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Enjoy!

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In the next 20 years, we're about to see

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what may turn out to
be the biggest changes

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to the way we live in human history.

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I'm James Burke, and I'm
gonna take you on a journey

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through time, joining
up about 10 connections,

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charting the people, objects, and ideas

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that change history in
the most surprising ways.

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(exciting music)

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To tell you the incredible
story of how we got here

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and where we're going next.

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This series is about the process of change

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and why the future is being
shaped by everything we do

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and is not going to be what we expect.

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Because that's the way change happens.

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Cause and effect, you
innovate to solve a problem,

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and even if you succeed,

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there's always an unexpected
outcome that triggers a need

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for another innovation, and so on.

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That's why nobody in the past
knew what was coming next.

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No one knew the sequence of connections

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leads like a falling set of
dominoes to an innovation

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that's set to transform human kind.

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So where do we want to go from here?

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What's the next connection?

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Watch Online Movies and Series for FREE
www.osdb.link/lm

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This is where we're headed, a
quantum computer so powerful

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that one day it will be able
to take colossal amounts

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of data, process it,
and predict the future.

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Because everything can be predicted,

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down to the clothes you
chose to wear today,

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which was dependent on
fashion, the weather,

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your income, your friend's clothes,

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what advertisements you watch, and so on.

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If all that data could be crunched,

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you could have eliminated
all other possibilities

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and predicted that choice of yours.

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Analyze data like that on a massive scale,

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and you can foresee how entire populations

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will interact and change,
triggering social unrest, strikes,

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elections, economics, stocks and shares,

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all the information
that leads to any event.

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All you need are computers
of unimaginable power

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looking into the future
like time machines.

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So to see how we're going
to get to this real life

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time machine, we're going
back in time, over 200 years,

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to the Emperor of France's
toothpick in 1814.

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See, that's when a coalition of allies,

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including Austria, Russia,
and the United Kingdom

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finally beat the Emperor of the French.

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You may have heard of him,

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he goes by the name of Napoleon Bonaparte.

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Now, Napoleon is a bit of a trouble maker.

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He and his French Army are busy invading

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surrounding countries so
he can take over Europe.

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And it takes everything Europe has

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to stop him, capture him,
and ship him off to somewhere

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he can't cause anymore trouble.

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The first solution, the
Italian island of Elba,

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which doesn't do the
job because he escapes

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and starts all over again.

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And they have to stop him all over again.

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The second time around, they
give some serious thought

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to an island it would be
really hard for Napoleon

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to get away from, like this one.

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A tiny dot as far from
anywhere as you can get,

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an island in the Mid-Atlantic
called Saint Helena,

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population too small to count.

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So where on this tiny dot to put the man

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who used to rule Europe?

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The best house standing on
the island of Saint Helena

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at the time is this place,
a property said to be

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particularly cold, uninviting,
and infested with rats.

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Not much of a residence for an ex-Emperor.

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But Napoleon still has
friends in high places,

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sympathizers in the British
government to be precise,

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and so he gets preferential treatment

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even though he has no power.

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They decide to fill his residence

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with the most amazing and ornate stuff

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they can get their hands
on to make him feel

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a bit more at home.

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Care of one of England's top
designers and furniture makers,

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name of George Bullock,
who's contracted to provide

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everything needed for the man
who used to have everything.

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Take a look at some of the
stuff Bullock produces,

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mahogany cabinets from the Americas,

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marble top tables from Wales,

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elegant silk covering
English chairs, card tables,

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book cases, bell poles to call
the servants in every room,

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writing desks with paper and ink,

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where Napoleon wrote his autobiography,

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the best seller of the
entire 19th century.

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And everywhere, Napoleon's
favorite color, green.

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Plus among thousands of other things,

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a billiard table, ivory
handled cheese scoops,

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24 nutcrackers, two mustard
pots, six wine coolers,

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84 toothbrushes, and you
guessed it, 132 toothpicks.

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And we know all this because
of the detailed bill,

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for almost a million
bucks in modern money,

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presented by George Bullock.

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Bullock takes inspiration for his designs

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from cultures all over the world.

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Back in England, he
famously ran a show room

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called the Grecian Rooms,
themed, you guessed it,

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on ancient Greece.

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This enthusiasm for
other people and places

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is also shared by his brother, William.

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Now this is a time when almost
nobody can afford to travel

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much beyond their own borders.

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So William sees an opportunity,

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and through artifacts,
brings the world to them.

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In 1809, William opens a museum in London

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and employs the novel
idea of using back drops

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and furnishings to create
an appropriate setting

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for each exhibit, just
like his brother did

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for Napoleon in his fake palace.

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Ironically in 1816, William
brings Napoleon's former world

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to the masses, exhibiting the ex-Emperor's

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original possessions,
including his carriage

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captured in battle.

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Talk about come up'ns.

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Bullock adds people to his
exhibitions to add authenticity,

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like a family of Laplanders with reindeer.

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There's even mummies with hieroglyphs.

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In 1823, a trip to Mexico
gets William enough stuff

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to open an ancient and
modern Mexico Exhibition

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the following year,

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complete with a real Mexican by the name

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of Jose Cayetana Ponce de Leon.

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He speaks his native language, of course,

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but he also speaks Italian and English

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to enthrall thousands
of visitors with tales

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of the Aztec King Moctezuma

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And including plastic cast models

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of Aztec sacrificial sterns, pyramids,

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and Montezuma's stone calendar,

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as well as 43 glass cases stuffed with

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prickly pear cactus,
bananas, avocados, and so on.

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The show ends up getting
more than 50,000 visitors.

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This first of it's kind view of Mexico

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totally blows away the
London chattering classes.

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Most of all, the star of
the show, a hummingbird,

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stuffed of course because
nobody ever manages

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to get the birds back to England alive.

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William is by now a fellow
of the Linnean Society,

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pioneering a new natural
history classification system,

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one we see in museums to this day.

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So where are we?

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Bear in mind that we're
heading for a computer

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that can predict anything.

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Napoleon is defeated and
incarcerated in Saint Helena,

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where his new home is filled with stuff

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from English designer George Bullock,

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who's brother brings the world to London

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in the form of his living museums,

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popular with the public keen
to experience the world.

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This culminates with
the first view of Mexico

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and introduces the Victoria's
to the startling hummingbird,

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which kicks off a Victorian craze.

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The biggest hummingbird
collection of more than 200 kinds

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ends up belonging to a guy
called George Loddiges.

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He's nuts about them, can't get enough.

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He writes the book on little hummingbirds

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to spread the word, but
it never gets published.

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His efforts are rewarded though

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because the hummingbird name, Loddigesia,

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used to this day, is so-called after him.

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Not content with hummingbirds,

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Loddiges also classifies plants.

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See, he's also a
nursery-man who's taken over

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his father's seed business
and grows thousands

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of plant varieties in his
horticultural gardens.

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He creates nearly 2,000 plates of plants

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in the nursery's own catalog,
"The Botanical Cabinet",

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which is published every
month starting in 1817.

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Loddiges's pal, Nathaniel
Ward, is also a serious

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plant person himself,
who also collects things

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in glass jars.

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And this is where a
friendship reshapes the entire

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global economy, and it all
happens because of an accident.

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Ward is a London doctor with
a perfectly understandable

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fixation for the sphinx
moth cocoon, and why not.

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Ward keeps the moths, among other things,

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in a sealed bottle with
leaves and moss soil.

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And then one day he
discovers that something odd

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is going on in the jar.

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Condensation is forming on the inside

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and has dripped down into the soil,

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which then germinates a fern spore.

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Ward has inadvertently
created a mini ecosystem

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without the need for watering.

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Ward has a eureka moment
and gets a carpenter

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to knock together a new version of a jar.

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Take a look.

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This little innovation
is going to be called

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the Wardian Case is
made of wood and glass.

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It's like a small greenhouse, see.

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Much bigger than the original jar,

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it can carry 28 plants.

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Ward tells his friend, Loddiges,

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who jumps at the chance to
expand his plant collection.

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Loddiges constructs 500 Wardian Cases

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to send plants to and get plants back from

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places like Australia.

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A six month trip each way
and the plants survive.

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No hum to you, but back then
this knocks the socks off

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horticulturalists everywhere.

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Because at the time, most
people had never laid eyes

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on exotic plants before because up to then

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plants had been impossible to ship.

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The salty air, lack of
light and fresh water

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kills them off.

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But now, Loddiges's global
plant distribution network

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enables him to fill his nursery garden

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with stuff nobody's
ever seen and sell them,

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making himself a fortune.

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Loddiges also owns the
world's biggest hothouse

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in North London, then
called The Grand Palm House.

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There are no other green houses

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anywhere on this kind of scale.

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At 40 foot high, the place can
hold a full-scale palm tree

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and is filled to the roof with palms,

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ferns, and exotic plants,

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including a brand new type of orchid

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brought all the way from
Mexico watered and alive

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in Wardian cases.

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It's name of course, Acropera loddigesii.

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Sprinklers in the Palm House
roof replicate the conditions

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showering tropical mist
and rain on the plants.

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Crowds of visitors come
to stare at the spectacle.

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Even Charles Darwin turns up
and must have been blown away

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by visible proof of his theory
of evolution through variety

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with all the varieties of
rose in George's gardens,

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1,279 to be precise.

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Now, the Wardian Case, it's
about to change the future

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in a big way thanks to
international espionage,

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economics, politics,
and a part of the world

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still closed to the West, China.

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See, in the early 19th century,

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China is pretty much
the only major producer

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of the one beverage no
Brit can do without, tea.

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Britain is exporting
so much silver to China

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to pay for the tea, the
British government is scared

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00:14:02,520 --> 00:14:06,420
the U.K. will go broke, while
China, with its tea monopoly,

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looks like becoming the
world's economic super power.

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This is why in 1848, a
rather unscrupulous outfit

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called the British government
backed East India Company,

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are looking for another way
to solve the tea problem,

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00:14:21,060 --> 00:14:22,473
but pay less for it.

251
00:14:23,674 --> 00:14:27,510
And as I said, they come
across a little Wardian Case.

252
00:14:27,510 --> 00:14:30,450
Quick as a flash, they hire a solution,

253
00:14:30,450 --> 00:14:32,973
Scottish botanist Robert Fortune.

254
00:14:34,800 --> 00:14:37,800
They sent him on a
secret mission to China,

255
00:14:37,800 --> 00:14:39,783
equipped with dozens of cases.

256
00:14:41,940 --> 00:14:45,450
It is a secret mission
because China's interior

257
00:14:45,450 --> 00:14:47,550
is closed to all foreigners.

258
00:14:47,550 --> 00:14:49,530
And Fortune has to wear a pigtail

259
00:14:49,530 --> 00:14:53,130
and dress up in Chinese clothes
and speak fractured Mandarin

260
00:14:53,130 --> 00:14:54,870
as if he comes from some remote province

261
00:14:54,870 --> 00:14:57,930
a long way from where he
is in China at the time

262
00:14:57,930 --> 00:15:00,210
and travel with a Chinese servant

263
00:15:00,210 --> 00:15:02,373
to handle the really
complicated sentences.

264
00:15:06,570 --> 00:15:10,410
In 1848, Fortune turns up
outside a big tea factory

265
00:15:10,410 --> 00:15:13,950
supplying Shanghai, and
the factory boss is asked

266
00:15:13,950 --> 00:15:16,530
if this honorable person
might be allowed in

267
00:15:16,530 --> 00:15:18,543
to see how their wonderful tea is made.

268
00:15:20,610 --> 00:15:22,773
This is what Fortune sees them doing,

269
00:15:23,730 --> 00:15:28,293
only the greatest of all Chinese
national security secrets.

270
00:15:40,088 --> 00:15:42,450
First, let the tea leaves lie in sunlight

271
00:15:42,450 --> 00:15:43,950
for a couple of hours.

272
00:15:43,950 --> 00:15:46,203
Then stir fry them in a hot wok.

273
00:15:47,910 --> 00:15:49,413
Then roll them back and forth.

274
00:15:51,720 --> 00:15:54,090
Then more stir fry.

275
00:15:54,090 --> 00:15:56,580
Then sort them into tightly wound leaves

276
00:15:56,580 --> 00:15:58,383
and take out any grit or dirt.

277
00:16:00,420 --> 00:16:03,423
And, as they say in Mandarin, bingo.

278
00:16:06,270 --> 00:16:08,340
Now that Fortune knows the secret,

279
00:16:08,340 --> 00:16:10,980
all he has to do is get the
raw material out of China,

280
00:16:10,980 --> 00:16:15,000
which he does, thanks to
the good old Wardian Case.

281
00:16:15,000 --> 00:16:18,750
In 1851, to the tune of
20,000 seedlings and plumes,

282
00:16:18,750 --> 00:16:21,420
smuggled to the northwest
provinces of India

283
00:16:21,420 --> 00:16:25,440
to set up what will become
a new Indian tea industry,

284
00:16:25,440 --> 00:16:28,083
entirely under U.K.
ownership and management.

285
00:16:30,330 --> 00:16:31,563
So, where are we?

286
00:16:32,460 --> 00:16:34,590
Remember, all these
connections are leading us

287
00:16:34,590 --> 00:16:37,203
to a computer that can predict anything.

288
00:16:41,760 --> 00:16:44,640
Napoleon is banished to a remote island,

289
00:16:44,640 --> 00:16:47,610
where his toothpicks are
supplied by George Bullock,

290
00:16:47,610 --> 00:16:50,280
whose brother imports hummingbirds

291
00:16:50,280 --> 00:16:52,020
collected by George Loddiges,

292
00:16:52,020 --> 00:16:55,290
whose pal, Nathaniel Ward,
invents the Wardian Case

293
00:16:55,290 --> 00:16:57,810
that George uses to
set up an international

294
00:16:57,810 --> 00:16:59,643
plant distribution network.

295
00:17:00,651 --> 00:17:02,400
This transforms horticulture in Britain

296
00:17:02,400 --> 00:17:05,820
and inspires the British
government to steal tea from China

297
00:17:05,820 --> 00:17:07,203
and grow it in India.

298
00:17:08,130 --> 00:17:11,490
Meanwhile, the fuss over
tea has also given rise

299
00:17:11,490 --> 00:17:16,290
to a brief moment of glory,
now about to end, for sailors.

300
00:17:16,290 --> 00:17:18,780
In the shape of some of the
most beautiful sailing ships

301
00:17:18,780 --> 00:17:23,460
ever designed, they have a
shallow draft and sleek bows

302
00:17:23,460 --> 00:17:26,130
and are built, above all, for speed

303
00:17:26,130 --> 00:17:28,653
and a light cargo, like tea.

304
00:17:29,640 --> 00:17:34,050
Known as clippers because they
sail along at quite a clip,

305
00:17:34,050 --> 00:17:36,540
faster than any other kind of ship,

306
00:17:36,540 --> 00:17:39,360
carrying more sail than you
could ever think possible.

307
00:17:39,360 --> 00:17:41,820
With the right wind, these beautiful ships

308
00:17:41,820 --> 00:17:44,160
sometimes hit over 17 knots,

309
00:17:44,160 --> 00:17:46,083
which is like sailing supersonic.

310
00:17:47,190 --> 00:17:50,043
Europe to Asia in just 90 days.

311
00:17:52,170 --> 00:17:54,540
While the clippers are amazing the world,

312
00:17:54,540 --> 00:17:57,450
bigger, less glamorous sailing
ships are also running down

313
00:17:57,450 --> 00:18:00,003
the West African coast, picking up cargo.

314
00:18:01,320 --> 00:18:03,000
The ships have to turn up,

315
00:18:03,000 --> 00:18:04,890
wait for a full hold of cargo,

316
00:18:04,890 --> 00:18:06,150
and then wait for the right wind

317
00:18:06,150 --> 00:18:08,160
to get them back to England.

318
00:18:08,160 --> 00:18:10,530
All this hanging around means
it can take a businessman

319
00:18:10,530 --> 00:18:14,430
back home months to get delivery
of his West African goods,

320
00:18:14,430 --> 00:18:19,323
gum, ivory, gold, ground
nuts, and animal hides,

321
00:18:21,000 --> 00:18:24,000
all goods too heavy and
bulky to fit in a clipper,

322
00:18:24,000 --> 00:18:26,650
but still needed back in
England as soon as possible.

323
00:18:27,630 --> 00:18:30,870
And the West African
cargo that matters most

324
00:18:30,870 --> 00:18:33,963
because it makes the
most profit, palm oil.

325
00:18:37,530 --> 00:18:40,830
Industry needs all the palm oil it can get

326
00:18:40,830 --> 00:18:45,063
for lubrication for
machinery, for candle making,

327
00:18:45,990 --> 00:18:49,473
and above all, food for
a growing workforce.

328
00:18:50,640 --> 00:18:54,570
And as always, with demand like
that waiting for a solution,

329
00:18:54,570 --> 00:18:56,550
necessity is the mother.

330
00:18:56,550 --> 00:18:59,490
In this case, a new kind of ship.

331
00:18:59,490 --> 00:19:03,000
Thanks to one Alfred
Holt, who from a young age

332
00:19:03,000 --> 00:19:05,373
grows up learning about engines.

333
00:19:06,420 --> 00:19:10,650
And then around 1865,
radically changes the future

334
00:19:10,650 --> 00:19:13,293
with his multiple expansion engine.

335
00:19:14,760 --> 00:19:16,470
Here's the amazing engine.

336
00:19:16,470 --> 00:19:19,200
It uses high pressure steam recycled

337
00:19:19,200 --> 00:19:20,940
from one cylinder to another,

338
00:19:20,940 --> 00:19:23,580
ensuring there's no wasted energy.

339
00:19:23,580 --> 00:19:26,610
This generates enough
power to drive pistons

340
00:19:26,610 --> 00:19:28,290
to turn a massive propeller.

341
00:19:28,290 --> 00:19:29,850
No need for wind.

342
00:19:29,850 --> 00:19:32,010
Holt puts this engine
into a new steam ship

343
00:19:32,010 --> 00:19:33,663
called the Agamemnon.

344
00:19:34,500 --> 00:19:37,023
At 309 feet long, it's huge.

345
00:19:38,160 --> 00:19:40,200
Cruising at a constant 10 knots,

346
00:19:40,200 --> 00:19:43,860
it can make the journey to
Asia in less than 60 days.

347
00:19:43,860 --> 00:19:48,390
Suddenly this one ship
can carry over 2,000 tons,

348
00:19:48,390 --> 00:19:51,630
the equivalent cargo of
three of the old clippers.

349
00:19:51,630 --> 00:19:55,143
So the number of traders buying
space goes up exponentially.

350
00:19:56,490 --> 00:19:59,730
And steam ships like this
can go nonstop from England

351
00:19:59,730 --> 00:20:02,850
to the east come storm, rain, or shine,

352
00:20:02,850 --> 00:20:07,850
refuel, and head back, all 15
days faster than a clipper.

353
00:20:08,010 --> 00:20:09,760
No more waiting for the right wind.

354
00:20:10,809 --> 00:20:14,850
(steam engine blowing)

355
00:20:14,850 --> 00:20:16,920
On the West African palm oil run,

356
00:20:16,920 --> 00:20:19,923
cargo ships under sail go out
of business almost overnight.

357
00:20:21,120 --> 00:20:24,150
The new steam ships also
allow access to ports

358
00:20:24,150 --> 00:20:27,063
that sail ships couldn't
reach because of the wind.

359
00:20:28,770 --> 00:20:33,630
In 1800, Britain imports
about 200 tons of palm oil

360
00:20:33,630 --> 00:20:35,250
from West Africa.

361
00:20:35,250 --> 00:20:40,250
By 1850, that figure is
more than 25,000 tons

362
00:20:40,620 --> 00:20:41,643
and rising fast.

363
00:20:44,237 --> 00:20:45,990
Now the great thing about palm oil is

364
00:20:45,990 --> 00:20:48,993
it's easy to grow and
even easier to process.

365
00:20:51,225 --> 00:20:54,390
In West Africa, the local have
been using it for centuries

366
00:20:54,390 --> 00:20:56,193
for food and even medicine.

367
00:20:57,030 --> 00:20:59,790
The fruit is about the size of an olive.

368
00:20:59,790 --> 00:21:01,770
The pulp is where the oil comes from,

369
00:21:01,770 --> 00:21:05,070
and there's lots more than
you can get from animal fat.

370
00:21:05,070 --> 00:21:08,760
So palm oil trees are
extremely productive.

371
00:21:08,760 --> 00:21:11,040
And demand is going to get even bigger

372
00:21:11,040 --> 00:21:13,470
because it turns out one other exciting

373
00:21:13,470 --> 00:21:16,920
and really money making
thing palm oil does,

374
00:21:16,920 --> 00:21:21,363
besides lubrication and
lighting, is make soap.

375
00:21:25,800 --> 00:21:28,080
In 1884, the son of an English grocer,

376
00:21:28,080 --> 00:21:32,610
William Lever and his brother
team up with a local chemist

377
00:21:32,610 --> 00:21:34,770
who's invented a way of making soap

378
00:21:34,770 --> 00:21:38,583
with a mix of palm oil,
cottonseed oil, and glycerin.

379
00:21:39,855 --> 00:21:43,710
This new soap is an instant success,

380
00:21:43,710 --> 00:21:47,310
mainly because the old way
to make soap with animals fat

381
00:21:47,310 --> 00:21:50,253
smells awful and doesn't
give you much of a wash.

382
00:21:51,870 --> 00:21:55,143
Palm oil soap smells nice and
makes a lot of lather, see.

383
00:21:56,100 --> 00:21:59,250
But what matters most is
that Lever's real talent

384
00:21:59,250 --> 00:22:01,020
lies in selling and marketing.

385
00:22:01,020 --> 00:22:03,680
First of all, he produces his new soap

386
00:22:03,680 --> 00:22:07,800
in a small individual
tablet, and he aims it

387
00:22:07,800 --> 00:22:11,013
at ordinary working people
because he makes it cheap.

388
00:22:12,390 --> 00:22:14,460
The soap ends up with the kind of name

389
00:22:14,460 --> 00:22:17,253
you'd never think of, Sunlight.

390
00:22:18,900 --> 00:22:21,390
And Lever puts it in special wrapping,

391
00:22:21,390 --> 00:22:23,973
the first branded laundry soap.

392
00:22:24,840 --> 00:22:25,740
How could he fail?

393
00:22:26,697 --> 00:22:29,280
(upbeat music)

394
00:22:35,625 --> 00:22:40,320
Within a decade, Sunlight Soap
is selling in 134 countries,

395
00:22:40,320 --> 00:22:44,493
along with two over Lever
washing products, Lux and Vim.

396
00:22:45,990 --> 00:22:48,960
Here's one of our unintended
consequences again,

397
00:22:48,960 --> 00:22:52,293
one that forms a beginning
of a society that can be

398
00:22:52,293 --> 00:22:54,840
educated, sheltered, and cared for.

399
00:22:54,840 --> 00:22:57,480
See, demand is so great
that Lever has an idea.

400
00:22:57,480 --> 00:23:01,023
How about housing the workers
next to his factories.

401
00:23:02,070 --> 00:23:04,770
In 1888, Lever begins
to build a model village

402
00:23:04,770 --> 00:23:09,448
for workers in Cheshire
and called Port Sunlight.

403
00:23:13,590 --> 00:23:17,220
700 cottages, one of them a
copy of Shakespeare's birthplace

404
00:23:17,220 --> 00:23:20,020
would you believe, but with
running water and bathrooms.

405
00:23:21,120 --> 00:23:26,100
And in a new piece of social
change, schools for 500 kids,

406
00:23:26,100 --> 00:23:30,180
as well as a concert hall
and theater, library, gym,

407
00:23:30,180 --> 00:23:31,530
and open-air swimming pool.

408
00:23:33,030 --> 00:23:36,150
Rent is one fifth the weekly wage.

409
00:23:36,150 --> 00:23:38,760
Social activities are available.

410
00:23:38,760 --> 00:23:43,380
It works, the factory produces
up to 5,000 tons of soap

411
00:23:43,380 --> 00:23:46,290
a week, but there's a downside.

412
00:23:46,290 --> 00:23:48,633
Lose your job and you lose your house.

413
00:23:50,100 --> 00:23:52,620
So halfway through our connections,

414
00:23:52,620 --> 00:23:54,870
leading us to the future where machines

415
00:23:54,870 --> 00:23:57,543
can predict anything,
let's see where we are.

416
00:23:59,700 --> 00:24:02,490
Napoleon's banishment and his furniture,

417
00:24:02,490 --> 00:24:05,253
hummingbirds, the Wardian Case,

418
00:24:06,188 --> 00:24:11,188
Chinese tea grows in
India as well as China,

419
00:24:11,220 --> 00:24:14,310
the British economy goes
into industrial overdrive,

420
00:24:14,310 --> 00:24:17,730
and surging demand to speed
up sailing ship imports

421
00:24:17,730 --> 00:24:19,503
triggers Holt's new steam engine.

422
00:24:21,780 --> 00:24:25,740
Imports pour in, especially palm oil,

423
00:24:25,740 --> 00:24:29,493
which Lever and his brother
use to create Sunlight Soap.

424
00:24:32,497 --> 00:24:35,160
(horses whinnying)

425
00:24:35,160 --> 00:24:38,160
By 1898, Lever has
himself one of the first

426
00:24:38,160 --> 00:24:41,070
modern multi-national companies.

427
00:24:41,070 --> 00:24:43,260
His challenge now is to break into

428
00:24:43,260 --> 00:24:45,243
the lucrative American market.

429
00:24:46,230 --> 00:24:47,940
And here's where we take a turn towards

430
00:24:47,940 --> 00:24:50,190
our ability to predict the future.

431
00:24:50,190 --> 00:24:53,163
It all starts with the
power of persuasion.

432
00:24:54,150 --> 00:24:58,770
See this, a soda cracker
with an interesting name.

433
00:24:58,770 --> 00:25:03,270
I'll spell it, U-N-E-E-D-A.

434
00:25:03,270 --> 00:25:05,133
Pronounce it and you'll see why.

435
00:25:06,540 --> 00:25:10,230
The tag is, "Do you know uneeda biscuit?"

436
00:25:10,230 --> 00:25:12,150
If ever there's a hint
of what's going to happen

437
00:25:12,150 --> 00:25:13,953
in the future, it's this.

438
00:25:15,030 --> 00:25:17,040
The story goes in 1898,

439
00:25:17,040 --> 00:25:19,920
a firm of biscuit makers called Nabisco

440
00:25:19,920 --> 00:25:23,550
hires the first advertising
agency, N.W. Ayer,

441
00:25:23,550 --> 00:25:25,230
to think of a name for a soda cracker

442
00:25:25,230 --> 00:25:27,540
the company wants to put on the market.

443
00:25:27,540 --> 00:25:30,180
Ayer comes up with a name, Uneeda.

444
00:25:30,180 --> 00:25:31,680
And two years later, they're selling

445
00:25:31,680 --> 00:25:34,890
10 million packets a month
and have to open new factories

446
00:25:34,890 --> 00:25:36,153
to keep up with demand.

447
00:25:39,030 --> 00:25:43,050
So in 1903, Lever tries an
experimental marketing approach

448
00:25:43,050 --> 00:25:48,050
of his own, he tries the
idea of soap and science.

449
00:25:48,240 --> 00:25:52,027
Soap in a lab, and adopts the tag line,

450
00:25:52,027 --> 00:25:55,530
"Expert Chemists Test Each Batch".

451
00:25:55,530 --> 00:25:58,230
What we're seeing here
is one of the world's

452
00:25:58,230 --> 00:26:00,600
first advertising campaigns.

453
00:26:00,600 --> 00:26:02,850
So rather than just coming
up with an attractive name

454
00:26:02,850 --> 00:26:05,610
for your product, like Sunlight for soap,

455
00:26:05,610 --> 00:26:08,100
and packaging to make your
product more attractive,

456
00:26:08,100 --> 00:26:11,490
now you also tell your prospective buyers

457
00:26:11,490 --> 00:26:13,650
it's going to improve their lives.

458
00:26:13,650 --> 00:26:16,950
And notice the idea of wear and tear

459
00:26:16,950 --> 00:26:20,130
and having to scrub
hard with ordinary soaps

460
00:26:20,130 --> 00:26:22,620
because around this time,
Lever also starts persuading

461
00:26:22,620 --> 00:26:26,250
women customers that
his soap will save them

462
00:26:26,250 --> 00:26:28,923
from the daily drudgery
that puts years on them.

463
00:26:36,043 --> 00:26:37,560
And as early as 1896,

464
00:26:37,560 --> 00:26:41,760
Lever pioneers the first
example of product placement.

465
00:26:41,760 --> 00:26:43,110
And how does he do it?

466
00:26:43,110 --> 00:26:47,400
Well, surreptitiously in a
film by the Lumière brothers,

467
00:26:47,400 --> 00:26:50,790
in this case, of a family
washing clothes in a tub

468
00:26:50,790 --> 00:26:52,590
in their garden.

469
00:26:52,590 --> 00:26:55,593
Note the boxes of Sunlight
Soap in the foreground.

470
00:26:58,500 --> 00:27:00,990
Lever also puts advertising
for his products

471
00:27:00,990 --> 00:27:04,440
on roadside billboards,
at railroad stations,

472
00:27:04,440 --> 00:27:05,763
and in local papers.

473
00:27:06,990 --> 00:27:08,880
And then in the 1920s and 30s comes

474
00:27:08,880 --> 00:27:13,391
an advertising game changer, radio.

475
00:27:18,330 --> 00:27:20,820
Thanks to a new kind of
program that is soon getting

476
00:27:20,820 --> 00:27:24,540
big audiences in the form
of a series of radio shows,

477
00:27:24,540 --> 00:27:27,810
both weekly and daily, all about the lives

478
00:27:27,810 --> 00:27:30,330
of the glamorous
characters whose goings on

479
00:27:30,330 --> 00:27:34,500
are complicated enough for
you to tune into the next show

480
00:27:34,500 --> 00:27:35,900
to see what happens to them.

481
00:27:37,080 --> 00:27:41,340
Lever funds these shows by way
of sponsorship for a price.

482
00:27:41,340 --> 00:27:44,160
They get product placement in the shows.

483
00:27:44,160 --> 00:27:46,170
Most of the other companies
sponsoring these shows

484
00:27:46,170 --> 00:27:49,080
are also in the business
of washing materials,

485
00:27:49,080 --> 00:27:54,030
so the new radio shows
become known as soap operas.

486
00:27:54,030 --> 00:27:56,880
Here's a bit of one of the earliest shows.

487
00:27:56,880 --> 00:27:58,350
Good
morning, radio listeners.

488
00:27:58,350 --> 00:28:01,743
Clara Lou and Em, brought to
you by Colgate Palm Olive,

489
00:28:02,735 --> 00:28:03,720
the makers of Palm Olive soap.

490
00:28:03,720 --> 00:28:06,000
I wish that you would
try this splendid soap

491
00:28:06,000 --> 00:28:07,350
for just 30 days.

492
00:28:07,350 --> 00:28:09,720
You'll want to use it always after that.

493
00:28:09,720 --> 00:28:12,300
Now, since sponsorship
advertising isn't cheap,

494
00:28:12,300 --> 00:28:13,770
it triggers a lot of questions

495
00:28:13,770 --> 00:28:16,050
that the sponsors need answers to.

496
00:28:16,050 --> 00:28:18,600
What are we getting for our money?

497
00:28:18,600 --> 00:28:21,660
I mean, are you getting a big
audience for your product?

498
00:28:21,660 --> 00:28:23,100
What kind of audience?

499
00:28:23,100 --> 00:28:25,080
What shows do people listen to?

500
00:28:25,080 --> 00:28:29,100
What time of day or week and for how long?

501
00:28:29,100 --> 00:28:33,453
Above all, basically
does radio sell product?

502
00:28:35,040 --> 00:28:37,530
That last question from the
Lever advertising manager

503
00:28:37,530 --> 00:28:41,100
in the U.S. catches the interest
of a couple of MIT types

504
00:28:41,100 --> 00:28:43,983
called Robert Elder and Louis Woodruff.

505
00:28:45,000 --> 00:28:48,000
And in 1936, they patent the solution.

506
00:28:48,000 --> 00:28:50,620
Survey the audience electronically

507
00:28:51,840 --> 00:28:54,243
with a gizmo called an Audimeter.

508
00:28:57,570 --> 00:28:58,570
Here's what it does.

509
00:29:00,143 --> 00:29:01,590
The radio has a dial you turn

510
00:29:01,590 --> 00:29:03,333
to tune to the station you want.

511
00:29:04,200 --> 00:29:06,240
The radio is linked to the Audimeter,

512
00:29:06,240 --> 00:29:09,750
which is fitted with gears
and connected to the dial.

513
00:29:09,750 --> 00:29:12,780
As you turn the dial, the Audimeter arm,

514
00:29:12,780 --> 00:29:14,280
with a pen on the end of it,

515
00:29:14,280 --> 00:29:17,460
moves across a slowly
unrolling strip of paper

516
00:29:17,460 --> 00:29:20,310
and stops once the station is chosen.

517
00:29:20,310 --> 00:29:22,320
And then the paper goes on rolling

518
00:29:22,320 --> 00:29:25,470
and the pen keeps marking a
continuous line on the paper,

519
00:29:25,470 --> 00:29:27,633
indicating how long they listened for.

520
00:29:28,560 --> 00:29:32,130
And it will do all this
till the paper runs out,

521
00:29:32,130 --> 00:29:33,660
which takes a month.

522
00:29:33,660 --> 00:29:36,660
At which point, the audience
research people turn up

523
00:29:36,660 --> 00:29:38,403
and take the roll for analysis.

524
00:29:43,560 --> 00:29:47,190
All this is described in a
presentation by Robert Elder

525
00:29:47,190 --> 00:29:49,500
during a meeting of the
Market Research Council

526
00:29:49,500 --> 00:29:50,913
at the New York Yale Club.

527
00:29:54,270 --> 00:29:55,890
And one of the people in the audience,

528
00:29:55,890 --> 00:30:00,420
who has a lovely idea, is a
chap called Arthur Nielsen,

529
00:30:00,420 --> 00:30:01,470
who already has a company

530
00:30:01,470 --> 00:30:04,239
analyzing sales figures for stores.

531
00:30:10,380 --> 00:30:15,380
By 1946, Nielsen has 1,300
Audimeters in 1,100 homes

532
00:30:15,390 --> 00:30:17,190
and has spent nearly 10 years

533
00:30:17,190 --> 00:30:19,173
and two million dollars to get there.

534
00:30:20,097 --> 00:30:21,930
And he's researched all of the families

535
00:30:21,930 --> 00:30:24,980
in each of the target
homes, how many people,

536
00:30:24,980 --> 00:30:26,283
at what age children,

537
00:30:29,190 --> 00:30:30,720
their jobs and incomes,

538
00:30:30,720 --> 00:30:32,580
and anything else they need to know

539
00:30:32,580 --> 00:30:36,390
so the tape analysis shows
who's listening to what when.

540
00:30:36,390 --> 00:30:38,370
Of course the Nielsen I'm talking about

541
00:30:38,370 --> 00:30:41,730
is the guy behind Nielsen ratings,

542
00:30:41,730 --> 00:30:44,913
which move on from radio to
TV once that's up and running.

543
00:30:54,720 --> 00:30:57,120
How can Nielsen process so much data?

544
00:30:57,120 --> 00:30:59,790
Well, by coincidence.

545
00:30:59,790 --> 00:31:03,150
See, in World War II,
the U.S. is churning out

546
00:31:03,150 --> 00:31:05,250
lots of new types of artillery shells

547
00:31:05,250 --> 00:31:07,173
that can hit distant targets.

548
00:31:08,070 --> 00:31:10,470
To be accurate, somebody has to calculate

549
00:31:10,470 --> 00:31:12,240
all their possible trajectories,

550
00:31:12,240 --> 00:31:15,000
based on a whole host of variables.

551
00:31:15,000 --> 00:31:19,567
Shell size, length of
barrel, wind speed, distance,

552
00:31:19,567 --> 00:31:20,613
you name it.

553
00:31:21,840 --> 00:31:24,240
A shell trajectory table would've taken

554
00:31:24,240 --> 00:31:27,000
a human mathematician,
at the time mostly women,

555
00:31:27,000 --> 00:31:29,760
more than 30 hours to calculate.

556
00:31:29,760 --> 00:31:32,040
These women, by the way, are
known as people who compute

557
00:31:32,040 --> 00:31:36,063
or computers, hence the
modern word for the machine.

558
00:31:37,320 --> 00:31:38,670
But that's about to change.

559
00:31:39,780 --> 00:31:41,790
Here comes the coincidence.

560
00:31:41,790 --> 00:31:44,880
During the way, Nielsen's
son has been working

561
00:31:44,880 --> 00:31:46,950
at a military establishment called

562
00:31:46,950 --> 00:31:50,460
the Ballistic Research
Lab in Aberdeen, Maryland,

563
00:31:50,460 --> 00:31:54,270
where they're building a top
secret 30 ton military machine

564
00:31:54,270 --> 00:31:57,720
to help make American
artillery more accurate.

565
00:31:57,720 --> 00:32:00,120
And it's all thanks to a
breakthrough that will shape

566
00:32:00,120 --> 00:32:01,443
everything we do today.

567
00:32:06,150 --> 00:32:07,293
Glass tube.

568
00:32:08,430 --> 00:32:11,880
In fact, it's been inside
radios and TVs all along.

569
00:32:11,880 --> 00:32:15,240
A little gizmo invented
back in 1904 by a guy

570
00:32:15,240 --> 00:32:18,963
called Fleming, working for
the Marconi Radio Company.

571
00:32:20,970 --> 00:32:23,400
It's called a vacuum tube.

572
00:32:23,400 --> 00:32:26,820
Basically, it's a glass
tube with a vacuum inside.

573
00:32:26,820 --> 00:32:30,690
Also in there is a bit of
metal called a cathode.

574
00:32:30,690 --> 00:32:33,810
Heat it and it gives off electrons.

575
00:32:33,810 --> 00:32:35,520
They flow to the other end of the tube

576
00:32:35,520 --> 00:32:39,390
to another unheated bit
of metal called an anode,

577
00:32:39,390 --> 00:32:41,310
which then gives off a signal.

578
00:32:41,310 --> 00:32:45,600
When that happens, the vacuum
tube is described as on.

579
00:32:45,600 --> 00:32:48,840
Now, you add a grid between
the cathode and an anode,

580
00:32:48,840 --> 00:32:50,670
put a current onto that grid,

581
00:32:50,670 --> 00:32:53,280
and it stops the flow of
electrons to the anode.

582
00:32:53,280 --> 00:32:56,760
So now the vacuum tube is off,

583
00:32:56,760 --> 00:32:59,490
and the electron flow can
be interrupted like that

584
00:32:59,490 --> 00:33:02,460
an amazing 100,000 times a second

585
00:33:02,460 --> 00:33:05,220
by any signal that puts
a load onto the grid

586
00:33:05,220 --> 00:33:07,530
and temporarily blocks the electron flow,

587
00:33:07,530 --> 00:33:09,510
turning a tube off.

588
00:33:09,510 --> 00:33:12,060
All that gobbly gook basically adds up

589
00:33:12,060 --> 00:33:16,293
to just an astronomically
fast on off adding machine.

590
00:33:19,800 --> 00:33:21,570
The amazing calculating machine

591
00:33:21,570 --> 00:33:24,900
that will do this clever
stuff is called ENIAC,

592
00:33:24,900 --> 00:33:28,050
electronic numerical
integrator and computer.

593
00:33:28,050 --> 00:33:30,093
And it fills a room.

594
00:33:31,620 --> 00:33:34,320
ENIAC has more than 17,000 vacuum tubes

595
00:33:34,320 --> 00:33:36,090
to do the on off counting,

596
00:33:36,090 --> 00:33:38,730
and it uses enough power for a small town.

597
00:33:38,730 --> 00:33:42,630
It also has 70,000
resisters, 10,000 capacitors,

598
00:33:42,630 --> 00:33:45,693
6,000 switches, and 1,500 relays.

599
00:33:47,370 --> 00:33:49,740
Whichever way you slice it,
ENIAC is going to change

600
00:33:49,740 --> 00:33:53,010
not just ballistic
trajectories, but everything,

601
00:33:53,010 --> 00:33:58,010
because it does a mind boggling
5,000 calculations a second.

602
00:33:58,350 --> 00:34:01,140
So for the ballistics
people doing the gun tables,

603
00:34:01,140 --> 00:34:03,453
it's a dream solution to their problems.

604
00:34:04,860 --> 00:34:07,020
So where does this connect to a future

605
00:34:07,020 --> 00:34:08,820
where machines can predict anything?

606
00:34:10,590 --> 00:34:14,790
Well, Nielsen's son, tells
his father all about ENIAC,

607
00:34:14,790 --> 00:34:17,220
and after the war, Nielsen
Senior gets ahold of

608
00:34:17,220 --> 00:34:19,500
one of the world's first
electronic computers,

609
00:34:19,500 --> 00:34:23,013
made by IBM and based on the
ENIAC military technology.

610
00:34:23,850 --> 00:34:26,180
Much smaller, it can still do more than

611
00:34:26,180 --> 00:34:28,740
10,000 operations a second.

612
00:34:28,740 --> 00:34:32,580
That allows Nielsen to calculate
his nationwide ratings data

613
00:34:32,580 --> 00:34:35,040
at the kind of scale and speed he needs

614
00:34:35,040 --> 00:34:37,290
once he gets into the much
bigger and more complicated

615
00:34:37,290 --> 00:34:38,793
TV ratings market.

616
00:34:41,640 --> 00:34:43,980
Thanks to the computer,
Nielsen can process

617
00:34:43,980 --> 00:34:46,740
a statistical technique
that allows, for instance,

618
00:34:46,740 --> 00:34:50,730
a car manufacturer to find
customers who will watch their ad

619
00:34:50,730 --> 00:34:52,800
and likely buy the car they make,

620
00:34:52,800 --> 00:34:55,593
so they can aim their ads only at them.

621
00:34:57,210 --> 00:34:59,253
You find your buyers like this.

622
00:35:00,210 --> 00:35:02,280
First, split potential consumers

623
00:35:02,280 --> 00:35:06,150
between those upper income and those not.

624
00:35:06,150 --> 00:35:07,650
Then of the upper income,

625
00:35:07,650 --> 00:35:10,620
between those who buy cars and those not.

626
00:35:10,620 --> 00:35:15,620
Then of car buyers, those who
buy sports cars and those not.

627
00:35:15,810 --> 00:35:17,370
Then of sports car buyers,

628
00:35:17,370 --> 00:35:21,210
those who buy classic
styles and those not.

629
00:35:21,210 --> 00:35:22,620
Then of classic buyers,

630
00:35:22,620 --> 00:35:26,370
those who go for stick
shift and those not.

631
00:35:26,370 --> 00:35:28,230
Then of those stick shift users,

632
00:35:28,230 --> 00:35:31,620
those who prefer Italian and those not.

633
00:35:31,620 --> 00:35:35,010
This final set is your target sample.

634
00:35:35,010 --> 00:35:37,713
Rich and likely to buy your product.

635
00:35:39,630 --> 00:35:42,780
This statistical process
giving you this information

636
00:35:42,780 --> 00:35:45,630
looks like branches and
twigs and leaves on a tree,

637
00:35:45,630 --> 00:35:48,540
and it's called a decision tree.

638
00:35:48,540 --> 00:35:50,880
And if you go back to your
starting population sample

639
00:35:50,880 --> 00:35:54,180
and change the conditions
of their choice in some way,

640
00:35:54,180 --> 00:35:55,920
you can then go back to your tree

641
00:35:55,920 --> 00:35:58,890
and see how the final
leaf ends up different.

642
00:35:58,890 --> 00:36:01,740
And if your search involves
a really complex issue

643
00:36:01,740 --> 00:36:04,650
and a really big population,
you can use several trees

644
00:36:04,650 --> 00:36:07,980
at once in what statisticians
call, what else,

645
00:36:07,980 --> 00:36:09,813
a decision forest.

646
00:36:12,840 --> 00:36:15,630
Computing gives Nielsen
the kind of capabilities

647
00:36:15,630 --> 00:36:17,223
nobody's ever had before.

648
00:36:18,150 --> 00:36:21,660
Above all, the means to
analyze from his radio's data

649
00:36:21,660 --> 00:36:24,600
much more detailed stuff about TV viewers.

650
00:36:24,600 --> 00:36:27,420
And a few other things regarding
what any retail product

651
00:36:27,420 --> 00:36:30,183
ought to be if he wants
to sell to those people.

652
00:36:31,095 --> 00:36:32,670
But now it's easy.

653
00:36:32,670 --> 00:36:36,270
And what kind of pictures and
words might help to sell it.

654
00:36:36,270 --> 00:36:39,750
As a consequence, the shape
of TV programming changes

655
00:36:39,750 --> 00:36:42,630
to boost revenues by
matching advertising spots

656
00:36:42,630 --> 00:36:44,490
with the most popular shows.

657
00:36:44,490 --> 00:36:48,300
So first of all, the radio
soaps moving to television.

658
00:36:48,300 --> 00:36:52,893
And sure enough, TV soaps
get giant audiences.

659
00:36:54,990 --> 00:36:58,740
So how is all of this
leading us to a future

660
00:36:58,740 --> 00:37:01,023
where machines predict the future?

661
00:37:02,310 --> 00:37:03,760
Let's see how far we've come.

662
00:37:07,500 --> 00:37:10,290
Napoleon's banishment and his furniture,

663
00:37:10,290 --> 00:37:13,320
hummingbirds, the Wardian Case,

664
00:37:13,320 --> 00:37:16,772
Chinese tea, Holt's new ship engine,

665
00:37:16,772 --> 00:37:20,730
palm oil, Lever's palm oil soap,

666
00:37:20,730 --> 00:37:23,100
and the radio and TV soap operas,

667
00:37:23,100 --> 00:37:26,310
Nielsen's need to get TV
and radio audience numbers

668
00:37:26,310 --> 00:37:28,137
triggers the Audimeter.

669
00:37:28,980 --> 00:37:31,350
Really big number audience
data takes Nielsen

670
00:37:31,350 --> 00:37:34,200
to the new World War II computer

671
00:37:34,200 --> 00:37:38,160
and how computing helps to
operate the vast decision tree

672
00:37:38,160 --> 00:37:40,113
that shows you who's going to buy what.

673
00:37:44,250 --> 00:37:45,720
And here's where it gets into more than

674
00:37:45,720 --> 00:37:47,133
advertising and sales.

675
00:37:50,289 --> 00:37:51,720
When Nielsen gets his computer,

676
00:37:51,720 --> 00:37:53,970
a similar computing machine gets used

677
00:37:53,970 --> 00:37:56,553
in the 1952 Presidential elections.

678
00:37:57,570 --> 00:38:00,600
This machine calculates the
early vote return numbers

679
00:38:00,600 --> 00:38:05,433
and predicts Eisenhower's
win with 99% accuracy.

680
00:38:07,890 --> 00:38:10,380
So amazing and unbelievable,

681
00:38:10,380 --> 00:38:13,041
TV people didn't want to
put the prediction on air.

682
00:38:17,640 --> 00:38:20,580
We are now well on our way to a future

683
00:38:20,580 --> 00:38:22,080
where we can predict anything.

684
00:38:25,834 --> 00:38:30,834
Today, we can replicate
all 30 tons on a chip

685
00:38:32,460 --> 00:38:33,633
the size of a pinhead.

686
00:38:34,500 --> 00:38:36,360
One of the most powerful super computers

687
00:38:36,360 --> 00:38:41,340
using that technology is now
the size of two tennis courts.

688
00:38:41,340 --> 00:38:43,200
We're able routinely to use computers

689
00:38:43,200 --> 00:38:45,900
to forecast events immensely more complex

690
00:38:45,900 --> 00:38:47,463
than any presidential election.

691
00:38:50,610 --> 00:38:53,160
We use them to predict
one of the most intricate

692
00:38:53,160 --> 00:38:55,140
and complex activities happening every day

693
00:38:55,140 --> 00:38:57,000
in the natural world,

694
00:38:57,000 --> 00:38:59,250
one that changes in thousands of ways

695
00:38:59,250 --> 00:39:02,253
simultaneously every second, the weather.

696
00:39:03,720 --> 00:39:06,390
A huge amount of variables
need to be factored in

697
00:39:06,390 --> 00:39:09,390
to get anything like a
reliable weather forecast,

698
00:39:09,390 --> 00:39:12,270
wind speeds, air pressures,
surface temperatures,

699
00:39:12,270 --> 00:39:14,730
sea temperature, weather
events in other countries,

700
00:39:14,730 --> 00:39:16,023
on other continents.

701
00:39:17,010 --> 00:39:20,640
Predicting human behavior
is even more complex

702
00:39:20,640 --> 00:39:22,263
and needs even more data.

703
00:39:23,790 --> 00:39:25,500
But of course with super computing,

704
00:39:25,500 --> 00:39:29,010
we've arrived at the amount
of data available today so big

705
00:39:29,010 --> 00:39:31,233
that we call it big data.

706
00:39:33,600 --> 00:39:37,230
Big data gives a whole new
meaning to what you can do

707
00:39:37,230 --> 00:39:38,230
when you know a lot.

708
00:39:41,280 --> 00:39:44,520
Which means that at any stage
of analyzing old populations

709
00:39:44,520 --> 00:39:46,410
and their likes and dislikes,

710
00:39:46,410 --> 00:39:49,020
you can take into account
the colossal number

711
00:39:49,020 --> 00:39:51,990
of interactions among
everybody in a population

712
00:39:51,990 --> 00:39:55,053
when it comes to any issue right now.

713
00:39:57,450 --> 00:40:00,240
Each person chooses
their own path in life,

714
00:40:00,240 --> 00:40:02,700
and for the first time,
we may soon be able

715
00:40:02,700 --> 00:40:05,670
to take every one of
those choices into account

716
00:40:05,670 --> 00:40:08,810
in a way we'll use the
data to shape the future.

717
00:40:09,830 --> 00:40:11,430
The data's all there to analyze.

718
00:40:12,330 --> 00:40:14,460
With every computer keyboard click,

719
00:40:14,460 --> 00:40:17,733
we're already able to collect
data on everything you buy,

720
00:40:19,680 --> 00:40:23,160
details on money activity,
your travel, your shoe size,

721
00:40:23,160 --> 00:40:26,640
health, medication, medical
history, birth place,

722
00:40:26,640 --> 00:40:30,390
gender, marital status,
social status, children,

723
00:40:30,390 --> 00:40:33,870
family structure, insurance, age, income,

724
00:40:33,870 --> 00:40:38,190
use of car, kind of car, use
of buses, train journeys,

725
00:40:38,190 --> 00:40:41,370
flights, commuting schedule, what you eat,

726
00:40:41,370 --> 00:40:43,740
TV radio and music program choices,

727
00:40:43,740 --> 00:40:45,810
your favorite papers and magazines,

728
00:40:45,810 --> 00:40:49,770
your education, job, hobbies,
residence and location,

729
00:40:49,770 --> 00:40:52,950
friends social life,
languages, favorite music,

730
00:40:52,950 --> 00:40:55,680
sports, clubs, spare time activities,

731
00:40:55,680 --> 00:40:58,680
religious beliefs, events
you attend, your ethnicity,

732
00:40:58,680 --> 00:41:02,040
personal grooming, pets, sweet
tooth, sexual activities,

733
00:41:02,040 --> 00:41:06,630
skills, financial worth,
investments, and everything else.

734
00:41:06,630 --> 00:41:08,880
It's called data exhaust,

735
00:41:08,880 --> 00:41:11,820
and it has supplied us
with more information

736
00:41:11,820 --> 00:41:15,960
than Nielsen ever dreamt of
about each and every choice

737
00:41:15,960 --> 00:41:17,823
we make every day.

738
00:41:19,290 --> 00:41:23,070
What if all these decisions
could be fed into a machine

739
00:41:23,070 --> 00:41:25,500
that could process this
astronomical amount of data

740
00:41:25,500 --> 00:41:28,080
and predict all possible outcomes

741
00:41:28,080 --> 00:41:30,480
to tell you which was most likely,

742
00:41:30,480 --> 00:41:32,030
just like the weather forecast.

743
00:41:33,420 --> 00:41:35,310
We've reached our destination,

744
00:41:35,310 --> 00:41:37,260
one which I believe will
move this possibility

745
00:41:37,260 --> 00:41:41,245
from the realms of sci-fi into reality.

746
00:41:49,110 --> 00:41:52,053
A quantum computer that
can predict the future.

747
00:41:55,590 --> 00:41:58,050
Apparently in its infancy, this technology

748
00:41:58,050 --> 00:41:59,800
will revolutionize the way we live.

749
00:42:01,320 --> 00:42:03,990
Now there are two ways to
explain a quantum computer.

750
00:42:03,990 --> 00:42:06,540
One is a four year
degree course in physics

751
00:42:06,540 --> 00:42:08,973
and the other now takes less time.

752
00:42:11,010 --> 00:42:13,980
So, an ordinary classical
computer calculates

753
00:42:13,980 --> 00:42:17,850
using zeros and ones, or an
electrical current on or off.

754
00:42:17,850 --> 00:42:20,820
This is what's called a binary system.

755
00:42:20,820 --> 00:42:24,300
Each binary number is called a bit.

756
00:42:24,300 --> 00:42:28,170
So two bits can represent four numbers,

757
00:42:28,170 --> 00:42:32,883
zero zero, zero one,
one zero, and one one.

758
00:42:33,990 --> 00:42:38,313
A group of eight bits can
therefore represent 256 numbers.

759
00:42:39,180 --> 00:42:41,490
Instead of using tiny electrical switches,

760
00:42:41,490 --> 00:42:43,980
like a classical computer
uses for each bit,

761
00:42:43,980 --> 00:42:47,190
a quantum computer uses
subatomic particles,

762
00:42:47,190 --> 00:42:50,070
like photons, to calculate numbers.

763
00:42:50,070 --> 00:42:52,530
These are called Qubits,

764
00:42:52,530 --> 00:42:54,660
and they can represent zero and one,

765
00:42:54,660 --> 00:42:56,340
but both at the same time.

766
00:42:56,340 --> 00:42:57,840
Take my word for that.

767
00:42:57,840 --> 00:43:00,540
They can also represent
an almost infinite number

768
00:43:00,540 --> 00:43:02,853
of positions between the zero and the one.

769
00:43:03,690 --> 00:43:07,113
So a group of several Qubits
can handle enormous numbers.

770
00:43:08,220 --> 00:43:12,058
A quantum computer with 400
Qubits could handle a number

771
00:43:12,058 --> 00:43:15,213
bigger than all the atoms in the universe.

772
00:43:18,360 --> 00:43:21,360
So, if you're working in
retail and you want to predict

773
00:43:21,360 --> 00:43:23,550
your next big seller, you need to take

774
00:43:23,550 --> 00:43:26,520
many, many different
scenarios into account

775
00:43:26,520 --> 00:43:27,870
and then find the best one.

776
00:43:28,980 --> 00:43:33,120
Or you want to enact a war
game, see how a future conflict

777
00:43:33,120 --> 00:43:35,643
might go without firing a single shot.

778
00:43:36,870 --> 00:43:38,790
Now this is something
that a quantum computer

779
00:43:38,790 --> 00:43:41,490
is better for because it
allows you to calculate

780
00:43:41,490 --> 00:43:42,940
many things at the same time.

781
00:43:44,880 --> 00:43:47,910
So once we're able to
build a 400 Qubit computer,

782
00:43:47,910 --> 00:43:49,650
likely in the next few years,

783
00:43:49,650 --> 00:43:51,480
handling the small
matter of all the actions

784
00:43:51,480 --> 00:43:53,640
and interactions of everybody on Earth

785
00:43:53,640 --> 00:43:55,500
and predicting what's
coming at every split second

786
00:43:55,500 --> 00:43:57,840
and every point in the
future for all of us

787
00:43:57,840 --> 00:43:59,343
will be a snip.

788
00:44:00,570 --> 00:44:02,220
The machine will know the consequence

789
00:44:02,220 --> 00:44:04,983
of any decision you
take before you take it.

790
00:44:07,500 --> 00:44:11,040
On a planet-wide scale,
this ongoing ability

791
00:44:11,040 --> 00:44:13,680
will give us control over everything.

792
00:44:13,680 --> 00:44:16,530
We'll be able to plan
everything in real time

793
00:44:16,530 --> 00:44:19,863
in every detail for every
adult on the planet.

794
00:44:21,990 --> 00:44:23,700
It doesn't feel like free will

795
00:44:23,700 --> 00:44:26,190
or personal liberty to choose
your individual direction

796
00:44:26,190 --> 00:44:27,303
in life, does it?

797
00:44:28,410 --> 00:44:31,811
The old autonomous freedom
of action to shape our lives

798
00:44:31,811 --> 00:44:35,403
that we've enjoyed for thousands of years.

799
00:44:39,750 --> 00:44:41,700
But maybe that's just
the old out-of-date way

800
00:44:41,700 --> 00:44:44,643
we used to do things before
the quantum computer.

801
00:44:47,190 --> 00:44:50,653
Maybe we need to learn
how to live in a world

802
00:44:50,653 --> 00:44:52,803
where there are no more surprises.

802
00:44:53,305 --> 00:45:53,659
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