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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.

Interactive Summary

The video features a casual and wide-ranging conversation between Kevin Rose and Tim Ferriss. The two discuss personal experiences, including reflections on life, loss, and the importance of staying present. They dive into their personal practices, such as meditation and fitness routines, while sharing anecdotes about their pets and daily habits. The conversation also explores the impact of AI on their productivity and creative work, the ethics of using new technologies for medical or cognitive interventions, and their personal investment philosophies.

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