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Envelope-to: dr.sultan@jack.ngo
Delivery-date: Thu, 19 Nov 2020 09:08:22 -0500
Date: Thu, 19 Nov 2020 08:07:36 -0600 (CST)
From: Canonical | Ubuntu <ubuntu-marketing@canonical.com>
Reply-To: ubuntu-marketing@canonical.com
To: dr.sultan@jack.ngo
Message-ID: <627509961.64556576.1605794856462@sjmktmail-batch1e.marketo.org>
Subject: Webinar: AI deployment and inference
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Hi=C2=A0Sultan,
As artificial intelligence reshapes traditional and new industries, challen=
ges arise for enterprises looking to innovate. Dell and Canonical address t=
hese topics in our upcoming webinar.

Join us to discuss:

=09- What happens after you have trained your AI model? This spans model de=
ployment for inference at the edge, to inference serving, to distributed tr=
aining and the handling of new data, to the underlying setup and operations=
.
=09- The importance of reliable hardware and software layers in critical ap=
plications and the benefits of using specialised data science workstations =
with Linux.
=09- How to streamline your AI operations to shorten your deployment cycles=
.

<http://mkto-g0030.com/s0PB3Vf0IOf90E1GfZ00h0V>
Tuesday, 1 December
And later on demand

We hope to see you there.

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px; color:#717073; font-family:Ubuntu, Arial, Helvetica, sans-serif; "><p><=
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none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-strok=
e-width: 0px; background-color: #ffffff; float: none; display: inline !impo=
rtant;">Hi&nbsp;</span><span style=3D"font-family: Ubuntu, Arial, Helvetica=
, sans-serif; font-style: normal; font-variant-ligatures: normal; font-vari=
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<td width=3D"560" align=3D"left" valign=3D"top" style=3D"color:#717073; fon=
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ont-family: Ubuntu, Arial, Helvetica, sans-serif; line-height:24px; font-si=
ze:15px; color:#717073; font-family:Ubuntu, Arial, Helvetica, sans-serif; "=
><p>As artificial intelligence reshapes traditional and new industries, cha=
llenges arise for enterprises looking to innovate. Dell and Canonical addre=
ss these topics in our upcoming webinar.</p> <p>Join us to discuss:<br></p>=
=20
<ul>=20
<li>What happens after you have trained your AI model? This spans model dep=
loyment for inference at the edge, to inference serving, to distributed tra=
ining and the handling of new data, to the underlying setup and operations.=
</li>=20
<li>The importance of reliable hardware and software layers in critical app=
lications and the benefits of using specialised data science workstations w=
ith Linux.</li>=20
<li>How to streamline your AI operations to shorten your deployment cycles.=
</li>=20
</ul> <p><br></p> <p><a href=3D
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to;"></a></p> <p style=3D"text-align: center;">Tuesday, 1 December<br>And l=
ater on demand<br></p> <p>We hope to see you there.<br></p></span></td>=20
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