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During the 2024 Volcano Engine FORCE Power Conference · Winter, Volcano Engine announced a brand new upgrade of the Doubao Large Model family, showcasing its latest advancements in the field of artificial intelligence. The daily tokens usage of the Doubao Large Model has exceeded 4 trillion, reflecting an increase of over 33 times since its release in May, demonstrating its widespread application and rapid growth in the industry.

The Beijing Academy of Artificial Intelligence (BAAI) recently announced the launch of an innovative 3D generation model, See3D, which can learn from large-scale unlabeled internet videos. This technological breakthrough marks an important step towards the concept of 'See Video, Get 3D'. The See3D model does not rely on traditional camera parameters but utilizes visual conditioning techniques to generate camera-direction controllable and geometrically consistent multi-view images using only visual cues from the video. This approach avoids the need for expensive 3D or camera calibration.

The Tencent Hunyuan 3D generation model is the industry's first open-source large model that supports both text and image-based 3D generation. The initial open-source models include a lightweight version and a standard version, with the lightweight version capable of generating high-quality 3D assets within 10 seconds. This model has been publicly released in the tech community, including complete model weights, inference code, and model algorithms, available for free use by developers, researchers, and other users.

GaussianCube is an explicitly structured 3D representation method that achieves high-precision fitting of 3D assets through a novel density-constrained Gaussian fitting algorithm, while ensuring a fixed number of free Gaussians is used during the fitting process.

Researchers have developed the 3D-GPT system, powered by large language models (LLM), which can generate complex 3D models and scenes based on brief text descriptions. The system breaks down 3D modeling tasks into manageable components through a multi-agent system, including task scheduling agents, conceptualization agents, and modeling agents. The key role of the task scheduling agent is to select the appropriate program generation functions based on user instructions, improving the efficiency of task coordination. 3D-GPT supports continuous instruction input, allowing users to edit and modify generated scenes, including object control.