David Sinclair: Extending the Human Lifespan Beyond 100 Years

00:00:00.000 | The following is a conversation with David Sinclair.

00:00:02.800 | He's a professor in the Department of Genetics at Harvard

00:00:06.240 | and co-director of the Paul F. Glenn Center

00:00:09.000 | for the Biology of Aging at Harvard Medical School.

00:00:12.320 | He's the author of the book "Lifespan"

00:00:14.240 | and co-founder of several biotech companies.

00:00:16.920 | He works on turning age into an engineering problem

00:00:20.840 | and solving it, driven by a vision of a world

00:00:23.960 | where billions of people can live much longer

00:00:26.000 | and much healthier lives.

00:00:28.180 | Quick mention of our sponsors,

00:00:30.380 | Onnit, Clear, National Instruments,

00:00:33.400 | and I, SimpliSafe and Linode.

00:00:36.840 | Check them out in the description to support this podcast.

00:00:40.040 | As a side note, let me say that longevity research

00:00:42.780 | challenges us to think how science and engineering

00:00:45.880 | will change society.

00:00:47.660 | Imagine if we can live 100,000 years,

00:00:50.400 | even under controlled conditions,

00:00:51.920 | like in a spaceship, say,

00:00:53.720 | then suddenly a trip to Alpha Centauri

00:00:55.960 | that is 4.37 light years away

00:00:58.840 | takes a single human lifespan.

00:01:01.280 | And on the psychological, maybe even philosophical level,

00:01:05.160 | as the horizons of death drifts farther into the distance,

00:01:08.720 | how will our search for meaning change?

00:01:11.120 | Does meaning require death

00:01:13.080 | or does it merely require struggle?

00:01:15.720 | Reprogramming our biology will require us

00:01:18.360 | to delve deeper into understanding the human mind

00:01:21.440 | and the robot mind.

00:01:23.680 | Both of these efforts are as exciting of a journey

00:01:26.560 | as I could imagine.

00:01:28.160 | This is the Lex Friedman Podcast

00:01:30.320 | and here is my conversation with David Sinclair.

00:01:33.400 | I usually feel like the same person when I was 12.

00:01:38.320 | Like when I, right now, as I think about myself,

00:01:42.460 | I feel like exactly the same person

00:01:45.040 | that I was when I was 12.

00:01:46.400 | And yet, I am getting older, both body and mind,

00:01:52.040 | and still feel like time hasn't passed at all.

00:01:54.280 | Do you feel this tension in yourself

00:01:56.920 | that you're the same person and yet you're aging?

00:02:01.040 | - Yeah, I have this tension that I'm still a kid.

00:02:04.680 | But that helps in my career.

00:02:05.920 | Scientists need to have a wonder about the world

00:02:07.960 | and you don't wanna grow up.

00:02:09.800 | 12-year-olds, and even younger,

00:02:11.700 | I would say six, seven-year-olds,

00:02:13.400 | I've still got that boy in me and I can look at things.

00:02:16.580 | It's a gift, I think, that I can see things

00:02:18.260 | for the first time if I choose to

00:02:20.000 | and then explain them as I would to a six-year-old

00:02:23.160 | 'cause I am that mentally.

00:02:24.960 | But on the other hand, I'm getting older.

00:02:26.720 | I run a lab of 20 people at Harvard.

00:02:29.260 | I've got a book, I've got science to do, companies to run.

00:02:33.520 | And so I have to, on most days,

00:02:35.680 | just pretend to be a grown-up and be mature,

00:02:38.160 | but I definitely don't feel that way.

00:02:40.680 | - There's something I really appreciated

00:02:43.400 | in the opening of your book.

00:02:44.920 | You talked about your grandmother.

00:02:46.920 | And on this kind of theme, on this kind of topic,

00:02:50.360 | she, first of all, had a big influence on you.

00:02:53.720 | My grandmother had a big influence on me.

00:02:56.520 | And you also mentioned this poem

00:02:59.080 | by the author of "Winnie the Pooh," Alan Alexander Milne.

00:03:03.760 | Maybe I can read it real quick 'cause I...

00:03:06.880 | (laughs)

00:03:08.480 | On the topic of being children,

00:03:10.280 | when I was one, I had just begun.

00:03:12.560 | When I was two, I was nearly new.

00:03:14.800 | When I was three, I was hardly me.

00:03:17.280 | When I was four, I was not much more.

00:03:19.840 | When I was five, I was just alive, but now I am six.

00:03:24.320 | I am as clever, as clever, so I think I'll be six,

00:03:27.500 | now, forever, and ever.

00:03:29.600 | So this idea of being six and staying six forever,

00:03:36.440 | being youthful, being curious, being childlike,

00:03:41.360 | this and other things, what influence has your grandmother

00:03:46.360 | had on your thinking about life, about death, about love?

00:03:51.520 | - Yeah, I was getting misty-eyed as you read that

00:03:54.920 | because that poem was read to me very often,

00:03:58.060 | if not every day, by my grandmother

00:03:59.520 | who partially raised me.

00:04:01.400 | And she was as much a bohemian as an artist, philosopher.

00:04:06.440 | And she's one of those people that wouldn't talk

00:04:08.880 | about the little things.

00:04:09.760 | She said, "I hate small talk.

00:04:11.520 | "Don't talk to me about politics or the weather.

00:04:13.900 | "Yeah, talk to me about human beings and culture."

00:04:16.960 | So I was raised on that, and this poem was one

00:04:19.720 | that she read to me often because she knew

00:04:22.480 | that the mind of a child is precious, it's honest,

00:04:27.480 | it's pure, and she grew up during the Second World War

00:04:31.520 | and in Hungary, in Budapest, witnessed the worst of humanity.

00:04:35.720 | She was trying to save a whole group of Jewish friends

00:04:40.100 | in her apartment, saw what happened after the World War,

00:04:43.220 | which was there was, the Russians were in control

00:04:47.800 | and locals weren't necessarily treated well

00:04:50.360 | if they were rebellious, which she was.

00:04:52.560 | And then there was the revolution in '56,

00:04:54.480 | which she was part of and had to escape the country.

00:04:57.280 | So she saw what can happen when humans do their worst.

00:05:01.300 | And her words to me, expressed in part through that poem,

00:05:05.280 | was, "David, always stay young and innocent

00:05:09.500 | "and have wonder about the world,

00:05:11.520 | "and then do your best to make humanity the best it can be."

00:05:15.440 | And that's who I am, that's what I live for,

00:05:18.340 | that's what I get up in the morning to do,

00:05:19.800 | is to leave the world a better place

00:05:21.680 | and show to whoever's watching us, whether it's aliens

00:05:24.040 | or some future human historian, that we can do better

00:05:27.640 | than we did in the 20th century.

00:05:29.280 | - You know, we mentioned offline this idea

00:05:33.200 | of bringing people back to life

00:05:34.920 | through artificial intelligence.

00:05:38.240 | Sort of, I don't know if you've seen videos

00:05:40.880 | of basically animating people back to life.

00:05:45.200 | Meaning, whether it's, for me personally,

00:05:47.960 | I've been working on, specifically about Albert Einstein,

00:05:51.600 | but also Alan Turing, Isaac Newton, and Richard Feynman.

00:05:55.740 | And it's an opportunity to bring people

00:05:59.540 | that meant a lot to others in the world.

00:06:02.360 | And animate them, and be able to have

00:06:05.600 | a conversation with them.

00:06:06.840 | At first, to try to visually,

00:06:10.260 | visually explore the full richness of character

00:06:17.200 | that they had as they struggled

00:06:18.800 | with the ideas of the modern age.

00:06:20.880 | Sort of, it's less about bringing back their mind,

00:06:24.100 | and more bringing back the visual quirks

00:06:27.420 | that made them who they are.

00:06:28.920 | And then maybe in the future,

00:06:30.920 | it's using the textual, the visual,

00:06:33.160 | the video, the audio data to actually compress

00:06:38.160 | down the person for who they are,

00:06:41.040 | and be able to generate text.

00:06:42.440 | There's a few companies, there's Replica,

00:06:44.480 | which is a chat engine that was born

00:06:46.880 | out of the idea of bringing,

00:06:48.440 | the founder lost her friend to,

00:06:53.440 | he got ran over by a car.

00:06:55.840 | And the initial reason she founded the company

00:06:59.720 | was trying to just have a conversation with her friend.

00:07:02.840 | She trained a machine learning,

00:07:05.520 | natural language system on the text

00:07:08.240 | that they exchanged with each other,

00:07:09.480 | and she had a conversation with him,

00:07:11.880 | sort of after he was gone.

00:07:13.880 | And it's very, the conversation was very trivial.

00:07:16.880 | It was obvious that it's, you know,

00:07:19.560 | a AI agent, but it gave her solace.

00:07:23.200 | It made her actually feel really good.

00:07:26.080 | And that's the way I wonder if it's possible

00:07:27.920 | to bring back people that are,

00:07:30.840 | that mean something to us personally,

00:07:32.520 | not just Einstein, but people that we've lost,

00:07:36.600 | and in that way achieve a kind of small,

00:07:40.480 | artificial immortality.

00:07:42.680 | I don't know if you think about this kind of stuff.

00:07:44.720 | - Well, I definitely think about a lot of things.

00:07:46.640 | That one's a really good one.

00:07:47.640 | There's a great Black Mirror episode

00:07:49.160 | about the wife who brings back the boyfriend or husband.

00:07:52.840 | I think one of the challenges

00:07:54.280 | with bringing back Richard Feynman

00:07:55.520 | would be to capture his sense of humor,

00:07:58.080 | but that would be awesome.

00:07:59.300 | But yeah, bringing back loved ones would be great,

00:08:00.920 | especially if it's, you know,

00:08:04.000 | they're young and they die early.

00:08:07.680 | Though it may hold you back from moving on.

00:08:09.180 | That's another thing that could happen as a negative.

00:08:11.840 | But I think that's great,

00:08:12.680 | and I also think that it's gonna be possible,

00:08:14.680 | especially when we're recording, some of us,

00:08:17.280 | every aspect of our lives,

00:08:18.440 | whether it's our face or things we see.

00:08:22.640 | Eventually one day, everything we see can be recorded.

00:08:26.000 | And then you can build somebody's experience

00:08:28.960 | and thoughts, speech,

00:08:31.840 | and you will have replicas of everybody,

00:08:34.980 | at least digitally and physically,

00:08:37.000 | you could do that too one day.

00:08:38.720 | But that's a good idea,

00:08:40.360 | especially 'cause there are people that I'd like to meet,

00:08:42.620 | and I think it's easier than building a time machine.

00:08:44.920 | One person I'd love to meet is Benjamin Franklin.

00:08:47.320 | - Really?

00:08:48.160 | - Well, I wouldn't go back in time, I would,

00:08:51.120 | but I'd prefer to bring him into the future and say,

00:08:54.080 | "Can you believe we have this thinking machine

00:08:57.000 | in our pockets now?"

00:08:58.440 | And just see the look on his face

00:09:00.240 | as to where humanity has come.

00:09:01.320 | 'Cause I think of him as a modern guy

00:09:03.500 | that just was before his time.

00:09:05.480 | - Yeah, so you're thinking Benjamin Franklin is a scientist,

00:09:08.520 | not Benjamin Franklin, the political thing.

00:09:10.400 | 'Cause he'd be very upset with Congress right now.

00:09:13.040 | - Right.

00:09:13.880 | - So maybe talk to him about science and technology,

00:09:16.160 | not politics.

00:09:18.160 | Or maybe just don't get him on Twitter,

00:09:19.580 | because he'll be very upset with human civilization.

00:09:22.400 | You know, I wonder what their personalities are like.

00:09:25.360 | Isaac Newton, it does seem complicated

00:09:28.640 | to figure out what their personality is like.

00:09:30.480 | Even Friedrich Nietzsche, who I also thought about.

00:09:33.320 | Feynman is, we just have enough video

00:09:36.800 | where we get the full kind of,

00:09:39.360 | I mean, it shows you how important it is

00:09:42.440 | to get not the official kind of book-level presentation

00:09:47.560 | of a human, but the authentic,

00:09:49.560 | the full spectrum of humanity.

00:09:51.940 | You mentioned collecting data about a person,

00:09:54.420 | collecting the whole thing, the whole of life,

00:09:57.260 | the ups and downs, the embarrassing stuff,

00:09:59.500 | the beautiful stuff,

00:10:00.660 | not just the things that's condensed into a book.

00:10:03.180 | And then with Feynman, you start to see that a little bit.

00:10:05.860 | Through conversations, you start to see peaks

00:10:07.940 | of like that genius.

00:10:09.420 | And then through stories about him from others.

00:10:12.900 | And then certainly you,

00:10:15.160 | the sad thing about Alan Turing, for example,

00:10:17.720 | is there's very little, if any, recording of him.

00:10:22.240 | In fact, I haven't been able to find recording.

00:10:24.180 | Allegedly, there's supposed to be a recording of him

00:10:27.600 | doing some kind of radio broadcast,

00:10:29.720 | but I haven't been able to find anything.

00:10:32.120 | And so that's truly sad.

00:10:34.720 | That it feels like, it makes you realize

00:10:36.840 | how the upside, how nice it is to collect data

00:10:42.320 | about a person, to capture that person.

00:10:45.900 | There's, that's the upside of the modern internet age,

00:10:48.740 | the digital age, that that information,

00:10:51.320 | yeah, creates a kind of immortality.

00:10:54.260 | And then you can choose to highlight

00:10:57.100 | the best parts of the person,

00:10:58.220 | maybe throw away the ugly parts

00:11:00.580 | and celebrate them even after they're gone.

00:11:03.460 | So that's a really interesting opportunity.

00:11:05.100 | You've also mentioned to me offline

00:11:07.900 | that you're really excited about all the different wearables

00:11:11.060 | and all the different ways we can collect information

00:11:14.040 | about our bodies, about, well, the whole thing.

00:11:18.400 | What's most exciting to you

00:11:20.280 | in terms of collecting the biological data

00:11:25.280 | about a human being?

00:11:27.840 | - Well, so I'm a biologist.

00:11:29.320 | I find animals and humans as machines very interesting.

00:11:33.140 | It's one of the reasons I didn't become an engineer

00:11:36.500 | or a surgeon, I wanted to understand

00:11:38.140 | how we actually are built.

00:11:40.600 | And so I think a lot about machines merging with humans.

00:11:45.600 | And the first of that are the bio wearables.

00:11:49.040 | And so I talked a lot about this,

00:11:50.300 | I wrote about it in "Lifespan," the book,

00:11:52.440 | and pictured a future where you would be monitored constantly

00:11:56.860 | so that you wouldn't suddenly have a heart attack,

00:11:59.280 | you'd know that was coming,

00:12:00.240 | or you wouldn't go to the doctor

00:12:02.640 | and they don't know if you need an antibiotic or not.

00:12:05.680 | Long-term, how old are you, how to fix things,

00:12:10.000 | what should you eat, what should you take,

00:12:11.560 | what should your doctor do?

00:12:12.980 | These devices, I predicted, would be smarter,

00:12:16.100 | better educated than your physician,

00:12:18.080 | and would augment them,

00:12:19.720 | and then there'd be a human that would just tick off

00:12:21.460 | to see if it's correct and they approve.

00:12:24.320 | I also was predicting in the book

00:12:26.840 | that we would have video conferences with our doctors

00:12:30.200 | and that medicines would be delivered,

00:12:32.040 | initially by courier, but eventually by drones

00:12:33.960 | and get it to you, sometimes in an emergency,

00:12:36.240 | and that we could even have pills

00:12:38.000 | that were synthesized or delivered in your kitchen,

00:12:41.820 | and combined, certainly.

00:12:43.920 | What's amazing about that is that, what are we now,

00:12:47.120 | two years since the book came out, even less,

00:12:50.200 | and that future is basically here already.

00:12:52.360 | COVID-19 accelerated that incredibly.

00:12:56.880 | So where we're at now in society is,

00:12:58.480 | if you want to pay for it,

00:12:59.740 | you can have a blood test that will detect cancer

00:13:01.680 | 10, 20 years earlier than it would

00:13:03.600 | before it forms a tumor.

00:13:05.360 | You can, of course, do your genome very cheaply

00:13:07.920 | for less than $100 now.

00:13:09.360 | There are bio-wearables already.

00:13:12.320 | I wear this ring from Aura

00:13:14.160 | that I have a number of years of data.

00:13:17.200 | I've been doing blood tests for the last 12 years

00:13:19.240 | with a company called InsideTracker, which I consult for,

00:13:22.600 | and so I have all of that data as well,

00:13:24.200 | and there's 34 different parameters on my testosterone,

00:13:27.720 | my blood glucose, my inflammation,

00:13:30.040 | and I use all that data to, of course,

00:13:32.720 | I wear a watch that measures things as well.

00:13:34.720 | I use that data to keep my body in optimal shape.

00:13:39.280 | So I'm now 51, and according to those parameters,

00:13:42.160 | I'm at least as good as someone in their early 40s,

00:13:45.760 | and if I really work at it,

00:13:47.200 | I can get my biochemistry down to mid-30s,

00:13:52.000 | though I like to now eat a little dessert once in a while.

00:13:56.240 | So that's the future we're in right now.

00:13:58.680 | Anyone can do what I just said,

00:14:00.920 | but in the very near future, just in the next few years,

00:14:04.320 | you can be wearing wearables.

00:14:06.400 | So I'm currently wearing a little,

00:14:08.560 | what's called a bio sticker.

00:14:10.160 | This one I just put on last night.

00:14:14.120 | It's about an inch long, a few millimeters.

00:14:18.640 | - Yeah, for people just listening, it's on David's chest.

00:14:21.680 | It's just the, how does it attach?

00:14:23.200 | It's just kinda--

00:14:24.320 | - It sticks on. - Sticks on.

00:14:25.400 | - Yeah, so on one side, you have an on button that you press.

00:14:27.760 | The lights come on, flashes four times, it's good to go.

00:14:30.520 | It immediately syncs to your phone,

00:14:33.000 | and this one, it's called a bio button, nice name.

00:14:37.280 | And there's another one that I have that I haven't tried yet

00:14:39.480 | that does EKG on your heart.

00:14:41.500 | This is mainly for doctors to monitor patients

00:14:43.360 | that go home after a heart attack or surgery,

00:14:45.640 | but that's medical-grade, FDA-approved device.

00:14:48.960 | So there will be a day, in fact, it's already here,

00:14:51.240 | that doctors are using these to get patients to go home

00:14:55.280 | and save a week in hospital, $2,000 at least

00:14:59.440 | for each patient.

00:15:00.920 | That's massive savings for the hospital.

00:15:04.440 | But ultimately, what I'm excited about is a future

00:15:06.560 | that isn't that far off where everybody,

00:15:10.760 | certainly in developed countries,

00:15:11.760 | eventually these will cost a few cents and rechargeable.

00:15:14.360 | The only cost will be the software subscription

00:15:16.620 | that can be monitored constantly.

00:15:19.240 | And to give you an idea what this is measuring me

00:15:21.020 | at 1,000 times a second is my vibrations as I speak,

00:15:26.020 | my orientation, it already has told me this morning

00:15:29.600 | how I slept, where I slept, what side I slept on.

00:15:33.220 | We've got sneezing, coughing, body temperature, heart rate,

00:15:38.060 | heart, other parameters of the heart

00:15:40.880 | that would indicate heart health.

00:15:42.520 | These data are being used to now to predict sickness.

00:15:49.040 | So eventually we'll have, just in the next year or so,

00:15:53.700 | the ability to predict whether something,

00:15:55.560 | or diagnose whether something is pneumonia

00:15:58.200 | or just a rhinovirus that can be treated or not.

00:16:02.200 | This is really going to not just revolutionize medicine,

00:16:06.400 | but I think extend lives dramatically.

00:16:08.520 | 'Cause if I'm gonna have a heart attack next week,

00:16:11.560 | and that's possible, this device should know that

00:16:14.480 | and I'll be in hospital before I even have it.

00:16:17.000 | Maybe you can talk a little bit about InsideTracker

00:16:19.320 | 'cause I saw that there's some really cool things in there.

00:16:22.220 | (laughs)

00:16:23.060 | Like it actually, so maybe you can talk about,

00:16:26.000 | I guess that you're collecting blood

00:16:28.040 | to give it the data.

00:16:29.280 | So, and it has like basic recommendations

00:16:32.520 | on how to improve your life.

00:16:34.200 | So we're not just talking about diseases, right?

00:16:36.560 | Like anticipating having a particular disease,

00:16:39.080 | but it's almost like guiding your trajectory to life,

00:16:41.880 | how to, whether it's extend your life

00:16:44.600 | or just live a more fulfilling,

00:16:46.680 | like improve the quality of life,

00:16:48.200 | I suppose this is the right way to say it.

00:16:50.280 | What, how does InsideTracker work?

00:16:52.480 | What the heck is it?

00:16:53.320 | 'Cause I saw that there was also pretty cool.

00:16:55.120 | - Yeah. - What is it?

00:16:55.960 | I guess it's something other people can use.

00:16:58.000 | - You can definitely use it.

00:16:59.720 | You can sign up, it's consumer.

00:17:02.080 | - It's like a company, consumer facing company?

00:17:04.480 | - It is, yeah. - Okay, cool.

00:17:06.080 | - And I also want to democratize the ability

00:17:09.000 | to just take a mouth swab eventually.

00:17:11.040 | We don't need to have a blood test necessarily,

00:17:13.600 | but for now it's a blood test

00:17:15.080 | and you'd go to a lab core request in the US.

00:17:18.420 | It's also available overseas.

00:17:19.880 | You can upload your own data for minimal cost

00:17:22.560 | and get the algorithms, the AI in the background

00:17:26.600 | to take that data, plot where you are against others

00:17:30.160 | in your age group, in terms of health and longevity,

00:17:33.600 | bio age they call it, no, inner age.

00:17:36.040 | But also it provides recommendations.

00:17:38.160 | And this isn't just a bunch of BS.

00:17:39.680 | It sounds like it might be to say,

00:17:41.640 | "Oh, go eat this or go to that restaurant and order that."

00:17:44.400 | But it's actually based on,

00:17:46.440 | they basically, this company has entered hundreds,

00:17:49.840 | now it would be thousands of scientific papers

00:17:51.800 | into their database,

00:17:53.200 | and hundreds of thousands of human data points.

00:17:55.760 | And they have tens of thousands of individuals

00:17:59.080 | that have been tracked over time.

00:18:00.400 | And anonymously, that data is used to say

00:18:02.960 | what works and what doesn't.

00:18:04.280 | If you eat that, what works?

00:18:05.760 | If you take that supplement, what works?

00:18:07.640 | And I was a co-author on a paper that showed

00:18:09.640 | that the recommendations for food and supplements

00:18:13.440 | was better than the leading drug for type two diabetes.

00:18:18.080 | - That's so cool.

00:18:19.800 | The idea that you can connect,

00:18:21.680 | like skipping the human having to do this work,

00:18:24.920 | you can connect the scientific papers,

00:18:27.400 | almost like meta-analysis of the science

00:18:30.120 | connected to the individual data.

00:18:32.520 | And then based on that, connect your data

00:18:35.440 | to whatever the proper group is

00:18:37.920 | within whatever the scientific paper is

00:18:40.480 | to make the suggestion of how that work applies to your life.

00:18:45.480 | And then that ultimately maps to a recommendation

00:18:49.680 | of what you should do with your life.

00:18:52.280 | Like this giant system that ultimately recommends

00:18:55.760 | you should drink more coffee or less.

00:18:58.480 | - Right, and we'll have the genome in there as well.

00:19:00.320 | You can upload that.

00:19:02.000 | And so these programs will know us way better

00:19:04.680 | than we do and our doctors as well.

00:19:07.520 | The idea of going to a doctor once a year

00:19:09.000 | for an annual checkup and having males

00:19:11.520 | get a finger up their butt and you cough,

00:19:14.680 | that to me is a joke.

00:19:16.040 | That's medieval medicine.

00:19:18.160 | And that's very soon going to be seen as medieval.

00:19:21.480 | - Yeah, to me as a computer science person,

00:19:25.960 | it's always upsetting to go to the doctor

00:19:28.640 | and just look at him and realize you know nothing about me.

00:19:32.540 | You're making your opinions based on,

00:19:37.840 | it is very valuable, years of intuition building

00:19:42.520 | about basic symptoms, but you're just like, it is medieval.

00:19:45.880 | They're very good at it.

00:19:47.200 | In fact, doctors in medieval times

00:19:49.600 | were probably damn good at working with very little.

00:19:53.600 | But the thing is, I'd rather prefer a doctor

00:19:58.520 | that doesn't really know what they're doing

00:20:00.060 | but has a huge amount of data to work with.

00:20:03.060 | - Well, you're right.

00:20:03.900 | And many of my good friends are doctors.

00:20:05.600 | I work at Harvard.

00:20:06.520 | So I'm not against the profession at all.

00:20:09.640 | But I think that they need just as much help

00:20:11.680 | as anyone else does.

00:20:13.480 | We wouldn't drive a car without a dashboard.

00:20:15.300 | We wouldn't think of it.

00:20:16.140 | So why would doctors do the same?

00:20:18.720 | If we could, can we step back to the big,

00:20:21.400 | profound, philosophical, both tragic

00:20:23.680 | and beautiful question about age?

00:20:25.500 | How and why do we age?

00:20:28.720 | Is it, from an engineering perspective,

00:20:31.520 | you said you like the biological machine.

00:20:33.720 | Is that a feature or a bug of the biological machine?

00:20:37.760 | - It is both a bug and a feature.

00:20:40.740 | Evolutionary speaking, we only live as long as we need to

00:20:44.640 | to replace ourselves efficiently.

00:20:47.360 | If you're a mouse, you're only gonna live

00:20:49.120 | two and a half years, three years.

00:20:50.600 | You're probably gonna die of starvation, predation,

00:20:52.460 | freezing in the winter.

00:20:54.440 | So they divert most of their resources

00:20:57.120 | to reproducing rapidly,

00:20:59.320 | but they don't put a lot of energy

00:21:00.960 | into preserving their soma, which is their body.

00:21:04.320 | Conversely, a baleen type of whale, a bowhead whale

00:21:07.400 | in particular, will live hundreds of years

00:21:09.320 | because they're at the top of the food chain

00:21:11.080 | and they can live as long as they want.

00:21:12.640 | So they breed slowly and build a body that lasts.

00:21:15.140 | We're somewhere in between

00:21:16.660 | because we've really only just come out of the savannas

00:21:19.680 | where we could be picked off by a cat.

00:21:22.080 | We were pretty wimpy going back 6 million years ago.

00:21:25.400 | So we actually need to evolve quicker than evolution will.

00:21:30.080 | And that's why we can use our oversized brains

00:21:33.560 | and intuition to give us what evolution

00:21:36.140 | not only didn't give us, but took away from us.

00:21:38.280 | Now we're pathetic.

00:21:39.320 | Look at our bodies.

00:21:40.680 | These arms, if any of us,

00:21:42.140 | even the strongest person in the world

00:21:43.260 | went in a cage with a chimpanzee,

00:21:45.000 | the chimp could knock that person's head off.

00:21:46.400 | No question.

00:21:47.400 | So we're pathetic.

00:21:48.240 | So we need to engineer ourselves

00:21:49.440 | to be healthier and longer lived.

00:21:51.580 | So getting to aging, we can do better.

00:21:55.680 | Whales do way better.

00:21:57.260 | We're trying to learn how whales do that.

00:21:59.520 | And if you ask really anybody in the field now,

00:22:02.840 | professor, they'll say there are eight or nine

00:22:06.320 | hallmarks of aging, which are really,

00:22:08.120 | it's a word for causes of aging.

00:22:11.520 | So you probably have heard of some of these.

00:22:13.500 | Your listeners will have loss of telomeres,

00:22:16.580 | the ends of the chromosomes,

00:22:17.740 | like the little ends of shoelaces, that kind of thing.

00:22:21.860 | They get too short, cells stop dividing,

00:22:23.540 | become senescent.

00:22:24.860 | They put out what are called mitogens

00:22:28.580 | that cause cancer and inflammatory molecules.

00:22:31.020 | So that's another aspect of aging, cellular senescence.

00:22:34.260 | Another one is loss of the energetics.

00:22:35.900 | So mitochondria, the battery packs, wind down.

00:22:38.680 | There's a whole bunch, stem cells, proteostasis.

00:22:43.060 | Well, these are our Achilles heels that I'm talking about

00:22:45.420 | that are common amongst all life forms, really.

00:22:48.380 | But if you want me to jump to the chasers to where,

00:22:51.640 | what is the upstream defining factor?

00:22:54.400 | If we boil it down, what do we get?

00:22:57.300 | So most biologists would say you can't boil it down.

00:22:59.700 | It's too complex.

00:23:01.200 | I would say you can boil it down to an equation,

00:23:03.660 | which is the preservation of information

00:23:05.860 | and loss due to entropy, i.e. noise.

00:23:08.820 | And that is the basis of my research.

00:23:12.380 | It originally came out of discoveries in yeast cells

00:23:14.820 | where I went to MIT in the 1990s.

00:23:17.260 | - You studied bread.

00:23:18.780 | - I kind of did.

00:23:20.220 | I studied the makers of bread,

00:23:22.980 | a little yeast called Saccharomyces cerevisiae,

00:23:25.460 | which at the time was one of the hottest,

00:23:28.060 | excuse the pun, organisms to work on.

00:23:30.920 | But we figured out in the lab why yeast cells get old

00:23:35.300 | and found genes that control that process

00:23:37.460 | and made them live longer,

00:23:38.980 | which was an amazing four years of my life.

00:23:42.340 | One of those genes had a name with an acronym SIR2.

00:23:46.740 | Now the two is irrelevant.

00:23:49.700 | The SIR is important.

00:23:51.820 | And the most important letter out of all of those three

00:23:53.960 | is I, which stands for information.

00:23:57.020 | Silent information regulator number two,

00:23:59.660 | when you put more copies of that gene in,

00:24:01.140 | just put in one more copy,

00:24:02.800 | the yeast cells live 30% longer

00:24:04.740 | and suppress the cause of aging,

00:24:06.100 | which was the dysregulation of information in the cell.

00:24:09.020 | And then, so fast forward to now,

00:24:11.660 | I've been looking in humans and mice,

00:24:14.620 | 'cause they live shorter and cheaper to study,

00:24:17.780 | where the loss of information in our bodies

00:24:20.780 | is a root cause of aging.

00:24:22.580 | And I think it is.

00:24:24.060 | - Your boldness in viewing biology in this way

00:24:28.060 | is fascinating because that also leads to a kind of,

00:24:34.500 | it's almost like allows for a theory of aging,

00:24:39.500 | like you could boil it down to a single equation

00:24:43.060 | and it leads to perhaps a metric

00:24:45.920 | that allows you to optimize aging,

00:24:48.620 | sort of in the fight against entropy.

00:24:50.660 | To figure out which mechanisms, like you said,

00:24:53.820 | the silent information regulator,

00:24:55.700 | which mechanisms allow you to preserve information

00:24:58.540 | without injecting noise, without creating entropy,

00:25:03.700 | without creating degradation of that information.

00:25:06.980 | For some reason, converting biology,

00:25:11.140 | which I thought was mostly impossible,

00:25:13.500 | into an engineering problem,

00:25:15.660 | feels like it makes it amenable to optimization,

00:25:19.380 | to solving problems, to creating technology that can,

00:25:23.420 | whether that's genetic engineering or AI,

00:25:26.660 | it makes it possible to create the technology

00:25:30.920 | that would improve the degradation of information and aging.

00:25:35.920 | Is there more concrete ways you think about

00:25:38.500 | the kind of information you want to preserve?

00:25:41.460 | And also, is there good ideas about regulators

00:25:46.140 | of that information, about ways to prevent the distortion,

00:25:51.140 | the degradation of that information?

00:25:54.020 | - Right, so we have silent information regulator genes

00:25:56.580 | in our bodies, we have seven of them.

00:25:58.820 | SIRT1 through seven, they're called.

00:26:00.380 | And we found in mice,

00:26:02.340 | one way to slow down the loss of information

00:26:04.020 | is to just give more of these, to upregulate these genes.

00:26:08.420 | So we made a mouse that has more of this SIRT1 gene,

00:26:11.980 | turned it on, and that slowed down the aging of the brain

00:26:15.140 | and preserved their information.

00:26:16.500 | Now, what information am I talking about, you might ask?

00:26:19.440 | Well, again, you can simplify biology.

00:26:21.980 | There are two types of information in the cell, primarily.

00:26:25.100 | The one we all read about and know about

00:26:27.180 | is the DNA, the genome.

00:26:29.020 | And that's base four information, ATCG,

00:26:32.460 | the four chemicals that make up the various sequences

00:26:35.260 | of the genome, billions of letters.

00:26:37.020 | And that also degrades over time.

00:26:39.980 | But what's been fascinating is that we find

00:26:42.620 | that that information is pretty much intact

00:26:45.140 | in old animals and people.

00:26:47.300 | You can clone a dog, one of my friends in LA

00:26:49.100 | just cloned his dog three times.

00:26:50.980 | So this is doable, right?

00:26:52.060 | That means that the genome can be intact.

00:26:53.780 | But what's the other type of information?

00:26:56.220 | It's the epigenome,

00:26:57.460 | the regulators of the genetic information.

00:27:01.220 | And physically, that's really just how the DNA is wrapped up

00:27:04.380 | or looped out for the cell to access it and read it.

00:27:08.060 | So it's similar to, and excuse this analogy,

00:27:11.220 | but it's a good one, a compact disc or DVD.

00:27:15.180 | Those pits in the foil are the digital information,

00:27:18.500 | that's the genome.

00:27:19.540 | And the epigenome is the reader of that information.

00:27:22.260 | And in a different cell, you'd read different music,

00:27:25.300 | different songs, different symphonies.

00:27:28.020 | And that's what gets laid down when we're in the womb.

00:27:31.620 | And that makes a skin cell forever a skin cell

00:27:34.620 | and not a brain cell tomorrow.

00:27:36.340 | Thank God, otherwise our brains wouldn't work very well.

00:27:38.740 | But over time, what we see is that the brain cells

00:27:41.220 | start to look more like skin cells.

00:27:42.860 | And the kidney cells start to look more like liver cells.

00:27:45.620 | And they, what we call X differentiate,

00:27:48.100 | this is a term that we use in my lab

00:27:49.420 | but isn't yet widely used.

00:27:52.080 | But we needed a term to explain this.

00:27:53.420 | And that process of X differentiation,

00:27:55.820 | the loss of the reader of the CD or the DVD,

00:28:00.820 | we liken that to scratches on the DVD

00:28:06.140 | so that the reader cannot fully access the information.

00:28:09.420 | Now we can slow down the scratches, as I mentioned.

00:28:11.460 | We can turn on these genes.

00:28:13.140 | We can even put in molecules into the cell

00:28:15.860 | or even eat them and turn on those pathways,

00:28:18.980 | which my father and I have been trying to do

00:28:21.520 | for about a decade to slow things down.

00:28:24.400 | But the question that I've had is,

00:28:26.380 | is there a repository of information still in the body?

00:28:30.820 | Because anyone who knows anything

00:28:32.220 | about the loss of information

00:28:33.400 | or even has tried to copy a cassette tape

00:28:35.540 | or photocopy or Xerox anything

00:28:37.580 | knows that over time you lose that information irreparably.

00:28:41.780 | So I've been looking for a backup copy

00:28:43.940 | inspired largely by Claude Shannon's work

00:28:46.700 | at MIT as well in the 1940s.

00:28:49.660 | His mathematical theory of communication is just brilliant.

00:28:53.040 | And so I've been looking for what he called the observer,

00:28:55.480 | which is the backup copy.

00:28:57.200 | We today might call that the TCP/IP protocol of the internet

00:29:01.500 | that stores information in case it doesn't make it

00:29:04.000 | to your computer, it will fill in the gaps.

00:29:06.920 | And we've been spending about the last five years

00:29:09.360 | to try and find if there really is a backup copy in the body

00:29:12.160 | to reset the epigenome and polish those scratches away.

00:29:15.960 | - That's incredible.

00:29:16.960 | So finding the backup,

00:29:18.520 | so whenever there are too many scratches pile up,

00:29:21.400 | you can just write a new version.

00:29:24.520 | Like write, not a new version,

00:29:26.540 | but go to the backup and restore it.

00:29:29.120 | - Right, that's really all we're talking about.

00:29:31.680 | It's not that hard once you know the trick.

00:29:34.440 | - And for people that actually remember

00:29:36.720 | like DVDs and scratches on them, how frustrating it is,

00:29:41.280 | that's a brilliant metaphor for aging.

00:29:45.800 | And then the reader is the thing that skips

00:29:50.800 | and then it could destroy your experience,

00:29:53.400 | the richness of the experience

00:29:54.800 | that is listening to your favorite song.

00:29:57.140 | - Right, but in biology, it's even worse

00:29:59.000 | 'cause you'll lose your memory, your kidneys will fail,

00:30:01.120 | you'll get diabetes, your heart will fail.

00:30:03.640 | And we call that aging and age-related diseases.

00:30:06.880 | So most people forget that diseases that we get

00:30:10.040 | when we get old are 80 to 90% caused by aging.

00:30:13.860 | And we've been trying to fix things with Band-Aids

00:30:15.960 | after they occur without even generally talking

00:30:19.040 | about the root cause of the problem.

00:30:21.360 | - Is there the scratches, do those come from,

00:30:26.240 | are those programmed or are they failures?

00:30:31.900 | Meaning is it, so if it's by design,

00:30:36.440 | then there's like a encoded timeline schedule

00:30:40.960 | that the body's just on purpose

00:30:43.000 | of degrading the whole thing.

00:30:44.560 | And then there's the just the wear and tear

00:30:47.080 | of like the scratches and a disc that happen through time.

00:30:50.160 | Which one is it that's the source of aging?

00:30:52.760 | - It's more akin to wear and tear, there isn't a program.

00:30:56.920 | Getting back to evolution, there's no selection for aging.

00:31:00.960 | We're not designed to age, we just live as long as we need to

00:31:03.800 | and then we're at the whim of entropy basically.

00:31:06.140 | Second law of thermodynamics, stuff falls apart.

00:31:09.120 | We live a bit longer than age 40

00:31:11.200 | only because there are robust resilient systems

00:31:13.400 | but eventually they fail as well.

00:31:15.320 | Current limit to the human lifespan

00:31:16.940 | where they completely fail is 122.

00:31:19.300 | But I don't like to think of it as wear and tear

00:31:23.240 | because there's two aspects to it.

00:31:25.880 | There's a system that's built to keep us alive

00:31:28.080 | when we're young but actually goes,

00:31:30.960 | comes back to bite us as we get older.

00:31:33.280 | And we call this issue antagonistic pleiotropy.

00:31:37.800 | What's good for you when you're young

00:31:39.480 | can cause problems when you're older.

00:31:42.920 | So we've been looking what is the cause of,

00:31:44.640 | the main causes of the noise

00:31:46.140 | and we've found two of them definitively.

00:31:49.320 | The first one is broken chromosomes.

00:31:52.000 | When a chromosome breaks, the cell has to panic

00:31:55.000 | because that's either gonna cause a cancer or kill the cell.

00:31:58.280 | There's only two outcomes, it's pretty much a problem.

00:32:01.200 | And so what the cell does is it reorganizes the epigenome

00:32:05.080 | in a massive way.

00:32:07.360 | What that leads to is,

00:32:09.160 | think of it as a tennis match or a ping pong game.

00:32:12.600 | The proteins are the balls

00:32:14.120 | and they now leave where they should be,

00:32:15.920 | which is regulating the genes that make the cell type,

00:32:19.120 | whatever it is.

00:32:20.040 | And they have a dual function,

00:32:21.600 | they actually go to the break,

00:32:23.080 | the chromosome will break and fix that.

00:32:25.620 | And then they come back.

00:32:26.820 | You might ask, well, why is it set up that way?

00:32:29.320 | Well, it's a beautiful system,

00:32:30.320 | it coordinates gene expression,

00:32:31.840 | the control systems with the repair.

00:32:33.780 | You want them coordinated.

00:32:35.960 | Problem is as we get older,

00:32:37.560 | this ping pong game, some of the balls get lost.

00:32:39.500 | They don't come back to where they originally started.

00:32:42.600 | And that's what we think is the main noise for aging.

00:32:46.960 | And we've also, the other cause of aging that we found

00:32:49.440 | is cell stress, we damage nerves and they age rapidly.

00:32:52.920 | So that's the other issue.

00:32:54.640 | There's probably others.

00:32:55.840 | Smoking chemicals, for example,

00:32:58.220 | we know accelerates biological age pretty dramatically.

00:33:00.960 | But the question is, can you slow that down

00:33:04.160 | or can you reset them to get those ping pong balls

00:33:06.200 | to go back to where they originally started in the game?

00:33:09.680 | And we think we've found a way to do that.

00:33:12.040 | - What, can you give me hints?

00:33:13.920 | Whose fault is it, and the ball's not coming back,

00:33:15.960 | is it the proteins themselves?

00:33:17.720 | Like, are they starting?

00:33:20.120 | Again, I've been obsessed with the protein folding problem

00:33:22.280 | from the AI perspective.

00:33:23.240 | So is it the proteins or is it something else?

00:33:25.680 | - Well, we know who hits the balls and recruits them.

00:33:29.280 | So that the break is recognized by proteins

00:33:33.080 | who send out a signal through phosphorylation

00:33:37.040 | is typical way cells talk to other proteins.

00:33:40.960 | And that recruits those repair factors,

00:33:43.540 | those ping pong balls to the break.

00:33:45.080 | So the cell's actively doing this to try and help itself.

00:33:49.120 | But we don't know who's to blame for them not coming back.

00:33:53.920 | That could just be a flaw in the quote unquote design.

00:33:58.480 | I don't think that there's something saying,

00:34:00.280 | well, 1% of you balls, proteins never go back.

00:34:04.200 | I just think it's hard to reset a system

00:34:06.120 | that's constantly changing.

00:34:07.680 | We have in our bodies close to a trillion DNA breaks

00:34:11.340 | every day, and imagine that over 80 years,

00:34:14.280 | what damage that does to our epigenomic information.

00:34:17.520 | Now we know that this is, well,

00:34:20.280 | we never know anything in biology,

00:34:21.540 | but we have strong evidence that this is true

00:34:23.960 | because we can mess with animals,

00:34:27.580 | we can create DNA breaks and tickle them

00:34:30.060 | with a few breaks, maybe raise it by threefold

00:34:32.940 | over background levels of normal breakage.

00:34:35.800 | And if we're right, those mice should get old.

00:34:38.320 | And they do.

00:34:40.380 | We can actually, we've created these breaks

00:34:42.420 | in a way that's titratable.

00:34:44.000 | We can, it's like a rheostat, we can send it to 11.

00:34:46.680 | I drove my Tesla here, I'm a big fan of Spinal Tap 2,

00:34:51.360 | going to 11.

00:34:52.200 | If we go to 11, we can make a mouse old

00:34:54.200 | in a matter of months.

00:34:55.740 | We prefer to go to a level of about four,

00:34:58.600 | and it gets old in 10 months.

00:35:00.180 | But it's definitely old.

00:35:01.160 | It's got all of the hallmarks of aging,

00:35:03.700 | it's got diseases, it looks old,

00:35:06.020 | its skin is old, it's got gray hair.

00:35:08.020 | But importantly, we can now measure age

00:35:09.980 | by looking at the scratches.

00:35:11.400 | We can look at the epigenome, we can measure it,

00:35:13.420 | and use machine learning to give us a number,

00:35:15.780 | and those mice are 50% older than normal.

00:35:19.140 | - So you can replicate the aging process

00:35:20.700 | in a controlled way.

00:35:21.860 | You can, I mean, in a way that you,

00:35:24.060 | I mean, you could accelerate it,

00:35:27.680 | in a controlled way, and measure how much exactly it's aging,

00:35:31.680 | and that gives you step one of a two-step process

00:35:34.960 | to when you can then figure out,

00:35:36.320 | well, how can we reverse this?

00:35:37.960 | - And now we're reversing those mice.

00:35:40.160 | - Is there a good, I love what you said.

00:35:42.520 | I mean, in biology, you really don't know.

00:35:44.620 | It's such a beautiful mess.

00:35:47.640 | Is there ideas how to do that?

00:35:51.480 | Is that on a genetic engineering level?

00:35:55.000 | Is it, like, what can you mess with?

00:35:57.580 | Is it going to the, trying to discover the backup copies,

00:36:02.280 | and restoring from them?

00:36:04.180 | Like, what's, if it's possible to convert it

00:36:06.380 | to natural language words, what are the ideas here?

00:36:09.480 | - What is the observer, and how do we contact it?

00:36:11.460 | - Exactly, what's the observer, and how do you contact it?

00:36:14.300 | Or if there's other ideas,

00:36:15.860 | how to reverse the balls-getting-lost process.

00:36:20.580 | - Yeah, well, you can slow it down.

00:36:22.860 | - Slow it.

00:36:23.700 | But we found a reset switch recently.

00:36:26.260 | We just published this in the December 2020 issue of Nature.

00:36:31.260 | And what we found is that there are three embryonic genes

00:36:36.900 | that we could put into the adult animal

00:36:39.800 | to reset the age of the tissues.

00:36:42.040 | And it only takes four to eight weeks to work well.

00:36:44.700 | And we can take a blind mouse

00:36:46.060 | that's lost its vision due to aging,

00:36:48.340 | neurons aren't working well towards the brain,

00:36:50.460 | reset those neurons back to a younger age,

00:36:52.660 | and now the mice can see again.

00:36:54.220 | These three genes are famous, actually,

00:36:57.220 | because they're a set of four genes

00:36:59.460 | discovered by Shinya Yamanaka,

00:37:01.700 | who won the Nobel Prize in 2016,

00:37:04.020 | for discovering that those four genes,

00:37:05.900 | when turned on at high levels in adult cells,

00:37:09.620 | can generate stem cells.

00:37:11.880 | And this is, I think, well-known now

00:37:14.060 | that we can create stem cells from adult tissue.

00:37:16.900 | But what wasn't known is, can you partially take age back

00:37:19.460 | without becoming a tumor,

00:37:20.820 | or generating a stem cell in the eye,

00:37:22.540 | which would be a disaster?

00:37:24.100 | And the answer is yes.

00:37:24.940 | There is a system in the body

00:37:26.620 | that can take the age of a cell back to a certain point,

00:37:29.060 | but no further, safely, and reset the age.

00:37:32.300 | And we're now using that to reset the age of the brain

00:37:36.580 | of those mice that we aged prematurely,

00:37:39.340 | and they're getting their ability to learn back.

00:37:42.540 | - This is really exciting, right?

00:37:44.300 | Like, what's the downside of this?

00:37:46.860 | - Well, the downside is if you overdo it,

00:37:49.100 | and you don't get it right, you might cause tumors.

00:37:53.020 | But we do it very carefully,

00:37:54.940 | and we also know that in the eye, it's very safe.

00:37:57.900 | We also injected these, we deliver them by viruses,

00:38:01.620 | so we can control where and when they get turned on.

00:38:06.040 | And in this paper, we've published that

00:38:08.540 | if we put high levels in the mouse,

00:38:10.540 | into their veins, throughout the body,

00:38:12.380 | they don't get cancer for over a year.

00:38:14.720 | So I'm so optimistic that we're going into human studies

00:38:18.620 | in less than two years from now.

00:38:20.420 | - Is there a place where AI can help?

00:38:23.980 | Sorry to inject one of the things

00:38:27.700 | I'm very excited about and passionate about.

00:38:30.220 | So Google DeepMind recently had a big breakthrough

00:38:35.060 | with AlphaFold2, but also AlphaFold two years ago,

00:38:39.100 | with achieving sort of state-of-the-art performance

00:38:44.100 | on the protein folding problem, single protein folding.

00:38:49.260 | But it also paints a hopeful picture

00:38:52.300 | of what's possible to do in terms of simulating

00:38:54.940 | the folding of proteins,

00:38:56.100 | but also simulating biological systems through AI.

00:39:00.740 | Is there something to you, combined with this brilliant work

00:39:04.900 | on the biology side that you're hopeful about,

00:39:07.940 | where AI can be a tool to help?

00:39:10.300 | - Where isn't that a tool?

00:39:11.580 | I mean, if you're not using AI right now in biology,

00:39:13.540 | you're getting left behind.

00:39:14.700 | We use it all the time.

00:39:15.580 | We're using it to generate these biological clocks

00:39:18.620 | to be able to read those scratches.

00:39:21.220 | We're using it to predict the folding of proteins

00:39:24.020 | so we can target molecules and modulate their activity.

00:39:27.500 | We're using it to assemble genomes of different species.

00:39:30.620 | What else?

00:39:32.460 | We use it to predict the longevity of a mouse

00:39:35.900 | based on how it reacts to certain things,

00:39:38.660 | hearing, eyesight, generally frailty.

00:39:41.140 | So we just put out a paper last year on that.

00:39:43.740 | The other thing we can use it for,

00:39:46.940 | which is a little off the track here,

00:39:49.140 | but we use it for predicting

00:39:51.340 | which microorganisms are in your body.

00:39:53.300 | Actually, not predicting, telling you.

00:39:55.700 | So our daughter, Natalie,

00:39:58.420 | was infected with Lyme disease a few years ago,

00:40:00.940 | almost went blind from it.

00:40:02.440 | And the test took four days.

00:40:03.780 | And I thought, just give me the DNA from her spinal fluid.

00:40:06.940 | I'll go tell you what's in it,

00:40:07.920 | if it's Lyme disease or not.

00:40:09.380 | They refused.

00:40:10.220 | And so at that point I said, this has to be done better.

00:40:12.620 | So I've started a company that now can take a sample

00:40:15.740 | of any part of your body.

00:40:17.300 | It's typically done now with liver transplant patients

00:40:21.660 | to detect viruses that come out of their organs.

00:40:24.920 | But that's another area that AI is extremely important for.

00:40:28.420 | I think if you're not, in five years,

00:40:31.500 | if you're not using deep learning, you've got a problem.

00:40:35.380 | Because the amount of data that we generate now

00:40:36.940 | as biologists is just terabytes.

00:40:39.460 | It can be terabytes per week,

00:40:40.460 | it'll eventually be terabytes per day.

00:40:42.300 | And then we just go from there.

00:40:43.940 | And I actually have trouble recruiting enough

00:40:46.340 | bioinformaticians.

00:40:47.680 | A lot of our work is now just number crunching.

00:40:51.380 | - A part of that is collecting the data,

00:40:55.140 | which is kind of something we've talked a little bit about.

00:40:57.580 | But is there something you can say about how we can collect

00:41:02.480 | more and more data?

00:41:04.460 | Not just on the one person level,

00:41:07.580 | like for you to understand your various markers,

00:41:13.220 | but to create huge datasets,

00:41:16.620 | to understand how we can detect certain pathogens,

00:41:20.460 | detect certain properties, characteristics of,

00:41:23.120 | whether it's aging or all the other ways

00:41:25.580 | that a human body can fail.

00:41:27.300 | It seems like with biology,

00:41:29.740 | there's a kind of privacy concerns that,

00:41:33.420 | well, actually not privacy concerns,

00:41:34.940 | it's almost like regulation that kind of prevents

00:41:38.220 | like hospitals from sharing data.

00:41:42.820 | I'm not sure exactly how to say it,

00:41:44.500 | but it seems like when you look at autonomous vehicles,

00:41:48.280 | people are much more willing to share data.

00:41:50.220 | When you look at human biology system,

00:41:52.580 | people are much less willing to share data.

00:41:54.380 | Is there a hopeful path forward where we can share

00:41:57.940 | more and more data at a large scale

00:42:00.240 | that ultimately ends up helping us understand

00:42:03.060 | the human body and then treat problems with the human body?

00:42:06.780 | - So we are right in the middle.

00:42:08.300 | We're living through what's going to be seen

00:42:10.140 | as one of the biggest revolutions in human health,

00:42:12.640 | through the gathering of data about our bodies.

00:42:16.380 | And 20 years ago, people didn't want to go on social media,

00:42:19.500 | they're worried about it.

00:42:20.340 | Now you have to, if you're a kid, that's for sure.

00:42:22.720 | Same with medical records.

00:42:25.500 | These are becoming all digitized and expanded.

00:42:29.420 | Ultimately, we're going to,

00:42:31.300 | even if we don't want to, have to be monitored.

00:42:34.780 | There's going to be a court case that,

00:42:36.700 | I bet two, three years from now, someone's going to say,

00:42:39.780 | how come my father died from a heart attack?

00:42:42.380 | You had these biosensors, 20 bucks, and you didn't use it.

00:42:45.740 | Lawsuit right there, and suddenly,

00:42:47.460 | all hospitals have to give you one of these.

00:42:49.500 | - There'll be a reversal, like to where,

00:42:51.800 | it's your fault if you don't collect the data,

00:42:54.780 | that's brilliant, and that's absolutely right.

00:42:58.140 | I mean, that's absolutely right.

00:43:00.800 | That's the frustration I feel in going to the doctor,

00:43:03.860 | is like, it's almost negligent to not collect the data,

00:43:10.580 | because you're making,

00:43:11.900 | there's something really wrong with me,

00:43:14.020 | and you're making decisions based on very few tests.

00:43:17.920 | That's almost negligent, when you have the opportunity

00:43:20.140 | to collect a huge amount more data.

00:43:22.000 | - Well, let me tell you something, Lex.

00:43:24.000 | I've got this inside tracker data for myself over a decade,

00:43:29.060 | and you'd think my doctor would roll his eyes at this.

00:43:31.820 | Oh, he's gone to a consumer company, blah, blah, blah.

00:43:34.780 | I had my first checkup in a year with him

00:43:37.420 | through video conference,

00:43:39.120 | and he was running blind.

00:43:42.680 | He really didn't know what was going on with me.

00:43:45.380 | He asked the usual things, how am I sleeping,

00:43:47.180 | how am I eating, these kind of usual things.

00:43:50.060 | And I said, well, I've got new tests back

00:43:52.340 | from inside tracker, and he said, great,

00:43:54.420 | I'd love to see them.

00:43:55.900 | So I share screen, and we look at the graphs,

00:43:58.120 | look at the data, and he's loving it,

00:44:00.860 | 'cause he cannot order these tests willy-nilly.

00:44:04.500 | So I said, well, let's order a HbA1c blood glucose levels,

00:44:08.980 | because I'm very interested in that.

00:44:10.140 | That tracks with longevity.

00:44:11.400 | And he said, well, I have no reason to order that.

00:44:13.940 | Do you have a family history?

00:44:15.500 | No.

00:44:16.340 | Do you have any symptoms of diabetes?

00:44:18.860 | No, well, I can't order the test.

00:44:20.660 | I almost wanted to reach through the computer

00:44:22.180 | and strangle him, but instead, I pay a little bit

00:44:25.980 | to get these tests done, and then he looks at them.

00:44:28.300 | So that's now the way consumer health is going,

00:44:30.600 | is that you can get better data than your doctor can,

00:44:32.820 | but they like you to do that.

00:44:34.500 | - Quick human question, maybe you can educate me.

00:44:38.320 | I think doctors sometimes have a bit of an ego.

00:44:42.420 | I understand that the doctor's super experienced

00:44:44.700 | with a lot of things, but this is a fundamental question

00:44:47.620 | of human variability.

00:44:49.260 | Like, I know a lot of specific details about,

00:44:51.580 | I mean, it depends, of course, what we're talking about,

00:44:54.660 | but I bring a lot of knowledge, and if I have data with me,

00:44:58.460 | then I have several orders of magnitude more knowledge.

00:45:02.980 | And I think there's an aspect to it

00:45:04.780 | where the doctor has to put their expert hat,

00:45:09.720 | like, take it off, and actually be a curious,

00:45:13.240 | open-minded person, and study, and look at that data.

00:45:16.540 | Do you think it's possible to sort of change the culture

00:45:20.000 | of the medical system to where the doctors are almost,

00:45:22.800 | as you said, are excited to see the data?

00:45:25.700 | Or is that already happening?

00:45:26.840 | - It's really happening.

00:45:27.680 | Now, we've probably lost the last generation.

00:45:30.640 | There are no hopers, but, so I teach

00:45:33.080 | at Harvard Medical School, and they're excited about this.

00:45:35.960 | They're excited about aging,

00:45:37.120 | which is a new aspect to medicine.

00:45:39.560 | Oh, wow, we can do something about that?

00:45:41.640 | And then, yeah, all this data, what do we do with it?

00:45:43.880 | There's still the traditional pathology

00:45:45.320 | and all that stuff, which they need to know.

00:45:47.180 | But time will change their mindset.

00:45:52.020 | I'm not worried about that.

00:45:54.360 | And like we were discussing, this isn't a question of if,

00:45:57.380 | it's just a matter of when.

00:45:59.020 | And it's, you know, I have a front row seat on all of this.

00:46:02.320 | I had breakfast with a CEO

00:46:04.520 | who is making this happen just yesterday.

00:46:08.300 | I can tell you for sure that most people have no idea

00:46:12.760 | that this revolution is occurring

00:46:14.620 | and is happening so quickly.

00:46:16.120 | If you're running a hospital

00:46:18.360 | and you can save $2,000 per cardiac patient,

00:46:21.360 | what are you going to do?

00:46:22.400 | You have to use it.

00:46:23.380 | Otherwise, you know, the hospital down the road

00:46:25.640 | is going to be beating you.

00:46:28.160 | And there are large hospital aggregations.

00:46:30.880 | So there's Ascension and others

00:46:32.920 | that just have to go this way for budgetary reasons.

00:46:37.560 | And right now the US spends, what is it,

00:46:39.800 | 17% of their GDP on healthcare.

00:46:42.460 | Let's say one of these buttons on my chest costs 20 bucks,

00:46:45.920 | it's rechargeable, and it can predict people's health

00:46:48.600 | and save on antibiotics, prevent heart attacks.

00:46:51.960 | How many billions, if not trillions of dollars

00:46:54.920 | will that save over the next decade?

00:46:57.240 | - Yeah, so when the public wakes up to this,

00:47:00.240 | they'll almost demand it.

00:47:01.480 | Like this should be accepted everywhere,

00:47:04.040 | this is obvious, it's going to save a lot of money,

00:47:06.000 | it's going to improve the quality of life.

00:47:07.640 | - Well, and the CFOs of hospital groups will have to.

00:47:11.480 | And insurance companies are going to want to get in on this.

00:47:15.720 | So now that gets to privacy, right?

00:47:17.600 | Should an insurance company have access to your data?

00:47:20.440 | I would say no, but you could voluntarily show them

00:47:23.320 | some of it if they give you a discount.

00:47:25.480 | And that's also being worked on right now.

00:47:28.980 | - I hope that we do create kind of systems

00:47:30.920 | where I can volunteer to share my data,

00:47:33.160 | and I can also take the data back,

00:47:35.800 | meaning like delete the data, request deletion of data.

00:47:39.040 | And then maybe policy creates rules

00:47:41.440 | to where you can share data, you could delete the data.

00:47:45.120 | And I think if I have the option to delete all my data

00:47:50.120 | that a particular company has,

00:47:52.660 | then I'll share my data with everyone.

00:47:55.940 | I feel like if, because that gives me the tools

00:48:00.940 | to be a consumer, an intelligent consumer,

00:48:04.580 | of awarding my data to a company that deserves it

00:48:08.700 | and taking it back when the company is misbehaving.

00:48:11.260 | And in that way, encourage as a consumer

00:48:14.260 | in the capitalist system,

00:48:15.800 | encourage the companies that are doing great work

00:48:18.780 | with that data.

00:48:20.300 | - Well, yeah, healthcare data security is number one

00:48:24.260 | in my mind, InsideTracker made sure that that was true.

00:48:27.740 | But these buttons on your chest,

00:48:31.180 | there's very private stuff.

00:48:32.200 | They can probably tell if you're having sex one night.

00:48:35.560 | So this is not the kind of stuff you want leaked.

00:48:37.820 | So I don't know whether it's blockchain or something.

00:48:39.860 | - Speak for yourself, I want this public.

00:48:41.860 | (Luke laughs)

00:48:43.060 | - Well, I guess it depends on how you go.

00:48:45.660 | But there's a lot of stuff you don't want out there.

00:48:48.980 | And this definitely has to be number one,

00:48:51.620 | 'cause it's one thing to have your credit card

00:48:54.500 | information stolen, it's another thing

00:48:55.860 | your health records are permanently out there.

00:48:57.700 | - Yeah, so there's, on the biology side,

00:48:59.860 | super exciting ways to slow aging.

00:49:03.620 | But there's also on the lifestyle side.

00:49:05.580 | I've recently did a 72 hour fast,

00:49:08.060 | just an opportunity to take a pause and appreciate life.

00:49:11.680 | Think about, there's something about fasting

00:49:14.380 | that encourages you to reflect deeper

00:49:19.300 | than you otherwise might.

00:49:21.080 | The time kind of slows, and you also realize

00:49:25.100 | that you're human because your body needs food.

00:49:27.420 | And you start to see your body's almost as a machine

00:49:31.020 | that takes food and produces thoughts.

00:49:33.720 | (Luke laughs)

00:49:35.180 | And then ends, I mean, you start to,

00:49:38.620 | depending who you are, if you're engineering minded,

00:49:41.780 | you start to think of this whole thing

00:49:43.660 | as a kind of, yeah, as a machine.

00:49:46.220 | And then also feelings fill this machine.

00:49:50.900 | Feelings of gratitude, of love,

00:49:52.500 | but also the uglier things of jealousy,

00:49:56.580 | and greed, and hate, and all those kinds of things.

00:49:59.700 | You start to think, okay, how do I manage this body

00:50:04.540 | to create a rich experience?

00:50:06.180 | All of that comes from fasting for me.

00:50:07.780 | Anyway, but there's also health benefits to fasting.

00:50:11.780 | I intermittent fast a lot.

00:50:13.380 | I eat just one meal a day most of the time.

00:50:16.580 | Is there something you could say

00:50:18.220 | about the benefits of fasting in your own life,

00:50:20.540 | and in general, the anti-aging process?

00:50:23.500 | - Wow, you're a philosopher too.

00:50:25.660 | - Sorry, I apologize.

00:50:26.940 | - No, I'm impressed.

00:50:28.500 | True Renaissance man.

00:50:30.420 | It's a joy to be here.

00:50:32.020 | So when it comes to fasting, this is,

00:50:34.140 | being abstemious is one of the oldest ways

00:50:37.220 | to improve health.

00:50:38.500 | Probably they knew this 5,000 plus years ago.

00:50:41.620 | So that's not new.

00:50:43.180 | But what we're figuring out is what is optimal,

00:50:45.660 | and how does it work?

00:50:47.100 | And one of the things we help contribute to,

00:50:49.540 | which I can speak to with some authority,

00:50:51.820 | is that these longevity genes we work on,

00:50:54.420 | we showed back in the early 2000s,

00:50:56.380 | are turned on by fasting.

00:50:58.620 | And at least in yeast, we were the first to show

00:51:01.380 | how calorie restriction fasting works to extend lifespan.

00:51:04.500 | And that was the first for any species.

00:51:06.480 | Something similar happens in our bodies.

00:51:08.220 | When we're hungry, or put our bodies

00:51:10.540 | under any other perceived adversity,

00:51:12.660 | such as running, our bodies think,

00:51:14.700 | wow, we're getting run, chased by a saber-toothed cat

00:51:17.940 | or something.

00:51:19.540 | If we're really hot or cold, these probably also work.

00:51:22.460 | To put our bodies in this defensive state,

00:51:24.780 | to activate these genes in the way that whales do

00:51:27.180 | and mice don't.

00:51:28.640 | And so hunger is the best way to do that.

00:51:31.340 | In fact, I don't think you have to feel hungry.

00:51:33.760 | You can get used to it.

00:51:35.340 | But if there was one thing I would recommend to anybody

00:51:38.300 | to slow down aging, would be to skip a meal or two a day.

00:51:42.860 | Now, it doesn't mean you don't have to live well.

00:51:44.460 | You can go out.

00:51:45.300 | I go to restaurants, I eat regular food.

00:51:47.720 | I try to be as healthy as possible.

00:51:50.060 | But I've gone from skipping breakfast most of my life,

00:51:53.380 | now to skipping lunch as well.

00:51:55.460 | And I have my physique back that I had when I was 20.

00:51:59.300 | I feel 20 mentally.

00:52:01.260 | I'm much sharper.

00:52:02.500 | I don't feel tired anymore.

00:52:03.500 | I sleep well.

00:52:04.660 | So I'm a huge fan of the one meal a day thing.

00:52:07.380 | Where I'm not good at is going beyond one day.

00:52:11.120 | But if you do three days--

00:52:12.380 | - Have you ever fasted longer than 24 hours?

00:52:15.620 | - I tried doing two days.

00:52:17.120 | I might've made it to the third and given up.

00:52:20.180 | I just find that I don't have a lot of willpower.

00:52:23.820 | I also hate exercise.

00:52:24.900 | So I'm not sure how long I'm gonna live.

00:52:27.820 | But I've managed to do one meal a day.

00:52:29.140 | So if I can do that, seriously, anybody can do that.

00:52:31.980 | To your listeners and viewers, I would say,

00:52:35.980 | don't try to do it all at once.

00:52:38.100 | You can't go from snacking and eating three meals a day

00:52:40.700 | to what I do easily.

00:52:42.800 | Work your way up to it, but also compensate with drinking.

00:52:45.560 | If you like tea, if you like coffee, put some milk in it.

00:52:48.840 | That's fine.

00:52:49.680 | You can fill your stomach up with liquids, diet sodas.

00:52:52.960 | I get criticized for drinking,

00:52:54.140 | but I'm gonna continue to have those.

00:52:56.500 | But then I power through the day.

00:52:58.220 | I definitely don't feel tired.

00:52:59.680 | I don't have a lag anymore.

00:53:00.820 | But also give it at least two weeks

00:53:02.640 | 'cause there's a habit as well.

00:53:04.860 | Having something in your mouth, chewing,

00:53:06.480 | feeling that fullness.

00:53:08.400 | You can break that habit.

00:53:09.460 | And within two, three weeks, you'll have done it.

00:53:12.040 | - Absolutely.

00:53:12.880 | So I'm not actually even that strict about it.

00:53:14.440 | You said diet soda.

00:53:15.960 | Yeah, people are very kind of weirdly strict

00:53:18.480 | about fasting, the rules and fasting.

00:53:20.840 | Like for example, I drank Element Electrolytes

00:53:25.640 | when I was fasting, and that has like five calories.

00:53:28.520 | And so technically it's not fasting.

00:53:31.200 | Or people will say like, if you drink coffee,

00:53:33.700 | there's caffeine.

00:53:34.540 | And they'll say that's technically not fasting

00:53:36.960 | 'cause there's some kind of biological effects of caffeine.

00:53:39.200 | But whatever.

00:53:40.280 | Of course, there's like biological benefits

00:53:42.400 | that you can argue about.

00:53:43.520 | But there's also just experiential benefits.

00:53:45.960 | Just calorie restriction broadly

00:53:48.780 | has a certain experience to it that,

00:53:51.260 | like for me personally, just as you said,

00:53:53.640 | has made me feel really good.

00:53:55.160 | That said, like especially I've gained quite a bit of weight,

00:54:00.000 | like maybe even like 15 pounds, something like that,

00:54:03.320 | since I moved to Austin, Texas.

00:54:05.640 | And I still keep the same diet.

00:54:08.480 | But I eat a lot of meat in that one,

00:54:12.840 | just because it's delicious,

00:54:14.040 | because it's also the amazing people I met in Texas.

00:54:19.040 | It's just there's like a camaraderie, a friendship,

00:54:22.280 | a love to the people that like makes you really enjoy

00:54:25.320 | the atmosphere of eating the brisket and the meat.

00:54:29.320 | - Is this Joe Rogan insisting?

00:54:31.060 | - Joe is, I mean, it's very different.

00:54:34.720 | Joe loves bread and pasta.

00:54:38.680 | Like he knows that his body feels best

00:54:42.200 | doing keto or carnivore.

00:54:44.280 | So that's what he usually tries to stick to.

00:54:47.440 | But he also does not hold back.

00:54:50.120 | And he'll just eat pasta when he does pasta.

00:54:52.680 | And he sort of enjoys life in that way.

00:54:55.120 | I can't, I don't know how to enjoy life in that way.

00:54:57.840 | I also love pasta, but I'm just not going to enjoy it

00:55:01.840 | because I know my body ultimately

00:55:05.760 | does not feel good with pasta.

00:55:07.000 | So it's a funny kind of dichotomy.

00:55:09.360 | I would like to cheat, I guess,

00:55:13.800 | by eating more meat than I, you know,

00:55:17.080 | like overeating on the things

00:55:20.400 | that I know my body feels good on,

00:55:22.340 | as opposed to eating stuff I shouldn't,

00:55:24.320 | like cake and all those kinds of things.

00:55:26.400 | I tend to find happiness in overeating the good stuff

00:55:32.400 | versus eating the bad stuff.

00:55:35.920 | And that's the kind of balance.

00:55:37.720 | Him, he's like, fuck it.

00:55:40.060 | Every once in a while, you got to enjoy it.

00:55:43.360 | And then also coupled with that for him is just exercise,

00:55:48.360 | like then faces demons the next day

00:55:51.060 | and just like burn a huge amount of calories,

00:55:53.480 | which is, I mean, whatever's up with that guy's mind,

00:55:58.800 | there's an ability to fully experience life,

00:56:03.760 | which is represented by the pasta

00:56:06.000 | and the ability to just like fight the demons,

00:56:09.160 | which is represented by all the crazy kettleballs

00:56:11.400 | and running the hills

00:56:13.040 | and all this kind of stuff that he does.

00:56:14.720 | That takes a lot out of you

00:56:16.040 | doing that kind of insane exercise.

00:56:17.520 | And I think I'm more like you,

00:56:20.400 | or at least towards your direction is like,

00:56:22.520 | I really hate exercise.

00:56:24.400 | So I do it, but I really hate it.

00:56:26.760 | And so it's a balance that you have to strike.

00:56:29.600 | Is there something you could say

00:56:30.640 | about the diet side of that for you personally,

00:56:34.900 | but in general, in order to achieve calorie restriction,

00:56:39.760 | like for me eating, I know it may not sound healthy,

00:56:43.920 | but eating carnivore, eating mostly meat

00:56:47.800 | has made me feel really good, both mentally and physically.

00:56:52.800 | Is there something you could say about the kinds of diets

00:56:56.240 | that may improve longevity,

00:56:57.760 | but also enable calorie restriction?

00:57:01.160 | - Well, sure.

00:57:02.000 | I mean, the first thing that's important to know

00:57:04.560 | is that while many people are interested/obsessed

00:57:08.720 | with what they eat,

00:57:11.220 | the data that's come out of animal studies at least

00:57:13.600 | is it's far more important when you eat than what you eat.

00:57:17.320 | And this was a fantastic study a few years ago

00:57:20.120 | by my friend, Rafael de Cabo

00:57:22.000 | at the National Institutes of Health in Bethesda.

00:57:24.720 | And he had 10,000 mice on different diets,

00:57:26.920 | hoping to find the perfect mix of carbs, protein, and fat.

00:57:30.960 | And it turns out that the only ones that lived longer

00:57:33.240 | were the ones that only ate once a day.

00:57:35.840 | And so that, we're not mice,

00:57:37.920 | but I think that we're close enough to mice

00:57:40.280 | that this tells us a lot.

00:57:42.600 | But okay, but I still think the best bang

00:57:44.880 | for the longevity buck is to do both well,

00:57:47.840 | eat less often and eat the right things.

00:57:51.600 | Now I'll preface this to say, I'm not a nut about this.

00:57:54.360 | I will eat very occasionally a dessert.

00:57:57.940 | Usually I steal from others, which doesn't count, right?

00:58:00.880 | - Exactly.

00:58:01.720 | - But you gotta live life, right?

00:58:02.680 | What's a long life if it's not enjoyable anyway?

00:58:05.480 | But what I also found,

00:58:07.060 | and this is, I'll get to your question in a second,

00:58:09.200 | but my microbiome right now and stomach is at a point

00:58:12.520 | where if I try to overeat on a steak,

00:58:15.700 | which I did a couple of days ago,

00:58:16.880 | I actually had a fried chicken specifically,

00:58:21.880 | for two days I felt terrible.

00:58:23.880 | I couldn't sleep, it wouldn't go down.

00:58:26.040 | So I'm now at a point where even if I want to binge

00:58:28.280 | on meat and fried foods, I just can't, it just feels bad.

00:58:31.620 | But what do I recommend?

00:58:34.280 | Well, what the data says, which I try to follow

00:58:37.040 | is that plant-based foods will be better

00:58:40.360 | than meat-based foods.

00:58:41.280 | And I know that there are a lot of people who disagree,

00:58:43.900 | but one of the facts is, well, there's a few facts.

00:58:46.220 | One is that people who live a long time

00:58:47.620 | tend to eat those type of diets,

00:58:48.800 | Mediterranean, Okinawa diet.

00:58:51.040 | They're eating mostly plants with a little bit of meat

00:58:53.960 | and not a lot of red meat.

00:58:55.920 | And the other fact is that in animals,

00:58:57.760 | we know that there's a mechanism that's called mTOR,

00:59:01.320 | little m, capital T-O-R, that responds to certain amino acids

00:59:05.400 | that are found in more abundance in meat.

00:59:07.600 | And when it responds, it actually shortens lifespan.

00:59:10.240 | And the converse, if you starve it of those three amino acids

00:59:13.600 | mostly in meat, then it extends lifespan.

00:59:17.520 | And there's a drug called rapamycin,

00:59:19.480 | which some people are experimenting with, that does that.

00:59:22.720 | So you might be able to,

00:59:24.080 | I'm just saying this here from all my colleagues,

00:59:26.600 | we don't know the results here,

00:59:27.640 | but you could potentially take a rapamycin-like drug

00:59:30.640 | and counteract the effects of meat in the long run.

00:59:34.280 | Don't know, we should try that, actually.

00:59:35.800 | We could do that in the lab.

00:59:37.320 | But getting to the bottom of this,

00:59:39.360 | what I think is going on is that

00:59:41.240 | just like testosterone and growth hormone,

00:59:42.920 | you will get temporary, maybe not temporary,

00:59:47.080 | immediate health benefits.

00:59:48.580 | You'll feel great, you'll get more muscle energy.

00:59:51.920 | But the problem is, I think it's at the expense

00:59:54.320 | of long-term health and longevity.

00:59:56.140 | - Well, this is actually something I worry about

01:00:00.480 | in terms of long-term effects

01:00:03.180 | or the cost in terms of longevity.

01:00:05.880 | It's very difficult to know

01:00:07.280 | how your choices affect your longevity

01:00:09.920 | because the impact is down the line.

01:00:12.920 | Just because something makes me feel good now,

01:00:17.760 | like eating only meat makes me feel good now,

01:00:20.420 | I wonder what are the costs down the line.

01:00:22.420 | - Well, think about what I was saying

01:00:23.860 | about the trade-offs between growth and reproduction,

01:00:27.240 | which is what a mouse does,

01:00:28.640 | and a whale that grows slowly, reproduces slowly,

01:00:31.660 | lives a long time.

01:00:33.060 | It's called the disposable soma theory.

01:00:35.020 | Kirkwood just proposed that in the '70s.

01:00:38.820 | What meat probably does is put you in the mouse category,

01:00:42.140 | super fertile, grow fast, heal fast.

01:00:44.780 | And then if you want to be a whale,

01:00:46.660 | you should restrict meat and do things

01:00:49.680 | that promote the preservation of your body.

01:00:53.380 | - Is it difficult to eat a plant-based diet

01:00:57.860 | that you perform well under, so mentally and physically?

01:01:01.940 | Just almost, I'm asking almost like an anecdotal question,

01:01:06.940 | unless you know the science.

01:01:08.400 | - Well, the science is still being worked out,

01:01:12.180 | but from the synthesis of everything that I've read,

01:01:15.220 | I try to eat a diet that's definitely full of leafy greens,

01:01:20.160 | particularly spinach is great,

01:01:22.620 | 'cause it's got the iron that we need, plenty of vitamins.

01:01:25.860 | I also try to avoid too much fruit and berries,

01:01:30.860 | particularly fruit juice,

01:01:34.020 | definitely avoid that sugar high.

01:01:35.900 | Spiking your sugar is not healthy in the long run.

01:01:39.900 | The other thing that's interesting is we discovered

01:01:42.660 | what we called xenohormetic molecules.

01:01:45.500 | Let me unpack that, 'cause it's a terrible name,

01:01:47.540 | and I take full responsibility

01:01:49.460 | with my friend Conrad Howitz.

01:01:51.740 | The xeno means cross species,

01:01:53.900 | and hormesis is the term that what doesn't kill you

01:01:57.400 | makes you live longer and be healthier.

01:02:01.180 | And so we're getting cross species health improvements

01:02:04.660 | by molecules that plants make.

01:02:06.980 | And plants make these molecules

01:02:08.260 | when they're also under adversity or perceived adversity.

01:02:11.820 | For instance, I understand

01:02:14.180 | if you want really healthy or good oranges,

01:02:16.740 | you can drive nails into the bark of the tree

01:02:19.360 | before you harvest.

01:02:20.400 | Same with wine, you typically want them to be dry

01:02:23.260 | before you harvest or covered in fungus.

01:02:26.020 | And that's because these plants make these colorful

01:02:28.860 | and xenohormetic molecules

01:02:30.720 | that make themselves stress resistant,

01:02:33.420 | turn on their sirtuin defenses, the sirt genes, remember.

01:02:37.740 | And when we eat them, we get those same benefits.

01:02:40.340 | That's the idea, and we've evolved to do so.

01:02:42.260 | This isn't a coincidence.

01:02:43.740 | It's my theory, our theory,

01:02:45.040 | that we want to know when our food supply

01:02:48.360 | is under adversity because we need to get ready for a famine.

01:02:52.020 | And so we hunker down and preserve our body.

01:02:54.580 | And by eating these colored foods,

01:02:55.860 | so practically speaking, if it's full of color,

01:02:58.780 | or if there's been some chewing by a caterpillar,

01:03:01.940 | organic, grown locally in local farms,

01:03:05.000 | I'll eat that versus a watery, insipid, light-colored,

01:03:10.520 | lettuce that's been grown in California.

01:03:12.800 | - So you want vegetables that have suffered.

01:03:14.560 | You want the David Goggins' of vegetables.

01:03:16.720 | That's the xenohormetic molecules.

01:03:19.280 | - I love that term.

01:03:20.800 | I'm gonna take that one with me, thank you.

01:03:23.320 | - Yeah.

01:03:24.160 | Oh, I follow him on Instagram, he's always screaming.

01:03:27.360 | So you want the, he's basically

01:03:29.920 | the xenohormetic version of a human.

01:03:34.880 | I like it.

01:03:36.920 | So these are the molecules that are representative

01:03:39.000 | of the stress that a plant has been under.

01:03:44.000 | - Yeah, the best example of that is resveratrol,

01:03:46.720 | which many people, including myself,

01:03:48.200 | take as a supplement.

01:03:49.720 | Grapes, grapevines produce that in abundance

01:03:52.720 | when they're dried out or they have too much light

01:03:55.840 | or fungus.

01:03:56.880 | And that, we've shown, activates the SIR2 enzyme

01:04:00.920 | in our bodies, which, remember,

01:04:02.280 | is what extends lifespan in yeast

01:04:03.840 | and slows down aging in the brain.

01:04:05.840 | - That's beautiful.

01:04:06.980 | Yeah, I tend to avoid fruit as well.

01:04:09.300 | So green veggies, anything that's not very sweet.

01:04:12.720 | So I would just say you're relatively low,

01:04:15.460 | like you try to avoid sugary things as well.

01:04:19.180 | - Yeah, I'm fairly militant about that.

01:04:21.540 | I rarely would add sugar to anything.

01:04:23.940 | Occasionally I would eat a slice of cheesecake,

01:04:27.860 | but that would be maybe once or twice a year.

01:04:31.100 | You have to give in occasionally.

01:04:32.940 | But yeah, anything that's sweet,

01:04:34.820 | I would rather substitute something like Stevia

01:04:37.500 | if I need a sugar hit.

01:04:38.660 | - What about exercise, your favorite topic?

01:04:43.620 | (both laugh)

01:04:45.300 | Is there a--

01:04:46.140 | - I don't like talking about it.

01:04:47.580 | (both laugh)

01:04:48.420 | - Yeah, okay, great.

01:04:49.260 | Is there benefits to longevity from exercise?

01:04:53.500 | - Well, no doubt.

01:04:54.340 | That's proven.

01:04:55.980 | Just like fasting, it's pretty clear that that works.

01:04:59.260 | For example, there are studies of cyclists.

01:05:01.900 | It was something like people that cycle

01:05:04.220 | over 80 miles a week have a 40% reduction

01:05:07.700 | in a variety of diseases, certainly heart disease.

01:05:10.400 | So that's not even a question.

01:05:11.640 | But what's interesting is that we're learning

01:05:13.500 | that you don't need much to have a big benefit.

01:05:15.660 | It's an asymptotic curve.

01:05:17.460 | And in fact, if you overdo it,

01:05:19.180 | you probably have reduced benefits,

01:05:20.680 | particularly if you start to wear out joints,

01:05:22.180 | that kind of thing.

01:05:23.540 | But just 10 minutes on a treadmill a few times a week,

01:05:25.740 | getting your, lose your breath, get hypoxic as it's called,

01:05:28.580 | seems to be very beneficial for long-term health.

01:05:32.660 | And that's the kind of exercise that I like to do, aerobic.

01:05:36.460 | Though I do enjoy lifting weights.

01:05:38.520 | So that is what I call my exercise,

01:05:40.920 | which has other benefits,

01:05:41.860 | including maintaining hormone levels, male hormone levels.

01:05:46.240 | But also really why I do it is I want to be able

01:05:49.900 | to counteract the effect of sitting for most of the day.

01:05:53.500 | And as you get older, you lose muscle mass.

01:05:55.780 | It's a percent or so a year.

01:05:57.660 | And I don't want to be frail when I'm older

01:05:59.460 | and fall over and break my hip,

01:06:00.860 | which happens every 20 seconds in this country.

01:06:04.140 | - So maintaining that strength,

01:06:05.500 | but also doing the cardio for the longevity,

01:06:07.940 | for avoiding the heart disease.

01:06:10.180 | Yeah, I definitely, just like with fasting,

01:06:13.100 | have the philosophical benefit of running long

01:06:15.620 | and running slow.

01:06:17.120 | I enjoy it 'cause it kind of clears the mind

01:06:19.340 | and allows you to think.

01:06:20.600 | I actually listen to brown noise as I run.

01:06:23.060 | It really helps remove myself from the world

01:06:26.380 | and just like zoom in on particular thoughts.

01:06:28.740 | - What is brown noise?

01:06:30.060 | - It's like white noise, but deeper.

01:06:31.900 | So like white noise is like shh,

01:06:35.100 | and then brown noise is more like,

01:06:37.140 | (makes whooshing sound)

01:06:38.880 | like ocean.

01:06:39.940 | - That sounds great.

01:06:40.860 | I might try that.

01:06:41.740 | - Yeah, yeah, it's a--

01:06:43.500 | - It's more soothing probably.

01:06:44.940 | - I'm not sure.

01:06:45.780 | There could be science to this.

01:06:46.600 | I need to look this up.

01:06:47.640 | I've been meaning to.

01:06:48.860 | But when I started, this is maybe like five years ago,

01:06:53.820 | I started listening to brown noise when I work.

01:06:56.080 | And the first time I listened to it,

01:06:58.400 | something happened to my mind

01:07:00.300 | where it just went like,

01:07:01.660 | (makes whooshing sound)

01:07:02.500 | zoomed in to like,

01:07:04.500 | in a way that it felt like really weird,

01:07:07.860 | like how precisely it was able to sort of remove

01:07:12.660 | the distractions of the world and really help my mind.

01:07:16.580 | Obviously, like the mind is trying to focus

01:07:19.660 | and then it just enabled that process

01:07:21.820 | of trying to focus on a particular problem.

01:07:24.540 | I don't know if this is generalizable to others.

01:07:26.340 | People should definitely try it if you're listening to this.

01:07:29.040 | Maybe it's just my own mind.

01:07:30.260 | But it's funny, like,

01:07:32.320 | it made me, brown noise made me realize

01:07:35.880 | that there's probably hacks out there

01:07:38.720 | that work for me that I should be constantly looking for.

01:07:41.880 | It's almost like an encouraging and motivating event

01:07:46.380 | that maybe there's other stuff out there.

01:07:49.980 | Maybe there's other brown noise-like things out there

01:07:52.840 | that truly, like almost immediately make me feel better.

01:07:56.120 | I don't know if it's generalizable to others,

01:07:57.840 | but it does seem that it's the case that

01:08:01.680 | there's probably for many others,

01:08:03.280 | things like that that could be discovered.

01:08:05.880 | And so it's always disappointing when I find things in life

01:08:10.360 | that I wish I would found earlier.

01:08:12.960 | I got LASIK eye surgery a few years ago.

01:08:17.360 | And the first thought I had like the next day

01:08:19.400 | when I woke up is like,

01:08:21.360 | damn it, why didn't I do this way earlier?

01:08:24.200 | There's other stuff of that nature

01:08:27.320 | that are yet to be discovered.

01:08:29.640 | So it pays to explore.

01:08:31.720 | - Yeah, though you have a different mind.

01:08:33.000 | You have quite a beautiful mind.

01:08:34.520 | So I suspect brown noise helps you focus

01:08:37.200 | and 'cause you're probably all over the place

01:08:39.140 | if you don't control it.

01:08:40.240 | - Yeah, exactly.

01:08:41.080 | It means something about it.

01:08:42.360 | It's a programmer thing.

01:08:43.560 | A programming is a really difficult mental journey

01:08:50.000 | 'cause you have to keep a lot of things in mind.

01:08:52.920 | You have to, so you're constantly designing things.

01:08:56.520 | Then you have to be extremely precise

01:08:58.120 | by making those things concrete in code.

01:09:01.120 | You also have to look stuff up on the internet

01:09:05.160 | to sort of feed like information

01:09:08.680 | and looking up stuff on the internet.

01:09:10.440 | Internet is full of like distracting things.

01:09:12.400 | So you have to be really focused

01:09:13.800 | in the way you look stuff up

01:09:15.560 | in pulling that information in.

01:09:16.800 | So it requires a certain discipline

01:09:19.120 | and a certain focus that I've been very much exploring

01:09:23.440 | how to do.

01:09:24.280 | Like I do it really well in the morning,

01:09:26.360 | coffee's involved, all those kinds of things.

01:09:28.320 | You're trying to optimize,

01:09:29.680 | keeping very positive inspired, no social media,

01:09:33.560 | all those kinds of things and trying to optimize for.

01:09:36.160 | And everybody has their own kind of little journey

01:09:38.680 | that they try to understand.

01:09:40.560 | You get this from like writers.

01:09:41.960 | When you read about the habits of writers,

01:09:45.840 | like the habits they do in the morning,

01:09:47.880 | they usually write like two, three, four hours a day

01:09:49.840 | and that's it.

01:09:51.000 | It's like they optimize that ritual.

01:09:53.440 | And then there's always Hunter Stobson.

01:09:55.480 | So sometimes it pays off to be wild.

01:10:00.480 | What about sleep?

01:10:04.600 | How important is sleep for longevity?

01:10:06.760 | - I would guess based on the evidence

01:10:10.760 | that it's really important.

01:10:12.200 | And because we don't know for sure.

01:10:15.080 | But what we know from animal studies is the following.

01:10:17.600 | If you restrict sleep from a rat for just two weeks,

01:10:20.280 | it'll develop type two diabetes.

01:10:22.200 | It's that important.

01:10:23.420 | So that's the main thing.

01:10:25.840 | What we also know is at the molecular level

01:10:28.480 | that if you disrupt your sleep-wake cycle,

01:10:33.360 | so we actually have proteins that go up and down

01:10:35.120 | that control our sleep-wake.

01:10:36.720 | All of us, most of our cells do that.

01:10:39.240 | If you disrupt that, you'll get premature aging.

01:10:42.480 | And guess what?

01:10:43.320 | The opposite is true.

01:10:44.140 | That as you get older, that cycle,

01:10:46.760 | the amplitude becomes diminished.

01:10:49.480 | And this is why it's harder to get to sleep as you get older

01:10:51.880 | and then you got all sorts of problems.

01:10:54.480 | And I think what's going on is there's positive feedback

01:10:56.920 | which is a disaster in your old age,

01:10:59.420 | which is you're aging.

01:11:02.040 | You can't at this moment totally prevent that.

01:11:05.760 | And then it's disrupting your sleep

01:11:06.880 | and you get not enough sleep.

01:11:08.020 | And then that's gonna accelerate your aging process.

01:11:10.440 | And so it's known that people who are shift workers

01:11:13.720 | are more susceptible to certain age-related diseases.

01:11:17.560 | So bottom line, you definitely wanna work on that.

01:11:19.960 | It's one of the reasons I have this ring on my finger

01:11:21.840 | which helps me optimize my sleep

01:11:23.320 | and learn what I do the day before if it was a bad idea.

01:11:27.420 | And I'll stop doing that like eating a fried chicken.

01:11:29.920 | (laughing)

01:11:31.760 | - I see you're still carrying the burdens of that decision.

01:11:34.860 | But is, yeah, you know, sleep is one of those things

01:11:37.920 | that's making me wonder about the variability

01:11:41.600 | between humans a little bit and how science

01:11:44.360 | is often focused on,

01:11:46.080 | like it's not often focused on high performers

01:11:51.500 | in a particular way.

01:11:52.600 | And it's looking at the aggregate

01:11:55.200 | versus the individual cases.

01:11:56.940 | For example, like for me,

01:11:59.360 | I don't know what the exact hours are,

01:12:00.940 | but like power naps are incredible.

01:12:04.280 | I tend to look at the metric of stress and happiness

01:12:10.680 | and joy and try to optimize those.

01:12:13.080 | So decreasing stress, increasing happiness,

01:12:16.020 | and using sleep as just one of the tools to do that.

01:12:20.160 | Because like hitting the five, six, seven, eight,

01:12:23.720 | nine hour mark or whatever the correct mark is,

01:12:27.200 | I find that to be stress inducing for me

01:12:30.000 | versus stress relieving.

01:12:32.320 | Like thinking about that,

01:12:34.200 | I feel best if I sleep sometimes for eight hours,

01:12:37.360 | sometimes for four hours and then power nap.

01:12:39.600 | And as long as I have a stupid,

01:12:42.200 | private usually smile on my face,

01:12:44.480 | that's when I'm doing good

01:12:46.200 | as opposed to getting a perfect amount of sleep

01:12:49.480 | according to whatever the latest blog post is.

01:12:53.320 | And I also pull all nighters still.

01:12:55.400 | I also think there's something about the body,

01:12:59.360 | like as long as you do it regularly,

01:13:02.900 | it's not as stress inducing.

01:13:04.440 | Like you know what it is.

01:13:06.840 | The reason I pull all nighters isn't for like,

01:13:09.000 | I'm playing Diablo three or something,

01:13:11.600 | is because I'm doing something I'm truly passionate about.

01:13:14.000 | Well, I'm also a video games,

01:13:15.860 | but I'm doing something I'm truly passionate about.

01:13:18.480 | And it's almost like there's the Jocko Willink feeling

01:13:21.440 | of when I'm up at 7 a.m. and I haven't slept all night

01:13:25.560 | and still I'm working on it.

01:13:27.200 | There's a kind of a celebration of the human spirit

01:13:29.520 | that I really enjoy it.

01:13:30.880 | And that's happiness.

01:13:33.760 | And to sort of then,

01:13:36.000 | and I usually don't tell that kind of stuff to people

01:13:38.000 | because their first statement will be like,

01:13:40.880 | you should get more sleep.

01:13:42.620 | It's like, no, I'm doing stuff I love.

01:13:46.240 | You should get more love in your life, bro.

01:13:49.040 | - That's right.

01:13:50.440 | - So, but that said in aggregate,

01:13:52.560 | when you look at the full span of life,

01:13:55.400 | is probably you should be getting

01:13:58.480 | a consistent amount of sleep.

01:14:00.760 | And it seems like it's in that seven, eight hour range.

01:14:04.960 | - Yeah, but it's similar to food.

01:14:06.760 | It's the quality, not the quantity.

01:14:09.360 | And when you get it.

01:14:10.760 | So I look at my data pretty often.

01:14:14.520 | And what makes a difference to me

01:14:16.040 | is not the amount of hours, but the quality, the depth

01:14:19.200 | and the deep sleep is what'll do it.

01:14:21.960 | So if I have a lot of alcohol before going to sleep

01:14:24.880 | and I can see my heart rate being different,

01:14:26.400 | but what really kills me is that I don't get a lot

01:14:28.440 | of that deep sleep and I wake up barely remembering stuff.

01:14:32.480 | So that, like you say, if you're happy and contented

01:14:34.440 | and you don't have these cortisol chemicals

01:14:37.160 | going through your body,

01:14:38.420 | you will more naturally get into that deep state.

01:14:40.720 | And even if you just get four hours,

01:14:42.320 | way better than eight hours of none of that.

01:14:45.420 | - Yeah, yeah, that's beautiful.

01:14:46.800 | And some of that could be genetic.

01:14:48.240 | For me, I just fall asleep like this.

01:14:52.040 | If you want me to fall asleep right now, I can do it.

01:14:54.160 | It's no, I have no problem with it combined with coffee.

01:14:58.180 | I just had two energy drinks, I can probably sleep.

01:15:01.480 | So that, I don't know if that's genetics

01:15:03.560 | or it's kind of, I don't know what it is.

01:15:06.680 | Or maybe that I don't have kids and I'm single.

01:15:09.720 | So I don't have, I'm almost listening

01:15:11.920 | to some kind of biological signal versus societal signal

01:15:15.400 | on when I'm supposed to go to sleep.

01:15:17.080 | So I just go to sleep whenever I feel like going to sleep.

01:15:20.720 | - Well, that's 'cause you're self-employed.

01:15:22.480 | - Self-employed. - Most people

01:15:23.360 | don't have that luxury, but we're lucky, the two of us,

01:15:26.120 | that we can make our own hours.

01:15:28.280 | But yeah, it's super important.

01:15:29.800 | And those people who have the shift work,

01:15:32.360 | I mean, they really need to change the way that works

01:15:35.480 | because they're literally killing those people.

01:15:37.840 | - Is there something you could say about the mind

01:15:43.640 | and stress in terms of effect on longevity?

01:15:48.200 | 'Cause I don't know if you think about it this way,

01:15:52.520 | but when you talk about the biological machine,

01:15:55.100 | it's always these mechanisms that are not necessarily

01:15:58.820 | directly connected to the brain

01:16:00.920 | or the operation of the brain.

01:16:02.640 | Like what's the role about stress and happiness

01:16:06.360 | and yeah, the sort of higher cognitive things

01:16:10.720 | going on in the brain on longevity?

01:16:13.060 | - Right, well, that's a great point.

01:16:16.240 | The brain is the center for longevity, actually.

01:16:19.320 | We do know that.

01:16:20.300 | First off, when I'm stressed, I can see, mentally stressed,

01:16:24.660 | then I can see it in my body.

01:16:27.120 | Heart rate, hormones, it's clear.

01:16:29.560 | That's no true surprise.

01:16:31.460 | So you've got to work on your brain first and foremost.

01:16:34.000 | If you are totally freaked out, agitated all the time,

01:16:39.000 | you will live shorter.

01:16:41.360 | I'm certain of it.

01:16:42.520 | I keep fish.

01:16:43.480 | I'm a big aquarium guy.

01:16:47.520 | And you can see the difference between the fish

01:16:49.500 | that's having a good time and dominant

01:16:51.480 | and the one that gets picked on.

01:16:53.340 | It just looks like crap.

01:16:55.200 | You don't want to be that, the little fish getting picked on

01:16:57.580 | if you can help it.

01:16:58.680 | So I used to be extremely stressed as a kid.

01:17:00.980 | I was a perfectionist, very shy,

01:17:03.380 | always worried about being a failure.

01:17:06.120 | If I didn't get an A plus, you know,

01:17:07.440 | I was crying in my bedroom, that kind of sad existence.

01:17:11.000 | I got into my 20s, then in my 30s and realized

01:17:14.820 | that's not the way to live.

01:17:15.800 | So I've worked very hard to get to this point

01:17:18.000 | where I almost never get stressed, never.

01:17:21.240 | There's nothing that, I've never gotten angry in my lab.

01:17:23.640 | I've got 20 kids.

01:17:24.640 | Sometimes it's like a, most of the time,

01:17:26.780 | it's like a kindergarten.

01:17:28.840 | I haven't lost my temper, I'm very calm.

01:17:31.440 | But that's intentional.

01:17:32.920 | And I don't worry about stuff.

01:17:34.960 | Millions of dollars, billions of dollars at stake sometimes.

01:17:37.960 | Keep it cool.

01:17:39.920 | It's only life.

01:17:40.740 | We're all headed to the same place anyway.

01:17:42.760 | Don't worry about it.

01:17:44.280 | But to answer your question, I think in a better way,

01:17:47.760 | if you manipulate the brain of an animal,

01:17:49.760 | I'll give you an example.

01:17:51.560 | If we turn on this SIRT gene that I mentioned, SIRT1,

01:17:54.920 | we, a good friend of mine at Wash U, she and I did this.

01:17:58.100 | They upregulated that gene just in the neurons

01:18:01.800 | of the animal.

01:18:03.220 | It lived longer.

01:18:04.800 | So that's sufficient to extend lifespan.

01:18:06.960 | We also know that you can manipulate the part of the brain

01:18:10.040 | called the hypothalamus, which leeches a lot of chemicals

01:18:12.700 | into the body and proteins, most of which we don't know yet,

01:18:17.120 | but just changing the inflammation of that little organ

01:18:21.040 | or part of the brain is sufficient

01:18:22.920 | to make animals live longer as well.

01:18:24.960 | So get your brain in order first

01:18:26.520 | before you tackle anything else, I would say.

01:18:29.480 | - So you kind of mentioned this.

01:18:31.700 | With the Insight Tracker, there's ability

01:18:34.440 | to take blood measurement and then infer from that

01:18:38.400 | a bunch of different things about your body

01:18:41.000 | and how you can improve the longevity.

01:18:44.720 | And you've also mentioned saliva and more efficient ways

01:18:50.000 | to get data.

01:18:52.520 | What does that involve?

01:18:55.440 | What's the future of data collection look like

01:18:57.440 | for the human biological system?

01:18:59.240 | - Right, well, yeah, the issue with blood

01:19:01.640 | is you need someone to take it.

01:19:03.400 | I mean, or you prick your finger, which hurts.

01:19:06.080 | So you've got to have something better.

01:19:07.160 | So I think what the future looks like

01:19:09.040 | is that you'll spit onto a little piece of paper

01:19:12.400 | and stick it in a machine, it'll do that for you.

01:19:14.760 | But we're not there yet.

01:19:15.640 | So the intermediate future that I'm building right now

01:19:20.640 | is that you would take a swab of the inside of your mouth,

01:19:24.220 | which is the easiest way to take cells out of your body,

01:19:26.800 | and just ship them off.

01:19:28.360 | Okay, so it's called a buckle swab.

01:19:30.800 | I think we became very used to that.

01:19:32.920 | Right now, because of COVID,

01:19:34.360 | people don't like going to the doctor as much.

01:19:36.120 | They don't like going out.

01:19:36.960 | They just want to have home tests.

01:19:38.840 | And so that I think is the next 10 years

01:19:40.800 | where you'll get a kit in the mail,

01:19:43.160 | you'll swab your cheeks, stick it back in an envelope,

01:19:45.280 | send it off, and a week later,

01:19:47.440 | you have either a doctor's report

01:19:50.240 | or a health recommendation.

01:19:52.880 | And what can you get off a cheek swab?

01:19:55.000 | Well, you can get anything.

01:19:55.840 | You can get hormones, stress hormones, blood glucose levels.

01:20:00.840 | You can also tell your age reasonably accurately doing that,

01:20:04.400 | actually quite accurately.

01:20:05.920 | And those clocks cannot just tell you

01:20:08.240 | how you're doing over time,

01:20:10.200 | but can be used to give you recommendations

01:20:12.200 | to slow that process down.

01:20:14.200 | 'Cause some people sometimes are 10 years older biologically

01:20:16.640 | than their actual chronological age.

01:20:19.600 | I mean, why does it matter how many times

01:20:21.940 | the Earth's gone around the sun?

01:20:23.000 | Seriously, who cares about birthdays?

01:20:24.920 | It's how long your body's clock has been ticking,

01:20:27.280 | and how fast.

01:20:28.560 | So I could take a cheek swab from you today, Lex,

01:20:31.040 | take it back to my lab,

01:20:32.720 | and we then by tomorrow tell you

01:20:35.400 | how old you are biologically

01:20:36.880 | based on what we call the epigenetic clock.

01:20:40.920 | And you might be freaked out, you might be happy,

01:20:43.120 | but either way, we can advise you

01:20:45.560 | on how to improve the trajectory.

01:20:47.840 | 'Cause we know that smoking increases

01:20:49.420 | the speed of that clock.

01:20:50.880 | We also know that fasting and people

01:20:52.880 | who eat the right foods have a slower clock.

01:20:55.960 | Without that knowledge, you're flying blind.

01:20:58.520 | But I like the idea of a swab 'cause it's just so easy.

01:21:01.280 | A lot of us have done something like that for COVID tests.

01:21:03.280 | It's not a big deal.

01:21:04.120 | - Yeah, I've been doing a nonstop rapid antigen test.

01:21:06.160 | So let me say that particular one, rapid antigen test,

01:21:11.080 | they've been a source of frustration for me

01:21:12.680 | because everybody should be doing it.

01:21:14.840 | It's so easy.

01:21:16.080 | - We've also been working in my lab

01:21:17.280 | on democratizing these tests

01:21:19.120 | to bring them down from a few hundred bucks to a dollar.

01:21:22.080 | - So just to clarify, you're talking about not research,

01:21:24.240 | you're talking about company stuff,

01:21:25.800 | like actual consumer-facing things?

01:21:28.600 | - Well, right.

01:21:29.440 | The research on bringing the price down

01:21:31.000 | has occurred in my lab at Harvard.

01:21:32.920 | And then that intellectual property is being licensed

01:21:35.080 | and has been licensed out to a company

01:21:37.240 | that will be consumer-facing.

01:21:40.300 | So anybody for a small amount of money can do this.

01:21:43.320 | - Well, you got subscriber number one obsessed.

01:21:46.400 | I think that's a beautiful, beautiful idea.

01:21:48.640 | So somebody who maybe I would have been more hesitant

01:21:51.480 | about it until COVID, but home tests are super easy.

01:21:56.360 | I almost wanted to share that data with the world,

01:21:59.360 | like in some way, not the entirety of the data,

01:22:01.840 | but like some visualization of like how I'm doing.

01:22:05.800 | Like, it's almost like, you know, when you share,

01:22:09.400 | if you had like a long run or something like that,

01:22:11.440 | I wish I could share, 'cause it inspires others.

01:22:14.560 | And then you can have a conversation about like,

01:22:16.920 | well, what are the hacks that you've tried?

01:22:18.820 | And have a conversation about like how to improve lifestyle

01:22:21.400 | and those kinds of things that's grounded in data.

01:22:23.680 | - That's exactly, that's what's gonna happen.

01:22:25.580 | Now, everything's anonymous, of course.

01:22:27.440 | We talked about security there,

01:22:29.600 | but once it's anonymized, you can then plot these numbers.

01:22:32.560 | And I've plotted my epigenetic age

01:22:35.580 | versus hundreds of other people who've taken this test now.

01:22:39.080 | And I can tell you where I fit relative to others

01:22:41.440 | in terms of my biological age.

01:22:43.600 | And I'm happy to share that with you all,

01:22:45.080 | 'cause it's pretty low.

01:22:46.340 | You can choose to share it, of course,

01:22:48.520 | not everyone wants to share that.

01:22:50.440 | But when you go to the doctor,

01:22:52.240 | first of all, your doctor does treat you

01:22:54.840 | as though you're an average person,

01:22:55.960 | and none of us are average, there's no such thing.

01:22:58.600 | But second of all, we never know how we're doing

01:23:00.920 | relative to others, 'cause we all, most of us,

01:23:04.280 | we don't share our information.

01:23:05.820 | So we might have this number and that number,

01:23:08.040 | but do you know that your numbers

01:23:09.480 | are good for your age or not?

01:23:11.280 | You have no idea.

01:23:12.720 | Even your doctor probably doesn't even know.

01:23:14.560 | So this graph that I'm talking about

01:23:16.360 | is the beginning of a world where you can say,

01:23:18.040 | how am I doing?

01:23:19.360 | I'm a, for the two of us, we're white and we're male

01:23:22.720 | and we're this age, and we do this.

01:23:25.400 | Are we good?

01:23:27.260 | Are we doing the right things or the wrong things?

01:23:28.600 | Do we need to fix certain things?

01:23:30.440 | And this is what the future is.

01:23:32.120 | It's, forget about just experimenting

01:23:35.360 | and not knowing the result.

01:23:36.320 | I mean, who doesn't experiment

01:23:37.280 | and doesn't look at the data?

01:23:38.520 | No one, it makes no sense.

01:23:40.220 | So we're gonna enter a world

01:23:41.240 | where we have a dashboard on our body,

01:23:43.480 | the swabs, the blood tests, the biosensors,

01:23:46.460 | where our doctors can look at that,

01:23:48.520 | but we can also look at it and they can recommend,

01:23:51.600 | go to this restaurant down the road,

01:23:52.960 | they've got this great meal.

01:23:54.400 | It's high in whatever you need today,

01:23:56.320 | 'cause you're lacking vitamin D and vitamin K too,

01:23:58.480 | go for it.

01:23:59.320 | - Ridiculous question, or perhaps not.

01:24:03.240 | If you look maybe 50 years from now

01:24:05.080 | or 100 years from now, a person born then,

01:24:07.760 | what do you think is a good goal

01:24:09.280 | in terms of how long a person would live?

01:24:12.320 | Like what is the maximum longevity

01:24:14.760 | that we can achieve through the methods

01:24:17.360 | that we have today of,

01:24:19.860 | or are developing some of the things

01:24:21.120 | we've been talking about

01:24:22.320 | in terms of genetics, in terms of biology?

01:24:26.280 | Is there a number?

01:24:28.160 | - Right, well, so it changes all the time

01:24:31.760 | because technology's changing so quickly.

01:24:33.420 | I keep revising the number upward,

01:24:36.240 | but I would say that if you do the right things

01:24:38.660 | during your life and start at an early age,

01:24:40.760 | let's say 25, we don't want malnutrition, starvation,

01:24:43.280 | that's not what I'm talking about,

01:24:45.160 | but in your 20s, start eating the kind of diets

01:24:48.840 | that I talked about, skipping meals.

01:24:51.880 | In animals, that gives you an extra 20 to 30%.

01:24:55.920 | We don't know if that's true for humans,

01:24:57.840 | and that would, even 5% more would be a good,

01:25:00.840 | a big deal for the planet.

01:25:03.220 | I think that we should all aim

01:25:05.120 | to at least reach a century.

01:25:06.640 | I'm a little bit behind.

01:25:09.360 | I was born too early to benefit the most

01:25:12.040 | from all of this discovery.

01:25:13.840 | Those of you who are in your 20s,

01:25:16.000 | you should definitely aim to reach 100.

01:25:18.680 | I don't see why not.

01:25:19.680 | Consider this, this is really important.

01:25:23.140 | The average lifespan of a human

01:25:25.040 | that looks after themselves but doesn't pay attention

01:25:28.120 | is about 80, okay?

01:25:31.000 | Japan, that's the average age for a male, a bit higher.

01:25:34.160 | If you do the right things in your life,

01:25:37.220 | which is eat healthy food, don't overeat,

01:25:41.140 | don't become obese, do a bit of exercise,

01:25:42.900 | get good sleep, and don't stress,

01:25:44.720 | that gives you, on average, 14 extra years.

01:25:47.220 | That gets you to 94.

01:25:49.060 | So getting to 100, if you just focus

01:25:51.100 | on what I'm talking about, it's not a big deal.

01:25:53.700 | So what's the maximum?

01:25:54.620 | Well, we know that one human made it to 122,

01:25:57.380 | and a number of them make it into their teens.

01:26:00.360 | I think that's also the next level

01:26:02.180 | of where we can get to with the types of technologies

01:26:06.300 | that I'm talking about.

01:26:07.580 | Medicines, like I mentioned rapamycin,

01:26:09.980 | there's one called metformin,

01:26:10.980 | which is the diabetes drug which I take.

01:26:14.420 | That, in combination with these lifestyle changes,

01:26:16.460 | should get us beyond 100.

01:26:18.380 | How long can we ultimately live?

01:26:19.640 | Well, there's no maximum limit to human lifespan.

01:26:22.260 | Why can a whale live 300 years, but we cannot?

01:26:24.600 | We're basically the same structure.

01:26:26.260 | We just need to learn from them.

01:26:27.980 | So anyone who says, "Oh, you max out at X,"

01:26:31.080 | I think is full of it.

01:26:33.280 | There's nothing that I've seen that says

01:26:35.360 | biological organisms have to die.

01:26:37.520 | There are trees that live for thousands of years,

01:26:39.520 | and their biochemistry is pretty close to ours.

01:26:42.480 | - What do you think it means to live for a very long time?

01:26:44.960 | Let's say if it's 200 years we're talking about,

01:26:47.280 | or 1,000 years.

01:26:48.640 | There's some sense, you could argue

01:26:54.600 | that there is immortal organisms already living on Earth.

01:26:58.020 | Like there's bacteria.

01:26:59.040 | So there's certain living organisms

01:27:03.740 | that in some fundamental way do not die,

01:27:07.940 | because they keep replicating their genetic information.

01:27:10.260 | They keep cloning themselves.

01:27:12.120 | Is it the same human if we can somehow persist

01:27:18.800 | the human mind, like copy-clone certain aspects,

01:27:23.900 | and just keep replacing body parts?

01:27:26.340 | Do you think that's another way to achieve immortality?

01:27:30.420 | To achieve a prolonged, sort of increased longevity

01:27:33.740 | is to replace the parts that break easily,

01:27:37.100 | and keep, 'cause actually from your theory

01:27:39.980 | of aging as a degradation of information,

01:27:44.440 | so an information theory view of aging,

01:27:46.540 | like what is the key information that makes a human?

01:27:51.480 | Can we persist that information,

01:27:53.440 | and just replace the trivial parts?

01:27:56.200 | - Yeah, I mean the short answer is yes.

01:27:59.340 | We're already replacing body parts,

01:28:01.340 | but what makes us human is our brain.

01:28:03.820 | Everything else is suboptimal except our brain.

01:28:07.360 | The ability to replace actual neurons is really hard.

01:28:13.760 | I think it might be easy to upload

01:28:16.220 | rather than replace neurons,

01:28:17.940 | because they're so tight, it's such a network,

01:28:20.500 | and just perturbing the system.

01:28:22.800 | You know, it's Schrödinger's cat.

01:28:25.720 | You change everything once you get in there.

01:28:28.760 | The problem is, well I guess the solution,

01:28:31.800 | let me go to the solution, that's more interesting.

01:28:34.160 | What we're learning is that

01:28:35.000 | if you reverse the age of nerve cells,

01:28:37.380 | it looks like they get their memories back.

01:28:41.400 | So the memories are not lost,

01:28:42.640 | they're just that the cells don't know how to interpret them

01:28:45.320 | and function correctly.

01:28:46.960 | And this is one of the things we're studying in my lab.

01:28:48.840 | If you take an old mouse that has learned something

01:28:50.440 | when it was young, but forgotten, does it get that back?

01:28:53.660 | And all evidence points to that being true.

01:28:56.460 | So I'd rather go in and rejuvenate the brain as it sits

01:28:59.620 | rather than replace individual cells,

01:29:01.300 | which would be really hard.

01:29:03.100 | - What do you think about efforts like Neuralink,

01:29:06.720 | which basically, you mentioned uploading,

01:29:10.260 | are trying to figure out,

01:29:11.740 | so creating brain-computer interfaces

01:29:13.660 | that are trying to figure out

01:29:14.620 | how to communicate with the brain.

01:29:16.900 | But one of the features of that

01:29:18.100 | is trying to record the human brain

01:29:20.860 | more and more accurately.

01:29:22.740 | Do you have hope for that to,

01:29:26.060 | of course, it will lead to us better understanding

01:29:30.780 | from a neuroscience perspective, the human mind,

01:29:33.220 | but do you have hope for it increasing longevity

01:29:36.060 | in terms of how it's used?

01:29:38.340 | - I think that it can help with certain diseases.

01:29:41.180 | But I see, at least within our lifetime,

01:29:42.980 | that's the best use of it,

01:29:43.980 | is to be able to replace parts of the body

01:29:46.100 | that are not functioning, such as the retina

01:29:49.380 | and other parts, the visual cortex back here.

01:29:51.860 | That's going to be doable.

01:29:53.900 | In terms of longevity,

01:29:55.300 | maybe we could put something on the hypothalamus

01:29:58.020 | and start secreting those hormones and get that back.

01:30:00.660 | Ultimately, I think the best way to preserve the brain

01:30:06.780 | is going to be to record it,

01:30:10.780 | but also, I think it's going to require death, unfortunately,

01:30:13.860 | to then do very detailed scans,

01:30:16.980 | even if you have enough time and money,

01:30:19.180 | atomic microscopy, and rebuild the brain from scratch.

01:30:22.500 | - Rebuild from scratch, yeah.

01:30:24.340 | We are living more and more in a digital world.

01:30:28.020 | I wonder if the scanning is good enough

01:30:31.500 | for the critical things in terms of memories,

01:30:34.420 | in terms of the particular quirks

01:30:36.420 | of your cognitive processes.

01:30:38.100 | - They're not.

01:30:38.940 | - We're not close, yes,

01:30:42.060 | but we've made quite a bit of progress.

01:30:44.740 | If you're an exponential type of person.

01:30:50.540 | - Well, let's dream a little here.

01:30:52.140 | - Yes, that's the point.

01:30:53.180 | - The way it would work, that I could see it working,

01:30:55.820 | is you take a single cell slice through your dead brain,

01:31:00.820 | and we can now, the problem with the engineering aspect

01:31:04.140 | is that the engineering is,

01:31:06.060 | the physical aspect of the brain is not even half the problem.

01:31:09.700 | The problem is which genes are switched on and off.

01:31:12.980 | This experience that we're having here

01:31:14.460 | is altering certain genes in neurons

01:31:18.260 | that will be preserved, hopefully, for a number of decades.

01:31:22.060 | But you cannot see that with a microscope easily.

01:31:25.300 | But there are technologies invented,

01:31:27.780 | actually, just down the hall in the building I'm at,

01:31:30.760 | George Church invented a way, his lab invented a way

01:31:33.500 | to look at which genes are switched on and off,

01:31:36.820 | not only in a single cell,

01:31:38.060 | which any lab can do these days,

01:31:40.100 | but in situ, where it's situated in the brain.

01:31:42.980 | So you can say, okay, this nerve cell

01:31:45.260 | had these genes switched on and these switched off,

01:31:47.700 | we can recreate that.

01:31:49.740 | But just scanning the brain

01:31:50.980 | and looking how the nerves are touching each other

01:31:52.540 | is not gonna do it.

01:31:53.540 | - Wow, okay, so you have to scan the full biology,

01:31:58.140 | the full details.

01:31:59.220 | - And look at the epigenome.

01:32:00.420 | - And the epigenome, too.

01:32:01.580 | - Yeah, which genes are on and off.

01:32:03.140 | It's just easier to reset the epigenome

01:32:05.100 | and get them to work like they used to.

01:32:07.540 | We're doing that now.

01:32:08.380 | - Use the hardware we already have,

01:32:09.760 | just figure out how to make that hardware last longer.

01:32:13.860 | - Right, ultimately, information will be lost.

01:32:15.700 | Even genetic information degrades slowly through mutation.

01:32:19.380 | So immortality is not achievable through that means,

01:32:22.500 | though I think we could potentially reset the body

01:32:25.260 | hundreds of times and live for thousands of years.

01:32:28.460 | - Okay, so we talked about biology.

01:32:31.540 | Let's, forgive me, but let's talk about philosophy

01:32:34.620 | for just a brief moment.

01:32:36.740 | So somebody I've enjoyed reading, Ernest Becker,

01:32:39.420 | wrote "The Denial of Death."

01:32:40.700 | There's also Martin Heidegger.

01:32:42.980 | There's a bunch of philosophers who claim

01:32:45.100 | that most people live life in denial of death.

01:32:51.940 | Sort of we don't fully internalize

01:32:56.940 | the idea that we're going to die.

01:33:04.180 | Because if we did, as they say,

01:33:06.940 | there will be a kind of terror of,

01:33:10.180 | I mean, a deep fear of death.

01:33:14.060 | The fact that we don't know what's,

01:33:17.220 | like we almost don't know what to do with non-existence,

01:33:22.220 | with disappearing.

01:33:24.820 | Like our, the way we draw meaning from life

01:33:28.300 | seems to be grounded in the fact that we exist

01:33:30.820 | and that we at some point will not exist is terrifying.

01:33:34.580 | And so we live in an illusion that we're not going to die

01:33:37.580 | and we run from that terror.

01:33:39.660 | That's what Ernest Becker would say.

01:33:41.700 | Do you think there's any truth to that?

01:33:44.220 | - Oh, I know there's truth to that.

01:33:45.420 | I experience it every day when I talk to people.

01:33:47.780 | We have to live that way.

01:33:49.660 | Although, unfortunately, I can't.

01:33:51.380 | But for most people, it's extremely distressing

01:33:56.380 | to think about their own mortality.

01:33:59.360 | We think about it occasionally.

01:34:00.540 | And if we really thought about it every day,

01:34:02.260 | we'd probably be brought to tears.

01:34:03.980 | How much we'd not just miss ourselves,

01:34:05.740 | but miss our family, our friends.

01:34:07.540 | We are of, all living life forms have evolved

01:34:11.740 | to not want to die.

01:34:14.380 | And when I mean want, biochemically, genetically, physically.

01:34:18.180 | That yeast cell, the cells that I studied at MIT,

01:34:21.620 | they were fighting for their lives.

01:34:23.660 | They didn't think.

01:34:25.220 | But our brain has evolved the same survival aspect.

01:34:28.940 | Of course, we don't want to die.

01:34:30.340 | But the problem for us, unfortunately,

01:34:32.500 | it's a curse and a blessing, is that we're now conscious.

01:34:34.920 | We know that we're going to die.

01:34:37.140 | Most species that have ever existed don't.

01:34:40.260 | That's a burden, that's a curse.

01:34:42.260 | And so what I think's happened is we've evolved, certainly,

01:34:44.700 | to want to live for a long time, perhaps never want to die.

01:34:49.120 | But the thought about dying is so traumatic

01:34:52.120 | that there is an innate part of our brains,

01:34:55.560 | and it's probably genetically wired, to not think about it.

01:35:00.040 | I really think that's part of being human.

01:35:03.140 | Because, you know, I think about tribes

01:35:05.240 | that obsessed with longevity every day

01:35:07.800 | and that were going to die.

01:35:09.580 | They probably didn't make much technological progress

01:35:12.280 | because they were just crying in their huts every day,

01:35:14.540 | or, you know, in the savanna.

01:35:16.240 | I really think that we've evolved to naturally deny aging.

01:35:20.320 | And it's one of the problems that I face in my career,

01:35:23.180 | and, you know, when I speak publicly and on social media,

01:35:26.760 | is that it's shocking.

01:35:28.340 | People don't want to think about their age,

01:35:29.900 | but I think it's getting better.

01:35:31.720 | I think my book has helped.

01:35:33.920 | These tests that we're developing should help people

01:35:36.280 | understand it's not a problem to think about

01:35:39.080 | your long-term health.

01:35:40.320 | In fact, if you don't, you're going to reach 80

01:35:42.680 | and really regret it.

01:35:43.840 | - And the other side of it, so again, Ernest Becker,

01:35:47.740 | but also Viktor Frankl,

01:35:49.160 | I recommend a highly manned social meeting.

01:35:51.320 | Bernard Williams is a moral philosopher.

01:35:54.900 | They kind of argue that this knowledge of death,

01:35:58.600 | even if we often don't contemplate it, we do at times.

01:36:03.600 | And the very, what you call the curse,

01:36:06.960 | which I agree with you, it's a curse and a blessing

01:36:10.640 | that we're able to contemplate our own mortality.

01:36:13.880 | That gives meaning to life.

01:36:16.580 | So death gives meaning to life.

01:36:18.840 | As what Viktor Frankl argues,

01:36:21.140 | I would probably argue the same.

01:36:22.600 | There's something about the scarcity of life

01:36:25.180 | and contemplating that,

01:36:27.140 | that makes each moment that much sweeter.

01:36:30.180 | Is there something to that?

01:36:32.380 | - I think it's individual.

01:36:33.860 | In my case, it's completely wrong.

01:36:35.940 | (laughing)

01:36:38.060 | - I appreciate you saying that.

01:36:39.820 | - I don't get joy out of every day

01:36:41.860 | because I think I'm going to die.

01:36:43.780 | I get joy out of every day because every day is joyous

01:36:46.060 | and I make it that way.

01:36:47.460 | And even if I thought I was going to live forever,

01:36:50.460 | I would still be enjoying this moment just as much.

01:36:53.140 | And I bet you would too.

01:36:56.340 | - Well, that's, I think about that a lot.

01:36:59.900 | I think it's very difficult to know.

01:37:03.580 | I'm almost afraid that I wouldn't enjoy it as much

01:37:06.720 | if I was immortal.

01:37:07.980 | I'm almost afraid to want to be immortal or to live longer

01:37:11.900 | because it perhaps is a kind of justification for me

01:37:18.900 | to accept that I'm going to die.

01:37:21.700 | It's saying like, oh, if I was immortal,

01:37:23.420 | I wouldn't be able to enjoy life as much as I do.

01:37:26.160 | But it's very possible that I wouldn't enjoy it

01:37:28.300 | just as much.

01:37:29.260 | Of course, enjoying life, whether you're mortal or not,

01:37:34.220 | takes work.

01:37:35.540 | Like it requires you to have the right kind of frame

01:37:38.940 | of mind.

01:37:39.840 | You can discover, you can focus your mind

01:37:42.460 | on the ugliness of life.

01:37:44.500 | There's plenty of ugly things in this world

01:37:46.900 | and you can focus on them.

01:37:47.960 | You can complain.

01:37:49.320 | Whenever, like, you know, if it's raining outside,

01:37:53.460 | you can focus on the fact that you have shelter

01:37:56.740 | and enjoy the hell out of it.

01:37:58.460 | Or you can enjoy running in the rain when it's warm

01:38:02.020 | and like the beauty of nature, just being one with nature.

01:38:05.700 | Or you can just complain,

01:38:06.780 | this fucking weather again in Boston.

01:38:08.980 | And then we see they're always raining or freezing, damn it.

01:38:11.740 | And like the same thing with like wifi going out

01:38:16.760 | on airplanes.

01:38:18.100 | Like you can either complain about like stupid wifi

01:38:23.100 | and JetBlue or something.

01:38:25.860 | Or you could say like how incredible it is

01:38:27.620 | that I can fly through the sky

01:38:29.180 | and in a matter of hours be anywhere else in the world.

01:38:31.820 | And then I could also on occasion watch,

01:38:34.020 | like check email and even watch movies

01:38:37.540 | while connecting through satellites

01:38:39.540 | that are flying through space.

01:38:40.500 | So it's a matter of perspective.

01:38:41.860 | And perhaps there's an extra level of work required

01:38:44.980 | when you're a mortal.

01:38:46.540 | Because it's easier when you're a mortal

01:38:48.680 | or live longer to be lazy, to delay stuff.

01:38:53.000 | But if you're not,

01:38:54.100 | you can still derive the same amount of joy.

01:38:56.220 | So it's possible, it's possible.

01:38:59.060 | - It's definitely possible.

01:38:59.900 | In my life, I went from being the,

01:39:02.360 | nothing's working to every day's great to wake up to.

01:39:06.620 | And I think even if you live,

01:39:08.920 | think you're going to live forever,

01:39:10.420 | you can enjoy every day.

01:39:12.140 | What I do is everything's relative.

01:39:14.900 | We can compare ourselves to our neighbor who has more money

01:39:17.860 | or to the flight that should have had wifi.

01:39:20.440 | Or which is what I do, I'm still six years old, remember.

01:39:23.540 | What a six year old does says,

01:39:25.280 | look, I can, when I tell my fingers to form a fist,

01:39:29.900 | they actually do that.

01:39:31.260 | That's really cool.

01:39:32.660 | That's how I live my life.

01:39:34.720 | I can pick up on your desk here, this metal object.

01:39:36.800 | It's a metal cube, about an inch by an inch by an inch.

01:39:39.820 | And I tell myself not about cubes,

01:39:42.540 | but about inanimate objects.

01:39:44.880 | Probably once a day I'll say,

01:39:46.280 | I'm a living thing.

01:39:48.240 | I can think, I can move, I can eat.

01:39:49.880 | I am full of energy.

01:39:51.840 | And there's that leaf or this cube here

01:39:53.880 | that will never be alive.

01:39:55.800 | That's what I look at and compare myself to.

01:39:59.160 | And for as long as I live, if it's forever,

01:40:01.080 | of course it won't be, but even if it was forever,

01:40:04.000 | the relative to this lump of metal on this table here,

01:40:07.800 | we are wondrous things in the universe.

01:40:10.840 | And probably the most wondrous things in the universe.

01:40:13.760 | Yeah, we're able to deeply appreciate the leaf or the cube

01:40:18.680 | and deeply appreciate ourselves,

01:40:20.560 | which is, it can be a curse, but it's mostly a gift.

01:40:24.400 | Especially when you're, it's such a beautiful poem.

01:40:28.140 | Now I'm six, I'm as clever as clever.

01:40:31.680 | So I think I'll be six now forever and ever.

01:40:35.400 | That's a good thing to aspire to.

01:40:37.880 | Your grandmother was onto something.

01:40:40.640 | David, this is a incredible conversation.

01:40:43.000 | I'm a huge fan of your work.

01:40:44.640 | So thank you for wasting your valuable time with me today.

01:40:49.360 | I really, really appreciate it.

01:40:50.520 | This was awesome.

01:40:51.360 | Thank you for having me on Lex, appreciate it.

01:40:54.000 | Thanks for listening to this conversation

01:40:55.520 | with David Sinclair.

01:40:56.560 | A thank you to Onnit, Clear, National Instruments,

01:41:01.240 | Simply Safe, and Linode.

01:41:03.640 | Check them out in the description to support this podcast.

01:41:07.160 | And now let me leave you with some words

01:41:08.720 | from Arthur Schopenhauer.

01:41:10.640 | All truth passes through three stages.

01:41:13.720 | First, it is ridiculed.

01:41:15.520 | Second, it is violently opposed.

01:41:18.280 | Third, it is accepted as being self-evident.

01:41:22.320 | Thank you for listening and hope to see you next time.

01:41:25.040 | [AUDIO OUT]

01:41:28.600 | [AUDIO OUT]

01:41:31.600 | you

David Sinclair: Extending the Human Lifespan Beyond 100 Years | Lex Fridman Podcast #189

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