Welcome to the AI Chat Podcast. Today on the podcast, we have the pleasure of being joined by Blair LaCourte.
I'm really excited to have Blair on the podcast today for a couple different reasons.
He's got an amazing background in tech, a lot of really incredible experiences.
He was the CEO over at ExoJet, which eventually merged with VistaJet and became one of the largest private airlines, which is super fascinating.
He worked with TPG, Autodesk, Sun Microsystems. He took AI technologies public.
He did the IPO, $1 .5 billion IPO, and a ton of interesting stuff.
He's currently trained to be an astronaut.
There is a lot going on.
Oh, and I guess I also got to mention the vice chairman of the Buck Institute working on longevity.
So he's invested over a thousand companies.
Excited to have you on the show today, Blair.
Yeah, thanks. Hey, I'm glad to be here.
you know but it's so funny because you know the longevity institute is on the last on your list and the tech is the first you know at my age the longevity issue is the first on my list and the tech is you know it's after that so it's that's awesome yeah we're in the world that's yeah that's funny uh makes a lot of sense a lot of exciting stuff is going on right now um in both of those sectors so we're going to get to all of it in the podcast today um i was wondering you know just i I always love asking people kind of right off the bat, what got you into the tech?
And let's talk about longevity and all that.
But like, what kind of got you into that, the tech ecosystem, the tech environment?
Was it something you're always passionate about?
What brought you into it?
Sure. Well, I'm probably going to give you a different answer than anyone you've ever had on this show before, because the only reason I got into tech is because back in my day, when When you were a consultant, if you missed your plane, they would actually make you pay for your plane flight if you didn't show up for the meeting.
I was in an airport in Topeka, Kansas, trying to get to Calgary to do a job at Mobile Upstream.
I was just about to miss my plane, and a buddy called me from General Electric.
He used to be the head of strategy at General Electric.
I had worked for him, and he said, listen to me.
Your dad told you you should work for people who care about you.
I care about you. I think you're really smart.
I'm going to a new company and I want you to come over there and be head of strategy.
And, you know, I just need you to say yes.
And I said, okay, yes.
He goes, you don't want to know what it is?
I said, dude, you had me at hello.
You know, your dad told me.
And so he said, okay, that's great.
He said, we're going to send you out the paperwork.
You know, I'm very excited about this.
So welcome to Sun. So I got on the the plane and I flew to Calgary and we had the big board meeting.
And after the board meeting, I went to my partner because we had this little consulting firm.
And I said, look, I'm going to be transitioning.
It's about time for me to take a year off and work in real industry.
I can always come back, but I'll be better than I was before.
And I'm going to work for Sun Oil.
And that's going to be great because we do a lot of oil and gas.
We do a lot of industrial.
Imagine I'm going to make some great connections.
So I get home because you travel five days a week.
And I ended Ended up, my girlfriend picked me up at the airport and we went out, unfortunately, doing karaoke and doing shots.
And I didn't actually get up the next day and go to the library because before the internet, that's what you did.
You went to the library to look up companies.
And so then Sunday hit and in Texas, all the libraries were closed.
And so I flew for another week.
So the second week I get home and there's a letter waiting for me and it's in my roommates, five roommates.
You know, I was at a mattress, I was sleeping on the floor.
And they said, hey, here's a letter for you.
And it said, Sun Microsystems. I looked at my roommate and I said, is this a subsidiary of Sun Oil?
He said, no, I think it's a tech company.
So I opened it up. It says, welcome to Sun Microsystems. So for your listeners who don't remember Sun Microsystems, it was one of the people who invented, really, we invented Java.
We invented the workstation, the Sun workstation.
Sun actually stood for Stanford University Network.
work. But that was one of the first high tech companies to really drive along with Silicon Graphics and such drive high, high end computing and distributed computing.
So at that moment in time, I said, I got two choices.
One is I can go beg for my job back because this does not look like an oil and gas company.
And the second is I'm a consultant.
I can just go fake it because we need a job.
And so that's how I got into high tech. I literally made a mistake.
And And when I showed up, I found out that I was head of strategy, you know, for field operations, which was, you know, 25000 people.
No, no big deal. But my first secretary I've ever had now, I mean, I should say assistant back then it was a secretary.
She said to me, you look really sick.
And I said, I need help.
So she wheeled the TV in and some videotapes.
There are those big things that you put into a VHS player.
Again, you may not remember that.
And I watched videotapes for a couple of days, and that was my beginning of tech. Once I understood the language, I learned to love it, the speed of it, the people.
I was intrigued by how much it was changing whatever people did every day.
Um, and I got some encouragement very, very early on in my second day, the head of R &D, when I was head of strategy was a guy named Eric Schmidt, who you may have heard of that went to run Google.
And he was head of R &D at, at the, uh, at the time.
And he looked at me and he said, listen to me, we got enough tech guys.
We need guys who help people get along together.
Cause all these tech people aren't getting along all the time.
So figure out how to work with people and you can make technology go faster.
And that, and from there on, you know, that was my, you know, I was a tech guy.
No one ever questioned it after that.
But I don't think they ever would have hired me.
That's amazing. Yes, I think, you know, Sun Microsystems, one of the incredible legendary, you know, companies in the tech space.
Something, if you listen to Steve Jobs' biography, you'll hear that company mentioned a lot.
Really, yeah, one of the most instrumental ones.
That's hilarious how you got into it on accident.
So you've obviously had a really impressive career.
You've done a lot of impressive things with tech. You're right there at the beginning of the tech revolution.
I'm curious, like what your thoughts are on, you know, you were at the beginning of so many changes that happened with technology.
I'm curious what your thoughts are on like in today in the last few years, what we've seen with AI and a lot of the advancements there.
A lot of people are saying, look like this is a whole new wave, a whole new way of doing doing things like what are some of the similarities or parallels you see from then till now?
Sure. And so when you get, you know, to my stature or age, you realize that every seven years there's a new thing that's going to change everything and it has.
So when I started out in tech, hardware was, that's where it was at. Faster, faster, better, better, you know, get the hardware to run.
And then I left and we took over a company called Autodesk, which at the time was the fourth largest software company in the world, and it's still one of the largest software companies in the world, doing CAD drawings.
So we really invented drawing on workstations and then drawing on PCs.
Anything you see out there, drawing packages, they were basically descendant of us.
So all of a sudden it went from hardware is the most important, software is going to change everything.
And again, it did, right?
Then once we got into the software era, a few years later, People came back and said, no, no, no, no. It's data.
It's databases. It's data is going to change everything.
Right. And then it's networking is going to change everything.
And so what I would tell you is that all of them did and all of them are cumulative.
When I started out, you could invent something and, you know, it was just new.
There was nothing else out there.
The difference today is that we have good hardware and we have good software and we have databases and we have networks, not just big networks, but small networks and distributed networks and things like that.
So it's really it's the age of AI because all those things exist. Without those things, AI would not have been possible.
And now AI is going to change everything again.
So I'm just putting it in perspective of that.
These are cycles. I would tell you that what we call AI today, 30 years ago, we would have called mechanization.
I'm going to use this workstation, and I'm going to go faster and better, and I'm going to process.
And then we called it automation.
Oh, not only am I going to just brute force do the same thing over and over again, I'm going to automate those processes so that I can audit them, and I can change them, and I can do things with software.
And now what we're saying is I have all these pieces.
What I really want to do is I want to make sense of complexity, which is what the human brain does.
The human brain is designed to take complexity and bring it to simplicity.
Right. So the first thing we did with large language models, if I could read everything and I could actually remember everything, how would I access it better?
So that's one way of looking at complexity to simplicity.
The other way of looking at it is actually more like the way quick twitch brain functions work, which is multiple neuron spikes.
It looks a lot like reinforcement learning.
I'm guessing about this, I'm testing it, and I'm coming back.
So, for instance, when you actually, I developed targeting systems for military jets and sensors for autonomous cars.
Now, one of the things when you think about that, you think, oh, I have to basically make it better than the human eye.
In order to make it for better than the human eye, you have to be able to collect data and process it better than the human eye, which is really AI, which is my last company was named AI.
And when you look at it, what we were doing is quick twitch neuron spikes.
Go see something, guess on it.
Go see something, guess on it.
Go see something, guess on it.
and therefore we actually get there faster.
My analogy with your face is that we don't store faces.
Humans don't store faces.
What they do is store nine different components of your face and when you're walking down the street, you look for the eye distance between the eyes, the shape of the head, the way the mouth looks and immediately you're guessing and as soon as you catch it, you just go, I know what it is and I recognize that person.
He's not going to kill me and I say hello, right?
Right. That's really what reinforcement learning is now doing.
So we're getting closer and closer.
We did it by brute force by we can analyze information or now we can use reinforcement learning.
And the only reason I say there's a lot of people on this podcast are saying, why is he explaining AI to me?
I'm explaining AI to you because I want you to realize that you can't separate AI from everything we've done for the past 30 years because all this is is just a new way of doing what we've always been trying to do.
And the people who try to say it's going to change everything because nothing before us matters will not make money.
And for people who say we'll change everything because everything we did before, we're going to do differently, or we're not going to do it all, are going to make a lot of money.
But the dreamers who think that there's a disconnection, again, we're just going from mechanization to automation to AI.
It's a transition of things, and it's wonderful.
Um, and it's going to change a lot of things, um, both for good and for bad, but that's what humans do is we, uh, we figure out how to push the envelope.
A hundred percent. Okay.
I love that explanation.
Um, I want to just double click for a second.
You know, a lot of people that listen to this podcast are, um, entrepreneurs, tech entrepreneurs, people building companies.
I would love to get from you some, some advice, you know, uh, talking about your experience with, um, AI technologies.
This is a company that, you know, you ended up taking public very successfully and you did some really impressive things there.
What's some advice that you would give to entrepreneurs or a technologist today building companies that you think is, you know, beneficial or important?
Maybe something that a misconception people aren't, you know, often paying attention to.
I think that people who build technology companies sometimes think that the technology is the most important point.
And it's just not. It's the humans, right?
At the end of the day, you're trying to solve a problem that humans have. And so, you have to start with the problem.
So, the problem we were solving at AI for autonomous cars was very simple.
You can use radar. You can use cameras to see what's out there.
But the reality is at high speeds, they're not fast enough.
Cameras actually have problems with light density, even though they're very, very good at density.
And radar goes very, very far distances, but it can't really tell what it is.
So we developed a LIDAR system, the same system we used on our military jets to target things or to defend themselves against things attacking them.
And we decided we got to figure out how to use this LIDAR because LIDAR was the only technology that existed that could see exact distance at long distances at At the speed of light.
Right. And so that was the problem.
The problem was I can put a camera system or a radar system on a car and I can go slow and I can process the world.
I can't get on a highway.
So, again, that was the the the impetus of our company.
And that's how we built our product.
Now, we have to use really sophisticated technology to do it, but I knew what my problem was, was that the German DMV had put a standard out there, and the standard actually was a worldwide standard on what you'd have to do to be able to be better than a human.
And then we tried to be better than a human, and you're seeing it roll out there.
Now, a lot of people will ask me, well, Elon Musk, he's a genius.
He didn't use LIDAR.
Elon Musk loves LIDAR, okay?
Okay. Elon Musk, when Tesla came out, they couldn't use LiDAR because the laser was too expensive.
It was $10 ,000 per unit.
So I can't have a consumer car and actually put $30 ,000 worth of sensors on it and still be able to sell it.
And so he did it with cameras and with radar at the beginning because it was the right business decision.
And then he just got better.
And at the end of the day, when people ask, why did he take LiDAR out?
Because in order to be as good as a LiDAR system his theory was if the radar and the camera agree there's a 99 .999 percent chance they know what they're seeing that makes a lot of sense until the camera or the radar don't agree because it's a it's a you're at dusk in the light the camera says I don't see anything and the radar goes I see something or the radar bounces off something metal and doesn't see something and what was happening is they realized that depending on both of them to agree, gave them a 1 % default rate.
So he was better to pull back and to actually just use camera and use an AI algorithm and a learning algorithm and a camera.
He had enough data that he was willing to go to one sensor versus two.
So that's a perfect example of someone using AI in the correct way.
He needed two sensors until the AI was good enough that he felt there it was a 99 .9 % and he had enough data and enough reinforcement learning that he could go back to just cameras.
And by the way, cameras are really cheap and there's a ton of cameras on a car already.
So back to think of the problem and then figure out what technology you'll use.
I love that. That's fantastic advice.
Okay. Something I also wanted to ask you about, I know that you are working with the Buck Institute on aging.
At the beginning of the the podcast you said this is one of the the most important things or top things you're looking at um first of all tell us a little bit about about the buck institute what inspired it uh how you kind of got involved with this concept there's a lot of interesting things going on in this space right now to talk about but i would also be curious like how you see ai changing in kind of this health and wellness we've seen a lot of stuff you know we just saw big announcements out of um You know, the White House yesterday with Oracle making their historic 500 billion dollar investment with SoftBank
and OpenAI. And you had Larry Ellison talking about using AI, you know, nanobots to scan your blood and make custom vaccines.
Like there's just crazy stuff going on.
So I'm just curious, based off of your perspective on what you're seeing and working on with the Buck Institute, how you see this kind of impacting the industry?
Sure. And I'll just use it as an analogy.
Even if you're not in healthcare or you're not in longevity, what I'm going to say to you applies to every industry.
Look, the buck itself is a legend, and it's the largest independent basic research institute in the Bay Area, which is saying something, and it's been around for 30 years.
and you know, it's a 30 -year overnight success in the sense that 30 years ago, no one was studying aging and longevity.
So there was a big grant and, you know, how can we change the world?
We're going to start an institute where we can hire people from all over the world and they're going to look at aging not as a disease, but they're going to look at aging as an impetus to diseases.
So we think of things as what are the age -related diseases.
Arthritis, Alzheimer's, heart disease, all of them, the highest correlate to those things, if you think about it, is the older you get, the more likely you're going to get it.
So, sometimes people go, oh, you know, that's an old person's disease.
The older you get, you get these diseases.
So, most people were spending time looking at them individually.
We looked at them and said, no, no, no, let's look horizontally and let's open up labs across all of them, because there's got to be commonality.
If these things are all being caused as you get older and they're all making our life miserable and we're dying earlier, there's got to be some connection.
And the connection is a really simple one.
When you get sick, you get inflammation and the inflammation is something's going in to try to solve the problem you have. But it turns out that you will get sick if you have chronic inflammation, which means you don't clear it out you know you get a cut it heals up it's you know the blood goes in and it goes out well if you have chronic inflammation of your body whether that's caused by food or it's caused by stress or it's caused by lack of sleep or it's caused by a lot of different things um you will actually um you will actually age faster right and that was the big it sounds simple today
but that was a big different it was a different way of looking at geroscience right and so what i would tell you about the Buck Institute is that what we have done in the last three years is really take a huge turn.
And there's a thing called the innovator's dilemma, which a great guy who I miss, Chris Christensen, wrote a book many years ago.
And it's really about the fact when you're really successful at something, it's so hard to innovate because the risk in doing something different is high.
And people understand that.
But what you forget is the other reason it's hard is because you're making money or being successful in what you're doing.
So if you take focus off that, you feel like you're falling behind.
So there's a double whammy.
You're doing well, and you're making money, and if you try something different, you may lose, right?
Yep. So the innovator's dilemma in some place like longevity is that we'll keep doing basic research, researching the body.
90 % of what we know about humans is ecometric, okay, which means that it's just by watching people over thousands of years.
The three -phase trials and all this this stuff we like to believe, very small percentage of science and medicine and longevity has got to do with that.
Now it's growing. Since we started sequencing the genome, we know a lot more, but only 7 % of the notes of your music are in your genetics and 93 % are how they express themselves in the environment that you're in.
So let's take an example of using AI.
Here we are, we're a great basic research institute.
We have more grants than anyone else in the world.
And we decided we would bring in two guys, Lee Hood, who helped sequence the genome with Venter, and ran Bill Gates' system biology unit, and another guy, Nathan Price, his protege.
And we would spend a bunch of money, and we would bring these guys in.
What they do is they sequence big data.
All of the labs that we have looked at us and said, why?
Why would we not be doing basic research?
We do great basic research on animal models, and then we transition it to human models, and it takes seven years.
What we found since they've been in here is we can now take data using AI and not only take what they're doing in basic research but expand it out to predict it, but we can then use those predictions to come back and change the basic research. That is fundamentally changing the way that you will develop drugs, and it's also fundamentally changing the way that you will personalize medicine.
So I'm going to give you guys the, you know, there's a book called Scientific Wellness that these guys wrote, which is one of the books I read and I knew we had to have them, right?
Scientific wellness basically makes the proposition that we are now at a time that science and big data is so good that I can now predict versus, um, predict and then prevent you from getting illness before you get it.
98 % of what your doctor does when you go and see him is look for illness.
And then once he finds it, if there's nothing wrong with you, he says, great job.
See you in a year. 100 % of what hospitals do is treats sickness.
So what that means is that since doctors only get activated in illness and hospitals only get activated in illness, most of our money has gone on curing illness, which means we wait till people break, which is the highest cost and the lowest return on when you could invest money.
Interesting. What AI is doing now is we can actually now use models to predict and prevent you from getting sick, which is the lowest cost and the highest impact, and changes the way that medicine gets done.
So and that's what Larry was alluding to.
The second piece of it is, I think, even more important for your listeners.
This isn't to do with your business.
This is to do with you, right?
If predict and prevent is where we should be looking.
working. So use science to find ways to not get sick.
There's a test called the Grail test, for example.
I'm not endorsing it.
I don't have stock in it.
But it screens for the top 50 cancers before they hit stage one.
Now if you're 50 years old and you're not screening for the top 50 cancers and you won't go to stage one, they're going to give you chemo and they're going to burn your cells.
It's ugly, right? But if you could actually find out you're predisposed now in the the next three years, and you could change your lifestyle to avoid it, spend the money and get the test. Okay?
But the second piece of this is personalize and participate.
Most healthcare has got their rules of thumb, but most healthcare has got to do with your personal system biology.
That's why some people get sick, some people don't get sick, some people get cancer, other people that don't get cancer, there's about 100 to 1 % of people out there that have a genome that reimagines its immune system every day.
I had a woman that we met the other day.
She's smoking a cigarette.
She drinks every day.
She's 100 years old.
That genetic makeup that she won the lottery with, she'll start deteriorating about 18 months before she dies.
She may get dementia.
She may may get arthritis, and then she'll die very quickly.
That is the best outcome ever.
You live the longest and you only decline for a short period of time.
Today in the United States, we actually die, we're 39th in the world behind Cuba, who we just took off the terrorism list and put back on again, and they have no money, right?
We're 39th in the world in longevity, and it's gone down in the last five years, right?
And we die longer than anyone else dies.
We start dying 14 years before we die.
And the way that's measured is how many, remember back to my chronic inflammation illnesses, how many chronic inflammation illnesses do you have?
By the time an American is 60, they have, most of them have one, 70 % of them have one.
And by the time they're 65, I think 58 % of them have two, which means even if you're alive, your life is becoming miserable, right?
And then when you add in dementia and Alzheimer's and things like that, oh my God, that's not just a chronic illness.
That's I'm losing who I am.
So we really need to think about how to actually stop ourselves from getting age -related diseases.
And we can predict disease, but really personalizing and participating means that you would be collecting data about yourself.
At your age with a one -year -old, you should be collecting and you're going to say, oh my God, you should be taking blood tests twice a year, and you should be be taking at least 50 biomarkers.
Why? Because later on in life, I can see the changes in your biomarkers, and it's the number one predictor of when illness is going to hit you.
Now, we didn't do that in my day and age, right?
But you can. And so back to this whole idea about how's AI going to change the world, everyone jumps on cures.
AI is going to do cures.
But the real impact is not to get sick.
And that's in scientific wellness.
Predict it and prevent it.
Personalize your data so that you can participate with your doctor.
When you get a sickness and you go to your doctor and he says you have cancer, the first thing you do is you go to a specialist and you become an expert at everything to do with that cancer and he talks to you about everything to do with that cancer and they collect every bit of data.
What if you collected data when you're healthy and you talked about your health so that you would optimize your health before you got sick.
At your age, if you do that, you'll live to over 100 by...
I'm not telling you you're going to live to 150.
I can't promise you that, but I can promise you that your health span will go up 10 years.
That was incredible.
That is incredible.
You had 10 more years of quality life.
Well, I think this is a very timely topic.
First of all, it's really exciting for me how much emphasis and energy and focus has been put on this kind of healthy living longevity focus right now, especially with, like you mentioned, some interesting things with AI and kind of personalized medicine.
Definitely, it's a good call out for me because it's not something I have done a lot of any of the biomarker stuff.
I've done blood tests and had my blood looked at and stuff like that in the past, but not twice a year.
So this is probably something I should focus on more.
Right, but when you've taken blood, they've been searching for illness.
You weren't taking blood to create a database so that you would know more about yourself.
And that's the difference.
You'll take different biomarkers when you're looking at health than when you're looking to find illness.
They're going to take your cholesterol, right?
But that's looking for illness.
So yeah, what would you recommend for people listening to get started on this?
I think a lot of people are interested.
we have, of course, the Don't Die documentary.
We have Brian Johnson, who's coming out with all of his supplements and longevity and healthcare kind of focused stuff.
So I think it's a big focus right now in America and probably other places in the world as well.
So what would you suggest for people to get started?
I'm going to give you five things with two things in each category that are universal, that they're not necessarily have to be personalized.
And then I'll give you five five tests that you could do to personalize the rest of the things you do in each category.
But what I would say before we get off of AI is that, like I said, there's going to be AI to cure illness.
There's going to be AI to prevent illness.
Right now, I think OpenAI just announced that they literally just did a special version of AI that's looking at longevity and looking at proton folding and looking at how your blood changes over time.
that's going to help, right?
Because we're going to be focused on how to predict and how to prevent illness.
So there are going to be a lot of new tools that are coming out over the next three or four years.
But that aside, what could you do today?
So the number one impact, why don't I ask you what you do?
Do you know by far there's more studies that prove this than any other study in medicine, what do you think the number one precursor or predictor of whether you're going to have a longer health span or not?
The top one is that humans are designed very differently than any other animal on earth.
Now, that doesn't mean we have similarities, but we have some real big differences, right?
And one of the big differences is we have a the parasympathetic nervous system that is based on a very unique vagus nerve that ties our brain to every organ in our body and our stomach biome.
And what that really means is that we are designed as pack animals and tribal animals.
And so the number one impact on health is, do you feel like you have connection in your life?
The number one cause of mental illness under 25 and the number number one cause of suicide is loneliness.
The number one cause of death over 65 is loneliness.
So above all else, you have to figure out whether you're an introvert or an extrovert or whether you don't want five relationships or one, you have to figure out how to be vulnerable enough to actually feel like you care about people and they care about you.
Underneath that, we call it a force multiplier.
If you do a good job at that, all of the things that I'll tell you get multiplied by 10.
And what are those things?
What fuel do you put in the machine?
How does the machine move every day?
How do you maintain the machine?
And where does the machine live?
Those four things. And so when you look at fuel, the number one thing that you can do to increase your longevity and your health span is calorie restriction.
And the worst thing you you can do is to be obese, which causes inflammation, which causes...
So clear. We've known that for a long time.
Easier said than done.
The number two thing that you can do, other than calorie restriction, if you went to 600 calories a day, which is awful, you'd live 10 more years.
Every animal we've tested, every human we've tested actually increases health span because what it does is put stress on the body.
And when the body's stressed stressed out.
It works harder and it lives longer.
It's just, you'll be miserable.
Right. The second thing that you can do.
Right. And, and by the way, there's a hack to this, right?
It's intermittent fasting.
So if you would intermittent fast and you give yourself 12 hour windows, you'll put stress on your body.
And because you have shorter eating windows, you're going to eat less calories.
It's not perfect. It's not as good as going to 600 calories, but you know, if you don't eat breakfast or you eat dinner before five o 'clock, you're going to have less inflammation in your your body and you're going to live longer.
Okay. Now that takes, you know, requires you to change, you know, a little bit of your lifestyle, right?
You're going to eat earlier or you're not going to eat breakfast, right?
The second thing is that if you actually put on a CGM, which is we develop for diabetics, you know, because we, we spend a lot of money on sick people.
It's a constant glucose monitor.
You can now get those when you're healthy and you can see what, what you're allergic to and what spikes your glucose.
So you can take a $100 food sensitivity test, or you can put a CGM on for 15 days.
And every time you eat, you just put what you ate, and it will tell you what things your body is reacting to.
If you did that, you would find out what things spike your sugar.
And spiking your sugar is one of the biggest reasons that your inflammation ends up in your body.
So just learning. So those two things are just two easy hacks to help yourself live longer with Fuel.
Now, anything below that is personalized.
I had two diet companies in my career.
And the reality is I love diet products because it's the only product you can sell to someone when they fail, they blame themselves, and they're back in 18 months because they always think it must have been them.
The reality is, you know, there's, it's a normal curve.
Some people are, keto is great for them.
Some people it isn't.
Some people, Mediterranean is great for them.
Some people it isn't.
You can't know until you test your biome and you look at your glucose absorption.
And those things are really easy today.
So when you look at what I just told you, you say, oh, I can do a food sensitivity test for $100 on collecting data.
I can do a CGM for 15 days at $150.
I can do a biome test for $250.
If you did all three of those things, you'd know a lot more about how your body absorbs fuel, right?
And what you're doing, using less fuel and you're putting fuel that your body likes, right?
The second category is the one you know, which we call exercise, but is really not exercise.
exercise it's movement if you had a machine and the machine had different ranges of motion you would want to test the range of motion of that machine every day right you want to go up and down and left and right just to make sure that the machine can move right and you'd want to put it on high intensity up to about 80 percent and then you'd want to bring it way down and let it rest on a low setting and so if you think of your body that way the trade of not moving 15 minutes every hour.
If you work out two hours a day, but you don't move 15 minutes every hour, it's a bad trait.
Humans weren't designed to exercise.
We've been in starvation for thousands of years.
We exercise to get food or to build things, right?
We don't exercise because we have to exercise.
What we thought is, well, if I sit around all day, I can exercise for two hours and make up for it.
If you can get up for 15 minutes or use a standing desk during the day, that is a better trade for your body because your body will actually um balance itself better right so moving 15 minutes every hour and the other one is HIT is a big trend I I had owned a company we managed gyms we had you know 1800 gyms I I know a lot about how you sell gyms um there's a lot of different ways you can exercise but it turns out that your body needs 10 minutes of HIT a day and 10 minutes of LIT.
If you do 30, that's great.
But it's interesting what that is.
That's your heart rate.
Right. So if you think you're a machine and I wanted my machine to get up above 85 percent RPMs to make sure all the oil is going and that all everything is activated, then I would do I would jump rope three minutes, three times a day.
As long as I get 10 minutes of HIT, my body found its upper bound.
And as long as I rest for 10 minutes.
Now, some people will call that meditation.
I call it watching a Hallmark movie.
But as long as you sit somewhere where you're rested, and one of the keys to this, if you're going to do something like meditation, is to get rid of the sounds around you.
You want sounds that are not discontinuous.
So the reason why 20 % of cancer cells die when patients are taking therapy, listening to classical music, is because your immune system likes it.
It relaxes and is able to fight the cancer cells better.
So why do people say take a walk in nature?
Because all the sounds in nature resolve like a classical song, right?
When you hear a sound in nature that is not resolving, it's a big bear going grrrr.
Then you go to the HIT and you start running as fast as you can until you get away from it and then you relax again.
But it's all about letting your body relax.
And your body relaxes when it's got that's visual, low visual stimulus and low sound stimulus, and that you can actually breathe.
Because the way that your vagus nerve, your brain to your body, rebalances itself, breathing is a very good way to do that, right?
Another way to do it is hit your pressure points for your vagus nerve, like pull down on your ears for a minute.
But your vagus nerve to get your body to rebalance is very important.
So in the first category, I said, reduce your calorie intake and find things that don't spike your glucose.
In your exercise category, move 15 minutes every hour, 10 minutes of HIT, 10 minutes of LIT.
Now anything above that you can do, and it's probably, it can be good for you, right?
But you don't, that the basics, if you don't do the basics, none of that stuff has the same impact.
In maintenance, maintenance is two things for a human.
One is sleep and the other is touch. So if you're not actually hugging people or no one touches you, or you're not getting a massage, um, then your body isn't reacting to that stimulus and calming itself down and your fasci inside of your body isn't relaxing.
Okay. So hugging is important.
Let's get a hug over 15 seconds, which is very uncomfortable in the U S but it's the right thing to do.
The thing around sleep is that yes, amount of sleep matters, but eight hours of sleep is just an average.
Some people need a little bit less than 1 % of people can get by.
And if you're sleeping less than six hours, you're lying to yourself.
Um, if you're sleeping more than 10 hours, you probably are depressed, right?
But eight hours is a nice average, but I can tell you the most important thing in sleep is going to bed at the same time, five days a week or of the the week.
Why? Because I called it maintenance.
If your body knows when your maintenance crew's coming in and it's aligned to your chronotype, you get all of your deep sleep in the first two hours of your chronotype.
So if your chronotype says I need to be in bed at 10 o 'clock, that means that if I go to bed later than that, I'm going to miss some of my deep sleep.
All of your REM sleep, not all of it, but the majority comes in the last two hours.
So if I go to bed too early and I wake up earlier, I don't get as much REM.
So aligning your chronotype and picking what time you go to bed, when your body knows you're going to go to bed at the same time, your maintenance crew knows when to come in and it's 20 % more effective.
So I get 20 % more sleep just by letting my body know.
It likes that consistency, right?
So two things in maintenance.
And the final thing is your environment, which you don't think about a lot.
We think about air pollution and we think about smoking.
And we say, oh, those are bad.
And they are, and it's completely correlated to breakdown in your system, which causes illness and cancers.
But if you also think of other things in your environment, so for instance, when you're washing your clothes, you're putting detergent and softener on those clothes.
Your skin is your largest organ.
None of them have been tested for long -term effects because that's not the way we test chemicals in the United States.
So if you're not using organic, you know, washing, you know, for your washer, organic detergent, you're putting chemicals on your body every day and it goes under your skin through your clothes.
And the other big thing in your environment is your dishwasher.
If you're not using organic, you know, detergent in your dishwasher, every time you take a glass or a plate and you eat, it transfers the chemicals to your body.
I'm not saying that on any given day that chemical is going to kill you.
what i am telling you is that consistent exposure to chemicals no matter what they are changes your system biology and reduces the effectiveness of your immune system so i just gave you 10 things to do find a relationship do things and be connected with people you know and do the two things that each of the other four that will impact your life now the other last thing i would would say is it's a both multivariate all the research shows doing one of them and not doing four or five is not clear it's not even close to as effective right you got to do a couple things in each category and all the things
I just told you you could do in less than a half an hour a day right so that's my that's my health talk it's pretty simple right Blair this has been amazing Amazing.
I feel like we have like a full blueprint right here with some absolutely incredible takeaways.
I'm personally excited to get started and actually work on a bunch of these things.
So I really appreciate you sharing.
The last thing I would just ask you as we're kind of wrapping up on all of this, do you know of any, like when people talk about AI being kind of used in personalized healthcare, maybe personalized in kind of a lot of this longevity stuff, Is there currently companies today like working on this that people could go to and use, or is this kind of something on the horizon that's coming?
Yeah, you know, there's a lot of companies working on individual things.
So your aura ring is getting smarter and smarter, right?
And it's giving you more and more things.
And so it's focused on sleep, but it's expressing out into other disciplines.
So a lot of people are working on algorithms and AI to help you.
But we're on the verge, I think, in the next year to two years of getting multivariate personalized personalized advice.
How do we get that today?
We go to our doctor.
We go to our trainer and we go to our spouse and we build a system for ourselves.
And we hopefully we can feel what's working for us, what's not.
We're getting really close.
If people go to the Buck website, the Buck Institute website, you'll see we just got a grant from ARPA, that will actually, and we'll be doing a study that's a very fast study.
It will be done in two months.
That's going to take 4 ,000 different pieces of data from someone over 24 hours a day, over 10 weeks.
And we're going to actually put that in and see if we can match what we've seen in the past, which is we collected data on people anonymously and then we predicted what would happen to those people.
And now we're going to do it and we're going to personalize it.
So we're starting that process.
So in the next year, you're going to start seeing this.
How do you get started today?
Collect your data because there'll be systems out there that will be able to eat it up.
But getting data over time is the hardest thing, longitudinal studies.
So again, you want to participate by collecting personalized data.
And as the technology advances, you can feed the data in and have it take a look at the trends.
and that's how you're going to be able to tell what you need versus someone else.
This has been absolutely fascinating, Blair.
Super excited. For the listener, I'm going to leave links in the description to everything that he's been talking about, specifically with the Buck Institute so you can go check all of that out.
Blair, thank you so much for coming on the show today.
I feel like I need to have you on again soon.
You have so many insights, I feel like you really scratched the surface.
But thank you so much for coming on.
to the listener. Thank you so much for tuning into the podcast. I'll leave a link in the show notes to Blair's LinkedIn.
If you want to go follow him there, he's posting all lots of amazing stuff.
Make sure to rate and review the podcast wherever you listen to it.
And I will see you next time.
All right, Jayden. Thank you.
