- Sometimes, it's hard to look back
and imagine how things used to be.
To think that our great great grandparents,
if not our great grandparents made do without cars,
definitely the internet, or even
penicillin, is just amazing.
When those things came about, they must
have seemed so new, so different, so magical.
That's how many of us feel
about speech-driven user experience
brought to life through services like Amazon's
Alexa or Microsoft's Cortana.
In a really interesting way, it's almost as if these types
of services are making machine learning,
or at least what it's like to live with machine learning
a household name, an everyday experience.
When's the last time your phone apologized
for not understanding something that you asked of it,
and then ask to teach it how to understand the next time.
Mine just did it before I recorded this video,
and it seems like it's doing it more
and more, all of the time.
That's machine learning at work, my friends.
That's because sitting behind these services
are ML algorithms that help them
to get more precise over time.
Welcome to the world of chat bots.
In a way, this is the gateway
to wider adoption for machine learning.
A chat bot is a computer program
that translates human speech into binary,
such that the application can actually have
a conversation with you.
Some are better than others.
If you're like me, you've experienced
the dreaded customer service scenario
where you're trying to get a representative
on the phone and you have to successfully navigate
this voice-driven, way-finding system first.
Sometimes, it hears exactly what you're saying,
and other times it gets it all wrong.
But again, these systems are getting smarter all the time.
And with marketers now being responsible
for the totality of the customer journey,
it's an important technology to begin
to understand more fully.
If you can develop a smarter chat bot
for certain customer experience activities,
then you can reduce costs, you can increase response times,
and perhaps you can get customers what they need
more quickly than if it was just a human-driven system.
So how does it work?
Well, in the case of Microsoft's Azure,
there is this infrastructure known as Cognitive Services.
It's a series of machine-learning APIs
that you can use to add intelligence
to your marketing applications.
Things like facial recognition,
the detection of emotion,
or in this case, speech recognition.
This infrastructure from Azure and services like
it from other providers represents an exciting new frontier.
It's clear that there's a whole crop
of new voice-activated applications
for marketing and for consumer engagement
just around the bend.