In the digital advertising ecosystem, how to efficiently and accurately identify and manage prohibited content has always been a core issue in industry governance. On July 3rd, ByteDance Engine officially released the self-developed advertising management large model Mamoda 2.5 version, marking a new step forward in its technological iteration in the field of content security risk control.

Looking back at the development of this model, Mamoda started from version 1.0, initially only possessing the ability to identify text content, mainly responsible for filtering basic prohibited text. As large model technology continued to evolve, its capabilities quickly expanded into diverse scenarios. In the 2.5 version, the model has completely broken through previous limitations in handling complex multimedia content, achieving comprehensive coverage of various material types such as images and short videos, especially deep analysis of the full form of videos, making precise management possible.

This technological advancement holds significant importance for improving the clarity of the advertising environment. By deeply understanding video content, Mamoda 2.5 can more sensitively detect potential compliance risks in videos, thus finding a new balance between ensuring user experience and improving platform governance efficiency.

Against the backdrop of increasingly mature AI governance capabilities, this 2.5 version release not only showcases ByteDance Engine's technical reserves in content risk control but also reflects a positive response from the industry to the demand for managing complex multimedia content. With the deployment of this capability, the advertising management system will become more efficient and refined, continuously providing a technical foundation for building a healthy digital advertising ecosystem.