Would you like to inspect the original subtitles? These are the user uploaded subtitles that are being translated:
1
00:00:00,719 --> 00:00:03,830
What's up, techno sapiens? I'm Grace
2
00:00:03,830 --> 00:00:03,840
What's up, techno sapiens? I'm Grace
3
00:00:03,840 --> 00:00:06,309
What's up, techno sapiens? I'm Grace
Coolish, but you can call me by my first
4
00:00:06,309 --> 00:00:06,319
Coolish, but you can call me by my first
5
00:00:06,319 --> 00:00:09,509
Coolish, but you can call me by my first
screen name, The Color Purple 29,
6
00:00:09,509 --> 00:00:09,519
screen name, The Color Purple 29,
7
00:00:09,519 --> 00:00:12,070
screen name, The Color Purple 29,
inspired by my favorite color unrelated
8
00:00:12,070 --> 00:00:12,080
inspired by my favorite color unrelated
9
00:00:12,080 --> 00:00:15,190
inspired by my favorite color unrelated
to the film about domestic abuse. Sorry,
10
00:00:15,190 --> 00:00:15,200
to the film about domestic abuse. Sorry,
11
00:00:15,200 --> 00:00:18,470
to the film about domestic abuse. Sorry,
Oprah. Anyway, this is Tech Yeah, where
12
00:00:18,470 --> 00:00:18,480
Oprah. Anyway, this is Tech Yeah, where
13
00:00:18,480 --> 00:00:21,670
Oprah. Anyway, this is Tech Yeah, where
I tell CPU all about the biggest stories
14
00:00:21,670 --> 00:00:21,680
I tell CPU all about the biggest stories
15
00:00:21,680 --> 00:00:24,470
I tell CPU all about the biggest stories
in tech. Let's begin with some news from
16
00:00:24,470 --> 00:00:24,480
in tech. Let's begin with some news from
17
00:00:24,480 --> 00:00:26,710
in tech. Let's begin with some news from
a town I've been told I'll never work in
18
00:00:26,710 --> 00:00:26,720
a town I've been told I'll never work in
19
00:00:26,720 --> 00:00:29,589
a town I've been told I'll never work in
again. Hollywood,
20
00:00:29,589 --> 00:00:29,599
again. Hollywood,
21
00:00:29,599 --> 00:00:32,310
again. Hollywood,
where the city of angels just might be
22
00:00:32,310 --> 00:00:32,320
where the city of angels just might be
23
00:00:32,320 --> 00:00:35,270
where the city of angels just might be
turning into the city of a angels. Two
24
00:00:35,270 --> 00:00:35,280
turning into the city of a angels. Two
25
00:00:35,280 --> 00:00:37,270
turning into the city of a angels. Two
of the biggest stars in the world, Brad
26
00:00:37,270 --> 00:00:37,280
of the biggest stars in the world, Brad
27
00:00:37,280 --> 00:00:39,590
of the biggest stars in the world, Brad
Pitt and Tom Cruz, apparently duking it
28
00:00:39,590 --> 00:00:39,600
Pitt and Tom Cruz, apparently duking it
29
00:00:39,600 --> 00:00:42,069
Pitt and Tom Cruz, apparently duking it
out on the roof of a skyscraper. But
30
00:00:42,069 --> 00:00:42,079
out on the roof of a skyscraper. But
31
00:00:42,079 --> 00:00:44,950
out on the roof of a skyscraper. But
it's completely fake, digitally created
32
00:00:44,950 --> 00:00:44,960
it's completely fake, digitally created
33
00:00:44,960 --> 00:00:47,510
it's completely fake, digitally created
with AI technology. It's the video that
34
00:00:47,510 --> 00:00:47,520
with AI technology. It's the video that
35
00:00:47,520 --> 00:00:49,670
with AI technology. It's the video that
has Hollywood freaking out.
36
00:00:49,670 --> 00:00:49,680
has Hollywood freaking out.
37
00:00:49,680 --> 00:00:54,069
has Hollywood freaking out.
>> YOU KILLED JEFFREY EPSTEIN, YOU ANIMAL.
38
00:00:54,069 --> 00:00:54,079
>> YOU KILLED JEFFREY EPSTEIN, YOU ANIMAL.
39
00:00:54,079 --> 00:00:57,990
>> YOU KILLED JEFFREY EPSTEIN, YOU ANIMAL.
>> HE WAS A GOOD MAN.
40
00:00:57,990 --> 00:00:58,000
41
00:00:58,000 --> 00:01:01,110
OKAY, THIS is crazy. I literally wrote a
42
00:01:01,110 --> 00:01:01,120
OKAY, THIS is crazy. I literally wrote a
43
00:01:01,120 --> 00:01:03,910
OKAY, THIS is crazy. I literally wrote a
movie with that exact scene in it. Great
44
00:01:03,910 --> 00:01:03,920
movie with that exact scene in it. Great
45
00:01:03,920 --> 00:01:06,550
movie with that exact scene in it. Great
minds, but I get why everyone in
46
00:01:06,550 --> 00:01:06,560
minds, but I get why everyone in
47
00:01:06,560 --> 00:01:09,429
minds, but I get why everyone in
Hollywood is freaking out. This looked
48
00:01:09,429 --> 00:01:09,439
Hollywood is freaking out. This looked
49
00:01:09,439 --> 00:01:12,070
Hollywood is freaking out. This looked
so real, right down to the glimmer of
50
00:01:12,070 --> 00:01:12,080
so real, right down to the glimmer of
51
00:01:12,080 --> 00:01:14,550
so real, right down to the glimmer of
hope in Tom Cruz's eyes that this stunt
52
00:01:14,550 --> 00:01:14,560
hope in Tom Cruz's eyes that this stunt
53
00:01:14,560 --> 00:01:17,590
hope in Tom Cruz's eyes that this stunt
would finally be the one that kills him.
54
00:01:17,590 --> 00:01:17,600
would finally be the one that kills him.
55
00:01:17,600 --> 00:01:20,710
would finally be the one that kills him.
Of course, some haters are worried that
56
00:01:20,710 --> 00:01:20,720
Of course, some haters are worried that
57
00:01:20,720 --> 00:01:23,109
Of course, some haters are worried that
it's going to destroy the entire film
58
00:01:23,109 --> 00:01:23,119
it's going to destroy the entire film
59
00:01:23,119 --> 00:01:25,670
it's going to destroy the entire film
industry and ruin countless lives along
60
00:01:25,670 --> 00:01:25,680
industry and ruin countless lives along
61
00:01:25,680 --> 00:01:28,149
industry and ruin countless lives along
the way. Well, you know what? That's
62
00:01:28,149 --> 00:01:28,159
the way. Well, you know what? That's
63
00:01:28,159 --> 00:01:30,230
the way. Well, you know what? That's
what Hollywood gets for not casting me
64
00:01:30,230 --> 00:01:30,240
what Hollywood gets for not casting me
65
00:01:30,240 --> 00:01:32,390
what Hollywood gets for not casting me
in sinners.
66
00:01:32,390 --> 00:01:32,400
in sinners.
67
00:01:32,400 --> 00:01:35,030
in sinners.
Michael B. Jordan gets to be two people
68
00:01:35,030 --> 00:01:35,040
Michael B. Jordan gets to be two people
69
00:01:35,040 --> 00:01:37,670
Michael B. Jordan gets to be two people
and I can't even be in one of the many
70
00:01:37,670 --> 00:01:37,680
and I can't even be in one of the many
71
00:01:37,680 --> 00:01:40,630
and I can't even be in one of the many
Connolingus scenes.
72
00:01:40,630 --> 00:01:40,640
Connolingus scenes.
73
00:01:40,640 --> 00:01:43,830
Connolingus scenes.
MAKE THAT MAKE SENSE.
74
00:01:43,830 --> 00:01:43,840
MAKE THAT MAKE SENSE.
75
00:01:43,840 --> 00:01:46,310
MAKE THAT MAKE SENSE.
BUT IF you can't make it in Hollywood,
76
00:01:46,310 --> 00:01:46,320
BUT IF you can't make it in Hollywood,
77
00:01:46,320 --> 00:01:48,950
BUT IF you can't make it in Hollywood,
you can always fall back on your second
78
00:01:48,950 --> 00:01:48,960
you can always fall back on your second
79
00:01:48,960 --> 00:01:50,230
you can always fall back on your second
dream job.
80
00:01:50,230 --> 00:01:50,240
dream job.
81
00:01:50,240 --> 00:01:52,069
dream job.
>> Whimo has come up with a low tech
82
00:01:52,069 --> 00:01:52,079
>> Whimo has come up with a low tech
83
00:01:52,079 --> 00:01:54,230
>> Whimo has come up with a low tech
solution for a high-tech problem.
84
00:01:54,230 --> 00:01:54,240
solution for a high-tech problem.
85
00:01:54,240 --> 00:01:56,230
solution for a high-tech problem.
Customers are leaving doors open after
86
00:01:56,230 --> 00:01:56,240
Customers are leaving doors open after
87
00:01:56,240 --> 00:01:58,069
Customers are leaving doors open after
exiting the self-driving vehicles,
88
00:01:58,069 --> 00:01:58,079
exiting the self-driving vehicles,
89
00:01:58,079 --> 00:02:00,469
exiting the self-driving vehicles,
making them inoperable. Whimo is now
90
00:02:00,469 --> 00:02:00,479
making them inoperable. Whimo is now
91
00:02:00,479 --> 00:02:02,870
making them inoperable. Whimo is now
paying nearby door dashers to shut the
92
00:02:02,870 --> 00:02:02,880
paying nearby door dashers to shut the
93
00:02:02,880 --> 00:02:05,030
paying nearby door dashers to shut the
open doors so the driverless cars can
94
00:02:05,030 --> 00:02:05,040
open doors so the driverless cars can
95
00:02:05,040 --> 00:02:07,990
open doors so the driverless cars can
pick up their next passenger.
96
00:02:07,990 --> 00:02:08,000
pick up their next passenger.
97
00:02:08,000 --> 00:02:11,589
pick up their next passenger.
>> Yes. It's just like they say when God
98
00:02:11,589 --> 00:02:11,599
>> Yes. It's just like they say when God
99
00:02:11,599 --> 00:02:14,949
>> Yes. It's just like they say when God
closes a door, he can make six bucks on
100
00:02:14,949 --> 00:02:14,959
closes a door, he can make six bucks on
101
00:02:14,959 --> 00:02:17,190
closes a door, he can make six bucks on
Door Dash.
102
00:02:17,190 --> 00:02:17,200
Door Dash.
103
00:02:17,200 --> 00:02:19,589
Door Dash.
Look how awesome this is. Most people
104
00:02:19,589 --> 00:02:19,599
Look how awesome this is. Most people
105
00:02:19,599 --> 00:02:22,390
Look how awesome this is. Most people
are stuck in an office all day, but you
106
00:02:22,390 --> 00:02:22,400
are stuck in an office all day, but you
107
00:02:22,400 --> 00:02:25,030
are stuck in an office all day, but you
you get to drive around hunting for open
108
00:02:25,030 --> 00:02:25,040
you get to drive around hunting for open
109
00:02:25,040 --> 00:02:28,070
you get to drive around hunting for open
car doors. And if you close enough of
110
00:02:28,070 --> 00:02:28,080
car doors. And if you close enough of
111
00:02:28,080 --> 00:02:30,309
car doors. And if you close enough of
them, you get to eat dinner. The future
112
00:02:30,309 --> 00:02:30,319
them, you get to eat dinner. The future
113
00:02:30,319 --> 00:02:33,030
them, you get to eat dinner. The future
is amazing.
114
00:02:33,030 --> 00:02:33,040
is amazing.
115
00:02:33,040 --> 00:02:35,430
is amazing.
I'd be great at this job. I love closing
116
00:02:35,430 --> 00:02:35,440
I'd be great at this job. I love closing
117
00:02:35,440 --> 00:02:38,550
I'd be great at this job. I love closing
things. Gates, trunks, coffins. I don't
118
00:02:38,550 --> 00:02:38,560
things. Gates, trunks, coffins. I don't
119
00:02:38,560 --> 00:02:41,270
things. Gates, trunks, coffins. I don't
care if the funeral is open casket, your
120
00:02:41,270 --> 00:02:41,280
care if the funeral is open casket, your
121
00:02:41,280 --> 00:02:44,630
care if the funeral is open casket, your
grandma is busted.
122
00:02:44,630 --> 00:02:44,640
grandma is busted.
123
00:02:44,640 --> 00:02:46,470
grandma is busted.
Moving on because it's time for
124
00:02:46,470 --> 00:02:46,480
Moving on because it's time for
125
00:02:46,480 --> 00:02:51,030
Moving on because it's time for
tonight's study that makes you go h
126
00:02:51,030 --> 00:02:51,040
tonight's study that makes you go h
127
00:02:51,040 --> 00:02:58,550
tonight's study that makes you go h
tonight's study is all about this
128
00:02:58,550 --> 00:02:58,560
129
00:02:58,560 --> 00:03:00,150
dancing. If
130
00:03:00,150 --> 00:03:00,160
dancing. If
131
00:03:00,160 --> 00:03:01,589
dancing. If
>> you wonder why some guys light up the
132
00:03:01,589 --> 00:03:01,599
>> you wonder why some guys light up the
133
00:03:01,599 --> 00:03:02,790
>> you wonder why some guys light up the
dance floor while others look like
134
00:03:02,790 --> 00:03:02,800
dance floor while others look like
135
00:03:02,800 --> 00:03:04,470
dance floor while others look like
they're swatting invisible flies,
136
00:03:04,470 --> 00:03:04,480
they're swatting invisible flies,
137
00:03:04,480 --> 00:03:06,470
they're swatting invisible flies,
science may have the answer. In a study
138
00:03:06,470 --> 00:03:06,480
science may have the answer. In a study
139
00:03:06,480 --> 00:03:08,790
science may have the answer. In a study
by North Umbrea University, volunteers
140
00:03:08,790 --> 00:03:08,800
by North Umbrea University, volunteers
141
00:03:08,800 --> 00:03:10,390
by North Umbrea University, volunteers
danced for 30 seconds while motion
142
00:03:10,390 --> 00:03:10,400
danced for 30 seconds while motion
143
00:03:10,400 --> 00:03:12,149
danced for 30 seconds while motion
sensors tracked every move. They were
144
00:03:12,149 --> 00:03:12,159
sensors tracked every move. They were
145
00:03:12,159 --> 00:03:14,309
sensors tracked every move. They were
later turned into faceless 3D avatars to
146
00:03:14,309 --> 00:03:14,319
later turned into faceless 3D avatars to
147
00:03:14,319 --> 00:03:15,910
later turned into faceless 3D avatars to
allow women to rank the routines. Men
148
00:03:15,910 --> 00:03:15,920
allow women to rank the routines. Men
149
00:03:15,920 --> 00:03:17,270
allow women to rank the routines. Men
rated as good dancers showed more
150
00:03:17,270 --> 00:03:17,280
rated as good dancers showed more
151
00:03:17,280 --> 00:03:19,110
rated as good dancers showed more
variety in upper body movement while
152
00:03:19,110 --> 00:03:19,120
variety in upper body movement while
153
00:03:19,120 --> 00:03:21,430
variety in upper body movement while
repetitive moves and sip twisting scored
154
00:03:21,430 --> 00:03:21,440
repetitive moves and sip twisting scored
155
00:03:21,440 --> 00:03:25,830
repetitive moves and sip twisting scored
near the bottom.
156
00:03:25,830 --> 00:03:25,840
157
00:03:25,840 --> 00:03:27,670
>> Thanks to this cuttingedge tech,
158
00:03:27,670 --> 00:03:27,680
>> Thanks to this cuttingedge tech,
159
00:03:27,680 --> 00:03:29,750
>> Thanks to this cuttingedge tech,
scientists have confirmed what we
160
00:03:29,750 --> 00:03:29,760
scientists have confirmed what we
161
00:03:29,760 --> 00:03:32,789
scientists have confirmed what we
already suspected. Women love men having
162
00:03:32,789 --> 00:03:32,799
already suspected. Women love men having
163
00:03:32,799 --> 00:03:34,949
already suspected. Women love men having
seizures.
164
00:03:34,949 --> 00:03:34,959
seizures.
165
00:03:34,959 --> 00:03:37,589
seizures.
My cousin has epilepsy and he is
166
00:03:37,589 --> 00:03:37,599
My cousin has epilepsy and he is
167
00:03:37,599 --> 00:03:40,789
My cousin has epilepsy and he is
drowning in [\h__\h]
168
00:03:40,789 --> 00:03:40,799
drowning in [\h__\h]
169
00:03:40,799 --> 00:03:43,589
drowning in [\h__\h]
And this data is very useful because now
170
00:03:43,589 --> 00:03:43,599
And this data is very useful because now
171
00:03:43,599 --> 00:03:45,830
And this data is very useful because now
we know if you're a good dancer and
172
00:03:45,830 --> 00:03:45,840
we know if you're a good dancer and
173
00:03:45,840 --> 00:03:50,070
we know if you're a good dancer and
can't get a date, you ugly brother.
174
00:03:50,070 --> 00:03:50,080
can't get a date, you ugly brother.
175
00:03:50,080 --> 00:03:52,309
can't get a date, you ugly brother.
Of course, you can't just dance to
176
00:03:52,309 --> 00:03:52,319
Of course, you can't just dance to
177
00:03:52,319 --> 00:03:54,710
Of course, you can't just dance to
attract women. You need to have the
178
00:03:54,710 --> 00:03:54,720
attract women. You need to have the
179
00:03:54,720 --> 00:03:57,670
attract women. You need to have the
perfect pickup line as well. Luckily, I
180
00:03:57,670 --> 00:03:57,680
perfect pickup line as well. Luckily, I
181
00:03:57,680 --> 00:03:59,030
perfect pickup line as well. Luckily, I
know just the one.
182
00:03:59,030 --> 00:03:59,040
know just the one.
183
00:03:59,040 --> 00:04:03,429
know just the one.
>> YOU KILLED JEFFREY EPSTEIN, YOU ANIMAL.
184
00:04:03,429 --> 00:04:03,439
>> YOU KILLED JEFFREY EPSTEIN, YOU ANIMAL.
185
00:04:03,439 --> 00:04:06,550
>> YOU KILLED JEFFREY EPSTEIN, YOU ANIMAL.
He was a good man.
186
00:04:06,550 --> 00:04:06,560
He was a good man.
187
00:04:06,560 --> 00:04:09,830
He was a good man.
>> Yeah, that's a panty dropper. And
188
00:04:09,830 --> 00:04:09,840
>> Yeah, that's a panty dropper. And
189
00:04:09,840 --> 00:04:12,789
>> Yeah, that's a panty dropper. And
speaking of underwear, if you like me
190
00:04:12,789 --> 00:04:12,799
speaking of underwear, if you like me
191
00:04:12,799 --> 00:04:15,350
speaking of underwear, if you like me
love putting gadgets in all the wrong
192
00:04:15,350 --> 00:04:15,360
love putting gadgets in all the wrong
193
00:04:15,360 --> 00:04:18,469
love putting gadgets in all the wrong
places, have I got a Tekken product for
194
00:04:18,469 --> 00:04:18,479
places, have I got a Tekken product for
195
00:04:18,479 --> 00:04:19,270
places, have I got a Tekken product for
you.
196
00:04:19,270 --> 00:04:19,280
you.
197
00:04:19,280 --> 00:04:21,270
you.
>> Researchers are looking for volunteers
198
00:04:21,270 --> 00:04:21,280
>> Researchers are looking for volunteers
199
00:04:21,280 --> 00:04:24,070
>> Researchers are looking for volunteers
to put on a new type of smart underwear
200
00:04:24,070 --> 00:04:24,080
to put on a new type of smart underwear
201
00:04:24,080 --> 00:04:26,550
to put on a new type of smart underwear
designed to track human flatulence and
202
00:04:26,550 --> 00:04:26,560
designed to track human flatulence and
203
00:04:26,560 --> 00:04:29,030
designed to track human flatulence and
also stress test them. University of
204
00:04:29,030 --> 00:04:29,040
also stress test them. University of
205
00:04:29,040 --> 00:04:30,790
also stress test them. University of
Maryland scientists say that the garment
206
00:04:30,790 --> 00:04:30,800
Maryland scientists say that the garment
207
00:04:30,800 --> 00:04:33,030
Maryland scientists say that the garment
has a snap-in device which acts like a
208
00:04:33,030 --> 00:04:33,040
has a snap-in device which acts like a
209
00:04:33,040 --> 00:04:35,670
has a snap-in device which acts like a
glucose monitor but for intestinal gas
210
00:04:35,670 --> 00:04:35,680
glucose monitor but for intestinal gas
211
00:04:35,680 --> 00:04:37,350
glucose monitor but for intestinal gas
and it says that it could open the door
212
00:04:37,350 --> 00:04:37,360
and it says that it could open the door
213
00:04:37,360 --> 00:04:43,590
and it says that it could open the door
to measuring gut microbiome metabolism.
214
00:04:43,590 --> 00:04:43,600
215
00:04:43,600 --> 00:04:45,990
Smell that? That is the smell of
216
00:04:45,990 --> 00:04:46,000
Smell that? That is the smell of
217
00:04:46,000 --> 00:04:48,070
Smell that? That is the smell of
innovation
218
00:04:48,070 --> 00:04:48,080
innovation
219
00:04:48,080 --> 00:04:50,950
innovation
and falafel. Sorry,
220
00:04:50,950 --> 00:04:50,960
and falafel. Sorry,
221
00:04:50,960 --> 00:04:53,990
and falafel. Sorry,
but I love this product. Finally a way
222
00:04:53,990 --> 00:04:54,000
but I love this product. Finally a way
223
00:04:54,000 --> 00:04:56,390
but I love this product. Finally a way
for health nuts to get in there 10,000
224
00:04:56,390 --> 00:04:56,400
for health nuts to get in there 10,000
225
00:04:56,400 --> 00:04:58,070
for health nuts to get in there 10,000
farts a day.
226
00:04:58,070 --> 00:04:58,080
farts a day.
227
00:04:58,080 --> 00:05:01,510
farts a day.
Heck, I think I'll get two. One for the
228
00:05:01,510 --> 00:05:01,520
Heck, I think I'll get two. One for the
229
00:05:01,520 --> 00:05:06,230
Heck, I think I'll get two. One for the
back and one to track my cooter tutors.
230
00:05:06,230 --> 00:05:06,240
back and one to track my cooter tutors.
231
00:05:06,240 --> 00:05:08,870
back and one to track my cooter tutors.
I swear when those two get to yapping,
232
00:05:08,870 --> 00:05:08,880
I swear when those two get to yapping,
233
00:05:08,880 --> 00:05:10,550
I swear when those two get to yapping,
I'M LIKE, "YOU GIRLS SHOULD START A
234
00:05:10,550 --> 00:05:10,560
I'M LIKE, "YOU GIRLS SHOULD START A
235
00:05:10,560 --> 00:05:18,870
I'M LIKE, "YOU GIRLS SHOULD START A
PODCAST."
236
00:05:18,870 --> 00:05:18,880
237
00:05:18,880 --> 00:05:22,150
>> SO, what have we learned from this data
238
00:05:22,150 --> 00:05:22,160
>> SO, what have we learned from this data
239
00:05:22,160 --> 00:05:25,110
>> SO, what have we learned from this data
so far? Previous studies asked people to
240
00:05:25,110 --> 00:05:25,120
so far? Previous studies asked people to
241
00:05:25,120 --> 00:05:27,350
so far? Previous studies asked people to
estimate and they guessed between 10 to
242
00:05:27,350 --> 00:05:27,360
estimate and they guessed between 10 to
243
00:05:27,360 --> 00:05:29,189
estimate and they guessed between 10 to
15 times a day. Early testing has
244
00:05:29,189 --> 00:05:29,199
15 times a day. Early testing has
245
00:05:29,199 --> 00:05:31,029
15 times a day. Early testing has
revealed something interesting. We found
246
00:05:31,029 --> 00:05:31,039
revealed something interesting. We found
247
00:05:31,039 --> 00:05:32,870
revealed something interesting. We found
that people farted an average of 32
248
00:05:32,870 --> 00:05:32,880
that people farted an average of 32
249
00:05:32,880 --> 00:05:35,029
that people farted an average of 32
times per day.
250
00:05:35,029 --> 00:05:35,039
times per day.
251
00:05:35,039 --> 00:05:39,830
times per day.
The average person farts 32 times a day.
252
00:05:39,830 --> 00:05:39,840
The average person farts 32 times a day.
253
00:05:39,840 --> 00:05:41,909
The average person farts 32 times a day.
Imagine if you're an above average
254
00:05:41,909 --> 00:05:41,919
Imagine if you're an above average
255
00:05:41,919 --> 00:05:45,430
Imagine if you're an above average
person. Like Beyonce must be farting
256
00:05:45,430 --> 00:05:45,440
person. Like Beyonce must be farting
257
00:05:45,440 --> 00:05:49,590
person. Like Beyonce must be farting
6,000 TIMES A DAY. WHAT a lucky horse.
258
00:05:49,590 --> 00:05:49,600
6,000 TIMES A DAY. WHAT a lucky horse.
259
00:05:49,600 --> 00:05:52,390
6,000 TIMES A DAY. WHAT a lucky horse.
Now I know what you're thinking. I must
260
00:05:52,390 --> 00:05:52,400
Now I know what you're thinking. I must
261
00:05:52,400 --> 00:05:55,350
Now I know what you're thinking. I must
be part of this study. Well, bad news
262
00:05:55,350 --> 00:05:55,360
be part of this study. Well, bad news
263
00:05:55,360 --> 00:05:57,830
be part of this study. Well, bad news
because due to overwhelming demand,
264
00:05:57,830 --> 00:05:57,840
because due to overwhelming demand,
265
00:05:57,840 --> 00:06:00,070
because due to overwhelming demand,
enrollment in the fart tracking study is
266
00:06:00,070 --> 00:06:00,080
enrollment in the fart tracking study is
267
00:06:00,080 --> 00:06:02,310
enrollment in the fart tracking study is
currently paused.
268
00:06:02,310 --> 00:06:02,320
currently paused.
269
00:06:02,320 --> 00:06:04,950
currently paused.
But lucky for you, I'm conducting my own
270
00:06:04,950 --> 00:06:04,960
But lucky for you, I'm conducting my own
271
00:06:04,960 --> 00:06:07,430
But lucky for you, I'm conducting my own
study. All you have to do is email me
272
00:06:07,430 --> 00:06:07,440
study. All you have to do is email me
273
00:06:07,440 --> 00:06:08,950
study. All you have to do is email me
every time you fart at the
274
00:06:08,950 --> 00:06:08,960
every time you fart at the
275
00:06:08,960 --> 00:06:14,390
every time you fart at the
colorpurps.com.
276
00:06:14,390 --> 00:06:14,400
277
00:06:14,400 --> 00:06:16,309
Well, that's all for this edition of
278
00:06:16,309 --> 00:06:16,319
Well, that's all for this edition of
279
00:06:16,319 --> 00:06:18,390
Well, that's all for this edition of
Tech Yeah. Tune in next time when we
280
00:06:18,390 --> 00:06:18,400
Tech Yeah. Tune in next time when we
281
00:06:18,400 --> 00:06:20,870
Tech Yeah. Tune in next time when we
debate which one of these pictures has a
282
00:06:20,870 --> 00:06:20,880
debate which one of these pictures has a
283
00:06:20,880 --> 00:06:23,270
debate which one of these pictures has a
motorcycle in it. If I get this wrong,
284
00:06:23,270 --> 00:06:23,280
motorcycle in it. If I get this wrong,
285
00:06:23,280 --> 00:06:27,160
motorcycle in it. If I get this wrong,
it's over for me.
24928
Can't find what you're looking for?
Get subtitles in any language from opensubtitles.com, and translate them here.