Journey from Python to Generative AI

Python -> Machine Learning -> Artificial Intelligence -> Generative AI

In todays’ modern era nobody is unaware of the role of Artificial Intelligence (AI) in our daily life. Its on everybody’s tip of tongue. As all the innovation revolves around AI these days.

But do you know the backbone of AI on which this big building stands on, yes you guess it right

Its Python the programming language which implements the complex statistical and Neural Network models to reality and get some concrete calculations with at most precision based on modelling and simulations.

Python connects with well defined libraries like TensorFlow, PyTorch and various Data Science libraries like numpy, scipy , matplotlib and pandas, which gives capability to run various statistical algorithms and models over huge data sets with great ease.

This process gives direction to apply complex models like Neural Network, Genetic Algorithm, Monte Carlo Simulations, Naive Bayes Theorem in real world situation and give results and reports.

This gives birth to another strong field popularly known as Machine Learning which leverage on above algorithms and huge date sets to process outputs which help us in important decision making.It also give power to choose best results out of multiple possible solutions for a given problem.

When these solutions are utilised to predict futuristic behaviours based on time series or a reference point, with fixed set of rules applied over it, leads to innovation of Artificial Intelligence.

Artificial Intelligence utilises the strength of machine learning, deep learning, neural networks to imitate the human behaviour relying on predictions done based on algorithms and datasets.

Final result of such interesting and complex phenomenon can be the famous products like:

AI Chatbots which helps in replacing human intervention on multiple call centres and reduces the workload of call centres and at the same time make information available to customers quicker and 24X7, so its win win situation for both users as well service providers.

Another important innovation done on Top of AI is Generative AI , which is one step ahead of AI. In Traditional AI you will be following set of rules to attain fixed goals , whereas in generative AI you are actually build creative data and information based small data or limited information availability. Lot of focus given to sentiments of the user/data to build new data on top if it.

For example:
If you give small information about yourself to Generative AI model it will give full About us Summary on your life, if you give more facts and figures it probably can write Autobiography for you on your behalf, and its very hard for readers to identify whether its written by a you/human or else.

With this technology still in nascent stage with advantages there are few risk and limitations associated to Generative AI. For details on Risk and how to mitigate that I will be discussing this in my next article, so stay tuned.
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