FINAL WORD
Artificial intelligence soon
inbuilt into cloud
A
t the recent Code Conference,
there was a lot of talk amongst
industry insiders about how
artificial intelligence will advance the
adoption of new technologies and
solutions. IBM CEO Ginni Rometty
predicts that, within five years, cognitive
artificial intelligence will impact every
decision made.
Although artificial intelligence has been around
since the 1960’s, advances in graphic processing
units and networking, along with the demand
of big data, have put it back into the forefront.
Given the explosion of data from applications
and Internet of Things sensors, and the need for
real-time decision making, artificial intelligence
is quickly becoming a key requirement and
differentiator for major cloud providers.
As a result, the adoption of machine
learning in the enterprise may be closer than
predicted as leading cloud providers are
making artificial intelligence more accessible
As-a-Service via open source platforms.
According to the Financial Times,
artificial intelligence in the cloud is
the next great disrupter and opens up
opportunities for businesses to create
powerful new artificial intelligence
applications fast, without building the
tools, infrastructure or expertise in house.
Amazon’s in-house artificial intelligence
expertise, such as for predictive analytics,
is available on Amazon Web Services via
its Machine Learning Service. Amazon
is also releasing as open source the
Deep Scalable Sparse Tensor Network
Engine, which drives Amazon’s customer
recommendation capabilities, suggesting
the types of books you may like to read or
movies that you may want to watch.
Google Cloud Platform offers a number
82
Jeroen Schlosser is Managing Director Middle
East and North Africa at Equinix
of home-grown artificial intelligence
capabilities, such as predictive analytics,
speech recognition, translation and image
content identification.
In addition to offering the platform,
Google is able to leverage its other products
to improve its artificial intelligence. For
example, the more pictures that Android
users take of cats that are uploaded to
Google, the better Google’s model is for
identifying cats.
Microsoft currently offers its Distributed
Machine Learning Toolkit to allow users
to run multiple and varied machinelearning applications simultaneously,
such as analysing images and using
Microsoft Computer Vision and language
comprehension.
IBM’s Watson Developer Cloud enables
developers to incorporate Watson
intelligence in their apps and provides its
Watson artificial intelligence engine as
an analytics cloud service.
Consider the following complex
problems in the transportation industry.
Shipping companies, such as FedEx and
UPS, want to figure out the most efficient
and cost-effective way to deliver the
most packages. Public transportation
organisations need to identify city traffic
patterns to keep vehicles moving without
creating gridlocks.
From analysing how to fit the maximum
number of packages in a delivery van,
to calculating and navigating the fastest
routes to deliver those packages, multiple
technologies such as the IoT and big data
analytics require artificial intelligence to
solve these complex problems.
When people think of artificial
intelligence, they tend to think of humanlike or general intelligence. And while
that may be possible in the future, today’s
platforms and models are fragmented
and capable of solving only very domainspecific problems.
So for enterprises with various complex
problems to solve, it requires multiple
services from disparate platforms working
together, which is why making artificial
intelligence technology and applications
available via open sources is so critical
to the enterprise. By leveraging multiple
artificial intelligence cloud services,
companies can innovate solutions to solve
an infinite number of complex problems.
With more than 500 cloud providers
collocating with partners like Equinix,
their role becomes an intersection
point for cloud-based artificial
intelligence platforms, making them
accessible to customers through direct
interconnections.
Issue 01
INTELLIGENT TECH CHANNELS