AI means asynchronous intelligence that thrives in a two dimensional academic flat land:Let's explore further in a thought experiment about what would education and research mean to cave men. It could mean another tool to solve their day to day issues such as trying to asynchronously communicate through a sketch on their cave walls where they had been hunting and where they would be leaving for the next hunt so that the next batch of hunting cave men who would be arriving at that cave a few days later could track their whereabouts? As cavemen evolved into us, the problems embedded in the whole ecosystem changed while human ability to learn through collective cognition didn't but became more refined. (Ref 31 https://medicinedepartment.blogspot.com/2021/06/draft-3a-scholarship-of-integration-and.html?m=1)
Rhetoric: Even now as humans continue to flow through time along with others who share the same space time globally, they and their uncertainties are like particles suspended in river water, which has a way of flowing around any object in it's path, a unique characteristic of the river that allows all other smaller particles in it to continue to flow unhindered albeit with a high degree of uncertainty of what future brings.
Human animals invented AI beginning with asynchronous intelligence through their ability to use cave painting tech to convert multidimensional real life data into two dimensional data in an xy axis cave wall that later evolved to paper and electronic media so that they could eventually manage their lives better as artistic modelling was easier in a two dimensional virtual plane than a multi dimensional real plane!
We have come all the way from primordial AI (aka asynchronous intelligence) to modern AI that models primordial AI to produce some currently interesting results particularly if the data capture is asynchronously hyperlocal.
Most learning is a process of objectively structuring subjective complex multidimensional real life data (blooms level 3-5) into a two dimensional space (blooms level 1 aka knowledge) that can be stored forwarded asynchronously and modeled conceptually to gain understanding (blooms level 2) through further analysis ( level 4) and evaluation (level 5) and then relooped into the learning ecosystem as creative communication/publication (level 6). This learning is cyclic and one can keep moving in and out of these levels at any entry or exit point regardless of level numbers.
Ref 32 :https://medicinedepartment.blogspot.com/2023/12/ongoing-project-draft-optimizing.html?m=1
https://medicinedepartment.blogspot.com/2024/11/technology-end-user-driven-ecosystem.html?m=1
Asynchronous communication of knowledge: asynchronous intelligence aka primordial AI and subsequently academic intelligence AI and finally current artificial intelligence AI
More here: https://medicinedepartment.blogspot.com/2021/06/introduction-to-evolution-of-human.html?m=0
Image CC licence: https://commons.m.wikimedia.org/wiki/File:Rock_Shelter_8,_Bhimbetka_02.jpg#mw-jump-to-license
Rhetoric: Human animals invented AI beginning with asynchronous intelligence through their ability to use cave painting tech to convert multidimensional real life data into two dimensional data in an xy axis cave wall that later evolved to paper and electronic media so that they could eventually manage their lives better as artistic modelling was easier in a two dimensional virtual plane than a multi dimensional real plane!
Let's look at where we have come all the way from primordial AI (aka asynchronous intelligence) to modern AI that models primordial AI to produce some currently interesting results particularly if the data capture is asynchronously hyperlocal.
Link to the actual lecture around this slide:
[15/08, 20:55]: Is there a philosophy of dimensionality reduction as in reducing multidimensional real world data to a two dimensional academic flat land data?
[15/08, 20:55] Meta AI: Yes, the concept of dimensionality reduction can indeed be explored philosophically, as it reflects a deeper epistemological tension between the complexity of reality and the simplifications we use to understand and communicate it. Here’s a breakdown of how this idea can be philosophically framed:
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1. The Philosophy of Abstraction and Simplification
Dimensionality reduction mirrors the philosophical process of abstraction, where we strip away details to focus on the "essence" of phenomena. In doing so:
- *Strengths*: It allows us to create models that are interpretable and communicable, much like reducing real-world complexity into simplified academic frameworks (e.g., graphs, tables, or theories).
- *Limitations*: It risks losing nuances, context, and emergent properties of higher-dimensional systems. Philosophers like Alfred North Whitehead warned of the "fallacy of misplaced concreteness," where abstractions are mistaken for the full reality they represent.
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2. Flatland and Dimensionality Reduction
The concept of "Flatland," popularized by Edwin Abbott's novella, serves as a metaphor for dimensionality reduction:
- *Flatland as a Reductionist Trap*: In reducing multidimensional data (or reality) to two dimensions, we risk oversimplifying and misinterpreting phenomena. For example, reducing a dynamic, interconnected social system to a single graph might obscure the complexity of human behavior.
- *Flatland as a Tool for Understanding*: At the same time, the reduction to "flatland" is a necessary step for human cognition, as we can only process and analyze so much complexity at once.
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3. Trade-offs Between Complexity and Interpretability
Dimensionality reduction reflects the philosophical trade-off between complexity and interpretability:
- *Kantian Perspective*: Immanuel Kant argued that human cognition is inherently limited by the categories of understanding (space, time, causality). Similarly, dimensionality reduction acknowledges our cognitive and computational limits, reducing data to manageable forms.
- *Pragmatism*: Philosophers like William James or John Dewey might argue that dimensionality reduction is justified if it serves practical purposes, even if it sacrifices some fidelity to the original complexity.
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4. Ethical and Epistemological Implications
- *Bias and Oversight*: Dimensionality reduction leaves room for bias in what dimensions are "reduced" and how. For instance, in reducing real-world diversity into academic metrics, whose perspectives and dimensions are prioritized or ignored?
- *Epistemological Humility*: Philosophically, dimensionality reduction reminds us of the limits of human knowledge. The act of reducing dimensions is a recognition that we are always operating with partial truths.
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5. Philosophical Analogies in Science and Art
- *Science*: The scientific method itself is a form of dimensionality reduction, distilling complex phenomena into laws, models, and theories (e.g., Newton’s laws or Einstein’s equations). These are not complete representations but tools of approximation.
- *Art*: In art, dimensionality reduction occurs when artists convey the essence of multidimensional experiences through limited media (e.g., a painting or a poem).
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6. Reconciling Reductionism with Holism
Philosophically, dimensionality reduction can be seen as part of a broader tension between reductionism and holism:
- *Reductionism*: Breaking down complexity into simpler, lower-dimensional components for analysis.
- *Holism*: Recognizing that the whole often has properties that cannot be fully understood by its parts alone.
Dimensionality reduction, when used wisely, can serve as a bridge between these approaches, helping us approximate the whole while acknowledging the limits of reductionism.
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Conclusion
The philosophy of dimensionality reduction is ultimately about balance: how much of reality can we afford to simplify without losing its essence? While it is a powerful tool for understanding, it also serves as a reminder of the inherent incompleteness of human knowledge. In this sense, dimensionality reduction is not just a mathematical or computational technique—it is a philosophical exercise in humility, abstraction, and the pursuit of meaning amidst complexity.
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