Adam Marblestone & Ben Reinhardt | FRO & PARPA: Innovating in Scientific Innovation

10:35AM Oct 19, 2021

Speakers:

Keywords:

people

project

technology

fro

working

research

coordination

funding

created

program

bit

proteins

big

idea

building

organizations

led

fund

futures

artificial

All right, everyone, welcome to foresight Institute's podcast, I am really happy to be joined here today by Adam Madison and Ben Reinhart. And both of them have previously joined us in phosphates, discussions, those can be found on YouTube. And they have lots of slides, which are really interesting to look at. But if you just want to hear the to speak in discussion, then I think this is a good challenge to do. So. We had to really think really quite eye opening discussions with them. Both of them are working on projects that are interesting and complimentary. And so I encourage you to check out the YouTube video if this conversation inspires some interest in in their focus areas. Maybe we just start with either of you, ideally, both introducing themselves briefly and you know, maybe then would you like to start?

Sure. Um, I've been right now I am working on visit and creating a private OR gate. So this is for Advanced Research Projects Agency. The goal is to work on coordinated research programs that are a little bit to research for startups and to engineer coordination heavy for, for academia with some of the explicit goal of have tried to, to work on areas like physical technology that are potentially what I call dual use between Earth base that help things on Earth, but also could be very useful in space. So that's, that's me. Great. Well, I met him our will stone i'm i'm also you could say working on this somewhat related set of questions about institutional and funding structures in science and somewhat related gaps of this idea of Sir to research for startups and to systems coordination oriented for for academia. But with a slightly different angle. We're working on trying to galvanize the creation of a set of projects that we're calling focus research organizations, across a few different fields. I'm slightly different, and I think complementary to the ARPA model. And formally, I am now the CEO of a new nonprofit entity called convergent research that we created as part of the Schmidt futures network to fund the first two futures funded Fr. Rose. And also I'm a consultant for the asteria Institute where we're working on five longevity related projects and and potentially other sort of fro shaped projects.

And that's it, I didn't even know Congratulations, first of all, maybe also, Ben, do you want to say a little bit about your background? And, and maybe also, how you got into the space, like the fact that both of you are tackling, you know, complimentary problems? And how is it that the two of you met and, and what what is it that that you think is going sub optimally right now on the way that we do r&d? And, and how are you projects?

Ready to? It's your one of the last questions First, I actually don't remember that. I'm thinking it and Adam can correct me. But I think it's one of those things where you just like, start seeing someone around on the internet and eventually, like, reach out to them. I remember it at some point. I think I maybe I ran it all, at once I read a couple of things that he'd done. There's there's like some lecture that he did at MIT, as part of a course, that was really sort of addressing, talking about the idea of like, road mapping technology. And I found this extremely inspirational, into I think I reached out, it was just like, hey, let's let's talk. Um, and and one thing led to another. Yeah, I don't actually remember either. Yeah. I think that's that's actually how good friendships are is like, you're just like, I don't know. You're just folks now. I'm in my background is very great. Like I have a, I'm sort of like a weird, mixed story, roboticist. And I sort of found myself leaping from one institution that's supposed to enable more awesome site by stuff to another from like, equity. It's NASA to startups to VC, and found of all sort of lacking and that they they had a set of constraints that seemed to be constraining our set of activities that that were very important into. And that sort of led to the conclusion that, well, maybe we need new institutional structures to enable these activities. And here we are.

Well, maybe let's start with what why is r&d interesting? And you know, I mean, you already said creating awesome sci fi, sci fi futures but what is it exactly why do we need it? Why do you guys care so much about this And what's currently going on sub optimally that you think, you know, we could be doing a bit better?

Well, I think maybe we should each answer that in in our own ways. I mean, I think that the, perhaps a shared observation that that we both have these, that there are parts of the research system that are are going fine, perhaps, but that we have maybe prematurely standardized on a certain relatively limited set of institutional models for carrying out r&d projects. And that means that there are some projects that we simply can't do or would be just unreasonably difficult to try to do now. And in particular, you, you can kind of point to the sort of university based Professor led research small research lab that receives funding from a centralized federal agency, kind of on a on a per project basis for, you know, a few grad students or postdocs kind of scale of projects in the academic model. And then on the other hand, we have a lot of startups, pursuing new technologies, those are kind of the dominant go to ways for scientists and technologists to pursue their visions now. And maybe that's just not, not every project fits in that category. And yeah.

Can you give us a few examples of like, what were historical things that make you really hopeful that actually we can do it? Like, what are inspiring examples that, you know, really show like the things that we're capable of, and to cooperate well,

and II think there's some some, there was like troops at this point. But like, the transistor is sort of like your, your canonical example of what I would argue is a incredibly impactful invention that could not be created now. Because it sort of required this mix of people simultaneously working on theory, and just like grinding in the machine shop, and talking to each other constantly. And because as, as Adam pointed out, because it's sort of the dominant models, nobody's incentivized to do that. And so, I think that that's, that's one example. But, you know, it's like, you sort of look around, wherever you if you're, you're in a built environment right now. And everything from like, the materials, you know, it's like the plastics that are probably around you to the screens to the thing that you're listening to this on. And, I would argue, are all products of a set of activities that don't wouldn't quite fit into the current institutional models. Yeah, you know, I would, I would also point even to some some examples of historical successes that that do require the kind of tight knit, you know, systems coordination that that were interested in, I mean, mRNA vaccine just coming up recently as in very heavily as a result of DARPA, or sort of DARPA involvement, participate in some ways, kind of rescuing a field that was otherwise very poorly supported. And also then later, you know, flagship ventures, very deliberately incubating and kind of nucleating a goal driven company that would do mRNA vaccines. And that required a pretty large scale, that sort of upfront work to do so that I think that's a big success story. Another one that people point to is that I think it's 2015 Nobel Prize was for this Laser Interferometer gravitational wave observatory logo that detected gravitational waves for the first time. That was like a many decade, very coordinated, difficult project to do. That required its own engineering team, it's on scientific team, and really shows I think, what, what the physics community was able to put together just for a pure basic science question. I think actually, to riff on that. One, I think perhaps, I'm guilty of distance, like over focusing on the technology piece of it, that only how it's coordinated effort can can lead to better technology, but you'll also see it sort of going the other way, like, the way that we discovered the cosmic microwave background is that you actually had some people tried to build like useful technology at Bell Labs, and they went and like, we're trying to get this this microwave antenna working, and they just couldn't get this noise. They couldn't be noise it until you actually the tight integration doesn't just lead to better technology. But we we've seen that also, historically, it's led to new scientific discoveries as well.

What a nice collateral benefit. Okay, lovely. Well, so now let's maybe drill a little bit deeper into how is it that each of your projects a popper and fo are trying to and trying to get help? And how are they complimentary?

So with it, Parker's trying to help is that were to just give it an overview of the way the model works is that you have a extremely powered program manager who's basically the CEO of the program, they can spend money, however they want, they go at the first sort of put together a program designed to say, Okay, this is this is our goal, as precise as possible, these are the different groups that will work on these different projects, this is sort of how it's gonna take a Hello, it's gonna take. And then they go and first fund a few initial sort of de risking spirits, sort of different parallel paths. So in various organizations, whether it's its startups, labs, or, you know, it's like contract research companies, and then eventually move on to a bigger program where they're sort of funding a number of parallel projects and coordinate and making sure that there's this coordination between them. And so one, one way that it helps is because it's private, it lets us be a little bit less responsible than big average. Is it the winning sort of by microarray analyses is that there's there's this fundamental tension in government manage research, in the sense that one, at least here in the United States use, the government is funded by taxpayers, and you sort of want them to be responsible with your money. At the same time, doing really sort of groundbreaking work often requires acting irresponsibly. So there's a fundamental tension there. So so that's one another is I think it actually sort of goes against the dominant paradigm, which is sort of having very opinionated funding in like, sort of, like top down managing it, as opposed to just say, like, okay, like tenders proposals for project symbol funding, I think that the coordination piece is important to know underdone in the three just sort of like explicitly going out and trying to look for areas that don't make that just are not incentivize and sort of, like delete that gap. And the way that they're complimentary is that you can almost imagine that an ideal outcome for a project would that be that eventually the the sort of like parallel tracks all sort of converge on a project that needs to sort of go all under one roof, and you could very easily imagine that the idea of a proper project would actually become an frm. So and this

is a great time to pay back. What is an F?

Great, great, yeah, absolutely. So and I think, I think it's a great way to introduce it also. Because it is targeting, in some ways, this the same type of issue of projects that require a kind of very coordinated effort of, of multiple people, a whole team to develop something even at a very pre commercial stage that one thinks of as still kind of fundamental research or tools to enable fundamental research. So I think there are going to be many, many problems that might fit this ARPA program model, where what you do is you have a relatively lightweight internal organization, often just a program manager and a couple of kind of advisory staff or things like that. And what they do is they distribute funding to a bunch of external existing entities, but they do it in a way that galvanizes those entities to coordinate with each other and reach for stretch goals or identify types of systems that they could develop, that they wouldn't develop on their own in the absence of that funding in that coordination. I think that will work for many, many problems. I think there's a subset of problems that require such tight knit coordination, particularly at later stages where you're trying to build a very reliable and robust system or process not just to sort of demonstrate that that it's such a process as possible but but to actually really refine it down to a to a working implementation, where you to some extent, you need more people under one roof. And so and so the inspiration for these focus research organizations is really less An ARPA program and more something that is functionally looks a little bit like the internal structure of, let's say, a series a biotech or kind of deep tech startup, where as a CEO, it has internal operations, it has management, it has a permit, you know, scientific stuff, although, although the frozen themselves would also be time bound projects that are sort of very much driven by a particular goal, rather than any sort of commercial or financial markets. And they're just defined by a particular goal. So you can sort of think of what fro is like, a little bit like a DARPA program under one roof, or a day as often targeted, or slightly later stage system development, but still in the realm of pre commercial research, or enabling tools.

Thank you. Okay, lovely. So now that we, I think, have a little bit of the theory down. And I would just suggest to everyone who's interested in this, you know, if you want to actually look at the structure of both of these organizations, and there's lots written on Adams and on Ben's website, and maybe we'll get into the particular funding sections, again, you know, later in this conversation, every time but I think, maybe to color it in a little bit of like, how would those programs actually work? And maybe, let's take an example. And nobody's after pink, then the one that we had in discussion a few weeks ago, about, and so maybe, you know, when you can keep us off with, what do you find particularly interesting about artificial molecular machines? And how could a popper like structure go about building them?

Yeah, so the, I mean, the thing that's interesting about them is so like, the long term vision, in my mind is, is like, I think that, you know, it's like, you look at findings, there's plenty at the bottom paper, this, this idea of like, we could, ideally with them, just like control matter at the atomic book written like that's, that's it's a big, like, what could we possibly do with that, like, big materials, you could never imagine making things big now, much less energy or much stupid situations. So that's, that's why they're exciting, why I think that the, I think, particularly excited through the lens of like, a probit. program is, so how familiar are people with artificial aquiver? sheet? Like, should I shouldn't say like, give them a brief what we're talking about? Yeah, so basically, the Yeah, is that there's, there's a whole lot of different sort of mechanisms that add sort of letter level, you can do things that you'd sort of imagined, like a macro scale machine doing, like moving something from one place to another or spinny. Or, or pushing into, there's, there's this sense that we should be able to combine all these machines together into a molecular factory, say, the reason that, I think that it's worth looking at from the perspective of with purpa is that it feels like there's all these like really high potential Lego pieces. And everybody is working on their particular Lego piece, molecular machine. And there's sort of like this a gear that they should be able to be combined into something amazing, but the problem is that people are not incentivized to combine them. And there's not a good sense of like, even if you put them together, like what is the picture on the Lego box? And so the hypothesis is that we should be like, with a little bit of, you know, coordinated coordination, the flanking and management, we should be able to figure out what, what we could actually combine them to do, and that incentivize the work to do that.

Okay, that's nice in a nutshell, and what does an artificial rhizome have to do with that entire thing?

So So artificial racism is is certainly the catchy term that sort of stuck all of this under where if you look at the red zone, which is the cells machinery for producing for taking RNA, which comes from DNA and turning it into proteins, it you can sort of abstract away from what it does, which is stick together the economical amino acids and say, look at it from sort of like a an architecture view. At the end of the day, my brain works sleeping systems engineer, so I look at it and I say like, Okay, what is this thing? It is, I think that tape bed is programmable, right? Like you program it with the RNA and it takes native skill building blocks, which are the The amino acids, and it creates covalent bonds between them, and then release them into the environment. And so the, the, I think a compelling framing on like what to do with liquid machines is to say like, okay, could we recreate this architecture, but with things that, like he or without it being limited to recombining the canonical amino acids, so you could possibly create 2d structures instead of one v structures you could possibly use non canonical amino acids or completely non amino acid building blocks. And that could lead to us be able to do many more things than what we could do just proteins.

Okay, thanks. And I think, you know, again, if you are interested in more of this, and check out the YouTube video that we did on this topic, and I think from Adam, you know, embed YouTube video, you have this amazing slide where like, when it's like, imagine it is a program that is a Verizon that looks something like that, and then fill in the blanks. And so Adam, can you fill us things to fill in those blanks?

Here? I'll say a few things about this. So one thing is, I think that this artificial ribosome idea is actually very good as the kind of pop up program in the sand as opposed to in frl, as opposed to other kinds of projects. Because it really is a kind of broadly interpretable idea of some how would you put the pieces together to make something like the rhizome, this natural machine that makes all the proteins in ourselves, but a different in some way are made artificial in some way. And you can imagine a part by type program, catalyzing researchers at all sorts of existing institutions and work on pieces of this to sort of say, well, whom well maybe we could make something that would actually make a different kind of polymer than protein. Or maybe we could make something that would be two dimensional instead of one dimensional chains. At the same time, I'm like, in my mind, I think it's interesting because there are certain kinds of systems within that class that seem to have some real technological interest. And like, you know, this is the foresight Institute, when I was a kid, I was reading about nanotechnology and molecular assemblers and those kinds of ideas. And if you think about what that involves, I mean, it basically involves being able to direct particular covalent bonds between particular small molecules, let's say, to form any particular pattern using some sort of position or spatial control or some kind of programmable control, as opposed to just letting those molecules bump into each other, and basically forming all possible bonds that they could possibly form with each other, consistent with sort of steric hindrance on what their shapes are, which is more like the self assembly or, or kind of traditional chemical synthesis paradigm, right? So you kind of want to have directed assembly, that also does make specific covalent bonds between specific molecules, right down at the molecular level. And if you think about it, if you start with the ribosome, and you sort of keep changing things, so maybe it doesn't have to just make one dimensional chains of amino acids, maybe you could make 2d covalent assemblies of things other than amino acids, maybe it wouldn't just use an RNA to program about assembly, it could use an external, you know, control system that could shine different wavelengths of light, or change the salt concentration or things like that, in the in the solution to tell it how to move along each axis of two or three dimensions to basically print, you know which building block goes where so if you sort of generalize this idea of the rhizome enough, you actually get something that looks like a molecular 3d printer, which, you know, internally kind of seems like a real interest potentially, in nanotechnology. But then on the other end of that spectrum, you're really just starting with kind of ideas that already existed, you know, out in fields are sort of saying, Well, you know, what, if we could get a few of you people to collaborate together more, and then make something more rhizome like. So this sort of you sort of have a path from where we exist in the academic fields that exist now to something that looks more like an interesting system. And that's, I think that's exactly why that would be a good that's an example of a parka. Type program.

Totally, I mean, it really sounds really interesting. But like, as a lay person, why would I care? What's like the elevator pitch? Like what kinds of applications I think, you know, like when you already mentioned, like, what's on top of the Lego box? Like, what what will be on what would be on the Lego box? Like what what house would I benefit and when.

So, the thing that I want to flag is like, the that attitude is, I think, one of the like, if I could answer that question in a very compelling way, then I could start a start up. Okay, so so like that's, that's the thing that I, I want to flag and the sort of work that needs to be done is like, we don't even know what the affordances are. The feeling would be, so I could, I can like say a few things, um, that are hypothetical, but like the, the the sort of like message they want to get across like sometimes like if so for example, transistors were like we thought that they were going to replace vacuum tubes and underwater sea cables. And that would not be very exciting to anybody. Because they had no idea that they're going to be able to be used for peers. So that being said, like some very concrete things to just like, imagine what proteins could do right now. And then imagine being able to do those things with different constraints. So for example, like proteins do, like catalyze all these reactions. And they sort of like bridges are like really good catalysts, and they can do all these things. But the D nature, I'm under pretty low temperatures comparatively. And they're huge. Because they need to use these like windy chains to fold up nerd to get up 3d active site. So if you could imagine, with creating that same active site, but much slower, that they will be able to lead back that candidates will be able to go places that they currently can't go like crossing the blood brain barrier, for example, or working in much harsher conditions that proteins can act on. So that's, that's, that's one thing. Another is like you can sort of imagine like, what do also like parties did while they make like all these, like incredible materials? Like what if we could create like tuneable wood? Right? Like, what is one of the most amazing engineering materials that exist? It's created just by by cells? And imagine if you could actually like, add to it to to have properties that you want? I think those are the two concrete examples.

Okay, I'm sold. Unless you have anything to add, and, you know, we Yeah,

well, I largely agree, I think that one of the struggles with molecular 3d printer ideas, it's it's distinctly unclear how, how good the first ones will be they it's, it's not at all clear that the first molecular 3d printer you make wouldn't be good enough to make the next molecular 3d printer even better, for example. And so it is actually inherently quite difficult a path, you know, to go on. But I that doesn't mean we shouldn't go on it, because I think it is potentially exploring a whole new area of fabrication, but also the more generally, the artificial ribosome idea has these other kinds of, you know, potential avenues that like that Ben was talking about. So

lots of collateral benefits that we may expect, who knows what we'll discover next? M. Okay, so let's say we have that visual resume as one potential example, I think, you know, you we really got quite concrete there as well. But you know, you surveyed a variety of different areas. So be super curious, what else you uncovered here? And I think, Adam, you know, you're particularly interested in a topic that's also very close to its heart apart from molecular machines, which is longevity? And could you tell us a little bit about your process there? And what you uncovered?

Yeah, well, I can actually tell you now we have, I would say, it's almost a fro it's kind of, I think, if we're being super honest about it's a fro inspired project, getting launched on longevity called the rejuvenation. And I think that it, this is funded by the astera Institute, and is also getting partially executed out of the asteria Institute, and then partially in collaboration with the buck Institute for Research on aging, that the sparrows is funding and partnering with. So this is sort of a fro shaped project in the sense that it requires some dedicated management and kind of full time staff to be spun up in a bespoke way. Not it's not an existing facility or something that that just does, you sort of have to just spin up the management of the goals and everything in the leadership and in a, in a bespoke project specific fashion. On this, it's sort of very goal driven. And it's, it is something that is at a level of scale, that if not, if not well incentivize for any one particular, you know, student or postdoc to have that be their PhD thesis or their their individual publication. It's really a a sort of systems are kind of large scale kind of medium scale science, I think is the way you would describe it. So So what is it so the basic observation, again, because of the way that academia is funded, you can think of it this way, where you have many different individual labs pursuing many different individual scientific hypotheses and they sort of need to be going for scientific novelty for each thing that becomes someone's PhD thesis or or tenure package or so on in the academic world. That is mostly the world that's that does aging biology research. Have a fundamental claim, as opposed to, let's say drug development for particular compounds or things like that that industry is doing more. In that world, you have this problem that like, let's say, I'm studying, you know, a particular molecule that might affect the aging process. Well, in a particular lab, I might be allowed to studies aging of the brain. So I might just look at the brain. Or I might have another lab that looks across the whole body, Edison, RNA biology labs with only looks at RNA doesn't look like protein. So with the rejuvenate, basically, we're just trying to create a systematic pipeline that will look at all of those things for a set of aging interventions. And we'll do it in genetically diverse mice across their age, across their lifespan. And it will basically try to understand what are the kind of axes of variation? What are the different kinds of ways you can affect the aging process that you imagine you have the old state, you have the young state, there's a huge number of differences between them, we don't really understand what causes aging, or what's really going on there various theories about it at different levels of abstraction, but we don't really understand so you have this huge vector, this huge, complicated state of the system that's old and you have the status system this young. If you do different perturbations to the old state, you know, what are the different directions you can go? If you combine perturbations, can you chart a path where you sort of make your way back to the young state, it's not enough to just ask about the liver or the kidney, or some particular thing to do that, you have to actually look at the whole body and you have to look at across genetically diverse animals to be able to characterize that. So that's what the human is going to do. And that is now something that has come into existence as a result of this kind of road mapping process that had been in I like to do this one was in collaboration with Jose Luis recon, and several others, and is now now led by Nick Strom, who was previously doing one of the previous larger scale aging projects at Stanford. So that we sort of charted this process of identifying a gap, and then building not exactly an institution, but a, in this case, it's sort of halfway between a fro and a Powerpuff. Type project.

Well, you have to come up with a name, which is when the to marry like a frog. I don't know

that you're not building sexual projects.

No, but you know, I remember when, when when will say a new presented to our group, like a year ago, about this, probably a lot has changed. So I am sure that no, people want some initial understanding of the project, they could maybe go back into their presentation, but probably there's lots and lots of, of new and more updated stuff that that will be published soon, and the organizations that you've just mentioned, and are there any other projects that you'd like to add? Is there anything you want to bring to people's minds? And you can only have your eyes on so many balls? would wish other people spin out on? Or? If nothing then is there anything particularly interesting that you learned along the way that were you like, this is interesting? Oh, no, it really isn't like any learnings here that you want to share for fellow people that go down the same path.

Oh, so I mean, parklet is working like that. The artificial rhizome. It's only one of several programs that we're looking to start. Frankly, like the the thing that we're bottlenecked on is amazing program managers, I have a giant list of programs that I look to read and I have extremely limited in my ability to come up with or discover ideas. So that's so it's certainly not the only thing everything from general purpose tell robotics to like pulling to make useful products out of carbon dioxide into the atmosphere of Mars or the earth to like artificial cells, because like the artificial ribosomes need to work in an enclosed out of equilibrium location to the idea of like atomic forges all sorts of things. So there's, there's sort of no limit there, I think, one lesson that, but maybe it's like, I need this, but like I learned it, ever more. So is that like, incentives matter? And so you sort of thinking about what is going to like the people that you want to work with, regardless of the project is like, thinking about what really motivates them. And at the end of the day, it's it's still all about people like we like to talk about research as like this kind of abstract things like oh, and there are papers, and in the paper, like the papers are knowledge and that knowledge combines to make more knowledge, but at the end of the day, it's about people in their idiosyncrasies, and what they want to do And I think actually, if I could say like one sort of like interesting meta learning is that I think that this like, sort of idea about this economist idea that like people just want more money better to buy buy more money is, it's completely wrong. And that people like, people want to be able to have a family and kids and like liquid they want, and they want enough money to be able to do that. And but beyond that they like really want to work on like, awesome stuff. So we sort of like figuring out like that sweet spot is is a big trip. Yeah, I agree with that. And I should say we're very actively seeking. You know, again, there's sort of these two entities that have expressed interest in FRS so far one one is this, this new convergent research nonprofits, that's part of the Schmidt futures network, which will both help to incubate the first two Fr. O's that we're doing one, one through that mechanism. One is on brain mapping technology. And one is on synthetic biology tools for sort of non model micro organisms, organisms, other than the typical ones, like E. coli and use that are mostly getting used and published on. But you know, it's also going to be working on actively finding and incubating more. And then also, you know, the asteria Institute has on his website, it is also in addition to pop up as a concept also interested in finding more fro so we're very actively looking for them, I would say one of the things that I'm struggling with, on that front is like generally, I'm very techno optimistic and sort of more technology is, is is good. And, and we want to have more tools in our tool belts, always. But I'm also trying to think a lot about sort of responding to this, like, if you want long term critique of, of tech development, which is to say, Well, you know, it really depends on which order, you do things. So if you make something we're synthesizing viruses, right and left, that might be great for gene therapy. And actually, gene therapy might in turn be great for getting off the planet and avoiding certain kinds of risks. But this might be particularly bad for, you know, engineered pandemic type risk, if people get really good at synthesizing viruses. So we're probably not going to do in fry synthesizing viruses, even though you know that that might be helpful for some things, but but we might be very much be looking for something like really advanced sequencing technology to help us detect the next pandemic before it starts. So I think that's another meta level question, if we really do get to the point where we can sort of shape more which technologies come out when beyond just the usual market forces, then we have a lot of responsibility to sort of choose those. Well, so that's, that's something that is definitely going to be top of mind also for us can can improve on that slowly? It is, I think, it's not just a matter of

timing of which technologies come out what, but really the context in which technologies are created. So my favorite historical example, this is nuclear power, which now you know, it's like you think of it, it's like I did like this. You see it with the atomic bomb, any considered imagine the world where they created nuclear power reactors, before they created the atomic bomb. And so people were first introduced to sort of, like, atomic based technology in the context of cheap power, as opposed to death and destruction. And we may live people living in a very different world today, and to sort of thinking about how to use technologies for something beneficial, first, can lead sheep will respond to

Yeah, I think the differential technology angles, like, you know, preferentially accelerating those applications that you know, people that that we want, I think, is a good angle to heaven. And even just that enculturation of like, you know, building high trust teams that are more transdisciplinary than you usually have, is, I think, also really important does on the long run, you know, when when risk pop up, people need to be able to cooperate. And I think doing that early, and when stakes are low, is potentially another collateral benefit that could come up, come out of it. And okay, great. So yeah, I love that we and that we, that we tackle that, that risk angle to me, I think, you know, the long term critique is definitely always like, you know, center of mind if we want to have a really long future, which of these things matter, then we should we need to get there too. And so, you know, now that we, I guess, have a few examples on our hand. You know, those are not theoretical, right? You guys are working on it day to day. So could you maybe talk a little bit about, you know, how does that look like? What are current bottlenecks here? You know, what are Yeah, like? How does it look like let's say, you know, if you were recruiting me, then you need more program managers, right? Like, what would I be doing? And what's the Korean bottleneck that you're facing? And, and how can I help

that so very quickly, it's like, wake up in the morning, you read some papers that you think might hint at an exciting area, like, like, you know, they're like research papers. And then you contact the authors, and you say, Oh, I saw your research paper was really interesting. Like, like, let's talk about, like, extensions of that are like, what, what are your bottlenecks as, as the researcher? And then, like, Who else should I talk to what other papers should agreed and sort of, like, do this when I didn't call it like, it was like a graph exploration of people, all the while sort of paying attention to who, who is, like, sort of excited to work, who's excited about the actual research, as opposed to like, just getting more funding to publish more papers? You know, who, who has has a vision? Which things seemed promising, which, which people do you talk to, or sort of forget, I call them the three things but maybe don't know about each other, it's sort of like building up this both in your mind, and then like, sort of fleshing it out in what I was call, like a proto roadmap or what have you. And then sort of figuring out like, who are the like, the relevant people then start running workshops, to sort of get people to like, slam ideas against each other, right? Like, it's very easy to go from person to person, and like, have all these fluffy ideas that what you really want to do, it's sort of like get it synthesis. And then eventually, sort of really coming up with a plan. It's like, okay, like, I want to fund these people to do these things. And so that's, that's sort of like the the day to day of starting a program. And so if that sounds interesting to people, then you should get in touch. Yeah, that's very similar also to how we think about finding frm sort of founding teams, the pharaohs are also constrained in in some other ways, I mean, it really has to be not good as a startup, because then you should just go and do a startup, it really has to be not doable as an academic project, we should just do that. And yet, it has to be sort of intrinsically motivating. I think there's, I think there's no way around it. Certainly, if you're creating new industries, you know, read the ground floor of something, and so on. But, but you know, these are nonprofits. And really, the purpose is to do projects, you really have to have people that have been itching to do a project, you know, for the last 10 years or something and not found a way to do that. And then have that then have the right shape, have those people be at the right place, and the right time to get involved in that, and then have the overall project that you create, in terms of the kinds of job opportunities that it has transition plans, and so on, that can come out of it. Be appealing also, to recruit that team. So I think that firms have, in some ways, a little bit more fertile. Harper has to get a really good program manager, and then probably there are going to be a decent number of researchers that are willing Tell me if this is wrong, then there'll be a decent number of researchers that you can find somewhere willing in their own homes, to to work on that program, the fro has a bit of a hurdle. But at the same time, I don't think there have to be 1000s and 1000s of rows, I think that we will want to do is for each field find and taking an account of differential technology development and other types of ethical types of issues and so on, we want to find what are maybe the dozen or so, you know, maybe a few dozen fro shaped bottlenecks across fields and that and then create ones for those. And so you have to solve this problem, but you don't have to solve it 1000s and 1000s of times, you may be able to solve it a few dozen times, collectively, both with our organizations and with what other funders and other people end up doing with their own interpretation of that concept. Because this fro idea really also is just like a meeting and even the arbor program ideas is in some ways just a meme. It's something that you want people to start organizing around but it doesn't have to be completely you know, narrowly defined when it's done by other people.

Okay, so that's you know, if I was potentially a program manager, you know, the leader of the project, and you know, if, let's say someone who's more on the funding side is listening to this right. And I know that you have the exact structures of your organizations which are, you know, have quite a complex legal angle. You know, to tackle this complex, and to take this really complex, innovative space on your websites, but you know, as a funder, you know, like philanthropic money, investing money, like, you know, what's interesting here on that from that perspective.

So, I think the way that I set up Harper at least his position like three is to try to appeal to fit in is from that account for a funders. So there's like, it's, it's sort of underground like that sort of like the concept of organization itself interesting. Like we can we have a nonprofit entity. But at the same time, like, I understand that, it's like, sort of like weird and new, and often people want to find, like, nope, sort of know what they're funding. And so the approach we're taking is to really sort of fun programs on it for rebate program basis. And then, at the same time, we've also said to set up a for profit entity, which is, is basically there as a holding company, for like, if, like we down the road, it ends up be making sense that like, the way he could also imagine that like, a program becomes a fro. And then at the end of the fro they're like, okay, like there's there's like actually a a business here. And the best way to get the technology to the world is by starting a business around it, which which like, eventually is often the case. We set up a for profit entity to capture some of that value, both to feed it back into the research, and to potentially make a return for vendors. And so that's there's sort of like those, there's three avenues. In the bet there is like, well, this is probably a big zero. But if we manage to admit to the industry, then it will not be

there'll be many big zeros after different numbers. Adam, how would

you? Yeah, well, so for froze, you know, there's a couple parallel efforts. So we are, you know, I got into this partly through Tom Coolio who you both know, who's been involved in many national science initiatives in the past, like the Brain Initiative and the National Nanotechnology Initiative. And we published a white paper through the day one project whose progress is to try to get the government basically to be exposed to good Science and Technology Policy type ideas. So there's one possibility the government could eventually fund froze as a kind of alternative mechanism for for some of the things that it does. But mostly, I'm thinking about philanthropists. And I think that fros are actually a very good match for philanthropists, because they're very goal driven. So rather than saying, Hey, I'm going to endow, you know, this university, this department, this general field of neuroscience, or something like that, you know, for the brain mapping project, we'd be saying, you know, this is a tool that we're going to develop in five years that if it works, and we're going to tightly manage it and drive it so that everything is focused on getting that to work. And if it works, is going to lift all the boats in neuroscience, but it was very well defined way. So you're really it's more like, in a not for profit sense. It's, it's more like a, well, a very well defined product, right? It's sort of here's what, here's what you get out. And I think that, in principle, a lot of philanthropist, including ones that have made their money on kind of big tech businesses are sort of executing milestone driven businesses or things like that, they would, they would, rather than just supporting a general amorphous area or cause area, they could say, well, we really got we're going to get the 10x speed up and brain mapping from this project, you know, in a defined period of time, so I think it could be a very good match for philanthropists across various areas.

Yeah, that coordination hurdle, I think, is a hard one, especially even people, you know, newly join offers, like groups and that I want to help but like, what are other people doing? where things are conditional on others? Like, like, Is there a plan? And so I think, you know, currently, it's done really quite essential. decentralize and, and via really the goodwill of lots of people in the space that take a lot of time to onboard people into the mix. And you know, but I think by with some coordination, we could definitely streamline and speed up a few things there perhaps, and, okay, maybe it's, you know, my last question here as a big one. And, you know, what, like, you know, take us a little bit like on a walk, like what would failure or success look like? I mean, those two things are, you know, you have two hypothesis, you're training them and testing them out in the wild, right? And like, what would it look like, you know, that stain and Tasha 10 years if you think if you said okay, actually like, Yeah, probably I wasn't quite right. This is not really the way that that we hit the end of that we hit the amazing, safer futures that we want. But on the other hand, also, what would it look like, if you like, Oh, well, this was extremely successful, perhaps not only in terms of the individual technology areas that you're focusing on, but also in terms of maybe creating, you know, broader scale, you know, change in the scientific ecosystem as a whole. If that is anything that you care about at all, or maybe it is just that you want to focus on this one tech and, and it should just get done. And we want to just, you know, run off, maybe it is that you're aiming a little bit more of it as a, you know, yeah, as a credible cloud of influence on the entire ecosystem to anyway, I didn't want to put words in your mouth. But here a few options.

Yeah, I think I think, you know, for for, for the FRS, I think they, first of all, they should be part of a broader ecosystem. Again, there's only a very small minority of problems that probably has that exact right shape. If we have frozen parka and several other new sort of diversification, some of the ecosystem, then you know, one thing that I think would be great, you know, if you're, you're graduating your, your grad school, or you're, you've been working in in a company for a while you're thinking, What's the next big thing that I should do that? This doing a fro is like, on the table for you? Like, right, like, right now, if you want to do a scientific sort of medium scale, kind of mega projects, like, like, endeavor? You know, unless you're the director of the Allen Institute, or, or genelia, or the NIH or something like that, it's very hard to contemplate, and again, there's this huge coordination barrier, how would you even conceive of finding the funders for that? How would you find co founders for that they're all doing something else, or so on. And so if we provide this locus that, like, a fro could just be an option, that you know, and people take that seriously, and maybe even go from one to the next? That would be really good.

You will throw intrapreneurs I love it, then what about you assume

in terms of success, I think, honestly, having one program that people to look at and say like, oh, that actually made something happen, that would not otherwise have happened, I sort of think of this as bending s curves. So you think of like an S curve. And, you know, everybody sort of looks at it, it's that before, before it's at the steep part, it's just sort of like, flat, and people look at it, and imagine that it's gonna be like that forever. And, but then, all of a sudden, like, there's some intervention, and it sort of picks up steam. So that would be that would be, I think, one level of tests, another level of sense would be people starting, sort of, like similar organizations to go after many different areas. So So I think, so we have to think strongly about research organizations is that they, they don't scale like startup companies. And so you really can't have a really massive one. And so what you need to do is have many different ones. And then, sort of at the, at the ecosystem level, I also think about new research organizations as sort of putting pressure on the legacy institutions in the sense that if, all of a sudden, he starts he enters aid and probiotics and other things, to having results that, you know, like national labs and universities or not, then you'll start to get pressure on people to be like, oh, like, what could we do better? Right, like, so I'm actually optimistic that the existing institutions can, can do better, but I think that he sort of need almost like, a little bit of competitive pressure to change that. So that's another sort of optimistic scenario. And it really just looks like either, like, the things that are successful, just being things that would would have been funded anyway. Or like, would just sort of put a bat in there anyway. Or simply just like, you know, you try to get off the ground, and it sort of ends up being a big,

nothing burger. Yeah, I really feel you're on the S curves, I think, you know, like, one thing that is interesting working for foresight is like when I go into our archives, you know, 30 years ago, people were like, really gung ho on much of the technology that we're now discussing. And and then you know, there was there seemed to be like another like, little bit of a dip of a winter he knows especially I mean, in lots of fields, you know, but from election machines into biotech in longevity and especially what you saw with longevity really just kicked off, and I think since COVID, that lots of crypto money coming in and and now suddenly, it was always this thing that was obviously going to happen, but I really remember just like three, four years ago, when you tell people about it, and we're just like, yeah, this is nuts. And so it's, it's really hard on the other end on the other side, to remember how it was just a For a few years ago, and suddenly janome

isn't even the biggest project in longevity anymore. But a year ago, it seemed like Gosh, wow, that's nigh impossible that that would ever work. And he sees this throughout history, like autonomous cars are another example where like, people have been working on them, like now now everybody picks up like economist cards is the future. But like, in the early 2000s, before the DARPA Grand Challenge, it was just like this weird, esoteric research area that people have been working on for decades. Same thing with neural nets, right, like everybody's like, oh, AI. But, you know, before, before the early 2010s, neurologically, people like couldn't get money to fund their research.

And I feel like mostly with I mean, longevity is now almost like a no brainer, but I think with molecular machine, certainly that there's still, I think we're still in that stage, we're probably in the next two to three, maybe even five years, that's when people will catch on, and they're like, oh, and that's when that new wave will come. And again, it will, like as an S curve does, you know, like weather out, and then we'll just have to strap our seatbelts on and kind of plow through while the next kind of phase

I agree to stay for 20 years in those fields because eventually they kick off but the key thing is that it's not inevitable this is the thing that I want to flag in with the reason that at least I'm doing what I'm doing and and Adam II don't want to put words in your mouth, but I think he feels to me really is that at the same time, like, like, it's easy to sort of like look back at the successes and say like, Oh, it was it was inevitable. We could also look back throughout history and see all these things that just to actually die for it, like you know, it's like like nuclear powered airplanes or steam powered cars. They've sort of all the nuclear he'd always make an argument for like, why the technology is fundamentally unsuitable, but I think you could equally make an argument that like well, you know, it just didn't have it's like S curve bending moment because it didn't do it intervention. So the thing is that like it's worth being really optimistic about but it's not something that it will just doesn't just happen on its own people need to like do things and have opinions and like push these things forward.

Sorry to kind of wait until the next podcast in 20 years when summer would have totally proven you wrong and use it as an example for why those things are actually amazing technologies that we always needed. But but this is exactly i think you know, what you what do you guys are trying to do just like you know, speed up that discovery process like that meta discovery process of finding out what actually is in the bucket of S curve and what is in the bucket of like, you know, weathering out and so yeah, I mean you know, I cannot wait until we have a continuation of this podcast maybe in you know, in 10 years and you know, we're just check back in on the progress and you know, we'll evaluate the experiment. Like you know, one thing that I think is really interesting, you know, I guess about the foster community when I come in and look into archives people have a really long breath you know, like so many folks that I still you know, and I know in our working groups they've been at this for so long and now I think it's kind of you know, on us to just pay it forward and also just be patient and plow away as you know as like you know, new means arise like and as new people move in and they move out again, you know, like, bubbles will burst but I think that on the long run Yeah, I'm super just really excited to look back at this meta experiment. And in 10 to 20 years then we'll probably have a variety of different throws poppers and other children spun out from berries from various Yeah, geniuses that are just being born as we speak.

All right. Yeah. foresight also a meta experiment I would say that same same category Yeah.

Well, let's see. Okay, well, thank you guys. I really like this. Yeah, this was quite uplifting, quite XRP and I'm hoping that people check out your individual websites do you just want to say one word about how best to find you? And then we can wrap

it up? Find me on twitter at then underscore rainford Yep, first name, last name, Twitter or.com.

I'm already excited when people will use which which social system they will use and next time I will speak. Let's see. Um, okay. Well, thank you so, so much for joining M and yeah, videos.