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as<00:00:03.859><c> technology</c><00:00:04.859><c> evolves</c><00:00:05.160><c> and</c><00:00:05.549><c> the</c><00:00:05.700><c> world's</c>

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as technology evolves and the world's
 

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as technology evolves and the world's
population<00:00:06.660><c> grows</c><00:00:07.400><c> so</c><00:00:08.400><c> does</c><00:00:08.460><c> the</c><00:00:08.700><c> amount</c><00:00:08.910><c> of</c>

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population grows so does the amount of
 

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population grows so does the amount of
data<00:00:09.360><c> being</c><00:00:09.660><c> generated</c><00:00:10.550><c> collecting</c><00:00:11.550><c> sorting</c>

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data being generated collecting sorting
 

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data being generated collecting sorting
and<00:00:12.389><c> analyzing</c><00:00:13.110><c> all</c><00:00:13.259><c> of</c><00:00:13.320><c> this</c><00:00:13.590><c> data</c><00:00:13.830><c> can</c><00:00:14.160><c> be</c>

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and analyzing all of this data can be
 

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and analyzing all of this data can be
pretty<00:00:14.580><c> time-consuming</c><00:00:15.230><c> however</c><00:00:16.230><c> that's</c>

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pretty time-consuming however that's
 

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pretty time-consuming however that's
starting<00:00:17.100><c> to</c><00:00:17.130><c> change</c><00:00:17.460><c> with</c><00:00:17.910><c> the</c><00:00:18.060><c> emergence</c><00:00:18.510><c> of</c>

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starting to change with the emergence of
 

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starting to change with the emergence of
something<00:00:18.900><c> called</c><00:00:19.320><c> machine</c><00:00:19.920><c> learning</c>

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something called machine learning
 

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something called machine learning
machine<00:00:21.539><c> learning</c><00:00:21.930><c> is</c><00:00:22.050><c> a</c><00:00:22.080><c> type</c><00:00:22.320><c> of</c><00:00:22.350><c> computer</c>

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machine learning is a type of computer
 

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machine learning is a type of computer
science<00:00:23.369><c> that</c><00:00:23.550><c> allows</c><00:00:23.880><c> computer</c><00:00:24.449><c> programs</c><00:00:24.930><c> to</c>

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science that allows computer programs to
 

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science that allows computer programs to
learn<00:00:25.410><c> and</c><00:00:25.710><c> improve</c><00:00:26.130><c> all</c><00:00:26.519><c> on</c><00:00:26.849><c> their</c><00:00:27.029><c> own</c><00:00:27.060><c> in</c>

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learn and improve all on their own in
 

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learn and improve all on their own in
the<00:00:28.170><c> past</c><00:00:28.380><c> computers</c><00:00:29.099><c> could</c><00:00:29.279><c> only</c><00:00:29.400><c> do</c><00:00:29.670><c> what</c><00:00:29.910><c> we</c>

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the past computers could only do what we
 

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the past computers could only do what we
programmed<00:00:30.570><c> them</c><00:00:30.810><c> to</c><00:00:30.840><c> do</c><00:00:31.140><c> but</c><00:00:31.740><c> with</c><00:00:31.949><c> machine</c>

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programmed them to do but with machine
 

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programmed them to do but with machine
learning<00:00:32.340><c> they</c><00:00:32.969><c> can</c><00:00:33.180><c> behave</c><00:00:33.329><c> like</c><00:00:33.690><c> humans</c><00:00:34.170><c> and</c>

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learning they can behave like humans and
 

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learning they can behave like humans and
gain<00:00:34.649><c> knowledge</c><00:00:34.920><c> based</c><00:00:35.489><c> on</c><00:00:35.700><c> their</c><00:00:35.820><c> past</c>

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gain knowledge based on their past
 

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gain knowledge based on their past
experiences<00:00:36.980><c> this</c><00:00:37.980><c> process</c><00:00:38.520><c> can</c><00:00:38.760><c> get</c><00:00:38.879><c> pretty</c>

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experiences this process can get pretty
 

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experiences this process can get pretty
complicated<00:00:39.660><c> but</c><00:00:40.230><c> here's</c><00:00:40.530><c> how</c><00:00:40.680><c> it</c><00:00:40.800><c> works</c><00:00:41.040><c> on</c><00:00:41.280><c> a</c>

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complicated but here's how it works on a
 

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complicated but here's how it works on a
basic<00:00:41.700><c> level</c><00:00:41.930><c> let's</c><00:00:42.930><c> say</c><00:00:43.140><c> we</c><00:00:43.379><c> want</c><00:00:43.590><c> a</c><00:00:43.680><c> program</c>

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basic level let's say we want a program
 

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basic level let's say we want a program
that<00:00:44.399><c> can</c><00:00:44.610><c> tell</c><00:00:44.820><c> the</c><00:00:44.969><c> difference</c><00:00:45.360><c> between</c>

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that can tell the difference between
 

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that can tell the difference between
apples<00:00:46.170><c> and</c><00:00:46.440><c> bananas</c><00:00:47.239><c> first</c><00:00:48.239><c> we'll</c><00:00:48.570><c> give</c><00:00:48.719><c> it</c>

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apples and bananas first we'll give it
 

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apples and bananas first we'll give it
some<00:00:48.870><c> labeled</c><00:00:49.410><c> pictures</c><00:00:49.800><c> of</c><00:00:49.980><c> each</c><00:00:50.129><c> the</c>

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some labeled pictures of each the
 

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some labeled pictures of each the
program<00:00:51.480><c> will</c><00:00:51.660><c> then</c><00:00:51.690><c> look</c><00:00:51.989><c> for</c><00:00:52.199><c> patterns</c><00:00:52.590><c> in</c>

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program will then look for patterns in
 

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program will then look for patterns in
the<00:00:52.829><c> fruits</c><00:00:53.160><c> and</c><00:00:53.460><c> start</c><00:00:53.789><c> to</c><00:00:53.969><c> remember</c><00:00:54.270><c> them</c><00:00:54.600><c> it</c>

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the fruits and start to remember them it
 

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the fruits and start to remember them it
can<00:00:55.739><c> then</c><00:00:55.920><c> use</c><00:00:56.160><c> these</c><00:00:56.370><c> memories</c><00:00:56.910><c> to</c><00:00:56.940><c> look</c><00:00:57.329><c> at</c>

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can then use these memories to look at
 

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can then use these memories to look at
unlabeled<00:00:58.109><c> pictures</c><00:00:58.500><c> of</c><00:00:58.710><c> apples</c><00:00:59.070><c> and</c><00:00:59.129><c> bananas</c>

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unlabeled pictures of apples and bananas
 

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unlabeled pictures of apples and bananas
and<00:00:59.730><c> determine</c><00:01:00.359><c> which</c><00:01:00.510><c> is</c><00:01:00.719><c> which</c><00:01:00.989><c> all</c><00:01:01.410><c> on</c><00:01:01.859><c> its</c>

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and determine which is which all on its
 

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and determine which is which all on its
own

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own
 

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own
believe<00:01:03.870><c> it</c><00:01:03.989><c> or</c><00:01:04.080><c> not</c><00:01:04.199><c> you</c><00:01:04.559><c> probably</c><00:01:05.040><c> encounter</c>

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believe it or not you probably encounter
 

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believe it or not you probably encounter
machine<00:01:05.939><c> learning</c><00:01:06.299><c> on</c><00:01:06.420><c> a</c><00:01:06.450><c> daily</c><00:01:06.840><c> basis</c><00:01:07.430><c> social</c>

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machine learning on a daily basis social
 

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machine learning on a daily basis social
media<00:01:08.729><c> sites</c><00:01:09.060><c> use</c><00:01:09.390><c> it</c><00:01:09.510><c> to</c><00:01:09.630><c> create</c><00:01:09.840><c> your</c><00:01:09.930><c> feed</c>

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media sites use it to create your feed
 

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media sites use it to create your feed
based<00:01:10.770><c> on</c><00:01:10.979><c> your</c><00:01:11.100><c> preferences</c><00:01:11.729><c> and</c><00:01:12.000><c> search</c>

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based on your preferences and search
 

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based on your preferences and search
engines<00:01:13.080><c> use</c><00:01:13.409><c> it</c><00:01:13.560><c> to</c><00:01:13.680><c> improve</c><00:01:14.010><c> the</c><00:01:14.220><c> accuracy</c>

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engines use it to improve the accuracy
 

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engines use it to improve the accuracy
of<00:01:15.000><c> their</c><00:01:15.119><c> search</c><00:01:15.360><c> results</c><00:01:16.580><c> it's</c><00:01:17.580><c> also</c><00:01:17.820><c> being</c>

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of their search results it's also being
 

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of their search results it's also being
used<00:01:18.450><c> on</c><00:01:18.630><c> a</c><00:01:18.689><c> larger</c><00:01:19.080><c> scale</c><00:01:19.320><c> the</c><00:01:19.950><c> medical</c>

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used on a larger scale the medical
 

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used on a larger scale the medical
industry<00:01:20.520><c> is</c><00:01:21.000><c> applying</c><00:01:21.330><c> machine</c><00:01:21.600><c> learning</c><00:01:22.110><c> to</c>

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industry is applying machine learning to
 

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industry is applying machine learning to
things<00:01:22.500><c> like</c><00:01:22.650><c> predicting</c><00:01:23.340><c> lifespans</c>

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things like predicting lifespans
 

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things like predicting lifespans
organizing<00:01:25.110><c> patient</c><00:01:25.530><c> data</c><00:01:25.740><c> and</c><00:01:26.009><c> even</c>

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organizing patient data and even
 

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organizing patient data and even
diagnosing<00:01:27.330><c> certain</c><00:01:27.630><c> diseases</c>

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diagnosing certain diseases
 

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diagnosing certain diseases
as<00:01:29.630><c> with</c><00:01:30.630><c> many</c><00:01:30.810><c> emerging</c><00:01:31.380><c> technologies</c>

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as with many emerging technologies
 

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as with many emerging technologies
there's<00:01:32.460><c> a</c><00:01:32.520><c> concern</c><00:01:32.970><c> that</c><00:01:33.000><c> machine</c><00:01:33.570><c> learning</c>

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there's a concern that machine learning
 

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there's a concern that machine learning
may<00:01:34.020><c> eliminate</c><00:01:34.409><c> certain</c><00:01:35.009><c> jobs</c><00:01:35.360><c> this</c><00:01:36.360><c> will</c>

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may eliminate certain jobs this will
 

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may eliminate certain jobs this will
vary<00:01:36.780><c> from</c><00:01:37.020><c> industry</c><00:01:37.320><c> to</c><00:01:37.530><c> industry</c><00:01:37.770><c> but</c><00:01:38.340><c> it</c>

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vary from industry to industry but it
 

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vary from industry to industry but it
does<00:01:38.759><c> have</c><00:01:38.939><c> the</c><00:01:39.060><c> potential</c><00:01:39.420><c> to</c><00:01:39.600><c> get</c><00:01:39.930><c> rid</c><00:01:40.140><c> of</c><00:01:40.170><c> or</c>

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does have the potential to get rid of or
 

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does have the potential to get rid of or
change<00:01:41.009><c> a</c><00:01:41.280><c> number</c><00:01:41.549><c> of</c><00:01:41.640><c> occupations</c><00:01:42.110><c> including</c>

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change a number of occupations including
 

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change a number of occupations including
drivers<00:01:43.460><c> bankers</c><00:01:44.460><c> and</c><00:01:44.729><c> potentially</c><00:01:45.509><c> even</c>

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drivers bankers and potentially even
 

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drivers bankers and potentially even
certain<00:01:46.200><c> doctors</c><00:01:47.630><c> while</c><00:01:48.630><c> it</c><00:01:48.780><c> may</c><00:01:48.930><c> have</c><00:01:49.110><c> some</c>

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certain doctors while it may have some
 

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certain doctors while it may have some
negative<00:01:49.439><c> effects</c><00:01:50.130><c> many</c><00:01:50.579><c> believe</c><00:01:50.909><c> that</c><00:01:51.210><c> it's</c>

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negative effects many believe that it's
 

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negative effects many believe that it's
positive<00:01:51.600><c> applications</c><00:01:52.470><c> will</c><00:01:52.829><c> outweigh</c><00:01:53.159><c> them</c>

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Goodwill<00:01:57.420><c> Community</c><00:01:57.900><c> Foundation</c><00:01:58.560><c> creating</c>

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Goodwill Community Foundation creating
 

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Goodwill Community Foundation creating
opportunities<00:01:59.580><c> for</c><00:01:59.610><c> a</c><00:01:59.880><c> better</c><00:01:59.909><c> life</c>