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Life<00:00:00.560><c> Sciences</c><00:00:00.920><c> model</c><00:00:01.280><c> helps</c><00:00:01.600><c> scientists</c>

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Life Sciences model helps scientists
 

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Life Sciences model helps scientists
make<00:00:02.480><c> faster</c><00:00:03.080><c> and</c><00:00:03.280><c> better</c><00:00:03.520><c> decisions</c><00:00:04.320><c> by</c>

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make faster and better decisions by
 

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make faster and better decisions by
combining<00:00:05.160><c> structured</c><00:00:05.600><c> data</c><00:00:05.800><c> retrieval,</c>

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combining structured data retrieval,
 

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combining structured data retrieval,
literature<00:00:07.040><c> search,</c><00:00:07.720><c> and</c><00:00:07.880><c> scientific</c>

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literature search, and scientific
 

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literature search, and scientific
analysis<00:00:09.120><c> into</c><00:00:09.400><c> a</c><00:00:09.480><c> repeatable</c><00:00:10.080><c> workflow</c><00:00:10.800><c> in</c>

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analysis into a repeatable workflow in
 

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analysis into a repeatable workflow in
Codex.<00:00:12.000><c> In</c><00:00:12.120><c> this</c><00:00:12.320><c> instance,</c><00:00:13.200><c> the</c><00:00:13.320><c> Life</c>

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Codex. In this instance, the Life
 

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Codex. In this instance, the Life
Sciences<00:00:13.960><c> model</c><00:00:14.360><c> is</c><00:00:14.410><c> [music]</c><00:00:14.600><c> asked</c><00:00:14.880><c> to</c>

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Sciences model is [music] asked to
 

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Sciences model is [music] asked to
compare<00:00:15.560><c> and</c><00:00:15.760><c> prioritize</c><00:00:16.640><c> three</c><00:00:16.880><c> targets:</c>

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compare and prioritize three targets:
 

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compare and prioritize three targets:
IL-33,

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IL-33,
 

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IL-33,
TSLP,<00:00:20.640><c> and</c><00:00:20.920><c> IL-1</c><00:00:21.560><c> RA1</c><00:00:22.200><c> for</c><00:00:22.440><c> asthma.</c><00:00:23.280><c> It</c><00:00:23.480><c> starts</c>

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TSLP, and IL-1 RA1 for asthma. It starts
 

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TSLP, and IL-1 RA1 for asthma. It starts
with<00:00:24.040><c> an</c><00:00:24.240><c> internal</c><00:00:24.840><c> evidence</c><00:00:25.240><c> package,</c><00:00:25.960><c> which</c>

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with an internal evidence package, which
 

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with an internal evidence package, which
includes<00:00:26.760><c> internal</c><00:00:27.440><c> assay</c><00:00:27.720><c> results,</c>

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includes internal assay results,
 

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includes internal assay results,
biomarker<00:00:29.160><c> strategy,</c><00:00:30.200><c> tractability</c><00:00:30.880><c> and</c>

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biomarker strategy, tractability and
 

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biomarker strategy, tractability and
safety,

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safety,
 

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safety,
as<00:00:32.439><c> well</c><00:00:32.640><c> as</c><00:00:32.880><c> a</c><00:00:33.000><c> target</c><00:00:33.520><c> product</c><00:00:34.040><c> profile.</c>

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The<00:00:40.880><c> Life</c><00:00:41.080><c> Sciences</c><00:00:41.480><c> model</c><00:00:42.000><c> gives</c><00:00:42.320><c> a</c><00:00:42.440><c> crisp,</c>

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The Life Sciences model gives a crisp,
 

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The Life Sciences model gives a crisp,
top-line<00:00:43.720><c> recommendation.</c>

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top-line recommendation.
 

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top-line recommendation.
It<00:00:45.360><c> ranks</c><00:00:45.720><c> the</c><00:00:45.850><c> [music]</c><00:00:45.880><c> targets</c>

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It ranks the [music] targets
 

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It ranks the [music] targets
and<00:00:47.760><c> grounds</c><00:00:48.120><c> the</c><00:00:48.200><c> recommendation</c><00:00:48.840><c> based</c><00:00:49.200><c> on</c>

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and grounds the recommendation based on
 

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and grounds the recommendation based on
the<00:00:49.480><c> local</c><00:00:49.840><c> data</c><00:00:50.120><c> files</c><00:00:50.520><c> found.</c>

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the local data files found.
 

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the local data files found.
Codex<00:00:51.880><c> also</c><00:00:52.520><c> implies</c><00:00:53.080><c> that</c><00:00:53.320><c> there's</c><00:00:53.600><c> an</c>

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Codex also implies that there's an
 

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Codex also implies that there's an
opportunity<00:00:54.360><c> to</c><00:00:54.480><c> expand</c><00:00:54.960><c> upon</c><00:00:55.020><c> [music]</c>

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opportunity to expand upon [music]
 

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opportunity to expand upon [music]
additional<00:00:56.120><c> evidence</c><00:00:56.640><c> around</c><00:00:57.520><c> human</c>

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additional evidence around human
 

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additional evidence around human
genetics<00:00:58.640><c> or</c><00:00:58.760><c> target</c><00:00:59.120><c> disease</c><00:00:59.520><c> evidence.</c>

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genetics or target disease evidence.
 

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genetics or target disease evidence.
The<00:01:01.040><c> Life</c><00:01:01.240><c> Sciences</c><00:01:01.600><c> model</c><00:01:01.920><c> can</c><00:01:02.160><c> also</c>

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The Life Sciences model can also
 

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The Life Sciences model can also
leverage<00:01:03.120><c> the</c><00:01:03.280><c> Life</c><00:01:03.520><c> Sciences</c><00:01:03.540><c> [music]</c>

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leverage the Life Sciences [music]
 

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leverage the Life Sciences [music]
research<00:01:04.519><c> plugin</c><00:01:05.160><c> to</c><00:01:05.320><c> pull</c><00:01:05.560><c> in</c><00:01:05.720><c> additional</c>

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research plugin to pull in additional
 

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research plugin to pull in additional
relevant<00:01:07.120><c> evidence.</c>

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relevant evidence.
 

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relevant evidence.
The<00:01:08.400><c> model</c><00:01:08.720><c> has</c><00:01:08.840><c> been</c><00:01:09.000><c> trained</c><00:01:09.520><c> on</c><00:01:09.760><c> when</c><00:01:10.040><c> best</c>

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The model has been trained on when best
 

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The model has been trained on when best
to<00:01:10.520><c> invoke</c><00:01:10.960><c> appropriate</c><00:01:11.600><c> Life</c><00:01:11.800><c> Sciences</c>

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to invoke appropriate Life Sciences
 

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to invoke appropriate Life Sciences
skills,<00:01:13.120><c> as</c><00:01:13.280><c> well</c><00:01:13.440><c> as</c><00:01:13.560><c> how</c><00:01:13.680><c> to</c><00:01:13.800><c> synthesize</c><00:01:14.480><c> the</c>

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skills, as well as how to synthesize the
 

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skills, as well as how to synthesize the
outputs<00:01:15.200><c> of</c><00:01:15.320><c> those</c><00:01:15.520><c> skills.</c>

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outputs of those skills.
 

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outputs of those skills.
Let's<00:01:16.800><c> also</c><00:01:17.120><c> leverage</c><00:01:17.600><c> the</c><00:01:17.720><c> power</c><00:01:18.000><c> of</c><00:01:18.120><c> Codex</c>

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Let's also leverage the power of Codex
 

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Let's also leverage the power of Codex
to<00:01:19.080><c> spawn</c><00:01:19.440><c> sub-agents</c><00:01:20.200><c> to</c><00:01:20.360><c> tackle</c><00:01:20.565><c> [music]</c>

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to spawn sub-agents to tackle [music]
 

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to spawn sub-agents to tackle [music]
each<00:01:20.960><c> lane</c><00:01:21.160><c> of</c><00:01:21.280><c> evidence.</c>

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each lane of evidence.
 

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each lane of evidence.
That<00:01:22.640><c> keeps</c><00:01:23.160><c> the</c><00:01:23.280><c> genetics,</c><00:01:24.280><c> translational</c>

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That keeps the genetics, translational
 

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That keeps the genetics, translational
biology,<00:01:25.720><c> regulatory</c><00:01:26.320><c> context,</c><00:01:27.040><c> and</c><00:01:27.240><c> other</c>

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biology, regulatory context, and other
 

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biology, regulatory context, and other
criteria<00:01:28.040><c> separate</c><00:01:28.720><c> and</c><00:01:28.960><c> unbiased</c><00:01:29.735><c> [music]</c>

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criteria separate and unbiased [music]
 

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criteria separate and unbiased [music]
until<00:01:30.240><c> the</c><00:01:30.360><c> final</c><00:01:30.680><c> synthesis.</c>

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until the final synthesis.
 

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until the final synthesis.
The<00:01:32.280><c> Life</c><00:01:32.520><c> Sciences</c><00:01:32.920><c> model</c><00:01:33.280><c> has</c><00:01:33.480><c> directed</c>

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The Life Sciences model has directed
 

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The Life Sciences model has directed
Pascal<00:01:34.480><c> to</c><00:01:34.600><c> be</c><00:01:34.760><c> responsible</c><00:01:35.600><c> for</c><00:01:35.920><c> all</c><00:01:36.160><c> of</c><00:01:36.240><c> the</c>

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Pascal to be responsible for all of the
 

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Pascal to be responsible for all of the
human<00:01:36.840><c> genetics</c><00:01:37.440><c> evidence</c><00:01:38.280><c> that</c><00:01:38.440><c> should</c><00:01:38.600><c> be</c>

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human genetics evidence that should be
 

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human genetics evidence that should be
leveraged<00:01:39.320><c> in</c><00:01:39.480><c> comparing</c><00:01:39.561><c> [music]</c><00:01:40.000><c> the</c><00:01:40.120><c> three</c>

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leveraged in comparing [music] the three
 

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leveraged in comparing [music] the three
asthma<00:01:40.880><c> targets.</c><00:01:41.720><c> It</c><00:01:41.880><c> correctly</c><00:01:42.400><c> outlines</c><00:01:43.360><c> a</c>

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asthma targets. It correctly outlines a
 

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asthma targets. It correctly outlines a
list<00:01:43.800><c> of</c><00:01:43.920><c> skills</c><00:01:44.360><c> that</c><00:01:44.480><c> are</c><00:01:44.600><c> relevant</c><00:01:45.240><c> in</c>

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list of skills that are relevant in
 

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list of skills that are relevant in
order<00:01:45.680><c> to</c><00:01:45.840><c> pull</c><00:01:46.200><c> in</c><00:01:46.400><c> the</c><00:01:46.560><c> right</c><00:01:47.040><c> level</c><00:01:47.440><c> of</c>

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order to pull in the right level of
 

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order to pull in the right level of
human<00:01:48.000><c> genetic</c><00:01:48.400><c> evidence.</c><00:01:49.440><c> Once</c><00:01:49.840><c> all</c><00:01:50.360><c> of</c><00:01:50.520><c> the</c>

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human genetic evidence. Once all of the
 

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human genetic evidence. Once all of the
six<00:01:51.280><c> agents</c><00:01:51.920><c> that</c><00:01:52.120><c> have</c><00:01:52.280><c> been</c><00:01:53.080><c> sub-spawned</c>

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six agents that have been sub-spawned
 

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six agents that have been sub-spawned
have<00:01:54.160><c> completed</c><00:01:54.626><c> [music]</c><00:01:54.640><c> their</c><00:01:54.840><c> output,</c>

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have completed [music] their output,
 

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have completed [music] their output,
the<00:01:56.160><c> total</c><00:01:56.800><c> outputs</c><00:01:57.400><c> will</c><00:01:57.560><c> be</c><00:01:57.760><c> synthesized</c><00:01:59.160><c> in</c>

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the total outputs will be synthesized in
 

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the total outputs will be synthesized in
order<00:01:59.600><c> to</c><00:01:59.760><c> generate</c><00:02:00.360><c> a</c><00:02:00.480><c> final</c>

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order to generate a final
 

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order to generate a final
prioritization.

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prioritization.
 

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prioritization.
By<00:02:02.960><c> leveraging</c><00:02:03.440><c> the</c><00:02:03.600><c> output</c><00:02:04.000><c> from</c><00:02:04.200><c> a</c><00:02:04.240><c> variety</c>

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By leveraging the output from a variety
 

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By leveraging the output from a variety
of<00:02:04.800><c> databases,</c><00:02:05.760><c> the</c><00:02:05.880><c> model</c><00:02:06.240><c> is</c><00:02:06.440><c> able</c><00:02:06.840><c> to</c>

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of databases, the model is able to
 

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of databases, the model is able to
surface<00:02:07.480><c> locus-to-gene</c><00:02:08.280><c> context,</c><00:02:09.160><c> follow</c>

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surface locus-to-gene context, follow
 

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surface locus-to-gene context, follow
signals<00:02:10.000><c> across</c><00:02:10.440><c> cohorts,</c><00:02:11.400><c> bring</c><00:02:11.640><c> in</c><00:02:11.760><c> target</c>

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signals across cohorts, bring in target
 

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signals across cohorts, bring in target
disease<00:02:12.560><c> evidence,</c><00:02:13.440><c> and</c><00:02:13.600><c> literature</c><00:02:14.120><c> to</c><00:02:14.280><c> help</c>

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disease evidence, and literature to help
 

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disease evidence, and literature to help
resolve<00:02:15.000><c> ambiguity.</c>

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resolve ambiguity.
 

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resolve ambiguity.
&gt;&gt; [music]

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[music]

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[music]
 

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[music]
&gt;&gt; The<00:02:22.240><c> Life</c><00:02:22.440><c> Sciences</c><00:02:22.880><c> model</c><00:02:23.280><c> is</c><00:02:23.480><c> primed</c><00:02:23.960><c> with</c>

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&gt;&gt; The Life Sciences model is primed with
 

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&gt;&gt; The Life Sciences model is primed with
greater<00:02:24.480><c> thinking</c><00:02:25.160><c> and</c><00:02:25.440><c> bio-intelligence</c>

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greater thinking and bio-intelligence
 

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greater thinking and bio-intelligence
for<00:02:26.721><c> [music]</c><00:02:26.760><c> complex</c><00:02:27.320><c> scientific</c><00:02:27.880><c> tasks.</c>

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