12 sustainable design ideas from nature | Janine Benyus

619,856 views ・ 2007-05-17

TED


Please double-click on the English subtitles below to play the video.

00:25
It is a thrill to be here at a conference
0
25000
4000
00:29
that's devoted to "Inspired by Nature" -- you can imagine.
1
29000
5000
00:34
And I'm also thrilled to be in the foreplay section.
2
34000
4000
00:38
Did you notice this section is foreplay?
3
38000
2000
00:40
Because I get to talk about one of my favorite critters,
4
40000
3000
00:43
which is the Western Grebe. You haven't lived
5
43000
3000
00:46
until you've seen these guys do their courtship dance.
6
46000
4000
00:50
I was on Bowman Lake in Glacier National Park,
7
50000
3000
00:53
which is a long, skinny lake with sort of mountains upside down in it,
8
53000
4000
00:57
and my partner and I have a rowing shell.
9
57000
2000
00:59
And so we were rowing, and one of these Western Grebes came along.
10
59000
6000
01:05
And what they do for their courtship dance is, they go together,
11
65000
5000
01:10
the two of them, the two mates, and they begin to run underwater.
12
70000
5000
01:15
They paddle faster, and faster, and faster, until they're going so fast
13
75000
4000
01:19
that they literally lift up out of the water,
14
79000
3000
01:22
and they're standing upright, sort of paddling the top of the water.
15
82000
4000
01:26
And one of these Grebes came along while we were rowing.
16
86000
5000
01:31
And so we're in a skull, and we're moving really, really quickly.
17
91000
4000
01:35
And this Grebe, I think, sort of, mistaked us for a prospect,
18
95000
7000
01:42
and started to run along the water next to us,
19
102000
4000
01:46
in a courtship dance -- for miles.
20
106000
5000
01:51
It would stop, and then start, and then stop, and then start.
21
111000
4000
01:55
Now that is foreplay.
22
115000
2000
01:57
(Laughter)
23
117000
3000
02:00
I came this close to changing species at that moment.
24
120000
9000
02:09
Obviously, life can teach us something
25
129000
4000
02:13
in the entertainment section. Life has a lot to teach us.
26
133000
4000
02:17
But what I'd like to talk about today
27
137000
3000
02:20
is what life might teach us in technology and in design.
28
140000
4000
02:24
What's happened since the book came out --
29
144000
2000
02:26
the book was mainly about research in biomimicry --
30
146000
3000
02:29
and what's happened since then is architects, designers, engineers --
31
149000
4000
02:33
people who make our world -- have started to call and say,
32
153000
3000
02:36
we want a biologist to sit at the design table
33
156000
4000
02:40
to help us, in real time, become inspired.
34
160000
3000
02:43
Or -- and this is the fun part for me -- we want you to take us out
35
163000
4000
02:47
into the natural world. We'll come with a design challenge
36
167000
2000
02:49
and we find the champion adapters in the natural world, who might inspire us.
37
169000
5000
02:54
So this is a picture from a Galapagos trip that we took
38
174000
4000
02:58
with some wastewater treatment engineers; they purify wastewater.
39
178000
4000
03:02
And some of them were very resistant, actually, to being there.
40
182000
3000
03:05
What they said to us at first was, you know, we already do biomimicry.
41
185000
5000
03:10
We use bacteria to clean our water. And we said,
42
190000
5000
03:15
well, that's not exactly being inspired by nature.
43
195000
4000
03:19
That's bioprocessing, you know; that's bio-assisted technology:
44
199000
4000
03:23
using an organism to do your wastewater treatment
45
203000
5000
03:28
is an old, old technology called "domestication."
46
208000
3000
03:31
This is learning something, learning an idea, from an organism and then applying it.
47
211000
7000
03:38
And so they still weren't getting it.
48
218000
3000
03:41
So we went for a walk on the beach and I said,
49
221000
2000
03:43
well, give me one of your big problems. Give me a design challenge,
50
223000
5000
03:48
sustainability speed bump, that's keeping you from being sustainable.
51
228000
3000
03:51
And they said scaling, which is the build-up of minerals inside of pipes.
52
231000
6000
03:57
And they said, you know what happens is, mineral --
53
237000
2000
03:59
just like at your house -- mineral builds up.
54
239000
2000
04:01
And then the aperture closes, and we have to flush the pipes with toxins,
55
241000
4000
04:05
or we have to dig them up.
56
245000
2000
04:07
So if we had some way to stop this scaling --
57
247000
3000
04:10
and so I picked up some shells on the beach. And I asked them,
58
250000
5000
04:15
what is scaling? What's inside your pipes?
59
255000
2000
04:17
And they said, calcium carbonate.
60
257000
3000
04:20
And I said, that's what this is; this is calcium carbonate.
61
260000
3000
04:23
And they didn't know that.
62
263000
3000
04:26
They didn't know that what a seashell is,
63
266000
2000
04:28
it's templated by proteins, and then ions from the seawater
64
268000
4000
04:32
crystallize in place to create a shell.
65
272000
3000
04:35
So the same sort of a process, without the proteins,
66
275000
4000
04:39
is happening on the inside of their pipes. They didn't know.
67
279000
3000
04:42
This is not for lack of information; it's a lack of integration.
68
282000
6000
04:48
You know, it's a silo, people in silos. They didn't know
69
288000
3000
04:51
that the same thing was happening. So one of them thought about it
70
291000
3000
04:54
and said, OK, well, if this is just crystallization
71
294000
4000
04:58
that happens automatically out of seawater -- self-assembly --
72
298000
5000
05:03
then why aren't shells infinite in size? What stops the scaling?
73
303000
5000
05:08
Why don't they just keep on going?
74
308000
2000
05:10
And I said, well, in the same way
75
310000
4000
05:14
that they exude a protein and it starts the crystallization --
76
314000
4000
05:18
and then they all sort of leaned in --
77
318000
4000
05:22
they let go of a protein that stops the crystallization.
78
322000
3000
05:25
It literally adheres to the growing face of the crystal.
79
325000
2000
05:27
And, in fact, there is a product called TPA
80
327000
4000
05:31
that's mimicked that protein -- that stop-protein --
81
331000
5000
05:36
and it's an environmentally friendly way to stop scaling in pipes.
82
336000
4000
05:40
That changed everything. From then on,
83
340000
4000
05:44
you could not get these engineers back in the boat.
84
344000
4000
05:48
The first day they would take a hike,
85
348000
3000
05:51
and it was, click, click, click, click. Five minutes later they were back in the boat.
86
351000
3000
05:54
We're done. You know, I've seen that island.
87
354000
4000
05:58
After this,
88
358000
2000
06:00
they were crawling all over. They would snorkel
89
360000
3000
06:03
for as long as we would let them snorkel.
90
363000
5000
06:08
What had happened was that they realized that there were organisms
91
368000
4000
06:12
out there that had already solved the problems
92
372000
4000
06:16
that they had spent their careers trying to solve.
93
376000
3000
06:19
Learning about the natural world is one thing;
94
379000
5000
06:24
learning from the natural world -- that's the switch.
95
384000
2000
06:26
That's the profound switch.
96
386000
3000
06:29
What they realized was that the answers to their questions are everywhere;
97
389000
4000
06:33
they just needed to change the lenses with which they saw the world.
98
393000
4000
06:37
3.8 billion years of field-testing.
99
397000
4000
06:41
10 to 30 -- Craig Venter will probably tell you;
100
401000
3000
06:44
I think there's a lot more than 30 million -- well-adapted solutions.
101
404000
4000
06:48
The important thing for me is that these are solutions solved in context.
102
408000
8000
06:56
And the context is the Earth --
103
416000
2000
06:58
the same context that we're trying to solve our problems in.
104
418000
5000
07:03
So it's the conscious emulation of life's genius.
105
423000
4000
07:07
It's not slavishly mimicking --
106
427000
2000
07:09
although Al is trying to get the hairdo going --
107
429000
3000
07:12
it's not a slavish mimicry; it's taking the design principles,
108
432000
4000
07:16
the genius of the natural world, and learning something from it.
109
436000
5000
07:21
Now, in a group with so many IT people, I do have to mention what
110
441000
4000
07:25
I'm not going to talk about, and that is that your field
111
445000
3000
07:28
is one that has learned an enormous amount from living things,
112
448000
4000
07:32
on the software side. So there's computers that protect themselves,
113
452000
4000
07:36
like an immune system, and we're learning from gene regulation
114
456000
3000
07:39
and biological development. And we're learning from neural nets,
115
459000
5000
07:44
genetic algorithms, evolutionary computing.
116
464000
3000
07:47
That's on the software side. But what's interesting to me
117
467000
5000
07:52
is that we haven't looked at this, as much. I mean, these machines
118
472000
5000
07:57
are really not very high tech in my estimation
119
477000
3000
08:00
in the sense that there's dozens and dozens of carcinogens
120
480000
5000
08:05
in the water in Silicon Valley.
121
485000
3000
08:08
So the hardware
122
488000
3000
08:11
is not at all up to snuff in terms of what life would call a success.
123
491000
5000
08:16
So what can we learn about making -- not just computers, but everything?
124
496000
5000
08:21
The plane you came in, cars, the seats that you're sitting on.
125
501000
4000
08:25
How do we redesign the world that we make, the human-made world?
126
505000
7000
08:32
More importantly, what should we ask in the next 10 years?
127
512000
4000
08:36
And there's a lot of cool technologies out there that life has.
128
516000
3000
08:39
What's the syllabus?
129
519000
2000
08:41
Three questions, for me, are key.
130
521000
4000
08:45
How does life make things?
131
525000
2000
08:47
This is the opposite; this is how we make things.
132
527000
3000
08:50
It's called heat, beat and treat --
133
530000
2000
08:52
that's what material scientists call it.
134
532000
2000
08:54
And it's carving things down from the top, with 96 percent waste left over
135
534000
5000
08:59
and only 4 percent product. You heat it up; you beat it with high pressures;
136
539000
5000
09:04
you use chemicals. OK. Heat, beat and treat.
137
544000
3000
09:07
Life can't afford to do that. How does life make things?
138
547000
4000
09:11
How does life make the most of things?
139
551000
3000
09:14
That's a geranium pollen.
140
554000
3000
09:17
And its shape is what gives it the function of being able
141
557000
5000
09:22
to tumble through air so easily. Look at that shape.
142
562000
4000
09:26
Life adds information to matter.
143
566000
5000
09:31
In other words: structure.
144
571000
2000
09:33
It gives it information. By adding information to matter,
145
573000
5000
09:38
it gives it a function that's different than without that structure.
146
578000
6000
09:44
And thirdly, how does life make things disappear into systems?
147
584000
5000
09:49
Because life doesn't really deal in things;
148
589000
5000
09:54
there are no things in the natural world divorced
149
594000
4000
09:58
from their systems.
150
598000
3000
10:01
Really quick syllabus.
151
601000
2000
10:03
As I'm reading more and more now, and following the story,
152
603000
6000
10:09
there are some amazing things coming up in the biological sciences.
153
609000
4000
10:13
And at the same time, I'm listening to a lot of businesses
154
613000
3000
10:16
and finding what their sort of grand challenges are.
155
616000
4000
10:20
The two groups are not talking to each other.
156
620000
2000
10:22
At all.
157
622000
3000
10:25
What in the world of biology might be helpful at this juncture,
158
625000
4000
10:29
to get us through this sort of evolutionary knothole that we're in?
159
629000
5000
10:34
I'm going to try to go through 12, really quickly.
160
634000
3000
10:37
One that's exciting to me is self-assembly.
161
637000
3000
10:40
Now, you've heard about this in terms of nanotechnology.
162
640000
4000
10:44
Back to that shell: the shell is a self-assembling material.
163
644000
4000
10:48
On the lower left there is a picture of mother of pearl
164
648000
4000
10:52
forming out of seawater. It's a layered structure that's mineral
165
652000
4000
10:56
and then polymer, and it makes it very, very tough.
166
656000
3000
10:59
It's twice as tough as our high-tech ceramics.
167
659000
3000
11:02
But what's really interesting: unlike our ceramics that are in kilns,
168
662000
4000
11:06
it happens in seawater. It happens near, in and near, the organism's body.
169
666000
5000
11:11
This is Sandia National Labs.
170
671000
2000
11:13
A guy named Jeff Brinker
171
673000
5000
11:18
has found a way to have a self-assembling coding process.
172
678000
4000
11:22
Imagine being able to make ceramics at room temperature
173
682000
4000
11:26
by simply dipping something into a liquid,
174
686000
4000
11:30
lifting it out of the liquid, and having evaporation
175
690000
3000
11:33
force the molecules in the liquid together,
176
693000
4000
11:37
so that they jigsaw together
177
697000
2000
11:39
in the same way as this crystallization works.
178
699000
4000
11:43
Imagine making all of our hard materials that way.
179
703000
3000
11:46
Imagine spraying the precursors to a PV cell, to a solar cell,
180
706000
7000
11:53
onto a roof, and having it self-assemble into a layered structure that harvests light.
181
713000
4000
11:57
Here's an interesting one for the IT world:
182
717000
4000
12:01
bio-silicon. This is a diatom, which is made of silicates.
183
721000
5000
12:06
And so silicon, which we make right now --
184
726000
2000
12:08
it's part of our carcinogenic problem in the manufacture of our chips --
185
728000
6000
12:14
this is a bio-mineralization process that's now being mimicked.
186
734000
4000
12:18
This is at UC Santa Barbara. Look at these diatoms.
187
738000
4000
12:22
This is from Ernst Haeckel's work.
188
742000
3000
12:25
Imagine being able to -- and, again, it's a templated process,
189
745000
5000
12:30
and it solidifies out of a liquid process -- imagine being able to have that
190
750000
4000
12:34
sort of structure coming out at room temperature.
191
754000
4000
12:38
Imagine being able to make perfect lenses.
192
758000
3000
12:41
On the left, this is a brittle star; it's covered with lenses
193
761000
5000
12:46
that the people at Lucent Technologies have found
194
766000
3000
12:49
have no distortion whatsoever.
195
769000
2000
12:51
It's one of the most distortion-free lenses we know of.
196
771000
3000
12:54
And there's many of them, all over its entire body.
197
774000
3000
12:57
What's interesting, again, is that it self-assembles.
198
777000
3000
13:00
A woman named Joanna Aizenberg, at Lucent,
199
780000
4000
13:04
is now learning to do this in a low-temperature process to create
200
784000
4000
13:08
these sort of lenses. She's also looking at fiber optics.
201
788000
4000
13:12
That's a sea sponge that has a fiber optic.
202
792000
3000
13:15
Down at the very base of it, there's fiber optics
203
795000
3000
13:18
that work better than ours, actually, to move light,
204
798000
3000
13:21
but you can tie them in a knot; they're incredibly flexible.
205
801000
6000
13:27
Here's another big idea: CO2 as a feedstock.
206
807000
4000
13:31
A guy named Geoff Coates, at Cornell, said to himself,
207
811000
3000
13:34
you know, plants do not see CO2 as the biggest poison of our time.
208
814000
4000
13:38
We see it that way. Plants are busy making long chains
209
818000
3000
13:41
of starches and glucose, right, out of CO2. He's found a way --
210
821000
6000
13:47
he's found a catalyst -- and he's found a way to take CO2
211
827000
3000
13:50
and make it into polycarbonates. Biodegradable plastics
212
830000
4000
13:54
out of CO2 -- how plant-like.
213
834000
2000
13:56
Solar transformations: the most exciting one.
214
836000
3000
13:59
There are people who are mimicking the energy-harvesting device
215
839000
4000
14:03
inside of purple bacterium, the people at ASU. Even more interesting,
216
843000
4000
14:07
lately, in the last couple of weeks, people have seen
217
847000
3000
14:10
that there's an enzyme called hydrogenase that's able to evolve
218
850000
5000
14:15
hydrogen from proton and electrons, and is able to take hydrogen up --
219
855000
4000
14:19
basically what's happening in a fuel cell, in the anode of a fuel cell
220
859000
5000
14:24
and in a reversible fuel cell.
221
864000
2000
14:26
In our fuel cells, we do it with platinum;
222
866000
3000
14:29
life does it with a very, very common iron.
223
869000
4000
14:33
And a team has now just been able to mimic
224
873000
4000
14:37
that hydrogen-juggling hydrogenase.
225
877000
5000
14:42
That's very exciting for fuel cells --
226
882000
2000
14:44
to be able to do that without platinum.
227
884000
3000
14:47
Power of shape: here's a whale. We've seen that the fins of this whale
228
887000
5000
14:52
have tubercles on them. And those little bumps
229
892000
3000
14:55
actually increase efficiency in, for instance,
230
895000
5000
15:00
the edge of an airplane -- increase efficiency by about 32 percent.
231
900000
5000
15:05
Which is an amazing fossil fuel savings,
232
905000
2000
15:07
if we were to just put that on the edge of a wing.
233
907000
5000
15:12
Color without pigments: this peacock is creating color with shape.
234
912000
4000
15:16
Light comes through, it bounces back off the layers;
235
916000
3000
15:19
it's called thin-film interference. Imagine being able
236
919000
3000
15:22
to self-assemble products with the last few layers
237
922000
3000
15:25
playing with light to create color.
238
925000
4000
15:29
Imagine being able to create a shape on the outside of a surface,
239
929000
5000
15:34
so that it's self-cleaning with just water. That's what a leaf does.
240
934000
5000
15:39
See that up-close picture?
241
939000
2000
15:41
That's a ball of water, and those are dirt particles.
242
941000
3000
15:44
And that's an up-close picture of a lotus leaf.
243
944000
3000
15:47
There's a company making a product called Lotusan, which mimics --
244
947000
5000
15:52
when the building facade paint dries, it mimics the bumps
245
952000
4000
15:56
in a self-cleaning leaf, and rainwater cleans the building.
246
956000
5000
16:01
Water is going to be our big, grand challenge:
247
961000
6000
16:07
quenching thirst.
248
967000
2000
16:09
Here are two organisms that pull water.
249
969000
3000
16:12
The one on the left is the Namibian beetle pulling water out of fog.
250
972000
4000
16:16
The one on the right is a pill bug -- pulls water out of air,
251
976000
3000
16:19
does not drink fresh water.
252
979000
3000
16:22
Pulling water out of Monterey fog and out of the sweaty air in Atlanta,
253
982000
7000
16:29
before it gets into a building, are key technologies.
254
989000
4000
16:33
Separation technologies are going to be extremely important.
255
993000
4000
16:37
What if we were to say, no more hard rock mining?
256
997000
4000
16:41
What if we were to separate out metals from waste streams,
257
1001000
6000
16:47
small amounts of metals in water? That's what microbes do;
258
1007000
4000
16:51
they chelate metals out of water.
259
1011000
2000
16:53
There's a company here in San Francisco called MR3
260
1013000
3000
16:56
that is embedding mimics of the microbes' molecules on filters
261
1016000
6000
17:02
to mine waste streams.
262
1022000
3000
17:05
Green chemistry is chemistry in water.
263
1025000
4000
17:09
We do chemistry in organic solvents.
264
1029000
2000
17:11
This is a picture of the spinnerets coming out of a spider
265
1031000
4000
17:15
and the silk being formed from a spider. Isn't that beautiful?
266
1035000
3000
17:18
Green chemistry is replacing our industrial chemistry with nature's recipe book.
267
1038000
8000
17:26
It's not easy, because life uses
268
1046000
5000
17:31
only a subset of the elements in the periodic table.
269
1051000
4000
17:35
And we use all of them, even the toxic ones.
270
1055000
4000
17:39
To figure out the elegant recipes that would take the small subset
271
1059000
5000
17:44
of the periodic table, and create miracle materials like that cell,
272
1064000
6000
17:50
is the task of green chemistry.
273
1070000
2000
17:52
Timed degradation: packaging that is good
274
1072000
4000
17:56
until you don't want it to be good anymore, and dissolves on cue.
275
1076000
4000
18:00
That's a mussel you can find in the waters out here,
276
1080000
3000
18:03
and the threads holding it to a rock are timed; at exactly two years,
277
1083000
4000
18:07
they begin to dissolve.
278
1087000
2000
18:09
Healing: this is a good one.
279
1089000
3000
18:12
That little guy over there is a tardigrade.
280
1092000
3000
18:15
There is a problem with vaccines around the world
281
1095000
6000
18:21
not getting to patients. And the reason is
282
1101000
3000
18:24
that the refrigeration somehow gets broken;
283
1104000
4000
18:28
what's called the "cold chain" gets broken.
284
1108000
2000
18:30
A guy named Bruce Rosner looked at the tardigrade --
285
1110000
3000
18:33
which dries out completely, and yet stays alive for months
286
1113000
6000
18:39
and months and months, and is able to regenerate itself.
287
1119000
3000
18:42
And he found a way to dry out vaccines --
288
1122000
3000
18:45
encase them in the same sort of sugar capsules
289
1125000
4000
18:49
as the tardigrade has within its cells --
290
1129000
3000
18:52
meaning that vaccines no longer need to be refrigerated.
291
1132000
5000
18:57
They can be put in a glove compartment, OK.
292
1137000
4000
19:01
Learning from organisms. This is a session about water --
293
1141000
5000
19:06
learning about organisms that can do without water,
294
1146000
3000
19:09
in order to create a vaccine that lasts and lasts and lasts without refrigeration.
295
1149000
7000
19:16
I'm not going to get to 12.
296
1156000
3000
19:19
But what I am going to do is tell you that the most important thing,
297
1159000
4000
19:23
besides all of these adaptations, is the fact that these organisms
298
1163000
5000
19:28
have figured out a way to do the amazing things they do
299
1168000
5000
19:33
while taking care of the place
300
1173000
3000
19:36
that's going to take care of their offspring.
301
1176000
5000
19:41
When they're involved in foreplay,
302
1181000
3000
19:44
they're thinking about something very, very important --
303
1184000
3000
19:47
and that's having their genetic material
304
1187000
4000
19:51
remain, 10,000 generations from now.
305
1191000
5000
19:56
And that means finding a way to do what they do
306
1196000
2000
19:58
without destroying the place that'll take care of their offspring.
307
1198000
4000
20:02
That's the biggest design challenge.
308
1202000
3000
20:05
Luckily, there are millions and millions of geniuses
309
1205000
6000
20:11
willing to gift us with their best ideas.
310
1211000
3000
20:14
Good luck having a conversation with them.
311
1214000
3000
20:17
Thank you.
312
1217000
1000
20:18
(Applause)
313
1218000
14000
20:32
Chris Anderson: Talk about foreplay, I -- we need to get to 12, but really quickly.
314
1232000
4000
20:36
Janine Benyus: Oh really?
315
1236000
1000
20:37
CA: Yeah. Just like, you know, like the 10-second version
316
1237000
3000
20:40
of 10, 11 and 12. Because we just -- your slides are so gorgeous,
317
1240000
3000
20:43
and the ideas are so big, I can't stand to let you go down
318
1243000
2000
20:45
without seeing 10, 11 and 12.
319
1245000
2000
20:47
JB: OK, put this -- OK, I'll just hold this thing. OK, great.
320
1247000
4000
20:51
OK, so that's the healing one.
321
1251000
3000
20:54
Sensing and responding: feedback is a huge thing.
322
1254000
3000
20:57
This is a locust. There can be 80 million of them in a square kilometer,
323
1257000
4000
21:01
and yet they don't collide with one another.
324
1261000
3000
21:04
And yet we have 3.6 million car collisions a year.
325
1264000
5000
21:09
(Laughter)
326
1269000
2000
21:11
Right. There's a person at Newcastle
327
1271000
4000
21:15
who has figured out that it's a very large neuron.
328
1275000
3000
21:18
And she's actually figuring out how to make
329
1278000
3000
21:21
a collision-avoidance circuitry
330
1281000
2000
21:23
based on this very large neuron in the locust.
331
1283000
4000
21:27
This is a huge and important one, number 11.
332
1287000
2000
21:29
And that's the growing fertility.
333
1289000
2000
21:31
That means, you know, net fertility farming.
334
1291000
4000
21:35
We should be growing fertility. And, oh yes -- we get food, too.
335
1295000
4000
21:39
Because we have to grow the capacity of this planet
336
1299000
5000
21:44
to create more and more opportunities for life.
337
1304000
3000
21:47
And really, that's what other organisms do as well.
338
1307000
2000
21:49
In ensemble, that's what whole ecosystems do:
339
1309000
3000
21:52
they create more and more opportunities for life.
340
1312000
3000
21:55
Our farming has done the opposite.
341
1315000
3000
21:58
So, farming based on how a prairie builds soil,
342
1318000
4000
22:02
ranching based on how a native ungulate herd
343
1322000
4000
22:06
actually increases the health of the range,
344
1326000
2000
22:08
even wastewater treatment based on how a marsh
345
1328000
5000
22:13
not only cleans the water,
346
1333000
2000
22:15
but creates incredibly sparkling productivity.
347
1335000
4000
22:19
This is the simple design brief. I mean, it looks simple
348
1339000
4000
22:23
because the system, over 3.8 billion years, has worked this out.
349
1343000
5000
22:28
That is, those organisms that have not been able to figure out
350
1348000
5000
22:33
how to enhance or sweeten their places,
351
1353000
4000
22:37
are not around to tell us about it.
352
1357000
3000
22:40
That's the twelfth one.
353
1360000
3000
22:43
Life -- and this is the secret trick; this is the magic trick --
354
1363000
4000
22:47
life creates conditions conducive to life.
355
1367000
4000
22:51
It builds soil; it cleans air; it cleans water;
356
1371000
4000
22:55
it mixes the cocktail of gases that you and I need to live.
357
1375000
3000
22:58
And it does that in the middle of having great foreplay
358
1378000
6000
23:04
and meeting their needs. So it's not mutually exclusive.
359
1384000
6000
23:10
We have to find a way to meet our needs,
360
1390000
3000
23:13
while making of this place an Eden.
361
1393000
6000
23:19
CA: Janine, thank you so much.
362
1399000
1000
23:20
(Applause)
363
1400000
1000
About this website

This site will introduce you to YouTube videos that are useful for learning English. You will see English lessons taught by top-notch teachers from around the world. Double-click on the English subtitles displayed on each video page to play the video from there. The subtitles scroll in sync with the video playback. If you have any comments or requests, please contact us using this contact form.

https://forms.gle/WvT1wiN1qDtmnspy7