopus Delicious. Watch My Octopus Teacher. Haven't had it once.

993
00:43:00,640 --> 00:43:02,040
Speaker 4: Since the same same I like to do it.

994
00:43:02,560 --> 00:43:05,359
Speaker 5: I've actually walked out of dinners where people have ordered

995
00:43:05,360 --> 00:43:06,600
Speaker 5: octopus after I told them.

996
00:43:06,440 --> 00:43:08,280
Speaker 1: Not to tell me that. Their argument is it's already

997
00:43:08,320 --> 00:43:09,120
Speaker 1: dood Yeah.

998
00:43:08,920 --> 00:43:10,759
Speaker 4: That's someone's gonna eat it. Yeah.

999
00:43:10,880 --> 00:43:16,359
Speaker 5: And I was actually at a restaurant, like a top

1000
00:43:16,440 --> 00:43:19,120
Speaker 5: mission restaurant in Mexico and with a guy and he

1001
00:43:19,280 --> 00:43:21,360
Speaker 5: was so pissed and I was like, I'll have the carrot.

1002
00:43:21,400 --> 00:43:23,279
Speaker 5: And he's like, I'm not going to eat a five

1003
00:43:23,320 --> 00:43:25,480
Speaker 5: star restaurant, a mission star restaurant a carrot.

1004
00:43:25,480 --> 00:43:27,160
Speaker 4: I was like, cool, then I'll buy myself right.

1005
00:43:27,320 --> 00:43:27,520
Speaker 1: Yeah.

1006
00:43:27,719 --> 00:43:29,680
Speaker 4: So I'm very religious about this now.

1007
00:43:30,000 --> 00:43:33,840
Speaker 5: But but anyway, we digressed James Reed, who did my

1008
00:43:33,840 --> 00:43:36,880
Speaker 5: Octice Teacher and One Oscar for it and critically claimed

1009
00:43:37,160 --> 00:43:39,840
Speaker 5: Chimp Empire. We've signed a partnership with him to do

1010
00:43:40,719 --> 00:43:43,960
Speaker 5: our docuseries. So we always talk about transparency, and I

1011
00:43:43,960 --> 00:43:46,320
Speaker 5: will tell you there's nothing more transparent than having cameras

1012
00:43:46,320 --> 00:43:48,600
Speaker 5: on you twenty four to seven. It's like when I

1013
00:43:48,640 --> 00:43:50,000
Speaker 5: was going to the E Sports Club this week, there

1014
00:43:50,000 --> 00:43:52,680
Speaker 5: were cameras in the car and it's it's it's it's

1015
00:43:52,680 --> 00:43:55,879
Speaker 5: intense and weird, but then everything's captured, right, And so

1016
00:43:56,040 --> 00:43:59,919
Speaker 5: we really wanted someone that could be independent, cared about

1017
00:44:00,080 --> 00:44:04,280
Speaker 5: capturing the content from the journey perspective, but also would

1018
00:44:04,280 --> 00:44:07,600
Speaker 5: be completely objective in it. And James is that guy

1019
00:44:07,760 --> 00:44:11,000
Speaker 5: in his team. Hopefully, you know, in the spirit of

1020
00:44:11,000 --> 00:44:13,440
Speaker 5: transparency and also the spirit of content. You know, hopefully

1021
00:44:13,560 --> 00:44:16,480
Speaker 5: that'll show up on a major streaming network in the

1022
00:44:16,520 --> 00:44:18,640
Speaker 5: future and get more behind the scenescause we can't let

1023
00:44:18,640 --> 00:44:20,360
Speaker 5: everyone come to the lab. We can't let everyone go

1024
00:44:20,360 --> 00:44:21,120
Speaker 5: to the Yukon with us.

1025
00:44:21,120 --> 00:44:22,640
Speaker 1: We can't let everyone, do you let anyone go to

1026
00:44:22,680 --> 00:44:23,000
Speaker 1: the lab?

1027
00:44:23,480 --> 00:44:25,799
Speaker 4: We do let some of our investors we've let come

1028
00:44:25,800 --> 00:44:25,960
Speaker 4: to the.

1029
00:44:26,000 --> 00:44:29,080
Speaker 1: Lab only investors, not podcasters or people on the.

1030
00:44:29,040 --> 00:44:31,880
Speaker 5: Radio, so I'm sure there's exceptions can always be made.

1031
00:44:31,920 --> 00:44:34,400
Speaker 5: We've had some media come in, so yes, if you

1032
00:44:34,440 --> 00:44:35,560
Speaker 5: want to come to our Dallas lab.

1033
00:44:35,440 --> 00:44:36,279
Speaker 4: I'm sure we caul figure it out.

1034
00:44:36,280 --> 00:44:36,919
Speaker 1: I won't touch anything.

1035
00:44:37,680 --> 00:44:40,600
Speaker 5: I'm gonna tell you it is so much cooler talking

1036
00:44:40,640 --> 00:44:43,600
Speaker 5: to them and seeing the amazing work that those women

1037
00:44:43,640 --> 00:44:45,200
Speaker 5: and men are doing is so much better than talking

1038
00:44:45,200 --> 00:44:45,400
Speaker 5: to me.

1039
00:44:45,520 --> 00:44:47,840
Speaker 4: So if you do come to Dallas, I'm sure we

1040
00:44:47,840 --> 00:44:48,479
Speaker 4: could figure something.

1041
00:44:48,520 --> 00:44:50,000
Speaker 1: This has been awesome talking to you, So if it's

1042
00:44:50,000 --> 00:44:50,839
Speaker 1: better talking to them.

1043
00:44:51,600 --> 00:44:52,719
Speaker 4: It's a thousand times.

1044
00:44:52,719 --> 00:44:53,480
Speaker 2: But are so cool.

1045
00:44:53,480 --> 00:44:55,640
Speaker 4: I'm not making MAMO, so I'm just kind of helping people.

1046
00:44:56,000 --> 00:44:57,239
Speaker 1: Yeah, how did you get involved with it?

1047
00:44:57,800 --> 00:45:00,239
Speaker 4: I called? I called called George Church because my last

1048
00:45:00,280 --> 00:45:01,279
Speaker 4: company was a satellite.

1049
00:45:01,040 --> 00:45:02,479
Speaker 1: Software I tried to do that. It didn't work.

1050
00:45:03,440 --> 00:45:03,960
Speaker 4: It worked for me.

1051
00:45:04,680 --> 00:45:07,080
Speaker 5: My last company was a satellite software and defense company,

1052
00:45:07,080 --> 00:45:10,080
Speaker 5: and we're building reconfigure overble satellites and some other stuff.

1053
00:45:10,120 --> 00:45:13,200
Speaker 5: And I wanted to build a synthetic I wanted to

1054
00:45:13,200 --> 00:45:16,439
Speaker 5: build an AI based synthetic biology software because I felt

1055
00:45:16,480 --> 00:45:22,319
Speaker 5: like we feel like the future of compute competitional analysis

1056
00:45:22,400 --> 00:45:25,680
Speaker 5: AI and eventually quantum will basically give us, like the

1057
00:45:25,760 --> 00:45:30,200
Speaker 5: CAD software, the core technologies to be to have like

1058
00:45:30,239 --> 00:45:31,840
Speaker 5: the CAD software for biology.

1059
00:45:31,960 --> 00:45:33,279
Speaker 1: I really tried to hold on to what you were

1060
00:45:33,320 --> 00:45:35,360
Speaker 1: saying here. I do not know what you just said.

1061
00:45:35,440 --> 00:45:38,879
Speaker 5: So basically, a lot a lot of innovations that are

1062
00:45:39,040 --> 00:45:42,000
Speaker 5: here and continuing to progress, and some new ones that

1063
00:45:42,040 --> 00:45:44,560
Speaker 5: are coming. I think together will make us like software

1064
00:45:44,680 --> 00:45:49,000
Speaker 5: will give us the We'll give us the foundational foundation.

1065
00:45:49,120 --> 00:45:51,920
Speaker 5: We need to build software that we can then engineer

1066
00:45:52,440 --> 00:45:55,279
Speaker 5: and do directed evolution on all of life like and

1067
00:45:55,320 --> 00:45:56,120
Speaker 5: so I see that coming.

1068
00:45:56,120 --> 00:45:58,560
Speaker 4: So I called George to talk to him about where he.

1069
00:45:58,520 --> 00:46:00,480
Speaker 5: Sees synthetic He's like the father of he is the

1070
00:46:00,520 --> 00:46:03,680
Speaker 5: father of synthetic biology. Yeah, so I called George to say,

1071
00:46:03,760 --> 00:46:06,760
Speaker 5: you know, where would this go? That lasted like seven

1072
00:46:06,800 --> 00:46:10,399
Speaker 5: minutes and then and then I said, what else you got?

1073
00:46:10,440 --> 00:46:12,360
Speaker 5: He started walking through all the other crazy stuff in

1074
00:46:12,360 --> 00:46:15,840
Speaker 5: his lab, like neural regeneration, and it was actually incredible,

1075
00:46:15,880 --> 00:46:19,640
Speaker 5: which is also incredible in itself, right, reversing aging through

1076
00:46:19,760 --> 00:46:22,719
Speaker 5: like these these weird cells in the blood.

1077
00:46:22,600 --> 00:46:26,640
Speaker 4: All kinds of crazy amazing. So show up.

1078
00:46:26,719 --> 00:46:28,839
Speaker 5: I was like, first, trust me, I'm first in line.

1079
00:46:29,280 --> 00:46:31,879
Speaker 5: I'm building George mammoth. So I'm first and lined enough

1080
00:46:32,520 --> 00:46:33,600
Speaker 5: and so uh.

1081
00:46:34,120 --> 00:46:36,320
Speaker 4: So we're in this thing. And then I said, but if.

1082
00:46:36,160 --> 00:46:38,719
Speaker 5: You had one project, you had unlimited cap if you

1083
00:46:38,719 --> 00:46:40,600
Speaker 5: had one thing and you couldn't do these hundred things,

1084
00:46:40,640 --> 00:46:42,480
Speaker 5: what would you do? And he's like, I would bring

1085
00:46:42,520 --> 00:46:45,320
Speaker 5: back the wooly mammoth and build technologies for the extinction

1086
00:46:45,360 --> 00:46:47,319
Speaker 5: in the species reservation. I was like, and then the

1087
00:46:47,360 --> 00:46:50,960
Speaker 5: call was over because it was like, it was like crying,

1088
00:46:51,239 --> 00:46:52,560
Speaker 5: all right, I have to go to my next meeting.

1089
00:46:52,760 --> 00:46:54,200
Speaker 5: I thought it was kind of a joke. And then

1090
00:46:54,320 --> 00:46:57,400
Speaker 5: as I listened to podcasts, read interviews, saw him on

1091
00:46:57,440 --> 00:47:00,000
Speaker 5: Colbert in sixteen minutes and there was this mammoth through line,

1092
00:47:00,000 --> 00:47:02,319
Speaker 5: and every time we talked about the mammoth, his voice changed.

1093
00:47:02,360 --> 00:47:04,320
Speaker 5: You noticed an inflection. So I called him back the

1094
00:47:04,360 --> 00:47:06,160
Speaker 5: next day, and then I didn't sleep that night. I

1095
00:47:06,160 --> 00:47:08,759
Speaker 5: called him back the next day, and as an entrepreneur,

1096
00:47:08,840 --> 00:47:11,319
Speaker 5: I've said a thousand times, you know, oh, I want

1097
00:47:11,360 --> 00:47:11,560
Speaker 5: to do this.

1098
00:47:11,560 --> 00:47:13,279
Speaker 4: Because it's gonna change the world. It's gonna have this

1099
00:47:13,320 --> 00:47:16,040
Speaker 4: massive impact. Sorry, it was just such an emotional moment

1100
00:47:16,080 --> 00:47:16,319
Speaker 4: for me.

1101
00:47:17,560 --> 00:47:21,399
Speaker 5: It's gonna have such a massive impact, that it could

1102
00:47:21,400 --> 00:47:23,719
Speaker 5: truly change the world, and being an entrepreneur that said

1103
00:47:23,760 --> 00:47:26,960
Speaker 5: that so many times, and then George just throwing this

1104
00:47:27,120 --> 00:47:30,160
Speaker 5: crazy opportunity to actually do it on my plate.

1105
00:47:30,239 --> 00:47:32,040
Speaker 4: I was like, I have to go do this.

1106
00:47:32,080 --> 00:47:34,000
Speaker 5: So a week later I was in his lab and

1107
00:47:34,040 --> 00:47:37,600
Speaker 5: we're like, we're gonna go build classle And here we are,

1108
00:47:37,719 --> 00:47:38,080
Speaker 5: and here we.

1109
00:47:38,080 --> 00:47:43,280
Speaker 1: Are, about two years away from starting the gestational process

1110
00:47:43,360 --> 00:47:43,880
Speaker 1: for me for a.

1111
00:47:44,200 --> 00:47:47,440
Speaker 5: Mammoth, but probably not two years away from the first pieces.

1112
00:47:47,880 --> 00:47:49,359
Speaker 1: You keep saying, this is such a tea you can't

1113
00:47:49,400 --> 00:47:50,839
Speaker 1: do this. So this is like the number one rule

1114
00:47:50,920 --> 00:47:53,399
Speaker 1: of radio is you have to deliver on the teas.

1115
00:47:53,560 --> 00:47:55,799
Speaker 1: Now I know that you didn't know that some of them.

1116
00:47:55,840 --> 00:47:58,480
Speaker 1: Let's go, but the teas thing, I can't wait. I'm

1117
00:47:58,480 --> 00:48:00,440
Speaker 1: gonna be so tuned in. It's Do I find it

1118
00:48:00,480 --> 00:48:02,200
Speaker 1: on Instagram Explorers Club or.

1119
00:48:04,120 --> 00:48:08,440
Speaker 5: On Instagram? Uh, it's it is colossal. On Twitter it

1120
00:48:08,520 --> 00:48:12,480
Speaker 5: is colossal, and then and then our.

1121
00:48:12,480 --> 00:48:13,840
Speaker 4: Webs is Colossal dot com.

1122
00:48:13,840 --> 00:48:15,759
Speaker 5: Okay, you can also follow the Explorers Club, which is

1123
00:48:15,800 --> 00:48:17,239
Speaker 5: a lot of stuff outside of what we do.

1124
00:48:17,320 --> 00:48:19,160
Speaker 1: Thank you so much for coming in and spending so

1125
00:48:19,239 --> 00:48:21,160
Speaker 1: much time with me and answering my million questions.

1126
00:48:21,200 --> 00:48:21,879
Speaker 4: Yeah, this is great.

1127
00:48:21,960 --> 00:48:24,000
Speaker 1: I feel smarter now. I'm gonna have to look up

1128
00:48:24,000 --> 00:48:25,480
Speaker 1: a lot of the stuff that you said, because again

1129
00:48:25,520 --> 00:48:27,239
Speaker 1: I was trying to hold on. But I think this

1130
00:48:27,280 --> 00:48:28,200
Speaker 1: is great. Thank you so much.

1131
00:48:28,360 --> 00:48:29,319
Speaker 4: Yeah, thanks for having me.

1132
00:48:37,480 --> 00:48:40,960
Speaker 1: Okay, Diamond, So after that, how do you feel?

1133
00:48:41,040 --> 00:48:45,200
Speaker 3: Oh, I'm into it, Like I'm I'm shocked that I'm

1134
00:48:45,239 --> 00:48:46,279
Speaker 3: so into it, but.

1135
00:48:46,520 --> 00:48:47,920
Speaker 1: I'm shocked that you're so into it.

1136
00:48:47,960 --> 00:48:50,279
Speaker 2: I love this Colossal just got to follow from me.

1137
00:48:50,480 --> 00:48:53,480
Speaker 1: Same. Yeah, and I'm going to join their Explorers club.

1138
00:48:53,840 --> 00:48:54,719
Speaker 2: Can go with you?

1139
00:48:54,840 --> 00:48:57,200
Speaker 1: Yeah, it seems like we have to be like a

1140
00:48:57,239 --> 00:48:59,439
Speaker 1: friend of the Explorers Club, like I haven't. I haven't

1141
00:48:59,440 --> 00:49:02,399
Speaker 1: really done any exploration. But it's not too late. Our

1142
00:49:02,440 --> 00:49:03,880
Speaker 1: next off the grid trip we could go dig some

1143
00:49:03,880 --> 00:49:04,279
Speaker 1: stuff up.

1144
00:49:04,280 --> 00:49:04,680
Speaker 4: I don't know.

1145
00:49:05,000 --> 00:49:07,799
Speaker 2: Well, once you get in, then bring me and I'm

1146
00:49:07,840 --> 00:49:08,719
Speaker 2: gonna get in done.

1147
00:49:09,080 --> 00:49:10,640
Speaker 1: I love that you liked it though, and now you're

1148
00:49:10,680 --> 00:49:11,279
Speaker 1: following them.

1149
00:49:11,440 --> 00:49:13,880
Speaker 2: Yeah, I'm into it, Diamond, that's like a whole new you.

1150
00:49:14,520 --> 00:49:15,319
Speaker 1: I'm into that.

1151
00:49:15,600 --> 00:49:16,480
Speaker 2: It's giving growth.

1152
00:49:16,719 --> 00:49:18,880
Speaker 1: It is giving growth. I like it, and I like

1153
00:49:18,920 --> 00:49:20,360
Speaker 1: that they're doing all kinds of stuff, not just the

1154
00:49:20,360 --> 00:49:22,680
Speaker 1: wooly mammoth. I get it. The woly mammoth is the sexiest.

1155
00:49:22,800 --> 00:49:25,680
Speaker 1: What they're gonna do if, if it is to work

1156
00:49:25,680 --> 00:49:28,080
Speaker 1: out the way he says it, I'm excited to see

1157
00:49:28,120 --> 00:49:31,200
Speaker 1: what they what this actually works out to be. What

1158
00:49:31,239 --> 00:49:33,479
Speaker 1: do you think is a tease? He keeps teasing. There's

1159
00:49:33,520 --> 00:49:35,680
Speaker 1: gonna be something else before the wooly Mammoth. What do

1160
00:49:35,680 --> 00:49:38,680
Speaker 1: we think that's gonna be? Actually, I don't know.

1161
00:49:38,719 --> 00:49:40,640
Speaker 3: I didn't think that deep. I was just so shocked

1162
00:49:40,640 --> 00:49:44,600
Speaker 3: that something is happening. What if they bring back a person,

1163
00:49:44,960 --> 00:49:49,160
Speaker 3: a human being well or caveman.

1164
00:49:50,080 --> 00:49:51,640
Speaker 1: No, we don't need them back. We already have them

1165
00:49:51,680 --> 00:49:52,160
Speaker 1: in the studio.

1166
00:49:52,239 --> 00:49:52,560
Speaker 2: Scary.

1167
00:49:52,600 --> 00:49:55,400
Speaker 1: Hello, they're everywhere.

1168
00:49:55,400 --> 00:49:59,160
Speaker 2: You just gotta look for this whole episode, just like.

1169
00:49:59,400 --> 00:50:01,280
Speaker 1: Just like this, PLU, I got lit up on fire.

1170
00:50:02,400 --> 00:50:05,239
Speaker 1: Oh but you have someone I know you want to

1171
00:50:05,239 --> 00:50:07,840
Speaker 1: put in the burn book, and I am wholeheartedly on

1172
00:50:07,920 --> 00:50:09,920
Speaker 1: board with this. Go ahead. Who are you burning today?

1173
00:50:10,000 --> 00:50:12,120
Speaker 2: Oh, Kathy Hulkel.

1174
00:50:12,160 --> 00:50:15,280
Speaker 3: If you don't know who Kathy Hlkel is, she is

1175
00:50:15,320 --> 00:50:18,360
Speaker 3: the governor of New York City, the first by default

1176
00:50:18,680 --> 00:50:22,560
Speaker 3: by default, yes, absolutely, we won't get into that one.

1177
00:50:22,640 --> 00:50:28,040
Speaker 3: But she is the first female governor of New York

1178
00:50:28,320 --> 00:50:30,799
Speaker 3: and I just want to know why she thinks that

1179
00:50:30,920 --> 00:50:35,400
Speaker 3: from her home in Albany or office in Albany as well,

1180
00:50:35,760 --> 00:50:38,239
Speaker 3: that she can run what we're doing here in the

1181
00:50:38,280 --> 00:50:40,680
Speaker 3: great New York City. I'm confused, but you know what,

1182
00:50:41,040 --> 00:50:44,200
Speaker 3: she's going to be holding hands burning with Eric Adams.

1183
00:50:44,520 --> 00:50:47,879
Speaker 3: I'm throwing his ass in there too, the mayor of

1184
00:50:48,120 --> 00:50:50,799
Speaker 3: New York City, who honestly is just a party boy.

1185
00:50:51,200 --> 00:50:52,759
Speaker 1: This is Democrat on Democrat crime.

1186
00:50:52,920 --> 00:50:55,359
Speaker 2: Yes, absolutely, and I'm standing by it.

1187
00:50:55,880 --> 00:50:56,840
Speaker 1: I'm Kathy Hukel.

1188
00:50:56,880 --> 00:51:00,279
Speaker 3: I don't understand why, as someone who was born in

1189
00:51:00,400 --> 00:51:02,959
Speaker 3: New York City, I have to pay fifteen dollars every

1190
00:51:03,040 --> 00:51:07,600
Speaker 3: day to come into the city from Brooklyn to work.

1191
00:51:07,920 --> 00:51:10,160
Speaker 1: So what Diamond is talking about we talked about on

1192
00:51:10,200 --> 00:51:12,360
Speaker 1: the show a couple of times. It's called congestion pricing,

1193
00:51:12,360 --> 00:51:14,799
Speaker 1: and they're about to enact it here, and if they do,

1194
00:51:14,960 --> 00:51:17,640
Speaker 1: that is going to cost people. I believe it was

1195
00:51:17,680 --> 00:51:22,040
Speaker 1: between three and seven thousand dollars a year, depending on

1196
00:51:22,120 --> 00:51:25,000
Speaker 1: where you're coming from. So if you come from Brooklyn,

1197
00:51:25,200 --> 00:51:28,120
Speaker 1: where Diamond lives, Jersey City, where I live, if you

1198
00:51:28,160 --> 00:51:30,800
Speaker 1: are going through a bridge or a tunnel anywhere below sixtieth,

1199
00:51:30,800 --> 00:51:32,040
Speaker 1: which is everywhere.

1200
00:51:32,120 --> 00:51:36,320
Speaker 3: Yeah, nobody goes to the East Side. I would say, literally,

1201
00:51:36,360 --> 00:51:38,839
Speaker 3: it's the housewives up there and they can't afford.

1202
00:51:39,480 --> 00:51:41,439
Speaker 1: People and they don't have to pay it. But they're

1203
00:51:41,440 --> 00:51:44,839
Speaker 1: about to tax everybody who comes into the city from

1204
00:51:44,920 --> 00:51:48,880
Speaker 1: outside the city and again outside the city Queens Brooklyn, Jersey,

1205
00:51:49,640 --> 00:51:52,600
Speaker 1: the people who keep the city running. Our entire show,

1206
00:51:53,239 --> 00:51:57,000
Speaker 1: You're about to get taxed fifteen dollars every day to come.

1207
00:51:56,800 --> 00:51:59,799
Speaker 3: To work, on top of what you're already paying for

1208
00:52:00,080 --> 00:52:01,600
Speaker 3: the bridges and tunnels.

1209
00:52:01,160 --> 00:52:03,920
Speaker 2: Which are expensive as booked and parking.

1210
00:52:04,160 --> 00:52:07,960
Speaker 3: Yep, I just I don't understand how, Eric Adams, this

1211
00:52:08,000 --> 00:52:09,279
Speaker 3: is why you're getting burned too.

1212
00:52:10,000 --> 00:52:14,120
Speaker 2: You're letting this woman ruin the city. I'm sorry, I.

1213
00:52:14,040 --> 00:52:15,719
Speaker 1: Just need to know what the endgame here is. I

1214
00:52:15,760 --> 00:52:17,839
Speaker 1: know that they're saying they're trying to make up like

1215
00:52:18,000 --> 00:52:21,239
Speaker 1: lost money from COVID and do all this stuff. They're

1216
00:52:21,280 --> 00:52:23,840
Speaker 1: coming after the wrong people, wrong people to do that.

1217
00:52:23,880 --> 00:52:27,680
Speaker 1: You're coming after people who cannot afford to spend three

1218
00:52:27,680 --> 00:52:30,360
Speaker 1: to seven thousand dollars more a year that they're not making.

1219
00:52:30,480 --> 00:52:32,480
Speaker 1: And I'd like to burn our company for a second.

1220
00:52:33,400 --> 00:52:34,960
Speaker 1: They're not helping us out with at all.

1221
00:52:35,360 --> 00:52:39,360
Speaker 3: Then you think about the people who live in this area.

1222
00:52:39,680 --> 00:52:42,080
Speaker 3: They don't have to pay anything, no, because they're already here.

1223
00:52:42,120 --> 00:52:45,000
Speaker 3: And these are the people who, according to Eric Adams,

1224
00:52:45,080 --> 00:52:46,240
Speaker 3: can afford these things.

1225
00:52:46,520 --> 00:52:46,680
Speaker 4: What.

1226
00:52:48,160 --> 00:52:50,200
Speaker 2: I'm sorry, it's crazy. I'm about to lose it now.

1227
00:52:50,239 --> 00:52:54,120
Speaker 3: But I don't understand and I don't think that Number one,

1228
00:52:54,239 --> 00:52:56,680
Speaker 3: it's right, even though we live in a world where

1229
00:52:56,719 --> 00:52:59,200
Speaker 3: nobody cares if things are right or wrong. They're trying

1230
00:52:59,200 --> 00:53:01,360
Speaker 3: to force people to get on the trains. Well, maybe

1231
00:53:01,440 --> 00:53:03,240
Speaker 3: I would get on the train if it was safer,

1232
00:53:03,640 --> 00:53:05,760
Speaker 3: if you weren't gonna murder me, and if you weren't

1233
00:53:05,760 --> 00:53:10,360
Speaker 3: putting the National Guard in only the popular areas. Kathy

1234
00:53:10,480 --> 00:53:15,400
Speaker 3: hulkl you know you know, Yeah, she's burning and gasoline draws.

1235
00:53:15,400 --> 00:53:18,920
Speaker 3: If you ask me, I'm sick of her. Ask Oh yeah, sorry.

1236
00:53:18,600 --> 00:53:23,000
Speaker 1: Diamon is not happy with Governor Hochel, Mayor Adams. I

1237
00:53:23,160 --> 00:53:24,239
Speaker 1: heart that was me.

1238
00:53:24,360 --> 00:53:28,520
Speaker 2: That's that she said, not me, You scared, You're scared. No,

1239
00:53:28,600 --> 00:53:30,120
Speaker 2: I gotta stand ten tones on this one.

1240
00:53:30,160 --> 00:53:32,200
Speaker 1: It's okay, that's okay, I'll take I'll take I heeart.

1241
00:53:33,280 --> 00:53:36,839
Speaker 1: It's funny because our company they actually like if if

1242
00:53:36,840 --> 00:53:38,880
Speaker 1: they're cool with you, and you're cool with them. You

1243
00:53:38,920 --> 00:53:40,040
Speaker 1: say whatever you want, they don't care.

1244
00:53:40,120 --> 00:53:41,120
Speaker 4: Oh well you do.

1245
00:53:41,160 --> 00:53:42,759
Speaker 1: So we're about to find out how cool I am?

1246
00:53:42,800 --> 00:53:47,319
Speaker 1: What I right now? Ah? All right? I feel like

1247
00:53:47,320 --> 00:53:49,320
Speaker 1: maybe we just skipped the ask me anything today because

1248
00:53:49,320 --> 00:53:51,240
Speaker 1: I know that we were with Ben for a long time.

1249
00:53:51,719 --> 00:53:53,160
Speaker 1: This has gone on for a minute.

1250
00:53:53,560 --> 00:53:54,000
Speaker 2: We'll be back.

1251
00:53:54,120 --> 00:53:57,560
Speaker 1: Hit us up right now, like follow, subscribe. We appreciate it.

1252
00:53:57,600 --> 00:54:00,719
Speaker 1: By the way, some motherfucker left review because I went

1253
00:54:00,719 --> 00:54:03,040
Speaker 1: and read it and it said worst podcast ever one star.

1254
00:54:03,520 --> 00:54:05,600
Speaker 1: No explanation was.

1255
00:54:05,520 --> 00:54:08,640
Speaker 3: That you no, but whoever it is, if you want

1256
00:54:08,640 --> 00:54:10,000
Speaker 3: to let me know who you are, I'll give you

1257
00:54:10,280 --> 00:54:12,640
Speaker 3: my congestion text of pricing for the day.

1258
00:54:12,680 --> 00:54:14,560
Speaker 2: I'll send you fifteen bucks just so that I know

1259
00:54:14,880 --> 00:54:17,520
Speaker 2: who did it is. That's hilarious, Literally.

1260
00:54:17,320 --> 00:54:19,360
Speaker 1: Just the worst podcast ever one star. I was like, wait,

1261
00:54:19,600 --> 00:54:23,560
Speaker 1: you can't tell me why? Okay, on purpose, please reach

1262
00:54:23,600 --> 00:54:26,239
Speaker 1: out to me. How can they reach out to you?

1263
00:54:26,280 --> 00:54:28,400
Speaker 2: Diamond at Diamond Sincere on Instagram.

1264
00:54:28,480 --> 00:54:31,560
Speaker 1: Yeah, great, love it at Baby Hot Sauce on Instagram.

1265
00:54:31,640 --> 00:54:34,800
Speaker 1: And we will be back next week with uh something

1266
00:54:34,880 --> 00:54:37,440
Speaker 1: kind of cool. If you're into teeth, I know that

1267
00:54:37,440 --> 00:54:39,000
Speaker 1: sounds weird, but we got a lot to talk about,

1268
00:54:39,000 --> 00:54:43,399
Speaker 1: all right, Say bye, bye bye,