Why We're Living in a Biological Singularity With Ben Lamm | MOONSHOTS Live #297

The Mates sit down with Ben Lamm at MOONSHOTS Live 2026 to discuss why we’re entering a biological singularity, from Anthropic’s move into biology and scalable gene editing to the possibility of artificial wombs within the next 24 months. This episode was filmed at Moonshots Live 2026. Learn more at https://moonshots.com/ Get access to metatrends 10+ years before anyone else - https://qr.diamandis.com/metatrends Peter H. Diamandis, MD, is the Founder of XPRIZE, Singularity University, ZeroG, and A360 Salim Ismail is the founder of Open ExO, a GP at Exponential Venture Capital/The Organizational Singularity Fund and a sought after global speaker and thought leader. Dave Blundin is the founder & GP of Link Ventures Dr. Alexander Wissner-Gross is a computer scientist and founder of Reified Ben Lamm is the co-founder and CEO of Colossal Biosciences, a biotechnology company using genetic engineering and AI to advance species preservation and de-extinction efforts. – This event is presented with: Google Circle Future Vision XPRIZE Partners: Salesforce ARK Invest Xsolla Range Build with Gemini XPRIZE Partner: Google _ Connect with Peter: ⁠X⁠ ⁠Instagram⁠ ⁠Substack⁠ ⁠Website⁠ ⁠Xprize⁠ ⁠A360⁠ Connect with Dave: ⁠Web⁠ ⁠X⁠ ⁠LinkedIn⁠ ⁠Instagram⁠ ⁠TikTok⁠ Connect with Salim: ⁠LinkedIn⁠ ⁠X⁠ ⁠Join Salim’s 10X Shift⁠ ⁠Subscribe to Salim’s YouTube channel⁠ ⁠Exponential Venture Capital⁠ Connect with Alex ⁠Website⁠ ⁠LinkedIn⁠ ⁠X⁠ Email ⁠Substack⁠ ⁠Spotify⁠ ⁠Threads Connect with Ben Website X LinkedIn Instagram Listen to MOONSHOTS: Apple YouTube Follow MOONSHOTS: Instagram TikTok X Threads – *Recorded on September 25th, 2026 *The views expressed by me and all guests are personal opinions and do not constitute Financial, Medical, or Legal advice. Learn more about your ad choices. Visit megaphone.fm/adchoices

• 0:05Speaker 00

  I was a little terrified backstage when Palmer's like, "There's something on the screen that says I'm not supposed to say this." I was like, "For the love of God, whatever it is, please don't make it about colossal."

• 0:14Speaker 01

  Please don't say it.

• 0:18Speaker 01

  So I remember at Abundance 360 last March, just before you came on, Elon was there. And he said, "Yeah, I want a pet woolly mammoth." How are you doing on that project?

• 0:32Speaker 00

  We get that request, yeah. But there was actually an amazing, I think it was either American Dad or Family Guy episode, where they explained, did you see this? I don't know if you guys saw this. It's like, explain CRISPR, and it was amazing. And it was amazing, because then at the end, they're like, "Yeah, and the woolly mammoths came out, and they're about the size of a dog." That's actually how big they were. The fossils were just wrong, right? It was like amazing, because it explains CRISPR. But I was like, you know, we get the requests, like, the number two request we get is teacup mammoths.

• 1:03Speaker 01

  Teacup?

• 1:04Speaker 00

  Teacup mammoths. Yeah, everybody wants a teacup. Like, they want to take a mammoth and put it like, yeah, and put it in your purse, right? And so, I mean, we can engineer a new melanin, make it pink, and then Paris may want one. So we're, uh, we are not working on that currently. But we're making good progress on the mammoth project, so.

• 1:22Speaker 01

  Amazing. So let me kick this off. So you've started like four successful companies before colossal, and gaming, and defense, and AI, and mobile. And so, you knew nothing about synthetic biology.

• 1:37Speaker 00

  Yeah.

• 1:38Speaker 01

  Before you started. Now a company worth over $10 billion. So why, what made you make the extinction your moonshot? And having no background in synthetic biology, was that a hindrance or an advantage?

• 1:54Speaker 00

  Oh, I think it's a massive advantage. You know, I think that it affords me the opportunity to go into rooms of, you know, Palmer talked a little bit about this too, like hiring people to replace you, and hiring people that are much smarter than you, right? And so, I get, what's great about this from my vantage point, is like, I get to deal with a lot of the same bullshit, but at the same time, I can go in and like, sit down with like, Beth Shapiro, and learn about ancient DNA extraction, and like, how not to do things. But then at the same, but then like, the next meeting, I can go learn about like, where we're pushing the boundaries of multiplex editing, and how many edits that we can make at once, right? And so, I would say that, you know, I knew how to, and I guess in all of my career, I've known how to ask the right questions, because I'm really curious.

• 2:36Speaker 00

  But I really do kind of subscribe to that old adage of like, putting the top, smartest women and men around you, just asking them the questions, right? And so, I get to go to meetings to just ask questions, and you know, 90% of the time, I think people are like, "Okay, if you knew more about biology, this meeting would go faster." But then 10% of the time, but then 10% of the time, they're like, "We never thought of it that way," right? Because it.

• 2:58Speaker 01

  By the way, this is such an important lesson for all of us as entrepreneurs, right? Just because you're not an expert in an area, doesn't make it an area that you shouldn't go into if you love, if you attract the best talent around you.

• 3:12Speaker 00

  Yeah, George Church, and like, this is the only brag that I will say, which I'm very proud of. George Church says that I am the best student he's never had. Because I will literally just pepper him and be like, "Hey, my favorite times of the year are during holiday seasons, when like, no one's working." Because I will just get on calls for hours and hours and hours with George Church, and just talk about the possibilities with synthetic biology.

• 3:34Speaker 01

  Who's George Church for everybody?

• 3:35Speaker 00

  So if you don't know George, George is the father of, arguably, the father of synthetic biology. He's the head of genetics at Harvard. And, you know, he's, a lot of the next-gen read-write technologies that were invented, came out of the Church lab. And his lab's prolific. It's, there's been numerous multi-billion dollar companies that spun out of the lab. It's probably the, probably most active startup biology lab in the world. And, and he's also, he's also like 6'7", with like narcolepsy and hilarious.

• 4:01Speaker 01

  And such a sweetheart guy.

• 4:03Speaker 00

  Yeah. And I mean, he is the most collaborative person ever, right? And so, he's also like hardcore, even though it doesn't come from software, he's hardcore into open source, and just like, trying, the democratization of technologies, like genome sequencing, he wanted that to go from billions to $100. Well, she was very active in that category. And so, he is literally just the most collaborative co-founder I've ever, you know, had the pleasure of working with.

• 4:29Speaker 01

  Dave?

• 4:30Speaker 02

  Yeah, really curious about the business model of biology. And this is like, I think we all know that of all the use cases of AI that are imminent, you know, like solving all disease, curing all pain is just like, highest on the priority list. The business model in biology is just always.

• 4:44Speaker 00

  Yeah.

• 4:44Speaker 02

  So, I mean, and it's great to get your perspective as a serial entrepreneur who came into biology from the outside. So my first question on like, the business model is the foundation models. Like, we just saw that like, out of the box, Astra can drive a car.

• 4:58Speaker 00

  Yeah, yeah.

• 4:59Speaker 02

  Is it gonna do biology out of the box? Or do you say, "No, no, no, no, we need to build our own"?

• 5:03Speaker 00

  So I'll have to, so the foundation models now, and we've been very fortunate to work with both OpenAI and Anthropic on getting early access to some of that stuff, which has been great. For a long time, we were leveraging it for kind of like thoughtful middleware, right? Coming from a software perspective. Where we were connecting lab notebooks and Jira. I mean, one of the hardest things that we did at the company was, retrain scientists to work in Jira. So that's harder than SimCity reprogramming at times. And so, and so we actually, for a long time, you know, these, the LLMs before the frontier models, were really good at writing term papers, right? They weren't really great at doing like ancestral state reconstruction or comparative genomics, right?

• 5:46Speaker 00

  Like, that, that's where they just didn't work, which would have been amazing. So for a long time, we were leveraging them for kind of like middleware layers of infrastructure, so you don't have to go hire the Deloitte's or Accenture's of the world to build all these systems and reporting, right? So we did, I think we were very successful at deploying that for a long, long time. Now, they're getting pretty far, where you can run simulation experiments. There's a bunch of companies out there that are standing up, Lila and others, that are like, trying to do lab automation around it, right? We've been pretty thoughtful about how and when we invest in that category. But I think that what you're gonna find is you're gonna find interesting insights between connections that are really still language problems, right? So like, so for example, if you go search the literature on, you know, everything on mice,

• 6:30Speaker 00

  you know, if you just wanna go build a new therapy company or whatever for humans, and you go look at all of the published papers on mice, many of them, they'll call a gene a different thing, they'll classify it differently, they'll run that experiment slightly differently. And so, you know, if you, if you go try to run the exact same experiment, you're gonna get like, somewhere between 40 and 60% failure rate on published work, which is terrible, right? So where I think AI is gonna be really helpful in the next kind of wave of, outside of like, small molecule drug discovery, I think it'll be very, very helpful, kind of eliminating that gap and bridging kind of that nomenclature between work. Like, there'll be times where we'll do work, and we'll find out later

• 7:11Speaker 00

  that there was a peer-reviewed published paper on one of the things that we were trying to solve, but the way we were looking for it wasn't findable on PubMed or whatnot. So I think in the short term, it's gonna bridge the communication layer. But I do think you're gonna, and you saw this, I think Anthropic announced this a couple of days ago, right? Where they've, and you have Ginkgo and others that are now going to test it, you're still gonna need to have a wet lab experiment to test and validate those. But running simulation design across a myriad of different experiments, and helping creatively come up with the next experiment, I think that's where we're gonna see AI in biology for the next, you know, three to five years.

• 7:48Speaker 02

  What about this, like, like, if I think about text data and research results, and going through, you know, thousands and thousands of prior tests, that's all LLM city. But what if my input vector is just a gene sequence? Like, if I dump that right now into Anthropic, pretty sure nothing good is gonna come out the other side.

• 8:07Speaker 00

  Yeah, but, but at scale, so, so, thank you for the tee up. So that is what, that is what I fundamentally believe is the importance of our global biobolt system that we're rolling out, right? So we're trying to roll out this like, Noah's Ark 2.0 model. Not that Noah didn't get it really right in the first stage, but like, at least ours is slightly different. We're doing like ATAC sequencing and other things that he didn't do. And so, we're going out and trying to work with governments around the world to stand up localized biobolts to get all of that, so that we can do T2T sequencing. And so, to your point, I do not think that a single genome is going to, like, you're not gonna feed it into Mythos, and it's gonna be like, "Oh, well, if you make these six changes, it's immortal," right?

• 8:51Speaker 00

  But I think that if you go look at like, you know, you know, thousands of genomes across all these evolutionary lanes in avian species, and see that they are not susceptible to many of these diseases, you'll look at that, right? We're doing that on a small scale with things like P53, immortal jellyfishes, other things, looking at kind of like, known outcomes of the species, and then try to backtrack it down the tree of life. So we're doing some of that right now at one of our companies, which we're pretty excited about, and early indications are positive. But to your point, you're not just gonna be all, throw a genome in, and it's gonna be like, "Oh, here's how you fix it and make it perfect." But I do think that that amount of data, from a comparative genomics perspective at scale,

• 9:36Speaker 00

  is, will get you there. But I also think that, so I would make the argument that, you know, the data set is more valuable than the model.

• 9:45Speaker 02

  Yeah, yeah, yeah.

• 9:45Speaker 00

  Because I have the data set.

• 9:46Speaker 01

  We've made that point so many times. Alex?

• 9:49Speaker 03

  Yeah, I'd love to talk a bit about de-extinction. I'm cognizant that you now have four-plus spinoffs. And, but nonetheless, de-extinction, I think, is still what you and colossal are perhaps best.

• 10:00Speaker 00

  And certain things we're not supposed to talk about.

• 10:01Speaker 03

  We won't talk about those, though. So, de-extinction. There was a Russian philosopher, Nikolai Fyodorov, late 19th century, parent of a strain of philosophy called Russian cosmism, that argued that the ultimate trajectory of humanity in developing science and technology would be essentially to develop the technology to revive every human who's ever lived. Russian cosmism, you can look it up. So, de-extinction, in some sense, you are.

• 10:31Speaker 00

  We are not doing that currently.

• 10:35Speaker 03

  Good to know. So, but in some sense, by de-extinguishing, de-extincting various model species, including the woolly mammoth, you're the first company, to my knowledge, on Earth that at least has a plausible business model, or at least technical trajectory, to try to go after the entire historical biosphere. So maybe not even just every human who's ever lived, but every non-human organism that's ever lived.

• 11:02Speaker 00

  Right.

• 11:04Speaker 03

  In an era of superintelligence, where grand challenges are falling left and right, do you think that humanity's common task, as the 19th-century Russian cosmists thought, that we'll ultimately have the technology to revive every organism that's ever lived, or at least every human, do you foresee that becoming possible?

• 11:24Speaker 00

  I do not. I think through DNA synthesis, prediction models, and, you know, some components of synthetic biology, we will be able to get pretty close approximates. I don't think, though, with two big caveats. Number one, just to get off of those other, Colossal does not use any of our technologies at Colossal for humans, so we won't do that, even though I think our-

• 11:49Speaker 03

  You don't need a spin-off for that, is that what you're saying?

• 11:51Speaker 00

  I think that when you start working with humans, you need different, sometimes different investors, sometime, and definitely different governance, right? And you go through a different process-

• 12:01Speaker 01

  And more patience.

• 12:02Speaker 00

  And more patience, right? That was actually really good advice I got from Bob Nelson. Bob Nelson, in the early days, was like, "Hey, don't apply any of this to humans for a while, because you effectively go into like code freeze with the FDA, and it's just a, like, you're just gonna be in this monotony forever. Go get to the technologies until they plateau before you then take them out." But back to your question, I think that fundamentally, most organisms, remember, these are the most organisms that we know, very few people realize this, but there's like, less than like 100 T. rexes that have ever been, and I just want to go down the path, it'll scare you, there's less than like 100 T. rexes that have ever been found, right? But with that, you know, there's billions that allegedly

• 12:44Speaker 00

  were on Earth at different points in time, right? And so, very few things leave a fossil record. So I think it's more likely that we will be able to engineer life, from a programmable life perspective, in the way that we want it, than just bring back everything that ever existed, because I don't even think we know, right? I think it's probably, highly likely, based on AI superintelligence at some point, where we get to the point where we're saying, "Oh, we're gonna engineer this thing." And to your question, maybe it did exist, but we just never know, because it left no fossil records, right? So I think it's more likely that we will be engineering life to our advantage, and trying to bring back things. And even if Colossal, or a subset of our technologies, both cloning and genome engineering, can

• 13:26Speaker 00

  bring back things, as you know, environmental factors, epigenetics, all these other things, like, if we could clone Mozart, that doesn't mean that he's gonna come out and be like, "Oh, I'm gonna like, solve where the terrible trajectory of music has gone."

• 13:39Speaker 03

  Well, just maybe a follow-up question. So, for Mozart specifically, we do know quite a bit about Mozart's life, so our arguendo, if we did want to resurrect Mozart, we'd have no problem at all with reconstructing his childhood environment.

• 13:52Speaker 00

  To a point, right? Like, to a point, right? And so, I'm not, and by the way, just to be very clear, I am not encouraging in any way this line of questioning, where we are taking humans and growing them, it's like, you're gonna make, like, you're gonna go down this like, Michael Jordan, LeBron, Super basketball-

• 14:09Speaker 01

  Oh, yeah.

• 14:10Speaker 00

  -second and scare me. So, the, I do think it's highly likely that if we were able, or it's not highly, it's 100% accurate to say that we understand their genetic disposition and aptitude towards these certain traits, and under the right environments, if you want to go like, you know, if you want to go all simulation design on them, and put them in the right environments, then they could probably, then your Mozart 2.0 could probably be better than the Mozart 1.0.

• 14:41Speaker 01

  But Ben, let's bring it back to the animal kingdom, because, right now, the whole thesis is that the AI systems can design the genome sequence that reflect a phenotype. So if you want an animal that's bigger-

• 14:55Speaker 00

  It's getting better. Is that 100% there yet?

• 14:57Speaker 01

  But that's the objective, right? If you want an animal that's got a longer snout, or an animal that has wings. So, like, I asked you on stage at FII, you know, "Could you make a Pikachu?"

• 15:08Speaker 00

  Yeah, that seems to be a weird, like, fan favorite, you know?

• 15:11Speaker 01

  Yeah.

• 15:11Speaker 00

  People are more accepting, I think, of Pikachu than these large genetic human camps that you're thinking.

• 15:18Speaker 03

  Branded species.

• 15:19Speaker 00

  Yeah, yeah, it is. Yeah, I think people are more open to that model of genome engineering than-

• 15:25Speaker 03

  But it sounds, just maybe to tie a bow on this, it sounds like it isn't a technical objection, per se, it's more worries of social, political, regulatory concerns.

• 15:34Speaker 00

  Correct, correct, yes. It's unethical.

• 15:35Speaker 04

  So this is where, this is where I'd like to jump in. You know, in, Stuart Brand made this famous comment, Peter, the title of your book, he said, "We are as gods, we might as well start acting like them," right? And he said that in 1968. We are at a point where you can de-extinct or bring back any species. How do you think through the ethics of, what should we bring back? Which ones, which ones shouldn't we bring back?

• 16:02Speaker 00

  So, I'm a huge Stuart fan, you know, I love him, love Ryan, that quote has been out there, kind of like, you know, Minnie from a famous dinosaur movie. But, I don't know if I would characterize it like Stuart, and then get like, on a plane. But, from my perspective, I would say that, like, we spend a lot of time, it is not plausible yet to bring back everything, or engineer everything from a synthetic biology perspective. So we try to be very thoughtful, and people ask us, "Is there a checklist? How exactly do you go about selecting your species?" Because there's a species that we've been very public about, and then there's species that we have not yet-

• 16:40Speaker 04

  But, hold on, I'm not thinking, I'm not talking about what you're doing specifically.

• 16:44Speaker 00

  Oh, you're saying philosophically?

• 16:45Speaker 04

  Generally philosophically, right? If we could bring back any species, who gets to decide? What evidence do you use to say, "Oh, bring this back or that"?

• 16:53Speaker 00

  Yeah.

• 16:53Speaker 04

  Just from a societal ethics perspective, how should we be thinking about that?

• 16:56Speaker 03

  Specisism, right?

• 16:57Speaker 04

  Yeah.

• 16:58Speaker 00

  Yeah, and so, it's a great question, and because we're kind of the, you know, guinea pig in this world, the way that we think about it is, what was their contribution to the environment? What was their contribution to the food web? What was their, why did they go extinct? What, how do indigenous people feel about it, right? Like- Some of the species that we work on, they have a deep spiritual connection to the indigenous people side of it, right? So I don't think you're gonna walk in and quote Stuart Brand to them, right? And so, I think that it's very important to kind of like, factor all those and weight those, and we're probably gonna get it wrong, and I think society's gonna get it wrong, but we're gonna continue to try. But then we also look at, like, is there an educational benefit to it, right? Like, one of the things that we did when we did the dire wolves, right, after working with the indigenous people

• 17:40Speaker 00

  groups, and the Red Wolf Coalition teams, and all these different components, is, we did, we did weigh in the pop culture nature to it. We thought, is there a way that we can bring all these people that focus on sci-fi, and Game of Thrones, and Magic the Gathering, can we bring them to wolf conservation? And can we bring them, can we teach them about genome engineering, because we brought something back that they thought was only a mythological creature in their fantasy universe, right? So, we try to weight all of these things differently. There's not a perfect kind of internal algorithm for how we look at it, but I do think that as the technologies proliferate, and more governments start deploying our technologies, they will have to weight that on a individual basis.

• 18:23Speaker 01

  Yes, they will.

• 18:24Speaker 00

  And I'm sure that all of us are gonna get it wrong at some point.

• 18:27Speaker 04

  Well, because there's so many different factors involved, right? Like, I'm some indigenous tribe, and I worship the Tasmanian devil. That doesn't mean you should or shouldn't bring it back, there's all sorts of other factors. We're gonna have to think through that at a very, because the power that you're bringing to the table here is something that we've never seen in the history of humanity.

• 18:48Speaker 00

  Yeah, yeah, I mean, it is quite-

• 18:49Speaker 04

  You're like a walking singularity.

• 18:51Speaker 00

  Yeah, we are, we do, I think that society doesn't fully understand, I mean, they all saw Jurassic Park, and I think that they've all heard, like, Ian Malcolm, like, talk about it, but I do think he was really right. Like, I do think that the technologies that are being developed with the kind of intersection of synthetic biology, compute, AI, and then eventually quantum, will be more powerful than any weapon system that's ever been created.

• 19:21Speaker 01

  Ben, we talk about solving everything, we talk about, you know, math is cooked, physics is next, chemistry and biology. Is there an inflection point, a singularity in biology, where all of a sudden, there is a complete knowledge base of all the ingested DNA, all the ingested phenotypes, and you can literally design an organism-

• 19:41Speaker 00

  You can have like, the CAD software for biology.

• 19:43Speaker 01

  You can design, you can prompt-

• 19:45Speaker 00

  Yeah.

• 19:45Speaker 01

  "Give me an animal that does this."

• 19:48Speaker 00

  Yeah, I think that DNA synthesis isn't quite there yet.

• 19:51Speaker 01

  But project for me here.

• 19:53Speaker 00

  Yeah, yeah, yeah. So I think that world is less than 10 years out.

• 19:57Speaker 01

  Okay. All right, so you can prompt your favorite Pikachu or animal in within 10 years?

• 20:02Speaker 00

  It doesn't mean whoever owns those technologies should do it for you, but I do think that the technologies of being able to engineer key phenotypes on base-level organisms in different clades, and be able to synthesize them, or multiplex engineer them, and then grow them ex utero, is within a decade.

• 20:19Speaker 01

  Okay, ex utero.

• 20:20Speaker 04

  Within a decade.

• 20:21Speaker 01

  Talk about, talk about your, what's that?

• 20:23Speaker 04

  Within a decade.

• 20:24Speaker 01

  Within a decade.

• 20:25Speaker 04

  Holy shit.

• 20:26Speaker 01

  Can you make it-

• 20:27Speaker 04

  This is unbelievable.

• 20:28Speaker 00

  Well, let me, let me give you a current curve, and this doesn't obviously mean that it's gonna continue on this curve. But, you know, we were taking victory laps at 20 edits delivered, and I think that 99% of biopharma and, I'd say 99% of biopharma and academia would do that today. We are delivering 300-plus, at 90-plus percent efficiency, consistently.

• 20:54Speaker 00

  Right? That was a year ago.

• 20:55Speaker 04

  Wow.

• 20:56Speaker 00

  We're now testing thousand.

• 20:58Speaker 04

  So that's an exponential growing curve.

• 21:00Speaker 00

  That doesn't mean it's going to continue, right? We're testing thousand curves. We're working, we're a thousand edit deliveries right now. Doesn't mean it's going to work, but we're working on it.

• 21:08Speaker 02

  Tripling year-over-year base edits?

• 21:10Speaker 00

  We don't know if it's going to work, but we are.

• 21:12Speaker 02

  But you think it might.

• 21:13Speaker 00

  It could. Early indicators have low efficiency, but it's working. But there is a point where large cargo swaps with DNA synthesis is just better. Unfortunately, the people in that category don't really have a business driver to synthesize DNA after a certain scale. So we just started doing that internally.

• 21:33Speaker 02

  So doing the math, tripling year-over-year, you're at a thousand base edits right now? That gives you like 12 years?

• 21:39Speaker 00

  We are consistently north of 300. We're testing 1,000. I don't want, I think it's highly likely we will get that working.

• 21:46Speaker 04

  What's the point at which it kind of really goes crazy and you can do whatever you want?

• 21:50Speaker 00

  Well, I think the synthesis is going to, I think synthesis will replace multiplex editing faster.

• 21:55Speaker 01

  Right, so basically a machine that generates the, you know, the gigabase code you want.

• 22:00Speaker 00

  I think that's high, I think that has a higher likelihood of success faster.

• 22:04Speaker 02

  Okay.

• 22:05Speaker 01

  So Ben, you've come up with the artificial egg. Not the kind you eat, but the kind that gives birth to an avian species. How far are we from a lady here in the audience, a young lady or older lady in the audience, having a baby in an artificial womb? A human?

• 22:21Speaker 00

  Well, you have, from a technology perspective, I think that's a very different answer than a societal and acceptance and ethics and regular.

• 22:30Speaker 01

  Okay, okay, so let's talk about an artificial womb for a mammal.

• 22:33Speaker 00

  Yeah, I think within 24 months, we will, Colossal will birth animal, mammals, fully ex utero.

• 22:42Speaker 01

  From gestation through delivery?

• 22:43Speaker 00

  Yeah, that never went into a surrogate.

• 22:45Speaker 01

  Wow.

• 22:46Speaker 02

  Wow.

• 22:47Speaker 01

  That's pretty amazing.

• 22:48Speaker 00

  Yeah.

• 22:48Speaker 02

  That's wild.

• 22:50Speaker 00

  Hopefully, hopefully sooner, but I think that 24 months is highly likely.

• 22:56Speaker 04

  Wow. I need to ask a quick question.

• 22:58Speaker 01

  Yeah.

• 22:59Speaker 04

  Just show of hands in the audience, is your mind blown? Like, okay, just checking, okay, got it.

• 23:05Speaker 01

  Yeah.

• 23:05Speaker 04

  Make sure I'm not alone here.

• 23:07Speaker 01

  So what's the iPhone moment in, in Colossal here? Is it the woolly mammoth stepping onto the stage? Or is there something else that like?

• 23:16Speaker 00

  I think that, I think it's, I think.

• 23:18Speaker 01

  A WTF moment?

• 23:19Speaker 00

  I think, well, I mean, I think we've had a little bit of those already, but I think that.

• 23:24Speaker 01

  You have.

• 23:25Speaker 00

  I think the next major inflection points are when we show the world the next extinct species, right? Like, I think always that kind of, in that kind of zero to one.

• 23:34Speaker 01

  That's next week, when is that? Just kidding.

• 23:37Speaker 00

  Coming soon. So, so I think, I think that showing another extinct species back through precision gene editing, number one. Number two, I think that mammalian artificial development and gestation is number two. And then, you know, we are working on some things that we haven't shared yet that I think are equally as interesting to like dire wolves, so we have some more surprise and delights, if that surprised you and delighted you. If that surprised and scared, well, then we have that for you too, so.

• 24:12Speaker 02

  Can I ask you about the dataset actually? So, so, you know, protein folding just really snuck up on everybody.

• 24:16Speaker 00

  Yeah, yeah.

• 24:17Speaker 02

  Like solved overnight.

• 24:18Speaker 00

  Yeah.

• 24:18Speaker 02

  Then just a total goldmine of change for all of biotech. And my daughter uses it every single day.

• 24:24Speaker 00

  Yeah, we use, I mean, yeah.

• 24:25Speaker 02

  Massive. So the equivalent, the genotype to phenotype mapping problem where you say, okay, this sequence produced, oh, that's Alex Wissner Gross, okay, this sequence, oh, that produced Salim, great. This is, oh, that's a Dodo bird, okay.

• 24:38Speaker 00

  I love this final jump there.

• 24:41Speaker 02

  Just a couple of.

• 24:41Speaker 00

  We'd love that jump, by the way.

• 24:44Speaker 02

  So is there a point where, given the dataset you're accumulating, you can interpolate and you can say, okay, now I don't have to create it, I know exactly what would come out?

• 24:51Speaker 00

  So, so we're doing it on a, from a product perspective, we're doing it on a species basis currently, but we're trying to extrapolate to large clades of animals. So like sizing's a big one, right? So if you go, if you're taking, like, our model species that we're working with for the Tasmanian tiger is, or thylacine, is a fat-tailed dunnart, and it's a 1,500x fold from a marsupial mouse to a marsupial wolf, right? So understanding that and extrapolating that and how that, whether, what regulates that, not just the genes, but how and when it regulates in development, how does that transfer to like, you know, can you make a killer whale the size of, you know, your pet goldfish?

• 25:33Speaker 00

  Probably not, but you could probably scale within certain levels of function. If you look at certain species like dogs and also certain, certain species groups of birds, they have tremendous scale functions, right, which are larger than 1,500.

• 25:47Speaker 02

  Yeah.

• 25:48Speaker 00

  And so, so we're 1,500x. So, so we're looking at it on a per, from a non-trait engineering perspective, but from a purist perspective in de-extinction to look specifically at the genes that drove X, Y, and Z. But separately, we are then trying to extrapolate that on a clade basis so that we can say, okay, how can we affect sizing even within some marginal, you know, 20, 50% offshoot within other species? So I think that it's, it's likely that like coat, coat color, sizing, you know, placate, like things that form skin, scales, feathers, all of that will be highly measurable.

• 26:28Speaker 02

  Yeah.

• 26:29Speaker 00

  And be able to be inducible very quickly.

• 26:32Speaker 02

  Interesting, so you can, all right.

• 26:34Speaker 00

  I don't know about everything, but like, you know, we have a whole AI team that's just working on patterning and stripes. It's actually a really hard problem.

• 26:42Speaker 01

  Tusk, stripes, length of snout.

• 26:45Speaker 00

  Yeah.

• 26:46Speaker 02

  Hair?

• 26:46Speaker 01

  Hair, yes, hair.

• 26:48Speaker 00

  Yeah.

• 26:49Speaker 01

  By the way.

• 26:50Speaker 00

  We get hair requests quite a bit.

• 26:51Speaker 01

  You know, when I took, when Chris and I took our boys down to Dallas to visit, it was a real surprise and delight to see the woolly mice there.

• 26:59Speaker 00

  Yep.

• 27:00Speaker 01

  How many gene edits did that take?

• 27:02Speaker 00

  The first generation, which is what we've shown the public, was eight.

• 27:06Speaker 01

  Yeah, amazing.

• 27:07Speaker 00

  In one delivery.

• 27:08Speaker 02

  Eight base pairs.

• 27:09Speaker 01

  Eight edits.

• 27:10Speaker 00

  Eight edits, so, in one, eight base edits in one delivery.

• 27:14Speaker 01

  Amazing. Let's go to some of the audience questions here. This is from Bruno.

• 27:18Speaker 00

  We may, we may have a, another version at some point that.

• 27:21Speaker 01

  Okay, I can't wait.

• 27:23Speaker 00

  Yeah, that's interesting.

• 27:24Speaker 01

  We'll have you back on Moonshot to talk about it.

• 27:25Speaker 00

  Yeah, great.

• 27:26Speaker 01

  All right, so Bruno asks, must a moonshot tackle one enormous problem?

• 27:30Speaker 00

  We had, we had Shatner there the other day and I was like, fuck, if we should have did a triple.

• 27:34Speaker 02

  A triple, oh, yeah.

• 27:34Speaker 00

  Yeah, like, we made this carrier and tailless, we could have like, gotten like, you know, Shatner very excited about triple.

• 27:41Speaker 02

  Yeah.

• 27:41Speaker 01

  No, the triples, that's right, we need triples, you could bring triples back.

• 27:45Speaker 00

  I think back is the wrong word, but I think we could.

• 27:47Speaker 02

  Forward, bring them forward.

• 27:49Speaker 00

  Yeah.

• 27:51Speaker 01

  All right, so Bruno asks the following of you. Must a moonshot tackle one enormous problem within a single vertical? Or can it be horizontal, addressing a seemingly mundane, everyday need that cuts across many verticals? And we'll ask that of Astro as well, Captain Moonshot, shortly.

• 28:09Speaker 00

  I think it can go across, like, cross verticals, right? Like, but remember, I have ADD, and so like, I think that the, that the lack of focus gives us a larger amount of wisdom across multiple categories, right? And so we look at de-extinction as a systems problem, but that same system modeling that can be used to preserve species, bring back species, can also be used to do all kinds of work specifically in human healthcare. So, so I think that if you ground your fundamentals in what you're trying to build, I think you can apply it to many use cases and it doesn't have to be so narrow that like, if you miss that window, it doesn't have other broader applicability.

• 28:45Speaker 01

  Here's a great question from Teresa. How are you planning the ethical issues in creating mammals ex utero? A mammal has emotional needs and just creating an animal doesn't relieve you of the emotional burden of a living creature.

• 29:00Speaker 02

  That's the same thing, like, if it's born ex utero, do you give it a family to live with or raise it in a?

• 29:06Speaker 00

  So we do a lot, I think most people don't know this because like, you know, the media doesn't always cover all of the stuff that we do. We have a foundation, we open source all of our technologies for conservation, so anybody can use any of our technologies for conservation for free. We have 75 global partners, we're very grateful for them, but we've also funded projects specifically around this, right? So like mammoths and elephants are highly social animals, right? So we're not going to bring back a mammoth, we're bringing back herds of them, we have 16 different lines being worked on at the same time.

• 29:35Speaker 01

  How many?

• 29:36Speaker 00

  We have 16 different lines working.

• 29:37Speaker 01

  No, no, how many total mammoths do you want to bring back?

• 29:39Speaker 00

  Do I want to bring back? Tens of thousands.

• 29:41Speaker 01

  Tens of thousands of mammoths?

• 29:42Speaker 00

  Yeah.

• 29:43Speaker 01

  Wow, in LA?

• 29:46Speaker 00

  They'd have to be Colombian mammoths for here or pygmy.

• 29:48Speaker 01

  I'm gonna steal your line. Mammoth in the room is where do the mammoths go?

• 29:52Speaker 00

  But going back to that, wait, wait, wait, wait. Yeah, I want to answer this because I think it's a really important thoughtful question, right? And so you've had, you've had, you know, California condors, you've had all these different close to extinct species that people work on in the rearing of it. And so we find, while there's a halo effect of the positivity of this for today for elephants, it also has a broader implication for what Colossal is trying to do. We find in Botswana, an incredible group called Elephant Havens, which is working with orphaned elephants, right, that have already been born, not ex-utero, but been born and been abandoned for whatever reason. And they are working to use, they use AI, they use a lot of different tools to figure out how do we,

• 30:34Speaker 00

  how do they create synthetic herds from a very matriarchal society of elephants? Where they, where elephants, where they don't currently get that? How do they rear those elephants and train them to be elephants and also work together in a herd, right? Because that's how elephants behave. Separately, we're funding and doing research in everything from satellite imaging to drones, AI, building programs in different elephant migratory patterns in corridors so that we can understand the social dynamics and hierarchy of moving, right? And so that benefit, all of that technology and that data impacts elephant conservation work today, right? Right? So you don't have like orphaned elephants, you have, you can rewild entire herds.

• 31:18Speaker 00

  But all of that data also informs us how we are going to rear these animals in a, in a way where if they are born ex-utero, how do they grow up in a social dynamic with the right hierarchy?

• 31:29Speaker 01

  Dave, you were gonna say?

• 31:31Speaker 02

  So true story, your guy, George Church, was at a presentation that we had at MIT and the topic was global warming. And he said, well, I have the, you know, I have the cure for global warming.

• 31:41Speaker 00

  Yeah, we have several, but yes.

• 31:44Speaker 02

  We're gonna bring back the woolly mammoth. The woolly mammoth's native habitat is Siberia and northern Canada.

• 31:49Speaker 01

  The tundras.

• 31:50Speaker 02

  The tundras. And back when they were around, there were no trees because the woolly mammoths walk around and knock down all the trees.

• 31:58Speaker 00

  And elephants actually do this in Africa, too. Yeah, yeah. Forest elephants, yeah, yeah. They're incredible at this.

• 32:04Speaker 02

  So we're like, well, what the hell is the connection to global warming? He goes, well, without the trees, the grass grows. The grass actually sequesters more carbon than the trees do.

• 32:12Speaker 00

  Yeah, it's about six times more efficient and a two to three X albedo effect for light reflection to space.

• 32:18Speaker 02

  Yeah, so I think, I don't think you guys checked in with the Canadians to see if it's okay, but you turn on loose, turn on loose in Canada.

• 32:23Speaker 00

  I don't live in the tundra. I'm from India, actually. Seriously, though, where do we build Jurassic Park? So, no, wait, this is, this is a really good point. So in the early days, and I'm a big data guy, so I, most of my background's in software and a little space hardware. But for the most part, I just want to go where the data takes us, right? So you have high conviction, really smart scientists like George, that will say, if you have this mammoth density at these places in the tundra, they'll have this impact on the permafrost, a lowering of six to eight degrees. In the summer months, it only melts so far. So you can extrapolate that out. We have actually done that exercise and it's quite interesting.

• 33:05Speaker 00

  Then, but then it goes back down to a top-down versus a bottom-up approach of how they affect the environment. There's other people in the scientific community, including at Colossal, that think that they will not have that level of impact, right? And so, but the good news is, is that generally speaking, whether they fall on the, what does, how do you solve climate change with mammoths at 10,000 plus mammoths in the Arctic? Doesn't really matter because they have a net positive benefit on the environment in terms of like helping restore that ecosystem. So what I try to do, and Palmer mentioned this in the last thing, is like, how do you get two assholes in a room and get them to agree? Well, it gets extrapolated to like the 10th degree when they're both PhDs. And so, which is like, in my experience, I don't have PhD

• 33:49Speaker 00

  and people think that I have a war on academia at times, but like the pretty hard to deal with people out there or PhDs, in my experience, they actually have a model where I have found though is when you sit them down and tell them that they're both right and you help them walk through that, it actually works. And so what I've said is maybe George is right. That this level of density of mammoths at this, at this long, at latitude, longitude, will have this level of impact, but maybe others are right saying that it will have a positive benefit on the flora and fauna, but it won't cure carbon trees, climate change. Either way, it doesn't really matter if it's having a net positive benefit on elephants today as well as the ecosystem that, of the tundra, which is highly degraded.

• 34:31Speaker 00

  So everyone can agree that the ecosystem sucks and we need to make it better, right? And so, so I've done that, you know, I don't know, I, I don't want to say that George is right, but I'll just say, I've looked at the math and I think George is pretty smart.

• 34:45Speaker 01

  Okay. Ben, you just spun out Astromech, a multi-billion dollar company from the start. What is Astromech doing?

• 34:53Speaker 00

  So we're looking at, so this was kind of a tip from your question. The foundation models and ant models aren't quite looking at the entire tree of life. And they're not like, they're not gonna magically overnight give them a genome and give us an answer. So we are trying to build, like what are kind of inflection, we call them internally inflection models? What are inflection models that can plug into those foundational models? That can say, okay, we've studied and we understand everything about this genome sequence across how it's evolved and more importantly, when it evolved and why it didn't evolve in related clades. And then we're looking at everything from like climate, like what spurred that? Because we want to build essentially a prediction model to say, okay, where did that go and why did it go?

• 35:37Speaker 00

  Because I don't think that Astromech's gonna have the like magic, you know, anthropic mythos, you know, four trillion dollar or whatever the latest round is, that solves all things all ways. But what I do think is I think it'll have enough of the unique data sets in how to classify and understand that data set, that it can plug into those so that when you do have global bio vaults and you have millions of samples that you can feed into a mythos, this can be acting like kind of the, or a mythos like competitor, this can be acting as like your traffic control cop of where to go and where to focus.

• 36:09Speaker 02

  Yeah.

• 36:10Speaker 01

  Yeah, I'm gonna synthesize a couple of questions here. What's the biggest problem you wish people were working on, the biggest moonshot that people are not right now?

• 36:18Speaker 00

  I think, I think that the, we are going to lose half of biodiversity in the next 25 years. And everyone who loves us and hates us agrees with that. So we need to do something about it. Governments, like this is not going to be solved by a zoo or a nonprofit. We have to have billions of dollars of federal funding across multiple governments working together to at least back up life. We back up everything else. We back up our, you know, we back up our photos, we back up our texts, our emails, we back up everything. But ultimately, I think most people back up their texts and emails, but some people do signal.

• 36:57Speaker 00

  But like for the most part, though, I really think that we have got to right now invest in infrastructure to back those species up. Because if you don't like, when we lose those species, we're gonna have negative impacts on ecosystems. When we lose those species, we're gonna have negative impacts in the food web for the animals. But so if you like ecosystems, you should back it up. If you don't like ecosystems and you hate the environment, but you like animals, you should back it up. If you hate the environment and animals, but you like fucking humans, you should back it up. Because there's data in there that will help humanity.

• 37:31Speaker 01

  I just, as a quick aside, you know, one of my companies with an amazing CEO, Bob Horry, called Cellularity, we have something called Life Bank USA that when your baby is born, you store all the placental cells.

• 37:45Speaker 00

  Yep.

• 37:46Speaker 01

  And you've got basically the original boot desk. You've got your kid's stem cells, T cells, natural killer cells, everything. And it's like if your baby came with an extra set of organs, would you throw them away? Probably not. But why throw away, you know, the placenta is the 3D printer that creates the, creates the baby. So, I mean, this kind of envisioning of safety, of backups is amazing. So this is what, this is what you're doing right now in Dubai?

• 38:13Speaker 00

  We're doing it in Dubai. We're, we just announced a partnership with US Fish and Wildlife here as part of Secretary of Interior's directive on backing up the natural resources that make America great. So we're doing that now here domestically. We have two other governments we haven't announced yet that will announce when they want to announce that are part of our framework. And then it's also kind of like what George and I also talk about with open source. It's completely open. So we, any nonprofit, any academic institution, any big foundation, any private individuals, to anybody in Palmer's secret billionaire boys' club that wants to throw money at this.

• 38:51Speaker 01

  Everyone wants to be boys now. Are you in the B-Boys group?

• 38:53Speaker 00

  So, so the, anybody that like, I'm not in any secret chat group.

• 39:00Speaker 04

  I have a quick question.

• 39:01Speaker 01

  All right, let's close it out with your quick question.

• 39:04Speaker 04

  I want to be Ben Lamm with the mind as creative and crazy as yours to envision these things. How do I go about doing that?

• 39:12Speaker 00

  Oh, how you do what?

• 39:14Speaker 04

  How do I go about?

• 39:15Speaker 01

  How did you become?

• 39:16Speaker 04

  How do I become, take on the mindset that you have to apply technology as incredibly creatively as you have done?

• 39:24Speaker 00

  So, well, it's very kind. I think that, I'm very curious, right? So, I like to just learn new things. And I think in a world, especially with AI, where everyone's got every answer to their tool, at their fingertips, I'm pretty good at telling people what I don't know. So, I think I kind of take a childlike wonder to things and just say, hey, I don't know this, but I'm sure I could go find the answer. And what I've also found, which most people, this is big advice that I'd also give everyone, people will help you. Like, I am an optimist. I believe in technology, but I believe in humanity first, and people will help you. So, like, I don't think people ask for help enough. I think everyone's like walking and on subways and shit, looking at their phones, but if you just look out for a second and ask for help, people will help you.

• 40:08Speaker 00

  And so, it's like, when I don't understand something, sometimes I will call people in this, like, some of our top advisors at Colossal are advisors, because I just cold emailed them, like, hey, I don't understand this, my teams are telling me this, you're the world's expert in this, can you have a meeting with me? They have no, this woman or man has no reason to talk to me, right? But they'll take the call. And so, I feel like I just have this general curiosity wrapped with it.

• 40:31Speaker 01

  People like you, they want to help you.

• 40:33Speaker 00

  No, I think that they'll like everybody, like, I really do. I think you can just, if people ask for help, nine out of 10 times, I believe in humanity, they will help you.

• 40:40Speaker 01

  A big, a quick, give it up for that, right? A curiosity mindset, a purpose-driven mindset, and a quick question from Kathy Wood backstage, who said, yesterday Anthropic, you know, set up their, announced their wet labs that were able to create something like CRISPR-like. Does this light a fire in your work? Or does it, you know, kill forward momentum?

• 41:05Speaker 00

  So, I think it's massively validating, right? Like, it's a great question, Kathy's great. I think it's really important, right? Like, there are so many problems to solve in biology, these technologies are, we are just, like, we haven't even opened the door, like, the door's barely cracked, barely, barely cracked open. I think that what they announced yesterday, like, people see that and say, oh my gosh, biotech's going to be dead because it should be Anthropic in their labs. That's not true, right? That's just not true. And so, I think that that was a huge watershed moment for the industry, to show that, like, you have the AI companies that understand, and yes, Dario has a background in biology, but, but you have the AI companies that, that understand that that will be one of the most accepted use cases and deployments of their technology, and that people want

• 41:48Speaker 00

  to have healthier families, healthier, longer lives, right? So, it was a great thing for the society.

• 41:53Speaker 01

  Really short.

• 41:54Speaker 04

  Do you have a P doom, or do you need to even think about the question?

• 41:58Speaker 00

  You know, I'm an optimist. Like, I, I, I'm an optimist. Like, I don't agree with, you know, I, I think we're going to have some scary moments.

• 42:08Speaker 04

  Of course.

• 42:09Speaker 00

  And I think that's okay, right? Because I do believe in human ingenuity to work through those problems, right? But I think that you've got to have a conversation. I do think that the media is overselling that a little bit right now, to, to, to be kind. But I do think that, like, you know, we, we really will get there, and we're going to have a couple scary moments, but it's like, you have turbulence on planes and everyone still lands, right? Like, that's okay.

• 42:34Speaker 01

  All right, welcome to the Oscars of optimism. Give it up for Ben Lamm.