ISSUE FOCUS
July/August 2019 | Residential Tech Today 43
“We have a ‘Do No Harm’ rule similar to the
Hippocratic Oath,” said Ted Bremekamp, one of
my fellow Parasol co-founders and the
company’s director of operations.
How do you train a machine to observe a “Do
No Harm” rule? As the old adage goes, you only
need three things to be successful: “practice,
practice, practice.”
Scudo Labs thinks they’ve solved both issues
by developing their Scudo Box (launching in
September), which leverages a large database of
“heartbeats” (unique to each product)
developed across hundreds of home technology
devices.
When the Scudo Box sees devices like an
Apple TV or cable box failing, it can reboot it
automatically using a virtual technician engine
developed by their engineers. “Devices don’t
usually fail suddenly, they fail slowly over time,”
said Jason Blais, Scudo Labs lead engineer. “We
want to be able to predict product failures down
the road and proactively notify our clients,
reducing support calls and creating revenue
opportunities for integrators.”
Artificial Intelligence (AI) to
Intelligence Assistance (IA)
Thomas Friedman’s book, Thank You For
Being Late, describes a key inflection point for
AI when it begins to help highly skilled workers
make better decisions at a faster rate, freeing
them up to spend more time working on ways to
improve their industries. In remote monitoring,
this dovetails perfectly into helping integrators
by asking them if they’d like to automate routine
behaviors or power cycle a system that may
affect other parts of a home. Each time the
integrator replies back to the AI, the machine
learning improves, delivering better future
results.
Companies from industries of all stripes are
working hard to create basic AI enhancements
to their businesses by training routine tasks first
and then moving on to more complex
operations. It’s not uncommon to hear examples
of learning AI applications in call centers
recording every step a customer service
representative takes and then eventually trying
to solve the issue itself while being corrected by
the human “trainer.”
Solutions like Zendesk’s Answer Bot are great
examples of early AI at work trying to better
assist support professionals. While customer
support agents are engaged in helping customers
in the moment, Answer Bot offers up suggested
solutions in real time based on chat or email
sessions. By measuring the efficacy of its own
answers, Answer Bot gets better and better each
time using machine learning.
While AI may be just getting started, we have a
long way to go. “Eighty percent of our customer
issues aren’t solved with a simple reboot,” said
Joseph Kolchinsky, founder and CEO of
OneVision Resources. “Today’s support data
aren’t clean enough to draw meaningful
conclusions using AI.”
Remote monitoring solutions will be some of
the earliest beneficiaries of innovation in the CI
channel and it looks like a human/machinefriendly
partnership is much more likely than an
outright replacement of talented technology
professionals. I’m excited about the possibilities
and will be positioning my technology
integration company to take full advantage. x
(Left) the Scudo Box network appliance. (Right) Visibility One’s user interface.
Photo: iStock.com/Vertigo3d
/Vertigo3d