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you

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you
 

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you
[Music]

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you

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so<00:00:21.090><c> I</c><00:00:21.690><c> work</c><00:00:22.290><c> on</c><00:00:22.710><c> autonomous</c><00:00:23.670><c> and</c><00:00:23.820><c> connected</c>

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so I work on autonomous and connected
 

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so I work on autonomous and connected
cars<00:00:24.510><c> for</c><00:00:25.110><c> General</c><00:00:25.560><c> Motors</c><00:00:25.910><c> amongst</c><00:00:26.910><c> other</c>

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cars for General Motors amongst other
 

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cars for General Motors amongst other
things<00:00:27.150><c> but</c><00:00:27.540><c> that's</c><00:00:27.720><c> kind</c><00:00:27.930><c> of</c><00:00:27.960><c> a</c><00:00:28.080><c> key</c><00:00:28.260><c> focus</c>

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things but that's kind of a key focus
 

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things but that's kind of a key focus
area<00:00:28.920><c> and</c><00:00:29.130><c> AI</c><00:00:30.090><c> is</c><00:00:30.300><c> the</c><00:00:31.020><c> practice</c><00:00:31.739><c> that</c><00:00:31.890><c> is</c>

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area and AI is the practice that is
 

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area and AI is the practice that is
really<00:00:32.340><c> helping</c><00:00:32.669><c> us</c><00:00:32.850><c> make</c><00:00:33.120><c> great</c><00:00:33.360><c> games</c><00:00:33.570><c> in</c>

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really helping us make great games in
 

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really helping us make great games in
terms<00:00:34.079><c> of</c><00:00:34.460><c> mapping</c><00:00:35.460><c> in</c><00:00:35.970><c> terms</c><00:00:36.239><c> of</c><00:00:37.190><c> we're</c><00:00:38.190><c> just</c>

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terms of mapping in terms of we're just
 

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terms of mapping in terms of we're just
being<00:00:38.820><c> able</c><00:00:39.060><c> to</c><00:00:39.210><c> the</c><00:00:39.600><c> further</c><00:00:39.870><c> safety</c><00:00:40.590><c> of</c>

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being able to the further safety of
 

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being able to the further safety of
passengers<00:00:42.230><c> we've</c><00:00:43.230><c> been</c><00:00:43.440><c> able</c><00:00:43.560><c> to</c><00:00:43.680><c> apply</c><00:00:43.980><c> it</c>

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passengers we've been able to apply it
 

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passengers we've been able to apply it
into<00:00:44.610><c> the</c><00:00:44.940><c> realm</c><00:00:45.210><c> of</c><00:00:45.360><c> sales</c><00:00:45.690><c> we've</c><00:00:46.200><c> been</c><00:00:46.380><c> able</c>

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into the realm of sales we've been able
 

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into the realm of sales we've been able
to<00:00:46.770><c> apply</c><00:00:47.130><c> to</c><00:00:47.250><c> the</c><00:00:47.489><c> realm</c><00:00:47.670><c> of</c><00:00:49.940><c> prognostics</c><00:00:50.940><c> and</c>

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to apply to the realm of prognostics and
 

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to apply to the realm of prognostics and
diagnostics<00:00:51.780><c> so</c><00:00:51.990><c> it's</c><00:00:52.170><c> got</c><00:00:52.380><c> a</c><00:00:52.410><c> wide</c><00:00:53.010><c> range</c><00:00:53.310><c> of</c>

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diagnostics so it's got a wide range of
 

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diagnostics so it's got a wide range of
applications<00:00:54.770><c> we</c><00:00:55.770><c> focused</c><00:00:56.220><c> a</c><00:00:56.490><c> little</c><00:00:57.000><c> bit</c>

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applications we focused a little bit
 

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applications we focused a little bit
more<00:00:57.360><c> on</c><00:00:57.480><c> machine</c><00:00:57.840><c> learning</c><00:00:57.870><c> than</c><00:00:58.350><c> sort</c><00:00:58.620><c> of</c>

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more on machine learning than sort of
 

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more on machine learning than sort of
general<00:00:59.160><c> AI</c><00:00:59.370><c> but</c><00:01:00.030><c> it's</c><00:01:00.870><c> definitely</c><00:01:01.110><c> a</c><00:01:01.350><c> key</c>

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general AI but it's definitely a key
 

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general AI but it's definitely a key
part<00:01:02.430><c> of</c><00:01:02.580><c> what</c><00:01:02.700><c> we're</c><00:01:02.820><c> doing</c><00:01:02.850><c> a</c><00:01:03.060><c> jam</c><00:01:07.640><c> so</c><00:01:08.640><c> right</c>

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part of what we're doing a jam so right
 

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part of what we're doing a jam so right
now<00:01:08.909><c> if</c><00:01:09.540><c> you've</c><00:01:09.900><c> got</c><00:01:10.200><c> data</c><00:01:10.920><c> sets</c><00:01:11.280><c> that</c><00:01:11.840><c> you</c>

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now if you've got data sets that you
 

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now if you've got data sets that you
know<00:01:12.960><c> the</c><00:01:13.200><c> some</c><00:01:13.950><c> of</c><00:01:14.040><c> the</c><00:01:14.070><c> leading</c><00:01:14.280><c> researchers</c>

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know the some of the leading researchers
 

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know the some of the leading researchers
can<00:01:15.119><c> work</c><00:01:15.390><c> with</c><00:01:15.630><c> and</c><00:01:15.869><c> trained</c><00:01:16.650><c> and</c><00:01:17.420><c> you've</c><00:01:18.420><c> got</c>

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can work with and trained and you've got
 

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can work with and trained and you've got
a<00:01:18.750><c> great</c><00:01:18.990><c> advantage</c><00:01:19.320><c> there's</c><00:01:19.679><c> a</c><00:01:19.710><c> lot</c><00:01:19.829><c> of</c><00:01:19.859><c> stuff</c>

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a great advantage there's a lot of stuff
 

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a great advantage there's a lot of stuff
around<00:01:20.490><c> some</c><00:01:20.789><c> healthcare</c><00:01:21.030><c> records</c><00:01:21.390><c> or</c>

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around some healthcare records or
 

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around some healthcare records or
radiology<00:01:22.560><c> scans</c><00:01:23.159><c> that</c><00:01:23.520><c> have</c><00:01:23.729><c> been</c><00:01:23.969><c> powering</c>

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radiology scans that have been powering
 

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radiology scans that have been powering
some<00:01:25.289><c> some</c><00:01:25.619><c> innovative</c><00:01:26.039><c> new</c><00:01:26.280><c> startups</c><00:01:27.229><c> when</c>

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some some innovative new startups when
 

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some some innovative new startups when
we<00:01:28.380><c> get</c><00:01:28.619><c> into</c><00:01:28.770><c> the</c><00:01:29.039><c> the</c><00:01:29.340><c> realm</c><00:01:29.579><c> of</c><00:01:30.079><c> tagging</c>

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we get into the the realm of tagging
 

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we get into the the realm of tagging
images<00:01:31.770><c> and</c><00:01:32.189><c> recognizing</c><00:01:33.060><c> objects</c><00:01:33.600><c> and</c>

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images and recognizing objects and
 

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images and recognizing objects and
localization<00:01:35.179><c> we're</c><00:01:36.179><c> going</c><00:01:36.299><c> to</c><00:01:36.359><c> need</c><00:01:36.569><c> to</c>

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localization we're going to need to
 

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localization we're going to need to
continually<00:01:37.590><c> add</c><00:01:37.979><c> more</c><00:01:38.549><c> data</c><00:01:38.729><c> not</c><00:01:39.060><c> just</c><00:01:39.119><c> data</c>

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continually add more data not just data
 

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continually add more data not just data
that<00:01:39.780><c> we</c><00:01:39.990><c> collect</c><00:01:40.469><c> but</c><00:01:40.859><c> that</c><00:01:41.189><c> is</c><00:01:41.340><c> collected</c><00:01:41.819><c> in</c>

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that we collect but that is collected in
 

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that we collect but that is collected in
new<00:01:42.929><c> areas</c><00:01:43.139><c> that</c><00:01:43.530><c> is</c><00:01:43.710><c> under</c><00:01:44.399><c> construction</c><00:01:44.670><c> and</c>

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new areas that is under construction and
 

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new areas that is under construction and
changing<00:01:45.600><c> all</c><00:01:45.689><c> the</c><00:01:45.719><c> time</c><00:01:45.810><c> so</c><00:01:46.319><c> I</c><00:01:46.350><c> others</c><00:01:46.979><c> one</c><00:01:47.130><c> of</c>

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changing all the time so I others one of
 

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changing all the time so I others one of
both<00:01:47.819><c> the</c><00:01:47.999><c> opportunities</c><00:01:48.539><c> and</c><00:01:48.689><c> challenges</c>

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both the opportunities and challenges
 

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both the opportunities and challenges
right<00:01:49.289><c> now</c>

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so<00:01:55.560><c> it's</c><00:01:55.710><c> a</c><00:01:55.770><c> talent</c><00:01:56.189><c> play</c><00:01:56.820><c> for</c><00:01:57.090><c> me</c><00:01:57.270><c> you</c><00:01:57.990><c> know</c>

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so it's a talent play for me you know
 

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so it's a talent play for me you know
there's<00:01:58.439><c> an</c><00:01:58.619><c> interesting</c><00:01:59.070><c> board</c><00:01:59.520><c> downstairs</c>

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there's an interesting board downstairs
 

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there's an interesting board downstairs
here<00:02:00.570><c> where</c><00:02:00.869><c> it</c><00:02:00.990><c> shows</c><00:02:01.259><c> the</c><00:02:01.670><c> companies</c>

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here where it shows the companies
 

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here where it shows the companies
looking<00:02:03.030><c> for</c><00:02:03.360><c> AI</c><00:02:04.080><c> machine</c><00:02:04.680><c> learning</c><00:02:05.009><c> talent</c>

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looking for AI machine learning talent
 

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looking for AI machine learning talent
and<00:02:05.700><c> people</c><00:02:05.850><c> who</c><00:02:06.180><c> are</c><00:02:06.330><c> looking</c><00:02:06.479><c> to</c><00:02:06.750><c> be</c><00:02:07.080><c> hired</c>

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and people who are looking to be hired
 

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and people who are looking to be hired
and<00:02:07.619><c> there's</c><00:02:07.860><c> a</c><00:02:08.090><c> real</c><00:02:09.090><c> imbalance</c><00:02:09.660><c> there</c>

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and there's a real imbalance there
 

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and there's a real imbalance there
there's<00:02:10.170><c> a</c><00:02:10.259><c> lot</c><00:02:10.739><c> fewer</c><00:02:11.100><c> talent</c><00:02:11.700><c> than</c><00:02:11.850><c> is</c>

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there's a lot fewer talent than is
 

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there's a lot fewer talent than is
needed<00:02:12.239><c> and</c><00:02:12.540><c> if</c><00:02:13.440><c> you</c><00:02:13.560><c> look</c><00:02:13.739><c> at</c><00:02:13.920><c> the</c><00:02:14.100><c> very</c><00:02:14.640><c> top</c>

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needed and if you look at the very top
 

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needed and if you look at the very top
most<00:02:15.540><c> productive</c><00:02:16.110><c> talent</c><00:02:16.590><c> a</c><00:02:16.770><c> lot</c><00:02:17.340><c> of</c><00:02:17.489><c> them</c><00:02:17.640><c> are</c>

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most productive talent a lot of them are
 

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most productive talent a lot of them are
being<00:02:18.030><c> kind</c><00:02:18.780><c> of</c><00:02:18.870><c> brought</c><00:02:19.200><c> into</c><00:02:19.680><c> companies</c>

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being kind of brought into companies
 

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being kind of brought into companies
where<00:02:20.340><c> they're</c><00:02:20.819><c> not</c><00:02:20.970><c> available</c><00:02:21.660><c> to</c><00:02:22.020><c> to</c><00:02:22.650><c> others</c>

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where they're not available to to others
 

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where they're not available to to others
and<00:02:23.310><c> you</c><00:02:24.270><c> know</c><00:02:24.360><c> usually</c><00:02:24.780><c> use</c><00:02:25.140><c> the</c><00:02:25.290><c> example</c><00:02:25.560><c> of</c>

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and you know usually use the example of
 

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and you know usually use the example of
Carnegie<00:02:27.870><c> Mellon</c><00:02:28.260><c> which</c><00:02:28.470><c> had</c><00:02:28.739><c> 32</c><00:02:29.400><c> of</c><00:02:29.610><c> their</c>

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Carnegie Mellon which had 32 of their
 

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Carnegie Mellon which had 32 of their
top<00:02:30.030><c> engineers</c><00:02:30.630><c> kind</c><00:02:31.110><c> of</c><00:02:31.170><c> scooped</c><00:02:31.410><c> up</c><00:02:31.590><c> by</c><00:02:31.620><c> uber</c>

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top engineers kind of scooped up by uber
 

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top engineers kind of scooped up by uber
so<00:02:32.850><c> you</c><00:02:33.660><c> know</c><00:02:33.750><c> we're</c><00:02:33.989><c> worried</c><00:02:34.290><c> a</c><00:02:34.380><c> little</c><00:02:34.530><c> bit</c>

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so you know we're worried a little bit
 

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so you know we're worried a little bit
about<00:02:35.010><c> the</c><00:02:35.700><c> brain</c><00:02:35.940><c> drain</c><00:02:36.239><c> in</c><00:02:36.480><c> some</c><00:02:36.690><c> of</c><00:02:36.750><c> the</c>

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about the brain drain in some of the
 

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about the brain drain in some of the
academic<00:02:37.470><c> the</c><00:02:38.130><c> leading</c><00:02:38.489><c> academic</c><00:02:39.150><c> programs</c>

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academic the leading academic programs
 

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academic the leading academic programs
because<00:02:40.560><c> we</c><00:02:40.680><c> want</c><00:02:40.920><c> to</c><00:02:41.010><c> train</c><00:02:41.250><c> more</c><00:02:41.519><c> and</c><00:02:41.640><c> more</c>

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because we want to train more and more
 

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because we want to train more and more
of<00:02:41.850><c> these</c><00:02:41.970><c> people</c><00:02:42.300><c> and</c><00:02:42.510><c> it's</c><00:02:42.780><c> not</c><00:02:42.989><c> going</c><00:02:43.170><c> to</c>

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of these people and it's not going to
 

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of these people and it's not going to
happen<00:02:43.350><c> if</c><00:02:43.890><c> we</c><00:02:44.310><c> take</c><00:02:44.489><c> them</c><00:02:44.670><c> out</c><00:02:44.850><c> at</c><00:02:45.090><c> that</c><00:02:45.209><c> sort</c>

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happen if we take them out at that sort
 

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happen if we take them out at that sort
of<00:02:45.720><c> in</c><00:02:46.140><c> a</c><00:02:46.530><c> teacher</c><00:02:46.970><c> trainer</c><00:02:47.970><c> labs</c><00:02:48.660><c> or</c><00:02:49.049><c> level</c>

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low<00:02:55.230><c> is</c><00:02:55.260><c> such</c><00:02:56.069><c> a</c><00:02:56.100><c> diverse</c><00:02:56.489><c> group</c><00:02:56.610><c> of</c><00:02:56.880><c> people</c>

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low is such a diverse group of people
 

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low is such a diverse group of people
today<00:02:57.690><c> we</c><00:02:58.380><c> had</c><00:02:58.500><c> people</c><00:02:58.739><c> from</c><00:02:59.160><c> a</c><00:02:59.930><c> city-planning</c>

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today we had people from a city-planning
 

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today we had people from a city-planning
point<00:03:01.920><c> of</c><00:03:02.040><c> view</c><00:03:02.220><c> talking</c><00:03:02.700><c> about</c><00:03:02.850><c> Singapore</c><00:03:03.329><c> we</c>

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point of view talking about Singapore we
 

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point of view talking about Singapore we
also<00:03:03.690><c> had</c><00:03:03.870><c> people</c><00:03:03.900><c> the</c><00:03:04.260><c> funding</c><00:03:04.680><c> side</c><00:03:05.090><c> looking</c>

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also had people the funding side looking
 

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also had people the funding side looking
for<00:03:06.390><c> you</c><00:03:06.630><c> know</c><00:03:06.720><c> how</c><00:03:06.930><c> do</c><00:03:06.989><c> we</c><00:03:07.170><c> give</c><00:03:07.470><c> the</c><00:03:08.060><c> food</c><00:03:09.060><c> to</c>

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for you know how do we give the food to
 

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for you know how do we give the food to
kind<00:03:10.109><c> of</c><00:03:10.200><c> get</c><00:03:10.530><c> up</c><00:03:10.680><c> to</c><00:03:10.799><c> the</c><00:03:10.890><c> next</c><00:03:11.100><c> level</c><00:03:11.190><c> and</c><00:03:11.760><c> we</c>

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kind of get up to the next level and we
 

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kind of get up to the next level and we
had<00:03:12.359><c> people</c><00:03:12.570><c> sort</c><00:03:13.049><c> of</c><00:03:13.140><c> very</c><00:03:13.320><c> deep</c><00:03:13.680><c> in</c><00:03:13.980><c> terms</c><00:03:14.250><c> of</c>

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had people sort of very deep in terms of
 

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had people sort of very deep in terms of
like<00:03:15.840><c> George</c><00:03:16.109><c> Hotz</c><00:03:16.350><c> and</c><00:03:16.590><c> coma</c><00:03:16.769><c> AI</c><00:03:17.040><c> and</c><00:03:17.519><c> expose</c>

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like George Hotz and coma AI and expose
 

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like George Hotz and coma AI and expose
on<00:03:18.359><c> you</c><00:03:19.260><c> know</c><00:03:19.380><c> that</c><00:03:19.590><c> the</c><00:03:20.519><c> real</c><00:03:20.700><c> bleeding</c><00:03:21.120><c> edge</c>

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on you know that the real bleeding edge
 

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on you know that the real bleeding edge
of<00:03:21.510><c> what</c><00:03:21.900><c> can</c><00:03:22.079><c> be</c><00:03:22.200><c> done</c><00:03:22.380><c> from</c><00:03:22.680><c> an</c><00:03:22.859><c> open</c><00:03:23.130><c> source</c>

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of what can be done from an open source
 

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of what can be done from an open source
point<00:03:23.519><c> of</c><00:03:23.640><c> view</c><00:03:23.760><c> so</c><00:03:23.970><c> it's</c><00:03:24.959><c> not</c><00:03:25.109><c> often</c><00:03:25.290><c> you</c><00:03:25.500><c> have</c>

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point of view so it's not often you have
 

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point of view so it's not often you have
that<00:03:26.190><c> variety</c><00:03:26.549><c> in</c><00:03:26.880><c> one</c><00:03:27.120><c> room</c><00:03:27.359><c> and</c><00:03:27.630><c> I</c><00:03:28.079><c> really</c>

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that variety in one room and I really
 

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that variety in one room and I really
appreciated<00:03:28.769><c> that</c>

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appreciated that
 

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appreciated that
you

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you
 

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you
[Music]

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you

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you