The iterative advancement of multimodal large models and generative artificial intelligence has transcended the constraints of conventional text‑to‑text translation, propelling the translation sector into a new era of global translation characterized by multimodal input and multimodal output. Moving beyond the conventional research lens of technological tool application, this paper centers on cross‑modal semantic alignment and cultural transcoding efficiency as core entry points. The paper systematically examines the disruptive restructuring of translation practice, communication logic, and industrial ecology brought by multimodal large models and generative artificial intelligence, probes deeply into their innovative value in addressing the last‑mile challenge of cultural communication, and underscores their enabling role in the high‑quality development of the translation field. This study focuses on two innovative application dimensions of multimodal large models and generative artificial intelligence. First, the mechanism of cross‑modal semantic symbiosis underlying multimodal large models is analyzed, detailing how synchronous translation and emotional alignment of multi‑dimensional information—including text, images, audio, video, and speech—are achieved, thereby mitigating information loss inherent in single‑modal translation. Using short‑video translation and virtual digital human translation and broadcasting as illustrative cases, it validates the immersive communication strengths of multimodal large models in cultural going global initiatives. Second, the dynamic adaptation and ethical governance of generative artificial intelligence are explored, departing from the traditional perception of AI‑assisted translation. The study investigates innovative applications of generative artificial intelligence in personalized translation, real‑time cross‑cultural transcoding, and low‑resource language adaptation, while confronting ethical risks arising from technological alienation in translation. A tripartite governance framework of technological empowerment, humanistic calibration, and normative constraint is proposed accordingly. This paper argues that multimodal large models and generative artificial intelligence are not merely auxiliary tools for enhancing translation efficiency, but value reconstructors that drive the transformation of the translation industry and facilitate cross‑cultural communication. Through precise cross‑modal semantic translation, they enable the intact transmission of cultural connotations; via generative innovation, they adapt to the reception habits of diverse overseas audiences; and through technological empowerment, they push the translation sector to upgrade profoundly from language conversion toward cultural interpretation and value transmission. This research offers a fresh perspective for the construction of translation disciplines, innovation in the language service industry, and translation practice for cultural going global, supporting the high‑quality development of translation and the deep advancement of cross‑cultural exchanges and mutual learning in the digital intelligence era.