To control the behavior of physics-based characters through language, Nvidia's PADL combines a language model with reinforcement learning. One thing that comes to mind when remembering the start of this wave of AI is certainly the strangely moving 3D figures from Deepmind and other research institutions. These three-legged spiders or humanoid 3D puppets had learned their movements through reinforcement learning. There are now numerous approaches to making digital animals or human-like figures learn movements on their own. The goal of these methods is to develop AI systems that can generate natural-looking movements for a variety of simulated figures and thus complement or replace manual animation and motion capture processes in the long term.

These are a bulk of people pondering the same question and exploring different answers but at a hanging stage not knowing which one is correct and which one should they follow. The answers are very conflicting some share it on the basis of the research while some share their personal experience which confuses the newbies as hell. Well, the answer to this question depends on what you are trying to develop and why have you indulged in developing a machine learning app in the first place. I know the answer is a diplomatic one. But, let me tell you one thing most of the popular development languages are adding their support to simplify the machine learning.