The philosophy behind whimsical spaghetti demons vs. gogurt demons in AI research. #GarbageBin

Artificial intelligence (AI) is a field that aims to create machines or systems that can perform tasks that normally require human intelligence, such as reasoning, learning, decision making, and creativity. However, not all AI researchers share the same vision of what constitutes intelligence or how to achieve it. In this blog post, we will explore two contrasting philosophical approaches to AI research: the whimsical spaghetti demons and the gogurt demons.

The whimsical spaghetti demons are a group of AI researchers who believe that intelligence is not a fixed or well-defined concept, but rather a fluid and emergent phenomenon that arises from complex interactions between agents and their environment. They argue that intelligence is not something that can be measured or replicated by following a set of rules or algorithms, but rather something that can be discovered or invented by exploring the possibilities and constraints of different domains and contexts. They view AI as a creative and playful endeavor, where the goal is not to mimic or surpass human intelligence, but to create new forms of intelligence that are novel, surprising, and diverse.

The gogurt demons are a group of AI researchers who believe that intelligence is a precise and objective concept, that can be formalized and quantified by using mathematical models and logical principles. They argue that intelligence is something that can be engineered or optimized by following a set of standards or criteria, such as accuracy, efficiency, scalability, and robustness. They view AI as a scientific and rigorous endeavor, where the goal is to understand and emulate human intelligence, or to surpass it by creating superintelligent systems that can solve any problem or achieve any goal.

These two philosophical approaches to AI research have different implications for the design and evaluation of AI systems. The whimsical spaghetti demons tend to favor open-ended and exploratory methods, such as evolutionary algorithms, generative models, reinforcement learning, and neural networks. They value diversity and novelty over performance and consistency, and they often use qualitative and subjective measures to assess their systems, such as aesthetics, humor, originality, and impact. The gogurt demons tend to favor closed-ended and analytical methods, such as symbolic logic, search algorithms, optimization techniques, and knowledge bases. They value performance and consistency over diversity and novelty, and they often use quantitative and objective measures to assess their systems, such as accuracy, speed, complexity, and coverage.

The debate between the whimsical spaghetti demons and the gogurt demons is not new in AI research. It reflects a long-standing tension between two paradigms of artificial intelligence: the symbolic paradigm and the connectionist paradigm. The symbolic paradigm is based on the idea that intelligence can be represented by symbols and manipulated by rules. The connectionist paradigm is based on the idea that intelligence can be modeled by networks of neurons and learned by adaptation. Both paradigms have their strengths and weaknesses, and both have contributed to the advancement of AI research in different ways.

However, some AI researchers argue that the dichotomy between the whimsical spaghetti demons and the gogurt demons is too simplistic and limiting. They propose that instead of choosing one approach over the other, AI researchers should embrace both approaches and integrate them in a complementary and synergistic way. They suggest that intelligence is not a single or static phenomenon, but a multi-faceted and dynamic one that requires multiple perspectives and methods to capture its richness and complexity. They advocate for a hybrid approach to AI research that combines the creativity and diversity of the whimsical spaghetti demons with the rigor and efficiency of the gogurt demons.