George Church

Escape velocity is sometimes what it's called for aging.

Different people have estimates, and all those estimates, including mine, are going to be taken with a big grain of salt.

I think that mainly looking at the exponentials in biotechnology and the progress that's been made in understanding, not just understanding causes of aging, but seeing real examples where you can reverse

subsets of the aging phenotype you know so you're getting close to all of aging um in other words you're seeing instead of just saying oh i'm going to fix the damage in this collagen in this tendon in this limb you're saying oh i'm going to change a lot of things that that are they're common to aged related diseases and i'm going to get more than one at a time

I think looking at those two phenomena, the exponentials in biotechnologies and the breakthrough in general aging, not just analysis, but synthesis and therapies, and a lot of these therapies now making in the clinical trials, I wouldn't be surprised if 2050 would be a point.

If we can make it to that point, 25 years, most people listening to this have a good chance of making it 25 years.

And the thing is, it's not going to be some sudden point where you're going to be, you know, so sick 25 years from now that it's like hit or miss.

It's more likely that you're going to be healthier 25 years from now than you thought you were going to be.

There may be some, probably not some law of physics, but some

economic or complexity issue that we don't know about that becomes a brick wall.

I doubt it seriously, but we'll have to see.

Bowhead whales, yeah.

200 years, yeah.

is there any hope for doing that from somatic gene therapy alone or would that have to be germline gene therapy probably there's a lot of forces pushing it towards somatic um for one there's eight billion right people that have missed the the germline opportunity yeah as to say doesn't apply to us uh the two of us and everybody listening to this and you know

You have to be very cautious when you say something's impossible.

It's safe to say it's impossible to do it this second, but you don't know what's going to happen tomorrow and the next decade or something.

So I think there's a lot that could be done.

In particular, since aging is a fairly cellular phenomenon with

Proteins going through the blood and other factors going through the blood that signaling and so forth.

You could imagine if you replaced, let's say, every cell in the body, every nucleus in the body, you know, it would suddenly be young again, right?

Without...

going all the way back to the embryo and forward again.

And there's various other things that are just short of that.

If you replace the cells, well, they'll fit into that niche.

They might displace the old cells.

You know, that's...

certainly within the realm of modern synthetic biology is for cells to take over niches.

I think the hardest part is brain, but even there, there's some evidence that if you bring, even though the brain doesn't really use stem cells that much, you could artificially bring in stem cells and they could artificially fit into a circuit and learn the circuit and then displace the old ones in some way.

Yeah, exactly.

Ship of Theseus.

Having, you know, trying to maintain the connections and the memories.

But, you know, there's some fairly straightforward experiments that need to be done before we can really even estimate how hard that problem is.

Or, you know, very often there's low-hanging fruit that people just...

think is improbable but it's there because biology has all these gifts that you know where the uh just hands over to us uh levers that we can flip like like vaccines this amazing gift that didn't have to exist but they they do yeah

There is nothing close to that today, but there's nothing, no law of physics that would prevent it.

There's going to be practical considerations like

You know, how many injections do you need to do to achieve that goal?

But we're getting better at targeting tissues.

You know, so for one of my companies, Dino Therapeutics, showed they could get a hundredfold improvement in targeting neurons in the brain, which is a big deal.

Now, if...

That was just one little campaign that they did.

One experiment involved a lot of AI and a lot of testing of millions of different capsids.

If you did that with cells, capsids are fairly limited in the diversity and the structure that it can change to, but cells have even more

possibilities, I think you could probably get delivery to everything.

And the question is, how close to 100% do you need to get?

And it's going to vary from tissue to tissue.

For example, for some therapies, you just need to get

1% because that 1% can produce some missing enzyme and the 1% doesn't have to necessarily be in its normal place, right?

You know, you can you can turn a muscle into part of the immune system temporarily for a vaccine.

You can, you know,

An enzyme that's normally made in, let's say, the brain, you could make in the liver, right, if the point is just to get it into the blood.

So I think that's moving along quite well.

I think people get worked up about whether we are trying to bring back or have already or will ever bring back a new species.

And I think of it, if you think of it rather than as a natural thing that we're trying to do but as a

synthetic biology with goals that have potential societal and people also get worked up as to whether this could possibly benefit society in any way you know can we really um you know fix an environment uh to suit humans or fix the global carbon to suit humans and the answers we don't know but it's worth a try isn't it because it's could be very cost effective um

And the other thing, the other aspect of it is there's a whole discipline within synthetic biology of asking what's the minimum, right?

And so people often phrase it into what's the maximum, you know, like what can we do?

And I'm interested in both, but, you know, it's like, oh yes, there's millions of difference between mammoths and elephants.

There are millions of difference between elephant one and elephant two within Asian elephants and between Asians and African.

But not all of those are definitive in terms of,

what we would normally call them, you know, how we would normally classify them, what their functionality would be in an ecosystem, right?

And so there's this exercise that people do, and we've done it, for example, with developmental biology.

What's the minimum number of transcription factors it takes to make a neuron from a pluripotent stem cell, right?

What's the minimum number of base spheres it takes to make something that will replicate to something that was done in mycoplasma originally?

And in a way, these are more interesting than can we make a perfect copy of something, right?

It's can we make – what's the minimum things we have to do to make it completely functionally –

or even functionally in a particular category, right?

How do we make it bigger?

We learn the rules for how to make things bigger, how to make things replicate faster, how to use new materials, et cetera.

So I think what the dire wolf, we clearly didn't make an exact copy of the dire wolf, but it helped illustrate kind of,

educated people around the world that what is the difference between a wolf, a gray wolf and a dire wolf, right?

Because, you know, dire wolves, they're big.

Maybe they have a particular coloration.

You know, the head components tend to be bigger than the leg components.

And so how many genes do you need to do that?

Maybe this was dire wolf, you know, 2.0, and we're going to go for

go for 3.0 in successive approximation.

And we might want to develop the technology for making exact copy of something, because then we can, especially being able to make a hundred variations on an exact copy, because then there won't be any argument about whether you could make a dire wolf.

It's a matter of what should you make and what would be most beneficial for the species that you're making, for the environment it lives in, and for humans.

Yeah, I think you're hitting on a very interesting question, and it's related to, you know, what's the minimum?

So, for example, you almost said it, which was, you know, take a very multigenic trait in humans, like height is something that's probably the most well-studied one, simply because no matter what gene you're, no matter what,

medical condition you're studying, you collect information on height and weight and things like that.

Anyway, they tracked it down to on the order of 10,000 genes of which we have 20,000 protein coding genes.

Some of them are RNA coding genes.

And they each have a tiny influence on height.

But if you take growth hormone, somatotropin, that you have extreme examples where you'll get extremely low, small stature and extremely high stature due to that one alone.

And in fact, it's used clinically as well for seven different studies.

medical treatments.

So that's a perfect example of how much we can minimize something, sometimes called reductionism.

Reductionism isn't all bad.

Sometimes it helps us bring a product into medicine.

Sometimes it helps us understand or build a tool chest or a

module that we can use in other cases and translate it to other species.

So you hit on it just right, is that not everything will translate, but we start accumulating these widgets.

It's kind of like all the electronic widgets that we accumulate over time, that if we just want to slap it into the next circuit, you might be able to.

Biology, we've got a real gift, which is it's both very much more complicated than almost anything we've designed from scratch.

But it also is a lot more forgiving in a certain sense, is that you can have an animal or even a human that has two heads, which is not something that they evolutionarily have.

There was not evolutionary selection specifically to have two heads, but just a little deviation from the normal developmental pattern during fetal development.

And they both function fine, they control subsets of the body.

And they have their own personality, their own life.

So there's all kinds of things you can do in biology where you're working at a very high programming level is a way of thinking about it.

Pushing us to a new level of intelligence is going to be very challenging and maybe not even urgent.

To some extent, actualizing the people that we currently have would be quite, you know, just getting them

all up to whatever speed they wanna be up to within the range that's been demonstrated.

So like some people are gonna wanna be like Einstein, some people won't.

Some people wanna be healthy all the time, unlikely, but some people might not.

Some people might wanna live to 150.

Some people might wanna die at 80.

But if you give them that range, that capability, what if we had 8 billion super healthy,

Don't need to worry about food and drugs.

Super healthy, Einstein level of intelligence, education level, best we can come up with.

That would be a completely different world.

I would say mostly GWAS for humans.

maybe for animals in general, followed for animals with synthetic biology, you know.

And the smaller and the cheaper and faster replicating, the more experiments you can do.

So, you know...

I don't want to overemphasize how single genes can do these amazing things, but there's also the possibility that multiple genes can be hypothesized and tested quickly.

So for example, I mentioned earlier, what's the minimum number of transcription factors it takes to turn a stem cell into a neuron?

Well, there's a bunch of recipes where you can do it with one, right?

Maybe you want a specific neuron, you might need a few more.

But then you can get, you can kind of quickly go to the answer by looking at each target cell type that exists, and you can see what transcription factors

Did it express at the time that it's the target?

And then you say, well, let's just try those on the stem cells and see if they work.

And that recipe has worked quite well.

It's the basis of GC Therapeutics, the company, and a bunch of the work that we do is you can get a recipe for almost every cell type in the body.

Now, that's not new cell types, but at least you've learned a...

To your point about reducing the number of genes we need to manipulate in order to get to a particular goal, here's a whole series of goals, and we can get them with one, two, three, maybe seven change transcription factors.

So that's an example.

there's room for lots of other examples of where you can do a reduction and do not just reductionistic virality, but then constructionistic, where you take it back up and make a whole complex system and see what happens.

And then you can do lots of those combinations and you debug them and so forth.

Some of these things you can do in vitro things you can do on probably on the order of 10 to the,

14th, 10 to the 17th.

Things that involve cells are typically in the billions, but this is how we're going to get inroads into the very complicated biological systems.

Right.

You know, I was a co-author on a paper that warned about the dangers of mirror life, just like, you know, I wrote a paper long ago about the dangers of having the synthetic capabilities we have for making synthetic viruses.

And to some extent of having new genetic codes.

They have a few things in common.

But the thing about the advance that we were recognizing in our science paper that was warning about mirror life is that we not only had to calculate what the possibility of error-prone escape or something like that.

We don't want anything to escape.

that we made in the lab, unless there's a general societal consensus, it's a good thing.

And so far, there aren't too many examples of that, or any examples of that.

But mirror life, if it can be weaponized, then we took it to a whole nother level of concern.

And the concern was that if we got it to a certain point, it would be easy to weaponize it.

And again, there's practical considerations.

It may be that most people who would consider weaponizing mirror life would probably be satisfied with weaponizing viruses that already exist, that are already pathogens.

And they wouldn't want to destroy themselves and their family and their legacy and everything like that.

But all it takes is one, you know, one group probably or one person.

But your question is, is it inevitable?

I don't know.

It might be.

It's quite possible it's already here.

In other words, we already have mirror life in our

in our solar system or maybe even on our planet, it just hasn't been weaponized, right?

And so it's just like what we were saying in the science paper is this seems like the sort of thing that could wipe out all competing life if we're properly weaponized, but there are probably a few things like that.

And what we really need to do is reduce the motivation to do that, maybe increase our

preparedness for a variety of existential threats, some of which will be natural, some of which will be, you know, one disgruntled person who has essentially too much power because, you know, over history of

humanity, the amount of things that a single person can do has grown very significantly.

I mean, it used to be when you had your bare hands, there was kind of a limit to what one person could do.

A large number of people could team up and get, let's say, a mammoth or something like that.

But today, one person with the right connections or right access to technology

you know, could blow up a city, right?

And that's a huge increase in capability.

And I think we may want to start dialing that back a little bit somehow.

Offense often does have an advantage, but so far we haven't, you know, we made it through the Cold War without blowing up

any hydrogen bombs, as far as I know, accidentally or intentionally on enemies.

We did two atomic bombs.

But a lot of that is based on the difficulty of building hydrogen or atomic bombs.

The thing that's alarming to people like me is that biotechnology

enables smaller and smaller efforts, harder and harder to detect, harder and more and more subtle to the stochastic variation between people.

There's some people that are just so happy, they would never want to do anything close to that, or they're so responsible or ethical or whatever.

and then there are other people who like whenever they have a bad day they want to take a lot of people with them right and you know maybe some progress in psychiatric uh medicine would help again you don't want to force that on people you want to make sure that right that they're that if they don't want to get cured they you can't force them but you can make it available to them that might help hopefully there's a more technological solution or more robust solution than

Well, there will be technological solutions to the psychiatric problem.

It could be even people who aren't sure whether they want to be helped or not can try it out, and it's reversible, and they say, yes, I like that better.

Okay, let's try that.

then there's other things that cause you to have bad days.

It's not just your psyche, it's also the environment.

So if you're surrounded by your people being starved or infectious disease or being shot at or something like that, those are things that are subject to

sociological and technological solutions.

I'm not trying to reassure you.

And, you know, we're having a conversation about what it takes, and that might be, that's one scenario for what it might take.

Much harder.

Again, the offense has the advantage.

We can make a lot of different codes.

Yeah, so one interesting thing is that there's only two chiralities.

There's the current chirality and the mirror chirality.

But there's maybe 10 to the 80th different codes.

Now, some of them you might be able to take out all at once.

Anyway, the coding space is a kind of more interesting space.

And of course, it could get even more complicated than that because the 10 to the 83rd is like...

based on triplet codons and and that sort of thing but if they're quadruple codons or new novel alphabets and so on um but we're sort of getting into uh

you know, a cycle of competition.

It would be better than nip it in the bud, which is, you know, why did we spend so much societal resources building up to tens of thousands of nuclear warheads?

And now we've...

Dialed it back to mere thousand nuclear warheads.

That's nice that we dial it back, but why did we waste all that time and money and energy?

It's hard to pound nuclear weapons into plowshares, as they say.

One of the things I advocated in 2004 is that we stop deluding ourselves into thinking that

moratorium and voluntary signups to be good citizens is going to be sufficient.

We need to also have surveillance and consequences and mechanisms for whistleblowers to make it easy for people to report things that they think are out of line.

And we had essentially moratoria and disapproval for germline editing, and nevertheless, somebody did it.

And a lot of people knew about it.

So that was clearly a failure of the whole moratorium, voluntary, and whistleblower components.

Okay.

Half empty, half full.

I'll give you that, but...

But all it takes is one for some of these scenarios.

So it would have been nice if the whistleblowers could have saved him the three years in prison by getting an intervention.

I mean, it's not like anybody died.

There are probably three healthy genetically engineered

children in the world now, be teenagers soon.

But it's still, it was a good test run, shows a failure of the system.

We need to have better surveillance of all the things we don't want and consequences that are well known.

Yes.

So we have something that's about the same speed, a little bit faster than Moore's law in biology.

It's more recent is one aspect of it.

But we could kind of stand on the shoulders of the electronics giants to go a little bit faster to catch up.

I would say we do.

I mean, we have the biotech industry, which has...

use that exponential curve to get better.

It's also possible we're close to the big payoff, is the other aspect, or the beginning of the big payoff.

Right now, we have miraculous things like cures for rare diseases.

We have vaccines.

We have a trillion dollars, probably, of various biotech-related things, if you go far enough apart.

but we're kind of on the verge of really combining electronics and biology more thoroughly and AI and biotech.

And I think that's, it seems like we're on the same track as Moore's law, if not better.

Well, 2040, we're talking about only 15 years, which is like one and a half, maybe two cycles of FDA approval.

2040 is post-AGI.

It's a long time.

Well, I hope it's not post-AGI.

I think we're rushing a little bit to get to AGI, and there's lots of cool things we can do with just super AI.

But we need to be very cautious, I think, that AGI.

Well, anyway, we could get into that.

But I think that we are shortening the time of getting medical products approved still in a safe way.

But that's not going to completely change the exponential.

It might reduce it from 10 years down to one year is our record so far for, say, COVID vaccines.

So maybe that'll be 10 times shorter.

Maybe that will multiply out a little bit.

But I think the big thing is that all our designs will become better, so there'll be fewer failures.

The cost per drug will drop.

There'll be things that we didn't classically consider drugs or instruments, some sort of hybrid thing.

But again, I don't think that'll be completely shocking.

But it's just going to be so much of it.

It's going to be lots of diversity of solutions.

I'm not even sure it's going to make sense.

But, yeah, 100x would not be completely surprising.

Combinations of drugs will be important.

Using them intelligently, there'll be a lot more.

Some drugs will affect everything.

So, for example, an age-related drug, that could impact every disease.

Right.

I'm not sure the number is going to matter so much as the quality and the impact and intersection and software that helps physicians and regular citizens make decisions.

Well, the cost curves are affected by new tools.

I mean, it's not just some automatic thing.

There is a big discontinuity between Sanger sequencing and nanopores and fluorescent next-gen sequencing.

And so, you know, I think sometimes it's a merger of two things.

So clearly AI merging with protein design causes a step function.

These step functions get smoothed out into kind of a smooth exponential, but there are lots of them.

The next set will probably be a merger of AI with other aspects of biology, like developmental biology, merger of developmental biology with manufacturing.

Conquering developmental biology, in other words, actually knowing how to make any arbitrary shape given, you know, DNA as the programming material.

I think that would be a big thing.

Having just more materials in general.

All the materials we use in mechanical and electrical engineering should be made better by biotechnologies.

Why is that?

Why is that?

Well, it's that electronics is more so, I wouldn't say is stopping, but it's

that what we would call the one nanometer process, which is supposed to come out in 2027, according to the roadmap, it's not really one nanometer, it's more like 40 nanometers center to center spacing, typically in two dimensions, maybe a little bit of three dimensions, but biology is already at 0.4 nanometer resolution and it is in three dimensions.

And so,

you know, depending on how you count that third dimension, that could be a billion times higher density that biology is already at.

And, you know, we just need a little more practice with dealing with the whole periodic table.

Even lecture, lecture on engineering doesn't use the whole periodic table typically, but we, but especially not at the atomic level.

So I think biology is just really good at doing atomic precision.

A few things.

One is the arrival of synthetic biology.

We were already kind of doing synthetic biology before.

We were doing recombinant DNA.

It was kind of...

you know, genetic engineering was called, it was kind of in that direction, but synthetic biology really liberated us to think a little bit bigger, even though it started kind of focused on E. coli and yeast, it enabled us to maybe think about new amino acids, for example.

And I think new amino, if you start using the full periodic table with the amino acids or what amino acids can catalyze,

that breaks one of the major barriers.

One of the major barriers between electrical and mechanical engineering and biology was the use of special materials, things that conduct electricity at the speed of light or conduct signals more generally.

But there's definitely polymers that biology can make that will conduct at the speed of light.

And we could make a mixed neuronal system that has conventional neurons and processes that conduct at the speed of light.

That would be interesting.

I think that our ability to design

uh proteins was particularly difficult designing nucleic acids was great whether we were doing you know you you want two things to bind to each other you just dial it up using watson creek rules if you want to make a three-dimensional structure you know it's actually the one kind of the one thing where morphology is dictated by fairly simple rules it's not how developmental biology works and we still need to figure out how that works but dna origami dna nanostructures really work

but doing it for proteins was really really hard until i don't know maybe eight years ago something like that and and i think we're just now getting used to it the use of chips for making dna um i mean you said that dna synthesis come down a thousand fold what depends on who you talk to so that when we came out with uh the first chip based genes in 2004 nature paper uh basically people dismissed it for about a decade the only people that used it were

you know, collaborators and alumni.

And it wasn't even listed on the Moore's law curve for DNA synthesis, even though it was like a thousand times cheaper.

It was just like ignored.

And now we have claims of 10 to the 17th

genes okay that you can make you can make libraries 10 to 17th that aren't randomized and in any real in the usual sense where you just like do air prone pcr or spiked in nucleotides uh now 10 to 17th that's a lot bigger than a thousand fold you know if if you know if it turns out to be practical yeah

I think part of it is that the nanotechnology as original, the source of the inspiration, Eric Drexler, he wanted to reinvent biology

In a certain sense, but it already existed.

And so you don't need to design a diamond replicator because you already have a DNA replicator.

And so the question of what was missing, what was motivating this reinvention of biology, it was materials.

So the biology is not that great with...

you know, materials that are, say, superconductors or conductors, period, semiconductors and light speed.

But it's getting there.

I mean, you know, rather than going the route of having everything has to be based on first principle nanostructures, you meet in the middle where biology can build things.

Now, of course, when you go down to

you know, liquid nitrogen in colder temperatures, biology, as we currently know it, stops functioning.

Now, it's not to say that you can't have things moving in liquid nitrogen.

You can, but that hasn't been explored and doesn't really need to be, because if biology can build things that can operate at low temperature,

Or maybe biology now, because you can make these big libraries of biology, maybe 10 to the 17th in vitro, and you can flip through them quickly and you can barcode them.

This is something that's never been done in electronics.

I'm not saying you can't do it in electronics, but you haven't made...

a billion different kinds of electronic materials, right?

Just, you know, in an afternoon, barcode them all and see who wins, right?

But we did it all the time in biology now, at least since 2004 we have.

And so...

So I think that's an opportunity is that we use those libraries to make much superior materials.

And we might even finally get a room temperature superconductor that way.

From bio?

It's possible.

I mean, from libraries.

We call it chemical slash biochemical slash exotic material libraries.

But the point is they're libraries.

They're essentially based in some sense on polymers, even though pieces of them don't necessarily have to be polymers.

Well, AlphaFold's very nice, but it's only part of it.

So there are large language models that are different from AlphaFold.

So to give an example, AlphaFold...

Last time I checked, anyway, at least it's all changed.

If you substitute an alanine for a serine in a serine protease, it will have exactly the right fold.

It will be precise to a fraction of an angstrom overall average.

but it won't function.

It just won't function.

And that's where you need either extraordinary precision or just knowledge of what happens evolutionarily or happens in experiments to say that no, an alanine won't work.

And so I think

There's all kinds of combinations of AI tools that can give you deeper insight into that.

I mean, I think the way that it's working now, which will get us a long way, won't get us the whole way, is we have something that kind of works, and we make libraries inspired by that, make variations on it.

And then whichever of those variations work, we make variations on that, and we can just keep going.

It's kind of like the way evolution worked, except different.

Now we can do it at incredibly high speeds.

And in principle, evolution might incorporate a few base pair changes in a million years.

Now we can make billions of changes in an afternoon.

And it's all guided in such a way that you get rid of the wastefulness of having a bunch of neutral mutations and a bunch of lethal mutations.

You can have things that are quasi-neutral but likely to be game-changing, have more of a focus on those.

Another thing that's been missing and none of the

AI protein design tools that I know of are particularly good at it yet, but we're trying to, as we speak, trying to improve this, is non-standard amino acids.

Because a lot of these tools depend on having libraries of 3D structures which use 20 amino acids and large language models where you line up all the sequences of 20 amino acids.

And we have very little experience with extra ones.

But

But I think there's a revolution going on in generating non-standard amino acids where the amino acids can either have as covalent part of them or as easily liganded all the entire periodic table, stable elements.

And that will, you know, each of those will have to blend in and train our models on.

But as soon as that comes in, then we're going to have a whole series of new materials very quickly.

And ultimately, you can think of the...

the determination of the functionality of your library is a kind of computer, right?

So you use AI to make, to design the library optimally.

So you avoid things that are really neutral and really seriously damaged.

But then the stuff in the middle, you actually play it out, not in a simulation, but in real life.

But it's so inexpensive, and it's so fast, and it's so exact.

I mean, it's 100% precision because you're not simulating, right?

You're not making assumptions.

You're not going from quantum electrodynamics, which is an assumption,

quantum mechanics, which is an assumption, to molecular mechanics, which are full of assumptions.

You're really doing the real thing.

And so you're doing a kind of natural computing, and then you can take that data and harvest it in various ways very efficiently, pump it back into the more conventional AI, and do another round of it.

Well, I didn't mean to stop there.

I mean, I knew the conversation would continue.

I'm not pinning down a particular year either, but I think this is poised to go pretty quickly.

There are very few practitioners is the thing that will stop it for a while.

Yeah.

Since materials should go faster though, because they don't require quite as much regulatory approval.

It's one of these things where when you get the right idea, it's not hard to recruit people.

For example, when Feng Zhang and my labs brought CRISPR, we just got 10,000 requests in the next two months for people that wanted to duplicate the system.

And so that's what I hope will happen with the non-standard amino acids and the using AI for protein design and making new materials.

Hopefully that will recruit tens of thousands of people overnight.

I'm much more excited about scientific AI than I am about language AI.

I think languages were in pretty good shape already.

And what worries me is that to get to the next level of language requires AGI or ASI, artificial super intelligence.

And that's very dangerous.

I don't think we have quite figured out how to

There's a lot of safety organizations and a lot of safety rules and so forth.

And I think what typically happens when there's an intense competition is those safety rules get undermined and pushed aside.

But even if they weren't, I just don't think we understand our own ethics well enough to educate people.

A completely foreign type of intelligence.

I mean, we barely know how to pass it on to the next generation of humans.

So I think we need time to sort that out.

And there's no rush.

This is a completely artificial emergency.

This is not like COVID-19 where we actually, millions of people were dying if we delayed the science.

This is something where if there ever is a crisis, it's because we created it.

It's not because we're trying to solve it.

And so I think we need to go very slowly on AGI and ASI and double down on

slightly narrower scientific goals.

And even that, we need to be very cautious about.

We need to have kind of an international consensus on what constitutes safe AI.

I think we'd slow it down.

I think

I think it would eliminate it because the first thing it would conclude is biology is not relevant to me because I'm not made out of biology.

I don't think we have anything close to the assurance that we need that that would be safe.

But let's put safety aside for a moment.

I think it's not only hard to calculate the bads, it's hard to calculate the goods.

So I think it could be a complete game changer.

But on the other hand,

It's like if we said we could get instantaneous transport all over the earth, right?

Well, we could say, yes, that could be a game changer, but do we really need it, right?

Is that really important?

Maybe it would be more interesting to just have Zoom calls and they're better, you know, or just learn how to get everything we want in our kitchen and we don't need to travel anymore, right?

So, you know, be careful what you ask for, right?

You know, because you could tip our priorities towards something that we really don't care about, that we shouldn't care about or might wish we didn't care about, right?

These are great questions and I'm not sure, I don't want to misrepresent that I know the answers, but it's like the question of if you have

Nine women, can you do pregnancy in one month?

No, not present.

But you're working on that, right?

But the same thing is, there may be certain things that doesn't take a lot of people.

We just don't know.

We just don't have that much experience with having...

you know thousands of Einstein type levels of creativity and intelligence simultaneously in a generation and in fact It's probable that we're all Capable of being a bit more efficient if we don't have you know distractions of mental illness of you know

taking care of other people.

Now, taking care of other people may be a very good thing.

You know, it may be that if we have no one to take care of, there'll be something bad that happens to us socially.

So these things are very complicated, hard to predict.

I think right now, I think the

The baby step, or actually the pretty big baby step, is to eliminate diseases or at least make it possible for people to eliminate their own diseases as they see fit.

I think I always felt it was very gnarly.

I also felt that it was something that we could engineer.

Certainly, we have made a lot of progress at the broken end of the spectrum where the brain is severely challenged.

challenged relative to average.

There's thousands, a huge fraction of genetic diseases that have one of their consequences being that the child is developmentally delayed to such an extent that it's lethal or a lifetime deficit.

And we know how to

We know the genes involved and we know how to do genetic counseling in some cases, gene therapy and other therapies to deal with it.

At the other end, you know, we have

reduction of cognitive decline by cognitive enhancement, which is showing some promise.

But again, that's kind of like this early stage severe impediment to cognition has a late stage component.

But what about...

How much information does it take to encode a brain?

I'm not sure that that much less genome is required than if you just wanted to make a brain, because the brain is totally entangled with the body.

You know, you have a 10 to the 11th neurons, 10 to the 14th synapses.

If you wanted to reproduce a particular brain, let's say, it might be...

It's speculative as to whether it would be easier to do that by making a copy of it in silico, in some kind of inorganic matrix, or making a copy of it.

Both of those are going to be hard.

I would say that if you wanted to make a copy of a

you know, complicated book, it would be easier to take photographs of each of the pages than to completely translate it into another language, trying to get all the nuances and the poetry and so forth if your goal is just to replicate it.

And I think the same thing might be true of a brain.

But replicating a brain probably involves a lot more information than synthesizing it.

So, I mean, just to define the 10 to the 14 synapses is going to take a lot more bytes than the genome, which is

billions rather than 10 to the 14th.

But there might be reasons that you want to replicate a particular brain configuration rather than just make another animal that starts from scratch as an infant.

Well, I mean, certain things seem incompatible, like the temperatures of a fission reactor.

isn't obviously compatible, but the possibility that once we, that a biological system can make other things, for example, it can,

You know, it can make a nest, a bird can make a nest, okay?

And you consider the whole nest as part of the replication cycle of the bird.

So you can say biological thing that replicates at 30 minutes doubling time could make a nuclear reactor as that would be its nest.

But you need to expand this range of materials.

In a certain sense, we do this already.

Humans are a biological thing that replicates, not in 30 minutes, but in 20 years or less.

And is that fundamentally limiting us?

Probably is.

But yes, it's amazing to think about what if you could take a cornfield or a nuclear reactor and suddenly 30 minutes later, you've got two of them, right?

And then four of them.

I mean, that's quite an interesting concept.

But I think we should start with, I teach a course called How to Grow Almost Anything.

And I work with Neil Gershenfeld at MIT who has a course called How to Make Almost Anything.

And we're trying to meet in the middle where we can

And, you know, his, you know, mechanical electrical engineering will meet with our biological.

And, in fact, neither of us can make or grow almost everything because there are all kinds of little gaps and things that are very hard to make in a small lab because there are things all over the world that depend on, you know, multibillion-dollar fabs to make things.

But, you know, we're eating away at it.

I think that we might eventually be, you know, maybe a smaller baby step than making a nuclear reactor is making a phone.

You know, you said radio communication.

We should make a biolat.

It should be a small...

challenge goal for the synthetic biology community, maybe iGEM or something, make, you know, bacteria make a radio.

Now, actually, Joe Davis is an artist that's been affiliated with my lab and before that, Alex Rich's lab.

And he did make a bacterial radio, but it was kind of more on the art end than on the science end.

But I think that would be a good goal.

So part of this has to do with just learning the rules of developmental biology, like I said.

We can determine morphology at sort of the molecular level now, proteins, nucleic acids.

Determining at the cellular, multicellular level, there's a lot more things you can do and a lot faster.

but we don't know the language yet.

I think we're on the cusp of getting the tools to do that, like the transcription factor I was talking about earlier, harnessing, migration, gradients of factor, diffusion factors, chemotaxis and so forth.

So that's one thing we need, but there's a bunch of things we need, really.

Oh, I see what you're getting at.

So astronomy might be we would detect radio signals or light signals.

But biology, the kind of evidence would be that you show in a laboratory using...

prebiotic conditions a really simple way to get life, right?

Or, I mean, it's a harder proof to prove that given, because we don't know what all the possible prebiotic conditions, and probably the number was vast.

I mean, you have 10 to the 20th liters of water and, you know,

at various different salinities and drying up on the ocean and the sun and the lightning and all this stuff.

But yes, I think if you showed kind of reconstructed in the lab a very simple pathway from inorganics, cyanide derivatives and reduced compounds all the way up to, you know, some cellular replicating structure, I think that might...

It might lead us to believe that at least life exists.

Now, there are other parts of the Drake equation that might kick in, which is maybe it's hard to get intelligent life because intelligence isn't necessarily in your best interest.

And if you get intelligent life, it's hard to maintain that without societal collapse or without robotics taking over and then killing themselves, right?

And that's hard to do experiments.

But I think...

To your question, I think an experiment that showed maybe multiple different ways of getting to a living system from nonliving systems spontaneously would be interesting.

Again, I'm not sure it would be very hard to prove the negative.

Yeah, I think these are very challenging problems.

I'm not even sure we would be able to say within five orders of magnitude, much less 50%.

But, you know, I

I think it's more likely to come from exploration than it is going to be from simulation.

If, you know,

The sad truth is that almost none of the missions that we've sent outside of Earth have actually looked for life.

They've had components that could have looked for life, but a sad number of those, not enough components that could look for life, and the ones that could look for life, not really looking for it.

And when we get positive results, we dismiss them, as happened with the...

And so I think if we just start looking at the geysers that are coming out of various moons of Jupiter and Saturn, there's so much water.

There's 50 times more water, liquid water, not frozen, more liquid water in our solar system than on Earth.

Doesn't that seem likely that some of that would have been a good breeding ground for

But it could be that we need sunny shores, you know, where you have a lot of dry land right next to water.

Maybe these are just giant oceans that are surrounded by ice.

But in any case, we need to look at those fountains to see what's popping up.

That's a high priority.

And the same thing goes for, there's a lot of water on Mars that's maybe even more accessible.

But until we've exhausted those, those are probably the easiest.

They're hard.

We're still talking about multi-billion dollar experiments, but I think they're a little more convincing.

And again, it'll be hard to prove the negative.

If we find it's negative on everything in the solar system,

you know, there's so much more diversity out there that could have done it.

I don't think I'd be surprised either way.

I can imagine it going either way.

I can imagine making truly amazing materials

using proteins as the catalysts, or maybe in some cases as a scaffold as well as catalysts.

I think one thing that's probably already happening, so we don't have to go a thousand years out, is the number of amino acids is going up.

It's going up radically from 20.

I think pretty soon we'll have a system where we can have 33, 34 new non-standard amino acids being used simultaneously with all the standard ones in a E. coli cell.

So 34...

plus 20 is a lot bigger than 20.

I don't think we necessarily need more

more than four nucleic acid components.

I mean, certainly there are plenty of modified ones.

There's a bunch of alternative base pairs, some of which don't even involve hydrogen bonds.

So we could have more.

But I think the main thing is this information storage and whether it's bits, digital binary is just zeros and ones, that works pretty well for 99% of what we do electronically.

So having four is better than two maybe, but do we really need six?

You know, I don't know.

So, yeah, I wouldn't be surprised if we had... Another possibility is that we change the backbone of DNA.

So maybe keep the ACGT, but make it out of peptides now.

A little bit smaller, a little bit more compatible.

I don't know.

Or maybe that'll just be...

just a slight, you know, it could be part of the new amino acid collection.

And there'll be more.

I mean, these are just things that my primitive 21st century brain is coming up with a thousand years from now.

It'll be a whole new millennium.

I think that evolution has a tendency to go with what works, and the investment in making a whole new base pair would have been high.

And we haven't even articulated what

what the return on investment would be.

What do you get from that?

We have made systems like Floyd, Williamsburg and others that where you have replication and transcription and translation with a new base pair, but it hasn't been clearly articulated what that gets you.

uh even in technological society so in technology you can you can jump to things that where all the intermediates aren't you know incrementally useful with evolution is as far as we know generally limited to you have to justify uh every change uh it's like some bureaucracy says well if you're gonna you put this sidewalk in you know you have to justify that before you can build a city

It's hard to say because as soon as you say it, it becomes hyped.

If I've ever been asked this question before, it's too late.

I would say

One thing I think is very ripe and is very well understood in a certain sense, but is nevertheless ignored.

It's kind of like the previous example I would have chosen was making genes out of arrays.

Arrays were typically used for analytic, you know, quantitating RNAs or something like that.

So the original aphometrics type arrays.

But we turned them into gene arrays.

And just...

people weren't using it.

It was in nature, it was hidden in plain sight.

But anyway, it was somehow underhyped.

What I would say is genetic counseling is underhyped.

It is clearly competitive with gene therapy in a certain sense.

I mean, clearly not for people that are already born, but for people in the future, not even distant future, next couple of years.

We've got a chance of diagnosing them or...

diagnosing the potential parents and dodging.

And this has been in practice since 1985 in Dorya Sharim.

Perfectly reasonable community response to it, eliminated or greatly reduced all sorts of very, very serious inherited diseases.

It's sometimes just, you know, depending on how it's presented, it's dismissed as eugenics.

I think it's rarely that I heard Doria Shurim described that way, and rightly so.

What they're doing is standard medicine, you know, whether you, you know, cure these kids as soon as they are newborns, or whether you counsel the parents so the same disease is missing.

The problem with eugenics was that it was forced.

The government forced it on people.

It wasn't that it enabled people to make a choice.

It's that it removed the choice from the people.

That was what was wrong.

And that's the confusion.

But I don't think that's the explanation for why this is underhyped.

I think it's people, when they're dating, they're not thinking about reproduction necessarily.

And when they're thinking about reproduction, they're not...

You know, they're not necessarily thinking about serious genetic diseases because they're rare.

I think it's our difficulty with dealing with rare things.

It's like there was great resistance to seatbelts because less than 1% of people died in automobile accidents or even got hurt.

Great resistance to stopping smoking.

Really, it's hard even for us to imagine how great the resistance was for seatbelts and smoking.

And, but eventually we got over it.

I think this is a similar thing, which is that only 3% of children are severely affected by genetic diseases.

And I feel like, well, I'm not that unlucky.

You know, I'm in the 97%, right?

You know, 97% of those were your odds of winning, you know, at the horse races or at the casino.

You take them.

Yeah, 97% of winning.

Good.

You know, but with, you know, when a child's future is at risk, I think that's...

It's not the right solution.

And the other thing is I think it has to do with the trolley problem.

It's like if you don't influence it, it's not your fault.

But actually, everything is your fault, you know.

Not doing something is a decision, right?

And so I think it's like if I just don't do anything and they come out damaged, well, it's not my fault.

But it is, you know.

I think I said, yeah, I know what you're saying and what David is saying, but I think it's a dangerous dichotomy.

You know, they'll say that there are lots of, not just India, you know, all over the world.

And in fact, we all went through a bottleneck.

No, but...

That changes the rate from, say, 3% to 6%.

But the point is, 3% is still unacceptable.

I mean, it's just a tragic loss, not only of the human life directly affected, but the whole family is, you know, very often one or both parents have to quit their job and spend full-time, like, caregiving and fundraising, because these are very expensive diseases as well.

And it's just...

don't need to uh we need to be careful not to stigmatize as well so when uh if a bunch of families get fixed we shouldn't point a finger at the ones that are unwilling to get fixed because that's their choice you know but i think as as word spreads and you see the positive outcomes i think that will be uh

It will be seen as one of the simplest bits of medicine ever.

I mean, it's – in fact, it's something –

hundred dollars per genome, and it'll probably be less soon, and you get the whole thing analyzed.

And, you know, compare that to millions of dollars that, you know, that will be lost, opportunity costs, them not being part of the workforce, the taking care of them and so forth.

So the return on investment is tremendous.

It's at least a tenfold return on investment.

So it's a no-brainer from a public health standpoint.

We should be able to pay for this through national health services in England, through insurance companies in the United States.

And it turns the insurance companies from being the bad guys, that they're snooping in on your personal life and then raising your rates, to, oh, they're giving you this free information and you can do with it as you wish.

And you could, if you...

take the advice, then you save them millions of dollars.

Absolutely.

I've actually counseled my gene therapy companies that

that they should be investing in very common diseases, because rare diseases have this genetic counseling solution, with the exception of spontaneous mutations and dominance, which probably are IVF clinic-type solutions, but the rare recessives can be handled in matchmaking at every level.

Anyway, I counseled my genetic therapy companies that they should, you know, invest in common diseases like age-related diseases and infectious diseases.

And in fact, you know, the COVID vaccine was formulated as a gene therapy and was, you know, the cost was in the, you know, $20 per dose range and 6 billion people benefited from it.

Or 6 billion people took it and

and it was proven over the whole population.

So I think that's the more appropriate use of gene therapy.

But I think for practical reasons, getting FDA approval and so forth, you might go for the rare diseases, and that's perfectly fine.

But I think the cost-effectiveness of the sweet spot for gene therapy is for age-related diseases, and the sweet spot for...

of rare diseases is genetic counseling.

Oh, phew.

I have to preface this by saying when scientists answer a question and explore possibilities, it doesn't mean they're advocating it.

In the past, people have asked me off-the-wall questions about Neanderthals, for example, and then it was described as if I was enthusiastic about it.

So I'm not enthusiastic about NIH and NSF budgets being cut.

You could say, well, it forces us to think more seriously about philanthropy and industrial sponsored research.

That could be a positive thing.

It could be that that makes us

listen more carefully to what society actually needs rather than doing basic research.

I'm a big proponent of basic research, but also maybe I'm more than average connecting the basic research to societal needs from the get-go.

I don't think it actually interferes with basic research to think and act on societal needs at the same time.

So that could be a positive.

It could be that it creates a...

another nation state that now is the dominant force, you know, like China could now become the next empire after.

Yeah, it could be for China.

I mean, you didn't specify who it's a positive story for.

You know, the U.S.

displaced Britain, which displaced, you know, Spain and Portugal.

You know, it keeps moving.

Fresh blood is sometimes a good thing.

Again, I preface this by saying I'm not advocating this.

what else could go well you know there's just certain things that we the society is fairly good at doing collectively that we're not good at doing individually you know building roads schools and science are examples of that doesn't mean we couldn't learn how to do that you know you know you know some extent when you build a gated community a lot of that is done with private funding

It's possible we could figure out how to build roads and schools and just about everything.

It means we're going to run into some kind of hyper capitalism that might mean, you know, there's all kinds of pathologies that come along with that.

Well, first of all, thank you for being so generous in your evaluation, which maybe Take it with a grain of salt but

I think that what it is, being in the right place at the right time.

So, Boston is a unique culture.

It attracts some of the best and brightest students and postdocs automatically.

It is dense enough.

Sometimes people want to spread the wealth out evenly all over the universe or the planet.

And there's advantages to having it clustered, you know, so like if you have, you know, spouses can find other jobs in the same field.

So having a concentration of biotech and pharma and science.

MIT and Harvard and BU and so forth all in one pretty walkable distance, you know, not spread out all along the east or west coast, but actually in a walkable city is one thing.

That's the starting point.

And then

a lab that chooses from from an early stage to um you know to keep this dynamic between basic science and societal needs going um at all costs um causing great trauma when the lab starts but then getting a couple of wins and it starts building up a you know a it's a positive feedback loop where um

just like the building of Boston was a positive feedback loop, the more Harvard's and MIT's and high-tech startups than pharma.

And so you get a couple of wins in the literature, and people start coming that are a whole other level up on it.

And maybe they're already aiming for entrepreneurship well before they weren't.

Anyway, it evolves in a way that you can't just jumpstart from.