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Envelope-to: dr.sultan@jack.ngo
Delivery-date: Thu, 13 Feb 2020 06:55:02 -0500
Date: Thu, 13 Feb 2020 05:54:21 -0600 (CST)
From: Canonical | Ubuntu <ubuntu-marketing@canonical.com>
Reply-To: ubuntu-marketing@canonical.com
To: dr.sultan@jack.ngo
Message-ID: <1618425380.834205222.1581594861401.JavaMail.mktmail@sjmas01.marketo.org>
Subject: Last Call: Edge AI in a 5G world
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Hi=C2=A0Sultan,
Deploying AI/ML solutions in latency-sensitive use cases requires a new sol=
ution architecture approach for many businesses.

Fast computational units (i.e. GPUs) and low-latency connections (i.e. 5G) =
allow for AI/ML models to be executed outside the sensors/actuators (e.g. c=
ameras & robotic arms). This reduces costs through lower hardware complexit=
y as well as compute resource sharing amongst the IoT fleet.

Strict AI responsiveness requirements that before required IoT AI model emb=
edding can now be met with co-located GPUs (e.g. on the same factory buildi=
ng) as the sensors and actuators. An example of this is the robot =E2=80=98=
dummification=E2=80=99 trend that is currently being observed for factory r=
obotics with a view to reducing robot unit costs and fleet management.

In=C2=A0today's webinar we will explore some real-life scenarios in which G=
PUs and low-latency connectivity can unlock previously prohibitively expens=
ive solutions now available for businesses to put in=20
place and lead the 4th industrial revolution.

<http://mkto-g0030.com/iPIE0fOTZLV00h030IG0V0f>

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tom: 11pt;">Deploying AI/ML solutions in latency-sensitive use cases requir=
es a new solution architecture approach for many businesses.<br><br>Fast co=
mputational units (i.e. GPUs) and low-latency connections (i.e. 5G) allow f=
or AI/ML models to be executed outside the sensors/actuators (e.g. cameras =
&amp; robotic arms). This reduces costs through lower hardware complexity a=
s well as compute resource sharing amongst the IoT fleet.<br><br>Strict AI =
responsiveness requirements that before required IoT AI model embedding can=
 now be met with co-located GPUs (e.g. on the same factory building) as the=
 sensors and actuators. An example of this is the robot =E2=80=98dummificat=
ion=E2=80=99 trend that is currently being observed for factory robotics wi=
th a view to reducing robot unit costs and fleet management.<br><br>In&nbsp=
;today's webinar we will explore some real-life scenarios in which GPUs and=
 low-latency connectivity can unlock previously prohibitively expensive sol=
utions now available for businesses to put in place and lead the 4th indust=
rial revolution.<br></p> <p style=3D"line-height: 1.8782608695652174; margi=
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