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EDITOR’S QUESTION
JAMES PETTER,
EMEA VP,
PURE STORAGE
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A
rtificial Intelligence (AI) is starting
to change how many businesses
operate. The ability to accurately
process, and deliver, data faster than any
human could, is already transforming how
we do everything.
With so much on offer and at stake, the
question is no longer simply what AI is
capable of, but rather where AI can best be
used to deliver immediate business benefits.
For those looking to implement AI or
Machine Learning (ML) projects, the
compute bottleneck that used to hold
back projects like these has largely been
eliminated. The application of graphics
processing unit (GPU) technology from the
likes of NVIDIA, has played a big part in this.
As a result, the challenge for many projects is
now providing the data fast enough to feed
the data analysis pipelines central to AI.
It is critical that organisations also carefully
consider the infrastructure needed to
support their AI ambitions. To innovate and
improve AI algorithms, storage has to deliver
uncompromised performance across all
manner of access patterns, all with the ability
to easily scale linearly and non-disruptively in
order to grow capacity and performance.
For legacy storage systems, meeting these
requirements is no mean feat. As a result,
data can easily end up in infrastructure siloes
at each stage of the AI pipeline – comprised
of ingest, clean and transform, explore,
train – making projects more time intensive,
complex and inflexible.
Bringing together data into a single
centralised data storage hub as part of a
deep learning architecture enables far more
efficient access to information, increasing
the productivity of data scientists and
making scaling and operating simpler and
more agile for the data architect.
www.intelligentcio.com
Modern all-flash based data platforms
are ideal candidates to act as that central
data hub. It’s the only storage technology
capable of underpinning and releasing
the full potential of projects operating
in environments that demand high
performance compute capabilities such as AI
and deep learning.
Flash storage arrays are best suited for AI
projects as they encompass a parallelism
that mimics the human brain and
enables multiple queries or jobs to run
simultaneously. By building this type of flash
technology into the very foundation of AI
projects, it vastly improves the rate at which
AI and ML initiatives can develop.
For years, slow, complex legacy storage
systems have been unable to cope with
modern data volume and velocity, and
have been a roadblock for next-generation
insights and progression. Purpose-built
flash storage array systems eliminate
that roadblock, removing the storage
infrastructure as a barrier to customers fully
leveraging data analytics and AI projects.
Whether AI is central to your company’s
core competency or not, it is a tool all
organisations should be looking at using
to bring efficiency and accuracy to their
data-heavy projects. Those who don’t
could be leaving their business at a severe
competitive disadvantage.
INTELLIGENTCIO
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