Playing God or Saving Nature? Gene Editing, Artificial Wombs & the Return of Extinct Species | Ben Lamm PT 1

Summary

Podcast Summary: Impact Theory with Tom Bilyeu

Episode Title: Playing God or Saving Nature? Gene Editing, Artificial Wombs & the Return of Extinct Species | Ben Lamm PT 1
Guest: Ben Lamm, CEO of Colossal Biosciences
Release Date: May 13, 2025

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Episode Overview

This sci-fi-meets-science episode dives deep into the advances and ethical dilemmas of gene editing and de-extinction. Tom Bilyeu welcomes Ben Lamm, founder of Colossal Biosciences, whose team is pioneering technologies to resurrect extinct species—including the legendary dire wolf—and pushing boundaries with artificial wombs, universal eggs, and multiplex genome editing. Beyond the headline-making animal projects, the conversation explores the coming revolution in human genomics, selection and gene editing, and the complex role of ethics in biotechnology.

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Key Discussion Points and Insights

1. Making Life Manually Editable: The Breakthroughs and Technology Stack

• Rise of Gene Editing Tools:

  • The discovery and refinement of CRISPR allowed not just single-nucleotide (letter) edits but also the synthesis and swapping in of large DNA blocks. These tools are combined in "multiplex editing" to make dozens of changes simultaneously.
    • "We're running victory laps on the fact that we made 20 edits with one multiplex array. Right. Which is unheard of." — Ben Lamm [04:16]
  • DNA blocks that contain a designed sequence of genetic letters can now be synthesized and swapped directly into an organism’s genome, making not only changes but entire design strategies possible.
    • "We can literally just insert, knock out that same little block and insert a block with the letters we want in the right order." — Ben Lamm [03:01]

• Multiplex Editing & Screening:

  • Combining various editing tools has enabled the creation of novel organisms, like the “woolly mouse,” and allowed scientists to confer complex traits efficiently.
  • Stringent screening for off-target effects remains crucial, as editing tools can sometimes cut or morph DNA in the wrong location.
    • "There's these things called off target effects where you get these unintended consequences." — Ben Lamm [07:19]

Memorable Quote:
"I don't even think that we're at the doorstep... I think we're just barely opening the door." — Ben Lamm [03:33]

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2. De-Extinction in Action: From Mammoths to Dire Wolves

• Real-life Jurassic Park:

  • Colossal Biosciences has engineered and brought to life dire wolves, using DNA recovered from paleontological remains.
    • "When you say worked on dire wolves... you mean they exist?" — Tom Bilyeu [15:48]
      "Exist, yeah, they exist. We have three dire wolves right now." — Ben Lamm [15:51]
  • Creation of the “woolly mouse” required eight specific edits that changed its hair and fat metabolism—mirroring findings from research into mammoth genetics.

• Techniques and Challenges:

  • Synthesis of large DNA blocks, somatic cell nuclear transfer, and reprogramming of cells are some of the complex processes used.
  • Creating patterns (like stripes on the thylacine) and developing hair organoids (test-tube-grown follicles) are among the latest frontiers.
    • "In addition to the woolly mouse, we actually built hair organoids for mammoths." — Ben Lamm [18:33]

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3. Next-Gen Biotechnology: Universal Eggs and Artificial Wombs

• Universal Egg Project:

  • The quest to generate a standardized mammalian egg removes barriers for conservation and biobanking of endangered species.
    • "If you could make a universal egg, that would be incredible for like all of conservation." — Ben Lamm [25:54]
  • Technical hurdles include differences in mitochondria between species, requiring advanced manipulation or swapping.

• Artificial Wombs:

  • Ben anticipates the first mammal will be born entirely ex utero (outside a living womb) using an artificial environment by late 2026, starting with small mammals and marsupials.
    • "By the end of 2026, I predict we will have the first mammal born fully ex utero." — Ben Lamm [31:22]
  • The technology relies on a mix of hydrogels, bioprinting, and close mimicry of natural placental and uterine environments, aiming for scalable impact in conservation and potentially healthcare.

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4. The Data Revolution: Embryo Screening, Sequencing, and AI

• Genotype-to-Phenotype Mapping:

  • A central challenge is predicting which genetic edits cause which physical traits—an area rapidly advancing with AI and massive sequencing projects.

• From Research to Engineering:

  • Ben forecasts a tipping point where data and computation shift genomics from slow, manual science to reproducible, engineering-driven discipline.
    • "In the next five years we will move from scientific research and scientific discovery to engineering." — Ben Lamm [09:41]

• Human Embryo Selection:

  • Both Tom and Ben discuss their experience and philosophical approach to embryo screening for health and trait selection, noting new companies like Orchid Health performing full genome sequencing on embryos.
    • "So they can do full genome sequencing... and so they can look for specific markers." — Ben Lamm [40:31]

Memorable Moment:
Tom’s surprise at the amount of technical knowledge needed for “simple” embryo selection and how traditional morphological grading can be misleading without genetic data.
"The morphological embryo that looked the best...had a genetic defect and was not compatible with life." — Ben Lamm [48:20]

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5. The Ethics of “Playing God” and the Coming Policy Dilemmas

• Do We Have a Duty to Intervene?

  • Ben frames gene editing, conservation efforts, and even medicine as different forms of “playing God,” arguing for a moral obligation to act if we can prevent extinction and disease.
    • "All of these choices are a form of playing God... I think we have a moral obligation to do something." — Ben Lamm [36:01]

• Personal vs. Societal Ethics:

  • Colossal Biosciences draws strict lines: no work on non-human primates or human embryos, mindful of the ethical and social consequences.
    • "We've made the decision that we're not going to work on anything because people get asked us about Neanderthal, right?... It's just too, too human." — Ben Lamm [38:04]

• Slippery Slopes and Moratoria:

  • International contrast is made clear: while the US has a moratorium on editing the human germline, China aggressively pursues genomics, with BGI openly mapping for intelligence markers.

• Consumer Choice, Data, and Eugenics Concerns:

  • Screening embryos for disease mutations is viewed as responsible; selecting for non-disease traits approaches eugenics.
    • "Selecting for a certain... skin color or hair or eye color, that's eugenics. Right. Seeing if your kid has...my truncation on my Titan gene... that's not eugenics." — Ben Lamm [51:09]

Memorable Quotable Ethics:
"It should be your choice... I'm a big believer in personal choice and freedom as long as you're not hurting anyone." — Ben Lamm [44:17]
"Data can help us be informed to make...more informed decisions...but not everyone does." — Ben Lamm [49:00]

• Social and Generational Perspective on Biotech:
  • Different cultures view long-term consequences and bioethics in very distinct ways, with the US being present-focused and some Asian countries taking a more generational approach.
    • "One of the things that makes America different than China is our ethics, is what we'll choose to do." — Ben Lamm [54:38]

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Notable Quotes & Memorable Moments

• On the pace of gene editing advances:
  "I don't even think that we're at the doorstep... I think we're just barely opening the door." — Ben Lamm [03:33]

• On resurrecting dire wolves:
  "We have three dire wolves right now." — Ben Lamm [15:51]
  "They've been extinct for 10,000 years." — Tom Bilyeu [15:59]

• On universal eggs and artificial wombs:
  "If you could make a universal egg, that would be incredible for all of conservation." — Ben Lamm [25:54]
  "By the end of 2026, I predict we will have the first mammal born fully ex utero." — Ben Lamm [31:22]

• On the inevitability and global competition:
  "Dude, this is inevitable." — Tom Bilyeu [46:37]
  "We are in a cold war with China. China is going to do everything that they can to beat us in AI." — Tom Bilyeu [46:37]

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Important Timestamps

• [01:00] — Introduction: Life as an editable system, de-extinction, and technology overview
• [02:08–04:16] — Evolution of DNA editing and synthetic biology
• [06:36] — Creation of the “woolly mouse” and multiplex gene editing
• [15:21] — Craziest Colossal projects & bringing back dire wolves
• [18:33] — Building hair organoids for mammoths
• [23:08–27:45] — Universal egg project and challenges in reprogramming cells
• [28:22–32:55] — Artificial womb technology and vision for ex utero mammal births
• [34:48] — Conservation applications: scaling up with artificial wombs and embryo editing
• [35:17] — The ethics of playing God in biotech
• [40:31–44:17] — IVF, embryo selection, and genome sequencing in practice
• [46:37–48:45] — US-China genomics arms race and societal implications
• [51:09–54:38] — Eugenics debates, embryo selection, ethics, and international differences

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Final Thoughts

This episode is a thought-provoking tour of biotechnology’s cutting edge—moving from fantastical creatures to headline-grabbing “playing God” debates, and the very real prospect of engineering life itself for conservation, medicine, and more. Ben Lamm’s enthusiasm for the science, balanced with a sober assessment of the ethical and social implications, sets the stage for the next wave of debates about who gets to wield this new power, and how.

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To be continued in Part 2!

Transcript

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[Tom Bilyeu]

We're entering into an era where life itself is editable. One company has already brought back the genetic code of extinct animals. They've resurrected DNA that hasn't walked the earth in over 10,000 years. Not as science fiction, not as metaphor, as living organisms from engineered, grown and born. Their founder isn't a biologist. He's a tech entrepreneur. And his team is using the same tools. Machine learning, crispr, synthetic biology. To build something we've never had before. The power to rewrite evolution. Today's guest is Ben Lamb, the CEO of Colossal Biosciences. His company just unveiled the world's first genetically engineered dire wolves. But this conversation isn't really about animals. It's about what happens when the interface to biology becomes a computer. It's about what we design next. I bring you Ben Lamb. Life seems so complex, so mysterious. How is it possible that we can manually edit it? Is there a specific breakthrough that's made it possible for you guys to de extinct animals?

[Ben Lamb]

If you look at the DNA twisted ladder that everyone thinks of when they think of DNA, to be able to edit one individual rung and either knock something out or knock know eventually even to change those into a different letter.

[Tom Bilyeu]

So eventually. We can't do that now.

[Ben Lamb]

Sorry, we can do that now, but. But when CRISPR first was discovered, it then moved into single nucleotide editing, editing, where you could edit certain individual letters. Right. And then it came into the DNA synthesis where we can actually synthesize big blocks and swap them in.

[Tom Bilyeu]

What do you mean synthesize?

[Ben Lamb]

So we can actually like with, you know, we do it internally at Colossal. But we also have third party partners that we work with some where we can actually string a bunch of those letters together. So instead of us wanting to go in, make like 20 edits or 100 edits or even a thousand edits in a particular order, we could, it may be easier just to sometimes synthesize that block.

[Tom Bilyeu]

So this block does this.

[Ben Lamb]

This block is this letters in this order. And so instead of us changing each one of those letters on that kind of twisted ladder, we can actually just design and build those letters in the right order so we don't have to change them or swap them. We can literally just insert, knock out that same little block and insert a block with the letters we want in the right order.

[Tom Bilyeu]

So this is so crazy.

[Ben Lamb]

So I love, I love. This is where we jumped in. Right? So this is great when I say

[Tom Bilyeu]

that I am literally obsessed with how far this can take us. Yeah, I'm obsessed. But I like to understand.

[Ben Lamb]

I don't even think that we're at the doorstep like where we are. Right. Because like, if you look at even what we're doing at Colossal right now, we use a combination of tools, right? So we're not using just one tool. It's not just like a knockout, meaning we're knocking out pieces of the genome. We're not knocking pieces of the genome where we're actually. Where we have something, we're trying to swap it out. We're not editing just individual nucleotides, like making individual letter changes. And we're not just doing DNA synthesis. We're doing all of it. So we're combining all of it. And that's what's called multiplex editing. And so one of the things that Colossal is trying to pioneer and push forward is this ability to take these tools that individually work, okay, in some cases, great. But in some, a lot of times. Okay. And deliver it in a mechanism where we can make a lot of edits that the genome at the exact same time. And we're still like, we're running victory laps on the fact that we made 20 edits with one multiplex array. Right. Which is unheard of.

[Tom Bilyeu]

Do you have to do that in one block? Or you can literally do 20 separate randomly placed all over the genome.

[Ben Lamb]

Yeah. Yo. Which is amazing. So we announced this woolly mouse. So to give you context, we announced this woolly mouse, which is objectively cute. Regardless of what you think about de extinction. We made this woolly mouse. It's amazing. It had eight edits to seven genes. So it just had eight Single nucleotide edits. Right. So it wasn't like we weren't synthesizing a big block. We were literally making eight specific edits in these seven genes. But what was interesting is they were the same mouse equivalents of what we saw in our mammoth to Asian elephant research. So we do a lot of computational analysis. We spend a lot of time looking at ancient genomes, comparing them to their closest living relatives, understanding the difference. And based on the region it's in, it kind of gives us a clue of whether it'll, you know, make a change to the hair phenotype, fat metabolism, or whatnot. But these eight edits, just these eight edits, conferred all of the hair type, hair length, coat color, hair density. Our chief science officer calls it floofiness. But basically, how are. How the hairs grow in slightly different ways. So it kind of gives it that. That kind of woolly texture. And then one was around fat metabolism. And if you look at, like, the control mouse, which just looks like your average smooth, like, gray mouse compared to this, you know, this. Our. Our woolly mice look like, you know, that they have a really cool fur coat on. Right. And we're still testing whether the fat metabolism works. We don't know if that one, you know, confers cold tolerance in the mice. What's interesting about that is a lot of people were like, whoa, that's absolutely amazing. But it's only eight edits. It's literally only eight edits. And people had made eight edits, but they had done them sequentially. Right. So they, like, made an edit in this line of mouse. That mouse, you know, had offspring. Then they made an edit in the next line, in the next line, and the next line, and they stacked them

[Tom Bilyeu]

over time eight kids deep. You finally have the. Yeah, very different.

[Ben Lamb]

Yes.

[Tom Bilyeu]

How are you doing that? Is this writing on the back of a virus that knows that it needs to go in and clip? Like, I have a vague understanding.

[Ben Lamb]

You've got it. You've got it. Right, Right. So we. So we design these crispr guides.

[Tom Bilyeu]

And a crispr guide is a virus.

[Ben Lamb]

Is a virus. So we go in, actually delivers it, knows exactly where to cut it, but it's not 100% right. So that's part of the problem.

[Tom Bilyeu]

What? It sometimes cuts in the wrong places.

[Ben Lamb]

It cuts in the wrong places sometimes. There's a lot of what's called linear repeats in the genomes, meaning that there's places where there's the same letters and some of these tools aren't quite there yet. I mean, we're still in the early stages. Like I said, I think we're just barely opening the door.

[Tom Bilyeu]

So it's like opening a book. And there's a few times where it says, and the people went, yeah, so if you tell it to look for. And the people went, you might be in the wrong chapter.

[Ben Lamb]

You might be in the wrong chapter or whatnot. Right. And so. Or if you change it, it may forget people. Right. Or may have knocked out people, too. So there's these things called off target effects where you get these unintended consequences. Right. And so the way that we fix it and the way that, you know, this isn't where I think the technology will exist long term, but where it exists today is we do an intense amount of, like, screening. So we screen all of the cells before we edit them, right. So we do sequencing on all of. So we're very heavy on compute. That may not be a surprise to you, given my background in software, but. So we spent a lot of time on understanding the existing genomes. Then after we make edits, after we let those cells kind of go through a couple passages, meaning they divide and we then sequence the cells that. That fully divide before we even go into things like the woolly mice, you know, people are like, well, how did you get, you know, all 36 of your mice that were born were healthy? It's like, well, because we screened all those embryos. We didn't take any embryos to term.

[Tom Bilyeu]

What are you looking for about human embryos and screening like that?

[Ben Lamb]

When people are doing ivf, they're looking at, like, morphological. For a lot of times, they're just

[Tom Bilyeu]

reading the code in the DNA and going, we know what this means. Ooh, this means something bad. And so we're going to.

[Ben Lamb]

I just went through ivf, so. And, yeah, and so we actually went through it, and I actually have a gene mutation that causes a truncated protein on the Titan gene. And so we didn't want to pass

[Tom Bilyeu]

that on, which has already been mapped. People already know about this, which is crazy. How much do we already know about this stuff?

[Ben Lamb]

I'll get pushback on this, but I think that we don't know very much. I think we are learning at an incredible rate. There's a ton of literature out there, but things like large language models and being able to ingest a lot of research. A lot of times people will call things different things in research. So if they're looking at a mouse model, they'll say, oh, this gene could have this effect. But that effect may be described differently in this paper than in this paper. So I think though there's been a lot of raw data created. I think that the kind of access to compute, AI and eventually quantum, which I hear is only two years away every two years, I think that those things coming together, we'll be able to ingest a lot of this historical data and existing data. I think that we are at this moment where, you know, in the next five years we will move from scientific research and scientific discovery to engineering. And I think that that is in another way.

[Tom Bilyeu]

Do you mean that instead of a bunch of people writing papers about this, we're going to know, okay, we've scanned 46 million people. This guy is six to this guy's five, four. Here's what it looks like. This guy has thick, luscious hair. This guy has like really cheesy thin hair. And we just start mapping all that stuff out and we go, oh, okay, cool. I know these letters in this place are going to result in this characteristic.

[Ben Lamb]

Yeah, and I think, I think we will. But that's, that's what's called genotype to phenotype. Like that translation layer is pretty hard.

[Tom Bilyeu]

What you mean?

[Ben Lamb]

No, it is, it is. So, but I think that's. I think that's very hard. There are certain things like. So one of the biggest challenges that Colossal is working on is size. So there's not like a single gene that you make like a single edit in and it makes like. And it's like, oh, well, we can now 3x something. We can now make a chicken that's 20 times larger. Right. And that's great for farming. We're not there yet. Right? We as humanity literally going to have

[Tom Bilyeu]

dinosaur chickens running around here.

[Ben Lamb]

I'm not, I'm not saying that, but

[Tom Bilyeu]

that, that was me.

[Ben Lamb]

We do get a lot of dinosaur. That's our number. The number one requested thing is God bless Jurassic Park. We get a lot. We've also heard that before too. Surprisingly shocking. But. But I do think that we're at this point where we're going to start to understand two major categories. One is expression of genes into physical traits or phenotypes. Right. So that we know that this gene or this combination of genes actually will have this effect and it's highly predictable. Right. So I think that that is the world. So Colossal spends a lot of time in that genotype to phenotype mapping. That's like a large portion of our time. Secondly though, I think that we're going to understand how. And there's been Previous research to do this. But the application of these technologies to human health care I think are going to be even more interesting than just like making woolly mammoths and whatnot. So the ability to understand that you have a predisposition to this type of cancer or this type of lung of Alzheimer's or diabetes, unlike a single gene mutation that only requires a single edit. You have to be able to edit all of those genomes at the same time with all those genes at the exact same time with a high degree of efficiency.

[Tom Bilyeu]

Right.

[Ben Lamb]

Because you don't want off target effects, especially if you're dealing with humans.

[Tom Bilyeu]

Can you do this to somebody that's already alive?

[Ben Lamb]

You will be able to. Right. And so what's, what's great about Colossal is that we work in, we do a combination of editing in micro injection into embryos, but also in editing cells that then we, we use a process called somatic cell nuclear transfer, where we're taking the nucleus of an egg or of a somatic cell and putting it into that of a germ cell or an egg cell, also known as an egg cell. And so we aren't doing that, but a lot of the gene therapy work and a lot of these other works are looking at how we target different tissue types for delivery. So you've got the gene editing requirements, you've got the computational requirements, then you have the delivery requirements. I mean, for us it's not, not, it's not as a high, as a high priority, but there's entire teams. I sat through a presentation at the Wyss Institute last year where there was like three teams that are just looking at kind of like air traffic control of how you push different targeted therapies to different tissue types in the body. So there are people working on it,

[Tom Bilyeu]

just meaning we put it into the body, but we need to tell it exactly where to go and what to

[Ben Lamb]

do and what to do. Yeah. So it targets your own cells. Yeah.

[Tom Bilyeu]

Okay.

[Ben Lamb]

And people are, people are looking at how that could be a form of treatment even for cancer. Right. Like how do we, how do we target things better? So targeting is a huge thing in, in this field.

[Tom Bilyeu]

Targeting is a huge thing that makes a lot of sense.

[Ben Lamb]

It affects Colossal less. Right. So we aren't focusing on much of it because like we're not trying to take a, you know, wolf and engineering traits to it in a, in a, you know, three year old wolf. We're starting at the cellular stage and the embryo stage.

[Tom Bilyeu]

Okay. So you're taking advantage of the fact that viruses already do this. They go in and they snip.

[Ben Lamb]

Yep.

[Tom Bilyeu]

When you say that you're training a virus, how do you give it the sequence of letters or whatever to look for?

[Ben Lamb]

I think I told you this before is like, I'm not a scientist, but I just get, like, nerd out on it. I come from a software perspective, so we actually have teams that just do all of the different guide design. So they actually design it. They actually put the letters in. They'll actually, in some cases, synthesize little pieces of the code that we want in the right order and then. And deliver that in the entire pack. Give that to the entire package that then goes into the cell to deliver it.

[Tom Bilyeu]

More with Ben Lam after this short

[Ben Lamb]

break,

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[Tom Bilyeu]

All right, we're back. Let's get into it. Yo. Okay, what's the craziest thing that you guys are doing right now with that technology?

[Ben Lamb]

The craziest. I'll give you. I'll give you three things that are just super weird. And I don't know if we'll get there, but we are trying to synthesize a massive block of DNA. There's a project that we're working on without going into it has.

[Tom Bilyeu]

Because you can't. Because Lord knows, with that smile, I want you to.

[Ben Lamb]

Yeah, yeah. So most people know we were working on the mammoth thylacine in dodo. People now know that we're working on. Or we have worked on dire wolves, but there's other projects. But like, for example, with the.

[Tom Bilyeu]

When you say just for anybody that doesn't know you, when you say worked on dire wolves. You mean they exist?

[Ben Lamb]

Exist, yeah, they exist. We have three direwolves right now.

[Tom Bilyeu]

Yo.

[Ben Lamb]

Yeah. Which I'm sure we'll talk about, which are amazing. So Romulus, Remus, and then Khaleesi.

[Tom Bilyeu]

So crazy. They've been extinct for 10,000 years.

[Ben Lamb]

10,000 years. A little over 10,000 years. We used a 73,000-year-old skull in a 12,000-year-old tooth to do all the computational analysis to kind of build to get the genome.

[Tom Bilyeu]

Yeah, right. Okay. So craziest thing.

[Ben Lamb]

So the craziest. So two crazy or three crazy things that we're doing right now. Number one is patterning both in the thylacine and other species is really important. Right? So like getting how the stripes, for example, you know, we can't just like, make up, like if direwolf. If we did the DNA analysis and saw that direwolves were striped, there's no preserved direwolves. So it's like. Okay, well, the stripes don't have to be 100% from a fidelity perspective, but we know exactly what the thylacine looked like. There's pictures, there's color corrected videos, there's hides. So to get that right, we're actually synthesizing large blocks of DNA, larger than anyone's ever synthesize, and we're working to safely deliver that in the cell. And one of the technologies that we've developed is we. We built it really large and assembled it. We're then cutting it at specific points, putting it in, and then trying to stitch it together all at the same time. So that's one really insane, hard thing that we're doing.

[Tom Bilyeu]

That's really hard because of the size of the block.

[Ben Lamb]

You're trying to side of the block because it's pretty fragile, right? It's going into the cell. There's only so much.

[Tom Bilyeu]

There' physical manipulation problem.

[Ben Lamb]

There's a. There's a. Yes, but it's all done with, like, chemicals. So we're not. We're not doing it with like, tiny robots that the virus isn't.

[Tom Bilyeu]

That's what I had in my head.

[Ben Lamb]

Yeah, yeah, but we aren't doing it right.

[Tom Bilyeu]

The.

[Ben Lamb]

The system. The virus is doing this.

[Tom Bilyeu]

But does the virus literally carry it like a tugboat?

[Ben Lamb]

It carries it like a tugboat, yeah.

[Tom Bilyeu]

It's insane.

[Ben Lamb]

So that's one. A separate thing that we. That I think's pretty interesting is we want to create a universal egg, which I know sounds a little weird, but. Because when. When you look at doing somatic cell nuclear transfer in this one.

[Tom Bilyeu]

I do tell. What's a somatic cell?

[Ben Lamb]

Okay, so somatic cell is basically any cell in your body that's not a egg or sperm cell. So whether that's a tissue, we actually have started using what's called EPCs. We did this on, on the direwolves, which is pretty cool. Endothelial progenitor cells. And we love them because they're only partially differentiated. So if you think about, like pluripotent stem cells, they're in the most naive state. So that you can use a bunch of different chemical factors to convince them to turn into different tissue types. Right. And so you can use these transcription factors to convince them to turn into different tissue types.

[Tom Bilyeu]

Right?

[Ben Lamb]

Which is pretty interesting. So we're using that with like, hair. It's kind of creepy, but interesting. So in addition to the woolly mouse, we actually built hair organoids for mammoths. So we are growing hair follicles just

[Tom Bilyeu]

to make sure it works.

[Ben Lamb]

Oh, yeah. To make sure it works. Right. So making sure that the edits that we are making in our elephant cells will actually deliver the phenotypes that we're looking for.

[Vrbo Commercial Voice]

Right?

[Tom Bilyeu]

Hold on, hold on, hold on. So we know enough about the soup it would need to be in to grow, that we can grow the hair by itself.

[Ben Lamb]

So that's a whole nother thing. So if you look at Colosseum. So this is what's interesting about, like, why I'm super fascinated with what we're working on is we don't just have to get multiplex editing, right? We don't just have to get computational analysis, right. We don't just have to have the screening for off targets. Right. Or the embryology. Right. Or the somatic. So nuclear transfer, which we'll talk about the cloning, right. We actually have to do things like media conditions, like the soup, right? Like, we have to get that right. And then we have to also create different soups or medias in order to make them change. And certain tissues do certain things.

[Tom Bilyeu]

Damn.

[Ben Lamb]

So it's not just adding. So you have to build a whole system. And so, and so it's funny, like, when we launched the woolly mouse, people were like, you know, there we have a lot of people that love us. We have some people that question us, which is great. You know, I think it increases the likelihood of us having great conversations about science, which is awesome. But some of the people that have questioned us and they push back on us. One of the things is they're like, well, it's only eight edits. And I was like, yeah, but it's eight edits in this system. Like we're focusing on this right. Where when in reality we need to look at the whole system.

[Tom Bilyeu]

Yeah. I find anybody that says this isn't interesting, completely uninteresting. Like, I don't even get that line of question. I hear you talk about it a lot like that one to me is just like, what? I don't have time for that.

[Ben Lamb]

But I think, look, I think that I believe in personal choice and freedom and as long as you're not hurting anyone. And you know, I think that what's interesting about this is that people sometimes don't respect like. Like the woolly mouse is like a technological triumph. I know it sounds insane because it's just, it's like, why would that sound. But it is, it's amazing. We literally, Matt, we took, we took 60 genomes in varying links from a 1.2 million year old step mammoth all the way down to a 3,500-year-old woolly mammoth, built a kind of this pan genome model, compared it to Asian elephants, African elephants, by the way, which genomes didn't exist. We had to go create those genomes. Like coming from software, I just assumed

[Tom Bilyeu]

it just hadn't been mapped.

[Ben Lamb]

Yeah, no one had mapped. So no one had one made the genomes and then no one had annotated the genome. So no one had gone out and said, this is this region of the genome. This is this region of the genome. No one had done that. Coming from software, I just, you know, I knew that like 23andMe existed. Right. The baby somewhere. Yeah. I just thought like, oh, we'll just log on to the GCP of species and be done with this thing. Right. Like, we'll just write, you know, comparison algorithms and call this a day. Yeah. But none of that, none of the data on either side had existed, which was crazy. So we had no data sets to start from a comparative side. So once we did all that and we identified all of these core regions, we started growing things like hair organoids. But before we grow hair organoids, we had to actually figure out how to turn elephant cells back into pluripotent stem cells so that we can then turn them from pluripotent stem cells, reprogramming them and turning them into organoids.

[Tom Bilyeu]

Jesus, man.

[Ben Lamb]

So there's a lot that goes into this and you know, we've only been around for three and a half years

[Tom Bilyeu]

going to say there's not only a lot that goes into It. But there's a lot you've already solved.

[Ben Lamb]

Yeah. And I mean, we're a long ways away from everything we want to do. But like that, that just little model right there, I think is like borderline magic. And so if you take all of that and then you map all of those edits that drive the hair phenotype, which is what we're looking for in our woolly mouse, to a mouse equivalent model. Right. Of that specific gene edit. Because we didn't want to just put mammoth genes in a mouse. We thought that was unethical. And we thought that there's 200 million years of genetic divergence between the two, so it probably wouldn't have been compatible with life. We actually had to engineer it. So we want to do this safely and responsibly. Then you sequence it. And all of that had to work to produce Amal. So we produced 36. And they're all healthy.

[Tom Bilyeu]

Jesus.

[Ben Lamb]

And objectively cute.

[Tom Bilyeu]

They definitely are cute. There's no doubt about that. But the, like you said, the. I don't know that it's borderline magic. Sounds like it spills over into proper magic.

[Ben Lamb]

Yeah.

[Tom Bilyeu]

This is by far the most sci fi episode I've ever done. This is bananas. Okay, so we know the soup, we know the areas of the gene that we can edit. We were going through the three craziest things.

[Ben Lamb]

That's one, these gigantic blocks. Yeah. The second one was going back to that somatic cell nuclear transfer, where we actually take the nucleus of a cell of a somatic cell and put it into an egg cell. Well, you have to have egg cells. So you kind of have like three choices for egg cells. Choice A or four choices. One, you can harvest egg cells from animals. Right. You know, and do it in a humane way where you actually have to, in some cases, develop devices to like, we do this on the Northern White Rhino project, where we actually have to go extract eggs so that we can bio bank them and fertilize them so that we have them in case that species goes extinct. Because it's functionally extinct. There's only two left.

[Tom Bilyeu]

And you'd rather start with a full blown egg than like a skin cell.

[Ben Lamb]

You need a germ cell, so you need a germ cell. Secondly, you can make germ cells through a process called gametogenesis because they're. They're gametes. And how you do that is you have to figure out, you have to take a cell like skin cell, turn it back into its most naive state, pluripotent stem cell and then from there you actually have to reprogram it and get it to turn into an egg cell that you can then edit. Right.

[Tom Bilyeu]

And get me reprogram it. What are you doing?

[Ben Lamb]

Doing? You're adding a combination of these chemical factors. Your.

[Tom Bilyeu]

Your

[Ben Lamb]

factors?

[Tom Bilyeu]

Yeah, that. Okay, so it's basically a chemical sequence.

[Ben Lamb]

Yes.

[Tom Bilyeu]

That does this.

[Ben Lamb]

Yes.

[Tom Bilyeu]

I can't believe somebody figured this out.

[Ben Lamb]

Okay, yeah, it's crazy, but they're all. But they're all different for different species, right. And so colossal works in non model species. Right? So like most people study mice, pigs, non human primates. Right. And so we're working in wolf cells, we're working in fat tailed Dunnart cells, we're working in pigeon cells, like we're working in elephant cells. We're working in these cells that just don't get a lot of attention. And so. And they just don't have a research. So we have to figure out those soups, we have to figure out the chemical transcription factors, the right combinations, and they all have uniquenesses, which is crazy. Like, so wait, so closing out the three crazy things. We can go on tangents for this forever because. Because it's fun and interesting, but one of the things that we're trying to do is to make a universal egg. But the egg donor will have a mitochondria, right? So we all have these like little powerhouses of our cell, these mitochondria. And there is a, is an ability, the further you go genetically in time, that you could have mitochondrial rejection, meaning that, that the mitochondria in the egg may not be compatible with what's in the nucleus. Right. And so I'm not, I'm not a. I don't get that deep in the epigenetic side of it or in the mitochondrial rejections out of it. But one of the things that we're trying to do is if we could make a universal egg, that would be incredible for like all of conservation and obviously all of our projects. Right. Because then you would never have to harvest oocytes or egg cells from a species, especially an endangered species.

[Tom Bilyeu]

When you say universal, do you mean any species?

[Ben Lamb]

Well, we're starting in mammals, right? So it'd be mammalian work to begin. Is that all that's what we're working on right now?

[Tom Bilyeu]

Jesus.

[Ben Lamb]

It's hard.

[Tom Bilyeu]

Okay, so failure of imagination on my part. I never would have thought that that's even possible.

[Ben Lamb]

And we don't know if it is yet.

[Tom Bilyeu]

But the theory is that there is a point at which we all share a set of things.

[Ben Lamb]

The, the egg cells for these different species are, are so different, right? But if you could get the right housing structure, the right ways to either change or manipulate the mitochondria or do mitochondrial swap in the egg cells, then you'd have kind of the building blocks like the Legos for building a universal leg. So then because there are species, so gametogenesis taking, taking cells back to their pluripotent stem state, their most naive state to then program from and sorry, reprogram from is hard. Hard. It's very, very hard. Hasn't been done. It's not like once again, there's not the GCP of that. There's not a book that just tells us how to do all this, right. Secondly then going through the gametogenesis process of making eggs and sperm, that's insanely hard. That's harder than making like a skin tissue. So if you could not have to do that for every single species and maybe AI and quantum just magically figures out, who knows? But I highly doubt it. If you could make a universal egg or at least have the building blocks for universal egg when you're working a non, like the northern white rhinos or elephants, you could just use that. So that's the second thing that, that we're working on that's, that's super weird. And then the third thing is the artificial womb. So we are working on a full end to end system to grow everything ex utero. Yo.

[Tom Bilyeu]

Yeah, stay tuned. We'll be right back with more from Ben Lamb after this.

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[Tom Bilyeu]

All right, we're back. Let's get into it. Tell me more about the artificial womb. That's like one of the. In my prep, I was like, okay, I've gotta know how far along we are with that.

[Ben Lamb]

If we are successful by the end of 2025 or probably into 2025, we'll show some implantation in a model species, like a mouse by the end of 2026, you know, say implantation.

[Tom Bilyeu]

What do you mean?

[Ben Lamb]

So what's interesting about this is that the placenta is this like awesome Amazing thing. But it comes from the embryo. So we don't have to engineer that. Right. We just have. I'm going to massively oversimplify it, but all we have to do is to create the right environment with the right chemical cueing in the right place. If it is a placental mammal and it needs to implant, like, 99.9% of placental mammals, like a mouse, then we have to give it a uterine wall or a synthetic wall that it can implant into. So that means that the.

[Tom Bilyeu]

So you'll implant an artificial womb.

[Ben Lamb]

So we'll implant. We will.

[Tom Bilyeu]

I always thought this was gonna be like a plastic bag.

[Ben Lamb]

So we'll. We'll hatch. So I think there's a part of it that is a plastic bag that's the most outer component. But I do think that you need internal component. We're doing it with a combination of hydrogels. Like, we're using these, like, super sticky membranes, but we're also using bioprinting. So we're actually having to print insanely small because it's massively vascularized. Right. Because if you think about how it works in, like, a human body or in a mammal, the embryo will hatch out a placenta. The placenta will attach or implant into the uterine wall. That uterine wall, the placenta, which is almost like this awesome alien. So it's amazing, literally. Yeah.

[Tom Bilyeu]

The more you look at this, the

[Ben Lamb]

more you're like, oh, God, yeah, yeah. But what's great is, like, I was like, we don't have to solve that part. Biology does that part for us. Like, it does want to work and want to live. And so it has to then connect and invade into the placenta wall. But it has to be able to, obviously, stay implanted. So it's got to be sturdy enough, but it can't be too sturdy that it can't implant. It then has to be able to be vascularized enough so that it's getting the right level of oxygen, nutrient excrement exchange, and chemical queuing. Because some of that chemical cueing comes through the placenta. Some of it also comes from the uterine wall in just that kind of amniotic sac. So you have to figure out. But once again, it sounds more like, to me like a data problem and a tissue engineering problem. Then it. I mean, it doesn't sound like magic. It sounds like just. It's just data. It's like if we track every single day of pregnancy and we test and understand what that chemical cueing is, then kind of like the Transcription factors for reprogramming stem cells. We kind of know what the variables are. Right. Is it glucose? What are these different knobs? And then we just have to tune them for every different species and I think over time if you get enough data then you can probably get 80% there. So if this goes great, by the end of 2026, I predict we will have the first mammal born fully ex utero. Which isn't that long from now. Yeah, not. It's not going to be a man. Yeah. It's not going to be mammoth. That can be a wolf, but yeah.

[Tom Bilyeu]

Do you already have one in mind?

[Ben Lamb]

It'll be a mouse or a marsupial.

[Tom Bilyeu]

Interesting. Are they just higher turnover rate?

[Ben Lamb]

Yeah. There's a. Our fat tailed dunnart, which is our model's fancy tailed fat tail dunnarts. It's literally the cute. It's. It will give the woolly mouse a run for its money on objectively cute factor. So. But if you look at the, if you, if you look at them, they only have about a 13 and a half day gestation because marsupials have so much gestation that happens outside the womb. Mice have a little north of 20 days.

[Tom Bilyeu]

Got it.

[Ben Lamb]

But mice, unlike mice, the, the placenta. Technically marsupials are placental mammals, but the placenta only shows up for a cameo for like the last day of gestation. So it's not really needed in terms of like gestation for the fat tailed on our.

[Tom Bilyeu]

Right. Okay, so when you say something will be born ex utero, would I be able to walk into the lab and see it like in its placenta just growing?

[Ben Lamb]

One, if we achieve it and then two, if we achieve it and it's highly replicatable, then yes, you'd be, we would probably stage. Get it. So you'd have it at every single, like you'd be able to say, oh, here's device one and it's at day three, this is at day seven, this is at day 24 or in this case day 2020. And it's birthing.

[Grainger Commercial Voice]

Bro.

[Tom Bilyeu]

This is so sci fi.

[Ben Lamb]

No, it's crazy legitimate. But I actually think that artificial wombs, if we're successful, will have way more impact to conservation than anything else. Like we work on the Northern White Rhino project and we're our, our job is to help them.

[Tom Bilyeu]

Is it just because you can do so many.

[Ben Lamb]

Yeah. So you can do it at scale. That's what, that's the beauty of the artificial womb. If we're really good at this instead of. It's great for Animal welfare perspective. It's also great for conservation because, you know, instead of having to do IVF and rhinos to help save the Northern White Rhino, right, And put them in Southern White Rhinos to birth them. This is how the technology stack immediately applies at scale to conservation. We could take a blood draw, isolate EPCs, endothelial progenitor cells, which is what we did on the wolves, edit those, engineering genetic diversity from a population map that we've done, a population map that we've done based on taking tissue samples of Northern White Rhinos in frozen zoos, in museums and other collections to overcome the cloning problem, genetic bottleneck problem. So, so then they're not, you know, they're not all clones. They're, they're all, they have enough genetic diversity so they all become their own founder lines, right? So then you take that, then you do somatic cell nuclear transfer. You make an embryo, put it in a universal egg or use gametogenesis to make it, and then you take those embryos after you've done some cell transfer and you put it in a ex utero device or an artificial womb and you grow it to turn. So the system, once again, the system model that we're applying to make mammoths or direwolves or thylacines or whatever has a direct application where we could become a technology partner for governments and NGOs around the world to go take our technology into conservation at a scale we've never seen.

[Tom Bilyeu]

This is a world that I don't think people fully understand how transformational this is going to be. We have a lot more to cover. But I do want to touch on the ethics of this. So I unfortunately and am the unhinged guy that wants to see this stuff, like pushed to the absolute max. But for people who their toes curl at the thought of us playing God, how do you think about this?

[Ben Lamb]

Well, I think that we have a moral. I think that we have a moral and ethical responsibility to do it. So because, you know, we actually have developed all of these tools and technologies as a species, we've become the apex predator on this planet. When we started the company, it was forecasted that we're going to lose up to 15% of biodiversity between now and 2050. That was three and a half years ago. It's now 50%. Those aren't our studies. Those are independent studies with.

[Tom Bilyeu]

Why is it going so much faster?

[Ben Lamb]

Well, because we're accelerating climate change, we're accelerating overfishing, over hunting, eradication of habitat. Right. And so polluting, cutting down the rainforest, all of that is a form of playing God, right? If like we go into the rainforest and like slash it all down and burn it, well, that is a form of playing God. We are changing that environment, right? I would even argue that taking cholesterol medication on a micro level is a form of playing God, right? Because you weren't, you weren't designed or engineered or got the random roll of the dice to have a specific cholesterol problem, right? And so I think all of these choices are a form of playing God. And so I think that we have a moral obligation to do something that, you know, with these technologies that can not only help and benefit human healthcare, but could help species.

[Tom Bilyeu]

Okay, talk to me about human healthcare. Is this going to be a. Dear parents, Everybody is going to have kids via ivf. Don't worry, it's going to become very cheap. It'll be de rigueur. Like everybody's going to be doing this. Don't worry. It's not just for the rich, but you're going to want to do that so that you can select.

[Ben Lamb]

Here's the beautiful thing for Colossal is we only work on animals in conservation.

[Tom Bilyeu]

Are you going to dodge like that?

[Ben Lamb]

No, I'm not going to dodge. I will answer the question. But I'm saying, saying Colossal takes the stance that we as a company aren't going to work on humans because we already get so many crazy conspiracy theories about the company. Given that Ink Utel and others are investors. They're like, what are they doing? What is the secret programs? They don't tell us about, but we're pretty transparent about what we're working on.

[Tom Bilyeu]

I was gonna say the things you're

[Ben Lamb]

talking about already or like they're already weird enough. I mean weird. I think people give us too much credit and like that we've got like crazy stuff.

[Tom Bilyeu]

Even more crazy things.

[Ben Lamb]

More crazy stuff. But what's interesting is, is for us it's like we at Colossal draw that line. So we won't, we aren't going to make those decisions. Why not?

[Tom Bilyeu]

Like Ben Lamb. Why do you not want to do it?

[Ben Lamb]

Well, I mean.

[Tom Bilyeu]

So too big of a headache?

[Ben Lamb]

No, I mean I, I think that the separation for Colossal is, is good between animals and, and humans. Like we won't even work on anything in the non human primate world. So anything in the monkey world we won't do. Or April, we won't do any of that because like there was a species, which I did. I don't think there's any DNA called Giant Apithecus, which was not King Kong, but much larger than, you know, our ring of tangs and apes. We wouldn't touch that project. We've made a decision that we're not going to work on anything because people get asked us about Neanderthal, right? And so they're like, oh, could you do a Neanderthal? I was like, it's just a slippery slope. So we've made the decision.

[Tom Bilyeu]

It's a slippery ethical slope because it's a slippery human.

[Ben Lamb]

It's just a slippery. Yes, it's just too, too human. It's too close. There's enough problems for Colossal to solve without doing it. With that said, all the technologies that we develop that have an application to human healthcare, we will license out. We'll spin them out so other people may use our technologies to eventually grow humans and artificial wombs and whatnot, even though Colossal will not do that. Right. But I do think that other people, thank God it's not us, but other people will have to think about what is the line between making selections for the betterment of a society from a genetics perspective before you go all out Gattaca, or you look like. Or it looks like eugenics, right? And so those are really hard things. Like, I'm glad that I don't have to, like, make those decisions. But I will say I just had a kid and went through ivf and there's. Now, have you seen this whole genome sequencing stuff that's come out? No. So most people, when they, when they go through ivf, they're great. Doctors out there will look at a morphological grade, like, how is the embryo doing on day one, day two, day three, day four, whatever. And so how is it developing? How is it ready? And they. A lot of times they'll grade them based on the morphologic. Like, how does it look? How's it. How's it behaving?

[Tom Bilyeu]

An ideal embryo would look just like

[Ben Lamb]

this, like this, right? Or be behaving like this at this stage, at this stage of development. So that's one. Well, then they started saying, okay, well, let's look for specific things like extra chromosomes or extra things that could, could. That could be. Could be. Could be really bad, right? And so they started looking at those types of things, right? And at least giving that data to the people, right? Like, you know, this is, this is an issue. A lot of times people have miscarriages because some. Something was broken in the genetics of it and of the developing embryo, and it just wasn't compatible with life. Even though it was developing on day one, day two, or day three. Well, so now there's a new company. Full disclosure. I use them as a service. I was so impressed with what came out of them. I did invest in them. So I'm not. I just always want to be transparent about my investments. But Orchid Health, which is pretty awesome. And what they do is they take a tiny little couple of cells from the outer ring. So not in the developing embryo, but in the. In the outer ring, they do full genome sequencing. So not. They're not doing. They're not doing like, 23andMe. They're doing, like, really deep sequencing.

[Tom Bilyeu]

Because 23andMe is too serious surface to surface.

[Ben Lamb]

Right. They didn't look for everything. Right. So they look for the. The core stuff, but they didn't go. I think there's a lot of reasons they want a business, but they. They went. They. They do the full genome sequencing. So they can do. They can look for their specific markers. Like, I had this Titan gene mutation, and so we did not want to pass that on because there's risk so that we could screen for that. Right.

[Tom Bilyeu]

Well, so you literally check the embryos. This one does, this one doesn't. The one that does don't implant.

[Ben Lamb]

Yeah. I mean, we still. Yeah. So you. You build. So I built a spreadsheet to kind of. And I built a relevance ranking. I like your style system of it.

[Tom Bilyeu]

Well, because embryos did you have.

[Ben Lamb]

So we went through two rounds of ivf, and so we ended up getting. I think at the end, we ended up having. We down. Selected down based on this kind of distributed kind of bell curve that we. That we made in a spreadsheet. And we ended up having nine.

[Tom Bilyeu]

Whoa. Okay. So nine that you personally were like, I'm gonna give these a grade before

[Ben Lamb]

we even did the morphological rating with the thing. So. So the other thing that's interesting. So you're talking about, like, other things

[Tom Bilyeu]

other than the Titan gene.

[Ben Lamb]

So. So there's also. And so this is. This gets into. And so this goes back into your question about, like, you know, and once again, this isn't colossal making this decision. This is me personally with, you know, in my. With my family making these decisions. And we started looking at. They actually do this, like, polygenic risk score, which some people don't.

[Tom Bilyeu]

What's polygenic?

[Ben Lamb]

So they basically look at, like. We do know that certain genes and certain mutations in addition to environmental factors could lead to higher diagnosis of early onset Alzheimer's or diabetes or certain types of cancers. Right. So one of the things that ORCA does, which I found pretty interesting, is it kind of gives you like the bell curve where most people fall, and then it can tell you like, this embryo fell here and it has this mutation follows here. Right. And so, you know, I think that, you know, the, the easiest grade is like, if you're looking at this, what the technologies currently allow for, the easiest grade is, you know, is it compatible with life? Does it look morphologically? Right. Okay. Are there major things that we want to screen. Screen for like extra chromosomes or chromosomal anomalies and then. And then from there you can look for specific things. Like in the case of me looking for this Titan gene mutation that we didn't want to pass on, and then it goes into this, like, area that's. I wouldn't say it's gray, but it's not like if you have this exact gene variant, you will get Alzheimer's.

[Tom Bilyeu]

Off white.

[Ben Lamb]

It's off white.

[Tom Bilyeu]

Okay.

[Ben Lamb]

But it's still interesting, right? It's not based on, like, you know,

[Tom Bilyeu]

if you want to push it all the way.

[Ben Lamb]

Why do I want to push all the way? So, I mean, I did, right? I mean that, that's as far as the technology goes today. So I did that. Like, we chose. We chose, you know, we looked at all of the data and we made a selection based on the data, but we didn't make the decision based on was it compatible with life and how did it morphologically look? We went through all the way to

[Tom Bilyeu]

the distributor talking about now and then

[Ben Lamb]

we built a spreadsheet.

[Tom Bilyeu]

Oh, God, I want to see that spreadsheet so bad.

[Ben Lamb]

I promise I will never show anyone that spreadsheet.

[Tom Bilyeu]

I figured that was going to be the answer. Wherever we are today, I have a feeling we're going to be able to read more and more things. Yep. One human response that while I get it, because humans are like, that strikes me as very strange. You've said this a few times in a very sort of polite way about looking for extra chromosomes, down syndrome. Now when you say, yeah, I wouldn't implant an embryo. This is Tom Bilyeu speaking. I would not implant an embryo that had down syndrome. But then. And you're gonna get. I will get backlash on that because people are pretty fiery about that.

[Ben Lamb]

In my family, we have people with down syndromes. Like, you know, in, in my extended family. Right. And so I'm not saying that you should or shouldn't, but that, but it should be your choice. That's, that's. I'm a big believer do you think

[Tom Bilyeu]

there's, there's too many morphological characteristics, like this kid is gonna be tall or beautiful or whatever that people think, or smarter? Let's get really big.

[Ben Lamb]

And so people have already said that, right? Like we, There's a general moratorium in the world, including the United States, on germline editing, meaning making edits that will get passed on to the gene pool. But then you've got certain places like in China, at the Beijing Genomics Institute, where they are like we are sequencing everyone and we are looking for genes and gene clusters that can drive intelligence. And so they're very open about that, right? And so it is a really hard thing, right? It's like if we could remove, I'll give you an example, like sickle cell anemia, which affects a percentage of the population. It's one gene edit, it's just one. So if we could eradicate that for all humanity, should we? I mean, I would make the argument yes, but I also don't have sickle cell anemia. Right. And so these things go beyond science in terms of capabilities, but go into not just ethics, but go into philosophy. It's like I would argue that we have some form of directed evolution as a species, right. You know, we are no longer just hunters and gatherers. We already have, we're already doing it, right. It's like when people say that like what colossal is doing is. Could go too far or that, you know, we. One of the things we get back, you know, people love to argue whether it's a dire, you know, whether we can classify it as a direwolf or not. But what people, which I'm sure we'll get into, but what people don't realize is that like these. And what people don't argue is that the technologies that we have, that we're now deploying here exist and they're only going to get better. And so we have to be thinking about what the applications are for humanity. But I would argue, I always tell people that, you know, we've been doing gene editing for a long time. We've just been really shitty at it, right? Like we've been, we've been like cross breeding stuff forever. Like whether it was weed or corn or dogs, you know, like, or who you pick as your spouse, we have been doing this the old fashioned way for a long time now. Let's just use data and let's just do it faster and more efficient where we have a high degree of predictability of the outcome.

[Tom Bilyeu]

Dude, this is inevitable. So I'll put My cards on the table. I have no idea how you're going to react, but we are in a cold war with China. China is going to do everything that they can to beat us in AI.

[Ben Lamb]

I agree. I agree.

[Tom Bilyeu]

So we can't play around.

[Ben Lamb]

Yeah.

[Tom Bilyeu]

China's gonna do everything they can. I saw a video today of a robot dog with a gun on its back and training it to autonomously do its thing. Y. If we know. So right now, as far as I know, the only place that has done edits on humans is China.

[Ben Lamb]

Yeah.

[Tom Bilyeu]

China. Yeah. You will often say the person that did that, the doctor that did that, was allegedly punished. I always find the use of the word alleged, it's.

[Ben Lamb]

It's interesting. Yeah. It's like you do something that big, it gets out of jail pretty quick.

[Tom Bilyeu]

Yeah. Because you have at least running in the back of your mind the possibility that that was sponsored or at least like, oh, well, if you're doing it.

[Ben Lamb]

China is an information state. So I find it hard to believe that people at various degrees of government didn't have the information.

[Tom Bilyeu]

It's a very delicate way to put it. Also, I feel like. Forget editing for a second selection of the embryos that you have. I would fully expect people to go as hard in the paint as they possibly can to get the ones that meet whatever characteristics that are desirable.

[Ben Lamb]

Can I add something? This is crazy. This is from my own personal journey. The morphological embryo that looked the best, based on this side, not going all the way out, but just this side, the one that actually looked the best, had a genetic defect and was not compatible with life.

[Tom Bilyeu]

Interesting.

[Ben Lamb]

So more than likely, our incredible doctor would have put in an embryo that would have led to a miscarriage.

[Tom Bilyeu]

Yo.

[Ben Lamb]

Which is. Which is emotionally taxing on the family, specifically on the female. And it's also. It's also economically taxing. And he wasn't wrong. Based on the morphological grade, like there's a grading system. You can look at it and. But it was not genetically compatible with life. But that's what would have been implanted.

[Tom Bilyeu]

Right.

[Ben Lamb]

If we wouldn't have done these other things. So I do think that data can help us be informed to make. We just make. We make more informed decisions with that data. Right. Doesn't mean they're always going to be the right decisions, but at least we have the personal choice to make those decisions.

[Tom Bilyeu]

Do you think that there's any of the gray in selecting from unedited but IVF created embryos?

[Ben Lamb]

No, I think that that's, you know, it's like the, like I don't know if you. Have you seen the gallery test, the braille test, the blood test?

[Tom Bilyeu]

Just got one. You did literally like a week ago.

[Ben Lamb]

You get your results?

[Tom Bilyeu]

I haven't got my results yet.

[Ben Lamb]

That's a little nerve wracking, isn't it? For me it is. I do, I do it every year.

[Tom Bilyeu]

I went in because literally as we're recording this, I had skin cancer removed from my face. So I was like, I want to know everything.

[Ben Lamb]

But you're one of those people. I'm one of those people. You know, I do, I do the function test and I do four quarterly blood tests in addition to the function test, which is already insane and incredible and comprehensive as it is. Then I do four blood. Then I do four quarterly blood tests. I do the grail gallery test, I don't know, grail.com, whatever it is they actually call it. I do all of that because I want the data. But a lot of people, they don't want that data. So going back. But that applies sometimes. It's hard for I think people like you and I to understand that. But if you and I, but. Because we're wired a certain way. But I think that goes the same way with embryo selection. I want the best amount of data to make the best decision. But not everyone does. Everyone. Some people are like, I, I just want to trust nature and trust. I just want to trust the universe and trust the chance system. Of course, I don't understand it, but they're entitled to it.

[Tom Bilyeu]

I definitely think people should be able to make their own decisions. Yeah, I just, just don't understand the pushback on the selection.

[Ben Lamb]

There's been pushback on Orchid and I'm like, here's this incredible woman that developed a technology and just wants to give people more data so that they can make a decision. Right.

[Tom Bilyeu]

Say more about this. What is it?

[Ben Lamb]

This is the Orcid health. This is the Orcid test that gives you that risk score. This is the system that we use. But it's like they got pushed back when they launched and I was like, it's just data.

[Tom Bilyeu]

Yeah.

[Ben Lamb]

You don't have to use the data. You don't have to take tests.

[Tom Bilyeu]

So can you steel, man, Their argument,

[Ben Lamb]

I think that their argument is with more data, you'll make a better decision and you will lead to healthier babies that have longer lives that will also have a longer term impact.

[Tom Bilyeu]

I mean, the people that hate it.

[Ben Lamb]

Oh, they hate it. I think they think it's a form. It goes back to it's a form of playing God. Right. It's like it's, or it's eugenics. Right. But I mean I think that selecting for, I think selecting for a certain like skin color or hair or eye color, that's eugenics. Right. Seeing if you're seeing if your kid has like my gene mutation that has a, my, that has the issue that I have with my truncation on my Titan gene. That's not new genics. That's just like I don't want to pass that on. I would argue that things like Orchid are a service to humanity. They're not just an individual service. Because your doge genesis will persist in the gene pool long after you're gone, it's a moral obligation to do this not just to you and your family and to your child, but to humanity as a whole. And, and because the ripple effects of

[Tom Bilyeu]

the gene pool, this will get so bizarre. If I'm a kid and my parents chose an option that they thought was cool or kind or there needs to be a distribution like wait a second, I could have been the embryo that was three times smarter. Like I'm now suing. Yeah, that's going to get certainly very bizarre.

[Ben Lamb]

It's going to get bizarre. And Orchid doesn't test for intelligence by the way.

[Tom Bilyeu]

Yet. Yet.

[Ben Lamb]

I mean I'm not part of it

[Tom Bilyeu]

and maybe they never will.

[Ben Lamb]

But that strikes to your comment bgi and this isn't like some like deep state, like dark web secret. Like they've been like the CEO of is like yeah, we do that. Like they're, they're very open about it.

[Tom Bilyeu]

They're like, please.

[Ben Lamb]

Yeah, they're like, why shouldn't we?

[Tom Bilyeu]

Yeah, that, that is quite literally my question. Okay, so by what mechanism do we decide what is eugenics and horrible and what is. Yeah, it's my kid. I want to fine tune a little bit here.

[Ben Lamb]

Yeah, I mean the good news is there's no germline. There's this moratorium on germline editing. And, and so we don't have to

[Tom Bilyeu]

make that decision, but let's pick an easy one. So I was just, for whatever reason this came across my feedback and my wife happens to have a very good friend of hers. Mixed race guy, white wife. They have twin daughters and one looks light skinned African American but not American because she's British but she looks light skinned black.

[Ben Lamb]

Yeah.

[Tom Bilyeu]

And then the other one is ginger freckles. Like how are these two twins? Obviously they are not monozygotic twins but twins nonetheless. And if you have that and you're looking at that, and you get to pick, like, instead of, you know, two, or you go through and you want every color of the rainbow or whatever. Like, ooh, where do we go?

[Ben Lamb]

It is in the realm of sci fi, right? And it's like leaning on this to. As it relates to government. What is government's decision in that? Right? Like, what is their right? You know, we have a general moratorium on not being able to.

[Tom Bilyeu]

Is that considered germline, though? You're just selective because that's already. Like, this is happening right now. I don't know if they were IVF or not, but I don't.

[Ben Lamb]

I don't think anyone out there has or is surfacing that type of data, like eye color. No one's surfacing that type of data.

[Tom Bilyeu]

So people are just like, we're not going to tell you. Yeah, I don't think that lasts forever.

[Ben Lamb]

I don't think it lasts forever. And, you know, one of the things that makes America different than China is our ethics, is what we'll choose to do, right? Like, yeah. I mean, and one of the things that, like, colossal. Certified by American Humane Society, the oldest humane organization in the world, we run everything by them, from where our animals live to how we treat them in the lab, to every single thing, right? It's hard. It's very, very hard. And if we didn't care about that and we just wanted to do something in a country like in a southeastern Asian country and, you know, be like, oh, we'll just go kill 100 elephants to do this, and we'll have a mammoth in two years. Like, we choose to do things as an American company in America by American standards, America's ethics and America's rules. And, you know, not all countries, you know, in this weird, complicated geopolitical world we live in, you know, play by the same rules and play by the same ethical standards. They also look at things. They also look at. Like, if you're. If you're looking at a lot of the Asian countries, they're looking generational, right? So they're making. They're thinking about what is the generational thing? And we're more of a society that looks at today and tomorrow. So I think there's cultural and kind of generational views that go into this that have a very, very big. It's like the old adage about how people steer, like a cruise boat, right? If you want to go over there, you make a small turn now, and it'll eventually go there. And I think that some countries think like that, and I think that affords them at least a perspective where they don't look at the ethics the same way we do.

[Tom Bilyeu]

Yeah. All right, guys, that's it for part one. But there's more to come in part two. Make sure you are following impact theory and leave us a review on Apple or Spotify. It really does help other people find the show. Please hit us up. Until next time, my friends. Be legendary. Take care. Nine out of the ten largest banks get it. They get advantagescore. The modern credit score is the leader

[Ben Lamb]

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