Digital architecture and difference: a theory of ethical transpositions towards nomadic embodiments in digital architecture

This thesis contributes to histories and theories of digital architecture of the past two decades, as it questions the narratives of its novelty. The main argument this thesis puts forward is that a plethora of methodologies, displacing the centrality of the architect from the architectural design process, has folded into the discipline in the process of its rewriting along digital protocols. These steer architecture onto a post-human path. However, while the redefinition of the practice unfolds, it does so epistemically only without redefining the new subject of architecture emerging from these processes, which therefore remains anchored to humanist-modern definitions. This unaccounted-for position, I argue, prevents novelty from emerging. Simultaneously, the thesis unfolds a creative approach – while drawing on nomadic, critical theory concepts, there surfaces an alternative genealogy already underpinning digital methodologies that enable a reconceptualization of novelty framed with difference to be articulated through nomadic digital embodiment. Regarding the first claim, I turn to the narratives as well as to the mechanisms of digital discourse emerging in two modes of production – mathematical and biological – in exploration of the ways perceptions of novelty are articulated: a) through close readings of its narratives as they consolidate into digital architectural theory (Carpo 2011; Lynn 2003, 2012; Terzidis 2006; Migayrou 2004, 2009); b) through an analysis of the two digital methodologies that support these narratives – parametric architecture and biodigital architecture. In parallel, this thesis draws on twentieth-century critical theory and twenty-firstcentury nomadic feminist theory to rethink two thematic topics: difference and subjectivity. Specifically, these are Gilles Deleuze’s non-essentialist, nonrepresentational philosophy of difference (1968, 1980, 1988) and Rosi Braidotti’s nomadic feminist reconceptualization of post-human, nonunitary subjectivity (2006, 2011, 2015). Nomadic feminist theory also informs my methodology. I draw on Rosi Braidotti’s cartographing and transposing (2006, 2011) because they engender a non-dualist approach to research itself that is dynamic and affirmative, insisting on grounding techniques – grounding in subject positions that are nevertheless post-human and nonunitary. This leads to a redefinition of novel digital practices with ethical ones

Detecting Deepfakes Without Seeing Any

Deepfake attacks, malicious manipulation of media containing people, are a serious concern for society. Conventional deepfake detection methods train supervised classifiers to distinguish real media from previously encountered deepfakes. Such techniques can only detect deepfakes similar to those previously seen, but not zero-day (previously unseen) attack types. As current deepfake generation techniques are changing at a breathtaking pace, new attack types are proposed frequently, making this a major issue. Our main observations are that: i) in many effective deepfake attacks, the fake media must be accompanied by false facts i.e. claims about the identity, speech, motion, or appearance of the person. For instance, when impersonating Obama, the attacker explicitly or implicitly claims that the fake media show Obama; ii) current generative techniques cannot perfectly synthesize the false facts claimed by the attacker. We therefore introduce the concept of "fact checking", adapted from fake news detection, for detecting zero-day deepfake attacks. Fact checking verifies that the claimed facts (e.g. identity is Obama), agree with the observed media (e.g. is the face really Obama's?), and thus can differentiate between real and fake media. Consequently, we introduce FACTOR, a practical recipe for deepfake fact checking and demonstrate its power in critical attack settings: face swapping and audio-visual synthesis. Although it is training-free, relies exclusively on off-the-shelf features, is very easy to implement, and does not see any deepfakes, it achieves better than state-of-the-art accuracy.Comment: Our code is available at https://github.com/talreiss/FACTO

What makes you think that you are a health expert? : the effect of objective knowledge and cognitive structuring on self-epistemic authority

Self-epistemic authority (SEA) refers to the subjective judgement of the level of expertise and knowledge a person has in a given domain. While it is reasonable to assume that people's perception of SEA reflects their level of objective knowledge in the given domain, there is evidence to show that people are not optimal judges of their own knowledge. Thus, the present study examined the interaction between the participants’ trait-like characteristics of need for cognitive closure (NFC) and efficacy to fulfill the need for cognitive closure (EFNC), which affects the use of cognitive structuring, as a source of SEA. Results of the study confirm that objective knowledge as well as a cognitive-motivational epistemic process (interaction between NFC and EFNC) affect SEA. For high EFNC individuals, the effect of NFC on SEA was positive. However, for low EFNC individuals, the relationship was negative

What makes you think that you are a health expert? : the effect of objective knowledge and cognitive structuring on self-epistemic authority

Self-epistemic authority (SEA) refers to the subjective judgement of the level of expertise and knowledge a person has in a given domain. While it is reasonable to assume that people's perception of SEA reflects their level of objective knowledge in the given domain, there is evidence to show that people are not optimal judges of their own knowledge. Thus, the present study examined the interaction between the participants’ trait-like characteristics of need for cognitive closure (NFC) and efficacy to fulfill the need for cognitive closure (EFNC), which affects the use of cognitive structuring, as a source of SEA. Results of the study confirm that objective knowledge as well as a cognitive-motivational epistemic process (interaction between NFC and EFNC) affect SEA. For high EFNC individuals, the effect of NFC on SEA was positive. However, for low EFNC individuals, the relationship was negative

Need for closure and cognitive structuring among younger and older adults

The paper reported two correlational studies. The aim of the Study 1 was to examine the hypothesis that age moderates the relationship between need for closure (NFC) and cognitive structuring. Results of the study revealed that aging with increased need for closure was associated with better recognition of irrelevant information than schema-relevant items, in testing hypotheses about the target person. These findings are interpreted as demonstrating the age-associated failure of cognitive abilities (i.e., low efficacy at fulfilling the need for closure), reducing tendency to behave according to the level of epistemic motivation. The results of Study 2 demonstrated that older participants are characterized by higher NFC but by lower EFNC than young participants. These results are consistent with the conclusion that the negative relationships between NFC and cognitive structuring demonstrated by the older participants in Study 1 can be attributed to their lower level of EFNC

TokenFlow: Consistent Diffusion Features for Consistent Video Editing

The generative AI revolution has recently expanded to videos. Nevertheless, current state-of-the-art video models are still lagging behind image models in terms of visual quality and user control over the generated content. In this work, we present a framework that harnesses the power of a text-to-image diffusion model for the task of text-driven video editing. Specifically, given a source video and a target text-prompt, our method generates a high-quality video that adheres to the target text, while preserving the spatial layout and motion of the input video. Our method is based on a key observation that consistency in the edited video can be obtained by enforcing consistency in the diffusion feature space. We achieve this by explicitly propagating diffusion features based on inter-frame correspondences, readily available in the model. Thus, our framework does not require any training or fine-tuning, and can work in conjunction with any off-the-shelf text-to-image editing method. We demonstrate state-of-the-art editing results on a variety of real-world videos. Webpage: https://diffusion-tokenflow.github.io

MultiDiffusion: Fusing Diffusion Paths for Controlled Image Generation

Recent advances in text-to-image generation with diffusion models present transformative capabilities in image quality. However, user controllability of the generated image, and fast adaptation to new tasks still remains an open challenge, currently mostly addressed by costly and long re-training and fine-tuning or ad-hoc adaptations to specific image generation tasks. In this work, we present MultiDiffusion, a unified framework that enables versatile and controllable image generation, using a pre-trained text-to-image diffusion model, without any further training or finetuning. At the center of our approach is a new generation process, based on an optimization task that binds together multiple diffusion generation processes with a shared set of parameters or constraints. We show that MultiDiffusion can be readily applied to generate high quality and diverse images that adhere to user-provided controls, such as desired aspect ratio (e.g., panorama), and spatial guiding signals, ranging from tight segmentation masks to bounding boxes. Project webpage: https://multidiffusion.github.i

Compatible director fields in R3\mathbb{R}^3

The geometry and interactions between the constituents of a liquid crystal, which are responsible for inducing the partial order in the fluid, may locally favor an attempted phase that could not be realized in $\mathbb{R}^3$. While states that are incompatible with the geometry of $\mathbb{R}^3$ were identified more than 50 years ago, the collection of compatible states remained poorly understood and not well characterized. Recently, the compatibility conditions for three-dimensional director fields were derived using the method of moving frames. These compatibility conditions take the form of six differential relations in five scalar fields locally characterizing the director field. In this work, we rederive these equations using a more transparent approach employing vector calculus. We then use these equations to characterize a wide collection of compatible phases.Comment: 37 pages (32 in the published version), 5 figures. Keywords: Geometric frustration, Incompatibility, Liquid crystal, Frobenius. Note: This version is essentially the same as the published one. In addition, it is part of a Collection: Soft Matter Elasticity (https://link.springer.com/collections/ijhficbgii

Charting the Topography of the Neural Network Landscape with Thermal-Like Noise

The training of neural networks is a complex, high-dimensional, non-convex and noisy optimization problem whose theoretical understanding is interesting both from an applicative perspective and for fundamental reasons. A core challenge is to understand the geometry and topography of the landscape that guides the optimization. In this work, we employ standard Statistical Mechanics methods, namely, phase-space exploration using Langevin dynamics, to study this landscape for an over-parameterized fully connected network performing a classification task on random data. Analyzing the fluctuation statistics, in analogy to thermal dynamics at a constant temperature, we infer a clear geometric description of the low-loss region. We find that it is a low-dimensional manifold whose dimension can be readily obtained from the fluctuations. Furthermore, this dimension is controlled by the number of data points that reside near the classification decision boundary. Importantly, we find that a quadratic approximation of the loss near the minimum is fundamentally inadequate due to the exponential nature of the decision boundary and the flatness of the low-loss region. This causes the dynamics to sample regions with higher curvature at higher temperatures, while producing quadratic-like statistics at any given temperature. We explain this behavior by a simplified loss model which is analytically tractable and reproduces the observed fluctuation statistics.Comment: 7 pages, 4 figure