AI Beyond Text: Integrating Vision, Audio, and Language for Multimodal Learning


Authors : Gopalakrishnan Arjunan

Volume/Issue : Volume 9 - 2024, Issue 11 - November

Google Scholar : https://tinyurl.com/4pzu4d36

Scribd : https://tinyurl.com/4dp7j8jb

DOI : https://doi.org/10.5281/zenodo.14287143

Abstract : This report delves into the integration of artificial intelligence (AI) with vision, audio, and language in the field of multimodal learning, which enables AI systems to process and analyze data coming from various sensory sources in order to gain a more overall view of the world. Multimodal AI enhances performance in tasks such as emotion recognition, image captioning, autonomous vehicle navigation, and medical diagnostics through the combination of visual, auditory, and linguistic information. Some of the notable applications of AI include personalized customer interactions via customer service, real-time decision making by autonomous vehicles, improved healthcare diagnosis and patient care, among other applications. The challenges in the responsible deployment of AI with respect to data fusion, privacy, bias, and transparency also feature within the report. Challenges notwithstanding, the report points to the enormous impact multimodal AI will make in revolutionizing industries through improved efficiency, safety, and personalization of a myriad of services. The prospect of future innovation of multimodal learning for AI promises to be path breaking and significantly advance the capabilities of AI systems in problems solving widely across domains.

Keywords : Artificial Intelligence, Multimodal Learning, Vision, Audio, and Language.

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This report delves into the integration of artificial intelligence (AI) with vision, audio, and language in the field of multimodal learning, which enables AI systems to process and analyze data coming from various sensory sources in order to gain a more overall view of the world. Multimodal AI enhances performance in tasks such as emotion recognition, image captioning, autonomous vehicle navigation, and medical diagnostics through the combination of visual, auditory, and linguistic information. Some of the notable applications of AI include personalized customer interactions via customer service, real-time decision making by autonomous vehicles, improved healthcare diagnosis and patient care, among other applications. The challenges in the responsible deployment of AI with respect to data fusion, privacy, bias, and transparency also feature within the report. Challenges notwithstanding, the report points to the enormous impact multimodal AI will make in revolutionizing industries through improved efficiency, safety, and personalization of a myriad of services. The prospect of future innovation of multimodal learning for AI promises to be path breaking and significantly advance the capabilities of AI systems in problems solving widely across domains.

Keywords : Artificial Intelligence, Multimodal Learning, Vision, Audio, and Language.

Video Explanation for Published paper

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