Authors - Bat-Erdene Batsukh, Ariunbold Tsoodol Abstract - Agentic AI significantly enhance the efficiency and quality of news writing by generating engaging headlines and concise summaries while maintaining the accuracy and objectivity of the original content. These tools leverage advanced algorithms and large language models (LLMs) to streamline the content creation process, ultimately improving audience engagement and journalistic productivity. The approaches range from using neural network algorithms to LLMs and question-answering systems, each with its unique strengths and challenges. Agent, like News writers, operate in a dynamic and fast-paced environment where staying updated with current global events is crucial. The digital era has transformed how journalists gather, verify, and disseminate information. The integration of Natural Language Processing (NLP) into a Flutter-based news app offers an amazing way to deliver personalized news feeds tailored to individual user experiences. By leveraging NLP techniques, the app can analyse user behaviour, understand content, provide relevant news recommendations, neural machine translations and news content summarizations. Developing a centralized AI-powered news app using Flutter presents a unique set of challenges that span technical, ethical, and operational domains. We conducted this research to discover ways to overcome these challenges and spectacles. In particular, we used artificial intelligence to automatically translate news into the reader's native language and to provide a summary view instead of a large amount of text when reading in detail.
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