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artificial<00:00:21.380><c> intelligence</c><00:00:21.949><c> is</c><00:00:22.160><c> the</c><00:00:22.610><c> problem</c>

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artificial intelligence is the problem
 

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artificial intelligence is the problem
of<00:00:23.829><c> giving</c><00:00:24.829><c> computers</c><00:00:25.310><c> to</c><00:00:25.490><c> make</c><00:00:25.700><c> decisions</c><00:00:26.329><c> on</c>

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of giving computers to make decisions on
 

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of giving computers to make decisions on
topics<00:00:28.009><c> where</c><00:00:28.189><c> we</c><00:00:28.279><c> haven't</c><00:00:28.520><c> already</c><00:00:28.849><c> prepared</c>

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topics where we haven't already prepared
 

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topics where we haven't already prepared
them<00:00:29.509><c> with</c><00:00:29.660><c> the</c><00:00:29.750><c> answer</c><00:00:30.369><c> specific</c><00:00:31.369><c> to</c>

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them with the answer specific to
 

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them with the answer specific to
self-driving<00:00:32.090><c> cars</c><00:00:32.500><c> artificial</c>

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self-driving cars artificial
 

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self-driving cars artificial
intelligence<00:00:34.010><c> helps</c><00:00:34.220><c> self-driving</c><00:00:34.940><c> cars</c><00:00:35.180><c> go</c>

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intelligence helps self-driving cars go
 

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intelligence helps self-driving cars go
out<00:00:35.510><c> into</c><00:00:35.809><c> the</c><00:00:35.930><c> world</c><00:00:36.110><c> and</c><00:00:36.470><c> figure</c><00:00:37.280><c> out</c><00:00:37.339><c> how</c><00:00:37.550><c> to</c>

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out into the world and figure out how to
 

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out into the world and figure out how to
navigate<00:00:37.910><c> the</c><00:00:38.420><c> environment</c><00:00:38.570><c> based</c><00:00:39.350><c> on</c>

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navigate the environment based on
 

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navigate the environment based on
changing<00:00:40.070><c> conditions</c><00:00:40.640><c> and</c><00:00:40.940><c> routes</c><00:00:41.900><c> that</c><00:00:42.199><c> may</c>

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changing conditions and routes that may
 

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changing conditions and routes that may
be<00:00:42.440><c> different</c><00:00:42.980><c> than</c><00:00:43.160><c> the</c><00:00:43.220><c> routes</c><00:00:43.519><c> that</c><00:00:43.820><c> they</c>

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be different than the routes that they
 

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be different than the routes that they
were<00:00:44.030><c> trained</c><00:00:44.420><c> on</c><00:00:44.690><c> and</c><00:00:45.640><c> problems</c><00:00:46.640><c> that</c><00:00:46.730><c> appear</c>

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were trained on and problems that appear
 

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were trained on and problems that appear
that<00:00:47.480><c> may</c><00:00:47.720><c> not</c><00:00:47.989><c> be</c><00:00:48.049><c> foreseen</c><00:00:48.860><c> but</c><00:00:49.129><c> that</c><00:00:49.309><c> they</c>

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that may not be foreseen but that they
 

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that may not be foreseen but that they
have<00:00:49.790><c> learned</c><00:00:50.059><c> how</c><00:00:50.299><c> to</c><00:00:50.330><c> deal</c><00:00:50.629><c> with</c><00:00:50.659><c> through</c>

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have learned how to deal with through
 

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have learned how to deal with through
training<00:00:52.339><c> on</c><00:00:52.909><c> lots</c><00:00:53.299><c> of</c><00:00:53.510><c> different</c><00:00:54.170><c> types</c><00:00:54.290><c> of</c>

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training on lots of different types of
 

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training on lots of different types of
data

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AI<00:00:59.659><c> has</c><00:00:59.989><c> been</c><00:01:00.199><c> really</c><00:01:00.680><c> successful</c><00:01:01.210><c> with</c>

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AI has been really successful with
 

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AI has been really successful with
rule-based<00:01:03.470><c> robotics</c><00:01:04.100><c> algorithms</c><00:01:04.699><c> a</c><00:01:04.909><c> lot</c><00:01:05.479><c> of</c>

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rule-based robotics algorithms a lot of
 

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rule-based robotics algorithms a lot of
the<00:01:06.260><c> autonomous</c><00:01:06.680><c> vehicles</c><00:01:07.310><c> that</c><00:01:07.640><c> are</c><00:01:07.909><c> on</c><00:01:08.150><c> the</c>

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the autonomous vehicles that are on the
 

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the autonomous vehicles that are on the
world<00:01:08.930><c> be</c><00:01:09.140><c> act</c><00:01:09.380><c> the</c><00:01:09.950><c> lot</c><00:01:10.670><c> of</c><00:01:10.790><c> the</c><00:01:10.880><c> autonomous</c>

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world be act the lot of the autonomous
 

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world be act the lot of the autonomous
vehicles<00:01:11.630><c> that</c><00:01:11.869><c> are</c><00:01:12.080><c> on</c><00:01:12.320><c> the</c><00:01:12.500><c> streets</c><00:01:12.770><c> being</c>

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vehicles that are on the streets being
 

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vehicles that are on the streets being
tested<00:01:13.340><c> today</c><00:01:13.520><c> are</c><00:01:14.439><c> built</c><00:01:15.439><c> with</c><00:01:15.799><c> the</c><00:01:16.790><c> types</c><00:01:17.030><c> of</c>

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tested today are built with the types of
 

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tested today are built with the types of
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robotics algorithms that have been
 

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robotics algorithms that have been
developed<00:01:18.710><c> over</c><00:01:19.310><c> the</c><00:01:19.400><c> last</c><00:01:19.430><c> 20</c><00:01:19.940><c> years</c><00:01:19.970><c> that</c>

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developed over the last 20 years that
 

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developed over the last 20 years that
say<00:01:21.200><c> in</c><00:01:21.440><c> this</c><00:01:21.590><c> situation</c><00:01:22.250><c> do</c><00:01:22.910><c> this</c><00:01:23.150><c> in</c><00:01:23.450><c> another</c>

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say in this situation do this in another
 

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say in this situation do this in another
situation<00:01:23.960><c> do</c><00:01:24.560><c> something</c><00:01:24.920><c> else</c>

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situation do something else
 

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situation do something else
what<00:01:26.210><c> is</c><00:01:26.540><c> really</c><00:01:26.870><c> exciting</c><00:01:27.470><c> about</c><00:01:28.180><c> artificial</c>

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what is really exciting about artificial
 

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what is really exciting about artificial
intelligence<00:01:30.010><c> coming</c><00:01:31.010><c> up</c><00:01:31.130><c> over</c><00:01:31.400><c> the</c><00:01:31.430><c> next</c>

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intelligence coming up over the next
 

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intelligence coming up over the next
five<00:01:31.850><c> years</c><00:01:32.090><c> is</c><00:01:32.270><c> machine</c><00:01:32.600><c> learning</c><00:01:33.020><c> and</c><00:01:33.140><c> in</c>

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five years is machine learning and in
 

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five years is machine learning and in
particular<00:01:33.680><c> deep</c><00:01:33.890><c> learning</c><00:01:34.340><c> and</c><00:01:34.490><c> the</c><00:01:34.940><c> idea</c><00:01:35.270><c> of</c>

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particular deep learning and the idea of
 

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particular deep learning and the idea of
using<00:01:35.900><c> data</c><00:01:36.260><c> to</c><00:01:36.590><c> train</c><00:01:37.220><c> cars</c><00:01:37.640><c> to</c><00:01:38.360><c> behave</c><00:01:39.140><c> in</c>

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using data to train cars to behave in
 

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using data to train cars to behave in
unpredictable<00:01:39.860><c> scenarios</c><00:01:40.900><c> so</c><00:01:41.900><c> before</c><00:01:42.350><c> we</c>

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unpredictable scenarios so before we
 

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unpredictable scenarios so before we
would<00:01:43.159><c> have</c><00:01:43.220><c> lots</c><00:01:44.000><c> of</c><00:01:44.150><c> rules</c><00:01:44.390><c> that</c>

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would have lots of rules that
 

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would have lots of rules that
interactive<00:01:45.229><c> in</c><00:01:45.350><c> lots</c><00:01:45.530><c> of</c><00:01:45.680><c> complicated</c><00:01:46.370><c> ways</c>

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interactive in lots of complicated ways
 

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interactive in lots of complicated ways
that<00:01:47.270><c> would</c><00:01:47.450><c> guide</c><00:01:47.780><c> a</c><00:01:47.840><c> car</c><00:01:48.290><c> as</c><00:01:48.620><c> far</c><00:01:48.800><c> as</c><00:01:48.950><c> how</c><00:01:49.100><c> to</c>

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that would guide a car as far as how to
 

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that would guide a car as far as how to
steer<00:01:49.550><c> and</c><00:01:49.729><c> when</c><00:01:49.850><c> to</c><00:01:49.970><c> hit</c><00:01:50.090><c> the</c><00:01:50.210><c> brakes</c><00:01:50.450><c> and</c><00:01:50.690><c> how</c>

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steer and when to hit the brakes and how
 

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steer and when to hit the brakes and how
fast<00:01:51.020><c> to</c><00:01:51.320><c> go</c><00:01:51.490><c> what</c><00:01:52.490><c> we're</c><00:01:52.610><c> seeing</c><00:01:52.820><c> a</c><00:01:52.940><c> lot</c><00:01:53.090><c> more</c>

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fast to go what we're seeing a lot more
 

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fast to go what we're seeing a lot more
of<00:01:53.330><c> now</c><00:01:53.720><c> is</c><00:01:54.340><c> gathering</c><00:01:55.340><c> data</c><00:01:55.490><c> from</c><00:01:55.970><c> human</c>

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of now is gathering data from human
 

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of now is gathering data from human
drivers<00:01:56.810><c> and</c><00:01:57.140><c> other</c><00:01:57.950><c> data</c><00:01:58.310><c> about</c><00:01:58.430><c> what</c><00:01:58.670><c> the</c>

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drivers and other data about what the
 

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drivers and other data about what the
world<00:01:58.970><c> looks</c><00:01:59.210><c> like</c><00:01:59.479><c> and</c><00:01:59.750><c> using</c><00:02:00.200><c> that</c><00:02:00.320><c> to</c><00:02:00.380><c> train</c>

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world looks like and using that to train
 

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world looks like and using that to train
a<00:02:01.430><c> computer</c><00:02:02.000><c> to</c><00:02:02.450><c> drive</c><00:02:02.690><c> the</c><00:02:02.930><c> car</c><00:02:03.170><c> in</c><00:02:03.740><c> all</c><00:02:04.130><c> sorts</c>

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a computer to drive the car in all sorts
 

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a computer to drive the car in all sorts
of<00:02:04.460><c> environments</c><00:02:04.610><c> that</c><00:02:05.150><c> we</c><00:02:05.270><c> never</c><00:02:05.510><c> could</c><00:02:05.750><c> have</c>

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of environments that we never could have
 

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of environments that we never could have
foreseen<00:02:06.200><c> the</c><00:02:06.320><c> rules</c><00:02:06.560><c> for</c>

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that<00:02:12.440><c> keeps</c><00:02:12.709><c> me</c><00:02:12.860><c> up</c><00:02:12.950><c> at</c><00:02:13.069><c> night</c><00:02:13.959><c> it</c><00:02:14.959><c> Udacity</c><00:02:15.590><c> we</c>

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that keeps me up at night it Udacity we
 

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that keeps me up at night it Udacity we
train<00:02:16.459><c> software</c><00:02:17.120><c> engineers</c><00:02:17.510><c> to</c><00:02:17.660><c> work</c><00:02:17.870><c> on</c>

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train software engineers to work on
 

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train software engineers to work on
autonomous<00:02:18.620><c> vehicles</c><00:02:19.069><c> this</c><00:02:19.580><c> is</c><00:02:19.640><c> really</c>

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autonomous vehicles this is really
 

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autonomous vehicles this is really
exciting<00:02:20.510><c> but</c><00:02:20.780><c> it's</c><00:02:20.900><c> also</c><00:02:21.020><c> really</c><00:02:21.230><c> hard</c>

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exciting but it's also really hard
 

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exciting but it's also really hard
because<00:02:21.830><c> this</c><00:02:22.099><c> is</c><00:02:22.250><c> a</c><00:02:22.280><c> really</c><00:02:22.880><c> deep</c><00:02:23.270><c> complex</c>

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because this is a really deep complex
 

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because this is a really deep complex
space<00:02:24.650><c> and</c><00:02:24.950><c> we</c><00:02:25.880><c> are</c><00:02:25.910><c> working</c><00:02:26.360><c> really</c><00:02:26.569><c> hard</c><00:02:26.720><c> to</c>

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space and we are working really hard to
 

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space and we are working really hard to
teach<00:02:27.380><c> students</c><00:02:27.950><c> exactly</c><00:02:28.250><c> what</c><00:02:28.580><c> they</c><00:02:28.700><c> need</c><00:02:28.880><c> to</c>

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teach students exactly what they need to
 

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teach students exactly what they need to
know<00:02:29.030><c> to</c><00:02:29.750><c> be</c><00:02:29.959><c> qualified</c><00:02:30.770><c> and</c><00:02:31.130><c> great</c>

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know to be qualified and great
 

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know to be qualified and great
candidates<00:02:31.910><c> for</c><00:02:32.060><c> the</c><00:02:32.660><c> jobs</c><00:02:32.900><c> that</c><00:02:33.020><c> they</c><00:02:33.260><c> would</c>

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candidates for the jobs that they would
 

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candidates for the jobs that they would
like<00:02:33.560><c> to</c><00:02:33.590><c> get</c><00:02:33.890><c> and</c><00:02:34.160><c> so</c><00:02:34.640><c> we</c><00:02:34.790><c> spend</c><00:02:35.030><c> a</c><00:02:35.120><c> lot</c><00:02:35.150><c> of</c>

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like to get and so we spend a lot of
 

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like to get and so we spend a lot of
time<00:02:35.690><c> thinking</c><00:02:35.989><c> about</c><00:02:36.380><c> what</c><00:02:37.190><c> is</c><00:02:37.519><c> the</c><00:02:37.940><c> best</c><00:02:38.150><c> way</c>

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time thinking about what is the best way
 

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time thinking about what is the best way
to<00:02:38.510><c> communicate</c><00:02:38.840><c> all</c><00:02:39.440><c> of</c><00:02:39.500><c> the</c><00:02:39.769><c> complexities</c>

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to communicate all of the complexities
 

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to communicate all of the complexities
of<00:02:40.430><c> artificial</c><00:02:41.060><c> intelligence</c><00:02:41.180><c> and</c><00:02:41.750><c> machine</c>

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of artificial intelligence and machine
 

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of artificial intelligence and machine
learning<00:02:42.050><c> to</c><00:02:42.890><c> students</c><00:02:43.310><c> so</c><00:02:43.489><c> that</c><00:02:43.640><c> they</c><00:02:43.819><c> are</c>

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learning to students so that they are
 

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learning to students so that they are
able<00:02:44.120><c> to</c><00:02:44.300><c> do</c><00:02:44.569><c> really</c><00:02:44.840><c> neat</c><00:02:45.200><c> things</c><00:02:45.560><c> with</c><00:02:45.860><c> the</c>

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able to do really neat things with the
 

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able to do really neat things with the
knowledge<00:02:46.280><c> that</c><00:02:46.489><c> they've</c><00:02:46.850><c> gained</c><00:02:47.150><c> and</c><00:02:47.450><c> be</c>

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knowledge that they've gained and be
 

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knowledge that they've gained and be
able<00:02:48.230><c> to</c><00:02:48.290><c> go</c><00:02:48.500><c> in</c><00:02:48.709><c> and</c><00:02:48.980><c> show</c><00:02:49.190><c> employers</c><00:02:49.549><c> that</c>

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able to go in and show employers that
 

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able to go in and show employers that
they<00:02:50.000><c> can</c><00:02:50.269><c> contribute</c><00:02:50.630><c> immediately</c><00:02:51.350><c> on</c>

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they can contribute immediately on
 

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they can contribute immediately on
autonomous<00:02:52.400><c> vehicle</c><00:02:52.790><c> teams</c><00:02:57.370><c> my</c><00:02:58.370><c> favorite</c>

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autonomous vehicle teams my favorite
 

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autonomous vehicle teams my favorite
part<00:02:58.940><c> about</c><00:02:58.970><c> the</c><00:02:59.150><c> conference</c><00:02:59.510><c> is</c><00:02:59.630><c> just</c><00:02:59.660><c> all</c><00:03:00.049><c> of</c>

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part about the conference is just all of
 

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part about the conference is just all of
the<00:03:00.350><c> people</c><00:03:00.650><c> who</c><00:03:00.769><c> are</c><00:03:00.890><c> here</c><00:03:01.100><c> who</c><00:03:01.220><c> are</c><00:03:01.250><c> so</c>

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the people who are here who are so
 

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the people who are here who are so
excited<00:03:02.060><c> about</c><00:03:02.440><c> artificial</c><00:03:03.440><c> intelligence</c>

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excited about artificial intelligence
 

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excited about artificial intelligence
and<00:03:04.340><c> especially</c><00:03:04.940><c> today's</c><00:03:05.420><c> session</c><00:03:05.840><c> on</c>

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and especially today's session on
 

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and especially today's session on
self-driving<00:03:06.410><c> cars</c><00:03:06.709><c> I've</c><00:03:07.040><c> just</c><00:03:07.400><c> talked</c><00:03:07.580><c> to</c><00:03:07.670><c> so</c>

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self-driving cars I've just talked to so
 

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self-driving cars I've just talked to so
many<00:03:08.030><c> different</c><00:03:08.209><c> people</c><00:03:08.540><c> who</c><00:03:09.230><c> are</c><00:03:09.440><c> super</c>

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many different people who are super
 

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many different people who are super
enthusiastic<00:03:10.910><c> about</c><00:03:11.060><c> working</c><00:03:11.989><c> in</c><00:03:12.320><c> autonomous</c>

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enthusiastic about working in autonomous
 

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enthusiastic about working in autonomous
vehicles<00:03:13.340><c> or</c><00:03:13.579><c> they're</c><00:03:13.730><c> already</c><00:03:14.030><c> starting</c><00:03:14.570><c> a</c>

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vehicles or they're already starting a
 

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vehicles or they're already starting a
company<00:03:14.950><c> related</c><00:03:15.950><c> to</c><00:03:16.220><c> self-driving</c><00:03:16.640><c> cars</c><00:03:17.000><c> and</c>

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company related to self-driving cars and
 

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company related to self-driving cars and
I<00:03:17.690><c> think</c><00:03:17.900><c> just</c><00:03:18.109><c> to</c><00:03:18.200><c> have</c><00:03:18.380><c> all</c><00:03:18.680><c> of</c><00:03:18.829><c> these</c><00:03:19.010><c> people</c>

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I think just to have all of these people
 

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I think just to have all of these people
together<00:03:19.579><c> to</c><00:03:20.239><c> kind</c><00:03:20.359><c> of</c><00:03:20.480><c> feed</c><00:03:20.690><c> off</c><00:03:20.720><c> each</c><00:03:20.900><c> other</c>

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together to kind of feed off each other
 

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together to kind of feed off each other
and<00:03:21.350><c> learn</c><00:03:21.620><c> from</c><00:03:21.799><c> each</c><00:03:21.980><c> other</c><00:03:22.220><c> and</c><00:03:22.459><c> get</c><00:03:23.329><c> the</c>

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and learn from each other and get the
 

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and learn from each other and get the
latest<00:03:23.660><c> information</c><00:03:23.900><c> about</c><00:03:24.560><c> what's</c>

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latest information about what's
 

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latest information about what's
happening<00:03:24.799><c> in</c><00:03:25.250><c> the</c><00:03:25.340><c> field</c><00:03:25.579><c> is</c><00:03:25.760><c> a</c><00:03:25.790><c> tremendous</c>

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happening in the field is a tremendous
 

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happening in the field is a tremendous
opportunity<00:03:26.450><c> and</c><00:03:27.140><c> it's</c><00:03:27.290><c> one</c><00:03:27.709><c> of</c><00:03:27.829><c> those</c><00:03:27.920><c> things</c>

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opportunity and it's one of those things
 

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opportunity and it's one of those things
that<00:03:28.400><c> leaves</c><00:03:28.609><c> me</c><00:03:28.880><c> walking</c><00:03:29.269><c> away</c><00:03:29.359><c> really</c>

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that leaves me walking away really
 

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that leaves me walking away really
really<00:03:29.840><c> energized</c><00:03:30.470><c> about</c><00:03:30.709><c> the</c><00:03:30.950><c> field</c><00:03:31.220><c> and</c><00:03:31.519><c> the</c>

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really energized about the field and the
 

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really energized about the field and the
potential<00:03:32.359><c> for</c><00:03:32.510><c> the</c><00:03:32.600><c> people</c><00:03:32.840><c> here</c><00:03:32.989><c> to</c>

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potential for the people here to
 

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potential for the people here to
transform<00:03:33.590><c> the</c><00:03:33.709><c> world</c>

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transform the world
 

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transform the world
you