TEDGlobal>Geneva
Caleb Harper: This computer will grow your food in the future
Caleb Harper: Denne computer vil i fremtiden dyrke din mad
Filmed:
Readability: 3.3
1,812,924 views
Hvad nu hvis vi kunne dyrke lækre, næringsrige fødevarer, indendørs overalt i verden? Caleb Harper, leder af CitiFARM ved MIT (Massachusetts Institute of Technology) Media Lab, vil ændre fødevaresystemet ved at forbinde planter med teknologi. Lær Harpers "Mad-computere" at kende, og få et indblik i, hvordan fremtidens landbrug kan se ud.
Caleb Harper - Principal Investigator and Director of the Open Agriculture Initiative
Caleb Harper leads a group of engineers, architects, urban planners, economists and plant scientists in the exploration and development of high performance urban agricultural systems. Full bio
Caleb Harper leads a group of engineers, architects, urban planners, economists and plant scientists in the exploration and development of high performance urban agricultural systems. Full bio
Double-click the English transcript below to play the video.
00:13
Food crisis.
0
1157
1264
Fødevarekrise.
00:14
It's in the news every day.
1
2445
1578
Det er i nyhederne hver dag.
00:16
But what is it?
2
4047
1322
Men hvad er det?
00:17
Some places in the world
it's too little food,
it's too little food,
3
5393
2899
Visse steder i verden
er der for lidt mad,
er der for lidt mad,
00:20
maybe too much.
4
8316
1190
- måske for meget.
00:21
Other places, GMO is saving the world.
5
9963
2329
Andre steder redder
gensplejset mad verdenen.
gensplejset mad verdenen.
00:24
Maybe GMO is the problem?
6
12821
1788
Måske er gensplejsning problemet?
00:27
Too much agricultural runoff
creating bad oceans, toxic oceans,
creating bad oceans, toxic oceans,
7
15355
3462
For store udslip fra landbruget
ødelægger havet,
ødelægger havet,
00:30
attenuation of nutrition.
8
18841
1637
begrænsning af gødning.
00:32
They go on and on.
9
20836
1666
De bliver ved.
00:34
And I find the current climate
of this discussion
of this discussion
10
22919
3225
-Og jeg synes det aktuelle
klima i denne diskussion
klima i denne diskussion
00:38
incredibly disempowering.
11
26168
2299
er utroligt afmagtende.
00:41
So how do we bring that
to something that we understand?
to something that we understand?
12
29110
3441
Så hvordan ændrer vi dette
til noget vi kan forstå?
til noget vi kan forstå?
00:45
How is this apple food crisis?
13
33508
2230
Hvordan kan dette æble
være en fødevarekrise?
være en fødevarekrise?
00:48
You've all eaten an apple
in the last week, I'm sure.
in the last week, I'm sure.
14
36194
2615
I har sikkert alle spist
et æble i ugens løb.
et æble i ugens løb.
00:51
How old do you think it was
from when it was picked?
from when it was picked?
15
39468
2753
Hvor lang tid tror I, der er
gået fra det blev plukket?
gået fra det blev plukket?
00:55
Two weeks?
16
43264
1184
2 uger?
00:56
Two months?
17
44472
1154
2 måneder?
00:58
Eleven months --
18
46887
1153
11 måneder -
01:00
the average age of an apple
in a grocery store in the United States.
in a grocery store in the United States.
19
48064
3355
- gennemsnittet for et æble
i et supermarked i USA.
i et supermarked i USA.
01:03
And I don't expect it
to be much different in Europe
to be much different in Europe
20
51443
2499
Og jeg tror ikke det er
meget anderledes i Europa
meget anderledes i Europa
01:05
or anywhere else in the world.
21
53966
1480
eller andre steder i Verden.
01:07
We pick them,
22
55470
1164
Vi plukker dem,
01:08
we put them in cold storage,
23
56658
2077
vi opbevarer dem i en kold lagerhal
01:10
we gas the cold storage --
24
58759
1268
vi gasser lagerhallen --
01:12
there's actually documented proof
25
60051
1897
Det er faktisk sket at,
01:13
of workers trying to go
into these environments
into these environments
26
61972
2243
ansatte har forsøgt at
gå ind i disse miljøer,
gå ind i disse miljøer,
01:16
to retrieve an apple,
27
64239
1594
for at få fat i et æble,
01:17
and dying,
28
65857
1168
og er omkommet.
01:19
because the atmosphere
29
67606
1155
Fordi den atmosfære
01:20
that they slow down the process
of the apple with is also toxic to humans.
of the apple with is also toxic to humans.
30
68785
3965
til at nedsætte ældningen af æblet,
også er giftig for mennesker.
også er giftig for mennesker.
01:25
How is it that none of you knew this?
31
73152
1899
Hvorfor vidste I det ikke?
01:27
Why didn't I know this?
32
75075
1504
Hvorfor vidste JEG det ikke?
01:29
Ninety percent of the quality
of that apple --
of that apple --
33
77086
2208
90% af det æbles kvalitet,
01:31
all of the antioxidants -- are gone
by the time we get it.
by the time we get it.
34
79318
2960
alle antioxidanterne
- er væk på det tidspunkt vi får æblet.
- er væk på det tidspunkt vi får æblet.
01:34
It's basically a little ball of sugar.
35
82719
2183
Det er bare en lille sukkerbold.
01:38
How did we get so information poor
36
86126
2782
Hvordan blev vi så fattige på information
01:40
and how can we do better?
37
88932
1458
og hvordan bliver det bedre?
01:43
I think what's missing is a platform.
38
91347
2856
Jeg tror der mangler en platform.
01:46
I know platforms -- I know computers,
39
94630
1809
Jeg kender platforme.
- computere,
- computere,
01:48
they put me on the Internet
when I was young.
when I was young.
40
96463
2119
de smed mig på internettet
da jeg var lille.
da jeg var lille.
01:50
I did very weird things --
41
98606
1246
Jeg lavede bizarre ting
01:51
(Laughter)
42
99876
1001
(Latter)
01:52
on this platform.
43
100901
1151
på denne platform.
01:54
But I met people,
and I could express myself.
and I could express myself.
44
102076
2093
Men jeg træf mennesker,
og kunne ytre mig.
og kunne ytre mig.
01:56
How do you express yourself in food?
45
104193
2014
Hvordan ytrer man sig med mad?
01:58
If we had a platform,
46
106556
1540
Hvis vi havde en platform,
02:00
we might feel empowered
to question: What if?
to question: What if?
47
108120
3147
vi kunne fristes til at spørge:
Hvad nu, hvis?
Hvad nu, hvis?
02:04
For me, I questioned:
48
112005
1151
Jeg spurgte:
02:05
What if climate was democratic?
49
113180
2746
Hvad nu hvis klimaet var demokratisk?
02:09
So, this is a map of climate in the world.
50
117830
2007
Så her er et klimaverdenskort.
02:11
The most productive areas in green,
the least productive in red.
the least productive in red.
51
119861
3340
De mest produktive områder er grønne,
mindst produktive er røde.
mindst produktive er røde.
02:15
They shift and they change,
52
123606
1308
De flytter sig og skifter,
02:16
and Californian farmers
now become Mexican farmers.
now become Mexican farmers.
53
124938
2671
og californiske landmænd
er nu mexicanske landmænd.
er nu mexicanske landmænd.
02:19
China picks up land in Brazil
to grow better food,
to grow better food,
54
127934
2897
Kina tager jord i Brasilien
for at dyrke bedre fødevarer
for at dyrke bedre fødevarer
02:22
and we're a slave to climate.
55
130855
2026
og vi er slaver til klimaet.
02:26
What if each country had
its own productive climate?
its own productive climate?
56
134056
3057
Hvad nu hvis alle lande havde
deres eget produktive klima?
deres eget produktive klima?
02:29
What would that change about how we live?
57
137612
2120
Hvordan ville det ændre vores hverdag?
02:32
What would that change
about quality of life and nutrition?
about quality of life and nutrition?
58
140233
2984
Hvordan ville det ændre
livskvalitet og ernæring?
livskvalitet og ernæring?
02:36
The last generation's problem
was, we need more food
was, we need more food
59
144257
3295
Den sidste generations problem var,
vi har brug for mere mad
vi har brug for mere mad
02:39
and we need it cheap.
60
147576
1181
- billigt.
02:41
Welcome to your global farm.
61
149194
2120
Velkommen til din globale bondegård.
02:43
We built a huge analog farm.
62
151338
2460
Vi bygger et stort analogt landbrug.
02:45
All these traces --
63
153822
1430
Alle disse streger --
02:47
these are cars, planes,
trains and automobiles.
trains and automobiles.
64
155276
2900
er fly, tog og biler.
02:50
It's a miracle that we feed
seven billion people
seven billion people
65
158597
3185
Det er mirakel, at vi brødføder
7 mia. mennesker
7 mia. mennesker
02:53
with just a few of us involved
in the production of food.
in the production of food.
66
161806
3045
med kun nogle få af os involveret
i produktionen af fødevarer.
i produktionen af fødevarer.
02:57
What if ...
67
165709
1168
Hvad nu hvis...
02:59
we built a digital farm?
68
167758
1676
vi byggede en digital bondegård?
03:01
A digital world farm.
69
169458
1163
En digital verdensgård.
03:02
What if you could take this apple,
70
170645
2809
Hvad nu hvis vi kunne tage dette æble,
03:06
digitize it somehow,
71
174052
1710
digitalisere det om muligt,
03:07
send it through particles in the air
72
175786
2468
sende det gennem luften
03:10
and reconstitute it on the other side?
73
178278
2410
og genskabe det i den anden ende?
03:13
What if?
74
181337
1160
Hvad nu hvis?
03:15
Going through some of these quotes,
75
183338
1675
Ved at læse nogle af disse citater,
03:17
you know, they inspire me to do what I do.
76
185037
2042
bliver jeg inspireret.
03:19
First one:
77
187103
1155
Den første:
03:20
["Japanese farming has no youth,
no water, no land and no future."]
no water, no land and no future."]
78
188282
4110
"Japansk landbrug har ingen ungdom,
intet vand, intet land og ingen fremtid."
intet vand, intet land og ingen fremtid."
03:24
That's what I landed to the day
that I went to Minamisanriku,
that I went to Minamisanriku,
79
192767
3738
Det var det jeg mødte,
da jeg var i Minamisanriku,
da jeg var i Minamisanriku,
03:28
one stop south of Fukushima,
80
196529
1573
ikke langt fra Fukushima,
03:30
after the disaster.
81
198126
1702
efter katastrofen.
03:31
The kids have headed to Sendai and Tokyo,
82
199852
2551
Børnene var taget til Sendai og Tokyo,
03:34
the land is contaminated,
83
202427
1375
jorden er forurenet,
03:35
they already import 70 percent
of their own food.
of their own food.
84
203826
2321
de importerer i forvejen
70% af deres fødevarer.
70% af deres fødevarer.
03:38
But it's not unique to Japan.
85
206171
2140
Men det gælder ikke kun Japan.
03:40
Two percent of the American population
is involved in farming.
is involved in farming.
86
208749
3397
2% af den amerikanske befolkning
er involveret i landbrug.
er involveret i landbrug.
03:45
What good answer comes
from two percent of any population?
from two percent of any population?
87
213091
3542
Hvilke gode svar får man fra 2%
af en hvilken som helst befolkning?
af en hvilken som helst befolkning?
03:49
As we go around the world,
88
217725
1585
Vi tager videre rundt i verden,
03:51
50 percent of the African
population is under 18.
population is under 18.
89
219334
3611
50% af den afrikanske befolkning
er under 18 år.
er under 18 år.
03:55
Eighty percent don't want to be farmers.
90
223905
2816
80% af disse vil ikke være landmænd.
03:58
Farming is hard.
91
226745
1454
At være landmand er hårdt.
04:00
The life of a small-shareholder
farmer is miserable.
farmer is miserable.
92
228651
3831
Livet som lille landmand er utåleligt.
04:05
They go into the city.
93
233381
1292
De tager ind til byen.
04:06
In India:
94
234697
1160
I Indien:
04:08
farmers' families not being able
to have basic access to utilities,
to have basic access to utilities,
95
236523
3190
landbrugsfamilierne har ikke
adgang til basale redskaber,
adgang til basale redskaber,
04:11
more farmer suicides this year
and the previous 10 before that.
and the previous 10 before that.
96
239737
3799
flere landmænd begår selvmord i år
og gjorde det sidste årti.
og gjorde det sidste årti.
04:15
It's uncomfortable to talk about.
97
243560
1635
Det er ubehageligt at tale om.
04:17
Where are they going?
98
245219
1168
Hvor går de hen?
04:18
Into the city.
99
246411
1208
Ind til byen.
04:20
No young people, and everyone's headed in.
100
248719
2168
Ingen unge mennesker,
og alle er på vej væk.
og alle er på vej væk.
04:22
So how do we build this platform
that inspires the youth?
that inspires the youth?
101
250911
3971
Hvordan bygger vi denne platform,
som kan inspirere de unge?
som kan inspirere de unge?
04:27
Welcome to the new tractor.
102
255687
1632
Velkommen til den nye traktor.
04:29
This is my combine.
103
257754
1827
Her er min mejetærsker.
04:32
A number of years ago now,
104
260224
1299
For er par år siden,
04:33
I went to Bed Bath and Beyond
and Home Depot
and Home Depot
105
261547
2162
Var jeg en tur i Jysk og Silvan
04:35
and I started hacking.
106
263733
1151
og begyndte at hacke.
04:36
And I built silly things
107
264908
1215
Jeg byggede skøre ting
04:38
and I made plants dance
108
266147
1151
fik planter til at danse
04:39
and I attached them to my computer
109
267322
1851
og jeg forbandt dem til min computer
04:41
and I killed them all --
110
269197
1290
og jeg slog dem alle ihjel
04:42
a lot.
111
270966
1173
- mange gange.
04:44
(Laughter)
112
272163
1000
(Latter)
04:45
I eventually got them to survive.
113
273773
1610
Jeg fik dem dog til at overleve.
04:47
And I created one of the most
intimate relationships
intimate relationships
114
275407
2466
Og jeg fik en af de mest intime forhold
04:49
I've ever had in my life,
115
277897
1215
Jeg nogensinde har haft,
04:51
because I was learning
the language of plants.
the language of plants.
116
279136
3105
fordi jeg lærte planternes sprog.
04:55
I wanted to make it bigger.
117
283008
1318
Jeg ville gøre det større.
04:56
They said, "Knock yourself out, kid!
118
284350
1763
De sagde: "Slå dig løs, knægt!"
04:58
Here's an old electronics room
that nobody wants.
that nobody wants.
119
286137
2901
Her er et gammelt elektronik-
værksted, som ingen vil have.
værksted, som ingen vil have.
05:01
What can you do?"
120
289062
1302
Hvad kan man gøre?
05:03
With my team, we built a farm
inside of the media lab,
inside of the media lab,
121
291031
2627
Vi opbyggede en gård inde
på IT-universitetet MIT,
på IT-universitetet MIT,
05:05
a place historically known
not for anything about biology
not for anything about biology
122
293682
3934
ikke just et sted man
forbinder med biologi,
forbinder med biologi,
05:09
but everything about digital life.
123
297640
2549
men alt om det digitale liv.
05:12
Inside of these 60 square feet,
124
300213
2642
I rummet på under 6 kvadratmeter,
05:14
we produced enough food to feed
about 300 people once a month --
about 300 people once a month --
125
302879
3126
producerede vi mad til omkring 300
personer én gang om måneden.
personer én gang om måneden.
05:18
not a lot of food.
126
306029
1152
Ikke meget mad,
05:19
And there's a lot of interesting
technology in there.
technology in there.
127
307205
2515
og der er en del interessant
teknologi derinde.
teknologi derinde.
05:21
But the most interesting thing?
128
309744
1655
Men det mest interessante?
05:24
Beautiful, white roots,
129
312226
1705
Smukke, hvide rødder,
05:26
deep, green colors
130
314478
2421
dybe, grønne farver
05:29
and a monthly harvest.
131
317629
1532
og en månedlig høst.
05:31
Is this a new cafeteria?
132
319668
2561
Er dette et nyt cafeteria?
05:34
Is this a new retail experience?
133
322787
3321
Er det en ny indkøbsoplevelse?
05:38
Is this a new grocery store?
134
326132
1574
Er det et nyt supermarked?
05:39
I can tell you one thing for sure:
135
327730
1881
Jeg kan garantere Jer én ting:
05:42
this is the first time
136
330127
1150
Dette var første gang
05:43
anybody in the media lab
ripped the roots off of anything.
ripped the roots off of anything.
137
331301
2881
nogle på IT-universitetet
rev rødderne af noget.
rev rødderne af noget.
05:46
(Laughter)
138
334613
1417
(Latter)
05:48
We get our salad in bags;
139
336528
1705
Vi får vores salat i poser,
05:50
there's nothing wrong with that.
140
338257
1736
der er intet galt med det.
05:52
But what happens
141
340400
1521
Men hvad sker der
05:53
when you have an image-based
processing expert,
processing expert,
142
341945
3111
når man har en billedbehandlingsekspert,
05:57
a data scientist,
143
345080
1415
en datamatiker,
05:58
a roboticist,
144
346996
1396
en robottekniker,
06:00
ripping roots off and thinking,
145
348933
1526
som river rødder af og tænker:
06:02
"Huh. I know something about --
146
350483
1880
"Hmm, jeg ved noget om -
06:04
I could make this happen, I want to try."
147
352387
2193
Jeg kunne gøre det, jeg vil prøve."
06:07
In that process we would
bring the plants out
bring the plants out
148
355364
2275
I denne proces ville vi tage planterne ud
06:09
and we would take some back to the lab,
149
357663
1909
og vi tog nogle tilbage til folkene,
06:11
because if you grew it,
you don't throw it away;
you don't throw it away;
150
359596
2256
da det du selv har dyrket,
smider du ikke væk.
smider du ikke væk.
06:13
it's kind of precious to you.
151
361876
1397
Det bliver kostbart for dig.
06:15
I have this weird tongue now,
152
363297
1397
Jeg har en mærkelig tunge nu,
06:16
because I'm afraid to let anybody eat
anything until I've eaten it first,
anything until I've eaten it first,
153
364718
3444
fordi jeg tør ikke lade andre spise noget,
inden jeg selv har smagt det,
inden jeg selv har smagt det,
06:20
because I want it to be good.
154
368186
1389
det skal være perfekt.
06:21
So I eat lettuce every day
155
369599
1246
Jeg spiser salat hver dag
06:22
and I can tell the pH
of a lettuce within .1.
of a lettuce within .1.
156
370869
2457
og kan smage pH-værdien
med 1 decimals præcision.
med 1 decimals præcision.
06:25
(Laughter)
157
373350
1005
(Latter)
06:26
I'm like, "No, that's 6.1 -- no,
no, you can't eat it today."
no, you can't eat it today."
158
374379
3171
Jeg siger: "Nej den er 6,1
så du kan ikke spise den i dag."
så du kan ikke spise den i dag."
06:29
(Applause)
159
377574
3145
(Klapsalver)
06:34
This lettuce that day was hyper sweet.
160
382042
2588
Denne salat var meget sød i smagen.
06:37
It was hyper sweet
because the plant had been stressed
because the plant had been stressed
161
385362
2548
Den var sød
fordi planten var blevet stresset
fordi planten var blevet stresset
06:39
and it created a chemical reaction
in the plant to protect itself:
in the plant to protect itself:
162
387934
3129
så den lavede en kemisk reaktion
for at beskytte sig selv:
for at beskytte sig selv:
06:43
"I'm not going to die!"
163
391087
1164
"Jeg vil ikke dø!"
06:44
And the plants not-going-to-die,
taste sweet to me.
taste sweet to me.
164
392275
3129
Og "Jeg-vil-ikke-dø"-planterne
smagte sødt.
smagte sødt.
06:48
Technologists falling backwards
into plant physiology.
into plant physiology.
165
396683
2862
Tekniknørderne blev
grebet af plantebiologi.
grebet af plantebiologi.
06:51
So we thought other people
needed to be able to try this.
needed to be able to try this.
166
399569
2705
Så vi tænkte, at andre
skulle have samme mulighed.
skulle have samme mulighed.
06:54
We want to see what people can create,
167
402298
1857
Vi ville se hvad folk kan skabe,
06:56
so we conceived of a lab
that could be shipped anywhere.
that could be shipped anywhere.
168
404179
2689
så vi forestillede os et væksthus
man kunne sende afsted.
man kunne sende afsted.
06:59
And then we built it.
169
407359
1232
Så vi byggede det.
07:02
So on the facade
of the media lab is my lab,
of the media lab is my lab,
170
410095
2623
Så på facaden af fakultetet
er mit væksthus,
er mit væksthus,
07:04
that has about 30 points
of sensing per plant.
of sensing per plant.
171
412742
2693
som har ca. 30 målepunkter pr. plante.
07:08
If you know about the genome or genetics,
172
416035
3169
Hvis du kender til genomer eller genetik,
07:11
this is the phenome, right?
173
419228
2503
her er phenomet, ikke?
07:13
The phenomena.
174
421755
1242
Fænomenet.
07:15
When you say, "I like
the strawberries from Mexico,"
the strawberries from Mexico,"
175
423021
2480
Når du siger, "Jeg foretrækker
jordbær fra Italien"
jordbær fra Italien"
07:17
you really like the strawberries
from the climate
from the climate
176
425525
2389
Mener du i virkeligheden,
vil have et jordbær
vil have et jordbær
07:19
that produced the expression
that you like.
that you like.
177
427938
2088
fra det klima, som producerede den smag.
07:22
So if you're coding climate --
178
430050
2189
Så hvis man indstiller klimaet -
07:24
this much CO2, this much O2 creates
a recipe -- you're coding
a recipe -- you're coding
179
432263
3301
så meget CO2, så meget O2,
så har vi en opskrift.
så har vi en opskrift.
07:27
the expression of that plant,
the nutrition of that plant,
the nutrition of that plant,
180
435588
3275
Du programmerer plantens egenskaber:
plantens næringsindhold,
plantens næringsindhold,
07:30
the size of that plant, the shape,
the color, the texture.
the color, the texture.
181
438887
3258
størrelse, form
farve, overflade.
farve, overflade.
07:35
We need data,
182
443683
1185
Vi har brug for data.
07:36
so we put a bunch of sensors in there
183
444892
1781
Så vi monterer en stak sensorer
07:38
to tell us what's going on.
184
446697
1303
til at observere planten.
07:40
If you think of your houseplants,
185
448024
1582
Tænk på dine stueplanter,
07:41
and you look at your houseplant
186
449630
1495
og du ser på din stueplante
07:43
and you're super sad, because you're like,
187
451149
2012
og du er trist, fordi du tænker:
07:45
"Why are you dying? Won't you talk to me?"
188
453185
2016
"Hvorfor dør du?
Vil du ikke tale?"
Vil du ikke tale?"
07:47
(Laughter)
189
455225
1000
(Latter)
07:48
Farmers develop the most beautiful
fortune-telling eyes
fortune-telling eyes
190
456659
2822
Landmænd udvikler de mest
utrolige øjne der kan spå
utrolige øjne der kan spå
07:51
by the time they're in their
late 60s and 70s.
late 60s and 70s.
191
459505
2171
når de er 60-70 år gamle.
07:53
They can tell you when you
see that plant dying
see that plant dying
192
461700
2193
De kan fortælle når
en plante er ved at dø:
en plante er ved at dø:
07:55
that it's a nitrogen deficiency,
a calcium deficiency
a calcium deficiency
193
463917
2539
"Det er kvælstofsmangel, kalkmangel,
07:58
or it needs more humidity.
194
466480
1404
eller luftfugtighed."
07:59
Those beautiful eyes
are not being passed down.
are not being passed down.
195
467908
2315
Disse fantastiske øjne
bliver ikke videregivet.
bliver ikke videregivet.
08:03
These are eyes in the cloud of a farmer.
196
471199
2318
Her er en landmands øjne online.
08:06
We trend those data points over time.
197
474080
2215
Vi laver kurver over
disse målinger over tid.
disse målinger over tid.
08:08
We correlate those data points
to individual plants.
to individual plants.
198
476805
2475
Vi sammenholder målinger
for hver type plante
for hver type plante
08:11
These are all the broccoli
in my lab that day, by IP address.
in my lab that day, by IP address.
199
479304
4050
Her er alle broccoliene i vores
laboratorium med deres IP-adresse.
laboratorium med deres IP-adresse.
08:15
(Laughter)
200
483378
1138
(latter)
08:16
We have IP-addressable broccoli.
201
484540
2721
Vi har IP-adressérbare brocollier.
08:20
(Applause)
202
488176
4514
(Klapsalver)
08:24
So if that's not weird enough,
203
492714
2675
Så hvis det ikke er skørt nok,
08:27
you can click one
and you get a plant profile.
and you get a plant profile.
204
495413
2489
du kan klikke på én,
og du får plantens profil
og du får plantens profil
08:29
And what this tells you
is downloadable progress on that plant,
is downloadable progress on that plant,
205
497926
3016
Her får du en status for planten,
som du kan downloade.
som du kan downloade.
08:32
but not like you'd think,
206
500966
1206
Men måske tænker du,
08:34
it's not just when it's ready.
207
502196
1445
Ikke blot når den er klar.
08:35
When does it achieve
the nutrition that I need?
the nutrition that I need?
208
503665
2276
Hvornår har den optaget
den næring jeg ønsker?
den næring jeg ønsker?
08:37
When does it achieve
the taste that I desire?
the taste that I desire?
209
505965
2780
Hvornår har den
den smag jeg vil have?
den smag jeg vil have?
08:41
Is it getting too much water?
210
509284
1676
Får den for meget vand?
08:42
Is it getting too much sun?
211
510984
1912
For meget sol?
08:44
Alerts.
212
512920
1164
Advarsler.
08:46
It can talk to me, it's conversant,
213
514108
1834
Den kan snakke til mig,
08:47
we have a language.
214
515966
1364
vi har et sprog.
08:50
(Laughter)
215
518043
1788
(Latter)
08:51
(Applause)
216
519855
4636
(Klapsalve)
08:56
I think of that as the first user
on the plant Facebook, right?
on the plant Facebook, right?
217
524515
4779
Jeg forestiller mig dette som den
første bruger på Plante-Facebook
første bruger på Plante-Facebook
09:01
That's a plant profile
218
529318
1206
En Plante-profil,
09:02
and that plant will start making friends.
219
530548
1993
og denne plante vil få venner.
09:04
(Laughter)
220
532565
1007
(Latter)
09:05
And I mean it -- it will make
friends with other plants
friends with other plants
221
533596
2619
Jeg mener det - den vil blive
venner med andre planter,
venner med andre planter,
09:08
that use less nitrogen, more phosphorus,
222
536239
2127
som bruger mindre kvælstof, mere fosfor,
09:10
less potassium.
223
538390
1198
mindre kalium.
09:11
We're going to learn about a complexity
224
539910
1981
Vi kommer til at lære om en kompleksitet,
09:13
that we can only guess at now.
225
541915
1617
som vi kun kan gætte om nu.
09:16
And they may not friend us back --
I don't know, they might friend us back,
I don't know, they might friend us back,
226
544048
3580
Og det er ikke sikkert de vil være
venner med os. Måske vil de være venner
venner med os. Måske vil de være venner
09:19
it depends on how we act.
227
547652
1199
hvis vi opfører os pænt.
09:20
So this is my lab now.
228
548875
1958
Her er mit væksthus nu.
09:23
It's a little bit more systematized,
229
551294
1738
Det er lidt mere systematiseret,
09:25
my background is designing data centers
in hospitals of all things,
in hospitals of all things,
230
553056
3231
Jeg plejer at designe datacentre
for hospitaler,
for hospitaler,
09:28
so I know a little bit about creating
a controlled environment.
a controlled environment.
231
556311
2968
så jeg ved lidt om hvordan
man skaber et kontrolleret miljø.
man skaber et kontrolleret miljø.
09:31
And so --
232
559303
1150
Så -
09:32
inside of this environment,
233
560754
1643
inde i dette miljø,
09:34
we're experimenting
with all kinds of things.
with all kinds of things.
234
562421
2373
eksperimenterer vi
med alle mulige ting.
med alle mulige ting.
09:36
This process, aeroponics, was developed
by NASA for Mir Space Station
by NASA for Mir Space Station
235
564818
4208
Denne proces, aeroponik, blev udviklet
af NASA til rumstationen MIR,
af NASA til rumstationen MIR,
09:41
for reducing the amount of water
they send into space.
they send into space.
236
569050
2548
for at reducere vandmængden
der sendes ud i rummet.
der sendes ud i rummet.
09:43
What it really does is give the plant
exactly what it wants:
exactly what it wants:
237
571622
2859
Det handler om at give planten
præcis hvad den vil have:
præcis hvad den vil have:
09:46
water, minerals and oxygen.
238
574505
1635
vand, mineraler og ilt.
09:48
Roots are not that complicated,
239
576164
1492
Rødder er ikke komplicerede,
09:49
so when you give them that,
you get this amazing expression.
you get this amazing expression.
240
577680
3912
så hvis du giver dem det,
får du denne fantastiske udstråling.
får du denne fantastiske udstråling.
09:54
It's like the plant has two hearts.
241
582472
3073
Det er som om planten har 2 hjerter.
09:57
And because it has two hearts,
242
585569
1665
Og fordi den har 2 hjerter,
09:59
it grows four or five times faster.
243
587958
2069
gror den 4 eller 5 gange hurtigere.
10:02
It's a perfect world.
244
590657
1154
Det er en perfekt verden
10:03
We've gone a long way into technology
and seed for an adverse world
and seed for an adverse world
245
591835
3213
Vi er gået langt med teknologi og
frø til en ugunstig verden
frø til en ugunstig verden
10:07
and we're going to continue to do that,
246
595072
1865
og vi bliver ved med at gøre dette,
10:08
but we're going to have a new tool, too,
247
596961
1913
men vi får brug for et værktøj mere,
10:10
which is perfect world.
248
598898
1683
som er en perfekt verden.
10:12
So we've grown all kinds of things.
249
600605
1679
Så vi har dyrket alle mulige ting.
10:14
These tomatoes hadn't been
in commercial production for 150 years.
in commercial production for 150 years.
250
602308
3808
Disse tomater er ikke blevet
dyrket kommercielt i 150 år.
dyrket kommercielt i 150 år.
10:18
Do you know that we have
rare and ancient seed banks?
rare and ancient seed banks?
251
606515
3274
Vidste du, at vi har banker
med gamle og sjældne frøsorter?
med gamle og sjældne frøsorter?
10:22
Banks of seed.
252
610312
1742
frøbanker.
10:24
It's amazing.
253
612078
1157
Det er fantastisk.
10:25
They have germplasm alive
and things that you've never eaten.
and things that you've never eaten.
254
613259
2882
De har levende kimplasma
og ting du aldrig har spist.
og ting du aldrig har spist.
10:28
I am the only person in this room
that's eaten that kind of tomato.
that's eaten that kind of tomato.
255
616165
3281
Jeg er den eneste person her i rummet,
som har spist denne tomatsort.
som har spist denne tomatsort.
10:31
Problem is it was a sauce tomato
and we don't know how to cook,
and we don't know how to cook,
256
619837
3001
Det var dog en madlavningstomat,
og da vi ikke kan lave mad,
og da vi ikke kan lave mad,
10:34
so we ate a sauce tomato,
which is not that great.
which is not that great.
257
622862
2356
spiste vi en tomat,
som ikke var ret interessant.
som ikke var ret interessant.
10:37
But we've done things with protein --
we've grown all kinds of things.
we've grown all kinds of things.
258
625242
3316
Men vi har gjort ing med proteiner,
vi har dyrket alle mulige ting.
vi har dyrket alle mulige ting.
10:40
We've grown humans --
259
628582
1173
Vi har dyrket mennesker
10:41
(Laughter)
260
629779
1642
(Latter)
10:44
Well maybe you could, but we didn't.
261
632103
1732
-måske kunne vi, men nej.
10:45
But what we realized is,
262
633859
1596
Men vi fandt ud af,
10:47
the tool was too big,
it was too expensive.
it was too expensive.
263
635479
2075
udstyret var for stort
og alt for dyrt.
og alt for dyrt.
10:49
I was starting to put them
around the world
around the world
264
637578
2004
Jeg var startet på at distribuere dem
10:51
and they were about 100,000 dollars.
265
639606
1817
rundt til mere end en ½ mio. kr.
10:53
Finding somebody with 100 grand
in their back pocket isn't easy,
in their back pocket isn't easy,
266
641447
3009
At finde typer med 500.000 kr.
til rådighed er ikke let,
til rådighed er ikke let,
10:56
so we wanted to make a small one.
267
644480
1580
så vi ville lave en mindre model.
10:58
This project was actually
one of my student's --
one of my student's --
268
646084
2297
Det var faktisk én af
mine studerendes projekt:
mine studerendes projekt:
11:00
mechanical engineering
undergraduate, Camille.
undergraduate, Camille.
269
648405
2856
Maskiningeniørstuderende, Camille.
11:03
So Camille and I and my team,
270
651851
1532
Så Camille, mit hold og jeg,
11:05
we iterated all summer,
271
653407
1858
forsøgte hele sommeren,
11:07
how to make it cheaper,
how to make it work better,
how to make it work better,
272
655289
2420
hvordan kunne vi:
lave udstyret billigere, bedre,
lave udstyret billigere, bedre,
11:09
how to make it so other
people can make it.
people can make it.
273
657733
2024
så andre selv kunne bygge det.
11:11
Then we dropped them off in schools,
seventh through eleventh grade.
seventh through eleventh grade.
274
659781
3303
Så uddelte vi dem i skoler
fra 7. klasse til gymnasieklasser.
fra 7. klasse til gymnasieklasser.
11:15
And if you want to be humbled,
try to teach a kid something.
try to teach a kid something.
275
663108
2999
Hvis du vil ydmyges,
så forsøg at lære en skoleelev noget.
så forsøg at lære en skoleelev noget.
11:18
So I went into this school and I said,
276
666131
1849
På en skole sagde jeg:
11:20
"Set it to 65 percent humidity."
277
668004
1893
"Indstil til en luftfugtighed på 65%."
11:21
The seventh grader
said, "What's humidity?"
said, "What's humidity?"
278
669921
2266
7.klasses-eleven sagde:
"Hva' er luftfugtighed?"
"Hva' er luftfugtighed?"
11:24
And I said, "Oh, it's water in air."
279
672211
1865
Og jeg sagde: "Det er vand i luften."
11:26
He said, "There's no water
in air, you're an idiot."
in air, you're an idiot."
280
674100
2444
Han svarede:
"Der er ingen vand i luften, dit fjols!"
"Der er ingen vand i luften, dit fjols!"
11:28
(Laughter)
281
676568
1019
(Latter)
11:29
And I was like, "Alright, don't trust me.
282
677611
2009
Min respons: "Okay glem hvad jeg sagde."
11:31
Actually -- don't trust me, right?
283
679644
1659
"Jeg mener det, glem det bare"
11:33
Set it to 100.
284
681327
1151
"Sæt den til 100%."
11:34
He sets it to 100 and what happens?
285
682502
1705
Han indstiller den til 100%...
11:36
It starts to condense, make a fog
and eventually drip.
and eventually drip.
286
684231
2774
og hvad sker der - der dannes damp,
kondens, og vanddråber.
kondens, og vanddråber.
11:39
And he says, "Oh. Humidity is rain.
287
687457
3224
Han siger: "Okay, luftfugtighed er regn."
11:43
Why didn't you just tell me that?"
288
691372
1630
"Hvorfor sagde du ikke bare det?!"
11:45
(Laughter)
289
693026
1970
(Latter)
11:47
We've created an interface
for this that's much like a game.
for this that's much like a game.
290
695489
2843
Vi designede en brugerflade,
som mindede meget om et spil.
som mindede meget om et spil.
11:50
They have a 3D environment,
291
698356
1316
Der var en 3D verden,
11:51
they can log into it anywhere in the world
292
699696
2016
de kan logge ind fra hele verden
11:53
on their smartphone, on their tablet.
293
701736
1783
via deres mobil eller tablet.
11:55
They have different parts of the bots --
the physical, the sensors.
the physical, the sensors.
294
703543
3427
De har forskellige dele af robotten:
Det fysiske og sensorerne.
Det fysiske og sensorerne.
11:58
They select recipes that have
been created by other kids
been created by other kids
295
706994
2640
De udvælger opskrifter,
lavet af andre børn
lavet af andre børn
12:01
anywhere in the world.
296
709658
1150
fra hele verden.
12:02
They select and activate that recipe,
they plant a seedling.
they plant a seedling.
297
710832
3031
De vælger og aktiverer en opskrift,
de planter et frø.
de planter et frø.
12:06
While it's growing, they make changes.
298
714324
1837
De laver ændringer mens det gror.
12:08
They're like, "Why does a plant
need CO2 anyway? Isn't CO2 bad?
need CO2 anyway? Isn't CO2 bad?
299
716185
3009
De siger: "Hvorfor skal en plante
overhovedet have CO2?
overhovedet have CO2?
12:11
It kills people."
300
719218
1151
"CO2 kvæler da folk."
12:12
Crank up CO2, plant dies.
301
720393
1371
Sluk for CO2, planten dør.
12:14
Or crank down CO2, plant does very well.
302
722404
2997
Eller skru op for CO2,
og planten klarer sig fint.
og planten klarer sig fint.
12:17
Harvest plant,
303
725425
1190
Høst planten,
12:19
and you've created a new digital recipe.
304
727130
2167
du har nu lavet en ny digital opskrift.
12:21
It's an iterative design and development
305
729821
2090
Det er et eksperimenterende design
12:23
and exploration process.
306
731935
1912
og en udforskende proces.
12:25
They can download, then,
307
733871
1412
De kan downloade
12:27
all of the data about that new plant
that they developed
that they developed
308
735307
2717
alle de måledata
om den nye plante de har lavet
om den nye plante de har lavet
12:30
or the new digital recipe
and what did it do --
and what did it do --
309
738048
2286
- eller den nye digitale opskrift -
12:32
was it better or was it worse?
310
740358
1444
var den bedre eller dårligere?
12:33
Imagine these as little cores
of processing.
of processing.
311
741826
2126
Forestil dig dette som
små udviklingskerner.
små udviklingskerner.
12:36
We're going to learn so much.
312
744771
1967
Vi kommer til at lære så meget.
12:39
Here's one of the food computers,
as we call them,
as we call them,
313
747764
2698
Her er en af Madcomputerne,
som vi kalder dem,
som vi kalder dem,
12:42
in a school in three weeks' time.
314
750486
2252
placeret på en skole i 3 uger.
12:45
This is three weeks of growth.
315
753793
1439
Her ses 3 ugers vækst.
12:47
But more importantly,
316
755256
1844
Men endnu mere vigtigt,
12:49
it was the first time that this kid
ever thought he could be a farmer --
ever thought he could be a farmer --
317
757124
3960
det var første gang at denne elev
overvejede, at han kunne blive landmand.
overvejede, at han kunne blive landmand.
12:53
or that he would want to be a farmer.
318
761658
2116
- eller at han endda ville være landmand.
12:56
So, we've open-sourced all of this.
319
764187
2015
Vi gjorde dokumentationen frit tilgængelig
12:58
It's all online; go home, try to build
your first food computer.
your first food computer.
320
766226
3086
Det er altsammen online.
Prøv at bygge din madcomputer derhjemme.
Prøv at bygge din madcomputer derhjemme.
13:01
It's going to be difficult --
I'm just telling you.
I'm just telling you.
321
769336
2389
Det bliver svært - jeg siger det bare.
13:03
We're in the beginning,
but it's all there.
but it's all there.
322
771749
2064
Vi er i startfasen, men det hele er der.
13:05
It's very important to me
that this is easily accessible.
that this is easily accessible.
323
773837
2699
Det er vigtigt for mig,
at det er let tilgængeligt.
at det er let tilgængeligt.
13:08
We're going to keep making it more so.
324
776560
1847
Vi bliver ved med at gøre det lettere.
13:10
These are farmers,
325
778946
1428
Her er landmænd:
13:13
electrical engineer, mechanical engineer,
326
781016
1977
elektronik- og maskiningeniører,
13:15
environmental engineer,
computer scientist,
computer scientist,
327
783017
2033
miljøingeniører, softwareprogrammører,
13:17
plant scientist,
economist, urban planners.
economist, urban planners.
328
785074
2594
planteforskere, økonomer, byplanlæggere.
13:20
On one platform, doing
what they're good at.
what they're good at.
329
788214
2754
På en samlet platform,
gør de hvad de er bedst til.
gør de hvad de er bedst til.
13:22
But we got a little too big.
330
790992
1824
Men vi blev lidt for store,
13:24
This is my new facility
that I'm just starting.
that I'm just starting.
331
792840
2832
Her er min nye bygning,
som vi lige har taget i brug.
som vi lige har taget i brug.
13:27
This warehouse could be anywhere.
332
795696
1840
Denne type hal findes overalt.
13:30
That's why I chose it.
333
798088
1265
Derfor valgte jeg den.
13:31
And inside of this warehouse
334
799718
1623
Og inde i denne hal
13:33
we're going to build something
kind of like this.
kind of like this.
335
801365
2369
vil vi bygge noget som det her.
13:35
These exist right now.
336
803758
1462
Disse eksisterer nu.
13:37
Take a look at it.
337
805244
1227
Kig på dem.
13:40
These exist, too.
338
808053
1331
De her eksisterer også.
13:42
One grows greens,
339
810034
1280
Den ene gror grøntsager,
13:43
one grows Ebola vaccine.
340
811338
1581
den anden Ebolavaccine.
13:46
Pretty amazing that plants
and this DARPA Grand Challenge winner
and this DARPA Grand Challenge winner
341
814212
3914
Ret vildt at planter og en
DARPA Grand Challenge vinder
DARPA Grand Challenge vinder
13:50
is one of the reasons
we're getting ahead of Ebola.
we're getting ahead of Ebola.
342
818150
2496
er én af grundene til,
at vi kan bekæmpe Ebola.
at vi kan bekæmpe Ebola.
13:53
The plants are producing
the protein that's Ebola resistant.
the protein that's Ebola resistant.
343
821130
3524
Planterne producerer et protein,
som er resistent overfor Ebola.
som er resistent overfor Ebola.
13:57
So pharmaceuticals, nutraceuticals,
344
825083
2538
Så farmaceuter, diætister,
13:59
all they way down to lettuce.
345
827645
1516
de ender alle ved salat.
14:01
But these two things look nothing alike,
346
829620
1938
Men disse to ting har intet til fælles,
14:03
and that's where I am with my field.
347
831582
2277
og det er der jeg står.
14:05
Everything is different.
348
833883
1389
Alt er anderledes.
14:07
We're in that weird "We're alright" stage
349
835629
3310
Vi er i en underlig
"Vi har det fint" tilstand,
"Vi har det fint" tilstand,
14:10
and it's like, "Here's my black box --"
350
838963
1863
hvor man siger:
"Her er min sorte boks"
"Her er min sorte boks"
14:12
"No, buy mine."
351
840850
1151
"Nej, køb min løsning"
14:14
"No, no, no -- I've got intellectual
property that's totally valuable.
property that's totally valuable.
352
842025
3361
"Nej nej - jeg har intellektuel
ejendomsret, som er meget værdifuld."
ejendomsret, som er meget værdifuld."
14:17
Don't buy his, buy mine."
353
845410
1200
"Køb ikke hans, køb min."
14:18
And the reality is,
we're just at the beginning,
we're just at the beginning,
354
846634
2285
Og realiteten er,
vi er kun ved begyndelsen.
vi er kun ved begyndelsen.
14:20
in a time when society is shifting, too.
355
848943
2143
I en tid, hvor samfundet også ændrer sig.
14:23
When we ask for more, cheaper food,
356
851110
1715
Når vi vil have mere, billigere mad,
14:24
we're now asking for better,
environmentally friendly food.
environmentally friendly food.
357
852849
3340
efterspørger vi nu bedre, miljøvenlig mad.
14:28
And when you have McDonald's advertising
what's in the Chicken McNugget,
what's in the Chicken McNugget,
358
856654
5313
Og McDonald's reklamerer nu med,
hvad deres kyllingenuggets indeholder,
hvad deres kyllingenuggets indeholder,
14:33
the most mysterious
food item of all time --
food item of all time --
359
861991
2095
Det mest mystiske fødevare der findes -
14:36
they are now basing
their marketing plan on that --
their marketing plan on that --
360
864110
2737
de baserer nu deres markedsføringsstrategi
på information.
på information.
14:38
everything is changing.
361
866871
1470
Alt ændrer sig.
14:40
So into the world now.
362
868365
1522
Nye ting ser dagens lys:
14:41
Personal food computers,
363
869911
1658
Personlige madcomputere,
14:44
food servers
364
872764
1150
madservere
14:47
and food data centers
365
875261
1411
og mad-datacentre
14:50
run on the open phenome.
366
878434
2419
kører på det åbne phenom.
14:53
Think open genome, but we're going
to put little climate recipes,
to put little climate recipes,
367
881245
3229
Som et åbent genom,
men vi vil tilføje små klimaopskrifter
men vi vil tilføje små klimaopskrifter
14:56
like Wikipedia,
368
884498
1161
som et Wikipedia
14:57
that you can pull down, actuate and grow.
369
885683
3481
du kan downloade, aktivere og dyrke.
15:03
What does this look like in a world?
370
891275
1730
Hvordan ser det ud på verdenskortet?
15:05
You remember the world
connected by strings?
connected by strings?
371
893029
2135
Husker du verdenen forbundet af streger?
15:07
We start having beacons.
372
895188
1547
Vi vil begynde at have stråler.
15:09
We start sending information about food,
373
897338
2086
Vi vil begynde at sende data om mad,
15:11
rather than sending food.
374
899448
1319
i stedet for at sende mad.
15:13
This is not just my fantasy,
375
901249
1718
Dette er ikke kun fiktion,
15:14
this is where we're already deploying.
376
902991
2038
det har vi allerede implementeret.
15:17
Food computers, food servers,
377
905578
1689
Madcomputere, madservere,
15:19
soon-to-be food data centers,
378
907291
1436
og snart mad-datacentre,
15:20
connecting people together
to share information.
to share information.
379
908751
2414
får folk til at samles
om at dele information.
om at dele information.
15:24
The future of food is not about fighting
over what's wrong with this.
over what's wrong with this.
380
912723
5357
Fremtiden for mad handler ikke om
at bekæmpe hvad der er galt med dette.
at bekæmpe hvad der er galt med dette.
15:30
We know what's wrong with this.
381
918556
1826
Vi ved hvad der er galt med dette.
15:33
The future of food is about networking
the next one billion farmers
the next one billion farmers
382
921128
4515
Fremtiden for mad handler om at forbinde
den næste milliard landmænd
den næste milliard landmænd
15:37
and empowering them with a platform
383
925667
2274
og give dem en platform
15:39
to ask and answer the question,
384
927965
2020
hvor de kan spørge og besvare spørgsmålet:
15:42
"What if?"
385
930693
1335
"Hvad nu, hvis?"
15:44
Thank you.
386
932052
1171
Mange tak.
15:45
(Applause)
387
933247
8833
(Klapsalver)
ABOUT THE SPEAKER
Caleb Harper - Principal Investigator and Director of the Open Agriculture InitiativeCaleb Harper leads a group of engineers, architects, urban planners, economists and plant scientists in the exploration and development of high performance urban agricultural systems.
Why you should listen
What do we know about the food we eat? What if there was climate democracy? These and other questions inform the work of Caleb Harper and his colleagues as they explore the future of food systems. He is the principal investigator and director of the Open Agriculture Initiative (OpenAG) at the MIT Media Lab. Under his guidance, a diverse group of engineers, architects, urbanists, economists and plant scientists (what he calls an “anti-disciplinary group”) is developing an open-source agricultural hardware, software and data common aiming to create a more agile, transparent and collaborative food system.
Caleb Harper | Speaker | TED.com