Written by Vijay Bhaskar Reddy Velagala, Director, Clinion
Introduction
In the early years, your phone’s predictive text made you wonder, then came Gmail’s Smart Reply feature that utilizes machine learning to provide one-sentence responses. Since then we have come a long way, all thanks to Generative AI or GenAI. This technology is now capable of creating art, composing coherent paragraphs, writing code, and even assisting scientists in clinical research. But what exactly is Generative AI, how has it evolved, and what role can it play in clinical research? Let’s delve deeper!
What is Generative AI?
Generative AI, in simple terms, is a type of artificial intelligence that can create things on its own, like writing text, generating images, or even composing music. It’s like having a computer program that can come up with new ideas and create content without human input. Generative AI learns from existing data and uses that knowledge to generate new and creative content, making it useful in various fields, from writing stories to designing artwork.
The Evolution of Generative AI
The Early Days
The initial forms of generative AI were very basic. It could barely suggest some random words and generate single sentences based on traditional machine learning algorithms which were not very useful. The main challenge was to make these systems ‘learn’ like a human does. Examples are the phone text and Gmail.
Generative AI in Clinical Research
Generative AI holds the potential to revolutionize the healthcare industry, especially in the realms of clinical research and trials. Some areas where it can make a significant impact include:
Read more: Generative AI in Clinical Research
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