You are living in the most disruptive time in human history. Given the advances in AI and biotechnology, you might have to contend with the possibility of human immortality. It's certainly not a guarantee, but advances in health, man, anti-aging and cellular biology make it one of the most important conversations of our time. Investments and decisions made now will reverberate for generations to come.
Here to talk about the state of affairs is Dr. Bill Green. You as an investor have a very difficult job. And as an investor, you have to bet against the consensus and be right.
So what I want to know is what is it that you really believe in in your specialty of biotech that you're willing to bet big on. Fundamentally, we're here to invest in people and companies and ideas that are going to lead to real breakthrough therapeutics that can treat, delay, and even prevent diseases of aging. More broadly in biotech, we're here to create the next generation of therapies that are safer, more effective, and more tailored to the actual problem that individuals have as opposed to really broad populations. And that's exciting.
How far are we going to be able to push it? So if we can slow down aging, I'm sure we can both agree on that. The question becomes, can we stop aging? Can we reverse it?
The short answer is absolutely. We know we can in worms, sometimes in mice. Can we do it in humans? At the level of ourselves?
Yes. Can we do at the level of our whole body? Maybe the question is, do we want to? What we really want to do is live our lives in health with vitality and not spend increasing portions of our lives debilitated by chronic disease.
That's what most people really think about. They don't necessarily want to live forever, but they definitely want to live healthy. I do. Most of us do.
And that absolutely has a role to play with the biology of aging, with slowing down the processes by which aging, if you will, goes wrong. I'll be very eager to have the debate about whether we should want to or actually live forever. But first I want to know, so given that you're looking at this, there's a real shot that we're going to be able to. We know we can reverse it in a cell, but there's a shot that we might be able to, as we get more breakthroughs, do that at the level of the whole body.
What is the bet? As you look at this as an investor, there's going to be a few things on the table that you think, okay, it's maybe one of these and I'll make this number up, but maybe one of these five things. What is that small handful of things that you think have a real shot to be a blockbuster? Some of what really leads to chronic disease and degenerative disease is fibrosis.
It literally, instead of being pliable and resilient, our tissues can get fibrotic and connective tissue builds up and actually not only reduces the ability to move, but actually reduces the function. So think about your heart, which has to be every second. If it becomes fibros, it can't expand, it can't relax, it can't beat strongly. And that's one of the causes of heart failure.
If we could actually, and we've thought that that fibrotic process is a one way street, once it starts, you may be can slow it down, but you could never stop it or reverse it. If we could reverse fibrosis, we could unlock a lot of resilience in our organs and tissues, and that could actually reverse some of the diseases of aging. Is there anything that we see in the research that that's promising? Like, is somebody actually working on this?
Lots of companies are working on it. And even more encouragingly, researchers from a variety of biology perspectives are really looking at the connection between chronic inflammation and how that leads to fibrosis and looking at that edge of how does it become, has it crossed that line from I'm inflamed to I'm actually building up unhealthy connective tissue and being becoming restrictive. So there's lots of research going on there. There's lots of sciences working on it.
I can't say today who's going to find the exact right thing, but I'm highly confident that given the thoughtful thoughtfulness and investment in research that we will have several ideas to try out as therapeutics. And one of them may well work. How do you evaluate a company? So for people listening that don't know a lot about biotech investing, it's had a brutal bear market the last couple of years.
Some people think that maybe we're beginning to thaw out again, going back to the idea, you have to be able to bet against the consensus and be right. How do you look into this? Are you evaluating the entrepreneurs? Are you evaluating the science?
How do you develop confidence when the world thinks you're crazy? You have to be a little crazy to invest in biotechnology because there's so many ways that things can go wrong. And at its heart, while we study the science, we utilize the science, we exploit the science. We don't know all the science.
So by doing clinical trials, by developing a drug, it turns out we discover more science. Unfortunately, sometimes that means the answer is no. So at its heart, we invest in people. It's people that make this work.
It's people that figure out the science, it's people that use what they're learning along the way to go back and question their assumptions and refocus to find the right path that they find around the wrong path. That's a hard skill. It's a rare quality. And that's what we look to invest in.
If we find those people and help those people create companies, there's a definitely higher chance of success. What do you think about somebody like Elon Musk? So I don't know how much you know about my background, but started out as an entrepreneur, had to learn business. And when I look at Elon, I see somebody that is a once in a generation, maybe even less than that mind in terms of his ability to actually get something across the finish line.
And I am a gas bill, a gas at the number of people that look at him and see a loose cannon, somebody that can't be trusted, people throw shaded him as an entrepreneur. You didn't found this out of the other. If I'm running my human evaluation algorithm on him, I come back. It's just all green lights, even though for sure he's going to get things wrong, there's no doubt about that.
But he from just a track record perspective and ability to process data quickly, he falls into a very elite category. But even he despite the number of billion dollar companies that he has been a meaningful contributor to, there's still people that discount him. So what does your algorithm look like as you evaluate an entrepreneur and use him as an example so I can understand how you think through this? With the caveat that I don't know a lot of Musk personally, I'm inclined to agree with you that he almost, he must have a once in a generation mind.
And he's incredibly smart, incredibly driven and clearly is able to, to organize people, drive people and get things done. There's no question. Those traits are necessary in any entrepreneurial activity and absolutely necessary in biotech too. In addition, what's a little different about biology and biotech compared to broadly speaking tech is often in tech, we know the science, we know the physics.
The question is, can the engineering work, can we actually make something that will do the thing that we want to do? In biotech, we don't have perfect knowledge. We actually don't know at the end of the day whether if we get all the science right, get the engineering right, get the clinical trials right, if it will actually work until we do the experiment in people. And that introduces a couple of things, they're different.
One, there's a tolerance for risk, embracing of that kind of risk that you just have to take. And we have to be data-driven, we have to actually accept the fact that sometimes we learn the biology is going in a different direction than we thought. And that's a little different. We can't just force that.
We can't force or cajole that to be different. The other thing that's a little different sometimes is when we're talking about making pharmaceuticals and making biotech drugs, we are talking about people. We do have to be really thoughtful about how we design clinical trials, who we put in clinical trials. And that's just another dimension beyond pure entrepreneurship that we have to take into account.
So all the entrepreneurial and brilliant slides flash green for me totally agree with you in a biotech setting. You have to have all that. And then also the ability to learn from the science, accept that you might have to really retrench and refocus and go in a different direction and really pay attention to how we're going to protect people as we do those clinical trials. I think that to me is exactly.
So what I hear you describing is basically first principles thinking. You have to go in, look at the data, you have to make sure that you're understanding what's really happening, you have to be willing to adjust to that. That to me in a nutshell is what makes Elon so fascinating is he thinks from first principles. So when I talk to budding entrepreneurs about how are you going to be successful?
It's what I call the physics of progress. The reason I call the physics of progress is it I really believe that it is foundational. I'll lay it out, but I don't think there's anything beneath this. And for people that haven't heard of first principles thinking, it's getting beyond analogy, you're getting to the actual root physics of the situation.
So progress to me happens in the following way. You're going to come up with a guess as to how to overcome an obstacle to reach your goal. So you need to know what your goal is. You need to know what's currently stopping you.
Like why will you not just automatically get to your goal? Entropy is one easy way to think about it. The world's just working against you in a thousand different ways, whether it's biology and it's incredibly complicated, whether it's humans in a biotech. Setting where there's not being compliant.
Other companies that are trying to scoop you and move faster, whatever it is, there's just going to be a lot of things working against you. So you have to identify, know where I want to go. I know what's standing between me and getting there. And I'm going to come up with my best guess on how to overcome that.
You're going to need to come up with a point of data that you're going to use to determine whether you actually move towards your goal or not. And then you're going to run a test and you're going to try that thing that you came up with. And it's probably not going to work as well as you want it to, but you're going to learn in that failure and then you're going to start over and you're going to be a little bit more informed. You're going to come up with a little bit better hypothesis, maybe a slightly different metric by which to judge it, you're going to run that experiment.
It's going to fail again. And you're just going to exist in that loop. The reason that Elon seems utterly fascinating to me and for people that don't know, he has a company called Neuralink and they are trying to do effectively computer brain interfaces. So he is somebody that's very much in the biotech space as well as many other spaces.
And when you hear him talk, that's his process. He wouldn't call it the physical progress, obviously, but you're just, you're trying something you're iterating, you're learning, you're getting your ego out of the way in order to build upon that. So if we agree that that is the only path forward, and if you see another path, now is the time to tell me, but if we can agree that that's the only path forward, how do you figure out if the person you're sitting across from is actually going to be able to do that? Great question.
And boy, I wish I had an algorithm that I could write it on a three by five card so I could interview potential CEOs and say, ah, got it. ABC. It's, it's hard. Um, and it's hard in part because no one goes to school to study how to have those qualities that ability to be data driven, that ability to wash rinse, repeat and get a little bit better and a little bit better and have the fortitude, uh, to, to be able to do it and to communicate effectively with stakeholders why we're doing it this way and why we took that step and why we're taking the next step.
Uh, it's, it's hard. I think it's a relatively rare skill. The, the algorithm that I use personally is asking people about what adversity they faced in their lives and professional, sometimes personal, but certainly professional lives, how they worked around it. Uh, what, what they did in the face of failure, uh, success.
What's the right answer to that question? There's more than one right answer. Absolutely. Um, the right answer that I really like is it hurt.
I was sad. I had to take a couple days and really think about why am I doing this? But then I, then I thought about it and I thought there was another path forward. What I have to do is this, what we have to do as a team is that whatever it is.
And then we went and did it and, and it was hard, but we got somewhere. That's an answer I love to hear. Now there is a very hard reality to be faced in entrepreneurship. And in fact, let me set the stage for people.
So according to your own website, I've heard you answer this question before. So I know what you're going to say, but according to your own website, you guys have up to a billion dollars a year to invest, um, with the goal of making health span available to everybody that gets complicated. I'm sure we'll talk more about that later. But the reason I bring that up now is you have a lot of money and by biotech standards, you guys are arguably the biggest player in the space.
And as the chief investment officer, you're the one that's going to have to make a call on a lot of people, uh, and with no sort of easy answer, you have to accept that even if the person gives that answer, there is just a sense of raw intellect. And I have interviewed to hire, I've interviewed over 1500 people, which doesn't sound like a lot unless you're an entrepreneur and you know just how many hours that is. Um, and what I've learned is that hiring borders on impossible and that the situation is so artificial that the only way for me to know, if somebody's going to be good, is to actually work with them for a while. So we ended up building in a 90 day probationary period.
My default answer is no. I know what metrics you're going to need to hit for me to be comfortable moving outside of the 90 day window, but I really need to see, are you smart? And I'm looking for people that are really smart. And if you know my personal philosophy, that makes me deeply uncomfortable.
That's a thing, but that's a real thing. Um, I'm also looking at not just resilience, which is what you described. I'm looking for raw, unadulterated obsession. I'm looking for somebody that borders on mentally ill that they, they are so all in that nothing is going to stop them.
I'm going to guess, given your experience, you know those things to be true. So my question becomes how, when you're not hiring somebody, how do you get to know them well enough to know if they're just giving you lip service in the meeting or if they really have what it takes to plow through what could be 10 years of sort of blind faith that you see something other people don't. And that they'll overcome the nigh insurmountable obstacles that are inevitably going to come their way. Yeah, important topic, important topic in, in anyone's work life, uh, and absolutely in ours.
Uh, and answer that in just a question, in just a moment, a couple of things about what we're doing at evolution from an investment standpoint that I think can be helpful. Uh, one of the challenges in biotech is, as you mentioned, experiment, fail, iterate, experiment, fail, iterate, move ever closer, uh, with each cycle to the ultimate goal is absolutely important in biotechnology, when each of those experiments or each of those efforts is a clinical trial. It's expensive. And, uh, one of the biggest challenges, possibly the biggest challenge in biotech is even if you're on the right path, getting more capital to do the experiment enough times to get you there is really hard.
Investors are fickle. Uh, even venture capitalists are a little bit fickle. They're, they have to be, they need most your average venture capital from has to obviously make money and a certain time period. It's more patient than high frequency trading, but it's not infinitely patient capital.
So one of the things that we bring as impact investors into the space is the ability to support companies and entrepreneurs through more cycles, uh, to hopefully give them the chance to succeed where other sources of capital might not initially give it to them. So that's a, that's a real intentional piece of why we have an investment function and, uh, why we're, we're supporting it with, with, to the extent that we are, because we think this, this space, new space, difficult biology, new biology needs companies need the ability to iterate more than once and get more than one shot at success if they have the right people on the right science. And so we're here to support them for a longer period of time, if that makes sense. Uh, to answer your question about how do you get to know leadership teams, uh, and development teams of biotech companies to, to both assess whether they have the, the raw obsession and the resilience to get there and to help them to build more of that into what they do.
Uh, it takes time. Um, one of the things that's challenging that's been, many things have been challenging about COVID, but being on boards during COVID, uh, is only superficially convenient because you do board meetings over Zoom, but, uh, there's a real piece that you miss by going and being with your leadership team in person, spending time with them, having dinner and lunch with them, standing around, having coffee and actually talking about what they did over the weekend, what's happening at home, how they're integrating their work life, uh, both professionally and personally, those three dimensional ways of understanding people are what give you the opportunity to catch them doing something right, which reinforces all the things we want to reinforce entrepreneurs and help them course correct if you can see something that, that they can be coached on. Let's talk about money. You're leaving on the table.
Every time you pay full price for a health product out of pocket, you could be missing out on 30% savings. There are over 40 million HSA accounts in the U S holding $159 billion in pre-tax dollars. That's where TrueMed comes in. TrueMed helps qualified customers use pre-tax HSA dollars on health products that can qualify as medical expenses under IRS guidelines.
You complete a health survey, TrueMed handles the documentation and the purchase. And you can save an average of 30% on products like eight sleep, Peloton, AG one and others that studies show, can treat or reverse many common chronic conditions, stop paying full price for products your HSA was built for. Go to truemed.com slash impact and check out what things you want that may qualify. It takes just a couple of minutes.
TrueMed is for qualified customers only. HSA FSA tax savings vary. Let's talk about the most powerful force in wealth building compounding. There's a reason that people have talked about this forever.
You put an asset to work. It generates more of itself over time. The curve bends way in your favor. Every serious wealth builder knows how compounding works.
Most gold owners though have completely opted out of it. Monetary metals changes that equation. They've built away for your gold to earn yield paid not in dollars, but in more physical gold up to 4% per year. More ounces stacking every single month compounding in one of the only assets that can't be printed inflated or debased.
And storage and insurance are included by the way. So hidden fees don't eat your yield. The average person is passively absorbing inflation. This is how you compound your way out of it.
Click the link in the show notes or visit monetary dash metals.com slash impact to learn more. This is a paid advertisement. Let's talk about the worst investment most guys make on repeat cheap clothes. You buy them.
They look fine, but six months later, they're pilling, shrinking or just falling apart. So you replace them. You do it again and again, you're spending more over time and you never actually have anything worth keeping or wearing for that matter. That's the whole model behind quince.
I've got one of their 100% pima cotton teas and the quality is immediately obvious. From the second you pick them up, they're soft, well constructed. The kind of thing that holds up over time and that is the point. Refresh your every day with luxury you'll actually use.
Head to quince.com slash impact pod for free shipping on your order and 365 day returns now available in Canada to that's quince Q U I N C E dot com slash impact pod for free shipping and 365 day returns. Quince.com slash impact pod. Do you know who John Wooden is? The coach?
Yes. Yeah. OK, so John Wooden famous college basketball coach. I don't think this is an apocryphal story, but even if it is, it's very interesting.
He said he used to spill water behind a star player and then see how they would respond. He would have like the towel, boy spill water and he would see how people would respond to them. And if they were kind and courteous, then he was like, OK, cool, I know this player has character. And if they were a jerk and mean spirited, then he was like, no matter how good of a player, I can't have somebody that brings that attitude.
Is there a similar spirit in entrepreneurs that you look to to see that they have the it factor that's going to help them be successful? 100%. This is a thank you for asking that question. I didn't know that story about John Wooden, but I love it.
I don't provoke CEOs and biotech executives by doing something annoying and seeing how they respond. Although it's not a bad idea. I absolutely look for the no job is too small attitude. I love leaders who come from a service mindset.
If I see a CEO making coffee for people, putting new paper towels on the paper towel roll, staying late to be in the last guy out of the office, not because he's driven. I mean, yes, he or she is driven, but also because they're cleaning up from from the day. I love that. I absolutely love the no job is too small attitude.
And I think that leaders who come from that place empower their people to think no job is too big for them. All right. If there are a few buckets in front of us of what you think is actually going to push health span forward, what do you have the most conviction in? I think there's almost no question that addressing chronic inflammation as a root cause of chronic disease will yield some really interesting and hopefully breakthrough therapies.
I also have a real belief that next generation, next there's some next generation technologies that are going to really have potentially have an impact here. And by that, I mean the kinds of technologies that can yield more than one kind of therapeutic. So getting away from one disease or one approach to disease, we've seen that gene editing is really exciting. There's been a lot of investment.
First, therapeutic has gotten approved in gene editing. That's good. But that of course, that's pretty permanent. That changes your genetic makeup.
We've also seen in the longevity and health span world, a lot of interest in cellular reprogramming, actually going and taking cells and moving them back to a more youthful state. Really exciting, but also sort of a blunt instrument. You're changing the whole cell, which could have all sorts of effects, good, and maybe less good. I'm really excited about what's the next set of advances in manipulating the genes and the cells that will take all the best things from those and and be really applicable to the long term for broad populations.
We talk about the epigenome a lot in aging. So the genome is your DNA. It's the blueprint of how you're built and what you do. The epigenome is how those genes are expressed and there's dynamic control over your life about genes expression goes up, gene expression goes down.
And there's lots of paths that the body uses to manipulate to change that. And those controls over not are you driving a car and is it a car or a submarine, but how fast is the car going? Is your foot on the gas or your foot on the brake? Those, those kinds of processes are really important for aging.
And if we could control the epigenome, if we could edit the epigenome, the way we can edit the genome, we might have a more dynamic way to change the expression of cells and to therefore maybe temporarily move them to a more youthful state or only move part of the cell to a more youthful state. And that potentially could have wide ranging impact over time. It's not an overnight thing, but over time, that sort of approach could be really important for chronic diseases. So I'm really excited about people doing fundamental research into how we can manipulate cells to get them to do the right thing in a more dynamic way.
OK, this is really interesting. There was a recent study that came out of Harvard that took mice and I think genetic or bred them to have a predisposition to breaking in the DNA because the fundamental question was, is this a DNA mutation problem where, hey, you get an x-ray, you fly, you're exposed, all these things that are damaging your DNA. And aging is basically the accumulation of these mutations where we're just putting the DNA back together in the wrong way. Or is it something to do with the epigenome where the starts to get complicated, but the way that you're marking the DNA for what genes to express is called methylation.
So your genes are tightly bound up and you basically loosen parts of it to say, I'm a skin cell, I'm a heart cell, I'm an eye cell, whatever differentiation. The theory went that it's either all of these gene mutations in the DNA that are causing the problem or it's the way that they are getting marked so that they're basically de-differentiating. So now, instead of being clearly an eye cell, and the wrong part of it has become loose and is expressing itself. And this very clever experiment showed that even these mice, that their DNA is constantly breaking and needing to be repaired, at the end when you look at their DNA, it was the same.
It wasn't accumulating a bunch of mutations. Instead, what was happening is that we were getting de-differentiation. The methylation, the bookmarking to use a very layman's term that you may hate, is the problem. And so that, to me, makes a lot of sense that you're really excited about this.
But what I want to know is, okay, one, do you think that would you be willing to make the declarative statement that the epigenome, where is in the epigenome, is aging? Ah, absolutely. The only caveat I'd say is that's not the only process of aging. It's not the only definition of aging.
But I believe it is a definition of aging. It is one of the processes that is aging. And when expression through the epigenome and control of the epigenome goes wrong, that is absolutely, I believe, one of the ways that aging goes wrong and we get to see. So it's one of the pathways that's really important.
Okay, so what are, let's go through the hallmarks of aging. I've heard you talk about something I've not heard other people talk about, which is emerging hallmarks of aging. So I'm going to guess it goes something like this. They're the things that we know and have already named and you're going to tell us what those are known as the hallmarks of aging, wrinkly skin being the one that everybody can see much to my dismay.
And then you've got things that we're just now discovering is what I'm guessing you're going to call the emerging hallmarks. And then I would love to lay those out. And then the last part of this is understanding which of those do you think are controlled by the epigenome? And then since you're not willing to say that that is the sum total of aging, what sits outside of that?
Well, this is a great conversation and there might be a job for you would have a Lucian in our science department actually helping create that future. You think about these things. So the term hallmarks of aging refers to a set of ways, if you will, that the cell can go bad. Over time, in response to all the slings and arrows and insults that cells are subject to as we live our lives, things can start going wrong.
DNA can break, of course, when DNA breaks accumulate enough and don't get repaired enough, in my mind, that sends you down the path of cancer. And the epigenome breaks that sends you down the path, potentially of cancer, but certainly of these chronic diseases and aging. But there are other ways that cells can go bad, if you will. They can lose their ability to fold proteins correctly, to actually create the architecture that they need to create.
And like any other structure, if you don't put the pieces of wood together, you don't get a house, you get something crazier. So misfolded proteins is a real hallmark of how cells can go wrong and that can lead to aging. The ability to clean house, if you will. So over time, proteins get misfolded and some things get created that don't work out or they just break.
And the cell has to renew itself and actually clean house and clean up messes and do constant upkeep like we have to do on our houses. The ability of cells to do that is critical. And if they lose the ability, which we give fancy terms to like autophagy, which is literally eating the cell eats the misfolded proteins, if we lose that ability, that's another way that we lose the ability to renew and be youthful. But another is energy.
Cells need energy. The battery, if you will, cells are these organelles called mitochondria. And if the mitochondria do a lot more than just the batteries, but think of them as a battery in your cell that provides energy, if the battery runs down and can't be recharged anymore, you need new batteries, but we're not great at making new mitochondria that are youthful. We can make new mitochondria that don't work as well as they used to.
So mitochondrial biology is another hallmark of aging. So these are examples of ways, if you will, the original hallmark of aging where how do cell processes go wrong and how does that lead to aging? On the emerging side, first of all, science marches on, we're learning more and always, and some hallmarks of aging may be less hallmark-y. Maybe they're more consequence than cause.
And one example that's been potentially controversial in the aging biology world is telomeres. We've heard a lot about telomere shortening. So is telomere shortening a cause of disease or is it a marker that bad things have happened? Don't know.
But to the extent it's the latter, then maybe telomere shortening isn't as much a hallmark of aging as some of the other things that are more fundamental. But new science will bring new processes and will learn more about how cells work. And there's a constant process on the academic science and thought-leader side on what are some of these other things we're seeing cells do and could they be hallmarks of aging? The other way that I like to think of hallmarks of aging, though, is to get out of, it's about cells.
It's not all about cells. Aging, as you said, is sure people should care about their cells, I guess. But it's pretty hard to tell people you should think about yourselves. You can definitely tell people you don't want wrinkly skin, right?
Do this. You don't want to lose your autophagy, so do this. That's a harder cell. But aging is so much more than cells.
What about intrinsic capacity? What about vitality, which let's make that more biologic? Muscle strength, the ability of your muscles to recover after exercising, self-renewing, be strong. What about your senses?
What about cognition broadly? And biologically, it's not just about neurodegenerative disease. Are there ways in which we could look at the biology of the aging brain and ask, can we enhance cognition? Biologically, and to embrace, if you will, those as hallmarks of aging, to worthy of the same scientific treatment, worthy of the same focus, and worthy of therapeutic development.
When you're looking at the complexity of all of this stuff, how do you think we're going to be able to begin weeding through this stuff? For me, AI feels like the closest thing that we have to magic cure. So if any sufficiently advanced technology is indistinguishable from magic, I would say that we're getting pretty close to that. And we're filming this not long after the firing of Sam Altman and the near immediate rehiring of Sam Altman.
And there is a lot who's the CEO of OpenAI. And there is a lot of debate about whether their new thing, I think, called QStar is AGI. And that spooked everybody. And that's why they fired him.
And this is really a battle around safety. But what do you think about that? How much of a difference do you think AI is going to make? How much does that fall into your investment thesis?
And is all the things you just laid out are incredibly complicated and it feels like we're sort of at base camp of Mount Everest and we have a long way to go. Because AI feel to you like the elevator to the top of Mount Everest that it feels to me. For me, AI is a tool. It's a great tool, potentially used well, like any tool.
Harnessed and exploited and adapted, I think AI is already an important tool in drug discovery and can be even more important. To your point, it's possible for folks like me to make things sound real complicated. But at the end of the day, the way we make progress is by breaking things down into doable tasks, take that hill, take the next hill, take the next hill. We don't, I don't stay up at night thinking this is hopelessly complicated.
I'm drowning. Rather, it's how can we address this question to answer that question to make that thing work. So that becomes then a set of addressable problems, a set of addressable puzzles. And AI is a remarkable tool for reducing complexity.
It's one of its best things, one of its best most validated uses. And to reduce complexity in what's a hallmark of aging? Because the connection between top of G and wrinkly skin, that's where AI is having a role today in our world and will have a really big role tomorrow. There's no question.
So is it the elevator to, from the base camp to the summit, I'd say it's the fixed ropes. You get to the next level and instead of being presented with, oh boy, it's windy, it's really steep. I'm afraid I'm going to fall off the mountain. Oh, there's a rope.
I can grab onto that and pull myself up and guide myself along. Now I'm feeling more sure-footed. I like that. That's a good analogy.
So let's talk about those questions that we have to ask and answer in order to get where we want to go. Do you have a sense of what they specifically are? The goal is to make it linear. So you're suggesting perhaps that there's a linear process.
We figure out the biology that translates into mice, that translates into people and that translates into drugs, which translates into prevention. The goal is to make it as linear as possible. What are the specific linear steps? So looking at the early side, we really need to understand as much cell biology as we can.
We're the questions about how these hallmarks of aging work together, how they interact, how one leads to another. And importantly, can we not just ask if we stop this bad process, we'll sell this bad because we know the answer is yes. But rather to ask, if we intervene late, there's already some damage because how do we know? We know that we're getting a disease when there's either a sign or a symptom.
So can we use that biology? Whichever hallmark of aging one wants to talk about or whichever biologic process might have gone through a fibrosis, whatever it is that you want to do, can we find ways to start when the damage has not become permanent but already started and move things backwards? So that opens up a whole set of inquiry at the early science level. Professors in labs, entrepreneurs in labs asking fundamental basic questions about how cells work.
That doesn't look like a drug yet. And there's a lot of work happening in that area and we need to have more of that. And evolution are funding new and emerging scientists to ask questions that we don't even know how to ask yet. But we want to know if we can intervene, if we can make mitochondria work better, if we can restart autophagy, if we can restart the process of unfolding and refolding misfolded proteins.
So there's some very specific sets of basic questions that scientists and labs need to answer. Then really important are the questions about translation. We can't go, we never could go and we never will go from, even with AI, even with the best AI from, we predict this chemistry, we'll do this in a cell. Let's put that in 5,000 people and see what happens.
Oh, there's some stuff we got to do in the middle. We certainly have to do our best to predict whether it will be actually useful and importantly whether it will be safe. So that's where translational science, animal testing, and the whole chunk of moving from discovery to development happens. So we know there's a whole bunch of questions that are pretty standard.
Every pharma company, every biotech company asks questions like, if there's a model of a disease and a mouse, does this therapy make the mouse better or not? Those are useful, those are important, but we need new questions, new models. We really need new models because aging isn't a disease that is A or B on or off, one or zero, it's a process. So we need to be thinking in some ways, linearly, but less statically about biomarkers, about predictive models.
Again, AI could help us ask some of those questions and maybe even could help us design organs on a chip so that we can iterate more cheaply in that is this likely to be safe. Let's make some predictions. Let's say organs on a chip, are we talking purely, we map out the way that a given organ reacts to given chemistry? Is that the punchline?
Is it basically just pure predictive? This is how we live or works. So that is actually a pretty useful tool. Yeah.
I think when people talk about organs on a chip, they talk about that. They also talk in a more physical way, literally taking cells, putting them together and helping them, encouraging them to interact with each other, to be not just a cell. Okay, a cell, we study it. Now we're going to make a prediction about a human.
What lies in the middle are groups of cells communicating with each other, cells working together. That becomes tissues that become organs that become people. So organ on a chip also is not just a predictive, an in-cellico, if you will, a computer predictive process. So a whole set of approaches today of taking groups of cells, putting together and studying them in a more systems way, asking what they can do as a group and putting them to work to ask questions about chemistry and stuff.
So literally creating many organs, sometimes called organoids and making them functional to answer questions so we can have a model now in between cells, worms and mice, actually model how organs might respond to aging or therapies that can interfere with that. Victoria moves in so many ways. This vibrant city on the Pacific Ocean is flavored by a rich culinary scene and deep history. It's a role a hidden alleyway or a colorful garden.
Explore an ancient rainforest or a collective art gallery. Discover a Victoria that never stands still. Visit us at tourismvictoria.com. Okay, there's something very, very intriguing here.
Let me ask you, do you think we live in a simulation? You think about this for a second? I'm going to say I'm already surprised. I thought you would give me a shoot from the hip answer that no, of course not.
All right, here's my answer. One of the things that makes humans demonstrably different from other organisms on the planet are we have consciousness and we think that's a good thing, but it gets us in trouble. And partly it gets us in trouble because thinking outside of your own head is really hard. It's hard personally.
It's hard professionally and it's actually hard scientifically. So in that light, we do create by by looking at all the experiences we've had, all the knowledge we've learned, all the things we've learned from iterating and experimenting and doing well in jobs and messing up and other jobs and watching other people do well and mess up. We think we know some truth. We say, this is my approach.
This is my approach to science. This is my approach to interpreting those data. We've all heard there's lies, damn lies and statistics. Well, we can convince ourselves that data is showing us a bunch of different things.
And in that light, we are living in our own heads and we are creating the simulation that we live in. We can't or it's very, very hard to say, I'm going to step back from my ground truth assumptions about what this experiment should show or what that drug should do and actually be open to looking at what's really happening. That's super hard. If we can do it even a little bit, breakthroughs happen.
People make breakthroughs in their careers. They make scientific breakthroughs and insights. They invent new things. So in that light, we are living in a simulation that we create in our heads.
And the interesting thing is everyone's simulation isn't exactly the same. Do I believe that there's objective reality of absolutely I'm a scientist, I believe in objective reality. There are facts and in that light, because if there weren't, if we were truly living in a simulation, it'd be probably a lot easier to develop drugs in the matrix in the real world where biology is messy and we don't know everything. So I don't think there's a difference.
So I'm on the record of having said that we don't live in a simulation. I don't think, but I've said many times what you just said, which is, is there really a difference between being trapped in your own mind and living in a true objective simulation? It is a fact that the human brain is in case in total darkness and yet as I look at you, it doesn't feel like that. It feels like light is hitting my brain and I'm simply seeing what is there versus electromagnetic signals being processed by my brain and creating a sense that I'm seeing something.
Given that we see .0035% of the available electromagnetic spectrum, we know that we are oversimplifying the world grossly and it becomes a question of, okay, well, if I'm simplifying it, then my brain is making decisions about what to show me and not show me. It's interpreting what it sees and what's the interpretation. All right, I want to set that aside for a second. And even though I don't know that I believe this, I'm going to make my best pitch for that we really do live in a simulation.
Okay, it goes like this. And the reason that I was thinking about this is you were talking about AI and the complexity of all this and being able to build organs in silico, that meaning on silica chips. It's a fancy way of saying that it's a computer simulation. So I spend the vast majority of my time building video games, which is not something people know much about me yet, but they will if I have anything to do with it.
And what you begin to realize is you can create a relatively simple set of procedural rules and from that is born an incredible amount of complexity. And so many of the most played video games and the one I will use. Have you ever seen Minecraft? Yes.
Okay. Oh, I love this. Okay. So I've got a daughter.
I have had the good fortune of encountering Minecraft very late in my life. So I don't take it for granted. So when I encountered Minecraft, I was like, what on earth is this incredibly complex universe that I've stumbled upon where everybody gets their unique seed? And as you explore the world, you realize it's more and more complicated.
I got tired of being blown up by what are known as creepers. And so I looked up online, like, how do you keep the creepers away? And it was like, put a cat in a boat. And I was like, what?
Like, that was AI had not seen a cat. And I did not understand why you would put a cat in a boat. Anyway, what I began to realize was from a relative, I mean, compared to biology, it is Minecraft is stupid, simple, but from this incredibly simple set of rules comes an unimaginable amount of emergent complexity. And as I was playing the game, I realized I was explaining to some of my teammates how I play and they're like, that's not how most people play Minecraft.
And I was like, well, why? And so anyway, you begin to realize not only is there emergent complexity, but then the behaviors of the people engaging with this simulation also have their own emergent ways of playing the game that weren't contemplated when the rules were set forth in motion. Now, given then that you can create from procedural rules, you can create something of near infinite complexity, that to me feels so analogous to the way that life is. And I think the mistake that people make when they're assessing biology is they mistake unknown for unknowable.
And I think that biology is knowable, even though it is very complicated. And even though right now we know so very little and therefore are able to make so few predictions, as AI becomes more complex, it, the reason that AI is so powerful and the reason that I consider this the elevator to the peak of Mount Everest is that what we have not been able to figure out yet are the patterns that emerge from the simple set of rules. Once we can identify the patterns, we can work backwards to the simple set of rules. But if we can't figure out the patterns first, I mean, this is like Newton's laws of motion, which then Einstein obviously refined upon, but by discovering simpler and simpler equations.
So my hope is that what AI will be able to do is stop being tricked by the apparent complexity of the emergent behavior. And it will be able to ascertain the simple set of rules that give rise to these patterns, but it has to be able to parse through these patterns first. So when I look at, okay, one, I want to get back to that the set of questions that you posed that we have to be able to ask an answer in order to truly tame biology. Okay.
So we have to ask and answer these questions to really be able to control biology, to do what I think we will be able to do, which is extend human life indefinitely. Now, I would like to introduce for people that don't know the Dunning-Kruger effect so that people don't waste time saying that this is Tom in the grips of this, which is true, by the way. All right, the Dunning-Kruger effect is you know so little, you think you know a lot. I completely acquiesce.
I know so little, it feels like I know a lot. But this is where I think that we can start to, I think that embracing the Dunning-Kruger effect is the right first step to embarking on a very complicated journey. And I think that it is actually useful to try to connect dots that may not connect in the end. And this is something that I look for in entrepreneurs.
Can you create a narrative that allows you to have a direction that you're moving in and at the same time question your own narrative because you know it's wrong. So what I'm about to lay out, I know is wrong, but it's going to allow me to move in a direction. Okay. So here are the questions that I think we have to answer.
What causes aging? That's question number one. If we understand what causes aging, then the question becomes can we reset that process? If we can reset that process, then can we solve for persistence?
The reason I think persistence matters is the only reason that humans care about each other, about themselves is there is a continual sense of identity. So I love my wife. My wife, even though she's changing over time and I'm changing over time, we have a sense of persistence. So I have a sense that I've shared my life with a continual entity.
I have a sense that I am a continual entity and all of that. Now the reason that I think that matters is right now there is an organism on Earth that is truly immortal, meaning unless it dies a violent death, it will never die. And that is this jellyfish. The thing is the jellyfish to renew its process.
It has to basically de-differentiate all of its cells back to a pluripotent state. So it basically becomes amorphous blob that then reconstitutes itself back into the jellyfish. Now I'm going to guess that if it had memory or whatever, which probably doesn't, but if it did, that would all be wiped out in that process of becoming pluripotent again and then reconstituting itself. So that feels like, again, fully embracing the Dunning-Kruger effect that this is way too simplistic and we will find over time that I'm just not getting enough into the nuance.
But that gives us something directional to work with. That what we have to figure out is what is aging, which I think we've covered, which aging is the epigenome beginning to break down, not mutations in DNA, but the way that we bookmark our DNA so that the cells begin to lose focus. And as the cells begin to lose focus, then we would, we age, we see all the things that we think of as aging. But to fix that, we would have to remove all of those things, which we have shown, the Yamanaka, for his first name, won the Nobel Prize for showing that you could bring a cell back to a pluripotent stage, but I have a feeling if we did that to the whole body that we would de-differentiate to the point of nonsensical, like we would cease to be the same organism.
And so we have to be able to solve for that problem if we actually want one organism to live forever. So some great topics to unpack there. In no particular order, you are, I believe you're correct. Can't prove it.
I believe you're correct that if we could become the jellyfish and actually piece by piece or as a whole organism, truly reprogram ourselves all the way back to the beginning, we would, this is the metaphysical part, I'll get to the biologic part in a second, we would almost certainly be resetting our brain, which would necessarily reset our consciousness, which would necessarily wipe out all those memories and all the things that we thought of as life. So speaking just for me, look, I'm not ready to die. I got a lot left to do in life. I got decades.
I got to live a really long time. But am I willing to say that sacrificing everything that I've seen, done, and felt in life to make my liver last forever? No, we're humans. We're not jellyfish.
So that's personal, that's philosophical. I think everyone would agree with you, including myself. On the AI part, it is a fascinating topic in applying this tool, but also this approach to thinking about aging, thinking about drug discovery, thinking about medicine is a fantastic topic. One of the things, the reason I call AI a tool and not the solution, it's a tool, is at the end of the day, as far as I know, I don't know everything, AI has to work with the dataset that it's presented with.
Not anymore. They're now creating synthetic datasets. This is one of the potential breakthroughs. Fine, no problem, but they are someone.
Someone's creating a synthetic dataset. The AI is creating a synthetic dataset now. It's on off of the original. I'm going to assert that my point isn't yet.
You may get to the part where my point is appreciated, but I'm going to assume that my point is still valid. At the end of the day, the algorithms are working from a set of ground truths that they have to be presented with. They're not making up ideas. If and when algorithms start making up ideas and saying, if that were true, then this might be true.
I'm not sure if it's true, but I wonder if this thing could happen. That's getting closer to what happens with humans. Let's assume for the moment that at some point, at some fundamental level, there's a set of facts that are taken as ground truths by the algorithm to reduce complexity, to make predictions, and even spin up synthetic datasets. What's never in that world, what's never going to go away is the need to create more ground truths, to actually make observations, to take human, to make living things, to take biology and actually ask questions that yield new pieces of data.
We need more data. We know that if we're building algorithms, for building neural networks, they love data, right? They get better and better the more data you feed them. They want more data.
We still have a lot of data to create. We don't know. We know a lot about the epigenome. We don't know everything.
We don't know all the observations that create those fundamental, simple sets of observations and rules that you spoke about. In Minecraft or a game, any game, you can set up a set of facts and create enormous complexity from it. I fundamentally believe we haven't observed all the fundamental facts of biology yet, and therefore, we're not going to put scientists out of business. We have to do experiments.
We have to make observations. We have to be curious and say, I wonder what would happen if we did this? What would that show and be surprised? Once we stop being surprised by every experiment, then AI can take over.
But until then, we're creating new pieces of information that will change those algorithms, that will change the predictions, that will change the synthetic datasets. We can't stop doing that real basic piece, that real fundamental, let's make observations about aging and biology. And that's the engine that will drive the whole thing forward. What is it you think humans will always be better at than AI?
The list is getting shorter, but I do think the word that keeps coming to my mind is curiosity. I think humans have a remarkable capacity to say, I wonder what would happen if. And I understand that you can certainly program a computer to try every simulation possible. That's a little different than making a choice that to your analogy of put a cat in a boat that's going to save you over here.
We could never see the path to that. We could never figure out from first principles why the cat in the boat means you're not going to get your head chopped off at a different place in a different chapter in a different part of the game, even if in retrospect it seemed obvious. But this is different. This is the imagining why, without knowing, without having any logical reason, why would we go ask that question?
Why would we try that thing out? That's what humans are really good at. And there's something about intuition that's real. It's not a random process.
I don't think scientists are essentially browning in motion just randomly doing experiments in every once in a while. Brownian motion, what's that? Random, essentially random motion of subatomic particles, electrons just kind of vibrating around molecules vibrating around. Do you think we live in a determined universe?
Again, there's an objectively correct answer if yes or no. I don't know it. I choose to believe that like a video game, the outcomes, the complex outcomes of the basic rules are somewhat predetermined. But unlike a game, we can change the rules.
That's where science comes in. That's where intuition and imagination- But changing the rules, are we just discovering more of what's already set in stone? I think there are some rules that we can't break, we can't change. I used to think, I think we all used to think, that was Newton's laws, right?
There's a speed limit in the universe and it's the speed of light. Except, I don't know, we'll find out. Maybe it's not all the way true. That's discovering something that already exists versus changing it.
But one level I agree with you. Add another because or humans are built off of those rules. If in fact, there's something we can learn about, and I'm not a particle physicist, so I'm way over my skis here. But let's just say we discovered an ability to actually, we discovered that light doesn't go always in a straight line.
It can be bent into a curve. Okay, fine. We discovered that. But if we could harness that, then we could absolutely be changing the rules by which bodies move in space, by which speed limits in outer space are constructed, and by analogy to something we care about here, change the rules of how diseases start, progress, and maybe go backwards.
If we can make it, if we can discover something, sure, that exists, but then manipulate that to make aging not a linear process, but a curved process that maybe can curve back upon itself, that you don't have to want to live forever. That's just a very pragmatic approach to totally changing the game on how therapeutics work. Do you believe you can violate the laws of physics? I know that I cannot violate the laws of physics.
Okay, so when you say change rules, what do you mean? Because when I think of rules, the rules set to me of how everything in life works, including biology, is the laws of physics. And the laws of physics, I'm going to guess, end up being relatively simple. And from that emerges the incredible complexity.
Sure. But there is no changing that. There's discovering it. There's, and once you understand it, then you can harness the power.
But I don't think Einstein changed Newton's laws. I think Newton just had an incomplete understanding of physics. Einstein got closer, but even Einstein died, not fully understanding physics. He still don't fully understand physics.
So it's not that I think we're changing things. I think we're discovering it. I don't know if this is core to your thesis and I'm just hung up. Or if it's core to your thesis, then we need to debate it.
If it's not core to your thesis, I will relent. But I am very much hung up on the idea of changing the rules. Oh, okay. Well, let's see if you agree with this.
There's rules and there's rules. It may be that the speed of light is the speed limit in the universe. It may be. That's a rule.
There's also a rule that the speed limit on I-280 in Cupertino is 65 miles an hour. You can choose to break that rule and there may be consequences, there may not be consequences. But you wouldn't have been able to break that rule if cars could only go 20 miles an hour. You had to learn more.
You had to discover more in order to create cars that could go 80 miles an hour. And then you have a choice to break the rules. So do I think that there are fundamental ground truths in the universe? I actually do.
I don't know who created them. I don't know what they are, but I think they exist. But how they get implemented and the rules by which, not just we choose how fast to drive, but the rules by which literally our organs interact, our body ages, are I actually think built on, they're built on those ground truths, but there's a lot more rules that come into play to create a body to create disease and to approach treating disease. So if we know more about those rules, we can, I think, break some assumption.
How about one way to say, one way to bridge the gap between this rule conversation is, if we replace rules with assumptions, we assume we know how humans work. We assume we know how to treat cancer. We assume that we can't reverse fibrosis. Well, that's true given the rules we know, but maybe we discover something and that says, oh, we can break that rule, but we had to put a cat about.
We had to give people vitamin E. We thought it wasn't good for you. Then we thought it was good for you, but now we're giving people vitamin E and it's doing this thing and that changes something. So I do think that we can change the rules of the game in medicine, but we need to know more to do it and we need to use tools like AI to actually reduce the complexity so we don't just randomly try stuff.
Do you think the AI is going to be able to learn to speak in DNA? Probably. I don't see why not. What does that look like?
At some romantic level, I suppose it could be creating life. It could be changing the nature of life. It could be changing our brain works. But in the more mundane way that things seem to work out in our world, what it's likely to do is to predict with far better certainty how to prevent damage to DNA, how to repair damage to DNA.
I think something, I think it will work and I think it will have a real impact, for example, in cancer in a way. I think that I don't know how far off this is, but I want to believe it's in our lifetime that using AI, we will be able to create tools, and by this I mean probably molecules or some version of a molecule, that can crawl down your chromosome, look at your DNA, find areas of damage and like repairing the ties on railroad tracks, repair them before the train comes and gets thrown off the rails. That is not possible today. People like to talk about it's not possible today.
We don't have a molecule that can crawl down your DNA and find the right damage to fix very specifically. We have holistic approaches, we give drugs that affect your whole body. Even gene editing, which sounds pretty precise, we know that edits are created in places other than where you want to make the edits. Now, we're pretty robust and that hasn't led to wholesale chaos in people, but there's consequences.
Every drug that works has negative consequences at some point. I think AI will help us to create tools that are much more dynamic in that sense. Let's talk about a pattern that is guaranteed to be killing your progress. You know what you need to do.
You need consistent nutrition. We all do. You need vitamins, probiotics, greens. We all know that we should be doing more of it.
Your morning gets chaotic. You skip it. When you travel, you skip it. When your routine breaks, everything tends to break and that inconsistency compounds against you every single day.
AG1 is designed to solve the execution problem. One scoop, eight ounces of water and you're done. You're getting 75 plus ingredients, vitamins and minerals, pre and probiotics. Nutrient dense superfoods, everything that used to require six, seven different supplements and perfect planning now happens in one drink that takes about 30 seconds to make.
Right now, AG1 is giving you $87 worth of free gifts with your first subscription. You get a welcome kit, travel packs, vitamin D3 plus K2 and flavor samples. Click the link in the show notes or visit drinkag1.com slash impact to claim this offer.