George Whitesides: A lab the size of a postage stamp

33,331 views ใƒป 2010-02-03

TED


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

ืžืชืจื’ื: Nirit Nachman ืžื‘ืงืจ: Sigal Tifferet
00:15
The problem I want to talk with you about is really the problem of:
0
15960
4976
ื”ื‘ืขื™ื” ืฉื‘ืจืฆื•ื ื™ ืœื“ื‘ืจ ืื™ืชื›ื ืขืœื™ื”
ื”ื™ื ืœืžืขืฉื” ื‘ืขื™ื™ืช
00:20
How does one supply health care in a world in which cost is everything?
1
20960
6806
ื”ืื•ืคืŸ ืฉื‘ื• ื ื™ืชืŸ ืœืกืคืง ืฉื™ืจื•ืชื™ ื‘ืจื™ืื•ืช
ื‘ืขื•ืœื ื‘ื• ื”ืขืœื•ืช ื”ื™ื ื”ื“ื‘ืจ ื”ื—ืฉื•ื‘ ื‘ื™ื•ืชืจ.
00:28
How do you do that?
2
28274
1237
ื›ื™ืฆื“ ืชืขืฉื” ื–ืืช?
00:30
And the basic paradigm we want to suggest to you,
3
30459
2335
ื•ื”ืคืจื“ื™ื’ืžื” ื”ื‘ืกื™ืกื™ืช ืฉืื ื—ื ื• ืจื•ืฆื™ื ืœื”ืฆื™ืข ืœื›ื,
00:32
I want to suggest to you,
4
32818
1225
ืื ื™ ืจื•ืฆื” ืœื”ืฆื™ืข ืœื›ื,
00:34
is one in which you say that in order to treat disease,
5
34067
3672
ื”ื™ื ื›ื–ื• ืฉืื•ืžืจืช
ืฉื›ื“ื™ ืœื˜ืคืœ ื‘ืžื—ืœื” ืขืœื™ื™ืš ืœื“ืขืช ืงื•ื“ื ื›ืœ ื‘ืžื” ืืชื” ืžื˜ืคืœ --
00:37
you have to first know what you're treating, that's diagnostics,
6
37763
3372
ื–ื”ื• ื”ืื‘ื—ื•ืŸ -- ื•ืื– ืขืœื™ืš ืœืขืฉื•ืช ืžืฉื”ื• ื‘ื ื“ื•ืŸ.
00:41
and then you have to do something.
7
41159
1647
00:42
The program we're involved in is something we call "Diagnostics for All,"
8
42830
4316
ืื ื›ืš, ื”ืชื•ื›ื ื™ืช ื‘ื” ืื ื• ืœื•ืงื—ื™ื ื—ืœืง ื”ื™ื ืžื” ืฉืื ื• ืžื›ื ื™ื
"ืื‘ื—ื•ืŸ ืœื›ืœ", ืื• "ืื‘ื—ื•ืŸ ื‘ืขืœื•ืช ืืคืก".
00:47
or "zero-cost diagnostics."
9
47170
2111
00:49
How do you provide medically relevant information
10
49305
3414
ื›ื™ืฆื“ ืชืกืคืง ืžื™ื“ืข ืจืคื•ืื™ ืจืœื•ื•ื ื˜ื™
00:52
at as close as possible to zero cost?
11
52743
2624
ื‘ืขืœื•ืช ืืคืกื™ืช ื›ื›ืœ ื”ืืคืฉืจ? ืื™ืš ืชืขืฉื” ื–ืืช?
00:55
How do you do it?
12
55391
1230
00:56
Let me just give you two examples.
13
56645
1791
ื”ืจืฉื• ืœื™ ืœื”ืฆื™ื’ ื‘ืคื ื™ื›ื ืฉืชื™ ื“ื•ื’ืžืื•ืช.
00:58
The rigors of military medicine are not so dissimilar from the third world:
14
58967
5866
ื”ืงืฉื™ื™ื ืฉื”ืจืคื•ืื” ื”ืฆื‘ืื™ืช ืžืชืžื•ื“ื“ืช ืขื™ืžื
ืœื ื›ืœ ื›ืš ืฉื•ื ื™ื ืžืืœื• ืฉืœ ื”ืขื•ืœื ื”ืฉืœื™ืฉื™ -
01:04
poor resources, a rigorous environment -- a series of problems --
15
64857
4352
ืžื—ืกื•ืจ ื‘ืžืฉืื‘ื™ื, ืชื ืื™ ืกื‘ื™ื‘ื” ืงืฉื™ื,
ืกื™ื“ืจื” ืฉืœ ื‘ืขื™ื•ืช ื‘ืชืื•ืจื”, ื‘ืžืฉืงืœ, ื•ื“ื‘ืจื™ื ืžืกื•ื’ ื–ื”.
01:09
light weight and things of this kind.
16
69233
1981
01:11
And also they're not so different from the home health care
17
71238
3434
ื”ื ื’ื ืœื ืžืื•ื“ ืฉื•ื ื™ื ืžื”ืงืฉื™ื™ื ืฉืœ ืžืขืจื›ืช ืฉื™ืจื•ืชื™ ื”ื‘ืจื™ืื•ืช ื”ื‘ื™ืชื™ื™ื
01:14
and diagnostic system world.
18
74696
2405
ื•ืžืขืจืš ื”ืื‘ื—ื•ืŸ.
01:17
So, the technology I want to talk about is for the third world,
19
77125
4848
ืื ื›ืš, ื”ื˜ื›ื ื•ืœื•ื’ื™ื” ืขืœื™ื” ื‘ืจืฆื•ื ื™ ืœื“ื‘ืจ
ืžื™ื•ืขื“ืช ืขื‘ื•ืจ ื”ืขื•ืœื ื”ืฉืœื™ืฉื™, ืขื‘ื•ืจ ื”ืขื•ืœื ื”ืžืชืคืชื—,
01:21
for the developing world,
20
81997
1398
01:23
but it has, I think, much broader application,
21
83419
2541
ืืš ื™ืฉ ืœื”, ืœื“ืขืชื™, ื™ื™ืฉื•ื ื”ืจื‘ื” ื™ื•ืชืจ ื ืจื—ื‘,
01:25
because information is so important in the health care system.
22
85984
3463
ืžืคื ื™ ืฉืžื™ื“ืข ื”ื•ื ื“ื‘ืจ ื—ืฉื•ื‘ ื›ืœ ื›ืš ื‘ืžืขืจื›ืช ื”ื‘ืจื™ืื•ืช.
01:30
So you see two examples here.
23
90301
1794
ืื–, ืืชื ืจื•ืื™ื ื›ืืŸ ืฉืชื™ ื“ื•ื’ืžืื•ืช.
01:32
One is a lab that is actually a fairly high-end laboratory in Africa.
24
92119
5749
ื”ืื—ืช ื”ื™ื ืžืขื‘ื“ื”, ืœืžืขืฉื” ื™ื•ืงืจืชื™ืช ืœืžื“ื™, ื‘ืืคืจื™ืงื”.
01:37
The second is basically an entrepreneur who is set up and doing who-knows-what
25
97892
4304
ื”ืฉื ื™ื™ื” ื”ื™ื ื™ื–ื
ืฉืคืชื— ืฉื•ืœื—ืŸ ื‘ืฉื•ืง ื•ืขื•ืฉื” ืืœื•ื”ื™ื-ื™ื•ื“ืข-ืžื”.
01:42
at a table in a market.
26
102220
1447
01:43
I don't know what kind of health care is delivered there.
27
103691
2947
ืื ื™ ืœื ื™ื•ื“ืข ืื™ื–ื” ืฉื™ืจื•ืชื™ ื‘ืจื™ืื•ืช ื ื™ืชื ื™ื ืฉื.
01:46
But it's not really what is probably most efficient.
28
106662
3852
ืื‘ืœ ื›ื ืจืื” ืฉืœื ืžื”ืกื•ื’ ื”ื™ืขื™ืœ ื‘ื™ื•ืชืจ.
01:51
What is our approach?
29
111601
2633
ืžื”ื™ ื”ื’ื™ืฉื” ืฉืœื ื•?
01:54
The way in which one typically approaches a problem of lowering cost,
30
114702
5525
ื•ื”ื“ืจืš ื‘ื” ื ื™ื’ืฉื™ื ืœืจื•ื‘
ืœื‘ืขื™ื” ืฉืœ ื”ื•ืจื“ืช ืขืœื•ื™ื•ืช,
02:00
starting from the perspective of the United States,
31
120251
2863
ื”ื—ืœ ืžื ืงื•ื“ืช ื”ืžื‘ื˜ ืฉืœ ืืจื”"ื‘,
02:03
is to take our solution,
32
123138
2143
ื”ื™ื ืœืงื—ืช ืืช ื”ืคืชืจื•ืŸ ื”ืงื™ื™ื,
02:05
and then try to cut cost out of it.
33
125305
2155
ื•ืื– ืœื ืกื•ืช ืœื”ื•ืจื™ื“ ืžืžื ื• ืขืœื•ื™ื•ืช.
ืœื ืžืฉื ื” ื›ื™ืฆื“ ืชืขืฉื” ื–ืืช
02:08
No matter how you do that,
34
128023
1413
02:09
you're not going to start with a $100,000 instrument
35
129460
2506
ืœื ืชื•ื›ืœ ืœื”ืชื—ื™ืœ ืžืžื›ืฉื™ืจ ืฉืœ 100,000 ื“ื•ืœืจ
02:11
and bring it down to no cost.
36
131990
1421
ื•ืœื”ื•ืจื™ื“ ืื•ืชื• ืœืขืœื•ืช ืืคืก. ื–ื” ืœื ื™ืขื‘ื•ื“.
02:13
It isn't going to work.
37
133435
1173
02:14
So the approach we took was the other way around, to ask:
38
134632
2859
ืื–, ื”ื’ื™ืฉื” ืฉื‘ื—ืจื ื• ื”ื™ื ื”ืคื•ื›ื”.
02:17
What is the cheapest possible stuff
39
137515
2465
ืœืฉืื•ืœ, "ืžื”ื• ื”ืฆื™ื•ื“ ื”ืืคืฉืจื™ ื”ื–ื•ืœ ื‘ื™ื•ืชืจ
ืฉื ื™ืชืŸ ืœื‘ื ื•ืช ืžืžื ื• ืžืขืจื›ืช ืื™ื‘ื—ื•ืŸ,
02:20
that you could make a diagnostic system out of,
40
140004
2936
02:22
and get useful information and add function?
41
142964
2547
ื•ืœืงื‘ืœ ืžื™ื“ืข ืฉื™ืžื•ืฉื™,
ื‘ืžืขืจื›ืช ืฉืขื•ื‘ื“ืช?" ื•ื”ื“ื‘ืจ ื‘ื• ื‘ื—ืจื ื• ื”ื•ื ื ื™ื™ืจ.
02:25
And what we've chosen is paper.
42
145535
1997
02:27
What you see here is a prototypic device.
43
147556
3024
ืžื” ืฉืืชื ืจื•ืื™ื ื›ืืŸ ื”ื•ื ืื‘ ื˜ื™ืคื•ืก ืฉืœ ืžื›ืฉื™ืจ.
02:30
It's about a centimeter on the side.
44
150604
1832
ืื•ืจื›ื• ื›ืกื ื˜ื™ืžื˜ืจ.
02:32
It's about the size of a fingernail.
45
152460
1977
ื”ื•ื ื‘ืขืจืš ื‘ื’ื•ื“ืœ ืฉืœ ืฆื™ืคื•ืจืŸ.
02:34
The lines around the edges are a polymer.
46
154461
3603
ื”ืงื•ื•ื™ื ืžืกื‘ื™ื‘ ืœืงืฆื•ื•ืช
ื”ื ืคื•ืœื™ืžืจ.
02:38
It's made of paper.
47
158088
1842
ื”ื•ื ืขืฉื•ื™ ืžื ื™ื™ืจ, ื•ื ื™ื™ืจ ื›ืžื•ื‘ืŸ ืกื•ืคื— ื ื•ื–ืœื™ื.
02:39
And paper, of course, wicks fluid, as you know, paper, cloth --
48
159954
4685
ื›ืคื™ ืฉืืชื ื™ื•ื“ืขื™ื, ืื ื ืฉืคืš ื™ื™ืŸ ืขืœ ืžืคืช ื”ืฉื•ืœื—ืŸ,
02:44
drop wine on the tablecloth,
49
164663
1876
02:46
and the wine wicks all over everything.
50
166563
2737
ื”ื™ื™ืŸ ื™ื™ืกืคื’ ื•ื™ื›ืชื™ื ื”ื›ืœ.
02:49
Put it on your shirt, it ruins the shirt.
51
169324
2039
ืื ื”ื•ื ื ืฉืคืš ืขืœ ื”ื—ื•ืœืฆื”, ื”ื•ื ื”ื•ืจืก ืืช ื”ื—ื•ืœืฆื”.
02:51
That's what a hydrophilic surface does.
52
171387
2739
ื–ื” ืžื” ืฉืžืฉื˜ื— ื”ื™ื“ืจื•ืคื™ืœื™ ืขื•ืฉื”.
02:54
So in this device, the idea is that you drip the bottom end of it
53
174150
3623
ืื ื›ืŸ, ื‘ืžื›ืฉื™ืจ ื–ื” ื”ืจืขื™ื•ืŸ ื”ื•ื ืœื˜ื‘ื•ืœ
ืืช ื—ืœืงื• ื”ืชื—ืชื•ืŸ ื‘ื˜ื™ืคื” ืฉืœ,
02:57
in a drop of, in this case, urine.
54
177797
2639
ื‘ืžืงืจื” ื–ื”, ืฉืชืŸ.
03:00
The fluid wicks its way into those chambers at the top.
55
180460
3748
ื”ื ื•ื–ืœ ืžื—ืœื—ืœ ืืœ ืชื•ืš ื”ืชืื™ื ื”ืืœื• ืœืžืขืœื”.
03:04
The brown color indicates the amount of glucose in the urine,
56
184232
4204
ื”ืฆื‘ืข ื”ื—ื•ื ืžืฆื‘ื™ืข ืขืœ ื›ืžื•ืช ื”ื’ืœื•ืงื•ื– ื‘ืฉืชืŸ.
03:08
the blue color indicates the amount of protein in the urine.
57
188460
3547
ื”ืฆื‘ืข ื”ื›ื—ื•ืœ ืžืฆื‘ื™ืข ืขืœ ื›ืžื•ืช ื”ื—ืœื‘ื•ื ื™ื ื‘ืฉืชืŸ.
ื•ื”ืฆื™ืจื•ืฃ ืฉืœ ืฉื ื™ื”ื,
03:12
And the combination of those two is a first-order shot
58
192031
3036
ื”ื•ื ืฉืœื‘ ืจืืฉื•ื ื™ ืžืชื•ืš ืžืกืคืจ
03:15
at a number of useful things that you want.
59
195091
3122
ื“ื‘ืจื™ื ืฉื™ืžื•ืฉื™ื™ื ื‘ื”ื ืืชื” ืžืขื•ื ื™ื™ืŸ.
03:18
So, this is an example of a device made from a simple piece of paper.
60
198237
3357
ืื ื›ืŸ, ื–ื•ื”ื™ ื“ื•ื’ืžื” ืœืžื›ืฉื™ืจ ืฉืขืฉื•ื™ ืžื—ืชื™ื›ืช ื ื™ื™ืจ ืคืฉื•ื˜ื”.
03:21
Now, how simple can you make the production?
61
201618
2260
ื›ืžื” ืคืฉื•ื˜ ืชื•ื›ืœ ืœืขืฉื•ืช ืืช ืชื”ืœื™ืš ื”ื™ื™ืฆื•ืจ?
03:24
Why do we choose paper?
62
204460
1765
ืœืžื” ืื ื• ื‘ื•ื—ืจื™ื ื‘ื ื™ื™ืจ?
03:26
There's an example of the same thing on a finger,
63
206719
2910
ื”ื ื” ื“ื•ื’ืžื” ืฉืœ ืžื›ืฉื™ืจ ื–ื”ื”, ืขืœ ืืฆื‘ืข
03:29
showing you basically what it looks like.
64
209653
2256
ืฉืžื“ื’ื™ื ื‘ืคื ื™ื›ื ืื™ืš ื”ื•ื ื‘ืขืฆื ื ืจืื”.
03:31
One reason for using paper is that it's everywhere.
65
211933
2428
ืกื™ื‘ื” ืื—ืช ืœืฉื™ืžื•ืฉ ื‘ื ื™ื™ืจ ื”ื™ื ืฉื”ื•ื ืžืฆื•ื™ ื‘ื›ืœ ืžืงื•ื.
03:34
We have made these kinds of devices using napkins and toilet paper
66
214385
5173
ื‘ื ื™ื ื• ืžื›ืฉื™ืจื™ื ื›ืืœื”
ืžืžืคื™ื•ืช ื ื™ื™ืจ ื•ืžื ื™ื™ืจ ื˜ื•ืืœื˜
03:39
and wraps, and all kinds of stuff.
67
219582
2230
ื•ืžืขื˜ื™ืคื•ืช, ื•ืžื›ืœ ืžื™ื ื™ ื“ื‘ืจื™ื.
03:41
So the production capability is there.
68
221836
2438
ืื ื›ืš, ื™ื›ื•ืœืช ื”ื™ื™ืฆื•ืจ ืงื™ื™ืžืช.
03:44
The second is, you can put lots and lots of tests in a very small place.
69
224298
4297
ื”ืกื™ื‘ื” ื”ืฉื ื™ื™ื” ื”ื™ื, ืฉื ื™ืชืŸ ืœืื—ืกืŸ ื”ืžื•ื ื™
ืขืจื›ื•ืช ื‘ื“ื™ืงื” ื‘ืžืงื•ื ืงื˜ืŸ ืžืื•ื“.
03:48
I'll show you in a moment that the stack of paper there
70
228619
2819
ืชื›ืฃ ืืจืื” ืœื›ื ืฉืขืจื™ืžืช ื”ื ื™ื™ืจ ืฉื
ื™ื›ื•ืœื” ืœืื—ืกืŸ ืžืฉื”ื• ื›ืžื•
03:51
would probably hold something like 100,000 tests,
71
231462
2732
100,000 ื‘ื“ื™ืงื•ืช. ืžืฉื”ื• ื‘ืจืžื” ื”ื–ื•.
03:54
something of that kind.
72
234218
1741
03:55
And then finally, a point you don't think of so much
73
235983
2845
ื•ืœื‘ืกื•ืฃ, ื ืงื•ื“ื” ืฉืœื ื›ืœ ื›ืš ื—ื•ืฉื‘ื™ื ืขืœื™ื”
03:58
in developed world medicine:
74
238852
2584
ื‘ืจืคื•ืื” ื‘ืขื•ืœื ื”ืžืคื•ืชื—,
04:01
it eliminates sharps.
75
241460
1679
ื”ื™ื ืžื ื™ืขืช ื”ืฆื•ืจืš ื‘ื“ื‘ืจื™ื ื—ื“ื™ื.
04:03
And what sharps means is needles, things that stick.
76
243163
3382
ื•ื“ื‘ืจื™ื ื—ื“ื™ื ืคื™ืจื•ืฉื ืžื—ื˜ื™ื, ื“ื‘ืจื™ื ื“ื•ืงืจื™ื.
04:06
If you've taken a sample of someone's blood
77
246569
2294
ืื ืœืงื—ืช ื“ื’ื™ืžืช ื“ื ืžืžื™ืฉื”ื•,
04:08
and the someone might have hepatitis C,
78
248887
2497
ืฉื™ืชื›ืŸ ื•ืกื•ื‘ืœ ืžื”ืคื˜ื™ื˜ื™ืก ืกื™,
04:11
you don't want to make a mistake and stick it in you.
79
251408
2547
ืœื ืชืจืฆื” ืœืขืฉื•ืช ื˜ืขื•ืช ื•ืœื”ื“ืงืจ ืžืžื ื”.
04:13
You don't want to do that.
80
253979
1297
ืคืฉื•ื˜, ืืชื” ืœื ืจื•ืฆื” ืฉื–ื” ื™ืงืจื”.
04:15
So how do you dispose of that?
81
255300
1489
ืื–, ืื™ืš ื ืคื˜ืจื™ื ืžืžื ื”? ื–ืืช ื‘ืขื™ื” ื›ืœืœื™ืช.
04:16
It's a problem everywhere, and here, you simply burn it.
82
256813
2682
ื•ื›ืืŸ ืืชื ืคืฉื•ื˜ ืฉื•ืจืคื™ื ืื•ืชื”.
04:19
So it's a sort of a practical approach to starting on things.
83
259519
3500
ืื ื›ืŸ, ื–ื•ื”ื™ ื’ื™ืฉื” ืžืขืฉื™ืช
ืœื”ืชื—ื™ืœ ื‘ื”.
04:24
Now, you say, "If paper is a good idea,
84
264677
3656
ื›ืขืช, ืชื•ื›ืœื• ืœื”ื’ื™ื“ ืฉืื ื ื™ื™ืจ ื”ื•ื ืจืขื™ื•ืŸ ื˜ื•ื‘,
ื‘ื˜ื— ืื ืฉื™ื ืื—ืจื™ื ื›ื‘ืจ ื—ืฉื‘ื• ืขืœ ื–ื”.
04:28
other people have surely thought of it."
85
268357
1963
ื•ื”ืชืฉื•ื‘ื” ื”ื™ื, ื›ืžื•ื‘ืŸ, ื›ืŸ.
04:30
And the answer is, of course, yes.
86
270344
1882
04:32
Those half of you, roughly, who are women,
87
272250
3820
ืžื—ืฆื™ืช ืžื›ื, ื‘ืงื™ืจื•ื‘,
ืฉื”ืŸ ื”ื ืฉื™ื,
04:36
at some point may have had a pregnancy test.
88
276094
2462
ื™ืชื›ืŸ ืฉืขืจื›ื• ื‘ื“ื™ืงืช ื”ื™ืจื™ื•ืŸ.
04:38
And the most common of these is in a device
89
278580
3984
ื•ื”ื‘ื“ื™ืงื•ืช ื”ืฉื›ื™ื—ื•ืช ื‘ื™ื•ืชืจ
ื”ืŸ ื‘ืžื›ืฉื™ืจ ืฉื ืจืื” ื›ืžื• ื–ื” ืฉืžืฉืžืืœ.
04:42
that looks like the thing on the left.
90
282588
1848
04:44
It's something called a lateral-flow immunoassay.
91
284460
2492
ื”ื•ื ื ืงืจื "ืชื‘ื—ื™ืŸ ื—ื™ืกื•ื ื™ ื‘ืืžืฆืขื•ืช ื–ืจื™ืžื” ืฆื™ื“ื™ืช".
04:46
In that particular test,
92
286976
1460
ื•ื‘ื‘ื“ื™ืงื” ื”ืกืคืฆื™ืคื™ืช ื”ื–ืืช
04:48
urine, either containing a hormone called hCG,
93
288460
3615
ื”ืฉืชืŸ, ืฉืขืฉื•ื™ ืœื”ื›ื™ืœ
ื”ื•ืจืžื•ืŸ ืฉื ืงืจื HCG,
04:52
does or does not flow across a piece of paper.
94
292099
3337
ื–ื•ืจื ืขืœ ืคื ื™ ื—ืชื™ื›ืช ื ื™ื™ืจ.
04:55
And there are two bars; one bar indicates that the test is working,
95
295460
3901
ื•ื™ืฉ ืฉื ื™ ืงื•ื•ื™ื. ืื—ื“ ืžืฆื™ื™ืŸ ืฉื”ื‘ื“ื™ืงื” ืคื•ืขืœืช.
04:59
and if the second bar shows up, you're pregnant.
96
299385
3165
ื•ืื ื”ืงื• ื”ืฉื ื™ ืžื•ืคื™ืข, ืืช ื‘ื”ื™ืจื™ื•ืŸ.
05:02
This is a terrific kind of test in a binary world,
97
302574
3171
ื–ื•ื”ื™ ื‘ื“ื™ืงื” ื ื”ื“ืจืช ื‘ืขื•ืœื ื‘ื™ื ืืจื™.
05:05
and the nice thing about pregnancy is either you are pregnant
98
305769
2915
ื•ื”ื“ื‘ืจ ื”ื ื—ืžื“ ื‘ื”ืจื™ื•ืŸ ื”ื•ื
ืฉืืช ื‘ื”ื™ืจื™ื•ืŸ ืื• ืฉืืช ืœื ื‘ื”ืจื™ื•ืŸ.
05:08
or you're not pregnant;
99
308708
1154
05:09
you're not partially pregnant or thinking about being pregnant
100
309886
2981
ืืช ืœื ื—ืœืงื™ืช ื‘ื”ืจื™ื•ืŸ ืื• ื—ื•ืฉื‘ืช ืขืœ ืœื”ื™ื•ืช ื‘ื”ืจื™ื•ืŸ
ืื• ืžืฉื”ื• ืžืกื•ื’ ื–ื”.
05:12
or something of that sort.
101
312891
1284
ืื ื›ืš, ื–ื” ืขื•ื‘ื“ ืžืฆื•ื™ื™ืŸ ื‘ืžืงืจื” ื”ื–ื”.
05:14
So it works very well there, but it doesn't work very well
102
314199
2735
ืื‘ืœ ื–ื” ืœื ืขื•ื‘ื“ ื›ืœ ื›ืš ื˜ื•ื‘ ื›ืฉืืชื” ื–ืงื•ืง ืœื ืชื•ื ื™ื ื›ืžื•ืชื™ื™ื ื™ื•ืชืจ.
05:16
when you need more quantitative information.
103
316958
2086
ื™ืฉื ื ื’ื ืžืงืœื•ื ื™ ืžื“ื™ื“ื” (dipsticks).
05:19
There are also dipsticks,
104
319068
1220
05:20
but if you look at the dipsticks,
105
320312
1746
ืื‘ืœ ืื ืชืกืชื›ืœ ืขืœ ืžืงืœื•ื ื™ ื”ืžื“ื™ื“ื”, ื”ื ื ื•ืขื“ื•
05:22
they're for another kind of urine analysis.
106
322082
2213
ืœืกื•ื’ ืฉื•ื ื” ืฉืœ ื ื™ืชื•ื— ื”ืฉืชืŸ.
05:24
There are an awful lot of colors and things like that.
107
324319
2877
ื™ืฉื ื ื”ืžื•ื ื™ ืฆื‘ืขื™ื ื•ื“ื‘ืจื™ื ืžืกื•ื’ ื–ื”.
05:27
What do you actually do about that in a difficult circumstance?
108
327220
3293
ืžื” ืืชื” ืขื•ืฉื” ื‘ื ื•ื’ืข ืœื›ืš ื›ืฉื”ืชื ืื™ื ืœื ื ื•ื—ื™ื?
ืื ื›ืŸ, ื”ื’ื™ืฉื” ืื™ืชื” ื”ืชื—ืœื ื•, ื”ื™ื ืœืฉืื•ืœ,
05:31
So the approach we started with is to ask:
109
331632
4309
05:35
Is it really practical to make things of this sort?
110
335965
3471
ื”ืื ื“ื‘ืจื™ื ืžืกื•ื’ ื–ื” ื”ื ื‘ืืžืช ืžืขืฉื™ื™ื?
05:39
And that problem is now, in a purely engineering way, solved.
111
339460
4287
ื•ื”ื‘ืขื™ื” ื”ื–ืืช ื‘ืื” ืขืœ ืคืชืจื•ื ื” ื›ืขืช, ื‘ื“ืจืš ื”ื ื“ืกื™ืช ื˜ื”ื•ืจื”.
05:43
And the procedure that we have is simply to start with paper.
112
343771
3549
ื•ื”ื”ืœื™ืš ืฉืœื ื• ื”ื•ื ืคืฉื•ื˜ ืœื”ืชื—ื™ืœ ืขื ื ื™ื™ืจ.
05:47
You run it through a new kind of printer called a wax printer.
113
347344
3546
ืืชื” ืžืขื‘ื™ืจ ืื•ืชื• ื“ืจืš ืกื•ื’ ื—ื“ืฉ ืฉืœ ืžื“ืคืกืช ืฉื ืงืจืืช ืžื“ืคืกืช ืฉืขื•ื•ื”.
05:50
The wax printer does what looks like printing.
114
350914
2632
ืžื“ืคืกืช ื”ืฉืขื•ื•ื” ืžื‘ืฆืขืช ืžืฉื”ื• ืฉื ืจืื” ื›ืžื• ื”ื“ืคืกื”.
05:53
It is printing.
115
353570
1158
ื”ื™ื ืื›ืŸ ืžื“ืคื™ืกื”. ืืชื” ืฉื ืืช ื–ื” ืžืขืœ, ืžื—ืžื ืืช ื–ื” ืงืฆืช.
05:54
You put that on, you warm it a little bit,
116
354752
2040
05:56
the wax prints through, so it absorbs into the paper,
117
356816
3043
ื”ืฉืขื•ื•ื” ืžื•ื“ืคืกืช ื“ืจืš ื–ื” ื›ืš ืฉื”ื™ื ื ืกืคื’ืช ื‘ื ื™ื™ืจ.
05:59
and you end up with the device you want.
118
359883
2144
ื•ื‘ืกื•ืคื• ืฉืœ ื“ื‘ืจ ืžืชืงื‘ืœ ื”ืžื›ืฉื™ืจ ืฉืจืฆื™ืช ื‘ื•.
ื”ืžื“ืคืกื•ืช ืขื•ืœื•ืช ื›ื™ื•ื 800 ื“ื•ืœืจ.
06:02
The printers cost 800 bucks now.
119
362051
3079
06:05
We estimate that if you were to run them 24 hours a day,
120
365154
3888
ืื ื• ืžืขืจื™ื›ื™ื ืฉืื ืชืคืขื™ืœ ืื•ืชืŸ ื‘ืžืฉืš 24 ืฉืขื•ืช ื‘ื™ืžืžื”
ื”ืŸ ื™ื™ืฆืจื• ื›-10 ืžืœื™ื•ืŸ ื‘ื“ื™ืงื•ืช ืœืฉื ื”.
06:09
they'd make about 10 million tests a year.
121
369066
2108
06:11
So it's a solved problem. That particular problem is solved.
122
371198
3224
ืื ื›ืŸ, ื–ื•ื”ื™ ื‘ืขื™ื” ืคืชื•ืจื”. ืžืฆืื ื• ืคืชืจื•ืŸ ืœื‘ืขื™ื” ื”ืกืคืฆื™ืคื™ืช ื”ื–ื•.
06:14
And there is an example of the kind of thing that you see.
123
374446
2776
ื•ื›ืืŸ ื™ืฉ ื“ื•ื’ืžื” ืฉืœ ืกื•ื’ ื”ื“ื‘ืจื™ื ืฉืžืชืงื‘ืœื™ื.
ื–ื” ืžื•ื ื— ืขืœ ื—ืชื™ื›ืช ื ื™ื™ืจ ื‘ื’ื•ื“ืœ 8 ืขืœ 12.
06:17
That's on a piece of 8 by 12 paper.
124
377246
1839
06:19
That takes about two seconds to make.
125
379109
2269
ืืช ื”ื“ื‘ืจ ื”ื–ื” ืœื•ืงื— ื›ืฉืชื™ ืฉื ื™ื•ืช ืœื”ื›ื™ืŸ.
06:21
And so I regard that as done.
126
381402
2642
ืื ื›ืš ืื ื™ ืžืชื™ื™ื—ืก ืœื ื•ืฉื ื›ื’ืžื•ืจ.
ื™ืฉ ื›ืืŸ ื ื•ืฉื ื—ืฉื•ื‘ ืžืื•ื“,
06:24
There's a very important issue here,
127
384068
1794
06:25
which is that because it's a printer, a color printer, it prints colors.
128
385886
4418
ื•ื”ื•ื ืฉืžืฉื•ื ืฉืžื“ื•ื‘ืจ ื‘ืžื“ืคืกืช,
ืžื“ืคืกืช ืฆื‘ืข, ื”ื™ื ืžื“ืคื™ืกื” ืฆื‘ืขื™ื. ื–ื” ืžื” ืฉืžื“ืคืกื•ืช ืฆื‘ืข ืขื•ืฉื•ืช.
06:30
That's what color printers do.
129
390328
1524
06:31
I'll show you in a moment, that's actually quite useful.
130
391876
2766
ืžื™ื“ ืืจืื” ืœื›ื, ืœืžืขืฉื” ื–ื” ืฉื™ืžื•ืฉื™ ืœืžื“ื™.
06:35
Now, the next question that you would like to ask is:
131
395911
2525
ืื ื›ืŸ, ื”ืฉืืœื” ื”ื‘ืื” ืฉืชืจืฆื• ืœืฉืื•ืœ
06:38
What would you like to measure? What would you like to analyze?
132
398460
3191
ื”ื™ื ืžื” ื‘ืจืฆื•ื ืš ืœืžื“ื•ื“? ืžื” ื‘ืจืฆื•ื ืš ืœื ืชื—?
06:41
And the thing you'd most like to analyze, we're a fair distance from.
133
401675
4761
ื•ื”ื“ื‘ืจ ืฉื”ื›ื™ ืชืจืฆื• ืœื ืชื—,
ื ืžืฆื ื‘ืžืจื—ืง ื”ื’ื•ืŸ ืžืื™ืชื ื•.
06:46
It's what's called "fever of undiagnosed origin."
134
406460
3976
ื–ื” ืžื” ืฉื ืงืจื "ื—ื•ื ื’ื‘ื•ื” ืžืžืงื•ืจ ื‘ืœืชื™-ื™ื“ื•ืข".
06:50
Someone comes into the clinic, they have a fever, they feel bad.
135
410460
3561
ืื“ื ืžื’ื™ืข ืœืงืœื™ื ื™ืงื”,
ื™ืฉ ืœื• ื—ื•ื, ื”ื•ื ืžืจื’ื™ืฉ ืจืข, ืžื” ื™ืฉ ืœื•?
06:54
What do they have?
136
414045
1166
ื”ืื ื™ืฉ ืœื• ืฉื—ืคืช? ื”ืื ื™ืฉ ืœื• ืื™ื™ื“ืก?
06:55
Do they have TB? Do they have AIDS? Do they have a common cold?
137
415235
3402
ื”ืื ื™ืฉ ืœื• ืฆื™ื ื•ืŸ ืคืฉื•ื˜?
06:58
The triage problem.
138
418661
1214
ื‘ืขื™ื™ืช ื”ืžื™ื•ืŸ ื”ืจืืฉื•ื ื™. ื–ื•ื”ื™ ื‘ืขื™ื” ืงืฉื”
06:59
That's a hard problem for reasons I won't go through.
139
419899
2656
ืžืกื™ื‘ื•ืช ืฉืœื ืื›ื ืก ืืœื™ื”ืŸ.
07:02
There are an awful lot of things that you'd like to distinguish among.
140
422579
3542
ื™ืฉื ื ื”ืจื‘ื” ืžืื•ื“ ื“ื‘ืจื™ื ืฉื”ื™ื™ืช ืจื•ืฆื” ืœื”ื‘ื—ื™ืŸ ื‘ื ื™ื”ื.
ืื‘ืœ ื™ืฉ ืกื“ืจื” ืฉืœ ื“ื‘ืจื™ื,
07:06
But then there are a series of things --
141
426145
2202
ืื™ื™ื“ืก, ืฆื”ื‘ืช, ืžืœืจื™ื”,
07:08
AIDS, hepatitis, malaria, TB, others --
142
428371
3584
ืฉื—ืคืช, ื•ืื—ืจื™ื.
07:11
and simpler ones, such as guidance of treatment.
143
431979
3495
ื•ื‘ืขื™ื•ืช ืคืฉื•ื˜ื•ืช ื™ื•ืชืจ ื›ืžื• ื”ื“ืจื›ื” ืœื’ื‘ื™ ืื•ืคืŸ ื”ื˜ื™ืคื•ืœ.
07:15
Now, even that's more complicated than you think.
144
435498
2938
ืืคื™ืœื• ื ื•ืฉื ื–ื” ื”ื•ื ืžื•ืจื›ื‘ ื™ื•ืชืจ ืžืžื” ืฉืืชื ื—ื•ืฉื‘ื™ื.
07:18
A friend of mine works in transcultural psychiatry,
145
438460
4215
ื™ื“ื™ื“ ืฉืœื™ ืขื•ื‘ื“ ื‘ืคืกื™ื›ื™ืื˜ืจื™ื” ื˜ืจื ืก-ืชืจื‘ื•ืชื™ืช (trans-cultural psychiatry).
07:22
and he is interested in the question
146
442699
2106
ื•ื”ื•ื ืžืชืขื ื™ื™ืŸ ื‘ืฉืืœื” ืฉืœ
07:24
of why people do and don't take their meds.
147
444829
2730
ืœืžื” ืื ืฉื™ื ืœื•ืงื—ื™ื ืื• ืœื ืœื•ืงื—ื™ื ืืช ื”ืชืจื•ืคื•ืช ืฉืœื”ื.
07:27
So Dapsone, or something like that, you have to take for a while.
148
447583
3575
ืื–, ื“ืคืกื•ืŸ (ืชืจื•ืคื”), ืื• ืžืฉื”ื• ื›ื–ื”,
ืขืœื™ื™ืš ืœืงื—ืช ืืช ื–ื” ืœื–ืžืŸ ืžื”.
07:31
He has a wonderful story of talking to a villager in India
149
451182
3616
ื™ืฉ ืกื™ืคื•ืจ ื ืคืœื ืขืœ ืฉื™ื—ื” ืขื ื‘ืŸ ื›ืคืจ ื‘ื”ื•ื“ื•
07:34
and saying,
150
454822
1151
ืื•ืžืจื™ื ืœื•, "ื”ืื ืœืงื—ืช ืืช ื”ื“ืคืกื•ืŸ ืฉืœืš?" "ื›ืŸ."
07:35
"Have you taken your Dapsone?" "Yes."
151
455997
1806
"ืœืงื—ืช ืื•ืชื• ื›ืœ ื™ื•ื?" "ื›ืŸ."
07:37
"Have you taken it every day?" "Yes."
152
457827
1866
07:39
"Have you taken if for a month?" "Yes."
153
459717
1954
"ืœืงื—ืช ืื•ืชื• ื‘ืžืฉืš ื—ื•ื“ืฉ?" "ื›ืŸ."
07:41
What the guy actually meant
154
461695
1501
ืœืžืขืฉื” ืžื” ืฉื”ื‘ื—ื•ืจ ื”ืชื›ื•ื•ืŸ ืœื•ืžืจ
07:43
was that he'd fed a 30-day dose of Dapsone to his dog that morning.
155
463220
3902
ื–ื” ืฉื”ื•ื ื”ืื›ื™ืœ ื‘ืžื ื” ืฉืœ 30 ื™ื•ื ื“ืคืกื•ืŸ
ืืช ื”ื›ืœื‘ ืฉืœื•, ื”ื™ื•ื ื‘ื‘ื•ืงืจ.
07:47
(Laughter)
156
467146
1125
(ืฆื—ื•ืง)
07:48
And he was telling the truth, because in a different culture,
157
468295
3756
ื”ื•ื ื“ื™ื‘ืจ ืืžืช. ืžืฉื•ื
ืฉื‘ืชืจื‘ื•ืช ืื—ืจืช,
07:52
the dog is a surrogate for you;
158
472075
2574
ื”ื›ืœื‘ ืžื”ื•ื•ื” ืžืžืœื ืžืงื•ื ืฉืœืš,
07:54
"today," "this month," "since the rainy season" --
159
474673
3143
ืืชื ื™ื•ื“ืขื™ื, "ื”ื™ื•ื", "ื”ื—ื•ื“ืฉ", "ืžืื– ืขื•ื ืช ื”ื’ืฉืžื™ื",
07:57
there are lots of opportunities for misunderstanding.
160
477840
2484
ื™ืฉ ื”ืžื•ืŸ ื”ื–ื“ืžื ื•ื™ื•ืช ืœืื™-ื”ื‘ื ื•ืช.
08:00
(Laughter)
161
480348
1007
ืื ื›ืŸ ื”ื ื•ืฉื ื›ืืŸ ื”ื•ื
08:01
And so an issue here is to, in some cases, figure out
162
481379
3564
ื‘ืžืงืจื™ื ืžืกื•ื™ืžื™ื ืœื”ื‘ื™ืŸ
08:04
how to deal with matters that seem uninteresting, like compliance.
163
484967
4111
ื›ื™ืฆื“ ืœื”ืชืžื•ื“ื“ ืขื ื ื•ืฉืื™ื ืฉื ื“ืžื” ืฉื”ื ืœื-ืžืขื ื™ื™ื ื™ื,
ื›ืžื• ื”ื™ืขื ื•ืช ื”ืžื˜ื•ืคืœ.
08:10
Now, take a look at what a typical test looks like.
164
490420
3545
ื•ื‘ื›ืŸ, ื”ืกืชื›ืœื• ื›ื™ืฆื“ ื ืจืื™ืช ื‘ื“ื™ืงื” ื˜ื™ืคื•ืกื™ืช.
08:14
Prick a finger, you get some blood -- about 50 microliters.
165
494679
3757
ื“ืงื™ืจื” ืฉืœ ื”ืืฆื‘ืข, ืชืงื‘ืœ ืงืฆืช ื“ื,
ื‘ืขืจืš 50 ืžื™ืงืจื•ืœื™ื˜ืจ.
08:18
That's about all you're going to get,
166
498460
1831
ื–ื” ื›ืœ ืžื” ืฉืืชื” ื”ื•ืœืš ืœืงื‘ืœ.
08:20
because you can't use the usual sort of systems.
167
500315
3976
ืžืคื ื™ ืฉืืชื” ืœื ื™ื›ื•ืœ ืœื”ืฉืชืžืฉ ื‘ืกื•ื’ ื”ืจื’ื™ืœ ืฉืœ ืžืขืจื›ื•ืช.
08:24
You can't manipulate it very well;
168
504845
1674
ืืชื” ืœื ื™ื›ื•ืœ ืœื‘ืฆืข ืžื ื™ืคื•ืœืฆื™ื•ืช ืžื•ืฆืœื—ื•ืช ืžืžืฉ ืขืœ ื”ื“ื’ื™ืžื”,
08:26
I'll show something about that in a moment.
169
506543
2116
ืœืžืจื•ืช ืฉืชื™ื›ืฃ ืืจืื” ืžืฉื”ื• ื‘ืงืฉืจ ืœื›ืš.
08:28
So you take the drop of blood, no further manipulations,
170
508683
2753
ืื ื›ืš, ืืชื” ืœื•ืงื— ื˜ื™ืคื” ืฉืœ ื“ื, ืœืœื ืขื™ื‘ื•ื“ ื ื•ืกืฃ.
08:31
you put it on a little device,
171
511460
1783
ืืชื” ืฉื ืื•ืชื” ืขืœ ืžื›ืฉื™ืจ ืงื˜ืŸ.
08:33
the device filters out the blood cells, lets the serum go through,
172
513267
4673
ื”ืžื›ืฉื™ืจ ืžืกื ืŸ ื”ื—ื•ืฆื” ืืช ืชืื™ ื”ื“ื, ืžืืคืฉืจ ืœื ื•ื–ืœ ื”ืคืœื–ืžื” ืœืขื‘ื•ืจ,
08:37
and you get a series of colors down in the bottom there.
173
517964
3761
ื•ืชืงื‘ืœ ืกื“ืจื” ืฉืœ ืฆื‘ืขื™ื
ืฉื ื‘ื—ืœืง ื”ืชื—ืชื•ืŸ.
08:41
And the colors indicate "disease" or "normal."
174
521749
4159
ื•ื”ืฆื‘ืขื™ื ืžืฆื™ื™ื ื™ื ืžื—ืœื” ืื• ืชืงื™ืŸ.
08:45
But even that's complicated,
175
525932
1682
ืื‘ืœ ืืคื™ืœื• ื–ื” ืชื”ืœื™ืš ืžืกื•ื‘ืš.
08:47
because to me, colors might indicate "normal,"
176
527638
3601
ืžืคื ื™ ืฉืขื‘ื•ืจืš, ืขื‘ื•ืจื™, ืฆื‘ืขื™ื ืขืฉื•ื™ื™ื ืœื”ืฆื‘ื™ืข ืขืœ ืชืงื™ื ื•ืช.
08:51
but after all, we're all suffering from probably an excess of education.
177
531263
4960
ืื‘ืœ ืื—ืจื™ ื”ื›ืœ ื›ื•ืœื ื• ืกื•ื‘ืœื™ื
ืžืžื” ืฉืขืฉื•ื™ ืœื”ื™ื•ืช ืขื•ื“ืฃ ื”ืฉื›ืœื”.
08:56
What do you do about something which requires quantitative analysis?
178
536247
4587
ืžื” ืชืขืฉื” ืœื’ื‘ื™ ืžืฉื”ื• ืฉื“ื•ืจืฉ
ื ื™ืชื•ื— ื›ืžื•ืชื™?
09:00
And so the solution that we and many other people
179
540858
2682
ื•ื›ืš ื”ืคืชืจื•ืŸ ืฉืื ื• ื•ืื ืฉื™ื ืจื‘ื™ื ืื—ืจื™ื
09:03
are thinking about there,
180
543564
1611
ื—ื•ืฉื‘ื™ื ืขืœื™ื•,
09:05
and at this point, there is a dramatic flourish,
181
545199
2589
ื•ื‘ื ืงื•ื“ื” ื–ื• ื™ืฉ ืคืจื™ื—ื” ื“ืจืžื˜ื™ืช,
09:07
and out comes the universal solution to everything these days,
182
547812
3172
ื•ืขื•ืœื” ื”ืคืชืจื•ืŸ ื”ืื•ื ื™ื‘ืจืกืœื™ ืœื”ื›ืœ ื‘ื™ืžื™ื ืืœื•,
ืฉื”ื•ื ื”ื˜ืœืคื•ืŸ ื”ืกืœื•ืœืจื™. ื‘ืžืงืจื” ื”ืกืคืฆื™ืคื™ ื”ื–ื”, ืžืฆืœืžืช ื˜ืœืคื•ืŸ.
09:11
which is a cell phone --
183
551008
1157
09:12
in this particular case, a camera phone.
184
552189
1998
ื”ื ื‘ื›ืœ ืžืงื•ื, ืฉื™ืฉื” ืžื™ืœื™ื•ืŸ ื‘ื—ื•ื“ืฉ, ื‘ื”ื•ื“ื•.
09:14
They're everywhere -- six billion a month in India.
185
554211
4225
09:18
And the idea is that what one does is to take the device,
186
558460
5522
ื•ื”ืจืขื™ื•ืŸ ื”ื•ื ืฉืžื” ืฉื”ืื“ื ืฆืจื™ืš ืœืขืฉื•ืช,
ื–ื” ืœืงื—ืช ืืช ื”ืžื›ืฉื™ืจ.
ืืชื” ื˜ื•ื‘ืœ ืื•ืชื•. ืืชื” ืžืคืชื— ืืช ื”ืฆื‘ืข.
09:24
you dip it, you develop the color,
187
564006
2430
09:26
you take a picture, the picture goes to a central laboratory.
188
566460
3225
ืืชื” ืžืฆืœื. ื”ืชืžื•ื ื” ืžื•ืขื‘ืจืช ืœืžืขื‘ื“ื” ืžืจื›ื–ื™ืช.
09:29
You don't have to send out a doctor,
189
569709
1727
ืืชื” ืœื ืฆืจื™ืš ืœืฉืœื•ื— ืจื•ืคื.
09:31
you send out somebody who can just take the sample,
190
571460
2741
ืืชื” ืฉื•ืœื— ืžื™ืฉื”ื• ืฉื™ื›ื•ืœ ืคืฉื•ื˜ ืœืงื—ืช ืืช ื”ื“ื’ื™ืžื”.
09:34
and in the clinic either a doctor, or ideally, a computer in this case,
191
574225
3725
ื•ื‘ืงืœื™ื ื™ืงื” ื”ืจื•ืคื, ืื• ื‘ืžืฆื‘ ืื™ื“ืืœื™ ืžื—ืฉื‘
09:37
does the analysis.
192
577974
1164
ื‘ืžืงืจื” ื–ื”, ืžื‘ืฆืข ืืช ื ื™ืชื•ื— ื”ื“ื’ื™ืžื”.
09:39
Turns out to work actually quite well,
193
579162
1851
ืžืกืชื‘ืจ ืฉื–ื” ืขื•ื‘ื“ ื‘ื›ืœืœ ืœื ืจืข, ื‘ืžื™ื•ื—ื“ ื›ืืฉืจ
09:41
particularly when your color printer has printed the color bars
194
581037
3092
ืžื“ืคืกืช ื”ืฆื‘ืข ืฉืœืš ื”ื“ืคื™ืกื” ืืช ืงื•ื•ื™ ื”ืฆื‘ืข
ืฉืžืฆื™ื™ื ื™ื ืื™ืš ื”ื“ื‘ืจื™ื ืขื•ื‘ื“ื™ื.
09:44
that indicate how things work.
195
584153
1821
09:45
So my view of the health care worker of the future
196
585998
3024
ืื ื›ืŸ, ื”ืื•ืคืŸ ื‘ื• ืื ื™ ืจื•ืื” ืืช ืขื•ื‘ื“ ืฉื™ืจื•ืชื™ ื”ื‘ืจื™ืื•ืช ืฉืœ ื”ืขืชื™ื“
ื”ื•ื ืœื ืจื•ืคื,
09:49
is not a doctor, but an 18-year-old,
197
589046
2567
ืืœื ืฆืขื™ืจ ื‘ืŸ 18, ืืฉืจ ื‘ื ืกื™ื‘ื•ืช ืื—ืจื•ืช ื”ื™ื” ืžื•ื‘ื˜ืœ
09:51
otherwise unemployed, who has two things:
198
591637
2752
ื•ื‘ืจืฉื•ืชื• ืฉื ื™ ื“ื‘ืจื™ื. ืชืจืžื™ืœ ื’ื‘ ืžืœื ื‘ื‘ื“ื™ืงื•ืช ื”ืœืœื•,
09:54
a backpack full of these tests and a lancet
199
594413
2083
ื•ืื™ื–ืžืœ ื ื™ืชื•ื—ื™ื ืฉื™ืืคืฉืจ ืœื• ืžื“ื™ ืคืขื ืœืงื—ืช ื“ื’ื™ืžื•ืช ื“ื,
09:56
to occasionally take a blood sample,
200
596520
1916
09:58
and an AK-47.
201
598460
1559
ื•ืจื•ื‘ื” ืงืœืฉื ื™ืงื•ื‘.
10:00
And these are the things that get him through his day.
202
600043
2596
ื•ืืœื• ื”ื“ื‘ืจื™ื ืฉื™ืืคืฉืจื• ืœื• ืœืฆืœื•ื— ืืช ื™ื•ืžื•.
10:02
(Laughter)
203
602663
1548
10:05
There's another very interesting connection here,
204
605372
2335
ื™ืฉ ื›ืืŸ ืงืฉืจ ื ื•ืกืฃ ืžืขื ื™ื™ืŸ ืžืื•ื“.
10:07
and that is, that what one wants to do is pass through useful information
205
607731
5540
ื•ื”ื•ื ืฉื”ืžื˜ืจื” ื›ืืŸ
ื”ื™ื ืœื”ืขื‘ื™ืจ ืžื™ื“ืข ืฉื™ืžื•ืฉื™
ื“ืจืš ืžืขืจื›ืช ื˜ืœืคื•ืŸ ืฉื”ื™ื ืœืจื•ื‘ ื’ืจื•ืขื” ืœืžื“ื™.
10:13
over what is generally a pretty awful telephone system.
206
613295
3531
10:16
It turns out there's an enormous amount of information
207
616850
2586
ืžืชื‘ืจืจ ืฉื™ืฉ ื‘ื—ื•ืฅ ื›ืžื•ื™ื•ืช ืขืฆื•ืžื•ืช ืฉืœ ืžื™ื“ืข
10:19
already available on that subject, which is the Mars Rover problem.
208
619460
3379
ื–ืžื™ืŸ ื‘ื ื•ืฉื ื–ื”, ื•ื–ื•ื”ื™ ืœืžืขืฉื” ื‘ืขื™ื™ืช Mars Rover (ืจื•ื‘ื•ื˜ ืฉืœ ื ืืก"ื).
10:22
How do you get back an accurate view of the color on Mars
209
622863
3867
ืื™ืš ืชืงื‘ืœ ืชืฆืคื™ืช ืžื“ื•ื™ื™ืงืช ืฉืœ ื”ืฆื‘ืข ืขืœ ืžืื“ื™ื,
10:26
if you have a really terrible bandwidth to do it with?
210
626754
3786
ืื ื™ืฉ ืœืš ืจื•ื—ื‘ ืคืก ืžืžืฉ ื’ืจื•ืข?
10:30
And the answer is not complicated,
211
630564
1872
ื•ื”ืชืฉื•ื‘ื” ืœื ืžืกื•ื‘ื›ืช.
10:32
but it's one which I don't want to go through here,
212
632460
2541
ืืš ืื ื™ ืœื ืจื•ืฆื” ืœื“ื•ืŸ ื‘ื” ื›ืืŸ,
ืจืง ืื•ืžืจ ืฉืžืขืจื›ื•ืช ื”ืชืงืฉื•ืจืช
10:35
other than to say that the communication systems for doing this
213
635025
3044
ื”ืžืฉืžืฉื•ืช ืœื›ืš ืžื•ื‘ื ื•ืช ื”ื™ื˜ื‘.
10:38
are really pretty well understood.
214
638093
1701
10:39
Also, a fact which you may not know
215
639818
2737
ื‘ื ื•ืกืฃ, ืขื•ื‘ื“ื” ืฉืื•ืœื™ ืœื ื™ื“ืขืชื,
10:42
is that the compute capability of this thing is not so different
216
642579
3734
ื”ื™ื ืฉื™ื›ื•ืœืช ื”ื—ื™ืฉื•ื‘ ืฉืœ ื”ื“ื‘ืจ ื”ื–ื”
ืื™ื ื” ืฉื•ื ื” ืžืื•ื“ ืžื™ื›ื•ืœืช ื”ื—ื™ืฉื•ื‘
10:46
from the compute capability of your desktop computer.
217
646337
2839
ืฉืœ ื”ืžื—ืฉื‘ ื”ื‘ื™ืชื™ ืฉืœืš.
10:49
This is a fantastic device which is only beginning to be tapped.
218
649200
3661
ื–ื”ื• ืžื›ืฉื™ืจ ืคื ื˜ืกื˜ื™ ืฉืจืง ืžืชื—ื™ืœ ืœื”ื™ื•ืช ืžื ื•ืฆืœ.
10:52
I don't know whether the idea of one computer, one child
219
652885
3446
ืื ื™ ืœื ื™ื•ื“ืข ื”ืื ื”ืจืขื™ื•ืŸ ืฉืœ ืžื—ืฉื‘ ืื—ื“, ื™ืœื“ ืื—ื“
10:56
makes any sense.
220
656355
1151
ื”ื•ื ื”ื’ื™ื•ื ื™. ื”ื ื” ื”ืžื—ืฉื‘ ืฉืœ ื”ืขืชื™ื“.
10:57
Here's the computer of the future,
221
657530
1906
10:59
because this screen is already there and they're ubiquitous.
222
659460
3201
ืžืฉื•ื ืฉื”ืžืกืš ื›ื‘ืจ ืฉื ื•ื”ื ื™ื›ื•ืœื™ื ืœื”ื™ืžืฆื ื‘ื›ืœ ืžืงื•ื ื‘ื• ื–ืžื ื™ืช.
11:04
All right, let me show you just a little bit about advanced devices.
223
664111
3237
ื›ืขืช ื”ืจืฉื• ืœื™ ืœื”ืฆื™ื’ ื‘ืคื ื™ื›ื ื‘ืงืฆืจื” ืืช ื”ืžื›ืฉื™ืจื™ื ื”ืžืชืงื“ืžื™ื.
ื•ื ืชื—ื™ืœ ื‘ื”ืฆื’ืช ื‘ืขื™ื” ืงื˜ื ื”.
11:07
And we'll start by posing a little problem.
224
667372
2154
11:09
What you see here is another centimeter-sized device,
225
669550
3397
ืžื” ืฉืืชื ืจื•ืื™ื ื›ืืŸ ื”ื•ื ืžื›ืฉื™ืจ ื ื•ืกืฃ ื‘ื’ื•ื“ืœ ืก"ืž.
11:12
and the different colors are different colors of dye.
226
672971
3983
ื•ื”ืฆื‘ืขื™ื ื”ืฉื•ื ื™ื ื”ื ืฆื‘ืขื™ ื”ื“ืคืกื” ืฉื•ื ื™ื.
11:16
And you notice something
227
676978
1178
ื•ืืชื ืžื‘ื—ื™ื ื™ื ื‘ืžืฉื”ื• ืฉืื•ืœื™ ื™ืจืื” ืœื›ื
11:18
which might strike you as a little bit interesting,
228
678180
2699
ืžืขื˜ ืžืขื ื™ื™ืŸ,
11:20
which is, the yellow seems to disappear,
229
680903
2857
ื•ื”ื•ื ืฉื”ืฆื”ื•ื‘ ื ืจืื” ื›ื ืขืœื,
11:23
get through the blue, and then get through the red.
230
683784
2489
ืขื•ื‘ืจ ื“ืจืš ื”ื›ื—ื•ืœ, ื•ืื– ื“ืจืš ื”ืื“ื•ื.
11:26
How does that happen?
231
686297
1153
ืื™ืš ื–ื” ืงื•ืจื”? ืื™ืš ืืชื” ื’ื•ืจื ืœืžืฉื”ื• ืœื–ืจื•ื ื“ืจืš ืžืฉื”ื• ืื—ืจ?
11:27
How do you make something flow through something?
232
687474
2575
ื•ื›ืžื•ื‘ืŸ ืฉื”ืชืฉื•ื‘ื” ื”ื™ื, "ืืชื” ืœื".
11:30
And, of course the answer is, "You don't."
233
690073
2195
ืืชื” ื’ื•ืจื ืœื• ืœื–ืจื•ื ืžืชื—ืช ื•ืžืขืœ.
11:32
You make it flow under and over.
234
692292
1743
ืื‘ืœ ื›ืขืช ื”ืฉืืœื” ื”ื™ื, ืื™ืš ืืชื” ื’ื•ืจื ืœื• ืœื–ืจื•ื
11:34
But now the question is:
235
694059
1161
11:35
How do you make it flow under and over in a piece of paper?
236
695244
3542
ืžืชื—ืช ื•ืžืขืœ ื‘ืชื•ืš ื—ืชื™ื›ืช ื ื™ื™ืจ?
11:38
The answer is that what you do --
237
698810
2946
ื•ื”ืชืฉื•ื‘ื” ื”ื™ื ืฉืžื” ืฉืืชื” ืขื•ืฉื”,
11:41
and the details are not terribly important here --
238
701780
2656
ื•ื”ืคืจื˜ื™ื ืœื ืžืื•ื“ ื—ืฉื•ื‘ื™ื ื›ืืŸ,
11:44
is to make something more elaborate:
239
704460
1891
ื–ื” ืœืงื—ืช ืžืฉื”ื• ื•ืœืฉื›ืœืœ ืื•ืชื•,
11:46
You take several different layers of paper,
240
706375
2077
ืืชื” ืœื•ืงื— ืžืกืคืจ ืฉื›ื‘ื•ืช ืฉื•ื ื•ืช ืฉืœ ื ื™ื™ืจ,
11:48
each one containing its own little fluid system,
241
708476
3071
ื›ืœ ืื—ืช ืžื›ื™ืœื” ืžืขืจื›ืช ื ื•ื–ืœื™ื ืงื˜ื ื” ืžืฉืœ ืขืฆืžื”,
11:51
and you separate them by pieces of, literally, double-sided carpet tape,
242
711571
4589
ื•ืืชื” ืžืคืจื™ื“ ื‘ื ื™ื”ืŸ ืขืœ ื™ื“ื™ ื—ืชื™ื›ื•ืช ืฉืœ,
ืคืฉื•ื˜ื• ื›ืžืฉืžืขื•, ื“ื‘ืง ืฉื˜ื™ื—ื™ื ื“ื•-ืฆื“ื“ื™.
11:56
the stuff you use to stick the carpets onto the floor.
243
716184
2886
ื–ื” ืฉืžืฉืชืžืฉื™ื ื‘ื• ื›ื“ื™ ืœื”ื“ื‘ื™ืง ืฉื˜ื™ื—ื™ื ืœืจื™ืฆืคื”.
11:59
And the fluid will flow from one layer into the next.
244
719094
3226
ื•ื”ื ื•ื–ืœ ื™ื–ืจื•ื ืžืฉื›ื‘ื” ืื—ืช ืœื‘ืื” ืื—ืจื™ื”.
12:02
It distributes itself, flows through further holes,
245
722344
3092
ื”ื•ื ืžืชืคื–ืจ, ื–ื•ืจื ื“ืจืš ื—ื•ืจื™ื ื ื•ืกืคื™ื,
12:05
distributes itself.
246
725460
1589
ืžืชืคื–ืจ.
12:07
And what you see, at the lower right-hand side there,
247
727073
3241
ื•ืžื” ืฉืืชื ืจื•ืื™ื ื‘ืฆื“ ื”ื™ืžื ื™ ื”ืชื—ืชื•ืŸ ืฉื
12:10
is a sample in which a single sample of blood has been put on the top,
248
730338
5299
ื”ื•ื ื“ื•ื’ืžื” ื‘ื” ื“ื•ื’ืžื™ืช ื‘ื•ื“ื“ืช
ืฉืœ ื“ื ื”ื•ื ื—ื” ืขืœ ื”ืงืฆื” ื”ืขืœื™ื•ืŸ,
12:15
and it has gone through and distributed itself
249
735661
2510
ื•ื”ื™ื ื–ืจืžื” ื•ื”ืชืคืฆืœื”
12:18
into these 16 holes on the bottom,
250
738195
3346
ืœืชื•ืš 16 ื”ื—ื•ืจื™ื ื”ืืœื• ื‘ืชื—ืชื™ืช,
12:21
in a piece of paper -- basically, it looks like a chip,
251
741565
2704
ื‘ืคื™ืกืช ื ื™ื™ืจ, ืœืžืขืฉื” ื–ื” ื ืจืื” ื›ืžื• ืฉื‘ื‘,
ืฉืชื™ ื—ืชื™ื›ื•ืช ืฉืœ ื ื™ื™ืจ ืขื‘ื”.
12:24
two pieces of paper thick.
252
744293
1738
12:26
And in this particular case,
253
746055
1483
ื•ื‘ืžืงืจื” ื”ืกืคืฆื™ืคื™ ื”ื–ื” ื”ื™ื™ื ื• ืžืขื•ื ื™ื™ื ื™ื ืจืง
12:27
we were just interested in the replicability of that.
254
747562
2764
ื‘ื™ื›ื•ืœืช ื”ืฉื—ื–ื•ืจ ืฉืœ ื–ื”.
12:30
But that is, in principle, the way you solve
255
750350
2304
ืื‘ืœ ื‘ืื•ืคืŸ ืขืงืจื•ื ื™, ื–ื• ื”ื“ืจืš ื‘ื” ื ื™ืชืŸ ืœืคืชื•ืจ
12:32
the "fever of unexplained origin" problem,
256
752678
2156
ืืช ื‘ืขื™ื™ืช ื”"ื—ื•ื ื’ื‘ื•ื” ืžืžืงื•ืจ ืœื ืžื•ืกื‘ืจ".
12:34
because each one of those spots then becomes a test
257
754858
2756
ืžืฉื•ื ืฉื›ืœ ืื—ืช ืžื”ื ืงื•ื“ื•ืช ื”ืืœื• ื”ื•ืคื›ืช
ืœืžื‘ื—ืŸ ืขื‘ื•ืจ ืงื‘ื•ืฆื” ืžืกื•ื™ื™ืžืช ืฉืœ ืกืžืžื ื™ื
12:37
for a particular set of markers of disease,
258
757638
3599
ืฉืœ ืžื—ืœื”.
12:41
and this will work in due course.
259
761261
2266
ื•ื–ื” ื™ืขื‘ื•ื“ ื‘ืขืชื™ื“ ื”ืงืจื•ื‘.
12:43
Here is an example of a slightly more complicated device.
260
763551
3316
ื•ื”ื ื” ื“ื•ื’ืžื” ืฉืœ ืžื›ืฉื™ืจ ืžืขื˜ ืžื•ืจื›ื‘ ื™ื•ืชืจ.
12:46
There's the chip.
261
766891
1182
ื–ื”ื• ื”ืฉื‘ื‘.
12:48
You dip in a corner.
262
768097
1216
ืืชื” ื˜ื•ื‘ืœ ืืช ืื—ืช ื”ืคื™ื ื•ืช. ื”ื ื•ื–ืœ ืขื•ื‘ืจ ืœืžืจื›ื–.
12:49
The fluid goes into the center.
263
769337
1547
12:50
It distributes itself out into these various wells or holes
264
770908
3783
ื”ื•ื ืžืชืคื–ืจ ื›ืœืคื™ ื—ื•ืฅ ืœืชื•ืš
ื”ื—ื•ืจื™ื ื•ื”ื ืงื‘ื™ื, ื•ื”ื•ืคืš ืœืฆื‘ืข.
12:54
and turns color,
265
774715
1236
12:55
all done with paper and carpet tape.
266
775975
2693
ื•ื”ื›ืœ ื ืขืฉื” ื‘ืืžืฆืขื•ืช ื ื™ื™ืจ ื•ื“ื‘ืง ืฉื˜ื™ื—ื™ื.
12:58
So it's, I think, as low-cost
267
778692
2157
ืื ื›ืš, ืื ื™ ื—ื•ืฉื‘ ืฉื ื™ืชืŸ ืœื”ื•ื–ื™ืœ ืขืœื•ื™ื•ืช
13:00
as we're likely to be able to come up and make things.
268
780873
2827
ื‘ื”ืชืื ืœื™ื›ื•ืœืชื ื• ืœื”ืžืฆื™ื ื•ืœื™ืฆื•ืจ ื“ื‘ืจื™ื.
13:04
Now, I have two last little stories to tell you
269
784692
3296
ื›ืขืช, ื™ืฉ ืœื™ ืกื™ืคื•ืจ ืื—ื“, ืฉื ื™ ืกื™ืคื•ืจื™ื ืื—ืจื•ื ื™ื
ืœืกืคืจ ืœื›ื, ืœืกื™ื›ื•ื ืฉืœ ื”ืขืกืง ื”ื–ื”.
13:08
in finishing off this business.
270
788012
2610
13:10
This is one:
271
790646
1165
ื–ื” ื”ืจืืฉื•ืŸ. ืื—ื“ ื”ื“ื‘ืจื™ื ืฉืฆืจื™ืš ืœืขืฉื•ืช ืœืคืขืžื™ื
13:11
One of the things you occasionally need to do
272
791835
2441
ื–ื” ืœื”ืคืจื™ื“ ืชืื™ ื“ื ืžื ื•ื–ืœ ื”ืคืœื–ืžื”.
13:14
is separate blood cells from serum.
273
794300
2647
ื•ื”ืฉืืœื” ื”ื™ืชื”,
13:18
And the question was,
274
798134
1685
13:19
here we do it by taking a sample,
275
799843
2101
ื›ืืŸ ืื ื• ืขื•ืฉื™ื ื–ืืช ืขืœ ื™ื“ื™ ืœืงื™ื—ืช ื“ื’ื™ืžื”.
13:21
we put it in a centrifuge, we spin it,
276
801968
3862
ืื ื—ื ื• ืฉืžื™ื ืื•ืชื” ื‘ืžื›ืฉื™ืจ ืฆื ื˜ืจื™ืคื•ื’ื”.
ืื ื• ืžืกื•ื‘ื‘ื™ื ืื•ืชื”, ื•ืžืชืงื‘ืœืช ื”ืคืจื“ื” ืฉืœ ืชืื™ ื”ื“ื. ื ืคืœื.
13:25
and you get blood cells out.
277
805854
2467
13:28
Terrific.
278
808345
1159
ืžื” ื”ื™ื” ืงื•ืจื” ืื™ืœื• ืœื ื”ื™ื” ืœืš ื—ืฉืžืœ,
13:29
What happens if you don't have electricity, a centrifuge, and whatever?
279
809528
3447
ื•ืฆื ื˜ืจื™ืคื•ื’ื”, ื•ื›ื•ืœื™?
13:32
And we thought for a while of how you might do this,
280
812999
2516
ื•ื—ืฉื‘ื ื• ื‘ืžืฉืš ื–ืžืŸ ืžื” ื›ื™ืฆื“ ื ื™ืชืŸ ืœืขืฉื•ืช ื–ืืช.
13:35
and the way, in fact, you do it, is what's shown here.
281
815539
2637
ื•ื”ื“ืจืš, ืœืžืขืฉื”, ื‘ื” ืขื•ืฉื™ื ื–ืืช, ื”ื™ื ืžื” ืฉืžื•ืฆื’ ื›ืืŸ.
ืืชื” ืœื•ืงื— ืžื˜ืจืคืช ื‘ื™ืฆื™ื,
13:38
You get an eggbeater, which is everywhere, and you saw off a blade,
282
818200
4607
ืฉื ื™ืชืŸ ืœื”ืฉื™ื’ ื‘ื›ืœ ืžืงื•ื. ื•ืืชื” ืžืกื™ืจ ืืช ื”ืœื”ื‘.
13:42
and then you take tubing, and you stick it on that.
283
822831
2483
ื•ืื– ืืชื” ืœื•ืงื— ืฆื™ื ื•ืจื™ืช,
ื•ืžื—ื‘ืจ ืื•ืชื”. ืืชื” ืžื›ื ื™ืก ืœืชื•ื›ื” ืืช ื”ื“ื. ืืชื” ืžืกื•ื‘ื‘ ืืช ื–ื”.
13:45
You put the blood in, somebody sits there and spins it.
284
825338
2740
ืžื™ืฉื”ื• ื™ื•ืฉื‘ ืฉื ื•ืžืกื•ื‘ื‘ ืืช ื–ื”.
13:48
It works really, really well.
285
828102
2119
ื–ื” ืขื•ื‘ื“ ืžืžืฉ ืžืžืฉ ื˜ื•ื‘.
13:50
And we sat down, we did the physics of eggbeaters
286
830245
2414
ื•ืื ื—ื ื• ืืžืจื ื• ืฉื‘ื ื™ื ื• ืืช ื”ืคื™ื–ื™ืงื” ืฉืœ ืžื˜ืจืคืช ื‘ื™ืฆื™ื
13:52
and self-aligning tubes and all the rest of that kind of thing,
287
832683
3077
ื•ืฆื™ื ื•ืจื™ื•ืช ืฉืžืกืชื“ืจื•ืช ืžืขืฆืžืŸ ื•ื›ืœ ื™ืชืจ ื”ื“ื‘ืจ ืžืกื•ื’ ื–ื”,
13:55
and sent it off to a journal.
288
835784
1462
ืฉืœื—ื ื• ืืช ื–ื” ืœื›ืชื‘-ืขืช ืžื“ืขื™.
13:57
We were very proud of this,
289
837270
1322
ื”ื™ื™ื ื• ืžืื•ื“ ื’ืื™ื ื‘ื–ื”, ื‘ืžื™ื•ื—ื“ ื‘ื›ื•ืชืจืช
13:58
particularly the title, which was "Eggbeater as Centrifuge."
290
838616
2862
ืฉื”ื™ื™ืชื” "ืžื˜ืจืฃ ื‘ื™ืฆื™ื ื›ืฆื ื˜ืจื™ืคื•ื’ื”".
14:01
(Laughter)
291
841502
1074
(ืฆื—ื•ืง)
14:02
And we sent it off,
292
842600
1151
ื•ืฉืœื—ื ื• ืืช ื–ื”, ื•ื–ื” ื—ื–ืจ ื‘ื“ื•ืืจ.
14:03
and by return mail, it came back.
293
843775
1907
14:05
I called up the editor and I said,
294
845706
1730
ื”ืชืงืฉืจืชื™ ืœืขื•ืจืš ื•ืืžืจืชื™,
14:07
"What's going on? How is this possible?"
295
847460
2122
"ืžื” ืžืชืจื—ืฉ ืคื”? ืื™ืš ื–ื” ื™ื›ื•ืœ ืœื”ื™ื•ืช?"
14:09
The editor said, with enormous disdain,
296
849606
3134
ื”ืขื•ืจืš ืืžืจ, ื‘ื‘ื•ื– ืขืฆื•ื,
14:12
"I read this.
297
852764
1443
"ืงืจืืชื™ ืืช ื–ื”.
14:14
And we're not going to publish it, because we only publish science."
298
854231
3756
ื•ืื ื—ื ื• ืœื ื”ื•ืœื›ื™ื ืœืคืจืกื ืืช ื–ื”, ืžืคื ื™ ืฉืื ื—ื ื•
ืžืคืจืกืžื™ื ืจืง ืžื“ืข."
14:18
(Laughter)
299
858011
1413
ื•ื–ื” ื ื•ืฉื ื—ืฉื•ื‘
14:19
And it's an important issue,
300
859448
1469
14:20
because it means that we have to, as a society,
301
860941
3398
ืžืฉื•ื ืฉื–ื” ืื•ืžืจ ืฉืื ื—ื ื• ื—ื™ื™ื‘ื™ื,
ื›ื—ื‘ืจื”,
14:24
think about what we value.
302
864363
1977
ืœื—ืฉื•ื‘ ืœืžื” ืื ื—ื ื• ื‘ื•ื—ืจื™ื ืœืชืช ื—ืฉื™ื‘ื•ืช.
14:26
And if it's just papers and Phys. Rev. letters,
303
866364
2784
ื•ืื ื–ื” ืจืง ืœื ื™ื™ืจ ื•ืœื›ืชื‘ื™ ืขืช ืžื“ืขื™ื™ื,
ืื ื—ื ื• ื‘ื‘ืขื™ื”.
14:29
we've got a problem.
304
869172
1243
14:31
Here is another example of something which is --
305
871078
3230
ื•ื›ืืŸ ื™ืฉ ื“ื•ื’ืžื” ื ื•ืกืคืช ืฉืœ ืžืฉื”ื• ืฉ --
14:34
this is a little spectrophotometer.
306
874332
2041
ื–ื” ืกืคืงื˜ืจื•ืคื•ื˜ื•ืžื˜ืจ ืงื˜ืŸ.
14:36
It measures the absorption of light in a sample.
307
876397
3290
ื”ื•ื ืžื•ื“ื“ ืืช ื‘ืœื™ืขืช ื”ืื•ืจ ื‘ื“ื’ื™ืžื”,
14:39
The neat thing about this is,
308
879711
1479
ื”ื“ื‘ืจ ื”ื™ืขื™ืœ ืฉื‘ื• ื”ื•ื, ืฉื™ืฉ ืœืš ืžืงื•ืจ ืื•ืจ ืฉืžื”ื‘ื”ื‘
14:41
you have a light source that flickers on and off at about 1,000 hertz,
309
881214
3691
ื‘ืชื“ื™ืจื•ืช ืฉืœ ื›-1,000 ื”ืจืฅ.
14:44
another light source that detects that light at 1,000 hertz,
310
884929
3669
ืžืงื•ืจ ืื•ืจ ื ื•ืกืฃ ืฉืžื–ื”ื” ืืช ื”ืื•ืจ ื‘-1,000 ื”ืจืฅ.
14:48
and so you can run this system in broad daylight.
311
888622
2814
ื•ื›ืš ืืชื” ื™ื›ื•ืœ ืœื”ืจื™ืฅ ืืช ื”ืžืขืจื›ืช ื‘ืื•ืจ ื™ื•ื ืžืœื.
14:51
It performs about equivalently
312
891460
2069
ื”ื‘ื™ืฆื•ืขื™ื ืฉืœื” ื›ืžืขื˜ ื–ื”ื™ื
14:53
to a system that's on the order of 100,000 dollars.
313
893553
4569
ืœืืœื• ืฉืœ ืžืขืจื›ืช ืžืกื“ืจ ื’ื•ื“ืœ ืฉืœ
100,000 ื“ื•ืœืจ.
14:58
It costs 50 dollars.
314
898146
1161
ื–ื” ืขื•ืœื” 50 ื“ื•ืœืจ. ืกื‘ื™ืจ ืœื”ื ื™ื— ืฉื ื•ื›ืœ ืœื”ื•ืจื™ื“ ืืช ื”ืขืœื•ืช ืœ-50 ืกื ื˜,
14:59
We can probably make it for 50 cents if we put our mind to it.
315
899331
4105
ืื ืจืง ื ืงื“ื™ืฉ ืœื›ืš ืžื—ืฉื‘ื”.
15:03
Why doesn't somebody do it?
316
903460
1873
ืœืžื” ืืฃ ืื—ื“ ืœื ืขื•ืฉื” ื–ืืช? ื•ื”ืชืฉื•ื‘ื” ื”ื™ื,
15:05
The answer is:
317
905357
1151
"ืื™ืš ืชื•ื›ืœ ืœื”ืคื•ืš ืืช ื–ื” ืœืจื™ื•ื•ื—ื™ ื‘ืžืขืจื›ืช ืงืคื™ื˜ืœื™ืกื˜ื™ืช?"
15:06
How do you make a profit in a capitalist system, doing that?
318
906532
3270
15:09
Interesting problem.
319
909826
1292
ื‘ืขื™ื” ืžืขื ื™ื™ื ืช.
15:12
So, let me finish by saying that we've thought about this
320
912575
4953
ืื ื›ืŸ, ื”ืจืฉื• ืœื™ ืœืกื™ื™ื ื‘ื›ืš ืฉืื•ืžืจ
ืฉื”ืชื™ื™ื—ืกื ื• ืœื–ื” ื›ืืœ ืกื•ื’ ืฉืœ ื‘ืขื™ื” ื”ื ื“ืกืื™ืช.
15:17
as a kind of engineering problem.
321
917552
2202
ื•ืฉืืœื ื•, ืžื”ื• ื”ืจืขื™ื•ืŸ ื”ืžื“ืขื™ ื”ื›ืœืœื™ ื›ืืŸ?
15:19
And we've asked: What is the scientific unifying idea here?
322
919778
4382
15:24
And we've decided we should think about this
323
924184
2124
ื•ื”ื—ืœื˜ื ื• ืฉืขืœื™ื ื• ืœื—ืฉื•ื‘ ืขืœ ื–ื”
ืœื ื‘ืžื•ืฉื’ื™ื ืฉืœ ืขืœื•ืช,
15:26
not so much in terms of cost, but in terms of simplicity.
324
926332
3104
ืืœื ื‘ืžื•ืฉื’ื™ื ืฉืœ ืคืฉื˜ื•ืช.
15:29
Simplicity is a neat word.
325
929460
1578
ืคืฉื˜ื•ืช ื”ื™ื ืžื™ืœื” ื™ืคื”. ื•ืขืœื™ื›ื ืœื—ืฉื•ื‘ ืขืœ
15:31
You've got to think about what simplicity means.
326
931062
2374
ืžื” ื”ืžืฉืžืขื•ืช ืฉืœ ืคืฉื˜ื•ืช.
ืื ื™ ื™ื•ื“ืข ืžื” ื–ื” ืคืฉื˜ื•ืช ืื‘ืœ ืœืžืขืฉื” ืื™ื ื ื™ ื™ื•ื“ืข ืžื” ื”ืžืฉืžืขื•ืช ืฉืœื”.
15:34
I know what it is,
327
934015
1156
15:35
but I don't actually know what it means.
328
935195
2177
15:37
So I actually was interested enough in this
329
937396
2097
ืื–, ื”ื ื•ืฉื ืขื ื™ื™ืŸ ืื•ืชื™ ืžืกืคื™ืง ื›ื“ื™ ืœืื’ื“
15:39
to put together several groups of people.
330
939517
3753
ืžืกืคืจ ืงื‘ื•ืฆื•ืช ืฉืœ ืื ืฉื™ื ื™ื—ื“.
15:43
The most recent involved a couple of people at MIT,
331
943904
2532
ื•ื”ืงื‘ื•ืฆื•ืช ื”ืื—ืจื•ื ื•ืช ื›ืœืœื• ืžืกืคืจ ืื ืฉื™ื ื‘ืžื›ื•ืŸ ื”ื˜ื›ื ื•ืœื•ื’ื™ MIT,
15:46
one of them being an exceptionally bright kid
332
946460
2120
ืื—ื“ ืžื”ื ื”ื•ื ื‘ื—ื•ืจ ืžื‘ืจื™ืง ื‘ืฆื•ืจื” ื™ื•ืฆืืช ืžืŸ ื”ื›ืœืœ
15:48
who is one of the very few people I would think of
333
948604
2710
ื•ื”ื•ื ืื—ื“ ื”ืื ืฉื™ื ื”ื‘ื•ื“ื“ื™ื ืฉืื ื™ ื™ื›ื•ืœ ืœื—ืฉื•ื‘ ืขืœื™ื”ื
ืฉื”ื ื’ืื•ื ื™ื ืืžื™ืชื™ื™ื.
15:51
who's an authentic genius.
334
951338
1389
15:52
We all struggled for an entire day to think about simplicity.
335
952751
4050
ื›ื•ืœื ื• ื”ืชืืžืฆื ื• ื‘ืžืฉืš ื™ื•ื ืฉืœื ื›ื“ื™ ืœื—ืฉื•ื‘ ืขืœ ืคืฉื˜ื•ืช.
15:56
And I want to give you the answer of this deep scientific thought.
336
956825
4182
ื•ืื ื™ ืจื•ืฆื” ืœืชืช ืœื›ื ืืช ื”ืชืฉื•ื‘ื”
ืฉืœ ื”ืžื—ืฉื‘ื” ื”ืžื“ืขื™ืช ื”ืขืžื•ืงื” ื”ื–ื•.
16:01
[What is simplicity?
337
961031
1333
[ืžื” ื”ื™ื ืคืฉื˜ื•ืช? "ืื™ ืืคืฉืจ ืœื“ืคื•ืง ืืช ื–ื”"] (ืฆื—ื•ืง)
16:02
"It's impossible to f..k it up"]
338
962388
1587
16:03
(Laughter)
339
963999
1049
ืืคืฉืจ ืœื”ืกืชื›ืœ ืขืœ ื–ื” ื›ืš, ืืชื” ืžืงื‘ืœ ืืช ืžื” ืฉืฉื™ืœืžืช ืขืœื™ื•.
16:05
So, in a sense, you get what you pay for.
340
965072
2450
16:07
Thank you very much.
341
967546
1509
ืชื•ื“ื” ืจื‘ื”.
16:09
(Applause)
342
969079
2085
(ืฆื—ื•ืง)
ื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