Latest news with #Matrix-Game2.0
Malaysian Reserve
9 hours ago
- Entertainment
- Malaysian Reserve
Matrix-Game 2.0 Launches as a Powerful Open-Source Alternative to Genie 3
SINGAPORE, Aug. 12, 2025 /PRNewswire/ — The SkyWork AI Technology Release Week officially kicked off on August 11. From August 11 to August 15, a new model will be unveiled each day, covering cutting-edge models for core multimodal AI scenarios. A week ago, DeepMind released a major update to its interactive world model—Genie 3—enabling real-time, long-sequence generation. This advancement has drawn significant attention to world models. However, Genie 3 was not open-sourced, leaving the community to speculate about its implementation. On August 12, Skywork unveiled an upgraded version of the self-developed Matrix series' interactive world model—Matrix-Game 2.0. It also delivers interactive, real-time, long-sequence generation in general scenarios. To drive progress in interactive world modeling, Matrix-Game 2.0 has been fully open-sourced, marking the industry's first open-source solution for real-time, long-sequence, interactive generation in general scenarios. Matrix-Game 2.0 open source addresses: Technical report: Project homepage: HuggingFace: GitHub: Matrix-Game 2.0 achieves a breakthrough in real-time generation and long-sequence handling. Compared to its predecessor, the 2.0 version prioritizes low-latency, high-frame-rate performance for extended interactions, enabling stable 25 FPS continuous video generation across complex scenes. Its generation length scales to minute-long sequences, drastically improving temporal coherence and real-world usability. While delivering a significant boost in inference speed, Matrix-Game 2.0 maintains precise comprehension of physical laws and scene semantics. It enables users to freely explore, manipulate, and construct virtual environments in real time through simple instructions—yielding well-structured, detail-rich, and logically coherent virtual spaces. With these capabilities, Matrix-Game 2.0 not only breaks down the barriers between content generation and interaction but also unlocks new possibilities for cutting-edge applications such as virtual humans, game engines, and embodied AI. It provides a robust technical foundation for building a universal virtual world. Currently, Matrix-Game 2.0 boasts three core advantages: High-frame-rate, real-time long-sequence generation: The model supports fluid movement (forward/backward, left/right) and camera/view rotation. Users can intuitively control characters in the scene via simple commands. The system generates seamless footage in real time at 25 FPS, enabling minute-long interactive sequences in a single session. Character movements are lifelike, smooth, and precisely responsive. Cross-scenario generalization capability: The model demonstrates exceptional cross-domain adaptability. It is not only suitable for specific task scenarios but also supports simulations of diverse styles and environments—including urban, wilderness, and other spatial types, as well as realistic, oil-painting, and various visual styles. Enhanced physical consistency: The model demonstrates a deeper understanding of physical rules. Characters generated by the model exhibit physically plausible movements when navigating complex terrains such as steps and obstacles, which improves immersion and controllability. The open-source release of Matrix-Game for interactive video generation underscores Skywork's strategic foresight in AI development. This initiative will accelerate development across Skywork's multi-model AI ecosystem. Moving forward, Skywork remains committed to pioneering and open-sourcing advanced AI solutions. By collaborating with global developers and users, we aim to build next-generation platforms that accelerate the global advancement of AGI.
Business Upturn
a day ago
- Business Upturn
Matrix-Game 2.0 Released: The First Open-Source Interactive World Model for Real-Time Long-Sequence Generation
Singapore, Aug. 11, 2025 (GLOBE NEWSWIRE) — On August 12, Skywork AI announced the release of Matrix-Game 2.0, the upgraded version of its Matrix series interactive world model. This breakthrough model delivers real-time, long-sequence interactive video generation across general-purpose scenarios, and the model is fully open-sourced, making it the first of its kind in the industry. Matrix-Game 2.0 represents a major leap in both real-time performance and long-sequence generation capabilities. With a focus on low latency and high frame rates, the model can stably generate continuous video at 25 FPS across complex environments, with durations extending to minutes. The result is significantly enhanced coherence, usability, and immersion. In addition to faster inference, Matrix-Game 2.0 maintains precise understanding of physics and scene semantics. Users can issue simple commands to freely explore, manipulate, and construct virtual environments that are structurally consistent, visually rich, and logically sound in real time. This breakthrough removes the barrier between content generation and interactive engagement, opening new possibilities for applications in virtual humans, gaming engines, embodied AI, and more. Model Architecture Matrix-Game 2.0 introduces a new vision-driven approach to interactive world modeling—moving away from language-prompt dependency and focusing on spatial understanding and physics-based learning. 3D Causal VAE Compression: Efficiently compresses spatial and temporal dimensions for better modeling and generation. Efficiently compresses spatial and temporal dimensions for better modeling and generation. Multimodal Diffusion Transformer (DiT): Combines vision encoding with user action commands to generate frame-by-frame realistic dynamic sequences. Combines vision encoding with user action commands to generate frame-by-frame realistic dynamic sequences. User Interaction Module: Adapts GameFactory and Genie-style frameworks to enable real-time control. Real-Time Autoregressive Video Generation Using a Self-Forcing training strategy, Matrix-Game 2.0 employs a novel autoregressive diffusion generation mechanism to overcome latency and error accumulation in conventional models: Causal Diffusion Model Distillation: Minimizes sequence delay by conditioning on past frames. Minimizes sequence delay by conditioning on past frames. Distribution Matching Distillation (DMD): Aligns training and inference distributions for more stable results. Aligns training and inference distributions for more stable results. KV Cache Mechanism: Enables seamless long video generation without redundant computation, supporting unlimited output length at 25 FPS on a single GPU. Applications & Performance Matrix-Game 2.0 supports dynamic, physics-consistent interactions—such as character movement and camera rotation—through keyboard and mouse input. It is applicable to diverse scenes, including GTA-style environments, Minecraft, and open-world exploration, with enhanced cross-domain adaptability and physical realism. Three Core Breakthroughs: High-FPS Real-Time Long-Sequence Generation: Minute-long, natural, and responsive interactions at 25 FPS. Multi-Scene Generalization: Adaptable to various styles and environments, from urban landscapes to artistical renderings. Enhanced Physical Consistency: Realistic movement over complex terrains, boosting immersion and controllability. Matrix-Game 2.0 sets a new milestone for spatial intelligence research and application, paving the way for embodied AI training, rapid virtual world construction, and content creation for films and the metaverse. Open-Source Links: is a consumer-facing AI workspace and creative platform that helps everyday users produce slides, spreadsheets, videos, documents, and interactive content in minutes – built around intuitive conversational workflows. The platform offers guided prompts, real-time previews, and integrations with common office tools to speed up workflows for students, freelancers, and small teams. Available on web and mobile, emphasizes ease of use, affordability, and rapid iteration—bringing advanced AI creativity tools directly to consumers. Disclaimer: The above press release comes to you under an arrangement with GlobeNewswire. Business Upturn takes no editorial responsibility for the same. Ahmedabad Plane Crash
