Congratulations to authors Rajesh Pasupuleti, Ravi Vadapalli, Christopher Mader, and Timothy Norris on the publication of their paper “Popular LLM-Large Language Models in Enterprise Applications” from the 2024 2nd International Conference on Foundation and Large Language Models (FLLM2024) by IEEE Xplore.*

Abstract

For the public, understanding Large Language Models (LLMs) can be likened to recognizing how a well-trained assistant works—one that has read an extensive library of information on virtually every topic imaginable. Imagine an assistant that not only reads and remembers all this information but also learns the nuances of how words and ideas are connected across different contexts. This assistant can then use this knowledge to write articles, answer questions, compose emails, or even generate creative stories, all in a manner that feels surprisingly human.

This capability comes from what’s known as “transformer architecture,” a type of design that helps the model pay attention to different parts of the text as it reads, making it adept at understanding and generating language. LLMs are a breakthrough in technology because they can understand and produce language with a level of subtlety and complexity that was previously unachievable, making them valuable tools across various industries.

This paper aims to provide a comprehensive analysis of the transformative impact of LLMs across various enterprise sectors. It intends to contribute to the understanding of how LLMs can enhance efficiency, innovation, and decision-making processes in industries such as healthcare, finance, education, and in the software engineering sector. It also provides a comprehensive overview of current popular LLMs in Enterprise applications, in various domains, and discusses the Ethical, Technical, and Regulatory challenges, future trends, and developments in this dynamic field.

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