The signature of the whole. Radical interconnectedness and its implications for global and environmental education

The author presents a holistic concept of Global Learning, concerning different scientific disciplines, spiritual suggestions and practical consequences. He interprets the global environmental crisis especially as a crisis of worldview, stamped by mechanistic belief. (DIPF/Orig.)Der Autor präsentiert ein holistisches Konzept Globalen Lernens in Auseinandersetzung mit verschiedenen Wissenschaftsdisziplinen, spirituellen Anregungen und praktischen Konsequenzen. Die globale Umweltkrise interpretiert er dabei v. a. als eine Krise der Betrachtung von Welt, die von mechanistischem Denken geprägt sei. (DIPF/Orig.

DiffDreamer: Consistent Single-view Perpetual View Generation with Conditional Diffusion Models

Perpetual view generation -- the task of generating long-range novel views by flying into a given image -- has been a novel yet promising task. We introduce DiffDreamer, an unsupervised framework capable of synthesizing novel views depicting a long camera trajectory while training solely on internet-collected images of nature scenes. We demonstrate that image-conditioned diffusion models can effectively perform long-range scene extrapolation while preserving both local and global consistency significantly better than prior GAN-based methods. Project page: https://primecai.github.io/diffdreamer

The Illusion of the Perpetual Money Machine

We argue that the present crisis and stalling economy continuing since 2007 are rooted in the delusionary belief in policies based on a "perpetual money machine" type of thinking. We document strong evidence that, since the early 1980s, consumption has been increasingly funded by smaller savings, booming financial profits, wealth extracted from house price appreciation and explosive debt. This is in stark contrast with the productivity-fueled growth that was seen in the 1950s and 1960s. This transition, starting in the early 1980s, was further supported by a climate of deregulation and a massive growth in financial derivatives designed to spread and diversify the risks globally. The result has been a succession of bubbles and crashes, including the worldwide stock market bubble and great crash of October 1987, the savings and loans crisis of the 1980s, the burst in 1991 of the enormous Japanese real estate and stock market bubbles, the emerging markets bubbles and crashes in 1994 and 1997, the LTCM crisis of 1998, the dotcom bubble bursting in 2000, the recent house price bubbles, the financialization bubble via special investment vehicles, the stock market bubble, the commodity and oil bubbles and the debt bubbles, all developing jointly and feeding on each other. Rather than still hoping that real wealth will come out of money creation, we need fundamentally new ways of thinking. In uncertain times, it is essential, more than ever, to think in scenarios: what can happen in the future, and, what would be the effect on your wealth and capital? How can you protect against adverse scenarios? We thus end by examining the question "what can we do?" from the macro level, discussing the fundamental issue of incentives and of constructing and predicting scenarios as well as developing investment insights.Comment: 27 pages, 18 figures (Notenstein Academy White Paper Series

InfiniteNature-Zero: Learning Perpetual View Generation of Natural Scenes from Single Images

We present a method for learning to generate unbounded flythrough videos of natural scenes starting from a single view, where this capability is learned from a collection of single photographs, without requiring camera poses or even multiple views of each scene. To achieve this, we propose a novel self-supervised view generation training paradigm, where we sample and rendering virtual camera trajectories, including cyclic ones, allowing our model to learn stable view generation from a collection of single views. At test time, despite never seeing a video during training, our approach can take a single image and generate long camera trajectories comprised of hundreds of new views with realistic and diverse content. We compare our approach with recent state-of-the-art supervised view generation methods that require posed multi-view videos and demonstrate superior performance and synthesis quality.Comment: ECCV 2022 (Oral Presentation