Infinite Growth: A Curse or a Blessing?
The article discusses the controversy over infinite growth. It analyzes the two dominant perspectives on economic growth and finds them based on a limited and subjective view of reality. An examination of the principal aspects of economic growth (economic activity, value, and value creation) helps to understand what fuels economic growth. The article also discusses the correlations between production, consumption, as well as resources and population dynamics. The article finds that infinite and exponential economic growth is essential for the survival of our civilization.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
The Blessing and Curse of Dimensionality in Safety Alignment
The focus on safety alignment in large language models (LLMs) has increased significantly due to their widespread adoption across different domains. The scale of LLMs play a contributing role in their success, and the gr…
Blessings and Curses of Covariate Shifts: Adversarial Learning Dynamics, Directional Convergence, and Equilibria
Covariate distribution shifts and adversarial perturbations present robustness challenges to the conventional statistical learning framework: mild shifts in the test covariate distribution can significantly affect the pe…
Experimental DesignregressionHigh--Dimensional Brain in a High-Dimensional World: Blessing of Dimensionality
High-dimensional data and high-dimensional representations of reality are inherent features of modern Artificial Intelligence systems and applications of machine learning. The well-known phenomenon of the "curse of dimen…
BIG-bench Machine LearningVocal Bursts Intensity PredictionA Game of Dice: Machine Learning and the Question Concerning Art
We review some practical and philosophical questions raised by the use of machine learning in creative practice. Beyond the obvious problems regarding plagiarism and authorship, we argue that the novelty in AI Art relies…
BIG-bench Machine LearningBreaking the Curse of Many Agents: Provable Mean Embedding Q-Iteration for Mean-Field Reinforcement Learning
Multi-agent reinforcement learning (MARL) achieves significant empirical successes. However, MARL suffers from the curse of many agents. In this paper, we exploit the symmetry of agents in MARL. In the most generic form,…
Multi-agent Reinforcement Learningreinforcement-learningReinforcement Learning (RL)