Where's Google going next? | Larry Page

1,096,291 views ใƒป 2014-03-22

TED


ืื ื ืœื—ืฅ ืคืขืžื™ื™ื ืขืœ ื”ื›ืชื•ื‘ื™ื•ืช ื‘ืื ื’ืœื™ืช ืœืžื˜ื” ื›ื“ื™ ืœื”ืคืขื™ืœ ืืช ื”ืกืจื˜ื•ืŸ.

ืžืชืจื’ื: Zeeva Livshitz ืžื‘ืงืจ: Ido Dekkers
00:13
Charlie Rose: So Larry sent me an email
0
13381
3626
ืฆ'ืืจืœื™ ืจื•ื–: ืื– ืœืืจื™ ืฉืœื— ืœื™ ืžื™ื™ืœ
00:17
and he basically said,
1
17007
1987
ื•ื‘ืขืฆื ืืžืจ,
00:18
we've got to make sure that we don't seem like we're
2
18994
3729
ืื ื—ื ื• ื—ื™ื™ื‘ื™ื ืœื•ื•ื“ื ืฉืื ื—ื ื• ืœื ื ืจืื™ื ื›ืžื•
00:22
a couple of middle-aged boring men.
3
22723
4491
ื–ื•ื’ ื’ื‘ืจื™ื ืžืฉืขืžืžื™ื ื‘ื’ื™ืœ ื”ืขืžื™ื“ื”.
00:27
I said, I'm flattered by that --
4
27214
3042
ืืžืจืชื™, ื–ื” ืžื—ืžื™ื ืœื™ --
00:30
(Laughter) โ€”
5
30256
2372
(ืฆื—ื•ืง) โ€”
00:32
because I'm a bit older,
6
32628
3515
ืžืฉื•ื ืฉืื ื™ ืงืฆืช ื™ื•ืชืจ ืžื‘ื•ื’ืจ.
00:36
and he has a bit more net worth than I do.
7
36143
4151
ื•ืœื• ื™ืฉ ืงืฆืช ืฉื•ื•ื™ ื ื˜ื• ืžืืฉืจ ืœื™.
00:40
Larry Page: Well, thank you.
8
40294
2599
ืœืืจื™ ืคื™ื™ื’: ื˜ื•ื‘, ืชื•ื“ื”.
00:42
CR: So we'll have a conversation about
9
42893
2980
ืฆ.ืจ.: ืื– ืชื”ื™ื” ืœื ื• ืฉื™ื—ื” ืขืœ
00:45
the Internet, and we'll have a conversation Google,
10
45873
2698
ื”ืื™ื ื˜ืจื ื˜, ื•ืชื”ื™ื” ืœื ื• ืฉื™ื—ื” ืขืœ ื’ื•ื’ืœ,
00:48
and we'll have a conversation about search
11
48571
1434
ื•ืชื”ื™ื” ืœื ื• ืฉื™ื—ื” ืขืœ ื—ื™ืคื•ืฉ
00:50
and privacy,
12
50005
1367
ื•ืคืจื˜ื™ื•ืช,
00:51
and also about your philosophy
13
51372
1555
ื•ื’ื ืขืœ ื”ืคื™ืœื•ืกื•ืคื™ื” ืฉืœืš
00:52
and a sense of how you've connected the dots
14
52927
2456
ื•ืชื—ื•ืฉื” ืฉืœ ืื™ืš ื—ื™ื‘ืจืช ืืช ื”ื ืงื•ื“ื•ืช
00:55
and how this journey that began
15
55383
2091
ื•ืื™ืš ืœืžืกืข ื”ื–ื” ืฉื”ื—ืœ
00:57
some time ago
16
57474
1284
ืœืคื ื™ ื›ืžื” ื–ืžืŸ
00:58
has such interesting prospects.
17
58758
1895
ื™ืฉ ื›ืืœื” ืชื—ื–ื™ื•ืช ืžืขื ื™ื™ื ื•ืช.
01:00
Mainly we want to talk about the future.
18
60653
2596
ื‘ืขื™ืงืจ ืื ื—ื ื• ืจื•ืฆื™ื ืœื“ื‘ืจ ืขืœ ื”ืขืชื™ื“.
01:03
So my first question: Where is Google
19
63249
1589
ืื– ื”ืฉืืœื” ื”ืจืืฉื•ื ื” ืฉืœื™: ืื™ืคื” ื’ื•ื’ืœ ื ืžืฆืืช
01:04
and where is it going?
20
64838
2046
ื•ืœืืŸ ื”ื™ื ื”ื•ืœื›ืช?
01:06
LP: Well, this is something we think about a lot,
21
66884
1459
ืœ.ืค.: ื•ื‘ื›ืŸ, ื–ื” ืžืฉื”ื•. ืฉืื ื—ื ื• ื—ื•ืฉื‘ื™ื ืขืœื™ื• ื”ืจื‘ื”,
01:08
and our mission we defined a long time ago
22
68343
3575
ื•ืืช ื”ืžืฉื™ืžื” ืฉืœื ื• ื”ื’ื“ืจื ื• ืœืคื ื™ ื–ืžืŸ ืจื‘
01:11
is to organize the world's information
23
71918
2263
ื•ื”ื™ื ืœืืจื’ืŸ ืืช ื”ืžื™ื“ืข ื‘ืขื•ืœื
01:14
and make it universally accessible and useful.
24
74181
3438
ื•ืœื”ืคื•ืš ืื•ืชื• ืœื ื’ื™ืฉ ื•ืฉื™ืžื•ืฉื™ ืื•ื ื™ื‘ืจืกืœื™ืช.
01:17
And people always say,
25
77619
2042
ื•ืื ืฉื™ื ืชืžื™ื“ ืื•ืžืจื™ื
01:19
is that really what you guys are still doing?
26
79661
2215
ื”ืื ื–ื” ื‘ืืžืช ืžื” ืฉืืชื ืขื“ื™ื™ืŸ ืขื•ืฉื™ื?
01:21
And I always kind of think about that myself,
27
81876
2118
ื•ืื ื™ ืชืžื™ื“ ืื™ื›ืฉื”ื• ื—ื•ืฉื‘ ืขืœ ื–ื” ื‘ืขืฆืžื™,
01:23
and I'm not quite sure.
28
83994
2196
ื•ืื ื™ ืœื ืžืžืฉ ื‘ื˜ื•ื—.
01:26
But actually, when I think about search,
29
86190
4007
ืื‘ืœ ื‘ืขืฆื, ื›ืฉืื ื™ ื—ื•ืฉื‘ ืขืœ ื—ื™ืคื•ืฉ.
01:30
it's such a deep thing for all of us,
30
90197
2616
ื–ื” ืžืฉื”ื• ืžืจื›ื–ื™ ืขื‘ื•ืจ ื›ื•ืœื ื•.
01:32
to really understand what you want,
31
92813
2243
ืœื”ื‘ื™ืŸ ื‘ืืžืช ืžื” ืืชื ืจื•ืฆื™ื.
01:35
to understand the world's information,
32
95056
2368
ืœื”ื‘ื™ืŸ ืืช ื”ืžื™ื“ืข ืฉืœ ื”ืขื•ืœื,
01:37
and we're still very much in the early stages of that,
33
97424
3532
ื•ืื ื—ื ื• ืขื“ื™ื™ืŸ ืžืื“ ื‘ืฉืœื‘ื™ื ื”ืžื•ืงื“ืžื™ื ืฉืœ ื–ื”,
01:40
which is totally crazy.
34
100956
1813
ืฉื–ื” ืžื˜ื•ืจืฃ ืœื’ืžืจื™.
01:42
We've been at it for 15 years already,
35
102769
2518
ืื ื—ื ื• ื›ื‘ืจ ื‘ืขื ื™ื™ืŸ ืžื–ื” 15 ืฉื ื”,
01:45
but it's not at all done.
36
105287
3575
ืื‘ืœ ื–ื” ื‘ื›ืœืœ ืœื ื’ืžื•ืจ.
01:48
CR: When it's done, how will it be?
37
108862
2676
ืฆ.ืจ.: ื›ืืฉืจ ื–ื” ื ื™ื”ื™ื” ื’ืžื•ืจ, ืื™ืš ื–ื” ื™ื”ื™ื”?
01:51
LP: Well, I guess,
38
111538
2717
ืœ.ืค.: ื•ื‘ื›ืŸ, ืื ื™ ืžื ื™ื—,
01:54
in thinking about where we're going --
39
114255
2400
ื›ืฉื—ื•ืฉื‘ื™ื ืขืœ ืœืืŸ ืื ื—ื ื• ื”ื•ืœื›ื™ื --.
01:56
you know, why is it not done? --
40
116655
2287
ืืชื” ื™ื•ื“ืข, ืœืžื” ื–ื” ืœื ื’ืžื•ืจ? --
01:58
a lot of it is just computing's kind of a mess.
41
118942
2436
ื”ืจื‘ื” ืžื–ื” ื”ื•ื ืจืง ื‘ืœื’ืŸ ืฉืœ ืžื™ื—ืฉื•ื‘.
02:01
You know, your computer doesn't know where you are,
42
121378
1803
ืืชื” ื™ื•ื“ืข, ื”ืžื—ืฉื‘ ืฉืœืš ืœื ื™ื•ื“ืข ืื™ืคื•ื ืืชื”,
02:03
it doesn't know what you're doing,
43
123181
2035
ื”ื•ื ืœื ื™ื•ื“ืข ืžื” ืืชื” ืขื•ืฉื”,
02:05
it doesn't know what you know,
44
125216
1682
ื”ื•ื ืœื ื™ื•ื“ืข ืžื” ืืชื” ื™ื•ื“ืข
02:06
and a lot we've been trying to do recently
45
126898
2576
ื•ื”ืจื‘ื” ืžืžื” ืฉื ื™ืกื™ื ื• ืœืขืฉื•ืช ืœืื—ืจื•ื ื”
02:09
is just make your devices work,
46
129474
3295
ื–ื” ืคืฉื•ื˜ ืœื’ืจื•ื ืœื”ืชืงื ื™ื ืฉืœื›ื ืœืขื‘ื•ื“,
02:12
make them understand your context.
47
132769
2341
ืœื’ืจื•ื ืœื”ื ืœื”ื‘ื™ืŸ ืืช ื”ื”ืงืฉืจ ืฉืœื›ื.
02:15
Google Now, you know, knows where you are,
48
135110
2003
ื’ื•ื’ืœ ืขื›ืฉื™ื•, ืืชื” ื™ื•ื“ืข, ื™ื•ื“ืขืช ื”ื™ื›ืŸ ืืชื” ื ืžืฆื,
02:17
knows what you may need.
49
137113
2182
ื™ื•ื“ืขืช ืžื” ืฉืืชื” ืขืฉื•ื™ ืœื”ื–ื“ืงืง ืœื•.
02:19
So really having computing work and understand you
50
139295
4108
ืื– ื‘ืืžืช ืœื’ืจื•ื ืœืžื—ืฉื•ื‘ ืœืขื‘ื•ื“ ื•ืœื”ื‘ื™ืŸ ืื•ืชืš
02:23
and understand that information,
51
143403
2056
ื•ืœื”ื‘ื™ืŸ ืืช ื”ืžื™ื“ืข ื”ื–ื”,
02:25
we really haven't done that yet.
52
145459
2310
ื‘ืืžืช ืœื ืขืฉื™ื ื• ื–ืืช ืขื“ื™ื™ืŸ.
02:27
It's still very, very clunky.
53
147769
1549
ื–ื” ืขื“ื™ื™ืŸ ืžืื•ื“ ืžืื“ ืžืกื•ืจื‘ืœ.
02:29
CR: Tell me, when you look at what Google is doing,
54
149318
2366
ืฆ.ืจ.: ืืžื•ืจ ืœื™, ื›ืฉืืชื” ืžืกืชื›ืœ ืขืœ ืžื” ื’ื•ื’ืœ ืขื•ืฉื”,
02:31
where does Deep Mind fit?
55
151684
2969
ืื™ืคื” "ื“ื™ืค ืžื™ื™ื ื“" ืžืฉืชืœื‘ืช?
02:34
LP: Yeah, so Deep Mind is a company
56
154653
1584
ืœ.ืค.: ื›ืŸ, ืื– "ื“ื™ืค ืžื™ื™ื ื“" ื”ื™ื ื—ื‘ืจื”
02:36
we just acquired recently.
57
156237
2531
ืฉืจื›ืฉื ื• ืžืžืฉ ืœืื—ืจื•ื ื”.
02:38
It's in the U.K.
58
158768
3082
ื–ื” ื‘ื‘ืจื™ื˜ื ื™ื”
02:41
First, let me tell you the way we got there,
59
161850
2654
ืจืืฉื™ืช, ื”ืจืฉื” ืœื™ ืœืกืคืจ ืœืš ืื™ืš ื”ื’ืขื ื• ืœืฉื,
02:44
which was looking at search
60
164504
2228
ืžื” ืฉื”ื™ื” ืœื”ื‘ื™ื˜ ืขืœ ื—ื™ืคื•ืฉ
02:46
and really understanding,
61
166732
1623
ื•ืžืžืฉ ืœื”ื‘ื™ืŸ,
02:48
trying to understand everything,
62
168355
2233
ื ื™ืกื™ื•ืŸ ืœื”ื‘ื™ืŸ ืืช ื”ื›ืœ.
02:50
and also make the computers not clunky
63
170588
1605
ื•ื’ื ืœื”ืคื•ืš ืืช ื”ืžื—ืฉื‘ื™ื ืœืœื ืžืกื•ืจื‘ืœื™ื
02:52
and really understand you --
64
172193
2201
ื•ืžืžืฉ ืœื”ื‘ื™ืŸ ืืชื›ื --
02:54
like, voice was really important.
65
174394
2112
ื›ืžื•, ื”ืงื•ืœ ื”ื™ื” ืžืžืฉ ื—ืฉื•ื‘.
02:56
So what's the state of the art on speech recognition?
66
176506
2861
ืื– ืžื” ื—ื“ืฉื ื™ ื‘ื–ื™ื”ื•ื™ ื“ื™ื‘ื•ืจ ?
02:59
It's not very good.
67
179367
1660
ื–ื” ืœื ืžืžืฉ ื˜ื•ื‘
03:01
It doesn't really understand you.
68
181027
2066
ื–ื” ืœื ืžืžืฉ ืžื‘ื™ืŸ ืืชื›ื.
03:03
So we started doing machine learning research
69
183093
2003
ืื– ื”ืชื—ืœื ื• ืœืขืฉื•ืช ืžื—ืงืจ ืœืžื™ื“ืช ืžื›ื•ื ื”
03:05
to improve that.
70
185096
1537
ื›ื“ื™ ืœืฉืคืจ ืืช ื–ื”.
03:06
That helped a lot.
71
186633
1703
ืฉืขื–ืจ ืžืื•ื“.
03:08
And we started just looking at things like YouTube.
72
188336
2367
ื•ื”ืชื—ืœื ื• ืจืง ืœื”ืกืชื›ืœ ืขืœ ื“ื‘ืจื™ื ื›ืžื• ื™ื•ื˜ื™ื•ื‘
03:10
Can we understand YouTube?
73
190703
1968
ื”ืื ื ื•ื›ืœ ืœื”ื‘ื™ืŸ ืืช ื™ื•ื˜ื™ื•ื‘?
03:12
But we actually ran machine learning on YouTube
74
192671
2686
ืื‘ืœ ื”ืจืฆื ื• ืœืžืขืฉื” ืžื›ื•ื ืช ืœืžื™ื“ื” ื‘-ื™ื•ื˜ื™ื•ื‘
03:15
and it discovered cats, just by itself.
75
195357
4085
ื•ื”ื™ื ื’ื™ืœืชื” ื—ืชื•ืœื™ื, ืคืฉื•ื˜ ื‘ืขืฆืžื”.
03:19
Now, that's an important concept.
76
199442
2091
ื›ืขืช, ื–ื” ืจืขื™ื•ืŸ ื—ืฉื•ื‘.
03:21
And we realized there's really something here.
77
201533
2991
ื•ื”ื‘ื ื• ืฉื‘ืืžืช ื™ืฉ ื›ืืŸ ืžืฉื”ื•.
03:24
If we can learn what cats are,
78
204524
2117
ืื ื ื•ื›ืœ ืœืœืžื•ื“ ืžื” ื”ื ื—ืชื•ืœื™ื,
03:26
that must be really important.
79
206641
2075
ื–ื” ื—ื™ื™ื‘ ืœื”ื™ื•ืช ืžืžืฉ ื—ืฉื•ื‘.
03:28
So I think Deep Mind,
80
208716
2629
ืื– ืื ื™ ื—ื•ืฉื‘ ืฉ"ื“ื™ืค ืžื™ื™ื ื“",
03:31
what's really amazing about Deep Mind
81
211345
2364
ืžื” ืฉืžื“ื”ื™ื ื‘ืืžืช ื‘"ื“ื™ืค ืžื™ื™ื ื“"
03:33
is that it can actually --
82
213709
2004
ื–ื” ืฉื”ื™ื ื™ื›ื•ืœื” ืœืžืขืฉื” --
03:35
they're learning things in this unsupervised way.
83
215713
3557
ื”ื ืœื•ืžื“ื™ื ื“ื‘ืจื™ื ื‘ื“ืจืš ืœืœื ืคื™ืงื•ื— ืฉื›ื–ื•
03:39
They started with video games,
84
219270
2567
ื”ื ื”ืชื—ื™ืœื• ืขื ืžืฉื—ืงื™ ื•ื™ื“ืื•,
03:41
and really just, maybe I can show the video,
85
221837
2493
ื•ืœืžืขืฉื” ืจืง, ืื•ืœื™ ืื ื™ ื™ื›ื•ืœ ืœื”ืจืื•ืช ืืช ื”ื•ื™ื“ืื•
03:44
just playing video games,
86
224330
2204
ืจืง ืžืฉื—ืงื™ื ื‘ืžืฉื—ืงื™ ื•ื™ื“ืื•,
03:46
and learning how to do that automatically.
87
226534
2015
ื•ืœื•ืžื“ื™ื ืื™ืš ืœืขืฉื•ืช ืืช ื–ื” ื‘ืื•ืคืŸ ืื•ื˜ื•ืžื˜ื™.
03:48
CR: Take a look at the video games
88
228549
1852
ืฆ.ืจ.:ื”ืกืชื›ืœื• ืขืœ ืžืฉื—ืงื™ ื”ื•ื™ื“ืื•
03:50
and how machines are coming to be able
89
230401
2410
ื•ืื™ืš ืžื›ื•ื ื•ืช ื ืขืฉื•ืช ืžืกื•ื’ืœื•ืช
03:52
to do some remarkable things.
90
232811
2456
ืœืขืฉื•ืช ื›ืžื” ื“ื‘ืจื™ื ืžืจืฉื™ืžื™ื.
03:55
LP: The amazing thing about this
91
235267
1329
ืœ.ืค.: ื”ื“ื‘ืจ ื”ืžื“ื”ื™ื ื‘ื–ื”
03:56
is this is, I mean, obviously,
92
236596
1680
ื”ื•ื ืฉื–ื”, ืื ื™ ืžืชื›ื•ื•ืŸ, ื›ืžื•ื‘ืŸ,
03:58
these are old games,
93
238276
1474
ืืœื” ื”ื ืžืฉื—ืงื™ื ื™ืฉื ื™ื,
03:59
but the system just sees what you see, the pixels,
94
239750
4798
ืื‘ืœ ื”ืžืขืจื›ืช ืจื•ืื” ืจืง ืžื” ืฉืืชื ืจื•ืื™ื , ื”ืคื™ืงืกืœื™ื.
04:04
and it has the controls and it has the score,
95
244548
2431
ื•ื™ืฉ ืœื” ืืช ื”ื‘ืงืจื•ืช ื•ื™ืฉ ืœื” ืืช ื”ืชื•ืฆืื”.
04:06
and it's learned to play all of these games,
96
246979
2211
ื•ื”ื™ื ืœืžื“ื” ืœืฉื—ืง ืืช ื›ืœ ื”ืžืฉื—ืงื™ื ื”ืืœื”,
04:09
same program.
97
249190
1579
ืื•ืชื” ืชื•ื›ื ื”.
04:10
It's learned to play all of these games
98
250769
2037
ื”ื™ื ืœืžื“ื” ืœืฉื—ืง ืืช ื›ืœ ื”ืžืฉื—ืงื™ื ื”ืืœื”
04:12
with superhuman performance.
99
252806
1786
ืขื ื‘ื™ืฆื•ืขื™ื ืขืœ-ืื ื•ืฉื™ื™ื.
04:14
We've not been able to do things like this
100
254592
1855
ืœื ื”ื™ื™ื ื• ื™ื›ื•ืœื™ื ืœืขืฉื•ืช. ื“ื‘ืจื™ื ื›ืืœื”
04:16
with computers before.
101
256447
1518
ืขื ืžื—ืฉื‘ื™ื ืœืคื ื™ ื›ืŸ.
04:17
And maybe I'll just narrate this one quickly.
102
257965
2295
ื•ืื•ืœื™ ืื ื™ ืืกืคืจ ืจืง ืืช ื”ืกื™ืคื•ืจ ื”ื–ื” ื‘ืžื”ื™ืจื•ืช.
04:20
This is boxing, and it figures out it can
103
260260
2805
ื–ื” ืื™ื’ืจื•ืฃ, ื•ื”ื•ื ืžื—ืฉื‘ ืฉื”ื•ื ื™ื›ื•ืœ
04:23
sort of pin the opponent down.
104
263065
2634
ืื™ื›ืฉื”ื• ืœื“ื—ื•ืฃ ืืช ื”ื™ืจื™ื‘ ืœืžื˜ื”
04:25
The computer's on the left,
105
265699
1739
ื”ืžื—ืฉื‘ ื”ื•ื ืžืฉืžืืœ.
04:27
and it's just racking up points.
106
267438
3085
ื•ื–ื” ืจืง ืฆื‘ื™ืจืช ื ืงื•ื“ื•ืช.
04:30
So imagine if this kind
107
270523
2086
ืื– ื“ืžื™ื™ื ื• ืื ืกื•ื’ ื–ื”
04:32
of intelligence were thrown at your schedule,
108
272609
2127
ืฉืœ ื‘ื™ื ื” ื”ื™ื” ื ื–ืจืง ืœืขื‘ืจ ืœื•ื— ื”ื–ืžื ื™ื ืฉืœื›ื,
04:34
or your information needs, or things like that.
109
274736
4637
ืื• ืฆื•ืจื›ื™ ื”ืžื™ื“ืข ืฉืœื›ื, ืื• ื“ื‘ืจื™ื ื›ืืœื”.
04:39
We're really just at the beginning of that,
110
279373
2618
ืื ื—ื ื• ื‘ืืžืช ืจืง ื‘ืชื—ื™ืœืชื• ืฉืœ ื“ื‘ืจ ื–ื”,
04:41
and that's what I'm really excited about.
111
281991
2365
ื•ื–ื” ืžื” ืฉืžืžืฉ ืžืจื’ืฉ ืื•ืชื™.
04:44
CR: When you look at all that's taken place
112
284356
2470
ืฆ.ืจ.: ื›ืืฉืจ ืืชื” ืžืกืชื›ืœ ืขืœ ื›ืœ ืžื” ืฉืงืจื”
04:46
with Deep Mind and the boxing,
113
286826
2584
ืขื "ื“ื™ืค ืžื™ื™ื ื“" ื•ื”ืื™ื’ืจื•ืฃ,
04:49
also a part of where we're going
114
289410
2340
ื’ื ื—ืœืง ืžืžื” ืฉืื ื—ื ื• ื”ื•ืœื›ื™ื ืืœื™ื•
04:51
is artificial intelligence.
115
291750
2889
ื”ื•ื ื‘ื™ื ื” ืžืœืื›ื•ืชื™ืช.
04:54
Where are we, when you look at that?
116
294639
2799
ืื™ืคื” ืื ื—ื ื•, ื›ืืฉืจ ืืชื” ืžืกืชื›ืœ ืขืœ ื–ื”?
04:57
LP: Well, I think for me,
117
297438
1785
ืœ.ืค.: ื•ื‘ื›ืŸ, ืื ื™ ื—ื•ืฉื‘ ืฉื‘ืฉื‘ื™ืœื™,
04:59
this is kind of one of the most exciting things
118
299223
1503
ื–ื” ืžืกื•ื’ ื”ื“ื‘ืจื™ื ื”ื›ื™ ืžืจื’ืฉื™ื
05:00
I've seen in a long time.
119
300726
1912
ืฉืจืื™ืชื™ ืžื–ื” ื–ืžืŸ ืจื‘.
05:02
The guy who started this company, Demis,
120
302638
2413
ืœื‘ื—ื•ืจ ืฉื™ื™ืกื“ ืืช ื”ื—ื‘ืจื” ื”ื–ืืช, ื“ืžื™ืก,
05:05
has a neuroscience and a computer science background.
121
305051
2778
ื™ืฉ ืจืงืข ื‘ืžื“ืขื™ ื”ืžื•ื— ื•ื‘ืžื“ืขื™ ื”ืžื—ืฉื‘.
05:07
He went back to school
122
307829
1630
ื”ื•ื ื—ื–ืจ ืœืœื™ืžื•ื“ื™ื
05:09
to get his Ph.D. to study the brain.
123
309459
3126
ื›ื“ื™ ืœืงื‘ืœ ืืช ื”ื“ื•ืงื˜ื•ืจื˜ ืฉืœื• ื‘ื—ืงืจ ื”ืžื•ื—.
05:12
And so I think we're seeing a lot of exciting work
124
312585
2620
ืื– ืื ื™ ื—ื•ืฉื‘ ืฉืื ื—ื ื• ืจื•ืื™ื ื”ืจื‘ื” ืขื‘ื•ื“ื” ืžืจื’ืฉืช
05:15
going on that sort of crosses computer science
125
315205
3081
ืžืชืจื—ืฉืช ื‘ืกื•ื’ ืฉืœ ื”ืฆื˜ืœื‘ื•ืช ืฉืœ ืžื“ืขื™ ื”ืžื—ืฉื‘
05:18
and neuroscience
126
318286
1750
ื•ืžื“ืข ื”ืžื•ื—
05:20
in terms of really understanding
127
320036
2325
ื‘ืžื•ื ื—ื™ื ืฉืœ ื”ื‘ื ื” ืžืžืฉื™ืช
05:22
what it takes to make something smart
128
322361
2454
ืฉืœ ืžื” ืฉื ื“ืจืฉ ื›ื“ื™ ืœืขืฉื•ืช ืžืฉื”ื• ื—ื›ื
05:24
and do really interesting things.
129
324815
1715
ื•ืœืขืฉื•ืช ื“ื‘ืจื™ื ืžืžืฉ ืžืขื ื™ื™ื ื™ื.
05:26
CR: But where's the level of it now?
130
326530
2138
ืฆ.ืจ: ืื‘ืœ ื‘ืื™ื–ื• ืจืžื” ื–ื” ืขื•ืžื“ ืขื›ืฉื™ื•?
05:28
And how fast do you think we are moving?
131
328668
2706
ื•ื›ืžื” ืžื”ืจ ืืชื” ื—ื•ืฉื‘ ืฉืื ื—ื ื• ืžืชืงื“ืžื™ื?
05:31
LP: Well, this is the state of the art right now,
132
331374
3269
ืœ.ืค.: ื•ื‘ื›ืŸ, ื–ื•ื”ื™ ืจืžืช ื”ื—ื“ืฉื ื•ืช ืขื›ืฉื™ื•,
05:34
understanding cats on YouTube
133
334643
2131
ื”ื‘ื ืช ื—ืชื•ืœื™ื ื‘ื™ื•ื˜ื™ื•ื‘
05:36
and things like that,
134
336774
1283
ื•ื“ื‘ืจื™ื ื›ืืœื”,
05:38
improving voice recognition.
135
338057
2147
ืฉื™ืคื•ืจ ื–ื™ื”ื•ื™ ืงื•ืœื™.
05:40
We used a lot of machine learning
136
340204
2418
ื”ืฉืชืžืฉื ื• ื”ืจื‘ื” ื‘ืœืžื™ื“ืช ืžื›ื•ื ื”
05:42
to improve things incrementally,
137
342622
2479
ื›ื“ื™ ืœืฉืคืจ ืืช ื”ื“ื‘ืจื™ื ื‘ืื•ืคืŸ ื”ื“ืจื’ืชื™,
05:45
but I think for me, this example's really exciting,
138
345101
3394
ืื‘ืœ ืื ื™ ื—ื•ืฉื‘ ืฉื‘ืฉื‘ื™ืœื™, ื“ื•ื’ืžื” ื–ื• ื”ื™ื ืžืžืฉ ืžืจื’ืฉืช,
05:48
because it's one program
139
348495
2243
ื›ื™ ื–ื• ืชื•ื›ื ื” ืื—ืช
05:50
that can do a lot of different things.
140
350738
2044
ืฉื™ื›ื•ืœื” ืœืขืฉื•ืช ื”ืจื‘ื” ื“ื‘ืจื™ื ืฉื•ื ื™ื.
05:52
CR: I don't know if we can do this,
141
352782
1138
ืฆ.ืจ.: ืื ื™ ืœื ื™ื•ื“ืข ืื ืื ื—ื ื• ื™ื›ื•ืœื™ื ืœืขืฉื•ืช ืืช ื–ื”,
05:53
but we've got the image of the cat.
142
353920
1185
ืื‘ืœ ื™ืฉ ืœื ื• ืืช ื”ืชืžื•ื ื” ืฉืœ ื”ื—ืชื•ืœ.
05:55
It would be wonderful to see this.
143
355105
1754
ื–ื” ื™ื”ื™ื” ื ื”ื“ืจ ืœืจืื•ืช ืืช ื–ื”.
05:56
This is how machines looked at cats
144
356859
2509
ื–ื” ืื™ืš ืžื›ื•ื ื•ืช ื”ืกืชื›ืœื• ืขืœ ื—ืชื•ืœื™ื
05:59
and what they came up with.
145
359368
1115
ื•ืžื” ื”ื ื”ืžืฆื™ืื•.
06:00
Can we see that image?
146
360483
1055
ื ื•ื›ืœ ืœืจืื•ืช ืืช ื”ืชืžื•ื ื” ื”ื–ื•?
06:01
LP: Yeah. CR: There it is. Can you see the cat?
147
361538
2402
ืœ.ืค.: ื›ืŸ. ืฆ.ืจ.: ื”ื ื” ื–ื”. ืืชื” ืจื•ืื” ืืช ื”ื—ืชื•ืœ?
06:03
Designed by machines, seen by machines.
148
363940
2027
ืขื•ืฆื‘ ืขืœ ื™ื“ื™ ืžื›ื•ื ื•ืช, ื ืจืื” ืขืœ ื™ื“ื™ ืžื›ื•ื ื•ืช.
06:05
LP: That's right.
149
365967
1110
ืœ.ืค.: ื–ื” ื ื›ื•ืŸ.
06:07
So this is learned from just watching YouTube.
150
367077
2607
ืื– ื–ื” ื ืœืžื“ ืจืง ืžืฆืคื™ื” ื‘ื™ื•ื˜ื™ื•ื‘.
06:09
And there's no training,
151
369684
1867
ื•ืื™ืŸ ืฉื•ื ื”ื“ืจื›ื”.
06:11
no notion of a cat,
152
371551
1384
ืฉื•ื ืจืขื™ื•ืŸ ืฉืœ ื—ืชื•ืœ,
06:12
but this concept of a cat
153
372935
2561
ืื‘ืœ ื”ืจืขื™ื•ืŸ ื”ื–ื” ืฉืœ ื—ืชื•ืœ
06:15
is something important that you would understand,
154
375496
2808
ื–ื” ืžืฉื”ื• ื—ืฉื•ื‘ ืฉืชื‘ื™ืŸ,
06:18
and now that the machines can kind of understand.
155
378304
2523
ื•ื›ืขืช, ืฉื”ืžื›ื•ื ื•ืช ื™ื›ื•ืœื•ืช ืื™ื›ืฉื”ื• ืœื”ื‘ื™ืŸ.
06:20
Maybe just finishing
156
380827
1172
ืื•ืœื™ ืจืง ืœืกื™ื•ื
06:21
also on the search part,
157
381999
2222
ื’ื ืฉืœ ื”ื—ืœืง ืฉืœ ื”ื—ื™ืคื•ืฉ,
06:24
it started with search, really understanding
158
384221
2786
ื–ื” ื”ืชื—ื™ืœ ืขื ื—ื™ืคื•ืฉ, ืœื”ื‘ื™ืŸ ื‘ืืžืช
06:27
people's context and their information.
159
387007
2564
ืืช ื”ื”ืงืฉืจ ืฉืœ ื‘ื ื™ ืื“ื ื•ื”ืžื™ื“ืข ืฉืœื”ื.
06:29
I did have a video
160
389571
1860
ื”ื™ื” ืœื™ ื•ื™ื“ืื•
06:31
I wanted to show quickly on that
161
391431
2010
ืฉืจืฆื™ืชื™ ืœื”ืจืื•ืช ื‘ืžื”ื™ืจื•ืช ืขืœ ื–ื”
06:33
that we actually found.
162
393441
1647
ืฉืœืžืขืฉื” ืžืฆืื ื•.
06:35
(Video) ["Soy, Kenya"]
163
395088
5112
(ื•ื™ื“ืื•) ["ืกื•ื™, ืงื ื™ื”"]
06:40
Zack Matere: Not long ago,
164
400580
1872
ื–ืืง ืžืื˜ืจ: ืœื ืžื–ืžืŸ,
06:42
I planted a crop of potatoes.
165
402452
2586
ืฉืชืœืชื™ ื™ื‘ื•ืœ ืฉืœ ืชืคื•ื—ื™ ืื“ืžื”.
06:45
Then suddenly they started dying one after the other.
166
405038
3400
ื•ืื– ืคืชืื•ื ื”ื ื”ืชื—ื™ืœื• ืœืžื•ืช ื‘ื–ื” ืื—ืจ ื–ื”.
06:48
I checked out the books and they didn't tell me much.
167
408438
2750
ื‘ื“ืงืชื™ ื‘ืกืคืจื™ื, ื”ื ืœื ื’ื™ืœื• ื”ืจื‘ื”.
06:51
So, I went and I did a search.
168
411188
1946
ืื–, ื”ืœื›ืชื™, ื•ืขืฉื™ืชื™ ื—ื™ืคื•ืฉ.
06:53
["Zack Matere, Farmer"]
169
413134
3119
["ื–ืืง ืžืื˜ืจ, ื—ืงืœืื™"]
06:57
Potato diseases.
170
417609
3147
ืžื—ืœื•ืช ืชืคื•ื—ื™ ืื“ืžื”.
07:00
One of the websites told me
171
420756
1728
ืื—ื“ ืžืืชืจื™ ื”ืื™ื ื˜ืจื ื˜ ืืžืจ ืœื™
07:02
that ants could be the problem.
172
422484
1902
ืฉื ืžืœื™ื ื™ื›ื•ืœื•ืช ืœื”ื™ื•ืช ื”ื‘ืขื™ื”.
07:04
It said, sprinkle wood ash over the plants.
173
424386
2271
ื”ื™ื” ื›ืชื•ื‘, ืžืคื–ืจื™ื ืืคืจ ืขืฆื™ื ืขืœ ื”ืฆืžื—ื™ื.
07:06
Then after a few days the ants disappeared.
174
426657
2284
ื•ืื– ืื—ืจื™ ื›ืžื” ื™ืžื™ื ื ืขืœืžื• ื”ื ืžืœื™ื.
07:08
I got excited about the Internet.
175
428941
2594
ื”ืชืœื”ื‘ืชื™ ืžื”ืื™ื ื˜ืจื ื˜.
07:11
I have this friend
176
431535
1665
ื™ืฉ ืœื™ ื—ื‘ืจ
07:13
who really would like to expand his business.
177
433200
3618
ืฉื‘ืืžืช ื”ื™ื” ืจื•ืฆื” ืœื”ืจื—ื™ื‘ ืืช ื”ืขืกืง.
07:16
So I went with him to the cyber cafe
178
436818
3195
ืื– ื”ืœื›ืชื™ ืื™ืชื• ืœืกื™ื™ื‘ืจ ืงืคื”
07:20
and we checked out several sites.
179
440013
2541
ื•ื‘ื“ืงื ื• ืžืกืคืจ ืืชืจื™ื.
07:22
When I met him next, he was going to put a windmill
180
442554
2541
ื›ืฉืคื’ืฉืชื™ ืื•ืชื• ืฉื•ื‘, ื”ื•ื ืขืžื“ ืœื”ืฆื™ื‘ ื˜ื—ื ืช ืจื•ื—
07:25
at the local school.
181
445095
2694
ื‘ื‘ื™ืช ื”ืกืคืจ ื”ืžืงื•ืžื™.
07:27
I felt proud because
182
447789
1604
ื—ืฉืชื™ ื’ืื•ื•ื” ื›ื™
07:29
something that wasn't there before
183
449393
2028
ืžืฉื”ื• ืฉืœื ื”ื™ื” ืฉื ืœืคื ื™ ื›ืŸ
07:31
was suddenly there.
184
451421
1887
ื”ื™ื” ืฉื ืคืชืื•ื.
07:33
I realized that not everybody
185
453308
2690
ื”ื‘ื ืชื™ ืฉืœื ื›ื•ืœื
07:35
can be able to access
186
455998
1534
ื™ื”ื™ื• ืžืกื•ื’ืœื™ื ืœื’ืฉืช
07:37
what I was able to access.
187
457532
1486
ืœืžื” ืฉืื ื™ ื™ื›ื•ืœืชื™ ืœื’ืฉืช ืืœื™ื•.
07:39
I thought that I need to have an Internet
188
459018
1838
ื—ืฉื‘ืชื™ ืฉืื ื™ ืฆืจื™ืš ืื™ื ื˜ืจื ื˜
07:40
that my grandmother can use.
189
460856
1801
ืฉืกื‘ืชื ืฉืœื™ ื™ื›ื•ืœื” ืœื”ืฉืชืžืฉ ื‘ื•.
07:42
So I thought about a notice board.
190
462657
2457
ืื– ื—ืฉื‘ืชื™ ืขืœ ืœื•ื— ืžื•ื“ืขื•ืช.
07:45
A simple wooden notice board.
191
465114
1916
ืœื•ื— ืžื•ื“ืขื•ืช ืคืฉื•ื˜ ืžืขืฅ.
07:47
When I get information on my phone,
192
467030
2315
ื›ืฉืื ื™ ืžืงื‘ืœ ืžื™ื“ืข ื‘ื ื™ื™ื“ ืฉืœื™
07:49
I'm able to post the information
193
469345
2237
ืื ื™ ื™ื›ื•ืœ ืœืคืจืกื ืืช ื”ืžื™ื“ืข
07:51
on the notice board.
194
471582
1722
ืขืœ ื’ื‘ื™ ืœื•ื— ื”ืžื•ื“ืขื•ืช.
07:53
So it's basically like a computer.
195
473304
2858
ืื– ื–ื” ื‘ืขืฆื ื›ืžื• ืžื—ืฉื‘.
07:56
I use the Internet to help people.
196
476162
3889
ืื ื™ ืžืฉืชืžืฉ ื‘ืื™ื ื˜ืจื ื˜ ื›ื“ื™ ืœืขื–ื•ืจ ืœืื ืฉื™ื.
08:00
I think I am searching for
197
480051
3410
ืื ื™ ื—ื•ืฉื‘ ืฉืื ื™ ืžื—ืคืฉ ืื—ืจ
08:03
a better life
198
483461
1541
ื—ื™ื™ื ื˜ื•ื‘ื™ื ื™ื•ืชืจ
08:05
for me and my neighbors.
199
485002
4114
ื‘ืฉื‘ื™ืœื™ ื•ื‘ืฉื‘ื™ืœ ื”ืฉื›ื ื™ื ืฉืœื™.
08:09
So many people have access to information,
200
489116
3984
ืื– ืœื”ืจื‘ื” ืื ืฉื™ื ื™ืฉ ื’ื™ืฉื” ืœืžื™ื“ืข,
08:13
but there's no follow-up to that.
201
493100
2581
ืื‘ืœ ืื™ืŸ ืžืขืงื‘ ืขืœ ื–ื”.
08:15
I think the follow-up to that is our knowledge.
202
495681
2508
ืื ื™ ื—ื•ืฉื‘ ืฉืžืขืงื‘ ืื—ืจ ื–ื” ื”ื•ื ื”ื™ื“ืข ืฉืœื ื•.
08:18
When people have the knowledge,
203
498189
1606
ื›ืืฉืจ ื™ืฉ ืœืื ืฉื™ื ื™ืฉ ื™ื“ืข,
08:19
they can find solutions
204
499795
1630
ื”ื ื™ื›ื•ืœื™ื ืœืžืฆื•ื ืคืชืจื•ื ื•ืช
08:21
without having to helped out.
205
501425
1984
ืœืœื ืฆื•ืจืš ืœืงื‘ืœ ืขื–ืจื”
08:23
Information is powerful,
206
503440
2121
ืžื™ื“ืข ื”ื•ื ืจื‘ ืขื•ืฆืžื”,
08:25
but it is how we use it that will define us.
207
505561
4602
ืื‘ืœ ื”ื“ืจืš ื‘ื” ืื ื• ืžืฉืชืžืฉื™ื ื‘ื• ื”ื•ื ืžื” ืฉื™ื’ื“ื™ืจ ืื•ืชื ื•.
08:30
(Applause)
208
510163
4381
(ืžื—ื™ืื•ืช ื›ืคื™ื™ื)
08:34
LP: Now, the amazing thing about that video,
209
514544
2546
ืœ.ืค.: ืขื›ืฉื™ื•, ื”ื“ื‘ืจ ื”ืžื“ื”ื™ื ื‘ืงืฉืจ ืœื•ื™ื“ืื•,
08:37
actually, was we just read about it in the news,
210
517090
1466
ืœืžืขืฉื”, ืฉืคืฉื•ื˜ ืงืจืื ื• ืขืœ ื–ื” ื‘ื—ื“ืฉื•ืช,
08:38
and we found this gentlemen,
211
518556
2505
ื•ืžืฆืื ื• ืืช ื”ืื“ื ื”ื–ื”,
08:41
and made that little clip.
212
521061
2315
ื•ืขืฉื™ื ื• ืืช ื”ืงืœื™ืค ื”ืงื˜ืŸ ื”ื–ื”.
08:43
CR: When I talk to people about you,
213
523376
1391
ืฆ.ืจ.: ื›ืฉืื ื™ ืžื“ื‘ืจ ืขื ืื ืฉื™ื ืขืœื™ืš.
08:44
they say to me, people who know you well, say,
214
524767
2605
ื”ื ืื•ืžืจื™ื ืœื™, ืื ืฉื™ื ืฉืžื›ื™ืจื™ื ืื•ืชืš ื˜ื•ื‘, ืื•ืžืจื™ื,
08:47
Larry wants to change the world,
215
527372
1891
ืœืืจื™ ืจื•ืฆื” ืœืฉื ื•ืช ืืช ื”ืขื•ืœื,
08:49
and he believes technology can show the way.
216
529263
4112
ื•ื”ื•ื ืžืืžื™ืŸ ืฉื˜ื›ื ื•ืœื•ื’ื™ื” ื™ื›ื•ืœื” ืœื”ืจืื•ืช ืืช ื”ื“ืจืš.
08:53
And that means access to the Internet.
217
533375
1858
ื•ื–ื” ืื•ืžืจ ื’ื™ืฉื” ืœืื™ื ื˜ืจื ื˜.
08:55
It has to do with languages.
218
535233
1731
ื–ื” ืงืฉื•ืจ ืœืฉืคื•ืช.
08:56
It also means how people can get access
219
536964
2829
ืคื™ืจื•ืฉ ื”ื“ื‘ืจ ื”ื•ื ื’ื ื›ื™ืฆื“ ืื ืฉื™ื ื™ื›ื•ืœื™ื ืœืงื‘ืœ ื’ื™ืฉื”
08:59
and do things that will affect their community,
220
539793
2706
ื•ืœืขืฉื•ืช ื“ื‘ืจื™ื ืฉื™ืฉืคื™ืขื• ืขืœ ื”ืงื”ื™ืœื” ืฉืœื”ื,
09:02
and this is an example.
221
542499
2493
ื•ื–ื• ื“ื•ื’ืžื”.
09:04
LP: Yeah, that's right, and I think for me,
222
544992
3576
ืœ.ืค.: ื›ืŸ, ื–ื” ื ื›ื•ืŸ, ื•ืื ื™ ื—ื•ืฉื‘ ืฉืžื‘ื—ื™ื ืชื™,
09:08
I have been focusing on access more,
223
548568
2382
ืื ื™ ื›ื‘ืจ ืžืชืžืงื“ ื™ื•ืชืจ ืขืœ ื’ื™ืฉื”,
09:10
if we're talking about the future.
224
550950
2198
ืื ืื ื—ื ื• ืžื“ื‘ืจื™ื ืขืœ ื”ืขืชื™ื“.
09:13
We recently released this Loon Project
225
553148
2674
ืœืื—ืจื•ื ื” ืคืจืกืžื ื• ืืช ืคืจื•ื™ื™ืงื˜ ืœื•ืŸ ื”ื–ื”
09:15
which is using balloons to do it.
226
555822
2300
ืฉืขื•ืฉื” ืฉื™ืžื•ืฉ ื‘ื‘ืœื•ื ื™ื ื›ื“ื™ ืœืขืฉื•ืช ืืช ื–ื”.
09:18
It sounds totally crazy.
227
558122
1660
ื–ื” ื ืฉืžืข ืžื˜ื•ืจืฃ ืœื’ืžืจื™
09:19
We can show the video here.
228
559782
2539
ืื ื—ื ื• ื™ื›ื•ืœื™ื ืœื”ืจืื•ืช ื›ืืŸ ืืช ื”ื•ื™ื“ืื•.
09:22
Actually, two out of three people in the world
229
562321
1480
ืœืžืขืฉื”, ืœืฉื ื™ื™ื ืžืชื•ืš ืฉืœื•ืฉื” ืื ืฉื™ื ื‘ืขื•ืœื
09:23
don't have good Internet access now.
230
563801
2386
ืื™ืŸ ื’ื™ืฉื” ื˜ื•ื‘ื” ืœืื™ื ื˜ืจื ื˜ ืขื›ืฉื™ื•.
09:26
We actually think this can really help people
231
566187
2906
ืœืžืขืฉื” ืื ื—ื ื• ื—ื•ืฉื‘ื™ื ืฉื–ื” ื‘ืืžืช ื™ื›ื•ืœ ืœืขื–ื•ืจ ืœืื ืฉื™ื
09:29
sort of cost-efficiently.
232
569093
2057
ืกื•ื’ ืฉืœ ื—ื™ืกื›ื•ืŸ ื‘ืขืœื•ืช.
09:31
CR: It's a balloon. LP: Yeah, get access to the Internet.
233
571150
3371
ืฆ.ืจ.: ื–ื” ื‘ืœื•ืŸ. ืœ.ืค.: ื›ืŸ, ืœืงื‘ืœ ื’ื™ืฉื” ืœืื™ื ื˜ืจื ื˜.
09:34
CR: And why does this balloon give you access
234
574521
2143
ืฆ.ืจ:, ื•ืœืžื” ื”ื‘ืœื•ืŸ ื”ื–ื” ื ื•ืชืŸ ืœืš ื’ื™ืฉื”
09:36
to the Internet?
235
576664
1213
ืœืื™ื ื˜ืจื ื˜?
09:37
Because there was some interesting things
236
577877
1215
ื›ื™ ื”ื™ื• ื›ืžื” ื“ื‘ืจื™ื ืžืขื ื™ื™ื ื™ื
09:39
you had to do to figure out how
237
579092
1834
ืฉื”ื™ื™ืช ืฆืจื™ืš ืœืขืฉื•ืช ื›ื“ื™ ืœื”ื‘ื™ืŸ ืื™ืš
09:40
to make balloons possible,
238
580926
2131
ืœื”ืคื•ืš ื‘ืœื•ื ื™ื ืœืืคืฉืจื™ื™ื,
09:43
they didn't have to be tethered.
239
583057
1749
ื”ื ืœื ื”ื™ื• ืฆืจื™ื›ื™ื ืœื”ื™ื•ืช ืงืฉื•ืจื™ื.
09:44
LP: Yeah, and this is a good example of innovation.
240
584806
2081
ืœ.ืค.: ื›ืŸ, ื•ื–ื• ื“ื•ื’ืžื” ื˜ื•ื‘ื” ืฉืœ ื—ื“ืฉื ื•ืช.
09:46
Like, we've been thinking about this idea
241
586887
2544
ื—ืฉื‘ื ื• ืขืœ ื”ืจืขื™ื•ืŸ ื”ื–ื”
09:49
for five years or more
242
589431
1772
ื‘ืžืฉืš ื—ืžืฉ ืฉื ื™ื ืื• ื™ื•ืชืจ
09:51
before we started working on it,
243
591203
1601
ืœืคื ื™ ืฉื”ืชื—ืœื ื• ืœืขื‘ื•ื“ ืขืœ ื–ื”,
09:52
but it was just really,
244
592804
1319
ืื‘ืœ ื–ื” ื”ื™ื” ื‘ืืžืช ืคืฉื•ื˜.
09:54
how do we get access points up high, cheaply?
245
594123
3520
ืื™ืš ืื ื—ื ื• ืžืงื‘ืœื™ื ื ืงื•ื“ื•ืช ื’ื™ืฉื” ื’ื‘ื•ื”, ื‘ืžื—ื™ืจ ื–ื•ืœ
09:57
You normally have to use satellites
246
597643
1792
ื‘ื“ืจืš ื›ืœืœ ืฆืจื™ืš ืœื”ืฉืชืžืฉ ื‘ืœื•ื•ื™ื™ื ื™ื
09:59
and it takes a long time to launch them.
247
599435
2939
ื•ื–ื” ืœื•ืงื— ื–ืžืŸ ืจื‘ ืœืฉื’ืจ ืื•ืชื.
10:02
But you saw there how easy it is to launch a balloon
248
602374
2494
ืื‘ืœ ืจืื™ืช ืฉื ื›ืžื” ืงืœ ืœืฉื’ืจ ื‘ืœื•ืŸ
10:04
and get it up,
249
604868
1519
ื•ืœื”ืขืœื•ืช ืื•ืชื• ืœืžืขืœื”
10:06
and actually again, it's the power of the Internet,
250
606387
2001
ื•ืœืžืขืฉื”. ืฉื•ื‘, ื–ื” ื”ื›ื•ื— ืฉืœ ื”ืื™ื ื˜ืจื ื˜,
10:08
I did a search on it,
251
608388
1780
ืขืฉื™ืชื™ ื—ื™ืคื•ืฉ ืขืœ ื–ื”,
10:10
and I found, 30, 40 years ago,
252
610168
2304
ื•ืžืฆืืชื™, ืฉืœืคื ื™ 30, 40 ืฉื ื”,
10:12
someone had put up a balloon
253
612472
1889
ืžื™ืฉื”ื• ืฉื™ื’ืจ ื‘ืœื•ืŸ
10:14
and it had gone around the Earth multiple times.
254
614361
2805
ื•ื”ื•ื ื”ืกืชื•ื‘ื‘ ืกื‘ื™ื‘ ื›ื“ื•ืจ ื”ืืจืฅ ืคืขืžื™ื ืจื‘ื•ืช.
10:17
And I thought, why can't we do that today?
255
617166
2835
ื•ืื ื™ ื—ืฉื‘ืชื™, ืžื“ื•ืข ืื™ื ื ื• ื™ื›ื•ืœื™ื ืœืขืฉื•ืช ืืช ื–ื” ื”ื™ื•ื?
10:20
And that's how this project got going.
256
620001
2367
ื•ื›ืš ื”ืคืจื•ื™ืงื˜ ื”ื–ื” ื”ืชื—ื™ืœ ืœื”ืชื’ืœื’ืœ.
10:22
CR: But are you at the mercy of the wind?
257
622368
2330
ืฆ.ืจ.: ืื‘ืœ ื”ืื ืื™ื ื›ื ื ืชื•ื ื™ื ืœื—ืกื“ื™ ื”ืจื•ื—?
10:24
LP: Yeah, but it turns out,
258
624698
2122
ืœ.ืค.: ื›ืŸ, ืื‘ืœ ืžืกืชื‘ืจ,
10:26
we did some weather simulations
259
626820
1493
ืฉืขืฉื™ื ื• ื›ืžื” ืกื™ืžื•ืœืฆื™ื•ืช ืžื–ื’ ืื•ื•ื™ืจ
10:28
which probably hadn't really been done before,
260
628313
2547
ืฉื›ื ืจืื” ืœื ื‘ืืžืช ื ืขืฉื• ื‘ืขื‘ืจ,
10:30
and if you control the altitude of the balloons,
261
630860
2110
ื•ืื ืืชื” ืฉื•ืœื˜ ื‘ื’ื•ื‘ื” ืฉืœ ื”ื‘ืœื•ื ื™ื,
10:32
which you can do by pumping air into them
262
632970
2281
ืฉื ื™ืชืŸ ืœืขืฉื•ืช ื–ืืช ืขืœ-ื™ื“ื™ ืฉืื™ื‘ืช ืื•ื•ื™ืจ ืœืชื•ื›ื
10:35
and other ways,
263
635251
1822
ื•ื“ืจื›ื™ื ืื—ืจื•ืช,
10:37
you can actually control roughly where they go,
264
637073
2929
ืืชื” ื™ื›ื•ืœ ืœืžืขืฉื” ืœืฉืœื•ื˜ ืคื—ื•ืช ื™ื•ืชืจ ืœืืŸ ื”ื ื”ื•ืœื›ื™ื.
10:40
and so I think we can build a worldwide mesh
265
640002
2205
ืื– ืื ื™ ื—ื•ืฉื‘ ืฉืื ื—ื ื• ื™ื›ื•ืœื™ื ืœื‘ื ื•ืช ืจืฉืช ืขื•ืœืžื™ืช
10:42
of these balloons that can cover the whole planet.
266
642207
3339
ืฉืœ ื”ื‘ืœื•ื ื™ื ื”ืืœื• ืฉื™ื›ื•ืœื” ืœื›ืกื•ืช ืืช ื›ืœ ื”ืคืœื ื˜ื”.
10:45
CR: Before I talk about the future and transportation,
267
645546
2242
ืฆ.ืจ.: ืœืคื ื™ ืฉืื“ื‘ืจ ืขืœ ื”ืขืชื™ื“ ื•ืขืœ ืชื—ื‘ื•ืจื”,
10:47
where you've been a nerd for a while,
268
647788
1895
ืื™ืคื•ื ืฉื”ื™ื™ืช ื—ื ื•ืŸ. ืœื–ืžืŸ ืžื”
10:49
and this fascination you have with transportation
269
649683
2424
ื•ื”ืžืฉื™ื›ื” ื”ื–ืืช ืฉื™ืฉ ืœืš ืœืชื—ื‘ื•ืจื”
10:52
and automated cars and bicycles,
270
652107
2063
ื•ืžื›ื•ื ื™ื•ืช ืื•ื˜ื•ืžื˜ื™ื•ืช ื•ืื•ืคื ื™ื™ื,
10:54
let me talk a bit about what's been the subject here
271
654170
1737
ื”ืจืฉื” ืœื™ ืœื“ื‘ืจ ืงืฆืช ืขืœ ืžื” ืฉื”ื™ื” ื›ื‘ืจ ื”ื ื•ืฉื ื›ืืŸ
10:55
earlier with Edward Snowden.
272
655907
2443
ืงื•ื“ื ืขื ืื“ื•ืืจื“ ืกื ื•ื“ืŸ
10:58
It is security and privacy.
273
658350
3106
ื–ื” ืื‘ื˜ื—ื” ื•ืคืจื˜ื™ื•ืช.
11:01
You have to have been thinking about that.
274
661456
2340
ืืชื” ื‘ื˜ื•ื— ื—ืฉื‘ืช ืขืœ ื–ื”,
11:03
LP: Yeah, absolutely.
275
663796
1354
ืœ.ืค: ื›ืŸ, ื‘ื”ื—ืœื˜.
11:05
I saw the picture of Sergey with Edward Snowden yesterday.
276
665150
2843
ืจืื™ืชื™ ืืช ื”ืชืžื•ื ื” ืฉืœ ืกืจื’ื™ื™ ืขื ืื“ื•ืืจื“ ืกื ื•ื“ืŸ ืืชืžื•ืœ.
11:07
Some of you may have seen it.
277
667993
2870
ื—ืœืง ืžื›ื ืื•ืœื™ ืจืื• ืืช ื–ื”
11:10
But I think, for me, I guess,
278
670863
3171
ืื‘ืœ, ืื ื™ ื—ื•ืฉื‘, ืžื‘ื—ื™ื ืชื™, ืื ื™ ืžื ื™ื—
11:14
privacy and security are a really important thing.
279
674034
3662
ืคืจื˜ื™ื•ืช ื•ืื‘ื˜ื—ื” ื”ื ื“ื‘ืจ ืžืื•ื“ ื—ืฉื•ื‘.
11:17
We think about it in terms of both things,
280
677696
2245
ืื ื—ื ื• ื—ื•ืฉื‘ื™ื ืขืœ ื–ื” ื‘ืžื•ื ื—ื™ื ืฉืœ ืฉื ื™ ื”ื“ื‘ืจื™ื.
11:19
and I think you can't have privacy without security,
281
679941
2903
ื•ืœื“ืขืชื™ ืœื ื™ื›ื•ืœื” ืœื”ื™ื•ืช ืคืจื˜ื™ื•ืช ืœืœื ืื‘ื˜ื—ื”,
11:22
so let me just talk about security first,
282
682844
2371
ืื– ืชืŸ ืœื™ ืงื•ื“ื ื›ืœ ืœื“ื‘ืจ ืขืœ ืื‘ื˜ื—ื”,
11:25
because you asked about Snowden and all of that,
283
685215
2596
ื‘ื’ืœืœ ืฉืฉืืœืช ืขืœ ืกื ื•ื“ืŸ ื•ื›ืœ ื–ื”,
11:27
and then I'll say a little bit about privacy.
284
687811
2441
ื•ืœืื—ืจ ืžื›ืŸ ืื ื™ ืื“ื‘ืจ ืงืฆืช ืขืœ ืคืจื˜ื™ื•ืช.
11:30
I think for me, it's tremendously disappointing
285
690252
3800
ืœื“ืขืชื™, ื–ื” ืžืื•ื“ ืžืื›ื–ื‘
11:34
that the government
286
694052
1439
ืฉื”ืžืžืฉืœื”
11:35
secretly did all this stuff and didn't tell us.
287
695491
2330
ืขืฉืชื” ืืช ื›ืœ ื–ื” ื‘ืกืชืจ ืžื‘ืœื™ ืœืกืคืจ ืœื ื•.
11:37
I don't think we can have a democracy
288
697821
3303
ืื ื™ ืœื ื—ื•ืฉื‘ ืฉื™ื›ื•ืœื” ืœื”ื™ื•ืช ืœื ื• ื“ืžื•ืงืจื˜ื™ื”
11:41
if we're having to protect you and our users
289
701124
3430
ืื ืื ื• ืฆืจื™ื›ื™ื ืœืงื‘ืœ ื”ื’ื ื” ืขืœื™ืš ื•ืขืœ ื”ืžืฉืชืžืฉื™ื ืฉืœื ื•
11:44
from the government
290
704554
1696
ืžื”ืžืžืฉืœื”
11:46
for stuff that we've never had a conversation about.
291
706250
2803
ืขืœ ื“ื‘ืจื™ื ืฉืžืขื•ืœื ืœื ื“ื™ื‘ืจื ื• ืขืœื™ื”ื.
11:49
And I don't mean we have to know
292
709053
1896
ื•ืื ื™ ืœื ืžืชื›ื•ื•ืŸ ืฉืื ื—ื ื• ื—ื™ื™ื‘ื™ื ืœื“ืขืช
11:50
what the particular terrorist attack is they're worried
293
710949
1695
ืžืื™ื–ื• ืžืชืงืคืช ื˜ืจื•ืจ ืžืกื•ื™ืžืช ื”ื ืžื•ื“ืื’ื™ื
11:52
about protecting us from,
294
712644
1762
ื›ื“ื™ ืœื”ื’ืŸ ืขืœื™ื ื• ืžืคื ื™ื”,
11:54
but we do need to know
295
714406
1798
ืื‘ืœ ืื ื—ื ื• ืฆืจื™ื›ื™ื ืœื“ืขืช
11:56
what the parameters of it is,
296
716204
2410
ืžื”ื ื”ืคืจืžื˜ืจื™ื ืฉืœ ื–ื”,
11:58
what kind of surveillance the government's
297
718614
2044
ืื™ื–ื” ืกื•ื’ ืฉืœ ืžืขืงื‘ ื”ืžืžืฉืœื”
12:00
going to do and how and why,
298
720658
2168
ื”ื•ืœื›ืช ืœืขืฉื•ืช, ื•ืื™ืš ื•ืœืžื”.
12:02
and I think we haven't had that conversation.
299
722826
2277
ื•ืื ื™ ื—ื•ืฉื‘ ืฉืœื ืงื™ื™ืžื ื• ืืช ื”ืฉื™ื—ื” ื”ื–ืืช.
12:05
So I think the government's actually done
300
725103
2567
ืื– ืื ื™ ื—ื•ืฉื‘ ืฉื”ืžืžืฉืœื” ื‘ืืžืช ื’ืจืžื”
12:07
itself a tremendous disservice
301
727670
2168
ืœืขืฆืžื” ื ื–ืง ืขืฆื•ื
12:09
by doing all that in secret.
302
729838
2161
ืขืœ-ื™ื“ื™ ื›ืš ืฉื‘ื™ืฆืขื” ื›ืœ ื–ืืช ื‘ื—ืฉืื™.
12:11
CR: Never coming to Google
303
731999
1615
ืฆ.ืจ.: ื‘ืœื™ ืœืคื ื•ืช ืœื’ื•ื’ืœ
12:13
to ask for anything.
304
733614
1525
ืœื‘ืงืฉ ืžืฉื”ื•.
12:15
LP: Not Google, but the public.
305
735139
2030
ืœ.ืค.: ืœื ื’ื•ื’ืœ, ืืœื ื”ืฆื™ื‘ื•ืจ.
12:17
I think we need to have a debate about that,
306
737169
3773
ืื ื™ ื—ื•ืฉื‘ ืฉืื ื—ื ื• ืฆืจื™ื›ื™ื ืœืงื™ื™ื ื“ื™ื•ืŸ ืขืœ ื›ืš,
12:20
or we can't have a functioning democracy.
307
740942
2499
ืื• ืฉืื™ื ื ื• ื™ื›ื•ืœื™ื ืฉืชื”ื™ื” ืœื ื• ื“ืžื•ืงืจื˜ื™ื” ืžืชืคืงื“ืช.
12:23
It's just not possible.
308
743441
1406
ื–ื” ืคืฉื•ื˜ ื‘ืœืชื™ ืืคืฉืจื™.
12:24
So I'm sad that Google's
309
744847
2244
ืื– ืื ื™ ืขืฆื•ื‘ ืฉื’ื•ื’ืœ ื”ื™ื
12:27
in the position of protecting you and our users
310
747091
2616
ื‘ืžืฆื‘ ืฉืœ ื”ื’ื ื” ืขืœื™ืš ื•ืขืœ ื”ืžืฉืชืžืฉื™ื ืฉืœื ื•
12:29
from the government
311
749707
1534
ืžื”ืžืžืฉืœื”
12:31
doing secret thing that nobody knows about.
312
751241
2244
ืฉืขื•ืฉื” ืงื˜ืข ืกื•ื“ื™ ืฉืืฃ ืื—ื“ ืœื ื™ื•ื“ืข ืขืœื™ื•.
12:33
It doesn't make any sense.
313
753485
1747
ื–ื” ืœื ื”ื’ื™ื•ื ื™.
12:35
CR: Yeah. And then there's a privacy side of it.
314
755232
2990
ืฆ.ืจ.: ื›ืŸ. ื•ืื– ื™ืฉ ื ื•ืฉื ื”ืคืจื˜ื™ื•ืช ืฉืœ ื–ื”.
12:38
LP: Yes. The privacy side,
315
758222
2427
ืœ.ืค.: ื›ืŸ. ื ื•ืฉื ื”ืคืจื˜ื™ื•ืช,
12:40
I think it's -- the world is changing.
316
760649
1969
ืœื“ืขืชื™ ื–ื” -- ื”ืขื•ืœื ืžืฉืชื ื”.
12:42
You carry a phone. It knows where you are.
317
762618
3905
ื™ืฉ ืขืœื™ืš ื ื™ื™ื“. ื”ื•ื ื™ื•ื“ืข ืื™ืคื” ืืชื”.
12:46
There's so much more information about you,
318
766523
3085
ื™ืฉ ื›ืœ ื›ืš ื”ืจื‘ื” ืžื™ื“ืข ืื•ื“ื•ืชื™ืš,
12:49
and that's an important thing,
319
769608
2846
ื•ื–ื” ื“ื‘ืจ ื—ืฉื•ื‘,
12:52
and it makes sense why people are asking
320
772454
2272
ื•ื–ื” ื”ื’ื™ื•ื ื™ ืœืžื” ืื ืฉื™ื ืฉื•ืืœื™ื
12:54
difficult questions.
321
774726
2036
ืฉืืœื•ืช ืงืฉื•ืช.
12:56
We spend a lot of time thinking about this
322
776762
3367
ืื ื—ื ื• ืžื‘ืœื™ื ื”ืจื‘ื” ื–ืžืŸ ื‘ืœื—ืฉื•ื‘ ืขืœ ื–ื”
13:00
and what the issues are.
323
780129
2711
ื•ืžื”ื ื”ื ื•ืฉืื™ื.
13:02
I'm a little bit --
324
782840
1729
ืื ื™ ืงืฆืช --
13:04
I think the main thing that we need to do
325
784569
1260
ืื ื™ ื—ื•ืฉื‘ ืฉื”ื“ื‘ืจ ื”ืขื™ืงืจื™ ืฉืื ื—ื ื• ืฆืจื™ื›ื™ื ืœืขืฉื•ืช
13:05
is just provide people choice,
326
785829
2362
ื”ื•ื ืคืฉื•ื˜ ืœืกืคืง ืœืื ืฉื™ื ืืคืฉืจื•ืช ื‘ื—ื™ืจื”
13:08
show them what data's being collected --
327
788191
2512
ืœื”ืจืื•ืช ืœื”ื ืžื”ื ื”ื ืชื•ื ื™ื ืฉื ืืกืคื• --
13:10
search history, location data.
328
790703
4751
ื”ื™ืกื˜ื•ืจื™ืช ื—ื™ืคื•ืฉ, ืžื™ื“ืข ืขืœ ืžื™ืงื•ื.
13:15
We're excited about incognito mode in Chrome,
329
795454
2772
ืื ื—ื ื• ื ืจื’ืฉื™ื ืื•ื“ื•ืช ืžืฆื‘ ื’ืœื™ืฉื” ื‘ืกืชืจ ื‘ื›ืจื•ื,
13:18
and doing that in more ways,
330
798226
2249
ื•ืขื•ืฉื™ื ืืช ื–ื” ื‘ื“ืจื›ื™ื ืจื‘ื•ืช ื™ื•ืชืจ.
13:20
just giving people more choice
331
800475
1396
ืคืฉื•ื˜ ื ื•ืชื ื™ื ืœืื ืฉื™ื ืืคืฉืจื•ืช ื‘ื—ื™ืจื” ื ื•ืกืคืช
13:21
and more awareness of what's going on.
332
801871
3293
ื•ื™ื•ืชืจ ืžื•ื“ืขื•ืช ืขืœ ืžื” ืฉืงื•ืจื”.
13:25
I also think it's very easy.
333
805164
2393
ืื ื™ ื’ื ื—ื•ืฉื‘ ืฉื–ื” ืงืœ ืžืื•ื“.
13:27
What I'm worried is that we throw out
334
807557
1277
ืžื” ืฉืžื“ืื™ื’ ืื•ืชื™ ืฉืื ื—ื ื• ื–ื•ืจืงื™ื
13:28
the baby with the bathwater.
335
808834
2090
ืืช ื”ืชื™ื ื•ืง ืขื ืžื™ ื”ืืžื‘ื˜ื™ื”.
13:30
And I look at, on your show, actually,
336
810924
2914
ื•ืื ื™ ืžืกืชื›ืœ ืขืœ, ื‘ืชื•ื›ื ื™ืช ืฉืœื›ื, ืœืžืขืฉื”,
13:33
I kind of lost my voice,
337
813838
1719
ืื ื™ ืื™ื›ืฉื”ื• ืื™ื‘ื“ืชื™ ืืช ื”ืงื•ืœ ืฉืœื™,
13:35
and I haven't gotten it back.
338
815557
1331
ื•ืœื ืงื™ื‘ืœืชื™ ืื•ืชื• ื‘ื—ื–ืจื”.
13:36
I'm hoping that by talking to you
339
816888
1644
ืื ื™ ืžืงื•ื•ื” ืฉื‘ืขื–ืจืช ื”ืฉื™ื—ื” ืื™ืชืš
13:38
I'm going to get it back.
340
818532
1653
ืื ื™ ื”ื•ืœืš ืœื”ืฉื™ื‘ ืื•ืชื• ื—ื–ืจื”.
13:40
CR: If I could do anything, I would do that.
341
820185
1732
ืฆ.ืจ.: ืื ืื ื™ ืื•ื›ืœ ืœืขืฉื•ืช ืžืฉื”ื•, ืืขืฉื” ื–ืืช.
13:41
LP: All right. So get out your voodoo doll
342
821917
2180
ืœ.ืค.: ื‘ืกื“ืจ. ืื– ืชืฉืœื•ืฃ ืืช ื‘ื•ื‘ืช ื”ื•ื•ื“ื• ืฉืœืš
13:44
and whatever you need to do.
343
824097
2419
ื•ื›ืœ ืžื” ืฉืืชื” ืฆืจื™ืš ืœืขืฉื•ืช.
13:46
But I think, you know what, I look at that,
344
826516
2328
ืื‘ืœ ืื ื™ ื—ื•ืฉื‘, ืืชื” ื™ื•ื“ืข ืžื”, ืื ื™ ืžืกืชื›ืœ ืขืœ ื–ื”,
13:48
I made that public,
345
828844
1830
ืคื™ืจืกืžืชื™ ืืช ื–ื” ื‘ืคื•ืžื‘ื™,
13:50
and I got all this information.
346
830674
1217
ื•ื™ืฉ ืœื™ ืืช ื›ืœ ื”ืžื™ื“ืข ื”ื–ื”.
13:51
We got a survey done on medical conditions
347
831891
2729
ื™ืฉ ืœื ื• ืกืงืจ ืฉื ืขืฉื” ืขืœ ืžืฆื‘ื™ื ืจืคื•ืื™ื™ื
13:54
with people who have similar issues,
348
834620
3371
ืขื ืื ืฉื™ื ืฉื™ืฉ ืœื”ื ื‘ืขื™ื•ืช ื“ื•ืžื•ืช,
13:57
and I look at medical records, and I say,
349
837991
4741
ื•ืื ื™ ืžืกืชื›ืœ ืขืœ ื”ืชื™ืง ื”ืจืคื•ืื™, ื•ืื•ืžืจ
14:02
wouldn't it be amazing
350
842732
1405
ื”ืื ื–ื” ืœื ื™ื”ื™ื” ืžื“ื”ื™ื
14:04
if everyone's medical records were available
351
844137
2050
ืื ื›ืœ ื”ืจืฉื•ืžื•ืช ื”ืจืคื•ืื™ื•ืช ืฉืœ ื›ื•ืœื ื”ื™ื• ื–ืžื™ื ื•ืช
14:06
anonymously
352
846187
1683
ื‘ืขื™ืœื•ื ืฉื
14:07
to research doctors?
353
847870
2636
ืœืจื•ืคืื™ ืžื—ืงืจ?
14:10
And when someone accesses your medical record,
354
850506
3041
ื•ื›ืืฉืจ ืžื™ืฉื”ื• ื ื™ื’ืฉ ืœืชื™ืง ื”ืจืคื•ืื™ ืฉืœืš,
14:13
a research doctor,
355
853547
1609
ืจื•ืคื ืžื—ืงืจ.
14:15
they could see, you could see which doctor
356
855156
2634
ื”ื ื™ื•ื›ืœื• ืœืจืื•ืช, ืืชื” ืชื•ื›ืœ ืœืจืื•ืช ืื™ื–ื” ืจื•ืคื
14:17
accessed it and why,
357
857790
1860
ื ื™ื’ืฉ ืืœื™ื• ื•ืžื“ื•ืข,
14:19
and you could maybe learn about
358
859650
1580
ื•ื”ื™ื™ืช ื™ื›ื•ืœ ืื•ืœื™ ืœืœืžื•ื“
14:21
what conditions you have.
359
861230
1630
ืžื” ื”ืžืฆื‘ ืฉืœืš.
14:22
I think if we just did that,
360
862860
1502
ืื ื™ ื—ื•ืฉื‘ ืฉืื ืจืง ื”ื™ื™ื ื• ืขื•ืฉื™ื ืืช ื–ื”,
14:24
we'd save 100,000 lives this year.
361
864362
2165
ื”ื™ื™ื ื• ื—ื•ืกื›ื™ื ื—ื™ื™ื ืฉืœ 100,000 ืื ืฉื™ื ื‘ืฉื ื” ื–ื•.
14:26
CR: Absolutely. Let me go โ€” (Applause)
362
866527
2948
ืฆ.ืจ.: ื‘ื”ื—ืœื˜. ืชืŸ ืœื™ ืœื”ืžืฉื™ืš - (ืžื—ื™ืื•ืช ื›ืคื™ื™ื)
14:29
LP: So I guess I'm just very worried that
363
869475
2762
ืœ.ืค.: ืื– ืื ื™ ืžื ื™ื— ืฉืื ื™ ืคืฉื•ื˜ ืžื•ื“ืื’ ืžืื“
14:32
with Internet privacy,
364
872237
1806
ืžื ื•ืฉื ื”ืคืจื˜ื™ื•ืช ื‘ืื™ื ื˜ืจื ื˜,
14:34
we're doing the same thing we're doing with medical records,
365
874043
2300
ืื ื—ื ื• ืขื•ืฉื™ื ืืช ืื•ืชื• ื”ื“ื‘ืจ ืฉืื ื—ื ื• ืขื•ืฉื™ื ืขื ื”ืชื™ืง ื”ืจืคื•ืื™,
14:36
is we're throwing out the baby with the bathwater,
366
876347
2529
ื•ื”ื•ื ืฉืื ื—ื ื• ื–ื•ืจืงื™ื ืืช ื”ืชื™ื ื•ืง ืขื ืžื™ ื”ืืžื‘ื˜ื™ื”.
14:38
and we're not really thinking
367
878876
1828
ื•ืื ื—ื ื• ืœื ื‘ืืžืช ื—ื•ืฉื‘ื™ื
14:40
about the tremendous good that can come
368
880704
2210
ืขืœ ื”ืชื•ืขืœืช ื”ืื“ื™ืจื” ืฉื–ื” ื™ื›ื•ืœ ืœื”ื‘ื™ื
14:42
from people sharing information
369
882914
2191
ืžืื ืฉื™ื ืฉืžืฉืชืคื™ื ืžื™ื“ืข
14:45
with the right people in the right ways.
370
885105
2577
ืขื ื”ืื ืฉื™ื ื”ื ื›ื•ื ื™ื ื‘ื“ืจื›ื™ื ื”ื ื›ื•ื ื•ืช.
14:47
CR: And the necessary condition
371
887682
2237
ืฆ.ืจ.: ื•ื”ืชื ืื™ ื”ื”ื›ืจื—ื™
14:49
that people have to have confidence
372
889919
1702
ืฉืื ืฉื™ื ืฆืจื™ื›ื™ื ืœื”ืืžื™ืŸ
14:51
that their information will not be abused.
373
891621
2455
ืฉื”ืžื™ื“ืข ืฉืœื”ื ืœื ื™ื ื•ืฆืœ ืœืจืขื”.
14:54
LP: Yeah, and I had this problem with my voice stuff.
374
894076
1777
ืœ.ืค.: ื›ืŸ, ื•ื”ื™ื™ืชื” ืœื™ ื‘ืขื™ื” ื–ื• ืขื ื ื•ืฉื ื”ืงื•ืœ ืฉืœื™.
14:55
I was scared to share it.
375
895853
1508
ืคื—ื“ืชื™ ืœื—ืœื•ืง ืื•ืชื•.
14:57
Sergey encouraged me to do that,
376
897361
1890
ืกืจื’ื™ื™ ืขื•ื“ื“ ืื•ืชื™ ืœืขืฉื•ืช ืืช ื–ื”
14:59
and it was a great thing to do.
377
899251
1827
ื•ื–ื” ื”ื™ื” ื“ื‘ืจ ื’ื“ื•ืœ ืœืขืฉื•ืช.
15:01
CR: And the response has been overwhelming.
378
901078
1734
ืฆ.ืจ.: ื•ื”ืชื’ื•ื‘ื” ื”ื™ืชื” ืžื“ื”ื™ืžื”.
15:02
LP: Yeah, and people are super positive.
379
902812
1660
ืœ.ืค.: ื›ืŸ, ื•ื”ืื ืฉื™ื ื”ื ืกื•ืคืจ ื—ื™ื•ื‘ื™ื™ื.
15:04
We got thousands and thousands of people
380
904472
2833
ื™ืฉ ืœื ื• ืืœืคื™ ืจื‘ื‘ื•ืช ืื ืฉื™ื
15:07
with similar conditions,
381
907305
1288
ืขื ืชื ืื™ื ื“ื•ืžื™ื,
15:08
which there's no data on today.
382
908593
3028
ืœืœื ืฉื•ื ืžื™ื“ืข ื”ื™ื•ื.
15:11
So it was a really good thing.
383
911621
1356
ืื– ื–ื” ื”ื™ื” ื‘ืืžืช ืžืฉื”ื• ื˜ื•ื‘.
15:12
CR: So talking about the future, what is it about you
384
912977
3019
ืฆ.ืจ. : ืื– ื›ืฉืžื“ื‘ืจื™ื ืขืœ ื”ืขืชื™ื“, ืžื” ื™ืฉ ืœืš
15:15
and transportation systems?
385
915996
3758
ืขื ืžืขืจื›ื•ืช ืชื—ื‘ื•ืจื” ?
15:19
LP: Yeah. I guess I was just frustrated
386
919754
2177
ืœ.ืค.: ื›ืŸ. ืื ื™ ืžื ื™ื— ืฉืื ื™ ื”ื™ื™ืชื™ ืคืฉื•ื˜ ืžืชื•ืกื›ืœ
15:21
with this when I was at college in Michigan.
387
921931
2539
ืžื–ื” ื›ืฉื”ื™ื™ืชื™ ื‘ืžื›ืœืœืช ืžื™ืฉื™ื’ืŸ.
15:24
I had to get on the bus and take it
388
924470
1450
ื”ื™ื™ืชื™ ืฆืจื™ืš ืœืขืœื•ืช ืขืœ ื”ืื•ื˜ื•ื‘ื•ืก ื•ืœืงื—ืช ืื•ืชื•
15:25
and wait for it.
389
925920
1642
ื•ืœื—ื›ื•ืช ืœื•.
15:27
And it was cold and snowing.
390
927562
2179
ื•ื”ื™ื” ืงืจ ื•ื™ืจื“ ืฉืœื’.
15:29
I did some research on how much it cost,
391
929741
2655
ืขืฉื™ืชื™ ืžื—ืงืจ ืงื˜ืŸ ืขืœ ื›ืžื” ื–ื” ืขื•ืœื”,
15:32
and I just became a bit obsessed with transportation systems.
392
932396
6425
ื•ื”ืคื›ืชื™ ืœื”ื™ื•ืช ืงืฆืช ืื•ื‘ืกืกื™ื‘ื™ ืขื ืžืขืจื›ื•ืช ืชื—ื‘ื•ืจื”.
15:38
CR: And that began the idea of an automated car.
393
938821
2370
ืฆ.ืจ.: ื•ื–ื” ืžื” ืฉื”ื—ืœ ืืช ื”ืจืขื™ื•ืŸ ืฉืœ ืžื›ื•ื ื™ืช ืื•ื˜ื•ืžื˜ื™ืช.
15:41
LP: Yeah, about 18 years ago I learned about
394
941191
1694
ืœ.ืค.: ื›ืŸ, ืœืคื ื™ ื›-18 ืฉื ื” ืœืžื“ืชื™ ืขืœ
15:42
people working on automated cars,
395
942885
3182
ืื ืฉื™ื ืฉืขื•ื‘ื“ื™ื ืขืœ ืžื›ื•ื ื™ื•ืช ืื•ื˜ื•ืžื˜ื™ื•ืช,
15:46
and I became fascinated by that,
396
946067
1623
ื•ื”ื•ืงืกืžืชื™ ืžื–ื”,
15:47
and it takes a while to get these projects going,
397
947690
2777
ื•ื–ื” ืœื•ืงื— ื–ืžืŸ ืœื”ื•ืฆื™ื ืคืจื•ื™ืงื˜ื™ื ื›ืืœื” ืœื“ืจืš,
15:50
but I'm super excited about the possibilities of that
398
950467
5097
ืื‘ืœ ืื ื™ ืžืื•ื“ ืžืชืจื’ืฉ ืœื’ื‘ื™ ื”ืืคืฉืจื•ื™ื•ืช ืฉืœ ื–ื”
15:55
improving the world.
399
955564
1668
ืœืฉืคืจ ืืช ื”ืขื•ืœื.
15:57
There's 20 million people or more injured per year.
400
957232
4526
20 ืžื™ืœื™ื•ืŸ ืื ืฉื™ื ืื• ื™ื•ืชืจ ื ืคื’ืขื™ื ื‘ื›ืœ ืฉื ื”.
16:01
It's the leading cause of death
401
961758
1986
ื–ื” ื”ื’ื•ืจื ืžืก. 1 ืœืžื•ื•ืช
16:03
for people under 34 in the U.S.
402
963744
2130
ืฉืœ ืื ืฉื™ื ืžืชื—ืช ืœื’ื™ืœ 34 ื‘ืืจืฆื•ืช ื”ื‘ืจื™ืช.
16:05
CR: So you're talking about saving lives.
403
965874
1551
ืฆ.ืจ.: ืื– ืืชื” ืžื“ื‘ืจ ืขืœ ื”ืฆืœืช ื—ื™ื™ื.
16:07
LP: Yeah, and also saving space
404
967425
2355
ืœ.ืค.: ื›ืŸ, ื•ื’ื ื—ื™ืกื›ื•ืŸ ื‘ืžืงื•ื
16:09
and making life better.
405
969780
3915
ื•ืœื”ืคื•ืš ืืช ื”ื—ื™ื™ื ืœื˜ื•ื‘ื™ื ื™ื•ืชืจ.
16:13
Los Angeles is half parking lots and roads,
406
973695
4245
ื—ืฆื™ ืžืœื•ืก ืื ื’'ืœืก ื”ื•ื ื—ื ื™ื•ื ื™ื ื•ื›ื‘ื™ืฉื™ื,
16:17
half of the area,
407
977940
1733
ื—ืฆื™ ืžื”ืื–ื•ืจ,
16:19
and most cities are not far behind, actually.
408
979673
2827
ื•ืจื•ื‘ ื”ืขืจื™ื ืœื ื ืžืฆืื•ืช ื”ืจื—ืง ืžืื—ื•ืจ, ืœืžืขืŸ ื”ืืžืช.
16:22
It's just crazy
409
982500
1564
ื–ื” ืคืฉื•ื˜ ืžื˜ื•ืจืฃ
16:24
that that's what we use our space for.
410
984064
1593
ืœืžื” ื”ืฉื˜ื— ืฉืœื ื• ืžืฉืžืฉ.
16:25
CR: And how soon will we be there?
411
985657
2343
ืฆ.ืจ.: ื•ื›ืžื” ืžื”ืจ ืื ื—ื ื• ื ื”ื™ื” ืฉื?
16:28
LP: I think we can be there very, very soon.
412
988000
1926
ืœ.ืค.: ืื ื™ ื—ื•ืฉื‘ ืฉื ื•ื›ืœ ืœื”ื™ื•ืช ืฉื ืžืื•ื“, ืžืื•ื“ ื‘ืงืจื•ื‘.
16:29
We've driven well over 100,000 miles
413
989926
3501
ืื ื—ื ื• ื ืกืขื ื• ืžืขืœ 160000 ืงื™ืœื•ืžื˜ืจ
16:33
now totally automated.
414
993427
4093
ื›ืขืช ืœื’ืžืจื™ ืื•ื˜ื•ืžื˜ื™ืช.
16:37
I'm super excited about getting that out quickly.
415
997520
3652
ืื ื™ ืžืžืฉ ื ืจื’ืฉ ืœืฆืืช ืขื ื–ื” ืžื”ืจ.
16:41
CR: But it's not only you're talking about automated cars.
416
1001172
2405
ืฆ.ืจ.: ืื‘ืœ ืืชื” ืœื ืจืง ืžื“ื‘ืจ ืขืœ ืžื›ื•ื ื™ื•ืช ืื•ื˜ื•ืžื˜ื™ื•ืช.
16:43
You also have this idea for bicycles.
417
1003577
2386
ื™ืฉ ืœืš ื’ื ืืช ื”ืจืขื™ื•ืŸ ื”ื–ื” ืœืื•ืคื ื™ื™ื.
16:45
LP: Well at Google, we got this idea
418
1005963
2246
ืœ.ืค.: ื˜ื•ื‘ ื‘ื’ื•ื’ืœ, ื™ืฉ ืœื ื• ืืช ื”ืจืขื™ื•ืŸ ื”ื–ื”
16:48
that we should just provide free bikes to everyone,
419
1008209
3451
ืฉืื ื—ื ื• ืฆืจื™ื›ื™ื ืจืง ืœืกืคืง ืื•ืคื ื™ื™ื ื‘ื—ื™ื ื ืœื›ื•ืœื.
16:51
and that's been amazing, most of the trips.
420
1011660
2768
ื•ื–ื” ื”ื™ื” ืžื“ื”ื™ื, ืจื•ื‘ ื”ื ืกื™ืขื•ืช.
16:54
You see bikes going everywhere,
421
1014428
1586
ืจื•ืื™ื ืื•ืคื ื™ื™ื ื‘ื›ืœ ืžืงื•ื,
16:56
and the bikes wear out.
422
1016014
1566
ื•ื”ืื•ืคื ื™ื™ื ืžืชื‘ืœื™ื.
16:57
They're getting used 24 hours a day.
423
1017580
1454
ืžืฉืชืžืฉื™ื ื‘ื”ืŸ 24 ืฉืขื•ืช ื‘ื™ืžืžื”.
16:59
CR: But you want to put them above the street, too.
424
1019034
2160
ืฆ.ืจ: ืื‘ืœ ืืชื” ืจื•ืฆื” ื’ื ืœืฉื™ื ืื•ืชื ืžืขืœ ื”ืจื—ื•ื‘,
17:01
LP: Well I said, how do we get people
425
1021194
1575
ืœ.ืค.: ื•ื‘ื›ืŸ ืืžืจืชื™, ืื™ืš ื’ื•ืจืžื™ื ืœืื ืฉื™ื
17:02
using bikes more?
426
1022769
1527
ืœื”ืฉืชืžืฉ ื™ื•ืชืจ ื‘ืื•ืคื ื™ื™ื?
17:04
CR: We may have a video here.
427
1024296
1625
ืฆ.ืจ.: ื™ื›ื•ืœ ืœื”ื™ื•ืช ืฉื™ืฉ ืœื ื• ื›ืืŸ ื•ื™ื“ืื•.
17:05
LP: Yeah, let's show the video.
428
1025921
1278
ืœ.ืค.: ื›ืŸ, ื‘ื•ืื• ื•ื ืจืื” ืืช ื”ื•ื™ื“ืื•.
17:07
I just got excited about this.
429
1027199
3092
ืื ื™ ืคืฉื•ื˜ ื ืจื’ืฉ ืžื–ื”.
17:10
(Music)
430
1030291
4042
(ืžื•ืกื™ืงื”)
17:16
So this is actually how you might separate
431
1036213
2425
ืื– ื›ืš ื‘ืขืฆื ืืชื” ื™ื›ื•ืœ ืœื”ืคืจื™ื“
17:18
bikes from cars with minimal cost.
432
1038638
3629
ืื•ืคื ื™ื™ื ืžืžื›ื•ื ื™ื•ืช ื‘ืขืœื•ืช ืžื™ื ื™ืžืœื™ืช.
17:26
Anyway, it looks totally crazy,
433
1046711
1755
ื‘ื›ืœ ืžืงืจื”, ื–ื” ื ืจืื” ืžื˜ื•ืจืฃ ืœื’ืžืจื™,
17:28
but I was actually thinking about our campus,
434
1048466
2327
ืื‘ืœ ืœืžืขืฉื” ื—ืฉื‘ืชื™ ืขืœ ื”ืงืžืคื•ืก ืฉืœื ื•.
17:30
working with the Zippies and stuff,
435
1050793
2060
ืขื‘ื•ื“ื” ืขื ืขืจื™ื ื•ื›ื“'.
17:32
and just trying to get a lot more bike usage,
436
1052853
2298
ื•ืจืง ืžื ืกื” ืœื”ืฉื™ื’ ื”ืจื‘ื” ื™ื•ืชืจ ืฉื™ืžื•ืฉ ื‘ืื•ืคื ื™ื™ื,
17:35
and I was thinking about,
437
1055151
1548
ื•ื—ืฉื‘ืชื™,
17:36
how do you cost-effectively separate
438
1056699
2831
ื›ื™ืฆื“ ื ื™ืชืŸ ื‘ืื•ืคืŸ ื—ืกื›ื•ื ื™ ืœื”ืคืจื™ื“
17:39
the bikes from traffic?
439
1059530
1414
ืืช ื”ืื•ืคื ื™ื™ื ืžื”ืชื ื•ืขื”?
17:40
And I went and searched,
440
1060944
1150
ื•ื”ืœื›ืชื™ ื•ื—ื™ืคืฉืชื™,
17:42
and this is what I found.
441
1062094
1371
ื•ื–ื” ืžื” ืฉืžืฆืืชื™.
17:43
And we're not actually working on this,
442
1063465
1845
ื•ืื ื—ื ื• ืœื ืžืžืฉ ืขื•ื‘ื“ื™ื ืขืœ ื–ื”,
17:45
that particular thing,
443
1065310
1292
ืขืœ ื”ื“ื‘ืจ ื”ืžืกื•ื™ื ื”ื–ื”.
17:46
but it gets your imagination going.
444
1066602
2054
ืื‘ืœ ื–ื” ื’ื•ืจื ืœื“ืžื™ื•ืŸ ืฉืœืš ืœืคืขื•ืœ.
17:48
CR: Let me close with this.
445
1068656
1764
ืฆ.ืจ.: ืชืŸ ืœื™ ืœืกื™ื™ื ืขื ื–ื”.
17:50
Give me a sense of the philosophy of your own mind.
446
1070420
2345
ืชืŸ ืœื™ ืชื—ื•ืฉื” ืฉืœ ื”ืคื™ืœื•ืกื•ืคื™ื” ืฉืœ ื”ืžื™ื™ื ื“ ืฉืœืš.
17:52
You have this idea of [Google X].
447
1072765
2488
ื™ืฉ ืœืš ืืช ื”ืจืขื™ื•ืŸ ืฉืœ ื’ื•ื’ืœ X.
17:55
You don't simply want
448
1075253
2996
ืืชื” ืœื ืจื•ืฆื” ืคืฉื•ื˜
17:58
to go in some small, measurable arena of progress.
449
1078249
5596
ืœืœื›ืช ื‘ื–ื™ืจื” ืงื˜ื ื” ืฉืœ ื”ืชืงื“ืžื•ืช, ืฉื ื™ืชื ืช ืœืžื“ื™ื“ื”.
18:03
LP: Yeah, I think
450
1083845
1713
ืœ.ืค: ื›ืŸ, ืื ื™ ื—ื•ืฉื‘
18:05
many of the things we just talked about are like that,
451
1085558
2131
ื”ืจื‘ื” ืžื”ื“ื‘ืจื™ื ืฉื“ื™ื‘ืจื ื• ืขืœื™ื”ื ื”ื ื›ืืœื”.
18:07
where they're really --
452
1087689
2952
ื”ื™ื›ืŸ ืฉื”ื ื‘ืืžืช --
18:10
I almost use the economic concept of additionality,
453
1090641
3630
ืื ื™ ื›ืžืขื˜ ืžืฉืชืžืฉ ื‘ืžื•ืฉื’ ื”ื›ืœื›ืœื™ ืฉืœ ื”ื•ืกืคื”,
18:14
which means that you're doing something
454
1094271
2190
ืžื” ืฉืื•ืžืจ ืฉืืชื” ืขื•ืฉื” ืžืฉื”ื•
18:16
that wouldn't happen unless you were actually doing it.
455
1096461
2948
ืฉืœื ื™ืงืจื” ืืœื ืื ื›ืŸ ืืชื” ื‘ืืžืช ืขื•ืฉื” ื–ืืช
18:19
And I think the more you can do things like that,
456
1099409
3140
ื•ืื ื™ ื—ื•ืฉื‘ ืฉื›ื›ืœ ืฉืืชื” ื™ื›ื•ืœ ืœืขืฉื•ืช ื™ื•ืชืจ ื“ื‘ืจื™ื ื›ืืœื”,
18:22
the bigger impact you have,
457
1102549
2071
ืชื”ื™ื” ืœืš ื™ื•ืชืจ ื”ืฉืคืขื”,
18:24
and that's about doing things
458
1104620
2990
ื•ื–ื” ืขืœ ืขืฉื™ื™ืช ื“ื‘ืจื™ื
18:27
that people might not think are possible.
459
1107610
3607
ืฉืื ืฉื™ื ืขืฉื•ื™ื™ื ืœื—ืฉื•ื‘ ืฉืื™ื ื ืืคืฉืจื™ื™ื.
18:31
And I've been amazed,
460
1111217
1829
ื•ื ื“ื”ืžืชื™,
18:33
the more I learn about technology,
461
1113046
2229
ื›ื›ืœ ืฉืื ื™ ืœื•ืžื“ ื™ื•ืชืจ ืขืœ ื˜ื›ื ื•ืœื•ื’ื™ื”,
18:35
the more I realize I don't know,
462
1115275
2196
ื™ื•ืชืจ ืื ื™ ืžื‘ื™ืŸ ืฉืื ื™ ืœื ื™ื•ื“ืข
18:37
and that's because this technological horizon,
463
1117471
3337
ื•ื–ื” ืžืฉื•ื ืฉื”ืื•ืคืง ื”ื˜ื›ื ื•ืœื•ื’ื™,
18:40
the thing that you can see to do next,
464
1120808
2897
ื”ื“ื‘ืจ ืฉืืชื” ื™ื›ื•ืœ ืœืจืื•ืช ืžื”ื• ื”ืฆืขื“ ื”ื‘ื.
18:43
the more you learn about technology,
465
1123705
1840
ื›ื›ืœ ืฉืืชื” ืœื•ืžื“ ื™ื•ืชืจ ืขืœ ื˜ื›ื ื•ืœื•ื’ื™ื”,
18:45
the more you learn what's possible.
466
1125545
2602
ืืชื” ืœื•ืžื“ ื™ื•ืชืจ ืžื” ืืคืฉืจื™.
18:48
You learn that the balloons are possible
467
1128147
2246
ืœืžื“ืช ืฉื”ื‘ืœื•ื ื™ื ืืคืฉืจื™ื™ื
18:50
because there's some material that will work for them.
468
1130393
2337
ืžืฉื•ื ืฉื™ืฉ ื—ื•ืžืจ ืฉื™ืขื‘ื•ื“ ืขื‘ื•ืจื.
18:52
CR: What's interesting about you too, though, for me,
469
1132730
2379
ืฆ.ืจ.: ืžื” ืฉืžืขื ื™ื™ืŸ ืขื‘ื•ืจื™ , ืื•ืœื
18:55
is that, we have lots of people
470
1135109
1711
ื–ื” ืฉื™ืฉ ืœื ื• ื”ืžื•ืŸ ืื ืฉื™ื
18:56
who are thinking about the future,
471
1136820
2142
ืฉื—ื•ืฉื‘ื™ื ืขืœ ื”ืขืชื™ื“,
18:58
and they are going and looking and they're coming back,
472
1138962
3268
ื•ื”ื ื”ื•ืœื›ื™ื ื•ืžืกืชื›ืœื™ื, ื•ื”ื ื—ื•ื–ืจื™ื,
19:02
but we never see the implementation.
473
1142230
2127
ืื‘ืœ ืื ื—ื ื• ืœื ืจื•ืื™ื ืืช ื”ืžื™ืžื•ืฉ.
19:04
I think of somebody you knew
474
1144357
1605
ืื ื™ ื—ื•ืฉื‘ ืขืœ ืžื™ืฉื”ื• ืฉื”ื›ืจืช
19:05
and read about, Tesla.
475
1145962
2907
ื•ืงืจืืช, ืขืœื™ื•, ื˜ืกืœื”.
19:08
The principle of that for you is what?
476
1148869
3804
ื”ืขื™ืงืจื•ืŸ ืฉืœ ื–ื” ื‘ืฉื‘ื™ืœืš ื”ื•ื ืžื”?
19:12
LP: Well, I think invention is not enough.
477
1152673
1785
ืœ.ืค.: ืœื“ืขืชื™ ืœื”ืžืฆื™ื ื–ื” ืœื ืžืกืคื™ืง.
19:14
If you invent something,
478
1154458
1221
ืื ืืชื” ืžืžืฆื™ื ืžืฉื”ื•.
19:15
Tesla invented electric power that we use,
479
1155679
3195
ื˜ืกืœื” ื”ืžืฆื™ื ืืช ื”ื–ืจื ื”ื—ืฉืžืœื™ ืฉื‘ื• ืื ื• ืžืฉืชืžืฉื™ื,
19:18
but he struggled to get it out to people.
480
1158874
2661
ืื‘ืœ ื”ื•ื ื ืื‘ืง ืœื”ื‘ื™ื ืืช ื–ื” ืœืื ืฉื™ื.
19:21
That had to be done by other people.
481
1161535
1684
ื–ื” ื”ื™ื” ื—ื™ื™ื‘ ืœื”ื™ืขืฉื•ืช ืขืœ ื™ื“ื™ ืื ืฉื™ื ืื—ืจื™ื.
19:23
It took a long time.
482
1163219
1626
ื–ื” ืœืงื— ื”ืจื‘ื” ื–ืžืŸ.
19:24
And I think if we can actually combine both things,
483
1164845
3867
ื•ืื ื™ ื—ื•ืฉื‘ ืฉืื ืื ื—ื ื• ื™ื›ื•ืœื™ื ืœืžืขืฉื” ืœืฉืœื‘ ืืช ืฉื ื™ ื“ื‘ืจื™ื,
19:28
where we have an innovation and invention focus,
484
1168712
3531
ื”ื™ื›ืŸ ืฉื™ืฉ ืœื ื• ืžื™ืงื•ื“ ืขืœ ื—ื“ืฉื ื•ืช ื•ื”ืžืฆืื”,
19:32
plus the ability to really -- a company
485
1172243
2972
ื‘ืชื•ืกืคืช ื”ื™ื›ื•ืœืช ืฉืชื”ื™ื” ืžืžืฉ -- ื—ื‘ืจื”.
19:35
that can really commercialize things
486
1175215
1998
ืฉื™ื›ื•ืœื” ืžืžืฉ ืœืžืกื—ืจ ื“ื‘ืจื™ื
19:37
and get them to people
487
1177213
1630
ื•ืœื”ื‘ื™ื ืื•ืชื ืœืื ืฉื™ื
19:38
in a way that's positive for the world
488
1178843
2075
ื‘ื“ืจืš ืฉื”ื™ื ื—ื™ื•ื‘ื™ืช ืœืขื•ืœื
19:40
and to give people hope.
489
1180918
2056
ื•ืœืชืช ืœืื ืฉื™ื ืชืงื•ื•ื”.
19:42
You know, I'm amazed with the Loon Project
490
1182974
2774
ืืชื” ื™ื•ื“ืข, ืื ื™ ื ื“ื”ื ืžืคืจื•ื™ื™ืงื˜ ืœื•ืŸ
19:45
just how excited people were about that,
491
1185748
2786
ืขื“ ื›ืžื” ืื ืฉื™ื ื”ื™ื• ื ืจื’ืฉื™ื ืžื›ืš,
19:48
because it gave them hope
492
1188534
1814
ื›ื™ ื–ื” ื ืชืŸ ืœื”ื ืชืงื•ื•ื”
19:50
for the two thirds of the world
493
1190348
1621
ืขื‘ื•ืจ ืฉื ื™ ืฉืœื™ืฉื™ื ืžื”ืขื•ืœื
19:51
that doesn't have Internet right now that's any good.
494
1191969
2726
ืฉืื™ืŸ ืœื”ื ืื™ื ื˜ืจื ื˜ ืขื›ืฉื™ื• ืฉื”ื•ื ืื™ื›ืฉื”ื• ื˜ื•ื‘.
19:54
CR: Which is a second thing about corporations.
495
1194695
2122
ืฆ.ืจ: ืฉื–ื” ื“ื‘ืจ ื”ืฉื ื™ ื‘ื ื•ืฉื ืชืื’ื™ื“ื™ื.
19:56
You are one of those people who believe
496
1196817
2476
ืืชื” ืื—ื“ ืžืืœื” ืฉืžืืžื™ื ื™ื
19:59
that corporations are an agent of change
497
1199293
2317
ืฉืชืื’ื™ื“ื™ื ื”ื ืกื•ื›ื ื™ื ืฉืœ ืฉื™ื ื•ื™
20:01
if they are run well.
498
1201610
1471
ืื ื”ื ืคื•ืขืœื™ื ื˜ื•ื‘.
20:03
LP: Yeah. I'm really dismayed
499
1203081
1821
ืœ.ืค.: ื›ืŸ. ืื ื™ ืžืžืฉ ื ื—ืจื“
20:04
most people think companies are basically evil.
500
1204902
3294
ืžื›ืš ืฉืจื•ื‘ ื”ืื ืฉื™ื ื—ื•ืฉื‘ื™ื ืฉื—ื‘ืจื•ืช ื”ืŸ ืจืขื•ืช ื‘ื™ืกื•ื“ืŸ.
20:08
They get a bad rap.
501
1208196
1766
ื”ืŸ ื–ื•ื›ื•ืช ืœืžื•ื ื™ื˜ื™ืŸ ื’ืจื•ืข.
20:09
And I think that's somewhat correct.
502
1209962
2241
ื•ืœื“ืขืชื™ ื–ื” ืงืฆืช ื ื›ื•ืŸ.
20:12
Companies are doing the same incremental thing
503
1212203
2870
ื—ื‘ืจื•ืช ืขื•ืฉื•ืช ืืช ืื•ืชื• ื“ื‘ืจ ื”ื“ืจื’ืชื™
20:15
that they did 50 years ago
504
1215073
1763
ืฉื”ืŸ ืขืฉื• ืœืคื ื™ 50 ืฉื ื”
20:16
or 20 years ago.
505
1216836
1631
ืื• ืœืคื ื™ 20 ืฉื ื”.
20:18
That's not really what we need.
506
1218467
1370
ืฉื–ื” ืœื ื‘ืืžืช ืžื” ืฉืื ื—ื ื• ืฆืจื™ื›ื™ื.
20:19
We need, especially in technology,
507
1219837
2218
ืื ื—ื ื• ืฆืจื™ื›ื™ื, ื‘ืžื™ื•ื—ื“ ื‘ืชื—ื•ื ื”ื˜ื›ื ื•ืœื•ื’ื™ื”,
20:22
we need revolutionary change,
508
1222055
2117
ืื ื—ื ื• ืฆืจื™ื›ื™ื ืฉื™ื ื•ื™ ืžื”ืคื›ื ื™,
20:24
not incremental change.
509
1224172
1413
ืœื ืฉื™ื ื•ื™ ื”ื“ืจื’ืชื™.
20:25
CR: You once said, actually,
510
1225585
1169
ืฆ.ืจ.: ืืžืจืช ืœื™ ืคืขื, ืœืžืขืฉื”,
20:26
as I think I've got this about right,
511
1226754
1818
ืฉืื ื™ ื—ื•ืฉื‘ ืฉื”ื‘ื ืชื™ ื–ืืช ื ื›ื•ืŸ,
20:28
that you might consider,
512
1228572
1645
ืฉื™ื™ืชื›ืŸ ืฉืืชื” ืชืฉืงื•ืœ.
20:30
rather than giving your money,
513
1230217
1753
ื‘ืžืงื•ื ืœืชืช ืืช ื”ื›ืกืฃ ืฉืœืš
20:31
if you were leaving it to some cause,
514
1231970
3320
ืื ื”ื™ื™ืช ืžืฉืื™ืจ ืื•ืชื• ืœืžื˜ืจื” ื›ืœืฉื”ื™,
20:35
just simply giving it to Elon Musk,
515
1235290
2006
ืคืฉื•ื˜ ืœืชืช ืื•ืชื• ืœืืœื•ืŸ ืžืืกืง,
20:37
because you had confidence
516
1237296
1163
ืžืฉื•ื ืฉื”ื™ื” ืœืš ื‘ื™ื˜ื—ื•ืŸ
20:38
that he would change the future,
517
1238459
1842
ืฉื”ื•ื ื™ืฉื ื” ืืช ื”ืขืชื™ื“,
20:40
and that you would therefore โ€”
518
1240301
1777
ื•ืฉื”ื™ื™ืช ืœืคื™ื›ืš -
20:42
LP: Yeah, if you want to go Mars,
519
1242078
1584
ืœ.ืค.: ื›ืŸ, ืื ืืชื” ืจื•ืฆื” ืœื”ื’ื™ืข ืœืžืื“ื™ื.
20:43
he wants to go to Mars,
520
1243662
1721
ื”ื•ื ืจื•ืฆื” ืœื”ื’ื™ืข ืœืžืื“ื™ื,
20:45
to back up humanity,
521
1245383
1971
ื›ื“ื™ ืœื’ื‘ื•ืช ืืช ื”ืื ื•ืฉื•ืช,
20:47
that's a worthy goal, but it's a company,
522
1247354
1672
ื–ื• ืžื˜ืจื” ืจืื•ื™ื”, ืื‘ืœ ื–ื• ื—ื‘ืจื”,
20:49
and it's philanthropical.
523
1249026
2555
ื•ื”ื™ื ืคื™ืœื ื˜ืจื•ืคื™ืช.
20:51
So I think we aim to do kind of similar things.
524
1251581
2952
ืื– ืื ื™ ื—ื•ืฉื‘ ืฉืื ื• ืฉื•ืืคื™ื ืœืขืฉื•ืช ืกื•ื’ ืฉืœ ื“ื‘ืจื™ื ื“ื•ืžื™ื.
20:54
And I think, you ask, we have a lot of employees
525
1254533
2987
ื•ืื ื™ ื—ื•ืฉื‘, ืฉืืชื” ืฉื•ืืœ, ืฉื™ืฉ ืœื ื• ื”ืจื‘ื” ืขื•ื‘ื“ื™ื
20:57
at Google who have become pretty wealthy.
526
1257520
3315
ื‘ื’ื•ื’ืœ ืฉื”ืคื›ื• ืœืขืฉื™ืจื™ื ืœืžื“ื™.
21:00
People make a lot of money in technology.
527
1260835
2520
ืื ืฉื™ื ืขื•ืฉื™ื ื”ืจื‘ื” ื›ืกืฃ ื‘ืชื—ื•ื ื”ื˜ื›ื ื•ืœื•ื’ื™ื”.
21:03
A lot of people in the room are pretty wealthy.
528
1263355
2156
ื”ืจื‘ื” ืื ืฉื™ื ื‘ืื•ืœื ื”ื ื“ื™ ืขืฉื™ืจื™ื.
21:05
You're working because you want to change the world.
529
1265511
2314
ืืชื” ืขื•ื‘ื“ ื›ื™ ืืชื” ืจื•ืฆื” ืœืฉื ื•ืช ืืช ื”ืขื•ืœื
21:07
You want to make it better.
530
1267825
1762
ืืชื” ืจื•ืฆื” ืœืขืฉื•ืช ืื•ืชื• ืœื˜ื•ื‘ ื™ื•ืชืจ.
21:09
Why isn't the company that you work for
531
1269587
3445
ืžื“ื•ืข ื”ื—ื‘ืจื” ืฉืืชื” ืขื•ื‘ื“ ื‘ืฉื‘ื™ืœื” ืื™ื ื”
21:13
worthy not just of your time
532
1273032
1943
ืจืื•ื™ื” ืœื ืจืง ืœื–ืžืŸ ืฉืœืš
21:14
but your money as well?
533
1274975
2151
ืืœื ื’ื ืœื›ืกืฃ ืฉืœืš?
21:17
I mean, but we don't have a concept of that.
534
1277126
1722
ืื ื™ ืžืชื›ื•ื•ืŸ, ืื‘ืœ ืื™ืŸ ืœื ื• ืืช ื”ืจืขื™ื•ืŸ ื”ื–ื”.
21:18
That's not how we think about companies,
535
1278848
2304
ื–ื” ืœื ืžื” ืฉืื ื—ื ื• ื—ื•ืฉื‘ื™ื ืขืœ ื—ื‘ืจื•ืช,
21:21
and I think it's sad,
536
1281152
1467
ื•ืื ื™ ื—ื•ืฉื‘ ืฉื–ื” ืขืฆื•ื‘,
21:22
because companies are most of our effort.
537
1282619
3767
ื›ื™ ื—ื‘ืจื•ืช ื”ืŸ ืจื•ื‘ ื”ืžืืžืฅ ืฉืœื ื•.
21:26
They're where most of people's time is,
538
1286386
2515
ื”ืŸ ืื™ืคื” ืฉืžื•ืฉืงืข ืจื•ื‘ ื–ืžื ื ืฉืœ ืื ืฉื™ื
21:28
where a lot of the money is,
539
1288901
1854
ืื™ืคื” ืฉื™ืฉ ื”ืจื‘ื” ื›ืกืฃ,
21:30
and so I think I'd like for us to help out
540
1290755
2352
ืื– ืื ื™ ื—ื•ืฉื‘ ืฉื”ื™ื™ืชื™ ืฉืžื— ืœื• ืขื–ืจื ื•
21:33
more than we are.
541
1293107
1126
ื™ื•ืชืจ ืžืืฉืจ ืื ื—ื ื• ืขื•ืฉื™ื ื–ืืช.
21:34
CR: When I close conversations with lots of people,
542
1294233
1721
ืฆ.ืจ.: ื›ืฉืื ื™ ืžืกื™ื™ื ืฉื™ื—ื•ืช ืขื ื”ืจื‘ื” ืื ืฉื™ื,
21:35
I always ask this question:
543
1295954
1779
ืื ื™ ืชืžื™ื“ ืฉื•ืืœ ืืช ื”ืฉืืœื” ื”ื–ื•:
21:37
What state of mind,
544
1297733
1515
ืžื” ื”ืœืš ื”ืจื•ื—,
21:39
what quality of mind is it
545
1299248
1809
ืžื”ื™ ืื™ื›ื•ืช ื”ืœืš ืจื•ื— ื–ื”
21:41
that has served you best?
546
1301057
1767
ืฉืฉื™ืจืช ืื•ืชืš ื”ื›ื™ ื˜ื•ื‘?
21:42
People like Rupert Murdoch have said curiosity,
547
1302824
2521
ืื ืฉื™ื ื›ืžื• ืจื•ืคืจื˜ ืžื•ืจื“ื•ืš ืืžืจื• ืกืงืจื ื•ืช,
21:45
and other people in the media have said that.
548
1305345
2628
ื•ืื ืฉื™ื ืื—ืจื™ื ื‘ืชืงืฉื•ืจืช ืืžืจื• ื–ืืช.
21:47
Bill Gates and Warren Buffett have said focus.
549
1307973
3024
ื‘ื™ืœ ื’ื™ื™ื˜ืก ื•ื•ื•ืจืŸ ื‘ืืคื˜ ืืžืจื• ืฉื”ื”ืชืžืงื“ื•ืช.
21:50
What quality of mind,
550
1310997
1427
ืื™ื–ื• ืื™ื›ื•ืช ืฉืœ ืžื™ื™ื ื“,
21:52
as I leave this audience,
551
1312424
1374
ื›ืฉืื ื™ ืขื•ื–ื‘ ื”ืงื”ืœ ื”ื–ื”,
21:53
has enabled you to think about the future
552
1313798
3530
ืืคืฉืจ ืœืš ืœื—ืฉื•ื‘ ืขืœ ื”ืขืชื™ื“
21:57
and at the same time
553
1317328
1647
ื•ื‘ืื•ืชื• ื”ื–ืžืŸ
21:58
change the present?
554
1318975
2205
ืœืฉื ื•ืช ืืช ื”ื”ื•ื•ื”?
22:01
LP: You know, I think the most important thing --
555
1321180
1670
ืœ.ืค.: ืืชื” ื™ื•ื“ืข, ืื ื™ ื—ื•ืฉื‘ ืฉื”ื“ื‘ืจ ื”ื—ืฉื•ื‘ ื‘ื™ื•ืชืจ --
22:02
I looked at lots of companies
556
1322850
1612
ื”ืกืชื›ืœืชื™ ืขืœ ื”ืจื‘ื” ื—ื‘ืจื•ืช
22:04
and why I thought they don't succeed over time.
557
1324462
3303
ื•ืขืœ ื”ืกื™ื‘ื” ืฉื—ืฉื‘ืชื™ ืฉื”ืŸ ืœื ืžืฆืœื™ื—ื•ืช ืœืื•ืจืš ื–ืžืŸ.
22:07
We've had a more rapid turnover of companies.
558
1327765
2833
ื”ื™ืชื” ืœื ื• ืชื—ืœื•ืคื” ืžื”ื™ืจื” ื™ื•ืชืจ ืฉืœ ื—ื‘ืจื•ืช.
22:10
And I said, what did they fundamentally do wrong?
559
1330598
2769
ื•ืืžืจืชื™, ื”ื™ื›ืŸ ื”ื ื˜ืขื• ื‘ืื•ืคืŸ ื‘ืกื™ืกื™?
22:13
What did those companies all do wrong?
560
1333367
2167
ืžื” ื›ืœ ืื•ืชืŸ ื—ื‘ืจื•ืช ื”ืืœื” ืขืฉื• ืœื ื‘ืกื“ืจ?
22:15
And usually it's just that they missed the future.
561
1335534
3272
ื•ื‘ื“ืจืš ื›ืœืœ ื–ื” ืจืง ืฉื”ื ืคืกืคืกื• ืืช ื”ืขืชื™ื“.
22:18
And so I think, for me,
562
1338806
2444
ืื– ืื ื™ ื—ื•ืฉื‘, ื‘ืฉื‘ื™ืœื™,
22:21
I just try to focus on that and say,
563
1341250
2424
ืื ื™ ืจืง ืื ืกื” ืœื”ืชืžืงื“ ืขืœ ื–ื” ื•ืœื•ืžืจ,
22:23
what is that future really going to be
564
1343674
2184
ืžื” ื”ืขืชื™ื“ ื”ื–ื” ื‘ืืžืช ื”ื•ืœืš ืœื”ื™ื•ืช
22:25
and how do we create it,
565
1345858
1787
ื•ืื™ืš ืื ื—ื ื• ื™ื•ืฆืจื™ื ืืช ื–ื”,
22:27
and how do we cause our organization,
566
1347645
4667
ื•ืื™ืš ื ื•ื›ืœ ืœื’ืจื•ื ืœืืจื’ื•ืŸ ืฉืœื ื•,
22:32
to really focus on that
567
1352312
2440
ืœื”ืชืจื›ื– ื‘ื–ื” ื‘ืืžืช
22:34
and drive that at a really high rate?
568
1354752
3325
ื•ืœื”ื ื™ืข ืืช ื–ื” ื‘ืงืฆื‘ ืžืžืฉ ื’ื‘ื•ื”?
22:38
And so that's been curiosity,
569
1358077
1360
ื•ื›ืš ื–ื• ื”ื™ืชื” ืกืงืจื ื•ืช,
22:39
it's been looking at things
570
1359437
1733
ื–ื” ื”ื™ื” ืœื”ืกืชื›ืœ ืขืœ ื“ื‘ืจื™ื
22:41
people might not think about,
571
1361170
1718
ืฉืื ืฉื™ื ืื•ืœื™ ืœื ืœื—ื•ืฉื‘ื™ื ืขืœื™ื”ื,
22:42
working on things that no one else is working on,
572
1362888
3105
ืœืขื‘ื•ื“ ืขืœ ื“ื‘ืจื™ื ืฉืืฃ ืื—ื“ ืื—ืจ ืœื ืขื•ื‘ื“ ืขืœื™ื”ื,
22:45
because that's where the additionality really is,
573
1365993
3306
ื›ื™ ื–ื” ืื™ืคื” ืฉื‘ืืžืช ื™ืฉ ื”ื•ืกืคื”,
22:49
and be willing to do that,
574
1369299
1551
ื•ืœื”ื™ื•ืช ืžื•ื›ืŸ ืœืขืฉื•ืช ื–ืืช
22:50
to take that risk.
575
1370850
1382
ืœืงื—ืช ืืช ื”ืกื™ื›ื•ืŸ.
22:52
Look at Android.
576
1372232
1065
ื”ืกืชื›ืœ ืขืœ ืื ื“ืจื•ืื™ื“.
22:53
I felt guilty about working on Android
577
1373297
2785
ื”ืจื’ืฉืชื™ ืืฉื ื‘ืœืขื‘ื•ื“ ืขืœ ืื ื“ืจื•ืื™ื“
22:56
when it was starting.
578
1376082
1316
ื›ืฉื–ื” ื”ืชื—ื™ืœ.
22:57
It was a little startup we bought.
579
1377398
1958
ื–ื” ื”ื™ื” ืกื˜ืืจื˜ืืค ืงื˜ืŸ ืฉืงื ื™ื ื•.
22:59
It wasn't really what we were really working on.
580
1379356
2670
ื–ื” ืœื ื”ื™ื” ืžืžืฉ ืžื” ืฉืื ื—ื ื• ื‘ืืžืช ืขื•ื‘ื“ื™ื ืขืœื™ื•.
23:02
And I felt guilty about spending time on that.
581
1382026
2495
ื•ื”ืจื’ืฉืชื™ ืืฉื ืœื‘ื–ื‘ื– ืขืœ ื–ื” ื–ืžืŸ.
23:04
That was stupid.
582
1384521
1454
ื–ื” ื”ื™ื” ื˜ื™ืคืฉื™.
23:05
That was the future, right?
583
1385975
1051
ื–ื” ื”ื™ื” ื”ืขืชื™ื“, ื ื›ื•ืŸ?
23:07
That was a good thing to be working on.
584
1387026
2285
ื–ื” ื”ื™ื” ื“ื‘ืจ ื˜ื•ื‘ ืœืขื‘ื•ื“ ืขืœื™ื•.
23:09
CR: It is great to see you here.
585
1389311
1417
ืฆ.ืจ.: ื–ื” ื ื”ื“ืจ ืœืจืื•ืช ืื•ืชืš ื›ืืŸ.
23:10
It's great to hear from you,
586
1390728
1460
ื–ื” ื ืคืœื ืœืฉืžื•ืข ืžืžืš,
23:12
and a pleasure to sit at this table with you.
587
1392188
2297
ื•ืชืขื ื•ื’ ืœืฉื‘ืช ื‘ืฉื•ืœื—ืŸ ื”ื–ื” ืื™ืชืš.
23:14
Thanks, Larry.
588
1394485
928
ืชื•ื“ื”, ืœืืจื™.
23:15
LP: Thank you.
589
1395413
2103
ืœ.ืค.: ืชื•ื“ื” ืœืš.
23:17
(Applause)
590
1397516
3932
(ืžื—ื™ืื•ืช ื›ืคื™ื™ื)
23:21
CR: Larry Page.
591
1401448
3311
ืฆ.ืจ.: ืœืืจื™ ืคื™ื™ื’.
ืขืœ ืืชืจ ื–ื”

ืืชืจ ื–ื” ื™ืฆื™ื’ ื‘ืคื ื™ื›ื ืกืจื˜ื•ื ื™ YouTube ื”ืžื•ืขื™ืœื™ื ืœืœื™ืžื•ื“ ืื ื’ืœื™ืช. ืชื•ื›ืœื• ืœืจืื•ืช ืฉื™ืขื•ืจื™ ืื ื’ืœื™ืช ื”ืžื•ืขื‘ืจื™ื ืขืœ ื™ื“ื™ ืžื•ืจื™ื ืžื”ืฉื•ืจื” ื”ืจืืฉื•ื ื” ืžืจื—ื‘ื™ ื”ืขื•ืœื. ืœื—ืฅ ืคืขืžื™ื™ื ืขืœ ื”ื›ืชื•ื‘ื™ื•ืช ื‘ืื ื’ืœื™ืช ื”ืžื•ืฆื’ื•ืช ื‘ื›ืœ ื“ืฃ ื•ื™ื“ืื• ื›ื“ื™ ืœื”ืคืขื™ืœ ืืช ื”ืกืจื˜ื•ืŸ ืžืฉื. ื”ื›ืชื•ื‘ื™ื•ืช ื’ื•ืœืœื•ืช ื‘ืกื ื›ืจื•ืŸ ืขื ื”ืคืขืœืช ื”ื•ื•ื™ื“ืื•. ืื ื™ืฉ ืœืš ื”ืขืจื•ืช ืื• ื‘ืงืฉื•ืช, ืื ื ืฆื•ืจ ืื™ืชื ื• ืงืฉืจ ื‘ืืžืฆืขื•ืช ื˜ื•ืคืก ื™ืฆื™ืจืช ืงืฉืจ ื–ื”.

https://forms.gle/WvT1wiN1qDtmnspy7