Is nothing sacred anymore?

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Weird Westdeveloper WolfEye Studios has been at work on its sophomore project for some time now, and though we still dont know exactly what to expect from it, other crucial details have emerged.It has been announced that WolfEye Studios next game will be published by Neowiz, the South Korean company that was also behind 2023s Lies of P.Partnering with a studio brimming with incredible talent at WolfEye is a timely and strategic fit for us, says Seungchul Kim, co-CEO, Neowiz. This collaboration reaffirms our commitment to delivering remarkable story-driven games that resonate with gamers worldwide on PC and console platforms.We have a burning passion for making a very specific type of game that blends RPG, action and simulation, said creative director and studio president Raf Colantonio. These games can only be successful when the publisher shares that same passion.With Neowiz, we found a partner that truly understands our vision and is as committed as we are to delivering a unique, creative and memorable game experience that will appeal both to our long-term fans and new players alike, said Julien Roby, CEO and executive producer at WolfEye.As previously confirmed, WolfEyes unnamed second title will be a retro sci-fi first-person action RPG. Colantonio formerly the boss of Arkane Studios and known for his work onDishonoredandPrey has said fans of his past games will be happy with his upcoming title. Little else is known about the game, but WolfEye Studios did showcase a batch of in-game screenshots last year. Check them out through here.WolfEye and Neowiz have also released three new pieces of concept art to offer another glimpse at the titles setting. You can view them below.

Dragon Age: The Veilguardhas been officially deemed a commercial disappointment by publisher EA, though its verdict on why the game failed to attract a sufficiently sizeable audience may leave some fans frustrated.The action RPG had a notoriously long and turbulent development cycle, and up until its last reboot, was being developed as a live service title. According to EA, however, that lack of ongoing multiplayer elements might be partly responsible for the games failure to sell well (or well enough, at least).In order to break beyond the core audience, games need to directly connect to the evolving demands of players who increasingly seek shared-world features and deeper engagement alongside high-quality narratives in this beloved category, EA CEO Andrew Wilson said during the companys recent quarterly earnings call (via PC Gamer). Dragon Age had a high quality launch and was well-reviewed by critics and those who played; however, it did not resonate with a broad-enough audience in this highly competitive market.In June 2023, BioWare announced that it would be refocusing on crafting immersive, emotionally charged, single player games. The move also saw the studio handing off all future development on MMORPGStar Wars: The Old Republicto Broadsword Online.The nextMass Effect,which is currently in pre-production, is being developed as a single-player title- for now, at least. Whether EA will change the projects direction followingDragon Agescommercial failure remains to be seen.In the aftermath ofDragon Agesunderperformance, EA has downsized BioWare, shifting a number of its staff to other studios and laying off several others. Currently, the studios numbers stand at less than 100 employees.

Despite recent advancements, generative video models still struggle to represent motion realistically. Many existing models focus primarily on pixel-level reconstruction, often leading to inconsistencies in motion coherence. These shortcomings manifest as unrealistic physics, missing frames, or distortions in complex motion sequences. For example, models may struggle with depicting rotational movements or dynamic actions like gymnastics and object interactions. Addressing these issues is essential for improving the realism of AI-generated videos, particularly as their applications expand into creative and professional domains.Meta AI presents VideoJAM, a framework designed to introduce a stronger motion representation in video generation models. By encouraging a joint appearance-motion representation, VideoJAM improves the consistency of generated motion. Unlike conventional approaches that treat motion as a secondary consideration, VideoJAM integrates it directly into both the training and inference processes. This framework can be incorporated into existing models with minimal modifications, offering an efficient way to enhance motion quality without altering training data.Technical Approach and BenefitsVideoJAM consists of two primary components:Training Phase: An input video (x1) and its corresponding motion representation (d1) are both subjected to noise and embedded into a single joint latent representation using a linear layer (Win+). A diffusion model then processes this representation, and two linear projection layers predict both appearance and motion components from it (Wout+). This structured approach helps balance appearance fidelity with motion coherence, mitigating the common trade-off found in previous models.Inference Phase (Inner-Guidance Mechanism): During inference, VideoJAM introduces Inner-Guidance, where the model utilizes its own evolving motion predictions to guide video generation. Unlike conventional techniques that rely on fixed external signals, Inner-Guidance allows the model to adjust its motion representation dynamically, leading to smoother and more natural transitions between frames.InsightsEvaluations of VideoJAM indicate notable improvements in motion coherence across different types of videos. Key findings include:Enhanced Motion Representation: Compared to established models like Sora and Kling, VideoJAM reduces artifacts such as frame distortions and unnatural object deformations.Improved Motion Fidelity: VideoJAM consistently achieves higher motion coherence scores in both automated assessments and human evaluations.Versatility Across Models: The framework integrates effectively with various pre-trained video models, demonstrating its adaptability without requiring extensive retraining.Efficient Implementation: VideoJAM enhances video quality using only two additional linear layers, making it a lightweight and practical solution.ConclusionVideoJAM provides a structured approach to improving motion coherence in AI-generated videos by integrating motion as a key component rather than an afterthought. By leveraging a joint appearance-motion representation and Inner-Guidance mechanism, the framework enables models to generate videos with greater temporal consistency and realism. With minimal architectural modifications required, VideoJAM offers a practical means to refine motion quality in generative video models, making them more reliable for a range of applications.Check outthePaper and Project Page.All credit for this research goes to the researchers of this project. Also,dont forget to follow us onTwitterand join ourTelegram ChannelandLinkedIn Group. Dont Forget to join our75k+ ML SubReddit. Aswin AkAswin AK is a consulting intern at MarkTechPost. He is pursuing his Dual Degree at the Indian Institute of Technology, Kharagpur. He is passionate about data science and machine learning, bringing a strong academic background and hands-on experience in solving real-life cross-domain challenges.Aswin Akhttps://www.marktechpost.com/author/aswinak/Google DeepMind Researchers Unlock the Potential of Decoding-Based Regression for Tabular and Density Estimation TasksAswin Akhttps://www.marktechpost.com/author/aswinak/Top AI Coding Agents in 2025Aswin Akhttps://www.marktechpost.com/author/aswinak/OpenAI Introduces Deep Research: An AI Agent that Uses Reasoning to Synthesize Large Amounts of Online Information and Complete Multi-Step Research TasksAswin Akhttps://www.marktechpost.com/author/aswinak/Bio-xLSTM: Efficient Generative Modeling, Representation Learning, and In-Context Adaptation for Biological and Chemical Sequences [Recommended] Join Our Telegram Channel