Now let's see some applications that
actually use big data and AI techniques at
web scale to achieve the prevalent of
predictive intelligence that we, human
exhibits in our every day lives.
The first and most prevalent example is
online advertising, where predicting our
intent when we search or read documents on
the web and our interests is a part of
every day life today.
Similarly gauging consumer sentiment from
the multitude of conversations which are
not public on Twitter and even some
Facebook forums and based on that,
predicting our own behavior is something
many organizations are already doing
without our actually being aware.
On the other side, adverse events such as
fires, strikes, floods, and even larger
disasters such as earthquakes, reach
Twitter first before hitting any news
channel or print media.
And organizations are now beginning to tap
into detecting such events as soon as
possible and rapidly predicting their
impact, so that they can react even
faster.
Intelligent question answering, such as in
the Watson Program that beat the Jeopardy
champions, is another example of
intelligence coming from, processing large
volumes of data garnered from the web.
Machines are also now able to categorize
and recognize places, faces and people
just as we humans do so every day because
there are a large volume of images and
videos available to process and learn
from.
In the future, personalize gnomic medicine
might become a reality and it's already
beginning to be explored as more and more
people share their DNA samples to get some
understanding of their ancestry or their
potential probability of contracting some
genetic diseases.
As more and more such data gets shared,
when it's quarterly date with clinical
data about the actual effectiveness of
different medicines on different kinds of
genetic profiles, we can potentially see
vast volumes of data leading to better
medication for all of us.
Similar examples are possible in other
arenas such as more intelligent
distribution and consumption of energy,
water and other scarce resources using
intelligent sensors and deep analytics on
the large volumes of data that one can
collect.
Securing ourselves better from bad guys is
another application of web intelligence
that is happening all the time, largely
without our knowing it.
Another term attracting a lot of attention
these days is big data analytics.
To a certain extent, this is all about
large enterprises.
Which are outside the web world
traditionally, trying to exploit more
efficient technology which was developed
by the web companies for their large scale
web intelligence tasks.
Technology which is proving to be equally
good if not better and cheaper than
traditional database technology.
Equal importantly though.
Big data analytics is about fusing the
social intelligence available from
external sources with the business
intelligence available from internal data
sources available within every large
enterprise.
In other words, a mix of private data and
web data on which the web intelligence
techniques used in the kinds of
applications we spoke about a few minutes
ago.
As a result, better sales and marketing,
more intelligence supply chains, and in
general digitally enabled, mobile enabled,
data driven business models and processes
are becoming possible using the same
techniques used by the web companies to
understand all of us better.
So in a nutshell, bit data analytics is
all about brick and mortar firms trying to
emulate the web companies by using exactly
the same techniques that they use for web