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  • On March 10, 2011,

  • I was in Cambridge at the MIT Media Lab

  • meeting with faculty, students and staff,

  • and we were trying to figure out whether

  • I should be the next director.

  • That night, at midnight,

  • a magnitude 9 earthquake

  • hit off of the Pacific coast of Japan.

  • My wife and family were in Japan,

  • and as the news started to come in,

  • I was panicking.

  • I was looking at the news streams

  • and listening to the press conferences

  • of the government officials

  • and the Tokyo Power Company,

  • and hearing about this explosion

  • at the nuclear reactors

  • and this cloud of fallout

  • that was headed towards our house

  • which was only about 200 kilometers away.

  • And the people on TV weren't telling us

  • anything that we wanted to hear.

  • I wanted to know what was going on with the reactor,

  • what was going on with the radiation,

  • whether my family was in danger.

  • So I did what instinctively felt like the right thing,

  • which was to go onto the Internet

  • and try to figure out

  • if I could take matters into my own hands.

  • On the Net, I found there were a lot of other people

  • like me trying to figure out what was going on,

  • and together we sort of loosely formed a group

  • and we called it Safecast,

  • and we decided we were going to try

  • to measure the radiation

  • and get the data out to everybody else,

  • because it was clear that the government

  • wasn't going to be doing this for us.

  • Three years later,

  • we have 16 million data points,

  • we have designed our own Geiger counters

  • that you can download the designs

  • and plug it into the network.

  • We have an app that shows you

  • most of the radiation in Japan and other parts of the world.

  • We are arguably one of the most successful

  • citizen science projects in the world,

  • and we have created

  • the largest open dataset of radiation measurements.

  • And the interesting thing here

  • is how did — (Applause) — Thank you.

  • How did a bunch of amateurs

  • who really didn't know what we were doing

  • somehow come together

  • and do what NGOs and the government

  • were completely incapable of doing?

  • And I would suggest that this has something to do

  • with the Internet. It's not a fluke.

  • It wasn't luck, and it wasn't because it was us.

  • It helped that it was an event

  • that pulled everybody together,

  • but it was a new way of doing things

  • that was enabled by the Internet

  • and a lot of the other things that were going on,

  • and I want to talk a little bit about

  • what those new principles are.

  • So remember before the Internet? (Laughter)

  • I call this B.I. Okay?

  • So, in B.I., life was simple.

  • Things were Euclidian, Newtonian,

  • somewhat predictable.

  • People actually tried to predict the future,

  • even the economists.

  • And then the Internet happened,

  • and the world became extremely complex,

  • extremely low-cost, extremely fast,

  • and those Newtonian laws

  • that we so dearly cherished

  • turned out to be just local ordinances,

  • and what we found was that in this

  • completely unpredictable world

  • that most of the people who were surviving

  • were working with sort of a different set of principles,

  • and I want to talk a little bit about that.

  • Before the Internet, if you remember,

  • when we tried to create services,

  • what you would do is you'd create

  • the hardware layer and the network layer and the software

  • and it would cost millions of dollars

  • to do anything that was substantial.

  • So when it costs millions of dollars to do something substantial,

  • what you would do is you'd get an MBA

  • who would write a plan

  • and get the money

  • from V.C.s or big companies,

  • and then you'd hire the designers and the engineers,

  • and they'd build the thing.

  • This is the Before Internet, B.I., innovation model.

  • What happened after the Internet was

  • the cost of innovation went down so much

  • because the cost of collaboration, the cost of distribution,

  • the cost of communication, and Moore's Law

  • made it so that the cost of trying a new thing

  • became nearly zero,

  • and so you would have Google, Facebook, Yahoo,

  • students that didn't have permission

  • permissionless innovation

  • didn't have permission, didn't have PowerPoints,

  • they just built the thing,

  • then they raised the money,

  • and then they sort of figured out a business plan

  • and maybe later on they hired some MBAs.

  • So the Internet caused innovation,

  • at least in software and services,

  • to go from an MBA-driven innovation model

  • to a designer-engineer-driven innovation model,

  • and it pushed innovation to the edges,

  • to the dorm rooms, to the startups,

  • away from the large institutions,

  • the stodgy old institutions that had the power

  • and the money and the authority.

  • And we all know this. We all know this happened on the Internet.

  • It turns out it's happening in other things, too.

  • Let me give you some examples.

  • So at the Media Lab, we don't just do hardware.

  • We do all kinds of things.

  • We do biology, we do hardware,

  • and Nicholas Negroponte famously said, "Demo or die,"

  • as opposed to "Publish or perish,"

  • which was the traditional academic way of thinking.

  • And he often said, the demo only has to work once,

  • because the primary mode of us impacting the world

  • was through large companies

  • being inspired by us

  • and creating products like the Kindle or Lego Mindstorms.

  • But today, with the ability

  • to deploy things into the real world at such low cost,

  • I'm changing the motto now,

  • and this is the official public statement.

  • I'm officially saying, "Deploy or die."

  • You have to get the stuff into the real world

  • for it to really count,

  • and sometimes it will be large companies,

  • and Nicholas can talk about satellites.

  • (Applause)

  • Thank you.

  • But we should be getting out there ourselves

  • and not depending on large institutions to do it for us.

  • So last year, we sent a bunch of students to Shenzhen,

  • and they sat on the factory floors

  • with the innovators in Shenzhen, and it was amazing.

  • What was happening there

  • was you would have these manufacturing devices,

  • and they weren't making prototypes or PowerPoints.

  • They were fiddling with the manufacturing equipment

  • and innovating right on the manufacturing equipment.

  • The factory was in the designer,

  • and the designer was literally in the factory.

  • And so what you would do is,

  • you'd go down to the stalls

  • and you would see these cell phones.

  • So instead of starting little websites

  • like the kids in Palo Alto do,

  • the kids in Shenzhen make new cell phones.

  • They make new cell phones like kids in Palo Alto

  • make websites,

  • and so there's a rainforest

  • of innovation going on in the cell phone.

  • What they do is, they make a cell phone,

  • go down to the stall, they sell some,

  • they look at the other kids' stuff, go up,

  • make a couple thousand more, go down.

  • Doesn't this sound like a software thing?

  • It sounds like agile software development,

  • A/B testing and iteration,

  • and what we thought you could only do with software

  • kids in Shenzhen are doing this in hardware.

  • My next fellow, I hope, is going to be

  • one of these innovators from Shenzhen.

  • And so what you see is

  • that is pushing innovation to the edges.

  • We talk about 3D printers and stuff like that,

  • and that's great, but this is Limor.

  • She is one of our favorite graduates,

  • and she is standing in front of a Samsung

  • Techwin Pick and Place Machine.

  • This thing can put 23,000 components per hour

  • onto an electronics board.

  • This is a factory in a box.

  • So what used to take a factory full of workers

  • working by hand

  • in this little box in New York,

  • she's able to have effectively

  • She doesn't actually have to go to Shenzhen

  • to do this manufacturing.

  • She can buy this box and she can manufacture it.

  • So manufacturing, the cost of innovation,

  • the cost of prototyping, distribution, manufacturing, hardware,

  • is getting so low

  • that innovation is being pushed to the edges

  • and students and startups are being able to build it.

  • This is a recent thing, but this will happen

  • and this will change

  • just like it did with software.

  • Sorona is a DuPont process

  • that uses a genetically engineered microbe

  • to turn corn sugar into polyester.

  • It's 30 percent more efficient than the fossil fuel method,

  • and it's much better for the environment.

  • Genetic engineering and bioengineering

  • are creating a whole bunch

  • of great new opportunities

  • for chemistry, for computation, for memory.

  • We will probably be doing a lot, obviously doing health things,

  • but we will probably be growing chairs

  • and buildings soon.

  • The problem is, Sorona costs about 400 million dollars

  • and took seven years to build.

  • It kind of reminds you of the old mainframe days.

  • The thing is, the cost of innovation

  • in bioengineering is also going down.

  • This is desktop gene sequencer.

  • It used to cost millions and millions of dollars to sequence genes.

  • Now you can do it on a desktop like this,

  • and kids can do this in dorm rooms.

  • This is Gen9 gene assembler,

  • and so right now when you try to print a gene,

  • what you do is somebody in a factory

  • with pipettes puts the thing together by hand,

  • you have one error per 100 base pairs,

  • and it takes a long time and costs a lot of money.

  • This new device

  • assembles genes on a chip,

  • and instead of one error per 100 base pairs,

  • it's one error per 10,000 base pairs.

  • In this lab, we will have the world's capacity

  • of gene printing within a year,

  • 200 million base pairs a year.

  • This is kind of like when we went

  • from transistor radios wrapped by hand

  • to the Pentium.

  • This is going to become the Pentium of bioengineering,

  • pushing bioengineering into the hands

  • of dorm rooms and startup companies.

  • So it's happening in software and in hardware

  • and bioengineering,

  • and so this is a fundamental new way of thinking about innovation.

  • It's a bottom-up innovation, it's democratic,

  • it's chaotic, it's hard to control.

  • It's not bad, but it's very different,

  • and I think that the traditional rules that we have

  • for institutions don't work anymore,

  • and most of us here

  • operate with a different set of principles.

  • One of my favorite principles is the power of pull,

  • which is the idea of pulling resources

  • from the network as you need them

  • rather than stocking them in the center

  • and controlling everything.

  • So in the case of the Safecast story,