Traditional summary generation approaches are limited by their reliance on isolated sources of data, restraining the quantity and quality of information gathered. This introduces the possibility of falsified content and provides limited support for multilingual and multimodal data. This paper presents a novel approach to summarization that tackles such challenges by utilizing the strength of multiple sources to deliver a more exhaustive and informative understanding of intricate topics. It progresses beyond conventional, unimodal sources such as text documents, integrating a diverse range of data, including YouTube playlists, pre-prints, and Wikipedia pages. The aforementioned multimodal sources are converted into a unified textual representation, enabling a holistic analysis. This multifaceted approach empowers us to extract pertinent information from a wider array of sources. The primary tenet of this approach is to maximize information gain, maintain a high level of informativeness while minimizing information overlap, and encourage the generation of highly coherent summaries.