← Lex Fridman

Bryan Johnson: Kernel Brain-Computer Interfaces

Episode 1862021-05-24English

Guests: Bryan Johnson

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§01Transcript · 00:00–08:17

00:00The following is a conversation with Brian Johnson,

00:02founder of Kernel, a company that has developed devices

00:06that can monitor and record brain activity.

00:09And previously, he was the founder of Braintree,

00:12a mobile payment company that acquired Venmo

00:14and then was acquired by PayPal and eBay.

00:17Quick mention of our sponsors,

00:19Four Sigmatic, NetSuite, Grammarly, and ExpressVPN.

00:24Check them out in the description to support this podcast.

00:27As a side note, let me say that this was a fun

00:30and memorable experience,

00:31wearing the Kernel Flow Brain interface

00:34in the beginning of this conversation,

00:35as you can see if you watch the video version

00:38of this episode.

00:39And there was a Ubuntu Linux machine sitting next to me,

00:42collecting the data from my brain.

00:44The whole thing gave me hope that the mystery

00:47of the human mind will be unlocked in the coming decades,

00:51as we begin to measure signals from the brain

00:53in a high bandwidth way.

00:55To understand the mind, we either have to build it

00:58or to measure it.

01:00Both are worth a try.

01:02Thanks to Brian and the rest of the Kernel team

01:04for making this little demo happen.

01:06This is the Lex Friedman Podcast,

01:08and here is my conversation with Brian Johnson.

01:12- You ready, Lex?

01:14- Yes, I'm ready.

01:15- Do you guys wanna come in

01:16and put the interfaces on our heads?

01:18And then I will proceed to tell you a few jokes.

01:22So we have two incredible pieces of technology

01:25and a machine running Ubuntu 2004 in front of us.

01:30What are we doing?

01:31- All right.

01:32- Are these going on our head?

01:33- They're going on our heads, yeah.

01:34And they will place it on our heads for proper alignment.

01:39- Does this support giant heads?

01:43Because I kind of have a giant head.

01:45Is this just giant head fine?

01:46- Are you saying as like an ego,

01:48or are you saying physically both?

01:51- I'm gonna drop it on you.

01:53- It's a nice massage.

01:57- Yes.

01:57Okay, how does this feel?

02:01- It's okay to move around?

02:04- Yeah.

02:05- It feels, oh yeah.

02:07Hey, hey.

02:08(laughing)

02:10This feels awesome.

02:11- It's a pretty good fit.

02:12- Thank you.

02:13- That feels good.

02:14- So this is big head friendly.

02:17- It suits you well, Lex.

02:19- Thank you.

02:20(laughing)

02:22I feel like I need to,

02:23I feel like when I wear this,

02:25I need to sound like Sam Harris,

02:27calm, collected, eloquent.

02:31I feel smarter, actually.

02:34I don't think I've ever felt quite as much

02:36like I'm part of the future as now.

02:38- Have you ever worn a brain interface,

02:40or had your brain imaged?

02:42- Oh, never had my brain imaged.

02:44The only way I've analyzed my brain

02:47is by talking to myself and thinking.

02:52No direct data.

02:53- Yeah, that is definitely a brain interface.

02:56(laughing)

02:57That has a lot of blind spots.

02:59- It has some blind spots, yeah.

03:01Psychotherapy.

03:02- That's right.

03:03All right, are we recording?

03:07- Yep, we're good.

03:08- All right.

03:09So Lex, the objective of this,

03:12I'm going to tell you some jokes,

03:16and your objective is to not smile,

03:18which as a Russian, you should have an edge.

03:22- Make the motherland proud, I gotcha.

03:25Okay.

03:26Let's hear the jokes.

03:29- Lex, and this is from the Colonel Crew.

03:32We've been working on a device that can read your mind,

03:37and we would love to see your thoughts.

03:39- Is that the joke?

03:43- That's the opening.

03:44- Okay.

03:45- All right.

03:46- If I'm seeing the muscle activation correctly

03:52on your lips, you're not gonna do well on this.

03:54Let's see.

03:55All right, here comes the first.

03:56- I'm screwed.

03:57- Here comes the first one.

03:58- Is this gonna break the device?

03:59Is it resilient to laughter?

04:04- Lex, what goes through a potato's brain?

04:09(laughing)

04:14- I got already failed.

04:15That's the hilarious opener.

04:17Okay, what?

04:19- Tater thoughts.

04:20What kind of fish performs brain surgery?

04:26- I don't know.

04:29- A neural surgeon.

04:30- And so we're getting data of everything

04:37that's happening in my brain right now?

04:39- Lifetime, yeah.

04:39- We're getting activation patterns of your entire cortex.

04:44- I'm gonna try to do better.

04:46I'll edit out all the parts where I laughed.

04:48Photoshop a serious face over me.

04:50- You can recover.

04:51- Yeah, all right.

04:52- Lex, what do scholars eat when they're hungry?

04:57- I don't know, what?

04:58- Academia nuts.

04:59- That was a pretty good one.

05:05- So what we'll do is, so you're wearing

05:08a kernel flow, which is an interface built

05:13using technology called spectroscopy.

05:17So it's similar to what we wear wearables on the wrist

05:20using light, so using LIDAR as you know.

05:24And we're using that to image,

05:27it's a functional imaging of brain activity.

05:30And so as your neurons fire,

05:32electrically and chemically,

05:35it creates blood oxygenation levels.

05:37We're measuring that.

05:38And so you'll see in the reconstructions we do for you,

05:41you'll see your activation patterns in your brain

05:43as throughout this entire time we were wearing it.

05:45So in the reaction to the jokes

05:47and as we were sitting here talking.

05:50And so it's a, we're moving towards a real time feed

05:54of your cortical brain activity.

05:56- So there's a bunch of things that are in contact

05:59with my skull right now.

06:02How many of them are there?

06:03And so how many of them are, what are they?

06:05What are the actual sensors?

06:07- There's 52 modules and each module has one laser

06:11and six sensors.

06:13And the sensors fire in about 100 picoseconds.

06:18And then the photons scatter and absorb in your brain.

06:21And then a few go in, a bunch go in,

06:25then a few come back out and we sense those photons

06:27and then we do the reconstruction for the activity.

06:30Overall, there's about a thousand plus channels

06:33that are sampling your activity.

06:35- How difficult is it to make it as comfortable as it is?

06:38'Cause it's surprisingly uncomfortable.

06:40I would not think it would be comfortable.

06:42Something that's measuring brain activity,

06:48I would not think it would be comfortable, but it is.

06:51- I agree.

06:52- In fact, I wanna take this home.

06:52- Yeah, yeah, that's right.

06:54So people are accustomed to being in big systems like fMRI

06:59where there's 120 decibel sounds

07:02and you're in a claustrophobic encasement

07:05or EEG, which is just painful or surgery.

07:09And so, yes, I agree that this is a convenient option

07:12to be able to just put on your head.

07:14It measures your brain activity

07:15in the contextual environment you choose.

07:18So if we want to have it during a podcast

07:20or if we wanna be at home in a business setting,

07:22it's freedom to be where to record your brain activity

07:27in the setting that you choose.

07:29- Yeah, but sort of from an engineering perspective,

07:31are these, what is it?

07:32There's a bunch of different modular parts

07:34and they're kinda, there's like a rubber band thing

07:38where they mold to the shape of your head.

07:40- That's right.

07:41So we built this version of the mechanical design

07:45to accommodate most adult heads.

07:48- But I have a giant head and it fits fine.

07:51It fits well, actually.

07:53So I don't think I have an average head.

07:55Okay, maybe I feel much better about my head now.

08:01Maybe I'm more average than I thought.

08:05Okay, so what else is there,

08:08interesting that you could say while it's on our heads.

08:10I can keep this on the whole time.

08:12This is kind of awesome.

08:13And it's amazing for me as a fan of Ubuntu.

08:16I use Ubuntu Mate.

08:17You guys should use that too.

§02Transcript · 08:18–17:51

08:18But it's amazing to have code running

08:22to the side measuring stuff and collecting data.

08:26I mean, I just, I feel like much more important now

08:30that my data is being recorded.

08:32Like somebody cares,

08:33like you know when you have a good friend

08:35that listens to you,

08:36that actually is listening to you?

08:40This is what I feel like.

08:41I'm like a much better friend

08:43because it's like accurately listening to me, Ubuntu.

08:47- What a cool perspective.

08:49I hadn't thought about that, of feeling understood.

08:53- Yeah.

08:54- Heard, yeah, heard deeply by the mechanical system

08:59that is recording your brain activity

09:01versus the human that you're engaging with,

09:04that your mind immediately goes to

09:06that there's this dimensionality

09:09and depth of understanding of this software system,

09:12which you're intimately familiar with.

09:14And now you're able to communicate with this system

09:17in ways that you couldn't before.

09:19- Yeah, I feel heard.

09:20- Yeah, I mean, I guess what's interesting about this is

09:26your intuitions are spot on.

09:28Most people have intuitions about brain interfaces

09:30that they've grown up with this idea

09:32of people moving cursors on the screen

09:34or typing or changing the channel or skipping a song.

09:38It's primarily been anchored on control.

09:41And I think the more relevant understanding

09:44of brain interfaces or neuroimaging

09:47is that it's a measurement system.

09:49And once you have numbers for a given thing,

09:53a seemingly endless number of possibilities

09:54emerge around that of what to do with those numbers.

09:57- So before you tell me about the possibilities,

09:59this was an incredible experience.

10:01I can keep this on for another two hours,

10:03but I'm being told that for a bunch of reasons,

10:08just because we probably wanna keep the data small

10:11and visualize it nicely for the final product,

10:13we wanna cut this off

10:15and take this amazing helmet away from me.

10:17So Brian, thank you so much for this experience

10:21and let's continue without helmet-less.

10:25- All right.

10:26- So that was an incredible experience.

10:28Can you maybe speak to what kind of opportunities

10:31that opens up that stream of data,

10:32that rich stream of data from the brain?

10:35- First, I'm curious, what is your reaction?

10:38What comes to mind when you put that on your head?

10:41What does it mean to you and what possibilities emerge

10:44and what significance might it have?

10:46I'm curious where your orientation is at.

10:49- Well, for me, I'm really excited by the possibility

10:54of various information about my body,

10:59about my mind being converted into data

11:03such that data can be used to create products

11:06that make my life better.

11:07So that to me is a really exciting possibility.

11:09Even just like a Fitbit that measures, I don't know,

11:13some very basic measurements about your body

11:15is really cool.

11:17But the bandwidth of information,

11:20the resolution of that information is very crude,

11:22so it's not very interesting.

11:23The possibility of recording,

11:25of just building a dataset coming in a clean way

11:31and a high bandwidth way from my brain

11:33opens up all kinds of, at the very,

11:39I was kind of joking when we were talking,

11:40but it's not really, is like I feel heard

11:44in the sense that it feels like the full richness

11:49of the information coming from my mind

11:51is actually being recorded by the machine.

11:56I mean, there's a, I can't quite put it into words,

12:00but there is a genuinely for me,

12:02this is not some kind of joke about me being a robot,

12:05it just genuinely feels like I'm being heard

12:09in a way that's going to improve my life.

12:13As long as the thing that's on the other end

12:16can do something useful with that data.

12:17But even the recording itself is like,

12:20once you record, it's like taking a picture.

12:24That moment is forever saved in time.

12:28Now, a picture cannot allow you to step back

12:32into that world, but perhaps recording your brain

12:37is a much higher resolution thing,

12:41much more personal recording of that information

12:44than a picture that would allow you to step back

12:48into that, where you were in that particular moment

12:51in history and then map out a certain trajectory

12:54to tell you certain things about yourself.

12:58That could open up all kinds of applications.

13:00Of course, there's health that I consider,

13:02but honestly, to me, the exciting thing is just being heard.

13:06My state of mind, the level of focus,

13:08all those kinds of things, being heard.

13:10- What I heard you say is you have an entirety

13:13of lived experience, some of which you can communicate

13:17in words and in body language,

13:20some of which you feel internally,

13:21which cannot be captured in those communication modalities.

13:24And that this measurement system captures

13:27both the things you can try to articulate in words,

13:29maybe in a lower dimensional space,

13:31using one word, for example, to communicate focus,

13:34when it really may be represented in a 20 dimensional space

13:37of this particular kind of focus,

13:39and that this information is being captured.

13:42So it's a closer representation to the entirety

13:46of your experience captured in a dynamic fashion

13:48that is not just a static image

13:50of your conscious experience.

13:53- Yeah, that's the promise.

13:56That was the feeling, and it felt like the future.

13:59So it was a pretty cool experience.

14:00And from the sort of mechanical perspective,

14:04it was cool to have an actual device

14:06that feels pretty good,

14:08that doesn't require me to go into the lab.

14:11And also the other thing I was feeling,

14:14there's a guy named Andrew Huberman,

14:16he's a friend of mine, amazing podcast,

14:17people should listen to it, Huberman Lab Podcast.

14:21We're working on a paper together

14:24about eye movement and so on.

14:25And we're kind of, he's a neuroscientist,

14:28and I'm a data person, machine learning person.

14:30We're both excited by how much the data,

14:35measurements of the human mind, the brain,

14:43and all the different metrics that come from that

14:45can be used to understand human beings

14:48and in a rigorous scientific way.

14:50So the other thing I was thinking about

14:52is how this could be turned into a tool for science.

14:55Sort of not just personal science,

14:57not just like Fitbit style,

14:59how am I doing my personal metrics of health,

15:04but doing larger scale studies of human behavior and so on.

15:07So like data not at the scale of an individual,

15:10but data at the scale of many individuals

15:12or a large number of individuals.

15:14So personal being heard was exciting

15:17and also just for science is exciting.

15:19'Cause it's very easy.

15:21Like there's a very powerful thing to it

15:23being so easy to just put on

15:25that you could scale much easier.

15:28- If you think about that second thing you said

15:30about the science of the brain,

15:35most, we've done a pretty good job,

15:40like we, the human race has done a pretty good job

15:43figuring out how to quantify the things around us

15:46from distant stars to calories and steps and our genome.

15:51So we can measure and quantify pretty much everything

15:55in the known universe except for our minds.

15:59And we can do these one-offs

16:02if we're going to get an fMRI scan

16:03or do something with a low res EEG system,

16:08but we haven't done this at population scale.

16:11And so if you think about human thought

16:14or human cognition is probably the single law,

16:19largest raw input material into society

16:23at any given moment.

16:24It's our conversations with ourselves

16:26and with other people.

16:27And we have this raw input that we can't,

16:32haven't been able to measure yet.

16:35And if you, when I think about it through that frame,

16:38it's remarkable.

16:42It's almost like we live in this wild, wild west

16:46of unquantified communications within ourselves

16:50and between each other

16:51when everything else has been grounded.

16:53I mean, for example, I know if I buy an appliance

16:55at the store or on a website,

16:58I don't need to look at the measurements on the appliance

17:01and make sure it can fit through my door.

17:03That's an engineered system of appliance manufacturing

17:06and construction.

17:07Everyone's agreed upon engineering standards.

17:10And we don't have engineering standards around cognition.

17:15It's not a, it has not entered

17:16as a formal engineering discipline

17:19that enables us to scaffold in society

17:21with everything else we're doing,

17:23including consuming news, our relationships,

17:26politics, economics, education, all the above.

17:29And so to me, the most significant contribution

17:33that kernel technology has to offer

17:36would be the formal,

17:37the introduction of the formal engineering of cognition

17:42as it relates to everything else in society.

17:45- I love that idea that you kind of think

17:49that there is just this ocean of data

17:51that's coming from people's brains

§03Transcript · 17:53–26:08

17:53as being in a crude way, reduced down to like tweets

17:57and texts and so on.

17:58So it's a very hardcore, many scale compression

18:03of actual, the raw data.

18:06But maybe you can comment,

18:08'cause you're using the word cognition.

18:10I think the first step is to get the brain data.

18:15But is there a leap to be taken

18:19to sort of interpreting that data in terms of cognition?

18:22So is your idea is basically you need

18:24to start collecting data at scale from the brain,

18:27and then we start to really be able to take little steps

18:32along the path to actually measuring

18:35some deep sense of cognition.

18:37Because as I'm sure you know,

18:40we understand a few things,

18:43but we don't understand most of what makes up cognition.

18:47- This has been one of the most significant challenges

18:50of building kernel.

18:51And kernel wouldn't exist if I wasn't able to fund it

18:53initially by myself.

18:55Because when I engage in conversations with investors,

18:59the immediate thought is what is the killer app?

19:02And of course, I understand that heuristic.

19:04That's what they're looking at is they're looking to de-risk.

19:07Is the product solved?

19:09Is there a customer base?

19:10Are people willing to pay for it?

19:11How does it compare to competing options?

19:14And in the case with Brain Interfaces,

19:15when I started the company,

19:17there was no known path to even build a technology

19:21that could potentially become mainstream.

19:24And then once we figured out the technology,

19:26we could commence having conversations with investors

19:29and it became what is the killer app?

19:31And so what has been...

19:33So I funded the first $53 million for the company

19:36and to raise the round of funding,

19:38the first one we did, I spoke to 228 investors.

19:42One said, yes.

19:43It was remarkable.

19:45And it was mostly around this concept

19:48around what is a killer app.

19:49And so internally, the way we think about it

19:51is we think of the go-to-market strategy

19:55much more like the Drake equation,

19:57where if we can build technology

20:00that has the characteristics of,

20:02it has the data quality is high enough,

20:05it meets some certain threshold,

20:07cost, accessibility, comfort,

20:11it can be worn in contextual environments.

20:12If it meets the criteria of being a mass market device,

20:17then the responsibility that we have

20:21is to figure out how to create the algorithm

20:24that enables the human...

20:27To enable humans to then find value with it.

20:32So the analogy is like brain interfaces

20:34are like early nineties of the internet.

20:37Is you wanna populate an ecosystem

20:39with a certain number of devices,

20:40you want a certain number of people

20:41who play around with them,

20:42who do experiments of certain data collection parameters,

20:44you want to encourage certain mistakes

20:46from experts and non-experts.

20:48These are all critical elements that ignite discovery.

20:51And so we believe we've accomplished

20:56the first objective of building technology

20:59that reaches those thresholds.

21:01And now it's the Drake equation component

21:03of how do we try to generate 20 years of value discovery

21:08in a two or three year time period?

21:12How do we compress that?

21:14- So just to clarify,

21:15so when you mean the Drake equation,

21:17which for people who don't know,

21:19I don't know why you...

21:19If you listen to this,

21:20I bring up aliens every single conversation.

21:22So I don't know how you wouldn't know

21:23what the Drake equation is,

21:25but you mean like the killer app,

21:28it would be one alien civilization in that equation.

21:31So meaning like this is in search of an application

21:34that's impactful and transformative.

21:36By the way, it should be...

21:37We need to come up with a better term than killer app.

21:40- It's also violent, right?

21:43- Very violent.

21:44You can go like viral app.

21:45That's horrible too, right?

21:46It's some very inspiringly impactful application.

21:51How about that?

21:52No. - Yeah.

21:53- Okay, so let's stick with killer app.

21:54That's fine.

21:55Nobody's--

21:56- But I concur with you.

21:57I dislike the chosen words in capturing the concept.

22:02- You know, it's one of those sticky things

22:03that is effective to use in the tech world,

22:08but when you now become a communicator

22:11outside of the tech world,

22:12especially when you're talking about software

22:14and hardware and artificial intelligence applications,

22:17it sounds horrible.

22:18- Yeah, no, it's interesting.

22:19I actually regret now having called attention

22:21to this, I regret having used that word

22:23in this conversation

22:24because it's something I would not normally do.

22:26I used it in order to create a bridge

22:29of shared understanding of how others would,

22:31what terminology others would use.

22:32- Yeah.

22:33- But yeah, I concur.

22:34- Let's go with impactful application.

22:38- Or just value creation.

22:40- Value creation.

22:41Something people love using.

22:43- There we go.

22:44- That's it.

22:45- Love app.

22:46Okay, so what, do you have any ideas?

22:49So you're basically creating a framework

22:51where there's the possibility of a discovery

22:54of an application that people love using.

22:57Is, do you have ideas?

22:59- We've began to play a fun game internally

23:01where when we have these discussions,

23:03we begin circling around this concept of,

23:06does anybody have an idea?

23:10Does anyone have intuitions?

23:11And if we see the conversation starting

23:13to veer in that direction,

23:15we flag it and say, human intuition alert, stop it.

23:20And so we really want to focus on the algorithm

23:23of there's a natural process of human discovery

23:26that when you populate a system with devices

23:30and you give people the opportunity to play around with it

23:33in expected and unexpected ways,

23:35we are thinking that is a much better system of discovery

23:40than us exercising intuitions.

23:41And it's interesting,

23:42we're also seeing a few neuroscientists

23:43who have been talking to us

23:45where I was speaking to this one young associate professor

23:49and I approached a conversation and said,

23:50hey, we have these five data streams that we're pulling off.

23:54When you hear that,

23:57what weighted value do you add to each data source?

23:59Like which one do you think is gonna be valuable

24:00for your objectives and which one's not?

24:03And he said, I don't care, just give me the data.

24:05All I care about is my machine learning model.

24:08But importantly, he did not have a theory of mind.

24:10He did not come to the table and say,

24:12I think the brain operates in this way

24:15and these reasons or have these functions.

24:16He didn't care.

24:17He just wanted the data.

24:19And we're seeing that more and more

24:20that certain people are devaluing human intuitions

24:25for good reasons,

24:27as we've seen in machine learning

24:28over the past couple of years.

24:30And we're doing the same

24:31in our value creation market strategy.

24:35- So collect more data, clean data,

24:40make the product such that the collection of data

24:42is easy and fun,

24:46and then the rest will just spring to life

24:50through humans playing around with it.

24:52- Our objective is to create the most valuable

24:56data collection system of the brain ever.

25:01And with that, then applying all the best tools

25:07of machine learning and other techniques

25:11to extract out, to try to find insight.

25:15But yes, our objective is really to systematize

25:18the discovery process,

25:19because we can't put definite timeframes on discovery.

25:24The brain is complicated

25:26and science is not a business strategy.

25:30And so we really need to figure out how to...

25:32This is the difficulty of bringing

25:35technology like this to market.

25:36That's why most of the time it just languishes

25:40in academia for quite some time.

25:42But we hope that we will cross over

25:46and make this mainstream in the coming years.

25:48- The thing was cool to wear,

25:50but are you chasing a good reason

25:54for millions of people to put this on their head

25:58and keep on their head regularly?

26:00Is there...

26:01Like who's going to discover that reason?

26:04Is it going to be people just kind of organically,

26:08or is there going to be a Angry Birds style application

§04Transcript · 26:12–35:00

26:12that's just too exciting to not use?

26:17- If I think through the things

26:19that have changed my life most significantly

26:22over the past few years,

26:23when I started wearing a wearable on my wrist

26:27that would give me data about my heart rate,

26:29heart rate variability, respiration rate,

26:33metabolic approximations, et cetera.

26:36For the first time in my life,

26:38I had access to information, sleep patterns,

26:41that were highly impactful.

26:43They told me, for example, if I eat close to bedtime,

26:48I'm not going to get deep sleep.

26:50And not getting deep sleep means

26:52you have all these follow-on consequences in life.

26:54And so it opened up this window of understanding of myself

26:59that I cannot self-introspect and deduce these things.

27:03This is information that was available to be acquired,

27:06but it just wasn't.

27:07I would have to get an expensive sleep study,

27:08then it's an end, like one night,

27:10and that's not good enough to run all my trials.

27:12And so if you look just at the information

27:15that one can acquire on their wrist,

27:17and now you're applying it to the entire cortex on the brain,

27:21and you say, what kind of information could we acquire?

27:25It opens up a whole new universe of possibilities.

27:28For example, we did this internal study at Kernel

27:30where I wore a prototype device,

27:32and we were measuring the cognitive effects of sleep.

27:36So I had a device measuring my sleep.

27:38I performed with 13 of my coworkers,

27:41we performed four cognitive tasks over 13 sessions.

27:45And we focused on reaction time, impulse control,

27:48short-term memory, and then a resting state task.

27:52And with mine, we found, for example,

27:55that my impulse control

27:57was independently correlated with my sleep

28:01outside of behavioral measures

28:02of my ability to play the game.

28:04The point of the study was I had,

28:07the brain study I did at Kernel

28:09confirmed my life experience.

28:12That if I, my deep sleep determined

28:17whether or not I would be able to resist temptation

28:20the following day.

28:21And my brain did show that as one example.

28:24And so if you start thinking,

28:25if you actually have data on yourself,

28:27on your entire cortex, you can control the settings,

28:30I think there's probably a large number of things

28:36that we could discover about ourselves.

28:37Very, very small and very, very big.

28:39I just, for example, like when you read news,

28:42what's going on?

28:44- Like when you use social media, when you use news,

28:47like all the ways we allocate attention.

28:51- That's right. - With a computer.

28:52I mean, that seems like a compelling place

28:54to where you would want to put on a Kernel.

28:58By the way, what is it called?

28:59Kernel flux, Kernel, like what?

29:00- Flow. - Flow.

29:02- Two technologies, you wore flow.

29:04- Flow, okay.

29:05So when you put on the Kernel Flow,

29:08it is, seems like to be a compelling time

29:15and place to do it is when you're behind a desk,

29:17behind a computer.

29:18'Cause you could probably wear it

29:19for prolonged periods of time

29:21as you're taking in content.

29:23And there could, a lot of,

29:25because some of our, so much of our lives

29:27happens in the digital world now.

29:29That kind of coupling the information

29:32about the human mind with the consumption

29:36and the behaviors in the digital world

29:39might give us a lot of information

29:40about the effects of the way we behave

29:43and navigate the digital world

29:45to the actual physical meat, space, effects on our body.

29:50It's interesting to think,

29:51so in terms of both like for work,

29:53I'm a big fan of, so Cal Newport,

29:57his ideas of deep work that I spend,

30:01with few exceptions, I try to spend

30:05the first two hours of every day,

30:07usually if I'm like at home

30:09and have nothing on my schedule,

30:11is going to be up to eight hours of deep work,

30:15of focus, zero distraction.

30:16And for me to analyze the,

30:18I mean I'm very aware of the waning of that,

30:22the ups and downs of that.

30:24And it's almost like you're surfing

30:27the ups and downs of that as you're doing programming,

30:29as you're doing thinking about particular problems,

30:32you're trying to visualize things in your mind,

30:34you start trying to stitch them together.

30:37You're trying to, when there's a dead end

30:40about an idea, you have to kind of calmly

30:43like walk back and start again,

30:45all those kinds of processes.

30:47It'd be interesting to get data

30:49on what my mind is actually doing.

30:51And also recently started doing,

30:53I just talked to Sam Harris a few days ago

30:55and been building up to that.

30:58I started using, started meditating using his app,

31:01waking up, very much recommend it.

31:05And be interested to get data on that.

31:07'Cause it's, you're very, it's like,

31:09you're removing all the noise from your head,

31:12and you're very much, it's an active process of,

31:15active noise removal, active noise canceling,

31:19like the headphones.

31:21And it'd be interesting to see what is going on in the mind

31:24before the meditation, during it, and after,

31:28all those kinds of things.

31:29- And in all of your examples, it's interesting that

31:32everyone who's designed an experience for you,

31:35so whether it be the meditation app or the deep work,

31:38or all the things you mentioned,

31:40they constructed this product

31:43with a certain number of knowns.

31:45- Yeah.

31:47- Now, what if we expanded the number of knowns by 10X,

31:50or 20X, or 30X?

31:51They would reconstruct their product,

31:54co-incorporate those knowns.

31:55So it'd be, and so this is the dimensionality

31:58that I think is the promising aspect,

32:00is that people will be able to use this quantification,

32:04use this information to build more effective products.

32:09And this is, I'm not talking about better products

32:11to advertise to you or manipulate you.

32:13I'm talking about our focus is helping people,

32:17individuals, have this contextual awareness

32:20and this quantification, and then to engage with others

32:23who are seeking to improve people's lives.

32:26That the objective is betterment across ourselves,

32:31individually and also with each other.

32:33- Yeah, so it's a nice data stream to have

32:35if you're building an app.

32:36Like if you're building a podcast listening app,

32:38it would be nice to know data about the listener

32:40so that if you're bored or you fell asleep,

32:42maybe pause the podcast.

32:44It's like really dumb, just very simple applications

32:48that could just improve the quality of the experience

32:50of using the app.

32:51- I'm imagining if you have your neuron, this is Lex,

32:56and there's a statistical representation of you,

32:59and you engage with the app, and it says,

33:02"Lex, your best to engage with this meditation exercise

33:07"in the following settings.

33:10"At this time of day, after eating this kind of food

33:13"or not eating, fasting, with this level of blood glucose

33:17"and this kind of night's sleep."

33:19But all these data combined to give you

33:23this contextually relevant experience,

33:26just like we do with our sleep.

33:27You've optimized your entire life

33:29based upon what information you can acquire

33:32and know about yourself.

33:33And so the question is, how much do we really know

33:37of the things going around us?

33:38And I would venture to guess in my life experience,

33:41my self-awareness captures an extremely small percent

33:46of the things that actually influence

33:47my conscious and unconscious experience.

33:50- Well, in some sense, the data would help encourage you

33:54to be more self-aware,

33:55not just because you trust everything the data is saying,

33:58but it'll give you a prod to start investigating.

34:04Like I would love to get a rating,

34:08like a ranking of all the things I do

34:11and what are the things,

34:12it's probably important to do without the data,

34:14but the data will certainly help.

34:16It's like rank all the things you do in life

34:19and which ones make you feel shitty,

34:21which ones make you feel good.

34:23Like you're talking about evening, Brian.

34:26It's a good example of somebody like,

34:30I do pig out at night as well.

34:32(Lex laughs)

34:33And it never makes me feel good.

34:35- Lex, you're in a safe space.

34:37- This is a safe space. - You're in a safe space.

34:39Let's hear it.

34:40- No, I definitely have much less self-control at night

34:43and it's interesting.

34:44And the same, people might criticize this,

34:47but I know my own body.

34:49I know when I eat carnivore, just eat meat,

34:52I feel much better

34:54than if I eat more carbs.

35:00The more carbs I eat, the worse I feel.

§05Transcript · 35:02–43:40

35:02I don't know why that is.

35:04There is science supporting it,

35:05but I'm not leaning on science.

35:06I'm leaning on personal experience.

35:07And that's really important.

35:09I don't need to read,

35:11I'm not gonna go on a whole rant about nutrition science,

35:13but many of those studies are very flawed.

35:17They're doing their best,

35:18but nutrition science is a very difficult field of study

35:21because humans are so different

35:24and the mind has so much impact

35:26on the way your body behaves.

35:28And it's so difficult from a scientific perspective

35:30to conduct really strong studies

35:32that you have to be almost like a scientist of one.

35:36You have to do these studies on yourself.

35:39That's the best way to understand what works for you or not.

35:41And I don't understand why, 'cause it sounds unhealthy,

35:44but eating only meat always makes me feel good.

35:47Just eat meat, that's it.

35:49And I don't have any allergies, any of that kind of stuff.

35:52I'm not full like Jordan Peterson,

35:54where if he deviates a little bit from the carnivore diet,

36:01he goes off like the cliff.

36:03No, I can have like chalk.

36:04I can go off the diet, I feel fine.

36:07It's a gradual worsening of how I feel.

36:12But when I eat only meat, I feel great.

36:17And it'd be nice to be reminded of that.

36:19Like it's a very simple fact

36:20that I feel good when I eat carnivore.

36:24And I think that repeats itself in all kinds of experiences.

36:27Like I feel really good when I exercise.

36:32Not I hate exercise, okay.

36:37But in the rest of the day,

36:39the impact it has on my mind and the clarity of mind

36:43and the experiences and the happiness

36:45and all those kinds of things, I feel really good.

36:48And to be able to concretely express that through data

36:52would be nice.

36:53It would be a nice reminder, almost like a statement.

36:55Like remember what feels good and what not.

36:58And there could be things like that I'm not,

37:02many things like you're suggesting

37:04that I could not be aware of.

37:07They might be sitting right in front of me

37:09that make me feel really good and make me feel not good.

37:12And the data would show that.

37:14- I agree with you.

37:14I've actually employed the same strategy.

37:17I fired my mind entirely

37:20from being responsible for constructing my diet.

37:23And so I started doing a program

37:24where I now track over 200 biomarkers every 90 days.

37:28And it captures, of course,

37:30the things you would expect like cholesterol,

37:32but also DNA methylation

37:34and all kinds of things about my body,

37:37all the processes that make up me.

37:39And then I let that data generate the shopping list.

37:42And so I never actually ask my mind what it wants.

37:45It's entirely what my body is reporting that it wants.

37:48And so I call this goal alignment with M. Brian.

37:51And there's 200 plus actors

37:53that I'm currently asking their opinion of.

37:55And so I'm asking my liver, how are you doing?

37:57And it's expressing via the biomarkers.

38:00And so then I construct that diet

38:02and I only eat those foods until my next testing round.

38:06And that has changed my life more than I think anything else

38:10because in the demotion of my conscious mind

38:15that I gave primacy to my entire life,

38:17it led me astray because like you were saying,

38:20the mind then goes out into the world

38:22and it navigates the dozens of different dietary regimens

38:27people put together in books.

38:29And it all has their supporting science

38:32in certain contextual settings, but it's not N of one.

38:35And like you're saying, this dietary really is an N of one.

38:39What people have published scientifically, of course,

38:41can be used for nice groundings,

38:46but it changes when you get to an N of one level.

38:48And so that's what gets me excited about brain interfaces

38:51is if I could do the same thing for my brain

38:54where I can stop asking my conscious mind for its advice

38:57or for its decision-making, which is flawed.

39:01And I'd rather just look at this data.

39:03And I've never had better health markers in my life

39:05than when I stopped actually asking myself

39:08to be in charge of it.

39:09- The idea of demotion of the conscious mind

39:13is such a sort of engineering way of phrasing

39:19like meditation with the-

39:20(laughs)

39:21- I mean, that's what we're doing, right?

39:22- Yeah, yeah, that's beautiful.

39:23That means really beautifully put.

39:26By the way, testing round, what does that look like?

39:28What's that?

39:29Well, you mentioned-

39:31- Yeah, the tests I do?

39:33- Yes.

39:34- So includes a complete blood panel.

39:37I do a microbiome test.

39:39I do a food inflammation, a diet-induced inflammation.

39:43So I look for exotokine expressions.

39:45So foods that produce inflammatory reactions.

39:48I look at my neuroendocrine systems.

39:50I look at all my neurotransmitters.

39:52I do, yeah, there's several micronutrient tests

39:57to see how I'm looking at the various nutrients.

39:59- What about like self-report of like how you feel?

40:04You know, almost like,

40:05you can't demote your,

40:09you still exist within your conscious mind, right?

40:12So that lived experience is of a lot of value.

40:16So how do you measure that?

40:17- I do a temporal sampling over some duration of time.

40:20So I'll think through how I feel over a week,

40:23over a month, over three months.

40:25I don't do a temporal sampling of

40:27if I'm at the grocery store in front of a cereal box

40:29and be like, you know what?

40:30Captain Crunch is probably the right thing for me today

40:33'cause I'm feeling like I need a little fun in my life.

40:36And so it's a temporal sampling.

40:37If the data set's large enough,

40:38then I smooth out the function of my natural oscillations

40:42of how I feel about life,

40:43where some days I may feel upset

40:45or depressed or down or whatever.

40:47And I don't want those moments

40:48to then rule my decision-making.

40:50That's why the demotion happens.

40:52And it says, really,

40:53if you're looking at health over a 90-day period of time,

40:56all my 200 voices speak up on that interval.

41:00And they're all given voice to say,

41:02this is how I'm doing and this is what I want.

41:04And so it really is an accounting system for everybody.

41:07So that's why I think that

41:09if you think about the future of being human,

41:13there's two things I think that are really going on.

41:17One is the design, manufacturing,

41:20and distribution of intelligence

41:21is heading towards zero, kind of cost curve,

41:25over a certain design, over a certain timeframe.

41:30But our ability to, you know,

41:31evolution produced us an intelligent,

41:34a form of intelligence.

41:35We are now designing our own intelligence systems.

41:38And the design, manufacturing,

41:39and distribution of that intelligence

41:40over a certain timeframe

41:42is gonna go to a cost of zero.

41:45- Design, manufacturing, distribution of intelligent

41:48costs is going to zero.

41:49- For example-- - Again,

41:51just give me a second.

41:52That's brilliant, okay.

41:54And evolution is doing the design, manufacturing,

41:58distribution of intelligence.

41:59And now we are doing the design, manufacturing,

42:02distribution of intelligence.

42:04And the cost of that is going to zero.

42:06That's a very nice way of looking at life on Earth.

42:10- So if that, that's going on.

42:12And then now in parallel to that,

42:14then you say, okay, what then happens

42:19if when that cost curve is heading to zero,

42:23our existence becomes a goal alignment problem,

42:28a goal alignment function.

42:31And so the same thing I'm doing

42:33where I'm doing goal alignment within myself

42:34of these 200 biomarkers, where I'm saying,

42:37when Brian exists on a daily basis

42:41and this entity is deciding what to eat

42:43and what to do and et cetera,

42:45it's not just my conscious mind, which is opining,

42:47it's 200 biological processes.

42:50And there's a whole bunch of more voices involved.

42:52So in that equation,

42:55we're going to increasingly automate

43:00the things that we spend high energy on today

43:03'cause it's easier.

43:05And now we're going to then negotiate

43:08the terms and conditions of intelligent life.

43:11Now we say conscious existence because we're biased

43:13because that's what we have,

43:15but it will be the largest computational exercise in history

43:18'cause you're now doing goal alignment with planet Earth,

43:22within yourself, with each other,

43:24within all the intelligent agents we're building,

43:26bots and other voice assistants.

43:29You basically have a trillions and trillions of agents

43:32working on the negotiation of goal alignment.

43:35- Yeah, this is in fact true.

43:39And what was the second thing?

43:40- That was it.

§06Transcript · 43:41–53:15

43:41So the cost, the design, manufacturing,

43:43distribution of intelligence going to zero,

43:45which then means what's really going on?

43:48What are we really doing?

43:50We're negotiating the terms and conditions of existence.

43:55- Do you worry about the survival of this process?

43:59That life as we know it on Earth comes to an end

44:04or at least intelligent life,

44:06that as the cost goes to zero,

44:09something happens where all of that intelligence

44:13is thrown in the trash by something like nuclear war

44:17or development of AGI systems that are very dumb.

44:20Not AGI, I guess, but AI systems, the paperclip thing,

44:25en masse is dumb but has unintended consequences

44:28to where it destroys human civilization.

44:31Do you worry about those kinds of things?

44:32- I mean, it's unsurprising that a new thing comes into

44:38this sphere of human consciousness.

44:41Humans identify the foreign object,

44:43in this case, artificial intelligence.

44:45Our amygdala fires up and says, "Scary, foreign.

44:49"We should be apprehensive about this."

44:53And so it makes sense from a biological perspective

44:57that humans, the knee jerk reaction is fear.

45:00What I don't think has been properly weighted with that

45:08is that we are the first generation

45:12of intelligent beings on this Earth

45:15that has been able to look out over their expected lifetime

45:18and see there is a real possibility of evolving

45:23into entirely novel forms of consciousness.

45:25So different that it would be totally unrecognizable

45:32to us today.

45:33We don't have words for it.

45:34We can't hint at it.

45:35We can't point at it.

45:35We can't, you can't look in the sky and see that.

45:38Thing that is shining, we're gonna go up there.

45:40You cannot even create an aspirational statement about it.

45:45And instead, we've had this knee jerk reaction of fear

45:51about everything that could go wrong.

45:53But in my estimation, this should be the defining aspiration

45:58of all intelligent life on Earth that we would aspire.

46:04That basically every generation surveys the landscape

46:08of possibilities that are afforded,

46:09given the technological, cultural

46:11and other contextual situation that they're in.

46:14We're in this context.

46:16We haven't yet identified this and said,

46:18this is unbelievable.

46:21We should carefully think this thing through,

46:24not just of mitigating the things that'll wipe us out,

46:27but like we have this potential.

46:29And so we just haven't given a voice to it,

46:31even though it's within this realm of possibilities.

46:33- So you're excited about the possibility

46:35of superintelligent systems

46:37and what the opportunities that bring.

46:39I mean, there's parallels to this.

46:41You think about people before the internet,

46:44as the internet was coming to life,

46:46I mean, there's kind of a fog through which you can't see.

46:51What does the future look like?

46:52Predicting collective intelligence,

46:56which I don't think we're understanding

46:57that we're living through that now,

46:59is that there's now, we've in some sense,

47:03stopped being individual intelligences

47:05and become much more like collective intelligences,

47:09because ideas travel much, much faster now.

47:13And they can, in a viral way,

47:16like sweep across the population.

47:18And so it's almost, I mean, it almost feels like

47:23a thought is had by many people now,

47:26thousands or millions of people,

47:27as opposed to an individual person.

47:29And that's changed everything.

47:30But to me, I don't think we're realizing

47:33how much that actually changed people or societies.

47:36But to predict that before the internet

47:38would have been very difficult.

47:41And in that same way, we're sitting here

47:43with the fog before us, thinking,

47:45what is superintelligence systems,

47:49how is that going to change the world?

47:51What is increasing the bandwidth,

47:54like plugging our brains into this whole thing,

47:59how is that going to change the world?

48:01And it seems like it's a fog, you don't know.

48:05And it could be, it could,

48:09whatever comes to be could destroy the world.

48:12We could be the last generation.

48:14But it also could transform in ways that creates

48:18an incredibly fulfilling life experience

48:24that's unlike anything we've ever experienced.

48:27It might involve dissolution of ego and consciousness

48:30and so on, you're no longer one individual.

48:32It might be more, that might be a certain kind of death,

48:37an ego death.

48:38But the experience might be really exciting and enriching.

48:42Maybe we'll live in a virtual,

48:44like it's funny to think about

48:47a bunch of sort of hypothetical questions of,

48:50would it be more fulfilling to live in a virtual world?

48:55Like if you were able to plug your brain in

48:59in a very dense way into a video game,

49:02like which world would you want to live in?

49:05In the video game or in the physical world?

49:08For most of us, we kind of,

49:11toying with the idea of the video game,

49:14but we still want to live in the physical world,

49:16have friendships and relationships in the physical world.

49:20But we don't know that.

49:21Again, it's a fog.

49:23And maybe in 100 years,

49:25we're all living inside a video game,

49:27hopefully not "Call of Duty."

49:29Hopefully more like "Sims 5."

49:31Which version is it on?

49:33For you individually though,

49:36does it make you sad that your brain ends?

49:39That you die one day very soon?

49:44That the whole thing,

49:46that data source just goes offline

49:50sooner than you would like?

49:53- That's a complicated question.

49:56I would have answered it differently.

49:59In different times in my life,

50:00I had chronic depression for 10 years.

50:03And so in that 10 year time period,

50:06I desperately wanted lights to be off.

50:09And the thing that made it even worse is,

50:12I was in a religious,

50:13I was born into a religion.

50:15It was the only reality I ever understood.

50:18It's difficult to articulate to people

50:20when you're born into that kind of reality,

50:22and it's the only reality you're exposed to,

50:24you are literally blinded

50:26to the existence of other realities,

50:28because it's so much the in-group, out-group thing.

50:31And so in that situation,

50:33it was not only that I desperately wanted lights out forever,

50:37it was that I couldn't have lights out forever.

50:38It was that there was an afterlife.

50:40And this afterlife had this system

50:45that would either penalize or reward you for your behaviors.

50:50And so it was almost like this indescribable hopelessness

50:57of not only being in hopeless despair

51:01of not wanting to exist,

51:02but then also being forced to exist.

51:05And so there was a duration of my time,

51:06of a duration of life where I'd say,

51:08like, yes, I have no remorse for lights being out,

51:13and actually wanted more than anything in the entire world.

51:16There are other times where I'm looking out at the future

51:21and I say, this is an opportunity for future,

51:25evolving human conscious experience

51:27that is beyond my ability to understand.

51:31And I jump out of bed and I race to work

51:34and I can't think about anything else.

51:37But I think the reality for me is,

51:42I don't know what it's like to be in your head,

51:45but in my head, when I wake up in the morning,

51:48I don't say, good morning, Brian, I'm so happy to see you.

51:52Like, I'm sure you're just gonna be beautiful to me today.

51:55You're not gonna make a huge long list

51:57of everything you should be anxious about.

51:59You're not gonna repeat that list to me 400 times.

52:01You're not gonna have me relive

52:03all the regrets I've made in life.

52:04I'm sure you're not doing any of that.

52:06You're just gonna just help me along all day long.

52:08I mean, it's a brutal environment in my brain.

52:11And we've just become normalized to this environment

52:15that we just accept that this is what it means to be human.

52:18But if we look at it,

52:20if we try to muster as much soberness as we can

52:24about the realities of being human, it's brutal.

52:27If it is for me.

52:28And so, am I sad that the brain may be off one day?

52:33It depends on the contextual setting.

52:38Like, how am I feeling?

52:39At what moment are you asking me that?

52:40And my mind is so fickle.

52:42And this is why, again, I don't trust my conscious mind.

52:45I have been given realities.

52:47I was given a religious reality

52:50that was a video game.

52:51And then I figured out it was not a real reality.

52:54And then I lived in a depressive reality,

52:56which delivered this terrible hopelessness.

52:59That wasn't a real reality.

53:00Then I discovered behavioral psychology,

53:03and I figured out how biased,

53:04188 chronicle biases,

53:06and how my brain is distorting reality all the time.

53:08I have gone from one reality to another.

53:11I don't trust reality.

53:13I don't trust realities that are given to me.

53:15And so, to try to make a decision on what I value

§07Transcript · 53:18–1:02:12

53:18or not value that future state,

53:20I don't trust my response.

53:22- So, not fully listening to the conscious mind

53:27at any one moment as the ultimate truth,

53:31but allowing you to go up and down as it does,

53:33and just kind of being observing it.

53:35- Yes, I assume that whatever my conscious mind

53:38delivers up to my awareness is wrong,

53:41on pond landing.

53:43And I just need to figure out where it's wrong,

53:45how it's wrong, how wrong it is,

53:46and then try to correct for it as best I can.

53:49But I assume that on impact,

53:52it's mistaken in some critical ways.

53:55- Is there something you can say by way of advice

53:58when the mind is depressive,

54:00when the conscious mind serves up something that,

54:03you know, dark thoughts,

54:07how you deal with that,

54:08like how in your own life you've overcome that,

54:11and others who are experienced in that can overcome it?

54:14- Two things.

54:16One, those depressive states

54:20are biochemical states.

54:25It's not you.

54:27And the suggestions that these things,

54:31that this state delivers to you

54:33about suggestion of the hopelessness of life,

54:35or the meaninglessness of it,

54:37or that you should hit the eject button,

54:41that's a false reality.

54:44- Yeah.

54:45- And that it's when I completely understand

54:50the rational decision to commit suicide.

54:52It is not lost on me at all

54:55that that is an irrational situation,

54:57but the key is when you're in that situation

54:59and those thoughts are landing,

55:01to be able to say, "Thank you, you're not real.

55:04I know you're not real."

55:07- Yeah.

55:08- And so I'm in a situation where for whatever reason

55:10I'm having this neurochemical state,

55:13but that state can be altered.

55:16And so again, it goes back to the realities

55:18of the difficulties of being human.

55:21And when I was trying to solve my depression,

55:22I tried literally, if you name it,

55:25I tried it systematically and nothing would fix it.

55:29And so this is what gives me hope with brain interfaces.

55:32For example, could I have numbers on my brain?

55:35Can I see what's going on?

55:36Because I go to the doctor and it's like,

55:38"How do you feel?"

55:39"I don't know, terrible."

55:41Like on a scale from one to 10,

55:42how bad do you want to commit suicide?

55:4310.

55:44(laughing)

55:45You're like, "Okay."

55:45- Yeah, at this moment.

55:47- Here's his bottle.

55:48How much should I take?

55:49"Well, I don't know."

55:50Like just.

55:51- Yeah, it's very, very crude.

55:52And this data opens up the,

55:55yeah, it opens up the possibility of really helping

56:00in those dark moments to first understand

56:03the ways, the ups and downs of those dark moments.

56:06On the complete flip side of that,

56:11I am very conscious in my own brain

56:14and deeply, deeply grateful that,

56:18it's almost like a chemistry thing, a biochemistry thing,

56:23that I go many times throughout the day,

56:26I'll look at like this cup and I'll be overcome with joy

56:31how amazing it is to be alive.

56:34Like I actually think my biochemistry is such

56:37that it's not as common.

56:40Like I've talked to people

56:42and I don't think that's that common.

56:44Like it's, and it's not a rational thing at all.

56:48It's like, I feel like I'm on drugs

56:51and I'll just be like, "Whoa."

56:54And a lot of people talk about like

56:56the meditative experience will allow you to sort of,

56:59you know, look at some basic things

57:01like the movement of your hand as deeply joyful

57:04because it's like, that's life.

57:06But I get that from just looking at a cup.

57:08Like I'm waiting for the coffee to brew

57:10and I'll just be like, "Fuck, life is awesome."

57:15And I'll sometimes tweet that,

57:16but then I'll like regret it later.

57:17Like, "God damn it, you're so ridiculous."

57:20But yeah, so, but that is purely chemistry.

57:24There's no rational, it doesn't fit with the rest of my life.

57:28I have all this shit, I'm always late to stuff.

57:30I'm always like, there's all this stuff,

57:32you know, I'm super self-critical,

57:34like really self-critical about everything I do.

57:37To the point I almost hate everything I do.

57:39But there's this engine of joy for life outside of all that.

57:43And that has to be chemistry.

57:45And the flip side of that is what depression probably is,

57:48is the opposite of that feeling of like,

57:53'cause I bet you that feeling of the cup being amazing

57:57would save anybody in a state of depression.

58:01Like that would be like fresh,

58:02you're in a desert and it's a drink of water.

58:07Shit, man, the brain is a,

58:09it would be nice to understand where that's coming from.

58:13To be able to understand how you hit those lows

58:18and those highs that have nothing to do

58:20with the actual reality.

58:21It has to do with some very specific aspects

58:24of how you maybe see the world.

58:27Maybe it could be just like basic habits that you engage in

58:31and then how to walk along the line

58:32to find those experiences of joy.

58:35- And this goes back to the discussion we're having

58:37of human cognition is in volume,

58:41the largest input of raw material into society.

58:45- Yeah.

58:46- And it's not quantified.

58:47We have no bearings on it.

58:50And so we just, you wonder,

58:53we both articulated some of the challenges

58:56we have in our own mind.

58:57And it's likely that others would say,

59:02I have something similar.

59:03And you wonder when you look at society,

59:05how does that contribute to all the other

59:10compound or problems that we're experiencing?

59:12How does that blind us to the opportunities

59:16we could be looking at?

59:18And so it really, it has this potential

59:21distortion effect on reality

59:25that just makes everything worse.

59:27And I hope if we can put some,

59:30if we can assign some numbers to these things

59:34just to get our bearings,

59:36so we're aware of what's going on,

59:38if we could find greater stabilization

59:40in how we conduct our lives and how we build society,

59:42it might be the thing that enables us to scaffold.

59:49'Cause we've really, again, we've done,

59:52humans have done a fantastic job

59:53systematically scaffolding technology

59:58and science and institutions.

60:00It's human, it's our own selves,

60:02which we have not been able to scaffold.

60:05We are the one part of this intelligence infrastructure

60:08that remains unchanged.

60:09- Is there something you could say about

60:14coupling this brain data with

60:18not just the basic human experience,

60:19but say an experience, you mentioned sleep,

60:22but the wildest experience, which is psychedelics.

60:27And there's been quite a few studies now

60:29that are being approved and run,

60:33which is exciting from a scientific perspective

60:36on psychedelics.

60:38Do you think, what do you think happens

60:40to the brain on psychedelics?

60:42And how can data about this help us understand it?

60:47And when you're on DMT, do you see elves?

60:50And can we convert that into data?

60:54- Can you add aliens in there?

60:56- Yeah, aliens, definitely.

60:57Do you actually meet aliens?

60:58And elves, are elves the aliens?

61:00I'm asking for a few Austin friends yet

61:04that are convinced that they've actually met the elves.

61:08- What are elves like?

61:09Are they friendly?

61:11Are they helpful?

61:11- I haven't met them personally.

61:12- Are they like the Smurfs,

61:13so like they're industrious

61:15and they have different skill sets and...

61:17- Yeah, I think they're very critical as friends.

61:25- They're trolls, the elves are trolls.

61:27- No, but they care about you.

61:30So there's a bunch of different version of trolls.

61:33There's loving trolls that are harsh on you,

61:37but they want you to be better.

61:38And there's trolls that just enjoy your destruction.

61:42And I think they're the ones that care for you.

61:45I think they're a criticism.

61:47See, I haven't met them directly.

61:49It's like a friend of a friend.

61:51- Yeah, they're via my telephone.

61:53- Yeah, a bit of a, and the whole point is on psychedelics

61:57and certainly on DMT,

61:58this is where the brain data versus word data fails,

62:04which is, words can't convey the experience.

62:08Most people that, you can be poetic and so on,

62:10but it really does not convey the experience

62:12of what it actually means to meet the elves.

§08Transcript · 1:02:16–1:11:59

62:16- To me, what baselines this conversation is,

62:18imagine if we were interested in the health of your heart

62:23and we started and said, okay, Lex, self-introspect,

62:28tell me how's the health of your heart.

62:29And you sit there and you close your eyes

62:31and you think, feels all right, like things feel okay.

62:36And then you went to the cardiologist

62:38and the cardiologist is like, hey Lex,

62:39tell me how you feel.

62:41And you're like, well, actually what I'd really like you

62:43to do is do an EKG and a blood panel

62:45and look at arterial plaques

62:47and let's look at my cholesterol.

62:49And there's like five to 10 studies you would do.

62:53They would then give you this report and say,

62:54here's the quantified health of your heart.

62:58Now with this data, I'm going to prescribe

63:01the following regime of exercise

63:03and maybe I'll put you on a statin, et cetera.

63:06But the protocol is based upon this data.

63:08You would think the cardiologist is out of their mind

63:11if they just gave you a bottle of statins based upon,

63:14you're like, well, I think something's kind of wrong.

63:16And they're just kind of experiment and see what happens.

63:20But that's what we do with our mental health today.

63:22So it's kind of absurd.

63:25And so if you look at psychedelics,

63:27to have, again, to be able to measure the brain

63:29and get a baseline state,

63:31and then to measure during a psychedelic experience

63:33and post the psychedelic experience

63:35and then do it longitudinally,

63:37you now have a quantification of what's going on.

63:39And so you could then pose questions,

63:41what molecule is appropriate at what dosages,

63:45at what frequency, in what contextual environment?

63:47What happens when I have this diet with this molecule,

63:50with this experience?

63:51All the experimentation you do

63:52when you have good sleep data or HRV.

63:55And so that's what I think happens,

63:57what we could potentially do with psychedelics

64:00is we could add this level of sophistication

64:03that is not in the industry currently.

64:05And it may improve the outcomes people experience,

64:09it may improve the safety and efficacy.

64:11And so that's what I hope we are able to achieve.

64:14And it would transform mental health

64:19because we would finally have numbers

64:21to work with to baseline ourselves.

64:22And then if you think about it,

64:24when we talk about things related to the mind,

64:26we talk about the modality.

64:28We use words like meditation or psychedelics

64:30or something else,

64:32because we can't talk about a marker in the brain.

64:34We can't use a word to say,

64:35we can't talk about cholesterol,

64:37we don't talk about plaque in the arteries,

64:38we don't talk about HRV.

64:40And so if we have numbers,

64:41then the solutions get mapped to numbers

64:45instead of the modalities being the thing we talk about.

64:47Meditation just does good things in a crude fashion.

64:51- So in your blog post,

64:53Zeroeth Principle Thinking, good title,

64:56you ponder how do people come up

64:57with truly original ideas.

64:59What's your thoughts on this as a human

65:02and as a person who's measuring brain data?

65:05- Zeroeth principles are building blocks.

65:09First principles are understanding of system laws.

65:14So if you take, for example, like in Sherlock Holmes,

65:17he's a first principles thinker.

65:18So he says, "Once you've eliminated the impossible,

65:23"anything that remains, however improbable, is true."

65:29Whereas Dirk Gently,

65:32the holistic detective by Douglas Adams says,

65:35"I don't like eliminating the impossible."

65:38So when someone says from a first principles perspective,

65:42and they're trying to assume the fewest number of things

65:48within a given timeframe.

65:50And so when I, after Brain Tree Venmo,

65:55I set my mind to the question of

65:59what single thing can I do

66:01that would maximally increase the probability

66:03that the human race thrives beyond what we can even imagine.

66:07And I found that in my conversations with others,

66:10in the books I read, in my own deliberations,

66:13I had a missing piece of the puzzle

66:16because I didn't feel like over,

66:20yeah, I didn't feel like the future could be deduced

66:25from first principles thinking.

66:26And that's when I read the book,

66:29"Zero, A Biography of a Dangerous Idea."

66:33And I-- - It's a really good book,

66:34by the way.

66:36- I think it's my favorite book I've ever read.

66:38- It's also a really interesting number, zero.

66:40- And I wasn't aware

66:42that the number zero had to be discovered.

66:44I didn't realize that it caused a revolution in philosophy

66:47and just tore up math and it tore up,

66:50I mean, it builds modern society,

66:52but it wrecked everything in its way.

66:55It was an unbelievable disruptor

66:56and it was so difficult for society

66:59to get their heads around it.

67:01And so zero is of course,

67:05a representation of a zero principle thinking,

67:06which is it's the caliber

67:09and consequential nature of an idea.

67:12And so when you talk about what kind of ideas

67:17have civilization transforming properties,

67:22oftentimes they fall in the zeroth category.

67:25And so in thinking this through,

67:28I was wanting to find a quantitative structure

67:31on how to think about these zeroth principles.

67:35So I came up with that to be a coupler

67:39with first principles thinking.

67:40And so now it's a staple as part of how I think

67:42about the world and the future.

67:45- So it emphasizes trying to identify,

67:47it lands on that word impossible,

67:49like what is impossible?

67:51Essentially trying to identify what is impossible

67:54and what is possible and being as,

67:56how do you, I mean, this is the thing

68:00is most of society tells you the range of things

68:04they say is impossible is very wide.

68:06So you need to be shrinking that.

68:08I mean, that's the whole process of this kind of thinking

68:11is you need to be very rigorous

68:14in trying to be,

68:17trying to draw the lines of what is actually impossible

68:22because very few things are actually impossible.

68:26I don't know what is actually impossible.

68:29Like it's the Joe Rogan is entirely possible.

68:32I like that approach to science,

68:36to engineering, to entrepreneurship.

68:38It's entirely possible.

68:40Basically shrink the impossible to zero,

68:43to very small set.

68:45- Yeah, life constraints favor first principles thinking

68:50because it enables faster action

68:55with higher probability of success.

68:57Pursuing zero of principle optionality

69:00is expensive and uncertain.

69:02And so in a society constrained by resources,

69:06time and money and desire for social status,

69:10accomplishment, et cetera,

69:11it minimizes zero principle thinking.

69:14But the reason why I think zero principle thinking

69:16should be a staple of our shared cognitive infrastructure

69:21is if you look to the history of past couple of thousand

69:25years, and let's just say we arbitrarily,

69:29we subjectively try to assess what is a zero level idea.

69:33And we say, how many have occurred on what time scales

69:37and what were the contextual settings for it?

69:40I would argue that if you look at AlphaGo,

69:43when it played Go from another dimension,

69:47with the human Go players,

69:51when it saw AlphaGo's moves,

69:53it attributed to like playing with an alien,

69:55playing Go with AlphaGo being from another dimension.

70:00And so if you say computational intelligence

70:04has an attribute of introducing zero-like insights,

70:09then if you say, what is going to be the occurrence

70:14of zeros in society going forward?

70:16And you could reasonably say,

70:19probably a lot more than have occurred

70:21and probably more at a faster pace.

70:24So then if you say, what happens if you have

70:26this computational intelligence throughout society

70:29that the manufacturing design and distribution

70:31of intelligence is now going to heading towards zero,

70:33you have an increased number of zeros being produced

70:37with a tight connection between human and computers.

70:40That's when I got to a point and said,

70:43we cannot predict the future with first principle thinking.

70:47We can't, that cannot be our imagination set.

70:50It can't be our sole anchor in the situation

70:55that basically the future of our conscious existence,

70:5720, 30, 40, 50 years is probably a zero.

71:01- So just to clarify, when you say zero,

71:06you're referring to basically a truly revolutionary idea.

71:11- Yeah, something that is currently not a building block

71:17of our shared conscious existence,

71:21either in the form of knowledge.

71:23Yeah, it's currently not manifest in what we acknowledge.

71:28- So zero principle thinking is playing with ideas

71:32that are so revolutionary that we can't even clearly reason

71:37about the consequences once those ideas come to be.

71:42- Yeah, or for example, like Einstein,

71:46that was a zeroth, I would categorize it

71:49as a zeroth principle insight.

71:51- You mean general relativity, space-time.

71:53- Yeah, space-time, yep, yep.

71:55That basically building upon what Newton had done

71:59and said, yes, also, and it just changed the fabric

§09Transcript · 1:12:04–1:21:15

72:04of our understanding of reality.

72:06And so that was unexpected, it existed.

72:09It became part of our awareness.

72:13And the moves AlphaGo made existed,

72:16it just came into our awareness.

72:19And so to your point, there's this question of,

72:24what do we know and what don't we know?

72:28Do we think we know 99% of all things

72:30or do we think we know 0.001% of all things?

72:34And that goes back to known known,

72:35known knowns and unknown unknowns.

72:37And first principles and zero principle thinking

72:39gives us a quantitative framework to say,

72:42there's no way for us to mathematically

72:45try to create probabilities for these things.

72:47Therefore, it would be helpful

72:50if they were just part of our standard thought processes,

72:53because it may encourage different behaviors

72:58in what we do individually, collectively as a society,

73:01what we aspire to, what we talk about,

73:03the possibility sets we imagine.

73:05- Yeah, I've been engaged in that kind of thinking

73:09quite a bit and thinking about

73:12engineering of consciousness.

73:14I think it's feasible.

73:16I think it's possible in the language that we're using here.

73:19And it's very difficult to reason about a world

73:21when inklings of consciousness can be engineered

73:26into artificial systems.

73:29Not from a philosophical perspective,

73:33but from an engineering perspective,

73:35I believe a good step towards engineering consciousness

73:39is creating engineering the illusion of consciousness.

73:44I'm captivated by our natural predisposition

73:50to anthropomorphize things.

73:53And I think that's what we,

73:56I don't wanna hear from the philosophers,

74:00but I think that's what we kind of do to each other.

74:05- Okay.

74:05- That consciousness is created socially.

74:10That much of the power of consciousness

74:16is in the social interaction.

74:18I create your consciousness, no,

74:21I create my consciousness by having interacted with you.

74:24And that's the display of consciousness.

74:27It's the same as the display of emotion.

74:30Emotion is created through communication.

74:32Language is created through its use.

74:36And then we somehow, humans kinda,

74:38especially philosophers,

74:39the heart problem of consciousness,

74:40really wanna believe that we possess this thing

74:44that's like there's an elf sitting there

74:49with a hat that's named taxes consciousness,

74:52and they're feeding this subjective experience to us,

74:57as opposed to it actually being an illusion

75:02that we construct to make social communication

75:04more effective.

75:05And so I think if you focus on

75:08creating the illusion of consciousness,

75:10you can create some very fulfilling experiences in software.

75:14And so that to me is a compelling space of ideas to explore.

75:18- I agree with you.

75:19And I think going back to our experience together

75:21with brain interfaces on,

75:23you could imagine if we get to a certain level of maturity.

75:26So first let's take the inverse of this.

75:28So you and I text back and forth,

75:30and we're sending each other emojis.

75:33That has a certain amount of information transfer rate

75:37as we're communicating with each other.

75:39And so in our communication with people via email

75:41and text and whatnot,

75:42we've taken the bandwidth of human interaction,

75:46the information transfer rate, and we've reduced it.

75:49We have less social cues.

75:51We have less information to work with.

75:53There's a lot more opportunity for misunderstanding.

75:55So that is altering the conscious experience

75:57between two individuals.

75:59And if we add brain interfaces to the equation,

76:01let's imagine now we amplify

76:03the dimensionality of our communications.

76:05That to me is what you're talking about,

76:07which is consciousness engineering.

76:09Perhaps I understand you with dimensions.

76:13So maybe I understand your,

76:15when you look at the cup

76:16and you experience that happiness,

76:17you can tell me you're happy.

76:18And I then do theory of mind and say,

76:20I can imagine what it might be like to be Lex

76:23and feel happy about seeing this cup.

76:25But if the interface could then quantify

76:26and give me a 50 vector space model

76:29and say, this is the version of happiness

76:31that Lex is experiencing as he looks at this cup,

76:34then it would allow me potentially

76:36to have much greater empathy for you

76:38and understand you as a human.

76:39This is how you experience joy,

76:41which is entirely unique from how I experienced joy,

76:44even though we assumed ahead of time

76:46that we're having some kind of similar experience.

76:48But I agree with you that

76:50we do consciousness engineering today in everything we do.

76:52When we talk to each other, when we're building products

76:55and that we're entering into a stage

76:59where it will be much more methodical

77:02and quantitative based and computational

77:06in how we go about doing it,

77:07which to me I find encouraging

77:09because I think it creates better guardrails

77:12to create ethical systems versus right now,

77:18I feel like it's really a wild, wild west

77:21on how these interactions are happening.

77:23- Yeah, and it's funny you focus on human to human,

77:25but that this kind of data enables

77:27human to machine interaction,

77:30which is what we're kind of talking about

77:33when we say engineering consciousness.

77:35- And that will happen, of course,

77:39let's flip that on its head.

77:40Right now we're putting humans as the central node.

77:44What if we gave GPT-3 a bunch of human brains

77:48and said, "Hey, GPT-3, learn some manners when you speak

77:54and run your algorithms on humans' brains

77:56and see how they respond so you can be polite

78:00and so that you can be friendly

78:01and so that you can be conversationally appropriate."

78:04But to inverse it, to give our machines a training set

78:09in real time with closed loop feedback

78:11so that our machines were better equipped

78:14to find their way through our society

78:19in polite and kind and appropriate ways.

78:22- I love that idea, or better yet,

78:24teach it some, have it read the finding documents

78:29and have it visit Austin and Texas

78:32and so that when you tell it,

78:34"Why don't you learn some manners?"

78:36GPT-3 learns to say no.

78:38It learns what it means to be free

78:43and a sovereign individual.

78:45So it depends, so it depends

78:47what kind of version of GPT-3 you want.

78:50One that's free, one that behaves well

78:52with the social. - Be met by a revolution.

78:54- You want a socialist GPT-3,

78:57you want an anarchist GPT-3,

79:00you want a polite, like you take it home

79:03to visit mom and dad GPT-3,

79:05and you want like party in like Vegas

79:08to a strip club GPT-3, you want all flavors.

79:11- And then you've gotta have goal alignment

79:13between all those.

79:14- Yeah, they don't want to manipulate each other for sure.

79:20- So that's, I mean, you kind of spoke to ethics.

79:24One of the concerns that people have

79:26in this modern world, the digital data,

79:29is that of privacy and security.

79:32But privacy, you know, they're concerned

79:34that when they share data,

79:35it's the same thing with you

79:38when we trust other human beings

79:40in being fragile and revealing something

79:44that we're vulnerable about.

79:48There's a leap of faith, there's a leap of trust

79:51that that's going to be just between us,

79:54there's a privacy to it.

79:55And then the challenge is when you're in the digital space,

79:58then sharing your data with companies

80:01that use that data for advertisement

80:03and all those kinds of things,

80:05there's a hesitancy to share that much data,

80:08to share a lot of deep personal data.

80:10And if you look at brain data,

80:12that feels a whole lot like it's richly,

80:16deeply personal data.

80:17So how do you think about privacy

80:20with this kind of ocean of data?

80:22- I think we got off to a wrong start with the internet,

80:26where the basic rules of play

80:29for the company that be was,

80:32if you're a company, you can go out

80:36and get as much information on a person

80:39as you can find without their approval.

80:42And you can also do things to induce them

80:46to give you as much information.

80:48And you don't need to tell them what you're doing with it.

80:51You can do anything on the backside,

80:52you can make money on it,

80:53but the game is who can acquire the most information

80:56and devise the most clever schemes to do it.

81:00That was a bad starting place.

81:01And so we are in this period

81:05where we need to correct for that.

81:07And we need to say, first of all,

81:09the individual always has control over their data.

81:14It's not a free for all.

81:15It's not like a game of hungry hippo,

§10Transcript · 1:21:17–1:30:19

81:17but they can just go out and grab as much as they want.

81:20So for example, when your brain data was recorded today,

81:22the first thing we did in the kernel app

81:24was you have control over your data.

81:27And so it's individual consent, it's individual control,

81:31and then you can build up on top of that.

81:33But it has to be based upon some clear rules of play.

81:36If everyone knows what's being collected,

81:39they know what's being done with it,

81:40and the person has control over it.

81:42- So transparency and control.

81:43So everybody knows, what does control look like?

81:46My ability to delete the data if I want.

81:48- Yeah, delete it and to know who it's being shared with

81:51under what terms and conditions.

81:53We haven't reached that level of sophistication

81:55with our products of, if you say, for example,

81:59hey, Spotify, please give me a customized playlist

82:04according to my neuron.

82:06You could say, you can have access

82:09to this vector space model,

82:10but only for this duration of time.

82:12And then you've got to delete it.

82:15We haven't gotten there to that level of sophistication,

82:16but these are ideas we need to start talking about

82:19of how would you actually structure permissions?

82:22- Yeah.

82:23- And I think it creates a much more stable set

82:26for society to build where we understand the rules of play

82:31and people aren't vulnerable to being taken advantage.

82:33It's not fair for an individual to be taken advantage of

82:39without their awareness, with some other practice

82:42that some company is doing for their sole benefit.

82:44And so hopefully we are going through a process now

82:46where we're correcting for these things

82:48and that it can be an economy wide shift

82:53that, because really these are,

82:56these are fundamentals we need to have in place.

83:01- It's kind of fun to think about like in Chrome,

83:05when you install an extension or like install an app,

83:07it's ask you like what permissions you're willing to give

83:10and be cool if in the future,

83:11it says like you can have access to my brain data.

83:15- I mean, it's not unimaginable in the future

83:20that the big technology companies have built a business

83:24based upon acquiring data about you

83:26that they can then create a view to model of you

83:27and sell that predictability.

83:29And so it's not unimaginable that you will create

83:31with like Kernel device, for example,

83:33a more reliable predictor of you than they could.

83:37And that they're asking you for permission

83:39to complete their objectives.

83:40And you're the one that gets to negotiate that with them

83:42and say, sure.

83:44But it's not unimaginable that might be the case.

83:47- So there's a guy named D-Law Musk

83:51and he has a company,

83:52one of the many companies called Neuralink

83:55that has, that's also excited about the brain.

83:59So it'd be interesting to hear your kind of opinions

84:01about a very different approach that's invasive,

84:03that requires surgery,

84:05that implants a data collection device in the brain.

84:09How do you think about the difference

84:10between Kernel and Neuralink in the approaches

84:12of getting that stream of brain data?

84:17- Elon and I spoke about this a lot early on.

84:20We met up, I had started Kernel

84:23and he had an interest in brain interfaces as well.

84:25And we explored doing something together,

84:28him joining Kernel.

84:29And ultimately it wasn't the right move.

84:31And so he started Neuralink

84:33and I continued building Kernel.

84:35But it was interesting because we were both

84:39at this very early time where it wasn't certain

84:44if there was a path to pursue,

84:47if now was the right time to do something

84:51and then the technological choice of doing that.

84:53And so we were both,

84:55our starting point was looking at invasive technologies.

84:58And I was building invasive technology at the time.

85:01That's ultimately where he's gone.

85:04A little less than a year after Elon and I were engaged,

85:08I shifted Kernel to do non-invasive.

85:11And we had this neuroscientist come to Kernel.

85:15We were talking about,

85:16he had been doing neural surgery for 30 years,

85:17one of the most respected neuroscientists in the US.

85:20And we brought him to Kernel to figure out

85:21the ins and outs of his profession.

85:23And at the very end of our three hour conversation,

85:26he said, "You know, every 15 or so years,

85:30"a new technology comes along that changes everything."

85:34He said, "It's probably already here.

85:37"You just can't see it yet."

85:38And my jaw dropped.

85:40I thought, 'cause I had spoken to Bob Greenberg

85:44who had built a second site first on the optical nerve

85:48and then he did an array on the optical cortex.

85:53And then I also became friendly with NeuralPace

85:57who does the implants for seizure detection and remediation.

86:01And I saw in their eyes what it was like

86:06to take something through,

86:08an implantable device through for a 15 year run.

86:11They initially thought it's seven years

86:13and it ended up being 15 years

86:15and they thought it'd be a hundred million,

86:16it was 300 or 400 million.

86:18And I really didn't want to build invasive technology.

86:22It was the only thing that appeared to be possible.

86:25But then once I spun up an internal effort

86:28to start looking at non-invasive options,

86:30we said, "Is there something here?

86:31"Is there anything here that again has the characteristics

86:34"of it has the high quality data,

86:37"it could be low cost, it could be accessible.

86:39"Could it make brain interfaces mainstream?"

86:42And so I did a bet the company move.

86:43We shifted from invasive to non-invasive.

86:47- So the answer is yes to that.

86:49There is something there, it's possible.

86:51- The answer is we'll see.

86:52We've now built both technologies

86:55and they're now, you experienced one of them today.

86:58We were applying, we're now deploying it.

87:02So we're trying to figure out what value is really there.

87:04But I'd say it's really too early to express confidence.

87:07I think it's too early to assess

87:12which technological choice is the right one

87:17on what timescales.

87:19- Yeah, timescales are really important here.

87:20- Very important.

87:21Because if you look at the, like on the invasive side,

87:24there's so much activity going on right now

87:27of less invasive techniques to get at the neuron firings,

87:32which what Neuralink is building,

87:36it's possible that in 10, 15 years,

87:39when they're scaling that technology,

87:40other things have come along,

87:42and you'd much rather do that.

87:44That thing starts to clock again.

87:45It may not be the case.

87:47It may be the case that Neuralink has properly chosen

87:49the right technology and that that's exactly

87:52what they wanna be, totally possible.

87:53And it's also possible that the paths we've chosen

87:55for non-invasive fall short for a variety of reasons.

87:58It's just, it's unknown.

88:00And so right now, the two technologies we chose,

88:03the analogy I'd give you to create a baseline

88:06of understanding is, if you think of it

88:09like the internet in the '90s,

88:11the internet became useful when people could do

88:13a dial-up connection.

88:15And then the paid, and then as bandwidth increased,

88:19so did the utility of that connection,

88:21and so did the ecosystem improve.

88:22And so if you say what, kernel flow is going to give you

88:27a full screen on the picture of information,

88:30but as you're gonna be watching a movie,

88:32but the image is going to be blurred

88:34and the audio is gonna be muffled.

88:36So it has a lower resolution of coverage.

88:39Kernel flux, our MEG technology,

88:43is gonna give you the full movie in 1080p.

88:46And Neuralink is gonna give you a circle on the screen

88:52of 4K.

88:53And so each one has their pros and cons,

88:57and it's give and take.

88:59And so the decision I made with kernel was

89:03that these two technologies, flux and flow,

89:06were basically the answer for the next seven years.

89:10And they would give rise to the ecosystem,

89:12which would become much more valuable

89:14than the hardware itself,

89:15and that we would just continue to improve

89:16on the hardware over time.

89:18And you know, it's early days, so--

89:20- It's kind of fascinating to think about that.

89:23You don't, it's very true that you don't know.

89:27Both paths are very promising.

89:30And it's like 50 years from now,

89:36we will look back and maybe not even remember one of them.

89:39And the other one might change the world.

89:43It's so cool how technology is.

89:44I mean, that's what entrepreneurship is.

89:47It's like, it's the zeroth principle.

89:50It's like you're marching ahead into the darkness,

89:52into the fog, not knowing.

89:54- It's wonderful to have someone else

89:56out there with us doing this.

89:57Because if you look at brain interfaces,

90:00anything that's off the shelf right now is inadequate.

90:06It's had its run for a couple of decades.

90:09It's still in hacker communities.

90:11It hasn't gone to the mainstream.

90:12The room-sized machines are on their own path.

90:19But there is no answer right now

§11Transcript · 1:30:20–1:38:13

90:20of bringing brain interfaces mainstream.

90:23And so it both, both they and us,

90:27we've both spent over $100 million.

90:29And that's kind of what it takes to have a go at this.

90:32'Cause you need to build full stack.

90:34I mean, at Kernel, we are from the photon and the atom

90:38through the machine learning.

90:40We have just under 100 people,

90:41I think it's something like 36, 37 PhDs

90:45in these specialties, these areas,

90:47that there's only a few people in the world

90:48who have these abilities.

90:50And that's what it takes to build next generation,

90:53to make an attempt at breaking into brain interfaces.

90:57And so we'll see over the next couple of years,

90:58whether it's the right time

91:00or whether we were both too early

91:01or whether something else comes along in seven to 10 years,

91:04which is the right thing that brings it mainstream.

91:08- So you see Elon as a kind of competitor

91:11or a fellow traveler along the path of uncertainty,

91:16or both?

91:17- Fellow traveler.

91:19It's like at the beginning of the internet

91:21is how many companies are going to be invited

91:25to this new ecosystem?

91:27Like an endless number.

91:30Because if you think the hardware just starts the process.

91:35And so, okay, back to your initial example,

91:37if you take the Fitbit, for example,

91:39you say, okay, now I can get measurements on the body.

91:42And what do we think the ultimate value

91:44of this device is going to be?

91:45What is the information transfer rate?

91:47And they were in the market for a certain duration of time

91:50and Google bought them for two and a half billion dollars.

91:53They didn't have ancillary value add.

91:55There weren't people building on top of the Fitbit device.

91:58They also didn't have increased insight

92:01with additional data streams.

92:02So it was really just the device.

92:04If you look, for example, at Apple

92:05and the device they sell,

92:07you have value in the device that someone buys,

92:09but also you have everyone who's building on top of it.

92:11So you have this additional ecosystem value.

92:13And then you have additional data streams that come in,

92:15which increase the value of the product.

92:17And so if you say, if you look at the hardware

92:20as the instigator of value creation,

92:24over time, what we've built may constitute

92:27five or 10% of the value of the overall ecosystem.

92:29And that's what we really care about.

92:30What we're trying to do is kickstart

92:33the mainstream adoption of quantifying the brain.

92:38And the hardware just opens the door to say

92:41what kind of ecosystem could exist.

92:45And that's why the examples are so relevant

92:47of the things you've outlined in your life.

92:50I hope those things, the books people write,

92:53the experiences people build,

92:54the conversations you have,

92:56your relationship with your AI systems,

92:59I hope those all are feeding on the insights

93:02built upon this ecosystem we've created to better your life.

93:05And so that's the thinking behind it.

93:07Again, with the Drake equation

93:08being the underlying driver of value.

93:11And the people at Kernel have joined

93:14not because we have certainty of success,

93:19but because we find it to be

93:21the most exhilarating opportunity we could ever pursue

93:24in this time to be alive.

93:26- You founded the payment system Braintree in 2007

93:32that acquired Venmo in 2012.

93:35And then in that same year was acquired by PayPal,

93:39which is now eBay.

93:40Can you tell me the story of the vision

93:45and the challenge of building an online payment system

93:48and just building a large successful business in general?

93:51- I discovered payments by accident.

93:54As I was, when I was 21,

93:56I just returned from Ecuador

94:00living among extreme poverty for two years.

94:02And I came back to the US and I was shocked by the opulence

94:06and the of the United States.

94:09And I just thought this is, I couldn't believe it.

94:12And I decided I wanted to try to spend my life

94:14helping others.

94:16Like that was the life objective

94:18that I thought was worthwhile to pursue

94:20versus making money and whatever the case may be

94:23for its own right.

94:24And so I decided in that moment

94:25that I was going to try to make enough money

94:28by the age of 30 to never have to work again.

94:32And then with some abundance of money,

94:33I could then choose to do things

94:36that might be beneficial to others

94:38but may not meet the criteria of being

94:41a standalone business.

94:42And so in that process, I started a few companies,

94:46had some small successes, had some failures.

94:49In one of the endeavors, I was up to my eyeballs in debt.

94:53Things were not going well

94:54and I needed a part-time job to pay my bills.

94:57And so I, one day I saw in the paper in Utah

95:02where I was living, the 50 richest people in Utah.

95:05And I emailed each one of their assistants and said,

95:08you know, I'm young, I'm resourceful,

95:10I'll do anything, I'll just wanna, I'm entrepreneurial.

95:13I tried to get a job that would be flexible

95:15and no one responded.

95:17And then I interviewed at a few dozen places.

95:21Nobody would even give me the time of day.

95:23Like, it wouldn't want to take me seriously.

95:25And so finally, it was on monster.com

95:28that I saw this job posting for credit card sales

95:31door to door.

95:32Commission. (laughs)

95:34- I did not know this story.

95:36This is great.

95:36- I love the head drop.

95:38That's exactly right.

95:39So it was-

95:39- The low points to which we're going like.

95:43- So I responded and, you know,

95:45the person made an attempt at suggesting

95:48that they had some kind of standards

95:50that they would consider hiring.

95:52But it's kind of like, if you could fog a mirror,

95:55like come and do this because it's 100% commission.

95:57And so I started walking up and down the street

95:59in my community, selling credit card processing.

96:02And so what you learn immediately in doing that is

96:05if you walk into a business,

96:07first of all, the business owner is typically there.

96:10And you walk in the door and they can tell

96:12by how you're dressed or how you walk,

96:14whatever their pattern recognition is.

96:16And they just hate you immediately.

96:17It's like, stop wasting my time.

96:18I really am trying to get stuff done.

96:20I don't want us to a sales pitch.

96:21And so you have to overcome the initial get out.

96:25And then once you engage,

96:27when you say the word credit card processing,

96:29the person's like, I already hate you

96:31because I have been taken advantage of dozens of times

96:34because you all are weasels.

96:37And so I had to figure out an algorithm

96:39to get past all those different conditions

96:41'cause I was still working on my other startup

96:43for the majority of my time.

96:44So I was doing this part time.

96:45And so I figured out that the industry really was

96:50built on people, on deceit.

96:55Basically people promising things that were not reality.

96:58And so I'd walk into a business, I'd say, look,

97:00I would give you a hundred dollars.

97:01I'd put a hundred dollar bill and say,

97:02I'll give you a hundred dollars

97:04for three minutes of your time.

97:05If you don't say yes to what I'm saying,

97:06I'll give you a hundred dollars.

97:08And then he usually crack a smile and say, okay,

97:10look what he got for me, son.

97:12And so I'd sit down, I just opened my book and I'd say,

97:15here's the credit card industry.

97:16Here's how it works.

97:17Here are the players.

97:17Here's what they do.

97:18Here's how they deceive you.

97:20Here's what I am.

97:21I'm no different than anyone else.

97:22It's like, you're gonna process your credit card.

97:24You're gonna get the money in the account.

97:25You're just gonna get a clean statement.

97:26You're gonna have someone who answers the call

97:28when someone asks and just like the basic, like you're okay.

97:31And people started saying yes.

97:32And then of course I went to the next business

97:34and be like, you know, Joe and Susie

97:36and whoever said yes to,

97:37and so I built a social proof structure

97:39and I became the number one salesperson

97:42out of 400 people nationwide doing this.

97:45And I worked, you know, half time

97:47still doing this other startup.

97:48And--

97:49- That's a brilliant strategy, by the way.

97:51It's very well, very well strategized and executed.

97:54- I did it for nine months.

97:57And at the time my customer base was making,

98:00was generating around, I think it was six,

98:03if I remember correctly, $62,504 a month

98:07were the overall revenues.

98:08I thought, wow, that's amazing.

98:09If I built that as my own company,

98:13I would just make $62,000 a month of income passively

§12Transcript · 1:38:16–1:47:51

98:16with these merchants processing credit cards.

98:19So I thought, hmm.

98:20And so that's when I thought I'm gonna create a company.

98:23And so then I started Braintree

98:25and the idea was the online world was broken

98:29because PayPal had been acquired by eBay

98:34around, I think, 1999 or 2000.

98:38And eBay had not innovated much with PayPal.

98:39So it basically sat still for seven years

98:42as the software world moved along.

98:45And then Authorize.net was also a company

98:46that was relatively stagnant.

98:47So you basically had software engineers

98:49who wanted modern payment tools,

98:51but there were none available for them.

98:53And so they just dealt with software they didn't like.

98:55And so with Braintree, I thought the entry point

98:58is to build software that engineers will love.

99:00And if we can find the entry point via software

99:02and make it easy and beautiful and just a magical experience

99:05and then provide customer service on top of that,

99:06that was easy, that would be great.

99:08What I was really going after though, it was PayPal.

99:11They were the only company in payments making money

99:14because they had the relationship with eBay early on.

99:19People created a PayPal account.

99:22They'd fund their account with their checking account

99:24versus their credit cards.

99:25And then when they'd use PayPal to pay a merchant,

99:28PayPal had a cost of payment of zero

99:31versus if you have coming from a credit card,

99:33you have to pay the bank the fees.

99:35So PayPal's margins were 3% on a transaction

99:39versus a typical payments company,

99:41which may be a nickel or a penny or a dime

99:43or something like that.

99:44And so I knew PayPal really was the model to replicate,

99:48but a bunch of companies had tried to do that.

99:50They tried to come in and build a two-sided marketplace.

99:52So get consumers to fund the checking account

99:55and merchants to accept it,

99:56but they'd all failed because building a two-sided

99:58marketplace is very hard at the same time.

100:01So my plan was I'm going to build a company

100:04and get the best merchants in the whole world

100:06to use our service.

100:08Then in year five, I'm going to acquire

100:11a consumer payments company

100:12and I'm going to bring the two together.

100:14And-

100:15- So focus on the merchant side.

100:18- Exactly.

100:18- And then get the payments company

100:19that does the customer, the whatever,

100:22the other side of it.

100:24- Yeah, this is the plan I presented

100:26when I was at the University of Chicago.

100:28And weirdly it happened exactly like that.

100:32So four years in our customer base included Uber,

100:36Airbnb, GitHub, 37signals, not Basecamp.

100:40We had a fantastic collection of companies

100:43that represented the fastest growing,

100:47some of the fastest growing tech companies in the world.

100:49And then we met up with Venmo

100:52and they had done a remarkable job in building product.

100:55There's then something very counterintuitive,

100:56which is make public your private financial transactions

100:59with people previously thought were something

101:01that should be hidden from others.

101:04And we acquired Venmo.

101:05And at that point we now had,

101:08we replicated the model

101:11'cause now people could fund their Venmo account

101:12with their checking account, keep money in the account.

101:15And then you could just plug Venmo in as a form of payment.

101:17And so I think PayPal saw that,

101:19that we were getting the best merchants in the world.

101:22We had people using Venmo.

101:25They were both the up and coming millennials at the time

101:28who had so much influence online.

101:30And so they came in and offered us an attractive number.

101:34And my goal was not to build

101:39the biggest payments company in the world.

101:40It wasn't to try to climb the Forbes billionaire list.

101:44It was, the objective was I want to earn enough money

101:48so that I can basically dedicate my attention

101:52to doing something that could potentially be useful

101:56on a society-wide scale.

101:58And more importantly, that could be considered

102:01to be valuable from the vantage point of 2050, 2100 and 2500.

102:06So thinking about it on a few hundred year timescale.

102:13And there was a certain amount of money I needed to do that.

102:17So I didn't require the permission of anybody to do that.

102:21And so that, what PayPal offered was sufficient

102:23for me to get that amount of money to basically have a go.

102:25And that's when I set off to survey everything

102:30I could identify in existence to say

102:33of anything in the entire world I could do,

102:36what one thing could I do that would actually have

102:38the highest value potential for the species?

102:42And so it took me a little while to arrive at Brainerd Faces,

102:45but payments in themselves are revolutionary technologies

102:50that can change the world.

102:54Like let's not sort of, let's not forget that too easily.

102:59I mean, obviously you know this,

103:03but there's quite a few lovely folks

103:08who are now fascinated with the space of cryptocurrency.

103:13And where payments are very much connected to this,

103:17but in general, just money.

103:19And many of the folks I've spoken with,

103:21they also kind of connect that to not just purely

103:25financial discussions, but philosophical

103:27and political discussions.

103:29And they see Bitcoin as a way, almost as activism,

103:34almost as a way to resist the corruption of centralized,

103:39of centers of power.

103:40And sort of basically in the 21st century,

103:42decentralizing control, whether that's Bitcoin

103:45or other cryptocurrencies, they see that's one possible way

103:50to give power to those that live in regimes

103:54that are corrupt or are not respectful of human rights

103:58and all those kinds of things.

103:59What's your sense, just all your expertise with payments

104:04and seeing how that changed the world,

104:05what's your sense about the lay of the land

104:09for the future of Bitcoin or other cryptocurrencies

104:12in the positive impact it may have on the world?

104:15- Yeah, and to be clear, my communication wasn't meant

104:20to minimize payments or to denigrate it in any way.

104:23It was an attempted communication

104:26that when I was surveying the world,

104:29it was an algorithm of what could I individually do?

104:35So there are things that exist that have a lot of potential

104:39that can be done, and then there's a filtering

104:43of how many people are qualified to do this given thing.

104:46And then there's a further characterization

104:48that can be done of, okay, given the number of qualified

104:50people, will somebody be a unique out performer

104:55of that group to make something truly impossible

104:57to be something done that otherwise couldn't get done?

104:59So there's a process of assessing

105:02where can you add unique value in the world.

105:04- And some of that has to do with you being very,

105:07very formal and calculative here,

105:09but some of that is just like what you sense,

105:13like part of that equation is how much passion you sense

105:16within yourself to be able to drive that through,

105:19to discover the impossibilities and make them possible.

105:21- That's right, and so we were a brain tree.

105:23I think we were the first company to integrate Coinbase

105:26into our, I think we were the first payments company

105:30to formally incorporate crypto, if I'm not mistaken.

105:35- For people who are not familiar, Coinbase,

105:37is a place where you can trade cryptocurrencies.

105:39- Yeah, which was one of the only places you could.

105:42So we were early in doing that.

105:45And of course, this was in the year 2013.

105:49So an attorney to go in cryptocurrency land.

105:52I concur with the statement you made of the potential

105:57of the principles underlying cryptocurrencies.

106:04And that many of the things that they're building

106:07in the name of money and of moving value

106:12is equally applicable to the brain

106:16and equally applicable to how the brain interacts

106:19with the rest of the world

106:20and how we would imagine doing goal alignment with people.

106:25So to me, it's a continuous spectrum of possibility.

106:29And your question is isolated on the money.

106:32And I think it just is basically a scaffolding layer

106:35for all of society.

106:35- So you don't see this money

106:37as particularly distinct from-

106:38- I don't.

106:39I think we, at Kernel, we will benefit greatly

106:44from the progress being made in cryptocurrency

106:47because it will be a similar technology stack

106:49we will want to use for many things we want to accomplish.

106:51And so I'm bullish on what's going on

106:55and think it could greatly enhance brain interfaces

106:58and the value of the brain interface ecosystem.

107:01- I mean, is there something you could say about,

107:02first of all, bullish on cryptocurrency versus fiat money?

107:05So do you have a sense that in 21st century,

107:08cryptocurrency will be embraced by governments

107:13and change the face of governments,

107:16the structure of government?

107:18- It's the same way I think about my diet,

107:23where previously it was conscious Brian

107:28looking at foods in certain biochemical states.

107:32Am I hungry?

107:33Am I irritated?

107:33Am I depressed?

107:34And then I choose based upon those momentary windows.

107:37Do I eat at night when I'm fatigued?

107:39Did I have low willpower?

107:40Am I gonna pig out on something?

107:42And the current monetary system

107:45is based upon human conscious decision-making

107:48and politics and power and this whole mess of things.

107:51And what I like about the building blocks

§13Transcript · 1:47:55–1:56:54

107:55of cryptocurrency is it's methodical, it's structured.

107:58It is accountable, it's transparent.

108:02And so it introduces this scaffolding,

108:04which I think again is the right starting point

108:07for how we think about building next generation

108:11institutions for society.

108:13And that's why I think it's much broader than money.

108:16- So I guess what you're saying is Bitcoin

108:18is the demotion of the conscious mind as well.

108:21In the same way you were talking about diet,

108:25it's like giving less priority to the ups and downs

108:29of any one particular human mind, in this case your own,

108:33and giving more power to the sort of data-driven.

108:37- Yes, yeah, I think that is accurate.

108:41That cryptocurrency is a version of what I would call

108:46my autonomous self that I'm trying to build.

108:51It is an introduction of an autonomous system

108:54of value exchange and the process of value creation

108:59in society, yes, there's similarities.

109:04- So I guess what you're saying is Bitcoin

109:06will somehow help me not pig out at night

109:08or the equivalent of, speaking of diet,

109:11if we could just linger on that topic a little bit.

109:15We already talked about your blog post of I fired myself,

109:20I fired Brian, the evening.

109:23Brian who is too willing to, not making good decisions

109:28for the long-term well-being and happiness

109:32of the entirety of the organism.

109:34Basically you were like pigging out at night.

109:36But it's interesting, 'cause I do the same.

109:41In fact, I often eat one meal a day.

109:43And like I have been this week, actually,

109:49and especially when I travel.

109:52And it's funny that it never occurred to me

109:57to just basically look at the fact

110:00that I'm able to be much smarter about my eating decisions

110:03in the morning and the afternoon than I am at night.

110:06So if I eat one meal a day,

110:08why not eat that one meal a day in the morning?

110:11Like I'm not, it never occurred to me.

110:16This revolutionary.

110:17(Lex laughing)

110:18Until you've outlined that.

110:21So maybe, can you give some details in what,

110:24this is just you, this is one person, Brian,

110:27arrived at a particular thing that they do.

110:29But it's fascinating to kinda look

110:32at this one particular case study.

110:34So what works for you, diet-wise?

110:36What's your actual diet?

110:37What do you eat?

110:38How often do you eat?

110:40- My current protocol is basically the result

110:44of thousands of experiments and decision-making.

110:48So I do this every 90 days.

110:50I do the tests, I do the cycle-throughs,

110:53then I measure again, and then I'm measuring all the time.

110:56And so what I, I, of course,

110:58I'm optimizing for my biomarkers.

111:00I want perfect cholesterol,

111:01and I want perfect blood glucose levels,

111:03and perfect DNA methylation processes.

111:07I also want perfect sleep.

111:12And so, for example, recently, in the past two weeks,

111:14my resting heart rate has been at 42 when I sleep.

111:20And when my resting heart rate's at 42,

111:22my HRV is at its highest.

111:24And I wake up in the morning feeling more energized

111:29than any other configuration.

111:30And so I know from all these processes

111:32that eating at roughly 8.30 in the morning,

111:34right after I work out on an empty stomach,

111:37creates enough distance between that completed eating

111:41and bedtime, where I have no,

111:43almost no digestion processes going on in my body,

111:47therefore my resting heart rate goes very low.

111:49And when my resting heart rate's very low,

111:51I sleep with high quality.

111:52And so basically I've been trying to optimize

111:54the entirety of what I eat to my sleep quality.

111:58And my sleep quality then, of course,

111:59feeds into my willpower, so it creates this virtuous cycle.

112:02And so at 8.30, what I do is I eat what I call super veggie,

112:06which is, it's a pudding of 250 grams of broccoli,

112:10150 grams of cauliflower,

112:11and a whole bunch of other vegetables,

112:13that I eat what I call nutty pudding, which is--

112:16- You make the pudding yourself, like the,

112:19what do you call it?

112:20Like a veggie mix, whatever thing, like a blender?

112:23- Yeah, you can be made in a high-speed blender.

112:25But basically I eat the same thing every day,

112:27veggie bowl, as in a form of pudding,

112:30and then a bowl in the form of nuts.

112:34And then I have--

112:35- So vegan?

112:36- Vegan, yes.

112:37- Vegan, so that's fat, and that's like,

112:39that's fat and carbs and protein and so on.

112:43- Did I have a third taste? - Does it taste good?

112:45- I love it.

112:46I love it so much, I dream about it.

112:49- Yeah, that's awesome.

112:50This is a--

112:52- And then I have a third dish,

112:53which is, it changes every day.

112:55Today it was kale and spinach and sweet potato.

112:58And then I take about 20 supplements

113:02that hopefully make,

113:06constitute a perfect nutritional profile.

113:09So what I'm trying to do is create the perfect diet

113:12for my body every single day.

113:14- Where sleep is part of the optimization.

113:16- That's right.

113:17- You're like, one of the things you're really tracking.

113:18I mean, can you, well, I have a million questions,

113:21but 20 supplements, like what kind would you say

113:24are essential?

113:25'Cause I only take,

113:26I only take athleticgreens.com/wax.

113:30That's like the multivitamin, essentially.

113:33That's like the lazy man, you know?

113:35Like if you don't actually wanna think about shit,

113:37that's what you take.

113:38And then fish oil, and that's it, that's all I take.

113:41- Yeah, you know, Alfred North Whitehead said,

113:45"Civilization advances as it extends

113:48the number of important operations it can do

113:50without thinking about them."

113:52- Yes.

113:53- And so my objective on this is,

113:55I want an algorithm for perfect health

113:59that I never have to think about.

114:00And that I want that system to be scalable to anybody,

114:03so that they don't have to think about it.

114:05And right now it's expensive for me to do it,

114:07it's time consuming for me to do it,

114:09and I have infrastructure to do it,

114:10but the future of being human

114:13is not going to the grocery store

114:16and deciding what to eat.

114:17It's also not reading scientific papers

114:19trying to decide this thing or that thing.

114:21It's all N of one.

114:23So it's devices on the outside and inside your body

114:26assessing real time what your body needs,

114:28and then creating closed loop systems for that to happen.

114:30- Yeah, so right now you're doing the data collection

114:33and you're being the scientist.

114:35It'd be much better if you just did the data,

114:39or it was being essentially done for you,

114:40and you can outsource that to another scientist

114:43that's doing the N of one study of you.

114:46- That's right, because every time I spend time

114:48thinking about this or executing, spending time on it,

114:50I'm spending less time thinking about

114:52building kernel or future of being human.

114:55And so we just all have the budget of our capacity

115:00on an everyday basis,

115:01and we will scaffold our way up out of this.

115:05And so, yeah, hopefully what I'm doing is really,

115:07it serves as a model that others can also build on.

115:11That's why I wrote about it,

115:12is hopefully people can then take it and improve upon it.

115:15I hold nothing sacred.

115:16I change my diet almost every day

115:19based upon some new test result or science

115:21or something like that.

115:23- Can you maybe elaborate on the sleep thing?

115:24Why is sleep so important?

115:27And why, presumably, what does good sleep mean to you?

115:34- I think sleep is a contender

115:37for being the most powerful

115:40health intervention in existence.

115:45It's a contender.

115:49I mean, it's magical what it does if you're well-rested

115:53and what your body can do.

115:56And I mean, for example,

115:57I know when I eat close to my bedtime,

116:01and I've done a systematic study for years

116:05looking at like 15-minute increments on time of day

116:07and where I eat my last meal,

116:09my willpower is directly correlated

116:12to the amount of deep sleep I get.

116:14So my ability to not binge eat at night

116:18when Rascal Bryan's out and about

116:22is based upon how much deep sleep I got the night before.

116:24- Yeah, yeah, there's a lot to that, yeah.

116:27- And so I've seen it manifest itself.

116:30And so I think the way I'd summarize this is,

116:34in society, we've had this myth of,

116:36we tell stories, for example, of entrepreneurship,

116:39where this person was so amazing,

116:41they stayed at the office for three days

116:43and slept under their desk.

116:44And we say, "Wow, that's amazing.

116:47"That's amazing."

116:48And now I think we're headed towards a state

116:52where we'd say that's primitive

116:54and really not a good idea on every level.

§14Transcript · 1:56:58–2:07:04

116:58And so the new mythology is going to be the exact opposite.

117:03- Yeah, by the way, just to sort of maybe push back

117:08a little bit on that idea.

117:10- Did you sleep under your desk, Alex?

117:13- Well, yeah, a lot.

117:14I'm a big believer in that, actually.

117:16I'm a big believer in chaos

117:19and giving into your passion.

117:22And sometimes doing things that are out of the ordinary,

117:25that are not trying to optimize health

117:29for certain periods of time in lieu of your passions

117:34is a signal to yourself that you're throwing everything away.

117:39So I think what you're referring to

117:42is how to have good performance

117:45for prolonged periods of time.

117:47I think there's moments in life

117:50when you need to throw all of that away,

117:52all the plans away, all the structure away.

117:54So I'm not sure I have an eloquent way

117:59to describe exactly what I'm talking about,

118:02but it all depends on different people.

118:06People are different.

118:07But there's a danger of over-optimization

118:10to where you don't just give in to the madness

118:14of the way your brain flows.

118:17I mean, to push back on my pushback is like,

118:21it's nice to have where the foundations

118:26of your brain are not messed with.

118:31So you have a fixed foundation where the diet is fixed,

118:35where the sleep is fixed, and that all of that is optimal.

118:37And the chaos happens in the space of ideas

118:39as opposed to the space of biology.

118:41But I'm not sure if there's a,

118:46that requires real discipline and forming habits.

118:50There's some aspect to which some of the best days

118:54and weeks of my life have been, yeah,

118:56sleeping under a desk kind of thing.

118:58And I don't, I'm not too willing to let go of things

119:03that empirically worked for things that work in theory.

119:09So again, I'm absolutely with you on sleep.

119:16Also, I'm with you on sleep conceptually,

119:19but I'm also very humbled to understand

119:23that for different people,

119:26good sleep means different things.

119:28I'm very hesitant to trust science on sleep.

119:33I think you should also be a scholar of your own body.

119:35Again, experiment of N of one.

119:38I'm not so sure that a full night's sleep is great for me.

119:43There is something about that power nap

119:47that I just have not fully studied yet,

119:50but that nap is something special.

119:52That I'm not sure I found the optimal thing.

119:54So like there's a lot to be explored

119:57to what is exactly optimal amount of sleep,

120:00optimal kind of sleep, combined with diet

120:02and all those kinds of, I mean, that all maps

120:04to sort of data leads to truth,

120:06exactly what everything you're referring to.

120:08- Here's a data point for your consideration.

120:10- Yes.

120:11- The progress in biology over the past,

120:16say decade has been stunning.

120:18- Yes.

120:19- And it now appears as if we will be able to replace

120:24our organs, zero transplantation.

120:28And so we probably have a path to replace

120:33and regenerate every organ of your body,

120:37except for your brain.

120:38You can lose your hand and your arm and a leg,

120:45you can have an artificial heart,

120:47you can't operate without your brain.

120:49And so when you make that trade-off decision

120:52of whether you're going to sleep under the desk or not

120:54and go all out for a four day marathon,

120:59there's a cost benefit trade-off of what's going on,

121:02what's happening to your brain in that situation.

121:05We don't know the consequences

121:07of modern day life on our brain.

121:09It's the most valuable organ in our existence.

121:15And we don't know what's going on

121:17if we, and how we're treating it today

121:19with stress and with sleep and with dietary.

121:23And to me, then if you say that you're trying to,

121:28you're trying to optimize life

121:30for whatever things you're trying to do,

121:32the game is soon,

121:34with the progress in anti-aging and biology,

121:36the game is very soon going to become different

121:38than what it is right now,

121:40with organ rejuvenation, organ replacement.

121:42And I would conjecture that we will value

121:47the health status of our brain above all things.

121:52- Yeah, no, absolutely.

121:54Everything you're saying is true, but we die.

121:58We die pretty quickly.

121:59Life is short.

122:01And I'm one of those people that I would rather die

122:06in battle than stay safe at home.

122:11It's like, yeah, you look at kinda,

122:14there's a lot of things that you can reasonably say,

122:17this is the smart thing to do,

122:19that can prevent you, that becomes conservative,

122:21that can prevent you from fully embracing life.

122:24I think ultimately, you can be very intelligent

122:27and data-driven and also embrace life.

122:30But I err on the side of embracing life.

122:33It takes a very skillful person

122:36to not sort of that hovering parent

122:39that says, no, you know what?

122:41There's a 3% chance that if you go out,

122:44if you go out by yourself and play, you're going to die.

122:47Get run over by a car, come to a slow or a sudden end.

122:51And I'm more a supporter of just go out there.

122:57If you die, you die.

122:59And it's a balance you have to strike.

123:02I think there's a balance to strike

123:04in long-term optimization and short-term freedom.

123:10For me, for a programmer, for a programming mind,

123:15I tend to over-optimize,

123:16and I'm very cautious and afraid of that,

123:19to not over-optimize and thereby be overly cautious,

123:24suboptimally cautious about everything I do.

123:27And the ultimate thing I'm trying to optimize for,

123:30it's funny you said sleep and all those kinds of things.

123:33I tend to think, this is,

123:37you're being more precise than I am,

123:40but I think I tend to want to minimize stress,

123:45which everything comes into that,

123:49from you sleeping, all those kinds of things.

123:50But I worry that whenever I'm trying

123:53to be too strict with myself, then the stress goes up

123:57when I don't follow the strictness.

124:00And so you have to kind of, it's a weird,

124:03there's so many variables in an objective function

124:05that it's hard to get right.

124:07And sort of not giving a damn about sleep

124:09and not giving a damn about diet

124:11is a good thing to inject in there every once in a while

124:14for somebody who's trying to optimize everything.

124:17But that's me just trying to,

124:19it's exactly like you said, you're just a scientist,

124:21I'm a scientist of myself, you're a scientist of yourself.

124:24It'd be nice if somebody else was doing it

124:25and had much better data than,

124:27because I don't trust my conscious mind,

124:29and I pigged out last night at some brisket in LA

124:32that I regret deeply.

124:34So-- - There's no point

124:37to anything I just said.

124:38(both laughing)

124:42- What is the nature of your regret on the brisket?

124:45Is it, do you wish you hadn't eaten it entirely?

124:49Is it that you wish you hadn't eaten as much as you did?

124:51Is it that?

124:53- I think, well, most regret, I mean,

124:58if we wanna be specific, I drank way too much diet soda.

125:04My biggest regret is having drank so much diet soda.

125:08That's the thing that really was the problem.

125:10I had trouble sleeping because of that,

125:12'cause I was programming and then I was editing.

125:14And so I'd stay up late at night

125:15and then I'd have to get up to go pee a few times,

125:18and it was just a mess.

125:19- A mess of a night.

125:20- It was, well, it's not really a mess,

125:22but it's so many, it's like the little things.

125:25I know if I just eat, I drink a little bit of water

125:30and that's it, and there's a certain,

125:31all of us have perfect days that we know diet-wise

125:36and so on that's good to follow, you feel good.

125:39I know what it takes for me to do that.

125:41I didn't fully do that, and thereby,

125:43because there's an avalanche effect

125:47where the other sources of stress,

125:50all the other to-do items I have pile on,

125:53my failure to execute on some basic things

125:55that I know make me feel good,

125:56and all of that combines to create a mess of a day.

126:02But some of that chaos, you have to be okay with it,

126:05but some of it I wish was a little bit more optimal.

126:07And your ideas about eating in the morning

126:11are quite interesting as an experiment to try.

126:14Can you elaborate, are you eating once a day?

126:18- Yes.

126:19- In the morning, and that's it.

126:22Can you maybe speak to how that,

126:24you spoke, it's funny, you spoke about the metrics of sleep,

126:30but you're also, you run a business,

126:34you're incredibly intelligent,

126:36most of your happiness and success

126:40relies on you thinking clearly.

126:43So how does that affect your mind and your body

126:45in terms of performance?

126:47So not just sleep, but actual mental performance.

126:50- As you were explaining your objective function of,

126:53for example, in the criteria you were including,

126:56you like certain neurochemical states,

126:59like you like feeling like you're living life,

127:02that life has enjoyment,

127:04that sometimes you want to disregard certain rules

§15Transcript · 2:07:07–2:16:42

127:07to have a moment of passion, of focus.

127:10There's this architecture of the way Lex is,

127:13which makes you happy as a story you tell,

127:16as something you kind of experience,

127:17maybe the experience is a bit more complicated,

127:19but it's in this idea you have, this is a version of you.

127:22And the reason why I maintain the schedule I do

127:26is I've chosen a game to say,

127:29I would like to live a life where I care more

127:33about what intelligent,

127:36what people who live in the year 2,500

127:41think of me than I do today.

127:43That's the game I'm trying to play.

127:46And so therefore the only thing I really care about

127:51on this optimization is trying to see past myself,

127:56past my limitations, using zero principle thinking,

127:59pull myself out of this contextual mesh we're in right now

128:04and say, what will matter 100 years from now

128:07and 200 years from now?

128:08What are the big things really going on

128:11that are defining reality?

128:13And I find that if I were to hang out with diet soda Lex

128:18and diet soda Brian were to play along with that

128:24and my deep sleep were to get crushed as a result,

128:28my mind would not be on what matters in 100 years

128:31or 200 years or 300 years.

128:32I would be irritable.

128:34I would be, you know, I'd be in a different state.

128:37And so it's just gameplay selection.

128:41It's what you and I have chosen to think about.

128:43It's what we've chosen to work on.

128:47And this is why I'm saying that no generation of humans

128:51have ever been afforded the opportunity to look

128:55at their lifespan and contemplate that they will

129:00have the possibility of experiencing

129:03an evolved form of consciousness that is undeniable.

129:06They would fall into zero category of potential.

129:11That to me is the most exciting thing in existence.

129:14And I would not trade any momentary neurochemical state

129:19right now in exchange for that.

129:21I would, I'd be willing to deprive myself

129:23of all momentary joy in pursuit of that goal

129:27because that's what makes me happy.

129:28- That's brilliant.

129:30But I'm a bit, I just looked it up.

129:34I just looked up Braveheart's speech in William Wallace.

129:39But I don't know if you've seen it.

129:41Fight and you may die, run and you'll live at least a while

129:45and dying in your beds many years from now,

129:48would you be willing to trade all the days

129:51from this day to that for one chance,

129:53just one chance, picture Mel Gibson saying this,

129:57to come back here and tell our enemies

129:59that they may take our lives with growing excitement,

130:03but they'll never take our freedom.

130:06I get excited every time I see that in the movie.

130:08But that's kind of how I approach life.

130:10- Do you think they were tracking their sleep?

130:13- They were not tracking their sleep

130:14and they ate way too much brisket

130:16and they were fat, unhealthy, died early

130:19and were primitive.

130:22But there's something in my eight brain

130:25that's attracted to that,

130:26even though most of my life is fully aligned

130:31with the way you see yours.

130:32Part of it is for comedy, of course,

130:34but part of it is like,

130:35I'm almost afraid of over-optimization.

130:38- Really what you're saying though,

130:39if we're looking at this,

130:41let's say from a first principles perspective,

130:43when you read those words,

130:44they conjure up certain life experiences,

130:46but you're basically saying,

130:47I experienced a certain neurotransmitter state

130:50when these things are in action.

130:53That's all you're saying.

130:54So whether it's that or something else,

130:55you're just saying you have a selection

130:57for how your state for your body.

130:59And so if you as an engineer of consciousness,

131:02that should just be engineerable.

131:04That's just triggering certain chemical reactions.

131:08And so it doesn't mean they have to be mutually exclusive.

131:11You can have that and experience that

131:13and also not sacrifice long-term health.

131:15And I think that's the potential of where we're going

131:17is we don't have to assume

131:21they are trade-offs that must be had.

131:25- Absolutely.

131:26And so I guess from my particular brain,

131:28it's useful to have the outlier experiences

131:32that also come along with the illusion of free will

131:35where I chose those experiences

131:37that make me feel like it's freedom.

131:39Listen, going to Texas made me realize,

131:41I spent, so I still am, but I lived at Cambridge at MIT.

131:46And I never felt like home there.

131:49I felt like home in the space of ideas with the colleagues

131:52like when I was actually discussing ideas.

131:54But there is something about the constraints,

131:57how cautious people are,

132:00how much they valued also kind of material success,

132:05career success.

132:06When I showed up to Texas, it felt like I belong.

132:12That was very interesting.

132:13But that's my neurochemistry, whatever the hell that is,

132:15whatever, maybe it probably is rooted to the fact

132:18that I grew up in the Soviet Union.

132:20It was such a constrained system

132:22that you really deeply value freedom.

132:23And you always want to escape the man

132:27and the control of centralized systems.

132:29I don't know what it is.

132:30But at the same time, I love strictness.

132:33I love the dogmatic authoritarianism of diet,

132:37of like the same habit, exactly the habit you have.

132:41I think that's actually when bodies perform optimally,

132:43my body performs optimally.

132:45So balancing those two, I think if I have the data,

132:48every once in a while, party with some wild people,

132:51but most of the time eat once a day,

132:53perhaps in the morning, I'm gonna try that.

132:56That might be very interesting.

132:57But I'd rather not try it.

133:00I'd rather have the data that tells me to do it.

133:03But in general, you're able to eating once a day,

133:07think deeply about stuff.

133:09Like that's a concern that people have is like,

133:11does your energy wane, all those kinds of things.

133:15Do you find that it's, especially 'cause it's unique,

133:19it's vegan as well.

133:21So you find that you're able to have a clear mind,

133:23a focus and just physically and mentally throughout?

133:27- Yeah, I find like my personal experience

133:29in thinking about hard things is,

133:36like oftentimes I feel like I'm looking through a telescope

133:40and I'm aligning two or three telescopes

133:42and you kind of have to close one eye

133:44and move back and forth a little bit

133:46and just find just the right alignment.

133:47Then you find just a sneak peek

133:49at the thing you're trying to find, but it's fleeting.

133:51If you move just one little bit, it's gone.

133:54And oftentimes what I feel like are,

133:57the ideas I value the most are like that.

134:00They're so fragile and fleeting and slippery

134:04and elusive and it requires a sensitivity to thinking

134:09and a sensitivity to maneuver through these things.

134:16If I concede to a world where I'm on my phone texting,

134:21I'm also on social media,

134:25I'm also doing 15 things at the same time

134:28because I'm running a company

134:29and I'm also feeling terrible from the last night.

134:33It all just comes crashing down

134:34and the quality of my thoughts goes to a zero.

134:38I'm a functional person to respond to basic level things,

134:42but I don't feel like I am doing anything interesting.

134:46- I think that's a good word, sensitivity,

134:49because that's what thinking deeply feels like,

134:53is you're sensitive to the fragile thoughts.

134:55And you're right, all those other distractions

134:57kind of dull your ability to be sensitive

135:01to the fragile thoughts.

135:02It's a really good word.

135:04Out of all the things you've done,

135:08you've also climbed Mount Kilimanjaro.

135:11Is this true?

135:14- It's true.

135:14- What do you, why and how,

135:23and what do you take from that experience?

135:25- I guess the backstory is relevant

135:26because in that moment, it was the darkest time in my life.

135:32I was ending a 13 year marriage, I was leaving my religion,

135:35I sold Braintree and I was battling depression

135:38where I was just at the end.

135:40And I got invited to go to Tanzania

135:45as part of a group that was raising money

135:47to build clean water wells.

135:49And I had made some money from Braintree

135:51and so I was able to donate $25,000.

135:54And it was the first time I had ever had money

135:57to donate outside of paying tithing in my religion.

136:01And it was such a phenomenal experience

136:04to contribute something meaningful

136:08to someone else in that form.

136:11And as part of this process,

136:12we were gonna climb the mountain.

136:13And so we went there and we saw the clean water wells

136:16we were building, we spoke to the people there

136:18and it was very energizing.

136:20And then we climbed Kilimanjaro

136:21and I came down with a stomach flu on day three

136:26and I also had altitude sickness,

136:30but I became so sick that on day four,

136:33we are summiting on day five,

136:34I came into the base camp at 15,000 feet,

136:38just going to the bathroom on myself

136:42and like falling all over.

§16Transcript · 2:16:44–2:26:35

136:44I was just a disaster, I was so sick.

136:47- So stomach flu and altitude sickness.

136:49- Yeah, and I just was destroyed from the situation.

136:55- Plus psychologically one of the lowest points

137:00you could go through. - Yeah, and I think

137:01that was probably a big contributor.

137:02I was just smoked as a human, just absolutely done.

137:06And I had three young children.

137:07And so I was trying to reconcile,

137:09like this is not a, whether I live or not

137:12is not my decision by itself.

137:14I'm now intertwined with these three little people

137:19and I have an obligation whether I like it or not,

137:22I need to be there.

137:24And so it did, it felt like I was just stuck

137:26in a straitjacket.

137:27And I had to decide whether I was going to summit

137:32the next day with the team.

137:34And it was a difficult decision

137:36because once you start hiking,

137:38there's no way to get off the mountain.

137:40And midnight came and our guide came in

137:43and he said, "Where are you at?"

137:44And I said, "I think I'm okay, I think I can try."

137:48And so we went.

137:49And so from midnight to, I made it to the summit at 5 a.m.

137:56It was one of the most transformational moments

137:59of my existence.

138:00And the mountain became my problem.

138:05It became everything that I was struggling with.

138:09And when I started hiking, it was,

138:12the pain got so ferocious that it was kind of like this,

138:17it became so ferocious that I turned my music to Eminem.

138:25And it was, Eminem was, he was the only person

138:28in existence that spoke to my soul.

138:31And it was something about his anger and his vibrancy

138:36and his multidimensional, he's the only person

138:39who I could turn on and I could just say,

138:40"Ah, I feel some relief."

138:42I turned on Eminem and I made it to the summit

138:46after five hours, but just 100 yards from the top.

138:51I was with my guide Ike and I started getting very dizzy

138:54and I felt like I was gonna fall backwards

138:57off this cliff area we were on.

138:58I was like, "This is dangerous."

139:00And he said, "Look, Brian, I know where you're at.

139:03"I know where you're at.

139:06"And I can tell you, you've got it in you.

139:08"So I want you to look up, take a step, take a breath,

139:13"and then look up, take a breath and take a step."

139:16And I did, and I made it.

139:19And so I got there and I just, I sat down with him

139:22at the top, I just cried like a baby.

139:24- Broke down.

139:25- Yeah, I just lost it.

139:26And so he'd let me do my thing.

139:29And then we pulled out the pulse oximeter

139:31and he measured my blood oxygen levels.

139:33And it was like 50 something percent

139:36and it was danger zone.

139:36So he looked at it and I think he was like really alarmed

139:39that I was in this situation.

139:41And so he said, "We can't get a helicopter here

139:44"and we can't get you to emergency evacuated.

139:46"You've got to go down.

139:46"You've got to hike down to 15,000 feet to get base camp."

139:49And so we went down the mountain.

139:53I got back down to base camp.

139:55And again, that was pretty difficult.

139:57And then they put me on a stretcher,

139:59this metal stretcher with this one wheel

140:01and a team of six people wheeled me down the mountain.

140:04And it was pretty torturous.

140:06I'm very appreciative they did.

140:07Also the trail was very bumpy.

140:09So they'd go over the big rocks.

140:10And so my head would just slam against this metal thing

140:14for hours.

140:15And so I just felt awful.

140:15Plus I'd get my head slammed every couple of seconds.

140:18So the whole experience was really a life changing moment.

140:22And that was the demarcation of me

140:25basically building a new life.

140:26Basically I said, "I'm going to reconstruct Brian.

140:31"My understanding of reality, my existential realities,

140:34"what I want to go after."

140:36And I try, I mean, as much as that's possible as a human,

140:39but that's when I set out to rebuild everything.

140:44- Was it the struggle of that?

140:46I mean, there's also just like the romantic, poetic,

140:50it's a fricking mountain.

140:52As a man in pain, psychological and physical,

140:58struggling up a mountain, but it's just struggle.

141:01Just in the face of,

141:04just pushing through in the face of hardship or nature too,

141:09something much bigger than you.

141:11Is that, was that the thing that just clicked?

141:14- For me, it felt like I was just locked in with reality

141:18and it was a death match.

141:21It was in that moment, one of us is going to die.

141:24- So you were pondering death, like not surviving.

141:27- Yeah, and it was, and that was the moment.

141:29And it was, the summit to me was,

141:32I'm going to come out on top and I can do this.

141:35And giving in was, it's like, I'm just done.

141:40And so it did, I locked in and that's why,

141:45mountains are magical to me.

141:47I didn't expect that, I didn't design that,

141:51I didn't know that was going to be the case.

141:54It would not have been something I would have anticipated.

141:56- But you were not the same man afterwards.

142:00Is there advice you can give to young people today

142:06that look at your story,

142:07that's successful in many dimensions?

142:09Advice you can give to them

142:12about how to be successful in their career,

142:14successful in life, whatever path they choose?

142:17- Yes, I would say, listen to advice

142:22and see it for what it is, a mirror of that person.

142:27And then map and know that your future

142:31is going to be in a zero principle land.

142:34And so what you're hearing today is a representation

142:38of what may have been the right principles

142:39to build upon previously,

142:41but they're likely depreciating very fast.

142:45And so I am a strong proponent that

142:49people ask for advice, but they don't take advice.

142:54- So how do you take advice properly?

142:59- It's in the careful examination of the advice.

143:03It's actually, the person makes a statement

143:06about a given thing somebody should follow.

143:09The value is not doing that,

143:10the value is understanding the assumption stack they built,

143:13the assumption and knowledge stack they built

143:15around that body of knowledge.

143:18That's the value, it's not doing what they say.

143:20- Considering the advice,

143:23but digging deeper to understand the assumption stack,

143:27like the full person,

143:29I mean, this is deep empathy, essentially,

143:32to understand the journey of the person

143:34that arrived at the advice.

143:36And the advice is just the tip of the iceberg.

143:38- That's right.

143:39- The journey is not the thing that gives you.

143:41- That's right.

143:42- It could be the right thing to do,

143:43it could be the complete wrong thing to do,

143:45depending on the assumption stack.

143:46So you need to investigate the whole thing.

143:49Is there some, are there been people in your startup,

143:54in your business journey,

143:55that have served that role of advice giver,

144:00has been helpful?

144:02Or do you feel like your journey felt like a lonely path,

144:08or was it one that was, of course,

144:11we're all, we're all are born and die alone.

144:14But, (laughs)

144:17do you fundamentally remember the experiences,

144:21one where you leaned on people

144:23at a particular moment in time that changed everything?

144:26- Yeah, the most significant moments of my memory,

144:30for example, like on Kilimanjaro,

144:33when Ike, some person I'd never met in Tanzania,

144:38was able to, in that moment, apparently see my soul,

144:41when I was in this death match with reality.

144:44- Yes.

144:45- And he gave me the instructions, look up, step.

144:48And so, there's magical people in my life

144:53that have done things like that.

144:56And I suspect they probably don't know.

145:00I probably should be better at identifying those things.

145:06But yeah, hopefully the,

145:07I suppose like the wisdom I would aspire to

145:18is to have the awareness and the empathy

145:22to be that for other people.

145:24Not a retail

145:29advertiser of advice, of tricks for life,

145:35but deeply meaningful and empathetic

145:40with a one-on-one context with people

145:42that it really could make a difference.

145:44- Yeah, I actually kind of experience,

145:47I think about that sometimes.

145:48You know, you have like a 18-year-old kid come up to you.

145:51It's not always obvious, it's not always easy

145:57to really listen to them.

146:00Like not the facts, but like see who that person is.

146:04- I think people say that about being a parent is,

146:08you know, you wanna consider that

146:10you don't wanna be the authority figure

146:14in a sense that you really wanna consider

146:16that there's a special, unique human being there

146:18with a unique brain that may be brilliant

146:23in ways that you are not understanding

146:25that you'll never be.

146:26And really try to hear that.

146:29So when giving advice, there's something to that.

146:31And so both sides should be deeply empathetic

146:34about the assumption stack.

146:35I love that terminology.

§17Transcript · 2:26:38–2:31:24

146:38What do you think is the meaning of this whole thing?

146:41Of life.

146:42Why the hell are we here, Brian Johnson?

146:46We've been talking about brains and studying brains

146:48and you had this very eloquent way of describing life

146:51on Earth as an optimization problem

146:54of the cost of intelligence going to zero.

146:59At first through the evolutionary process

147:01and then eventually through building,

147:04through our technology building

147:07more and more intelligent systems.

147:09You ever ask yourself why is doing that?

147:13- Yeah, I think the answer to this question,

147:17again, the information value is more in the mirror

147:21it provides of that person, which is a representation

147:25of the technological, social, political context of the time.

147:30So if you asked this question a hundred years ago,

147:32you would get a certain answer that reflects

147:34that time period.

147:35Same thing would be true of a thousand years ago.

147:36It's rare.

147:38It's difficult for a person to pull themselves

147:40out of their contextual awareness.

147:42- Yeah, very true.

147:43- And offer a truly original response.

147:45And so knowing that I am contextually influenced

147:48by the situation, that I am a mirror for our reality,

147:52I would say that in this moment,

147:54I think the real game going on

148:00is that evolution built a system of scaffolding intelligence

148:05that produced us.

148:10We are now building intelligence systems

148:13that are scaffolding higher dimensional intelligence.

148:18That's developing more robust systems of intelligence.

148:28In doing in that process with the cost going to zero,

148:32then the meaning of life becomes goal alignment,

148:37which is the negotiation of our conscious

148:41and unconscious existence.

148:43And then I'd say the third thing is,

148:45if we're thinking that we wanna be explorers

148:47is our technological progress is getting to a point

148:52where we could aspirationally say,

148:57we want to figure out what is really going on,

149:01really going on.

149:02Because does any of this really make sense?

149:06Now we may be 100, 200, 500, 1000 years away

149:09from being able to poke our way out of whatever is going on.

149:14But it's interesting that we could even state an aspiration

149:20to say, we wanna poke at this question.

149:22But I'd say in this moment of time,

149:26the meaning of life is that we can build a future state

149:30of existence that is more fantastic

149:35than anything we could ever imagine.

149:37- The striving for something more amazing.

149:41- And that defies expectations

149:47that we would consider bewildering and all the things

149:54that that's, and I guess the last thing,

149:57if there's multiple meanings of life,

149:59it would be infinite games.

150:00James Kars wrote the book, "Finite Games, Infinite Games."

150:04The only game to play right now is to keep playing the game.

150:08And so this goes back to the algorithm

150:11of the Lex algorithm of diet soda and brisket

150:14and pursuing the passion.

150:16What I'm suggesting is there's a moment here

150:19where we can contemplate playing infinite games.

150:22Therefore, it may make sense to err on the side

150:25of making sure one is in a situation

150:27to be playing infinite games if that opportunity arises.

150:31So it's just the landscape of possibilities

150:33changing very, very fast.

150:35And therefore our old algorithms

150:36of how we might assess risk assessment

150:38and what things we might pursue

150:39and why those assumptions may fall away very quickly.

150:42- Well, I think I speak for a lot of people

150:46when I say that the game you, Mr. Brian Johnson,

150:50have been playing is quite incredible.

150:53Thank you so much for talking today.

150:54- Thanks, Lex.

150:55- Thanks for listening to this conversation

150:57with Brian Johnson and thank you to Four Sigmatic,

151:01NetSuite, Grammarly, and ExpressVPN.

151:04Check them out in the description to support this podcast.

151:08And now let me leave you with some words

151:10from Diane Ackerman.

151:11Our brain is a crowded chemistry lab

151:15bustling with nonstop neural conversations.

151:18Thank you for listening and hope to see you next time.

151:21(upbeat music)

151:24(upbeat music)

— A LITTLE MORE TO THINK ABOUT. —