Smart Industry 2/2018

Smart Solutions Data
structured data sets with the insights
of skillfully trained AI opens
additional value streams not otherwise
accessible.
Another simple example is the
amalgamation of all data on autowipers
in cars (wiper on = rain). A
car manufacturer that captured
and processed that data could become
the timeliest weather forecasting
service. Remember that The
Weather Company was sold to IBM –
which is housing it under its Watson
AI group – for a reported $2 billion
in 2016.
Look at the infrastructure
These developments could have
a bigger impact on industry than
any incremental steps of automation
because they allow value to be
unlocked in parts of organizations
that were not deemed valuable in
the past. For example, Volkswagen
would arguably not have attributed
a ten-figure valuation to its wiper
division.
To be able to surface these values,
it is necessary for organizations to
look at their data infrastructure and
Machines,
robots, and
sensors have
become
data nodes
and the true
opportunities
can now be
unleashed.
Now everybody’s
doing it!
All major players are
now offering a new
wave of enterprise
services that come
with a specific sensitivity
as they handle
the very core of a
company’s data
infrastructure.
bring it into a shape where it can
easily be accessed and processed.
Arcane legacy systems will hamper
the efficient deployment of IoT solutions
as value can only be partially
unlocked.
This requires the building of a data
science function that can dive deep
into the leading edge of AI systems.
The building blocks for such systems
are now widely and easily available
but the minutiae in their deployment
is varied (do Monte Carlo
systems perform better than multiarmed
bandits? No, I wouldn’t know
either…) and the integration of
such functions are not trivial. When
well implemented, they will boost
almost every organization’s ability
to extract, analyze, and action data
sets to improve performance on all
facets of the value chain: faster and
better product development, deeper
customer understanding, more
focused product innovation cycles,
higher productivity.
We are thus looking at a new wave
of enterprise services that come
with a specific sensitivity as they
handle the very core of a company’s
data infrastructure. This will
likely take the shape of a layered
cake: the various data layers residing
in the company’s domain,
whilst the processing of (often anonymized)
data sets taking place
in standardized AI frameworks
hosted in the cloud. All major players
are now offering suites of services
and tools to handle the key
elements of this, including Google
(TensorFlow), Microsoft (Cortana),
IBM (Watson), and Amazon (Lex
and Polly via AWS).
Lex and Polly via AWS
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