Machine Learning is changing the world.
Not long ago, when an application(enterprise or otherwise) was deployed, it was considered a black box. No one knew what was happening, and log files were cryptic entities that were looked into only when users complained about issues.
Fast forward to the current day, and we have intelligent algorithms telling us what the users did(and did not do), recommending offers that are suitable for individual users. We also have some adventurous companies “instrumenting” the real world, using sensors, and segmenting the customers and employees with data gathered from the environment.
Gone are the days when companies were left making best guesses about the “success” or “failure” of a campaign. In these days of A/B testing, users do not need to rely on opinions, when the decision can be based on cold, hard data.
Also gone are the days when decisions were taken by HiPPOs (“highest paid person’s opinion”). These days even the junior most employee can put his ideas to test and expect a proper data-based answer in a matter of hours or days.
What kind of applications should we build in this brave new world?
Some examples are:
- Applications that can adapt based on user’s action or inaction.
- Applications that can respond to stimuli in the environment(both virtual and physical)
- Applications that recommend actions based on the goals specified.
- Applications that can continuously learn and improve/fix itself via. multiple ways like anomaly detection, user actions, signals from the physical world etc.
VinodAth 