MAN
freight routing was easy to optimise using the detailed mapping, traffic, shipping, and weather information, which has all materialised online in the llast few years. But the biggest push recently for A has been in healthcare. One m ch cited example i
freight routing w s easy to optimise usi g the detai ed m pping, traffic, shi ping, and weather i ich
formation, s a l m teria ised ine in th
Typically, as supervised AI requiires good data and good training, most early success will come in industries that use common data. For example, logistics companies all use the same types of road p, w ather, and traffic data. Likewise, virtu lly all retailers u e the sam
ast few years. But the biggest push recently for AI has been in healthcare. One much cited example is the use of IBM’s Watson which can identify very early stage diseases by exam tomography and other data. rvised
the use of
s W tson whi h can i entify very early stage diseases by examining tomography and other data. cally, as su
re
good data and good training, success w ll co
in in com on data. For example, res st earl
stries that u gisti
companies al use the same types of road map, weather, and traffic data. Likewise, virtually all retailers use the same
Universal Product Code (UPC) to identify products, which m ans AI techniques appl ed to UPC data benefits a large number of cus omer com anies to
Universal Product Code (UPC) to i entify products, which means AI techniques applied to UPC data benefits a large number of customers, and this will drive AI companies to buiild solutions for
and t wi dr ld solutions fo
retailers. In other words, industries adopt AI when the solutions begin to emerge. So,
dustr s rea ily e w ll h ve A solutio ready sooner than others. WHAT IES AHEAD WHA AT LIES AHEAD
But as m nufacturing i volves m re data than ever,
But as manufacturing involves more data than ever, we’re going to see AI with computer vision (CV) continue to
e going to see AI w th computer vision (CV) continue to
retai ers. In other words, i dustries adopt AI when the solutions begin to emerge. So, industries with high-quality data that iis readily available will have AI solutions ready sooner than others.
s with high-qual ty data that la
streamline how all that data gets streamline how all that data gets
captured. For example, a factory worker should be able to take raw materials stock from the shelf and have the inventory transaction created automatically based on a camera serving the pro ess. T is will b th natural user interface, just completing the task at hand not inputting or scanning things i to a system. That is ere the future of A seems to be, or rather, should be, going.
automatical y based on a camera observing the process. This will be the natural user interface, just completing the task at hand not inputting or scanning things into a system. That is where the future of AI seems to be, or rather, should be, going.
SiSimilarly, AI and IoT are going to rly, AI and I T are going to
continue to become m re closely l nked. IoT i remarkable in that the basic technology is being deployed rapidly, even though the outcomes and security aspects haven’t real
continue to become more closely linked. T is remarkable i
that the basi
technology i being deployed rapidly, even though the outcomes and security aspects haven’t really been thought through. Having detailed operational finished goods i
been thought
to change m rkets and production tactics. IoT willl provide a way to delliver supplsupplies and services to customers who might not realise they are needed. In addition, IoT can send detailed telemetry back to producers and distributors to analyse qual y and factors that mght rive failu es.
through. Having detai d operational sensors isensors in finished goods is clearly going to change markets and production tactics. Io
clearl going l pro ide a to ive
s and services to customers w ght not real se they are needed. I
addition, oT can send detai d telemetry back to producers and distributors to analyse quality and factors that might drive failures. In sh rt, Io
In short, IoT is an incoming tsunami of data that AI can use to reason over and evolve. T is will h lp
is an inco tsu
data that AI can use to reason over and evolve. This will help augmented generative design processes where
ente generative design processes w ere
products are reiproducts are reimagined in ways more akin to evolution.
agined i ways m re
akin to evolution. AI
don’t buy i off the shelf and use it, you infuse it in everything you do to augment your business and products and unlock potential for future business growth. e u
AI is not yet a turn-key solution. You don’t buy it off the shelf and use i fuse i
llin to invest in th you everything you do to augment
your business and products and unlock potential for future business growth. Those unwiilling to invest in the
technology sooner rather than later, will be the ones watching competitors becom re competitive and create a w rld- class supply chain capable of del veri not onlym re ti
efficiency, but both productive and financial efficiencies. cor Software ww. pi
Epicor Softw re www
ww
technology sooner rather than later, will be the ones watching competitors become more competitive and create a world- class supply chain capable of delivering not only more time efficiency, but both productive and financial efficiencies.
T: 01344 468468T: 01344 468468
www.epicor.com E:
nfo.uk@epi or om E:
info.uk@
epicor.com not yet a turn-key solution. You
captured. For example, a factory worker should be able to take raw m terial stock fromthe shelf and have the ventory transaction created
MANUFAC
ACTURING SOFTWARTWARE
FEA
FEAT RE ATURE
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