In this paper, we provide a comprehensive examination of the evolution of graphics Application Programming Interfaces (APIs). We begin by exploring traditional graphics APIs, elucidating their distinct features and inherent challenges. This sets the stage for a detailed exploration of modern graphics APIs, with a focus on four critical design principles. These principles are further analyzed through specific case studies and categorical examinations. The paper then introduces MoerEngine, a bespoke rendering engine, as a practical case to demonstrate the real-world application of these modern principles in software engineering. In conclusion, the study offers insights into the potential future trajectory of graphics APIs, spotlighting emerging design patterns and technological innovations. It also ventures to predict the development trends and capabilities of next-generation graphics APIs.

The emerging new services in the sixth generation (6G) communication system impose increasingly stringent requirements and challenges on video transmission. Semantic communications are envisioned as a promising solution to these challenges. This paper provides a highly-efficient solution to video transmission by proposing a scalable semantic transmission algorithm, named scalable semantic transmission framework for video (SST-V), which jointly considers the semantic importance and channel conditions. Specifically, a semantic importance evaluation module is designed to extract more informative semantic features according to the estimated importance level, facilitating high-efficiency semantic coding. By further considering the channel condition, a cascaded learning based scalable joint semantic-channel coding algorithm is proposed, which autonomously adapts the semantic coding and channel coding strategies to the specific signal-to-noise ratio (SNR). Simulation results show that SST-V achieves better video reconstruction performance, while significantly reducing the transmission overhead.