Scholarlink

In recent years, the remarkable advancements in Large Language Models (LLMs) and generative AI tools have ushered in a transformative era across various industries. This research paper provides a comprehensive exploration of LLMs, delving into their architectural foundations and training methodologies, while highlighting their versatile applications spanning natural language processing, content generation, and problem-solving. We also delve into the ethical considerations and challenges surrounding LLMs, including bias mitigation and responsible AI deployment. Furthermore, this paper sheds light on how these technological breakthroughs have reverberated in the hardware industry, particularly in semiconductor manufacturing, where the demand for AI-optimized chips has surged. Additionally, we offer a detailed comparative analysis of leading LLMs and generative AI frameworks, offering nuanced insights for researchers, practitioners, and decision-makers to harness the transformative potential of these technologies and adapt to the evolving landscape of the AI industry.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Catalysts of Transformation: Deep Dive on Transformer Architecture the Tech Behind Large Language Models and Generative AI

  • 会议论文

  • 发表日期：

    2026年

查看全文
  • Praneet Amul Akash Cherukuri,
  • Shivani Yadao,
  • Vijender Kumar Solanki

摘要

In recent years, the remarkable advancements in Large Language Models (LLMs) and generative AI tools have ushered in a transformative era across various industries. This research paper provides a comprehensive exploration of LLMs, delving into their architectural foundations and training methodologies, while highlighting their versatile applications spanning natural language processing, content generation, and problem-solving. We also delve into the ethical considerations and challenges surrounding LLMs, including bias mitigation and responsible AI deployment. Furthermore, this paper sheds light on how these technological breakthroughs have reverberated in the hardware industry, particularly in semiconductor manufacturing, where the demand for AI-optimized chips has surged. Additionally, we offer a detailed comparative analysis of leading LLMs and generative AI frameworks, offering nuanced insights for researchers, practitioners, and decision-makers to harness the transformative potential of these technologies and adapt to the evolving landscape of the AI industry.