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my<00:00:14.010><c> name</c><00:00:14.160><c> is</c><00:00:14.280><c> Adam</c><00:00:14.549><c> Pingle</c><00:00:14.879><c> I</c><00:00:15.059><c> worked</c><00:00:15.510><c> for</c>

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my name is Adam Pingle I worked for
 

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my name is Adam Pingle I worked for
LexisNexis<00:00:16.440><c> where</c><00:00:16.650><c> I'm</c><00:00:16.740><c> a</c><00:00:16.860><c> senior</c><00:00:17.279><c> director</c>

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LexisNexis where I'm a senior director
 

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LexisNexis where I'm a senior director
of<00:00:17.610><c> software</c><00:00:18.029><c> engineering</c><00:00:18.330><c> I</c><00:00:23.810><c> think</c><00:00:24.810><c> for</c><00:00:25.230><c> us</c>

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of software engineering I think for us
 

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of software engineering I think for us
we're<00:00:26.370><c> building</c><00:00:26.640><c> end-to-end</c><00:00:26.970><c> products</c><00:00:27.720><c> all</c>

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we're building end-to-end products all
 

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we're building end-to-end products all
the<00:00:28.410><c> way</c><00:00:28.500><c> from</c><00:00:28.710><c> data</c><00:00:28.920><c> science</c><00:00:29.280><c> through</c><00:00:29.520><c> to</c>

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the way from data science through to
 

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the way from data science through to
front-end<00:00:31.380><c> application</c><00:00:31.950><c> and</c><00:00:32.129><c> visualizations</c>

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front-end application and visualizations
 

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front-end application and visualizations
and<00:00:33.059><c> so</c><00:00:33.270><c> I</c><00:00:33.300><c> think</c><00:00:33.510><c> the</c><00:00:33.750><c> hardest</c><00:00:33.960><c> challenge</c><00:00:34.350><c> is</c>

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and so I think the hardest challenge is
 

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and so I think the hardest challenge is
being<00:00:35.310><c> able</c><00:00:35.370><c> to</c><00:00:35.520><c> integrate</c><00:00:35.970><c> all</c><00:00:36.150><c> of</c><00:00:36.239><c> those</c>

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being able to integrate all of those
 

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being able to integrate all of those
layers<00:00:36.540><c> very</c><00:00:36.780><c> quickly</c>

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I'd<00:00:45.130><c> say</c><00:00:45.400><c> for</c><00:00:46.000><c> us</c><00:00:46.059><c> it's</c><00:00:46.450><c> the</c><00:00:47.220><c> the</c><00:00:48.220><c> amount</c><00:00:48.400><c> of</c>

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I'd say for us it's the the amount of
 

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I'd say for us it's the the amount of
data<00:00:48.760><c> and</c><00:00:48.940><c> the</c><00:00:49.330><c> complexity</c><00:00:49.780><c> of</c><00:00:49.809><c> the</c><00:00:49.930><c> data</c>

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data and the complexity of the data
 

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data and the complexity of the data
we're<00:00:50.739><c> not</c><00:00:50.890><c> necessarily</c><00:00:51.070><c> the</c><00:00:51.610><c> high</c><00:00:52.030><c> traffic</c>

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we're not necessarily the high traffic
 

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we're not necessarily the high traffic
volume<00:00:52.809><c> kind</c><00:00:53.350><c> of</c><00:00:53.500><c> site</c><00:00:53.739><c> but</c><00:00:54.670><c> the</c><00:00:54.879><c> the</c>

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volume kind of site but the the
 

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volume kind of site but the the
complexity<00:00:56.290><c> of</c><00:00:56.410><c> the</c><00:00:56.650><c> data</c><00:00:56.770><c> is</c><00:00:57.070><c> is</c><00:00:57.400><c> really</c><00:00:57.640><c> that</c>

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complexity of the data is is really that
 

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complexity of the data is is really that
the<00:00:57.910><c> biggest</c><00:00:58.180><c> scaling</c><00:00:58.809><c> issue</c><00:00:58.930><c> and</c><00:00:59.290><c> so</c><00:01:00.600><c> doing</c>

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the biggest scaling issue and so doing
 

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the biggest scaling issue and so doing
fast<00:01:02.080><c> analytics</c><00:01:02.680><c> on</c><00:01:02.920><c> the</c><00:01:03.730><c> the</c><00:01:03.970><c> kinds</c><00:01:04.300><c> of</c>

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fast analytics on the the kinds of
 

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fast analytics on the the kinds of
entities<00:01:05.229><c> that</c><00:01:05.560><c> we're</c><00:01:05.650><c> extracting</c><00:01:05.920><c> from</c><00:01:06.310><c> our</c>

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entities that we're extracting from our
 

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entities that we're extracting from our
corpus<00:01:07.360><c> of</c><00:01:07.479><c> case</c><00:01:07.660><c> law</c><00:01:07.810><c> we</c><00:01:08.470><c> need</c><00:01:08.619><c> to</c><00:01:09.009><c> get</c><00:01:09.130><c> those</c>

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corpus of case law we need to get those
 

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corpus of case law we need to get those
down<00:01:09.970><c> you</c><00:01:10.270><c> know</c><00:01:10.360><c> well</c><00:01:10.570><c> under</c><00:01:10.780><c> sub</c><00:01:10.990><c> ii</c><00:01:11.410><c> and</c>

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down you know well under sub ii and
 

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down you know well under sub ii and
those<00:01:11.619><c> can</c><00:01:11.830><c> be</c><00:01:11.860><c> pretty</c><00:01:12.509><c> substantial</c><00:01:13.509><c> queries</c>

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those can be pretty substantial queries
 

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those can be pretty substantial queries
that<00:01:14.410><c> would</c><00:01:14.530><c> involve</c><00:01:14.789><c> in</c><00:01:15.789><c> some</c><00:01:15.850><c> cases</c>

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that would involve in some cases
 

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that would involve in some cases
hundreds<00:01:16.600><c> of</c><00:01:16.660><c> thousands</c><00:01:17.020><c> of</c><00:01:17.050><c> documents</c><00:01:24.270><c> I</c>

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hundreds of thousands of documents I
 

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hundreds of thousands of documents I
think<00:01:25.810><c> well</c><00:01:26.770><c> now</c><00:01:26.800><c> now</c><00:01:27.550><c> that</c><00:01:27.789><c> we're</c><00:01:28.630><c> a</c><00:01:28.660><c> part</c><00:01:28.899><c> of</c>

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think well now now that we're a part of
 

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think well now now that we're a part of
LexisNexis<00:01:29.289><c> I</c><00:01:29.680><c> came</c><00:01:29.890><c> in</c><00:01:30.070><c> through</c><00:01:30.280><c> an</c>

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LexisNexis I came in through an
 

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LexisNexis I came in through an
acquisition<00:01:30.759><c> five</c><00:01:31.300><c> months</c><00:01:31.539><c> ago</c><00:01:31.660><c> was</c><00:01:32.590><c> formerly</c>

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acquisition five months ago was formerly
 

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acquisition five months ago was formerly
with<00:01:33.310><c> Ravel</c><00:01:34.000><c> law</c><00:01:34.979><c> we're</c><00:01:35.979><c> encountering</c><00:01:36.280><c> a</c><00:01:36.550><c> lot</c>

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with Ravel law we're encountering a lot
 

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with Ravel law we're encountering a lot
more<00:01:37.509><c> kinds</c><00:01:38.380><c> of</c><00:01:38.500><c> data</c><00:01:38.880><c> previously</c><00:01:39.880><c> we</c><00:01:40.270><c> were</c>

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more kinds of data previously we were
 

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more kinds of data previously we were
confined<00:01:40.780><c> to</c><00:01:40.960><c> case</c><00:01:41.200><c> law</c><00:01:41.490><c> but</c><00:01:42.490><c> of</c><00:01:42.640><c> course</c>

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confined to case law but of course
 

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confined to case law but of course
LexisNexis<00:01:43.509><c> has</c><00:01:43.539><c> just</c><00:01:44.729><c> orders</c><00:01:45.729><c> of</c><00:01:45.820><c> magnitude</c>

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LexisNexis has just orders of magnitude
 

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LexisNexis has just orders of magnitude
more<00:01:46.210><c> data</c><00:01:46.509><c> than</c><00:01:46.720><c> we</c><00:01:47.020><c> previously</c><00:01:47.229><c> did</c><00:01:47.740><c> so</c><00:01:48.040><c> I</c>

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more data than we previously did so I
 

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more data than we previously did so I
think<00:01:49.000><c> it's</c><00:01:49.150><c> getting</c><00:01:49.299><c> a</c><00:01:49.450><c> handle</c><00:01:49.689><c> on</c><00:01:49.780><c> that</c>

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think it's getting a handle on that
 

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think it's getting a handle on that
prioritizing<00:01:50.740><c> it</c><00:01:50.860><c> and</c><00:01:51.040><c> figuring</c><00:01:51.640><c> out</c><00:01:51.700><c> what</c>

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prioritizing it and figuring out what
 

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prioritizing it and figuring out what
are<00:01:51.909><c> the</c><00:01:51.970><c> highest</c><00:01:52.150><c> value</c><00:01:52.689><c> bits</c><00:01:53.500><c> of</c><00:01:53.770><c> NLP</c><00:01:54.759><c> or</c>

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are the highest value bits of NLP or
 

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are the highest value bits of NLP or
Sheen<00:01:55.390><c> learning</c><00:01:55.659><c> that</c><00:01:55.750><c> we</c><00:01:55.840><c> can</c><00:01:55.990><c> do</c><00:01:56.110><c> to</c><00:01:56.350><c> build</c>

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Sheen learning that we can do to build
 

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Sheen learning that we can do to build
products<00:01:57.520><c> and</c><00:01:57.640><c> get</c><00:01:57.729><c> them</c><00:01:57.850><c> in</c><00:01:57.939><c> front</c><00:01:58.060><c> of</c>

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products and get them in front of
 

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products and get them in front of
customers

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I<00:02:05.299><c> think</c><00:02:06.299><c> in</c><00:02:06.450><c> many</c><00:02:06.840><c> ways</c><00:02:07.049><c> I</c><00:02:08.030><c> think</c><00:02:09.030><c> the</c><00:02:10.370><c> its</c>

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I think in many ways I think the its
 

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I think in many ways I think the its
principled<00:02:11.940><c> in</c><00:02:12.060><c> a</c><00:02:12.120><c> way</c><00:02:12.239><c> that</c><00:02:12.450><c> a</c><00:02:12.480><c> lot</c><00:02:12.569><c> of</c><00:02:12.720><c> other</c>

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principled in a way that a lot of other
 

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principled in a way that a lot of other
engineering<00:02:15.680><c> languages</c><00:02:16.680><c> if</c><00:02:17.250><c> you</c><00:02:17.430><c> will</c><00:02:17.580><c> are</c>

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engineering languages if you will are
 

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engineering languages if you will are
not<00:02:18.480><c> so</c><00:02:18.959><c> design</c><00:02:19.319><c> patterns</c><00:02:19.769><c> for</c><00:02:20.190><c> instance</c><00:02:20.459><c> I</c>

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not so design patterns for instance I
 

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not so design patterns for instance I
I'd<00:02:21.000><c> rather</c><00:02:21.269><c> use</c><00:02:21.569><c> patterns</c><00:02:22.319><c> from</c><00:02:22.470><c> abstract</c>

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I'd rather use patterns from abstract
 

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I'd rather use patterns from abstract
algebra<00:02:23.160><c> or</c><00:02:23.220><c> category</c><00:02:23.670><c> theory</c><00:02:23.879><c> any</c><00:02:24.000><c> day</c><00:02:24.209><c> over</c>

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algebra or category theory any day over
 

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algebra or category theory any day over
over<00:02:25.410><c> the</c><00:02:25.530><c> use</c><00:02:25.769><c> typical</c><00:02:26.310><c> Gang</c><00:02:26.879><c> of</c><00:02:27.000><c> Four</c><00:02:27.060><c> design</c>

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over the use typical Gang of Four design
 

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over the use typical Gang of Four design
patterns<00:02:27.870><c> I</c><00:02:28.680><c> also</c><00:02:29.010><c> think</c><00:02:29.340><c> it's</c><00:02:29.959><c> it</c><00:02:30.959><c> attracts</c><00:02:31.950><c> a</c>

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patterns I also think it's it attracts a
 

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patterns I also think it's it attracts a
pretty<00:02:32.910><c> interesting</c><00:02:33.299><c> set</c><00:02:33.930><c> of</c><00:02:34.200><c> Engineers</c><00:02:34.980><c> I</c>

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pretty interesting set of Engineers I
 

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pretty interesting set of Engineers I
think<00:02:35.250><c> the</c><00:02:35.340><c> culture</c><00:02:35.849><c> that</c><00:02:36.000><c> goes</c><00:02:36.120><c> with</c>

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think the culture that goes with
 

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think the culture that goes with
functional<00:02:36.870><c> programming</c><00:02:37.170><c> is</c><00:02:37.349><c> really</c>

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functional programming is really
 

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functional programming is really
powerful<00:02:37.910><c> and</c><00:02:39.410><c> I</c><00:02:40.410><c> think</c><00:02:40.650><c> I</c><00:02:40.920><c> believe</c><00:02:41.489><c> that</c><00:02:41.849><c> that</c>

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powerful and I think I believe that that
 

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powerful and I think I believe that that
it<00:02:42.390><c> does</c><00:02:42.569><c> lead</c><00:02:42.810><c> to</c><00:02:42.840><c> higher</c><00:02:43.140><c> quality</c><00:02:43.290><c> software</c>

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it does lead to higher quality software
 

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it does lead to higher quality software
that<00:02:44.310><c> it</c><00:02:44.610><c> leads</c><00:02:45.090><c> to</c><00:02:45.180><c> fewer</c><00:02:45.450><c> bugs</c><00:02:45.829><c> that</c><00:02:46.829><c> it's</c>

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that it leads to fewer bugs that it's
 

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that it leads to fewer bugs that it's
easier<00:02:47.190><c> to</c><00:02:47.280><c> reason</c><00:02:47.459><c> about</c><00:02:47.640><c> the</c><00:02:48.090><c> software</c><00:02:48.510><c> so</c><00:02:48.780><c> I</c>

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easier to reason about the software so I
 

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easier to reason about the software so I
would<00:02:49.290><c> say</c><00:02:49.440><c> in</c><00:02:49.500><c> many</c><00:02:49.739><c> ways</c><00:02:49.980><c> function</c><00:02:50.760><c> program</c>

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would say in many ways function program
 

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would say in many ways function program
has<00:02:51.090><c> paid</c><00:02:51.239><c> off</c><00:02:51.360><c> for</c><00:02:52.079><c> us</c>

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seeing<00:02:59.970><c> everybody</c><00:03:00.360><c> really</c><00:03:00.870><c> we've</c><00:03:01.200><c> got</c><00:03:01.349><c> people</c>

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seeing everybody really we've got people
 

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seeing everybody really we've got people
coming<00:03:01.709><c> over</c><00:03:02.190><c> from</c><00:03:02.400><c> from</c><00:03:02.880><c> Europe</c><00:03:03.270><c> and</c><00:03:03.450><c> all</c>

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coming over from from Europe and all
 

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coming over from from Europe and all
over<00:03:03.930><c> the</c><00:03:04.110><c> the</c><00:03:04.680><c> US</c><00:03:04.950><c> and</c><00:03:05.310><c> South</c><00:03:06.120><c> America</c><00:03:06.599><c> so</c>

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over the the US and South America so
 

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over the the US and South America so
it's<00:03:07.380><c> just</c><00:03:07.470><c> great</c><00:03:07.680><c> to</c><00:03:07.709><c> see</c><00:03:07.800><c> people</c><00:03:07.920><c> in</c><00:03:08.310><c> person</c>

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it's just great to see people in person
 

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it's just great to see people in person
that<00:03:08.819><c> you</c><00:03:09.239><c> interact</c><00:03:09.569><c> with</c><00:03:09.660><c> on</c><00:03:09.989><c> github</c><00:03:10.590><c> or</c>

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that you interact with on github or
 

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that you interact with on github or
Twitter<00:03:10.950><c> from</c><00:03:11.130><c> time</c><00:03:11.280><c> to</c><00:03:11.400><c> time</c>

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