This work introduces systematic approach for enhancing large language models (LLMs) to address Bangla AI mathematical challenges. Through the assessment of diverse LLM configurations, fine-tuning with specific datasets, and the implementation of Retrieval-Augmented Generation (RAG), we enhanced the model's reasoning precision in a multilingual setting. Crucial discoveries indicate that customized prompting, dataset augmentation, and iterative reasoning improve the model's efficiency regarding Olympiad-level mathematical challenges.

Ethnic media, which caters to diaspora communities in host nations, serves as a vital platform for these communities to both produce content and access information. Rather than utilizing the language of the host nation, ethnic media delivers news in the language of the immigrant community. For instance, in the USA, Bangla ethnic media presents news in Bangla rather than English. This research delves into the prospective integration of large language models (LLM) and multi-lingual machine translations (MMT) within the ethnic media industry. It centers on the transformative potential of using LLM in MMT in various facets of news translation, searching, and categorization. The paper outlines a theoretical framework elucidating the integration of LLM and MMT into the news searching and translation processes for ethnic media. Additionally, it briefly addresses the potential ethical challenges associated with the incorporation of LLM and MMT in news translation procedures.

It didn't take long for the downsides of a generative AI-empowered newsroom to make themselves obvious, between CNet's secret chatbot reviews editor last November and Buzzfeed's subsequent mass layoffs of human staff in favor of AI-generated "content" creators. The specter of being replaced by a "good enough AI" looms large in many a journalist's mind these days with as many as a third of the nation's newsrooms expected to shutter by the middle of the decade. But AI doesn't have to necessarily be an existential threat to the field. As six research teams showed at NYU Media Lab's AI & Local News Initiative demo day in late June, the technology may also be the key to foundationally transforming the way local news is gathered and produced. Now in its second year, the initiative is tasked with helping local news organizations to "harness the power of artificial intelligence to drive success." It's backed as part of a larger $3 million grant from the Knight Foundation which is funding four such programs in total in partnership with the Associated Press, Brown Institute's Local News Lab, NYC Media Lab and the Partnership on AI.