1
00:00:00,000 --> 00:00:03,000
It is actually a reality today

2
00:00:03,000 --> 00:00:07,000
that you can download products from the Web --

3
00:00:07,000 --> 00:00:10,000
product data, I should say, from the Web --

4
00:00:10,000 --> 00:00:13,000
perhaps tweak it and personalize it

5
00:00:13,000 --> 00:00:15,000
to your own preference or your own taste,

6
00:00:15,000 --> 00:00:18,000
and have that information sent

7
00:00:18,000 --> 00:00:21,000
to a desktop machine

8
00:00:21,000 --> 00:00:23,000
that will fabricate it for you on the spot.

9
00:00:23,000 --> 00:00:25,000
We can actually build for you,

10
00:00:25,000 --> 00:00:27,000
very rapidly,

11
00:00:27,000 --> 00:00:30,000
a physical object.

12
00:00:30,000 --> 00:00:32,000
And the reason we can do this

13
00:00:32,000 --> 00:00:34,000
is through an emerging technology

14
00:00:34,000 --> 00:00:36,000
called additive manufacturing,

15
00:00:36,000 --> 00:00:39,000
or 3D printing.

16
00:00:39,000 --> 00:00:41,000
This is a 3D printer.

17
00:00:41,000 --> 00:00:43,000
They have been around

18
00:00:43,000 --> 00:00:45,000
for almost 30 years now,

19
00:00:45,000 --> 00:00:47,000
which is quite amazing to think of,

20
00:00:47,000 --> 00:00:49,000
but they're only just starting

21
00:00:49,000 --> 00:00:51,000
to filter into the public arena.

22
00:00:51,000 --> 00:00:54,000
And typically, you would take data,

23
00:00:54,000 --> 00:00:57,000
like the data of a pen here,

24
00:00:57,000 --> 00:01:00,000
which would be a geometric representation of that product in 3D,

25
00:01:00,000 --> 00:01:02,000
and we would pass that data with material

26
00:01:02,000 --> 00:01:04,000
into a machine.

27
00:01:04,000 --> 00:01:06,000
And a process that would happen in the machine

28
00:01:06,000 --> 00:01:08,000
would mean layer by layer that product would be built.

29
00:01:08,000 --> 00:01:11,000
And we can take out the physical product,

30
00:01:11,000 --> 00:01:13,000
and ready to use,

31
00:01:13,000 --> 00:01:16,000
or to, perhaps, assemble into something else.

32
00:01:16,000 --> 00:01:19,000
But if these machines have been around for almost 30 years,

33
00:01:19,000 --> 00:01:21,000
why don't we know about them?

34
00:01:21,000 --> 00:01:24,000
Because typically they've been too inefficient,

35
00:01:24,000 --> 00:01:27,000
inaccessible,

36
00:01:27,000 --> 00:01:29,000
they've not been fast enough,

37
00:01:29,000 --> 00:01:31,000
they've been quite expensive.

38
00:01:31,000 --> 00:01:33,000
But today,

39
00:01:33,000 --> 00:01:35,000
it is becoming a reality

40
00:01:35,000 --> 00:01:37,000
that they are now becoming successful.

41
00:01:37,000 --> 00:01:39,000
Many barriers are breaking down.

42
00:01:39,000 --> 00:01:41,000
That means that you guys

43
00:01:41,000 --> 00:01:43,000
will soon be able to access one of these machines,

44
00:01:43,000 --> 00:01:46,000
if not this minute.

45
00:01:46,000 --> 00:01:48,000
And it will change and disrupt

46
00:01:48,000 --> 00:01:50,000
the landscape of manufacturing,

47
00:01:50,000 --> 00:01:53,000
and most certainly our lives, our businesses

48
00:01:53,000 --> 00:01:55,000
and the lives of our children.

49
00:01:55,000 --> 00:01:58,000
So how does it work?

50
00:01:58,000 --> 00:02:00,000
It typically reads CAD data,

51
00:02:00,000 --> 00:02:02,000
which is a product design data

52
00:02:02,000 --> 00:02:04,000
created on professional product design programs.

53
00:02:04,000 --> 00:02:06,000
And here you can see an engineer --

54
00:02:06,000 --> 00:02:09,000
it could be an architect or it could be a professional product designer --

55
00:02:09,000 --> 00:02:12,000
create a product in 3D.

56
00:02:12,000 --> 00:02:14,000
And this data gets sent to a machine

57
00:02:14,000 --> 00:02:17,000
that slices the data

58
00:02:17,000 --> 00:02:19,000
into two-dimensional representations of that product

59
00:02:19,000 --> 00:02:21,000
all the way through --

60
00:02:21,000 --> 00:02:24,000
almost like slicing it like salami.

61
00:02:24,000 --> 00:02:27,000
And that data, layer by layer, gets passed through the machine,

62
00:02:27,000 --> 00:02:29,000
starting at the base of the product

63
00:02:29,000 --> 00:02:32,000
and depositing material, layer upon layer,

64
00:02:32,000 --> 00:02:36,000
infusing the new layer of materials to the old layer

65
00:02:36,000 --> 00:02:38,000
in an additive process.

66
00:02:38,000 --> 00:02:41,000
And this material that's deposited

67
00:02:41,000 --> 00:02:43,000
either starts as a liquid form

68
00:02:43,000 --> 00:02:46,000
or a material powder form.

69
00:02:46,000 --> 00:02:48,000
And the bonding process can happen

70
00:02:48,000 --> 00:02:51,000
by either melting and depositing or depositing then melting.

71
00:02:51,000 --> 00:02:54,000
In this case, we can see a laser sintering machine developed by EOS.

72
00:02:54,000 --> 00:02:56,000
It's actually using a laser

73
00:02:56,000 --> 00:02:59,000
to fuse the new layer of material to the old layer.

74
00:02:59,000 --> 00:03:01,000
And over time --

75
00:03:01,000 --> 00:03:03,000
quite rapidly actually, in a number of hours --

76
00:03:03,000 --> 00:03:05,000
we can build a physical product,

77
00:03:05,000 --> 00:03:07,000
ready to take out of the machine and use.

78
00:03:07,000 --> 00:03:11,000
And this is quite an extraordinary idea,

79
00:03:11,000 --> 00:03:14,000
but it is reality today.

80
00:03:14,000 --> 00:03:17,000
So all these products that you can see on the screen

81
00:03:17,000 --> 00:03:19,000
were made in the same way.

82
00:03:19,000 --> 00:03:21,000
They were all 3D printed.

83
00:03:21,000 --> 00:03:23,000
And you can see,

84
00:03:23,000 --> 00:03:25,000
they're ranging from shoes,

85
00:03:25,000 --> 00:03:28,000
rings that were made out of stainless steal,

86
00:03:28,000 --> 00:03:30,000
phone covers out of plastic,

87
00:03:30,000 --> 00:03:33,000
all the way through to spinal implants, for example,

88
00:03:33,000 --> 00:03:35,000
that were created out of medical-grade titanium,

89
00:03:35,000 --> 00:03:37,000
and engine parts.

90
00:03:37,000 --> 00:03:39,000
But what you'll notice about all of these products

91
00:03:39,000 --> 00:03:41,000
is they're very, very intricate.

92
00:03:41,000 --> 00:03:44,000
The design is quite extraordinary.

93
00:03:44,000 --> 00:03:47,000
Because we're taking this data in 3D form,

94
00:03:47,000 --> 00:03:50,000
slicing it up before it gets past the machine,

95
00:03:50,000 --> 00:03:52,000
we can actually create structures

96
00:03:52,000 --> 00:03:54,000
that are more intricate

97
00:03:54,000 --> 00:03:57,000
than any other manufacturing technology --

98
00:03:57,000 --> 00:04:01,000
or, in fact, are impossible to build in any other way.

99
00:04:01,000 --> 00:04:04,000
And you can create parts with moving components,

100
00:04:04,000 --> 00:04:06,000
hinges, parts within parts.

101
00:04:06,000 --> 00:04:09,000
So in some cases, we can abolish totally

102
00:04:09,000 --> 00:04:11,000
the need for manual labor.

103
00:04:11,000 --> 00:04:13,000
It sounds great.

104
00:04:13,000 --> 00:04:15,000
It is great.

105
00:04:15,000 --> 00:04:17,000
We can have 3D printers today

106
00:04:17,000 --> 00:04:19,000
that build structures like these.

107
00:04:19,000 --> 00:04:22,000
This is almost three meters high.

108
00:04:22,000 --> 00:04:24,000
And this was built

109
00:04:24,000 --> 00:04:27,000
by depositing artificial sandstone layer upon layer

110
00:04:27,000 --> 00:04:31,000
in layers of about five millimeters to 10 mm in thickness --

111
00:04:31,000 --> 00:04:33,000
slowly growing this structure.

112
00:04:33,000 --> 00:04:36,000
This was created by an architectural firm called Shiro.

113
00:04:36,000 --> 00:04:38,000
And you can actually walk into it.

114
00:04:38,000 --> 00:04:40,000
And on the other end of the spectrum,

115
00:04:40,000 --> 00:04:42,000
this is a microstructure.

116
00:04:42,000 --> 00:04:44,000
It's created depositing layers

117
00:04:44,000 --> 00:04:47,000
of about four microns.

118
00:04:47,000 --> 00:04:50,000
So really the resolution is quite incredible.

119
00:04:50,000 --> 00:04:52,000
The detail that you can get today

120
00:04:52,000 --> 00:04:55,000
is quite amazing.

121
00:04:55,000 --> 00:04:57,000
So who's using it?

122
00:04:57,000 --> 00:05:00,000
Typically, because we can create products very rapidly,

123
00:05:00,000 --> 00:05:03,000
it's been used by product designers,

124
00:05:03,000 --> 00:05:06,000
or anyone who wanted to prototype a product

125
00:05:06,000 --> 00:05:09,000
and very quickly create or reiterate a design.

126
00:05:09,000 --> 00:05:13,000
And actually what's quite amazing about this technology as well

127
00:05:13,000 --> 00:05:16,000
is that you can create bespoke products en masse.

128
00:05:16,000 --> 00:05:19,000
There's very little economies of scale.

129
00:05:19,000 --> 00:05:22,000
So you can now create one-offs very easily.

130
00:05:22,000 --> 00:05:24,000
Architects, for example,

131
00:05:24,000 --> 00:05:26,000
they want to create prototypes of buildings.

132
00:05:26,000 --> 00:05:28,000
Again you can see,

133
00:05:28,000 --> 00:05:31,000
this is a building of the Free University in Berlin

134
00:05:31,000 --> 00:05:33,000
and it was designed by Foster and Partners.

135
00:05:33,000 --> 00:05:36,000
Again, not buildable in any other way.

136
00:05:36,000 --> 00:05:39,000
And very hard to even create this by hand.

137
00:05:41,000 --> 00:05:44,000
Now this is an engine component.

138
00:05:44,000 --> 00:05:47,000
It was developed by a company called Within Technologies

139
00:05:47,000 --> 00:05:50,000
and 3T RPD.

140
00:05:50,000 --> 00:05:52,000
It's very, very, very detailed

141
00:05:52,000 --> 00:05:54,000
inside with the design.

142
00:05:54,000 --> 00:05:56,000
Now 3D printing

143
00:05:56,000 --> 00:05:58,000
can break away barriers in design

144
00:05:58,000 --> 00:06:00,000
which challenge the constraints

145
00:06:00,000 --> 00:06:02,000
of mass production.

146
00:06:02,000 --> 00:06:05,000
If we slice into this product which is actually sitting here,

147
00:06:05,000 --> 00:06:09,000
you can see that it has a number of cooling channels pass through it,

148
00:06:09,000 --> 00:06:12,000
which means it's a more efficient product.

149
00:06:12,000 --> 00:06:15,000
You can't create this with standard manufacturing techniques

150
00:06:15,000 --> 00:06:17,000
even if you tried to do it manually.

151
00:06:17,000 --> 00:06:19,000
It's more efficient

152
00:06:19,000 --> 00:06:22,000
because we can now create all these cavities within the object

153
00:06:22,000 --> 00:06:24,000
that cool fluid.

154
00:06:24,000 --> 00:06:26,000
And it's used by aerospace

155
00:06:26,000 --> 00:06:29,000
and automotive.

156
00:06:29,000 --> 00:06:32,000
It's a lighter part

157
00:06:32,000 --> 00:06:34,000
and it uses less material waste.

158
00:06:34,000 --> 00:06:37,000
So it's overall performance and efficiency

159
00:06:37,000 --> 00:06:40,000
just exceeds standard mass produced products.

160
00:06:40,000 --> 00:06:42,000
And then taking this idea

161
00:06:42,000 --> 00:06:44,000
of creating a very detailed structure,

162
00:06:44,000 --> 00:06:46,000
we can apply it to honeycomb structures

163
00:06:46,000 --> 00:06:49,000
and use them within implants.

164
00:06:49,000 --> 00:06:51,000
Typically an implant

165
00:06:51,000 --> 00:06:53,000
is more effective within the body

166
00:06:53,000 --> 00:06:55,000
if it's more porous,

167
00:06:55,000 --> 00:06:57,000
because our body tissue will grow into it.

168
00:06:57,000 --> 00:07:00,000
There's a lower chance of rejection.

169
00:07:00,000 --> 00:07:03,000
But it's very hard to create that in standard ways.

170
00:07:03,000 --> 00:07:05,000
With 3D printing,

171
00:07:05,000 --> 00:07:07,000
we're seeing today

172
00:07:07,000 --> 00:07:09,000
that we can create much better implants.

173
00:07:09,000 --> 00:07:11,000
And in fact, because we can create

174
00:07:11,000 --> 00:07:14,000
bespoke products en masse, one-offs,

175
00:07:14,000 --> 00:07:16,000
we can create implants

176
00:07:16,000 --> 00:07:18,000
that are specific to individuals.

177
00:07:18,000 --> 00:07:20,000
So as you can see,

178
00:07:20,000 --> 00:07:24,000
this technology and the quality of what comes out of the machines is fantastic.

179
00:07:24,000 --> 00:07:26,000
And we're starting to see it being used

180
00:07:26,000 --> 00:07:28,000
for final end products.

181
00:07:28,000 --> 00:07:30,000
And in fact, as the detail is improving,

182
00:07:30,000 --> 00:07:32,000
the quality is improving,

183
00:07:32,000 --> 00:07:35,000
the price of the machines are falling

184
00:07:35,000 --> 00:07:37,000
and they're becoming quicker.

185
00:07:37,000 --> 00:07:39,000
They're also now small enough

186
00:07:39,000 --> 00:07:41,000
to sit on a desktop.

187
00:07:41,000 --> 00:07:43,000
You can buy a machine today for about $300

188
00:07:43,000 --> 00:07:45,000
that you can create yourself,

189
00:07:45,000 --> 00:07:47,000
which is quite incredible.

190
00:07:47,000 --> 00:07:49,000
But then it begs the question,

191
00:07:49,000 --> 00:07:52,000
why don't we all have one in our home?

192
00:07:52,000 --> 00:07:54,000
Because, simply, most of us here today

193
00:07:54,000 --> 00:07:56,000
don't know how to create the data

194
00:07:56,000 --> 00:07:58,000
that a 3D printer reads.

195
00:07:58,000 --> 00:08:00,000
If I gave you a 3D printer,

196
00:08:00,000 --> 00:08:02,000
you wouldn't know how to direct it

197
00:08:02,000 --> 00:08:04,000
to make what you want it to.

198
00:08:04,000 --> 00:08:06,000
But there are more and more

199
00:08:06,000 --> 00:08:08,000
technologies, software and processes today

200
00:08:08,000 --> 00:08:10,000
that are breaking down those barriers.

201
00:08:10,000 --> 00:08:12,000
I believe we're at a tipping point

202
00:08:12,000 --> 00:08:15,000
where this is now something

203
00:08:15,000 --> 00:08:17,000
that we can't avoid.

204
00:08:17,000 --> 00:08:19,000
This technology

205
00:08:19,000 --> 00:08:21,000
is really going to disrupt

206
00:08:21,000 --> 00:08:23,000
the landscape of manufacturing

207
00:08:23,000 --> 00:08:25,000
and, I believe, cause a revolution

208
00:08:25,000 --> 00:08:27,000
in manufacturing.

209
00:08:27,000 --> 00:08:29,000
So today,

210
00:08:29,000 --> 00:08:31,000
you can download products from the Web --

211
00:08:31,000 --> 00:08:33,000
anything you would have on your desktop,

212
00:08:33,000 --> 00:08:36,000
like pens, whistles, lemon squeezers.

213
00:08:36,000 --> 00:08:39,000
You can use software like Google SketchUp

214
00:08:39,000 --> 00:08:41,000
to create products from scratch

215
00:08:41,000 --> 00:08:44,000
very easily.

216
00:08:44,000 --> 00:08:46,000
3D printing can be also used

217
00:08:46,000 --> 00:08:49,000
to download spare parts from the Web.

218
00:08:49,000 --> 00:08:51,000
So imagine you have, say,

219
00:08:51,000 --> 00:08:53,000
a Hoover in your home

220
00:08:53,000 --> 00:08:56,000
and it has broken down. You need a spare part,

221
00:08:56,000 --> 00:08:59,000
but you realize that Hoover's been discontinued.

222
00:08:59,000 --> 00:09:01,000
Can you imagine going online --

223
00:09:01,000 --> 00:09:03,000
this is a reality --

224
00:09:03,000 --> 00:09:05,000
and finding that spare part

225
00:09:05,000 --> 00:09:07,000
from a database of geometries

226
00:09:07,000 --> 00:09:09,000
of that discontinued product

227
00:09:09,000 --> 00:09:12,000
and downloading that information, that data,

228
00:09:12,000 --> 00:09:14,000
and having the product made for you at home,

229
00:09:14,000 --> 00:09:17,000
ready to use, on your demand?

230
00:09:17,000 --> 00:09:19,000
And in fact, because we can create spare parts

231
00:09:19,000 --> 00:09:21,000
with things the machines

232
00:09:21,000 --> 00:09:23,000
are quite literally making themselves.

233
00:09:23,000 --> 00:09:26,000
You're having machines fabricate themselves.

234
00:09:26,000 --> 00:09:28,000
These are parts of a RepRap machine,

235
00:09:28,000 --> 00:09:31,000
which is a kind of desktop printer.

236
00:09:31,000 --> 00:09:34,000
But what interests my company the most

237
00:09:34,000 --> 00:09:36,000
is the fact that you can create

238
00:09:36,000 --> 00:09:39,000
individual unique products en masse.

239
00:09:39,000 --> 00:09:41,000
There's no need to do a run

240
00:09:41,000 --> 00:09:43,000
of thousands of millions

241
00:09:43,000 --> 00:09:46,000
or send that product to be injection molded in China.

242
00:09:46,000 --> 00:09:50,000
You can just make it physically on the spot.

243
00:09:50,000 --> 00:09:52,000
Which means

244
00:09:52,000 --> 00:09:54,000
that we can now present to the public

245
00:09:54,000 --> 00:09:57,000
the next generation of customization.

246
00:09:57,000 --> 00:09:59,000
This is something that is now possible today,

247
00:09:59,000 --> 00:10:01,000
that you can direct personally

248
00:10:01,000 --> 00:10:04,000
how you want your products to look.

249
00:10:04,000 --> 00:10:06,000
We're all familiar with the idea

250
00:10:06,000 --> 00:10:08,000
of customization or personalization.

251
00:10:08,000 --> 00:10:10,000
Brands like Nike are doing it.

252
00:10:10,000 --> 00:10:12,000
It's all over the Web.

253
00:10:12,000 --> 00:10:14,000
In fact, every major household name

254
00:10:14,000 --> 00:10:16,000
is allowing you

255
00:10:16,000 --> 00:10:18,000
to interact with their products

256
00:10:18,000 --> 00:10:20,000
on a daily basis --

257
00:10:20,000 --> 00:10:22,000
all the way from Smart Cars

258
00:10:22,000 --> 00:10:24,000
to Prada

259
00:10:24,000 --> 00:10:26,000
to Ray Ban, for example.

260
00:10:26,000 --> 00:10:28,000
But this is not really mass customization;

261
00:10:28,000 --> 00:10:30,000
it's known as variant production,

262
00:10:30,000 --> 00:10:33,000
variations of the same product.

263
00:10:33,000 --> 00:10:36,000
What you could do is really influence your product now

264
00:10:36,000 --> 00:10:39,000
and shape-manipulate your product.

265
00:10:39,000 --> 00:10:41,000
I'm not sure about you guys,

266
00:10:41,000 --> 00:10:43,000
but I've had experiences

267
00:10:43,000 --> 00:10:45,000
when I've walked into a store and I've know exactly what I've wanted

268
00:10:45,000 --> 00:10:48,000
and I've searched everywhere for that perfect lamp

269
00:10:48,000 --> 00:10:50,000
that I know where I want to sit in my house

270
00:10:50,000 --> 00:10:52,000
and I just can't find the right thing,

271
00:10:52,000 --> 00:10:55,000
or that perfect piece of jewelry

272
00:10:55,000 --> 00:10:57,000
as a gift or for myself.

273
00:10:57,000 --> 00:10:59,000
Imagine that you can now

274
00:10:59,000 --> 00:11:02,000
engage with a brand

275
00:11:02,000 --> 00:11:04,000
and interact,

276
00:11:04,000 --> 00:11:07,000
so that you can pass your personal attributes

277
00:11:07,000 --> 00:11:11,000
to the products that you're about to buy.

278
00:11:11,000 --> 00:11:13,000
You can today

279
00:11:13,000 --> 00:11:15,000
download a product with software like this,

280
00:11:15,000 --> 00:11:17,000
view the product in 3D.

281
00:11:17,000 --> 00:11:19,000
This is the sort of 3D data

282
00:11:19,000 --> 00:11:21,000
that a machine will read.

283
00:11:21,000 --> 00:11:23,000
This is a lamp.

284
00:11:23,000 --> 00:11:25,000
And you can start iterating the design.

285
00:11:25,000 --> 00:11:27,000
You can direct what color that product will be,

286
00:11:27,000 --> 00:11:29,000
perhaps what material.

287
00:11:29,000 --> 00:11:32,000
And also, you can engage in shape manipulation of that product,

288
00:11:32,000 --> 00:11:34,000
but within boundaries that are safe.

289
00:11:34,000 --> 00:11:37,000
Because obviously the public are not professional product designers.

290
00:11:37,000 --> 00:11:40,000
The piece of software will keep an individual

291
00:11:40,000 --> 00:11:44,000
within the bounds of the possible.

292
00:11:44,000 --> 00:11:46,000
And when somebody is ready to purchase the product

293
00:11:46,000 --> 00:11:48,000
in their personalized design,

294
00:11:48,000 --> 00:11:51,000
they click "Enter" and this data gets converted

295
00:11:51,000 --> 00:11:55,000
into the data that a 3D printer reads

296
00:11:55,000 --> 00:12:00,000
and gets passed to a 3D printer,

297
00:12:00,000 --> 00:12:03,000
perhaps on someone's desktop.

298
00:12:03,000 --> 00:12:05,000
But I don't think that that's immediate.

299
00:12:05,000 --> 00:12:07,000
I don't think that will happen soon.

300
00:12:07,000 --> 00:12:09,000
What's more likely, and we're seeing it today,

301
00:12:09,000 --> 00:12:11,000
is that data gets sent

302
00:12:11,000 --> 00:12:13,000
to a local manufacturing center.

303
00:12:13,000 --> 00:12:16,000
This means lower carbon footprint.

304
00:12:16,000 --> 00:12:19,000
We're now, instead of shipping a product across the world,

305
00:12:19,000 --> 00:12:21,000
we're sending data across the Internet.

306
00:12:21,000 --> 00:12:24,000
Here's the product being built.

307
00:12:24,000 --> 00:12:26,000
You can see, this came out of the machine in one piece

308
00:12:26,000 --> 00:12:28,000
and the electronics were inserted later.

309
00:12:28,000 --> 00:12:30,000
It's this lamp, as you can see here.

310
00:12:30,000 --> 00:12:32,000
So as long as you have the data,

311
00:12:32,000 --> 00:12:34,000
you can create the part on demand.

312
00:12:34,000 --> 00:12:36,000
And you don't necessarily need to use this

313
00:12:36,000 --> 00:12:38,000
for just aesthetic customization,

314
00:12:38,000 --> 00:12:40,000
you can use it for functional customization,

315
00:12:40,000 --> 00:12:42,000
scanning parts of the body

316
00:12:42,000 --> 00:12:44,000
and creating things that are made to fit.

317
00:12:44,000 --> 00:12:47,000
So we can run this through to something like prosthetics,

318
00:12:47,000 --> 00:12:50,000
which is highly specialized to an individual's handicap.

319
00:12:50,000 --> 00:12:54,000
Or we can create very specific prosthetics

320
00:12:54,000 --> 00:12:56,000
for that individual.

321
00:12:56,000 --> 00:12:58,000
Scanning teeth today,

322
00:12:58,000 --> 00:13:00,000
you can have your teeth scanned

323
00:13:00,000 --> 00:13:02,000
and dental coatings made in this way to fit you.

324
00:13:02,000 --> 00:13:04,000
While you wait at the dentist,

325
00:13:04,000 --> 00:13:07,000
a machine will quietly be creating this for you

326
00:13:07,000 --> 00:13:09,000
ready to insert in the teeth.

327
00:13:09,000 --> 00:13:13,000
And the idea of now creating implants,

328
00:13:13,000 --> 00:13:16,000
scanning data, an MRI scan of somebody

329
00:13:16,000 --> 00:13:18,000
can now be converted into 3D data

330
00:13:18,000 --> 00:13:22,000
and we can create very specific implants for them.

331
00:13:22,000 --> 00:13:24,000
And applying this

332
00:13:24,000 --> 00:13:26,000
to the idea of building up what's in our bodies.

333
00:13:26,000 --> 00:13:29,000
You know, this is pair of lungs and the bronchial tree.

334
00:13:29,000 --> 00:13:31,000
It's very intricate.

335
00:13:31,000 --> 00:13:33,000
You couldn't really create this or simulate it in any other way.

336
00:13:33,000 --> 00:13:35,000
But with MRI data,

337
00:13:35,000 --> 00:13:37,000
we can just build the product,

338
00:13:37,000 --> 00:13:39,000
as you can see, very intricately.

339
00:13:41,000 --> 00:13:43,000
Using this process,

340
00:13:43,000 --> 00:13:46,000
pioneers in the industry are layering up cells today.

341
00:13:46,000 --> 00:13:49,000
So one of the pioneers, for example, is Dr. Anthony Atala,

342
00:13:49,000 --> 00:13:51,000
and he has been working

343
00:13:51,000 --> 00:13:53,000
on layering cells to create body parts --

344
00:13:53,000 --> 00:13:57,000
bladders, valves, kidneys.

345
00:13:57,000 --> 00:13:59,000
Now this is not something that's ready for the public,

346
00:13:59,000 --> 00:14:02,000
but it is in working progress.

347
00:14:02,000 --> 00:14:04,000
So just to finalize, we're all individual.

348
00:14:04,000 --> 00:14:07,000
We all have different preferences, different needs.

349
00:14:07,000 --> 00:14:09,000
We like different things.

350
00:14:09,000 --> 00:14:11,000
We're all different sizes and our companies the same.

351
00:14:11,000 --> 00:14:13,000
Businesses want different things.

352
00:14:13,000 --> 00:14:15,000
Without a doubt in my mind,

353
00:14:15,000 --> 00:14:17,000
I believe that this technology

354
00:14:17,000 --> 00:14:19,000
is going to cause a manufacturing revolution

355
00:14:19,000 --> 00:14:22,000
and will change the landscape of manufacturing as we know it.

356
00:14:22,000 --> 00:14:24,000
Thank you.

357
00:14:24,000 --> 00:14:28,000
(Applause)