How algorithms shape our world - Kevin Slavin
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this<00:00:16.340> is<00:00:16.460> a<00:00:16.490> photograph<00:00:16.790> by<00:00:17.360> the<00:00:17.420> artist
this is a photograph by the artist
this is a photograph by the artist
Michael<00:00:18.619> Najjar<00:00:19.040> and<00:00:19.970> it's<00:00:20.119> real<00:00:20.390> in<00:00:21.380> the
Michael Najjar and it's real in the
Michael Najjar and it's real in the
sense<00:00:21.710> that<00:00:21.830> he<00:00:22.160> went<00:00:22.550> there<00:00:22.730> to<00:00:23.060> Argentina<00:00:23.750> to
sense that he went there to Argentina to
sense that he went there to Argentina to
take<00:00:24.080> the<00:00:24.230> photo<00:00:24.580> but<00:00:25.580> it's<00:00:25.700> also<00:00:25.820> a<00:00:26.000> fiction
take the photo but it's also a fiction
take the photo but it's also a fiction
there's<00:00:26.810> a<00:00:26.869> lot<00:00:27.020> of<00:00:27.200> work<00:00:27.560> that<00:00:27.829> went<00:00:28.070> into<00:00:28.250> it
there's a lot of work that went into it
there's a lot of work that went into it
after<00:00:28.579> that<00:00:28.849> and<00:00:28.910> what<00:00:29.210> he's<00:00:29.329> done<00:00:29.540> is<00:00:29.750> he's
after that and what he's done is he's
after that and what he's done is he's
actually<00:00:30.460> reshaped<00:00:31.460> digitally<00:00:32.419> all<00:00:32.599> of<00:00:32.750> the
actually reshaped digitally all of the
actually reshaped digitally all of the
contours<00:00:33.950> of<00:00:34.010> the<00:00:34.070> mountains<00:00:34.430> to<00:00:34.640> follow<00:00:34.880> the
contours of the mountains to follow the
contours of the mountains to follow the
vicissitudes<00:00:35.840> of<00:00:36.140> the<00:00:36.290> Dow<00:00:36.440> Jones<00:00:36.470> index<00:00:37.250> so
vicissitudes of the Dow Jones index so
vicissitudes of the Dow Jones index so
what<00:00:38.420> you<00:00:38.540> see<00:00:38.870> that<00:00:39.350> precipice<00:00:39.890> that<00:00:40.070> high
what you see that precipice that high
what you see that precipice that high
precipice<00:00:40.940> with<00:00:41.120> the<00:00:41.210> valley<00:00:41.390> is<00:00:41.750> the<00:00:41.960> 2008
precipice with the valley is the 2008
precipice with the valley is the 2008
financial<00:00:43.160> crisis<00:00:44.030> the<00:00:44.300> photo<00:00:44.780> was<00:00:45.020> made<00:00:45.230> when
financial crisis the photo was made when
financial crisis the photo was made when
we<00:00:45.470> were<00:00:45.680> deep<00:00:45.920> in<00:00:46.130> the<00:00:46.190> valley<00:00:46.700> over<00:00:47.150> there<00:00:47.660> I
we were deep in the valley over there I
we were deep in the valley over there I
don't<00:00:47.810> know<00:00:47.990> where<00:00:48.230> we<00:00:48.410> are<00:00:48.440> now<00:00:49.270> this<00:00:50.270> is<00:00:50.540> the
don't know where we are now this is the
don't know where we are now this is the
Hang<00:00:51.440> Seng<00:00:51.770> Index<00:00:51.830> or<00:00:52.520> Hong<00:00:52.730> Kong<00:00:52.760> and<00:00:53.710> similar
Hang Seng Index or Hong Kong and similar
Hang Seng Index or Hong Kong and similar
topography<00:00:55.400> I<00:00:55.430> wonder<00:00:56.030> why<00:00:56.240> and<00:00:56.890> this<00:00:57.890> is<00:00:58.070> art
topography I wonder why and this is art
topography I wonder why and this is art
right<00:00:59.060> this<00:00:59.329> is<00:00:59.570> metaphor<00:01:00.470> but<00:01:01.220> I<00:01:01.460> think<00:01:02.090> the
right this is metaphor but I think the
right this is metaphor but I think the
point<00:01:02.329> is<00:01:02.390> is<00:01:02.540> that<00:01:02.690> this<00:01:02.780> is<00:01:02.989> metaphor<00:01:03.560> with
point is is that this is metaphor with
point is is that this is metaphor with
teeth<00:01:04.460> and<00:01:05.000> it's<00:01:05.180> with<00:01:05.390> those<00:01:05.600> teeth<00:01:05.930> that<00:01:06.229> I
teeth and it's with those teeth that I
teeth and it's with those teeth that I
want<00:01:06.530> to<00:01:06.650> propose<00:01:07.460> today<00:01:07.939> that<00:01:08.270> we<00:01:08.479> rethink<00:01:09.140> a
want to propose today that we rethink a
want to propose today that we rethink a
little<00:01:09.619> bit<00:01:09.799> about<00:01:10.430> the<00:01:10.610> role<00:01:10.820> of
little bit about the role of
little bit about the role of
contemporary<00:01:12.530> math<00:01:12.799> not<00:01:13.130> just<00:01:13.399> financial
contemporary math not just financial
contemporary math not just financial
math<00:01:14.119> but<00:01:14.420> math<00:01:14.630> in<00:01:15.170> general<00:01:15.530> that<00:01:15.770> it's
math but math in general that it's
math but math in general that it's
transition<00:01:17.540> from<00:01:17.720> being<00:01:17.900> something<00:01:18.080> that<00:01:18.200> we
transition from being something that we
transition from being something that we
sort<00:01:18.620> of<00:01:18.740> extract<00:01:19.550> and<00:01:19.880> derive<00:01:20.210> from<00:01:20.510> the
sort of extract and derive from the
sort of extract and derive from the
world<00:01:20.840> to<00:01:21.020> something<00:01:21.470> that<00:01:21.860> actually<00:01:22.070> starts
world to something that actually starts
world to something that actually starts
to<00:01:22.760> shape<00:01:23.150> it<00:01:23.360> the<00:01:24.110> world<00:01:24.320> around<00:01:24.650> us<00:01:24.920> in<00:01:25.250> the
to shape it the world around us in the
to shape it the world around us in the
world<00:01:25.490> inside<00:01:26.360> us<00:01:26.600> and<00:01:26.810> it<00:01:26.930> specifically
world inside us and it specifically
world inside us and it specifically
algorithms<00:01:28.760> which<00:01:29.000> are<00:01:29.210> basically<00:01:30.049> the<00:01:30.200> math
algorithms which are basically the math
algorithms which are basically the math
that<00:01:30.680> computers<00:01:31.250> used<00:01:31.490> to<00:01:31.640> decide<00:01:32.000> stuff<00:01:32.590> they
that computers used to decide stuff they
that computers used to decide stuff they
acquire<00:01:34.130> the<00:01:34.970> sensibility<00:01:35.690> of<00:01:35.780> truth<00:01:36.110> because
acquire the sensibility of truth because
acquire the sensibility of truth because
they<00:01:36.680> repeat<00:01:37.159> over<00:01:37.340> and<00:01:37.640> over<00:01:37.790> again<00:01:37.970> and<00:01:38.120> they
they repeat over and over again and they
they repeat over and over again and they
kind<00:01:38.360> of<00:01:38.420> ossify<00:01:39.170> and<00:01:39.470> calcify<00:01:40.130> and<00:01:40.549> they<00:01:40.610> kind
kind of ossify and calcify and they kind
kind of ossify and calcify and they kind
of<00:01:40.850> become<00:01:41.659> real<00:01:42.650> and<00:01:42.979> I<00:01:43.580> was<00:01:43.670> thinking<00:01:43.850> about
of become real and I was thinking about
of become real and I was thinking about
this<00:01:44.409> of<00:01:45.409> all<00:01:45.650> places<00:01:46.190> on<00:01:46.460> a<00:01:46.490> transatlantic
this of all places on a transatlantic
this of all places on a transatlantic
flight<00:01:47.000> a<00:01:47.690> couple<00:01:48.170> years<00:01:48.320> ago<00:01:48.470> because<00:01:49.130> I
flight a couple years ago because I
flight a couple years ago because I
happen<00:01:49.549> to<00:01:49.610> be<00:01:49.670> seated<00:01:50.030> next<00:01:50.210> to<00:01:50.420> a<00:01:50.869> Hungarian
happen to be seated next to a Hungarian
happen to be seated next to a Hungarian
physicist<00:01:51.860> about<00:01:52.250> my<00:01:52.430> age<00:01:52.610> and<00:01:53.030> we<00:01:53.119> were
physicist about my age and we were
physicist about my age and we were
talking<00:01:53.570> about<00:01:53.740> what<00:01:54.740> life<00:01:54.920> was<00:01:55.100> like<00:01:55.159> during
talking about what life was like during
talking about what life was like during
the<00:01:55.580> Cold<00:01:55.820> War<00:01:56.060> for<00:01:56.090> physicists<00:01:56.960> in<00:01:57.320> Hungary
the Cold War for physicists in Hungary
the Cold War for physicists in Hungary
and<00:01:57.979> I<00:01:58.340> said<00:01:58.640> so<00:01:58.790> what<00:01:58.909> were<00:01:59.060> you<00:01:59.210> doing<00:01:59.240> and<00:01:59.570> he
and I said so what were you doing and he
and I said so what were you doing and he
said<00:01:59.810> well<00:01:59.930> we<00:02:00.049> were<00:02:00.200> mostly<00:02:01.159> breaking
said well we were mostly breaking
said well we were mostly breaking
stealth<00:02:02.060> and<00:02:02.600> I<00:02:02.720> said<00:02:02.930> that's<00:02:03.140> a<00:02:03.229> good<00:02:03.470> job
stealth and I said that's a good job
stealth and I said that's a good job
that's<00:02:04.880> interesting<00:02:05.650> how<00:02:06.650> does<00:02:06.830> that<00:02:06.979> work
that's interesting how does that work
that's interesting how does that work
and<00:02:07.610> so<00:02:07.759> to<00:02:07.820> understand<00:02:08.360> that<00:02:08.509> you<00:02:08.629> have<00:02:08.659> to
and so to understand that you have to
and so to understand that you have to
understand<00:02:09.110> a<00:02:09.170> little<00:02:09.200> bit<00:02:09.470> about<00:02:10.399> how
understand a little bit about how
understand a little bit about how
stealth<00:02:10.879> works<00:02:11.209> and<00:02:11.450> so<00:02:11.629> this<00:02:12.470> is<00:02:12.650> a
stealth works and so this is a
stealth works and so this is a
oversimplification<00:02:14.120> but<00:02:14.269> basically<00:02:14.659> it's
oversimplification but basically it's
oversimplification but basically it's
not<00:02:15.830> like<00:02:16.040> you<00:02:16.159> can<00:02:16.370> just<00:02:16.400> pass<00:02:17.390> a<00:02:17.450> radar
not like you can just pass a radar
not like you can just pass a radar
signal<00:02:18.170> right<00:02:18.500> through
signal right through
signal right through
156<00:02:20.629> tons<00:02:21.019> of<00:02:21.230> steel<00:02:21.560> in<00:02:21.769> the<00:02:21.889> sky<00:02:22.129> it's<00:02:22.430> not
156 tons of steel in the sky it's not
156 tons of steel in the sky it's not
just<00:02:22.730> going<00:02:22.879> to<00:02:22.939> disappear
just going to disappear
just going to disappear
but<00:02:24.980> if<00:02:25.070> you<00:02:25.160> can<00:02:25.340> take<00:02:25.700> this<00:02:26.090> big<00:02:26.480> massive
but if you can take this big massive
but if you can take this big massive
thing<00:02:27.530> and<00:02:27.830> you<00:02:28.490> could<00:02:28.730> turn<00:02:29.690> it<00:02:29.870> into<00:02:29.990> a
thing and you could turn it into a
thing and you could turn it into a
million<00:02:31.700> little<00:02:31.730> things<00:02:32.030> something<00:02:32.840> like<00:02:33.710> a
million little things something like a
million little things something like a
flock<00:02:34.190> of<00:02:34.220> birds<00:02:34.640> well<00:02:35.540> then<00:02:35.690> the<00:02:35.780> radar
flock of birds well then the radar
flock of birds well then the radar
that's<00:02:36.320> looking<00:02:36.650> for<00:02:36.830> that<00:02:36.980> has<00:02:37.190> to<00:02:37.340> be<00:02:37.430> able
that's looking for that has to be able
that's looking for that has to be able
to<00:02:37.880> see<00:02:38.120> every<00:02:38.780> flock<00:02:39.050> of<00:02:39.080> birds<00:02:39.470> in<00:02:39.740> the<00:02:39.890> sky
to see every flock of birds in the sky
to see every flock of birds in the sky
and<00:02:40.430> if<00:02:41.210> you're<00:02:41.360> a<00:02:41.390> radar<00:02:41.870> that's<00:02:42.140> a<00:02:42.230> really
and if you're a radar that's a really
and if you're a radar that's a really
bad<00:02:42.830> job
bad job
bad job
and<00:02:44.960> he<00:02:45.110> said<00:02:45.350> yeah<00:02:45.590> he<00:02:46.250> said<00:02:46.430> but<00:02:46.640> that's<00:02:46.790> if
and he said yeah he said but that's if
and he said yeah he said but that's if
you're<00:02:47.180> a<00:02:47.210> radar<00:02:47.750> he<00:02:48.140> said<00:02:48.320> so<00:02:48.440> we<00:02:48.530> didn't<00:02:48.740> use
you're a radar he said so we didn't use
you're a radar he said so we didn't use
a<00:02:48.890> radar<00:02:49.160> we<00:02:49.550> built<00:02:50.240> a<00:02:50.390> black<00:02:50.600> box<00:02:50.900> that<00:02:51.470> was
a radar we built a black box that was
a radar we built a black box that was
looking<00:02:51.890> for<00:02:52.000> electrical<00:02:53.000> signals
looking for electrical signals
looking for electrical signals
electronic<00:02:54.020> communication<00:02:54.890> and<00:02:55.460> whenever<00:02:55.880> we
electronic communication and whenever we
electronic communication and whenever we
saw<00:02:56.390> a<00:02:56.630> flock<00:02:57.110> of<00:02:57.140> birds<00:02:57.530> that<00:02:57.920> had<00:02:58.100> electronic
saw a flock of birds that had electronic
saw a flock of birds that had electronic
communication<00:02:59.060> we<00:02:59.120> thought<00:02:59.330> probably<00:02:59.840> has
communication we thought probably has
communication we thought probably has
something<00:03:00.590> to<00:03:00.620> do<00:03:00.860> with<00:03:00.890> the<00:03:01.100> Americans<00:03:01.670> and<00:03:02.270> I
something to do with the Americans and I
something to do with the Americans and I
said<00:03:02.840> yeah<00:03:03.560> that's<00:03:03.890> that's<00:03:04.730> good<00:03:05.090> that's<00:03:05.420> good
said yeah that's that's good that's good
said yeah that's that's good that's good
so<00:03:05.810> you've<00:03:06.020> effectively<00:03:06.950> negated<00:03:07.610> 60<00:03:08.060> years
so you've effectively negated 60 years
so you've effectively negated 60 years
of<00:03:08.390> aeronautical<00:03:09.230> research<00:03:09.260> what's<00:03:09.980> your<00:03:10.310> act
of aeronautical research what's your act
of aeronautical research what's your act
to<00:03:11.330> you<00:03:11.810> know<00:03:11.930> like<00:03:12.110> what<00:03:12.230> do<00:03:12.290> you<00:03:12.320> do<00:03:12.470> when<00:03:12.650> you
to you know like what do you do when you
to you know like what do you do when you
grow<00:03:13.070> up<00:03:13.100> and<00:03:13.580> he<00:03:14.360> said<00:03:14.660> he<00:03:15.290> said<00:03:15.530> well<00:03:15.740> you
grow up and he said he said well you
grow up and he said he said well you
know<00:03:16.330> financial<00:03:17.330> services<00:03:17.810> and<00:03:18.590> I<00:03:18.680> said<00:03:18.890> oh
know financial services and I said oh
know financial services and I said oh
because<00:03:20.480> those<00:03:20.750> have<00:03:20.930> been<00:03:21.020> in<00:03:21.080> the<00:03:21.290> news
because those have been in the news
because those have been in the news
lately<00:03:22.540> and<00:03:23.540> I<00:03:23.810> said<00:03:24.080> I<00:03:24.230> said<00:03:24.410> how<00:03:24.500> does<00:03:24.560> that
lately and I said I said how does that
lately and I said I said how does that
work<00:03:24.860> and<00:03:24.890> I<00:03:25.010> said<00:03:25.070> well<00:03:25.190> there's<00:03:25.340> 2,000
work and I said well there's 2,000
work and I said well there's 2,000
physicists<00:03:26.600> on<00:03:26.720> Wall<00:03:26.900> Street<00:03:27.230> now<00:03:27.440> and<00:03:27.709> I'm
physicists on Wall Street now and I'm
physicists on Wall Street now and I'm
one<00:03:28.640> of<00:03:28.760> them<00:03:28.940> and<00:03:29.180> I<00:03:29.360> said<00:03:29.420> well<00:03:29.660> so<00:03:29.840> what's
one of them and I said well so what's
one of them and I said well so what's
the<00:03:30.200> black<00:03:30.410> box<00:03:30.709> for<00:03:31.550> Wall<00:03:31.700> Street<00:03:31.730> and<00:03:32.269> he
the black box for Wall Street and he
the black box for Wall Street and he
said<00:03:32.840> well<00:03:32.959> it's<00:03:33.050> funny<00:03:33.230> that<00:03:33.290> you<00:03:33.470> asked<00:03:33.620> that
said well it's funny that you asked that
said well it's funny that you asked that
because<00:03:33.920> it's<00:03:34.190> actually<00:03:34.310> called<00:03:34.760> black<00:03:35.390> box
because it's actually called black box
because it's actually called black box
trading<00:03:35.989> and<00:03:36.820> it's<00:03:37.820> also<00:03:38.030> sometimes<00:03:38.540> called
trading and it's also sometimes called
trading and it's also sometimes called
algo<00:03:39.320> trading<00:03:39.350> algorithmic<00:03:40.340> trading<00:03:40.580> and
algo trading algorithmic trading and
algo trading algorithmic trading and
algorithmic<00:03:42.739> trading<00:03:42.980> involved<00:03:43.700> in<00:03:43.880> part
algorithmic trading involved in part
algorithmic trading involved in part
because<00:03:45.550> institutional<00:03:46.550> traders<00:03:46.790> have<00:03:47.150> the
because institutional traders have the
because institutional traders have the
same<00:03:47.540> problems<00:03:48.140> that<00:03:48.380> the<00:03:48.709> United<00:03:49.070> States
same problems that the United States
same problems that the United States
airforce<00:03:49.519> had<00:03:50.000> which<00:03:50.750> is<00:03:50.900> that<00:03:51.080> they're
airforce had which is that they're
airforce had which is that they're
moving<00:03:51.680> these<00:03:52.340> positions<00:03:53.060> whether<00:03:53.450> it's
moving these positions whether it's
moving these positions whether it's
Procter<00:03:54.049> and<00:03:54.170> Gamble<00:03:54.590> or<00:03:54.739> etc<00:03:55.400> or<00:03:55.459> whatever
Procter and Gamble or etc or whatever
Procter and Gamble or etc or whatever
they're<00:03:55.940> moving<00:03:56.209> like<00:03:56.239> a<00:03:56.360> million<00:03:57.140> shares<00:03:57.500> of
they're moving like a million shares of
they're moving like a million shares of
something<00:03:58.340> through<00:03:58.610> the<00:03:58.730> market<00:03:59.120> and<00:03:59.269> if<00:03:59.810> they
something through the market and if they
something through the market and if they
do<00:04:00.019> that<00:04:00.470> all<00:04:00.709> at<00:04:00.890> once<00:04:01.100> it's<00:04:01.340> like<00:04:01.400> playing
do that all at once it's like playing
do that all at once it's like playing
poker<00:04:02.000> and<00:04:02.269> just<00:04:02.450> going<00:04:02.630> all-in<00:04:02.870> right<00:04:03.290> away
poker and just going all-in right away
poker and just going all-in right away
right<00:04:04.010> you<00:04:04.160> just<00:04:04.310> tip<00:04:04.519> your<00:04:04.700> hand<00:04:04.910> and<00:04:05.150> so<00:04:06.140> they
right you just tip your hand and so they
right you just tip your hand and so they
have<00:04:06.440> to<00:04:06.590> find<00:04:06.920> a<00:04:07.100> way<00:04:07.310> and<00:04:07.730> they<00:04:07.880> use
have to find a way and they use
have to find a way and they use
algorithms<00:04:08.540> to<00:04:08.930> do<00:04:09.110> this<00:04:09.290> to<00:04:09.769> break<00:04:10.130> up<00:04:10.370> that
algorithms to do this to break up that
algorithms to do this to break up that
big<00:04:10.940> thing<00:04:11.180> into<00:04:11.450> a<00:04:11.480> million<00:04:12.049> little
big thing into a million little
big thing into a million little
transactions<00:04:13.130> and<00:04:13.370> the<00:04:13.880> magic<00:04:14.390> and<00:04:14.600> the
transactions and the magic and the
transactions and the magic and the
horror<00:04:15.080> of<00:04:15.470> that<00:04:15.580> is<00:04:16.580> is<00:04:16.760> that<00:04:16.910> the<00:04:17.030> same<00:04:17.359> math
horror of that is is that the same math
horror of that is is that the same math
that<00:04:18.320> you<00:04:18.350> use<00:04:18.739> to<00:04:18.950> break<00:04:19.250> up<00:04:19.489> the<00:04:19.880> big<00:04:20.090> thing
that you use to break up the big thing
that you use to break up the big thing
into<00:04:20.720> a<00:04:20.750> million<00:04:21.080> little<00:04:21.109> things<00:04:21.380> can<00:04:22.070> be<00:04:22.190> used
into a million little things can be used
into a million little things can be used
to<00:04:22.640> find<00:04:22.940> a<00:04:23.210> million<00:04:23.600> little<00:04:23.840> things<00:04:23.960> and<00:04:24.350> sew
to find a million little things and sew
to find a million little things and sew
them<00:04:24.650> back<00:04:24.710> together<00:04:25.010> and<00:04:25.250> figure<00:04:25.669> out<00:04:25.700> what's
them back together and figure out what's
them back together and figure out what's
actually<00:04:26.360> happening<00:04:26.960> in<00:04:27.080> the<00:04:27.169> market<00:04:27.500> so<00:04:27.650> if
actually happening in the market so if
actually happening in the market so if
you<00:04:27.919> need<00:04:28.190> to<00:04:28.669> have<00:04:28.910> some<00:04:29.360> image<00:04:29.750> of<00:04:29.960> what's
you need to have some image of what's
you need to have some image of what's
happening<00:04:30.979> in<00:04:31.130> the<00:04:31.580> stock<00:04:31.820> market<00:04:32.240> right<00:04:32.360> now
happening in the stock market right now
happening in the stock market right now
what<00:04:32.810> you<00:04:32.930> can<00:04:33.110> picture<00:04:33.349> is<00:04:33.710> a<00:04:33.770> bunch<00:04:34.280> of
what you can picture is a bunch of
what you can picture is a bunch of
algorithms<00:04:35.060> that<00:04:35.270> are<00:04:35.660> basically<00:04:35.990> programmed
algorithms that are basically programmed
algorithms that are basically programmed
to<00:04:36.830> hide
to hide
to hide
and<00:04:37.960> a<00:04:38.020> bunch<00:04:38.199> of<00:04:38.259> algorithms<00:04:38.770> that<00:04:38.919> are
and a bunch of algorithms that are
and a bunch of algorithms that are
programmed<00:04:39.430> to<00:04:39.520> go<00:04:39.699> find<00:04:40.060> them<00:04:40.270> and<00:04:40.419> act<00:04:40.900> and
programmed to go find them and act and
programmed to go find them and act and
all<00:04:41.740> of<00:04:41.889> that's<00:04:42.009> great<00:04:42.639> and<00:04:42.880> it's<00:04:43.120> fine<00:04:43.479> and
all of that's great and it's fine and
all of that's great and it's fine and
that's<00:04:44.770> 70%<00:04:45.610> of<00:04:46.449> the<00:04:47.110> United<00:04:47.350> States<00:04:47.530> stock
that's 70% of the United States stock
that's 70% of the United States stock
where<00:04:47.860> 70%<00:04:48.250> of<00:04:48.820> the<00:04:48.970> operating<00:04:49.479> system
where 70% of the operating system
where 70% of the operating system
formerly<00:04:50.500> known<00:04:50.800> as<00:04:51.100> your<00:04:51.610> pension
formerly known as your pension
formerly known as your pension
your<00:04:53.770> your<00:04:54.400> mortgage<00:04:54.940> and<00:04:55.620> what<00:04:56.620> could<00:04:56.770> go
your your mortgage and what could go
your your mortgage and what could go
wrong<00:04:57.570> right<00:04:58.570> what<00:04:58.780> could<00:04:58.930> go<00:04:58.960> wrong<00:04:59.259> is<00:04:59.620> is
wrong right what could go wrong is is
wrong right what could go wrong is is
that<00:05:00.100> a<00:05:00.130> year<00:05:00.520> ago
that a year ago
that a year ago
9%<00:05:02.110> of<00:05:02.199> the<00:05:02.259> entire<00:05:02.530> market<00:05:02.770> just<00:05:03.070> disappears
9% of the entire market just disappears
9% of the entire market just disappears
in<00:05:04.090> five<00:05:04.389> minutes<00:05:04.810> and<00:05:04.930> they<00:05:05.080> called<00:05:05.259> it<00:05:05.380> the
in five minutes and they called it the
in five minutes and they called it the
flash<00:05:05.740> crash<00:05:05.979> of<00:05:06.280> 2:45<00:05:06.970> right<00:05:08.139> all<00:05:08.410> of<00:05:08.650> a
flash crash of 2:45 right all of a
flash crash of 2:45 right all of a
sudden<00:05:08.740> 9%<00:05:09.370> just<00:05:09.520> goes<00:05:09.759> away<00:05:10.030> and<00:05:10.539> nobody<00:05:11.500> to
sudden 9% just goes away and nobody to
sudden 9% just goes away and nobody to
this<00:05:12.010> day<00:05:12.310> can<00:05:12.820> even<00:05:13.030> agree<00:05:13.360> on<00:05:13.539> what<00:05:14.169> happened
this day can even agree on what happened
this day can even agree on what happened
because<00:05:15.039> nobody<00:05:15.610> ordered<00:05:16.270> it<00:05:16.389> nobody<00:05:16.780> asked
because nobody ordered it nobody asked
because nobody ordered it nobody asked
for<00:05:17.229> it<00:05:17.530> nobody<00:05:18.070> had<00:05:18.430> any<00:05:18.639> control<00:05:19.180> over<00:05:19.960> what
for it nobody had any control over what
for it nobody had any control over what
was<00:05:20.139> actually<00:05:20.500> happening<00:05:20.740> all<00:05:21.310> they<00:05:21.610> had<00:05:22.199> was
was actually happening all they had was
was actually happening all they had was
just<00:05:23.260> a<00:05:23.620> monitor<00:05:24.130> in<00:05:24.280> front<00:05:24.310> of<00:05:24.610> them<00:05:24.900> that<00:05:25.900> had
just a monitor in front of them that had
just a monitor in front of them that had
the<00:05:26.229> numbers<00:05:26.590> on<00:05:26.770> it<00:05:26.800> and<00:05:27.010> just<00:05:27.460> a<00:05:27.550> red<00:05:27.760> button
the numbers on it and just a red button
the numbers on it and just a red button
that<00:05:28.419> said<00:05:28.750> stop<00:05:29.710> and<00:05:30.510> that's<00:05:31.510> the<00:05:31.780> thing
that said stop and that's the thing
that said stop and that's the thing
right<00:05:32.380> is<00:05:32.590> is<00:05:32.710> that<00:05:32.889> we're<00:05:33.039> writing<00:05:33.610> things
right is is that we're writing things
right is is that we're writing things
we're<00:05:34.599> writing<00:05:34.900> these<00:05:35.199> things<00:05:35.440> that<00:05:35.530> we<00:05:35.650> can
we're writing these things that we can
we're writing these things that we can
no<00:05:36.039> longer<00:05:36.070> read<00:05:36.729> and<00:05:37.030> it's<00:05:37.840> we've<00:05:38.080> we've
no longer read and it's we've we've
no longer read and it's we've we've
rendered<00:05:38.800> something<00:05:39.550> kind<00:05:40.030> of<00:05:40.120> illegible<00:05:40.900> and
rendered something kind of illegible and
rendered something kind of illegible and
we've<00:05:43.150> lost<00:05:43.570> the<00:05:44.229> sense<00:05:44.620> of<00:05:44.919> what's<00:05:45.310> actually
we've lost the sense of what's actually
we've lost the sense of what's actually
happening<00:05:46.120> in<00:05:47.020> this<00:05:47.590> world<00:05:47.650> that<00:05:48.070> we've<00:05:48.190> made
happening in this world that we've made
happening in this world that we've made
and<00:05:48.580> we're<00:05:48.880> starting<00:05:49.419> to<00:05:49.570> make<00:05:49.840> our<00:05:50.080> way
and we're starting to make our way
and we're starting to make our way
there's<00:05:50.860> a<00:05:50.979> company<00:05:51.340> in<00:05:51.430> Boston<00:05:52.360> called
there's a company in Boston called
there's a company in Boston called
Nanak's<00:05:53.050> and<00:05:53.550> they<00:05:54.550> use<00:05:54.789> math<00:05:55.389> and<00:05:55.840> magic<00:05:56.260> and
Nanak's and they use math and magic and
Nanak's and they use math and magic and
I<00:05:56.860> don't<00:05:56.889> know<00:05:57.159> what<00:05:57.460> and<00:05:57.669> they<00:05:58.030> reach<00:05:58.330> in<00:05:58.630> to
I don't know what and they reach in to
I don't know what and they reach in to
all<00:05:59.080> the<00:05:59.229> market<00:05:59.560> data<00:05:59.740> and<00:05:59.949> they<00:06:00.789> find
all the market data and they find
all the market data and they find
actually<00:06:01.780> sometimes<00:06:02.229> some<00:06:02.470> of<00:06:02.500> these
actually sometimes some of these
actually sometimes some of these
algorithms<00:06:02.949> and<00:06:03.400> they<00:06:03.550> when<00:06:03.970> they<00:06:04.090> find<00:06:04.360> them
algorithms and they when they find them
algorithms and they when they find them
they<00:06:04.570> they<00:06:04.990> pull<00:06:05.680> them<00:06:05.889> out<00:06:06.010> and<00:06:06.220> they<00:06:06.280> pin
they they pull them out and they pin
they they pull them out and they pin
them<00:06:06.970> to<00:06:07.120> the<00:06:07.210> wall<00:06:07.389> like<00:06:07.659> butterflies<00:06:08.229> and
them to the wall like butterflies and
them to the wall like butterflies and
they<00:06:09.669> do<00:06:09.729> what<00:06:10.090> we've<00:06:10.270> always<00:06:10.539> done<00:06:10.780> when
they do what we've always done when
they do what we've always done when
confronted<00:06:12.010> with<00:06:12.159> huge<00:06:12.610> amounts<00:06:12.909> of<00:06:13.030> data
confronted with huge amounts of data
confronted with huge amounts of data
that<00:06:13.360> we<00:06:13.570> don't<00:06:13.720> understand<00:06:14.349> which<00:06:14.860> is<00:06:14.889> that
that we don't understand which is that
that we don't understand which is that
they<00:06:15.250> give<00:06:15.400> them<00:06:15.580> a<00:06:15.669> name<00:06:15.940> and<00:06:16.240> a<00:06:16.750> story<00:06:16.810> so
they give them a name and a story so
they give them a name and a story so
this<00:06:17.949> is<00:06:18.130> one<00:06:18.280> that<00:06:18.430> they<00:06:18.550> found<00:06:19.050> they<00:06:20.050> called
this is one that they found they called
this is one that they found they called
the<00:06:21.220> knife
the<00:06:24.789> carnival
the carnival
the carnival
the<00:06:26.979> Boston<00:06:27.520> shuffler
the Boston shuffler
the Boston shuffler
Twilight<00:06:30.280> and<00:06:30.520> the
Twilight and the
Twilight and the
gag<00:06:32.710> is<00:06:33.099> that<00:06:33.430> of<00:06:33.520> course<00:06:33.750> these<00:06:34.750> aren't<00:06:35.020> just
gag is that of course these aren't just
gag is that of course these aren't just
running<00:06:35.620> through<00:06:35.860> the<00:06:35.979> market<00:06:36.400> right<00:06:36.820> you<00:06:36.970> can
running through the market right you can
running through the market right you can
find<00:06:37.599> these<00:06:38.169> kinds<00:06:38.650> of<00:06:38.740> things<00:06:39.159> wherever<00:06:39.520> you
find these kinds of things wherever you
find these kinds of things wherever you
look<00:06:39.880> once<00:06:40.240> you<00:06:40.419> learn<00:06:40.659> how<00:06:40.690> to<00:06:40.960> look<00:06:41.199> for<00:06:41.260> them
look once you learn how to look for them
look once you learn how to look for them
right<00:06:42.130> you<00:06:42.280> can<00:06:42.430> find<00:06:42.699> it<00:06:42.820> here<00:06:42.970> this<00:06:43.750> book
right you can find it here this book
right you can find it here this book
about<00:06:44.470> flies<00:06:44.889> that<00:06:45.520> you<00:06:45.669> may<00:06:45.849> have<00:06:46.000> been
about flies that you may have been
about flies that you may have been
looking<00:06:46.270> at<00:06:46.539> on<00:06:46.690> Amazon<00:06:47.349> you<00:06:47.529> may<00:06:47.650> have
looking at on Amazon you may have
looking at on Amazon you may have
noticed<00:06:48.159> it<00:06:48.340> when<00:06:48.639> its<00:06:48.820> price<00:06:49.120> started<00:06:49.690> at<00:06:49.779> 1.7
noticed it when its price started at 1.7
noticed it when its price started at 1.7
million<00:06:50.740> dollars<00:06:51.250> it's<00:06:51.870> out-of-print<00:06:52.550> still
million dollars it's out-of-print still
million dollars it's out-of-print still
if<00:06:55.290> you<00:06:55.590> had<00:06:55.800> bought<00:06:56.040> it<00:06:56.220> at<00:06:56.340> 1.7<00:06:56.850> it<00:06:57.030> would
if you had bought it at 1.7 it would
if you had bought it at 1.7 it would
have<00:06:57.240> been<00:06:57.330> a<00:06:57.360> bargain<00:06:57.720> a<00:06:57.810> few<00:06:58.050> hours<00:06:58.170> later<00:06:58.500> it
have been a bargain a few hours later it
have been a bargain a few hours later it
had<00:06:58.980> gone<00:06:59.160> up<00:06:59.370> to<00:06:59.900> twenty<00:07:00.900> three<00:07:01.200> point<00:07:01.530> six
had gone up to twenty three point six
had gone up to twenty three point six
million<00:07:02.100> dollars<00:07:02.550> plus<00:07:02.910> shipping<00:07:03.360> and
million dollars plus shipping and
million dollars plus shipping and
handling<00:07:03.630> and<00:07:04.200> the<00:07:04.620> question<00:07:05.160> is<00:07:05.340> nobody<00:07:06.000> was
handling and the question is nobody was
handling and the question is nobody was
buying<00:07:06.390> or<00:07:06.690> selling<00:07:06.720> anything<00:07:07.290> what<00:07:07.830> was
buying or selling anything what was
buying or selling anything what was
happening<00:07:08.490> and<00:07:08.610> you<00:07:08.730> see<00:07:09.000> this<00:07:09.180> behavior<00:07:09.720> on
happening and you see this behavior on
happening and you see this behavior on
Amazon<00:07:10.410> as<00:07:10.620> surely<00:07:11.040> as<00:07:11.160> you<00:07:11.190> see<00:07:11.520> it<00:07:11.610> on<00:07:11.730> Wall
Amazon as surely as you see it on Wall
Amazon as surely as you see it on Wall
Street<00:07:12.270> and<00:07:12.360> when<00:07:12.720> you<00:07:12.900> see<00:07:13.170> this<00:07:13.350> kind<00:07:13.530> of
Street and when you see this kind of
Street and when you see this kind of
behavior<00:07:13.740> what<00:07:14.250> you<00:07:14.370> see<00:07:14.670> is<00:07:14.880> the<00:07:15.240> evidence<00:07:15.270> of
behavior what you see is the evidence of
behavior what you see is the evidence of
algorithms<00:07:16.980> in<00:07:17.160> conflict<00:07:17.850> algorithms<00:07:18.780> locked
algorithms in conflict algorithms locked
algorithms in conflict algorithms locked
in<00:07:19.350> loops<00:07:19.620> with<00:07:19.890> each<00:07:20.010> other<00:07:20.220> without<00:07:20.640> any
in loops with each other without any
in loops with each other without any
human<00:07:21.750> oversight<00:07:22.410> without<00:07:22.890> any<00:07:23.100> adult
human oversight without any adult
human oversight without any adult
supervision<00:07:24.420> to<00:07:24.810> say<00:07:24.990> actually<00:07:25.580> 1.7<00:07:26.580> million
supervision to say actually 1.7 million
supervision to say actually 1.7 million
is<00:07:27.600> plenty<00:07:28.020> you<00:07:28.800> stick<00:07:29.100> with<00:07:29.250> it<00:07:29.400> and<00:07:29.960> as<00:07:30.960> with
is plenty you stick with it and as with
is plenty you stick with it and as with
Amazon<00:07:31.890> so<00:07:32.250> it<00:07:32.370> is<00:07:32.490> with<00:07:32.670> Netflix<00:07:33.020> and<00:07:34.020> so
Amazon so it is with Netflix and so
Amazon so it is with Netflix and so
Netflix<00:07:34.980> has<00:07:35.970> gone<00:07:36.180> through<00:07:36.390> several
Netflix has gone through several
Netflix has gone through several
different<00:07:37.140> algorithms<00:07:37.590> over<00:07:37.740> the<00:07:37.920> years<00:07:38.130> they
different algorithms over the years they
different algorithms over the years they
started<00:07:38.610> with<00:07:38.730> cinema<00:07:39.090> and<00:07:39.360> they've<00:07:39.450> they've
started with cinema and they've they've
started with cinema and they've they've
tried<00:07:40.230> a<00:07:40.290> bunch<00:07:40.530> of<00:07:40.620> others<00:07:40.890> there's<00:07:41.100> dinosaur
tried a bunch of others there's dinosaur
tried a bunch of others there's dinosaur
planet<00:07:41.670> there's<00:07:42.000> gravity<00:07:42.450> they're<00:07:42.630> using
planet there's gravity they're using
planet there's gravity they're using
pragmatic<00:07:43.410> chaos<00:07:43.770> now<00:07:44.070> pragmatic<00:07:44.700> chaos<00:07:45.030> is
pragmatic chaos now pragmatic chaos is
pragmatic chaos now pragmatic chaos is
like<00:07:46.320> all<00:07:46.530> of<00:07:46.830> Netflix<00:07:47.220> algorithms<00:07:47.640> trying<00:07:47.850> to
like all of Netflix algorithms trying to
like all of Netflix algorithms trying to
do<00:07:47.970> the<00:07:48.060> same<00:07:48.210> thing<00:07:48.390> it's<00:07:48.540> trying<00:07:48.780> to<00:07:48.840> get<00:07:48.900> a
do the same thing it's trying to get a
do the same thing it's trying to get a
grasp<00:07:49.230> on<00:07:49.530> you<00:07:50.100> on<00:07:50.340> the<00:07:50.400> firmware<00:07:51.330> inside<00:07:51.960> the
grasp on you on the firmware inside the
grasp on you on the firmware inside the
human<00:07:52.350> skull<00:07:52.530> so<00:07:52.920> that<00:07:53.100> it<00:07:53.370> can<00:07:53.610> recommend
human skull so that it can recommend
human skull so that it can recommend
what<00:07:54.900> movie<00:07:55.350> you<00:07:56.010> might<00:07:56.250> want<00:07:56.490> to<00:07:56.550> watch<00:07:56.730> next
what movie you might want to watch next
what movie you might want to watch next
which<00:07:57.660> is<00:07:57.780> a<00:07:57.810> very<00:07:58.230> very<00:07:58.740> difficult<00:07:59.220> problem
which is a very very difficult problem
which is a very very difficult problem
but<00:08:00.450> the<00:08:00.540> difficulty<00:08:01.020> of<00:08:01.050> the<00:08:01.230> problem<00:08:01.260> and
but the difficulty of the problem and
but the difficulty of the problem and
the<00:08:02.220> fact<00:08:02.430> that<00:08:02.460> we<00:08:02.610> don't<00:08:02.940> really<00:08:03.270> quite<00:08:03.750> have
the fact that we don't really quite have
the fact that we don't really quite have
it<00:08:04.380> down<00:08:04.640> it<00:08:05.640> doesn't<00:08:06.000> take<00:08:06.150> away<00:08:06.180> from<00:08:06.540> the
it down it doesn't take away from the
it down it doesn't take away from the
effects<00:08:07.710> the<00:08:08.010> pragmatic<00:08:08.520> chaos<00:08:08.790> has<00:08:09.000> bring
effects the pragmatic chaos has bring
effects the pragmatic chaos has bring
out<00:08:09.630> a<00:08:09.660> chaos<00:08:09.930> like<00:08:10.800> all<00:08:11.040> Netflix<00:08:11.670> algorithms
out a chaos like all Netflix algorithms
out a chaos like all Netflix algorithms
determines<00:08:12.900> in<00:08:13.170> the<00:08:13.320> end<00:08:13.880> 60%<00:08:14.880> of<00:08:15.350> what<00:08:16.350> movies
determines in the end 60% of what movies
determines in the end 60% of what movies
end<00:08:17.040> up<00:08:17.400> being<00:08:17.670> rented<00:08:18.060> right<00:08:18.360> so<00:08:18.570> one<00:08:18.930> piece
end up being rented right so one piece
end up being rented right so one piece
of<00:08:19.410> code<00:08:19.650> with<00:08:19.980> one<00:08:20.280> idea<00:08:20.810> about<00:08:21.810> you<00:08:22.230> is
of code with one idea about you is
of code with one idea about you is
responsible<00:08:24.210> for<00:08:24.240> 60%<00:08:24.720> of<00:08:25.020> those<00:08:25.170> movies<00:08:25.500> but
responsible for 60% of those movies but
responsible for 60% of those movies but
what<00:08:26.670> if<00:08:26.790> you<00:08:26.970> could<00:08:27.210> rate<00:08:27.810> those<00:08:28.080> movies
what if you could rate those movies
what if you could rate those movies
before<00:08:29.250> they<00:08:29.730> get<00:08:29.910> made<00:08:30.150> right<00:08:30.390> wouldn't<00:08:31.050> that
before they get made right wouldn't that
before they get made right wouldn't that
be<00:08:31.440> handy<00:08:31.800> well<00:08:32.070> so<00:08:32.400> a<00:08:32.430> few<00:08:32.940> data<00:08:33.150> scientists
be handy well so a few data scientists
be handy well so a few data scientists
from<00:08:34.080> the<00:08:34.140> UK<00:08:34.590> or<00:08:34.800> in<00:08:34.830> Hollywood<00:08:35.370> and<00:08:35.520> they
from the UK or in Hollywood and they
from the UK or in Hollywood and they
have<00:08:36.090> story<00:08:36.690> algorithms<00:08:37.470> and<00:08:37.710> company<00:08:38.010> called
have story algorithms and company called
have story algorithms and company called
epic<00:08:38.430> oh<00:08:38.550> jokes<00:08:38.820> and<00:08:39.150> you<00:08:39.510> can<00:08:39.690> run<00:08:39.960> your
epic oh jokes and you can run your
epic oh jokes and you can run your
script<00:08:40.620> through<00:08:41.400> there<00:08:41.670> and<00:08:41.850> they<00:08:42.210> can<00:08:42.360> tell
script through there and they can tell
script through there and they can tell
you<00:08:42.870> quantifiably<00:08:43.800> that<00:08:44.070> that's<00:08:44.220> a<00:08:44.340> 30
you quantifiably that that's a 30
you quantifiably that that's a 30
million<00:08:44.940> dollar<00:08:45.150> movie<00:08:45.510> or<00:08:45.630> a<00:08:45.660> 200<00:08:46.200> million
million dollar movie or a 200 million
million dollar movie or a 200 million
dollar<00:08:46.500> movie<00:08:47.430> and<00:08:47.610> the<00:08:48.000> thing<00:08:48.180> is<00:08:48.270> is<00:08:48.420> that
dollar movie and the thing is is that
dollar movie and the thing is is that
this<00:08:49.170> isn't<00:08:49.440> Google<00:08:49.800> right<00:08:50.400> this<00:08:50.610> isn't
this isn't Google right this isn't
this isn't Google right this isn't
information<00:08:51.900> these<00:08:52.020> aren't<00:08:52.230> financial<00:08:52.980> stats
information these aren't financial stats
information these aren't financial stats
this<00:08:53.610> is<00:08:53.820> culture<00:08:54.480> and<00:08:54.630> what<00:08:55.620> you<00:08:55.740> see<00:08:55.980> here<00:08:56.400> or
this is culture and what you see here or
this is culture and what you see here or
what<00:08:56.760> you<00:08:56.850> don't<00:08:57.090> really<00:08:57.330> see<00:08:57.720> normally<00:08:58.380> is<00:08:58.530> is
what you don't really see normally is is
what you don't really see normally is is
that<00:08:59.220> these<00:08:59.370> are<00:08:59.430> the<00:08:59.670> physics<00:09:00.180> of<00:09:00.360> culture
that these are the physics of culture
that these are the physics of culture
and
and
and
if<00:09:03.060> these<00:09:03.360> algorithms<00:09:04.170> like<00:09:04.620> the<00:09:04.770> algorithms
if these algorithms like the algorithms
if these algorithms like the algorithms
on<00:09:05.340> Wall<00:09:05.640> Street<00:09:05.940> just<00:09:06.150> crashed<00:09:06.510> one<00:09:06.930> day<00:09:07.110> and
on Wall Street just crashed one day and
on Wall Street just crashed one day and
went<00:09:07.500> awry<00:09:08.240> how<00:09:09.240> would<00:09:09.420> we<00:09:09.600> know<00:09:10.130> what<00:09:11.130> would
went awry how would we know what would
went awry how would we know what would
it<00:09:11.370> look<00:09:11.400> like<00:09:11.520> and
it look like and
it look like and
they're<00:09:13.440> in<00:09:13.590> your<00:09:13.740> house<00:09:13.980> right<00:09:14.640> there<00:09:15.540> in
they're in your house right there in
they're in your house right there in
your<00:09:15.900> house<00:09:16.080> right<00:09:16.380> these<00:09:16.590> are<00:09:16.710> two
your house right these are two
your house right these are two
algorithms<00:09:17.250> competing<00:09:17.910> for<00:09:18.060> your<00:09:18.150> living
algorithms competing for your living
algorithms competing for your living
room<00:09:18.540> these<00:09:18.690> are<00:09:18.750> two<00:09:18.990> different<00:09:19.140> cleaning
room these are two different cleaning
room these are two different cleaning
robots<00:09:20.640> that<00:09:20.940> have<00:09:21.000> very<00:09:21.450> different<00:09:21.690> ideas
robots that have very different ideas
robots that have very different ideas
about<00:09:22.410> what<00:09:22.620> clean<00:09:22.950> means<00:09:22.980> and<00:09:23.850> you<00:09:23.910> can<00:09:24.060> see
about what clean means and you can see
about what clean means and you can see
it<00:09:24.450> if<00:09:24.600> you<00:09:25.080> slow<00:09:25.380> it<00:09:25.530> down<00:09:25.560> and<00:09:25.980> attach<00:09:26.250> lights
it if you slow it down and attach lights
it if you slow it down and attach lights
to<00:09:27.150> them<00:09:27.330> and<00:09:27.510> there's<00:09:28.320> sort<00:09:28.410> of<00:09:28.500> like<00:09:28.560> secret
to them and there's sort of like secret
to them and there's sort of like secret
architects<00:09:29.820> in<00:09:29.940> your<00:09:30.120> bedroom<00:09:30.570> yeah<00:09:31.290> and<00:09:31.470> the
architects in your bedroom yeah and the
architects in your bedroom yeah and the
idea<00:09:32.310> that<00:09:32.370> architecture<00:09:32.790> itself<00:09:33.750> is<00:09:34.110> somehow
idea that architecture itself is somehow
idea that architecture itself is somehow
subject<00:09:35.100> to<00:09:35.520> algorithmic<00:09:36.090> optimization<00:09:36.750> is
subject to algorithmic optimization is
subject to algorithmic optimization is
not<00:09:37.410> far-fetched<00:09:37.890> it's<00:09:38.400> super<00:09:39.120> real<00:09:39.570> and<00:09:39.810> it's
not far-fetched it's super real and it's
not far-fetched it's super real and it's
happening<00:09:40.440> around<00:09:40.800> you<00:09:41.370> you<00:09:41.700> feel<00:09:41.730> it<00:09:42.060> most
happening around you you feel it most
happening around you you feel it most
when<00:09:43.650> you're<00:09:43.740> in<00:09:43.860> a<00:09:43.950> sealed<00:09:44.310> metal<00:09:44.520> box<00:09:45.330> a<00:09:45.840> new
when you're in a sealed metal box a new
when you're in a sealed metal box a new
style<00:09:47.400> elevator<00:09:47.850> they're<00:09:48.030> called
style elevator they're called
style elevator they're called
destination<00:09:48.570> control<00:09:49.140> elevators<00:09:49.710> these<00:09:50.070> are
destination control elevators these are
destination control elevators these are
the<00:09:50.250> ones<00:09:50.430> where<00:09:50.670> if<00:09:50.970> to<00:09:51.120> press<00:09:51.360> what<00:09:51.570> floor
the ones where if to press what floor
the ones where if to press what floor
you're<00:09:52.050> going<00:09:52.170> to<00:09:52.230> go<00:09:52.350> to<00:09:52.380> before<00:09:52.950> you<00:09:53.130> get<00:09:53.250> in
you're going to go to before you get in
you're going to go to before you get in
the<00:09:53.520> elevator<00:09:53.610> and<00:09:54.090> it<00:09:54.270> uses<00:09:54.420> what's<00:09:54.660> called<00:09:54.720> a
the elevator and it uses what's called a
the elevator and it uses what's called a
bin<00:09:55.110> packing<00:09:55.560> algorithm<00:09:55.800> so<00:09:56.400> none<00:09:56.610> of<00:09:56.640> this
bin packing algorithm so none of this
bin packing algorithm so none of this
mishegoss<00:09:57.120> of<00:09:57.570> just<00:09:57.720> letting<00:09:57.960> everybody<00:09:58.200> go
mishegoss of just letting everybody go
mishegoss of just letting everybody go
into<00:09:58.950> whatever<00:09:59.190> car<00:09:59.430> they<00:09:59.580> want<00:09:59.820> everybody
into whatever car they want everybody
into whatever car they want everybody
wants<00:10:00.930> to<00:10:00.990> go<00:10:01.110> the<00:10:01.260> tenth<00:10:01.500> floor<00:10:01.680> goes<00:10:01.920> into
wants to go the tenth floor goes into
wants to go the tenth floor goes into
car<00:10:02.370> two<00:10:02.580> and<00:10:02.820> everybody<00:10:03.060> wants<00:10:03.240> to<00:10:03.270> go<00:10:03.360> the
car two and everybody wants to go the
car two and everybody wants to go the
third<00:10:03.600> floor<00:10:03.810> goes<00:10:03.990> into<00:10:04.200> car<00:10:04.380> five<00:10:04.620> and<00:10:05.270> the
third floor goes into car five and the
third floor goes into car five and the
problem<00:10:06.720> with<00:10:06.870> that<00:10:07.050> is<00:10:07.350> is<00:10:07.530> that<00:10:07.560> people
problem with that is is that people
problem with that is is that people
freak<00:10:09.360> out<00:10:09.480> people<00:10:10.470> panic<00:10:10.920> and<00:10:10.950> you<00:10:11.160> see<00:10:11.820> why
freak out people panic and you see why
freak out people panic and you see why
right<00:10:12.750> you<00:10:13.050> see<00:10:13.260> why<00:10:13.470> it's<00:10:13.950> because<00:10:14.310> the
right you see why it's because the
right you see why it's because the
elevator<00:10:15.270> is<00:10:15.540> missing<00:10:16.260> some<00:10:16.530> important
elevator is missing some important
elevator is missing some important
instrumentation<00:10:17.730> like<00:10:17.880> the<00:10:18.060> buttons<00:10:18.450> right
instrumentation like the buttons right
instrumentation like the buttons right
like<00:10:20.550> the<00:10:20.730> things<00:10:21.000> that<00:10:21.180> people<00:10:21.480> use<00:10:21.930> all<00:10:22.530> it
like the things that people use all it
like the things that people use all it
has<00:10:23.190> is<00:10:23.670> just<00:10:24.330> the<00:10:24.990> number<00:10:25.440> that<00:10:25.890> moves<00:10:26.130> up<00:10:26.310> or
has is just the number that moves up or
has is just the number that moves up or
down<00:10:26.520> and<00:10:27.000> that<00:10:27.510> red<00:10:27.720> button<00:10:27.930> that<00:10:28.320> says<00:10:28.820> stop
down and that red button that says stop
down and that red button that says stop
and<00:10:30.650> this<00:10:31.650> is<00:10:31.800> what<00:10:31.950> we're<00:10:32.130> designing<00:10:32.550> for
and this is what we're designing for
and this is what we're designing for
we're<00:10:33.060> designing<00:10:33.570> for<00:10:33.960> this<00:10:34.320> kind<00:10:34.710> of<00:10:34.860> machine
we're designing for this kind of machine
we're designing for this kind of machine
dialect<00:10:36.780> all<00:10:37.410> right<00:10:37.500> and<00:10:37.650> how<00:10:37.980> far<00:10:38.310> can<00:10:38.520> you
dialect all right and how far can you
dialect all right and how far can you
take<00:10:38.850> that<00:10:38.910> how<00:10:39.750> far<00:10:40.020> can<00:10:40.200> you<00:10:40.230> take<00:10:40.440> it<00:10:40.530> you
take that how far can you take it you
take that how far can you take it you
can<00:10:41.010> take<00:10:41.190> it<00:10:41.310> really<00:10:41.670> really<00:10:42.000> far<00:10:42.930> and<00:10:43.110> so<00:10:43.230> let
can take it really really far and so let
can take it really really far and so let
me<00:10:43.410> take<00:10:43.560> it<00:10:43.680> back<00:10:43.950> to<00:10:44.460> Wall<00:10:44.670> Street<00:10:45.200> okay
me take it back to Wall Street okay
me take it back to Wall Street okay
because<00:10:46.680> the<00:10:46.950> algorithms<00:10:47.670> of<00:10:47.820> Wall<00:10:48.060> Street
because the algorithms of Wall Street
because the algorithms of Wall Street
are<00:10:48.630> dependent<00:10:49.620> on<00:10:49.800> one<00:10:50.250> quality<00:10:50.640> above<00:10:50.730> all
are dependent on one quality above all
are dependent on one quality above all
else<00:10:51.300> which<00:10:51.570> is<00:10:51.750> speed<00:10:52.140> and<00:10:52.320> they<00:10:53.310> operate<00:10:53.880> on
else which is speed and they operate on
else which is speed and they operate on
milliseconds<00:10:54.870> and<00:10:54.990> microseconds<00:10:55.890> and<00:10:56.040> just
milliseconds and microseconds and just
milliseconds and microseconds and just
to<00:10:56.700> give<00:10:56.850> you<00:10:56.940> a<00:10:56.970> sense<00:10:57.240> of<00:10:57.390> what<00:10:57.510> microseconds
to give you a sense of what microseconds
to give you a sense of what microseconds
are<00:10:58.230> it<00:10:58.320> takes<00:10:58.590> you<00:10:58.950> five<00:10:59.520> hundred<00:10:59.970> thousand
are it takes you five hundred thousand
are it takes you five hundred thousand
microseconds<00:11:01.140> just<00:11:01.500> to<00:11:01.590> click<00:11:01.830> a<00:11:02.010> mouse<00:11:02.280> but
microseconds just to click a mouse but
microseconds just to click a mouse but
if<00:11:03.030> you're<00:11:03.180> a<00:11:03.210> Wall<00:11:03.420> Street<00:11:03.450> algorithm<00:11:04.050> and
if you're a Wall Street algorithm and
if you're a Wall Street algorithm and
you're<00:11:04.320> five<00:11:04.650> microseconds<00:11:05.430> behind<00:11:05.570> you're<00:11:06.570> a
you're five microseconds behind you're a
you're five microseconds behind you're a
loser
loser
loser
so<00:11:09.510> if<00:11:09.630> you<00:11:09.750> were<00:11:09.870> an<00:11:09.990> algorithm<00:11:10.650> you'd<00:11:11.250> look
so if you were an algorithm you'd look
so if you were an algorithm you'd look
for<00:11:11.610> an<00:11:11.670> architect<00:11:12.150> like<00:11:12.360> the<00:11:12.480> one<00:11:12.600> that<00:11:12.750> I<00:11:12.780> met
for an architect like the one that I met
for an architect like the one that I met
in<00:11:13.080> Frankfurt<00:11:13.590> who<00:11:13.830> was<00:11:13.980> hollowing<00:11:14.610> out<00:11:14.730> a
in Frankfurt who was hollowing out a
in Frankfurt who was hollowing out a
skyscraper<00:11:15.420> throwing<00:11:15.840> out<00:11:15.960> all<00:11:15.990> the
skyscraper throwing out all the
skyscraper throwing out all the
furniture<00:11:16.470> all<00:11:17.160> the<00:11:17.460> infrastructure<00:11:18.030> for
furniture all the infrastructure for
furniture all the infrastructure for
human<00:11:18.660> use<00:11:18.690> and<00:11:18.990> just<00:11:19.080> running<00:11:19.560> steel<00:11:19.950> on<00:11:20.220> the
human use and just running steel on the
human use and just running steel on the
floors<00:11:20.880> to<00:11:21.090> get<00:11:21.210> ready<00:11:21.390> for<00:11:21.570> the<00:11:21.690> stacks<00:11:21.960> of
floors to get ready for the stacks of
floors to get ready for the stacks of
servers<00:11:22.590> to<00:11:22.620> go<00:11:22.920> in<00:11:23.130> all<00:11:24.120> so<00:11:24.690> that<00:11:24.840> an
servers to go in all so that an
servers to go in all so that an
algorithm<00:11:25.320> could<00:11:26.010> get<00:11:26.190> close<00:11:26.610> to<00:11:27.210> the
algorithm could get close to the
algorithm could get close to the
internet<00:11:27.690> and
internet and
internet and
you<00:11:29.610> think<00:11:30.000> of<00:11:30.180> the<00:11:30.300> Internet<00:11:30.660> as<00:11:30.840> this<00:11:31.080> kind
you think of the Internet as this kind
you think of the Internet as this kind
of<00:11:31.529> distributed<00:11:32.070> system<00:11:32.700> and<00:11:32.850> of<00:11:32.940> course<00:11:32.970> it
of distributed system and of course it
of distributed system and of course it
is<00:11:33.330> but<00:11:33.510> it's<00:11:33.660> distributed<00:11:34.260> from<00:11:34.950> places
is but it's distributed from places
is but it's distributed from places
right<00:11:35.730> in<00:11:35.850> New<00:11:36.000> York<00:11:36.300> this<00:11:36.480> is<00:11:36.630> where<00:11:36.750> it's
right in New York this is where it's
right in New York this is where it's
distributed<00:11:37.200> from<00:11:37.350> its<00:11:37.560> carrier<00:11:38.190> hotel
distributed from its carrier hotel
distributed from its carrier hotel
located<00:11:39.570> on<00:11:39.839> Hudson<00:11:40.260> Street<00:11:40.470> and<00:11:40.710> this<00:11:41.610> is
located on Hudson Street and this is
located on Hudson Street and this is
really<00:11:41.940> where<00:11:42.150> the<00:11:42.180> wires<00:11:42.630> come<00:11:43.140> right<00:11:43.470> up
really where the wires come right up
really where the wires come right up
into<00:11:43.800> the<00:11:44.010> city<00:11:44.220> and<00:11:44.870> the<00:11:45.870> reality<00:11:46.650> is<00:11:46.740> is<00:11:46.860> that
into the city and the reality is is that
into the city and the reality is is that
the<00:11:47.130> further<00:11:47.430> away<00:11:47.730> you<00:11:47.760> are<00:11:47.940> from<00:11:48.089> that
the further away you are from that
the further away you are from that
you're<00:11:48.600> a<00:11:48.630> few<00:11:48.960> microseconds<00:11:49.680> behind<00:11:49.800> every
you're a few microseconds behind every
you're a few microseconds behind every
time<00:11:50.339> these<00:11:50.910> guys<00:11:51.210> down<00:11:51.570> a<00:11:51.630> Wall<00:11:51.960> Street<00:11:51.990> Marco
time these guys down a Wall Street Marco
time these guys down a Wall Street Marco
Polo<00:11:53.010> and<00:11:53.040> Cherokee<00:11:53.580> Nation<00:11:53.910> they're<00:11:54.210> eight
Polo and Cherokee Nation they're eight
Polo and Cherokee Nation they're eight
microseconds<00:11:55.620> behind<00:11:55.860> all<00:11:56.580> these<00:11:57.420> guys<00:11:57.690> going
microseconds behind all these guys going
microseconds behind all these guys going
in<00:11:58.800> to<00:11:59.310> the<00:11:59.400> empty<00:11:59.730> buildings<00:12:00.210> being<00:12:00.540> hollowed
in to the empty buildings being hollowed
in to the empty buildings being hollowed
out<00:12:01.370> up<00:12:02.370> around<00:12:03.000> the<00:12:03.570> carrier<00:12:03.870> hotel<00:12:04.520> right
out up around the carrier hotel right
out up around the carrier hotel right
and<00:12:05.700> that's<00:12:06.360> going<00:12:06.480> to<00:12:06.600> keep<00:12:06.810> happening<00:12:07.430> we're
and that's going to keep happening we're
and that's going to keep happening we're
going<00:12:08.550> to<00:12:08.610> keep<00:12:08.790> hollowing<00:12:09.330> them<00:12:09.510> out<00:12:09.660> because
going to keep hollowing them out because
going to keep hollowing them out because
you<00:12:11.250> inch<00:12:11.670> for<00:12:12.210> inch<00:12:12.240> and<00:12:12.750> pound<00:12:13.380> for<00:12:13.650> pound
you inch for inch and pound for pound
you inch for inch and pound for pound
and<00:12:14.190> dollar<00:12:14.339> for<00:12:14.610> dollar<00:12:14.930> none<00:12:15.930> of<00:12:16.080> you<00:12:16.350> could
and dollar for dollar none of you could
and dollar for dollar none of you could
squeeze<00:12:17.010> revenue<00:12:17.520> out<00:12:17.730> of<00:12:17.790> that<00:12:18.000> space<00:12:18.360> like
squeeze revenue out of that space like
squeeze revenue out of that space like
the<00:12:19.050> Boston<00:12:19.440> shuffler<00:12:19.860> could
the Boston shuffler could
the Boston shuffler could
but<00:12:22.230> if<00:12:22.350> you<00:12:22.440> zoom<00:12:22.680> out<00:12:23.120> if<00:12:24.120> you<00:12:24.630> zoom<00:12:24.839> out<00:12:25.050> you
but if you zoom out if you zoom out you
but if you zoom out if you zoom out you
would<00:12:26.040> see<00:12:26.280> an<00:12:26.370> 825<00:12:27.240> mile<00:12:28.230> trench<00:12:28.970> between<00:12:29.970> New
would see an 825 mile trench between New
would see an 825 mile trench between New
York<00:12:30.450> City<00:12:30.839> and<00:12:31.080> Chicago's<00:12:31.890> been<00:12:32.190> built<00:12:32.430> over
York City and Chicago's been built over
York City and Chicago's been built over
the<00:12:32.700> last<00:12:32.820> few<00:12:33.060> years<00:12:33.089> by<00:12:33.570> a<00:12:33.600> company<00:12:34.080> called
the last few years by a company called
the last few years by a company called
spread<00:12:34.589> networks<00:12:35.390> this<00:12:36.390> is<00:12:36.540> a<00:12:36.570> fiber-optic
spread networks this is a fiber-optic
spread networks this is a fiber-optic
cable<00:12:37.860> that<00:12:38.040> was<00:12:38.130> laid<00:12:38.460> between<00:12:39.120> those<00:12:39.330> two
cable that was laid between those two
cable that was laid between those two
cities<00:12:39.870> to<00:12:40.460> just<00:12:41.460> be<00:12:41.700> able<00:12:41.850> to<00:12:42.030> traffic<00:12:42.390> one
cities to just be able to traffic one
cities to just be able to traffic one
signal<00:12:43.310> 37<00:12:44.310> times<00:12:44.490> faster<00:12:44.970> than<00:12:45.120> you<00:12:45.210> can
signal 37 times faster than you can
signal 37 times faster than you can
click<00:12:45.570> a<00:12:45.600> mouse<00:12:46.190> just<00:12:47.190> for<00:12:47.790> these<00:12:48.270> algorithms
click a mouse just for these algorithms
click a mouse just for these algorithms
just<00:12:49.410> for<00:12:50.070> the<00:12:50.160> carnival<00:12:50.670> and<00:12:50.820> the<00:12:50.880> knife<00:12:51.450> and
just for the carnival and the knife and
just for the carnival and the knife and
when<00:12:52.800> you<00:12:52.920> think<00:12:53.250> about<00:12:53.339> this<00:12:53.730> that<00:12:54.300> we're
when you think about this that we're
when you think about this that we're
running<00:12:55.170> through<00:12:55.950> the<00:12:56.100> United<00:12:56.610> States<00:12:56.640> with
running through the United States with
running through the United States with
dynamite<00:12:57.690> and<00:12:57.930> rock<00:12:58.620> saws<00:12:59.180> so<00:13:00.180> that<00:13:00.360> an
dynamite and rock saws so that an
dynamite and rock saws so that an
algorithm<00:13:00.839> can<00:13:01.230> close<00:13:01.530> the<00:13:01.770> deal<00:13:02.010> three
algorithm can close the deal three
algorithm can close the deal three
microseconds<00:13:03.450> faster<00:13:04.080> all<00:13:04.350> for<00:13:05.130> a
microseconds faster all for a
microseconds faster all for a
communications<00:13:05.880> framework<00:13:06.270> that<00:13:06.540> no<00:13:06.780> human
communications framework that no human
communications framework that no human
will<00:13:07.530> ever<00:13:07.560> know
will ever know
will ever know
that's<00:13:11.040> a<00:13:11.160> kind<00:13:11.400> of<00:13:11.490> manifest<00:13:12.030> destiny<00:13:12.150> and
that's a kind of manifest destiny and
that's a kind of manifest destiny and
we'll<00:13:13.440> always<00:13:13.650> look<00:13:14.070> for<00:13:14.339> a<00:13:14.370> new<00:13:14.550> frontier<00:13:15.180> and
we'll always look for a new frontier and
we'll always look for a new frontier and
fortunately<00:13:16.620> we<00:13:17.190> have<00:13:17.339> our<00:13:17.490> work<00:13:17.640> cut<00:13:17.880> out<00:13:17.910> for
fortunately we have our work cut out for
fortunately we have our work cut out for
us<00:13:18.300> this<00:13:18.860> is<00:13:19.860> just<00:13:19.980> theoretical<00:13:20.640> this<00:13:20.940> is<00:13:21.089> some
us this is just theoretical this is some
us this is just theoretical this is some
mathematicians<00:13:22.020> at<00:13:22.440> MIT<00:13:22.709> and<00:13:23.100> the<00:13:23.910> truth<00:13:24.180> is<00:13:24.390> I
mathematicians at MIT and the truth is I
mathematicians at MIT and the truth is I
don't<00:13:24.810> really<00:13:25.170> understand<00:13:25.920> a<00:13:26.130> lot<00:13:26.370> of<00:13:26.490> what
don't really understand a lot of what
don't really understand a lot of what
they're<00:13:26.790> talking<00:13:27.180> about<00:13:27.209> it<00:13:27.750> involves<00:13:28.290> light
they're talking about it involves light
they're talking about it involves light
cones<00:13:29.220> and<00:13:29.550> quantum<00:13:29.970> entanglement<00:13:30.780> and<00:13:30.930> I
cones and quantum entanglement and I
cones and quantum entanglement and I
don't<00:13:31.140> really<00:13:31.560> understand<00:13:32.160> any<00:13:32.280> of<00:13:32.310> that<00:13:32.370> but
don't really understand any of that but
don't really understand any of that but
I<00:13:32.610> can<00:13:32.960> this<00:13:33.140> map<00:13:33.380> and<00:13:34.010> what<00:13:34.790> this<00:13:34.940> map<00:13:35.210> says<00:13:35.630> is
I can this map and what this map says is
I can this map and what this map says is
is<00:13:36.350> that<00:13:36.529> if<00:13:36.680> you're<00:13:36.920> trying<00:13:37.250> to<00:13:37.430> make<00:13:37.610> money
is that if you're trying to make money
is that if you're trying to make money
on<00:13:38.089> the<00:13:38.210> markets<00:13:38.660> where<00:13:38.839> the<00:13:38.960> red<00:13:39.170> dots<00:13:39.500> are
on the markets where the red dots are
on the markets where the red dots are
that's<00:13:39.980> where<00:13:40.160> people<00:13:40.550> are<00:13:40.850> where<00:13:41.000> the<00:13:41.149> cities
that's where people are where the cities
that's where people are where the cities
are<00:13:41.630> your<00:13:41.990> going<00:13:42.110> to<00:13:42.170> have<00:13:42.260> to<00:13:42.320> put<00:13:42.529> the
are your going to have to put the
are your going to have to put the
servers<00:13:43.160> where<00:13:43.399> the<00:13:43.520> blue<00:13:43.700> dots<00:13:43.970> are<00:13:44.270> to<00:13:44.779> do
servers where the blue dots are to do
servers where the blue dots are to do
that<00:13:45.170> most<00:13:45.380> effectively<00:13:45.589> and<00:13:46.339> the<00:13:46.700> thing<00:13:46.880> that
that most effectively and the thing that
that most effectively and the thing that
you<00:13:47.330> might<00:13:47.510> have<00:13:47.630> noticed<00:13:47.839> about<00:13:48.200> those<00:13:48.560> blue
you might have noticed about those blue
you might have noticed about those blue
dots<00:13:49.100> is<00:13:49.339> that<00:13:49.490> a<00:13:49.520> lot<00:13:49.730> of<00:13:49.760> them<00:13:49.970> are<00:13:50.120> in<00:13:50.690> the
dots is that a lot of them are in the
dots is that a lot of them are in the
middle<00:13:51.050> of<00:13:51.110> the<00:13:51.170> ocean
middle of the ocean
middle of the ocean
so<00:13:53.060> that's<00:13:53.300> what<00:13:53.510> we'll<00:13:53.660> do<00:13:53.810> we'll<00:13:54.020> build
so that's what we'll do we'll build
so that's what we'll do we'll build
bubbles<00:13:55.010> or<00:13:55.250> something<00:13:55.610> or<00:13:55.730> or<00:13:55.990> platforms
bubbles or something or or platforms
bubbles or something or or platforms
will<00:13:57.200> actually<00:13:57.649> part<00:13:58.250> the<00:13:58.459> water<00:13:58.700> right<00:13:59.600> to
will actually part the water right to
will actually part the water right to
pull<00:14:00.170> money<00:14:00.890> out<00:14:01.220> of<00:14:01.580> the<00:14:01.640> air<00:14:01.820> because<00:14:02.180> it's<00:14:02.330> a
pull money out of the air because it's a
pull money out of the air because it's a
bright<00:14:02.779> future<00:14:03.380> if<00:14:03.770> you're<00:14:04.520> an<00:14:04.760> algorithm<00:14:05.380> and
bright future if you're an algorithm and
bright future if you're an algorithm and
it's<00:14:07.970> not<00:14:08.089> the<00:14:08.240> money<00:14:08.540> that's<00:14:09.230> so<00:14:09.500> interesting
it's not the money that's so interesting
it's not the money that's so interesting
actually<00:14:10.250> it's<00:14:10.670> what<00:14:10.850> the<00:14:11.000> money<00:14:11.209> motivates
actually it's what the money motivates
actually it's what the money motivates
right<00:14:12.709> that<00:14:13.040> we're<00:14:13.190> actually<00:14:13.870> terraforming
right that we're actually terraforming
right that we're actually terraforming
the<00:14:15.320> earth<00:14:15.589> itself<00:14:16.220> with<00:14:17.000> this<00:14:17.089> kind<00:14:17.360> of
the earth itself with this kind of
the earth itself with this kind of
algorithmic<00:14:17.839> efficiency<00:14:18.140> and<00:14:18.830> in<00:14:19.520> that<00:14:19.700> light
algorithmic efficiency and in that light
algorithmic efficiency and in that light
you<00:14:20.390> go<00:14:21.020> back<00:14:21.260> and<00:14:21.620> you<00:14:21.770> look<00:14:21.920> at<00:14:22.040> Michael<00:14:22.370> no
you go back and you look at Michael no
you go back and you look at Michael no
jars<00:14:22.760> photographs<00:14:23.450> and<00:14:23.870> you<00:14:24.649> realize<00:14:24.980> that
jars photographs and you realize that
jars photographs and you realize that
they're<00:14:25.370> not<00:14:25.490> metaphor<00:14:26.089> they're<00:14:26.779> prophecy
they're not metaphor they're prophecy
they're not metaphor they're prophecy
right<00:14:28.220> they're<00:14:28.430> prophecy<00:14:29.029> for<00:14:29.540> the<00:14:29.600> kind<00:14:29.779> of
right they're prophecy for the kind of
right they're prophecy for the kind of
seismic
seismic
seismic
terrestrial<00:14:32.660> effects<00:14:33.230> of<00:14:33.380> the<00:14:33.770> math<00:14:34.010> that
terrestrial effects of the math that
terrestrial effects of the math that
we're<00:14:34.850> making<00:14:35.000> and<00:14:35.390> the<00:14:36.350> the<00:14:36.740> landscape<00:14:37.250> was
we're making and the the landscape was
we're making and the the landscape was
always<00:14:37.970> made<00:14:38.270> by<00:14:38.630> this<00:14:38.690> sort<00:14:39.110> of<00:14:39.170> weird<00:14:39.920> uneasy
always made by this sort of weird uneasy
always made by this sort of weird uneasy
collaboration<00:14:41.300> between<00:14:41.540> nature<00:14:42.020> and<00:14:42.440> man<00:14:43.180> but
collaboration between nature and man but
collaboration between nature and man but
now<00:14:44.330> there's<00:14:44.600> this<00:14:44.720> kind<00:14:44.870> of<00:14:44.990> third
now there's this kind of third
now there's this kind of third
co-evolutionary<00:14:46.400> force<00:14:47.050> algorithms<00:14:48.050> the
co-evolutionary force algorithms the
co-evolutionary force algorithms the
Boston<00:14:48.980> shuffler<00:14:49.459> the<00:14:49.940> carnival<00:14:50.480> and<00:14:50.630> we<00:14:51.380> will
Boston shuffler the carnival and we will
Boston shuffler the carnival and we will
have<00:14:51.680> to<00:14:51.800> understand<00:14:52.310> those<00:14:52.580> as<00:14:52.820> nature<00:14:53.209> and
have to understand those as nature and
have to understand those as nature and
in<00:14:54.050> a<00:14:54.140> way<00:14:54.320> they<00:14:55.130> are<00:14:55.240> thank
in a way they are thank
in a way they are thank
[Applause]
[Applause]
[Applause]
[Music]
Kevin Slavin, TEDEducation, TED-Ed, TED, Ed, code, algorithms, math mathematics computer
