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