0:11

And now to the stunning and exciting

0:13

news which , i believe you'll agree , shows

0:15

once again that at Whipples we

0:17

only take forward steps . This

0:23

is the X109B14

0:26

Modified , transistorized , totally

0:28

Automatic Assembly Machine which eliminates

0:32

61,000 jobs

0:34

, 73

0:37

bulky inefficient machines , 81,000

0:41

needless man

0:43

hours per 11 working days

0:45

and $4

0:48

million in expenditures each year

0:50

for employee hospitalization , employee

0:53

insurance , employee welfare and

0:55

employee profit participation . Within

0:58

six months , our entire production

1:00

facilities will be totally

1:02

automated .

1:04

Well , mr Whipple , try to

1:06

warn us .

1:08

Yeah .

1:10

Yeah , so automation , it's

1:14

not that bad , is it ?

1:16

To me . I mean I get it , but at

1:18

the same time , you know , i'm all about human contact

1:20

and interaction . I mean

1:23

that's the field I'm in , but

1:25

you know . So you

1:27

know the direction of this is just , it's

1:30

great for now , but it's going to take off and it's

1:32

the direction is I don't know For

1:34

right now . You know it's going to

1:36

be very costly to start these , these

1:39

AI , setting them up

1:41

in these restaurants , since

1:43

we're going to be talking about how they're taking over restaurants

1:45

and businesses . Send

1:47

these things up in restaurants . They're going to be

1:49

taking , it's going to be , a lot of money setting

1:51

these things up . You

1:53

know .

1:55

Well , i guess it just depends , it just it just

1:57

really depends on the type of , on

2:00

the type of the company , right

2:02

, and you

2:06

know how big the company is , right as well . We

2:09

started to see a lot of corporations start

2:12

to move towards this

2:14

, actually , and I think it's a to

2:17

me , i think it's a good thing , right . But

2:19

are we fully there yet

2:21

to say , hey , let's go fully automated

2:24

on , say

2:26

, about 50% of the industry , of all

2:28

industries ? not yet , not yet

2:30

. I don't think the infrastructure

2:33

is there . Maybe the technology is there , but not the infrastructure

2:35

as far as in , you

2:37

know , implement it , having

2:40

it mass adopted , mainstream

2:42

, because of the a lot of the technical

2:45

difficulties .

2:46

It's going to be a lot and it's costly to have these

2:48

machines .

2:50

Well , actually , i'm going to break that down for you . And

2:53

it's not as costly as you think .

2:55

So what about the machines , like the arms and all of that and not

2:57

?

2:58

Yeah , yeah , i'm going to get to that , i'm going to get to that

3:00

watch and I'm going to , i'm going to show you

3:02

and we're going to do a little bit of a

3:04

math here also

3:07

. So that's going to be fun , right , so

3:09

? but here

3:11

, here we can go . We look at McDonald's

3:14

is the This

3:17

is , is was one of the first

3:19

restaurants well , one

3:22

of the first mainstream

3:25

restaurants that decided

3:27

that they want to go completely automated

3:29

For one of their

3:31

locations location . Yeah , so the first

3:33

location was actually in Fort Worth

3:36

, texas , right ? So

3:39

there's no in this location . There's no

3:41

humans in there , right , there's

3:43

no seating areas either . This

3:46

is basically like a drive , drive

3:48

through experience only And

3:51

I think it is . It will save

3:53

a lot , a

3:55

lot , a lot , of , a

3:57

lot of money , a lot of time , right

3:59

? So any of you might say

4:01

, hey , i know you're just saying hey , wait a minute , this is going to cost

4:04

a lot more for these .

4:06

Businesses to start , i would think , because

4:09

to put the technology in there , it

4:11

will cost more . And then there's a lot

4:13

of other issues that go along with that

4:15

, like data breach , where people put their card

4:17

in , and all kind of security issues as well .

4:20

So I think the , the

4:22

, i would say , i would say the That

4:28

security part of it is not

4:30

going to be such a big issue because they will use the same

4:32

security systems like banks and what

4:34

they currently use right for their transaction security transactions . I

4:36

don't think it would be that bad , too different . No

4:38

, i don't . I don't think so . I

4:41

don't think it would be that bad because the simple fact that

4:43

we have that infrastructure already in place that

4:45

we don't have Now

4:50

there is , of course , there are some times that

4:53

data breach happens , yeah , but

4:56

it's not a thing that people worry about too much anymore because typically

4:59

the , the company itself would

5:02

be insured and plus also , the

5:04

data breach doesn't automatically just means

5:06

that they would have your entire information . Sometimes

5:09

it could just be your name and

5:11

your email address and

5:14

that would be considered a data breach . Right , but

5:18

not necessarily knowing your credit card numbers

5:20

or anything like that . You know it could just say

5:23

your name and you . You know you

5:25

was at this McDonald's

5:27

right at this time . I think it would

5:29

be fine . But so that just kind of

5:31

break , that's kind of like bring it back and break down the numbers for you a little

5:33

bit here . So

5:36

you're thinking that it may cause

5:38

a lot to run

5:40

one of these pro mom operations

5:42

, but I don't think so right now . So let's just say

5:44

look at it . If we take this , say

5:46

, a minimum approach , right , i

5:49

don't know what the minimum salary

5:52

is like , minimum wage in Texas

5:54

or whatever But let's just

5:56

say on average a person would bring home twenty

5:58

five , fifteen dollars . Fifteen dollars now , okay

6:00

, they

6:03

would bring home about twenty five hundred

6:05

dollars a month , right

6:07

, okay , that's

6:10

just one person to work eight hours

6:12

, right , one person

6:14

to work eight hours . Typically

6:18

, for McDonald's to run , you need about 16 to 19 people to

6:20

run it . You need the cash register . You

6:25

need the person for the bagging , the food , prepping the drinks , serving the foods

6:27

, serving the drinks , taking orders , doing

6:29

the cash transactions , right . Prepare

6:32

the food There's about seven people alone just to prepare

6:34

the food , you know , as far as the

6:37

grill in the patties , frying the chicken

6:39

, doing the fries , you know

6:41

you need three people alone just to brew

6:44

tea , because you need somebody to make it , somebody

6:46

to clean it , somebody to serve it . Right

6:48

, that alone right . And then you need a restaurant

6:51

manager , so he's typically maybe

6:53

bringing home fifty plus , right

6:56

. So in order to

6:58

actually run a machine

7:01

, one

7:05

of the machines , okay , so , one of the machines

7:08

like to do the cooking , let's

7:10

just say just narrow it down , just to say the cooking

7:12

itself , right , we already said that it

7:15

takes about seven people . Seven

7:17

people just to do the cooking itself

7:19

, right , to work the food part , right , just

7:22

to do it . One machine

7:24

will cost the

7:26

company about $3,000 a month for

7:28

maintenance . So

7:30

if you average average

7:33

, right , say , let's just say that we're gonna

7:35

go on the lower end . If you pay us somebody

7:38

$2,500

7:40

, right a month and

7:42

you times that by seven , right , so

7:46

that's $17,000 a month that

7:48

you're paying these people . Now that's just

7:50

only to cover one shift

7:52

. Now

7:54

you would double that Now if you was

7:57

to double that right , and just to say

7:59

the morning shift and the night shift at some time . There's

8:01

even three shifts or whatever . It's three shifts , yeah

8:03

, so $35,000

8:05

a month . And

8:08

then we're not including

8:11

the paid

8:14

leave , insurance and all Insurance

8:16

. We're not including any of

8:18

that .

8:19

Well , maybe on this scale I can see

8:21

where you're going with this . Maybe on the McDonald's

8:24

scale it may be a little cheaper

8:26

to have the machine , the arm and all of this

8:28

and that , but when it starts to get bigger

8:30

it's gonna be more costly .

8:33

bigger as far as like bigger corporations

8:35

, well look look , i

8:37

don't think so , and this is why I say

8:39

this right , you know

8:42

that beautiful restaurant

8:44

Chili's , oh

8:46

God , neighborhood Grill . Right , you know

8:48

what I mean .

8:50

No , it was beautiful , but okay .

8:53

You get your food is like cardboard

8:55

on top of you , mm-mm Yeah

8:57

.

8:57

Yeah .

8:59

Or we'll cook the chicken wing , yes , so

9:01

they are now experimenting

9:04

with this idea as well . It

9:07

takes them very , very , let's

9:09

say , about I think about nine minutes to make a hamburger

9:12

. But they're moving to automated grill

9:14

cooking now , so that if the actual

9:16

grill itself will cook the hamburger both

9:18

sides kind of like , smashes it down like a pancake

9:20

type thing , and then it

9:23

actually will cut the by 30%

9:25

, i believe the cooking time . So if you

9:27

might say , well , you know , 30%

9:29

is not that much of a difference , but look , cut

9:31

this out . If a person was to

9:33

go into Chili's and a actual

9:36

chef were to cook their food

9:38

right , a well done steak

9:40

would take 13

9:43

minutes . Well , well done , right

9:45

, with this robot

9:47

, this automation process

9:49

right , it would just only take four minutes and 15

9:52

seconds . So reason

9:55

being because A lot more people

9:57

could come in and leave out .

9:59

No , i'm saying why the robot ? why

10:02

? I'm just wondering what is Flippi

10:04

doing so different ? Why was this ? This is not Flippi

10:06

. Oh , i'm gonna get the Flippi

10:08

. I'm gonna get the Flippi . It's Flippi's next . I'm just naming

10:10

all of them Flippi . So what is this particular

10:12

robot doing that's making it so

10:15

fast ?

10:16

Well , what it does is like it's kind

10:18

of like a giant think of a giant

10:20

trash compactor , right , and

10:22

it has the top , so it's just pressing

10:25

it down harder , pressing it down . I see what you're saying

10:27

, and the temperature is perfectly regulated

10:29

too . So if you have , i

10:31

guess , if you wanna say you wanna cook four steaks

10:33

on this grill , one is gonna be medium

10:35

, rare , rare and well done , you

10:38

can actually cook all of them At the same

10:40

time Because it's divided into . So it's like

10:42

I would say maybe about it , i would

10:44

say about a 12 by 12 pressure

10:47

, right , and it's like three or four

10:49

different ones , right ?

10:50

So this thing can cook them all at once at different

10:52

temperatures At different temperatures . I see , no , that's the

10:54

difference . I guess it's not just one

10:56

on one , One cook on one steak

10:59

. Okay , well , I see .

11:00

I see what you're going with Perfect tip . So now

11:02

what this does , also for

11:04

the restaurant , is speeds of production , because while

11:07

the presser

11:10

is making the food , the

11:13

employee can actually attend to

11:15

other things . Maybe they have

11:17

to drop fries , or maybe do another

11:19

order , start another order , and they don't

11:21

have to worry about Like watching

11:23

it so close , like standing over it . Yeah , Okay

11:26

. Over cooking it , under cooking it . We don't

11:28

have to worry about that problem anymore , and it's gonna be

11:30

done at four minutes rather than 13

11:32

minutes , so that time , so

11:35

you could actually serve twice as many customers

11:38

within the same time as you

11:40

would have to normally wait before . So

11:42

they have this and they're . this

11:45

is just one of the many stores that I'm gonna get to some more

11:47

actually . So this is one of the

11:49

many stores that have adopted

11:51

this ideology . So the chain

11:53

itself has over 1600 locations

11:56

and they're trying to roll this on out

11:58

very slowly . So they just trying

12:01

to test . this

12:03

is kind of tested . This is kind of tested . yeah , like a soft

12:05

introduction , Yes , yes , just to see

12:07

to come , because you have to train up these employees

12:10

and getting them used to this right . So

12:13

I think it's a great idea

12:15

.

12:17

I'm looking at it from a business perspective And

12:20

I get it from a business perspective and

12:22

I get that . Everything starts off great , everything

12:25

you can get more customers , fast

12:27

production , blah , blah , blah . But my

12:30

concern is more and the when

12:33

it's mass adopted . I'm more concerned

12:35

about way in the future

12:37

, how this no

12:40

contact with humans eventually

12:42

, you know we're gonna just have no contact

12:44

with humans . No , it's gonna get better .

12:47

But look , this kind of thing of a deal when

12:50

you go to a restaurant

12:52

. Now we have went to a really nice restaurant like

12:55

the Gordon Chef Ramsey

12:57

restaurant yeah , cooper's

12:59

Hall , those things are . Those are really nice restaurants

13:01

, even bone fish grill . You

13:04

meet the actual chef itself , right

13:06

, we ancestors ? How

13:09

often do you really meet the chef in

13:11

a restaurant that you typically go to ?

13:14

Just depends on the how high you're going

13:16

off there . Well , we're a person

13:18

that really well dying Well , okay

13:20

time , realistically the average person

13:23

with a regular salary . Don't

13:25

right , you don't ?

13:27

right . So this is why it

13:29

wouldn't ever matter if he go automated .

13:34

Right , nice

13:36

, when the chef comes out and tell you

13:39

it's just really have you ever ?

13:41

have you ever say oh man , i

13:43

wish the chef will come out ? I mean

13:45

, the chefs don't get respect , like they supposed to Neither

13:48

do butchers , but that's another story .

13:49

But yeah , um no , i Know

13:52

I haven't said dang I wish , but when that's when

13:55

we've had a chef or they come out , i love me

13:57

think about it . I mean I'm not

13:59

really . No , i mean I don't really at all . What

14:01

you think about is that the server . Right

14:04

, you think about it coming and how good

14:06

is it . Yeah , right .

14:07

Because if something is wrong , guess who you gonna blame ? You know , gonna

14:09

you . Typically , people don't blame the

14:11

chef , who they blame first ? the server Mm-hmm

14:13

right , which she's gonna get replaced

14:15

, or he is gonna get replaced into . So

14:18

that's , that's other man , that's another

14:20

part of the industry , that yeah

14:22

that's gonna , it's gonna , it's gonna cut

14:24

jobs , create more unemployment

14:27

.

14:27

That's one of my issues with it , because

14:30

You know it's gonna take a lot of

14:32

jobs and it's gonna be sometime . It might

14:34

be hard for people to actually understand how

14:36

to learn the new system and it's

14:39

you know , it's a lot of things better get on board

14:41

.

14:42

Better get on board , but look

14:44

. So moving on actually to White Castle

14:46

. Well , we talked about Flippy , right , your

14:48

?

14:48

favorite robot .

14:49

Yeah , flippy , so Flippy , actually

14:52

he can do or I

14:54

don't know it can do 120

14:57

configurations , right , and

15:00

, like I said , it costs about $3,000 a month

15:02

, and we know we just did the numbers . Typically to run

15:04

our operation , you're gonna be up worth

15:06

a $35,000 plus if you

15:08

look at all of the expenses . Now , that's

15:11

just employees just to run the

15:13

cook , the food . We're not talking about the management . We're not

15:15

talking about the building lease . We're not talking about

15:17

the Insurance of the property

15:19

itself . We're not talking about any of it . We're not

15:21

even talking about inventory yet , like when

15:24

I talk about any of that , right ? So who

15:26

knows , it could be thinking maybe 50

15:28

plus could be more Just

15:30

to run a one McDonald's

15:32

. It could be , but it could be upwards

15:34

of that , right ? So

15:36

you would get to have one of these

15:38

robots in your , your

15:41

establishment . I think that a

15:43

lot of Restaurant owners are

15:45

gonna see a huge benefit in it and

15:47

a huge profit margin , right

15:49

? It's two ways that you , a lot of people

15:51

, like to make money , right , when it comes

15:53

to business . There's two ways , right ? One

15:57

of the ways is make things automated

15:59

, right ? You save time , you're

16:02

gonna save money , right . Second

16:04

way , which WWE likes

16:06

to do is let cool people Right

16:09

.

16:09

I thought you say make things quick . Well

16:11

, i don't want any split , well , i don't .

16:14

And automated you out the way . So , yeah

16:16

, so you know Now your person

16:19

that's not in the way . Slug things down . Wow

16:21

, you're probably one of those people that's slowing things down at the

16:23

company and do it get rid of you . Yeah

16:26

, so those are two the

16:29

, the ways that big organization

16:31

Love to make money , and I can't

16:33

blame them . I can't blame them because

16:36

It

16:38

costs a lot to run a business

16:40

and over time , it

16:42

doesn't matter how much a person , a

16:44

company , raises his prices

16:46

Um the more that

16:48

it has to it only the razor , but the price

16:51

of a . So much . Right , because every time what deflation

16:53

has to raise This price , right , but

16:55

it's only but so much , depending on the type

16:57

of business that you have , that you're gonna be allowed

16:59

to raise it . And I said what I say allowed

17:01

. Let's say , like Mike Donaldsburg

17:03

King Mm-hmm , we Shit

17:06

even the dog store , right , yeah , they

17:08

, yeah , they can't have it became . It's not a don't

17:10

treat anymore . Is a dollar Five

17:12

cents or right , all the 25 cents , door now Mm-hmm

17:15

. So , and five below is now five

17:17

below anymore . Five and above now . So

17:20

, but

17:22

yeah , they switch the name

17:24

, right , i mean It's five

17:26

and above . Yes , i thought five and

17:28

above something .

17:29

Oh , okay , well , I thought it's

17:31

been there , but it's funny . Okay

17:34

, it's a real but thing .

17:35

Yeah , it's a real thing . That's what I'm saying

17:37

. Like you , you have to , you

17:39

have to find ways , some .

17:41

I didn't even know that about five below .

17:43

Yeah , it's just . Uh , i

17:45

say I think that's the name restore

17:47

now . Or they have a section in the store called five

17:49

and above . I guess it's one of those , but I

17:51

know I've seen the science at five and above and

17:54

and and it was related to that

17:56

store , mm-hmm . So I

17:59

think at this point he might have just called it five and above

18:01

and so the floor mark would be at

18:03

the five dollar mark . So we can't do it at the

18:06

highest mile . You're gonna

18:08

spend it as five dollars for something , the minimum

18:10

you are spending it's fine right .

18:12

They may have to change it . They haven't already .

18:14

I'm So , and I think too , i

18:16

mean , you know , just

18:18

that's one of the things you just have to do . Another

18:22

company this is the one remember when we

18:24

went to Vegas , and this is like a mile

18:26

mall the mile is the mile

18:28

. Yeah , yeah yeah

18:30

, so the tips , you robot .

18:32

Oh yeah , He was , oh yeah . Yeah

18:34

it was there . Yeah , arm

18:36

pulling , pulling down the alcohol

18:38

. Yes the ceiling and different drinks ?

18:40

Yeah , Yep , yep . So I

18:43

personally , if , if

18:46

I own the bar , this is the route I

18:48

will take , right , so this will

18:50

say but this is not too bad , this

18:53

is not too bad . They have two robots

18:55

and Eight humans . That were okay

18:57

.

18:58

So what's about to ? how about the humans and the robot

19:01

? because some people want to go to a bar

19:03

You're seeing cheers . They want to go , everybody on

19:05

a name . They want to sit down and want to drink . They want to

19:07

talk to people . That's the reason why

19:09

we don't want the world to be sold

19:11

. I know you like

19:13

robots and Technology

19:15

, ai and all that , but I am

19:18

in the field of human services , so you know

19:20

that I love people and so I

19:22

get it , but I'm 50 50

19:25

. Maybe we work alongside of them , but

19:27

yet we still have , you

19:29

know , human contact . Nobody wants to go

19:31

to a bar After work

19:33

and just not have

19:36

, you know , your people around . Some , you know Well

19:39

.

19:39

I mean you go to typically . Well . Well

19:41

, I guess you actually just saying just the typically

19:43

people go to the bar . They will , they

19:46

will mingle with the person that they came with

19:48

or somebody that or might be a spot

19:50

that they just have Yeah or sometimes

19:52

you date . There is your favorite bartender .

19:54

Yeah , we had ours in Virginia .

19:56

Yeah , yeah so , but

19:59

then again , when we move , did

20:01

we miss that person ? No , i

20:03

mean but really gives a shit . Nobody

20:06

gives a shit . When you do that bar

20:08

, nobody gives a damn but we go

20:10

for The human

20:13

interaction .

20:14

We like our bartenders and I'm

20:16

like it's okay . Yeah , we probably didn't miss

20:18

them Enough to like go back to

20:20

Regina and go hang out , but what I'm saying is that it

20:22

was our spot and so a lot

20:25

of big cities Have a lot of

20:27

people that go to certain spots and this is their

20:29

spot after work . It's their spot on the weekend

20:31

and , because of the interaction with

20:33

people , people like to go sit in cafes , get

20:36

out of , out of the house , because they're

20:38

around people and join environment

20:40

, getting energy , you know . So

20:42

if you kill all of that and it's just robots

20:44

everywhere , Well

20:47

, I don't know you .

20:48

This is this is what I'm thinking too . It

20:50

seems like the sentiment is starting to

20:52

change on that , right . So we not

20:55

we started to see a lot of not

20:57

a lot , but we started to see restaurants that

21:00

Replace waiters and

21:02

waitresses with Robotics

21:05

.

21:05

Yeah , i've seen it you know , server

21:07

right .

21:08

We've seen that and it's only gonna get better as

21:10

time goes on . Right , as we

21:12

move into the future , The robot technology

21:14

is gonna get better . Well , whatever the case

21:16

might be right Now

21:19

there's a commercial that I've seen With

21:22

an investment firm . It was pretty interesting

21:25

Is it was a young

21:27

lady . She was this

21:29

. She's working hot dog stand

21:31

at a stadium right and

21:34

it was a robot like

21:36

next to her , and a robot

21:39

was also serve hot dogs and

21:41

, and , and

21:43

, but the hot dog . The robot

21:45

was able to serve maybe about 10 hot dogs

21:47

in the same time . It was able to take this . This lady

21:50

deserve one . Ah and

21:52

the thing is too when they look at the commercial

21:55

. The lady had her hands on on , the lady had I

21:57

mean we get it for the

21:59

.

21:59

Yeah for the . What

22:01

is it this ? sanitize Annotation

22:04

, right to be cleaner and things of

22:06

that nature , less germs and disease

22:09

spread .

22:09

I mean it has its pros and it has its cons

22:12

and I get that well , but I'm saying , though , we're

22:15

seeing this as a commercial

22:17

, and commercial is just

22:19

basically .

22:21

It's just another . See , this is another soft

22:23

introduction . That's exactly just so you

22:25

can understand what's coming , because every I

22:27

believe everything on TV is coming , you know .

22:29

Yeah , and , and , and . Look also the bright

22:31

line . When you go to the bright

22:33

line , you could just tap your credit card and

22:35

have a mixed drink . Hmm , no

22:38

human interaction at all . Yeah , that's

22:40

our train station here , i think is look

22:43

, but we are The

22:45

only ones to blame is ourselves . We

22:48

want instant gratification with everything .

22:50

We want everything really fast

22:52

and But we humans

22:55

and we always are the most . We do

22:57

want everything and once we get we are our own

22:59

greatest demise . We always end

23:01

up Doing the most and

23:03

then suffering because of ending . You know

23:06

, we create all of this well .

23:07

It just depends , though . It just depends on what

23:09

side of the spectrum you are . Well

23:12

, you know , i'm , if you know how to

23:14

, if you look at it as a business , mm-hmm

23:16

, there's this , like I get it from that aspect

23:18

. Yeah , from that , and I

23:21

mean to me That's , that's all I because you're

23:23

a business minded , but I'm a human search

23:25

you .

23:25

I'm a people person , so I

23:28

don't mind you . Strictly business

23:30

technology , okay , that's you . I

23:32

enjoy people and interaction with

23:34

people to a certain extent sometimes , okay

23:36

, but sometimes

23:38

You know , i can get maybe

23:40

working alongside , of course . I

23:43

mean cuz some I'm not even gonna sit up here in front

23:45

and lie . Like Technology is great

23:47

, like the zooms , people working from home

23:49

, i mean , it has its perks . I just don't

23:51

want it to get sold To

23:54

the point where that it's just only

23:56

AI Everywhere , like it's no

23:59

human world . That well , let me , actually I

24:01

don't think we'll see that in our lifetime . I hope I

24:03

don't .

24:04

Well , I don't know , you know , you know must . Ai

24:06

robot is coming out . Well , a good prototype

24:09

is coming out 2025 . It's a general

24:11

robot and they can actually do general

24:13

things , like it's supposed to be able to just

24:15

go to let . It's probably be able to Go to the grocery

24:17

store and do stuff like house

24:19

cleaning and things like that . Yeah , clean your house . They

24:22

could drive your car to the . They could drive your test

24:24

of car . You get to test the car .

24:26

It'll be able to drive it , you know so you

24:28

have a little virtual , you can have a minute virtual .

24:30

You have your little physical assistant , okay

24:33

so let me just ask you these kind of questions , then , right

24:35

, mm-hmm , let's just say how

24:37

the the Okay

24:41

, let's just say how The

24:45

Tesla robot is designed to do things . right mm-hmm

24:48

. We'll just

24:50

stick with the food part of

24:52

this conversation , right ? Okay , Would

24:56

you if you was able to say you buy a robot

24:58

for $30,000 , right ? He

25:01

says it's actually going to be cheaper than a Tesla . So

25:03

I'm thinking of maybe about $20,000 , right , Let's

25:05

just say you were able to buy a

25:08

robot for $20,000

25:10

. It's

25:12

free software updates , free

25:14

maintenance for five years on

25:17

your robot , right , But this

25:19

robot can be able to clean your house

25:21

, cook all your food , come up with new recipes

25:23

. You needed to run errands

25:25

for you . You don't have to worry about run errands . You

25:28

could be at work and say hey , Mr

25:30

Roboto , I need you to go to CVS

25:32

and pick up my prescription , Blah

25:34

, blah , blah . And it

25:36

could do all of this , right , Would

25:39

you be ? would you still

25:41

have that mindset of ?

25:42

oh , the humans . I gotta

25:46

say the humans , because that's fine

25:48

that Mr Roboto can do that

25:51

, that's wonderful . But someday somewhere

25:53

in my life , in my week

25:55

, my day , i'm going to want human

25:57

interaction . And that's because , look it

26:00

, we order stuff , we have the

26:02

people drop stuff off . I mean we kind

26:04

of do that , maybe not to the extent of it having it

26:06

be a robot , but

26:09

at the end of the day , yes , i still would like human

26:11

interaction . I mean , that's fine and dandy , because we kind

26:13

of do stuff like that now .

26:14

Would you like your Uber driver to be a robot or

26:16

driverless , or a human , which you prefer

26:19

?

26:20

As far as an Uber , I'd say

26:22

robot , because I'm by

26:24

myself . I don't know what you , what

26:26

you about to do , So but

26:28

then it's going to be a point where we ain't going to know what the robot's

26:31

about to do . Keep on going this

26:33

way .

26:33

the robot's going to turn . That's a good thing . if

26:35

you own your own , then you have to worry about it . We're going to

26:37

start turning on us humans , so kind

26:39

of like going back then , just kind

26:42

of like going back to the full conversation

26:44

. So , right , well , if you thought that

26:46

was bad , right , your

26:51

press is . you know , now you're getting your steak

26:53

just pressed on right , right

26:55

, you know that's what doesn't happen

26:57

in right , in chilies , right

26:59

, mm-hmm , you think that's bad , do

27:03

you don't ? you know that you can actually

27:05

print 3D food

27:07

now .

27:09

Mm-hmm , i didn't know that .

27:10

Yeah , this was a concept , was actually done back in 1983

27:14

. You know why it was done ? Why this

27:16

whole concept of why

27:18

we should even want

27:21

to eat 3D printed food

27:23

, mm-hmm ? Well , because NASA

27:25

wanted their

27:28

astronauts to be able

27:30

to eat pizza , mm-hmm

27:32

. All right . So , for a long time , 3d printed

27:35

food . this is how we kind of like evolve

27:37

, right ? The

27:40

3D printer , of course , was able

27:42

to just do general printing , right Of this

27:44

, general items like toys or whatever the case might be . Then

27:48

, when the food industry started to come into it

27:51

, a lot of other

27:53

companies . There's actually

27:55

a restaurant in the UK that everything

27:57

is aside , the restaurant is 3D printed

27:59

, really . Yeah , the forks , the chairs .

28:01

So your food , what do they use ? They use

28:03

ingredients . It's a 3D .

28:04

Yeah , It's a . They

28:06

use like plant-based ingredients

28:09

Okay , Nutrients or whatever .

28:11

Okay .

28:12

And it would produce a 3D

28:14

printed food right

28:16

. So

28:19

this is what it wanted to do , but

28:21

it's . I

28:24

want to say this is

28:26

going to be a thing . If you think

28:28

automation is bad at the restaurants , this is

28:30

going to be something that's going to be , i

28:32

think , household thing

28:34

.

28:35

What 3D printing ?

28:36

Yeah , In your house

28:38

, right . So right now , 3D printing

28:40

, the most popular food you can do

28:43

is pasta , pizza , mashed

28:45

potatoes . Right , You can do

28:47

icing . You could do cakes

28:50

, right , you could do raw meats , i'm

28:52

guessing , from like the protein .

28:53

I was going to say what ingredient

28:55

.

28:56

yeah , You just have like a certain , a certain

28:58

, a certain protein , and then it could be 3D printed

29:00

. You could do pancakes , you

29:03

could do chocolate , even right

29:05

. So where this

29:08

is going to , i think this is why I think automation

29:10

is going to be beautiful , like

29:12

when I was in the Navy . This was , like you know

29:15

, 1999 . I

29:17

had a conversation with a guy I think I told you about this

29:19

too , but this guy was telling me that he's

29:21

in the future . Everybody

29:25

he was , he was , he was on something like I was at the time

29:27

. I was like , let's do this crazy . That was like the hell he's talking

29:30

about , right , but it's , you know , just 20 years

29:32

ago . But , as you said , eight men

29:34

in the future , there's going to be

29:38

, there's going to be . Everybody is inside . They're

29:40

going to be able to have a black box in the house . I think he

29:42

was talking about nanotechnology , but this is kind of close to

29:44

this is going to be the thing before nanotechnology

29:47

. But he was like everybody's going to be

29:49

able to have a box in your house , like

29:51

a giant box , and you can be

29:53

able to print anything you want . I

29:56

mean , you'll be able to , you know , make anything they want

29:58

for your house .

30:00

So like the cabbage .

30:01

Yeah , you know what All

30:03

these things . You may say . Hey , how the hell

30:06

a 3D printer is going to

30:08

make a raw meat that

30:10

I still got to cook and I'm still going to need my oven to cook

30:12

it . Right , but no . It

30:15

comes out prepared ? Yes , because

30:18

they use lasers to cook the food as

30:20

it's being printed at the same time .

30:22

So it's so weird . Yeah

30:24

, i've heard of it , i just didn't know the extent

30:27

, like the ingredient , but I didn't know they . they

30:29

did 3D printing , of course

30:31

, for homes and those type of materials

30:33

for houses as well , which that's

30:36

another thing that takes people away from work

30:38

.

30:40

So I'm saying this too is because you

30:42

can just , i would , i would

30:44

, i would , i would expect , expect

30:46

10 , 15 years from now , it's

30:48

going to be everybody's going to have something like this on the

30:50

countertop . It looks like , like how we

30:52

have a countertop for toast

30:55

to ovens , things like that . Right , This is

30:57

going to be the new thing . You'll be able

30:59

to print your food And

31:01

eat it right off , right off .

31:03

So how do you think that's gonna put all of the

31:05

? So I guess we'll just be buying

31:07

instead of bread . Will buy ingredients

31:09

, yes , like wheat and meat , yeah , by

31:11

the soy bean or whatever to do to

31:13

make protein . Yes , so that'll be the new

31:15

grocery stores , which is so it'll

31:18

just be ingredients , ingredients and

31:20

not well , i mean hey , anything

31:22

you never know with this world . I mean , i'm not gonna

31:24

say I don't know about 15 years

31:26

. I think it's kind of soon , but maybe

31:28

eventually , i mean , they are Introduced . They've

31:31

introduced it Already

31:33

, the 3d print .

31:34

Yeah , like , because it has to

31:36

me . It's like There's

31:39

, you know it's a lot cleaner eating

31:41

, right , mm-hmm . And if one

31:43

of the big thing I will say that I'm

31:46

a big fan of 3d printing food is

31:48

, well one , you could

31:50

make very great designed foods

31:52

. Mm-hmm , like how that movie was Um

31:54

menu . No

31:57

, you're making that by hand , Yeah

31:59

but the 3d printer machine

32:01

would be able to do that instead , right To

32:03

it would actually cut down on a lot of food

32:06

waste that we have already in the world

32:08

. Right At a

32:10

3 it would do . It will cut down

32:12

on the Like

32:15

how we have the slaughter animals .

32:17

Right , so farmers would be out . Well , unless

32:20

there's building wheat or something

32:22

that we , you know , maybe whatever that , yeah

32:25

, maybe the ingredient that we need for certain , yeah

32:27

, foods yeah

32:29

would maybe we'll have . They will skyrocket

32:32

the weed or something like that . But yeah

32:34

, we'll cut down on animal slaughter .

32:36

Yeah , I mean because the lot of they

32:38

like was called methane gas or whatever

32:40

That's what . As for , like you know

32:43

, with animals produce the methane

32:45

. You know that when they fart and shit and all that

32:47

It's like about

32:49

a smell , we go to the farm . That's like

32:51

methane gas , mm-hmm . So they will cut down

32:53

all that . What it wouldn't

32:56

be , so I would be safe . A giant

32:58

science factory Instead

33:00

of a farm , yeah , now

33:03

that , of course , i know what you're saying It would . It

33:05

wouldn't make it harder for farm

33:08

raised cattle , yeah , or

33:10

any kind of .

33:12

Because we weren't , we won't be eating the actual

33:14

meat , right .

33:15

Would it be in the proteins of him , so

33:18

? but then again , when you eat just

33:20

the proteins of it , you

33:22

, your cholesterol , is no cholesterol

33:24

in that meat in the print to

33:26

be .

33:27

So the health , so as a healthier choice

33:29

, yeah , okay , it's a healthy alternative

33:31

, mm-hmm , well , that could be another so

33:33

then my issue they But with

33:35

the , with the food you buy , the ingredient

33:38

, they probably be putting stuff in that

33:40

to make it plumber and Got

33:42

it .

33:42

You know , this country , this world is just

33:44

, i mean , it sounds good in

33:46

theory , well , you know well we'll just

33:48

to see if you , if we decide

33:51

to , to use the

33:53

plant-based ingredients to

33:55

make this , these foods , and

33:57

it's probably okay . But I know what you're saying , but what

34:00

the GMO see is I

34:02

, then I understand . I understand where The

34:04

concern would and what direction it could

34:06

go with .

34:07

Okay , well , since the , the people are

34:09

buying ingredient for the 3d printer

34:12

, they'll start stuffing it and filling it

34:14

with shit that doesn't need to be the plump of the

34:16

steak more . I , yeah , make the pizza

34:18

bigger or the week fluffier . Yeah

34:20

, that was stuff like that . I mean , they do it now .

34:22

What they do it already . Yeah , exactly

34:24

. So you know that that'd

34:26

be a way to capitalize , yeah

34:29

, on industry . Yeah , but they'd be able to sustain

34:31

. Well see this is kind of like all going

34:33

to two wars where you

34:35

know the direction of AI

34:38

. Yeah yeah , because once the

34:41

time what we do all know is coming Maybe it's

34:43

not next , 60 , 70 years from

34:45

now when people will have to have started

34:47

living in space . Hmm , you know

34:49

, or have an option to live in space

34:51

? Right , there's no way that you'll be

34:54

able to grow Food like

34:56

that up there . You're right , you

34:58

have to find . So that's why all this

35:00

is going towards that direction

35:02

itself , because we have to make us , if

35:04

we're able to , like our Elon Musk wants to

35:06

be into Planetary species

35:09

. There's no way that

35:12

We could keep coming down earth to

35:14

grab up . Yes , it flies back there

35:16

and you know there's not gonna work . An alternative No , that's

35:18

not have to find out a way to make it on site

35:21

. This is what's why we're doing it itself . Okay

35:23

well that's just my thoughts on

35:25

that . Any final thoughts on

35:27

this crazy new world that we go into when it

35:29

comes to food ?

35:30

well , i Agree

35:33

with some of the technology in

35:35

the restaurant industry , yes , and

35:37

that is needed for production and to

35:39

be faster , but I also think that I

35:41

don't want to stray too far away from human

35:44

interaction either .

35:47

I say Put

35:49

met my order down . I would like to have

35:51

to Johnny . All right guys

35:53

? Thank you for listening and have a good

35:55

night , good night .