Generative AI is abbreviated as GenAI, it’s a subpart of Artificial Intelligence, its advanced version of traditional AI that mainly focuses on creating new content by resembling real-world data. GenAI can generate articles, music, images, videos, and many more by operating learning patterns from a large Datapool.

What is Generative AI in simple terms?

In simple terms, it’s the same as traditional AI but with some advanced machine learning applications. of Generative AI is trained using advanced machine learning techniques and deep learning algorithms. Large Language Models (LLMs), Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) are the core models of GenAI for data analysis and replication. It can generate unique content by analysing live and existing data, and with its decision-making ability it can create new content.

Key points of Generative AI

• Generate New Content: It has the ability to generate unique information that never existed like creating personalized music, videos and many more.
• Used in vibrant fields: GenAI is habituated in many fields including art, research, finance and gaming, with which users are getting new ideas and opportunities.
• Feeds on updated data: Operate on a large dataset of real-world data so you can get feeds on a day-to-day basis.
• Act on Prompts: Just with your imagination hit prompt on the tool and you are ready to get your personalized data which is unique in the field.

The key difference between Generative AI and AI

Key Point	Generative AI	Traditional AI
Learning Approach	It is trained using advanced machine learning and deep learning algorithms, and it is often trained using unsupervised learning models with unstructured data.	Data trained on predefined rule-based and supervised learning eventually confines the adaptability and requires human intervention
Functionality	Operated in a free environment it has no boundaries and analyzes real-world data to make decisions, it allows to generate of unique information	It focuses on existing data makes predictions within predefined boundaries and operates in a structured environment.
Creativity	Unleash the productivity and produce the original content.	It lacked imagination as it operated on predefined rules
Applications	Used in fields such as entertainment, and design where content creation is dominant	Used where it requires specific tasks like service automation and analysis.
Conclusion	More creative and advanced capability	More Structured and tasks-oriented

What is an example of a Generative AI model?

Knowingly or unknowingly it becoming part of our day-to-day life. Whether you are using an iPhone or Android it has has smart assistant i.e. Siri, Google-assistant or Alexa. It feeds on live data you gave an instruction and post-processing you get your result. For creative guys, this is the best gift with their inspiration they can achieve and showcase their credibility. Imagination is the powerhouse of their technology and even with its true power it can give you genuine information but the condition is that you need to be specific while giving commands the prompt should be clear.

In vibrant fields, it’s showcasing its magic in Art, gaming, music and video creation. It is widely used in popular AI tools or sites, and it includes:

• Text/Articles: ChatGPT, Gemini, perplexity.ai
• Images: DALL-E, Midjourney
• Videos: Runway, Pictory, Synthesia
• Music: AIVA, Soundraw, Beatoven.ai

Is ChatGPT a Generative AI?

In terms, GenAi is more like a personal creative assistant with unique ideas learned from the real world and other hand ChatGPT is like a gentle AI with a structured and enclosed model that runs on specific data only which is bounded by rules. ChatGPT is also just a few steps back and OpenAi parent company of ChapGPT upgrading it so that it can cope with live data. To fight over which one is best is not supposed to be a debating topic rather than how we can utilize it for good work.