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The Seed team of ByteDance announced the release of the experimental diffusion language model Seed Diffusion Preview, marking a major technological breakthrough in the field of language models. The model aims to validate the feasibility of the discrete diffusion technology route as a foundational framework for next-generation language models through structured code generation experiments. Seed Diffusion Preview has achieved significant improvements in inference speed, reaching 2146 tokens per second, which is 5 times faster than equivalent-scale autoregressive models.

MirageLSD, the world's first AI real-time video conversion model with 40ms latency, enables instant scene/outfit changes via gestures. Applied in gaming/livestreaming, its LSD model uses Diffusion Forcing to eliminate long-generation errors.....

The AI-driven video editing tool Diffusion Studio Pro has officially launched, drawing significant attention from the industry. This innovative product, which claims to combine 'CapCut + Cursor', offers a non-linear editing experience based on a browser with a local-first approach. It integrates over 16 generative AI models, providing strong support for professional video creators and developers. Key highlights: Multi-modal AI Empowers Non-linear Editing Diffusion Studio Pro is a tool completely based on

Recently, tech giant NVIDIA, in collaboration with the Massachusetts Institute of Technology (MIT) and the University of Hong Kong, released a new framework called Fast-dLLM. This innovative framework aims to significantly increase the inference speed of diffusion models (Diffusion-based LLMs), up to 27.6 times, providing stronger technical support for AI applications. The challenges and opportunities of diffusion models make them strong competitors to traditional autoregressive models.

Black Forest Labs (BFL), founded by the creator of the renowned Stable Diffusion model, recently launched its next-generation image generation model FLUX.1Kontext. This model not only generates and edits photos but also allows users to modify images multiple times via text and reference images, bringing new possibilities to enterprise AI applications. Multiple versions and platform support are available from BFL for FLUX.1Kontext.

3DV-TON (Textured 3D-Guided Consistent Video Try-on via Diffusion Models) is an innovative technology that delivers a realistic video try-on experience with texture 3D guidance using diffusion models. According to AIbase, 3DV-TON leverages advanced 3D geometry and texture modeling combined with video diffusion models to ensure consistency and realism of clothing in dynamic videos, offering significant potential for e-commerce, fashion, and virtual reality applications.

The Ostris team has released Flex.2-preview, an 800 million parameter text-to-image diffusion model designed for integration into ComfyUI workflows. According to AIbase, this model excels at generating images with strong control over lines, poses, and depth. It supports general control and inpainting functionality, continuing the fine-tuning evolutionary path from Flux.1Schnell to OpenFlux.1 and Flex.1-alpha. Flex.2-preview is available on Hu...

Scientists at Alibaba Group have introduced VACE, a universal AI model designed to unify a wide range of video generation and editing tasks. At the heart of VACE is an enhanced Diffusion Transformer architecture, innovating with a novel input format called "Video Conditional Unit" (VCU). VCU distills diverse modalities such as text prompts, reference images or video sequences, and spatial masks into a unified representation, and through a specialized mechanism coordinates different inputs to avoid conflicts. Concept decoupling enables fine-grained control.

Kunlun Wanwei's SkyReels team has officially released and open-sourced SkyReels-V2, the world's first infinite-length movie generation model using a diffusion-forcing framework. This model achieves synergistic optimization by combining a multimodal large language model (MLLM), multi-stage pre-training, reinforcement learning, and a diffusion-forcing framework, marking a new stage in video generation technology.

AMD's advancements in AI are noteworthy, particularly its latest optimizations for the Stable Diffusion model. Recently, Stability AI released an ONNX-optimized version of Stable Diffusion, resulting in significantly improved performance for AMD Radeon GPUs and Ryzen integrated graphics in AI tasks, with speed increases up to 3.8 times faster. This progress narrows the gap with NVIDIA's ecosystem...

Recent advancements in generative AI have fueled innovation in video generation. A new video diffusion technology called FramePack has garnered significant attention. According to information compiled by AIbase from recent posts on X, FramePack's remarkably low VRAM requirements and efficient generation capabilities promise to usher in a new era of video generation accessible to mainstream GPUs. Technical Breakthrough: Only 6GB VRAM needed, effortlessly generating thousands of frames. FramePack's most significant advantage is its extremely low...