WEBVTT
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Hello everyone And welcome to the switch statement podcast It's a podcast for investigations into miscellaneous tech topics
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This is episode seven of The Coming Wave by Mustafa Suleyman We'd love to hear from you.
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Send your comments and feedback to team@tkp.co.
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Hey, John.
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How are you doing?
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Hello, Matt.
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I'm doing very, very well.
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How are you doing?
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Oh, very, very well.
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That's, that's great.
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Um, you know, I'm, I'm getting by.
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I'm getting by
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You staying cool?
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Oh my God, dude, it's a million degrees outside
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degrees.
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It's crazy
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Wow.
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You're just gonna, you're just gonna correct me like that?
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Well, 100 might as well be a million
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my dad and I, been working on my car actually.
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It's got that's a long story, but, we wanted to beat the heat.
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We went out like quarter to 6:00 AM, and we're like,"All right, it's gotta be like pretty mild at
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Yeah, it was like already 85 degrees
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you swing the door open, you just get hit in the face, and you're like,"Nope,
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Yeah
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It's not nice out."
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Yep.
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My wife and I planned on going for a bike ride this morning, and we went out and we were like,"Uh..." And I actually ended up going for a run because I,
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Oh my God,
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wanted to get some physical.
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Yeah.
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Yeah, it was rough.
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I kinda like running in the heat, though.
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It feels very, like, you know, it just feels like all the toxicity is sorta leaving your body.
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It's probably I'm just delirious, but
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You sweat it out.
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who knows?
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I mean, maybe before long we'll be able to bioengineer a molecule that you can take so you're not as hot.
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You can just don't, or you don't feel the heat.
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Yeah.
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Where's the, where is the GLP-1 for not being hot?
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Yes.
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I think they'll have that soon.
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I think they're probably actively working on that.
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They-- I feel like they have GLP-1s for everything these days.
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It's like you want more energy?
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You want muscles?
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Like, it's kinda crazy.
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They're just coming out of the
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Oh, okay.
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I have always wanted to do that, do a little bit of...
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do a little biohacking.
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but I don't know.
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I kinda wanna see how it I wanna give other people a
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you're a quitter.
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You're a quitter.
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You gotta, you gotta dare greatly
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It scares me.
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I mean, this is why, like, I don't have any tattoos or anything.
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I've always been afraid of, like, permanent, like, body changes, and that's part of what scares me about, you know, doing something like Ozempic.
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Although I did, I did try to get Ozempic, but
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unlabeled Chinese peptides.
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You're not
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Yeah, exactly.
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that into your neck.
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like I have a friend who like does all sorts of stuff, and he's constantly telling me like,"Yeah, you gotta get on the gray market.
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Get some, get some retta." And I'm like,"What are you
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is he, um, would you say he is, is thriving as a result?
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Well, he's not necessarily thriving, uh, but I don't know if I don't know if him not, you know, thriving is related to to that.
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But I mean, he's thriving in a way.
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Like, I guess it just depends on your definition of thriving.
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He looks good.
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You know, he's
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Okay
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He, you know, he's got a nice body.
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But anyway, he's pretty jacked.
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Uh, anywhos, so we're talking about biology.
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We're talking about the technology of life
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Yeah, there's a bunch of people who are doing things that are a little, little more, uh, I don't know, have a little more gravitas than making you, making random dudes jacked.
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Uh, so yeah, we got them curing blindness.
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This is actually something I wanted to talk about.
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It's like, you know, you don't really think about it, but biology somehow was able to produce a...
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Like, some substance, like, in your, in your fucking head that is, like, jiggling whenever light hits it.
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It's unbelievable
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Oh, dude, it's crazy.
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I mean, I've talked about this book a few times.
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Song of the Cell, I think it's called.
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Yes
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Um, that book goes into these really in-depth...
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Well, I mean, I say in-depth, uh, that's a relative term'cause it was, you know, for mass consumption or whatever.
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But just these, like, brief discussions about how complex the body actually is.
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Uh, you know, for something so simple as, like, you eating an apple or something, just, like, talking about all the mechanisms that are taking place while that apple is being, you know, consumed by the various parts of your body.
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It's absolutely astounding what is actually happening within your body, all these different chemical reactions, and yeah, it's just insane
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Well, this is interesting'cause I have kind of a, I think a very, um, a very controversial opinion, which is like, you know, you talked about the complexity of, of life and like obviously in a lot of ways, like that's necessary.
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Like, there's just no other way to do it.
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But like, I'm really excited about, you know, like the...
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There's like 17 different chain reactions that need to happen in order for like something to happen in your body, and it's like, can we get that down?
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Like, that sounds overcomplicated.
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Like, is there any way we can refactor that biological pathway?
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Dude, it, it's funny you call this out'cause I feel like biology in a lot of ways is like the very definition of tech debt.
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Like, biology does not refactor.
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Evolution is not a refactoring process.
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Like, it's just like add on, you know,"Oh, you got an appendix?
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Eh, let's
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You just bolted.
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Oh, it's fine.
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Yeah, we'll leave it there.
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It's not, not hurting anything, so,
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you don't need that.
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Nipples on a guy?
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Who cares?" It's just like...
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But
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no, I mean, as long as that guy isn't getting killed by his nipples, you know, life, life's not worried about it.
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Exactly.
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Exactly.
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But yeah, so I, I mean, you mentioned he discusses, there's a brief section of the book where he's talking about these diseases that are just getting cured.
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I mean, this guy's blindness getting cured.
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And it just so happened that at the time there was this headline about sickle cell being treated, the first time sickle cell was ever treated.
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And, uh, I don't think Mustafa mentioned this in the book, but I just thought it was interesting that, like, as I was reading this, there was also this, you know, amazing headline.
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I mean, sickle cell is this, like, debilitating disease.
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It's been around for hundreds of years, and it's like we just treated it.
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It's amazing
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Yeah.
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Unbelievable.
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but he does start to go into, like, maybe a li- and I guess this kind of dovetails with your peptides, conversation.
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He goes into some of the, like, seedier underbelly where, like, you know, we might have to worry about athletes, like, what are they taking?
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Well, and actually, in a way, I don't think they had the...
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What was it?
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The, like, unrestricted games or, like, the un- There was that, like,
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Oh, yeah
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that was dedicated to, like, you could just take whatever steroids, uh, or the enhanced
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Enhanced games.
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Yeah, that did not go over well
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but I guess Mustafa Suleiman couldn't, uh, pre-predict that humanity was gonna le-really lean into, uh, gene doping.
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Yeah, I mean, I'll be honest, like I was-- I, I mean, conceptually I'm interested in that.
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Like, I mean, I don't want people to like destroy their bodies or whatever, but it is interesting to me.
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It's like, you know, if you just allow someone to take whatever drugs, like h- what is the pinnacle of, you know, human ability?
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Yeah.
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And that's ostensibly what that was supposed to be, but I guess they didn't even break any world records, right?
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Well, a lot of the, a lot of the people who won the, or like who won were natties.
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Like they were just training for the Olympics anyway, so th- and they just weren't even doping at all.
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Uh, which, like is that a controversy?
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It's like,"Ugh, this guy didn't even take anything.
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Like get him out of here."
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Yeah, that's kind of amazing
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there's an anti-doping scandal.
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But, did you see this part where they talked about the first gene-edited baby being...
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I don't know if you had these, this in your notes, but like there was the guy, this guy in China who
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Yeah, the rogue.
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Yes
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And he, uh, he was like,"All right, I'm just gonna edit, edit the genes of these, these two babies." And like the whole community was like,"Well, d- like bro, like what are you doing?
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Like d- you're not curing a disease.
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You did a shitty job." You know, which feels a little bit like it's kind of the least important aspect of this whole thing.
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But,
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This is the, uh, Lulu and Nana born in 2018.
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You know, I meant to look up, like, how are they doing?
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How are Lulu and Nana?
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They're eight years old at this point, right?
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Yeah, I guess so
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I guess they're still kicking about.
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Maybe they're, maybe they have, like, superpowers
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flourishing.
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Yeah.
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Are they, like, flying around yet or what?
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But yeah, I mean, this guy, he was basically ostracized from the scientific community.
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Like, like you said, he did this rogue...
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You know, he didn't consult with the community.
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He didn't, publish white papers beforehand or anything.
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He just sort of, like, went ahead and did it.
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And, uh, yeah, so not necessarily the way that we want these things to be happening, a milestone nonetheless, I guess
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it's interesting because I get-- I think back to what he was saying about technology not being able to be stopped, and this almost feels like a nuclear, you know, like a nuclear technology situation where, yes, the access to these, the, like, component technologies is, expanding every day.
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It's making, getting cheaper and what have you.
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But, I, I don't know that we're gonna have to worry about, like, backroom genetically modified babies for li- for the foreseeable future.
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Maybe I'm wrong about that.
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But it feels like there is, like, society as a whole...
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It's difficult enough, and society has really, like, kind of spoken in terms of, like, it's like,"No, this shit is not okay." So, like, maybe, I don't know.
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hopefully it's, not something we need to worry about.
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I, I'd be inclined to agree with you, but I do think it's one of those things where there is a demand.
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You know?
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It's like if you're-- Say you're about to have a child and you know your child is gonna be genetically predisposed to having some disease, and, you know, you know some fringe doctor who's willing to perform some sort of procedure that's not necessarily, uh, you know, sanctioned by the,
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Я
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the larger medical community.
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Like, as a parent, I feel like there's a tremendous demand or a tremendous desire to do something like that.
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So I think, it's like I agree with you that this is sort of like a very difficult technology to even unlock, and the only people who, really have access to it are like, you know, they're doctors.
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They're like these medical professionals who aren't gonna just throw away their whole career to like do some random gene editing.
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Aside from, uh, what's his...
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I, I don't even know if he na- he's named.
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Yeah, I didn't write his name down
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the scientist.
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I don't think they say it in the book.
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But I think where it differs from nuclear is that there is a demand for it.
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Like, even within individuals in society, there's this demand, which I think is kind of missing for nukes.
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It's like the only one-- The only people who demand nukes are, like, heads of state or, like, terrorists or whatever
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Yeah, exactly.
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Like your typical hyper-competitive parent doesn't have much of a need for, for a nuclear weapon, whereas they may, like, I don't know, the Joneses down the street, they, you know, you heard whispers that they, I don't know, went to some back room, to get modific- an illegal genetic modification,
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Dude,
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have to too
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some of my colleagues at work seem genetically modified to me.
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They're just like ultra smart and kind of like, yeah,
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They're just like perfect hu- human beings.
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a little factoid that I kinda loved.
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DNA is the most efficient storage mechanism we know of.
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All of the world's data could be stored in one kilogram of DNA.
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this, goes back to something you said in the l- in the last episode, I think, where you were talking about how biology sort of works on the atomic level.
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So it's like, this is why DNA is so efficient.
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It's like literally just these individual molecules that are chained together.
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And so yeah, dense, uh, very information dense
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It, it is, it really is unbelievable.
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But, but Yeah, so he segues into the last part of this chapter is where he starts to get into the synergy story of like, well, the fact that we now have all these expanding AI capabilities are actually gonna dovetail in a synergistic way with, with these biological technologies
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Yeah, he talks about this really cool contest, which this actually hearkens back to something you said in another episode where you called out the woman who started the, like, image recognition con...
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Yeah, Fei-Fei Li, uh, which I thought was really cool that you sort of called her out and gave her credit.
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This is another contest that, you know, it's called the Critical Assessment for Structured Prediction.
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Man, it's hard to read these acronyms.
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Uh, predicting protein folding.
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Yeah
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so CASP is what, you know, the, the...
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That's the acronym.
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Basically, what CASP is, is the con- it's a contest based on, uh, telling how a protein will fold.
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So it sort of gives you this, like, recipe for a protein or whatever, and you have to give back the answer of like,"Okay, the protein will fold in this exact manner." And we've s- we've discussed this on the podcast before, but this is just a property of proteins.
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It's like,
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Right
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like there's millions of proteins.
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It's, uh, it's ridiculously complicated, and each one folds in these, like, very unique ways.
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And this actually, like, this is the reason some biology behaves the way it does because of the structures of these proteins.
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It's like they interlock in very particular ways, which, you know, causes certain things to happen in your body.
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and historically, it was very difficult to know how these proteins would fold.
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It was a very...
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You know, the only way to really do it was, like, these very brute force approaches.
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There's no, like, you know, simple, like, efficient algorithm for doing this.
00:13:59.831 --> 00:14:05.654
so yeah, that's why they created this contest to sort of see, who could predict these, these foldings.
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And similar to the last contest that we discussed, a new kid on the block, AlphaFold, came along and just absolutely crushed the competition.
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And
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the first year that they were in the competition, they just, like, rock up like,"All right."
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Yeah.
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Yeah.
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So they just waltz right in and, like, just demolish everyone else and drop the mic, and it's this amazing event.
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And, and Mustafa was a part of it.
00:14:33.190 --> 00:14:40.692
I mean, AlphaFold came out of DeepMind, so, you know, Mustafa Suleyman and Demis Hassabis, they were the co-founders of DeepMind at the time.
00:14:41.150 --> 00:14:47.831
But similar to the image recognition, jump in ability, it was all based on neural networks.
00:14:48.211 --> 00:15:01.511
You know, they, they were using an underlying neural network that they had sort of learned based on all these training examples of various protein foldings, and this network was the thing that was demolishing the competition.
00:15:01.511 --> 00:15:12.418
The competition were these more sort of, I always wanna say conventional algorithms, you know, these more brute force style algorithms taking into account all the various rules that we understand with chemistry.
00:15:12.754 --> 00:15:15.224
and those were not as effective as a neural network.
00:15:15.491 --> 00:15:17.292
Yeah, it's, it, it's just wild.
00:15:17.292 --> 00:15:27.918
And so the, you know, the long and the short of it is they literally stopped running, the CASP contest by the next year, because it was just so good that it was like, well, it's done.
00:15:27.928 --> 00:15:29.798
You know, the problem is, is solved
00:15:29.850 --> 00:15:50.490
essentially became a solved problem, which is truly, I mean, people don't talk about this, but this protein folding thing I think is a massive milestone in this biological hacking because as I mentioned, like proteins are the, are what underpin all of the interactions that are taking place in your body.
00:15:50.850 --> 00:15:53.250
It's like the reason things are happening the way they
00:15:53.321 --> 00:15:57.100
The reason your body does anything at all, it's all proteins,
00:15:57.184 --> 00:15:58.205
all proteins.
00:15:58.264 --> 00:16:00.263
So yeah, I mean, this is huge.
00:16:00.292 --> 00:16:13.797
and yeah, just like you're saying, so AlphaFold dominated in year one, and then by year two they had AlphaFold 2, I guess, which had like a 99% accuracy with, you know, solving these protein foldings, so they just cr- they just killed the competition
00:16:13.956 --> 00:16:25.325
yeah, and so DeepMind basically just, like, they folded, like, 200 million, like, basically all known protein sequences, and then they just, like, uploaded it for everyone to, to see.
00:16:25.325 --> 00:16:31.076
And I think this is exactly to your point, where it's like we don't even have any idea what the, like, what the long term...
00:16:31.076 --> 00:16:34.275
'Cause all of this stuff, all this research takes a long time to do.
00:16:34.316 --> 00:16:36.576
Like, there's just a bunch of hoops you have to jump through.
00:16:36.576 --> 00:17:08.248
So, there's such a lag behind, like, where the, like, the results take behind actually getting a candidate that I think, like, maybe, like, a year or, like, however long the, drug approval cycle is, like, we're-- I think we're probably gonna see some cr- a crazy, like, uptick after, you know, the uploading of all of those, of those protein sequences, those folded sequences by, by AlphaFold to, uh, that we're, we're gonna just see these amazing new, new treatments
00:17:09.049 --> 00:17:09.970
Dude, I think you're right.
00:17:09.970 --> 00:17:11.009
I think you're absolutely right.
00:17:11.289 --> 00:17:15.038
Another thing I'm excited about is, uh, just Demis.
00:17:15.118 --> 00:17:32.744
Demis, you know, ch- uh, the head of DeepMind, he is sort of, uh, like a somewhat mysterious figure even within Google, and a lot of people talk about how he's very focused on disease, you know, sickness, you know, human frailty, all those things.
00:17:32.884 --> 00:17:36.474
And he essentially has carte blanche within Google.
00:17:36.914 --> 00:17:37.565
You know, it's Demis.
00:17:37.615 --> 00:17:40.025
You're not gonna, you're not gonna, like, give orders to Demis, right?
00:17:40.025 --> 00:17:42.005
So he's able to do whatever he wants.
00:17:42.276 --> 00:17:50.804
he has tremendous resources at his disposal, and he's an absolute genius, and that is what this guy is working on, is like he wants to fold proteins.
00:17:50.804 --> 00:17:52.144
He wants to solve disease.
00:17:52.511 --> 00:17:53.862
Solve disease.
00:17:53.932 --> 00:18:05.122
That, like the way that he f- talks about it is almost alien because it's like he literally, you know, like the other problems that he has solved, he's like,"No, we're gonna do it all." Like,"We're gonna..."
00:18:05.231 --> 00:18:05.382
Yeah.
00:18:05.980 --> 00:18:07.000
it's just wild
00:18:07.422 --> 00:18:13.752
It is wild, but it, it's weird how it doesn't even sound that crazy because we really are.
00:18:13.752 --> 00:18:18.313
It's like we- we're at this confluence of technology, large language models help us research.
00:18:18.563 --> 00:18:20.423
We've figured out all the protein folding.
00:18:20.423 --> 00:18:21.212
We have CRISPR.
00:18:21.222 --> 00:18:22.403
We can edit DNA.
00:18:22.606 --> 00:18:27.797
So we really are at this, you know, feels like we're sort of on this threshold, this confluence of technology,
00:18:28.574 --> 00:18:29.034
Yeah
00:18:29.346 --> 00:18:30.317
unlock some of these things.
00:18:30.653 --> 00:18:32.074
I think, I think you're right.
00:18:32.334 --> 00:18:42.017
And speak, speaking of unlocks, this, towards the end of this chapter they describe something that sounded like it came out of a movie, but I guess is real.
00:18:42.136 --> 00:18:50.855
There's this company, there's this company called Cortical Labs, and e- evidently they grew a brain in a vat and taught it to play Pong
00:18:51.309 --> 00:19:01.289
Dude, we're gonna have, we're gonna have biologic-- Like, we- we're at the beginning of this, of this interface between, you know, traditional computing and neural computing.
00:19:01.819 --> 00:19:03.339
It's pretty wild.
00:19:03.420 --> 00:19:04.349
Pretty wild to think about.
00:19:04.694 --> 00:19:05.455
Wild indeed
00:19:05.877 --> 00:19:06.337
all right.
00:19:06.337 --> 00:19:16.358
Well, I think, um, I think we can leave it there, and then we'll tune in next week for The Wider Wave, chapter six
00:19:16.689 --> 00:19:18.848
The wider wave sounds exciting
00:19:19.200 --> 00:19:19.589
All right.
00:19:19.619 --> 00:19:20.420
Well, I'll see you there, John
00:19:21.096 --> 00:19:21.527
See you, Matt
00:00:08.329 --> 00:00:15.048
Hello everyone And welcome to the switch statement podcast It's a podcast for investigations into miscellaneous tech topics
00:00:15.949 --> 00:00:21.381
This is episode seven of The Coming Wave by Mustafa Suleyman We'd love to hear from you.
00:00:21.591 --> 00:00:25.460
Send your comments and feedback to team@tkp.co.
00:00:31.236 --> 00:00:31.896
Hey, John.
00:00:32.106 --> 00:00:32.436
How are you doing?
00:00:33.338 --> 00:00:33.819
Hello, Matt.
00:00:33.819 --> 00:00:35.189
I'm doing very, very well.
00:00:35.189 --> 00:00:35.768
How are you doing?
00:00:36.542 --> 00:00:38.082
Oh, very, very well.
00:00:38.383 --> 00:00:39.402
That's, that's great.
00:00:40.052 --> 00:00:43.003
Um, you know, I'm, I'm getting by.
00:00:43.012 --> 00:00:43.662
I'm getting by
00:00:43.719 --> 00:00:44.389
You staying cool?
00:00:44.780 --> 00:00:47.509
Oh my God, dude, it's a million degrees outside
00:00:47.965 --> 00:00:48.844
degrees.
00:00:49.034 --> 00:00:49.655
It's crazy
00:00:49.985 --> 00:00:50.305
Wow.
00:00:50.473 --> 00:00:53.037
You're just gonna, you're just gonna correct me like that?
00:00:54.274 --> 00:00:56.154
Well, 100 might as well be a million
00:00:56.374 --> 00:00:59.088
my dad and I, been working on my car actually.
00:00:59.088 --> 00:01:02.401
It's got that's a long story, but, we wanted to beat the heat.
00:01:02.420 --> 00:01:07.899
We went out like quarter to 6:00 AM, and we're like,"All right, it's gotta be like pretty mild at
00:01:08.010 --> 00:01:09.870
Yeah, it was like already 85 degrees
00:01:10.203 --> 00:01:13.272
you swing the door open, you just get hit in the face, and you're like,"Nope,
00:01:13.527 --> 00:01:14.016
Yeah
00:01:14.230 --> 00:01:15.200
It's not nice out."
00:01:15.486 --> 00:01:15.757
Yep.
00:01:15.826 --> 00:01:24.605
My wife and I planned on going for a bike ride this morning, and we went out and we were like,"Uh..." And I actually ended up going for a run because I,
00:01:24.665 --> 00:01:25.286
Oh my God,
00:01:25.486 --> 00:01:26.786
wanted to get some physical.
00:01:27.096 --> 00:01:27.256
Yeah.
00:01:27.665 --> 00:01:28.436
Yeah, it was rough.
00:01:28.906 --> 00:01:30.225
I kinda like running in the heat, though.
00:01:30.225 --> 00:01:35.944
It feels very, like, you know, it just feels like all the toxicity is sorta leaving your body.
00:01:35.954 --> 00:01:37.694
It's probably I'm just delirious, but
00:01:37.927 --> 00:01:38.867
You sweat it out.
00:01:39.028 --> 00:01:39.489
who knows?
00:01:39.489 --> 00:01:46.929
I mean, maybe before long we'll be able to bioengineer a molecule that you can take so you're not as hot.
00:01:47.239 --> 00:01:49.349
You can just don't, or you don't feel the heat.
00:01:49.789 --> 00:01:49.998
Yeah.
00:01:49.998 --> 00:01:55.269
Where's the, where is the GLP-1 for not being hot?
00:01:55.472 --> 00:01:56.313
Yes.
00:01:56.423 --> 00:01:57.912
I think they'll have that soon.
00:01:57.923 --> 00:02:00.637
I think they're probably actively working on that.
00:02:00.677 --> 00:02:03.206
They-- I feel like they have GLP-1s for everything these days.
00:02:03.436 --> 00:02:04.637
It's like you want more energy?
00:02:04.727 --> 00:02:05.596
You want muscles?
00:02:05.816 --> 00:02:07.007
Like, it's kinda crazy.
00:02:07.066 --> 00:02:07.727
They're just coming out of the
00:02:07.804 --> 00:02:08.584
Oh, okay.
00:02:08.911 --> 00:02:11.270
I have always wanted to do that, do a little bit of...
00:02:11.320 --> 00:02:12.651
do a little biohacking.
00:02:12.985 --> 00:02:13.975
but I don't know.
00:02:14.252 --> 00:02:18.948
I kinda wanna see how it I wanna give other people a
00:02:19.021 --> 00:02:19.771
you're a quitter.
00:02:19.981 --> 00:02:20.662
You're a quitter.
00:02:20.921 --> 00:02:22.692
You gotta, you gotta dare greatly
00:02:23.639 --> 00:02:24.289
It scares me.
00:02:24.310 --> 00:02:26.919
I mean, this is why, like, I don't have any tattoos or anything.
00:02:26.919 --> 00:02:35.637
I've always been afraid of, like, permanent, like, body changes, and that's part of what scares me about, you know, doing something like Ozempic.
00:02:35.657 --> 00:02:37.997
Although I did, I did try to get Ozempic, but
00:02:38.268 --> 00:02:40.217
unlabeled Chinese peptides.
00:02:40.228 --> 00:02:40.578
You're not
00:02:40.675 --> 00:02:41.444
Yeah, exactly.
00:02:41.548 --> 00:02:42.677
that into your neck.
00:02:42.925 --> 00:02:49.594
like I have a friend who like does all sorts of stuff, and he's constantly telling me like,"Yeah, you gotta get on the gray market.
00:02:49.662 --> 00:02:52.550
Get some, get some retta." And I'm like,"What are you
00:02:52.854 --> 00:02:57.883
is he, um, would you say he is, is thriving as a result?
00:02:58.395 --> 00:03:07.752
Well, he's not necessarily thriving, uh, but I don't know if I don't know if him not, you know, thriving is related to to that.
00:03:07.891 --> 00:03:09.662
But I mean, he's thriving in a way.
00:03:09.731 --> 00:03:12.301
Like, I guess it just depends on your definition of thriving.
00:03:12.472 --> 00:03:13.271
He looks good.
00:03:13.581 --> 00:03:14.042
You know, he's
00:03:14.283 --> 00:03:14.764
Okay
00:03:14.764 --> 00:03:16.283
He, you know, he's got a nice body.
00:03:16.653 --> 00:03:18.911
But anyway, he's pretty jacked.
00:03:19.157 --> 00:03:21.578
Uh, anywhos, so we're talking about biology.
00:03:21.578 --> 00:03:23.518
We're talking about the technology of life
00:03:23.629 --> 00:03:33.009
Yeah, there's a bunch of people who are doing things that are a little, little more, uh, I don't know, have a little more gravitas than making you, making random dudes jacked.
00:03:33.500 --> 00:03:36.939
Uh, so yeah, we got them curing blindness.
00:03:37.240 --> 00:03:39.340
This is actually something I wanted to talk about.
00:03:39.819 --> 00:03:46.397
It's like, you know, you don't really think about it, but biology somehow was able to produce a...
00:03:46.790 --> 00:03:53.550
Like, some substance, like, in your, in your fucking head that is, like, jiggling whenever light hits it.
00:03:54.080 --> 00:03:55.100
It's unbelievable
00:03:55.379 --> 00:03:56.289
Oh, dude, it's crazy.
00:03:56.319 --> 00:03:58.849
I mean, I've talked about this book a few times.
00:03:59.144 --> 00:04:01.584
Song of the Cell, I think it's called.
00:04:01.725 --> 00:04:02.425
Yes
00:04:02.574 --> 00:04:06.614
Um, that book goes into these really in-depth...
00:04:06.805 --> 00:04:12.344
Well, I mean, I say in-depth, uh, that's a relative term'cause it was, you know, for mass consumption or whatever.
00:04:12.344 --> 00:04:18.432
But just these, like, brief discussions about how complex the body actually is.
00:04:18.665 --> 00:04:31.480
Uh, you know, for something so simple as, like, you eating an apple or something, just, like, talking about all the mechanisms that are taking place while that apple is being, you know, consumed by the various parts of your body.
00:04:31.793 --> 00:04:40.093
It's absolutely astounding what is actually happening within your body, all these different chemical reactions, and yeah, it's just insane
00:04:40.942 --> 00:04:55.300
Well, this is interesting'cause I have kind of a, I think a very, um, a very controversial opinion, which is like, you know, you talked about the complexity of, of life and like obviously in a lot of ways, like that's necessary.
00:04:55.300 --> 00:04:57.290
Like, there's just no other way to do it.
00:04:57.639 --> 00:05:01.069
But like, I'm really excited about, you know, like the...
00:05:01.079 --> 00:05:07.730
There's like 17 different chain reactions that need to happen in order for like something to happen in your body, and it's like, can we get that down?
00:05:07.730 --> 00:05:09.279
Like, that sounds overcomplicated.
00:05:09.300 --> 00:05:12.610
Like, is there any way we can refactor that biological pathway?
00:05:12.898 --> 00:05:19.158
Dude, it, it's funny you call this out'cause I feel like biology in a lot of ways is like the very definition of tech debt.
00:05:19.377 --> 00:05:21.687
Like, biology does not refactor.
00:05:21.718 --> 00:05:24.577
Evolution is not a refactoring process.
00:05:24.735 --> 00:05:27.524
Like, it's just like add on, you know,"Oh, you got an appendix?
00:05:27.584 --> 00:05:28.165
Eh, let's
00:05:28.247 --> 00:05:29.057
You just bolted.
00:05:29.127 --> 00:05:29.916
Oh, it's fine.
00:05:29.947 --> 00:05:30.877
Yeah, we'll leave it there.
00:05:30.877 --> 00:05:32.146
It's not, not hurting anything, so,
00:05:32.235 --> 00:05:32.855
you don't need that.
00:05:32.855 --> 00:05:33.785
Nipples on a guy?
00:05:33.795 --> 00:05:35.504
Who cares?" It's just like...
00:05:36.495 --> 00:05:36.894
But
00:05:37.228 --> 00:05:42.968
no, I mean, as long as that guy isn't getting killed by his nipples, you know, life, life's not worried about it.
00:05:43.213 --> 00:05:44.004
Exactly.
00:05:44.153 --> 00:05:44.764
Exactly.
00:05:45.069 --> 00:05:52.329
But yeah, so I, I mean, you mentioned he discusses, there's a brief section of the book where he's talking about these diseases that are just getting cured.
00:05:52.408 --> 00:05:54.574
I mean, this guy's blindness getting cured.
00:05:54.745 --> 00:06:02.410
And it just so happened that at the time there was this headline about sickle cell being treated, the first time sickle cell was ever treated.
00:06:02.410 --> 00:06:10.627
And, uh, I don't think Mustafa mentioned this in the book, but I just thought it was interesting that, like, as I was reading this, there was also this, you know, amazing headline.
00:06:10.627 --> 00:06:13.447
I mean, sickle cell is this, like, debilitating disease.
00:06:13.456 --> 00:06:17.166
It's been around for hundreds of years, and it's like we just treated it.
00:06:17.317 --> 00:06:17.916
It's amazing
00:06:18.130 --> 00:06:18.500
Yeah.
00:06:18.687 --> 00:06:19.497
Unbelievable.
00:06:19.579 --> 00:06:25.119
but he does start to go into, like, maybe a li- and I guess this kind of dovetails with your peptides, conversation.
00:06:25.129 --> 00:06:33.303
He goes into some of the, like, seedier underbelly where, like, you know, we might have to worry about athletes, like, what are they taking?
00:06:33.423 --> 00:06:36.257
Well, and actually, in a way, I don't think they had the...
00:06:36.276 --> 00:06:36.706
What was it?
00:06:36.706 --> 00:06:40.187
The, like, unrestricted games or, like, the un- There was that, like,
00:06:40.338 --> 00:06:41.408
Oh, yeah
00:06:41.416 --> 00:06:46.646
that was dedicated to, like, you could just take whatever steroids, uh, or the enhanced
00:06:47.021 --> 00:06:47.891
Enhanced games.
00:06:47.891 --> 00:06:49.261
Yeah, that did not go over well
00:06:49.617 --> 00:06:55.807
but I guess Mustafa Suleiman couldn't, uh, pre-predict that humanity was gonna le-really lean into, uh, gene doping.
00:06:58.011 --> 00:07:03.161
Yeah, I mean, I'll be honest, like I was-- I, I mean, conceptually I'm interested in that.
00:07:03.170 --> 00:07:08.142
Like, I mean, I don't want people to like destroy their bodies or whatever, but it is interesting to me.
00:07:08.142 --> 00:07:15.535
It's like, you know, if you just allow someone to take whatever drugs, like h- what is the pinnacle of, you know, human ability?
00:07:15.812 --> 00:07:16.312
Yeah.
00:07:16.351 --> 00:07:21.591
And that's ostensibly what that was supposed to be, but I guess they didn't even break any world records, right?
00:07:21.793 --> 00:07:25.863
Well, a lot of the, a lot of the people who won the, or like who won were natties.
00:07:25.894 --> 00:07:30.963
Like they were just training for the Olympics anyway, so th- and they just weren't even doping at all.
00:07:30.973 --> 00:07:33.153
Uh, which, like is that a controversy?
00:07:33.774 --> 00:07:35.708
It's like,"Ugh, this guy didn't even take anything.
00:07:35.757 --> 00:07:36.627
Like get him out of here."
00:07:37.190 --> 00:07:38.341
Yeah, that's kind of amazing
00:07:38.716 --> 00:07:40.107
there's an anti-doping scandal.
00:07:40.117 --> 00:07:44.490
But, did you see this part where they talked about the first gene-edited baby being...
00:07:44.500 --> 00:07:49.740
I don't know if you had these, this in your notes, but like there was the guy, this guy in China who
00:07:50.247 --> 00:07:51.247
Yeah, the rogue.
00:07:51.968 --> 00:07:52.497
Yes
00:07:53.490 --> 00:08:03.000
And he, uh, he was like,"All right, I'm just gonna edit, edit the genes of these, these two babies." And like the whole community was like,"Well, d- like bro, like what are you doing?
00:08:03.000 --> 00:08:04.560
Like d- you're not curing a disease.
00:08:04.790 --> 00:08:10.454
You did a shitty job." You know, which feels a little bit like it's kind of the least important aspect of this whole thing.
00:08:10.464 --> 00:08:10.745
But,
00:08:10.992 --> 00:08:14.742
This is the, uh, Lulu and Nana born in 2018.
00:08:14.982 --> 00:08:17.850
You know, I meant to look up, like, how are they doing?
00:08:18.000 --> 00:08:18.980
How are Lulu and Nana?
00:08:18.980 --> 00:08:20.750
They're eight years old at this point, right?
00:08:21.346 --> 00:08:22.276
Yeah, I guess so
00:08:22.761 --> 00:08:23.891
I guess they're still kicking about.
00:08:23.891 --> 00:08:25.980
Maybe they're, maybe they have, like, superpowers
00:08:26.077 --> 00:08:26.867
flourishing.
00:08:26.867 --> 00:08:27.288
Yeah.
00:08:27.288 --> 00:08:29.187
Are they, like, flying around yet or what?
00:08:29.610 --> 00:08:34.731
But yeah, I mean, this guy, he was basically ostracized from the scientific community.
00:08:34.731 --> 00:08:37.375
Like, like you said, he did this rogue...
00:08:37.465 --> 00:08:40.475
You know, he didn't consult with the community.
00:08:40.485 --> 00:08:43.581
He didn't, publish white papers beforehand or anything.
00:08:43.581 --> 00:08:45.541
He just sort of, like, went ahead and did it.
00:08:46.390 --> 00:08:52.686
And, uh, yeah, so not necessarily the way that we want these things to be happening, a milestone nonetheless, I guess
00:08:53.015 --> 00:09:13.042
it's interesting because I get-- I think back to what he was saying about technology not being able to be stopped, and this almost feels like a nuclear, you know, like a nuclear technology situation where, yes, the access to these, the, like, component technologies is, expanding every day.
00:09:13.052 --> 00:09:14.731
It's making, getting cheaper and what have you.
00:09:14.731 --> 00:09:22.330
But, I, I don't know that we're gonna have to worry about, like, backroom genetically modified babies for li- for the foreseeable future.
00:09:22.350 --> 00:09:23.409
Maybe I'm wrong about that.
00:09:23.419 --> 00:09:25.917
But it feels like there is, like, society as a whole...
00:09:25.917 --> 00:09:34.177
It's difficult enough, and society has really, like, kind of spoken in terms of, like, it's like,"No, this shit is not okay." So, like, maybe, I don't know.
00:09:34.248 --> 00:09:36.847
hopefully it's, not something we need to worry about.
00:09:36.923 --> 00:09:42.679
I, I'd be inclined to agree with you, but I do think it's one of those things where there is a demand.
00:09:42.830 --> 00:09:43.190
You know?
00:09:43.190 --> 00:10:01.765
It's like if you're-- Say you're about to have a child and you know your child is gonna be genetically predisposed to having some disease, and, you know, you know some fringe doctor who's willing to perform some sort of procedure that's not necessarily, uh, you know, sanctioned by the,
00:10:02.075 --> 00:10:02.274
Я
00:10:02.576 --> 00:10:04.046
the larger medical community.
00:10:04.046 --> 00:10:10.407
Like, as a parent, I feel like there's a tremendous demand or a tremendous desire to do something like that.
00:10:10.407 --> 00:10:20.177
So I think, it's like I agree with you that this is sort of like a very difficult technology to even unlock, and the only people who, really have access to it are like, you know, they're doctors.
00:10:20.177 --> 00:10:26.193
They're like these medical professionals who aren't gonna just throw away their whole career to like do some random gene editing.
00:10:27.735 --> 00:10:29.696
Aside from, uh, what's his...
00:10:29.926 --> 00:10:31.666
I, I don't even know if he na- he's named.
00:10:31.719 --> 00:10:33.058
Yeah, I didn't write his name down
00:10:33.200 --> 00:10:33.970
the scientist.
00:10:34.000 --> 00:10:35.309
I don't think they say it in the book.
00:10:35.379 --> 00:10:40.309
But I think where it differs from nuclear is that there is a demand for it.
00:10:40.529 --> 00:10:46.529
Like, even within individuals in society, there's this demand, which I think is kind of missing for nukes.
00:10:46.529 --> 00:10:51.919
It's like the only one-- The only people who demand nukes are, like, heads of state or, like, terrorists or whatever
00:10:52.197 --> 00:10:53.227
Yeah, exactly.
00:10:53.227 --> 00:11:10.663
Like your typical hyper-competitive parent doesn't have much of a need for, for a nuclear weapon, whereas they may, like, I don't know, the Joneses down the street, they, you know, you heard whispers that they, I don't know, went to some back room, to get modific- an illegal genetic modification,
00:11:10.888 --> 00:11:11.227
Dude,
00:11:11.384 --> 00:11:12.214
have to too
00:11:12.398 --> 00:11:15.278
some of my colleagues at work seem genetically modified to me.
00:11:15.288 --> 00:11:19.932
They're just like ultra smart and kind of like, yeah,
00:11:20.601 --> 00:11:22.815
They're just like perfect hu- human beings.
00:11:28.985 --> 00:11:31.475
a little factoid that I kinda loved.
00:11:31.985 --> 00:11:35.615
DNA is the most efficient storage mechanism we know of.
00:11:36.294 --> 00:11:42.615
All of the world's data could be stored in one kilogram of DNA.
00:11:44.054 --> 00:11:51.934
this, goes back to something you said in the l- in the last episode, I think, where you were talking about how biology sort of works on the atomic level.
00:11:51.955 --> 00:11:54.654
So it's like, this is why DNA is so efficient.
00:11:54.654 --> 00:11:58.995
It's like literally just these individual molecules that are chained together.
00:11:59.486 --> 00:12:02.116
And so yeah, dense, uh, very information dense
00:12:02.514 --> 00:12:04.914
It, it is, it really is unbelievable.
00:12:04.945 --> 00:12:23.222
But, but Yeah, so he segues into the last part of this chapter is where he starts to get into the synergy story of like, well, the fact that we now have all these expanding AI capabilities are actually gonna dovetail in a synergistic way with, with these biological technologies
00:12:24.110 --> 00:12:36.160
Yeah, he talks about this really cool contest, which this actually hearkens back to something you said in another episode where you called out the woman who started the, like, image recognition con...
00:12:36.561 --> 00:12:42.892
Yeah, Fei-Fei Li, uh, which I thought was really cool that you sort of called her out and gave her credit.
00:12:43.101 --> 00:12:50.792
This is another contest that, you know, it's called the Critical Assessment for Structured Prediction.
00:12:51.341 --> 00:12:53.022
Man, it's hard to read these acronyms.
00:12:53.562 --> 00:12:55.902
Uh, predicting protein folding.
00:12:56.740 --> 00:12:57.049
Yeah
00:12:57.172 --> 00:12:59.841
so CASP is what, you know, the, the...
00:12:59.892 --> 00:13:00.741
That's the acronym.
00:13:01.182 --> 00:13:08.725
Basically, what CASP is, is the con- it's a contest based on, uh, telling how a protein will fold.
00:13:08.957 --> 00:13:22.625
So it sort of gives you this, like, recipe for a protein or whatever, and you have to give back the answer of like,"Okay, the protein will fold in this exact manner." And we've s- we've discussed this on the podcast before, but this is just a property of proteins.
00:13:22.625 --> 00:13:23.054
It's like,
00:13:23.524 --> 00:13:23.784
Right
00:13:24.095 --> 00:13:25.485
like there's millions of proteins.
00:13:25.485 --> 00:13:30.654
It's, uh, it's ridiculously complicated, and each one folds in these, like, very unique ways.
00:13:31.065 --> 00:13:39.533
And this actually, like, this is the reason some biology behaves the way it does because of the structures of these proteins.
00:13:39.533 --> 00:13:45.432
It's like they interlock in very particular ways, which, you know, causes certain things to happen in your body.
00:13:45.919 --> 00:13:50.899
and historically, it was very difficult to know how these proteins would fold.
00:13:50.909 --> 00:13:51.649
It was a very...
00:13:51.659 --> 00:13:55.230
You know, the only way to really do it was, like, these very brute force approaches.
00:13:55.419 --> 00:13:59.519
There's no, like, you know, simple, like, efficient algorithm for doing this.
00:13:59.831 --> 00:14:05.654
so yeah, that's why they created this contest to sort of see, who could predict these, these foldings.
00:14:05.933 --> 00:14:18.094
And similar to the last contest that we discussed, a new kid on the block, AlphaFold, came along and just absolutely crushed the competition.
00:14:18.402 --> 00:14:18.912
And
00:14:19.105 --> 00:14:24.072
the first year that they were in the competition, they just, like, rock up like,"All right."
00:14:24.414 --> 00:14:24.875
Yeah.
00:14:25.004 --> 00:14:25.325
Yeah.
00:14:25.325 --> 00:14:31.830
So they just waltz right in and, like, just demolish everyone else and drop the mic, and it's this amazing event.
00:14:31.830 --> 00:14:33.190
And, and Mustafa was a part of it.
00:14:33.190 --> 00:14:40.692
I mean, AlphaFold came out of DeepMind, so, you know, Mustafa Suleyman and Demis Hassabis, they were the co-founders of DeepMind at the time.
00:14:41.150 --> 00:14:47.831
But similar to the image recognition, jump in ability, it was all based on neural networks.
00:14:48.211 --> 00:15:01.511
You know, they, they were using an underlying neural network that they had sort of learned based on all these training examples of various protein foldings, and this network was the thing that was demolishing the competition.
00:15:01.511 --> 00:15:12.418
The competition were these more sort of, I always wanna say conventional algorithms, you know, these more brute force style algorithms taking into account all the various rules that we understand with chemistry.
00:15:12.754 --> 00:15:15.224
and those were not as effective as a neural network.
00:15:15.491 --> 00:15:17.292
Yeah, it's, it, it's just wild.
00:15:17.292 --> 00:15:27.918
And so the, you know, the long and the short of it is they literally stopped running, the CASP contest by the next year, because it was just so good that it was like, well, it's done.
00:15:27.928 --> 00:15:29.798
You know, the problem is, is solved
00:15:29.850 --> 00:15:50.490
essentially became a solved problem, which is truly, I mean, people don't talk about this, but this protein folding thing I think is a massive milestone in this biological hacking because as I mentioned, like proteins are the, are what underpin all of the interactions that are taking place in your body.
00:15:50.850 --> 00:15:53.250
It's like the reason things are happening the way they
00:15:53.321 --> 00:15:57.100
The reason your body does anything at all, it's all proteins,
00:15:57.184 --> 00:15:58.205
all proteins.
00:15:58.264 --> 00:16:00.263
So yeah, I mean, this is huge.
00:16:00.292 --> 00:16:13.797
and yeah, just like you're saying, so AlphaFold dominated in year one, and then by year two they had AlphaFold 2, I guess, which had like a 99% accuracy with, you know, solving these protein foldings, so they just cr- they just killed the competition
00:16:13.956 --> 00:16:25.325
yeah, and so DeepMind basically just, like, they folded, like, 200 million, like, basically all known protein sequences, and then they just, like, uploaded it for everyone to, to see.
00:16:25.325 --> 00:16:31.076
And I think this is exactly to your point, where it's like we don't even have any idea what the, like, what the long term...
00:16:31.076 --> 00:16:34.275
'Cause all of this stuff, all this research takes a long time to do.
00:16:34.316 --> 00:16:36.576
Like, there's just a bunch of hoops you have to jump through.
00:16:36.576 --> 00:17:08.248
So, there's such a lag behind, like, where the, like, the results take behind actually getting a candidate that I think, like, maybe, like, a year or, like, however long the, drug approval cycle is, like, we're-- I think we're probably gonna see some cr- a crazy, like, uptick after, you know, the uploading of all of those, of those protein sequences, those folded sequences by, by AlphaFold to, uh, that we're, we're gonna just see these amazing new, new treatments
00:17:09.049 --> 00:17:09.970
Dude, I think you're right.
00:17:09.970 --> 00:17:11.009
I think you're absolutely right.
00:17:11.289 --> 00:17:15.038
Another thing I'm excited about is, uh, just Demis.
00:17:15.118 --> 00:17:32.744
Demis, you know, ch- uh, the head of DeepMind, he is sort of, uh, like a somewhat mysterious figure even within Google, and a lot of people talk about how he's very focused on disease, you know, sickness, you know, human frailty, all those things.
00:17:32.884 --> 00:17:36.474
And he essentially has carte blanche within Google.
00:17:36.914 --> 00:17:37.565
You know, it's Demis.
00:17:37.615 --> 00:17:40.025
You're not gonna, you're not gonna, like, give orders to Demis, right?
00:17:40.025 --> 00:17:42.005
So he's able to do whatever he wants.
00:17:42.276 --> 00:17:50.804
he has tremendous resources at his disposal, and he's an absolute genius, and that is what this guy is working on, is like he wants to fold proteins.
00:17:50.804 --> 00:17:52.144
He wants to solve disease.
00:17:52.511 --> 00:17:53.862
Solve disease.
00:17:53.932 --> 00:18:05.122
That, like the way that he f- talks about it is almost alien because it's like he literally, you know, like the other problems that he has solved, he's like,"No, we're gonna do it all." Like,"We're gonna..."
00:18:05.231 --> 00:18:05.382
Yeah.
00:18:05.980 --> 00:18:07.000
it's just wild
00:18:07.422 --> 00:18:13.752
It is wild, but it, it's weird how it doesn't even sound that crazy because we really are.
00:18:13.752 --> 00:18:18.313
It's like we- we're at this confluence of technology, large language models help us research.
00:18:18.563 --> 00:18:20.423
We've figured out all the protein folding.
00:18:20.423 --> 00:18:21.212
We have CRISPR.
00:18:21.222 --> 00:18:22.403
We can edit DNA.
00:18:22.606 --> 00:18:27.797
So we really are at this, you know, feels like we're sort of on this threshold, this confluence of technology,
00:18:28.574 --> 00:18:29.034
Yeah
00:18:29.346 --> 00:18:30.317
unlock some of these things.
00:18:30.653 --> 00:18:32.074
I think, I think you're right.
00:18:32.334 --> 00:18:42.017
And speak, speaking of unlocks, this, towards the end of this chapter they describe something that sounded like it came out of a movie, but I guess is real.
00:18:42.136 --> 00:18:50.855
There's this company, there's this company called Cortical Labs, and e- evidently they grew a brain in a vat and taught it to play Pong
00:18:51.309 --> 00:19:01.289
Dude, we're gonna have, we're gonna have biologic-- Like, we- we're at the beginning of this, of this interface between, you know, traditional computing and neural computing.
00:19:01.819 --> 00:19:03.339
It's pretty wild.
00:19:03.420 --> 00:19:04.349
Pretty wild to think about.
00:19:04.694 --> 00:19:05.455
Wild indeed
00:19:05.877 --> 00:19:06.337
all right.
00:19:06.337 --> 00:19:16.358
Well, I think, um, I think we can leave it there, and then we'll tune in next week for The Wider Wave, chapter six
00:19:16.689 --> 00:19:18.848
The wider wave sounds exciting
00:19:19.200 --> 00:19:19.589
All right.
00:19:19.619 --> 00:19:20.420
Well, I'll see you there, John
00:19:21.096 --> 00:19:21.527
See you, Matt
