Generative AI is a subset of AI that creates new content, such as text, images, audio, or videos. Unlike traditional AI, Gen AI mimics human intelligence to analyse data, identify patterns, and create new content. It is called generative because of its ability to “generate” human-like responses to prompts. On the other hand, traditional AI, focuses on automation.
GenAI took the world by storm when OpenAI, an AI research and deployment company, released its GPT-3.5 chatbot on November 30, 2022. Since then, many other companies have launched their GenAI chatbots.
With each day, AI is becoming an increasingly integral part of various aspects of daily life. As its influence continues to grow, let us understand more about it.
1 September 2025
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Journey Of Generative AI
According to Gartner, a research and advisory firm, in 2010, researchers found that natural language translation AI models exposed to a vast amount of text perform better than other models. They use Natural Language Processing (NLP), a branch of AI, to understand human language and translate it into a target language.
In 2014, the language model started understanding the meaning of natural language words by analysing the context.
Between 2017 and 2022, advanced language models were developed for creating a customised language model.
In 2022, ChatGPT provided users a simple way to access a large language model (LLM) that could understand and converse in the natural language of humans.
How Does It Work?
GenAI uses neural network architecture, an organised structure of artificial neurons and their layers to learn patterns like humans by exposing it to massive datasets of text, images, etc. When a prompt is given, it uses these learned patterns to generate an original response quickly.
It identifies the patterns, structures, connections, and relationships within data to forecast a possible next element, such as syntax in a text.
It uses unsupervised and semi-supervised learning approaches to continuously understand and analyse the patterns.
Its ability to rapidly utilise a large amount of data from ongoing inputs and feedback enables continuous improvement in its responses.
Use-Case And Tools
Typically, people use GenAI-powered chatbots and virtual assistants to get answers to their questions quickly without searching different websites, such as consulting for medical issues, getting financial advice, among other use cases.
One of the most common uses of GenAI is creating or augmenting content. Examples include ChatGPT for generating original text, images, audio, or video; DALL-E and Midjourney for producing unique and captivating images; Canva Magic for design; Runway for video editing; and GitHub Copilot or CodeGPT for coding, among many others.
Organisations have started using GenAI for generating reports, automating document scanning, filing, analysing large datasets, and leveraging it for decision making, and so on.
