Sunday, March 5, 2017

Instantaneous Systems in Future (Applications of AI, ML and DA)

A lot has been already talked about AI, Machine Learning and Data at a superficial level. There is very little clarity among people that how it would affect our day to day lives. Most people I know have the impression of AI as a Robot that has near human intelligence and would take over the planet earth. This particular use case (although highly exciting) is a rare possibility in future.  In this article I would list the possible use cases of AI, Machine Learning and Data Analysis.

Use Case 1: Cooking food
In the current scenario, we think of what we would like to eat, go to grocery store, pick the right recipe ingredients and then go home and cook the food. This is way too tiring.

Future Case Scenario:-
There is an app which knows and understands your tastes very well. You need to select your mood, and based on the data it has from millions of consumers, it would suggest which food you would like to eat, along with an estimated price for the ingredients. You tap the food, the self driving cars come to your house, delivering the grocery. They put it in a chef-robot-machine which knows how to cook that particular dish very well (from an algorithm) and you can enjoy the food you love. Further customisation could be done for the robot by the mobile application in your pocket.

You can get a personalised experience, 100% quality assurance and very quick results based on the algorithms controlling the robot.

Use Case 2: Education AI
In the current scenario, a teacher comes to the class, and teaches to class with the help of blackboard, or some PowerPoint Presentation at maximum. The students are merely brick in the walls.

Future Case Scenario:-
Every student opens the mobile application on their mobile phones/tablets. The student gets huge variety of courses, along with reviews from industries and professors doing research. After committing to a particular course, students would be grouped and assigned a physical classroom. The learning process would be completely personalised. The mobile application would control assignments, in class exercises and submission of assignments (using photographs). The teacher would give the evaluation to the mobile application and the algorithm would compute the actionable insights for each and every student. All the actionable insights would be categorised and separate sessions would be held to work on those actionable insights. There would be no exams to evaluate knowledge, instead there would be peer-to-peer feedback to understand co-cooperativeness,  projects to understand vision and creativity and finally continuous human-jamming sessions to understand the thinking of students and help them in achieving their goals. To ensure a student has learnt something properly, interviews(vivas) and a small written test would be held which could be given at any time, according to the student's convenience.
Most of this is about re-imagining workflow but again at each of the crucial junctions, it need machine learning and artificial intelligence.

Use Case 3: Energy
I have already written an article where I talked about internet of things in much clearer sense in my article written over here ,