Playing God or Saving Nature? Gene Editing, Artificial Wombs & the Return of Extinct Species | Ben Lamm PT 2

Summary

Impact Theory with Tom Bilyeu

Episode: Playing God or Saving Nature? Gene Editing, Artificial Wombs & the Return of Extinct Species | Ben Lamm PT 2
Guest: Ben Lamm
Date: May 14, 2025

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Episode Overview

This episode of Impact Theory dives into the cutting-edge world of de-extinction, synthetic biology, and gene editing, featuring entrepreneur and Colossal Biosciences CEO Ben Lamm. Tom Bilyeu and Ben candidly discuss the scientific, ethical, and practical challenges of bringing back extinct species like the woolly mammoth and the dire wolf, harnessing gene editing for conservation, and the promise—and peril—of future biotechnology. The conversation also pivots to longevity, plastic-eating microbes, and thought experiments on engineering nature.

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Key Discussion Points & Insights

Parallel Pathways in Extinction Reversal

[01:30–05:57]

• Parallelization over Linearity:
  Ben explains that instead of a stepwise approach, Colossal runs many parts of its projects at once—computational analysis, cell editing, organoid growth, and IVF—all by different teams.

  • “You can parallel path a lot of it.” (Ben Lamm, [01:45])

• The P53 "Cancer Gene" Challenge:
  Discussion on how editing elephant cells (for mammoth de-extinction) needs careful regulation of P53, a gene that in elephants prevents cancer but complicates gene editing.

  • “We had to figure out how to regulate P53. How do you turn it down so you can make the edit… and then turn it back up because you don’t want, you know, super cancer elephants.” (Ben Lamm, [03:48])

• Massive Collaborative Effort:
  Ben details the scale: 172 scientists, collaborations with the National Academy of Sciences, 4 labs, and nearly half a billion dollars in funding.

Why Bring Back Extinct Species?

[05:57–08:48]

• System Innovation:
  Restoring species isn’t only about the animals; it drives technology with broad applications:

  • “Anytime you look at things as a system versus a point solution, …you innovate and build technologies that have far reaching application.” (Ben Lamm, [05:59])

• Inspiration for Humanity:
  The Apollo program is cited as a parallel—the ripple effect of inspiring children to pursue science, which Ben claims is already happening with kids fascinated by dire wolves and mammoths ([07:10]).

The “Trash Version” of Gene Editing

[08:48–10:36]

• Current Tools are Primitive:
  Tom reflects on how science can already manipulate DNA, but compared to where we could be, “This is the trash version.” (Tom Bilyeu, [09:29])

• AI as a Biotech Copilot:
  Ben describes internal AI models that predict gene editing outcomes, optimizing which editing modality to use for maximum efficiency.

  • “We train it all ourselves.” (Ben Lamm, [10:37])

AI Understanding Biology

[10:40–11:19]

• Imminent Advancements:
  Ben is confident that, given enough focus and funding, AI could master biological understanding within 5-10 years, paralleling progress in language models.
  • “If the same amount of effort were going into AI models around genomes, I think that that would be something that could be done in the next five to ten years.” (Ben Lamm, [10:57])

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Protein Folding and Genetics for “Superhumans”

[12:54–14:36]

• AlphaFold and Deep Progress:
  They discuss recent strides in modeling protein folding and how that knowledge enables predicting biological outcomes, like the size gene (LCORL) in canines.

• Gene Editing Realities:
  Making large canids (“dire wolves”) involves piecing together multiple gene variants—a misrepresented process by media headlines ([16:38–19:53]).

On Cloning vs. Gene Editing

[19:58–21:29]

• Limitations of Cloning:
  Cloning requires a living cell, which is rarely available from extinct species. Ben notes future advances may allow full DNA synthesis, removing this barrier.

• Purity Debates Are Misguided:
  Ben critiques the idea of genetic “purity” in de-extinction as unrealistic given that natural variation and incomplete data mark all present-day species.

Addressing “Jurassic Park” Fears

[25:27–27:25]

• Risk Mitigation:
  Ben outlines comprehensive containment and monitoring plans for rewilded animals, partnerships with conservation groups, and an acknowledgment that unintended ecosystem consequences can never be fully predicted but should be carefully measured and managed.

• Conservation Nuances:
  Colossal commits to responsible rewilding only with government, indigenous, and ecologist support.

Creating & Managing De-Extinct Animals

[27:27–28:54]

• Engineering, Not Breeding:
  Additional dire wolves will be engineered and birthed by domestic dogs, which afterward are rehomed anonymously to prevent spectacle.

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Longevity and Human Health

[30:14–37:44]

• Science Exceptionalists:
  Ben defends high-profile biohacker Brian Johnson, viewing experimentation on longevity as a public good, even if results or methodologies are debatable.

• On “Longevity Escape Velocity”:
  Tom asks if humanity will surpass a 1:1 ratio of years lived to years added. Ben is confident:

  • "Yes." (Ben Lamm, [32:52])
  • Predicts achievement in roughly 20 years ([32:55]).
  • Anticipates breakthroughs in blood cleansing, cholesterol drugs, and combo “longevity shots.”

• Confluence of Techniques:
  Next-level health will likely come from combinations of exogenous treatments, gene-guided interventions, and, eventually, AI-driven personalization ([36:10–36:48]).

• Data Preservation:
  Ben laments the generational loss of knowledge when expert scientists die, imagining future AI able to “think like George Church,” preventing intellectual loss ([37:44]).

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Technical Barriers and Breakthroughs

[39:33–43:21]

• Engineering at Scale:
  Colossal’s work is more dependent on innovation and improved tools than on solving currently “impossible” problems (no FTL analog in biology).

• Biological Oddities:
  Creating a marsupial like the Thylacine involves unique physical and genetic barriers, driving invention of specialized tools (e.g., quartz vibration needles to pierce tough egg shells) ([39:33–42:34]).

• Genome Assembly:
  With ancient DNA, sequencing is incomplete, so making an “end-to-end” genome always involves assembling dozens of partial genomes and accepting uncertainty.

Why Thylacine?

[45:02–47:16]

• Ethical Recompense:
  The Thylacine was hunted to extinction by humans, making its resurrection particularly meaningful.

• Genetic Leap:
  The project involves editing a marsupial mouse (fat-tailed dunnart) with 70 million years of genetic divergence.

• Ecological Impact:
  Restoring apex predators helps correct “trophic downgrading,” potentially controlling outbreaks of disease, such as the Tasmanian devil facial tumor.

• Misinformation Challenges:
  Ben notes how misrepresentations in popular media persist for years, complicating both public and scientific understanding.

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Synthetic Biology for Environmental Solutions

[51:29–55:24]

• Plastic-Eating Microbes:
  Colossal is collaborating with the Wyss Institute to develop “Breaking,” an enzyme-producing microbe that degrades plastics in salt water, reducing degradation from 800 years to less than two years, and aiming for 24-hour breakdown times.

  • “It would take plastics that have never degraded… and in a couple of years, completely degrade them… It actually breaks the chemical bonds in plastic.” (Ben Lamm, [53:29])

• Broader Impact:
  Applications include waste water, textiles, and environmental cleanup, with pilots already underway ([55:28–56:04]).

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Philosophy, Future Visions, and Dream Challenges

[57:58–60:33]

• Ultimate Synthetic Biology Challenges:

  • 1. Engineered Living Architecture:
    Imagine trees that grow into houses, or dwellings with integrated bioluminescent lighting:
    • “Why can’t a tree grow in the form of a dwelling? …But then why can’t it have bioluminescent fungi and it, like, light everything up…?” (Ben Lamm, [58:05])
  • 2. Underwater Living:
    Ben dreams of oceanic colonization, creating resilient coral and stable, self-sustaining underwater cities.

• Longevity and Optimism:
  Ben's conviction: If we achieve longevity escape velocity, almost any sci-fi–level future becomes plausible.

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Notable Quotes & Memorable Moments

• On public misperception:
  “The misguided headlines from five years ago—because Game of Thrones… everyone [thought] direwolves were jackals. And that got into, like, the cultural knowledge base of the world. And it was just… misinformation.” (Ben Lamm, [19:19])

• On future genetic editing:
  “Once we do that and we have the ability to do full DNA synthesis… The ability for us to truly guide biology the way we want… completely changes.” (Ben Lamm, [11:19])

• On the power of phenotype vs. genotype:
  “I would argue not only are they dire wolves, but [based on] how 99.9% of every species is classified… they’re even more dire wolves than anyone could predict.” (Ben Lamm, [24:52])

• On media and scientific communication:
  “We worked closely with a handful of people… Even though The New Yorker broke embargo and kind of screwed us for a while, which was… a very, very painful week for us.” (Ben Lamm, [29:49])

• On the legacy of science and public backlash:
  “It’s unfortunate when people like Brian [Johnson] get backlash. This guy is taking biomarkers to an extreme and… we should be thanking him.” (Ben Lamm, [31:25])

• On the role of synthetic biology in environmental restoration:
  “In the cane toad project, we have made a single edit… it confers 5,000 times resistance to cane toad toxin, which is super cool.” (Ben Lamm, [50:38])

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Important Timestamps for Key Segments

• Parallel vs. Linear Scientific Process – [01:30–05:57]
• Philosophy of De-Extinction – [05:59–08:48]
• Gene Editing & AI Tools – [09:25–11:19]
• On Longevity & Human Health – [32:43–37:44]
• Plastic-Eating Microbes (“Breaking”) – [52:21–55:24]
• Ultimate Synthetic Biology Challenges – [57:58–60:33]

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Takeaways & Tone

• The conversation balances awe and pragmatism, frequently referencing how “science fiction” is rapidly becoming science fact.
• There’s a candid tone throughout, with Ben Lamm and Tom Bilyeu both skeptical and optimistic, and unafraid to highlight scientific, ethical, and practical complexities.
• The episode is saturated with curiosity—about life, about innovation, and about the social ripple effects of synthetic biology.

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For anyone interested in the intersection of genetics, conservation, AI, and the future of life on Earth, this episode offers a nuanced yet exhilarating glimpse into what’s next.

Transcript

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[Tom Bilyeu]

I'm Tom Bilyeu and this is Impact Theory. Welcome back to part two of my conversation with Ben Lamb. Let's dive right back in. As you look at what is going to be possible, everything has to be done in order. You can't do everything all at once.

[Ben Lam]

What you can actually, you can parallel path a lot of it.

[Tom Bilyeu]

Say more.

[Ben Lam]

Yeah. So. So in this whole system, right, so we're doing. While we're doing the computational analysis, we know we're going to edit Asian elephant cells. So we have to get Asian elephant cells, right? We have to get the soup or the medium to grow them and grow them happily. We actually. So one of the things that's interesting about we're having this. I had this conversation last night over drinks with Bob Nelson about P53. So do you know anything about P53

[Tom Bilyeu]

having just had cancer removed from my face? Yes.

[Ben Lam]

Yes. So not everyone does. Right. And so what's interesting about P53 is us in mice have one copy of it and the in elephants and blue whales, which are harder to study than elephants for the whole breathing thing is has a. They have about 20 times the expression. And what we know about. We don't understand everything about P53, but what we know about it in overexpression is when a mutation occurs. Cancer is a mutation when what it does is the cell senesces it, like auto terminates itself, just kills itself. Right. So then it doesn't turn into a tumor and then go crazy. And so we know this about blue whales, we know this about elephants specifically. And if you look at the age that elephants live and the body weight that they have, it's called. I think it's called Pedo's paradox. And you look at this distribution curve, they actually don't get cancer. They get cancer a fraction of what they should, like a. A minuscule fraction. They basically don't get cancer compared to what we would if we had the same. We have roughly the same lifespan, if not a little bit more now, but had the same body weight and had the same mass, and so we had the same number of cellular divisions.

[Tom Bilyeu]

Yeah.

[Ben Lam]

And so what's interesting about that is like, you know, to your parallel path point, we had to figure out, if you start editing, a cell looks like a mutation, because it is a mutation. It's a forced mutation, looks like cancer. So we had to figure out how to regulate P53. How do you turn it down so you can make the edge?

[Tom Bilyeu]

What animal did you find this on in Asian elephants?

[Ben Lam]

And then you had to figure out how you turn it back up.

[Tom Bilyeu]

This is in the woolly mammoth experimentation.

[Ben Lam]

Yeah, in the woolly mammoth project. So this goes back to your parallel path is like while we're doing computational analysis in your data, like more data is more data. Right. So as we're getting more and we're looking at more of these, as we're running, like our woolly mice experiment, as we're growing organoids over here, as we're creating induced pluripotent stem cells so that we can create organoids in the first place, and then eventually gametes. Then we're also working over here on the actual editing of this, of the targets that we made in the woolly mouse, of the mammoth equivalent. We're also working on the. We had to figure out before we could even do that, how to regulate P53 and turn it down, but then turn it back up because you don't want, you know, super cancer elephants. And then we also have a whole team over here that's working on Elephant IVF.

[Tom Bilyeu]

How on earth do you turn P53 down for a bit and then back

[Ben Lam]

up it's a great question. I don't know. That sounds like someone on our science team that's much farther than me can tell you that.

[Tom Bilyeu]

That is crazy. So are you turning it back up in the same creature?

[Ben Lam]

You're in the same cell line, right? Because what you don't want it to do is you want to be, you want to make sure that you can turn on. It's kind of like the reverse of like immortalization constructs. If you put an immortalization construct so that the cell just keeps dividing, keeps dividing, well, eventually it would turn into cancer. You got to eventually sometimes when you're making lots of edits, take out those immortalization constructs. And so it's a similar kind of thought process on the P53 that, that is.

[Tom Bilyeu]

So yeah, I don't know what to do with that. I don't know how that's possible.

[Ben Lam]

That's. But it goes, it goes back to your core question is like, you know, we're not, if we did all this linearly, we would have animals, it would take us a decade per animal. But you know, the reason why we, you know, we have four labs, we have 172 scientists, including, you know, people a part of the, you know, National Academy of Sciences, our chief science officer. We have 17 academic partners around the world, we fund 40 postdocs and we have 95 scientific advisors with all of that, you know, we've, we've tried to pull all that together and then we've raised a lot of capital, raised roughly half a billion dollars to do this. And you have to do this because you have to build the system. And if you want to do it, you know, and have like all these species back, you have to do it in a parallel pathway.

[Tom Bilyeu]

Okay, why do we want all these species back?

[Ben Lam]

So, you know, a couple of core reasons. Number one, I think that, and I think you probably get this from your background, anytime you look at things as a system versus a point solution is a higher. It's known through like every scientific and every engineering feat like the Apollo program that you innovate and build technologies that have far reaching application than you have any idea for is a point solution. Where it's like, oh, I'm going to have a hammer and a nail and I'm going to just, I, I just want this piece of wood to go here, right? Whereas a system model is. I want to build a sustainable house that can survive all of the elements. Right? So you have to build all of those systems, right? Where you have clean water, get rid of extreme, get rid of all, you know, be able to do air filtration, have power. So it's a very, very different way of looking at things versus like, I just want to solve X. And sometimes I get negative feedback on this when I talk about it as it relates to scientific papers, because I'm a very big believer in looking at the system and document showing the science over time. But that's not the priority. Right. The priority is, can we do this? So anytime you develop a system and specifically one that has an application to conservation, I think that's interesting and it allows us to innovate. So number one is it's a system model that drives a lot of potential for both support for conservation as well as technologies that could apply for human healthcare, both monetarily and monetized, but also that could also just help humans. Right. So that's one reason why I think we do this. A second reason why we do this is I think that doing things that are hard teach us more. They make us ask harder questions. Like, we had a whole conversation about eugenics today. Would we have had that conversation if we weren't talking about gene engineering and pushing gene engineering to the limits? Because we made a dire wolf and a woolly mice? I don't know. And so I think it also helps us, from a human condition perspective, think bigger and then expand kind of what. How does it widen our aperture in terms of what is possible? And then the third thing is kids, like, we people, like, love to just like, skirt over this when we're talking. The people that don't love what we're doing love to skirt over this. But every week we get stacks of like, letters and drawings and paintings and stuff from teachers and parents and kids saying, my kid wants to go be a scientist, or my kid wants to be a biologist, or my kid and I, like, we had a woman from Florida sent us a note saying that her classroom won't be quiet except when they're talking about dire wolves and woolly mice and mammoths and all this stuff. And they're obsessed with it. And so I think inspiring the next generation, like the Apollo program and the effects of the Apollo program, I think created, I think outside of the success of going to space and opening up space in kind of that monumental triumph for humanity, I think it changed the human consciousness on a level of what was possible. Yeah.

[Tom Bilyeu]

When I look at gene editing, when I look at particle physics, I feel the same way that you see these things that just exist, they seem so fundamental, they seem unalterable. The process by which they come into being feels like magic.

[Ben Lam]

Yeah.

[Tom Bilyeu]

And then to hear. Oh, no, no, no. Like, you can. You can read the DNA, you can go in, you can make edits. You give the virus a little tugboat thing. It drags it in, it puts it in the right place. Like, it's just. It makes me realize the world does not work the way that I thought it did and that there are levels to how much I can engineer it.

[Ben Lam]

Yeah. And I think that we're just going to get better at it. Right. Like, we, we as a thing.

[Tom Bilyeu]

Like, this is the trash version.

[Ben Lam]

Yeah, this is. That's a good point. We are. We are the trash version. But I, I do think we're at this point where, you know, over the next five to 10 years, we are going to be moving more and more into using AI and big data to. And compute to essentially be able to do simulation of design. Right. So it's like, how do we. Like, we have a tool. This is kind of weird. And this is a very. This is a trash version of it. We have a tool where because there's so many different editing modalities based, we continually feedback into this, into this model, what works, the efficiency, what off targets were like, unintended consequences happen. We keep feeding back in the model. And so we've got this like this internal software product that we built where it's basically so we can now put in those guides and put in the designs that we're trying to design. And it will recommend what different editing modality which will and predicts what is the highest level of efficiency it thinks that we'll do based on that combination.

[Tom Bilyeu]

Did you guys train the AI yourself?

[Ben Lam]

Yeah, we train it all ourselves.

[Tom Bilyeu]

Crazy.

[Ben Lam]

Yeah.

[Tom Bilyeu]

Are you.

[Ben Lam]

We're doing a lot of editing.

[Tom Bilyeu]

Do you think that AI will be able to master. Might be the wrong word. But will it be able to understand biology in the way that it understands language?

[Ben Lam]

Yes.

[Tom Bilyeu]

How close are we? How long is that going to take?

[Ben Lam]

I think it's. It depends on focus and funding. Right. Like, you know, people want it to write, you know, jokes and essay papers. Right. It's like if the same amount of effort we're going into AI and training large language models around genomes, I think that that would be something that could be done in the next five to ten years.

[Tom Bilyeu]

Whoa.

[Ben Lam]

Yeah. Once we do that and we have the ability to do full DNA synthesis, like be able to write everything that we know we need to write with a high degree of confidence that it's going to Work or multiplex edit on a scale where we're making things thousands of edits at once with 100% efficiency. Once we're able to do all of those things and do all those things really, really well, then I mean I think that the field of synthetic biology, the ability for us to do accelerated directed evolution, the ability for us to truly guide biology the way we want and not just based on environmental factors and random chance completely changes.

[Tom Bilyeu]

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[Tom Bilyeu]

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[Tom Bilyeu]

All right, we're back.

[Ben Lam]

Let's get into it.

[Tom Bilyeu]

Put your sci fi rudder hat on for a second. So we have the five to 10 years of, of training the model. The model is now for people that don't know, it's probably worth going into a little bit of alpha fold protein folding. How far we've already come on that, but on the other side of that, so we map all this stuff out, what starts to happen are we like oh, we take a 25 year old and we make sure that they can withstand radiation and we send them to Mars. We take a 78 year old and we make them look 26.

[Ben Lam]

Yeah. So all the above. So I, I think that we will look at being able to, to engineer things.

[Tom Bilyeu]

First of all, give me protein folding. What makes you believe that this is going to happen?

[Ben Lam]

Why I'm gonna, why I believe it because I think we're getting really under. We are, we are getting so good at understanding like how a protein, how a specific thing that that is made from, from our body, how its actual shape is and how it binds you. You probably heard about how different blood types and other and other reasons why certain diseases like Covid there's different ways that based on how it actually folds, how it fits together. So think of it as like a complex puzzle. Right. So it's not a two dimensional puzzle. It's a three dimensional puzzle and how you put those things together. They can only bind or fit together certain ways. And it's based on how the folding, how the protein is folded. We've gotten so good. We, not we as colossal we as humanity have gotten so good with Rosetta Fold and Alfold and all these, all these tools that we are now understanding the shapes of proteins so that we can predict what it will bind to and how it will bind.

[Tom Bilyeu]

What do the machines look at? Are they looking at a sequence of letters and they say, oh, this will create a protein that looks like this.

[Ben Lam]

They're looking at a sequence of letters that then will do that prediction. And then I don't know what the functional assays are that they then do it and the molecular assays are to verify it or. But it's highly accurate. So we did, we went through a process with a, with a gene called L coral, specifically for which, which drives size or it's known to drive size. It's not the only thing in size. So it's not like, once again, some of these things are multigenic in nature. Meaning that we can't just like, oh, we can't just make the super L coral. And then you do have like an elephant size Chihuahua, right? Like, you just can't do that. It's, it's, it's a lot of these genes working in concert together that produces some of these phenotypes. But we know for a fact that a truncation in El coral in how it folds looks in Great Danes is different than that in Chihuahuas, for example. Right? And we know that drives some percentage of size. We don't know if it's, we don't know if it's like 100% or 200% or 5% or 20%. But we know, we do know from looking at mice, from looking at doing candidate analysis, we know from years of scientific research that that gene specifically with this truncation creates a larger sized canid. Like, we know that. And so when we went to look at the phenotypes for the dire wolf, we looked and said, okay, what is the L coral variant? Does it match the gray wolf? Does it match the Chihuahua? Does it match the Great Dane? It looked a lot more, a lot more like a Great Dane than it looked like a wolf or whatnot. So, you know, so we put that variant in, right? And so that truncation in that gene, you know, increase. You know, we have much larger wolves than typical wolves at the size and the age that they are. So we think that, you know, that was. That truncation helped lead to that.

[Tom Bilyeu]

Did you pull the one. The exact Great Dane version of it, just to make sure that it would

[Ben Lam]

be compatible, the direwolf version of it. So, because direwolves are. Because there was debate on this, which, once again, this is an educational opportunity, right? So, like, when we. There was a paper that came out in 20. It's like 2021, 2022, because direwolves were popular, because Game of Thrones and they were only able to get. And Best Shapiro, our chief science officer, along with another 30 incredible scientists were on this paper that basically the results of the paper, because they only got 0.15x, so they didn't get a full read of the genome. So they only got about 15% of the genome. They didn't get a full pass based on the sample that they had at the time and the technologies that they were employing to do it. They looked at this and the conclusion that they came to in where a dire wolf fell was it was somewhere between a wolf and a jackal. I don't know if you've seen, though, sometimes the results of those discoveries when they make it to media are. And this was not us. This was years ago. Dire wolves weren't wolves. They were jackals. That's not what the paper said, right. I was involved, like, I was running another business. I. I didn't even know about this at the time. Didn't. Didn't read the paper. But that's what the headline in a moderately reputable news magazine, news outlet of today said and is like the Direwolves Jackals. And so still to this day, so now, so fast forward, colossal has 500 times, not 500, like 500 times more data about two different variants or two different samples of dire wolves that have 60,000 years of genetic divergence between our two samples. Whoa, that's a lot, right? What people don't realize is that there's more genetic divergence between sample A and sample B, that Colossal sequence, than sample A and today. Because that's 12,000 years, right? And so it's like, it's very. It's very, very simple, right, to see that. But what people don't realize. So we took all that data, we went back to that initial author list on that first paper, and we built a phylogenetic tree, and we said, on the phylogenetic tree, where do direwolves fall? And it turns out that they were like everything in life. They were a hybridization of an extinct lineage of canids that were closer to wolves. That doesn't mean that. The paper that came out years ago that said we don't. With the result was we don't know if they're closer to wolves or jackals. It's inconclusive, but it's somewhere between there. It doesn't. This is just more data so that we know. Oh, it skews more towards the More towards gray wolf lineage than jackal. Right. And that's kind of what everyone thought. But, you know, the misguided headlines from five years ago, because Game of Thrones, everyone got so excited, but then they're like, oh, direwolves were like, these are. These are fantasy in the show because they're really jackals and they're jackals. And that got into, like, the cultural, like, knowledge base of the world. And it was just. It was just, you know, misinformation. Yeah. So now. And so we. We literally get comments. We're like, these guys don't know what they're doing. They started with the gray wolf. Gray wolves aren't clustered.

[Tom Bilyeu]

Such a weird reaction.

[Ben Lam]

I know.

[Tom Bilyeu]

Look, I fully understand. It's what humans do, but it was a weird.

[Ben Lam]

It was fun.

[Tom Bilyeu]

What a strange way to respond in the face of what is possible.

[Ben Lam]

Yeah.

[Tom Bilyeu]

Okay, so why not clone? Why not go grab, like, I get maybe a direwolf. There's nothing where you've got 100 of it, but with things that you could get 100% of the sequence. Is cloning better at that point?

[Ben Lam]

Well, you need a living cell to clone. Right. Because you're taking a living nucleus and taking it from a living cell and putting it into.

[Tom Bilyeu]

That's the only way to clone. You can't clone off of a DNA strand.

[Ben Lam]

No, but what you can do, this goes into the. This goes into the artificial egg and, you know, with mitochondrial. Figuring out mitochondrial rejection and then DNA synthesis. So instead of synthesizing a big block, what if you could synthesize the whole block? Right. And so I think eventually we'll get there. It's unclear, but. But this is where. This is where it's funny that we talked about eugenics. I made a. I made a joke on a podcast that wasn't well received by the scientific community, which is like, I've never seen the scientific community so eugenicsy about a wolf before because they all wanted to argue over. Because it's true. It's like, you know, if you look at the phylogenetic tree and. And you look at all life that's ever been like the tree of life. Right. Better known as the Tree of life. And you look at all of it, 99.9 to the nth degree is based on where it lived, when it lived and what it looked like. We don't have DNA from anything. We don't have, as I mentioned, we don't have DNA from the animals that live today. And so this idea of purity of direwolf is just a psychotic perspective. That's just weird.

[Tom Bilyeu]

Okay, well, let me steel man their argument for a second. This is a Ferrari chassis on top of a Toyota engine. How is it not that try to

[Ben Lam]

go pet that that Toyota engine and see how it works out for you?

[Tom Bilyeu]

Because just the way that they, I

[Ben Lam]

mean, if you look at just their size and where they were located, one, our genetic donor was where we, we got it from, where they're located. So we took gray wolves, which were American gray wolves. We didn't import them. Right. So we kind of met that standard and we looked at. And if you looked at just the. So that that kind of fits where they came from. We, we chose the same wolves from the same place that they came from. Right. We didn't import magic wolves, number one. Number two, if you look at kind of the phenotypes, here's what we know about direwolves. This is all we know about dire wolves. They were 20 based on the fossil record. I'm going to tell you something else that we didn't know until Colossal did it, but no one seems to care. One is that they were 20 to 25% bigger. They had a larger cranial facial morphology which implied that they had a stronger bite. And based on their bone density and their bones, specifically in their shoulders and in their, and in their legs, most likely, you know, they were, they were heavier, right? So they were a stockier animal. That is what we know. So if we just did that, I would argue that from a functional de extinction perspective and the same way that we classify 99.9 literally indefinite species in the tree of life, they would be classified as direwolves. But we didn't. What we also did is we said, oh, this is interesting, their coats were white. And we know that because we looked at the data and we found in the DNA that there's no direwolf. There's no frozen direwolf, there's no frozen samples of this. People thought because of a paleo artist rendition of that paper from five years ago that they were red because they were like. We got a reddish brown because they're like. We got to make them look more like, you know, jackals because they're closer to jackals because someone read an article that was inaccurate at the time. And even people in that paper will tell you from that paper, that paper didn't say they were jackals. I know it. Because these people wrote it. Because they were like, we wrote it. We're the ones that wasn't in the conclusion of the paper. And so we actually took it a step further in two categories. One, we found kind of like in the woolly mouse, the hair variant that drives the hair. And so they have a much thicker hair. I mean, when they were born, they kind of look like baby polar bears. They're amazing. They're like these cute little fluff balls. And then. Which. There's pictures all over the Internet of them. And then if you look at their hair now, super thick, It's. It. There's like waves to it.

[Tom Bilyeu]

It's.

[Ben Lam]

It's amazing. They almost have this, like, ridge line to them and, like, mane across their back, which is amazing. We had no idea of that from the fossil record. We also didn't know they were white. We had only misinformed the public and said that they were red or brown because of a conclusion of a paper that. That the paper didn't come to that conclusion anyway five years ago. And so I would argue that not only are they dire wolves, but based on how 99.9% of every species is currently classified on the planet. But, you know, there are even more direwolves than anyone could predict based solely on those phenotypes. Because we identified things in the. In the DNA.

[Tom Bilyeu]

And so you guys, how many, like, DNA blocks?

[Ben Lam]

So we edited. So we edited 2014 genes with 20 edits, okay?

[Tom Bilyeu]

And starting with a gray wolf.

[Ben Lam]

Starting with a gray wolf. This is our genetic donor because they're 99.5% the same genetically.

[Tom Bilyeu]

Got it.

[Ben Lam]

Comparable to what Asian elephant is to mammoth.

[Tom Bilyeu]

Okay.

[Ben Lam]

And most people don't realize this, but Asian elephants are closer related to mammoths than Asian elephants are to African elephants.

[Tom Bilyeu]

How do we not end up in a Jurassic park scenario where we made something and it has an unintended consequence in the ecosystem?

[Ben Lam]

Well, it's a great question. And for all these species, we go, like people think about. And I don't think that was the exact premise of Jurassic park because they weren't rewilding the Jurassic Parks, right? Like, they didn't have a. They did not have an ecosystem restoration or a conservation subplot that. Unless that just got, like, you know, on the cutting room floor. But so I don't think it's exactly the Jurassic park scenario. But to the ecosystem restoration unintended consequences is we have to measure all this stuff. Right. Anybody that tells you like, hey, you can introduce this species back here, will have zero unintended consequences or will have this intended consequence is just wrong. But the beautiful thing about rewilding is that colossal people kind of, I think, once again give us too much credit. They're like, oh, they're just going to rewild them. And it's like we have a foundation that we raised $50 million for and we have 48 conservation partners, including some of the top rewilding partners in the. Specifically on the direwolf project. We actually work with some of the gentlemen that ran the Yellowstone rewilding program for gray wolves back into Yellowstone. So we, you know, if, if, if the government, indigenous people groups and ecologists and everyone wants to rewild direwolves at some point, we would work with them to do that. Right. Like we built a rewilding plan. Because I think anytime you do this, you should at least be like, what are the possibilities? Right. So you should think about that. But they live on a 2,000 acre, secure, expansive ecological preserve that are monitored 24 7. They've got 10 that's certified by American Humane Society. They've got 10 full time people to attend to them. Security, they've got storm shelters and animal. We built the animal hospital in case anything happens to them, that we can treat them right there. They don't have to like, it's not like calling 911 and then having to take them to the hospital. We have a hospital and a full time vet there.

[Tom Bilyeu]

Are you guys gonna make more direwolves?

[Ben Lam]

So we are gonna make three to five more. So we to have a pack size of roughly five to eight. Because.

[Tom Bilyeu]

Will you impregnate the ones that you have?

[Ben Lam]

No, we'll engineer them. So we're going to engineer them and

[Tom Bilyeu]

they'll be birthed by a gray wolf or by a.

[Ben Lam]

No, no, by domestic dog. That's crazy.

[Tom Bilyeu]

What kind of dog?

[Ben Lam]

So they're just large hound mixes.

[Tom Bilyeu]

Is that dog like what just came out of me or do they just.

[Ben Lam]

They nurse them and everything here they get the colostrum from and everything. They nurse them and take care of them. It's great.

[Tom Bilyeu]

So to them it's like, I just have weird looking kids.

[Ben Lam]

Yeah. Or super cool kids. Depends on how you want to look at it. But then, but then all of our, you know, and then we work. This is, this to me is Kind of fun is that, you know, because we work with American Humane Society, so. Well, all of our dog. All of our dog mothers, our chariots, get adopted through an anonymous adoption program to their forever home. So that's kind of fun. There's people out there that have, you know, moms of direwolves, but you don't

[Tom Bilyeu]

want them to know. For some reason, we.

[Ben Lam]

It's just like, I feel like that's, like, a spectacle of the animal, right? Like, not saying that anyone do that. Like, I think that if I. If, like, you know, people I know adopted them, they'd probably be like, oh, that's cool. And they may tell their friends, but who knows? I mean, people are. You know, we're all weird in our own ways. Someone could try to exploit that, right, and be like, oh, this is the mother. You know, like, in Game of Throw, like, mother of dragons. This is the mother of direwolves. And it's like, I don't think that's good for the animals. That's.

[Tom Bilyeu]

Oh, man.

[Ben Lam]

What people sometimes don't think about is, like, if my job was to raise money and hire an awesome team and let them just do stuff in the lab, this job would be very boring and easy. What's interesting about this job is that we have conversations like this, right? We go meet with the government. We go meet with indigenous people, leaders we work with. Okay, how do we adopt our surrogate moms, Right? Like, there are so many nuances to how we think about this that that's what sometimes is hard, that unless you, like, say, you know, when. When we launched the Darwol story, we worked very closely with a handful of people. Rolling Stone, Time Magazine, the New Yorker, and others. Even though the New Yorker broke embargo and kind of screwed us for a while, which was very, very painful week for us because we didn't have our website up. We didn't have our. Our scientific paper hadn't been submitted.

[Tom Bilyeu]

Did they apologize or did they do it on purpose?

[Ben Lam]

Well, they definitely did on purpose because it was in print. You don't like. It's not like someone, like, spilled coffee and hit the publish button, right? They're like, oh, yeah, that looks good in print. Indesign or whatever. And. And that's going to the printer, and that's going to newsstands tomorrow, so that doesn't feel like an accident.

[Tom Bilyeu]

Yeah.

[Ben Lam]

So they have not publicly apologized, but we'll just never work with them again. So it's fine.

[Tom Bilyeu]

Yeah. Interesting. Okay, let's bring this all back to humans, okay? So you've got Brian Johnson, the don't die movement.

[Ben Lam]

Yeah, I know.

[Tom Bilyeu]

Jevity Escape Velocity.

[Ben Lam]

How Peter D Man is. You actually have a lot of people here in L. A. Yeah, yeah, Peter.

[Tom Bilyeu]

I know well, Brian. I know well. Ish.

[Ben Lam]

And I don't think Brian gets enough credit because, like, people like, you know, we live in a. We live in this like armchair Twitter X people where they just want to criticize. They don't want to do anything. Right. Like, what's that famous quote that's like, you know, the, the that, you know, people are either on the field or in the stands. And there's a lot more people in the stands bitching with people on the field a lot. Yeah. And. And like, you know, I'm not going to do everything that Brian does because it's a. That is insanely hard lifestyle. But I'm glad that someone's doing it. Like, so that's the way I look at it. Right. It's like, Brian's not hurting you. Yeah. I don't understand Brian's. But there's this weird backlash towards Brian. I don't agree with everything he's doing, but he's not like saying, you know, hey, you have to do this, you have to do this. You know, he's not showing up with like ski mask and like making people do red light therapy.

[Tom Bilyeu]

And so it's so that I kind of would get behind that I would go buy a new business model for it.

[Ben Lam]

I love red light therapy. But like, I think that it's unfortunate when people like Brian get backlash. It's like this guy is taking biomarkers to an extreme and he is running an experiment that we. That someone in science should be. We should be lucky. We should be thanking him that he's doing this.

[Tom Bilyeu]

Yeah. Kick off as much data as you can.

[Ben Lam]

And I'm not saying I agree with all of his. The results from it, but you know, if you sit down with Brian, which sounds like you have, he'll tell you like, the number one thing is sleep. Like, the first is like, you don't even have to get weird on like your eating schedule or workout schedule. He's like, you really need. He said the number one thing to me is like what your resting heart rate is and variable heart rate is going into sleep in that transition mode to sleep.

[Tom Bilyeu]

Yeah, that makes a lot of sense. More with Ben Lam after this short break.

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[Tom Bilyeu]

All right, we're back.

[Ben Lam]

Let's get into it.

[Tom Bilyeu]

Do you think we will actually hit longevity escape velocity where science adds a year of life for every year I live?

[Ben Lam]

Yes.

[Tom Bilyeu]

How soon?

[Ben Lam]

In the next 20 years. Yo. Yeah.

[Tom Bilyeu]

What's going to be. What are the sequence of breakthroughs that we need to get there?

[Ben Lam]

I think the biggest thing that we need is. So there's been a lot of stuff on cleansing blood. A Yo.

[Tom Bilyeu]

I didn't see that coming.

[Ben Lam]

Yeah. So this is. This is a newer thing.

[Tom Bilyeu]

Super kidneys.

[Ben Lam]

No. You remember the Silicon Valley blood boy episodes? Yeah. Where they'd like circulate the blood.

[Tom Bilyeu]

Bro, that was real. So get your boy hooked up.

[Ben Lam]

So get ready. So there is a. Not that service, but there is a service that's not currently available in the United States. States. I have not done it and nor do I endorse it because I haven't done the research on it.

[Tom Bilyeu]

Sure.

[Ben Lam]

But Gary Bruck has talked about it. A handful of other people have talked about it. But where they basically do. It's like a super dialysis machine. Right. So it's a transfusion. Takes all your blood out, runs it through a system that's basically like this super mesh and it takes out precancerous tumors, old cells, just all this stuff and it pumps it back into your body. And it's supposedly like the blood that goes back into you is like the equivalent of like a 26 year old. So that's. Do you know what that's called? No. We can find it.

[Tom Bilyeu]

We just call height did something like that.

[Ben Lam]

Peter Diamandis knows it too. I forgot. So I think you're gonna have like the cleansing side of that side. Right. And then I think what you have. And so I think that's here today. Another thing that's here today, if you look at like the. The big causes of. Of death in America is like you have heart disease, you have diabetes. Many people think that Alzheimer's and dementia are basically type 3 diabetes and just bled from inflammation. Right. Which is diet. And a lot of things can be driven by that. But if you look at things like cholesterol, we have medications now that you can absolutely lower your cholesterol and not have heart buildup. So my Gary and I have a site, I'm learning more. Gary's got really good ideas. But you know my, my LDL is in the 30s which is, and what they've shown is anything under 60 you start to reverse any plaque or any buildup in any of your veins and arteries.

[Tom Bilyeu]

And you got there by taking something.

[Ben Lam]

Yeah, I take a, I take a repatha which is made by Amgen. I don't, Injection and an injection. Yeah. And so, so, so you, you have things like that. Then you've got things like metformin. Right. And you've got other things to lower your A1C. So I would argue that we have roughly defeated diabetes and major forms of heart disease today. Right. Like I, I, I, I truly believe that like you know, if you, if you, if you don't eat sugar, if you do, if you eat a moderately healthy lifestyle and you take certain therapeutics. We have done that. I think the GLP1 some people hate the GLP1s but I think the GLP1s are really, really interesting. They' because you have these GLP1 receptors not only in your brain but all of your body. You're starting to see things like kidney function improving, muscle function and heart improving from this. And these are all non BMI related studies. So there are people that think that GLP1s will lead to lower Alzheimer's in dementia, but those are a lot of.

[Tom Bilyeu]

So do you think the punchline is gonna be a bunch of exogenous stuff or do you think the punchline is gonna be A.I. reads your genome? We get very good at this.

[Ben Lam]

I think that the punchline for longevity escape velocity, which is one to one is a combination of therapeutics. And then I think eventually kind of like the function blood test or others, you will get a combination. So instead of taking like a repatha shot, a you know, GLP one shot, whatever the frequency is and whatever the doses is, you take your metformin. I think you'll have a single like shot. I think it'll probably be administered via shot versus orally.

[Tom Bilyeu]

That's really interesting.

[Ben Lam]

So I think you'll have like a combo shot that is like your longevity shot that keeps all your biomarker, that gives you like Brian Johnson level biomarkers. So I think you'll have that and I think you'll have that before we have, you know, the point that we are, you know, do doing full kind of like AI and I think AI could be applicable to that. But I think eventually we have AI that, you know, tells us, like, hey, here's xyz, you know, edits to your body. That that is because you're close enough

[Tom Bilyeu]

to that problem to know how hard that's going to be.

[Ben Lam]

Yeah, it's really hard. But I mean, there's people out there, like, you know, I mentioned Bob Nelson. His. He's got numerous companies including like Altos Labs. George has Rejuvenate Bio, that's doing insanely cool stuff. And these are there. There's biotech companies right now that are in preclinical trials and some in clinical trials that have, you know, potential, like massive potential for longevity.

[Tom Bilyeu]

Hmm. It's interesting.

[Ben Lam]

Longevity. I think that, that there is a, A. I think that there is a. And I think I potentially could help solve this. But there is a very large drop off in that transitional data between like the world's experts. If you take like the world's expert in like epigenetics or the world's expert in genome engineering like George, and he dies, you can go read all his research and you can go, but unless you've trained an AI to think like George, be creative like George, have every thought that George has had then, then you're going to lose. Even if you have the next best geneticist in the world, they're. They're not like there's going. There's still like this generational loss of data that occurs. Right. Because there's problems that you probably think of or I think of that we don't write down doesn't mean that, that on some like, background thread they're not running all the time and you're not thinking about them, but you probably just haven't like, I'm going to go solve this problem. I'm interested and I've accumulated data based on this interest. But you haven't like put that into something that if you were gone, that I or someone else could go read. And so I think that, I think I can help with that. But I think that if we can increase some lifespan and increase even if we don't get to full longevity, escape velocity, I think that coupled with AI, that coupled with health span so that you are more productive to society longer, you eventually get to the point that it's where it's just immortality.

[Tom Bilyeu]

Mm. What are the roadblocks that you see coming with what you're studying right now? Like, when I look at AI, I say, okay, well, if there is no computation problem, meaning we have enough chips, if there's no energy problem, then I don't See why we don't get to asi do you see like are there similar things like that with what you do where you're like well we'd first have to be able to solve for this problem.

[Ben Lam]

So for us with, with what we are trying to do at Colossal, there's no FTL problem, right? It's like we don't have to solve faster to us to get to our Alpha Centauris. We don't have to solve faster than light travel. It takes us a longer time and it costs more money. So ours is an efficiency, ours is more of an innovation play than an invention play. Right. We are trying to innovate these technologies. That doesn't mean we're not trying to invent new things along the way. So we are doing some discovery. But, but you know our bank is that AI and some of these other access to compute will accelerate the efficiency of these technologies because we are doing it right now on a rudimentary scale. And you know, when we started the business people were making one edit at a time. Our thylacine project, we've made 300 edits in the cell line. We haven't taken that to term yet because we haven't solved the cloning, the symmax on the code transfer process in, in marsupials yet. We have a team that's working on it.

[Tom Bilyeu]

Why is it different?

[Ben Lam]

It's so once all these on model species are unique. So so for example, this outer shell in a mar old because you think giant big elephant, right? Or human, right. And then you see these like little bitty dun art and you'd probably think what's probably got the weakest little cell ever ever. It's got this zona palooza, this outer shell zona palosa, which is insane.

[Tom Bilyeu]

That's the literal name.

[Ben Lam]

Yeah, that's the literal name. So we, we, we have created this laser assisted system for drilling in using a laser in so that we can extract DNA. We're now doing it with computers and, and robotics and AI. It's pretty air in computer vision. It's pre. But we hit it with the laser doesn't move the outer shell. Whoa. Doesn't move it. We go up to like 11 or whatever the highest dial is and then some and just the cell just blows up because you just like hit it with like the Death Star, right? And so what? And so and then if you use, and the reason you use that because if you use like a needle, if you're going in and you're in your jamming the needle it's like you are damaging the DNA in that.

[Tom Bilyeu]

Right.

[Ben Lam]

It's like the fact that, like, Dolly even worked with, like, all the blunt instruments is a ma. Is magic in itself. Right. I don't think the team at Edinburgh and the team that did Dali gets enough credit. That is a miracle in itself. Like, people don't realize that they're just like, oh, they just moved to sell. But given that they were like. They're like flying using nails and hammers and wrenches, it was incredible what they did. And so now it's come a long way. So for specifically that, we actually had to invent a. So a lot of times we'll even make our own tech. So we actually make our own needles, in many cases, our own glass needles. So we had to make it out of quartz so that we could. So that we could vibrate it at the right frequency so that the vibration. So that the. Because the glass couldn't take it, but the quartz could because it was hard enough. And then that quartz needle at that vibration could pierce into it because the laser wasn't strong enough. And when we dialed it up too much just destroyed the cell.

[Tom Bilyeu]

That is fascinating.

[Ben Lam]

But see, those are the weird things that we have to solve when people are like, oh, it's. It's. It's just a. It's just the most genetically modified animal on the planet. I was like, yeah, but we had to do a bunch of other stuff.

[Tom Bilyeu]

What do you think is the upper limit of the number of edits you can make without.

[Ben Lam]

Without DNA synthesis, without just synthesizing it? And you mean. You mean through multiplex editing?

[Tom Bilyeu]

Yes.

[Ben Lam]

Thousands, maybe tens of thousands.

[Tom Bilyeu]

Whoa.

[Ben Lam]

That's all you really need because you're doing Target. I mean, the more I would argue, though, once again, this is coming from a software perspective. I'll get shit about this from a biologist. But the smarter you are in computational analysis, the more you know, the less edits you make. Because every edit you make is going to have some level of risk because

[Tom Bilyeu]

things are redundant or they're not necessary to the final form.

[Ben Lam]

Yeah. And the thing that people don't realize, like, when you get a genome sequence of all these letters, right. And you run it through the reason why you need so much coverage. We talked about, like, I think we ended up having 13 or 14x coverage. That means that we had 13 or 14 full reads of the genome for the direwolves, whereas before they had 0.15x, they didn't have even a full one read. The reason why you need that is because. And you need to have at least probably about 6 or 8x, I think, to do DE extinction properly, because your BA. The machines aren't perfect. So. And the DNA is degraded. So it's giving you. At every single site where it's saying, this is a XYZ letter, right? This is a C or a G or whatever. When it's doing that, it says it's giving you a probability score that this is a C. It actually isn't 100%. So they're like, oh, it's like 50%, 99%. So the more you do, then the higher probability is that you get that. Right. And so even when we as humanity get the point that you can synthesize a full genome and this is where not to argue the weird eugenics points again about what makes a mammoth a mammoth, even if you get to an end. To end. To an end mammoth. There is no end to end mammoth genome. So right now we're doing an assembly of a mammoth genome, building a reference genome, but we're using 60 genomes that we're putting together, right? And so then you've got to go look at that and then you've got to go say. So even if you synthesize all of that, you're still going to have holes. So we have a. We announced in October of last year that we have a 99.9 complete genome for. For the Tasmanian tiger or thylacine, which is amazing.

[Tom Bilyeu]

How are you picking what animals you do? In what order? Oh, well, like a thylacine. What the.

[Ben Lam]

Yeah.

[Tom Bilyeu]

What? So it sounds like a period in time. It does not sound like an animal.

[Ben Lam]

Yeah, it's, It's. There's a Jurassic and you've seen a thylacine, right? I think.

[Tom Bilyeu]

I think so.

[Ben Lam]

Can we show you?

[Tom Bilyeu]

Yeah. Pull it up.

[Ben Lam]

Yeah.

[Tom Bilyeu]

Can you?

[Ben Lam]

It's amazing. It's like a zebra.

[Tom Bilyeu]

It looks fake.

[Ben Lam]

It's like a zebra wolf.

[Tom Bilyeu]

It's like a kid was drawing and had a seizure halfway through. That's what that looks like.

[Ben Lam]

It's awesome. And there's videos of them and everything.

[Tom Bilyeu]

Are they going extinct or are they.

[Ben Lam]

Yeah, they went extinct in 1936. Yo. So they're awesome. They're. They're okay.

[Tom Bilyeu]

But why. Why this one?

[Ben Lam]

Thylacine. Oh. So specifically, why the thylacine is. We hunted it to extinction. So the Australian government put a bounty on its head and actually paid farmers and hunters to kill the thylacine.

[Tom Bilyeu]

Doesn't that tell you this thing's a pain in the ass?

[Ben Lam]

No, they Got a bad rap. They the sheep farmers which were stealing each other's sheep, killing each other's sheep for competition. Blame the thylacine. There's no data like I've spent a ton of time in Tasmania. I spent a ton of time with all the thylacine experts and the researchers. There's no data that shows that they would ever attack a sheep or eat anything that size. They actually killed mostly kind of those mezzanine marsupials like Tasmanian devils and whatnot. So they were.

[Tom Bilyeu]

Now is this a marsupial?

[Ben Lam]

Yes. So.

[Tom Bilyeu]

Huh.

[Ben Lam]

Yeah. And like the. And like the wombat it's got a backwards pouch. So if you think of a lot of. Most marsupials have a pouch like you know up front and like the joey's in it. But it suggested this was a. And there's. There are thylacine dens that have been found. So it was a burrowing animal. So it actually burrowed and if the pouch was facing forward it would fill it full of dirt and kill it just like the wombat. That's so cool. Yeah, it's super cool. But so. So we picked that species because one, we as humanity made it go extinct. Two, there's great DNA. This is not an ancient. We had to go build the genomes. But this is a genetic engineering feat. Right. So there's 70 million years of genetic divergence between a fat tailed dunnart and which is like a marsupial mouse and we're turning into a marsupial wolf. Which is crazy.

[Tom Bilyeu]

That is crazy.

[Ben Lam]

But it's amazing. Yeah. So wow. But once again going back to.

[Tom Bilyeu]

So you pull just sort of from what's going to be the most fascinating what do we have connections to that

[Ben Lam]

we could rebuild what is possible. Right. Is there a reason to it in this case we removed it. There's not been another apex predator that has replace the thylacine in lower Australia or Tasmania. And we know.

[Tom Bilyeu]

Is that creating problems?

[Ben Lam]

Yeah. So there's a concept called tropic downgrading where you basically have a ripple. It's a ripple effect. Right. So you have this entire ripple effect on the ecosystem when you have a missing predator. We've seen this in Yellowstone, we've seen this all over the world. And so what's interesting for the thylacine is that have you seen this? We shouldn't look it up because it's. It's awful to look at. But have you seen the facial tumor disease?

[Tom Bilyeu]

No. I've heard you talk about it. I very aggressively resist.

[Ben Lam]

Don't look it up. It's rough. It's like I. It's bad, but don't you dare.

[Tom Bilyeu]

I could see him over there typing already.

[Ben Lam]

It's so bad. It's like out of a horror movie, right?

[Tom Bilyeu]

I'm gonna have my producer, Drew, arrested.

[Ben Lam]

Yeah, it's. It's bad.

[Tom Bilyeu]

But.

[Ben Lam]

But what's interesting is that if you look at predators, they're. They have some terminal internal calculus of energy expenditure, right? So not every pursuit of a kill results in a kill. And we've seen this in Africa with cheetahs and with big cats. If they go so long without making a kill, they're so unsuccessful for making a kill, eventually they're too tired to pursue it again and they die. Right. So there is some internal biology, you know, model that they use to decide whether they're going to go after a kill. But what's interesting is, so they typically pick the young, the old, and the sick and weak. And so this goes back to the survival of the fittest. This is great from a genes perspective. And so there. There's been people like Dr. Andrew Pask and others that have said that, you know, if we do. If. If the thylacines were here, the.

[Tom Bilyeu]

The.

[Ben Lam]

There would still be probably the facial tumor disease, but it'd be a lot more controlled because, like, if you see a devil, a Tasmanian devil with facial tumor disease, it can barely. It's like walking, it's stumbling, like it can't see well. So it kind of attacks everything. That's how it transmits its disease so much. Because when they're eating, they'll actually attack each other because they're pretty aggressive when they're in these, like, swarm eating.

[Tom Bilyeu]

Right. Woof. Have you read the book 1493?

[Ben Lam]

No.

[Tom Bilyeu]

Oh, man. Dude, you've got to read it. It is all about how humans have transformed the earth in ways that they were never even aware of.

[Ben Lam]

Yeah.

[Tom Bilyeu]

Like, I am almost certain the following is true. Earthworms are not indigenous to North America.

[Ben Lam]

That's amazing.

[Tom Bilyeu]

Oh. I was like, what?

[Ben Lam]

What?

[Tom Bilyeu]

And they were brought over here because they would use dirt as, like, a ballast in ships. And so then when they got here and they unloaded everything or when they loaded things up. Yeah. So they would bring the dirt over because they knew they were going to load a bunch of stuff up. So when they were about to load up, they would dump all the dirt, and in the dirt were a bunch of worms. And they have spread all across North America and just completely changed the soil and all of that same things with potatoes like potatoes are from.

[Ben Lam]

Yeah, we're. We're bad at this. We, like, you probably heard me talk about like the cane toads. Like we introduced the zoestra and they're killing all the marsupials.

[Tom Bilyeu]

Yeah.

[Ben Lam]

Because we. Because the marsupials didn't evolve next to them, so they're eating them and dying. Yeah.

[Tom Bilyeu]

Is that a big driver for you guys? Just like we think logical balance.

[Ben Lam]

Yeah. So we think it's interesting. Right. So like, you know, in the cane toad project, we have made a single edit. So one edit, and it confers 5,000 times resistance to cantotoxin, which is super cool. Right. Because then you can make like super. You can make you like one genetic. You can make a handful of these, of these super quals, which is what's eating them and dying. And then. And other animals are eating them too and dying, but not as much as the quals, because frogs and toads are primarily their diet. Well, then these super coals can get that population under check and then the coals can live. And then it can also have this halo effect to getting rid of the cane toad. You have that even a bigger halo effect of protecting other marsupials.

[Tom Bilyeu]

Have you come across any cool things like that in humans? Like you could have an increased tolerance for. Oh, plastic, which I know you have a great punchline for, or. Because we've got microplastic problems. We've got radiation.

[Ben Lam]

Yeah. I mean, I think radiation and cancer suppression are two really interesting areas that, you know, I think that data that we see from some of our work and that we see other people working on, I think that that could be minor changes. I think we'll have a. A cancer vaccine in the next. Not we as colossal, but I think humanity will have a cancer. No.

[Tom Bilyeu]

Why a vaccine?

[Ben Lam]

Because it's about 200 different types of diseases. Like cancer isn't one thing.

[Tom Bilyeu]

It's about what's making it a vaccine

[Ben Lam]

work because then it just trains your body to go attack it.

[Tom Bilyeu]

Interesting, huh?

[Ben Lam]

There's a lot of people obviously focusing on cancer, which is great. But you know, going back to like, like longevity escape velocity, you know that and you know, Alzheimer's. Unless we can see if Alzheimer's and dementia is directly connected to environmental accelerance inflammation.

[Tom Bilyeu]

So talk to me about this enzymatic breakdown process the company's called. Break or breaking.

[Ben Lam]

Breaking. Yeah, breaking.com. this is great. Yeah. So Sukanya and Vaskar and her incredible team at the Wyss Institute actually found this microbe that when put in with Only adding salt water.

[Tom Bilyeu]

Naturally occurring.

[Ben Lam]

Naturally occurring, Naturally occurring. It would break down and visibly degrade. At the time, we didn't know why any type of plastic that was in there, so if you had a vial of salt water and you put in, and you put the enzyme in or put the microbe in that creates this enzyme, and you put nylon, fishing nets, anything in there, right? I guess mostly fish nets. Any other types of industrial plastics at different rates. But it would take plastics that have never degraded or only degraded a little bit or would degrade over 800 years and in a couple years completely degrade them. And what it was doing was it's breaking the chemical bonds. Why I named it breaking. It actually breaks the chemical bonds in plastic.

[Tom Bilyeu]

So it turns plastic into just normal biomass.

[Ben Lam]

Into normal biomass. That is awesome. It's really, really cool. And so what we did is one of the things that's been this halo effect of colossal that's been pretty interesting is that because we have a computational biology core right in software and we know how to look at genomes in this type of data. And because we have genome engineering capabilities, a lot of researchers are bringing us really cool projects where they need AI computational analysis and genome engineering. And so they came to us and said, hey, we have this microbe. We think it does this. Can we do an analysis? So we did a lot of analysis work and we looked at it and we found, yeah, like it's creating this enzyme. It's actually a couple things working together to create this specific enzyme that breaks down. And everything we threw at it, it broke down. So then we're like, how do we make it hungrier? How do we make it where it exudes more of that enzyme? That's a genetic engineering challenge. That's not a, that's. That, that's not just a directed evolution challenge. Right. Like, we're not going to be like breeding this, right? We're going to, we're going to be accelerating it through synthetic biology and actually editing the genes that, that make some of those enzymes.

[Tom Bilyeu]

That sounds like a huge breakthrough. Is it, is it a big breakthrough?

[Ben Lam]

Yeah, it is. I mean, right now, you know, our goal is, you know, I mean, my goal is to get it to 24 hours that you can break down any plastic based on the amount of distributed surface area that you need. Which is really interesting because is a lot of the plastic degradation tools out there are just making smaller plastics. They're not actually disintegrating the plastics, number one. They're also not. A lot of them are having you they have to be heated or pre treated with the chemical. Some of those chemicals are worse than plastic. Great. Yeah, so it's not helpful. And so our thought process was. So we did this, we incubated it, we got it where we wanted it to be. Now it was 22 months, now it's about 18 months. But our goal is to get it to 24 hours. That's still, it's amazing.

[Tom Bilyeu]

Massive. It truly was. 800 years to two years is already huge.

[Ben Lam]

And we're, and it's, we currently have. It's either 14 or 16. I should know this because we just had a board meeting on it. But 14 or 16 pilots. So we're working with. I can't say the names of them. I mean I could, but I don't think I'm supposed to, but screening things that come through water and then, and then trading it, number one. Another area is textiles. Like a lot of the, a lot of the stuff that we make, especially like in fast fashion and others has, you know, huge has. There's a lot of plastics in our clothing that most people don't realize.

[Tom Bilyeu]

Yeah, that's really starting to make my radar now. Yeah, yeah, that one feels like it's massive.

[Ben Lam]

And we're gonna, we're gonna rate. Yeah, it's going well. So like the, so, so I, I think about these companies in kind of like, you know, three categories, right? Like, is there a general desire for them in the world, right? Is it, is it solving a use case and is there a general desire? Because those can be the same or those can be different. Right. I think everyone generally agrees that loss of biodiversity is bad. And everyone generally agrees that the accumulation of plastic, everything from the oceans to our bodies is bad. Right? And I think that everyone agrees that doing really cool things, inspiring kids for science, and in both those cases do it right, then those things are good. And so in both of these projects or companies, we see those all being all signs. Yes. Well then the science has got to work, right? So we have to be able to create a woolly mouse. We have to be able to create a direwolf. We have to be able to degrade plastic from 800 years to 2 years. And then it's really just the business modeling side. And so I've kind of fallen, coming from software and not being a biologist at all and kind of being good enough at learning it. I've just fallen in love with this idea that the combination of AI compute and synthetic biology, we can solve a lot of really cool challenges. And I Think we can do it in cool and interesting ways that gets people excited. Right? Like, if you have a plastic degradation company, that's awesome. If you then take the plastic degradation company, work in a bunch of textiles behind the scenes, that's awesome. But then if you do that and you bring in like, you know, people, you know, from like Noah or from like Jacques Cousteau's foundation or celebrities that care about the ocean, then you're going to bring awareness to science and these problems. And so, you know, one of the things that I think that, that we do with our companies, which is interesting, is like, we're solving really hard things, but we also try to do it in a fun, flashy way that gets people excited.

[Tom Bilyeu]

What's the coolest challenge you want to

[Ben Lam]

solve with these companies or ever?

[Tom Bilyeu]

Let's go with ever.

[Ben Lam]

I think it'd be really interesting. So I don't want to be in the therapeutic space. I think there's enough people in the therapeutic space. But I would like to, if I could have two solutions, is I would like to be able to engineer plants into doing whatever we want. George and I joke about this treehouse concept of like, you know, not to get too weird and hippie ish, but it's like, why can't a tree grow in the form of a dwelling? And why can't it. Like, we weren't on mushrooms when we did this, but it's like. But then why can't it have bioluminescent fungi and it, like, it light everything and like, you know, it would be like the ultimate kind of like cleansing for the environment, right? Because you see redwoods that live in all kinds of environments. So. So I love to be able to engineer plants in a way that like, we're not just like chopping down forests, but that like, the plants could build our cities. That's like the weirdest most. I'm not working on that. But it's a really weird thing. That's one, two is I'm very interested in the oceans. We're not working on this either right now, but I think that there is a huge opportunity if we look at, you know, the most stable patterns of, of weather globally and where life persists consistently. It's somewhere between 30 and 70ft under the water and it's pretty stable there regardless of like, the ocean churn above it. So if you could build tools and technologies to make coral more resilient and through synthetic biology, not by just macro, by micro fragmentation, then all of it grow faster, but it's still going to die. So you have to do genetically modified corals. If you do that, and you build closed systems for underwater living. I think that's really interesting. That's very interesting because, I mean, if you look at the ocean and you look at the surface of the Earth, you could build. I mean, what is the economic value of the California coast? A trillion dollars? I don't know. It's a lot, right? If you owned all of it? Well, there's no wildfires 30ft under. You have to build closed systems. So the same technologies that you're developing without needing major heat and cooling inversions and radiation tolerance that you're spending a fortune on cost a kilogram to put to space, you could apply those same technologies to Earth and, you know, work on underwater cities.

[Tom Bilyeu]

Do you think that's going to be something that happens in our lifetime?

[Ben Lam]

I mean, I think that we're going to achieve longevity, escape velocity. So the answer to any of those questions is yes, because there are a lot of times indefinite yes.

[Tom Bilyeu]

Oh, God, I hope that that really comes to pass. My man, I cannot thank you enough. Where can people follow you?

[Ben Lam]

I'm just on Twitter or X. Justin Lamp.

[Tom Bilyeu]

There it is. Two M's. All right, everybody, if you haven't already, be sure to subscribe. And until next time, my friends, be legendary. Take care. Peace.