0:04

Brigwah and Dan Beaston are

0:07

smart enough to to know better.

0:18

Welcome to episode to episode of of

0:20

Up To Know Better. to are

0:22

a podcast of science. a And

0:24

comedy. of And ignorance. And I'm Dan

0:26

And And I'm Dan Beeston. And I'm in

0:29

this episode of smart

0:31

enough to know better, Enough to

0:33

Know Better, Aragato, Dr. Roboto. not

0:35

building any bridges, nor am I

0:37

getting over it. I And in

0:39

the it. of in the your brain wins

0:41

brain it dies. it dies. But before

0:43

we get there, what happened to

0:45

you, happened this week in this week in science?

0:47

I found found out something, something we

0:49

talked about years and years and

0:51

years and years ago. Do you

0:54

remember Do you amazing the amazing -impaired person

0:56

called Daniel called Daniel Kish, the man? man?

0:58

Yes. And he would click. Like

1:01

a dolphin. Like a dolphin. That's even got people I

1:04

did it I did went and and around

1:06

my house a couple house a the blindfold of

1:08

to try and echolocate around my house

1:10

and started picking up the ability to and

1:12

so I a bit up the out where there

1:14

was like echo hear the difference between out

1:16

there's a wall like, it was a hear

1:18

the and a lower pitched when it

1:20

was had to go further away. I a

1:22

that all of our listeners can it was

1:24

around my recording room ever since I

1:26

moved back in and don't have enough

1:28

absorbent around in the room. room. So

1:31

we do this is about this before, but

1:33

there's now a study released by

1:35

Durham now a study that Durham blind or

1:37

sighted blind in just 10 weeks.

1:39

The time it takes you to

1:41

throw away your New Year's it takes

1:44

you could be away your New as a

1:46

superhero, you could just be clicking

1:48

away and echolocating a over the

1:50

place. You could and punching is away and echo

1:53

to the all over the is it? Oh, I

1:55

assume they've got all the ninja training out

1:57

of the way first, but this is

1:59

just to the echo location, though, is it? want to learn

2:01

to be easy to learn to fight

2:03

when you can see and then you

2:05

blind yourself and then in 10 weeks

2:07

later you can echo locate that's what

2:09

I'm advocating right become a ninja blind

2:12

yourself 10 weeks later echo locate That's

2:14

the smart enough, a better promise. So

2:16

they did brain scans on people who

2:18

trained for Echo Locate, and so they

2:20

took scans of their visual cortex, so

2:22

the part that handles all the seeing,

2:25

and they were looking at how quickly

2:27

it changed. And within that 10 weeks,

2:29

it actually rewired the visual bit to

2:31

handle echoes. When I say people with

2:33

visual impairment, not just you and I

2:35

learning, but they look at these people

2:38

and were like, okay, we took their

2:40

brain scans, we looked them after they

2:42

sort of became vision impaired. The visual

2:44

cortex has now been rewired to handle

2:46

echoing, so you can hear the echo.

2:49

So you're seeing echoes now, or at

2:51

least the part of your brain that

2:53

handles seeing has been repurposed to handle

2:55

echoes, which is pretty incredible. Oh, that's

2:57

how we can learn to echo locate.

2:59

It's our plasticity of our brain. That's

3:02

a really, really cool thing. But they

3:04

went, well, what about people who aren't

3:06

vision impaired? And the answer is, if

3:08

you wear a blindfold, long enough, then

3:10

you can learn how to do this

3:13

very, very, very, very, very quickly. You

3:15

can train for very short periods of

3:17

time. So twice a week for two

3:19

or three hours, and train twice a

3:21

week for two or two or three

3:23

hours, and you can, for two or

3:26

two, two, two, two, two, two, two,

3:28

two, two, two, two, two, three, three,

3:30

two, three, three, three, three, three, three,

3:32

three, three, three, three, three, three, three,

3:34

three, three, three, three, three, three, three,

3:37

three, three, three, three, three, three, three,

3:39

three, three, three, three, three, three, three,

3:41

three, three, three, three as long as

3:43

you train properly for those two or

3:45

three hours. It's not like you have

3:47

to do it all the time, but

3:50

I found really interesting as well. With

3:52

the people who actually are vision impaired,

3:54

when they looked at the people who

3:56

did learn to echo locate, their lives

3:58

became so much much much better because

4:01

they became slightly more independent again. They

4:03

felt more independent again. They felt more

4:05

confident in the world. They didn't feel

4:07

as lost. So it's just basically. I'm

4:09

kind of surprised that it doesn't arise

4:11

spontaneously in vision impaired people like it

4:14

seems like that's the sort of you'd

4:16

start list you start hearing noises and

4:18

you'd be like oh I can get

4:20

a for something when there's a noise

4:22

in the room so I'll just start

4:24

making noise and like I'm amazed it

4:27

doesn't arrive I'm amazed that you have

4:29

to be introduced to the concept first

4:31

generally I wonder how many people have

4:33

gone like click yeah the study has

4:35

said that you know that idea you

4:38

don't take it too far but the

4:40

idea that you know you lose one

4:42

sense the other ones become more heightened

4:44

you don't I don't want to push

4:46

that too far and it's not the

4:48

same for every person, it's not the

4:51

same for every sense, but you can

4:53

start relying on other centers strongly and

4:55

it can therefore build it up. There

4:57

are more connections made in that part

4:59

of the brain. So you will start

5:02

using your hearing more and you see

5:04

your hearing become better or could become

5:06

better. It could become better. I should

5:08

say could at all times. The echo

5:10

location, the weird things about that, it

5:12

seems to be because you're trying to

5:15

use it for navigation. it seems to

5:17

go into the visual cortex. What used

5:19

to be the visual cortex, which is

5:21

now just sitting fallow doing nothing, so

5:23

it gets repurposed. So you have a

5:26

navigation cortex rather than a visual cortex,

5:28

and it just depends what you hit

5:30

it with. I think navigation, you're right,

5:32

maybe navigation is probably, now we're going

5:34

to stepping outside of the study. Navigation

5:36

is very much linked in humans to

5:39

vision more than anything else. I'm wondering

5:41

if all the rooms in your house

5:43

had a different smell in them, whether

5:45

your off-factory system would start to wire

5:47

itself into there. It would be interesting

5:50

if you set up your house like

5:52

a smart house system that always pumped

5:54

a certain perfume into a room just

5:56

slightly so that you always, there was

5:58

a different smell in each sector of

6:00

the house. I'm pretty certain your brain

6:03

might, once in, I guess, your brain

6:05

would start picking up in your house.

6:07

You would instinctively know where you were

6:09

based on the smell of your house.

6:11

What a guess. There's a thing called

6:14

a cent clock, I think. Like where

6:16

you burn incense and a particular time,

6:18

the incense changes to alert you to

6:20

a thing. Imagine being able to wire

6:22

in ICALL, like your internet calendar, into

6:24

an oil burner, that would like tip

6:27

different things in at different times, where

6:29

you'd just be working and just go,

6:31

oh, dentist appointment. Exactly. It's lunch time.

6:33

I need to go to work. As

6:35

long as and the way the brain

6:37

works, we've talked to this before, the

6:40

plasticity of the brain, you may not,

6:42

you wouldn't necessarily go, oh, that's lavender,

6:44

it must be lunchtime. Your brain would

6:46

just go, it's lunchtime, because you now

6:48

have this new sense of smell equals

6:51

thing. Once again, I'm going under, it's

6:53

not in the study, but I'm going

6:55

on a limb and saying, yeah, I

6:57

don't see why not. As long as

6:59

it's time to do something, Have a

7:01

different scream. Here's a scream to alert

7:04

you to the thing. A hygner. Yeah,

7:06

we do ignore. So that's my week

7:08

in science. I just want to say,

7:10

oh, here's foreshadowing. Brain plasticity is going

7:12

to come up again in my next

7:15

story. Ooh, later on, sizzle, sizzle, listener.

7:17

How can I prepare myself for that?

7:19

Brace yourself Dan, just you have to,

7:21

at any moment, I can leap out

7:23

and science all over you. How is

7:25

your week in science? We found a

7:28

raft of eggs on our back door.

7:30

And that's the worst way to get

7:32

eggs. Like a container of eggs? A

7:34

clutch of eggs? These are great. A

7:36

raft of eggs sounds sticky. What's a

7:39

tiny lump that looked a little like

7:41

a chunk of baby corn. It was

7:43

bright yellow and after a couple of

7:45

weeks we noticed some tiny yellow bugs

7:47

emerging. And these little yellow bugs were

7:49

being greeted by some tiny black bugs.

7:52

Oh, lovely. We could stop by and

7:54

check in them and there were always

7:56

one or two little yellow bugs emerging

7:58

and they were being greeted by more

8:00

and more little black bugs. Do you

8:03

have any theories as to what was

8:05

happening? Gregoire. I'm going to say some

8:07

bug was being born and other bugs

8:09

were coming and eating them or it's

8:11

going to be some bugs were being

8:13

born and other bugs were grabbing them

8:16

and using them as slaves. You know

8:18

ants can slave? Oh great. We've got

8:20

slaves and they grab them and take

8:22

them home somewhere. These are both great

8:24

theories. Both wrong. Ah stupid. Stupid. So

8:26

stupid. turns out these were assassin bugs.

8:29

Oh my God, this doesn't sound good.

8:31

These bugs can be found all over

8:33

the world and can give a nasty

8:35

bite. Right. They were adorable little babies

8:37

and when they hatched there are bright

8:40

translucent yellow, but that yellow carapas actually

8:42

changes to an opaque black over the

8:44

course of the next few minutes. Right.

8:46

So there were always like two being

8:48

born, but then they would change to

8:50

black really quickly. And so all the

8:53

black bugs that were loitering around were

8:55

the exact same bugs. They just turned

8:57

from yellow into black in a very

8:59

short time. Right, right, right. Okay. Age?

9:01

Was it pupating or just their armor

9:04

was like exoskeleton was armoring up and

9:06

hiding or something like that? Maybe it

9:08

was drying? I haven't found out yet.

9:10

Oh, okay. I have reached out to

9:12

a bug scientist at the Queensland Museum.

9:14

They have not yet responded. Dr. Raven,

9:17

he was, he did Iraq, but anyway,

9:19

he might know someone. Yeah, Dr. Raven,

9:21

maybe it'll come across his desk. Yeah,

9:23

yeah. These guys, little assassin bugs, they

9:25

are great to have in the garden.

9:28

They prey on myrids. And myrids are

9:30

nasty little bugs that eat my crops.

9:32

So the assassin bugs are a natural

9:34

pesticide. They inject their big old proboscis

9:36

into the bug and melt it from

9:38

the inside. The entire internal structure becomes

9:41

a delicious soup and the assassin bug

9:43

sucks it out and leaves a husk.

9:45

That must be a horrific way to

9:47

go. I'm sure it's not fast. You're

9:49

not like instantly turning to goo. Be

9:52

like, ah, everything hurts. Oh God, it

9:54

hurts. And then it's like, yes, yes.

9:56

Oh, look at you, always siding with

9:58

the mirrored bucks. Oh, Dan, have some

10:00

empathy for the mirrored bugs. The mirrored

10:02

bug has just as much right as

10:05

the assassin bug to live. But all

10:07

right, Greg, I think it helps to

10:09

think of it like this. Like, imagine

10:11

the mirrored bug is like nature's version.

10:13

the CEO of a health care insurance

10:16

company that refuses almost a third of

10:18

all insurance requests leading vulnerable people at

10:20

the brink of bankruptcy and suicide. If

10:22

that person, the heretical person, were to

10:24

be assassinated just stabbed with a giant

10:26

proboscis and melted into a sludge outside

10:29

some midtown hotel on 6th Street. Some

10:31

might consider that to be an act

10:33

of virtue that helps society as a

10:35

whole. This is what the assassin bug

10:37

is. A tiny little vigilante that keeps

10:39

my garden safe from greedy little scumbags

10:42

who just don't over up all the

10:44

resources. So if you find

10:46

a tiny chunk of baby corn,

10:49

maybe let it sit, maybe nurture

10:51

it, because you'll get a garden

10:53

of helpful little assassins. In fact,

10:55

the more assassin, bugs that we

10:58

support, the more cautious the mirrored

11:00

Beatles will have to be, and

11:02

we can all live in a

11:05

much more fruitful garden that everyone

11:07

can enjoy. Uh-huh. Thanks, Dan. Thanks

11:09

Dan for your, uh... societal changing

11:12

ways of protecting everyone in the

11:14

garden. That way leads to anarchy

11:16

Dan, total anarchy. Does it? People

11:19

killing each other because what? People

11:21

killing people for the sake of,

11:23

oh I want to do something,

11:25

it's all fun and games when

11:28

it's people you want killed, but

11:30

then someone kills people that you

11:32

don't want killed and oh no

11:35

it's a thing. What I'm hearing

11:37

is it's all fun and games.

11:40

When it comes to real estate,

11:42

people always talk about location, location,

11:45

location. And it turns out that

11:47

your brain is like the most

11:49

ruthless real estate market of all.

11:52

Like there is crazy levels of

11:54

location holding going on in your

11:56

brain. That's where I send all

11:59

the resources. yes, that's so yes,

12:01

so those carbohydrates down and send

12:03

them to the top baby 30%

12:06

That's it. They're like at least

12:08

30% so it's really really the

12:10

brain is we talked before about

12:13

brain plasticity and this is absolutely

12:15

what I'm gonna talk about now

12:17

is absolutely that on steroids metaphorical

12:20

steroids. So I've because I'm getting

12:22

some mixed messages here can

12:25

help you in this part of the

12:27

story. So remember what we talked about

12:29

before with the brain and echo locating

12:31

and the visual part of the brain.

12:33

So the visual part of the brain,

12:35

the visual part of the brain, the

12:38

visual cortex, can be repurposed for other

12:40

things. And it can be senses or

12:42

anything like hearing or whatever it can

12:44

be. It can process touch and sound.

12:46

It's been shown that this plasticity, this

12:48

change, this loss of function of an

12:51

area can happen in under an hour.

12:53

So if you put blindfolds on someone,

12:55

this has been done in the study,

12:57

put blindfolds on people and then scan

12:59

their brains to see what's going on,

13:01

in under an hour some other parts

13:03

of the brain will start to colonize

13:06

the visual cortex. Now is this, do

13:08

you know the age group of the

13:10

people studied? Is it like three year

13:12

olds or ninety year olds? We'll get

13:14

to that later on. So these are

13:16

adults but they're talking about, they have

13:19

done studies on connected studies, not literally

13:21

on this, but they're talking about working

13:23

with younger people in other areas and

13:25

the implications to that. But we'll get

13:27

back to that. What the study was

13:29

about actually was dreaming? What is the

13:32

purpose of dreaming? Oh yeah. An actual

13:34

scientific study of what is dreaming. And

13:36

there's been lots of theories about dreaming.

13:38

Have you heard any theories about dreaming

13:40

Dan? Yes, I've heard that there was

13:42

a study that I think we might

13:45

have discussed at one point where they

13:47

forgot all their participants to get into

13:49

a like a ski machine like where

13:51

you pretended to ski down a hill

13:53

just before they went to sleep. And

13:55

then they woke them up after like

13:57

30 minutes and all of their dreams.

14:00

sliding in some way. They proposed

14:02

that it was about taking all

14:05

the information of the day and

14:07

sort of categorizing it and working

14:09

out what's important and trying to

14:12

get it to just getting your

14:14

brain to like store memory in

14:16

a slightly more effective way. Yep.

14:18

And REM sleep is where we

14:21

dream. That's a really important part

14:23

of sleep. If you don't get

14:25

that, you get psychological problems real

14:28

fast. So people talk about like,

14:30

is it about categorization? Is it

14:32

about cleaning the brain up? It's

14:34

because people who just rest physically,

14:37

you've got to go. Because REM

14:39

sleep is about getting your, your

14:41

ed and sort of compartmentalizing it,

14:43

where you put me in a

14:46

spotlight. Very

14:48

good. Losing your religion? Yes, it's

14:50

a... That happened twice as a guy.

14:53

So we don't really know why we

14:55

are E.M. sleep, but we know that

14:57

we don't have it, thinking you're

14:59

very wrong very quickly. The idea of

15:02

your brain needs to sleep to

15:04

kind of clear itself out of lots

15:06

of problems, that it does that, but

15:08

that's not necessarily dreaming or it's not

15:11

necessarily dreaming or it's not necessarily

15:13

dreaming or it's not necessarily connected to

15:15

dreaming. So why do we dream?

15:17

And why are dreams heavily visual, people,

15:19

but when most people talk about something

15:22

they saw? We're a visual ape, but

15:24

we use our vision much more

15:26

than we use. Some people aren't, are

15:28

they? Some people have pros of

15:30

prognosis and can't visualize in their heads,

15:33

but they can still dream supposedly. That's

15:35

crazy. So they have visual dreams, but

15:37

not can't visualize things in there.

15:39

I don't know about that. I just,

15:42

as I said, that I was

15:44

like, oh, there's a lot to unpack

15:46

there. So we'd have to look into

15:48

that. I think Prossopagnosia is, I think

15:51

Prossopagnosia is actually the one where

15:53

you associate colors with numbers and stuff.

15:55

That's in a synesthesia. Oh, right.

15:57

So maybe it is I

16:00

think it's a prosyphagnosis and you can't

16:02

do it. Why? We're getting well off

16:04

trafficking. Let's stay back on track. So

16:06

the idea is, why do we dream?

16:08

What's going on? So this is a

16:10

study based on this and looking at

16:12

the problem. The problem is that human

16:15

beings, and even as mammals for millions

16:17

of years, we have a habit of

16:19

going to sleep at night when things

16:21

are dangerous. So at night time, we

16:23

can still hear things, because sound travels.

16:25

Wait. I thought mammals started off as

16:27

nocturnal and we're the deviant. So you're

16:29

right. So yes, that's true. Yes, true.

16:31

So yes, you're right. So you're right.

16:34

Actually, to begin with mammals did from

16:36

the day stay still in the day

16:38

and at night time sort of wandered

16:40

around so we can see things in

16:42

the dark and all the rest and

16:44

better thing. But as I should say

16:46

humans, I should say humans, not at

16:48

mammals, apologize. I misspoke there. So humans

16:50

changed became became diurnal instead of being

16:53

nocturnal. munched. But in the dark we

16:55

can still hear quite well and we

16:57

can still smell just as fine and

16:59

it's our vision is the problem. And

17:01

so these people doing the study when

17:03

they realize they went well hang on

17:05

a minute if you blindfold someone and

17:07

within 60 minutes their brain starts becoming

17:09

colonized by other senses. What happens when

17:12

you can't see anything over eight hours

17:14

or 12 hours of darkness? Is there

17:16

actually loss of visual areas of the

17:18

brain? Does it get colonized? And the

17:20

answer is yes. So in the dark,

17:22

if you hang out in the... I'm

17:24

joining dots. I'm joining dots. So if

17:26

you stand in the dark, full darkness,

17:29

other areas of your brain will start

17:31

to recolonize the visual cortex. So the

17:33

moment that there is no longer visual

17:35

input coming to it, the brain's like...

17:37

Oh, that's not being used. We probably

17:39

should use this. This is an amazing

17:41

resource. We should probably hand it over

17:43

to, like smells like, I'm here! And

17:45

Touch is like, I'm ready to move

17:48

in, everyone. And that calculation's like, this

17:50

is mine, bitches. And you start losing

17:52

your function real fast. You think that

17:54

would mean we would just lose everything

17:56

and you'd have to wake up in

17:58

the morning, you have to fight back

18:00

to your visual cortex. no, no, well,

18:02

you start over your eyes. Takes me

18:04

like an hour before I can, like,

18:07

look at anything at Valley. But you

18:09

can still see. That's why people wake

18:11

up in the morning and they squint

18:13

their eyes like that. And I can

18:15

only let in a little bit of

18:17

visual. Give me taste. Give me coffee

18:19

or tea. And that'll help wake up

18:21

the other senses. I've got a thing.

18:23

This is now just side, we haven't

18:26

even got to the main point of

18:28

this yet, but side note already. That

18:30

sounds like the podcast. I'm a thing

18:32

where I noticed a few years myself

18:34

doing it, but recently a lot more.

18:36

When I wake up and I'm really

18:38

tired, only one eye opens, I have

18:40

one eye. And it's my left eye,

18:42

it's always my left. My left eye

18:45

opens, and my left, my left eye

18:47

opens, and my left eye opens, and

18:49

I'll walk around, and my right eye

18:51

is not squinting shut. It's just fully

18:53

closed. I'm like a pirate eye, it's

18:55

just opened up. Well you're very paranoid

18:57

right? You get like night terrors. Do

18:59

you sleep with one eye open maybe?

19:01

Maybe, maybe. Here's my theory. It's a

19:04

totally crazy theory based on almost nothing.

19:06

Because it's my left eye that opens.

19:08

So it's my right eye that opens.

19:10

So it's my right eye. So it's

19:12

my right eye that opens. So it's

19:14

my right eye. So I like the

19:16

idea of my left part of my

19:18

brain. Handle the morning thing. And when

19:20

I feel better about the whole thing,

19:23

we'll join it all up together into

19:25

one big unit. and I realize I'm

19:27

quite happy to use my left eye

19:29

just to handle everything. So I don't

19:31

know, based on nothing, but it's an

19:33

odd thing I've noticed about myself. The

19:35

left eye is the one that's sort

19:37

of in charge. That's the dexterous eye.

19:39

That's the right-hand side of the brain.

19:42

Yes, it crosses over, yes. So that's

19:44

the right-hand side is where the language

19:46

is. That's what I was thinking. I

19:48

think I'm right there. So the right-hand

19:50

side is mainly where language comes from.

19:52

So that's the part that needs to

19:54

be awake so I can communicate as

19:56

a human. The left-hand side of the

19:58

brain doesn't have as much language or

20:01

doesn't have language. So maybe it's just

20:03

like, well, I'm not needed. five more

20:05

minutes. Five more minutes. I can't say

20:07

it. Anyway, I don't know. Back to

20:09

the story. Your brain is being colonized

20:11

or parts of your brain, but your

20:13

brain has a security guard to stop

20:15

all this nonsense. And it's something called

20:17

the PGO wave. The brain stem sends

20:20

out the signal, and it's called the

20:22

pontogenocular occipital wave, and it's sent from

20:24

the brain stem, from the lower part

20:26

of your brain, into the visual cortex.

20:28

to give it information so that it

20:30

can't be easily colonized. So it gets

20:32

random signals sent up from the brain

20:34

stem that only only goes to the

20:36

visual cortex, not just floods the brain.

20:39

So it's like this, hey everyone, hey

20:41

no, thanks everyone, thanks for your application,

20:43

but actually visual cortex is here and

20:45

vision needs this area of the brain.

20:47

It's like beer. Yeah, it's like the

20:49

brain is water and there is all

20:51

these sort of microbes that want to

20:53

get in, but we just put in

20:55

a bunch of yeast and the yeast

20:58

just displaces everything else. And that's all

21:00

it's doing. Right, sure. and producing the

21:02

alcohol. Yeah, which is like dream logic.

21:04

Oh, I see. Yes, yes, that's what

21:06

you're saying. So this signal that's sent

21:08

into the area of the brain is

21:10

that they don't think that signal is

21:12

the dreaming signal, by the way. They

21:14

don't think that's been turned into dreams.

21:17

It's just the thing that keeps the

21:19

visual cortex going clicking over so that

21:21

it doesn't, so it's working, get colonized

21:23

as quickly. It can basically hold everything

21:25

off. Right. The other connection is the

21:27

more plastic your brain, the plastic your

21:29

brain, the more REM sleep you require.

21:31

So humans get about a percentage of

21:33

21% of REM sleep and the other

21:36

primates and other monkeys, or primates, basically

21:38

have less and less, so the recess

21:40

monkeys, chimpanzees, 16%, vervet monkeys are 6%.

21:42

baboons are like 13% and they get

21:44

less rem sleep. So the more basically

21:46

the more rem sleep you get the

21:48

more you lose your visual cortex or

21:50

actually defend your visual cortex. So the

21:52

more complicated your vision a trichromatic primate,

21:55

so it's a full color vision, on

21:57

average get about 50% more REM sleep

21:59

than monochromatic or dichromatic primates. So if

22:01

you have primates that can't see all

22:03

the range of colors that we can,

22:05

they actually need less REM sleep than

22:07

we do. So the connection here is

22:09

that they think that dreams may be

22:11

the visual cortex of the brain throwing

22:14

up its own signals, saying fine, if

22:16

you haven't got signals, I will create

22:18

my own signals so that I don't

22:20

get colonized. Yeah, that's right. Now, where

22:22

they come from and how they make

22:24

them, that's a different thing, well, for

22:26

another time. This study seems to state

22:28

that they're there as a placeholder for

22:31

your visual cortex. So if you're visual

22:33

information, so your visual information from your

22:35

eyes, which I found really, really interesting.

22:37

So it's a back in five minutes.

22:39

Yeah, yeah, basically. Yes, that's right. Just

22:41

watch this real show. That'd be great.

22:43

So baby is going on to babies.

22:45

Babies need 50% of sleep is REM.

22:47

Young adults is 2025. And the elderly

22:50

is about 10 to 20% REM sleep.

22:52

We don't need as much REM sleep.

22:54

So it's like these cards in a

22:56

TV show, like for a TV station,

22:58

where it says technical difficulties. And it

23:00

just shows you. Bupa-pah-pah-pah-pah-pah-pah-pah-pah-pah-pah-pah-pah-pah-pah-pah-pah-pah-pah-pah-pah-pah-pah-pah-pah-pah-pah-pah-pah-pah-pah-pah-pah-pah-pah-pah-pah-pah-pah-pah-pah-pah-p It really really

23:02

really really really could be absolutely. Babies

23:04

are making a lot more connections in

23:06

the brain. Their brains are being built

23:09

so they need a lot of REM

23:11

sleep to do that. We don't want

23:13

to rebuild everything in the brain. Old

23:15

do you get the less plastic your

23:17

brain becomes or less REM sleepier it

23:19

comes. All right here's a really interesting

23:21

point though. Elephants totally buck this trend

23:23

when it comes to mammals. Well not

23:25

just primates but mammals. Elephants only get

23:28

a few minutes of REM sleep per

23:30

night and they only get a few

23:32

minutes of REM sleep per night. They

23:34

don't need a few minutes. And sometimes

23:36

they may not have any REM sleep

23:38

at all, like in a night. They

23:40

will after a while, but they don't

23:42

need it necessarily every day. Elephants in

23:44

the captivity sleep more and have more

23:47

REM sleep. This could blow out of

23:49

the water. But the theory here, connected

23:51

to all, what we just talked here,

23:53

is that elephants also have very good

23:55

adaption for night vision. And because they

23:57

only sleep a little bit, they don't.

23:59

to have the system to stop their

24:01

brain from being colonized because they're constantly

24:03

watching in the dark. They're up a

24:06

lot and they need to sleep a

24:08

little bit and so they can have

24:10

it. They ram a little bit to

24:12

protect the brain but they don't need

24:14

to have it because they're looking around.

24:16

They're awake and they can see in

24:18

the dark. or relatively well. Let's think

24:20

about another way, maybe they had to

24:22

develop the ability to not sleep very

24:25

often, because as soon as that nose

24:27

gets an in, like that nose is

24:29

a big, like there are all factory

24:31

systems like, I will take you down.

24:34

Absolutely. This ties it also with things like

24:36

medical conditions. So if you have macular degeneration,

24:38

people report very complex visual hallucinations and people

24:40

in, you go into solitary confinement, lots of

24:42

visual hallucinations come from there. deprivation tanks, which

24:45

I've experienced, visual hallucinations from that. People who

24:47

live in constant darkness, like it's 12, you

24:49

know, 30 hours or 30 days of night,

24:51

visual hallucinations like no one's business, they think

24:53

that's also connected to the brain. Your visual

24:56

cortex, like, oh my God, we're not getting

24:58

enough input or any input, and we're going

25:00

to lose everything if we don't start throwing

25:02

up crazy pictures. Once again, where those pictures

25:04

come from, why are those pictures? Who knows?

25:07

But it seems to be connected to it.

25:09

I wonder if that's why some people struggle

25:11

to get to sleep, because they, as soon

25:13

as they close their eyes, their brain's like,

25:15

we just got a, dada, dada, dada, dada,

25:18

dada, dah, dah, dah, it could be, absolutely,

25:20

really, really, really, it could be. The thing

25:22

I say about the modern sleep problems, fragmented

25:24

sleep and having, and having certain drugs and

25:26

alcohol, and alcohol, stopping this part of the

25:29

brain, stopping this part of the brain, a

25:31

system set up that it needs to run.

25:33

And if you don't let it run that

25:35

system, the brain gets upset. So let your

25:37

brain do what it needs to do, try

25:40

and get sleep, try and have REM sleep,

25:42

try not to have lots of drugs that

25:44

break it up and try not to have

25:46

fragmented sleep if you possibly can. Try and

25:48

have chunks of sleep, like what is an

25:51

hour and a half for a most average

25:53

human cycle. So try and sleep in one

25:55

and a half hour cycles and actually get

25:57

some sleep. Yeah. But I did that for

25:59

13. like a bastard.

26:01

Well, yeah, I mean, it

26:04

wasn't the end of the

26:06

world as I knew it.

26:08

You feel fine? Yeah, I

26:10

feel fine. Next up, Dan

26:12

doesn't leave, they put a

26:14

man on the moon. That's

26:16

a propped, right-end turn for

26:18

the podcast. So Gregor, you

26:20

spent a week in Perth

26:22

recently. I did. I found

26:25

myself thinking, if I wanted

26:27

to visit you, how would

26:29

I go about that? To

26:31

travel from Brisbane to Perth.

26:33

What would be the best

26:35

solution? Any ideas, Gregor? Fly?

26:38

An airplane? Oh, well that

26:40

makes more sense. Yes. So

26:42

that's a great idea. That's

26:44

great. But what if I,

26:46

for some unknown reason, didn't

26:48

want to cross, say, running

26:50

water? Let's say it's been

26:52

quite rainy over the entire

26:55

continent and I can't cross

26:57

running water for reasons that

26:59

neither you nor Abraham Van

27:01

Helsing need look any further

27:03

into. Is it weird

27:05

to me that my brain is set

27:07

up in such a way that moment

27:10

you mentioned running water? I'm like, he's

27:12

a vampire. Is that, that, I don't

27:14

have to. No, no, no, no, no,

27:16

I'm just saying I just maybe think

27:19

of something. Yeah. At any rate, I

27:21

am coming to get, meet you. I'm

27:23

coming to meet you. and I need

27:25

to find a path that doesn't involve

27:28

crossing a stream or a river. Now

27:30

I don't want to mention my star

27:32

location because I have made some pretty

27:34

concerning statements about mirrored beetles recently and

27:37

I don't want to create a bread

27:39

come trail. But let's start off by

27:41

saying that I don't live on an

27:43

island. I mean I do live on

27:46

an island continent of Australia, but I

27:48

don't live on say Harley Island, which

27:50

is in the Pine River. I can

27:52

walk west from my house and meander

27:54

through the neighborhoods until I get to

27:57

the Bunnyville Conservation Park. It's like up

27:59

in the nearest set of what we

28:01

would call mountains. the rest of the

28:03

world would call hills. Vague foothills. Yes.

28:06

Embarrassing lumps. Yes. Oh look, I've seen

28:08

some international embarrassing lumps. I'm subscribed to

28:10

it. Doesn't matter. What

28:13

I've had to do is navigate between

28:15

the tributaries of Cabbage Tree Creek to

28:17

the south and Pine River to the

28:19

north. But those tributaries never cross. Streams

28:21

don't really do that. I will have

28:23

followed a natural crest between those areas.

28:25

Now the Brisbane River is further to

28:27

the south but extends back towards Lake

28:30

Wyvernhoe and then back north towards Somerset

28:32

Dam and then the catchment area for

28:34

that extends all the way back towards

28:36

like towards the sort of northeast towards

28:38

West Caloundra on the coast. So it

28:40

is huge. This is very specific to

28:42

anyone who leave and I'm like, what

28:44

are you talking about? Yes. In fact,

28:47

my next line that I've written down

28:49

is now this is becoming very location

28:51

specific and potentially losing our international listeners.

28:53

In fact, anyone that doesn't live in

28:55

the southeast corner of Queensland. But what

28:57

I'm getting at here is that it's

28:59

all about the catchment areas. If you

29:01

look at the edge of Australia or

29:04

in fact any country and you look

29:06

at the big rivers, they all come

29:08

from smaller and smaller streams. You can

29:10

kind of imagine it like a tree

29:12

made of water with the main river

29:14

that dumps into the sea being the

29:16

trunk, growing back into the land mass.

29:18

and becoming thinner and thinner branches of

29:21

the tree. And here's something interesting without,

29:23

because I'm not saying down and I

29:25

never talk about what story is going

29:27

to be, just coincidentally, I happened to

29:29

watch a YouTube video recently talking about

29:31

why Australia isn't more colonised and why

29:33

there aren't more people, you know, why

29:35

aren't there more people in this country,

29:37

though we could definitely fit them. that

29:40

we have a land mass equivalent to

29:42

the United States, mainland United States, why

29:44

don't we have 350 million people? The

29:46

answer is desert. But the point of

29:48

this is, I didn't realize before that

29:50

major rivers are only about one third,

29:52

a quarter to a third from the

29:54

east coast going inland. that's it. The

29:57

rest of it, there are no major

29:59

rivers. There's the Swan and a few

30:01

others, but there over in Perth, there's

30:03

nothing like running through the center of

30:05

the country or splitting the country. There

30:07

isn't a Mississippi Delta, anything like that.

30:09

We just don't have that. We will

30:11

get into that a little bit, actually.

30:14

Oh, okay. So yeah, I just found

30:16

that really, I was like, I never

30:18

visualized before, I went, oh yeah, the

30:20

East Coast all the way down, has

30:22

rivers, rivers, rivers, rivers, rivers, rivers, rivers,

30:24

rivers, rivers, rivers, rivers, rivers, rivers, rivers,

30:26

rivers, rivers, rivers, rivers, rivers, rivers, rivers,

30:28

rivers, rivers, rivers, rivers, rivers, rivers, rivers,

30:31

rivers, rivers, rivers, rivers, rivers, rivers, rivers,

30:33

rivers, rivers, rivers, rivers, rivers, rivers, rivers,

30:35

rivers, rivers, rivers, rivers, and then, rivers,

30:37

rivers, rivers, rivers, rivers, rivers, rivers, and

30:39

No, you're pretty much right. If we're

30:41

visualizing like the big rivers along the

30:43

East Coast, and they're not very big,

30:45

they don't extend very far, because we've

30:48

got like a land, like the mountains.

30:50

What are the mountains called? The blue

30:52

mountains? The great dividing range. Great dividing

30:54

range, that's the one. Between the bigger

30:56

river systems there, you would have lots

30:58

of little river systems that kind of

31:00

look like shrubs between the trees. The

31:02

important thing is that they don't intersect

31:05

with each other. So if I want

31:07

to get to Perth, I need to

31:09

find the line between the edge of

31:11

every catchment area and those are the

31:13

paths that I can travel on if

31:15

I don't want to cross running water.

31:17

That means you have to walk along

31:19

the ridges of foothills and mountains. Pretty

31:22

much. Yep, yep, you could do that.

31:24

There are several decent-sized catchments along the

31:26

eastern Queensland coast, but I need to

31:28

navigate inland, so I go north of

31:30

the Brisbane catchment area and south of

31:32

the Mary Valley catchment area, and as

31:34

I progress inland, I hit a problem.

31:36

The Murray Darling Basin takes up a

31:38

million square kilometers, one seventh of the

31:41

entire land mass of Australia. Yes. It's

31:43

bigger than Texas by a considerable amount.

31:45

It's larger than Egypt, twice as big

31:47

as France. It dumps into Victor Harbour

31:49

just east of Adelaide, right down the

31:51

bottom. But it doesn't flow all the

31:53

time, does it? It's seasonal, is that

31:55

right? It does flow all the time,

31:58

but obviously the tributaries are going to

32:00

be drier and drier. There's always water,

32:02

it's in some part of the maridale.

32:04

in this scenario, very rainy, every stream

32:06

in Australia has running water. Otherwise, being

32:08

a vampire in Australia, very easy. That's

32:10

true. Now we're shooting things like the

32:12

Artesian basin is not running water and

32:15

it's also underground that everyone doesn't count.

32:17

Well, we're not going to have... We're

32:19

getting to that. Where

32:21

are we? The Murray-Darling Basin. There is

32:24

no way around it to the south

32:26

because it dumps into the ocean. So

32:28

I have to travel northwest and continue

32:31

close to the center of Queensland where

32:33

the top of the, where the Murray-Darling

32:35

starts. Sure. The international listeners, that's like

32:38

halfway up the continental landmass from the

32:40

East Coast, basically. Probably even more. Okay,

32:42

further north than that, okay? Two thirds

32:44

of the way up? Yeah, and that's

32:47

where I have a very interesting decision

32:49

to make. If every water basin made

32:51

it to the ocean, then there was

32:54

only one path to get from any

32:56

one place to any other place, if

32:58

we rule out islands and river deltas.

33:01

But this is not the case, because

33:03

you know what, we just hit, Greguire?

33:05

What's that? The Lake Air Basin. Oh,

33:08

so we're there. Okay, I thought we're

33:10

further up. Okay, right, right, right. We

33:12

are further up. Oh, okay. The Lake

33:15

Air Basin covers 1.2 million square kilometers

33:17

and pools in Lake Air in the

33:19

north of South Australia, or as I

33:21

like to call it, the middle. I

33:24

thought we were two-thirds up the continent.

33:26

That's well into Queensland. You're in South

33:28

Australia. You're down the bottom. Lake Air

33:31

is in the north part of South

33:33

Australia, but the Lake Air Basin actually

33:35

extends really far north. Oh, okay, that's

33:38

the Old Inland Sea area, isn't it?

33:40

Yes. Okay, so go on, I'm sorry,

33:42

yes. It's an Old Inland Sea area,

33:45

but what it's called now is an

33:47

Indoor Heek Lake. The water never makes

33:49

it to the sea. It just evaporates.

33:51

If there was 60 meters of rainfall

33:54

in that basin, it would spill out

33:56

into the Murray darling. But if that

33:58

amount of water is moving around the

34:01

atmosphere, you've got more problems than just

34:03

vampires. just ignore that. I'm just rambling.

34:05

When you say vampires, I assume. No,

34:08

I didn't say, no, no, no. It's

34:10

fine. When you say vampires, I'm assuming

34:12

you mean, you know, like in meteorological

34:15

effects, there are, you know, like lightings

34:17

called sprites and ghosts and red, red

34:19

devils or what are they called? I

34:22

assume you just mean vampires, like some

34:24

sort of meteorological thing. It

34:26

gathers from further north than Mount Izer

34:28

and further south than Broken Hill. 1400

34:31

kilometers and it is right in my

34:33

way. I follow the southern edge of

34:35

the basin because my gold is Perth

34:37

which is fairly south. Can I ask

34:39

a question here though? Is it running

34:41

water if it's not running through a

34:43

river? If it's evaporating away I would

34:45

say it's still water not running water.

34:48

Water from the tributaries of the Lake

34:50

Eyre Basin, make it to Lake Eyre,

34:52

if it's raining enough. Sure. In the

34:54

scenario. Lots of rain. Okay, yes. We

34:56

said that's okay, but so water for

34:58

the tributaries is going into a place

35:00

that's a storage area. Is that still

35:03

considered running water? You've decided that's no

35:05

running water though. Oh, the lake itself.

35:07

The lake itself, yes. That's a very

35:09

good question. It's not flowing out. It's

35:11

not flowing anywhere. It's evaporating away. You

35:13

know, it's flowing into the sky. Yes,

35:15

we could say that. If there was

35:18

a lake... If a lake has a

35:20

tributary coming into it, but it also

35:22

releases out. Yes, like it then, you

35:24

would probably consider that lake to be

35:26

running water. Yes, like the Panama Canal,

35:28

I can't remember the name, the lake

35:30

that is halfway through the Panama Canal,

35:32

that has a tributary coming in, well,

35:35

the canal, I guess, and then it

35:37

flows out the other way. So you

35:39

can say that's running water all the

35:41

way through, but is lake air. But

35:43

only intermittently, if you could like, because

35:45

each section is like still water, except

35:47

for the time where it's draining. Well,

35:50

these vampires madly crossing during the, uh,

35:52

anyway, not the. but you decide, we're

35:54

going to say Lake Air is running

35:56

water for this case. Yeah, if it's

35:58

not, I guess you could like make

36:00

your way all the way down to

36:02

the lake and then paddle across the

36:05

lake. But in the story, Dracula, in

36:07

order to cross the sea, he had

36:09

to be in a, taken in a

36:11

casket with earth from his homeland. I

36:13

thought he had to sleep in it.

36:15

That was to sleep in it though.

36:17

He does have to sleep in it.

36:19

So I don't know how to cross.

36:22

Ocean is not considered running water, I

36:24

don't think. Yeah. Otherwise, he couldn't cross

36:26

it. But he can be dragged across

36:28

it by his minions. Oh, he's not

36:30

choosing to cross it. He's just gone

36:32

to sleep and people moved him. Maybe.

36:34

I'm not sure. Not that matters because

36:37

vampires don't exist at time. Yeah, it's

36:39

crazy. That's silly. But I follow the

36:41

southern edge of the basin because my

36:43

goal is Perth, which is fairly south

36:45

and not Broom, which is further north

36:47

in Western Australia. Once I'm clear of

36:49

that basin things get a lot easier.

36:52

I'm on the Great Western Plateau. This

36:54

is full of little tiny catchments that

36:56

drain into their own indoor heek lakes.

36:58

I just need to make my way

37:00

through the little patchwork pattern of catchments

37:02

until I get to Calguli, 500 kilometers

37:04

east of Perth. Here... By this point

37:06

in time you've traveled close to 3,000

37:09

kilometers of this... Like you've traveled a

37:11

lot of distance. Yep. Yep. Yep. Just

37:13

once again, give people the idea. Once

37:15

in one tenth of the way around

37:17

the planet, not quite one ninth the

37:19

way around the planet, like a big,

37:21

yeah. But it's not that hard if

37:24

you can transform into bats or wolves.

37:26

Not that I can. Well, drive a

37:28

car or whatever, you know, whatever. Yeah,

37:30

I can drive a car. truck probably

37:32

plenty of spare tires and fuel. Yep.

37:34

But at any rate, here I've reached

37:36

the Swan Avon catchment area. It's like

37:39

400 kilometers from north to south. All

37:41

I need is to establish what side

37:43

of the river you're on. Southside, I

37:45

need to head south of Lake Grace

37:47

and then back up to Perth. If

37:49

you're on the north side, I just

37:51

need to go north by just as

37:53

much distance. Yeah, yeah, yeah. And then

37:56

I've made it to you without ever

37:58

having to cross running water. Fantastic. It's

38:00

a bit tricky. Yeah, yeah. It's interesting

38:02

to think that in where environments vampires

38:04

would have to hunt along these narrow

38:06

pathways. Like if you were hunting vampires,

38:08

you could set up choked points where

38:11

you know they need to go. But

38:13

vice versa in the concept of vampires,

38:15

I like the idea that vampires, if

38:17

they are like, they're a super predatory

38:19

human species, basically a subspecies of humans,

38:21

it predates on humans, normal, vertical humans,

38:23

normal, vertical, normal, normal, normal humans, and

38:26

in this case it would be a

38:28

river hunting species. It would be a,

38:30

it would have to sit up on

38:32

the ridges and then come down into

38:34

the river areas, but that's where humans

38:36

like to hang out. Up on the

38:38

creepy outcomes. I get higher up, exactly.

38:40

But vampires could descend from their earies

38:43

and predate on humans and go back

38:45

up to the ridges. So they would

38:47

control the ridges, as you see. And

38:49

when humans moved up there to build

38:51

castles, the vampires are waiting for them.

38:53

But if the vampires, after you run

38:55

across a bridge, nothing you can do.

38:58

Yeah. But on the ridge, there's no

39:00

where you can kind of go at

39:02

that point. Sort of... I mean, if

39:04

you could find tributaries, you could like,

39:06

cross them quite quickly, maybe, but yeah,

39:08

you'd want it to be rainy. Oddly

39:10

enough, stormy rainy weather, perfect time to

39:13

avoid vampires. Nice dry sunny sky, well

39:15

not sunny, but nice clear skies. You're

39:17

in trouble. Yeah, yeah, yeah. Once again,

39:19

on the ridges, it doesn't make a

39:21

difference if it's raining or not, because

39:23

you're up on a ridge. So the

39:25

vampires just have to wait, and they'll

39:27

only parade on the, you said, on

39:30

one side of the river. Most of

39:32

the time in a lot of towns

39:34

and cities, they may start on one

39:36

side of the river, but they'll probably

39:38

end up going to the other side.

39:40

Though it could be a reason why.

39:42

is very much built on the north

39:45

side of the Thames and then yes

39:47

it's obviously now spread everywhere but it

39:49

took a long time to kind of

39:51

cross and south side of the Thames

39:53

you just didn't because everyone who went

39:55

over there was drained of their blood.

39:57

But that's the if you had blood-sucking

40:00

monsters on the other side and you

40:02

didn't realize that you just went there

40:04

would be these weird on one side

40:06

of the river that would be predated

40:08

on more and therefore you'd have less

40:10

things going on there than the other

40:12

side. So your idea about like air

40:14

was interesting. What happens if you hit

40:17

a dam? Yeah, exactly. You dam the

40:19

water instead of a bridge and then

40:21

there's no water underneath you and you

40:23

can walk straight across it. Yeah, in

40:25

Australia, like you go long reach and

40:27

you have dry river beds that could

40:29

say dry for years and then they

40:32

can flow like, well the Don River

40:34

in Bowen in North Queensland where I

40:36

grew up, that was dry and when

40:38

it flooded, when it flowed it was

40:40

like the second fastest flowing river in

40:42

the southern hemisphere. It was crazy. So

40:44

they would be dangerous places for vampires

40:47

sometimes. Well, they're not dangerous, I just

40:49

wouldn't, you wouldn't be able to cross

40:51

them when they flood. So, you know,

40:53

it's fine. Can you make running water?

40:55

Are you allowed to dig a trench

40:57

and have water being pumped around and

40:59

around and around? Is that considered running?

41:01

If a vampire can't flow over running

41:04

water... Like if they can't fly over

41:06

it, then it shouldn't matter how deep

41:08

the running water is. There's something about

41:10

that running water being underneath them that

41:12

stop prevents them from crossing. So they

41:14

can cross a dam, but only one's

41:16

completely closed off. So what about plumbing?

41:19

Old castles aren't plumbed, but vampires today

41:21

are constantly faced with a crisp crossing

41:23

of water pipes. to create a nest

41:25

of problems for the undead. Yeah. Also

41:27

in crosses as well, we've accidentally made

41:29

all these pipes that probably make little

41:31

fun crosses for them not to be

41:34

able to handle as well. Yeah, although

41:36

I think they kind of have to

41:38

see the cross. It's always about showing

41:40

that they like avert their eyes from

41:42

the cross. But maybe they're like, I'm

41:44

going to smash open this wall with

41:46

my supernatural strength. Bam! They knock down

41:48

the white, the white stuff. thank you

41:51

and they're like ah sod there's running

41:53

water and crosses and oh well the

41:55

vertical running water wouldn't be a problem

41:57

but you could you could create an

41:59

open air vampire trap by running a

42:01

pipe underground in a spiral and then

42:03

you lure the vampire like a water

42:06

slide where it goes in a spiral

42:08

so then you but you don't put

42:10

run water through it then you lure

42:12

the vampire inside the spiral start the

42:14

water up vampire then has a circle

42:16

of running water trapping it in position

42:18

It can't cross running water, then you

42:21

just wait for daybreak, baby. And then

42:23

you, I like the idea, it just

42:25

spirals in, it has to spiral in,

42:27

it's just a spiral. The only way

42:29

you can go is back out, which

42:31

you've blocked off, it can't, it has

42:33

to spiral in. It doesn't know what's

42:35

going on. It doesn't know what's going

42:38

on. It doesn't know what's going on.

42:40

It doesn't know what's going on. It

42:42

doesn't know what's going on. It's a

42:44

spiraling, it's has to spiral in. It

42:46

doesn't know what's has to spiraling, it

42:48

doesn't know what's has to spiral in.

42:50

It doesn't know what's has to spiraling,

42:53

it doesn't know what's has to spiraling.

42:55

It doesn't know what's has to spiraling.

42:57

It doesn't know what's has to spiraling.

42:59

It doesn't know what's has to spiraling,

43:01

it. It doesn't know what's has to

43:03

spiraling, it. It doesn't know that you

43:05

only have to like deal with that

43:08

small area. Yeah. Good old vampires. So

43:10

very, very easy monster to stop turns

43:12

out. Still saying, I still asked if

43:14

I can enter people's houses and people

43:16

still let me in those. That's always

43:18

fun. I can't believe I did. Listeners,

43:20

I knew Gregwa did this. And we

43:22

moved into our new house and I

43:25

was like, this is it baby. And

43:27

I had a house warming party and

43:29

I knew he was gonna do it.

43:31

And he turns up and I'm like,

43:33

hey, come on in. God damn it!

43:37

Many people don't tell everyone of course, only

43:39

people listen to the podcast, but yeah, it's

43:41

in Perth, a friend of mine has just

43:44

moved into a new house and I walked

43:46

up to the door and she walked inside

43:48

and I stood there for a moment and

43:50

looked down and went, can I come in?

43:52

Yeah, of course he can. Step. Like a

43:54

very, very definite step into the house. Always

43:56

loved doing it. It's just a fun thing

43:59

to do. Because there's not a thing to

44:01

worry about. Like why would you... not a

44:03

thing. So if it's not a thing, it'd

44:05

be really easy in the modern day and

44:07

age if there was a creature that needed

44:09

that. You wouldn't think about it. You would

44:11

just go, Cussey can. Cussey can. I still

44:13

want to write a vampire story about vampire

44:16

hunters that work in pairs and crash mobile

44:18

homes into each other with the vampire in

44:20

between. Just paste. They can just never get

44:22

out of that. Yeah. That's very good. I

44:24

love it. There is a

44:26

fun story about the idea of vampires in

44:28

Australia and trying to, like the concept of

44:31

running water and as you talk about the

44:33

artesian basin, because that's underground, that's flowing, it

44:35

slowly flows to the south. And I like

44:37

that, in my mind, like it takes millions

44:40

of years to speculate, and then flow, it's

44:42

not like a fast running thing. But I

44:44

like the idea that there might be parts

44:46

of Australia and the other parts of the

44:49

world where they just feel uneasy, where they're

44:51

like, like, It'd be like having a high-pitched

44:53

wine and you hear the whole thing like,

44:55

oh I don't, no, no, no, we're not

44:58

going to stay here. We'll cross this and

45:00

get the hell out of here, that'll be

45:02

great, thanks. And you go, oh, there's running

45:04

water around. Oh, it's a big, oh, yuck,

45:07

yuck, yuck, yuck, yuck. No, thank you. No,

45:09

thank you. Oh, yuck, thank you. No, thank

45:11

you. No, yuck, thank you. No, thank you,

45:13

thank you, thank you, thank you, thank you.

45:16

No, thank you, thank you, thank you, no,

45:18

thank you, thank you, thank you, no, thank

45:20

you, no, thank you, no, no, thank you,

45:22

no, thank you, no, thank you, thank you,

45:25

no, no, no, no, thank you, thank you,

45:27

thank you, thank you, thank you, thank you,

45:29

thank you, no, What are they going to

45:31

feed on? Other people? There's not much out

45:34

here. No large predators. There's livestock, but you'll

45:36

notice that. Like there's one hanging around. Roos?

45:38

Yeah, roos. They can move pretty quickly though.

45:40

Soaken vampires. Get across the bird pretty quick

45:43

smart. But the we're roos, Dan. What about

45:45

the we're roos? Jump up and kick a

45:47

vampire into the sun. As

45:51

you know Dan I'm quite fascinated by

45:53

the promise and the terrors of AI.

45:55

There's a lot of hype. There's a

45:58

lot of hype. always tried to dig

46:00

through what's the real stuff that's going

46:02

on compared to the hype. And I

46:05

found this one a little study I

46:07

found very interesting. So I was talking

46:09

about 50 doctors and they're testing their

46:11

diagnostic abilities. So some of the doctors

46:14

were given data. So they were given

46:16

lots of data as a patient. So

46:18

this is just literal data of patients.

46:21

Okay. Yep. So here's some data about

46:23

all these patients. I want you to

46:25

diagnose what's wrong with these patients. So

46:28

some of the doctors were given just

46:30

the data. Some doctors were given access

46:32

to chat-GPT and chat-GPT was just given

46:35

access to the data. The data. Okay,

46:37

so some got the data and some

46:39

filtered it through the AI. Well, yeah,

46:42

some doctors, some doctors, some doctors were

46:44

just, some large, in this case, we're

46:46

just a large language model AI, something.

46:49

Not one that was set up in

46:51

anywhere specifically, it was just a general

46:53

frontier model. So you had doctors with

46:56

data, you had doctors with access to

46:58

AI and the data, and then the

47:00

AI was given access to the data

47:03

and left to their own devices, go,

47:05

go, go. What do you think happened

47:07

from this? What do you think? So

47:10

the goal was to make diagnoses? Yes,

47:12

yes, of patient, real patient's data. Okay,

47:14

I think that the doctors went through

47:16

the data and made decisions based on

47:19

their training and that they got lots

47:21

of something's wrong, but mostly things right.

47:23

And I think the AI didn't get

47:26

as many things right. And when it

47:28

made mistakes, they were like crazy mistakes.

47:30

Fair enough. Yep. Yep. That's fair enough.

47:33

I think it's a reasonable reasonable assumption.

47:35

We've avoided talking about large language metals

47:37

a fair bit. Did this? Yes. No,

47:40

you know that you're like a bit

47:42

pro and I'm a bit anti. That's

47:44

why I said at the start. I

47:47

just wanted to come and say that.

47:49

I guess I didn't say what you.

47:51

So yeah, sure, you have, I guess

47:54

out of between the two of us,

47:56

I would say I'm the two of

47:58

two. just want to set up the

48:01

characters in some sort of action in

48:03

case things get off the rails. No,

48:05

that's right. When we start threatening Sam

48:08

Altman with assassination with a bug or

48:10

something, yeah, sure. Ah, look, you know,

48:12

sometimes these things happen. Oh God. All

48:14

right. First thing, first thing, first, the

48:17

difference between the doctors by themselves and

48:19

the doctors with chatch EPT, how long

48:21

it took them to go through the

48:24

data and diagnose was about the same.

48:26

So it was about 10 minutes, roughly.

48:28

Really? Yeah, to diagnose. So the doctors,

48:31

it was very, very, there's like a

48:33

difference of a minute in the favor

48:35

of using with chatch EPT. So I'm

48:38

just, I'm talking about the doctors with

48:40

chatch EPT and the doctors by themselves.

48:42

Oh, I see. So they're actually asking

48:45

the questions and stuff and... Yeah, so

48:47

that's right. So going through, so, well,

48:49

looking at the data, going through all

48:52

the data and then making a diagnosis

48:54

for about 10 minutes. About 10 minutes.

48:56

I may have screwed up here. So

48:59

it's not the, you're not just taking

49:01

the first, you're not feeding the data

49:03

and taking the first answer that AI

49:06

comes in. There's a doctor looking at

49:08

that answer. Okay. Hang on, wait, wait,

49:10

yes, so just absolutely clear. We've got,

49:13

the experiment is, we have lots of

49:15

patients' data, that's all tabulated with all

49:17

the test results, nothing like that, ready

49:19

to go, so lovely data. That data

49:22

is given to doctors by themselves, so

49:24

doctors go, I'm a doctor, thanks, and

49:26

they go through and they diagnose each

49:29

patient and they make a decision, blah,

49:31

blah, blah. that information is also given

49:33

to doctors who have access to chat.

49:36

Right. So they can make, they can

49:38

go, I think this, and they can

49:40

check on chat TV and use chat

49:43

TV. So the chat TVT could be

49:45

used to go through data faster and

49:47

make a faster one. But it also

49:50

might throw out weird results that may

49:52

or may not be beneficial for the

49:54

doctor. Because he might be like, no,

49:57

that's obviously not right, but he might

49:59

be like. Oh, I hadn't considered that.

50:01

Exactly. That's a very good point. Now

50:04

the third one, the third group here

50:06

is just chat-GPT. The information is uploaded

50:08

into chat-GPT all by itself. looking at

50:11

it. Gotcha. Just like, they're the three,

50:13

they're the three groups. So, doctors by

50:15

themselves took about 10 minutes, her diagnoses,

50:18

looking through all the data. Doctors with

50:20

chat cheapity took about nine minutes to

50:22

do the same thing. It didn't really,

50:24

wasn't that much an increase, but all

50:27

time is useful. Chat cheapity did it

50:29

almost instantly. That's what it does, right?

50:31

Cool. That's just time though. So, let's

50:34

have a look at. accuracy. So regular

50:36

doctors, doctors by themselves, were correct about

50:38

74% of the time with their diagnoses.

50:41

Gosh, that's so low. Yeah, it's still

50:43

pretty low. Doctors with chat GPT, 76%.

50:45

So only slightly better. I'm going to

50:48

even say within error. Honestly, within error.

50:50

That feels not significant to me. I

50:52

wonder what the level of like. Because

50:55

all these patients had different outcomes, results.

50:57

I'm assuming it's different different different different

50:59

diseases, different illnesses, different issues, and the

51:02

doctor, it's their area of expertise or

51:04

at least they shouldn't be able to

51:06

handle it. It wasn't like a trick.

51:08

Because if I go to a doctor

51:10

and I say, I got a sore

51:12

shoulder, they're like, look, there's a 80%

51:14

chance it's going to be this. So

51:16

do this. Yeah. But they might be

51:18

like, well, there's a 1% chance for

51:20

this, but I'm not going to tell

51:22

them that because there's only a 1%

51:24

chance. So I wonder if you got

51:26

all the things that they were being

51:29

checked for, whether 74% actually matches the

51:31

doctors, what the doctor is most likely

51:33

going to say. Let's put a pin

51:35

in that because I think that's a

51:37

really good point, but I want to,

51:39

I think that's something for the end.

51:41

I'll explain why later on, but I

51:43

think that's a, you made a very

51:45

good point there. Like, because doctors are

51:47

never going to be 100% right, because

51:49

there's so many things that thing could

51:51

be based on the results. Yes, and

51:53

there is that too. I think that

51:55

two very good points. Let's go back

51:58

to that. We'll get back to that.

52:00

with ChatGPT or LMAI,

52:03

76%. Here's the thing

52:06

that honestly shocked me.

52:08

ChatGPT by itself, using

52:11

the data alone, 92%

52:13

accuracy. What? 92%

52:16

accuracy. That is unexpected. Even for me,

52:18

and I'm pro, not crazy pro, but

52:20

I am pro, even I went, bullshit.

52:22

I said, no. Because in my mind,

52:24

here's what I honestly thought when I

52:26

read this before, I was going to

52:28

be, Chatchibitee will crash and burn, regular

52:30

doctors will do okay. Doctors with Chatibity

52:32

will do the best and buy a

52:35

lot. And what I was basing that

52:37

basing that on was looking at people

52:39

who do chess now, and they do

52:41

like the guy, oh, I forget his

52:43

forget his name, I forget his name.

52:45

I forget his name. Deep Blue, that

52:47

guy. It will be some sort of

52:49

Russian name, right? Yeah. And your Taylor

52:51

Joy, is that? Gary Kasparov, yeah, thank

52:53

you. I should have known that, Gary

52:55

Kasparov. So the chess world, where you

52:57

had deep blue defeat Gary Kasparov, sorry,

52:59

human, and then he went and practiced

53:01

and got better and came back and

53:03

sort of won OK, but then deeper

53:05

blue came out and then he just

53:07

realized he could never win chess. So

53:09

he went underground for a long time,

53:12

was very sad, but then came back

53:14

saying, actually, let's use these things together.

53:16

And so he created a computer slash

53:18

human chess league, where the computer program

53:20

and the human always defeat the human

53:22

or the computer program. you can add

53:24

the two strengths and I thought to

53:26

be the same doctors in chat cheapity

53:28

would win by far a chat cheap

53:30

tea would suck us and doctors would

53:32

be somewhere in the middle totally wrong

53:34

totally wrong chat cheap tea wins by

53:36

a lot this is odd and it's

53:38

interesting and useful and and I'm glad

53:40

the study didn't go so all doctors

53:42

should be fired and we're still having

53:44

to chat cheapity because that's odd I

53:47

wonder what the other 8%, like in

53:49

my mind the other 8% is like,

53:51

you should inject bleach. That'll get rid

53:53

of it. Yes, you've got a bad

53:55

case of griffins or something. Yeah. Leaches,

53:57

nothing but leaches. let's break down what

53:59

the study says about this. And the

54:01

listeners, I'm interested, like, are you shocked

54:03

by this? Because yeah, I was. To

54:05

start off with, you made a good

54:07

point before. It's one thing to be

54:09

handed a dossier of perfectly aligned data

54:11

that says their blood pressure was this,

54:13

and their tests were this, and there's

54:15

ECG for this, and bone density was

54:17

checked, and blah, blah, blah, blah, body

54:19

mass index, or whatever tests, all the

54:22

exciting tests they needed to do. That's

54:24

not how humans turn up at doctors.

54:26

So turn us to, they go, I've

54:28

got this lump or I'm a bit

54:30

tired and the doctor, human being has

54:32

to go, it's 80% that they're lazy

54:34

and need to move a bit more

54:36

or they need to cut out the

54:38

sweeties. It's like 1% this shocking cancer

54:40

that's going to kill the day. Well,

54:42

I went to the doctor the other

54:44

day and they said the pain that

54:46

I'm getting in a part of my

54:48

body and they're like, well, there's a

54:50

thing that it's almost definitely not. But

54:52

I'm going to get you to stand

54:54

up and walk around on your tip

54:57

toes and then the ball's your feet.

54:59

Yeah, you can do that fine? There's

55:01

not that. And it's like, that's a

55:03

clever little diagnostic thing that she had

55:05

to remember was worthwhile doing. And that's

55:07

something they can't, machines, and I'm not

55:09

turning us into a things machines can

55:11

do because one day they probably can.

55:13

There is something about the messiness of

55:15

it. And also the study wasn't saying,

55:17

let's get rid of doctors. That's not

55:19

what I was talking about. The other

55:21

thing they pointed, so basically gathering the

55:23

data and knowing the right data to

55:25

gather, so we can do all the

55:27

tests in the world, but we don't

55:29

have the time or the money to

55:32

do that. There has to be decisions

55:34

based on what tests need to be

55:36

done, who needs to do them. there

55:38

isn't end of those resources and end

55:40

of time to do things. But there

55:42

are pretty fast tests you can do.

55:44

You could get a professional to do

55:46

a bunch of little tests, do a

55:48

blood test, full spec, get all those

55:50

numbers. I guess one thing that the

55:52

large language model is good with good

55:54

at doing is like looking at all

55:56

the numbers and the interaction between them

55:58

and just not knowing what they do,

56:00

but matching them to other people with

56:02

a. similar numbers. So that's why I

56:04

can do it very quickly. I think

56:07

you hit it up right. And which

56:09

is why a doctor is not going

56:11

to be thinking about the interaction of

56:13

all these numbers. Like they can't hold

56:15

all that mathematical data in their head.

56:17

Not that the AI is holding mathematical

56:19

data, but it's. It's a pattern matching

56:21

thing. It's made connections, a lot of

56:23

connections based on data. It's ingested. Humans

56:25

are great at pattern matching, but not

56:27

when it comes to things like numbers.

56:29

Also, we don't have the memory width.

56:31

You want to think of that way

56:33

that AI has. You can dump a

56:35

lot. It can hold a lot of

56:37

inverted commerce concepts in its inverted commerce

56:39

head. for a long time. I'm very

56:42

careful as anthropomorphize it, but just our

56:44

language is limited. So it can think

56:46

about invertecomers think about many different things

56:48

at once that we cannot do. We're

56:50

not, it doesn't pass language nor data

56:52

in the same way that we do.

56:54

It's not us in a machine. It's

56:56

just not. It works in a very

56:58

different way. So that gives us strengths

57:00

and weaknesses. What I'm amazed at. is

57:02

that the doctors who looked at the

57:04

chat GPT would have seen the right

57:06

answer and then gone no I trust

57:08

my intuition more yes yes they would

57:10

have looked at it and gone no

57:12

that thing that will turn out to

57:14

be right is not right yes and

57:17

that's very cute I'm glad you came

57:19

to that. I wasn't going to bring

57:21

it up, but I was, yes, I

57:23

had that exact same thought. And I

57:25

was like, hang on, it would have

57:27

spat out a very similar answer, the

57:29

correct answer, and it would have been

57:31

overridden by a person. Like that doctor

57:33

would have gone. Now I'm looking at

57:35

the data and in 75% of chances,

57:37

it's going to be this thing. Yeah.

57:39

But the pattern of like these three

57:41

numbers or something. Yes, the new ones

57:43

was enough to go, the chat sheet

57:45

or the LM went, it's this, most

57:47

time it's going to be this, but

57:49

these numbers here make me think it's

57:52

that. And then, and the doctor was

57:54

like, there's no way it's that without

57:56

questioning it. Now, let's go back a

57:58

bit because. questions that were brought up

58:00

about the study, no training was provided

58:02

on using the AI. So you just

58:04

handed a very general powerful tool to

58:06

doctors and went, have fun. Some of

58:08

those doctors would be like me and

58:10

be like, oh cool, let's play with

58:12

the stuff. And some doctors, no offense,

58:14

would be like you and who is

58:16

not. all that for it and it

58:18

probably hasn't had the same experience of

58:20

me using it you wouldn't just have

58:22

the skills in using that technology as

58:24

much as I would I would assume

58:27

maybe you do and sorry if I'm

58:29

making assumptions there but it's it's just

58:31

a level of how much you've used

58:33

it. Oh no I'm fucking throwing wrenches

58:35

into looms baby. Give a live on

58:37

a ridge, vampire friends. So you can't

58:39

expect someone to use a high powerful

58:41

machine. We're like handing me a machine

58:43

gun and going, defend the Western Front.

58:45

You go, I'm sure I could fire

58:47

it down range a lot. But when

58:49

it jammed, what am I going to

58:51

do with it? Like how can I

58:53

reload it? What can I, how do

58:55

I keep it clean? It's a precision

58:57

instrument. So there's that. Finally, go back

58:59

to what we're saying before, it's still

59:02

about collecting the data and using the

59:04

data, but I think it's going to

59:06

be an assistant that you can use

59:08

to question and you're going to have

59:10

to be good enough in whatever your

59:12

field is, whether it's doctoring or education

59:14

or web design or whatever it is,

59:16

that you have to know enough to

59:18

tell the machine to get nicked to

59:20

get nicked. Or you have to know

59:22

enough about it to know when you

59:24

tell yourself to get micked. Because you

59:26

go, wait, I know enough now to

59:28

think I might be wrong here. So

59:30

you have to have enough humility to

59:32

know when you're wrong, but enough knowledge

59:34

and experience to know when you're right.

59:36

That's a real hard line to walk.

59:39

Doctors generally are known for their humility,

59:41

aren't they? I wasn't going to say

59:43

that. Yeah, thank you for bringing it

59:45

up. Because it's one of the last

59:47

professions in the world. They're like, we

59:49

are gods. Hard working and underappreciated. Well,

59:51

I don't know, underappreciated, but yes, very

59:53

hard working. Certainly in the last 30

59:55

seconds, they've been pretty underappreciated. Yes, I'm

59:57

not saying you're at doctors. I'm just

59:59

saying. are going to be tasks in

1:00:01

all our jobs, AI is going to

1:00:03

be useful to help us with, and

1:00:05

we're going to have to, we will

1:00:07

be integrating these things into us to

1:00:09

make us more efficient. We're going to

1:00:11

have to be trained properly using it

1:00:14

to integrate it, and it's going to

1:00:16

be trained properly so that it's useful

1:00:18

to us. Here, Endith. Oh man, you

1:00:20

have no idea, Dan. How hard I

1:00:22

went writing this in a way that

1:00:24

wouldn't drive you insane? Yeah, I appreciate

1:00:26

it. I think I

1:00:28

vaguely succeeded. I'm pretty agitated, but

1:00:30

that's a pretty good line, I

1:00:32

guess. I'm just worried that you're

1:00:35

going to send some sort of

1:00:37

assassin bug after me. Welcome to

1:00:39

the walk of shame, where Greg

1:00:41

and I make mistakes and you

1:00:43

the listener point out what those

1:00:46

mistakes are and how we can

1:00:48

do better. I messed up by

1:00:50

referring to baby butterflies. Of course,

1:00:52

there are no baby butterflies. Socrates

1:00:54

explained that butterflies spontaneously appear. From

1:00:56

cocoon. Every time you're near? No,

1:00:59

I'm sorry. Of course, a baby

1:01:01

butterfly is in a butterfly. It's

1:01:03

larval form. It's a caterpillar. But

1:01:05

Jesse mentioned that in the same

1:01:07

context, you discussed baby group not

1:01:10

retaining the memories and experience of

1:01:12

legacy group. If we're using butterflies

1:01:14

as a yardstick, Jesse suggests this

1:01:16

isn't as cut and dried. In

1:01:18

2008, scientists ran a test where

1:01:21

they trained caterpillars to avoid a

1:01:23

certain scent, else they get an

1:01:25

electric shock. The resulting butterflies. Science

1:01:27

is great. Isn't it wonderful? The

1:01:29

resulting butterflies also avoided the smell

1:01:32

that caused pain indicating that despite

1:01:34

the caterpillar creating a cocoon and

1:01:36

becoming a soup, or as I

1:01:38

like to call it, a butterpillar,

1:01:40

that that organism still held its

1:01:43

memories through the soup segment of

1:01:45

the process and onwards to its

1:01:47

majestic winged insect phase. I'm happy

1:01:49

with that makes perfect sense. I'm

1:01:51

happy with that. There is, I

1:01:53

think, did we talk about the

1:01:56

last podcast or was it something

1:01:58

research since, it doesn't turn into

1:02:00

a soup. That's very, we have

1:02:02

to be very careful about that.

1:02:04

When you look at it, there

1:02:07

is actually, when you look at

1:02:09

a larval butterfly caterpillar, there are

1:02:11

structures in its cell membranes which

1:02:13

are the pattern for the wings

1:02:15

and for its adult phase, already

1:02:18

built into the caterpillar phase. So

1:02:20

there are cells, it's almost like

1:02:22

a blueprint for what it's going

1:02:24

to be already immeshed into the

1:02:26

flesh of it. So it's not

1:02:29

just it turns into a soup

1:02:31

and rebuilds entirely, there's already some

1:02:33

sort of structure slash blueprint slash

1:02:35

super structure that it can build

1:02:37

itself off. So that implies to

1:02:40

me there could be some sort

1:02:42

of memory holding. Yeah. Yeah, that's

1:02:44

so cool. I don't know, but

1:02:46

it could be. So Jesse signs

1:02:48

off this email as your obedient

1:02:50

servant, Jesse. And I've never had

1:02:53

an obedient servant before, Greg. I've

1:02:55

had a disobedient one. But this

1:02:57

means we can tell Jesse to

1:02:59

do whatever we want. Because Jesse,

1:03:01

I've got a problem with some

1:03:04

mirrored bugs, if you know what

1:03:06

I mean. Oh dear. Yes, things

1:03:08

are so baby group, I guess,

1:03:10

would have memories. I think baby

1:03:12

group would have memories of the

1:03:15

old one or parts of it.

1:03:17

It's almost like genetics, isn't it?

1:03:19

Almost like a genetics, like a

1:03:21

sideways. Epid genetic transfer, which isn't

1:03:23

always, you know, from one creature

1:03:26

to another. Oh Dan, Dan, Dan,

1:03:28

Dan, you have literally waken the

1:03:30

dragon, grand dragon, Dan. When we...

1:03:32

When we... Still not on board

1:03:34

with that name. When

1:03:36

we started talking about dragons, this is

1:03:39

the first time we had a walk

1:03:41

of shame, now this walk of shame,

1:03:43

from an old walk of shame that

1:03:45

has drawn me as much into it

1:03:47

and IMAs now implicated in your crimes

1:03:50

as you were. Because if what people

1:03:52

hate about people making mistakes on something

1:03:54

called walk of shame, is when the

1:03:56

other person who is being asked to

1:03:59

call them out. a quizzling

1:04:01

traitor and sides with their co-host against

1:04:03

the listeners. This caused a lot of

1:04:05

alarm? Numerous emails to be sent to

1:04:07

me why I was incorrect and how

1:04:10

one person wrote and said, I won't

1:04:12

say who they are. I love that

1:04:14

I don't get. I got all of

1:04:16

this! I got one person who got

1:04:19

so upset, and when I wrote back

1:04:21

in a conciliatory but kind of jokey

1:04:23

way, got sent back up, I'm too

1:04:25

upset to handle the comedy right now,

1:04:28

so they were pissed. Sounds like your

1:04:30

comedy's not very good. No, well, that

1:04:32

could be true. So I was like,

1:04:34

oh, no. So, all right, so for

1:04:36

the listeners who don't know what we're

1:04:39

talking about. There was a comment made

1:04:41

about how they're interesting as dragons, and

1:04:43

then someone wrote in saying, well, actually,

1:04:45

not dragons. Look, you know, what about

1:04:48

Camoto dragons? What about these sort of?

1:04:50

And Dan was like, you can call

1:04:52

whatever you like, but it's not a

1:04:54

dragon. That's just a name. And we

1:04:56

had a big discussion about it. We

1:04:59

went check Wikipedia, the best sort of

1:05:01

knowledge in the best sort of knowledge

1:05:03

in the universe. and came out that

1:05:05

Camoto dragons are actually called something else.

1:05:08

So that is just a generic name

1:05:10

for this animal that we call a

1:05:12

Camoto dragon. And so I- Well, no,

1:05:14

it's a specific name. We call a

1:05:16

monitor. I don't think it's a monitor.

1:05:19

Yeah, monitor lizards. Yeah, that's right. Yes.

1:05:21

So we sort of went, oh, OK,

1:05:23

damn it. And I, so I capitulated

1:05:25

and went, sure, I said, really, this

1:05:28

social thing is dragons, I'm going to

1:05:30

let you have to let you have

1:05:32

this. Big mistake for a big mistake

1:05:34

for Greg, but cause multiple people. Colin

1:05:36

being one of them, but other people,

1:05:39

two other people riding and going, it's

1:05:41

different levels of anger and... So Colin

1:05:43

was the nicest. Actually, there are dragons,

1:05:45

and it was pointed towards a type

1:05:48

of lizard. actually called a dracco, a

1:05:50

genus of agamid lizards. They are known

1:05:52

as flying lizards, flying dragons or gliding

1:05:54

lizards. These lizards are capable of gliding

1:05:56

flights. So they're kind of gliding ones,

1:05:59

but they're called dracco. after after

1:06:01

the animal animal, the

1:06:03

Have a Have a look up

1:06:05

of lizard and AGAMID -G -A -M -I -D

1:06:07

a genus, it's a genus, a it's a

1:06:09

it's a sorry, of lizards. So there and

1:06:11

that is dragons. So they

1:06:13

are dragons, they are

1:06:16

called dragons and they are the they

1:06:18

are the lizards. lizards. All right, no, that looks like

1:06:20

looks like I've a to take a

1:06:22

walk Okay, now, so thank you Dan, I appreciate you,

1:06:24

Dan. I appreciate that. And you heard

1:06:26

you heard that. Please stop sending

1:06:28

me me angry. Please, please. I've learned my lesson, I've

1:06:30

I'm lesson. I'm sorry. I'm sorry.

1:06:32

All right. dragons, the world is a is a

1:06:34

beautiful place. I do believe they man on

1:06:36

the moon. on the think I've seen

1:06:38

one of these. one of these. I've

1:06:40

seen on on TV. I went to I went to

1:06:42

I was seeing all these I was seeing all

1:06:44

these little birds to tree and then tree, and then

1:06:46

I'm like, a bird. not a bird. a little lizard

1:06:49

there's a little lizard tree the tree and

1:06:51

flying to another tree. It's amazing! Gliding,

1:06:53

gliding, gliding! Gliding. Yeah, gliding. Careful. Little

1:06:55

dragon. Yes, a little dragon. There

1:06:57

you get little dragon, dragon. When you become a full

1:06:59

When you become a can have these you

1:07:02

can have these sort of put on

1:07:04

your person. Many species

1:07:06

dragons or dragon lizards. lizards.

1:07:08

at that. Look at that. All

1:07:10

right, all right, I can't. In fact,

1:07:12

I In fact, accept

1:07:14

that. That's really that, very

1:07:16

cool. cool. listeners. And

1:07:19

I do you listeners. And I In appreciate aside, I

1:07:21

jokes aside. I love the fact that

1:07:23

people get passionate about this stuff and I

1:07:25

don't mind you sending it to me. I

1:07:27

totally fine. you I love the fact that

1:07:29

you were so upset with me for

1:07:31

not digging deeper into it. Fair enough. were

1:07:33

Fair enough. Keep me honest. me That's kind

1:07:35

of your job, isn't it? into tell you,

1:07:37

this is your walk of shame. Keep me your job,

1:07:39

isn't it? not You had to take the walk, to take

1:07:41

the walk. But I'm the one weird. it's

1:07:44

weird. It's funny how it works works there, but yeah,

1:07:46

That's fine. fine. All right. Steve All one

1:07:48

of our Stewart, one of our favorite

1:07:50

you out for mentioning out coffee

1:07:52

beans to a cat. beans to

1:07:54

a cat. There a delicacy

1:07:56

called called Civit Coffee, or Copi

1:07:58

Luwack. The coffee cherry. fermented in

1:08:00

the Asian palm civet's digestive system,

1:08:03

which it then poops out. This

1:08:05

makes the bean better in taste

1:08:07

by two mechanisms. One is that

1:08:09

there is a chemical process occurring

1:08:12

within the civet. The second is

1:08:14

that the civet is being selective

1:08:16

with the cherries, so you're more

1:08:18

likely to get good beans and

1:08:21

avoid mixing in rubbish ones. They

1:08:23

are pre-tasted. The frog princess has

1:08:25

actually tried this. She said, and

1:08:27

I quote, it tastes like coffee.

1:08:31

Also, it turns out that there

1:08:33

are some animal welfare issues from

1:08:35

the farmed ones. Turns out that

1:08:37

when humans are struggling with their

1:08:39

quality of life, that they don't

1:08:41

have many resources to turn towards

1:08:44

farmed animals' quality of life. Sure.

1:08:46

So if you want really good

1:08:48

civet coffee, get the wild stuff

1:08:50

and the farm stuff, maybe not

1:08:52

as good. Maybe don't farm cats

1:08:54

or civet cats. That's fair enough.

1:08:56

The mistake that you made, Greg,

1:08:58

I thought to say, where's the

1:09:01

mistake of it? Is that what

1:09:03

is affectionally referred to as the

1:09:05

civet cat is not a cat.

1:09:07

Oh! You've got your phileformia, which

1:09:09

is cat-like creatures, which branches off

1:09:11

in two directions. One leads to

1:09:13

cats and lions and lynxes and

1:09:16

lynxes and lynxes and lynxes and

1:09:18

lynxes. The other becomes hyenas, meerkats,

1:09:20

mongooses, or monges, monges, monges, mongenoids,

1:09:22

and also Asian civits. Oh, so

1:09:24

it's more like a hyena. Oh,

1:09:26

okay. Oh, and a mongo. So

1:09:28

that's a, they're very different, wow,

1:09:30

okay, interesting, interesting stuff. Oh, there

1:09:33

you go. So it's not a

1:09:35

cat at all. I stand corrected.

1:09:37

So cat, coffee is not a

1:09:39

cat. Coffee is not a cat.

1:09:41

It is a cat. It is

1:09:43

not a cat like. But it's

1:09:45

interesting that the entire bunch of

1:09:48

creatures are described as cat-like creatures.

1:09:50

It's like. One of those, one

1:09:52

of those many branches became something

1:09:54

we call a cat and you

1:09:56

guys just all under that. Oh

1:09:58

you look like them. and

1:10:01

hyenas are very different animals.

1:10:03

Not genetically. Yeah, well, yeah,

1:10:05

but they're different families of

1:10:07

things. Like, you know what

1:10:10

I mean? Like, they're sort

1:10:12

of like... They're right next

1:10:14

to each other. Oh, wow.

1:10:16

Okay, there you have it.

1:10:18

Yeah. Genetics, man. It's messed

1:10:21

up. Geological time is crazy

1:10:23

powerful. Very true. You

1:10:25

have been listening to Dan

1:10:28

at smartnuff.org. And also Greg

1:10:30

at smartnuff.org. If you would

1:10:32

like to support the podcast,

1:10:34

there are many ways to

1:10:37

do so. One of them

1:10:39

is our patron, so a

1:10:41

big thank you to our

1:10:43

level two patrons, Mariana Scott.

1:10:45

Andrew Potts, Steve Stewart, Matt

1:10:48

Ewers, Brita Rogofsky, Andrew Whitehurst,

1:10:50

Gronia McGuire, Amy Greenberry, Matthew

1:10:52

Toy, Andrew Trausau, Lindsay Jenkinson,

1:10:54

Ilana Mitchell, Ivan and Catherine

1:10:56

Cook. Thank you also much

1:10:59

for supporting the podcast. There

1:11:01

is also our Tier 3

1:11:03

members and they get insulted

1:11:05

for their enormous contribution to

1:11:07

the podcast. I was recently

1:11:10

in Vietnam. where at one

1:11:12

point in history the locals

1:11:14

used a trove of monstrously

1:11:16

inhumane traps against the invaders

1:11:19

who committed war crimes in

1:11:21

pursuit of cheap magnesium. While

1:11:23

there, I needed a converter

1:11:25

for my electrical plugs, so

1:11:27

these insults are inspired by

1:11:30

the electrical systems. Tom Siri!

1:11:32

My interactions with you involve

1:11:34

too much frequency. Scott

1:11:39

Driscoll, you can socket. Rick

1:11:41

LaPoitven, you're just like a

1:11:43

Tucker telephone. I don't understand

1:11:45

it. Oh, a Tucker telephone

1:11:47

is you get an American

1:11:49

army field telephone and you

1:11:51

convert it so that the

1:11:53

electrical charge in the phone

1:11:55

instead runs through the toes

1:11:57

of your prison. war. Oh

1:11:59

my goodness. Oh right. Torture

1:12:01

Rick, just flat out torture

1:12:04

and you should be punished

1:12:06

but you're so, you're too

1:12:08

powerful to be punished aren't

1:12:10

you? But your day will

1:12:12

come America, Rick LaPoyderven, soon

1:12:14

your elites will have to

1:12:16

pay for your crimes done

1:12:18

in the name of capitalism.

1:12:20

What's going on? blood and

1:12:22

then around the world the

1:12:24

people will rise up the

1:12:26

slaves will rise up the

1:12:29

poor will rise up the

1:12:31

obedient servants will rise up

1:12:33

and cut the the obedience

1:12:35

oh oh we're not doing

1:12:37

this we're not doing this

1:12:39

and a big thank you

1:12:41

to these top-tier members Al

1:12:43

Batson Joey Wesley Eric Wilson

1:12:45

Mortimer and Michael Barnes you

1:12:47

guys are transformative Add

1:12:50

a shout out to former top-tier patron

1:12:52

Steve Ikenhout who is now a special

1:12:55

education teacher. I can't insult him anymore

1:12:57

because I'm just too down proud of

1:12:59

him. Oh, well done Steve. Actually, congratulations.

1:13:01

That's amazing. Well done. It's great. That's

1:13:04

very, very cool. I love it when

1:13:06

people are like, I'm going to be

1:13:08

a valued part of human society. Absolutely.

1:13:10

If you still haven't had enough of

1:13:12

me Dan Peston and... Dan's on the

1:13:15

tear last couple of podcasts. It's the

1:13:17

end of the year. He's all feisty.

1:13:19

Feisty. There is the annual Science Says

1:13:21

game show. Sadly, Greg wasn't able to

1:13:24

be there this year. But I was

1:13:26

on board and so in the show

1:13:28

notes there is a link to the

1:13:30

YouTube video for this year's science game

1:13:32

show. It is plenty of fun. So

1:13:35

if you like, you can jump over

1:13:37

there and listen to me. Oh my

1:13:39

goodness. I haven't seen that. I want

1:13:41

to see that too. I'm going to

1:13:43

go check it straight after this podcast.

1:13:46

Amazing. Fantastic. I just have to hunt

1:13:48

down the yorral again. That's amazing. Thanks

1:13:50

for sharing that. Definitely. and find it.

1:13:52

Amazing. Oh, I guess. Sorry that this

1:13:55

took so long of just down and

1:13:57

I have been so traveling a lot

1:13:59

and all over the place. This is

1:14:01

out much later. Don't worry. You're not

1:14:03

missing out. You're still going to be

1:14:06

getting all the amazing smart off the

1:14:08

better that you expect. It's just going

1:14:10

to just give me a couple of

1:14:12

weeks later than we normally are. But

1:14:15

you have missed out numbers. We've not

1:14:17

missed a podcast. I mean, they know

1:14:19

that this. So this is the November

1:14:21

of the November one. Yes, this is

1:14:23

November. That's right. This is uploaded in

1:14:26

the third week of November. They just

1:14:28

took eight. There's something wrong with your

1:14:30

podcast machine, I think. People probably are

1:14:32

asking this. No one actually has. So

1:14:35

there you go. Whoops. But yes. So

1:14:37

we apologize to that. It's not something

1:14:39

we like to do. We normally, you

1:14:41

know how we like. Just this time,

1:14:43

both Dan and I, we're traveling a

1:14:46

button doing over this time and other

1:14:48

life stuff got in the way. But

1:14:50

we, you haven't. You haven't missed out.

1:14:52

You haven't missed out. You haven't missed

1:14:54

out. You will still get the same

1:14:57

number. You will still get the same

1:14:59

number of stuff. You will still get

1:15:01

the same number of stuff. Yeah, happy

1:15:03

Christmas by the way. Yeah, that's not

1:15:06

going to come out before then. Oh

1:15:08

yeah, good point! If that's your thing,

1:15:10

yeah, whatever, whatever, whatever, whatever, whatever, just,

1:15:12

it's that time of the year and

1:15:14

hopefully, just chill out everyone, just chill

1:15:17

out, I intend to, enjoy some holidays

1:15:19

that are happy. Yes, oh, that's a...

1:15:21

Which is something Christians have been saying

1:15:23

for hundreds of years, happy holidays. Happy,

1:15:26

happy, happy, happy, holidays. Yes, oh look,

1:15:28

I'm off, I'm off, I'm off of

1:15:30

dressing, I'm actually dressing up this for

1:15:32

the first time in a while, in

1:15:34

my new job, I'm dressing up as

1:15:37

Krampus and turning up at the work

1:15:39

Christmas party. Only two people know. The

1:15:41

organizer and my boss, thank God, so

1:15:43

I probably won't get fired and I'm

1:15:46

just going to turn up his crampus.

1:15:48

People don't know me well enough. They'll

1:15:50

go, oh yeah, it's going to be

1:15:52

Greg. Some random Christmas demon, more to

1:15:54

the point, some random guy in a

1:15:57

costume is going to turn up. It's

1:15:59

going to cause alarm. I'm really looking

1:16:01

forward to it. I'll tell you how

1:16:03

it goes next time. Don't you also

1:16:05

have one co-workerker who listens to the

1:16:08

podcast? Yes, but that's my boss and

1:16:10

therefore they already know. No, isn't there

1:16:12

another one who like meets eyes across

1:16:14

the cafeteria occasionally? Yes, oh no, that's,

1:16:17

no, that's, yes, yes, yes, yes, yes,

1:16:19

yes, yes, yes, no, we don't, we

1:16:21

work in the same building for same

1:16:23

organization, not for the same, they won't

1:16:25

be at the same, that Christmas, that,

1:16:28

that Christmas, sorry, sorry, sorry. Yes I

1:16:30

apologize yes but you will see yes

1:16:32

I will tell you all about it

1:16:34

I'll see if I get well that's

1:16:37

why I have to have my boss

1:16:39

edge make sure I don't get punched

1:16:41

or you know people I get crash-tackled

1:16:43

or shot by the police or something

1:16:45

like that I go no no he's

1:16:48

just special he's not dangerous foot deer

1:16:50

monster at my Christmas party I wish

1:16:52

I wish that's in the future I'm

1:16:54

more of a pint-sized pint-sized crampus I'm

1:16:57

still quite aggressive though I make up

1:16:59

for its feistiness. You're the wolverine of

1:17:01

campus. Kind of am. And as we

1:17:03

always like to see, the political views

1:17:05

of Dan Beeston are not necessarily the

1:17:08

political, no, not even not necessarily, are

1:17:10

definitely not the political views of Smartness

1:17:12

No Better. That's not what we always

1:17:14

like to say. That's what we always

1:17:16

have to say. And we legally have

1:17:19

to say, the whole new segment of

1:17:21

the podcast, legally, that basically, don't, we

1:17:23

don't advocate violence on anyone. It's all,

1:17:25

it's done as comedy? Please take that

1:17:28

as comedy. It's comedy, it's comedy. And

1:17:30

sometimes comedy might not be your comedy,

1:17:32

but it's still comedy. You know what

1:17:34

I think is funny? Eating the rich.

1:17:36

Hilarious. Europe

1:17:46

away, so you're off doing exciting

1:17:48

world travel, expanding your horizons in

1:17:51

beautiful Southeast Asia. No matter where

1:17:53

it was, Horizon was the same

1:17:55

size. Oh, okay. It's almost like

1:17:58

we live on a ball. Yeah,

1:18:02

because you did speed that. Let

1:18:04

me rephrase that. You went to

1:18:06

another state and you performed in

1:18:08

a play that I wrote. And

1:18:10

I also wrote, we wrote, we

1:18:12

wrote, we wrote, we both wrote

1:18:14

this play. I wrote it and

1:18:16

you and Natalie helped me write

1:18:19

it. Right, I see. I like

1:18:21

to state that one. Is that

1:18:23

the story we're going with now?

1:18:25

Okay, good, good. Thank you very

1:18:27

much. And look, I really appreciate

1:18:29

you guys' help on that. You

1:18:31

all... It's the little people that

1:18:34

lift me up so high, says

1:18:36

Dan. Sure the little... It's the

1:18:38

little people that I stand on

1:18:40

to get so high. That's right.

1:18:42

I'm the willy wanker of Act

1:18:44

React, and I thank all the

1:18:46

umpa lumpers for drowning those children

1:18:48

for me. Thank you, umpa lumpers,

1:18:51

for taking that fall. Umpa lumpers

1:18:53

have less distance to fall. That's

1:18:55

true. So

1:18:58

the only fretful bit is when they

1:19:00

drop us at an airport and go,

1:19:02

now it's time for your domestic flight.

1:19:04

And you're like, all right, I say,

1:19:06

how do we do this again? Yeah.

1:19:08

I need a person, a little man,

1:19:11

to make me an oompa to take

1:19:13

me to the front. Well, that's the

1:19:15

frog princess. That's my oompa lumpa. When

1:19:17

I was a kid, I saw some

1:19:19

ad for someone diving off a boat

1:19:21

in deep water and swimming around in

1:19:23

deep water. And I was like, that

1:19:25

looks brilliant. I'll do that. My grandfather

1:19:27

took us out on his boat into

1:19:30

the islands of Morton Bay and parked

1:19:32

in deep water and I was like,

1:19:34

fuck that. How many monsters could be

1:19:36

under me right now? Yeah. All of

1:19:38

them. And the thing is, Morton Bay,

1:19:40

fuller monsters. Mm-hmm. Follow monsters. Halomba, they're

1:19:42

like, no, no, there's no monsters here,

1:19:44

or at least they stay deep. Like,

1:19:46

there's a bunch of squids, but they

1:19:48

don't get real big, you know, hot

1:19:51

water, you don't get big sharks, you

1:19:53

get little sharks, because you get all

1:19:55

these little fish. But in cold water,

1:19:57

you get big seals. the sharks are

1:19:59

like, I'm gonna get big enough to

1:20:01

eat that. So yeah, so Helen Bay,

1:20:03

they're like, oh yeah, we jump off

1:20:05

the boat every day. And so I

1:20:07

jumped off the boat in Helen Bay

1:20:10

and floated around for an hour and

1:20:12

I'm like, this is ideal. This is

1:20:14

what holiday should be. Yeah. It was

1:20:16

this funny thing where I haven't gone

1:20:18

swimming in ages. And I'm like, Oh,

1:20:20

swimming's this skill that I just don't

1:20:22

think about. I jump into water that's

1:20:24

16 meters deep and swim around for

1:20:26

an hour. And I'm like, I'm not

1:20:29

even tired. I'm not like, oh no,

1:20:31

what if the very mild current takes

1:20:33

me away from the boat? I will

1:20:35

just swim back to the boat. I

1:20:37

barely thought about it. And then someone

1:20:39

came back from paddling a kayak, some

1:20:41

old man, you know, poorly fitting life

1:20:43

jacket, came back, tried to climb onto

1:20:45

the boat and fell into the water

1:20:48

and fell into the water. and was

1:20:50

like, oh no, how do I get

1:20:52

back to the boat? And I'm like,

1:20:54

oh, well, this guy actually needs to

1:20:56

be rescued, despite the fact he's wearing

1:20:58

a life jacket, because he has no

1:21:00

swimming ability. Oh, yeah. He was strong

1:21:02

enough swimmer to get back to the

1:21:04

boat. And he's like, I guess we'll

1:21:07

find out. I'm like, I might need

1:21:09

an adult here. So the guy sort

1:21:11

of in charge of people safe and

1:21:13

I helped him get back because he

1:21:15

couldn't just get back onto the kayak

1:21:17

and get back onto the boat. He

1:21:19

had to, we had to get him

1:21:21

all the way around this massive boat

1:21:23

to the other boat with the ladder

1:21:26

and it was a whole thing, a

1:21:28

whole divide. And he was just like,

1:21:30

I could float and I'm slowly floating

1:21:32

away from the boat into the open

1:21:34

ocean. I was like, well, let's stop

1:21:36

that first. Yeah, that's not, that's interesting

1:21:38

isn't it? That's seriously what you grew

1:21:40

up with. And he's starting to panic

1:21:42

and so the biggest trick was like,

1:21:45

let's stop this guy from panicking. Yeah,

1:21:47

yeah, yeah. Because it's so weak because

1:21:49

I have no life jacket on and

1:21:51

I'm like, no, no, no, this is

1:21:53

completely safe. And I don't, I don't

1:21:55

think I used science. Can the Queen

1:21:57

Knight herself? the Queen saved someone, well

1:21:59

not anymore, can the King save himself,

1:22:01

or save someone himself and get a

1:22:04

knight himself? I suppose being the king

1:22:06

makes you, being the monarch, makes you

1:22:08

higher than a knight. I mean, shimming

1:22:10

the king of England would be like

1:22:12

the knight of the garter as well

1:22:14

or something weird like that. But maybe

1:22:16

not. Maybe they were and now they're

1:22:18

not. I don't know how it works.

1:22:20

It's all madness. So you'd have the

1:22:23

title that once you're a, you wouldn't

1:22:25

call yourself, sir, once you were, once

1:22:27

you were king. Once you were king.

1:22:29

But could you like give yourself a

1:22:31

little pat on the back if you

1:22:33

like saved someone's life or did some

1:22:35

sort of great thing for humanity? Well

1:22:37

I suppose if you could, I mean

1:22:39

if you went, if you were a

1:22:41

literal king and you went to war

1:22:44

and then you won the Victoria Cross

1:22:46

or whatever for, or got a purple

1:22:48

heart if you were American or something

1:22:50

like that, you wouldn't be a king

1:22:52

then, but you know what I mean,

1:22:54

like if you were the president and

1:22:56

ran into combat and shot someone and

1:22:58

did cool stuff, I don't know, Yeah,

1:23:00

you would show heroism under fire or

1:23:03

whatever it is. Yeah, I mostly just

1:23:05

communicated properly to the people and calmed

1:23:07

him down a little bit. So psychology

1:23:09

maybe, and that's not a real science.

1:23:11

No, no, it's not. There's a whole

1:23:13

lot of made-up stuff. I mean, you're

1:23:15

trying to make changes with words. It's

1:23:17

magic. Let's all agree that. One step

1:23:19

up from economics, which is one step

1:23:22

up from mines. Wait, hang on. Economics,

1:23:24

yeah, that's just sigil's, isn't it? That's

1:23:26

just putting sigil's together until something catches

1:23:28

fire? And telling people, and telling people

1:23:30

what's going to happen, so Suf's saying,

1:23:32

and when it doesn't happen, explaining why

1:23:34

it didn't happen, because you didn't have

1:23:36

this information that you now have, that

1:23:38

you would have definitely have known, what

1:23:41

was going to happen if you had

1:23:43

that post- She'd heard about this thing

1:23:45

called egg coffee when you get the

1:23:47

yoke of an egg and it

1:23:49

in with condensed

1:23:51

milk and it becomes

1:23:53

like a meringue like

1:23:55

a meringue then you

1:23:57

put it on you put

1:24:00

it on coffee and it kind of

1:24:02

it kind of

1:24:04

heats up enough to

1:24:06

it from it from

1:24:08

poisoning you. don't get don't

1:24:10

get or or whatever.

1:24:12

What do you get get from any raw eggs

1:24:14

it's the It's the other one. Salmonella

1:24:16

probably? probably maybe salmonella And so she's

1:24:18

like a bit a bit about this

1:24:20

idea. idea. No pun No pun intended. got it

1:24:22

served to but she got it served

1:24:24

to her at one point and

1:24:26

she tried it. She's like, so

1:24:29

is so much better than it

1:24:31

has any right to be. she kept

1:24:33

so these egg coffees ordering these egg coffees

1:24:35

an like, coffee is an egg coffee

1:24:37

is basically on top of the top

1:24:39

of the ever coffee you could ever taste.

1:24:41

So she kept scooping this lovely thing

1:24:43

off and then tasting the coffee and

1:24:45

going, and going, blah. Have

1:24:47

some Have some drinks and record us

1:24:49

drinks and go, this is a

1:24:51

special Christmas is special is the airing

1:24:53

of the episode. This is the airing of the

1:24:56

me tell you Dan about Let hell.

1:24:58

you, Dan, about let's get back to hell.

1:25:00

Okay, geese over the these once and

1:25:02

for all. the Arctic Circle once in a roll. Welcome

1:25:04

to the to the final episode of

1:25:06

the podcast. That's right. We're already

1:25:09

three sheets to the wind. the And

1:25:11

you know what I think of

1:25:13

our listeners. of our listeners.