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The Random Show! Mortality, AI, Supplements, Rock Climbing, & More

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The Random Show! Mortality, AI, Supplements, Rock Climbing, & More

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3405 segments

0:00

Kev Kev Tim, good to see you, man. Good

0:03

to see you. Let's figure out which one

0:04

there we go. Cheers. Cheers. All right.

0:09

>> You know, I know the cool kids are down

0:11

on alcohol, but every once in a while, I

0:13

think there's a place for it.

0:14

>> There's a time and place.

0:16

>> And this is the time.

0:17

>> I think this is the time and the place.

0:19

And I think paying a tax for it the next

0:21

day is a feature, not a bug.

0:22

>> Are you getting taxed harder on?

0:25

>> Of course. Yeah. Is it getting worse?

0:26

>> Every old bastard.

0:27

>> Yeah, I know.

0:28

>> That's genderneutral. gets taxed as you

0:30

can process ethanol less and less well

0:33

over time. But I'm cool with it. I don't

0:36

have that much, but today has been

0:39

hectic.

0:39

>> Yeah.

0:40

>> You know, take a little hard day. Take a

0:42

little edge off.

0:44

>> And people may not like the sound of

0:45

that. It's a little antiquated maybe for

0:47

all the cool ketamine kids. No offense,

0:50

>> but don't put that [ __ ] on me. I try it

0:53

one time and I get freaking

0:56

bastard. You [ __ ] a goat once and then

0:58

they call me the goat [ __ ]

1:01

>> Can't get around it.

1:03

>> I still stand by that experience

1:05

>> when you're doing it in a supervised

1:07

setting by a medical professional.

1:09

>> Here we go.

1:10

>> No, I'm telling you it's You've done it.

1:12

>> Of course I have.

1:13

>> Okay, so there we go.

1:14

>> Well, yeah, because I wanted to be able

1:16

to speak.

1:16

>> I saw you at a party one time and you

1:18

were just like,

1:18

>> that's not true. That's not true.

1:22

>> Still have all my nostrils intact. No

1:24

ketamine cramps, you know. I don't even

1:26

know what that is. Is that a thing?

1:28

>> That's when you use too much.

1:29

>> Okay.

1:30

>> Way, way, way, way too.

1:31

>> Oh, yeah. It hurts bad on the bladder,

1:32

right?

1:33

>> Yeah. Your bladder can get a little

1:34

grumpy or a lot grumpy as the case might

1:37

be.

1:37

>> Yeah. I'm good.

1:38

>> You know, I'm good. Kevin, random show

1:41

number 3,479.

1:43

>> Yeah. You know what's crazy, dude, is I

1:45

looked up a random show the other day

1:48

and you had a bit of hair like way back

1:53

in the day. way back.

1:54

>> We were babies.

1:56

>> I know.

1:57

>> So much [ __ ] has happened.

1:58

>> I know.

1:59

>> The only constant I think is like maybe

2:01

like Toaster who's barely alive.

2:05

>> Toaster. I know. Seriously,

2:06

>> Toaster was a tiny tiny little pup.

2:09

>> Yeah.

2:09

>> Who was chewing through the XLR cables.

2:11

>> Oh my god.

2:12

>> On your couch in San Francisco way way

2:14

way back in the day.

2:17

>> Toer's 15.

2:18

>> And I'll tell a quick little story. A

2:20

week ago, I get this call and Daria

2:24

calls me and she's like, "You got to get

2:25

over the house. Toaster is shaking

2:27

violently and he's 15. He's like running

2:30

into walls and [ __ ] you know? He's

2:31

getting up there and he's legs are

2:33

collapsing so he can't stand up and he

2:34

couldn't stand up and he's shaking

2:36

violently and I'm like just flying over

2:39

there."

2:40

>> Mhm.

2:40

>> I throw him in my car. He's on my lap

2:43

driving, you know, to get to this

2:46

emergency vet as fast as possible. And

2:48

he just sprays [ __ ] all over me. Like

2:52

literally I I heard it like I could felt

2:54

his stomach be like

2:56

and then like 10 seconds later

2:59

>> I'm not even talking like oh like oh he

3:01

had a little [ __ ] like no no no no like

3:04

shotgun against the car door like the

3:07

whole thing. And it's all down my pants.

3:09

>> We're toasty.

3:10

>> I know. But you know what's funny dude?

3:11

It's like I rushed him in and long story

3:14

short he's okay now.

3:15

>> What was it? He had gone into the vet

3:17

the day prior and he was so nervous that

3:20

he stood for he had to be there for like

3:23

a multi-our blood draw

3:24

>> because he was having some other issues

3:26

and he stood for like 6 hours straight.

3:28

>> That's too long for he can only stand

3:30

for like 10 minutes like max.

3:33

>> And so he had just overtaxed himself and

3:36

got like there's a syndrome that they

3:38

can get when they're like super stressed

3:39

out and all. So

3:40

>> little Molly's had it or big Molly.

3:42

She's on the floor right here.

3:43

>> She's sleeping. Ollie's 12. It's crazy.

3:46

>> But long story short, he's okay. But I

3:49

thought to myself, it's so weird because

3:51

when I walked in there and there was

3:52

like [ __ ] and like I'm literally I'm in

3:54

tears cuz I think I'm about to have to

3:55

put down my dog, you know?

3:57

>> Of course.

3:57

>> And I just thought it's okay. I'll do

4:01

this any day for this dude. When you

4:02

care about your animals that much, none

4:05

of that matters.

4:06

>> Yeah.

4:06

>> Like you would do anything for them. And

4:08

it's just like just that love. It's so

4:11

crazy how much you love these little

4:12

beasts. Like it's insane, dude. It's

4:15

like a kid. It's like a kid.

4:16

>> Yeah. It's

4:18

wild to think about if you really sit

4:20

down and think about it. Some of these

4:22

super common daily

4:25

experiences like communing with a dog or

4:29

pointing and having a dog recognize that

4:31

you're pointing for instance.

4:34

>> That's really rare in the animal

4:35

kingdom. That recognition of pointing as

4:38

just one example. But how unusual it is

4:40

that we have this and yes we have cats.

4:43

I grew up with four cats and two dogs. I

4:45

get it. But in particular dogs as like

4:48

companions,

4:50

co-hunters, etc. The fact that we've

4:52

evolved co-evolved in a sense

4:55

>> and sort of co-domemesticated.

4:58

>> Yeah.

4:58

>> Also, right, it's not necessarily one

5:01

way. Read the botney of desire by

5:02

Michael Pollen for more on that

5:04

>> is incredible.

5:05

>> Yeah. Right. The fact that we have like

5:07

we're totally calm having this 60 plus

5:10

pound beast with giant fangs on the

5:13

floor is nuts.

5:15

>> Yeah. I mean, I'm sure you've seen that

5:16

those Instagram posts where it's like

5:18

where I was and where I am now today and

5:20

like they show like the wild like wolf

5:22

like out in the countryside like eating

5:24

a rabbit and then they show like a

5:25

poodle in a tutu outfit and [ __ ] like

5:27

all like dme I'm going to go grab some

5:30

scraps from those weird monkeys. What's

5:32

the worst that could happen? And then

5:33

it's like 10,000 years later, right?

5:36

with a bonnet on.

5:37

>> What else is going on, Kevin? I got a

5:39

couple things on my list.

5:40

>> There's a lot to talk about.

5:41

>> There's a lot to talk about.

5:42

>> First, I'll say that lately life has

5:45

been lifing me. It's been doing all the

5:47

things. We lost a dear colleague Malik.

5:51

>> Oh man, there started

5:53

>> very notorious like just amazing early

5:58

tech just creative author

6:01

thinker.

6:02

>> Very sweet guy.

6:04

>> The nicest. Nice.

6:05

>> And we lost him within the last week.

6:07

>> Yeah, he passed away. So, that was

6:09

tough. That was

6:10

>> really tough. I found out when I was at

6:12

a a retreat. I went to a 5-day silent

6:14

meditation retreat, which is great, but

6:16

bummer to hear that. But, I mean, this

6:18

is the thing that I realized the other

6:19

day. I was thinking about, you know,

6:22

Toaster and M and other stuff I have

6:24

going on and my mom getting older and

6:26

following and all these things. And in

6:28

some sense, it's unavoidable, number

6:30

one, and number two, I kind of wouldn't

6:33

have it any other way. It's what makes

6:34

life interesting. Like when M passed.

6:37

>> You mean death?

6:38

>> Well, just everything the chaos of it

6:41

all.

6:41

>> Yeah.

6:41

>> If you can just take a step back and be

6:43

like, well, or I could just be sitting

6:46

there living a really boring life and

6:47

nothing could be happening. Like when

6:50

passed, what I felt was a severe sense

6:53

of loss and sorrow and sadness. But I

6:55

realized that that gap is just love at

6:59

the end of the day because I wouldn't

7:01

have it unless I loved this man so much.

7:04

Like I I cared for this person so much.

7:07

How lucky am I to have crossed paths

7:09

with this person to get to know them?

7:11

>> And you were tied in through True

7:12

Ventures obviously and prior to that.

7:14

>> Yeah. But like anyone in general that

7:15

you lose that you love, you know? I

7:17

mean, when I lost my dad, like that is

7:19

just a gaping hole of love manifested

7:22

through sorrow and sadness.

7:24

>> Yeah.

7:24

>> And once you realize that, it's like,

7:26

wow, I had this great father that did

7:29

all these amazing things with me.

7:31

>> And you can kind of convert that or just

7:33

be okay with it. Not that you need to

7:35

change that feeling,

7:36

>> right? Recognize that it's a consequence

7:38

of the love.

7:39

>> It's a consequence of the love, the deep

7:41

love.

7:42

>> Yeah. You know, I heard about his

7:44

passing and I want to give credit where

7:47

credit is due for a few things. Matt

7:49

Mullenweg,

7:50

>> my mutual friend. He was incredibly

7:52

close to

7:54

>> and I'm really grateful to Matt for a

7:56

few things. One, I mean, many things. I

7:58

could give a long list, but there are a

8:00

few. One is he organized a trip to

8:03

Antarctica. I've never been to

8:04

Antarctica or hadn't. And on that trip

8:07

were just a handful of people including

8:09

M. So, I got to spend quality time.

8:11

timing. Trust me, when you're in

8:13

Antarctica, you are indoors most of the

8:16

time. What that means is you're either

8:17

trying to sleep in your tent, but it's

8:19

going to be during the summer, so it's

8:20

like a spotlight in your face 24 hours a

8:22

day,

8:22

>> or you're in one of these other

8:24

structures where you're probably like

8:26

having wine and junk food, let's be

8:28

honest. And there's a lot of talking, so

8:30

we got to hang out. And M was also an

8:32

avid photographer. And so, we got to

8:34

like go to this nearby empire penguin

8:37

colony, which was a once in a-lifetime

8:39

experience. and you just sit and talk

8:43

and

8:44

if there were going to be any small

8:46

talk, which there wasn't going to be

8:47

with M or me really for that matter, it

8:50

all falls away after the first half day,

8:52

right?

8:52

>> And then everybody's kind of like

8:54

psychologically naked, right? So, I

8:56

really want to thank Matt for that

8:58

opportunity to bond with him. And I'd

9:00

spent a lot of time with him, but it was

9:02

always in these little bits and pieces.

9:04

Yeah. You know, not for several days

9:06

straight where you're basically like

9:08

locked in together.

9:09

>> Yeah.

9:10

And separately, Matt introduced me to

9:14

this short blog post by someone who

9:16

typically writes very long blog posts,

9:18

Tim Urban, called The Tail End. I don't

9:21

know if I ever sent this to you.

9:22

>> People should know by way.

9:25

>> Yeah, fantastic blog. And the tail end

9:28

makes the point among many others that

9:31

by the time you I think it's graduate

9:33

from high school, let's assume you're

9:35

headed off to college away from your

9:38

parents, you've spent something like 90

9:39

95%

9:41

of the total hours you will ever spend

9:43

with your parents by the time you

9:45

graduate from high school.

9:46

>> And when you start to visualize that,

9:48

and Tim Urban is really good at laying

9:49

it out visually,

9:51

>> it can provoke some really profound

9:53

changes for me. Yeah. I mean, just

9:54

reading that short blog post sent to me

9:56

by Matt ended up leading to taking my

9:58

family on these family trips as like

10:02

awkward and uncomfortable that was at

10:04

points cuz my family doesn't really

10:07

emote much.

10:08

>> Mhm.

10:08

>> And so you stick us together in the way

10:11

that I was together with and it's it can

10:13

be super uncomfortable

10:16

>> but making the effort right at least

10:18

feeling like look

10:20

>> this runway is not infinite.

10:22

>> Yeah. And it's like, let me just make

10:23

the effort. And I'm glad I did because

10:24

we got to a point where it's like with

10:26

my dad's mobility, he's really

10:28

compromised. He needs a wheelchair now

10:30

for a lot.

10:30

>> I just saw him a few days ago and it was

10:32

great to see him, dude. It was so great

10:34

to see him. He's so kind. He's like,

10:37

Kevin, like so happy and you know, he

10:39

has a little cane and it was just like

10:41

so sweet to see him, man. I hadn't seen

10:43

him for like years. It had been like

10:45

seven years or something like that.

10:46

>> Something like that. And I'm glad I took

10:48

those trips because before you know it,

10:51

you can't do it anymore. And it makes me

10:54

think of, you mentioned meditation. This

10:56

really good short, I'll call it a

10:58

meditation for simplicity, but

11:01

>> it's like an audiobook chapter by Sam

11:03

Harris called The Last Time. I think

11:04

it's called The Last Time. And he

11:07

reflects on these various experiences

11:10

that at the time you don't recognize are

11:13

the last time for something, right? So

11:15

he he went skiing. He went skiing. He

11:18

went skiing. And there was a time when

11:19

he stopped, but he didn't realize that

11:21

that was going to be the last time,

11:22

>> right?

11:24

>> And you just [ __ ] don't know. Do you

11:27

ever try and like I think about this

11:29

dude and then I try and do it one more

11:31

time.

11:31

>> Yeah, that's right. I always end up

11:33

injured, dude. I went to the bouncy

11:35

house with my kids and like I'm 49, you

11:37

know, and I was like, I'm going to

11:39

[ __ ] do a flip right now. And like

11:40

literally people were like, "Don't do

11:42

it. Don't like like call me off, you Oh,

11:44

and I did it and I stuck it and it felt

11:47

good.

11:47

>> You're good on a trampoline.

11:48

>> Might be my last time.

11:49

>> It might be your last time. You are good

11:51

on a trampoline. This is so weird, man.

11:53

Dude, I kid you not. I had a dream last

11:55

night of the two of us going to House of

11:58

Air at Chrissy Field in San Francisco

12:01

and you were doing like front flips off

12:02

your knees. You dropped your hat and

12:05

then you like kicked the trampoline to

12:06

bounce it back up to your head and I was

12:07

like, "What?"

12:08

>> Wait, wait, wait, wait. So, you know, I

12:09

sent you that video of me dropping my

12:11

hat and kicking it back.

12:12

>> You can do it live, too. Yeah. Yeah.

12:15

Okay. So, it was just made it way in the

12:16

dream

12:16

>> and I was just like, "What?" I literally

12:18

had that in my dreams last night. That's

12:20

wild.

12:20

>> And I had the assless chaps on like I

12:22

normally do when you're

12:23

>> Yeah, you had the ass traps on which

12:24

like depending on your angle can be kind

12:26

of awkward.

12:26

>> Yeah, exactly. Cuz you like doing the

12:28

straddle flip.

12:31

>> So, it's a little awkward.

12:32

>> I've heard about these dreams before. I

12:34

know.

12:34

>> I always text them to Kevin. I'm like, I

12:36

was thinking of you last night.

12:37

>> The chaps were back.

12:39

>> So, what do you got, man? I mean, people

12:41

should check out My hands are too

12:42

sweaty, so I'm thinking about

12:44

>> death.

12:45

>> Yeah. In the chat.

12:48

>> Wow, that's the perfect audio.

12:50

>> The uh Well, the retreat was fantastic.

12:52

I spent 5 days going really deep on my

12:56

[ __ ] doing a lot of work on it.

12:59

>> Moo,

13:00

>> which you can listen to Henry Shikman on

13:02

your podcast if people are interested

13:03

about what Zen is all about, like real

13:05

true traditional Zen with coons. And you

13:08

probably heard that sound of one hand

13:10

clapping. That actually is a one of 500

13:12

plus cohons. Yeah, it was fantastic. I

13:15

had a couple little micro insights,

13:17

which was good. And I was kind of rushed

13:19

through to the Zen master to explain

13:21

them and try and get some clarity on

13:22

them, which is great.

13:23

>> How do you know that you're having a

13:24

micro insight? So, it's not like my

13:26

balls are shaving in this position. It's

13:28

something else.

13:29

>> Yes. This

13:32

but close. No, I essentially was sitting

13:36

and you know Henry, one of the Zen

13:39

masters who you've had on the show, uh

13:41

dear friend of ours was there and then

13:42

his Roshi from Japan was there. So it's

13:45

very special and then comes every two

13:46

years.

13:46

>> What's his name? Yamada

13:49

Roshi. Yeah. So basically I was kind of

13:52

pulled Henry aside. You're not supposed

13:53

to. He's not talking. But I was like

13:55

he's like you know how's it going? Like

13:56

this and that. And I was like well I had

13:57

this thing happen. What do you think

14:00

about this? And he's like, "You got to

14:02

come with me right now."

14:03

>> Well, not come with me, but he like got

14:05

me right in front cuz there's a line to

14:07

see the Roshi to go have your private

14:09

interview where you go and like check

14:11

your practice with them. Yeah.

14:12

>> So, it's behind closed doors. You go in,

14:14

you sit down with the Roshi. You

14:15

typically get between two and 10 minutes

14:18

to sit down and talk about your progress

14:20

on your practice. And you do that like,

14:22

you know, once every day and a half when

14:23

you're out there.

14:24

>> Mhm.

14:24

>> That's cool.

14:25

>> Enough to where Henry was like, "You

14:27

should go talk to him right away.

14:28

>> Skip the line." TSA preaching. go

14:30

through the free check and it was

14:32

beautiful and it was a it was a micro

14:34

little thing.

14:34

>> I can share it if you're curious.

14:36

>> Yeah, of course I'm curious.

14:37

>> Yeah. So, I'm looking forward to hearing

14:38

myself talk. That's why I'm here talk to

14:40

you.

14:41

>> So, I'm sitting here staring against the

14:42

wall because in Zen you stare against

14:44

the wall with your eyes open and you're

14:46

staring about 3/4 down kind of just

14:48

glancing out. I'm working on my co and

14:49

for people that don't know how you do

14:51

that is essentially on the outreath you

14:53

just slowly internally

14:56

say your co. It's almost like a mantra

14:58

in some sense, but a little bit more

15:00

involved.

15:01

>> Yeah. It's like a question you're kind

15:03

of asking yourself slowly that doesn't

15:04

make sense and eventually it pops. But

15:07

what happened is I had about two seconds

15:11

of this sense that

15:14

there was and this is going to be hard

15:17

to explain because it's not from the

15:18

world of thought which is already hard

15:20

to explain.

15:20

>> It's like a sneeze in the perennium. No.

15:24

>> No.

15:24

>> All right.

15:25

>> Close. I had a sense of nothing lacking.

15:28

>> That sounds nice.

15:29

>> Nothing needed to be added and nothing

15:32

even possibly could be added and nothing

15:34

possibly could be taken away because

15:37

everything

15:39

at that moment was full in the way that

15:42

it should be.

15:44

>> But what was interesting about it is

15:48

it wasn't an emotion. It was just like a

15:50

steady state of being. So it wasn't

15:53

like, "Oh, I feel free right now." No,

15:55

none of that. It was just like, "Oh,

15:59

this everything is here

16:02

perfectly present."

16:05

And it was just

16:08

wild. Wild in what sense? In the felt

16:12

sense of that experience or

16:15

>> wild in the sense that wild in the I

16:18

just drank too much tequila after not

16:19

having much tequila since. I haven't had

16:21

any tequila, but in the sense that we

16:23

often times so often like go inside in

16:26

in our into our brain to try and find

16:30

something, figure something out, an

16:33

emotional state that's either bothering

16:35

you or feels good or feels bad or

16:36

something else. And then just to know

16:38

that everything, and I don't mean like

16:41

objects, everything was one

16:45

unit of nothing lacking.

16:47

>> Mhm. And it was just a micro sense of

16:50

kind of like, oh, there's actually

16:53

nothing to do because everything's

16:56

already here.

16:57

>> Yeah.

16:58

>> And they talk about this in Zen a bit

17:00

where you already have everything that

17:02

you need.

17:04

>> So it's just they call the removal of

17:06

the veil. Mhm.

17:08

>> So it's like it's an expansive awareness

17:10

that you get from

17:12

a deep continued practice over years and

17:15

decades.

17:16

>> Mhm.

17:16

>> But it was already there all along.

17:18

>> Can I give a shameless plug?

17:19

>> Yeah, let's hear it.

17:20

>> All right. So you and I are both

17:22

involved with the way which is this

17:24

guided single path meditation app which

17:29

is guided by Henry Shukman who you

17:31

mentioned

17:32

>> and it's the

17:35

sort of progressive development of

17:37

skills on a single path which I really

17:39

like as opposed to just what is the

17:41

meditation dour with no coherence

17:44

>> and a few of my favorite meditations I

17:48

have a lot of different sessions

17:49

bookmarked and I've done hundreds and

17:51

hundreds and hundreds. And by the way,

17:52

for people who are like, "Ah, these guys

17:53

are just shilling their bags."

17:57

>> I do think it can be a good business,

17:58

but this is sort of a ideologically

18:02

philosophical

18:04

investment

18:06

>> of time and money, right?

18:07

>> It's like the reason we invested in the

18:09

dog aging study with rapomy. Like

18:12

University of Washington, it's like this

18:13

needs to exist.

18:14

>> These exist,

18:15

>> it's good for the world. Let's try it.

18:17

Yeah. So, sure, we've got some chips on

18:20

the table, but this is this is mostly

18:22

because we believe in it.

18:24

>> And a few of my favorites, if people

18:26

ever try it,

18:28

Whole Earth is Medicine is one. Another

18:31

one is This Too is me, which makes me

18:33

think about what you're saying.

18:35

>> So, this too is me

18:38

>> is a meditation led by Henry, which this

18:43

is going to sound maybe esoteric, but

18:45

it's not. When you recognize that

18:49

all of the things you experience are

18:50

mediated by your mind,

18:54

>> right? And therefore, like when you hear

18:56

something, when you feel something, when

18:58

you're interrupted by something,

19:01

etc., etc., anything you can possibly

19:03

imagine experiencing is also you because

19:07

ultimately

19:09

it is entirely mediated by your mind.

19:12

Let's just use that instead of brain.

19:15

And it's incredibly, at least for me,

19:18

and I'm not comparing it to your

19:20

experience because I think it's probably

19:21

characteristically different, is

19:23

incredibly relaxing to let go even just

19:28

for a moment because my brain is like

19:30

the ultimate

19:34

like

19:35

>> dog chasing a squirrel kind of brain,

19:38

right? Like I'm always looking for

19:39

something to fix, something to improve,

19:41

what I need to do, what is happening

19:43

next week. And meditation is

19:46

>> you are the squirrel.

19:47

>> I am the squirrel. It right. It can be

19:49

excruciatingly painful, right? Like

19:52

meditation can be super hard.

19:53

>> That's a very common thing. People are

19:55

like, I can't do this.

19:56

>> But when Henry gives you permission to

19:58

include all of that as you I know this

20:02

might sound very bizarre. It allows you

20:05

to kind of drop this burden that you

20:07

didn't realize you were carrying. So, in

20:10

any case, you don't have to do a

20:12

week-long meditation retreat if you're

20:14

just doing 10 minutes twice a day. And I

20:16

do think there's some alchemy to twice a

20:18

day. I don't know why exactly. I have

20:21

some theories around Vegas nerve

20:23

stimulation and stuff, but you get a lot

20:25

out of it.

20:26

>> So, in any case, I didn't mean to

20:28

interrupt your story. No, I think

20:29

there's two things that I love that

20:31

Henry says quite often when he starts

20:33

some of these meditations, which is take

20:36

everything that you came in the door

20:37

with, like all the thoughts, worries,

20:39

emotions, things, and leave it at the

20:42

door just for now.

20:44

>> You can come back to it in 20 minutes,

20:46

>> but just for now. The permission to set

20:48

those things down for yourself just for

20:51

now

20:52

>> is such a beautiful thing. And then like

20:54

the little instructions where he's like,

20:56

"Drop your jaw an eighth of an inch."

20:58

Yeah.

20:58

>> And I'm like, "Whoa, I didn't even

20:59

realize I was Can I tell you something

21:01

crazy about that?"

21:02

>> Yeah.

21:02

>> All right. So, I got fitted for a

21:05

mandibular device, which is a fancy way

21:07

of saying a double-decker mouthpiece.

21:10

>> Yeah.

21:11

>> That is an easier approach to resolving

21:16

sleep apnnea or snoring. So, I don't

21:19

snore a ton, but every once in a while I

21:21

do. Drives my lady insane,

21:23

understandably. And if you take the jaw

21:28

and drop it down an eighth of an inch

21:30

and forward an eighth of an inch, you

21:32

open your airway.

21:34

>> Mhm.

21:34

>> And I was thinking about that because

21:37

Henry will often say, as you're alluding

21:39

to, like drop your jaw

21:41

>> and leave it forward as if it's resting

21:43

on a small pillow ever so slightly, and

21:46

it increases your air flow.

21:47

>> Mhm. I mean, these ancients hit on some

21:50

stuff by trial and error

21:53

>> that really just works. It's like, yeah,

21:55

if you want to have better respiration

21:57

while you're meditating

21:59

>> and better alignment and blah blah blah

22:01

blah blah,

22:03

just do what Henry's describing. And I

22:05

will say his doulet British tones.

22:08

>> Yeah.

22:08

>> If you just want a relaxing voice,

22:11

>> Yeah. that will help you with chilling

22:13

the [ __ ] out when your monkey mind is

22:15

ricocheting inside your skull. Like, try

22:18

Henry out. Like, you can find free stuff

22:20

everywhere. I've had him on the podcast

22:21

a bunch as well as meditation Mondays

22:23

for a while, which were these very short

22:25

episodes of guided meditations. In any

22:28

case,

22:28

>> yeah, it's great.

22:29

>> I've been so It's the right word. I mean

22:31

overjoyed is this sounds too dramatic

22:34

but I'll just say happy for you to watch

22:37

your path with meditation cuz it seems

22:39

like you get so much nourishment and

22:42

grounding from it and no offense like

22:45

you're kind of a spaz you're kind of

22:48

>> you're kind of spazz like you get

22:50

excited about [ __ ] and then you drop

22:52

stuff that is very well exemplified and

22:54

like Tim you got to buy this stock and

22:55

then you never tell me when you sell and

22:56

I'm like oh [ __ ] I'm [ __ ] Oh, but you

22:58

want to talk about hold cuz you winner.

23:03

>> Yeah,

23:03

>> you should have held. It's fine.

23:04

>> No, but anyway, literally Tim gives me

23:07

this tip and I'm like, "All right, I'm

23:08

in." And then like a day and a half

23:10

later, I'm down like I know that's why

23:13

you got to wait. But the point of the

23:14

story is I thought this meditation thing

23:17

just like every nine months you're like

23:20

I'm moving to Android. I'm like, "Let me

23:22

start the timer for two weeks before you

23:24

come back to iPhone.

23:27

I'm like, "Yeah, this meditation thing."

23:29

Yeah, sure. We'll see. I give it two

23:32

weeks. And you've stuck with it.

23:33

>> Come up on five years now.

23:35

>> Yeah. It's really made me

23:38

happy as your friend to see something

23:40

that gives you that consistency.

23:44

>> That's it. There's nothing more to add.

23:46

I've been really, what's the right word?

23:50

Not sure of the right way to put it.

23:51

I've just been very reassured.

23:53

>> Yeah. by you having that constant in

23:56

your life.

23:56

>> One of the things I'm curious about,

23:58

speaking of constants and kind of like

24:00

how things changed since we've known

24:01

each other and you had hair and all that

24:03

other [ __ ] My hair wasn't great.

24:04

>> Still got plenty of hair. It's not on my

24:06

head. Yeah,

24:06

>> exactly. The braids down there. Um the

24:11

the question I'm I'm I'm curious about

24:13

is I've been thinking a lot lately as I

24:15

kind of march towards 50. What are the

24:18

things that I've always said that I want

24:19

to do that I'm just like, you know, I've

24:22

got a thousand bookmarks on Instagram

24:23

like all these Japanese woodworking

24:25

things and like

24:26

>> it's always woodworking little always

24:28

woodworking.

24:28

>> Well, I even have, you know, this is how

24:30

bad of my speaking the monkey mind and

24:32

bouncing around. I literally have for

24:34

some reason the algorithm is now giving

24:37

me like those [ __ ] boats inside

24:39

of bottles. People making the boats in

24:41

the bottles and I'm like am I going to

24:42

be a boat in the bottle guy? Like I

24:44

don't know. Maybe. Like I realize now I

24:47

think these next couple decades

24:49

>> I want to stop bullshitting myself and

24:51

stop saying like hey one day

24:53

>> one day I'll get in Japanese

24:55

woodworking. One day I'll do this and

24:57

really start doing some things.

24:58

>> Yeah.

24:59

>> You've been really good cuz you archery

25:02

hunting like the stuff that you've

25:03

gotten into you've gone deep on in the

25:05

last few years.

25:06

>> Yeah. Super deep. Are there any things

25:08

that are on your kind of bucket list of

25:09

things where you say one day, you know,

25:12

you're busy with your podcast and all

25:13

the [ __ ] you got going podcast, shoot me

25:15

in the head. It's it's fine and it's fun

25:18

most of the time, but it's so crowded

25:20

and it's like, man, if if 20 other

25:22

people are trying to do the same job, I

25:23

don't want to do this job.

25:24

>> Yeah. Right.

25:25

>> It is wild how many new podcasters there

25:27

are out there that they're also

25:29

optimizing every little freaking thing.

25:31

all the thumbnails like what you need to

25:34

know before your crypto crashes next

25:36

week now and I'm like ah god

25:39

>> I just don't want to play that game. And

25:42

>> for me I would say the most top of mind

25:45

is rock climbing. Actually I just did

25:48

some outdoor rock climbing a couple days

25:50

ago and

25:51

>> I love rock climbing. I was always for

25:54

at least the last 15 years limited by my

25:56

right elbow which I had surgically

25:57

repaired. So, it's ready to go. And I

26:00

want to do some multi- pitch stuff in

26:02

Yose,

26:02

>> dude. Let's go.

26:04

>> Yeah. So, I don't know if I want to say

26:06

this.

26:08

>> All right, that's a good start. So, you

26:11

is a big rock climber.

26:12

>> Yeah. And he goes, he goes out to

26:15

Euseite.

26:15

>> I'm sure

26:16

>> we should go cuz he's invited me to go

26:19

up there and do some climbing.

26:20

>> He looks like someone who would be good.

26:21

>> Apparently, he's amazing. So, and I'm

26:23

like, dude, I can't go do multi- pitch

26:25

with you. And he's like, ah, just come

26:27

out. We'll have fun. Blah blah blah.

26:28

>> No, that's how you end up [ __ ]

26:30

>> Exactly.

26:31

>> I did multi- pitch when I was like 24

26:35

and it was like three pitches.

26:37

>> Like I didn't I didn't do ease.

26:40

>> Yeah. No, that's a commitment.

26:41

>> Yeah. So the idea of having something

26:43

like that to strive for having some type

26:48

of physical goal like that for me is

26:50

very helpful because just

26:54

not dying like training to not die

26:56

sooner than is necessary is not

26:59

sufficient for me. I'm just like that's

27:00

such a

27:02

>> depressing uninvigorating goal.

27:06

>> I'd much rather have something

27:08

>> that has a deadline, right? It's like,

27:10

"All right, you need to be able to do

27:12

X." In the case of the archery, it's

27:13

like Lancaster Classic. Here's the date.

27:16

You need to do this type of training and

27:18

this type of volume with this type of

27:20

deliberate practice.

27:21

>> Yeah.

27:22

>> In order to be prepared to train and

27:24

then compete, right? Okay.

27:26

>> Similarly, for something like a multi-

27:28

pitch, it's like, okay, you can break

27:31

that down. And I just enjoy doing that

27:32

stuff,

27:33

>> dude. So, let me ask you a question. The

27:35

number two, I don't know if you saw this

27:36

on my my story list. The number two

27:38

story I had was this guy Michael

27:40

Eckhart. Do you know who? No. No idea.

27:42

>> Oh my god. Okay. So, Herman and Rogan,

27:45

all these guys, they've talked about him

27:47

publicly about this guy. He has won

27:50

multiple pull-up world championships.

27:52

>> Okay.

27:53

>> And dude, when you watch him do a

27:54

pull-up, he's kind of one of those guys

27:55

that can bring the bar all the way down

27:57

and do like the circer and all that

27:59

stuff.

28:00

>> Yeah. Like where you can walk with your

28:01

feet and [ __ ] all the calisthenic

28:03

stuff. But he has a series of videos

28:05

that that teach you how to do finger

28:07

strength training

28:09

>> and I bought his course and I'm doing

28:12

this right now. But you got me into that

28:14

wooden device.

28:14

>> The nug.

28:15

>> The nug. So dude, you got to watch his

28:17

videos. They're amazing. Like seriously,

28:19

Joe's really into him. Like this guy

28:22

name is Michael Eckhart. You can find

28:23

him on Instagram. And it's all about

28:26

grip strength, pull-ups, and he's not

28:29

big, but he's shredded. Yeah. And I

28:31

think when I think about like the next

28:33

10 years, like I don't need to be big

28:35

big. It's probably not what you want,

28:38

>> right? Especially for rock climbing.

28:40

>> Yeah. Exactly. I mean, you need to be

28:41

lean, right? And strong. And that's what

28:44

I love about this. So, I'm getting into

28:46

I'm doing these every single day. Well,

28:47

I'm 2 days in, but

28:51

I'm getting into it, you know. But tell

28:53

us about the nug, cuz that was something

28:54

that you turned me on to.

28:55

>> The nug. I mean, I have it in my

28:56

suitcase at the hotel here.

28:59

It's just a simple little

29:02

wooden device. It looks like a very

29:05

large bar of soap with these different

29:07

indentations carved into the sides and

29:09

>> like little finger indentations.

29:11

>> Yeah, exactly. So, you can use a

29:12

carabiner to connect it to say a cable

29:14

machine of some type in any gym. And

29:18

look, you could use a loading pin and

29:20

all this then the other thing and a

29:21

daisy chain. But let's put that aside.

29:22

at a gym, you could use a cable and

29:25

connect it through the loop with a

29:26

carabiner and work on your hand

29:28

strength.

29:29

>> And you brought this to Santa Fe when we

29:30

were out there doing that meditation

29:31

thing.

29:32

>> I did. Yeah. I mean, it's literally

29:34

something small enough to slip into my

29:36

sweatshirt pocket. So, it's easy to

29:38

travel with.

29:39

>> I always travel with that and a band for

29:43

multiple purposes for like something

29:45

called DNS kind of core exercises. And I

29:48

>> Oh, yeah. I know DNS.

29:49

>> Yeah. So, I use a band for that and it's

29:52

incredibly easy to travel with

29:53

>> and then a handful of other things.

29:55

Something called an alpha ball, which I

29:57

use for different types of kind of

29:59

mobility. It's the size of like a very

30:01

large soft ball. And all this stuff fits

30:05

into the corner of a suitcase. And then

30:09

I'll do also something that maybe we

30:13

haven't talked about called Abrahes,

30:15

which so Abraham Hamson, Emil

30:19

Abrahamson, very well-known rock climber

30:21

on YouTube. And Abra hangs

30:24

>> I'm writing this down right now. Abra

30:26

hangs.

30:26

>> Abra hangs are pretty simple. I mean,

30:28

it's partial body weight hangs in

30:30

different positions for 10 seconds on,

30:33

50 seconds off for 10 minutes. And you

30:35

do that twice a day. And it's very very

30:39

moderate in intensity

30:41

>> with like a wooden kind of rock climbing

30:43

kind of like

30:44

>> use a hangboard. Yeah.

30:46

>> I mean you could also use a pull-up bar

30:47

depending on how you position your

30:49

hands.

30:49

>> And that's what I was doing in Santa Fe

30:51

was that kind of stuff. 10 seconds on 50

30:53

seconds off. And

30:55

>> the endurance and strength gains that

30:58

you get in your hands are just insane.

31:00

Your I should say your lower arms.

31:03

>> And

31:05

it really helps. So, I've been doing

31:07

indoor climbing, but ultimately I'm

31:08

like, you know what? As a stretch goal,

31:11

multi- pitch outdoor yuseite.

31:13

>> Yeah.

31:14

>> And I am deadly terrified of heights.

31:17

Deadly. Like just talking like look,

31:19

look at my hands. Like I'm sweaty just

31:21

talking about.

31:22

>> Dude, when I watch Free Solo, my hands

31:24

are sweating the entire time.

31:26

>> Yeah. Yeah.

31:26

>> For people that haven't seen that

31:27

documentary, even if you're not into

31:29

rock climbing, that is amazing.

31:31

>> Yeah. Watch Free Solo. It'll freak you

31:33

out. So, that's one that I'm thinking

31:35

about going deep on. I'd say that's very

31:37

high up on the list because

31:38

>> that's awesome, dude. We're going to be

31:40

Let's do that together. I'm totally

31:41

down. I'm into it.

31:42

>> I am totally into it. I mean, rock

31:44

climbing when approached in a reasonable

31:46

way, like a systematic, reasonable way,

31:48

not with like crazy dino movements on

31:50

bouldering necessarily. I mean, look,

31:53

younger bodies can handle it. Certain

31:54

bodies can handle it. My body, not so

31:56

much.

31:57

>> Yeah.

31:57

>> I do not want to fall repeatedly from

31:59

10, 15 feet up. I'm just not into it.

32:01

So,

32:03

In the case of doing it reasonably

32:05

though, for instance, I spent a bunch of

32:07

time I've spent a lot of time in Utah

32:09

and climbing in some of the Salt Lake

32:11

City indoor gyms. You have incredible

32:14

athletes and I'll I'll make that a

32:18

little finer tuned. When I would go to

32:21

the gym, it was generally like 11:00

32:23

a.m., right? Who the hell goes to the

32:26

rock climbing gym at 11:00 a.m. on a

32:28

weekday? These are retirees

32:31

>> and moms. So you would see for instance

32:34

these like 60, 70, 75, almost 80 year

32:38

olds were doing like 5'11 plus.

32:42

>> This is when you were single. So that

32:43

was like prime hunting.

32:45

>> Exactly. Cougarville. And

32:48

you would just see these people in their

32:50

60s and 70s doing things that I could

32:53

not even imagine doing with complete

32:56

inversion on overhangs.

32:57

>> Oh yeah. I've seen this. 60, 70 ft up,

32:59

you had the national speed climbing

33:03

team, you had Olympians, but more than

33:06

like the young guns, right, the

33:08

15year-olds who are doing all this crazy

33:09

stuff because they're impervious.

33:11

>> Yeah.

33:12

>> It was the people in their 60s and 70s

33:15

who were climbing every day that

33:18

inspired me to want to take this more

33:20

seriously. So, I was like, "Okay,

33:22

>> I want to play the long game here.

33:24

>> What can I do that's fun? It's a puzzle.

33:27

There's a lot of Tetris.

33:28

>> They literally call bouldering they call

33:31

them problems.

33:31

>> Yeah. Problems. Yeah. Exactly. And so

33:34

there's a lot of brain power involved

33:36

and also it's just to give an idea of

33:39

the technicality. I mean there are for

33:42

example women who cannot do five

33:44

pull-ups who can climb 513 514. That's

33:49

very very very very hard. Just for

33:51

people who have no reference point like

33:53

world class like 514 515 like insane

33:55

insane. Like that's when you're in the

33:57

magazines.

33:59

>> And it's because of sort of the

34:03

technical adeptness. And yeah, there's

34:04

like ape index and other physiological

34:06

factors that play into it. But that is a

34:09

very long answer to your question of

34:12

what I'm thinking about now, which is

34:14

rock climbing. The archery was great and

34:16

the competition was fantastic. I love

34:18

competing. However, archery is by

34:21

definition incredibly solitary. like

34:24

you're just by yourself doing the same

34:25

thing over and over and over again

34:28

thousands of times.

34:29

>> And

34:31

I have had enough of that in my life.

34:32

I've hit my quota.

34:34

>> I want to hang out with other people.

34:35

>> Timing is super social cuz you'll sit

34:37

there and if neither of you can do it,

34:38

you'll you'll be like, "Ah, like what if

34:40

you put your like foot in like that and

34:43

like kind of lunged up that way and

34:45

stretched, you know what I mean? Like

34:46

>> Yeah. And then you can ask other people

34:48

for tips like beta, right? Hey, can you

34:50

give me some beta on this?"

34:51

>> It's fun.

34:52

>> It's really fun. I just love it. You

34:55

know, I wanted to mention something if

34:57

people haven't read it. The Blade

34:59

Itself, which is a series, it's not very

35:02

long. I think it's two or three volumes

35:04

by Joe Abberrombie. It's fantasy novels.

35:07

They're really good. The audio books are

35:09

incredible. And the reason I thought of

35:11

this, the Blade itself,

35:14

is because of our conversation around M

35:17

and Toaster. And you know, a friend of

35:19

mine just died in a plane crashes. Less

35:22

than two weeks.

35:22

>> Wait, the one that the Nets one that

35:25

went you knew him?

35:27

>> Yeah, Josh.

35:28

>> Oh, god. That was a latitude, too.

35:30

>> Yeah, I know. I know. I know. So, you

35:33

just don't know when your time is up.

35:34

And in the blade itself, I mean, there

35:36

are a lot of serious sucks.

35:38

>> Yeah. Thanks. And we weren't like super

35:40

close friends, but certainly like

35:42

friendly, you know, acquaintances like

35:44

we've It wouldn't be strange to text.

35:47

>> And you just don't know when your time

35:49

is up. And the blade itself explores

35:52

this in a million different dimensions.

35:55

It's really really outstanding. I've

35:57

read I say that as someone who's read a

35:58

lot of fantasy

36:00

and it just talks about the randomness

36:02

of life or death and war, right? It's

36:05

like you happen to like squat down, take

36:07

a [ __ ] and the guy next to you gets an

36:08

arrow through the head. It's like it's

36:10

just dumb luck.

36:11

>> Yeah. Yeah. which is a way to I suppose

36:14

reiterate the gratitude piece that you

36:18

were mentioning earlier. So, I mean

36:20

that's going to be a tough act to

36:22

follow, but where do you want to go from

36:24

that?

36:24

>> Yeah, I mean a few things. Let's change

36:27

it up into Well, let's just go straight

36:29

into like working out. Have you tried

36:31

this?

36:32

>> Yeah, I have actually.

36:33

>> Okay. I really like it. So for people

36:35

that are on audio, I just got turned on

36:37

to this new protein called Pioneer

36:39

Pastures and it's 30 grams in this

36:41

little tiny shake.

36:42

>> It's A2, so it has lactose removed and

36:45

it's also from that special genetic cow.

36:46

Do you know more about the A2? Can you

36:48

speak to

36:48

>> I've heard about the A2. I don't know a

36:49

whole lot about it. It's like the whole

36:51

and some other cow and da da da da.

36:54

>> More people tolerate A2 better than not.

36:58

I don't get any stomach issues or

37:00

anything with this type of whey protein.

37:02

Anyway, I'm not an investor or any [ __ ]

37:04

like that. You can get it at Target or

37:05

whatever. It's tasty as hell and it's 30

37:08

grams and I don't know like I'm trying

37:10

if you're trying to put a little muscle

37:11

mass on.

37:12

>> I love that this is next to the Lo

37:13

tequila.

37:14

>> Yeah, exactly. I mean, you can mix them

37:16

if you want.

37:16

>> Everything a growing boy needs.

37:17

>> Anyway, I just I just wanted to know if

37:18

you had tried it cuz like we always This

37:20

is the random show. We talk about [ __ ]

37:21

>> Yeah, I tried it.

37:22

>> You like it?

37:22

>> I do. Yeah. There was a gym I can't

37:24

remember exactly. I think it Brooklyn

37:26

Barbell Club where they sold this and I

37:28

tried it then and I did. Yeah. Tolerated

37:30

it super well. didn't get the grumpy

37:32

guts. Yeah.

37:33

>> As one might.

37:33

>> What's your favorite protein? Out of

37:35

curiosity.

37:36

>> I mean, my protein, I mean, this is a

37:38

softball pitch, but

37:40

>> funny you should ask, Kevin,

37:42

>> and look, I'm involved with this one,

37:44

but you know what? I It's like I always

37:47

disclose. Have you noticed how few

37:49

[ __ ] people disclose what they're

37:51

involved with? They're like, "Yeah, I've

37:52

heard of this great thing. Oh my god."

37:54

And they never disclose they're

37:55

involved. The fact that

37:56

>> you could literally go to jail for that

37:58

[ __ ]

37:58

>> No, I know. Uh, but the FTC doesn't

38:00

enforce that stuff. Anyway, I mean,

38:02

right now, like I'm traveling with Maui

38:04

Nui as usual. This one though is kind of

38:06

interesting.

38:07

>> I probably get 40% of my protein from

38:11

Maui Newi venison. This is wild

38:13

harvested axis deer from Hawaii. There's

38:16

a long story there, but incredibly

38:18

nutrientdense.

38:19

>> I love this [ __ ] And this is not an ad,

38:21

but I do have a hard question for you.

38:23

Like a real hard question. And this is

38:25

how you know that it's not an ad because

38:27

what I'm about to say. Let's hear it.

38:28

>> Processed meat nitrates

38:31

>> linked to a lot of cancer and bad [ __ ]

38:33

>> What are your thoughts on that?

38:34

>> This is very very very minimally

38:36

processed. So you can get summer sausage

38:39

or the sticks. This is free of most of

38:41

that [ __ ]

38:42

>> What do you think that is? Cuz it is

38:43

real. Like people that eat more like

38:46

nitrate processed ultrarocessed meats.

38:48

>> Yeah. If it's ultrarocessed and the

38:50

shelf life is like 3 years, I would

38:52

raise an eyebrow and probably hit pause.

38:54

So the fact of the matter is most of

38:55

this stuff that is minimally processed

38:58

almost definitionally is not going to

39:00

last very long on the shelf.

39:01

>> What do they mean by minimally processed

39:03

when you see like a a meat stick? Like

39:05

what do you think about like that versus

39:07

is it the amount of salt content that

39:09

creates the nitrates? No, no, it's

39:11

actually nitrates are a totally separate

39:13

category. So you're looking to I think

39:15

an easy heruristic for this is just

39:18

shelf life, right? Like how long will

39:20

this

39:20

>> How long are those?

39:21

>> Uh your eyes are going to be better than

39:23

mine. If you can read the size two font

39:25

on this, then you can tell me.

39:26

>> Good then.

39:27

>> Give it a go. I'll buy you some time. In

39:29

the meantime,

39:29

>> 27 years.

39:30

>> No, I'm just kidding. Yeah.

39:32

>> 25 years.

39:34

>> It doesn't say on here.

39:35

>> Yeah, it'll say somewhere on the box.

39:36

There we go.

39:37

>> Oh, buy.

39:38

>> Yeah, 27. So, it's like less than one

39:40

year, I think, actually. Looking at

39:41

here.

39:42

>> Yeah, less than one year. Wow. And what

39:44

makes this interesting is that this I

39:47

give also Molly looks really good for 12

39:50

years.

39:50

>> Mhm.

39:50

>> I give her probably two or three of

39:52

these a week. The way I think of this,

39:54

this is peppered 10. So they're a bunch

39:56

of these different sticks. Like every

39:58

professional team you can imagine uses

40:00

these things in their training. But this

40:04

is made with wild harvested venison,

40:06

liver, and heart. So it has some organ

40:08

meat in it. You do not taste that. It

40:11

just tastes like regular jerky stick.

40:15

But I treat this like a multivitamin. So

40:18

it's like I take, let's call it two or

40:20

three of these a week and limit it to

40:22

that and then the rest of the time I'm

40:23

taking their other either peppered or

40:25

regular sticks. But this is when I'm on

40:29

the go. I mean literally this was in my

40:30

bag when I got here, right?

40:32

>> When I'm on the go, I'm traveling with

40:34

this. Probably some nuts of some type

40:36

like pistachios or whatever. Walnuts

40:39

pretty good for a host of reasons. And

40:42

that's about it. I mean, I might have a

40:46

couple of servings of exogenous ketones,

40:48

but I haven't taken that stuff in a

40:50

couple of months.

40:50

>> You told me. You freaked me out. It

40:52

messes up your liver. This is a

40:54

controversial topic. So, yeah, there are

40:56

certain

40:58

exogenous ketones that contain something

41:00

called 13b butane dial. It's very

41:02

common, and there's a lot of debate

41:04

around this. So, the jury is still out,

41:06

but some people believe that that can

41:09

produce liver toxicity.

41:12

So, I consume anything with 13 butane

41:16

dial in moderation.

41:18

>> Now, to play devil's advocate to a

41:21

counterpoint, a lot of the people who

41:23

are putting forth that hypothesis or

41:26

claiming that's true are selling their

41:28

own ketone salts. So, they're actually

41:30

selling a competitive product. I see. I

41:32

see.

41:32

>> So, question mark.

41:34

But I mean look, you can look at the

41:36

peer-reviewed literature and decide for

41:37

yourself. What I have decided personally

41:40

is that you should use the exogenous

41:43

ketones very intermittently. I have

41:45

experimented a lot with every type of

41:48

exogenous ketone you can imagine. I

41:49

mean, you got me on that good [ __ ] It's

41:51

expensive as hell, but like that stuff

41:53

goes straight to your head. The one that

41:54

you didn't want. We can talk about it.

41:56

>> You know what's funny is like when Tim

41:58

This is how you know it's good off

42:00

camera. Tim's like, "I don't want to

42:02

mention the brand because if I do, it'll

42:04

sell out and I won't be able to get my

42:06

own supply." And that's how I knew I was

42:08

like, "That's some good shit." And Tim

42:09

wants to guard his own supply of it.

42:12

Like, you know, it's good. Yeah. And it

42:14

is good, but it's BHB.

42:17

I won't get too much into the

42:18

technicality here, but it's beta

42:21

hydroxybutyrate bonded to 13 butin dial.

42:24

So, you're still getting that 13b butane

42:26

dial, which means you should take it in

42:28

moderation, but

42:30

in a pinch when you want it for a

42:32

podcast or something like that, man, it

42:35

really works.

42:35

>> It does work.

42:36

>> It really works. And I mean, I've given

42:38

it to relatives with dementia

42:41

>> and within 20 minutes their sentences

42:43

have like 5xed in length and they're

42:45

more acute verbally. It's wild. How do

42:48

you give it? I wish they had it in pill

42:50

form because in some sense it's really

42:52

hard to give that to someone that has

42:55

dementia because it's like it tastes

42:56

like gasoline. It doesn't taste great.

42:58

It's not the worst thing. I mean, I've

43:00

had a lot of foul stuff in my life. I

43:02

just did a shot with this person and I

43:04

was like, I'll do it with you and then

43:06

we went for a walk and that was it.

43:08

There are some concerns around 13 butane

43:10

dial and balance. So, particularly in

43:16

older adults, you do not want to

43:18

contribute to any risk of breaking a

43:21

hip.

43:22

>> Yeah, 100%.

43:22

>> That's just the death nail for a lot of

43:25

people.

43:26

>> I just had to put my mom into a

43:27

different home. It's actually kind of

43:28

cool. It's sad, but she's been falling

43:31

and they had this like like new AI orb

43:33

that sits up there and it kind of does

43:35

like a kind of radar type situation

43:37

>> and it detects falls.

43:38

>> Oh, wow. So the second she falls in the

43:40

home like they can rush in and like help

43:42

her out and all that and they they

43:44

carpet the hell out of it now and stuff

43:45

like that. So

43:46

>> how do you think about sort of preg

43:48

grieving that or contending with that

43:50

yourself

43:51

>> in terms of

43:52

>> with family? That's rough. I mean

43:54

>> yeah I mean

43:54

>> doesn't sound easy cuz if you like play

43:56

forward the tape right it's like I mean

43:58

I think about this with my own parents

43:59

and it's just like nobody nobody lasts

44:01

forever. It's one of those things where

44:03

it's so funny because when you're a

44:04

teenager and I remember when my dad was

44:06

having a hard time standing and this was

44:08

like when I was much younger before he

44:09

passed and I was like, "Oh, dad's going

44:11

to be in like the thing that I might

44:12

have to like push him on it if he has to

44:14

sit down." Kind of those walkers that

44:15

can also be something you can push

44:16

somebody on.

44:17

>> I was so embarrassed, you know? I was

44:19

like, "Oh, people are looking at us or

44:20

whatever."

44:21

>> And now I like push my mom with pride in

44:23

her walker thing. And I'm like,

44:26

>> I don't know. You don't know when it's

44:28

going to what's going to happen, but the

44:30

only thing you can do is just make sure

44:31

to show up, you know, and hang out.

44:33

>> And and I'm very lucky that my mom has

44:36

dementia, but it's it is a type that

44:40

>> it's not Alzheimer's, so it's probably

44:41

vascular or something.

44:43

>> So, I can walk in and she knows who I

44:44

am. She can't tell what she had for

44:46

breakfast, but she knows who I am, which

44:48

is like, I'll take that all day long for

44:49

sure, you know? So,

44:51

>> yeah.

44:51

>> I know you have family members that are

44:53

in the same boat, which is tough. a ton

44:55

of family members with Alzheimer's. I

44:57

mean, literally, I got a call from one

44:59

of my relatives wanting to discuss

45:02

interventions and it's a tough

45:05

conversation because there really isn't

45:06

much like you have to, as far as I can

45:10

tell, act preemptively, which is why

45:13

actually this relates to another bullet

45:15

of mine.

45:15

>> Do you have five?

45:16

>> What was that?

45:17

>> How many bullets did you have?

45:18

>> Oh, how many bullets? Yeah, that was

45:21

good. of all of all the rye whisies.

45:23

It's the only one that I can tolerate. I

45:26

loathe stationary bikes. I just I I

45:29

really find stationary biking to be one

45:31

of the most soul crushing things in the

45:33

world.

45:34

>> It's the worst.

45:35

>> However, yeah, I mean, I've tried

45:37

Pelaton and didn't like the ergonomics

45:41

and so on for a bunch of reasons. And

45:44

then I have tried very expensive, very,

45:48

very expensive setups recommended to me

45:50

by fancy doctors. and so on which are

45:52

just like too uncomfortable. Like I'm

45:54

incredibly hunched over like my back is

45:56

basically parallel with the floor.

45:58

>> What are you talking about?

45:58

>> And I'm like kneing myself in the

46:00

stomach. It's so

46:01

>> uncom. What are you talking?

46:02

>> No. No. I'm talking about getting on

46:03

like a stationary bike. But if you're in

46:04

like a racing position,

46:06

>> you have to adopt this hunchback. And

46:08

like there are a million reasons why I

46:10

find that uncomfortable.

46:11

>> There is a bike, however, it's very easy

46:14

to find. It's pretty common in public

46:16

gyms called the Kaiser M3i

46:19

studio indoor bike. I don't know why

46:21

they have to make it so difficult in its

46:24

nomenclature, but the Kaiser M3i is

46:28

unique in my experience in that you can

46:31

elevate the handlebars enough to sit in

46:34

a comfortable position with a decent

46:36

saddle, meaning the seat such that I can

46:39

do the V2 and the V4 and all of that

46:43

training

46:44

>> for me in a comfortable position without

46:47

compromising my low back, which has been

46:48

a huge step forward. So, this is the

46:50

only bike that I've used consistently

46:52

>> for this kind of training. And I was

46:54

having a number of conversations with a

46:56

neuroscientist named Dr. Tommy Wood over

46:59

a period of weeks. And if for instance

47:02

you do something called the Norwegian

47:04

4x4, there's data to suggest that if you

47:07

do it's V2 max training, so it's very

47:09

very very intense, but it's like

47:11

>> 4 minutes on 3 to four minutes off.

47:13

Let's just call it 3 minutes. Four

47:15

minutes on, three minutes off and you do

47:16

that for four rounds. This is the only

47:19

bike that I've been able to use to do

47:21

this consistently. And if you do that

47:23

for I think it's three times a week

47:26

>> for five to six months, the

47:31

volutric changes, meaning the

47:32

neuroanatomical changes in the

47:34

hippocampus and other areas that are

47:37

certainly indicated in things like

47:38

Alzheimer's lasts for up to 5 years.

47:41

>> Wow. So if you do 5 to 6 months of

47:43

gutting it out three times a week, the

47:45

result [ __ ] the dividends pay off for it

47:48

seems up to or possibly beyond 5 years.

47:52

>> Holy [ __ ]

47:52

>> Crazy. So

47:53

>> throwing some sauna in there and you're

47:55

like

47:56

>> well that's why I'm doing Yeah. I'm

47:57

doing all the usual stuff, right? I'm

47:58

doing the sauna and

48:01

>> don't let perfect be the enemy of good.

48:03

You know what I mean? It's like okay,

48:05

sure. You don't have 30 minutes to do

48:07

like do 10 minutes. Like you can't do a

48:08

sauna, take a hot bath. Like,

48:10

>> yeah,

48:10

>> figure it out.

48:11

>> You know what my good is that I like?

48:13

>> What's that?

48:13

>> It's not perfect, but it's good. Which

48:15

is I go on my treadmill. I set it to

48:19

4.75

48:20

or something incline.

48:21

>> So, it's like not crazy, but it's not,

48:23

you know, I can still do [ __ ]

48:25

>> Yeah.

48:25

>> And I set it to only like 2.5 on the

48:29

walking.

48:29

>> Yeah.

48:30

>> And I'll play Duolingo chess cuz they

48:33

have chess on there now for Duolingo.

48:36

They teach you chess. It's amazing. And

48:37

you can play friends and live people and

48:39

all that stuff and they do game replays

48:41

and like teach and I'm learning a ton.

48:43

>> Yeah.

48:44

>> And 30 40 minutes go by and you're

48:46

drenched in sweat. I know it's not high

48:48

intensity and all the benefits on the

48:50

the cognitive side seem to be around

48:51

like a lot of highend hits.

48:53

>> Yeah. But who knows?

48:54

>> But it's good.

48:56

>> It's doing something right. So I've

48:58

really enjoyed that. Like if you if you

48:59

just want something

49:00

>> to both be like learning and engaged and

49:03

kind of like having fun.

49:05

>> Yeah. So, you forget about the time. Do

49:07

you know what I'm talking about? Where

49:08

it's like you just like, "Oh, wait. What

49:10

time is it? Oh, [ __ ] I've been on for

49:11

37 minutes. I can get off now." You

49:12

know? Like I I love that type of cardio.

49:16

>> Yeah. I mean, for me, I mean, this is

49:18

this is going to sound like maybe a step

49:20

down, but it's like the older I get, the

49:22

more I realize a little goes a long way.

49:25

Like yesterday for instance, I had a

49:27

bunch of stuff stacked up and I won't

49:29

bore people with the commitments, but I

49:32

didn't really have any time to go to the

49:33

gym and it was my day to go to the gym

49:35

to do X, Y, and Z exercise. And I went

49:37

in and I did three sets. I was literally

49:40

in there for 5 minutes and I left.

49:42

>> But it's better than nothing,

49:44

>> right? Totally

49:44

>> right. Something is better than nothing.

49:48

I'm not going to go to the Olympics with

49:49

that approach, but let's [ __ ] be

49:51

real. I'm not going to

49:52

>> You're never going to lose it.

49:54

>> I mean, maybe as like a bystander like

49:56

like in the

49:59

>> Oh, man. So, I'll throw some new random

50:02

stuff in there. There's a study that got

50:04

my attention. It's been It's been out

50:06

since 2025.

50:08

September 202. This is in Jamma.

50:11

And this is the title. single treatment

50:15

with MM120 and then in parenthesis

50:18

laseride I think is how that's

50:20

pronounced in generalized anxiety

50:22

disorder

50:23

>> GAD GAD. This is a randomized clinical

50:26

trial looking at anxiety which is often

50:29

comorbid meaning happening at the same

50:31

time as depressive disorders and I think

50:34

this is sponsored by a company called

50:37

Definium which used to be MindMed.

50:39

>> I know where this is going. I just

50:41

looked it up. Oh my god.

50:42

>> Yeah. Well, what's interesting about

50:43

this, and they're not going to maybe

50:45

love my comparison, but so MM120 Leride,

50:50

I mean, it's comparable to LSD,

50:53

>> right?

50:54

>> And this is a multi-arm clinical trial.

50:58

They did five arms, which is rare to do

51:01

because the risk is that they'll blend

51:03

together. So the arm means a group who

51:06

has is treated with a different

51:07

intervention in this case. So they've

51:09

got placebo, 25 micrograms, 50

51:12

micrograms, 100 micrograms, and 200

51:15

micrograms. 100 mics.

51:17

>> That's what they give standard for LSD.

51:19

>> That's that's what you can think of as a

51:21

standard hit. 100 micrograms.

51:23

>> And the results are wild, man. If you

51:26

look at the ham a score, this is up to

51:29

12 weeks out. You can see, I'll just

51:31

show you how it's dose dependent. the

51:34

more you take basically the better it

51:36

goes up to and I'm not sure how long the

51:39

follow-ups continued but where you land

51:42

is you see that like the 100 micrograms

51:44

and 200 are very very close to it like

51:47

25 and 50 are certainly a lot higher

51:50

>> now are you still getting the same

51:51

psychedelic experience

51:54

>> with this stuff or

51:55

>> in the case of this particular compound

51:58

I don't know my guess would be yes I

52:01

could be totally wrong in that to

52:03

definium feel free to correct me. I am

52:06

guessing the answer is yes with MM120

52:09

but what that says to me is hey 12 weeks

52:14

of relief with GAD generalized anxiety

52:18

disorder which I've been clinically

52:20

diagnosed with that and OCD like 12

52:23

weeks is pretty good and it seems like

52:25

at least according to the data in this

52:27

study the minimum effective dose would

52:28

be 100 micrograms. Now, 100 micrograms,

52:32

at least for me and for a lot of people,

52:34

you will be tripping your balls off. Not

52:36

to get too technical. Wait a second,

52:38

dude. It says that this was done at

52:40

Neuroscape at UCSF.

52:41

>> Was it really?

52:42

>> This is Adam's lab.

52:44

>> No [ __ ] Are you serious?

52:45

>> I'm dead serious. I just clicked through

52:46

on it. It says phase three trial of

52:48

MM120 for GAD.

52:51

>> Trial. This is our buddy.

52:52

>> This is our buddy Adam. Okay. Well, I

52:54

have a text that I need to send them.

52:56

>> Oh my god,

52:57

>> that's awesome. I wonder if I indirectly

52:59

funded this because I helped fund some

53:01

of Neuroscape stuff. That's funny. I

53:03

>> Isn't that hilarious?

53:04

>> Yeah, I did not look at that. That's

53:06

hilarious. Small world.

53:08

>> Yeah.

53:09

>> Okay, there you go. So, you know, it's

53:12

interesting for GAD. We were talking

53:15

about dementia.

53:16

There's a case report with highdosese

53:19

salosabia mushrooms. I don't think it

53:21

was actually psilocybin synthesized

53:24

looking at this particular I think it

53:26

was a Japanese elderly woman with

53:28

dementia may have been Alzheimer's who

53:31

took I can't believe they did this to

53:33

her

53:33

>> five grams right

53:34

>> yeah and then she took five grams so

53:36

Terrence McKenna heroic dose somehow

53:38

fell asleep for like 19 hours or

53:41

something obscene which would be very

53:43

very worrisome if you're the child of

53:46

said parent wakes up and then starts

53:48

having like whole expositional

53:52

conversations

53:53

in contrast with her previous

53:55

monoselabic or or single word responses

53:58

to things and it was transient. It

54:00

didn't last forever but it raises some

54:02

very interesting questions. I've seen at

54:04

least some case reports also with LSD

54:07

producing similar effects and I've been

54:10

interested in this for probably a

54:12

decade. I've hypothesized this could be

54:14

the case. It's just like, do you really

54:16

want to give your parent like under what

54:18

circumstances is it ethical

54:21

>> to give someone hallucinating?

54:22

>> See, I could never do that to my mom

54:24

because she was always anti all this

54:26

stuff.

54:27

>> Yeah.

54:27

>> And then the second, god forbid they

54:29

have a bad trip. Like why would you want

54:31

to put them through that, you know? So,

54:32

it's curious. I was sent something by

54:34

someone I won't mention, but a very

54:37

interesting case report on micro doing

54:40

with LSD

54:42

>> with someone with dementia. But did it

54:44

work?

54:45

>> Yeah.

54:45

>> Oh, really?

54:46

>> Yeah. And in terms of similar to the

54:48

ketones, not saying the mechanism is the

54:51

same, but producing much more verbal

54:54

fluidity, right? Going from like, uh,

54:57

I'm good. It depends,

54:59

>> right? I have relatives who are limited

55:01

to that now. Like, they're basically

55:02

giving answers that are non-answers.

55:04

Sounds good, right? Like these things

55:05

that you could use as a reply to

55:07

anything, right? They're not necessarily

55:10

groing what's happening

55:12

to full paragraphs,

55:15

>> right? Which means to my interpretation,

55:18

it's like offline to online, right? It's

55:20

a really stark difference because with

55:22

the one word, two-word answers, like you

55:24

don't actually know if they're

55:26

understanding what's happening.

55:27

>> Yeah. Yeah. Do you have some MM120 on

55:30

you right now?

55:30

>> No, I don't. I don't. If I did, I would

55:33

probably not take

55:34

>> the podcast. If you see a weird cut in

55:36

the the video and then we get infinitely

55:39

smarter. Yeah, you you'll know.

55:41

>> Little glitch here there. Yeah, exactly.

55:43

It's a flash and all of a sudden we're

55:45

just like, yeah, for smarter I would

55:46

keep it probably to 20 mics or below.

55:48

We'll see. But, you know, I found this

55:50

pretty interesting for for GD

55:52

especially. And then for the dementia

55:54

piece, but it raises a lot of ethical

55:55

questions.

55:56

>> What is ethical to use as a treatment

55:58

and someone who cannot give consent?

56:00

>> Right. Right.

56:02

>> That's a tough gnarly problem. Right.

56:05

>> Yeah.

56:06

>> Especially if you're dealing with stuff

56:07

that is not exactly prescription

56:09

medication.

56:10

>> Yeah. I mean, that's the whole thing. If

56:11

it goes sideways, you feel like an

56:13

[ __ ]

56:14

>> Well, and to put it mildly.

56:16

>> Yeah. To put it mildly. But if it's

56:17

amazing and it gives you another, you

56:19

know, half day with a parent or a loved

56:22

one and you can full have conversations

56:25

and they see you and you see them in a

56:26

way that you hadn't in 6 months like or

56:28

a year. Like that's amazing, right? or

56:31

if it potentially slows the decline,

56:34

>> right? I I think it's too much to hope

56:37

for a reversal, frankly.

56:39

>> Yeah.

56:39

>> But there are some strange phenomena out

56:41

there, man. Like there's this phenomenon

56:44

called terminal lucidity where someone

56:46

like on their deathbed when they've been

56:48

off this. There's that book that I told

56:50

you read. Did you read that?

56:51

>> I'm not the afterlife book.

56:53

>> No, I didn't read that.

56:54

>> Okay. Cuz they they talk about that.

56:55

>> This is well this is well documented

56:56

where people suddenly they've been

56:58

basically vegetative,

56:59

>> right? or completely unable to respond

57:02

>> in their last two days. They come fully

57:04

lucid. Yeah,

57:04

>> they become totally lucid. They have

57:06

full-blown extensive conversations.

57:08

That's why what the [ __ ] is going on?

57:10

>> Dude, I'm telling you, it is so weird to

57:12

me that we think like like a lot of the

57:14

things that we do in physical form, like

57:16

what we do in life mimics nature in many

57:18

ways. And all of our data is like backed

57:22

up in the cloud. And we're like, "Oh,

57:24

we're not backed up in the cloud in any

57:25

Right. And then there's these people

57:26

with like full-blown entanglements in

57:28

their brain, fullon, you know, the

57:31

Alzheimer's for like a decade and they

57:33

become completely

57:35

>> lucid. Where is that coming from?

57:37

>> Okay, I see what you're saying. I wasn't

57:38

tracking that fully for a second, but if

57:40

I'm hearing you correctly, it's like if

57:41

it's all

57:43

>> localized No, I'm saying like if all of

57:45

that ability is localized within the

57:48

confines of the skull.

57:49

>> Mhm.

57:50

>> How do you explain

57:51

>> right

57:51

>> this given all the structural

57:53

deterioration?

57:54

>> Exactly. Exactly. Yeah. I don't have

57:56

good answers for that. I just don't. It

57:58

is a well doumented, as far as I know, a

58:00

well doumented phenomenon.

58:02

>> So, it's like, go figure that one out. I

58:04

mean, I'm not qualified. Way above my

58:06

pay grade. It's

58:07

>> crazy, man.

58:08

>> It's wild.

58:09

>> It is wild.

58:10

>> So, I'll give a shout out to somebody.

58:12

We're not going to open this right now

58:13

cuz we'll start chewing on them and

58:14

we'll be up all night.

58:15

>> Is that the 120?

58:16

>> No, this is Newtonic.

58:19

Nu T O N I C. No tropics. See, that's a

58:22

pun. No tropics. cuz these are

58:25

toothpicks that I was given by a

58:28

podcaster you may recognize named Chris

58:30

Williamson. And they they have like 20

58:34

>> I want to say 20 I might be getting that

58:36

off but like 20 25 milligrams of

58:39

caffeine in each toothpick.

58:40

>> Oh wow.

58:40

>> And there are a couple of other

58:41

nutropics aka coffee. Yeah. smart trucks

58:45

in there and they're great

58:48

>> because if I have cups of coffee, I will

58:51

chug a cup of coffee and then if it gets

58:53

refilled, I'll chug another cup of

58:54

coffee and it's a problem. These

58:56

actually is in terms of pacing

58:59

>> have been fantastic. So that's been my

59:03

sort of not exactly quite as interrupt

59:06

for people who get that but sort of

59:10

ad libidum interruptus. Yeah, the

59:12

avoiding overconumption of coffee and

59:14

other stimulants. This helps me to kind

59:16

of pace it cuz even if I chew on this

59:18

thing until it's fragments of wood, max

59:21

I can squeeze out of it is 20 25

59:22

>> milligs.

59:23

>> What else do you got, Kevin?

59:24

>> Yeah. I mean, the only other thing that

59:26

I have that I think is is interesting is

59:28

what's happening in the world of I don't

59:31

want to talk a lot about AI because I'm

59:32

just frankly AIDed out, but I will say

59:35

that the idea that we can all now kind

59:38

of take control of

59:41

our productivity and pretty much

59:44

anything that we want to control now,

59:45

like device-wise,

59:47

>> we can do with just a few simple prompts

59:50

on AI. And I had a buddy that came over

59:53

to my house and he was like, "Hey, you

59:55

got cameras in your house." I have

59:57

something called ubiquity, which is

59:58

like, you know, like they have cameras

60:00

and there it's a very common kind of

60:01

household type situation when you want

60:03

to have security system, front door

60:05

thing, cameras, sensors, water detectors

60:09

underneath things in case things leak

60:11

and you're out of town, whatever.

60:12

>> And so I've got this whole setup and

60:14

he's like, "Hey, you know, they have a

60:16

full-on API where you can just tell

60:18

Claude or whatever to code against it."

60:20

And I was like, "Okay, this is

60:22

interesting." Well, like, well, what can

60:23

it do? And so, the cameras now have AI

60:27

sensors where they can detect who it is

60:30

that's walking in.

60:31

>> So, it's like, "Oh, Tim's coming up to

60:33

your door. Oh, that's your daughter.

60:35

That's your dog." What? It detects my

60:37

dog, Toaster. Like, it sees him and it

60:38

puts it like a little dog emblem above

60:40

his head when he's walking around and it

60:42

knows that it's Toaster. But the crazy

60:44

[ __ ] is I was like, "Okay, well, what if

60:47

I can go further and I can tell it to do

60:51

actions because there there's a speaker

60:53

hooked up to as well." So that's for

60:55

security. Yeah.

60:56

>> So basically, if anyone loiters in my

60:58

alleyway and it detects it, it's like I

61:01

have I play some like really funky [ __ ]

61:02

where it's like detected like loiter in

61:04

the alleyway like or whatever. And just

61:06

to scare people off in case they're

61:08

>> I am the bad man.

61:09

>> Yeah. Well, I mean, you could draw

61:10

little areas around where they shouldn't

61:12

be, which is like at your door fiddling

61:14

with your door, and say, "If they stand

61:15

here for more than 30 seconds, play said

61:18

audio out of speaker."

61:19

>> So, I was like, "Okay, this is

61:20

interesting. Well,

61:21

>> what if when I walk in my house,

61:25

>> if I'm wearing like a hat of like my

61:27

favorite sports team and they're

61:29

playing, it like reads me the scores

61:32

like I walk in." Mhm.

61:34

>> So you can think about all these things

61:36

where it's doing stuff based on your

61:39

activity, right? So like if you're out

61:41

there gardening, it'll be like, "Hey

61:43

Kevin, I noticed that the plant over

61:44

here wasn't watered enough or like so

61:46

it's watching all of this stuff."

61:49

>> And so there's a lot of if then then

61:51

that kind of situation like if I see you

61:53

doing X. So, like the latest I have is I

61:57

programmed it so when it sees the

61:58

license plate on my car,

62:00

>> it automatically knows to open the gate

62:02

>> because it knows it's me.

62:03

>> Yeah. Yeah.

62:04

>> And the camera looks at the license

62:06

plate on the freaking car, checks it

62:08

against the database, and allows me in.

62:11

How crazy is that?

62:13

>> And for people that are listening, I'm

62:14

not talking about $10,000 systems. The

62:16

camera is like $200.

62:19

>> Anyone can do this at home, you know?

62:21

>> It's just wild to think about. Finally,

62:23

we had all these these kind of discrete

62:25

systems that you know I had some Nest

62:27

stuff and I had some Google Home stuff.

62:29

Now they're all talking to each other.

62:31

>> So you can just do kind of really crazy

62:33

I know you would like this because

62:35

>> you're the kind of person that you've

62:36

told me before like you don't like to

62:38

answer your door cuz if the delivery

62:40

person is like Tim then all of a sudden

62:43

your address is all over the internet

62:45

>> docs. Yeah.

62:47

>> Yeah. I mean, I know you said you don't

62:49

I'm also pretty AIed out, but at the

62:51

same time, it's like I can't I can't

62:54

resist going back to the opium den. It's

62:56

so fascinating.

62:57

>> What are you doing now with the with the

62:58

eye stuff?

62:59

>> Well, I mean, I'm more curious to hear

63:01

your thoughts and predictions, frankly,

63:03

because I think you're better at it. But

63:07

>> I mean, I'm using clawed code with

63:09

various APIs to do tons of like inbox

63:11

analysis and stuff, right? I'm doing a

63:14

20 year retrospective analysis of angel

63:17

investing.

63:18

>> It's like who made what introductions,

63:20

which companies did I not reply to that

63:22

ended up being successes, which did I

63:25

turn down that ended up being

63:27

>> really important.

63:28

>> You really want to do that to yourself.

63:30

>> Well, I suspected it would be worse than

63:32

it was. I actually have not I haven't

63:34

missed that many explicit opportunities.

63:37

I wanted to test my own stories against

63:41

data, right? because I have all sorts of

63:43

stories, right, about why I did certain

63:45

things, why certain things worked out,

63:47

>> and I have certain stories about my

63:51

>> batting average. And I'm like,

63:53

>> but is it true?

63:54

>> Right? Really, is it really true? Let's

63:56

look at some hard numbers. The sad

63:59

truth, and I have a buddy that wears the

64:02

bracelet, and you've seen me with the

64:02

necklace around the it categorizes your

64:05

AI and listens to you 24/7.

64:06

>> Yeah. It's about 70ish% that we think we

64:11

know, but is actually what we know.

64:13

>> Yeah.

64:13

>> Out of the 100% of like what we think we

64:15

know. This is the truth. I said I wanted

64:17

a dark chocolate bar at 7:00 p.m.

64:18

>> Yeah.

64:19

>> It's like, no, you said it at 5 and you

64:22

said it this way. You know,

64:23

>> you said it was milk chocolate.

64:24

>> Yeah, exactly. So, it's always about 20%

64:26

off from where you actually think your

64:28

brain's at.

64:29

>> Sure.

64:29

>> Which is brutal.

64:31

>> Well, plus I mean, that's like last

64:32

week, right? If you're talking about

64:34

like 15 years ago.

64:35

>> Exactly. I mean, if you listen to any

64:37

Genesis story of any startup, you're

64:39

like, "Wait a minute now." Like, this is

64:42

like a startup comic working on

64:43

material, but he's been working on this

64:45

one 5minute bit so long that now he

64:47

believes that's actually truth.

64:49

>> Yeah.

64:50

>> I mean, the sanitizing and the editing

64:52

of these startup Genesis stories is

64:54

hilarious. And there's no reason to

64:56

think that I would be or you would be

64:57

exempt from it,

64:58

>> right? When you're telling your own

65:00

story, even if you're just telling it to

65:01

yourself. So, what's the number one

65:03

thing that you've learned by applying AI

65:05

to your life in this fashion? Like,

65:07

what's the thing where you walked away

65:08

and said,

65:09

>> "Damn, that was insightful and I'm going

65:11

to change my behavior or I learned

65:14

something new about myself that I

65:15

wouldn't have if I had not used AI."

65:17

Well, I think from a holistic health

65:20

perspective, by holistic I mean having

65:23

enough data related to medications,

65:25

supplements, predispositions, side

65:28

effects, what happened to me 2 weeks

65:30

ago. The LLMs have been incredibly

65:33

helpful. I mean, the picture that they

65:35

get and the speed with which they can

65:38

deliver an answer that I can interrogate

65:40

is just incredible. What did you learn?

65:42

Like what was the thing that you

65:44

>> I mean, honestly, it's mostly avoiding

65:46

disaster, right? It's like, are any of

65:48

these things contraindicated with one

65:50

another? Could A, B, or C explain D? And

65:54

you have to keep in mind these things

65:55

can still hallucinate, but you can I

65:59

don't want to say eliminate that, but

66:00

minimize it by just fact-checking across

66:03

LLMs. There's that. I would say that

66:05

there's a lot of insight on hopefully

66:08

that that can translate to future

66:10

decision-m related to investing, which

66:13

investing for me is not just amassing

66:16

more chips. What's fun about investing

66:18

to me is it's a way to scorecard your

66:22

thinking and decision-m.

66:24

>> It's just a very objective way to decide

66:28

if something was the right or the wrong

66:30

decision. And you can fine- slice that.

66:32

And there are ways that you could maybe

66:34

question that. But

66:37

if you're asking yourself, "Was I

66:39

thinking well last month?" That's not a

66:42

very helpful question. Where do you go

66:43

from there?

66:44

>> Mhm.

66:44

>> If you're logging maybe every decision

66:46

you make every day and then trying to

66:48

cross reference outcomes with blah blah

66:50

blah, like, "Yeah, but you're never

66:51

going to do that."

66:52

>> Mhm.

66:53

>> But when you're making relatively

66:55

frequent investments, you can do that.

66:58

You can also run counterfactuals, right?

67:00

What if I did the opposite? What if I

67:01

had not sold that? What if I had kept

67:03

that? What if I had done this? What if I

67:04

had done that? Is that worth your time,

67:06

though? At the end of the day, you could

67:08

throw everything into the S&P 500 and

67:10

just go to bed.

67:11

>> Well, there's that. I would say it's

67:12

worth it to me because I find it

67:14

interesting. I actually enjoy the

67:17

intellectual exercise of it. But

67:20

otherwise, I would say with in terms of

67:23

like how AI has has impacted me, I would

67:27

say that the honest answer is not that

67:30

much because most [ __ ] isn't worth doing

67:32

in the first place. People are finding

67:34

very very clever ways to expedite

67:38

automating workflows of all different

67:40

types and doing something well does not

67:43

make it important or worth doing in the

67:45

first place. So there's a lot I think

67:46

the level of [ __ ] that is being done

67:49

just at a very fast efficient rate is

67:51

skyrocketing.

67:52

>> Yeah.

67:53

>> But simultaneously there are definitely

67:55

cases where

67:58

I look back at say this analysis of 20

68:01

years of stuff to do that manually would

68:04

be impossible.

68:05

>> Sure.

68:05

>> All right. It would take me a year

68:07

full-time with multiple people to do

68:09

that.

68:10

>> And with a claude code, Gmail API and

68:14

leaving my computer running for a

68:16

handful of hours a few times, it's like

68:18

what you get back is [ __ ] incredible.

68:20

Yeah.

68:20

>> Like it's unbelievable. And I haven't

68:23

even scratched the surface.

68:24

>> Yeah. I will say also another way that

68:26

AI has maybe affected my life in a

68:30

net negative way and I'm not we have

68:33

another mutual friend who maybe we

68:34

shouldn't name who feels very similarly

68:36

is we'll bleep that out but yeah Jesus

68:41

Christ so if you train

68:45

AIS on your writing

68:48

they're really good

68:50

>> and I think I feel this is a stretch of

68:53

a comparison obviously cuz I'm not

68:57

an adept like a world class Go player,

68:59

but when Alph Go defeated one of the top

69:02

Korean players,

69:03

>> he was kind of like, I'm done. Like, I

69:05

don't find joy in this anymore.

69:06

>> Yeah. Yeah.

69:07

>> If we're playing against machines.

69:08

>> Yeah.

69:09

>> And when I see these AIs very

69:14

beautifully, I'm not going to lie, and

69:16

they're we're like in the top of the

69:18

first inning, right? This stuff is going

69:19

to get so much better. spit out stuff

69:21

that is so much better.

69:24

>> Yeah.

69:24

>> I mean, I can still write, but what they

69:26

can do in 30 seconds is what would take

69:29

me 30 hours. And I'm just like, [ __ ] It

69:33

really drains the motivation for me to

69:36

put in those 30 hours.

69:37

>> Yeah.

69:38

>> Why wouldn't it? Of course it would.

69:39

Right.

69:40

>> Yeah. But in some sense, you can

69:42

consider it a really good co-pilot

69:44

because for it to come up with novel

69:46

ideas that would engage an audience

69:48

that's still the holy grail where it's

69:50

not quite there yet, right? Like it's

69:52

going to make you sound it's going to

69:54

button up your copy and it might expand

69:58

upon it in ways that you wouldn't, but

70:00

it's not going to come up with the

70:01

original thesis for the whole thing,

70:03

right? Yeah. It's going to have trouble

70:04

with the original thesis, but even

70:06

there, I think it does a pretty good

70:09

job. getting better. I haven't tried

70:11

with writing stuff.

70:12

>> Well, if you just do a data dump and

70:13

you're like create amazing.

70:15

>> Oh, you sent me that link.

70:16

>> Yeah. If you just do a data dump, you're

70:18

like create.

70:18

>> Remember you sent me that link. You were

70:19

like, "What should Tim do in the next 5

70:20

years?"

70:21

>> Oh, yeah. That was good.

70:22

>> That was really interesting. Tell people

70:24

what you did because they might find

70:25

this they could apply this to their own

70:26

life.

70:27

>> Sure. So, you could do this in whichever

70:29

model you're using, whether it's, you

70:31

know, Claude or Chat GPT or whatever.

70:33

>> If it knows you,

70:34

>> you can tie in your inbox, too.

70:36

>> Yeah, you can tie in your inbox. In my

70:37

case, I didn't do that. But if it has

70:40

enough history on you, you can just ask,

70:42

"What do you think I should do in the

70:44

next 5 years? What might be some

70:48

rewarding paths of exploration?" I think

70:51

I put something like that.

70:52

>> What are three to five ideas that you

70:56

think could be rewarding career

70:58

exploration in the next x period of

71:01

time? So for people listening, if

71:03

they've used AI for, let's call it 3 to

71:05

6 months, and you've probably given it

71:06

several hundred things to think about,

71:08

it will span across those conversations

71:11

as long as you turn this on. It's I

71:13

think it's on by default now, but it

71:14

used to be an opt-in thing. We're going

71:15

to say allow the AI to look cross

71:18

conversation, so it has a holistic

71:20

understanding of who you are. And the

71:22

answers were [ __ ] outstanding.

71:24

>> Yeah. I mean, really, really good.

71:26

>> Yeah.

71:27

>> And I sent it to a few friends, sent to

71:29

you. I sent it to a few of my closest

71:31

friends and they were like, "That's

71:32

pretty [ __ ] good."

71:33

>> Yeah. I

71:34

>> It was really cool. Some of the ideas I

71:36

was like, "Damn, you should do that,

71:37

dude." It had this one business idea for

71:39

you to do and it wasn't a book and I was

71:42

like,

71:42

>> "Dude, I texted you back. I was like,

71:44

that's awesome. Like, go build that."

71:47

>> There were business ideas. There were

71:49

certainly kind of nonrevenue

71:51

but philosophically aligned ideas. It

71:54

was shocking to me. So that's actually a

71:57

very good example of something that has

71:59

deeply informed what I'm mulling over as

72:02

I imagine the future. I was like, man,

72:04

that actually is a really good because

72:07

keeping in mind I'm asking questions

72:09

about

72:11

>> things of interest, things I like,

72:13

things I don't like. I am asking

72:15

questions about

72:17

different scientific interests related

72:19

to Sciate Foundation, my nonprofit

72:21

foundation.

72:22

>> I'm asking questions about investing.

72:24

I'm asking questions about writing. I'm

72:25

asking questions about relationships.

72:27

I'm asking questions about organizing

72:29

trips for friends. I'm asking so many

72:31

different questions.

72:32

>> Am I still on the board? You're a

72:33

nonprofit. I

72:34

>> think you're like secretary or

72:35

something.

72:36

>> Yeah, some

72:39

heard anything about it.

72:40

>> Yeah. I don't know. Maybe you were

72:42

honorably discharged.

72:43

>> I don't think you did. I never heard any

72:44

paperwork around it. I haven't heard

72:46

anything in like 3 years. I'm like,

72:47

okay.

72:48

>> Yeah. Well, I said it was going to be a

72:49

light lift. It's a light lift.

72:50

>> Light lift.

72:52

>> That's a very good example, right? I

72:54

mean that that may be the best example

72:56

because if that even 10% informs like a

73:00

major next chapter

73:02

like that's a big deal for me certainly

73:05

>> and it makes me think a little bit about

73:09

podcast listeners especially readers

73:13

also but to a greater extent podcast

73:15

listeners who come up to me and most

73:18

most listeners I run into are really

73:20

great and not I mean there are always a

73:22

couple of weirdos But most are fantastic

73:25

and they'll say something often like,

73:27

"I'm so sorry you don't know me at all

73:29

and I feel like I know you." And what I

73:32

say a lot of the time is actually if you

73:34

listen to my podcasts every week or even

73:37

every month, you do know me pretty well.

73:39

>> Yeah.

73:40

>> And then you think about

73:43

>> a machine that never forgets.

73:45

>> Yeah.

73:46

>> It's going to know you pretty damn well.

73:48

>> Yeah. Yeah. Of course.

73:49

>> And it's spooky in a way.

73:50

>> Yeah. But I started getting more out of

73:54

the LLMs when I started asking

73:57

questions. Now, you have to be, I think,

73:59

a little careful with outsourcing this

74:02

and absolving yourself of responsibility

74:04

to think about these things. But when

74:05

you ask it open-ended personal questions

74:08

in the way that you would ask a close

74:09

friend, right?

74:11

>> What do you think are three to five

74:12

creative ways I might explore things

74:15

professionally in the next 5 years?

74:17

>> Yeah. as opposed to something that you

74:20

think is more suitable for a robot.

74:21

>> Yeah. Yeah.

74:22

>> You get some really interesting

74:25

responses.

74:25

>> That's so cool. That's a great use case.

74:28

>> Yeah.

74:28

>> The one thing I've been playing around

74:29

with lately that I haven't told you

74:31

about yet, but you know, I think about

74:33

all these AI startups and everyone

74:35

that's creating all these different apps

74:36

and all that stuff. And for me, you

74:38

know, that's kind of fun to watch as a

74:41

kind of bystander being like, "Oh, cool.

74:42

You're going to make this." But I I

74:44

really want to explore things that just

74:48

no one has done before. It's always been

74:49

interesting to me more than just like it

74:51

iterative kind of like sanding down the

74:53

rough edges. A lot of startups go will

74:55

go out there and be like, "Hey, you know

74:56

what sucks is word processing doesn't do

74:59

this, so I'm going to like make a

75:00

slightly better word processor. I'm just

75:02

making this up." But I like the kind of

75:05

wilder crazier like I'd rather have it

75:07

fail and say I did something new than

75:11

just do something boring. If that makes

75:12

sense. Oh, I get it.

75:14

>> And so lately, what I've done is

75:16

>> part of why I have so many fatalities.

75:18

>> So many fatalities. Yeah, exactly. Same.

75:20

What I've done lately is I've taken I

75:24

went and bought a bunch of these decks

75:25

of cards on Amazon that are values

75:28

cards.

75:29

>> What does that mean?

75:30

>> Meaning like they give you like a deck

75:31

of a hundred things and like what are

75:32

your core values?

75:33

>> Okay. Yeah.

75:34

>> And you're like empathy or kindness or

75:36

like you like flip through them

75:38

>> and the way they typically work is that

75:40

you have like a really high value, a

75:42

medium, and a low value. And then you

75:44

put them into different stacks and then

75:45

you walk away and you say, "Oh, this is

75:47

my high value stack of things that are

75:49

my core values that mean a lot to me."

75:52

And it might be 10 or 15 different

75:53

cards, right?

75:54

>> And what's interesting is to do that

75:56

with like friends and partners and

75:58

things like that. And then compare them

76:00

and say, "Hey, what do we align on? What

76:01

we don't?" And I can imagine for like an

76:03

intimate partner, this would be a pretty

76:05

important thing to do, right?

76:06

>> And so I started there and I'm like,

76:08

"Okay, well, I'm going to scan these

76:10

cards in and then I'm going to pair it

76:12

down and make these core values where

76:14

you come in and say, "This matters to

76:15

me." Almost like a swiping like, you

76:17

know, dating app or something like,

76:18

"Yes, I'm into

76:19

>> yes, I'm into empathy." No, I'm not.

76:21

>> Yeah. Exactly. But you swipe through

76:22

them and then when you're done with

76:23

that, then you've got your list of like

76:26

these values and they can change over

76:28

time. And so I think the important thing

76:30

is to log that and say these are my

76:32

values today but tomorrow one might

76:34

shift a little bit right and then I

76:38

thought about contractual bonds and so

76:40

like the working title I have for it is

76:41

just called bond and where I can say

76:43

like with a partner I'm going to create

76:45

a contract with you where we both have

76:46

to shake on it meaning like a virtual

76:49

shake. You think of it almost like a sim

76:50

city like situation. this is my city,

76:52

this is her city or a friend's city and

76:55

we're going to agree that I take the

76:57

trash out every Tuesday night

76:59

>> and there's an emotional shake on both

77:00

sides. And if I break this bond,

77:04

it results in what? And so from the

77:07

partner's side, it will result in a 1 to

77:10

10 on how much damaging this is to me.

77:12

So not taking the trash, I'd probably be

77:14

like, "Ah, that sucks because the trash

77:15

is going to overflow." That's probably a

77:16

three to most people, right? And so then

77:19

I kind of get negative points in case I

77:21

break that bond. But what's interesting

77:23

though is that will link back to a core

77:26

value of theirs and a core value of

77:27

mine. And I want to show up as a good

77:29

partner and there will be a core value

77:30

associated with that. And then you could

77:32

see those bonds between multiple people.

77:34

And the reason I say this is because

77:37

I've always been one of these people

77:38

historically that have said yes to so

77:40

many things and then be a last minute.

77:42

I'm the worst at that, you know, where

77:44

I'm like I'm in and then I'm like I'm an

77:46

introvert. I'm out, you know, at the

77:48

last minute, right?

77:49

>> And so I just think that there needs to

77:51

be a system where

77:53

>> almost like a LinkedIn for like values

77:55

and trust and bonds. There's a great

77:57

Wueng quote that's like word is bond and

78:01

ultimately like I really believe that

78:02

like there's something really cool about

78:03

saying you know we have the better

78:05

business bureau that's like the best we

78:07

got, right? Like oh this person they did

78:09

well by their customers 2,000 times.

78:12

What about individuals and saying like,

78:14

"Hey, this person was always empathetic

78:17

towards me or this person was kind and

78:19

helped me move on a Sunday."

78:21

>> What prompted all this?

78:22

>> I don't know. I'm just thinking about

78:23

it.

78:24

>> Just like the thing I think about is

78:26

that there

78:27

>> such a satisfying answer.

78:28

>> No, hold on. Let me give you the real

78:30

answer.

78:31

>> I call this dark information.

78:32

>> Dark information.

78:33

>> Yeah. So, dark information is

78:34

information that exists in the real

78:36

world, but we have yet to put in

78:38

physical form.

78:39

>> Okay? And so right now you and I have a

78:41

trust thing.

78:42

>> You know that if the camera was turned

78:44

off, there are certain things that you

78:45

can tell me that you're pretty certain I

78:47

will not tell anyone else,

78:48

>> right?

78:49

>> Every once in a while I do, but you know

78:51

where that line is, right?

78:53

>> But that hasn't been concretized in any

78:55

type of like visual real format.

78:59

>> And so there's something interesting.

79:01

I'm just brainstorming with you in real

79:02

time because we've had a couple of

79:03

drinks. But like my point is if there

79:06

was a system where I could say I've

79:09

created these bonds, I've built up this

79:10

reputation,

79:12

>> but it would also give me a way to

79:13

reflect back and be like, you know what,

79:15

I can see now historically that I've

79:17

often bailed on events that I've signed

79:19

up for. Let me improve that in myself.

79:22

Right. The whole point of what you

79:23

brought up a minute ago was

79:26

>> if I use AI to go back historically and

79:28

look across things, I can detect these

79:29

trends and then make course corrections

79:30

based on those trends. Right. Yeah.

79:32

>> And so there's something interesting

79:34

about this idea of there are these

79:37

different facets. So there's these like

79:39

emotional facets we have with every

79:41

individual. How might we track those?

79:44

Well, what jumps out at me about this is

79:47

maybe a cool use case would be

79:49

identifying. You could write it out or

79:52

you could have cards your values, but

79:55

maybe to put a finer point on it, the

79:57

type of person you believe yourself to

79:59

be.

80:00

very different than what people perceive

80:01

you to be

80:01

>> or the type of person you want to be.

80:04

And then it's like, let's take a look at

80:05

your calendar and your email and your

80:07

iMessage to see how much your story of

80:10

what you think you are or what you want

80:12

to be matches up with your behavior and

80:13

then you get a report card. I built a

80:15

prototype for exactly this. So remember

80:17

maybe seven years ago you did a 360

80:19

review for me.

80:20

>> Yeah, those things are brutal. For

80:22

people that don't know what 360 reviews

80:24

are, it's like you give 10 of your

80:25

friends to somebody, they interview

80:27

them, they collect all the data

80:29

anonymously.

80:30

>> Could also be like co-workers,

80:31

employees,

80:31

>> co-orkers, employees, friends, whatever.

80:33

And then you get a report back being

80:35

like, here are the deficiencies and

80:37

positives that this person brings.

80:39

>> Anonymized.

80:40

>> Anonymized. And they are very different

80:42

than what you think you're you how you

80:44

show up.

80:44

>> Totally.

80:44

>> And so like that's the idea.

80:46

>> I literally was looking at mine from

80:48

like 12 years ago.

80:51

Yeah, I know.

80:53

>> So tough.

80:54

>> I know cuz you get it back and you're

80:56

like, who said this?

80:58

>> I know some of it is brutal.

81:00

>> I think I know what you said, by the

81:01

way. Do you ever use the word child

81:03

rearing?

81:04

>> Child rearing.

81:05

>> Would you ever say that?

81:07

>> Child rearing. I mean,

81:09

>> to throw me off. Would you ever say that

81:11

>> to throw you off the sun trail?

81:13

>> Because before I had kids, somebody in

81:15

my anonymous 360 review said like, "Oh,

81:17

he's going to have a hard time with

81:19

child rearing." Oh no, that wasn't me.

81:20

>> I'm like, who the [ __ ] would say [ __ ] I

81:22

don't have any friends that even have

81:23

that in their vocabulary. And I'm like,

81:25

the only person that could do that would

81:26

be Tim trying to throw me off with a

81:28

[ __ ] smartass word.

81:30

>> No, that wasn't me. That wasn't me. That

81:31

wasn't me. No. No. I think I'd be able

81:34

to identify whatever response. That's

81:36

the one thing that stuck with me after

81:38

like 15 years. I'm like, that man,

81:41

you're lucky if you got off of that.

81:42

I've got so much more. Good lord.

81:45

You know what I've been doing that has

81:48

been really helpful because the blank

81:51

page is something I struggle with with

81:53

writing which is part of the reason why

81:54

the AI is so demoralizing in a sense

81:56

because the LLM's within like 30 seconds

81:58

are just like boom how you like me now

82:00

try to match that

82:02

>> but using even though I certainly don't

82:05

know the future of this company because

82:06

it might get replaced by features that

82:08

are innate to X Y or Z but whisper flow

82:12

oh god I love it. Yeah. So using Whisper

82:14

Flow as a data dump,

82:16

>> I wish I was an investor.

82:17

>> You may you may have recommended this to

82:19

me. I can't recall, but

82:20

>> basically doing a dump of a conversation

82:22

as I'm walking with Whisper Flow,

82:25

>> into a note on my phone,

82:28

>> then taking that, dropping into Claude,

82:30

asking it to like clean it up and turn

82:32

it into something readable

82:34

>> has been so helpful. Not necessarily for

82:36

publication, but for emails, especially

82:39

uncomfortable emails. You're like, "God,

82:41

like I just like I'm putting it off.

82:42

procrastinates. I don't want to do it.

82:45

>> Just doing like a 10-minute brain dump.

82:47

It's shocking how quickly things come

82:49

together. Like I incredibly helpful. And

82:51

I'll just give a shout out to my friend

82:54

Alain Lee, co-founder of Exploding

82:56

Kittens. He recommended this headset cuz

82:57

I was on a call with him. I'm like,

82:59

"Man, that audio is awesome. What are

83:00

you using?"

83:01

>> Can you put it on just for the viewers?

83:03

It's going to look as good as I hope it

83:04

does.

83:05

>> It looks so good.

83:06

>> Yeah, it's pretty good, right? So, this

83:08

is the Shocks S H O KZ open meet U

83:12

openear bone conduction headset. So, he

83:16

was talking and I'm like, "What the hell

83:17

are you wearing?" I was like, "The audio

83:18

is really good." So, it looks pretty

83:19

dorky. This is like a

83:21

>> No, it's great.

83:23

>> And the bone conduction is right here,

83:26

effectively on my cheekbones. And when

83:28

you first use them, you're like, "Wait a

83:30

second. I feel like this is playing out

83:31

of speakers. Like, this is nonsense.

83:33

This is complete BS." But then you

83:35

totally plug your ears and you can still

83:37

hear perfectly well.

83:39

>> Which is crazy. And what I like about

83:40

these is a the audio quality is great

83:43

and you know the connectivity varies,

83:45

but the audio quality is fantastic. You

83:48

can hear. So if I'm like walking my dog,

83:51

walking Molly and I want to be able to

83:53

hear traffic and so on, I can use this

83:55

cuz I especially if I'm using Whisper

83:58

Flow to data dump into a text file of

84:01

some type, I don't really need to be

84:03

listening. It's not like I'm on a phone

84:05

call or a Zoom call or something.

84:07

>> So, I find this very very helpful so

84:08

that I can actually pay attention to my

84:10

surroundings.

84:11

>> And that's all I got. It's basically

84:13

this and AirPods. I mean, there there

84:15

are other headphones that I will use for

84:17

professional recording and stuff, but

84:20

thus far, I'll share one more tech thing

84:22

real quick. These this little baggie

84:25

here is the Sennheiser Pro Audio

84:28

Condenser Microphone. It's very simple.

84:32

I've just been very impressed with the

84:34

audio when I'm on the road recording

84:36

stuff for the podcast like intros or

84:38

sponsor reads or whatever. It's just a

84:40

simple lav mic. It's so simple. But the

84:43

audio quality, even in a hotel room that

84:46

is really bouncy, lots of glass, lots of

84:48

metal where it should sound terrible.

84:51

>> If I use a fancy like this is a sure mic

84:54

that we have right here. If I were to

84:56

use this exact mic, cuz I have it at

84:58

home,

84:58

>> y

84:59

>> in some of these bouncy rooms, it would

85:01

sound worse, I'm not kidding, than what

85:03

I get for my purposes.

85:05

>> Crazy

85:05

>> with this.

85:06

>> It's pretty wild. And I love Sure. I use

85:08

their mics on a lot of podcasts. But in

85:11

terms of minimizing bounce,

85:13

>> yeah,

85:13

>> for whatever reason, this little baggie

85:15

that I can stick in a pocket, right,

85:17

it's like this is my portable

85:20

sort of recording studio.

85:22

>> Have you recorded on the iPhone with it?

85:25

I have.

85:26

>> It sounds good.

85:26

>> It sounds great.

85:27

>> That's amazing.

85:28

>> And I don't have my phone with me. There

85:30

is

85:31

>> an app that you can use for really

85:33

highfidelity recording. It's called

85:36

>> like fite or something like that.

85:38

>> It's like lossless recording, right?

85:39

>> Lossless recording. It's like f e r r i

85:41

t e something like that. I'll put the

85:43

link in the show notes

85:44

>> for this for people who are interested.

85:46

The quality is absurd. And you can also

85:49

use descript or one of these programs to

85:51

do AI cleanup. And it's crazy.

85:56

>> Yeah. You didn't even need sadly. You

85:57

don't even need to script anymore. Like

85:59

you can just use all the models do it.

86:00

Gemini is actually quite good at

86:02

multi-modal

86:04

>> audio video all that stuff.

86:06

>> Oh, cool. Gemini, honestly, I've been

86:08

using Gemini more and more just because

86:10

it's such plugandplay with fast with G

86:13

Suite also.

86:14

>> Yeah. I mean, 35 Flash like is a great

86:16

model. Although the new Sonnet just came

86:19

out and that's from Anthropic that just

86:21

came out and that's I haven't played

86:24

with it yet because it was literally

86:25

launched today and it's it's supposed to

86:27

be fantastic.

86:28

>> What do you think the landscape looks

86:29

like in a few years? You've got

86:30

Anthropic and OpenAI racing to IPO. See

86:33

where that goes. You've got Mythos Fable

86:36

taking off.

86:36

>> Mythos is out tomorrow, right?

86:38

>> Back out tomorrow, right? Okay. Was a

86:40

national security threat yesterday but

86:41

it isn't today.

86:42

>> Exactly.

86:43

>> What do you think? I mean I think the

86:45

>> It's the big three is three players.

86:47

It's Google, Anthropic, and OpenAI.

86:49

>> Mhm.

86:50

>> And X is trying and I would never ever

86:53

count out Elon obviously like he has the

86:57

funds to make it happen. Well, also

86:59

Anthropic and Google are buying excess

87:01

capacity from Colossus, right?

87:02

>> Yeah. But that means that their product

87:05

isn't working.

87:06

>> Yeah.

87:06

>> Because they bought that capacity for

87:07

themselves,

87:08

>> right?

87:08

>> So that means that no one's using Grock,

87:11

you know? I mean, I actually like Grock.

87:13

I use Grock more than people might

87:14

realize. Well, here's what's interesting

87:15

about it

87:16

>> for current events and synthesizer.

87:17

>> Yes. So, it has direct access to the X

87:20

API and that it has actually X tools

87:23

built into GRO. So, if you want to like

87:25

get like you said current events, news,

87:27

things like that. And they've also said

87:28

that it is one of the most grounded

87:32

models and doesn't hallucinate. So, that

87:34

it's really good at. And so on dig when

87:37

we relaunch it and we use a lot of AI to

87:39

kind of come up with the different

87:40

stories and all that. We use it a ton

87:43

because we want that grounded

87:45

information that is true, you know, and

87:47

so it's really important to have that.

87:48

And I I don't know. I mean, I think I

87:50

wouldn't count them out. I should

87:51

probably include them in that list.

87:52

>> So big three. What do you think things

87:54

look like in two years? You're very good

87:56

at this. I'm not saying obviously this

87:58

is just [ __ ] bullshitting and

87:59

speculating, but

88:01

>> what's your guess?

88:03

>> I mean,

88:04

>> I'm pretty heavy into Alpha. thanks to

88:06

you which uh

88:06

>> you had in Alphabet.

88:08

>> Yeah.

88:08

>> Yeah. I mean

88:09

>> and then they had a 40% pop on a $4

88:11

trillion company.

88:13

>> What is going on? I mean

88:15

>> I haven't even watched. Is it up?

88:17

>> Oh well I mean look this was a while

88:19

back that I mean a while back in AI time

88:21

which is like dog years. So by that I

88:23

mean like five months ago.

88:24

>> Yeah. Exactly. Five months is like 10

88:26

years now. So here is why I like Google.

88:31

They own the full stack. So they have

88:32

their own chips. Yeah.

88:34

>> And so one of the things that I did a

88:36

deep dive on was the chips that they are

88:39

building. They really confused the

88:41

industry. It's my understanding that

88:44

they made them insanely high bandwidth

88:46

and kind of memory throughput when

88:47

everyone was like, "Hey, why are you

88:49

opening up these channels and making

88:50

them so high bandwidth for this kind of

88:52

like data flow, right?" And I talked to

88:56

Buddy and he was like, "Yeah, everyone

88:57

was confused at first when they saw the

88:58

architecture for their their latest AI

89:01

chips." And then they realized that we

89:05

live in a world right now where a model

89:07

drops like Fable goes live tomorrow on

89:10

Wednesday, right?

89:11

>> And the next OpenA model goes live, you

89:15

know, in two weeks or whatever cuz they

89:16

have that rumored one. It's like old

89:19

software deployment where it was like

89:21

model trained released out. Model

89:24

trained released out. That's the cadence

89:26

we're on right now.

89:28

>> What Google is betting, and I know I

89:30

know they're all thinking this, but what

89:31

Google's betting with this high

89:33

throughput kind of wide memory

89:35

architecture is the future is continuous

89:39

learning.

89:40

>> And so everyone is saying like we're 12

89:42

to 18 months out, maybe a little bit

89:43

longer from self-improving models.

89:46

>> I see. Yeah. So 24/7 it's not no longer

89:49

about like oh Mythos came out today. Woo

89:52

crazy. It's not about those new models

89:54

dropping. It's about just like a child

89:56

learning.

89:56

>> Tomorrow it'll be better than today for

89:58

forever.

90:00

>> And when that happens and they own the

90:02

full stack. So Google's got the chips.

90:05

Granted they're going to be constrained

90:06

by TSMC which is the the only player

90:09

that's producing. I mean there's a few

90:11

others. Samsung and Micron and a few

90:13

others, but like TSMC is like the leader

90:15

and they're producing I believe they're

90:16

producing Google's chips as well. But

90:18

they've got the chips architecture,

90:20

they've got the models, they've got the

90:22

engineers. They're freaking I mean they

90:24

lost a great one like a week ago, but

90:26

it's crazy what they're paying these

90:27

engineers. Did you see some of this?

90:29

>> It's like a billion dollars like

90:31

situation. Like it's insane what they're

90:33

paying some of these people to like

90:34

stick around.

90:35

>> Meta was doing to poach. Also,

90:37

>> Meta I just don't think they're going to

90:38

make it, man.

90:39

>> Yeah. Listen, they have great

90:41

businesses. Instagram is phenomenal.

90:44

They've got these fantastic assets, but

90:48

I just don't think they have the talent

90:52

to pull off what these other bigs are

90:54

pulling off, you know?

90:56

>> What do the big three look like in two

90:58

years, do you think?

90:59

>> Because Google has a lot of advantages

91:01

like you like you mentioned, right? I

91:03

mean, also like vast data center

91:05

expertise. They have the data centers.

91:08

They have Android.

91:10

>> Yeah.

91:11

>> Which is like 60ome percent of the

91:14

population or something like that. So

91:16

they have the install base.

91:17

>> Mhm.

91:18

>> I have a hard time believing that if you

91:21

believe that AI inference and all the

91:24

costs associated with AI eventually kind

91:26

of settles.

91:27

>> Mhm.

91:27

>> And it's affordable. And yes, it'll

91:29

probably be like a Netflix type plan

91:30

where we're all like, "Oh yeah, that's

91:32

our extra $30 a month to get all the AI

91:34

[ __ ] whatever." if it's coming on your

91:36

device. And also, Google's powering a

91:39

lot of Apple [ __ ] although Apple has

91:41

some unique tech.

91:43

>> It's interesting. Apple is kind of

91:45

coming up. I wouldn't write off Apple

91:46

either. Apple's another one, but they're

91:47

probably another a couple years out. I

91:49

don't know. I mean, at the end of the

91:50

day, for me, I'm old enough now to not

91:53

want to be like, "Hey, this is the

91:54

10xer."

91:55

>> Yeah. Actually, was interesting. I

91:57

called on your podcast. I don't know if

91:58

you know this, but like four years ago,

92:01

I was like, "Dude, Nvidia is going to

92:02

crush it." Blah, blah, blah. There's

92:04

some been some dumb predictions. We've

92:06

definitely made some bad ones, too. So,

92:07

I'm not going to say it's been all good,

92:08

but we've called out some stuff. In the

92:11

world of AI, I don't think it's win or

92:12

take all.

92:13

>> Yeah.

92:14

>> Unless somebody hits some kind of crazy

92:16

escape velocity that is like truly

92:19

it's like aware. What do you think? Just

92:21

I'm curious cuz you're you're so much

92:23

better at this kind of stuff than I am.

92:25

I'm like good at my dumb little corners

92:26

here and there, but you've worked at

92:29

Google, right? And you worked on their

92:31

ill- fitted social product at one point,

92:34

right? What was it called? Can't even

92:35

remember.

92:36

>> Plus, plus, right?

92:37

>> Yeah. It was horrible. I left right

92:38

away,

92:39

>> right? And very wisely segueed to Google

92:43

Ventures. I guess my point is like when

92:45

people think consumer, not enterprise.

92:48

>> When they think AI right now, they think

92:49

Chat GPT, right?

92:51

>> Yeah.

92:51

>> Chat GPT has raised a ton of [ __ ]

92:53

money. They've got to figure out ads

92:55

almost certainly. That's not easy. That

92:57

is very, very, very hard to do. Like I'm

93:00

pretty familiar with the ads business at

93:01

Google. Very hard to do at a high level,

93:03

right? However, when

93:07

average Joe or Jane on the street thinks

93:09

AI, they think chat GPT.

93:10

>> Mhm.

93:11

>> And when I have tried to set up the

93:14

Gmail API for Claude, the process on the

93:17

Google side is such dog [ __ ] Like the

93:20

UX is terrible. Like it is so bad.

93:24

>> Yeah.

93:24

>> And I'd like to think myself reasonably

93:27

decent with tech stuff. Not as not as

93:29

technical as you are, but pretty good, I

93:32

would like to think. Nonetheless, I need

93:34

someone like on my staff to walk me

93:36

through step by step to do it because

93:38

it's so counterintuitive and their

93:39

errors all over the place.

93:40

>> And then you've got, you know,

93:42

Anthropic, which is, if we are to

93:45

believe the headlines on ARR, just like

93:48

crushing, right, on the enterprise side,

93:50

like the fastest scaling business of all

93:52

time on a lot of different measures.

93:54

However, right, they've gotten a number

93:57

of pretty strong [ __ ] slaps from the

93:59

administration.

94:01

At the same time, it seems

94:04

unlikely that any of these frontier labs

94:07

are going to be left unconstrained by

94:09

the government,

94:10

>> right?

94:10

>> So, that's like a huge question.

94:12

>> H I think China will push that.

94:13

>> Okay, tell me.

94:14

>> Well, so China's been launching new

94:16

models and they just did one like a week

94:18

ago that is on par with Fable.

94:20

>> Was that Alibaba or someone else? No,

94:22

it's uh

94:23

>> doesn't matter. But

94:24

>> yeah, so but these are open source

94:26

models. So it's actually really

94:27

interesting because China is like,

94:28

"Okay, listen. We're gonna open source

94:30

this

94:31

>> and people will use our tech." They're

94:35

almost doing it the American way.

94:37

>> Yeah.

94:37

>> Like they're not closed sourcing

94:38

anything. They're like, "Okay, here's

94:40

the free model. Come use ours because

94:42

you can run it yourself if you want

94:44

locally." Mhm.

94:46

>> And that is going to be increasingly

94:49

I think that will be increasingly common

94:53

like AMD came out I don't know if you

94:54

saw what she the CEO she's brilliant she

94:57

came out with this new box that is this

95:00

like little $4,000 box or somewhere

95:02

around there and it can run like these

95:04

massive multi-billion parameter models

95:06

locally and so those charges that you

95:08

were getting

95:10

>> for you know like $1,000 a month or

95:12

$5,000 a month or whatever in AI

95:14

expenses is now just that one box that

95:16

just runs the model locally. Now

95:18

granted, it's probably eight months

95:20

behind in terms of like the model it can

95:22

run versus the frontier model who cares

95:24

>> for a lot of people who cares

95:26

>> from a business perspective and I know

95:28

that's tightly related to all sorts of

95:31

technical considerations, but

95:33

>> where do you think Google I still hate

95:36

hate saying Alphabet. Let's just say

95:37

Google the word on the street is that

95:40

they have models that are more advanced

95:42

than Fable. They have not launched them

95:45

because one the government's going to

95:47

step in and stop them

95:49

>> and two they are very expensive to run

95:51

>> y

95:52

>> and it would cost them a lot of money.

95:54

They would lose money doing so

95:56

>> and so I think in a year we're really

96:00

like 12 months we'll really know where

96:02

Google's at

96:03

>> cuz I'm telling you they're holding [ __ ]

96:05

back.

96:06

>> Of course they are.

96:06

>> They're holding [ __ ] back cuz they have

96:08

the bankroll to do that

96:09

>> and it's [ __ ] Google.

96:10

>> Yeah.

96:10

>> Like you don't understand my time there.

96:13

Sergey took me, and I'm not saying this

96:15

is a flex. I'm just like, this is just

96:17

what happened. Sergey took me and Bill

96:19

Maris, who ran Google Ventures,

96:21

>> smart dude.

96:22

>> Bill's amazing, through Google X. And

96:25

this was years ago. And we got to tour.

96:27

And he was like,

96:28

>> that's the moonshot factor.

96:29

>> It's like, dude, you already work there.

96:31

And like they make you sign [ __ ] when

96:33

you walk in. Don't [ __ ] say anything.

96:35

>> Google X is like the Willy Wonka.

96:36

>> So I'm like seeing the Whimos before

96:39

they even talked about them freaking 10

96:41

plus years ago, you know?

96:44

thing. And so I saw the crazy balloon

96:46

projects and a couple others they

96:47

shutter that I can't even talk about.

96:48

But I'm telling you, they're sitting on

96:50

deck that's like 5 years that like don't

96:54

underestimate how many freaking PhDs

96:56

they have working on this [ __ ]

96:58

>> Yeah.

96:58

>> You just can't imagine what's under the

97:01

hood there.

97:02

>> Sure.

97:03

>> Yeah. So for me, I'm not a fan of like

97:06

at this point when I think about

97:07

investing into the future and this is

97:08

not investment advice. When the

97:11

anthropics and the open AI and the

97:13

Google's like you name the top five,

97:16

>> it's kind of almost like what they said

97:17

back in the day when they had the

97:19

acronym they used for like Netflix,

97:21

Google, what was the uh

97:23

>> changes all the time,

97:24

>> but you know what I'm talking about.

97:25

FANG. Yeah. Like fang was a thing and

97:27

then there's another one and there's

97:28

another one. you're going to want to own

97:30

like those five, you know, and you'll

97:32

sit back and you'll be like, "Damn, if I

97:33

only just owned Google, I'd be up like

97:35

70%." But you're like, "Oh, you know

97:37

what? In combination, I'm up like 30%,

97:38

the market's doing 10." You'll be

97:40

stoked, right?

97:41

>> Yeah. You sent me a graph. We can delete

97:43

this.

97:43

>> The NASDAQ 100.

97:44

>> Yes.

97:45

>> Yeah. So, I mean, for you looking

97:47

forward, right, cuz you bust my balls

97:49

about some of the swings that I take,

97:51

which is is good. You should No, no, you

97:53

should bust my balls. I bust it because

97:54

I'm like, Tim, what are you optimizing

97:56

for, dude? Another zero. You don't need

97:58

another zero on the bank account.

98:00

>> I get it. I get it. I get it. But I'm

98:01

asking you, right? I mean, look,

98:04

>> we're all looking for the feeling of

98:05

being alive. Part of the way I feel

98:06

alive is by taking swings, right?

98:09

>> Fair.

98:10

>> Okay. My question for you is you're not

98:12

you're not just going to do S&P 500. I

98:14

find that hard to believe.

98:15

>> I dabble.

98:17

>> Okay. So, if you were

98:19

>> I'm like you. I bought Whimo stock and

98:21

you got pissed at me because I didn't

98:22

offer you any.

98:23

>> You're such a prick.

98:25

keeps all the the shiny stuff for

98:27

himself. He's so such a greedy little

98:28

pig.

98:29

>> I didn't know you wanted it.

98:30

>> Oh, you 100% know that I want it because

98:34

I sent this was actually turned out

98:37

pretty well. It's part of the reason why

98:38

I I pulled the trigger on Google was

98:40

such a simple approach. I took five

98:44

names, was it? It was like Google,

98:46

Anthropic, OpenAI, Whimo,

98:48

handful of other companies.

98:51

And

98:52

there's Versel, Crusoe, a couple of

98:54

others.

98:54

>> Damn it.

98:55

>> And and I sent this list out and I sent

98:57

it to like

98:58

>> I don't know five smart people I know

99:00

who are very very good investors, have

99:02

good track records, cross asset classes,

99:05

>> and a few of them sent that to like

99:07

their technical analysts who specialize

99:08

in different fields. And I was like,

99:10

that's when you know,

99:11

>> but I was like, h maybe, maybe not. And

99:13

I was like, you have 10 chips. Where do

99:15

you put those 10 chips as a bet? That's

99:17

it. No further guidance, no caveats, no

99:19

explanation. And look, I'm not saying

99:22

this is the most sophisticated

99:24

investment thesis in the world. But you

99:26

know that I wanted Whimo because it was

99:28

on that list and it was one of the

99:29

winners that came back in terms of if we

99:31

are to believe the consensus of this

99:33

small.

99:33

>> To be fair, I offered you some of my own

99:36

purchase and you you turn me down.

99:38

>> I may still take you up on it.

99:40

>> Yeah. years to wait on the 6 months for

99:41

the valuation. We just wait. Hey,

99:43

remember brother get that across.

99:46

>> Saw the news. I would love to revisit

99:48

our conversation from earlier.

99:49

>> But I think for the average person

99:51

listening like the good news is that

99:53

these companies are going out soon.

99:54

>> Yeah.

99:54

>> Like meaning they're going to be

99:55

publicly traded companies. They may seem

99:57

very expensive and very pricey and you'd

100:00

be right to say that. And so did Amazon

100:02

when it went out in 2000. You know,

100:04

>> I mean what was the market cap when

100:06

Amazon IP?

100:07

>> It was like

100:08

>> it's got to be tiny.

100:09

>> No, no, no. It's not about market cap.

100:11

It's about price to earnings, right?

100:12

Yeah. Okay.

100:13

>> So, I looked at the price.

100:15

>> Now, price to earnings will depend a

100:16

lot. I mean, it's going to be very

100:18

different for Open AI and Anthropic,

100:19

right?

100:20

>> Well, what's crazy is SpaceX is like 30%

100:23

bump on price to earnings on the peak of

100:25

Amazon. So, like SpaceX is like, did you

100:28

invest in SpaceX or No.

100:29

>> Yeah, I started investing in SpaceX like

100:31

10 12 years ago.

100:32

>> Oh, so you're stoked.

100:33

>> I mean, look, yeah, I'm fine. But, you

100:35

know, I would say here also it's like if

100:37

you're like, "Oh, I missed it because

100:38

only the fancy people get to invest

100:39

beforehand." It's like, "No." I mean,

100:41

SpaceX right now, I'm looking at the

100:43

chart, launched at 160, like had this

100:47

huge bump obviously, but then dropped

100:49

down and like you could have bought it

100:51

for 156, 154, 153, and now it's climbing

100:55

back up. I mean, there's a lot going on

100:57

here. And honestly, I still find public

101:00

equity investing terrifying cuz there's

101:02

so many sharks and there's

101:03

>> short sellers and like derivatives and

101:05

all this craziness going on and like

101:07

what happens when it's listed and put

101:09

into these indexes and blah blah blah.

101:10

Like all those dynamics are way beyond

101:12

my do the day trading thing.

101:14

>> I don't do day trading.

101:15

>> No, I'm just saying like for example

101:16

SpaceX. I don't have a position in

101:18

SpaceX, but if I did, it would be to

101:20

hold for the next 10 years. Here's a

101:22

good takeaway. You're asking like what's

101:23

what's the takeaway from like my 20 year

101:27

analysis of the angel investing? It's

101:28

still incomplete. Like there's a lot

101:30

left to do.

101:30

>> Shopify.

101:31

>> Oh god. Well, that's a good example,

101:34

right? It's like this is going to sound

101:36

so dumb and yeah, duh to so many people

101:39

who are more

101:41

just better investors than I am. But

101:42

yeah, I've done pretty well. I think the

101:44

decisions I made at the time to sell

101:46

certain things were very logical given

101:48

the information and my financial status

101:51

at the time. Totally reasonable, right?

101:53

So, I don't want to judge a good poker

101:55

play based on like where I am 20 years

101:59

hence. That's not reasonable. But the

102:02

takeaway is like you got to let your

102:03

winners run as long as possible.

102:05

>> I've lost more money by selling stocks

102:08

early than I've ever probably made

102:10

buying the original stock.

102:12

>> And the other thing I would say also for

102:13

people listening who are like, "Oh my

102:14

god, if these 1 percenters are jerking

102:16

each other off any longer, I'm going to

102:17

vomit." if you adjust and some some very

102:21

famous firm did this maybe it was

102:22

Sequoia or Benchmark I can't recall but

102:26

they looked at their gains from

102:30

initial investment all the way through

102:32

follow-on rounds to IPO and then 6

102:35

months post so after lockup for let's

102:38

just keep it simple for all intents and

102:40

purposes

102:41

>> and then they looked at what you would

102:43

have gained if you bought at IPO and

102:45

just held for like 10 years

102:46

>> and you would have paid as much or more

102:49

if you would just bought as a retail

102:51

investor.

102:51

>> Yep. That is the silver lining here,

102:53

which is I for some reason get fed all a

102:55

lot of these Instagram videos.

102:57

>> You're on Instagram so much. You send so

102:59

many Instagram [ __ ]

103:02

>> You do.

103:02

>> But the interesting thing about it is

103:05

>> so many times as individuals and I've

103:08

fallen into this trap as well, which is

103:11

you find something that you love and you

103:13

buy said object when you should actually

103:15

buy the company.

103:16

>> Yeah. So, so let's just pretend you're

103:18

going to spend $500 on iPhone every year

103:20

since it came out, right?

103:22

>> And there was this great woman that came

103:23

in and she was like, "Okay, how do you

103:25

just for the first four years of the

103:27

iPhone coming out, rather than buy an

103:28

iPhone,

103:29

>> put it into Apple?

103:29

>> Just put it into Apple.

103:30

>> That's so cool." And it was like

103:31

hundreds of thousands of dollars.

103:33

>> And my buddy sadly like I love you

103:37

Prager. David Prager. The second the

103:39

Tesla came out, not the first one, but

103:41

the the one that was consumer friendly,

103:43

you know,

103:44

>> he went out, he's like he had made a

103:45

little money and he's like, "You know

103:46

what? I'm going to do it. I'm going to

103:48

splurge."

103:48

>> Yeah.

103:48

>> I'm going to deck it out. I'm spend 100

103:51

grand on this thing and he got the

103:52

freaking top of the line Tesla. We did

103:55

the math for him because we're bastards

103:57

and it was like $15 million or something

104:01

like that. Had he just invested in Tesla

104:04

the second he loved the product. But the

104:06

moral of the story is if you love

104:08

something and this is going to happen

104:10

over and over again for decades to come.

104:12

If you're like, "Hey, Claude is my [ __ ]

104:14

I use it every single day. I think it's

104:16

great because of X Y and Z." And they go

104:18

public. Like set it and forget it.

104:20

>> Come in whatever you can afford. I don't

104:22

care if it's $100 or $1,000 or $100,000.

104:26

>> It's meaningful at the end of the day.

104:29

>> That's my It's great advice. I mean,

104:31

look,

104:33

>> that's part of the reason. And I have

104:34

gotten so much [ __ ] from this by some

104:37

VCs, I won't mention their names, who

104:39

are just like what? Because they've got

104:40

their like 30 slide our proprietary

104:43

investment thesis [ __ ] that they show

104:44

pension funds and stuff, right? And I'm

104:46

like,

104:47

>> I just try to invest in stuff that I

104:49

will use every day. Yeah.

104:50

>> Right. And it's not true for everything

104:52

like Commonwealth Fusion Systems. All

104:53

right, I'm not using them every day, but

104:55

SpaceX, you know, I mean, outside of

104:57

Starlink, but it's like there are

104:59

exceptions, but it's like with something

105:00

like this, right, where it's like I am

105:03

>> eating close to half of my protein

105:06

calories every day of this stuff. And

105:07

I'm like, I should just invest in the

105:09

company, right? It's just like

105:10

>> that is what makes sense. You know, the

105:12

first stock I ever bought is when I was

105:14

like,

105:15

>> Delonics,

105:17

>> that'd be something you use every day.

105:18

>> Tell it. Yeah. Can't go wrong. For

105:20

people that don't know what Dill Donics

105:22

say this Jesus. Yeah, that'll be another

105:23

round show notes. Um, but the uh it was

105:28

Pixar. Oh [ __ ]

105:30

>> Yeah. My dad bought me some book on

105:32

stock investing. Honestly, I couldn't

105:33

make any sense of it cuz it was getting

105:35

into like price to earning and this and

105:36

that earning per share and I was like,

105:38

"Ah, I don't really understand this."

105:39

That's so cool your dad bought you that

105:40

book.

105:41

>> It was cool. It was cool.

105:42

>> Do do you like

105:43

>> That's cool.

105:44

>> It's cool.

105:44

>> It's cool. it was his his way of like

105:46

showing love, you know, like we can't

105:48

all do it the way necessarily people

105:50

want to receive it. But

105:51

>> yeah,

105:52

>> in any case, the point of that was I

105:55

loved comics. I tracked comics and

105:58

animation and I saw Toy Story number

106:01

one. I even saw shorts and I was like

106:05

that is the future. I know that's the

106:07

future.

106:07

>> Exactly. And when I was whatever 15 or

106:10

something, first stock Pixar, I have I

106:12

have the original like shareholder

106:14

poster they mailed out like last year

106:17

and jobs and stuff.

106:18

>> Oh, dude, that's amazing.

106:19

>> Yeah. And for me, it's like look at your

106:22

credit card statement.

106:23

>> Do you know what I mean? I mean, this is

106:24

not investment advice. I'm just saying

106:26

this is the way I personally approach

106:27

it. So,formational

106:30

purposes only. But it's like, yeah, if

106:32

you're spending hundreds of dollars on

106:34

like

106:36

Amazon and Amazon Prime, it's like,

106:37

well,

106:38

>> maybe, who knows?

106:40

>> Totally.

106:40

>> You know, are you going to be spending

106:42

more or less on that in 5 years? Like,

106:43

just forget about the market. Forget

106:45

about analysts like you personally.

106:48

>> Will you be spending more or less on

106:49

this in three or five years time?

106:51

>> That's exactly right.

106:52

>> Okay. And we'll put something in the

106:54

intro on this is not investment advice,

106:56

but it's like you don't need to be a

106:58

quant hedge fund manager. Well, and to

106:59

be fair, like when you look at Buffett's

107:01

portfolio and the things that he's

107:02

bought over the years, like it's the

107:04

consumer staples and the things that

107:06

were just like he's like, "Yes, more

107:08

people will want and drink Coca-Cola in

107:11

the future. It's a fantastic brand. The

107:14

margins are impeccable. It's a well-run

107:16

business. I know the CEO. It's like

107:18

prone to disruption."

107:20

>> Yeah. Exactly. In downturns, guess what?

107:22

People still drink Coke.

107:23

>> Yeah.

107:23

>> You know, it's like

107:24

>> He's also a clever bastard, though. He's

107:26

been very good with his ash grandpa

107:29

branding. He's very good at that. But

107:31

that dude is a stone cold killer

107:33

>> in terms of

107:34

>> Geico is cash machine. And

107:36

>> yeah, I know

107:37

>> being like the lender of first resort

107:39

when going sideways. People call uncle

107:42

uncle Uncle Buffett and he's like sure

107:44

here's my offer.

107:46

>> Take or leave.

107:48

>> But yes, very bright guy.

107:50

>> All right.

107:50

>> What have we missed? Uh I the only thing

107:52

I would say is that um

107:54

>> tell Doddonics.

107:55

>> Yes, that I relaunched. If you want to

107:58

learn about the latest tech and AI news,

108:00

I relaunched DIG.

108:01

>> You're showing me some numbers. That's

108:03

crazy.

108:03

>> It's crazy. We went from 20,000 people a

108:06

week using it. Now we've close to

108:08

500,000.

108:10

So it's been growing quite a bit and

108:11

it's pulling across the entire zeitgeist

108:13

of the web. So we're we're like we don't

108:15

want to start another social network.

108:16

So, we pull from X and we pull from a

108:18

few other feeds when we'll be putting in

108:20

like videos from YouTube and Tik Tok and

108:22

others and it's just been a fun little

108:23

hobby. It's a fun hobby and it's like

108:25

doing millions of page views a month and

108:27

I'm proud of that. It's like it's

108:28

awesome to see it working again. So,

108:29

it's good.

108:30

>> Digg.com

108:31

>> digg.com Kevin Rose on Instagram and

108:35

yeah,

108:35

>> sweet. What should I say? I guess

108:37

tim.blog you can find thousand plus blog

108:39

posts. If you want to read about my

108:41

cadaavver on the table, my book sales as

108:43

a result of AI, that is a crazy blog

108:46

post. I don't even know if you were

108:47

aware of this. Oh yeah, my uh

108:49

>> all format book sales.

108:51

>> Oh, I saw that.

108:52

>> Yeah. Isn't it crazy down?

108:54

>> Well, you look at the graph and it's

108:56

like stable annuity, stable annuity,

108:58

stable annuity, very predictable. And

109:01

then in 2013, because what happened in

109:04

November 2022, chat GBT 3.5, and you see

109:08

a slip by 5%, then you see a slip by

109:11

like I'm making up these numbers, but

109:13

they're close. Negative - 28%, then it's

109:15

like -49%.

109:17

>> But it turns out you're going to be

109:18

okay.

109:19

>> I'll be fine. The implications are

109:20

pretty interesting. And now if we

109:22

continue the pace in 2026 down like 67%.

109:26

These are

109:27

>> [ __ ]

109:27

>> These are sort of compounding in the

109:29

wrong direction, right? I mean, it's not

109:30

quite the right terminology to use, but

109:32

you get it.

109:32

>> Yeah. So, stuff to think about. People

109:34

can check that out if you search AI

109:36

non-fiction Tim Ferrris. That's a blog

109:38

post. It's actually pretty interesting

109:40

read. But on a less dystopian view,

109:44

ultimately the message isn't dystopian.

109:46

Tim.blog,

109:48

Tim Ferris on Instagram, TF TF RS on

109:52

Twitter. But like honestly, I'm not so

109:54

active on the socials cuz I've deleted

109:55

those from my phone for a couple years.

109:57

You're listening to the podcast so I

109:58

don't have to sell the podcast. Oh, five

110:00

bullet Friday.

110:02

>> My diary.

110:03

>> Can you add one?

110:04

>> Can I add one? What?

110:05

>> I don't know. It's like like six

110:06

bullets.

110:07

>> Well, every once in a while if I'm lazy,

110:09

there are

110:12

>> no if I'm lazy and I'm like I don't want

110:13

to do it cuz I still I still do this

110:15

thing myself. Hold on one sec. We're

110:17

almost done.

110:18

>> Relax. You and your prostate.

110:19

>> I No, no, it's not the prostate. It's

110:20

the fact that we had You gave me

110:22

tequila.

110:23

>> Oh, I gave you tequila. You were over

110:24

served. Hold on a second. Just give me

110:26

two [ __ ] seconds, you old man. Old

110:28

bastard. So I know I'm going to make

110:30

this really long. Come on. So yeah, five

110:34

bill Friday every once in a while. You

110:35

did this yourself. Turns into six

110:36

bullets Saturday if I'm just not feeling

110:38

it. But yeah, 2 million subscribers.

110:40

It's free. Easy to unsubscribe. tim.blog

110:44

Friday. And that's all I got.

110:45

>> All right. You want to go pee, man?

110:47

>> Yeah, I will. All right. Good to see

110:48

you, buddy. Good to see you. Love you,

110:50

brother. Love you, too.

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