How Training AI Models In Simulated Environments Is Helping Researchers | Analytics India Magazine

The entire AI training process occurs during the simulation and without needing to go through the tedious process of data collection that is both difficult and expensive by Vishal Chawla, senior tech journalist at Analytics India Magazine (AIM).

Photo:  Analytics India Magazine

While artificial intelligence is impacting the world in different ways, the capability of machine learning algorithms profoundly relies upon the data. Reinforcement learning specifically where the model learns from feedback from the environment. But it takes a lot of time and data to train a model, deploy in production which makes predictions in the real world.

So, in many instances, researchers working to train advanced AI/ML models are restricted by both the quality and the amount of data. So, on the off chance that you need to show a vehicle to drive itself, you will require a great many miles of human driving data. On the other hand, with the help of simulation just as humans do in their brains, researchers can create a great many training data sets and come up with innovative models...

Reinforcement Learning In Conjunction With Simulation 
An algorithm in order to devise an intelligent policy needs to experience a multitude of experience, running in millions of parameters. In a situation where there is a lack of data, simulation is what allows it to do that. Over the past few years, we have started seeing superhuman accuracy coming out of machine learning algorithms in a wide variety of complex problems. 
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Source: Analytics India Magazine