Neil Gershenfeld: The beckoning promise of personal fabrication

82,218 views ・ 2007-03-23

TED


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

00:25
This meeting has really been about a digital revolution,
0
25000
4000
00:29
but I'd like to argue that it's done; we won.
1
29000
3000
00:33
We've had a digital revolution but we don't need to keep having it.
2
33000
4000
00:37
And I'd like to look after that,
3
37000
2000
00:39
to look what comes after the digital revolution.
4
39000
3000
00:42
So, let me start projecting forward.
5
42000
2000
00:44
These are some projects I'm involved in today at MIT,
6
44000
4000
00:48
looking what comes after computers.
7
48000
3000
00:51
This first one, Internet Zero, up here -- this is a web server
8
51000
5000
00:56
that has the cost and complexity of an RFID tag --
9
56000
3000
00:59
about a dollar -- that can go in every light bulb and doorknob,
10
59000
3000
01:02
and this is getting commercialized very quickly.
11
62000
2000
01:04
And what's interesting about it isn't the cost;
12
64000
2000
01:06
it's the way it encodes the Internet.
13
66000
1000
01:07
It uses a kind of a Morse code for the Internet
14
67000
3000
01:10
so you could send it optically; you can communicate acoustically
15
70000
3000
01:13
through a power line, through RF.
16
73000
2000
01:15
It takes the original principle of the Internet,
17
75000
2000
01:17
which is inter-networking computers,
18
77000
2000
01:19
and now lets devices inter-network.
19
79000
3000
01:22
That we can take the whole idea that gave birth to the Internet
20
82000
3000
01:25
and bring it down to the physical world in this Internet Zero,
21
85000
3000
01:28
this internet of devices.
22
88000
2000
01:30
So this is the next step from there to here,
23
90000
2000
01:32
and this is getting commercialized today.
24
92000
3000
01:35
A step after that is a project on fungible computers.
25
95000
5000
01:40
Fungible goods in economics can be extended and traded.
26
100000
3000
01:43
So, half as much grain is half as much useful,
27
103000
2000
01:45
but half a baby or half a computer is less useful than
28
105000
3000
01:48
a whole baby or a whole computer,
29
108000
2000
01:50
and we've been trying to make computers that work that way.
30
110000
3000
01:53
So, what you see in the background is a prototype.
31
113000
2000
01:55
This was from a thesis of a student, Bill Butow, now at Intel,
32
115000
3000
01:58
who wondered why, instead of making bigger and bigger chips,
33
118000
3000
02:01
you don't make small chips, put them in a viscous medium,
34
121000
3000
02:04
and pour out computing by the pound or by the square inch.
35
124000
2000
02:06
And that's what you see here.
36
126000
2000
02:08
On the left was postscript being rendered by a conventional computer;
37
128000
3000
02:11
on the right is postscript being rendered from the first prototype
38
131000
3000
02:14
we made, but there's no frame buffer, IO processor,
39
134000
4000
02:18
any of that stuff -- it's just this material.
40
138000
2000
02:20
Unlike this screen where the dots are placed carefully,
41
140000
2000
02:22
this is a raw material.
42
142000
1000
02:23
If you add twice as much of it, you have twice as much display.
43
143000
3000
02:26
If you shoot a gun through the middle, nothing happens.
44
146000
3000
02:29
If you need more resource, you just apply more computer.
45
149000
4000
02:33
So, that's the step after this -- of computing as a raw material.
46
153000
3000
02:36
That's still conventional bits, the step after that is --
47
156000
3000
02:39
this is an earlier prototype in the lab;
48
159000
2000
02:41
this is high-speed video slowed down.
49
161000
2000
02:43
Now, integrating chemistry in computation, where the bits are bubbles.
50
163000
3000
02:46
This is showing making bits, this is showing --
51
166000
2000
02:48
once again, slowed down so you can see it,
52
168000
2000
02:50
bits interacting to do logic and multiplexing and de-multiplexing.
53
170000
4000
02:54
So, now we can compute that the output arranges material
54
174000
3000
02:57
as well as information. And, ultimately, these are some slides
55
177000
4000
03:01
from an early project I did, computing where the bits are stored
56
181000
3000
03:04
quantum-mechanically in the nuclei of atoms, so
57
184000
3000
03:07
programs rearrange the nuclear structure of molecules.
58
187000
4000
03:11
All of these are in the lab pushing further and further and further,
59
191000
4000
03:15
not as metaphor but literally integrating bits and atoms,
60
195000
3000
03:18
and they lead to the following recognition.
61
198000
3000
03:21
We all know we've had a digital revolution, but what is that?
62
201000
3000
03:24
Well, Shannon took us, in the '40s, from here to here:
63
204000
3000
03:27
from a telephone being a speaker wire that degraded with distance
64
207000
4000
03:31
to the Internet. And he proved the first threshold theorem, that shows
65
211000
4000
03:35
if you add information and remove it to a signal,
66
215000
3000
03:38
you can compute perfectly with an imperfect device.
67
218000
2000
03:40
And that's when we got the Internet.
68
220000
2000
03:42
Von Neumann, in the '50s, did the same thing for computing;
69
222000
3000
03:45
he showed you can have an unreliable computer but restore its state
70
225000
3000
03:48
to make it perfect. This was the last great analog computer at MIT:
71
228000
4000
03:52
a differential analyzer, and the more you ran it,
72
232000
2000
03:54
the worse the answer got.
73
234000
2000
03:56
After Von Neumann, we have the Pentium, where the billionth transistor
74
236000
3000
03:59
is as reliable as the first one.
75
239000
3000
04:02
But all our fabrication is down in this lower left corner.
76
242000
3000
04:05
A state-of-the-art airplane factory rotating metal wax at fixed metal,
77
245000
3000
04:08
or you maybe melt some plastic. A 10-billion-dollar chip fab
78
248000
3000
04:11
uses a process a village artisan would recognize --
79
251000
3000
04:14
you spread stuff around and bake it.
80
254000
3000
04:17
All the intelligence is external to the system;
81
257000
2000
04:19
the materials don't have information.
82
259000
2000
04:21
Yesterday you heard about molecular biology,
83
261000
3000
04:24
which fundamentally computes to build.
84
264000
2000
04:26
It's an information processing system.
85
266000
2000
04:28
We've had digital revolutions in communication and computation,
86
268000
4000
04:32
but precisely the same idea, precisely the same math
87
272000
3000
04:35
Shannon and Von Neuman did, hasn't yet come out
88
275000
2000
04:37
to the physical world. So, inspired by that,
89
277000
3000
04:40
colleagues in this program -- the Center for Bits and Atoms
90
280000
2000
04:42
at MIT -- which is a group of people, like me,
91
282000
3000
04:45
who never understood the boundary between physical science
92
285000
3000
04:48
and computer science. I would even go further and say
93
288000
3000
04:51
computer science is one of the worst things that ever happened
94
291000
2000
04:53
to either computers or to science --
95
293000
2000
04:55
(Laughter)
96
295000
1000
04:56
-- because the canon -- computer science --
97
296000
4000
05:00
many of them are great but the canon of computer science
98
300000
2000
05:02
prematurely froze a model of computation
99
302000
3000
05:05
based on technology that was available in 1950,
100
305000
3000
05:08
and nature's a much more powerful computer than that.
101
308000
2000
05:10
So, you'll hear, tomorrow, from Saul Griffith. He was one of the
102
310000
4000
05:14
first students to emerge from this program.
103
314000
3000
05:17
We started to figure out how you can compute to fabricate.
104
317000
3000
05:20
This was just a proof of principle he did of tiles
105
320000
3000
05:23
that interact magnetically, where you write a code,
106
323000
2000
05:25
much like protein folding, that specifies their structure.
107
325000
3000
05:28
So, there's no feedback to a tool metrology;
108
328000
3000
05:31
the material itself codes for its structure in just the same ways
109
331000
5000
05:36
that protein are fabricated. So, you can, for example, do that.
110
336000
4000
05:40
You can do other things. That's in 2D. It works in 3D.
111
340000
3000
05:43
The video on the upper right -- I won't show for time --
112
343000
2000
05:45
shows self-replication, templating so something can make something
113
345000
4000
05:49
that can make something, and we're doing that now over, maybe,
114
349000
3000
05:52
nine orders of magnitude. Those ideas have been used to show
115
352000
3000
05:55
the best fidelity and direct rate DNA to make an organism,
116
355000
3000
05:58
in functionalizing nanoclusters with peptide tails
117
358000
3000
06:01
that code for their assembly -- so, much like the magnets,
118
361000
2000
06:03
but now on nanometer scales.
119
363000
2000
06:05
Laser micro-machining: essentially 3D printers that digitally fabricate
120
365000
4000
06:09
functional systems, all the way up to building buildings,
121
369000
3000
06:12
not by having blueprints,
122
372000
1000
06:13
but having the parts code for the structure of the building.
123
373000
3000
06:16
So, these are early examples in the lab of emerging technologies
124
376000
5000
06:21
to digitize fabrication. Computers that don't control tools
125
381000
4000
06:25
but computers that are tools, where the output of a program
126
385000
4000
06:29
rearranges atoms as well as bits.
127
389000
4000
06:33
Now, to do that -- with your tax dollars, thank you --
128
393000
3000
06:36
I bought all these machines. We made a modest proposal
129
396000
4000
06:40
to the NSF. We wanted to be able to make anything on any length scale,
130
400000
4000
06:44
all in one place, because you can't segregate digital fabrication
131
404000
4000
06:48
by a discipline or a length scale.
132
408000
2000
06:50
So we put together focused nano beam writers
133
410000
4000
06:54
and supersonic water jet cutters and excimer micro-machining systems.
134
414000
5000
06:59
But I had a problem. Once I had all these machines,
135
419000
3000
07:02
I was spending too much time teaching students to use them.
136
422000
3000
07:05
So I started teaching a class, modestly called,
137
425000
2000
07:07
"How To Make Almost Anything." And that wasn't meant to be provocative;
138
427000
3000
07:10
it was just for a few research students.
139
430000
2000
07:12
But the first day of class looked like this.
140
432000
2000
07:14
You know, hundreds of people came in begging,
141
434000
2000
07:16
all my life I've been waiting for this class; I'll do anything to do it.
142
436000
3000
07:19
Then they'd ask, can you teach it at MIT? It seems too useful?
143
439000
3000
07:22
And then the next --
144
442000
1000
07:23
(Laughter)
145
443000
2000
07:25
-- surprising thing was they weren't there to do research.
146
445000
1000
07:26
They were there because they wanted to make stuff.
147
446000
2000
07:28
They had no conventional technical background.
148
448000
4000
07:32
At the end of a semester they integrated their skills.
149
452000
2000
07:34
I'll show an old video. Kelly was a sculptor, and this is what she did
150
454000
4000
07:38
with her semester project.
151
458000
2000
07:40
(Video): Kelly: Hi, I'm Kelly and this is my scream buddy.
152
460000
3000
07:45
Do you ever find yourself in a situation
153
465000
3000
07:48
where you really have to scream, but you can't because you're at work,
154
468000
5000
07:53
or you're in a classroom, or you're watching your children,
155
473000
3000
07:56
or you're in any number of situations where it's just not permitted?
156
476000
5000
08:01
Well, scream buddy is a portable space for screaming.
157
481000
4000
08:05
When a user screams into scream buddy, their scream is silenced.
158
485000
5000
08:10
It is also recorded for later release where, when and how
159
490000
4000
08:14
the user chooses.
160
494000
1000
08:36
(Scream)
161
516000
2000
08:39
(Laughter) (Applause)
162
519000
4000
08:43
So, Einstein would like this.
163
523000
2000
08:45
This student made a web browser for parrots --
164
525000
1000
08:46
lets parrots surf the Net and talk to other parrots.
165
526000
3000
08:49
This student's made an alarm clock you wrestle
166
529000
2000
08:51
to prove you're awake; this is one that defends --
167
531000
2000
08:53
a dress that defends your personal space.
168
533000
2000
08:55
This isn't technology for communication;
169
535000
2000
08:57
it's technology to prevent it.
170
537000
2000
08:59
This is a device that lets you see your music.
171
539000
3000
09:02
This is a student who made a machine that makes machines,
172
542000
3000
09:05
and he made it by making Lego bricks that do the computing.
173
545000
3000
09:08
Just year after year -- and I finally realized
174
548000
2000
09:10
the students were showing the killer app of personal fabrication
175
550000
4000
09:14
is products for a market of one person.
176
554000
2000
09:16
You don't need this for what you can get in Wal-Mart;
177
556000
2000
09:18
you need this for what makes you unique.
178
558000
1000
09:19
Ken Olsen famously said, nobody needs a computer in the home.
179
559000
4000
09:23
But you don't use it for inventory and payroll;
180
563000
2000
09:25
DEC is now twice bankrupt. You don't need personal fabrication
181
565000
3000
09:28
in the home to buy what you can buy because you can buy it.
182
568000
2000
09:30
You need it for what makes you unique, just like personalization.
183
570000
4000
09:34
So, with that, in turn, 20 million dollars today does this;
184
574000
4000
09:38
20 years from now we'll make Star Trek replicators that make anything.
185
578000
4000
09:42
The students hijacked all the machines I bought to do personal fabrication.
186
582000
4000
09:46
Today, when you spend that much of your money,
187
586000
2000
09:48
there's a government requirement to do outreach, which often means
188
588000
3000
09:51
classes at a local school, a website -- stuff that's just not that exciting.
189
591000
3000
09:54
So, I made a deal with my NSF program managers that
190
594000
4000
09:58
instead of talking about it, I'd give people the tools.
191
598000
2000
10:00
This wasn't meant to be provocative or important,
192
600000
2000
10:02
but we put together these Fab Labs. It's about 20,000 dollars in equipment
193
602000
4000
10:06
that approximate both what the 20 million dollars does and where it's going.
194
606000
5000
10:11
A laser cutter to do press-fit assembly with 3D from 2D,
195
611000
3000
10:14
a sign cutter to plot in copper to do electromagnetics,
196
614000
2000
10:16
a micron scale,
197
616000
2000
10:18
numerically-controlled milling machine for precise structures,
198
618000
2000
10:20
programming tools for less than a dollar,
199
620000
3000
10:23
100-nanosecond microcontrollers. It lets you work from microns
200
623000
3000
10:26
and microseconds on up, and they exploded around the world.
201
626000
4000
10:30
This wasn't scheduled, but they went from inner-city Boston
202
630000
2000
10:32
to Pobal in India, to Secondi-Takoradi on Ghana's coast
203
632000
4000
10:36
to Soshanguve in a township in South Africa,
204
636000
3000
10:39
to the far north of Norway, uncovering, or helping uncover,
205
639000
4000
10:43
for all the attention to the digital divide,
206
643000
3000
10:46
we would find unused computers in all these places.
207
646000
4000
10:50
A farmer in a rural village -- a kid needs to measure and modify
208
650000
3000
10:53
the world, not just get information about it on a screen.
209
653000
4000
10:57
That there's really a fabrication and an instrumentation divide
210
657000
2000
10:59
bigger than the digital divide.
211
659000
3000
11:02
And the way you close it is not IT for the masses but IT development for the masses.
212
662000
3000
11:05
So, in place after place
213
665000
3000
11:08
we saw this same progression: that we'd open one of these Fab Labs,
214
668000
3000
11:11
where we didn't -- this is too crazy to think of.
215
671000
3000
11:14
We didn't think this up, that we would get pulled to these places;
216
674000
3000
11:17
we'd open it. The first step was just empowerment.
217
677000
2000
11:19
You can see it in their face, just this joy of, I can do it.
218
679000
3000
11:22
This is a girl in inner-city Boston who had just done a high-tech
219
682000
2000
11:24
on-demand craft sale in the inner city community center.
220
684000
4000
11:28
It goes on from there to serious hands-on technical education
221
688000
4000
11:32
informally, out of schools. In Ghana we had set up one of these labs.
222
692000
5000
11:37
We designed a network sensor, and kids would show up
223
697000
2000
11:39
and refuse to leave the lab.
224
699000
1000
11:40
There was a girl who insisted we stay late at night --
225
700000
3000
11:43
(Video): Kids: I love the Fab Lab.
226
703000
2000
11:45
-- her first night in the lab because she was going to make the sensor.
227
705000
3000
11:48
So she insisted on fabbing the board, learning how to stuff it,
228
708000
3000
11:51
learning how to program it. She didn't really know
229
711000
2000
11:53
what she was doing or why she was doing it, but she knew
230
713000
2000
11:55
she just had to do it. There was something electric about it.
231
715000
3000
11:58
This is late at, you know, 11 o'clock at night
232
718000
2000
12:00
and I think I was the only person surprised when what she built
233
720000
3000
12:03
worked the first time.
234
723000
2000
12:05
And I've shown this to engineers at big companies, and they say
235
725000
2000
12:07
they can't do this. Any one thing she's doing, they can do better,
236
727000
3000
12:10
but it's distributed over many people and many sites
237
730000
3000
12:13
and they can't do in an afternoon
238
733000
1000
12:14
what this little girl in rural Ghana is doing.
239
734000
3000
12:33
(Video): Girl: My name is Valentina Kofi; I am eight years old.
240
753000
4000
12:37
I made a stacking board.
241
757000
3000
12:40
And, again, that was just for the joy of it.
242
760000
3000
12:43
Then these labs started doing serious problem solving --
243
763000
3000
12:46
instrumentation for agriculture in India,
244
766000
2000
12:48
steam turbines for energy conversion in Ghana,
245
768000
2000
12:50
high-gain antennas in thin client computers.
246
770000
4000
12:54
And then, in turn, businesses started to grow,
247
774000
1000
12:55
like making these antennas.
248
775000
1000
12:56
And finally, the lab started doing invention.
249
776000
2000
12:58
We're learning more from them than we're giving them.
250
778000
2000
13:00
I was showing my kids in a Fab Lab how to use it.
251
780000
3000
13:03
They invented a way to do a construction kit out of a cardboard box --
252
783000
4000
13:07
which, as you see up there, that's becoming a business --
253
787000
2000
13:09
but their design was better than Saul's design at MIT,
254
789000
3000
13:12
so there's now three students at MIT doing their theses on
255
792000
3000
13:15
scaling the work of eight-year-old children
256
795000
3000
13:18
because they had better designs.
257
798000
1000
13:19
Real invention is happening in these labs.
258
799000
3000
13:22
And I still kept -- so, in the last year I've been spending time with
259
802000
2000
13:24
heads of state and generals and tribal chiefs who all want this,
260
804000
3000
13:27
and I keep saying, but this isn't the real thing.
261
807000
2000
13:29
Wait, like, 20 years and then we'll be done.
262
809000
2000
13:31
And I finally got what's been going on. This is Kernigan and Ritchie
263
811000
3000
13:34
inventing UNIX on a PDP.
264
814000
3000
13:37
PDPs came between mainframes and minicomputers.
265
817000
2000
13:39
They were tens of thousands of dollars, hard to use,
266
819000
3000
13:42
but they brought computing down to work groups,
267
822000
2000
13:44
and everything we do today happened there.
268
824000
2000
13:46
These Fab Labs are the cost and complexity of a PDP.
269
826000
3000
13:49
The projection of digital fabrication
270
829000
2000
13:51
isn't a projection for the future; we are now in the PDP era.
271
831000
3000
13:54
We talked in hushed tones about the great discoveries then.
272
834000
3000
13:57
It was very chaotic, it wasn't, sort of, clear what was going on.
273
837000
3000
14:00
In the same sense we are now, today, in the minicomputer era
274
840000
3000
14:03
of digital fabrication.
275
843000
2000
14:05
The only problem with that is it breaks everybody's boundaries.
276
845000
4000
14:09
In DC, I go to every agency that wants to talk, you know;
277
849000
3000
14:12
in the Bay Area, I go to every organization you can think of --
278
852000
2000
14:14
they all want to talk about it, but it breaks
279
854000
2000
14:16
their organizational boundaries. In fact, it's illegal for them,
280
856000
3000
14:19
in many cases, to equip ordinary people to create
281
859000
4000
14:23
rather than consume technology.
282
863000
1000
14:24
And that problem is so severe that the ultimate invention
283
864000
4000
14:28
coming from this community surprised me:
284
868000
3000
14:31
it's the social engineering. That the lab in far north of Norway --
285
871000
4000
14:35
this is so far north its satellite dishes look at the ground
286
875000
2000
14:37
rather than the sky because that's where the satellites are --
287
877000
4000
14:41
the lab outgrew the little barn that it was in.
288
881000
1000
14:42
It was there because they wanted to find animals in the mountains
289
882000
3000
14:45
but it outgrew it, so they built this extraordinary village for the lab.
290
885000
4000
14:49
This isn't a university; it's not a company. It's essentially
291
889000
2000
14:51
a village for invention; it's a village for the outliers in society,
292
891000
5000
14:56
and those have been growing up around these Fab Labs
293
896000
2000
14:58
all around the world.
294
898000
1000
14:59
So this program has split into an NGO foundation,
295
899000
4000
15:03
a Fab Foundation to support the scaling, a micro VC fund.
296
903000
4000
15:07
The person who runs it nicely describes it as
297
907000
1000
15:08
"machines that make machines need businesses that make businesses:"
298
908000
4000
15:12
it's a cross between micro-finance and VC to do fan-out,
299
912000
3000
15:15
and then the research partnerships back at MIT for what's
300
915000
2000
15:17
making it possible.
301
917000
3000
15:20
So I'd like to leave you with two thoughts.
302
920000
2000
15:22
There's been a sea change in aid, from top-down mega-projects
303
922000
5000
15:27
to bottom-up, grassroots, micro-finance investing in the roots,
304
927000
4000
15:31
so that everybody's got that that's what works.
305
931000
3000
15:34
But we still look at technology as top-down mega-projects.
306
934000
3000
15:37
Computing, communication, energy for the rest of the planet
307
937000
3000
15:40
are these top-down mega-projects.
308
940000
2000
15:42
If this room full of heroes is just clever enough,
309
942000
2000
15:44
you can solve the problems.
310
944000
2000
15:46
The message coming from the Fab Labs is that
311
946000
2000
15:48
the other five billion people on the planet
312
948000
2000
15:50
aren't just technical sinks; they're sources.
313
950000
2000
15:52
The real opportunity is to harness the inventive power of the world
314
952000
3000
15:55
to locally design and produce solutions to local problems.
315
955000
4000
15:59
I thought that's the projection 20 years hence into the future,
316
959000
3000
16:02
but it's where we are today.
317
962000
2000
16:04
It breaks every organizational boundary we can think of.
318
964000
2000
16:06
The hardest thing at this point is the social engineering
319
966000
3000
16:09
and the organizational engineering, but it's here today.
320
969000
3000
16:12
And, finally, any talk like this on the future of computing
321
972000
2000
16:14
is required to show Moore's law, but my favorite version --
322
974000
4000
16:18
this is Gordon Moore's original one from his original paper --
323
978000
5000
16:23
and what's happened is, year after year after year,
324
983000
2000
16:25
we've scaled and we've scaled and we've scaled
325
985000
1000
16:26
and we've scaled, and we've scaled and we've scaled,
326
986000
4000
16:30
and we've scaled and we've scaled,
327
990000
1000
16:31
and there's this looming bug of what's going to happen
328
991000
2000
16:33
at the end of Moore's law; this ultimate bug is coming.
329
993000
4000
16:37
But we're coming to appreciate, is the transition from 2D to 3D,
330
997000
5000
16:42
from programming bits to programming atoms,
331
1002000
3000
16:45
turns the ends of Moore's law scaling from the ultimate bug
332
1005000
2000
16:47
to the ultimate feature.
333
1007000
2000
16:49
So, we're just at the edge of this digital revolution in fabrication,
334
1009000
4000
16:53
where the output of computation programs the physical world.
335
1013000
3000
16:56
So, together, these two projects answer questions
336
1016000
3000
16:59
I hadn't asked carefully. The class at MIT shows the killer app
337
1019000
4000
17:03
for personal fabrication in the developed world
338
1023000
2000
17:05
is technology for a market of one: personal expression in technology
339
1025000
4000
17:09
that touches a passion unlike anything I've seen in technology
340
1029000
3000
17:12
for a very long time.
341
1032000
2000
17:14
And the killer app for the rest of the planet is the instrumentation
342
1034000
4000
17:18
and the fabrication divide: people locally developing solutions
343
1038000
3000
17:21
to local problems. Thank you.
344
1041000
2000
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