Family.Guy.S01E01.Death.Has.a.Shadow.INTERNAL.DVDRip.XviD-SChiZO.eng.srt

1
00:00:06,973 --> 00:00:09,942
Mom, Dad, I found cigarettes
in Greg's jacket.

2
00:00:10,043 --> 00:00:12,273
- Greg, were you smoking cigarettes?
- No, Dad.

3
00:00:12,379 --> 00:00:14,279
He's lying. There's no doubt about that.

4
00:00:14,381 --> 00:00:17,748
Greg, I'm afraid your punishment
will be four hours in the snakepit.

5
00:00:17,851 --> 00:00:20,081
That'll give you time to think about
what you did.

6
00:00:20,186 --> 00:00:21,380
Man!

7
00:00:22,088 --> 00:00:23,055
That'll teach him.

8
00:00:23,156 --> 00:00:25,886
Jan, I'm afraid you've earned
a day in the fire chamber...

9
00:00:25,992 --> 00:00:27,653
...for tattling on your brother.

10
00:00:29,095 --> 00:00:32,360
Smoking. How does
a boy like that go so wrong?

11
00:00:32,465 --> 00:00:34,626
- They live in a crummy neighborhood.
- The Bradys?

12
00:00:34,734 --> 00:00:37,965
Yeah. They got robbers, thugs,
drug dealers. You name it.

13
00:00:38,071 --> 00:00:39,538
You folks want some pancakes?

14
00:00:39,639 --> 00:00:43,075
No, thanks. See, that's the worst
we got is Jemima's Witnesses.

15
00:00:43,810 --> 00:00:46,802
"It seems today that all you see

16
00:00:47,147 --> 00:00:50,378
"is violence in movies and sex on TV

17
00:00:50,483 --> 00:00:53,884
"But where are those good,
old-fashioned values

18
00:00:53,987 --> 00:00:56,547
"on which we used to rely?

19
00:00:57,323 --> 00:01:00,292
"Lucky there's a family guy

20
00:01:00,393 --> 00:01:03,521
"Lucky there's a man who'll
positively tell you

21
00:01:03,630 --> 00:01:05,359
"all the things that make us

22
00:01:05,465 --> 00:01:06,955
"laugh 'n' cry

23
00:01:07,067 --> 00:01:11,731
"He's a family guy"

24
00:01:17,410 --> 00:01:20,641
Mom, my lips are too thin.
Can I please get collagen injections?

25
00:01:20,747 --> 00:01:23,215
Meg, you don't need to change
the way you look.

26
00:01:23,316 --> 00:01:26,717
You know, most of the world's problems
stem from poor self-image.

27
00:01:36,229 --> 00:01:39,221
Excellent! The mind-control device
is nearing completion!

28
00:01:39,332 --> 00:01:41,630
Stewie, I said no toys at the table.

29
00:01:41,734 --> 00:01:42,928
Damn you, vile woman!

30
00:01:43,036 --> 00:01:46,403
You've impeded my work since the day
I escaped from your wretched womb.

31
00:01:46,506 --> 00:01:49,566
Don't pout, honey. When you were born...

32
00:01:49,676 --> 00:01:53,237
...the doctor said you were
the happiest looking baby he'd ever seen.

33
00:01:53,346 --> 00:01:57,442
But, of course. That was my victory day.
The fruition of my deeply-laid plans...

34
00:01:57,550 --> 00:02:01,748
...to escape from that cursed ovarian
bastille! Return the device, woman!

35
00:02:01,855 --> 00:02:03,379
No toys, Stewie.

36
00:02:03,490 --> 00:02:04,457
Very well, then.

37
00:02:04,557 --> 00:02:08,493
Mark my words, when you least expect it,
your uppance will come!

38
00:02:10,563 --> 00:02:11,928
Mom, can I turn the heat up?

39
00:02:12,031 --> 00:02:15,091
Don't touch the thermostat, Meg.
Your father gets upset.

40
00:02:15,201 --> 00:02:17,192
Come on. This thing goes up to 90.

41
00:02:17,303 --> 00:02:18,235
Who touched the thermostat?

42
00:02:18,338 --> 00:02:19,896
God, how does he always know?

43
00:02:20,006 --> 00:02:22,201
Brain implant, Meg. Every father's got one.

44
00:02:22,308 --> 00:02:24,208
Tells you when the kids mess with the dial.

45
00:02:24,310 --> 00:02:26,278
My thing went off!
Your thermostat okay?

46
00:02:26,379 --> 00:02:28,279
- Yeah, it's all right.
- Is my kid over here?

47
00:02:28,381 --> 00:02:29,439
Forget it! False alarm!

48
00:02:30,116 --> 00:02:31,777
Ass ahoy.

49
00:02:31,885 --> 00:02:35,377
Peter, it's 7:00 and you've still got
your pants on. What's the occasion?

50
00:02:35,488 --> 00:02:37,046
He's going to a stag party.

51
00:02:37,157 --> 00:02:39,819
Lois, I work hard all week
to provide for this family.

52
00:02:39,926 --> 00:02:41,154
I am the man of the house.

53
00:02:41,261 --> 00:02:44,458
As the man, I order you
to give me permission to go to this party.

54
00:02:44,564 --> 00:02:48,193
Look, at least promise me you won't drink.
Alcohol always leads to trouble.

55
00:02:48,601 --> 00:02:50,330
Come on. You're worrying about nothing.

56
00:02:50,503 --> 00:02:54,166
Remember when you got drunk
off the Communion wine at church?

57
00:02:54,607 --> 00:02:57,576
And so the Lord God smote poor Job...

58
00:02:57,710 --> 00:03:00,042
...with festering boils all over his body.

59
00:03:00,146 --> 00:03:02,307
Man, I hate it when he tells this story.

60
00:03:02,448 --> 00:03:06,612
Yet, miraculously,
Job was still able to retain his dignity.

61
00:03:06,719 --> 00:03:10,052
- Is that really the blood of Christ?
- Yes.

62
00:03:10,290 --> 00:03:13,282
Man, that guy must've been wasted
24 hours a day.

63
00:03:13,960 --> 00:03:16,656
And then there was that time
at the ice cream store.

64
00:03:17,096 --> 00:03:19,394
Butter Rum's my favorite.

65
00:03:21,501 --> 00:03:24,732
Remember you had an Irish coffee
the day we went to see Philadelphia?

66
00:03:30,543 --> 00:03:34,104
I got it. That's the guy from Big.
Tom Hanks, that's it.

67
00:03:34,347 --> 00:03:37,282
Funny guy, Tom Hanks.
Everything he says is a stitch.

68
00:03:37,383 --> 00:03:38,645
I have AIDS.

69
00:03:40,486 --> 00:03:42,784
- Promise me, Peter.
- Lois, honey, I promise.

70
00:03:42,889 --> 00:03:45,722
Not a drop of alcohol is gonna touch
these lips tonight.

71
00:03:45,825 --> 00:03:47,725
Who wants to play Drink The Beer?

72
00:03:47,827 --> 00:03:49,226
Right here.

73
00:03:49,329 --> 00:03:50,921
- You win.
- All right. What do I win?

74
00:03:51,030 --> 00:03:52,088
Another beer!

75
00:03:52,198 --> 00:03:53,756
I'm going for the high score!

76
00:03:53,866 --> 00:03:56,096
Actually, Charlie's got the high score.

77
00:03:56,202 --> 00:03:58,067
Man. Your clock won't flush.

78
00:03:59,172 --> 00:04:02,164
I feel kind of bad, guys.
I promised my wife I wouldn't drink.

79
00:04:02,275 --> 00:04:05,176
- Don't feel bad, Peter.
- Gee. I never thought of it like that.

80
00:04:05,411 --> 00:04:06,639
Did you bring the porno?

81
00:04:06,746 --> 00:04:10,375
Did I bring the porno?
You're gonna love it. It's a classic.

82
00:04:11,017 --> 00:04:12,917
Listen, Ilsa. If I take this thing out...

83
00:04:13,019 --> 00:04:16,011
...and you're not on it, you'll regret it.
Not today or tomorrow.

84
00:04:16,122 --> 00:04:18,090
But soon, and for the rest of your life.

85
00:04:18,191 --> 00:04:19,852
Come on, llsa! Get on it!

86
00:04:23,129 --> 00:04:25,324
The statue was a gift from France.

87
00:04:25,431 --> 00:04:26,591
What is this?

88
00:04:26,699 --> 00:04:29,497
Man. My kid must've taped
over this for history class.

89
00:04:30,770 --> 00:04:33,295
The Statue of Liberty?
What are we gonna do?

90
00:04:33,406 --> 00:04:37,740
- Boys, we're gonna drink till she's hot.
- That's just crazy enough to work.

91
00:04:43,449 --> 00:04:45,076
Meg, finish your pancakes.

92
00:04:45,184 --> 00:04:47,914
- Chris, elbows off your father.
- Thanks, son.

93
00:04:48,021 --> 00:04:51,787
37 beers. You're setting
a great example for the kids, Peter.

94
00:04:51,891 --> 00:04:55,019
Yeah. A new family record.
Way to raise the bar, Dad.

95
00:04:55,128 --> 00:04:57,119
Chris, you're 13. Don't talk like that.

96
00:04:57,230 --> 00:04:59,790
Kids, Daddy only drank
so the Statue of Liberty...

97
00:04:59,899 --> 00:05:01,298
...would take her clothes off.

98
00:05:01,401 --> 00:05:04,893
- What did you promise me last night?
- I wouldn't drink at the stag party.

99
00:05:05,004 --> 00:05:07,871
- And what did you do?
- Drank at the stag...

100
00:05:07,974 --> 00:05:11,034
I almost walked right into that one. God!

101
00:05:11,144 --> 00:05:14,204
Feels like accountants
are cranking adding machines in my head.

102
00:05:18,685 --> 00:05:21,552
Dick, you ever wonder
what's outside those walls?

103
00:05:21,654 --> 00:05:24,623
That's dangerous thinking, Paul.
You best stick to your work.

104
00:05:24,724 --> 00:05:25,691
Okay.

105
00:05:26,426 --> 00:05:30,487
You see? A hangover is nature's way
of telling you I was right. I mean...

106
00:05:30,596 --> 00:05:32,461
Mom, are you all right?

107
00:05:32,565 --> 00:05:36,262
My goodness.
This chair leg was loose. Isn't that silly?

108
00:05:36,369 --> 00:05:38,360
I could've broken my neck.

109
00:05:38,538 --> 00:05:39,596
Damn!

110
00:05:41,207 --> 00:05:43,641
Honey. I took a cab home,
I slept on the table...

111
00:05:43,743 --> 00:05:46,041
...so I wouldn't wake you up.
Nothing bad happened.

112
00:05:46,145 --> 00:05:47,976
I guess you're right.

113
00:05:48,081 --> 00:05:50,743
Apology accepted.
All right, I'm going to work.

114
00:05:50,850 --> 00:05:52,613
Somebody's gotta put food on this table.

115
00:05:56,289 --> 00:05:57,620
How are you coming, Johnson?

116
00:05:57,724 --> 00:06:00,056
Mr. Weed, I've been working
on the new G.I. Jew line.

117
00:06:00,159 --> 00:06:02,320
And as you can see, they look great.

118
00:06:02,428 --> 00:06:03,452
You call these bagels?

119
00:06:03,563 --> 00:06:05,861
I'm glad he's on our side!

120
00:06:08,267 --> 00:06:09,359
Peter!
What?

121
00:06:09,469 --> 00:06:10,663
Are you sleeping on the job?

122
00:06:10,770 --> 00:06:13,933
No. There's a bug in my eye
and I'm trying to suffocate him.

123
00:06:14,040 --> 00:06:17,874
Peter, I like you. But I need you to be
more than just eye candy around here.

124
00:06:17,977 --> 00:06:21,105
It's your job to watch for toys
that could be hazardous to kids.

125
00:06:21,214 --> 00:06:23,444
- Now, look sharp!
- Yes, sir!

126
00:06:35,294 --> 00:06:39,958
And now back to Action News 5.
Our top story tonight, "When Toys Attack. "

127
00:06:40,066 --> 00:06:41,693
Quite a situation we've got here, Tom.

128
00:06:41,801 --> 00:06:44,167
Quite a situation we've got here, Tom,
indeed, Diane.

129
00:06:44,270 --> 00:06:47,171
The Happy-Go-Lucky Toy Company
of Quahog, Rhode Island...

130
00:06:47,273 --> 00:06:50,333
...has released highly unsafe
products into the retail market.

131
00:06:50,710 --> 00:06:52,803
Come on, Timmy! Throw the Silly Ball!

132
00:06:54,680 --> 00:06:56,705
Boy! A Pound Poochie!

133
00:06:57,917 --> 00:07:00,408
Come on, Baby Heimlich, spit it out.

134
00:07:03,089 --> 00:07:04,181
Peter, I'm appalled.

135
00:07:04,290 --> 00:07:07,123
Your negligence has damaged
this company's reputation.

136
00:07:07,226 --> 00:07:08,215
You're fired!

137
00:07:08,327 --> 00:07:09,521
Jeez. For how long?

138
00:07:12,098 --> 00:07:13,588
My God! You got fired?

139
00:07:13,699 --> 00:07:17,328
- Way to go, Dad! Fight the machine!
- How do you know about the machine?

140
00:07:17,437 --> 00:07:20,167
Don't worry.
I'll still put food on this table.

141
00:07:20,273 --> 00:07:22,833
Just not as much.
So it might get a little competitive.

142
00:07:22,942 --> 00:07:27,470
Who cares about food? Now we'll never
be able to afford my lip injections!

143
00:07:27,613 --> 00:07:29,979
Can we put her
out in the yard for a while?

144
00:07:30,082 --> 00:07:32,073
Okay, who's hungry?

145
00:07:32,552 --> 00:07:34,884
Jeez. How the hell
am I gonna break this to Lois?

146
00:07:34,987 --> 00:07:38,514
If she finds out I got fired for drinking,
she's gonna blame me!

147
00:07:38,624 --> 00:07:42,082
Lie to her. It's okay to lie
to women. They're not people like us.

148
00:07:42,195 --> 00:07:44,686
I don't know. Hey, where's the other guy?

149
00:07:45,932 --> 00:07:48,560
Come on, you bastard! I'm late for work.

150
00:07:48,668 --> 00:07:49,794
This is perfect!

151
00:07:50,369 --> 00:07:52,599
Look, I don't want your mom to worry,
all right?

152
00:07:52,705 --> 00:07:55,105
When she worries, she says,
"I told you so" and:

153
00:07:55,208 --> 00:07:59,110
"Stop doing that. I'm asleep. "
So I'm just gonna tell a little lie, okay?

154
00:07:59,212 --> 00:08:01,544
Not a word to your mom
about me getting canned.

155
00:08:01,647 --> 00:08:03,046
What's that, Peter?

156
00:08:03,149 --> 00:08:06,141
- Nothing. The lost-my-job smells great.
- What?

157
00:08:06,252 --> 00:08:09,244
Meg, honey, can you pass
the fired-my-ass-for-negligence?

158
00:08:09,355 --> 00:08:11,016
Peter, are you feeling okay?

159
00:08:11,123 --> 00:08:13,785
I feel great!
I haven't got a job in the world.

160
00:08:13,893 --> 00:08:15,520
All right, then let's eat.

161
00:08:15,628 --> 00:08:18,324
I know you all hate eggplant, but...

162
00:08:19,465 --> 00:08:21,330
What on earth was that?

163
00:08:23,803 --> 00:08:26,499
What the deuce are you staring at?
It's tuna fish...

164
00:08:26,906 --> 00:08:27,998
...and nothing else.

165
00:08:32,445 --> 00:08:33,878
How's your job search going?

166
00:08:33,980 --> 00:08:37,245
It sucks, Brian. I've already
been through two jobs this week.

167
00:08:37,350 --> 00:08:38,874
I got fired off of that commercial.

168
00:08:38,985 --> 00:08:41,647
Try it again.
"I'm caca for Cocoa Puffs. "

169
00:08:41,754 --> 00:08:43,483
No, damn it! Take 26!

170
00:08:43,956 --> 00:08:47,357
Then I had that job as the sneeze guard
for that restaurant's salad bar.

171
00:08:50,029 --> 00:08:51,189
Take it outside, lady.

172
00:08:51,531 --> 00:08:53,624
I thought I could win money
in that talent show.

173
00:08:54,000 --> 00:08:57,436
And the prize goes
to The von Trapp Family Singers!

174
00:08:57,737 --> 00:08:58,829
That is bull...

175
00:09:01,307 --> 00:09:03,172
Peter, I know it's a dangerous precedent...

176
00:09:03,276 --> 00:09:05,506
...but you might want to tell Lois the truth.

177
00:09:05,611 --> 00:09:08,739
What? That I can't provide for my family?
That she's always right?

178
00:09:08,848 --> 00:09:11,282
That I didn't stand up to a tank
in Tiananmen Square?

179
00:09:15,855 --> 00:09:18,756
Screw this!
I just came over to buy some fireworks!

180
00:09:19,292 --> 00:09:21,590
You can't keep lying to her
about losing your job.

181
00:09:21,694 --> 00:09:24,322
Eventually, she'll find out
where you're going every day.

182
00:09:24,430 --> 00:09:25,362
Yeah.

183
00:09:28,601 --> 00:09:31,161
Yeah, you're right.
Okay, I'll tell her tonight.

184
00:09:47,954 --> 00:09:49,444
Victory is mine!

185
00:09:49,855 --> 00:09:51,789
I'll need the checkbook
in the morning.

186
00:09:51,891 --> 00:09:53,916
I'm going to Stop 'N Shop
for some sweet corn.

187
00:09:54,026 --> 00:09:55,687
You're spending money on food again?

188
00:09:55,795 --> 00:09:57,422
Lois, we just had dinner.

189
00:09:57,530 --> 00:10:01,660
I enjoyed it so much,
I thought we'd eat again tomorrow.

190
00:10:01,767 --> 00:10:04,361
Since when are you so concerned
about our food budget?

191
00:10:04,470 --> 00:10:05,664
I just...

192
00:10:05,771 --> 00:10:08,934
Lois, this is really hard for me to say, but...

193
00:10:09,041 --> 00:10:10,838
What is it, Peter?

194
00:10:11,978 --> 00:10:14,105
- You're getting kind of fat.
- What?

195
00:10:14,213 --> 00:10:16,477
It's just... It's not healthy.

196
00:10:16,582 --> 00:10:19,881
Peter, I do my Jane Fonda workout tape
three times a week.

197
00:10:19,986 --> 00:10:21,851
When was the last time you saw your toes?

198
00:10:21,954 --> 00:10:24,445
I thought you people were
supposed to be jolly.

199
00:10:24,557 --> 00:10:26,855
Peter, what the hell is the matter with you?

200
00:10:26,959 --> 00:10:30,053
Honey, if there's something wrong,
you can tell me.

201
00:10:30,196 --> 00:10:34,064
- Sorry, man. Am I late? What did I miss?
- Thank God you're here. What do I do?

202
00:10:34,166 --> 00:10:36,396
Tell him to keep quiet. He's in too deep.

203
00:10:36,502 --> 00:10:38,094
I don't know.

204
00:10:38,437 --> 00:10:39,563
Where's the other guy?

205
00:10:40,873 --> 00:10:42,397
This is unbelievable!

206
00:10:43,442 --> 00:10:46,707
I promise you, everything's fine.
You got nothing to worry about.

207
00:10:46,812 --> 00:10:49,975
Well, well, Mother!
We meet again!

208
00:10:50,082 --> 00:10:52,607
Stewie, I thought
I tucked you in an hour ago.

209
00:10:52,718 --> 00:10:55,846
Not tightly enough it would seem.
And now you contemptible harpy...

210
00:10:55,955 --> 00:10:58,423
...I shall end your reign
of matriarchal tyranny.

211
00:10:58,524 --> 00:11:00,458
You can play tomorrow, honey.

212
00:11:00,559 --> 00:11:02,049
Right now it's bedtime.

213
00:11:02,728 --> 00:11:05,128
Blast you and your estrogenical treachery!

214
00:11:05,231 --> 00:11:06,528
Sweet dreams, kiddo.

215
00:11:06,632 --> 00:11:07,997
You have the power to end this!

216
00:11:11,103 --> 00:11:12,468
How'd she take it?

217
00:11:12,571 --> 00:11:14,436
I told her she was fat.

218
00:11:14,540 --> 00:11:15,802
No.

219
00:11:16,509 --> 00:11:18,306
I hate lying to Lois. It's just...

220
00:11:18,411 --> 00:11:20,504
It's the best way
to keep her from the truth.

221
00:11:20,613 --> 00:11:23,081
You have no choice.
Your unemployment will dry up soon.

222
00:11:23,182 --> 00:11:26,618
She'll probably sense something's amiss
when they repossess your house.

223
00:11:26,719 --> 00:11:28,949
You really oughta think
of your family's welfare.

224
00:11:29,055 --> 00:11:30,522
Jeez, Brian! That's a great idea!

225
00:11:32,725 --> 00:11:36,923
Okay, do you have any disabilities,
past injuries, physical anomalies?

226
00:11:37,697 --> 00:11:40,325
I didn't have gas
for the first time until I was 30.

227
00:11:44,837 --> 00:11:46,702
What the hell was that?

228
00:11:48,274 --> 00:11:51,607
Guys, our money problems
are over! We're officially on welfare.

229
00:11:51,711 --> 00:11:54,145
Come on, help me scatter car parts
on the front lawn.

230
00:11:54,246 --> 00:11:55,406
How much are we getting?

231
00:11:55,514 --> 00:11:57,778
Let's see. $150 a week.

232
00:11:58,284 --> 00:12:00,013
Wait. That's a comma, not a decimal.

233
00:12:02,154 --> 00:12:03,143
Whoops.

234
00:12:03,522 --> 00:12:05,786
No, I haven't seen Peter all afternoon.

235
00:12:05,891 --> 00:12:07,483
I was giving a piano lesson.

236
00:12:08,327 --> 00:12:10,557
Stewie, why don't you play
in the other room?

237
00:12:10,663 --> 00:12:11,994
Why don't you burn in hell?

238
00:12:12,798 --> 00:12:14,459
No dessert for you, young man.

239
00:12:15,034 --> 00:12:17,502
Who would've thought getting drunk
would get me...

240
00:12:17,603 --> 00:12:20,470
...$150,000 a week from the government?

241
00:12:20,606 --> 00:12:21,868
This is why I don't vote.

242
00:12:21,974 --> 00:12:24,238
Maybe somebody down there
was drinking, too.

243
00:12:24,677 --> 00:12:27,771
Mr. President, why do you think
the public supports you...

244
00:12:27,880 --> 00:12:29,575
...during these impeachment proceedings?

245
00:12:29,682 --> 00:12:31,149
Probably because you're so fat.

246
00:12:33,085 --> 00:12:34,882
Peter, you might want to call
the Welfare Commission.

247
00:12:34,987 --> 00:12:36,887
That check is obviously an oversight.

248
00:12:36,989 --> 00:12:40,516
Not necessarily. Maybe I'm like
their one millionth customer.

249
00:12:40,626 --> 00:12:42,685
What?
You're gonna spend $150,000 a week?

250
00:12:42,795 --> 00:12:44,854
- Yeah.
- On what?

251
00:12:45,431 --> 00:12:49,731
Oh, my God!
Peter, you bought the statue of David?

252
00:12:49,835 --> 00:12:52,326
No. I just rented it.
But they're gonna be ticked.

253
00:12:52,438 --> 00:12:55,066
The penis broke off
while I was loading it into the car.

254
00:12:58,144 --> 00:12:59,941
I shall call you "Eduardo. "

255
00:13:00,246 --> 00:13:01,941
Peter, how can we afford this?

256
00:13:02,047 --> 00:13:04,015
You won't believe it, Mom! Dad's getting...

257
00:13:04,116 --> 00:13:05,208
A big raise!

258
00:13:05,317 --> 00:13:06,978
Peter, that's wonderful!

259
00:13:07,086 --> 00:13:08,075
But, Dad, I thought...

260
00:13:08,187 --> 00:13:11,418
The kind of raise that'll allow me
to give my kids a big allowance...

261
00:13:11,524 --> 00:13:14,049
...just for keeping their big mouths shut.
Come on, guys.

262
00:13:14,160 --> 00:13:16,594
I'll buy us
the most expensive meal we've ever had.

263
00:13:17,696 --> 00:13:20,722
Yeah.
I'd like 6,000 chicken fa-ji-tas, please.

264
00:13:20,833 --> 00:13:21,800
I beg your pardon?

265
00:13:21,901 --> 00:13:23,892
6,000 chicken fa-ji-tas.

266
00:13:24,003 --> 00:13:25,800
And a "So-sage" McBiscuit, please.

267
00:13:27,706 --> 00:13:29,503
Peter, what's the big surprise?

268
00:13:29,608 --> 00:13:32,577
You know how I always said
you should be treated like a queen?

269
00:13:32,678 --> 00:13:34,578
I got you your own jester.

270
00:13:35,748 --> 00:13:37,477
Good to be here in New England.

271
00:13:37,583 --> 00:13:39,642
And what's the deal
with "New" England anyway?

272
00:13:39,752 --> 00:13:44,052
It's over 200 years old!
Last time I checked, that's not that new.

273
00:13:48,694 --> 00:13:49,661
This is great.

274
00:13:49,762 --> 00:13:53,391
I can finally afford to give my little girl
the lips she's always dreamed of.

275
00:13:53,499 --> 00:13:55,228
Thank you, Daddy!

276
00:13:56,702 --> 00:13:58,465
I don't know, Peter. Lips are one thing.

277
00:13:58,571 --> 00:14:01,335
But did you have to buy
breast implants for Chris?

278
00:14:01,440 --> 00:14:02,566
It makes him happy.

279
00:14:02,675 --> 00:14:04,404
These are cool.

280
00:14:08,013 --> 00:14:09,503
When did you get a pool?

281
00:14:09,615 --> 00:14:11,014
It's a moat.

282
00:14:11,116 --> 00:14:12,105
I know it's silly...

283
00:14:12,218 --> 00:14:15,654
...but my husband thinks our family
needs extra protection now that...

284
00:14:15,754 --> 00:14:17,119
...we're rich.

285
00:14:17,223 --> 00:14:18,247
Does it work?

286
00:14:18,357 --> 00:14:20,951
It does keep the Black Knight at bay.

287
00:14:25,197 --> 00:14:28,963
Congratulations in all your success.
Here's your welfare check.

288
00:14:29,468 --> 00:14:30,435
What the...

289
00:14:35,274 --> 00:14:36,639
Hi, honey.

290
00:14:38,611 --> 00:14:39,635
What?

291
00:14:39,745 --> 00:14:43,545
I know what I did was wrong.
But I only did it for you and the kids.

292
00:14:43,649 --> 00:14:46,516
Except for the jukebox in the bathroom.
That was for Peter.

293
00:14:46,619 --> 00:14:50,783
Yeah, from the American taxpayers.
I am so mad I can't see straight.

294
00:14:50,890 --> 00:14:52,881
No problem.
We got money to get that fixed...

295
00:14:52,992 --> 00:14:57,395
...with enough left for us to buy our way
out of any trouble our kids might get into.

296
00:14:57,496 --> 00:14:58,622
Just like the Kennedys.

297
00:14:58,731 --> 00:15:01,325
I feel like I don't
even know you anymore, Peter.

298
00:15:01,433 --> 00:15:04,266
The man I married would never think
he could fix a problem...

299
00:15:04,370 --> 00:15:05,894
...just by spending money!

300
00:15:07,172 --> 00:15:08,730
Boy, she's pretty pissed.

301
00:15:08,841 --> 00:15:11,173
Who thought fraud
would be one of her buttons?

302
00:15:11,277 --> 00:15:14,610
Why have a jukebox
in the john if your wife's mad at you?

303
00:15:14,713 --> 00:15:17,477
Peter, you may have to return
that money to the taxpayers.

304
00:15:17,583 --> 00:15:19,778
But I gotta make sure
Lois knows I'm doing it.

305
00:15:19,885 --> 00:15:21,716
I need an event with thousands of people.

306
00:15:21,820 --> 00:15:23,845
Something that everybody cares about.

307
00:15:25,291 --> 00:15:27,225
We might have to leave
Rhode Island for this.

308
00:15:27,793 --> 00:15:31,695
The air is electric here
at Super Bowl XXXllI tonight!

309
00:15:31,797 --> 00:15:34,732
Pat, it's safe to say that all
these fans came out here...

310
00:15:34,833 --> 00:15:36,824
...to watch a game of football!

311
00:15:36,936 --> 00:15:38,927
John, we're in commercial.

312
00:15:39,038 --> 00:15:42,735
Yeah, I know.
I'm just making conversation. Come on.

313
00:15:43,709 --> 00:15:44,869
Football!

314
00:15:47,313 --> 00:15:50,908
Amazing. You can barely drive a car.
Yet you were allowed to fly a blimp?

315
00:15:51,016 --> 00:15:53,678
Yeah, America's great, isn't it?
Except for the South.

316
00:15:53,786 --> 00:15:55,549
Boy, I hope Lois is watching.

317
00:15:55,654 --> 00:15:57,815
Okay, taxpayers, here you go!

318
00:15:59,658 --> 00:16:02,320
Looks like we're getting some rain
here tonight, John.

319
00:16:02,428 --> 00:16:05,886
Yeah. Hey, wait a second!
This is no ordinary rain!

320
00:16:06,198 --> 00:16:08,291
It's some kind of crazy money rain!

321
00:16:08,400 --> 00:16:11,801
I'm being told it's a man and his dog
throwing cash out of a blimp.

322
00:16:11,904 --> 00:16:15,670
Man. I hope this works. Otherwise,
I'm gonna have to start dropping these.

323
00:16:20,579 --> 00:16:23,707
The crowd is storming the field!
This is pandemonium!

324
00:16:23,816 --> 00:16:26,410
Have you ever seen anything like this, Pat?

325
00:16:27,553 --> 00:16:31,614
Just once. The 1975 Cotton Bowl.
This is the old "trying to make amends...

326
00:16:31,724 --> 00:16:35,524
"... for spending $150,000 a week
in misappropriated welfare funds" play.

327
00:16:35,627 --> 00:16:40,360
I don't care what it is! That guy's ruining
a perfectly good game of football!

328
00:16:40,499 --> 00:16:42,763
- Madden to Fox Security.
- Go ahead.

329
00:16:42,868 --> 00:16:44,665
Take them down!
Yes, sir.

330
00:16:53,846 --> 00:16:54,938
How was your shower?

331
00:16:55,047 --> 00:16:57,948
I tell you, all of the rumors
about dropping the soap are true.

332
00:16:58,050 --> 00:16:59,039
Really?

333
00:16:59,151 --> 00:17:01,346
You can't hold onto that thing
to save your life.

334
00:17:01,453 --> 00:17:03,717
It was slipping everywhere.
Guys were laughing.

335
00:17:03,822 --> 00:17:05,983
There's the guy
that couldn't hold the soap.

336
00:17:06,091 --> 00:17:07,718
That was classic.

337
00:17:08,360 --> 00:17:10,726
Boy. I really let Lois down this time.

338
00:17:10,829 --> 00:17:12,126
Do you think she'll wait for me?

339
00:17:12,231 --> 00:17:13,789
If every woman dumped her husband...

340
00:17:13,899 --> 00:17:16,595
...for crashing a blimp,
no one would be married.

341
00:17:16,702 --> 00:17:19,102
Yeah, you're right.
Okay, I got the top bunk.

342
00:17:22,074 --> 00:17:24,599
My collagen is wearing off.

343
00:17:24,710 --> 00:17:27,110
Honey, sagging lips are just nature's way...

344
00:17:27,212 --> 00:17:30,204
...of telling you you shouldn't
cover for your father's lie.

345
00:17:30,315 --> 00:17:33,512
What does it mean when your armpits
cry stinky tears?

346
00:17:33,619 --> 00:17:35,678
It means you're becoming a man.

347
00:17:35,788 --> 00:17:39,519
But hopefully not the kind who stays out
all day and doesn't call...

348
00:17:39,625 --> 00:17:42,150
...like your father
who shall remain nameless.

349
00:17:42,261 --> 00:17:45,094
Hello, Mother.
Hi there, sweetie.

350
00:17:45,197 --> 00:17:47,757
You know, Mother,
life is like a box of chocolates.

351
00:17:47,866 --> 00:17:50,130
You never know what you're going to get.

352
00:17:50,235 --> 00:17:52,897
Your life, however,
is more like a box of active grenades!

353
00:17:54,506 --> 00:17:57,475
Now, I offer one last chance
for deliverance.

354
00:17:57,576 --> 00:18:00,636
Return my mind-control device
or be destroyed.

355
00:18:01,447 --> 00:18:04,211
You just want your toy back.

356
00:18:04,316 --> 00:18:06,011
Okay, here you go, honey.

357
00:18:06,885 --> 00:18:09,080
Yes... Well, victory is mine!

358
00:18:13,225 --> 00:18:14,419
Damn you all!

359
00:18:16,128 --> 00:18:17,254
Hello?

360
00:18:18,063 --> 00:18:19,428
Oh, my God!

361
00:18:25,003 --> 00:18:26,903
Lois, am I glad to see you.

362
00:18:27,005 --> 00:18:28,870
I have nothing to say to you, Peter.

363
00:18:28,974 --> 00:18:31,101
I gave the money back.
Why are you still steamed?

364
00:18:31,210 --> 00:18:34,611
Peter, you lied to me,
you betrayed my trust.

365
00:18:34,713 --> 00:18:37,011
Compared to that,
welfare fraud doesn't even matter.

366
00:18:37,116 --> 00:18:40,085
Really?
Let's hope the judge feels that way.

367
00:18:41,220 --> 00:18:42,915
This court will come to order.

368
00:18:43,722 --> 00:18:46,190
I figured the sooner I cashed the check...

369
00:18:46,291 --> 00:18:49,055
...the sooner they'd catch their mistake.

370
00:18:49,428 --> 00:18:51,328
Why are we making a federal case
out of this?

371
00:18:51,430 --> 00:18:53,955
Don't you think you should
have alerted the government...

372
00:18:54,066 --> 00:18:55,363
...of such a gross overpayment?

373
00:18:55,467 --> 00:18:58,732
I was gonna call them.
But my favorite episode...

374
00:18:58,837 --> 00:19:01,863
...of Different Strokes was on.
The one where Arnold and Dudley...

375
00:19:01,974 --> 00:19:04,306
...get sexually molested
by the bike shop owner?

376
00:19:04,776 --> 00:19:07,609
All right. Now I want you boys
to scream real loud at my ass.

377
00:19:07,980 --> 00:19:10,414
And everybody learns a valuable lesson.

378
00:19:10,516 --> 00:19:12,211
Mr. Griffin, have you learned a lesson?

379
00:19:12,317 --> 00:19:14,842
Yes. Stay the hell away
from that bike shop.

380
00:19:16,989 --> 00:19:20,550
Okay, everybody, I feel really bad
about what I did. I just...

381
00:19:20,659 --> 00:19:22,183
I don't know. I saw the one chance...

382
00:19:22,294 --> 00:19:25,491
...I'd ever have to give my family
the things they deserve.

383
00:19:25,597 --> 00:19:27,827
I guess I screwed it up.
I cheated the government.

384
00:19:27,933 --> 00:19:30,424
And worst of all, I lied to my wife.

385
00:19:30,836 --> 00:19:32,463
And she deserves better.

386
00:19:32,571 --> 00:19:34,004
I'm sorry, honey.

387
00:19:34,106 --> 00:19:37,041
Mr. Griffin, I think your words
have touched us all.

388
00:19:37,142 --> 00:19:39,269
I'm sentencing you to 24 months in prison.

389
00:19:39,611 --> 00:19:40,600
No!

390
00:19:40,712 --> 00:19:41,770
- No!
- No!

391
00:19:41,880 --> 00:19:42,778
No!

392
00:19:42,881 --> 00:19:43,848
Yeah!

393
00:19:50,522 --> 00:19:52,717
Excuse me, Your Honor?
Yes?

394
00:19:52,824 --> 00:19:56,157
Look, my husband may be
a bit thoughtless at times.

395
00:19:56,261 --> 00:19:59,753
He may even be downright stupid.

396
00:19:59,865 --> 00:20:02,197
But I know he only accepted that money...

397
00:20:02,301 --> 00:20:05,202
...because he wanted to be
a good husband and father.

398
00:20:05,737 --> 00:20:08,365
But what he needs to remember
is that we love him.

399
00:20:08,473 --> 00:20:11,374
And no matter what,
I'll always stand by him.

400
00:20:11,476 --> 00:20:13,307
I love you too, honey.

401
00:20:13,478 --> 00:20:17,380
That was very moving, Mrs. Griffin.
Okay, you can go to jail with him!

402
00:20:17,482 --> 00:20:18,449
What?

403
00:20:18,550 --> 00:20:22,577
24 months in prison? Unacceptable!
Intolerable as it may be...

404
00:20:22,688 --> 00:20:25,987
...I'm completely dependent upon
those wretched drones for sustenance.

405
00:20:26,091 --> 00:20:29,151
Let us see how the constitution
of American justice fares...

406
00:20:29,261 --> 00:20:31,092
...against the device!

407
00:20:40,839 --> 00:20:42,101
Is that your boy?

408
00:20:42,207 --> 00:20:44,038
What? Yeah. That's Stewie.

409
00:20:44,142 --> 00:20:48,977
Gosh. I can't separate a kid that young
from his father. It's unjudgmenly.

410
00:20:49,081 --> 00:20:51,208
- Hell, you've learned your lesson, right?
- Yeah.

411
00:20:51,316 --> 00:20:54,376
- All right. You're free.
- Wow! Can you give me my job back?

412
00:20:54,486 --> 00:20:55,475
No.

413
00:20:56,121 --> 00:20:57,884
- Yes.
- All right!

414
00:21:02,327 --> 00:21:03,885
That was a crazy one, Dick.

415
00:21:03,996 --> 00:21:07,159
It sure was. In this next blooper
from Joanie Loves Chachi...

416
00:21:07,266 --> 00:21:09,564
...watch what happens when Scott Baio
tries to say:

417
00:21:09,668 --> 00:21:11,761
"She sells seashells
down by the seashore. "

418
00:21:11,870 --> 00:21:13,269
What does your mom do?

419
00:21:13,372 --> 00:21:14,862
She sells seashells down by the...

420
00:21:16,842 --> 00:21:18,366
That is kind of a tongue twister.

421
00:21:18,477 --> 00:21:20,536
It's good to have you home, Peter.

422
00:21:20,646 --> 00:21:22,944
Honey, I knew everything
would turn out okay.

423
00:21:23,048 --> 00:21:24,481
I sure am gonna miss being rich.

424
00:21:24,583 --> 00:21:26,551
Don't worry.
I got a way to get money.

425
00:21:26,652 --> 00:21:28,176
Not another welfare scam?

426
00:21:28,287 --> 00:21:30,448
No. Minority scholarship.

427
00:21:37,596 --> 00:21:39,826
No.
Are you insane?

428
00:21:39,931 --> 00:21:42,695
Okay, I mean sexual harassment suit.

429
00:21:43,869 --> 00:21:45,131
No.
Don't think so.

430
00:21:45,237 --> 00:21:46,465
Absolutely outrageous.

431
00:21:46,571 --> 00:21:48,004
Okay, disability claim.

5 ways to ask questions like a native speaker

0:00Hi, everyone. I'm Jade. Today, I want to talk to you about native speaker questions, how
0:06native ask questions. I'm sure you already know how to ask questions in English. That's
0:14just basic stuff. That's baby stuff. But do you know the different phrases that native
0:21speakers use to ask questions and the slightly different grammar? Maybe you don't. Maybe
0:27you don't already know that. That's why I made today's video. So they watching, and
0:32I'm going to explain all about that, how to ask questions like a native speaker.
0:40First things first. You have to learn the question phrases that native speakers will
0:49use when they're asking a question. Here they are. "Could you tell me?" "I wonder." "I wanted
0:55to know." "Do you know?" And "Who knows?" So what you do is you take one of these phrases.
1:05Then, you put the normal question that you're going to ask, but you have to change the order
1:13of the grammar slightly. So here are some examples. Just baby English sentences. You
1:19already know how to make questions like this. Here's the question word. In the middle is
1:25the verb, and in the last position is the object. "Where is he?" "Who is that?" "What
1:32are they?" "When is it?" So what do we do then? Do we just use the
1:37phrase and put this there? No. No, no. That would be too easy. So what we do is we need
1:48to swap. And I'm sorry this is the same colour. It would be really helpful to change the colour
1:55here. So we swap the position of the verb and the object. We have to swap the position
2:04-- excuse me while I put the pen down. And I'm going to put it back here. "Could you
2:10tell me where he is?" Feels a little bit weird at first saying that, doesn't it? Because
2:18it goes against the structure that you're used to. "I wonder who that is. I wonder who
2:25that is." "I wanted to know what they are." "Do you know when it is?" That's part one.
2:38Unfortunately, not all questions are as simple as baby questions when speaking English. Something
2:44that causes quite a bit of confusion is questions in the present and past simple because these
2:52questions are the ones with the "do, did, does" also in the question.
2:59So what we want to know now is how do we fit a question that's the present or the past
3:06simple such as, "When does the lesson start?" This is the present simple form. "When did
3:15they do it?" That's the past simple question form. And "What do you do?" That's the present
3:20simple form again. How do we take these sentences and fit them with our phrases for asking questions?
3:31Well, it's actually not that hard because you can take out the "does, did, do". You
3:41have to forget about them. You don't need them. So in one sense, it makes it easier.
3:45But you do sometimes have to pay attention to the verb conjugation. So let's have a look.
3:53"Could you tell" -- oh, I need to -- what am I doing? I need to show you that we're
3:57removing those. Also in the blue pen. I'm sorry about the blue pen. I don't have any
4:04other pens at the moment. "Could you tell me when the lesson start." You can't say that.
4:13"Could you tell me when the lesson start." This is what I mean about verb conjugation.
4:18You have to say "when the lesson starts". Back to the pen, and it's going to be a very
4:25small S because there's no space. Why am I making so many excuses today? It's a blue
4:31pen. That's what you're getting. So here you go. "I wonder how they do it." This one is
4:41the present simple. We can keep it like that if we're still talking about the present simple.
4:48If we want to talk about the past, we can say, "I wonder how they did it."
4:53The next example, "I wanted to know what do you do?" This is fine, also. Let's move this
5:01down for the other examples. So when the question phrase has "you" in it, as subject, you might
5:09need to change the rest of the question. "Do you know how they do it?" Well, not for that
5:18one. "Do you know when the lesson starts?" That's another example. The same way that
5:24we needed to change this with the S because of "you" here, we need to change here also.
5:32"Do you know when the lesson starts?" And let's do one more example, "Who knows
5:42what you do?" That would almost be rude. Now, we're ready to go to the final stage
5:47of asking questions like a native speaker. What you do is you take one of the phrases,
5:53and then you use "if" or "whether". It's in orange. Can you squint to see it? "If" or
6:02"whether". And then, we take a question, but these questions are different because there
6:08is no question word like "what", "when", "why", "how". We don't have those question words.
6:17And we don't have "did", "does", "do". We don't have those question words either.
6:23Here are some examples. "Is it expensive?" "Have they got a car?" And "Can I have a cake?"
6:32So then, we put all the pieces together using "if" or "whether". "If" or "whether" basically
6:40mean the same thing. "Whether" is a little bit more British English, I would say, or
6:46possibly more British English, plus more formal. "Could you tell me whether it is expensive?"
6:55Ah-ha! Ah-ha! So we have to swap again. We have to swap the position of the verb. So
7:06notice how the position of "is" has changed. It's not at the beginning of the question
7:13anymore over here. "Could you tell me whether it is expensive?" "I wonder if they have got
7:25a car." "I wanted to know whether I can have a cake." Let's do two more. "Do you know if
7:38it is expensive?" "Who knows if they have a car."
7:49Asking questions like a native speaker. You need to practise it a bit because your mind
7:59is used to saying the sentence structure in a fixed way. So it's a little bit tricky to
8:06do at first. But with practice and patience, you can ask questions like a native speaker.
8:13Thank you so much for watching today. I want to invite you please, invite you, encourage
8:20you, love you -- love you? I would love you. I would love you to come and join my mailing
8:30list. I have a growing family of people on my mailing list. And I'm in touch a couple
8:35of times a week with my personal coaching emails. So I write to you about something
8:42motivational, or I share something with you. So why not join me like all the other people?
8:48I would appreciate it so much. Come back again soon to my channel where I have videos about
8:54English, communication, introvert things -- all things, really, on my channel. So until next
9:03time, see you. Bye-bye.

Hacking Language Learning

a big part of why I work
0:10with endangered languages is because I myself am a descendant
0:13love a speech community that even today is struggling to survive
0:17look at the name over there you can probably guess which one it is
0:20but for many of my friends
0:23language loss is much more immediate much more intense
0:26for them its loss over trunk of their sovereignty
0:30to connection to their past a connection to their cultural wealth of
0:35a grounding in their history now my work
0:39I've seen time and time again just how much
0:43have wrenching it can be for parents and child
0:47a grandparent and grandchild to become disconnected in a way that goes
0:51far beyond any kind of national generation gap but even if you care
0:57even if you sympathize you may think well
1:01endangered languages to start with saving because you probably think
1:04they'll cost a fair bit
1:06share much fair bit too safe not just
1:10money but also time and energy and attention and these are things that are
1:13all in short supply these days
1:15and especially so for a lot of these very same community switchers often
1:18faced with
1:19even more immediate even more material challenges but what if it cost
1:24next to nothing next to nothing to learn a new language
1:28what if we could radically reduce linguistic entry costs
1:31well then the arguments against sustaining linguistic diversity
1:35would not sounds a reasonable because all of us could
1:39easily jump from language to language sister show respect to our host or guest
1:44or to enjoy the expressive capacities that this particular language allows us
1:47or simply because between you and me this language is the one that feels the
1:52most like home
1:53so the obvious question is how long does it take to learn a new language
1:57not perfectly not you know without a single tear
2:01i not even flew me but just enough to get your foot in the door enough to get
2:04started enough to get going to join that speech community
2:07and departed well in my experience
2:10it's about a week or so and
2:13you know I was just as shocked as you discover this in the summer I've
2:18June I and summer of 2003 after just 10 days in Bulgaria with my new in-laws
2:23I was able to talk well enough to translate for my sister when she came
2:26and in the same thing happen again the next summer I went to the Czech Republic
2:30for my cousin's wedding
2:31showed up about a week early and by the time the wedding rolled around as just
2:34chatting away with all my new check relatives
2:36I wasn't fluent and I wasn't flawless but I was effective
2:41now real fluency in my experience does take a long time
2:45does take hanging out with the speech community but still
2:48just one week and change to get a foot in the door
2:53to be able to party with the checks to be able to hang on Bulgarian cafes in
2:56order french fries with aplomb
2:58that seem like an idea worth sharing
3:01now of course I'm a train field linguists you probably think will your
3:05self-selected you've got experience you've got talent right
3:08but when I do it it doesn't feel
3:12hola talent not much like experience either all it feels like it's a really
3:16clear sense
3:17have what to do how to handle vocabulary pronunciation grammar and more than
3:22anything else
3:23how to make it through any conversation and this
3:28this is what I think we're missing when we struggle with language is when we
3:32fail to learn languages
3:33we'll get our languages we don't get tight
3:37how to learn languages and that's what I've been working on for quite some time
3:40it now
3:40how to translate experience the skill set up a train feeling listen to form
3:45the
3:45anybody any %uh view can pick up quickly and used to become
3:49active learners confident learners to can step right out into the street the
3:53scary Street
3:54love realize language you a real-life language
3:57use with very little fear if we can do this
4:02and it doesn't just change how you and me learn languages
4:05but it also has the potential to radically reshape how
4:10linguistic majorities and linguistic minorities can live and work together in
4:13the same world
4:15because now separate linguistic traditions are no longer communicative
4:18obstacles
4:19but actually resources social cultural
4:23intellectual even emotional resources that we can all
4:27share and enjoy together sup
4:30how we do it how we get that foot in the door at least that foot in the door well
4:33first and foremost
4:34what we need to understand is our own psychology we need to understand that
4:37it's the social and emotional aspects of language learning
4:41that decide everything company for start online which it's humiliating
4:44it's embarrassing it's frustrating
4:47so excuse you guys are rushing out the door to learn language
4:51but this is because as adults as teenagers we measure ourselves and how
4:55well we can present ourselves with our words
4:57in a new language we lose their control and women screaming away from that
5:01we dodge conversations we hide in the linguistic sidelines we do anything to
5:05avoid a simple face to face conversation
5:08which is the one thing the only thing that's going to make us better and
5:11English speakers in today's world
5:12the world is very accommodating if that make it very easy for us to you
5:17indulge in a in states just bailout when we get linguistic stage fright
5:22so what we do well the short answer is we learned to check
5:26our shame at the door we learn to embrace this loss of control
5:30enjoy the fact that we've been or less involuntarily
5:33given a second childhood in any language
5:36right so
5:40if we can do this if we can do this then
5:43we have learned to shift our job we frame our
5:46reformer job to you not from
5:49trying to seek out perfection not making any mistakes but instead
5:53just learning to cope well and
5:56the best place to learn linguistic coping skills
6:00is through simply learning how to you
6:04improvise learning how to use description:
6:07metaphor analogy to work around the words that we don't know
6:10so for example if I ate on has a tiger in your language
6:14I'll say the thing it's like a cat with big
6:17and orange and the one behind you looks a little bit hungry
6:23it's these clunky but effective descriptions that actually get us
6:26through
6:27that actually get us through any conversation and
6:30when we learn to congratulate ourselves on them when we realize that
6:34how this person actually understood what I said
6:37then we feel good about ourselves and we find
6:41they understood I said and now even better the time he had to say it right
6:45that's a language lesson that we will never ever forget
6:48never so I am there's actually a second lesson inside this which is that
6:53language is not all on you when you when I speak together
6:57we make meaning together so learning to cope well in another language
7:01is as much if not more about learning to lean on the other person's
7:05full and complete knowledge of the language and even more on their
7:08willingness
7:09to help you make this conversation happen
7:12so again if we learn to re free Marjah
7:16re Famer task reformer job as
7:20as being effective not perfect
7:24that every conversation stops being this potentials minefield I've
7:28in embarrassing mistakes and errors instead is an exciting place first come
7:32back to every time
7:33because you get to be your own MacGyver you get to rummage around in linguistic
7:36packets and pull a toothbrush
7:38a button and a paperclip and couple that all together and somehow
7:42poll of the communicative job right
7:45when you feel that three love being a linguistic euro time and time again you
7:49come back to conversations you seek them out
7:51you want to be there and when you n when you approach the task like that
7:56will pretty soon you find yourself fairly close to fluid so that's how we
7:59cope with
8:00linguistic with linguistic stage fright with linguistic performance anxiety
8:05which is 90 percent of what holds us back the only thing left
8:09is of course the language all the pronunciation
8:12all the grammar all the vocabulary it's really intimidating
8:15but mostly because we're all trying to juggle it all at once we've got no way
8:18to organize it no way to prioritize it
8:22there is a way what we need is a simple
8:25practical understanding if the design features of language
8:30so let me give you just a brief taste that I am
8:33take pronunciation anybody can learn to pronounce
8:36any sound in any language bro anyone to view I love you
8:40if you don't believe me it's probably because you've heard the following
8:42freeze listen
8:43and repeat after me that doesn't work it doesn't work
8:47what does work is learning the clear and simple setup instructions for how to
8:51move your mouse to make that weird sound
8:53after that we need is a little bit exercise to work your mouth for that
8:56orel choreography
8:58and very soon you find that your muscles limber up in with seemed
9:01unfamiliar unpronounceable unreachable even becomes a must as familiar
9:06as every other send you putting your whole life so you don't need any special
9:09talent you don't need any special
9:11on any special here for language you just don't
9:15even more importantly is have been
9:18is rhythm and melody when you go after the distinct cadence of language
9:23when you try to internalize that you didn't lyndon that that particular
9:26language is
9:27uses than and use that as the foundation of your own finance issue
9:30well then it turns out that your own words come out fluently
9:36they flow in at cadence the cadence is the current the Carrizo you words
9:39even better when you have the kids internalize and you're waiting for
9:42expecting it
9:43and suddenly something was miraculous happens which is that you an
9:47native speaker speech certainly doesn't seem so fast because it's that prism and
9:51that melody
9:51that actually tells you where the words begin and
9:55that's pretty Asian without primer members terrifying right
10:00it's only because we teach grammar as a million little disconnected
10:03are retracing rules when in fact grammer's are tiny little ecosystem
10:06every little part fits and every little part
10:08and if you look at those ecosystems from the top we can see a very hopeful
10:11simplicity
10:12which is that I love those rules fall down on one side or the other
10:16what we do when we talk which is we mentioned general concepts
10:20things like cat and dog events Lake
10:23bite and chase right and then we tie them into
10:27the specifics at this conversation my cat your dog
10:30it bit me in yesterday's passed its
10:34turns up all grammatical rules actually fall somewhere along the line between
10:37the general conceptual
10:39any conversation specific and want to play around with this idea for a while
10:42grammatical rules become extremely easy to remember because now you know
10:46where they live in the neighborhood and what the relationship started their
10:48neighbors
10:49after that the only thing that's left is vocabulary
10:53vocabulary dictionaries for love all the words you don't know yet
10:56it turns out we don't actually need to know that much for capital because we
11:00have are coping skills we can talk around the words that we don't know
11:03we can list from context work out a lot of new words we're hearing
11:08and when all else fails now we know we have a license to simply ask for help
11:13so what words do we actually need to learn first
11:18the short words the small words the little linking words
11:21thing is one of them a the words like
11:25and or but love to who what when where and why
11:28because these will get you the most expressive bang for your buck
11:31these are the these are the words that will save you when you needed the
11:35conversation
11:36you know exactly what you want to say then boom it this far because you
11:39realize you have not learned
11:40the word almost
11:44when you focus on those words from the get-go that you find you have the frame
11:47the outlines have language up and running
11:49and then there's only one thing left the rest of the language
11:53and there's a trick for this is a check for this and to prioritize the restive a
11:57cafe get what you need first
11:59you can start with the egocentric experience the body you say okay my eyes
12:03they see
12:05they see in a look here's the missing in the here my hands to pick up and put
12:08down
12:09my mind it it knows it feels it loves it understands when it tries to learn
12:14language sometimes it remembers and sometimes it forgets
12:18when you get these words the score verbs interaction
12:21an experience and tied them together with all those little words this little
12:24linking words
12:25if a very small said a vocabulary that you actually know but it happens to be
12:28precisely the setup expressive tools
12:30that you need to make your way through any conversation
12:34so I hope that I have commits to you
12:38that this is just this is not just for linguists
12:41anybody can learn a language anybody can get that foot in the door
12:44which is the part that really matters I'm
12:47you can do it here right now
12:50on all it really takes all really takes
12:54is a somewhat better sense of where r motions are at
12:58where our heart is at me go to learn language and also some a better sense
13:02how language actually does fit into our minds
13:06and if this is possible and it means that joining in his speech community
13:10is much easier than you think and that can take a lot of the pressure of people
13:13who have been told
13:14you need to abandon your small language in favor I'll
13:17in favor of this big large language
13:21but there's more every language that I have ever learned
13:24every language that even started to learn has radically reshaped
13:30how I look at the world how I deal with people
13:33how I think and that's lovely but even more important than that
13:37are the people that I've met in the ways that have been able to meet them
13:41because I've learning a language they changed my life
13:44in more ways than I can even begin to describe here
13:48now up till now the kind of opportunities only been available to
13:51train linguists and
13:52the occasional genius servant polyglot
13:56but now now we all have been its
13:59and so there's nothing more I can say except go for it
14:03good luck

Hackschooling makes me happy

When you're a kid,
0:18you get asked this one particular question a lot.
0:21It really gets kind of annoying.
0:23"What do you want to be when you grow up?"
0:26Now, adults are hoping for answers like
0:29"I want to be an Astronaut" or
0:30"I want to be a Neurosurgeon".
0:33You adults and your imaginations. (Laughter)
0:36Kids,
0:37they are more likely to answer with pro skateboarder
0:39surfer or Minecraft player.
0:42I asked my little brother, and he said,
0:44"Seriously dude, I'm 10, I have no idea,
0:46probably a pro skier.
0:48Let's go get some ice cream!"
0:49(Laughter)
0:50See, us kids are going to answer
0:52with something we're stoked on
0:54What we think is cool.
0:55What we have experience with,
0:57and that's typically the opposite of what adults want to hear.
1:01But if you ask a little kid,
1:02sometimes you'll get the best answer,
1:05something so simple, so obvious,
1:07and really profound.
1:10"When I grow up, I want to be happy".
1:13For me, when I grow up,
1:14I want to continue to be happy
1:16like I am now.
1:17I'm stoked to be here at TEDx,
1:19I've been watching TED videos
1:20for as long as I can remember.
1:22But I never thought I'd make it on stage here so soon.
1:25I mean, I just became a teenager,
1:26and like most teenage boys,
1:28I spend most of my time wondering:
1:30"How did my room get so messy all on its own?" (Laughter)
1:33Did I take a shower today? (Laughter)
1:35And the most perplexing of all,
1:37How do I get girls to like me? (Laughter)
1:41Neuroscientists say that the teenage brain is pretty weird.
1:44Our prefrontal cortex is underdeveloped,
1:46but we actually have more neurons than adults.
1:48Which is why we can be so creative, and impulsive, and moody,
1:52and get bummed out.
1:55But what bums me out is to know that
1:57a lot of kids today are just wishing to be happy,
2:01to be healthy, to be safe, not bullied,
2:03and be loved for who they are.
2:05So it seems to me when adults say,
2:08"What do you want to be when you grow up?"
2:10They just assume that you'll automatically be happy and healthy.
2:14But maybe that's not the case.
2:16Go to school. Go to college. Get a job.
2:18Get married. Boom!
2:20Then you'll be happy, right?
2:22We don't seem to make learning how to be happy and healthy
2:25a priority in our schools.
2:26It's separated from schools,
2:28and for some kids, it doesn't exist at all.
2:31But what if we didn't make it separate?
2:33What if we based education on the study
2:35and practice of being happy and healthy?
2:37Because that's what it is, a practice.
2:40And a simple practice like that.
2:43Education is important,
2:45but why is being happy and healthy
2:46not considered education?
2:48I just don't get it.
2:51I've been studying the science of being happy and healthy.
2:54It really comes down to practicing these 8 things:
2:57Exercise, diet and nutrition,
2:59time in nature, contribution and service to others,
3:02relationships, recreation,
3:04relaxation and stress management,
3:07and religious or spiritual involvement.
3:09Yes, I got that one. (Laugther)
3:11So these 8 things come from Dr. Roger Walsh.
3:15He calls them "Therapeutic Lifestyle Changes"
3:17or TLCs for short,
3:19He's a scientist that studies how to be happy and healthy.
3:22In researching this talk,
3:24I got a chance to ask him a few questions like:
3:26"Do you think better schools today are making these 8 TLCs a priority?"
3:30His response was no surprise.
3:32It was essentially "No".
3:34But he did say
3:35that many people do try to get this kind of education
3:38outside of the traditional arena
3:40through reading or practices such as meditation or yoga.
3:44But what I thought was his best response
3:46was that much of education is oriented,
3:48for better or worse,
3:50towards making a living rather than making a life.
3:55In 2006, Sir Ken Robinson gave
3:57the most popular TED talk of all time,
4:00"Schools Kill Creativity."
4:02His message is that creativity is as important as literacy,
4:06and we should treat it with the same status.
4:09A lot of parents watched those videos,
4:11some of those parents like mine counted it as one of the reasons
4:13they felt confident to pull their kids from traditional school,
4:16to try something different.
4:19I realize that I am part of this small but growing revolution of kids
4:22who are going about their education differently.
4:24And you know what? It freaks a lot of people out.
4:28Even though I was only 9
4:30when my parents pulled me out of the school system,
4:32I can still remember my mom being in tears
4:34when some of her friends told her she was crazy, and it was a stupid idea.
4:37Looking back, I'm thankful she didn't cave to peer pressure,
4:41and I think she is too.
4:43So out of the 200 million people
4:48that have watched Sir Ken Robinson's talk,
4:50why aren't there more kids like me out there?
4:55Shane McConkey is my hero.
4:57I loved him because he was the world's best skier.
4:59But then one day I realized what I really loved about Shane.
5:03He was a hacker.
5:04Not a computer hacker,
5:06he hacked skiing.
5:07His creativity and inventions made skiing what it is today,
5:11and why I love to ski.
5:14A lot of people think of hackers as geeky computer nerds
5:17who live in their parent's basement, and spread computer viruses.
5:20But, I don't see it that way.
5:22Hackers are innovators.
5:24Hackers are people who challenge and change the systems
5:27to make them work differently, to make them work better.
5:30It's just how they think, it's a mindset.
5:33I'm growing up in a world
5:35that needs more people with the hacker mindset,
5:37and not just for technology.
5:39Everything is up for being hacked, even skiing,
5:42even education.
5:45So whether it's Steve Jobs,
5:47Mark Zuckerberg or Shane McConkey,
5:49having the hacker mindset can change the world.
5:54Healthy, happy, creativity,
5:56and the hacker mindset are all a large part of my education.
5:59I call it "Hack-Schooling".
6:01I don't use any one particular curriculum,
6:03and I'm not dedicated to anyone's particular approach.
6:06I hack my education.
6:09I take advantage of opportunities in my community,
6:11and through a network of my friends and family.
6:14I take advantage of opportunities to experience what I'm learning.
6:17And I'm not afraid to look for shortcuts
6:19or hacks to get a better, faster result.
6:23It's like a remix or a mashup of learning.
6:27It's flexible, opportunistic,
6:29and it never loses sight of making happy,
6:31healthy and creativity a priority.
6:34And here's the cool part because it's a mindset
6:37not a system.
6:39Hack-schooling can be used by anyone even traditional schools,
6:45So, what does my school look like?
6:47Well it looks like Starbucks a lot of the time. (Laughter)
6:50But, like most kids,
6:52I study a lot of math, science, history, and writing.
6:56I didn't used to like to write
6:58because my teachers made me write about butterflies and rainbows.
7:01And I wanted to write about skiing.
7:04It was a relief when my good friend's mom
7:06started The Squaw Valley Kids Institute
7:08Where I got to write through my experiences and my interests
7:12while connecting with great speakers from around the nation
7:15and that sparked my love of writing.
7:18I realize that
7:20once you're motivated to learn something,
7:23you can get a lot done in a short amount of time
7:25and on your own.
7:27Starbucks is pretty great for that.
7:30Hacking physics was fun.
7:32We learned all about Newton and Galileo,
7:35and we experienced some basic physics concepts like
7:38kinetic energy though experimenting and making mistakes.
7:41My favorite was the giant Newton's cradle that we made out of bocci balls.
7:47We experimented with a lot of other things like bowling balls
7:50and even giant jawbreakers.
7:54Project Discovery's Ropes Course is awesome
7:57and slightly stressful.
7:59When you're 60 feet off the ground,
8:01you have to learn how to handle your fears,
8:03communicate clearly and most importantly, trust each other.
8:08Community organizations play a big part in my education.
8:11A High Fives Foundations Basics Program:
8:14"Being Aware and Safe in Critical Situations"
8:18We spent a day with the Squaw Valley ski patrol
8:20to learn more about mountain safety.
8:21The next day we switched to the science of snow,
8:24weather, and avalanches.
8:26But most importantly,
8:27we learned that making bad decision puts you
8:29and your friends at risk.
8:32Young Shu-Tak Woo brings history to life.
8:35You study a famous character in history,
8:37so you can stand on stage and perform as that character.
8:40and answer any question about their lifetime.
8:44In this photo,
8:45you see Al Capone and Bob Marley
8:47getting grilled with questions
8:49at the historical Piper's Opera House in Virginia City.
8:52The same stage where Harry Houdini got his start.
8:57Time in nature is really important to me.
8:59It's calm, quiet, and I get to just log out of reality.
9:04I spend one day a week outside all day.
9:07At my Foxwalker classes,
9:09our goal is to be able to survive in the wilderness with just a knife.
9:12We learn to listen to nature, we learn to sense our surroundings,
9:16and I've gained a spiritual connection to nature
9:19that I never knew existed.
9:21But the best part is that we get to make spears,
9:23bows and arrows, fires with just a bow drill,
9:26and survival shelters for the snowy nights when we camp out.
9:31Hanging out at The Moment Factory
9:33where they hand make skis and design clothes,
9:35has really inspired me to one day have my own business.
9:38the guys at the factory have showed me why I need to be good at math,
9:42be creative and get good at sewing.
9:45So I got an internship at Big Short Brand
9:48to get better at design and sewing.
9:50Between fetching lunch, scrubbing toilets,
9:53and breaking their vacuum cleaner,
9:54I'm getting to contribute to clothing design,
9:56customizing hats, and selling them.
9:59The people who work there are happy, healthy, creative
10:02and stocked to be doing what they're doing.
10:04This is by far, my favorite class.
10:08So, this is where I'm really happy,
10:10powder days.
10:12And it's a good metaphor for my life,
10:14my education,
10:16my Hack-schooling.
10:17If everyone skied this mountain
10:19like most people think of education,
10:21everyone would be skiing the same line,
10:23probably the safest,
10:24and most of the "powder" would go untouched.
10:27I look at this and see a thousand possibilites.
10:30Dropping the cornice, shredding the spine,
10:32looking for a [unclear] from cliff to cliff.
10:35Skiing to me is freedom, and so it's my education.
10:39It's about being creative, doing things differently.
10:42it's about community, and helping each other,
10:44it's about being happy and healthy
10:46among my very best friends.
10:49So I'm starting to think I know
10:51what I might want to do when I grow up.
10:53But if you ask me what do I want to be when I grow up,
10:56I'll always know that I want to be happy.
10:59Thank you. (Applause)

Ancient DNA -- What It Is and What It Could Be

i'ma
0:05molecular paleontologist some sophisticated
0:09actually I just made it up I spend most my time
0:12in the lab or in front of a computer but during the summer
0:15I prefer to spend my days and nights in the far north
0:19where I divide my time between waging war against mosquitoes
0:23and searching for the remains have Ice Age animals
0:26which I bring back to the lab to extract their ancient DNA
0:29as an early career scientist I was interested in ancient DNA for three
0:34reasons:
0:34first it was an opportunity to combine my interests in paleontology geology and
0:40molecular evolution
0:41I could get DNA from fossils and use this to watch species evolve
0:46through time second it was a brand new field
0:49absolutely bursting with enthusiasm and excitement
0:53a career in ancient DNA promise to be different definitely cool and
0:57hopefully useful and a third I'd really wanted to go to the Arctic
1:01so what about the Arctic is so good for DNA
1:05well it is the best place for the long-term preservation have DNA
1:09and the reason why is quite straightforward it's called
1:12and it's been called consistently for at least the last million years
1:16this period was characterized by dramatic shifts between very cold
1:20glacial intervals
1:21and much warmer interglacial periods like the one we're in today
1:24during the glacial periods or ice ages the I
1:28the sea level was a lot lower than it is today because much to the planet's water
1:31was taken up into the glaciers forming on
1:33the confidence the lower sea level exposed a massive lands that connected
1:37at the Asian and North American continents
1:39this land mass was called the India and it's where I do much of my work
1:43now crucially brings your was not glaciated
1:46during the last ice age instead it was a rich tundra grassland
1:50that was home to an equally rich diversity have ice age: plants and
1:54animals
1:54today most to the species are extinct but their bones and other hard bits
1:59tusks
1:59teeth hair sometimes even for monies survive frozen to the ground
2:03called permafrost we look for frozen bones wherever the permafrost is melting
2:09along river beds around lakes and active gold mining sites such as this one in
2:13Canada's Yukon Territory
2:14all the gold miners wash away the permafrost to get to the gold
2:18there and gravels beneath thousands have bones are unearthed
2:21over the last decades I and colleagues from around the world have extracted DNA
2:26from
2:26tens of thousands of these bounds and use them to better understand
2:30how Ice Age animals were affected by climate change in particular the last
2:35ice age
2:36we've learned for example that bison horses and ma'am it's really liked it
2:40when I was cold
2:41this is when their populations with the biggest genetic diversity
2:44the most part as a got warmer many these populations order to decline and
2:49eventually went extinct
2:50we watched brown bears during the last ice age disperse out of alaska across
2:54Asia and into europe
2:56presumably chasing after these growing populations over before us
2:59we've asked questions such as why do some species including
3:03the the cave lion go extinct while others
3:06but the caribou continue to thrive today and today we find ourselves in the
3:11middle at the gym Nomex revolution
3:13once again with growing enthusiasm to push this a little bit further
3:16we find ourselves more and more frequently being asked and asking each
3:20other
3:20can we sequence a complete genome of an extinct animal and
3:23dare we say it actually bring one back to life to answer this let me first
3:29recap very quickly when I'm going to call the seven that they describe a
3:33deeply oversimplified steps
3:35to bringing an extinct species back to life first you have to sequence the
3:38genome
3:39and somewhere in there are the jeans from its these ABC's geez antes
3:43the genes that code for the proteins that make the cells are the body's the
3:46behaviors have the things we're trying to bring back
3:48then we have to get these genomes on the chromosomes because chromosomes are the
3:53way that genetic material
3:54is carried in the cells then we have to get the chromosomes into the nucleus
3:58and the nucleus into the cell so they can start to divide and then we have to
4:01get the cell
4:03at the embryo into a surrogate mother
4:06so that it can actually grow up and develop and become something and
4:08presumably
4:09her genome isn't going to have too much to say about this developmental process
4:14and then she's got to take this developing embryo and fetus actually
4:17two-term
4:18in this case this is also not simple there's a
4:21very large size difference between the much larger mammoth
4:25and smaller elephants and it's not known whether it will actually be
4:28physically possible for female elephant to carry a baby mammoth two-term
4:33without disaster but assuming disaster is a burden the mammoth can be bored and
4:38learn how to be a mammoth we then have to find a place for to live
4:41so can go about doing mammoth the stuff and eventually make more mammoth
4:45pretty straightforward k so easy might be an exaggeration
4:50or an outright lie but let's not get caught and semantics a.m.
4:54so where are we in this with a mammoth the first attempts to sequence a
4:58complete genome a mammoth was published in 2008
5:01in the journal Nature the authors manage to sequence 3.3 billion base pairs
5:06have mammoth DNA when this was all put together in back to the elephant that
5:09look like
5:10about fifty percent have the mammoth genome had been sequenced
5:1350 percent that's about half so said if this we're working with
5:17this but that's okay that's great that was state-of-the-art in 2008 and its
5:22pretty much stay to the arts today in fact does anybody know
5:25how many vertebrate genomes have been completely sequenced including
5:30modern vertebrates living vertebrate species
5:33give you a hint it's not a very big number none
5:37not even our own genome for which an honest to goodness ridiculous amount of
5:41sequence data has been published
5:42we do not know the complete sequence of our own team
5:46I'm being a little bit unfair we do know more than 99 percent
5:49have the genome the party barge in on that actually codes for things where the
5:52jeans live
5:53the you chromatin it's the other part the heterochromatin
5:56that is made as tightly condensed repeat sequences that are just super hard to
6:00sequence through
6:02the heterochromatin doesn't make up a very big part of our genome it might not
6:05actually be that important but we don't know
6:08because we have a menace to sequence it for living thing
6:12for the mammoth we don't know the heterochromatin we also don't know where
6:15the jeans are much less
6:17where the specific genes that make a mammoth look like a mammoth
6:20are so we can find them and use that said
6:23hybridized so what we do how we fix this problem
6:27well seems pretty clear let's finish it we go into the Arctic we find a really
6:32well preserved mammoth bone we take a chunk out of it and bring it back to the
6:35lab them
6:35sequence the genome that's where the fun begins
6:38if I'm gonna sequence my own genome I could start with say a piece of my hair
6:43and I could dissolve enough in the extraction stuff
6:46and sequence everything that was in there and the results would look like
6:49this
6:50pretty much everything inside that DNA extract would be me
6:53my own DNA that's because I'm alive my DNA is in good condition
6:57left my hair has it anywhere particularly weird not so for the
7:00mammoth
7:02a similar experiment performed on a mammoth bone from alaska
7:05resulted in about 50 percent or more than half of the sequences in that tone
7:09being mammoth
7:10the other half was a combination of plants bacteria other stuff for the
7:13gotten into the bone
7:14while it was in the soil and stuff that might have been introduced into the bone
7:18during the process of excavation and sequencing we touched a boner
7:22breathe on the sample but they're still pretty good permafrost preserved more
7:25than fifty percent
7:27here's a similar experiment for a Neandertal from a cave in Croatia
7:31here only three percent have the sequences in that extract were actually
7:35primate and that includes both Neandertal sequences and any potentially
7:39contaminating
7:40human sequences but this is still good there's still
7:43the other told DNA in this sample just not much of it
7:46so presumably what that means is all we have to do is sequence a lot more of it
7:51and to some extent that's absolutely true but there is another problem
7:55you imagine that our own DNA is like a rope or a ridin or
7:59party streamers say like those were gonna put up to celebrate
8:02the birth of our first cloned mammoth the mammoth DNA itself is actually going
8:07to be
8:07more like confetti
8:11that's been run over by a part of mammoths in the rain
8:16water oxygen solar radiation bacterial decay all of these things
8:21will begin to act on the long strands to DNA immediately after an organism dies
8:27and eventually that DNA will be chopped down into smaller and smaller fragments
8:31until there's nothing left so this is what we have to make
8:35this to make the EU's and eventually that
8:40it's a hard problem its problem that probably won't be solved without
8:44new and different biotechnology than what's available today
8:48but as we progress toward this goal we're going to learn a tremendous amount
8:51about these extinct animals
8:53knowledge that I have no doubt will help us to win battles against extinction
8:57that are happening in our world today
9:00will learn where the jeans are we learned what genes make them look
9:04an act the way they did will learn a lot more about how genes interact with the
9:08environment
9:09and will finally hopefully discover why some populations
9:14and some species are so much more susceptible to extinction
9:17than others are at the same time we will get better at extracting DNA from
9:22our ancient the ancient bones we will learn how to fix the broken bits so we
9:27can start piecing together these little tiny fragments into longer and longer
9:30fragments
9:32if that's what we want to do we will eventually be able to sequence the
9:36complete genome of an extinct animal
9:38and then we will have completed step 1: thank you

Speak Like Your Idols, Become What you Want

they're not worth listening to that's good information
1:0721 I do I told him something that would find
1:12me more trustworthy in his eyes I told him that you know what
1:16last year I had a seminar with mister Tony Blair
1:20and he told me the exact same thing your woman
1:23and you're given a seminar to me or with me I'm so glad the futures
1:28here and the preface and the professor look at me and he told me
1:39okay so you're somebody but the funny thing is
1:43I made him want to listen to me and that's what I'm talking about I'm
1:47a communication consultant I teach people the art wanting people to listen
1:51to you
1:52and the first man I wanna show you as Martin Luther King
1:55he's the one who people tell us that we should talk like you should go to your
2:00brothers and sisters and colleagues to tell them
2:03I have a dream there's nothing wrong with that way
2:06Martin Luther King spoke but I think you should find
2:10the Martin Luther King in your world so that's the first question
2:14I ask people who is martin luther king in your world
2:18and in my world my Martin Luther King was
2:22my elementary school teacher can wanna
2:25can allow she was smoking
2:28a pipe she had long blonde hair and she had caliber
2:33posh look and I remember the first week in school
2:37she told us there she is and that's me
2:42on the top I hated being the top I was tallest one in the class
2:46somebody asked me if I was a boy I think that's not fair
2:49anyways at the first week
2:52she gave us a great task she asked us
2:55what do you want to be what you want to do for a living
2:59when you grow up I was seven years old I had no idea what I wanted to do
3:04and my mother she's from Brazil she's very dynamic and passionate
3:08she told me lane you should go to the stubborn saying get inspiration
3:12I grew up in the suburbs and I went to the first magical place I knew at the
3:17time
3:18the candy store and I stood there for half an hour
3:23looking at the female working at the Campus Store she had the poster
3:27other precedent she was always eating the candy
3:31while she was working as you have this book and I was about seven years old I
3:35was looking at her thinking
3:36that's the best job in the whole world and I went back to school
3:42and I had my first presentation and Aston frontman
3:46in front my class telling all my classmates when I grow up
3:50I'm gonna work at the candy store
3:55Carolina she didn't look to you she was actually worried about me
3:59she was smoking her pipe in the back in the classroom and then she came to me
4:04stood at her knees shemale she said
4:08Elaine you're not gonna work at the candy store
4:11you're going to be an author I had no idea what that was at the time
4:18but my first bestselling book at Dominion techniques
4:22I actually dedicated it to my teacher Carol A
4:26can I wanna know something that all I should know
4:29something about personal leadership she was herself
4:34as opposed to the professional robot
4:37a lot of us are professional robots when we worked
4:41and I don't know if you met a professional robot you know when you go
4:45to
4:45as to where you want it by phone
4:49Amy salesperson ago hello you feel
4:52hi you don't want to meet a professional robot you wanna be a person
4:58so my Martin Luther King in my world is
5:01catalana she made me want to listen
5:04to what she had to say so in order to make other people want to listen to you
5:09think about who is martin luther king in your world doesn't have to be
5:12politicians
5:13actually I don't think politicians are good communicators
5:16at all just for the record
5:20so don't be a professional robot
5:23be yourself that's the best thing you can be but you have to think about what
5:27people think when they see you
5:29I keep my first step into communication
5:33the year 2001 that's when I started my first day
5:36to my bachelor degree and communication
5:40and I remember sitting at the University waiting for the first speaker
5:44they're worth about 200 students sitting listening
5:48well trying to listen this tall man
5:51when up States any started talking for 10 minutes
5:56and we can hear word he said why he had a scar
6:00across and that was only thing
6:04we could think about he'd refuse to tell us that he had a scar across your face
6:09he refused to tell us where he got it from and that was the
6:13we think we could think about after ten minutes he gave up
6:17and he told us I got this car
6:21in a car accident in the seventies my name is Bill
6:25you know what I never forgot his name
6:30third quarter to make people want to listen to you
6:33you have to put your looks in perspective you need to know what people
6:37think when they see you
6:38before you say anything just like it was when I met this professor in Berlin
6:44I remember when them I had a
6:49I had a seminar to Swedish television and
6:52once again they were wondering wear a sling
6:55racism and that we're waiting for this Elaine even sound like a man to you
6:59no not really have some people think ally or something
7:03him and they were waiting for a lane
7:06and I'm so happy about my granddad arnett my granddad he was born on the
7:1128th
7:12and he was kinda rough he always taught me if you want men
7:16to listen to you you need to know what the boxers
7:19you I was like what do you mean what the boxers do well you know the boxers
7:24they always jab jab with jab
7:27well jab it means that you need to hit a little I
7:30just a test the strength that the other person and that's what we
7:34we men do all the time we hear each other verbally
7:38and what you're supposed to do is to hit back I had no clue about this did you
7:44well probably all men did but with the women we didn't
7:47so I tried my first jab
7:51six years ago I had a seminar for Swedish television
7:54and I was about to have it and the bank was waiting for a lane and i was
8:00standing in front of him
8:01and he was like yearly and I said yes I'm away
8:04he say wow that's amazing asset well
8:08yeah it's pretty amazing and any tell me
8:12so when were you born in
8:15yesterday in that's a jab
8:18and what i do. and how about yourself
8:23polishing your coffin
8:28and history action was quite nice he was like who
8:33because then he fell okay she's strong enough to handle
8:36the percent is a Swedish television the only thing that happened that I wasn't
8:41prepared a
8:42was I got another jab or maybe a knock out when I started my seminar
8:46I was about to accept myself in front of all these people
8:50and this female rose her hand she said Elaine
8:54I don't really know why I should listen to you you're still
8:58young I don't feel motivated and I don't know about you guys but have you ever
9:04met people who speak further
9:06with their eyes closed and that taught me about body language
9:11and I didn't know what to do she thought I was too young
9:15and maybe she didn't think I was friendly now so I tried to smile maybe I
9:19became this professional robot to her
9:21so I tried to smile sigh just my letter
9:24but her ice for called and I heard myself say well you're perfectly right
9:30i'm not as old as you are
9:36she looks so angry and I didn't know how to find myself after that
9:40and the other people in the audience started laughing
9:43she didn't but afterwards she the clanking
9:47for too many said I really like your job you're giving knock out sometimes
9:52maybe you could be our rhetorical expert I said okay
9:55have you ever heard those nervous laugh
9:58people give them all the time is that rhetorical trick
10:03that I hear when I coached people had to make people listen to them
10:06I the main thing that any two races the nervous laugh
10:10when they tried to convince people that they're right and they say you know this
10:13is really important
10:14it's not a good thing
10:17I'll but in order to handle
10:21comments like these you too young your female
10:24your matter whatever unique you put yourself in perspective is a good or bad
10:30to look the way I look what is your scar
10:32when it comes to making people want to listen to what you say kiss
10:36people will hear word they will just look at you and they will think
10:40either your trustworthy or you're not and they'll make the decision you need
10:44to handle it
10:45so personal leadership one good word that you could
10:50remember is copia I don't really know how to pronounce it is lacked in
10:56but it means that if you want people to listen you should
10:59study though who are being listened to
11:03what are they doing do I speak to a debut
11:07or do I or Dona I I when I said
11:11and comment our politicians 310
11:14sometimes I sit with male experts
11:18and one thing I noticed that a lot of men
11:21take their time and television there's only one problem
11:25when you in the media there is no time but if you take your time you come
11:30across as more trustworthy
11:32as opposed to a lot of you my love us we we tend to
11:36we tend to speak really fast so
11:40what happened this guy get this expert get
11:44question from the journalist and he goes there's two ways
11:52we can look at this the first thing is he
11:56really took his time and I'm like she this it's not you can speak this slowly
12:00when you're in television
12:01so what did I do I started speaking
12:04really really fat asses sports commentator and what happened
12:08I became less trustworthy because if you speak too fast
12:13is like your excusing the message that you want to send people
12:17so don't speak fast this morning I was in television
12:21again and I try to do the opposite you know what happen
12:26journalist asked me a question I when
12:29and the mail
12:32expert next to me he started Obama
12:39get it right so we should do is study those
12:43who are being listened to but don't do it their way I'm not saying study Martin
12:50Luther King go to college to say I have a dream
12:53and study the way he speaks do it
12:57but do it your way and maybe sometime you can take their place
13:01it's not a bad thing and I think I did
13:05thank you

What we learned from 5 million books

Erez Lieberman Aiden: Everyone knows that a picture is worth a thousand words. But we at Harvard were wondering if this was really true. (Laughter) So we assembled a team of experts, spanning Harvard, MIT, The American Heritage Dictionary, The Encyclopedia Britannica and even our proud sponsors, the Google. And we cogitated about this for about four years. And we came to a startling conclusion. Ladies and gentlemen, a picture is not worth a thousand words. In fact, we found some pictures that are worth 500 billion words.
1:02
Jean-Baptiste Michel: So how did we get to this conclusion? So Erez and I were thinking about ways to get a big picture of human culture and human history: change over time. So many books actually have been written over the years. So we were thinking, well the best way to learn from them is to read all of these millions of books. Now of course, if there's a scale for how awesome that is, that has to rank extremely, extremely high. Now the problem is there's an X-axis for that, which is the practical axis. This is very, very low.
1:29
(Applause)
1:32
Now people tend to use an alternative approach, which is to take a few sources and read them very carefully. This is extremely practical, but not so awesome. What you really want to do is to get to the awesome yet practical part of this space. So it turns out there was a company across the river called Google who had started a digitization project a few years back that might just enable this approach. They have digitized millions of books. So what that means is, one could use computational methods to read all of the books in a click of a button. That's very practical and extremely awesome.
2:03
ELA: Let me tell you a little bit about where books come from. Since time immemorial, there have been authors. These authors have been striving to write books. And this became considerably easier with the development of the printing press some centuries ago. Since then, the authors have won on 129 million distinct occasions, publishing books. Now if those books are not lost to history, then they are somewhere in a library, and many of those books have been getting retrieved from the libraries and digitized by Google, which has scanned 15 million books to date.
2:33
Now when Google digitizes a book, they put it into a really nice format. Now we've got the data, plus we have metadata. We have information about things like where was it published, who was the author, when was it published. And what we do is go through all of those records and exclude everything that's not the highest quality data. What we're left with is a collection of five million books, 500 billion words, a string of characters a thousand times longer than the human genome -- a text which, when written out, would stretch from here to the Moon and back 10 times over -- a veritable shard of our cultural genome. Of course what we did when faced with such outrageous hyperbole ... (Laughter) was what any self-respecting researchers would have done. We took a page out of XKCD, and we said, "Stand back. We're going to try science."
3:32
(Laughter)
3:34
JM: Now of course, we were thinking, well let's just first put the data out there for people to do science to it. Now we're thinking, what data can we release? Well of course, you want to take the books and release the full text of these five million books. Now Google, and Jon Orwant in particular, told us a little equation that we should learn. So you have five million, that is, five million authors and five million plaintiffs is a massive lawsuit. So, although that would be really, really awesome, again, that's extremely, extremely impractical. (Laughter)
4:03
Now again, we kind of caved in, and we did the very practical approach, which was a bit less awesome. We said, well instead of releasing the full text, we're going to release statistics about the books. So take for instance "A gleam of happiness." It's four words; we call that a four-gram. We're going to tell you how many times a particular four-gram appeared in books in 1801, 1802, 1803, all the way up to 2008. That gives us a time series of how frequently this particular sentence was used over time. We do that for all the words and phrases that appear in those books, and that gives us a big table of two billion lines that tell us about the way culture has been changing.
4:34
ELA: So those two billion lines, we call them two billion n-grams. What do they tell us? Well the individual n-grams measure cultural trends. Let me give you an example. Let's suppose that I am thriving, then tomorrow I want to tell you about how well I did. And so I might say, "Yesterday, I throve." Alternatively, I could say, "Yesterday, I thrived." Well which one should I use? How to know?
4:59
As of about six months ago, the state of the art in this field is that you would, for instance, go up to the following psychologist with fabulous hair, and you'd say, "Steve, you're an expert on the irregular verbs. What should I do?" And he'd tell you, "Well most people say thrived, but some people say throve." And you also knew, more or less, that if you were to go back in time 200 years and ask the following statesman with equally fabulous hair, (Laughter) "Tom, what should I say?" He'd say, "Well, in my day, most people throve, but some thrived." So now what I'm just going to show you is raw data. Two rows from this table of two billion entries. What you're seeing is year by year frequency of "thrived" and "throve" over time. Now this is just two out of two billion rows. So the entire data set is a billion times more awesome than this slide.
5:59
(Laughter)
6:01
(Applause)
6:05
JM: Now there are many other pictures that are worth 500 billion words. For instance, this one. If you just take influenza, you will see peaks at the time where you knew big flu epidemics were killing people around the globe.
6:16
ELA: If you were not yet convinced, sea levels are rising, so is atmospheric CO2 and global temperature.
6:24
JM: You might also want to have a look at this particular n-gram, and that's to tell Nietzsche that God is not dead, although you might agree that he might need a better publicist.
6:33
(Laughter)
6:35
ELA: You can get at some pretty abstract concepts with this sort of thing. For instance, let me tell you the history of the year 1950. Pretty much for the vast majority of history, no one gave a damn about 1950. In 1700, in 1800, in 1900, no one cared. Through the 30s and 40s, no one cared. Suddenly, in the mid-40s, there started to be a buzz. People realized that 1950 was going to happen, and it could be big. (Laughter) But nothing got people interested in 1950 like the year 1950. (Laughter) People were walking around obsessed. They couldn't stop talking about all the things they did in 1950, all the things they were planning to do in 1950, all the dreams of what they wanted to accomplish in 1950. In fact, 1950 was so fascinating that for years thereafter, people just kept talking about all the amazing things that happened, in '51, '52, '53. Finally in 1954, someone woke up and realized that 1950 had gotten somewhat passé. (Laughter) And just like that, the bubble burst.
7:52
(Laughter)
7:54
And the story of 1950 is the story of every year that we have on record, with a little twist, because now we've got these nice charts. And because we have these nice charts, we can measure things. We can say, "Well how fast does the bubble burst?" And it turns out that we can measure that very precisely. Equations were derived, graphs were produced, and the net result is that we find that the bubble bursts faster and faster with each passing year. We are losing interest in the past more rapidly.
8:24
JM: Now a little piece of career advice. So for those of you who seek to be famous, we can learn from the 25 most famous political figures, authors, actors and so on. So if you want to become famous early on, you should be an actor, because then fame starts rising by the end of your 20s -- you're still young, it's really great. Now if you can wait a little bit, you should be an author, because then you rise to very great heights, like Mark Twain, for instance: extremely famous. But if you want to reach the very top, you should delay gratification and, of course, become a politician. So here you will become famous by the end of your 50s, and become very, very famous afterward. So scientists also tend to get famous when they're much older. Like for instance, biologists and physics tend to be almost as famous as actors. One mistake you should not do is become a mathematician. (Laughter) If you do that, you might think, "Oh great. I'm going to do my best work when I'm in my 20s." But guess what, nobody will really care.
9:14
(Laughter)
9:17
ELA: There are more sobering notes among the n-grams. For instance, here's the trajectory of Marc Chagall, an artist born in 1887. And this looks like the normal trajectory of a famous person. He gets more and more and more famous, except if you look in German. If you look in German, you see something completely bizarre, something you pretty much never see, which is he becomes extremely famous and then all of a sudden plummets, going through a nadir between 1933 and 1945, before rebounding afterward. And of course, what we're seeing is the fact Marc Chagall was a Jewish artist in Nazi Germany.
9:55
Now these signals are actually so strong that we don't need to know that someone was censored. We can actually figure it out using really basic signal processing. Here's a simple way to do it. Well, a reasonable expectation is that somebody's fame in a given period of time should be roughly the average of their fame before and their fame after. So that's sort of what we expect. And we compare that to the fame that we observe. And we just divide one by the other to produce something we call a suppression index. If the suppression index is very, very, very small, then you very well might be being suppressed. If it's very large, maybe you're benefiting from propaganda.
10:34
JM: Now you can actually look at the distribution of suppression indexes over whole populations. So for instance, here -- this suppression index is for 5,000 people picked in English books where there's no known suppression -- it would be like this, basically tightly centered on one. What you expect is basically what you observe. This is distribution as seen in Germany -- very different, it's shifted to the left. People talked about it twice less as it should have been. But much more importantly, the distribution is much wider. There are many people who end up on the far left on this distribution who are talked about 10 times fewer than they should have been. But then also many people on the far right who seem to benefit from propaganda. This picture is the hallmark of censorship in the book record.
11:11
ELA: So culturomics is what we call this method. It's kind of like genomics. Except genomics is a lens on biology through the window of the sequence of bases in the human genome. Culturomics is similar. It's the application of massive-scale data collection analysis to the study of human culture. Here, instead of through the lens of a genome, through the lens of digitized pieces of the historical record. The great thing about culturomics is that everyone can do it. Why can everyone do it? Everyone can do it because three guys, Jon Orwant, Matt Gray and Will Brockman over at Google, saw the prototype of the Ngram Viewer, and they said, "This is so fun. We have to make this available for people." So in two weeks flat -- the two weeks before our paper came out -- they coded up a version of the Ngram Viewer for the general public. And so you too can type in any word or phrase that you're interested in and see its n-gram immediately -- also browse examples of all the various books in which your n-gram appears.
12:06
JM: Now this was used over a million times on the first day, and this is really the best of all the queries. So people want to be their best, put their best foot forward. But it turns out in the 18th century, people didn't really care about that at all. They didn't want to be their best, they wanted to be their beft. So what happened is, of course, this is just a mistake. It's not that strove for mediocrity, it's just that the S used to be written differently, kind of like an F. Now of course, Google didn't pick this up at the time, so we reported this in the science article that we wrote. But it turns out this is just a reminder that, although this is a lot of fun, when you interpret these graphs, you have to be very careful, and you have to adopt the base standards in the sciences.
12:42
ELA: People have been using this for all kinds of fun purposes. (Laughter) Actually, we're not going to have to talk, we're just going to show you all the slides and remain silent. This person was interested in the history of frustration. There's various types of frustration. If you stub your toe, that's a one A "argh." If the planet Earth is annihilated by the Vogons to make room for an interstellar bypass, that's an eight A "aaaaaaaargh." This person studies all the "arghs," from one through eight A's. And it turns out that the less-frequent "arghs" are, of course, the ones that correspond to things that are more frustrating -- except, oddly, in the early 80s. We think that might have something to do with Reagan.
13:28
(Laughter)
13:30
JM: There are many usages of this data, but the bottom line is that the historical record is being digitized. Google has started to digitize 15 million books. That's 12 percent of all the books that have ever been published. It's a sizable chunk of human culture. There's much more in culture: there's manuscripts, there newspapers, there's things that are not text, like art and paintings. These all happen to be on our computers, on computers across the world. And when that happens, that will transform the way we have to understand our past, our present and human culture.
13:57
Thank you very much.
13:59
(Applause)