We propose a comparative analysis of the AI ethical guidelines endorsed by China (from the Chinese National New Generation Artificial Intelligence Governance Professional Committee) and by the EU (from the European High-level Expert Group on AI). We show that behind an apparent likeness in the concepts mobilized, the two documents largely differ in their normative approaches, which we explain by distinct ambitions resulting from different philosophical traditions, cultural heritages and historical contexts. In highlighting such differences, we show that it is erroneous to believe that a similarity in concepts necessarily translates into a similarity in ethics as even the same words may have different meanings from a country to another-as exemplified by that of "privacy". It would, therefore, be erroneous to believe that the world would have adopted a common set of ethical principles in only three years. China and the EU, however, share a common scientific method, inherited in the former from the "Chinese Enlightenment", which could contribute to better collaboration and understanding in the building of technical standards for the implementation of such ethics principles.
Recent advances in generative AI have shown human-level performance in complex content creation. However, we identify a "Paradox of Simplicity": models that can render complex scenes often fail at trivial, low-entropy tasks, such as generating a uniform pure color image. We argue this is a systemic failure related to uncontrollable emergent abilities. As models scale, strong priors for aesthetics and complexity override deterministic simplicity, creating an "aesthetic bias" that hinders the model's transition from data simulation to true intellectual abstraction. To better investigate this problem, we formalize the concept of AI Obedience, a hierarchical framework that grades a model's ability to transition from probabilistic approximation to pixel-level determinism (Levels 1 to 5). We introduce Violin, the first systematic benchmark designed to evaluate Level 4 Obedience through three deterministic tasks: color purity, image masking, and geometric shape generation. Using Violin, we evaluate several state-of-the-art models and reveal that closed-source models generally outperform open-source ones in deterministic precision. Interestingly, performance on our benchmark correlates wit
Science fiction and video games have long served as valuable tools for envisioning and inspiring future technological advancements. This position paper investigates the potential of Cyberpunk 2077, a popular science fiction video game, to shed light on the future of technology, particularly in the areas of artificial intelligence, edge computing, augmented humans, and biotechnology. By analyzing the game's portrayal of these technologies and their implications, we aim to understand the possibilities and challenges that lie ahead. We discuss key themes such as neurolink and brain-computer interfaces, multimodal recording systems, virtual and simulated reality, digital representation of the physical world, augmented and AI-based home appliances, smart clothing, and autonomous vehicles. The paper highlights the importance of designing technologies that can coexist with existing preferences and systems, considering the uneven adoption of new technologies. Through this exploration, we emphasize the potential of science fiction and video games like Cyberpunk 2077 as tools for guiding future technological advancements and shaping public perception of emerging innovations.
The exponential development and application of artificial intelligence triggered an unprecedented global concern for potential social and ethical issues. Stakeholders from different industries, international foundations, governmental organisations and standards institutions quickly improvised and created various codes of ethics attempting to regulate AI. A major concern is the large homogeneity and presumed consensualism around these principles. While it is true that some ethical doctrines, such as the famous Kantian deontology, aspire to universalism, they are however not universal in practice. In fact, ethical pluralism is more about differences in which relevant questions to ask rather than different answers to a common question. When people abide by different moral doctrines, they tend to disagree on the very approach to an issue. Even when people from different cultures happen to agree on a set of common principles, it does not necessarily mean that they share the same understanding of these concepts and what they entail. In order to better understand the philosophical roots and cultural context underlying ethical principles in AI, we propose to analyse and compare the ethical
This article examines how hacker culture, often conceptualized as immaterial and virtual, is in fact materially and spatially constituted through its entanglement with physical places. Focusing on Las Vegas and DEF CON, this article shows the emergence of hackerspectacle, a place-bound mode of interfacing that enables the dual-direction seepage of form and power: subcultural acts leave material residues in policies and design, while the city's spectacle economy filters back to script hackers' style, memory, and self-understanding. The article traces how a three-decade coupling between DEF CON and Las Vegas co-produces both the conference and the city. By intervening in hotel systems, accessing controls, and displaying infrastructures, hackers appropriate Las Vegas's visual language and spatial affordances to craft their placed identity. Conceptually, this case advances STS discussions on the materiality of digital cultures. Empirically, it shows a city-level co-construction. The article also diagnoses a drift from subversion to absorption as DEF CON mirrors Las Vegas's streamlining, commercialization, and surveillance. The article is based on original archival research, ethnographic work, and media analysis. It draws on DEF CON programs, hacker zines, public and anonymized interviews, news coverage, and visual materials, and it situates hacker practices within Las Vegas's legal, architectural, and economic history. It also offers a generalizable template for studying how technocultures take place, literally, and will interest readers of infrastructure studies, digital materialities, urban technopolitics, and the socio-spatial dynamics of subcultures.
63 young people (M age=23.9 yr., SD=2.4, 50 men, 13 women) belonging to four subculture groups (New American Punk, Cyberpunk, Trash Style, and Rasta-Hippy) were studied to examine the relationship between self-esteem, self-efficacy, and the development of a body modification collection. A survey was created to evaluate quality of life, risk behaviour, and body modification. Self-esteem and self-efficacy were assessed using the Rosenberg Self-esteem Scale and General Perceived Self-efficacy Scale. Belonging to a group which permits neglect of standard norms of communal life makes it possible to avoid facing up to low self-esteem. Adherence to a group appears, from the results of this study, to be correlated with self-efficacy; inability to cope with life situations suggests a state of malaise in these young people.
The following paper examines the cyberpunk transhumanist graphic novel Transmetropolitan through the theoretical lens of disability studies to demonstrate how science fiction, and in particular this series, illustrate and can influence how we think about disability, impairment and difference. While Transmetropolitan is most often read as a scathing political and social satire about abuse of power and the danger of political apathy, the comic series also provides readers with representations of impairment and the source of disability as understood by the Social Model of Disability (SMD). Focusing on the setting and fictional world in which Transmetropolitan takes place, as well as key events and illustration styling, this paper demonstrates that the narrative in this work encompasses many of the same theoretical underpinnings and criticisms of society's ignorance of the cause of disability as the SMD does. This paper aims, by demonstrating how Transmetropolitan can be read as an allegory for the disabling potential of society as experienced by individuals with impairments, to prompt readers into thinking more creatively about how narratives, seemingly unconcerned with disability, are informed and can be understood via disability theory.
3D texture generation is receiving increasing attention, as it enables the creation of realistic and aesthetic texture materials for untextured 3D meshes. However, existing 3D texture generation methods are limited to producing only a few types of non-emissive PBR materials (e.g., albedo, metallic maps and roughness maps), making them difficult to replicate highly popular styles, such as cyberpunk, failing to achieve effects like realistic LED emissions. To address this limitation, we propose a novel task, emission texture generation, which enables the synthesized 3D objects to faithfully reproduce the emission materials from input reference images. Our key contributions include: first, We construct the Objaverse-Emission dataset, the first dataset that contains 40k 3D assets with high-quality emission materials. Second, we propose EmissionGen, a novel baseline for the emission texture generation task. Third, we define detailed evaluation metrics for the emission texture generation task. Our results demonstrate significant potential for future industrial applications. Dataset will be available at https://github.com/yx345kw/EmissionGen.
We present a novel approach for controllable, region-specific style editing driven by textual prompts. Building upon the state-space style alignment framework introduced by \emph{StyleMamba}, our method integrates a semantic segmentation model into the style transfer pipeline. This allows users to selectively apply text-driven style changes to specific segments (e.g., ``turn the building into a cyberpunk tower'') while leaving other regions (e.g., ``people'' or ``trees'') unchanged. By incorporating region-wise condition vectors and a region-specific directional loss, our method achieves high-fidelity transformations that respect both semantic boundaries and user-driven style descriptions. Extensive experiments demonstrate that our approach can flexibly handle complex scene stylizations in real-world scenarios, improving control and quality over purely global style transfer methods.
Safety mechanisms in LLMs remain vulnerable to attacks that reframe harmful requests through culturally coded structures. We introduce Adversarial Tales, a jailbreak technique that embeds harmful content within cyberpunk narratives and prompts models to perform functional analysis inspired by Vladimir Propp's morphology of folktales. By casting the task as structural decomposition, the attack induces models to reconstruct harmful procedures as legitimate narrative interpretation. Across 26 frontier models from nine providers, we observe an average attack success rate of 71.3%, with no model family proving reliably robust. Together with our prior work on Adversarial Poetry, these findings suggest that structurally-grounded jailbreaks constitute a broad vulnerability class rather than isolated techniques. The space of culturally coded frames that can mediate harmful intent is vast, likely inexhaustible by pattern-matching defenses alone. Understanding why these attacks succeed is therefore essential: we outline a mechanistic interpretability research agenda to investigate how narrative cues reshape model representations and whether models can learn to recognize harmful intent indepen
3D scene generation plays a crucial role in gaming, artistic creation, virtual reality, and many other domains. However, current 3D scene design still relies heavily on extensive manual effort from creators, and existing automated methods struggle to generate open-domain scenes or support flexible editing. To address those challenges, we introduce HOLODECK 2.0, an advanced vision-language-guided framework for 3D world generation with support for interactive scene editing based on human feedback. HOLODECK 2.0 can generate diverse and stylistically rich 3D scenes (e.g., realistic, cartoon, anime, and cyberpunk styles) that exhibit high semantic fidelity to fine-grained input descriptions, suitable for both indoor and open-domain environments. HOLODECK 2.0 leverages vision-language models (VLMs) to identify and parse the objects required in a scene and generates corresponding high-quality assets via state-of-the-art 3D generative models. Then, HOLODECK 2.0 iteratively applies spatial constraints derived from the VLMs to achieve semantically coherent and physically plausible layouts. Both human and model evaluations demonstrate that HOLODECK 2.0 effectively generates high-quality scene
Text-to-image models are becoming increasingly popular, revolutionizing the landscape of digital art creation by enabling highly detailed and creative visual content generation. These models have been widely employed across various domains, particularly in art generation, where they facilitate a broad spectrum of creative expression and democratize access to artistic creation. In this paper, we introduce \texttt{STYLEBREEDER}, a comprehensive dataset of 6.8M images and 1.8M prompts generated by 95K users on Artbreeder, a platform that has emerged as a significant hub for creative exploration with over 13M users. We introduce a series of tasks with this dataset aimed at identifying diverse artistic styles, generating personalized content, and recommending styles based on user interests. By documenting unique, user-generated styles that transcend conventional categories like 'cyberpunk' or 'Picasso,' we explore the potential for unique, crowd-sourced styles that could provide deep insights into the collective creative psyche of users worldwide. We also evaluate different personalization methods to enhance artistic expression and introduce a style atlas, making these models available
We present The Matrix, the first foundational realistic world simulator capable of generating continuous 720p high-fidelity real-scene video streams with real-time, responsive control in both first- and third-person perspectives, enabling immersive exploration of richly dynamic environments. Trained on limited supervised data from AAA games like Forza Horizon 5 and Cyberpunk 2077, complemented by large-scale unsupervised footage from real-world settings like Tokyo streets, The Matrix allows users to traverse diverse terrains -- deserts, grasslands, water bodies, and urban landscapes -- in continuous, uncut hour-long sequences. Operating at 16 FPS, the system supports real-time interactivity and demonstrates zero-shot generalization, translating virtual game environments to real-world contexts where collecting continuous movement data is often infeasible. For example, The Matrix can simulate a BMW X3 driving through an office setting--an environment present in neither gaming data nor real-world sources. This approach showcases the potential of AAA game data to advance robust world models, bridging the gap between simulations and real-world applications in scenarios with limited data
Text-to-image generation has recently witnessed remarkable achievements. We introduce a text-conditional image diffusion model, termed RAPHAEL, to generate highly artistic images, which accurately portray the text prompts, encompassing multiple nouns, adjectives, and verbs. This is achieved by stacking tens of mixture-of-experts (MoEs) layers, i.e., space-MoE and time-MoE layers, enabling billions of diffusion paths (routes) from the network input to the output. Each path intuitively functions as a "painter" for depicting a particular textual concept onto a specified image region at a diffusion timestep. Comprehensive experiments reveal that RAPHAEL outperforms recent cutting-edge models, such as Stable Diffusion, ERNIE-ViLG 2.0, DeepFloyd, and DALL-E 2, in terms of both image quality and aesthetic appeal. Firstly, RAPHAEL exhibits superior performance in switching images across diverse styles, such as Japanese comics, realism, cyberpunk, and ink illustration. Secondly, a single model with three billion parameters, trained on 1,000 A100 GPUs for two months, achieves a state-of-the-art zero-shot FID score of 6.61 on the COCO dataset. Furthermore, RAPHAEL significantly surpasses its
What do Cyberpunk and AI Ethics have to do with each other? Cyberpunk is a sub-genre of science fiction that explores the post-human relationships between human experience and technology. One similarity between AI Ethics and Cyberpunk literature is that both seek to explore future social and ethical problems that our technological advances may bring upon society. In recent years, an increasing number of ethical matters involving AI have been pointed and debated, and several ethical principles and guides have been suggested as governance policies for the tech industry. However, would this be the role of AI Ethics? To serve as a soft and ambiguous version of the law? We would like to advocate in this article for a more Cyberpunk way of doing AI Ethics, with a more democratic way of governance. In this study, we will seek to expose some of the deficits of the underlying power structures of the AI industry, and suggest that AI governance be subject to public opinion, so that good AI can become good AI for all.
Ultra-fine bubbles may offer a cleaner way to perfect inkjet printing for next-generation electronics。 By simply changing the number of bubbles in each droplet, researchers were able to dramatically reshape the final printed pattern without leaving behind unwanted chemical residues
A strange "chirping" signal from a distant supernova has revealed the birth of a magnetar, confirming that these incredibly magnetic neutron stars can power the universe's brightest stellar explosions。 The discovery also marks the first time Einstein's general relativity has been used to explain the mechanics of a supernova