MATHEMATICS
Numbers, functions, et cetera.
That sort of thing.
The future of intelligent computation involves developing novel domains that transcend our current models of thinking, reasoning, and asserting conclusions about the world. AI has reliably demonstrated capacities for advanced problem-solving despite its flaws, and this constitutes a new paradigm that must be addressed swiftly and properly in the name of notkilleveryonism.
The buzzwords of today’s tech industry such as “alignment”, “black box engineering”, “ emergent consciousness”, “intelligence”, “reasoning” etc. are underdeveloped as rigorous abstract constructs, and the nature of these ongoing developments will inherently affect our preconceived intuitions about human consciousness and morality. How you personally understand consciousness/agency affects how you perceive and treat other entities which may or may not be conscious/agentic.
The time has come to discuss the foundations of knowledge and how to use it.
How do we consider knowledge about knowledge?
Is this meta-knowledge necessarily more/less useful in certain cases relative to concrete knowledge of the world?
How might we go about constructing a model of a system within which knowledge may naturally emerge, e.g. consciousness?
What is the optimal model of models, and what might be the least reducible symbolic construct(s) associated with this model?
The answers may be closer than you think that you think.
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An explorative, user friendly approach to examining knowledge models and their structure while justifying the examination methods via metamodels.
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A brief walkthrough of the general concept/structure of metamodels, with demonstrations of potential use cases inspired by category theory and functional schema.
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A 5-page starter guide for understanding "things", models, symbols, and self-reference/recursion.
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A meta-analysis of models and complementarity which asserts a correlation between the recursive process of constructing models and the recursive structure of the integers.