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I<00:00:20.020><c> just</c><00:00:21.020><c> find</c><00:00:21.200><c> AI</c><00:00:21.380><c> is</c><00:00:21.560><c> actually</c><00:00:22.010><c> way</c><00:00:22.310><c> too</c><00:00:22.340><c> broad</c>

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I just find AI is actually way too broad
 

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I just find AI is actually way too broad
and<00:00:22.970><c> it's</c><00:00:23.180><c> actually</c><00:00:23.420><c> it's</c><00:00:23.630><c> actually</c><00:00:23.900><c> several</c>

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and it's actually it's actually several
 

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and it's actually it's actually several
subfields<00:00:24.460><c> so</c><00:00:25.460><c> when</c><00:00:25.610><c> people</c><00:00:25.730><c> think</c><00:00:25.880><c> about</c><00:00:26.090><c> AI</c>

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subfields so when people think about AI
 

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subfields so when people think about AI
they<00:00:27.230><c> should</c><00:00:27.380><c> think</c><00:00:27.500><c> about</c><00:00:27.619><c> the</c><00:00:28.369><c> first</c><00:00:28.790><c> thing</c>

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they should think about the first thing
 

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they should think about the first thing
should<00:00:29.090><c> ask</c><00:00:29.240><c> is</c><00:00:29.450><c> what</c><00:00:29.960><c> field</c><00:00:30.230><c> and</c><00:00:30.500><c> by</c><00:00:31.189><c> default</c>

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should ask is what field and by default
 

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should ask is what field and by default
you<00:00:31.790><c> should</c><00:00:31.939><c> probably</c><00:00:32.090><c> think</c><00:00:32.270><c> machine</c>

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you should probably think machine
 

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you should probably think machine
learning<00:00:32.989><c> and</c><00:00:33.280><c> then</c><00:00:34.280><c> in</c><00:00:34.579><c> the</c><00:00:34.700><c> context</c><00:00:35.090><c> of</c><00:00:35.180><c> my</c>

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learning and then in the context of my
 

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learning and then in the context of my
work<00:00:35.480><c> we're</c><00:00:36.440><c> departing</c><00:00:36.710><c> company</c><00:00:37.160><c> so</c>

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work we're departing company so
 

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work we're departing company so
everything<00:00:38.510><c> everything</c><00:00:38.930><c> we</c><00:00:39.020><c> do</c><00:00:39.140><c> in</c><00:00:39.320><c> AI</c><00:00:39.470><c> is</c>

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everything everything we do in AI is
 

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everything everything we do in AI is
machine<00:00:40.790><c> intelligence</c><00:00:41.000><c> related</c><00:00:41.570><c> deep</c>

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machine intelligence related deep
 

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machine intelligence related deep
learning<00:00:41.780><c> related</c><00:00:46.059><c> right</c><00:00:47.059><c> so</c><00:00:47.329><c> a</c><00:00:47.660><c> lot</c><00:00:47.899><c> well</c><00:00:48.109><c> so</c>

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learning related right so a lot well so
 

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learning related right so a lot well so
a<00:00:48.800><c> lot</c><00:00:49.219><c> of</c><00:00:49.460><c> honestly</c><00:00:50.120><c> a</c><00:00:50.149><c> lot</c><00:00:50.539><c> of</c><00:00:50.660><c> what</c><00:00:50.839><c> works</c>

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a lot of honestly a lot of what works
 

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a lot of honestly a lot of what works
right<00:00:51.260><c> now</c><00:00:51.410><c> is</c><00:00:51.679><c> we</c><00:00:52.460><c> can</c><00:00:52.640><c> count</c><00:00:52.879><c> things</c><00:00:53.179><c> and</c><00:00:53.420><c> we</c>

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right now is we can count things and we
 

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right now is we can count things and we
can<00:00:53.629><c> we</c><00:00:53.839><c> can</c><00:00:53.870><c> point</c><00:00:54.230><c> at</c><00:00:54.350><c> things</c><00:00:54.559><c> so</c><00:00:55.339><c> we</c><00:00:55.489><c> can</c>

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can we can point at things so we can
 

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can we can point at things so we can
count<00:00:55.879><c> and</c><00:00:56.030><c> we</c><00:00:56.120><c> can</c><00:00:56.269><c> label</c><00:00:56.859><c> that's</c><00:00:57.859><c> what</c><00:00:58.070><c> works</c>

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count and we can label that's what works
 

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count and we can label that's what works
really<00:00:58.399><c> well</c><00:00:58.579><c> right</c><00:00:58.730><c> now</c><00:00:58.789><c> and</c><00:00:58.910><c> that's</c><00:00:59.120><c> what</c>

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really well right now and that's what
 

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really well right now and that's what
that's<00:00:59.449><c> what</c><00:00:59.570><c> most</c><00:00:59.719><c> people</c><00:00:59.989><c> are</c><00:01:00.050><c> actually</c>

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that's what most people are actually
 

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that's what most people are actually
deploying<00:01:00.679><c> you</c><00:01:01.309><c> might</c><00:01:01.519><c> and</c><00:01:01.699><c> then</c><00:01:01.789><c> you</c><00:01:01.909><c> may</c><00:01:02.030><c> be</c>

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deploying you might and then you may be
 

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deploying you might and then you may be
you<00:01:02.449><c> might</c><00:01:02.659><c> add</c><00:01:02.809><c> forecasting</c><00:01:03.530><c> in</c><00:01:03.620><c> there</c>

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you might add forecasting in there
 

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you might add forecasting in there
everything<00:01:05.360><c> else</c><00:01:05.480><c> doesn't</c><00:01:06.550><c> so</c><00:01:07.550><c> if</c><00:01:07.730><c> you</c><00:01:07.850><c> hear</c>

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everything else doesn't so if you hear
 

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everything else doesn't so if you hear
about<00:01:08.150><c> some</c><00:01:08.540><c> new</c><00:01:08.690><c> paper</c><00:01:08.900><c> from</c><00:01:09.770><c> Google</c><00:01:10.270><c> it's</c>

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about some new paper from Google it's
 

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about some new paper from Google it's
probably<00:01:11.600><c> not</c><00:01:11.690><c> gonna</c><00:01:11.810><c> work</c><00:01:12.020><c> for</c><00:01:12.230><c> you</c><00:01:12.380><c> because</c>

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probably not gonna work for you because
 

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probably not gonna work for you because
it's<00:01:13.640><c> actually</c><00:01:13.760><c> just</c><00:01:14.090><c> it's</c><00:01:14.300><c> a</c><00:01:14.450><c> bleeding</c><00:01:15.140><c> edge</c>

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it's actually just it's a bleeding edge
 

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it's actually just it's a bleeding edge
paper<00:01:15.560><c> meant</c><00:01:16.159><c> to</c><00:01:16.220><c> demonstrate</c><00:01:16.370><c> a</c><00:01:16.670><c> concept</c>

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paper meant to demonstrate a concept
 

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paper meant to demonstrate a concept
like<00:01:17.120><c> most</c><00:01:17.659><c> AI</c><00:01:17.900><c> out</c><00:01:18.140><c> there</c><00:01:18.350><c> that</c><00:01:18.620><c> you</c><00:01:18.680><c> see</c><00:01:18.710><c> is</c>

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like most AI out there that you see is
 

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like most AI out there that you see is
that's<00:01:19.130><c> really</c><00:01:19.280><c> cool</c>

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that's really cool
 

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that's really cool
is<00:01:19.910><c> actually</c><00:01:20.480><c> just</c><00:01:20.600><c> a</c><00:01:20.660><c> proof</c><00:01:20.780><c> of</c><00:01:20.930><c> concept</c><00:01:21.260><c> for</c>

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is actually just a proof of concept for
 

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is actually just a proof of concept for
something<00:01:22.250><c> that's</c><00:01:22.370><c> gonna</c><00:01:22.460><c> be</c><00:01:22.640><c> built</c><00:01:22.880><c> on</c><00:01:23.000><c> over</c>

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something that's gonna be built on over
 

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something that's gonna be built on over
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time and then within with it so within
 

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time and then within with it so within
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my subfield it turns out that's how we
 

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my subfield it turns out that's how we
make<00:01:28.160><c> money</c><00:01:28.310><c> we</c><00:01:28.580><c> label</c><00:01:29.270><c> and</c><00:01:29.390><c> count</c><00:01:29.540><c> things</c><00:01:29.810><c> and</c>

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make money we label and count things and
 

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make money we label and count things and
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we do forecasting and then from there it
 

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we do forecasting and then from there it
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just depends on the vertical that you're
 

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just depends on the vertical that you're
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um<00:01:39.860><c> honestly</c><00:01:40.460><c> like</c><00:01:41.680><c> actually</c><00:01:42.680><c> the</c><00:01:43.400><c> hype</c><00:01:44.020><c> the</c>

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um honestly like actually the hype the
 

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um honestly like actually the hype the
hut<00:01:45.200><c> you</c><00:01:45.230><c> know</c><00:01:45.380><c> cuz</c><00:01:45.620><c> because</c><00:01:45.950><c> you</c><00:01:46.280><c> know</c>

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hut you know cuz because you know
 

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hut you know cuz because you know
because<00:01:46.460><c> we</c><00:01:46.640><c> build</c><00:01:46.850><c> deep</c><00:01:47.030><c> learning</c><00:01:47.120><c> for</c><00:01:47.360><c> the</c>

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because we build deep learning for the
 

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because we build deep learning for the
fortune<00:01:47.690><c> 2000</c><00:01:48.260><c> and</c><00:01:48.440><c> a</c><00:01:48.520><c> lot</c><00:01:49.520><c> of</c><00:01:49.610><c> those</c><00:01:49.700><c> guys</c>

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fortune 2000 and a lot of those guys
 

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fortune 2000 and a lot of those guys
don't<00:01:50.570><c> care</c><00:01:50.990><c> what</c><00:01:51.230><c> the</c><00:01:51.320><c> algorithm</c><00:01:51.710><c> is</c><00:01:51.740><c> they</c>

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don't care what the algorithm is they
 

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don't care what the algorithm is they
don't<00:01:52.160><c> care</c><00:01:52.370><c> what</c><00:01:52.430><c> the</c><00:01:52.550><c> math</c><00:01:52.730><c> is</c><00:01:52.960><c> they</c><00:01:53.960><c> just</c>

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don't care what the math is they just
 

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don't care what the math is they just
they<00:01:54.410><c> see</c><00:01:54.980><c> the</c><00:01:55.220><c> hype</c><00:01:55.370><c> and</c><00:01:55.520><c> they're</c><00:01:55.640><c> just</c><00:01:55.730><c> like</c>

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they see the hype and they're just like
 

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they see the hype and they're just like
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it's magic right you can do anything I'm
 

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it's magic right you can do anything I'm
like<00:01:58.160><c> no</c><00:01:58.310><c> no</c><00:01:58.370><c> no</c><00:01:58.460><c> so</c><00:01:58.850><c> there's</c><00:01:59.480><c> a</c><00:01:59.540><c> lot</c><00:01:59.690><c> of</c>

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like no no no so there's a lot of
 

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like no no no so there's a lot of
problems<00:02:00.050><c> here</c><00:02:00.260><c> and</c><00:02:00.800><c> then</c><00:02:00.980><c> half</c><00:02:01.550><c> of</c><00:02:01.640><c> what</c><00:02:01.790><c> I</c><00:02:01.820><c> do</c>

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problems here and then half of what I do
 

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problems here and then half of what I do
is<00:02:02.150><c> market</c><00:02:02.390><c> education</c><00:02:02.510><c> so</c><00:02:03.200><c> if</c><00:02:03.590><c> I</c><00:02:03.920><c> could</c><00:02:04.100><c> you</c>

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is market education so if I could you
 

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is market education so if I could you
know<00:02:04.340><c> the</c><00:02:04.850><c> other</c><00:02:04.940><c> thing</c><00:02:05.180><c> is</c><00:02:05.360><c> you</c><00:02:06.140><c> know</c><00:02:06.200><c> data</c>

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know the other thing is you know data
 

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know the other thing is you know data
scientists<00:02:07.040><c> they</c><00:02:07.520><c> you</c><00:02:07.910><c> know</c><00:02:08.000><c> they</c><00:02:08.149><c> think</c>

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scientists they you know they think
 

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scientists they you know they think
because<00:02:08.930><c> they</c><00:02:09.080><c> can</c><00:02:09.200><c> spin</c><00:02:09.410><c> up</c><00:02:09.500><c> AWS</c><00:02:09.950><c> and</c><00:02:10.160><c> they</c>

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because they can spin up AWS and they
 

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because they can spin up AWS and they
can<00:02:10.850><c> run</c><00:02:11.000><c> a</c><00:02:11.030><c> tutorial</c><00:02:11.360><c> that</c><00:02:11.540><c> they're</c><00:02:11.840><c> deep</c>

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can run a tutorial that they're deep
 

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can run a tutorial that they're deep
learning<00:02:12.080><c> expert</c><00:02:13.030><c> no</c><00:02:14.030><c> you're</c><00:02:14.180><c> not</c><00:02:14.300><c> you</c><00:02:15.140><c> have</c><00:02:15.290><c> a</c>

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learning expert no you're not you have a
 

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learning expert no you're not you have a
lot<00:02:15.500><c> of</c><00:02:15.560><c> work</c><00:02:15.680><c> to</c><00:02:15.800><c> do</c><00:02:15.890><c> like</c><00:02:16.100><c> neural</c><00:02:16.310><c> nets</c>

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lot of work to do like neural nets
 

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lot of work to do like neural nets
themselves<00:02:17.060><c> are</c><00:02:17.470><c> empirical</c><00:02:18.470><c> you</c><00:02:18.980><c> need</c><00:02:19.220><c> to</c>

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themselves are empirical you need to
 

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themselves are empirical you need to
tune<00:02:19.490><c> them</c><00:02:19.670><c> you</c><00:02:19.790><c> need</c><00:02:19.940><c> to</c><00:02:20.000><c> spend</c><00:02:20.270><c> time</c>

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tune them you need to spend time
 

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tune them you need to spend time
actually<00:02:20.780><c> trying</c><00:02:21.050><c> to</c><00:02:21.110><c> understand</c><00:02:21.560><c> what</c><00:02:22.460><c> does</c>

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actually trying to understand what does
 

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actually trying to understand what does
this<00:02:22.790><c> graph</c><00:02:23.030><c> tell</c><00:02:23.330><c> me</c><00:02:23.510><c> you</c><00:02:23.750><c> get</c><00:02:23.930><c> you</c><00:02:24.050><c> need</c><00:02:24.230><c> to</c>

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this graph tell me you get you need to
 

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this graph tell me you get you need to
do<00:02:24.440><c> that</c><00:02:24.620><c> if</c><00:02:24.740><c> you're</c><00:02:24.860><c> gonna</c><00:02:24.950><c> do</c><00:02:25.310><c> like</c><00:02:25.550><c> if</c>

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do that if you're gonna do like if
 

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do that if you're gonna do like if
you're<00:02:25.910><c> gonna</c><00:02:26.000><c> succeed</c><00:02:26.240><c> in</c><00:02:26.510><c> this</c><00:02:26.600><c> field</c><00:02:26.660><c> it's</c>

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you're gonna succeed in this field it's
 

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you're gonna succeed in this field it's
not<00:02:27.530><c> magic</c><00:02:28.040><c> and</c><00:02:28.160><c> you</c><00:02:28.550><c> shouldn't</c><00:02:28.820><c> treat</c><00:02:28.940><c> it</c><00:02:29.060><c> as</c>

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not magic and you shouldn't treat it as
 

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not magic and you shouldn't treat it as
such<00:02:33.610><c> so</c><00:02:34.610><c> I</c><00:02:34.640><c> so</c><00:02:35.540><c> I</c><00:02:35.570><c> mean</c><00:02:35.870><c> I've</c><00:02:35.960><c> been</c><00:02:36.080><c> a</c><00:02:36.110><c> speaker</c>

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such so I so I mean I've been a speaker
 

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such so I so I mean I've been a speaker
to<00:02:36.680><c> Lexi's</c><00:02:36.950><c> conferences</c><00:02:37.430><c> for</c><00:02:37.880><c> last</c><00:02:38.390><c> couple</c>

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to Lexi's conferences for last couple
 

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to Lexi's conferences for last couple
years<00:02:38.690><c> now</c><00:02:38.900><c> and</c><00:02:39.410><c> I</c><00:02:39.890><c> always</c><00:02:40.250><c> love</c><00:02:40.610><c> how</c>

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years now and I always love how
 

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years now and I always love how
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down-to-earth and practical the
 

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down-to-earth and practical the
conference's<00:02:43.970><c> are</c><00:02:44.230><c> you</c><00:02:45.230><c> know</c><00:02:45.350><c> it's</c><00:02:45.560><c> great</c>

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conference's are you know it's great
 

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conference's are you know it's great
networking<00:02:46.070><c> he</c><00:02:46.489><c> gets</c><00:02:46.640><c> great</c><00:02:46.760><c> speakers</c><00:02:47.150><c> in</c><00:02:47.270><c> the</c>

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networking he gets great speakers in the
 

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networking he gets great speakers in the
room<00:02:47.540><c> he</c><00:02:48.020><c> always</c><00:02:48.170><c> picks</c><00:02:48.410><c> amazing</c><00:02:48.830><c> venues</c><00:02:49.390><c> and</c>

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room he always picks amazing venues and
 

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room he always picks amazing venues and
then<00:02:50.750><c> oh</c><00:02:50.840><c> you</c><00:02:51.050><c> know</c><00:02:51.140><c> so</c><00:02:51.260><c> the</c><00:02:51.350><c> networking</c><00:02:51.620><c> is</c>

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then oh you know so the networking is
 

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then oh you know so the networking is
quality<00:02:52.190><c> you</c><00:02:52.880><c> know</c><00:02:53.000><c> the</c><00:02:53.330><c> you</c><00:02:53.930><c> know</c><00:02:54.050><c> it</c><00:02:54.230><c> this</c>

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quality you know the you know it this
 

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quality you know the you know it this
the<00:02:54.800><c> conference</c><00:02:55.190><c> is</c><00:02:55.310><c> small</c><00:02:55.570><c> which</c><00:02:56.570><c> is</c><00:02:56.600><c> amazing</c>

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the conference is small which is amazing
 

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the conference is small which is amazing
like<00:02:57.260><c> it's</c><00:02:57.410><c> it's</c><00:02:57.650><c> just</c><00:02:57.980><c> the</c><00:02:58.070><c> right</c><00:02:58.190><c> size</c><00:02:58.250><c> for</c>

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like it's it's just the right size for
 

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like it's it's just the right size for
you<00:02:59.030><c> to</c><00:02:59.120><c> get</c><00:02:59.239><c> networking</c><00:02:59.660><c> in</c><00:02:59.810><c> and</c><00:03:00.110><c> and</c><00:03:00.320><c> all</c>

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you to get networking in and and all
 

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you to get networking in and and all
that<00:03:00.590><c> other</c><00:03:00.680><c> stuff</c><00:03:00.770><c> so</c><00:03:01.370><c> it's</c><00:03:01.520><c> it's</c><00:03:01.730><c> just</c><00:03:01.880><c> a</c><00:03:01.970><c> sum</c>

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that other stuff so it's it's just a sum
 

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that other stuff so it's it's just a sum
of<00:03:02.480><c> a</c><00:03:02.720><c> lot</c><00:03:03.110><c> of</c><00:03:03.140><c> small</c><00:03:03.320><c> things</c>

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of a lot of small things
 

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of a lot of small things
you