TED2010
Nathan Myhrvold: Could this laser zap malaria?
Filmed:
Readability: 3.7
965,317 views
Nathan Myhrvold and team's latest inventions -- as brilliant as they are bold -- remind us that the world needs wild creativity to tackle big problems like malaria. And just as that idea sinks in, he rolls out a live demo of a new, mosquito-zapping gizmo you have to see to believe.
Nathan Myhrvold - Polymath
Nathan Myhrvold is a professional jack-of-all-trades. After leaving Microsoft in 1999, he's been a world barbecue champion, a wildlife photographer, a chef, a contributor to SETI, and a volcano explorer. Full bio
Nathan Myhrvold is a professional jack-of-all-trades. After leaving Microsoft in 1999, he's been a world barbecue champion, a wildlife photographer, a chef, a contributor to SETI, and a volcano explorer. Full bio
Double-click the English transcript below to play the video.
00:15
We invent.
0
0
2000
00:17
My company invents
1
2000
2000
00:19
all kinds of new technology
2
4000
2000
00:21
in lots of different areas.
3
6000
2000
00:23
And we do that for a couple of reasons.
4
8000
2000
00:25
We invent for fun --
5
10000
2000
00:27
invention is a lot of fun to do --
6
12000
3000
00:30
and we also invent for profit.
7
15000
2000
00:32
The two are related because
8
17000
2000
00:34
the profit actually takes long enough that if it isn't fun,
9
19000
2000
00:36
you wouldn't have the time to do it.
10
21000
2000
00:38
So we do this
11
23000
2000
00:40
fun and profit-oriented inventing
12
25000
2000
00:42
for most of what we do,
13
27000
2000
00:44
but we also have a program where we invent for humanity --
14
29000
3000
00:47
where we take some of our best inventors,
15
32000
2000
00:49
and we say, "Are there problems
16
34000
2000
00:51
where we have a good idea for solving a problem the world has?" --
17
36000
3000
00:54
and to solve it in the way we try to solve problems,
18
39000
3000
00:57
which is with dramatic, crazy,
19
42000
2000
00:59
out-of-the-box solutions.
20
44000
2000
01:01
Bill Gates is one of those smartest guys of ours
21
46000
2000
01:03
that work on these problems
22
48000
2000
01:05
and he also funds this work, so thank you.
23
50000
3000
01:08
So I'm going to briefly discuss
24
53000
2000
01:10
a couple of problems that we have
25
55000
2000
01:12
and a couple of problems where
26
57000
2000
01:14
we've got some solutions underway.
27
59000
2000
01:16
Vaccination is one of the
28
61000
3000
01:19
key techniques in public health,
29
64000
2000
01:21
a fantastic thing.
30
66000
2000
01:23
But in the developing world a lot of vaccines
31
68000
3000
01:26
spoil before they're administered,
32
71000
2000
01:28
and that's because they need to be kept cold.
33
73000
3000
01:31
Almost all vaccines need to be kept at refrigerator temperatures.
34
76000
3000
01:34
They go bad very quickly if you don't,
35
79000
2000
01:36
and if you don't have stable power grid, this doesn't happen,
36
81000
3000
01:39
so kids die.
37
84000
2000
01:41
It's not just the loss of the vaccine that matters;
38
86000
3000
01:44
it's the fact that those kids don't get vaccinated.
39
89000
3000
01:47
This is one of the ways that
40
92000
3000
01:50
vaccines are carried:
41
95000
2000
01:52
These are Styrofoam chests. These are being carried by people,
42
97000
3000
01:55
but they're also put on the backs of pickup trucks.
43
100000
2000
01:57
We've got a different solution.
44
102000
3000
02:00
Now, one of these Styrofoam chests
45
105000
3000
02:03
will last for about four hours with ice in it.
46
108000
2000
02:05
And we thought, well, that's not really good enough.
47
110000
3000
02:08
So we made this thing.
48
113000
2000
02:10
This lasts six months with no power;
49
115000
3000
02:13
absolutely zero power,
50
118000
2000
02:15
because it loses less
51
120000
2000
02:17
than a half a watt.
52
122000
2000
02:19
Now, this is our second generations prototype.
53
124000
3000
02:22
The third generation prototype is, right now,
54
127000
2000
02:24
in Uganda being tested.
55
129000
3000
02:27
Now, the reason we were able to come up with this
56
132000
2000
02:29
is two key ideas:
57
134000
2000
02:31
One is that this is similar to a cryogenic Dewar,
58
136000
2000
02:33
something you'd keep liquid nitrogen or liquid helium in.
59
138000
3000
02:36
They have incredible insulation,
60
141000
2000
02:38
so let's put some incredible insulation here.
61
143000
2000
02:40
The other idea is kind of interesting,
62
145000
3000
02:43
which is, you can't reach inside anymore.
63
148000
3000
02:46
Because if you open it up and reach inside,
64
151000
2000
02:48
you'd let the heat in, the game would be over.
65
153000
2000
02:50
So the inside of this thing actually looks like a Coke machine.
66
155000
3000
02:53
It vends out little individual vials.
67
158000
3000
02:56
So a simple idea,
68
161000
2000
02:58
which we hope is going to change the way vaccines are distributed
69
163000
3000
03:01
in Africa and around the world.
70
166000
2000
03:04
We'll move on to malaria.
71
169000
2000
03:06
Malaria is one of the great public health problems.
72
171000
3000
03:09
Esther Duflo talked a little bit about this.
73
174000
2000
03:11
Two hundred million people a year.
74
176000
3000
03:14
Every 43 seconds a child in Africa dies;
75
179000
3000
03:18
27 will die during my talk.
76
183000
3000
03:23
And there's no way for us here in this country
77
188000
3000
03:26
to grasp really what that means to the people involved.
78
191000
3000
03:29
Another comment of Esther's
79
194000
2000
03:31
was that we react when there's
80
196000
2000
03:33
a tragedy like Haiti,
81
198000
2000
03:35
but that tragedy is ongoing.
82
200000
2000
03:37
So what can we do about it?
83
202000
2000
03:39
Well, there are a lot of things people have tried
84
204000
2000
03:41
for many years for solving malaria.
85
206000
2000
03:43
You can spray; the problem is there are environmental issues.
86
208000
3000
03:46
You can try to treat people and create awareness.
87
211000
3000
03:49
That's great, except the places that have malaria really bad,
88
214000
3000
03:52
they don't have health care systems.
89
217000
2000
03:54
A vaccine would be a terrific thing,
90
219000
2000
03:56
only they don't work yet.
91
221000
2000
03:58
People have tried for a long time. There are a couple of interesting candidates.
92
223000
3000
04:01
It's a very difficult thing to make a vaccine for.
93
226000
3000
04:05
You can distribute bed nets,
94
230000
2000
04:07
and bed nets are very effective if you use them.
95
232000
3000
04:10
You don't always use them for that. People fish with them.
96
235000
2000
04:12
They don't always get to everyone.
97
237000
2000
04:14
And bed nets
98
239000
2000
04:16
have an effect on the epidemic,
99
241000
2000
04:18
but you're never going to make it extinct with bed nets.
100
243000
3000
04:21
Now, malaria is
101
246000
2000
04:23
an incredibly complicated disease.
102
248000
3000
04:26
We could spend hours going over this.
103
251000
2000
04:28
It's got this sort of soap opera-like lifestyle;
104
253000
2000
04:30
they have sex, they burrow into your liver,
105
255000
3000
04:33
they tunnel into your blood cells ...
106
258000
3000
04:36
it's an incredibly complicated disease,
107
261000
2000
04:38
but that's actually one of the things we find interesting about it
108
263000
3000
04:41
and why we work on malaria:
109
266000
2000
04:43
There's a lot of potential ways in.
110
268000
3000
04:47
One of those ways might be better diagnosis.
111
272000
3000
04:50
So we hope this year
112
275000
2000
04:52
to prototype each of these devices.
113
277000
3000
04:56
One does an automatic malaria diagnosis
114
281000
3000
04:59
in the same way that a diabetic's glucose meter works:
115
284000
3000
05:02
You take a drop of blood,
116
287000
2000
05:04
you put it in there and it automatically tells you.
117
289000
2000
05:06
Today, you need to do a complicated laboratory procedure,
118
291000
3000
05:09
create a bunch of microscope slides
119
294000
2000
05:11
and have a trained person examine it.
120
296000
3000
05:14
The other thing is, you know,
121
299000
2000
05:16
it would be even better if you didn't have to draw the blood.
122
301000
3000
05:19
And if you look through the eye,
123
304000
2000
05:21
or you look at the vessels on the white of the eye,
124
306000
3000
05:24
in fact, you may be able to do this
125
309000
2000
05:26
directly, without drawing any blood at all,
126
311000
3000
05:29
or through your nail beds.
127
314000
2000
05:31
Because if you actually look through your fingernails, you can see blood vessels,
128
316000
3000
05:34
and once you see blood vessels, we think we can see the malaria.
129
319000
3000
05:38
We can see it because of this molecule
130
323000
2000
05:40
called hemozoin.
131
325000
2000
05:42
It's produced by the malaria parasite
132
327000
3000
05:45
and it's a very interesting crystalline substance.
133
330000
3000
05:49
Interesting, anyway, if you're a solid-state physicist.
134
334000
2000
05:51
There's a lot of cool stuff we can do with it.
135
336000
3000
05:54
This is our femtosecond laser lab.
136
339000
3000
05:57
So this creates pulses of light
137
342000
2000
05:59
that last a femtosecond.
138
344000
2000
06:01
That's really, really, really short.
139
346000
3000
06:05
This is a pulse of light that's
140
350000
2000
06:07
only about one wavelength of light long,
141
352000
2000
06:09
so it's a whole bunch of photons
142
354000
2000
06:11
all coming and hitting simultaneously.
143
356000
2000
06:13
It creates a very high peak power
144
358000
2000
06:15
and it lets you do all kinds of interesting things;
145
360000
2000
06:17
in particular, it lets you find hemozoin.
146
362000
2000
06:19
So here's an image of red blood cells,
147
364000
3000
06:22
and now we can actually map
148
367000
2000
06:24
where the hemozoin and where the malaria parasites are
149
369000
3000
06:27
inside those red blood cells.
150
372000
2000
06:29
And using both this technique
151
374000
2000
06:31
and other optical techniques,
152
376000
2000
06:33
we think we can make those diagnostics.
153
378000
2000
06:35
We also have another hemozoin-oriented
154
380000
2000
06:37
therapy for malaria:
155
382000
2000
06:39
a way, in acute cases, to actually
156
384000
2000
06:41
take the malaria parasite and filter it out of the blood system.
157
386000
3000
06:44
Sort of like doing dialysis,
158
389000
2000
06:46
but for relieving the parasite load.
159
391000
3000
06:49
This is our thousand-core supercomputer.
160
394000
3000
06:52
We're kind of software guys,
161
397000
2000
06:54
and so nearly any problem that you pose,
162
399000
3000
06:57
we like to try to solve with some software.
163
402000
3000
07:00
One of the problems that you have if you're trying to eradicate malaria
164
405000
3000
07:03
or reduce it
165
408000
2000
07:05
is you don't know what's the most effective thing to do.
166
410000
3000
07:08
Okay, we heard about bed nets earlier.
167
413000
2000
07:10
You spend a certain amount per bed net.
168
415000
2000
07:12
Or you could spray.
169
417000
2000
07:14
You can give drug administration.
170
419000
2000
07:16
There's all these different interventions
171
421000
2000
07:18
but they have different kinds of effectiveness.
172
423000
2000
07:20
How can you tell?
173
425000
2000
07:22
So we've created, using our supercomputer,
174
427000
2000
07:24
the world's best computer model of malaria,
175
429000
2000
07:26
which we'll show you now.
176
431000
3000
07:29
We picked Madagascar.
177
434000
3000
07:32
We have every road,
178
437000
2000
07:34
every village,
179
439000
2000
07:36
every, almost, square inch of Madagascar.
180
441000
3000
07:39
We have all of the precipitation data
181
444000
3000
07:42
and the temperature data.
182
447000
2000
07:44
That's very important because the humidity and precipitation
183
449000
3000
07:47
tell you whether you've got
184
452000
2000
07:49
standing pools of water for the mosquitoes to breed.
185
454000
3000
07:52
So that sets the stage on which you do this.
186
457000
3000
07:55
You then have to introduce the mosquitoes,
187
460000
2000
07:57
and you have to model that
188
462000
2000
07:59
and how they come and go.
189
464000
2000
08:01
Ultimately, it gives you this.
190
466000
2000
08:03
This is malaria spreading
191
468000
2000
08:05
across Madagascar.
192
470000
2000
08:07
And this is this latter part of the rainy season.
193
472000
3000
08:10
We're going to the dry season now.
194
475000
2000
08:12
It nearly goes away in the dry season,
195
477000
2000
08:14
because there's no place for the mosquitoes to breed.
196
479000
3000
08:17
And then, of course, the next year it comes roaring back.
197
482000
3000
08:21
By doing these kinds of simulations,
198
486000
3000
08:24
we want to eradicate or control malaria
199
489000
2000
08:26
thousands of times in software
200
491000
3000
08:29
before we actually have to do it in real life;
201
494000
3000
08:32
to be able to simulate both the economic trade-offs --
202
497000
3000
08:35
how many bed nets versus how much spraying? --
203
500000
3000
08:38
or the social trade-offs --
204
503000
2000
08:40
what happens if unrest breaks out?
205
505000
3000
08:43
We also try to study our foe.
206
508000
2000
08:45
This is a high-speed camera view
207
510000
2000
08:47
of a mosquito.
208
512000
2000
08:50
And, in a moment,
209
515000
2000
08:52
we're going to see a view of the airflow.
210
517000
3000
08:55
Here, we're trying to visualize the airflow
211
520000
2000
08:57
around the wings of the mosquito
212
522000
2000
08:59
with little particles we're illuminating with a laser.
213
524000
3000
09:02
By understanding how mosquitoes fly,
214
527000
2000
09:04
we hope to understand how to make them not fly.
215
529000
3000
09:07
Now, one of the ways you can make them not fly
216
532000
2000
09:09
is with DDT.
217
534000
2000
09:11
This is a real ad.
218
536000
2000
09:13
This is one of those things you just can't make up.
219
538000
3000
09:16
Once upon a time, this was the primary technique,
220
541000
3000
09:19
and, in fact, many countries got rid of malaria through DDT.
221
544000
3000
09:22
The United States did.
222
547000
2000
09:24
In 1935, there were 150,000 cases a year
223
549000
3000
09:27
of malaria in the United States,
224
552000
3000
09:30
but DDT and a massive public health effort
225
555000
2000
09:32
managed to squelch it.
226
557000
3000
09:35
So we thought,
227
560000
2000
09:37
"Well, we've done all these things that are focused on the Plasmodium,
228
562000
3000
09:40
the parasite involved.
229
565000
2000
09:42
What can we do to the mosquito?
230
567000
2000
09:44
Well, let's try to kill it with consumer electronics."
231
569000
3000
09:48
Now, that sounds silly,
232
573000
2000
09:50
but each of these devices
233
575000
2000
09:52
has something interesting in it that maybe you could use.
234
577000
3000
09:55
Your Blu-ray player has
235
580000
2000
09:57
a very cheap blue laser.
236
582000
2000
09:59
Your laser printer has a mirror galvanometer
237
584000
2000
10:01
that's used to steer a laser beam very accurately;
238
586000
3000
10:04
that's what makes those little dots on the page.
239
589000
3000
10:07
And, of course, there's signal processing
240
592000
2000
10:09
and digital cameras.
241
594000
2000
10:11
So what if we could put all that together
242
596000
3000
10:14
to shoot them out of the sky with lasers?
243
599000
3000
10:17
(Laughter)
244
602000
2000
10:19
(Applause)
245
604000
3000
10:22
Now, in our company, this is what we call
246
607000
3000
10:25
"the pinky-suck moment."
247
610000
2000
10:27
(Laughter)
248
612000
2000
10:29
What if we could do that?
249
614000
2000
10:31
Now, just suspend disbelief for a moment,
250
616000
3000
10:34
and let's think of what could happen
251
619000
2000
10:36
if we could do that.
252
621000
2000
10:38
Well, we could protect very high-value targets like clinics.
253
623000
3000
10:41
Clinics are full of people that have malaria.
254
626000
3000
10:44
They're sick, and so they're less able to defend themselves from the mosquitoes.
255
629000
3000
10:47
You really want to protect them.
256
632000
2000
10:49
Of course, if you do that,
257
634000
2000
10:51
you could also protect your backyard.
258
636000
2000
10:53
And farmers could protect their crops
259
638000
2000
10:55
that they want to sell to Whole Foods
260
640000
2000
10:57
because our photons
261
642000
2000
10:59
are 100 percent organic. (Laughter)
262
644000
2000
11:01
They're completely natural.
263
646000
3000
11:04
Now, it actually gets better than this.
264
649000
2000
11:06
You could, if you're really smart,
265
651000
3000
11:09
you could shine a nonlethal laser on the bug
266
654000
3000
11:12
before you zap it,
267
657000
2000
11:14
and you could listen to the wing beat frequency
268
659000
2000
11:16
and you could measure the size.
269
661000
2000
11:18
And then you could decide:
270
663000
2000
11:20
"Is this an insect I want to kill,
271
665000
2000
11:22
or an insect I don't want to kill?"
272
667000
2000
11:24
Moore's law made computing cheap;
273
669000
2000
11:26
so cheap we can weigh
274
671000
2000
11:28
the life of an individual insect
275
673000
2000
11:30
and decide thumbs up
276
675000
3000
11:33
or thumbs down. (Laughter)
277
678000
3000
11:36
Now, it turns out we only kill the female mosquitoes.
278
681000
3000
11:39
They're the only ones that are dangerous.
279
684000
2000
11:41
Mosquitoes only drink blood
280
686000
2000
11:43
to lay eggs.
281
688000
2000
11:45
Mosquitoes actually live ... their day-to-day nutrition
282
690000
3000
11:48
comes from nectar, from flowers --
283
693000
2000
11:50
in fact, in the lab, we feed ours raisins --
284
695000
3000
11:53
but the female needs the blood meal.
285
698000
3000
11:56
So, this sounds really crazy, right?
286
701000
2000
11:58
Would you like to see it?
287
703000
2000
12:00
Audience: Yeah!
288
705000
2000
12:02
Nathan Myhrvold: Okay, so our legal department prepared a disclaimer,
289
707000
3000
12:06
and here it is.
290
711000
2000
12:08
(Laughter)
291
713000
3000
12:13
Now, after thinking about this a little bit
292
718000
3000
12:16
we thought, you know, it probably would be simpler
293
721000
2000
12:18
to do this with a nonlethal laser.
294
723000
2000
12:20
So, Eric Johanson, who built the device,
295
725000
3000
12:23
actually, with parts from eBay;
296
728000
2000
12:25
and Pablos Holman over here,
297
730000
2000
12:27
he's got mosquitoes in the tank.
298
732000
2000
12:29
We have the device over here.
299
734000
2000
12:31
And we're going to show you,
300
736000
2000
12:33
instead of the kill laser,
301
738000
2000
12:35
which will be a very brief, instantaneous pulse,
302
740000
2000
12:37
we're going to have a green laser pointer
303
742000
2000
12:39
that's going to stay on the mosquito for, actually, quite a long period of time;
304
744000
3000
12:42
otherwise, you can't see it very well.
305
747000
2000
12:44
Take it away Eric.
306
749000
2000
12:46
Eric Johanson: What we have here
307
751000
2000
12:48
is a tank on the other side of the stage.
308
753000
2000
12:50
And we have ... this computer screen
309
755000
2000
12:52
can actually see the mosquitoes as they fly around.
310
757000
2000
12:54
And Pablos, if he stirs up our mosquitoes a little bit
311
759000
3000
12:57
we can see them flying around.
312
762000
2000
12:59
Now, that's a fairly straightforward image processing routine,
313
764000
2000
13:01
and let me show you how it works.
314
766000
2000
13:03
Here you can see that the insects are being tracked
315
768000
2000
13:05
as they're flying around,
316
770000
2000
13:07
which is kind of fun.
317
772000
3000
13:10
Next we can actually light them up with a laser. (Laughter)
318
775000
2000
13:12
Now, this is a low powered laser,
319
777000
2000
13:14
and we can actually pick up a wing-beat frequency.
320
779000
2000
13:16
So you may be able to hear some mosquitoes flying around.
321
781000
3000
13:19
NM: That's a mosquito wing beat you're hearing.
322
784000
3000
13:24
EJ: Finally, let's see what this looks like.
323
789000
3000
13:29
There you can see mosquitoes as they fly around, being lit up.
324
794000
3000
13:32
This is slowed way down
325
797000
2000
13:34
so that you have an opportunity to see what's happening.
326
799000
2000
13:36
Here we have it running at high-speed mode.
327
801000
2000
13:38
So this system that was built for TED is here to illustrate
328
803000
2000
13:40
that it is technically possible to actually deploy a system like this,
329
805000
3000
13:43
and we're looking very hard at how to make it
330
808000
3000
13:46
highly cost-effective to use in places like Africa and other parts of the world.
331
811000
3000
13:49
(Applause)
332
814000
6000
13:56
NM: So it wouldn't be any fun to show you that
333
821000
3000
13:59
without showing you what actually happens when we hit 'em.
334
824000
3000
14:02
(Laughter)
335
827000
2000
14:10
(Laughter)
336
835000
3000
14:13
This is very satisfying.
337
838000
2000
14:15
(Laughter)
338
840000
2000
14:18
This is one of the first ones we did.
339
843000
2000
14:20
The energy's a little bit high here.
340
845000
2000
14:22
(Laughter)
341
847000
3000
14:27
We'll loop around here in just a second, and you'll see another one.
342
852000
2000
14:29
Here's another one. Bang.
343
854000
2000
14:31
An interesting thing is, we kill them all the time;
344
856000
3000
14:34
we've never actually gotten the wings to shut off in midair.
345
859000
3000
14:37
The wing motor is very resilient.
346
862000
2000
14:39
I mean, here we're blowing wings off
347
864000
2000
14:41
but the wing motor keeps all the way down.
348
866000
3000
14:45
So, that's what I have. Thanks very much.
349
870000
2000
14:47
(Applause)
350
872000
16000
ABOUT THE SPEAKER
Nathan Myhrvold - PolymathNathan Myhrvold is a professional jack-of-all-trades. After leaving Microsoft in 1999, he's been a world barbecue champion, a wildlife photographer, a chef, a contributor to SETI, and a volcano explorer.
Why you should listen
Since leaving his post as Microsoft's Chief Technology Officer in 1999 (with fortune in tow), Nathan Myhrvold has been a professional exemplar of the spirit of the "Renaissance Man," proudly following his interests wherever they've led. His dispersed passions have triggered an impressive list of accomplishments, including world barbecue championships, major archeological finds (several Tyrannosaurus rex skeletons), prize-winning wildlife photography, building a section of Babbage's Difference Engine #2, s, and a new and consuming interest in the sous-vide cooking technique.
Malcolm Gladwell's 2008 New Yorker profile of him revealed an impish but truly inspired character whose latest company, Intellectual Ventures -- which brainstorms and patents a wide array of inventions -- has been accused in some quarters of acting like a 'patent troll' but is described by Myhrvold as "a disruptive organization providing an efficient way for patent holders to get paid for the inventions they own, and... for technology companies to gain easy access to the invention rights they need." After funding big-vision projects such as the Allen Telescope Array, exploring active volcanoes and investigating penguin digestion, Myhrvold insists that his hobbies aren't as discursive as they seem. They do have a common denominator, after all: him.
Nathan Myhrvold | Speaker | TED.com