0:00:01.480,0:00:06.016
I thought I would start[br]with a very brief history of cities.

0:00:06.040,0:00:10.616
Settlements typically began[br]with people clustered around a well,

0:00:10.640,0:00:13.974
and the size of that settlement[br]was roughly the distance you could walk

0:00:13.998,0:00:15.936
with a pot of water on your head.

0:00:15.960,0:00:19.456
In fact, if you fly[br]over Germany, for example,

0:00:19.480,0:00:22.480
and you look down and you see[br]these hundreds of little villages,

0:00:22.504,0:00:24.240
they're all about a mile apart.

0:00:24.264,0:00:27.056
You needed easy access to the fields.

0:00:27.080,0:00:30.456
And for hundreds, even thousands of years,

0:00:30.480,0:00:33.056
the home was really the center of life.

0:00:33.080,0:00:35.656
Life was very small for most people.

0:00:35.680,0:00:41.776
It was a center of entertainment,[br]of energy production, of work,

0:00:41.800,0:00:43.016
a center of health care.

0:00:43.040,0:00:46.336
That's where babies were born[br]and people died.

0:00:46.360,0:00:51.216
Then, with industrialization,[br]everything started to become centralized.

0:00:51.240,0:00:55.256
You had dirty factories that were moved[br]to the outskirts of cities.

0:00:55.280,0:00:59.616
Production was centralized[br]in assembly plants.

0:00:59.640,0:01:03.216
You had centralized energy production.

0:01:03.240,0:01:04.935
Learning took place in schools.

0:01:04.959,0:01:07.920
Health care took place in hospitals.

0:01:09.000,0:01:11.016
And then you had networks that developed.

0:01:11.040,0:01:13.656
You had water, sewer networks

0:01:13.680,0:01:17.536
that allowed for this[br]kind of unchecked expansion.

0:01:17.560,0:01:21.176
You had separated functions, increasingly.

0:01:21.200,0:01:22.936
You had rail networks

0:01:22.960,0:01:25.776
that connected residential,[br]industrial, commercial areas.

0:01:25.800,0:01:27.416
You had auto networks.

0:01:27.440,0:01:30.696
In fact, the model was really,[br]give everybody a car,

0:01:30.720,0:01:32.056
build roads to everything,

0:01:32.080,0:01:34.536
and give people a place to park[br]when they get there.

0:01:34.560,0:01:36.256
It was not a very functional model.

0:01:36.280,0:01:38.656
And we still live in that world,

0:01:38.680,0:01:40.816
and this is what we end up with.

0:01:40.840,0:01:42.896
So you have the sprawl of LA,

0:01:42.920,0:01:45.096
the sprawl of Mexico City.

0:01:45.120,0:01:48.216
You have these unbelievable[br]new cities in China,

0:01:48.240,0:01:50.576
which you might call tower sprawl.

0:01:50.600,0:01:51.936
They're all building cities

0:01:51.960,0:01:54.896
on the model that we invented[br]in the '50s and '60s,

0:01:54.920,0:01:56.936
which is really obsolete, I would argue,

0:01:56.960,0:01:59.246
and there are hundreds[br]and hundreds of new cities

0:01:59.270,0:02:01.326
that are being planned all over the world.

0:02:01.350,0:02:05.376
In China alone, 300 million people,[br]some say 400 million people,

0:02:05.400,0:02:07.736
will move to the city[br]over the next 15 years.

0:02:07.760,0:02:10.256
That means building the equivalent

0:02:10.280,0:02:13.096
of the entire built infrastructure[br]of the US in 15 years.

0:02:13.120,0:02:14.336
Imagine that.

0:02:14.360,0:02:19.016
And we should all care about this[br]whether you live in cities or not.

0:02:19.040,0:02:22.616
Cities will account for 90 percent[br]of the population growth,

0:02:22.640,0:02:27.416
80 percent of the global CO2,[br]75 percent of energy use,

0:02:27.440,0:02:29.936
but at the same time[br]it's where people want to be,

0:02:29.960,0:02:31.536
increasingly.

0:02:31.560,0:02:34.376
More than half the people[br]now in the world live in cities,

0:02:34.400,0:02:37.096
and that will just continue to escalate.

0:02:37.120,0:02:40.736
Cities are places of celebration,[br]personal expression.

0:02:40.760,0:02:44.056
You have the flash mobs[br]of pillow fights that --

0:02:44.080,0:02:46.176
I've been to a couple. They're quite fun.

0:02:46.200,0:02:47.416
You have --

0:02:47.440,0:02:48.696
(Laughter)

0:02:48.720,0:02:51.536
Cities are where most[br]of the wealth is created,

0:02:51.560,0:02:55.256
and particularly in the developing world,[br]it's where women find opportunities.

0:02:55.280,0:02:58.696
That's a lot of the reason[br]why cities are growing very quickly.

0:02:58.720,0:03:01.336
Now there's some trends[br]that will impact cities.

0:03:01.360,0:03:04.256
First of all, work is becoming[br]distributed and mobile.

0:03:04.280,0:03:07.896
The office building is basically obsolete[br]for doing private work.

0:03:07.920,0:03:12.296
The home, once again,[br]because of distributed computation --

0:03:12.320,0:03:14.336
Communication is becoming[br]a center of life,

0:03:14.360,0:03:18.536
so it's a center of production[br]and learning and shopping and health care

0:03:18.560,0:03:21.336
and all of these things[br]that we used to think of

0:03:21.360,0:03:24.176
as taking place outside of the home.

0:03:24.200,0:03:27.176
And increasingly,[br]everything that people buy,

0:03:27.200,0:03:28.536
every consumer product,

0:03:28.560,0:03:31.496
in one way or another,[br]can be personalized.

0:03:31.520,0:03:33.936
And that's a very important[br]trend to think about.

0:03:33.960,0:03:36.576
So this is my image[br]of the city of the future.

0:03:37.059,0:03:39.416
(Laughter)

0:03:39.440,0:03:41.696
In that it's a place for people, you know.

0:03:41.720,0:03:44.416
Maybe not the way people dress, but --

0:03:44.440,0:03:45.869
You know, the question now is,

0:03:45.893,0:03:49.336
how can we have all the good things[br]that we identify with cities

0:03:49.360,0:03:51.176
without all the bad things?

0:03:51.200,0:03:52.416
This is Bangalore.

0:03:52.440,0:03:56.496
It took me a couple of hours[br]to get a few miles in Bangalore last year.

0:03:56.520,0:03:59.056
So with cities, you also have[br]congestion and pollution

0:03:59.080,0:04:01.736
and disease and all these negative things.

0:04:01.760,0:04:03.976
How can we have the good stuff[br]without the bad?

0:04:04.000,0:04:06.572
So we went back and started looking[br]at the great cities

0:04:06.596,0:04:08.696
that evolved before the cars.

0:04:08.720,0:04:13.056
Paris was a series of these[br]little villages that came together,

0:04:13.080,0:04:14.976
and you still see that structure today.

0:04:15.000,0:04:17.953
The 20 arrondissements of Paris[br]are these little neighborhoods.

0:04:17.977,0:04:22.696
Most of what people need in life[br]can be within a five- or 10-minute walk.

0:04:22.720,0:04:25.936
And if you look at the data,[br]when you have that kind of a structure,

0:04:25.960,0:04:27.656
you get a very even distribution

0:04:27.680,0:04:31.056
of the shops and the physicians[br]and the pharmacies

0:04:31.080,0:04:32.976
and the cafes in Paris.

0:04:33.000,0:04:35.936
And then you look at cities[br]that evolved after the automobile,

0:04:35.960,0:04:37.696
and it's not that kind of a pattern.

0:04:37.720,0:04:40.736
There's very little[br]that's within a five-minute walk

0:04:40.760,0:04:43.056
of most areas of places like Pittsburgh.

0:04:43.080,0:04:44.336
Not to pick on Pittsburgh,

0:04:44.360,0:04:48.896
but most American cities[br]really have evolved this way.

0:04:48.920,0:04:51.096
So we said, well,[br]let's look at new cities,

0:04:51.120,0:04:55.336
and we're involved in a couple[br]of new city projects in China.

0:04:55.360,0:04:57.816
So we said, let's start[br]with that neighborhood cell.

0:04:57.840,0:04:59.736
We think of it as a compact urban cell.

0:04:59.760,0:05:03.336
So provide most of what most people want[br]within that 20-minute walk.

0:05:03.360,0:05:06.896
This can also be[br]a resilient electrical microgrid,

0:05:06.920,0:05:10.496
community heating, power,[br]communication networks, etc.

0:05:10.520,0:05:12.296
can be concentrated there.

0:05:12.320,0:05:15.176
Stewart Brand would put[br]a micronuclear reactor

0:05:15.200,0:05:17.176
right in the center, probably.

0:05:17.200,0:05:18.656
And he might be right.

0:05:18.680,0:05:22.216
And then we can form,[br]in effect, a mesh network.

0:05:22.240,0:05:25.856
It's something of an Internet[br]typology pattern,

0:05:25.880,0:05:28.376
so you can have a series[br]of these neighborhoods.

0:05:28.400,0:05:29.856
You can dial up the density --

0:05:29.880,0:05:32.376
about 20,000 people per cell,[br]if it's Cambridge.

0:05:32.400,0:05:34.936
Go up to 50,000 if it's Manhattan density.

0:05:34.960,0:05:37.056
You connect everything with mass transit

0:05:37.080,0:05:41.336
and you provide most of what most people[br]need within that neighborhood.

0:05:41.360,0:05:44.576
You can begin to develop[br]a whole typology of streetscapes

0:05:44.600,0:05:47.656
and the vehicles that can go on them.

0:05:47.680,0:05:50.096
I won't go through all of them.[br]I'll just show one.

0:05:50.120,0:05:54.016
This is Boulder. It's a great example[br]of kind of a mobility parkway,

0:05:54.040,0:05:56.776
a superhighway for joggers and bicyclists,

0:05:56.800,0:05:59.324
where you can go from one end[br]of the city to the other

0:05:59.348,0:06:01.096
without crossing the street,

0:06:01.120,0:06:04.896
and they also have bike-sharing,[br]which I'll get into in a minute.

0:06:04.920,0:06:07.096
This is even a more interesting solution

0:06:07.120,0:06:08.336
in Seoul, Korea.

0:06:08.360,0:06:10.776
They took the elevated highway,[br]they got rid of it,

0:06:10.800,0:06:14.416
they reclaimed the street,[br]the river down below,

0:06:14.440,0:06:15.816
below the street,

0:06:15.840,0:06:18.176
and you can go from one end[br]of Seoul to the other

0:06:18.200,0:06:21.856
without crossing a pathway for cars.

0:06:21.880,0:06:25.200
The High Line in Manhattan[br]is very similar.

0:06:26.360,0:06:30.536
You have these rapidly emerging[br]bike lanes all over the world.

0:06:30.560,0:06:32.216
I lived in Manhattan for 15 years.

0:06:32.240,0:06:34.496
I went back a couple of weekends ago,

0:06:34.520,0:06:40.096
took this photograph of these fabulous[br]new bike lanes that they have installed.

0:06:40.120,0:06:42.936
They're still not to where Copenhagen is,

0:06:42.960,0:06:46.376
where something like 42 percent[br]of the trips within the city

0:06:46.400,0:06:47.616
are by bicycle.

0:06:47.640,0:06:51.416
It's mostly just because they have[br]fantastic infrastructure there.

0:06:51.440,0:06:54.136
We actually did exactly[br]the wrong thing in Boston.

0:06:54.160,0:06:56.216
The Big Dig --

0:06:56.240,0:06:58.736
(Laughter)

0:06:58.760,0:07:02.776
So we got rid of the highway[br]but we created a traffic island,

0:07:02.800,0:07:07.496
and it's certainly not a mobility pathway[br]for anything other than cars.

0:07:07.520,0:07:10.256
Mobility on demand is something[br]we've been thinking about,

0:07:10.280,0:07:13.576
so we think we need an ecosystem[br]of these shared-use vehicles

0:07:13.600,0:07:15.696
connected to mass transit.

0:07:15.720,0:07:18.776
These are some of the vehicles[br]that we've been working on.

0:07:18.800,0:07:20.456
But shared use is really key.

0:07:20.480,0:07:24.376
If you share a vehicle, you can have[br]at least four people use one vehicle,

0:07:24.400,0:07:26.256
as opposed to one.

0:07:26.280,0:07:31.200
We have Hubway here in Boston,[br]the Vélib' system in Paris.

0:07:32.760,0:07:37.016
We've been developing,[br]at the Media Lab, this little city car

0:07:37.040,0:07:40.216
that is optimized[br]for shared use in cities.

0:07:40.240,0:07:43.616
We got rid of all the useless things[br]like engines and transmissions.

0:07:43.640,0:07:45.616
We moved everything to the wheels,

0:07:45.640,0:07:47.016
so you have the drive motor,

0:07:47.040,0:07:49.536
the steering motor, the breaking --[br]all in the wheel.

0:07:49.560,0:07:52.736
That left the chassis unencumbered,[br]so you can do things like fold,

0:07:52.760,0:07:58.416
so you can fold this little vehicle up[br]to occupy a tiny little footprint.

0:07:58.440,0:08:01.896
This was a video that was[br]on European television last week

0:08:01.920,0:08:07.536
showing the Spanish Minister of Industry[br]driving this little vehicle,

0:08:07.560,0:08:09.376
and when it's folded, it can spin.

0:08:09.400,0:08:12.656
You don't need reverse.[br]You don't need parallel parking.

0:08:12.680,0:08:14.296
You just spin and go directly in.

0:08:14.320,0:08:15.896
(Laughter)

0:08:15.920,0:08:18.696
So we've been working[br]with a company to commercialize this.

0:08:18.720,0:08:21.816
My PhD student Ryan Chin[br]presented these early ideas

0:08:21.840,0:08:24.496
two years ago at a TEDx conference.

0:08:24.520,0:08:27.016
So what's interesting is,

0:08:27.040,0:08:29.856
then if you begin to add[br]new things to it, like autonomy,

0:08:29.880,0:08:32.655
you get out of the car,[br]you park at your destination,

0:08:32.679,0:08:36.496
you pat it on the butt, it goes[br]and it parks itself, it charges itself,

0:08:36.520,0:08:41.096
and you can get something[br]like seven times as many vehicles

0:08:41.120,0:08:44.456
in a given area as conventional cars,

0:08:44.480,0:08:46.056
and we think this is the future.

0:08:46.080,0:08:49.776
Actually, we could do this today.[br]It's not really a problem.

0:08:49.800,0:08:53.336
We can combine shared use[br]and folding and autonomy

0:08:53.360,0:08:56.656
and we get something[br]like 28 times the land utilization

0:08:56.680,0:08:58.336
with that kind of strategy.

0:08:58.360,0:09:00.218
One of our graduate students then says,

0:09:00.242,0:09:04.376
well, how does a driverless car[br]communicate with pedestrians?

0:09:04.400,0:09:06.576
You have nobody to make eye contact with.

0:09:06.600,0:09:08.736
You don't know[br]if it's going to run you over.

0:09:08.760,0:09:10.336
So he's developing strategies

0:09:10.360,0:09:12.936
so the vehicle can communicate[br]with pedestrians, so --

0:09:12.960,0:09:14.376
(Laughter)

0:09:14.400,0:09:17.336
So the headlights are eyeballs,[br]the pupils can dilate,

0:09:17.360,0:09:21.536
we have directional audio,[br]we can throw sound directly at people.

0:09:21.560,0:09:23.016
What I love about this project

0:09:23.040,0:09:26.656
is he solved a problem[br]that doesn't exist yet, so --

0:09:26.680,0:09:29.616
(Laughter)

0:09:29.640,0:09:33.496
We also think that we can[br]democratize access to bike lanes.

0:09:33.520,0:09:37.416
You know, bike lanes are mostly used[br]by young guys in stretchy pants. So --

0:09:37.440,0:09:38.816
(Laughter)

0:09:38.840,0:09:42.656
We think we can develop a vehicle[br]that operates on bike lanes,

0:09:42.680,0:09:47.656
accessible to elderly and disabled,[br]women in skirts, businesspeople,

0:09:47.680,0:09:50.256
and address the issues[br]of energy congestion, mobility,

0:09:50.280,0:09:52.536
aging and obesity simultaneously.

0:09:52.560,0:09:53.776
That's our challenge.

0:09:53.800,0:09:56.656
This is an early design[br]for this little three-wheel.

0:09:56.680,0:09:58.176
It's an electronic bike.

0:09:58.200,0:10:01.936
You have to pedal[br]to operate it in a bike lane,

0:10:01.960,0:10:04.576
but if you're an older person,[br]that's a switch.

0:10:04.600,0:10:08.376
If you're a healthy person, you might[br]have to work really hard to go fast.

0:10:08.400,0:10:10.696
You can dial in 40 calories[br]going into work

0:10:10.720,0:10:13.376
and 500 going home,[br]when you can take a shower.

0:10:13.400,0:10:17.656
We hope to have that built this fall.

0:10:17.680,0:10:21.056
Housing is another area[br]where we can really improve.

0:10:21.080,0:10:23.256
Mayor Menino in Boston says

0:10:23.280,0:10:26.216
lack of affordable housing[br]for young people

0:10:26.240,0:10:28.976
is one of the biggest[br]problems the city faces.

0:10:29.000,0:10:31.736
Developers say, OK,[br]we'll build little teeny apartments.

0:10:31.760,0:10:36.016
People say, we don't really want to live[br]in a little teeny conventional apartment.

0:10:36.040,0:10:40.096
So we're saying, let's build[br]a standardized chassis,

0:10:40.120,0:10:41.456
much like our car.

0:10:41.480,0:10:46.576
Let's bring advanced technology[br]into the apartment,

0:10:46.600,0:10:49.136
technology-enabled infill,

0:10:49.160,0:10:54.136
give people the tools[br]within this open-loft chassis

0:10:54.160,0:10:55.976
to go through a process of defining

0:10:56.000,0:10:58.936
what their needs[br]and values and activities are,

0:10:58.960,0:11:02.536
and then a matching algorithm[br]will match a unique assembly

0:11:02.560,0:11:04.536
of integrated infill components,

0:11:04.560,0:11:09.656
furniture, and cabinetry,[br]that are personalized to that individual,

0:11:09.680,0:11:11.056
and they give them the tools

0:11:11.080,0:11:13.096
to go through the process[br]and to refine it,

0:11:13.120,0:11:15.496
and it's something like working[br]with an architect,

0:11:15.520,0:11:16.776
where the dialogue starts

0:11:16.800,0:11:21.480
when you give an alternative[br]to a person to react to.

0:11:22.800,0:11:27.496
Now, the most interesting[br]implementation of that for us

0:11:27.520,0:11:29.576
is when you can begin[br]to have robotic walls,

0:11:29.600,0:11:33.416
so your space can convert[br]from exercise to a workplace,

0:11:33.440,0:11:35.176
if you run a virtual company.

0:11:35.200,0:11:36.350
You have guests over,

0:11:36.374,0:11:40.056
you have two guest rooms[br]that are developed.

0:11:40.080,0:11:43.936
You have a conventional[br]one-bedroom arrangement

0:11:43.960,0:11:45.164
when you need it.

0:11:45.188,0:11:46.716
Maybe that's most of the time.

0:11:46.740,0:11:47.896
You have a dinner party.

0:11:47.920,0:11:51.976
The table folds out to fit 16 people[br]in otherwise a conventional one-bedroom,

0:11:52.000,0:11:53.616
or maybe you want a dance studio.

0:11:53.640,0:11:57.056
I mean, architects have been thinking[br]about these ideas for a long time.

0:11:57.080,0:11:59.296
What we need to do now,

0:11:59.320,0:12:04.816
develop things that can scale[br]to those 300 million Chinese people

0:12:04.840,0:12:08.976
that would like to live in the city,[br]and very comfortably.

0:12:09.000,0:12:11.296
We think we can make[br]a very small apartment

0:12:11.320,0:12:16.656
that functions as if it's twice as big[br]by utilizing these strategies.

0:12:16.680,0:12:20.216
I don't believe in smart homes.[br]That's sort of a bogus concept.

0:12:20.240,0:12:23.456
I think you have to build dumb homes[br]and put smart stuff in it.

0:12:23.480,0:12:25.736
(Laughter)

0:12:25.760,0:12:31.176
And so we've been working[br]on a chassis of the wall itself.

0:12:31.200,0:12:32.736
You know, standardized platform

0:12:32.760,0:12:35.536
with the motors and the battery[br]when it operates,

0:12:35.560,0:12:40.096
little solenoids that will lock it[br]in place and get low-voltage power.

0:12:40.120,0:12:41.936
We think this can all be standardized,

0:12:41.960,0:12:45.896
and then people can personalize the stuff[br]that goes into that wall,

0:12:45.920,0:12:48.616
and like the car, we can integrate[br]all kinds of sensing

0:12:48.640,0:12:51.016
to be aware of human activity,

0:12:51.040,0:12:54.336
so if there's a baby[br]or a puppy in the way,

0:12:54.360,0:12:55.576
you won't have a problem.

0:12:55.600,0:12:56.616
(Laughter)

0:12:56.640,0:12:59.376
So the developers say,[br]well, this is great.

0:12:59.400,0:13:03.456
OK, so if we have a conventional building,[br]we have a fixed envelope,

0:13:03.480,0:13:05.536
maybe we can put in 14 units.

0:13:05.560,0:13:07.656
If they function[br]as if they're twice as big,

0:13:07.680,0:13:09.216
we can get 28 units in.

0:13:09.240,0:13:11.265
That means twice as much parking, though.

0:13:11.289,0:13:12.596
Parking's really expensive.

0:13:12.620,0:13:15.256
It's about 70,000 dollars per space

0:13:15.280,0:13:19.056
to build a conventional parking spot[br]inside a building.

0:13:19.080,0:13:22.656
So if you can have folding and autonomy,

0:13:22.680,0:13:25.096
you can do that[br]in one-seventh of the space.

0:13:25.120,0:13:27.296
That goes down to 10,000 dollars per car,

0:13:27.320,0:13:28.896
just for the cost of the parking.

0:13:28.920,0:13:32.856
You add shared use,[br]and you can even go further.

0:13:32.880,0:13:35.936
We can also integrate[br]all kinds of advanced technology

0:13:35.960,0:13:37.176
through this process.

0:13:37.200,0:13:40.336
There's a path to market[br]for innovative companies

0:13:40.360,0:13:42.016
to bring technology into the home.

0:13:42.040,0:13:44.616
In this case, a project[br]we're doing with Siemens.

0:13:44.640,0:13:47.216
We have sensors on all[br]the furniture, all the infill,

0:13:47.240,0:13:49.936
that understands where people are[br]and what they're doing.

0:13:49.960,0:13:51.656
Blue light is very efficient,

0:13:51.680,0:13:55.816
so we have these tunable[br]24-bit LED lighting fixtures.

0:13:55.840,0:13:59.976
It recognizes where the person is,[br]what they're doing,

0:14:00.000,0:14:04.216
fills out the light when necessary[br]to full spectrum white light,

0:14:04.240,0:14:10.456
and saves maybe 30, 40 percent[br]in energy consumption, we think,

0:14:10.480,0:14:15.936
over even conventional[br]state-of-the-art lighting systems.

0:14:15.960,0:14:19.376
This just shows you the data[br]that comes from the sensors

0:14:19.400,0:14:21.096
that are embedded in the furniture.

0:14:21.120,0:14:23.936
We don't really believe in cameras[br]to do things in homes.

0:14:23.960,0:14:27.936
We think these little wireless sensors[br]are more effective.

0:14:27.960,0:14:30.216
We think we can also personalize sunlight.

0:14:30.240,0:14:32.907
That's sort of the ultimate[br]personalization in some ways.

0:14:32.931,0:14:35.896
So we've looked at articulating[br]mirrors of the facade

0:14:35.920,0:14:39.816
that can throw shafts of sunlight[br]anywhere into the space,

0:14:39.840,0:14:42.216
therefore allowing you[br]to shade most of the glass

0:14:42.240,0:14:44.456
on a hot day like today.

0:14:44.480,0:14:46.336
In this case, she picks up her phone,

0:14:46.360,0:14:50.936
she can map food preparation[br]at the kitchen island

0:14:50.960,0:14:53.376
to a particular location of sunlight.

0:14:53.400,0:14:58.576
An algorithm will keep it in that location[br]as long as she's engaged in that activity.

0:14:58.600,0:15:01.517
This can be combined[br]with LED lighting as well.

0:15:02.760,0:15:04.856
We think workplaces should be shared.

0:15:04.880,0:15:07.690
I mean, this is really[br]the workplace of the future, I think.

0:15:07.714,0:15:09.210
This is Starbucks, you know.

0:15:09.234,0:15:10.416
Maybe a third --

0:15:10.440,0:15:12.696
And you see everybody[br]has their back to the wall

0:15:12.720,0:15:14.720
and they have food and coffee down the way

0:15:14.744,0:15:17.176
and they're in their own[br]little personal bubble.

0:15:17.200,0:15:19.896
We need shared spaces[br]for interaction and collaboration.

0:15:19.920,0:15:22.136
We're not doing a very good job with that.

0:15:22.160,0:15:26.216
At the Cambridge Innovation Center,[br]you can have shared desks.

0:15:26.240,0:15:30.936
I've spent a lot of time in Finland[br]at the design factory of Aalto University,

0:15:30.960,0:15:35.656
where the they have a shared shop[br]and shared fab lab, shared quiet spaces,

0:15:35.680,0:15:39.816
electronics spaces, recreation places.

0:15:39.840,0:15:43.296
We think ultimately,[br]all of this stuff can come together,

0:15:43.320,0:15:47.016
a new model for mobility,[br]a new model for housing,

0:15:47.040,0:15:49.336
a new model for how we live and work,

0:15:49.360,0:15:52.176
a path to market[br]for advanced technologies.

0:15:52.200,0:15:55.105
But in the end, the main thing[br]we need to focus on are people.

0:15:55.129,0:15:56.696
Cities are all about people.

0:15:56.720,0:15:58.736
They're places for people.

0:15:58.760,0:16:01.216
There's no reason[br]why we can't dramatically improve

0:16:01.240,0:16:03.536
the livability and creativity of cities

0:16:03.560,0:16:07.456
like they've done in Melbourne[br]with the laneways

0:16:07.480,0:16:12.056
while at the same time[br]dramatically reducing CO2 and energy.

0:16:12.080,0:16:15.416
It's a global imperative.[br]We have to get this right.

0:16:15.440,0:16:16.656
Thank you.

0:16:16.680,0:16:21.200
(Applause)