Bhattacharya Manojit, Pal Soumen, Chatterjee Srijan, Lee Sang-Soo, Chakraborty Chiranjib
Department of Zoology, Fakir Mohan University, Vyasa Vihar, Balasore, Odisha 756020, India.
School of Mechanical Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu 632014, India.
Mol Ther Nucleic Acids. 2024 Jun 15;35(3):102255. doi: 10.1016/j.omtn.2024.102255. eCollection 2024 Sep 10.
After ChatGPT was released, large language models (LLMs) became more popular. Academicians use ChatGPT or LLM models for different purposes, and the use of ChatGPT or LLM is increasing from medical science to diversified areas. Recently, the multimodal LLM (MLLM) has also become popular. Therefore, we comprehensively illustrate the LLM and MLLM models for a complete understanding. We also aim for simple and extended reviews of LLMs and MLLMs for a broad category of readers, such as researchers, students in diversified fields, and other academicians. The review article illustrates the LLM and MLLM models, their working principles, and their applications in diversified fields. First, we demonstrate the technical concept of LLMs, working principle, Black Box, and the evolution of LLMs. To explain the working principle, we discuss the tokenization process, token representation, and token relationships. We also extensively demonstrate the application of LLMs in biological macromolecules, medical science, biological science, and other areas. We illustrate the multimodal applications of LLMs or MLLMs. Finally, we illustrate the limitations, challenges, and future prospects of LLMs. The review acts as a booster dose for clinicians, a primer for molecular biologists, and a catalyst for scientists, and also benefits diversified academicians.
ChatGPT发布后,大语言模型(LLMs)变得更加流行。院士们出于不同目的使用ChatGPT或LLM模型,并且ChatGPT或LLM的使用正在从医学领域扩展到多元化领域。最近,多模态大语言模型(MLLM)也开始流行起来。因此,为了全面理解,我们对LLM和MLLM模型进行了全面阐述。我们还旨在为广大读者,如研究人员、不同领域的学生和其他院士,对LLM和MLLM进行简单且深入的综述。这篇综述文章阐述了LLM和MLLM模型、它们的工作原理以及在多元化领域的应用。首先,我们展示了LLM的技术概念、工作原理、黑箱以及LLM的演变。为了解释其工作原理,我们讨论了分词过程、词元表示和词元关系。我们还广泛展示了LLM在生物大分子、医学、生物科学和其他领域的应用。我们阐述了LLM或MLLM的多模态应用。最后,我们阐述了LLM的局限性、挑战和未来前景。这篇综述对临床医生起到推动作用,为分子生物学家提供入门知识,为科学家充当催化剂,也使不同领域的院士受益。