Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Chandra, J.; Malviya, Meenakshi; Sabu, Samson; Rajendran, Rajesh Kanna; Joseph, Alwin Title A name given to the resource Applications and future directions in multimodal large language model: opportunities and challenges Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2026 Source A related resource from which the described resource is derived Challenges and Applications of Generative Large Language Models;pp.219-241 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1016/B978-0-443-33592-1.00006-1" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/B978-0-443-33592-1.00006-1</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105032983757?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105032983757?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Chandra J., Department of Computer Science, Christ University, Karnataka, Bengaluru, India; Malviya M., Department of Computer Science, Christ University, Karnataka, Bengaluru, India; Sabu S., Department of Computer Science, Christ University, Karnataka, Bengaluru, India; Rajendran R.K., Department of Computer Science, Christ University, Karnataka, Bengaluru, India; Joseph A., Department of Computer Science, Christ University, Karnataka, Bengaluru, India Description An account of the resource Multimodal large language models (MLLMs) are an application of artificial intelligence that is rapidly growing by integrating numerous use cases. MLLMs have the capability to process data from several sources, including structured and unstructured. It enables large language models (LLMs) to give insights to the user by analyzing data from various formats. The traditional way of analyzing the data was done with a single data format. While using MLLMs, multiple data modalities are handled to manage complicated multimodal tasks, like generating content, multimodal perception, and augmenting human-computer interaction. This chapter discusses in detail the insights from data from multiple modalities and domains of the use cases of MLLMs. We also discuss the advantages of MLLMs and explain the transformative benefits from unimodal systems to multimodal systems in different sectors. We also focus on the ethical usage of MLLMs by addressing the challenges related to privacy, operational limits, bias, computational difficulties, and data scarcity. The scarce assessment metrics and trials in accomplishing robust explainability are also discussed. To train these MLLMs, acquiring and training the data utilizes more computation and power consumption, along with addressing the data security and privacy concerns. The chapter also discusses the sensible usage of AI through different problems and practices. Detailed analysis and strategies for addressing global challenges and promoting novelty in model development, outlining how these MLLMs shape the upcoming technological innovation focusing on ethical application of technology with an advantage on society. 2026 Elsevier Inc. All rights reserved. Subject The topic of the resource automation; customer care; healthcare assistant; information management; machine learning; Multimodal large language models Publisher An entity responsible for making the resource available Elsevier Relation A related resource ISBN: 978-044333592-1; 978-044333593-8; Language A language of the resource English Type The nature or genre of the resource Book chapter Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online