1 Unveiling the Power of Generative AI: A Journey into Large Language Models
A. Ashwini, J. Jency Rubia, H. Sehina, B. Sundaravadivazhagan · 2024
The artificial intelligence (AI) space has been revolutionized recently by the advent of generative AI models that allow machine-generated content to appear visually identical to content generated by real people. The newly emerging field employs a variety of techniques and architectures to produce different kinds of outputs, ranging from text and images to music and full synthetic environments. One of the most popular paradigms of such field is the family of generative models, and, recently, the subfamily of large language models (LLMs). Thus, generative AI, including LLMs, is based on the conception of probability distribution. This is when technology feds many datasets and learns the patterns and laws that hide under that data, enabling the AI to write effectively. LLMs have been used to schedule and seed texts naturally across various domains, from training transformer-like models, to code prototyping, writing, and journal narration. Thus, to resolve the challenges associated with it, an integrated nature of modeling with the training techniques is evolved, which eventually follows all the rules, regulations, as well as guidelines that help in successful implementation of generative models and LLMs.