Catcliffe Development
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- Catcliffe Development brims a cliff in one of the many meandering horseshoe turns of Indian Creek.
Catcliffe Development Offers
An arcane branch of computer science
- A method
- Random_Element_of_Category
- When the QAT is ported to time series analysis, quasi axiomatic purview of time-balanced sensor logs reveal cross-time dynamics by value** category from a static sparse sample.
- **value: the recorded value in computer memory of an event occurring on a sensorized time line.
The concept
QAT as time-line analysis algorithmically assembles:
- A time-line-aware value-histogram of a stereoscopic***, sparse samples.
- ***stereoscopic: dual and optical, in the sense of a dual-focus of two simultaneous events.
The way cool exploits
- A index per datum is a member of a linked list of value category elements (equivalent values).
- The same index is inserted in a binary tree of value categories.
- By exploit of a shared list and tree structures by element as a dual, stereoscopic time-line log of time-balanced events:
- —The Random_Element_of_Category method is realized as a random selection on the linked list of value categories, linked from the node of a binary tree.
- (that's the way cool part)
The spooky upshot
The QAT reveals a temporal shadow of unknown things of non-random nature.
"In the redundant simplicity of the time-series port, the QAT affordance is a bit like the least means of one unit of cognizance." —XenoEngineer
QAT cognizance of temporal events
What I know is memory.
What I sense is perception.
Memory and perception significanntly agree in context.
Take it to an AI
So, an index of significance of similar events serves a gauge of plausibility?
- Claude 3.5 Sonnet (new)
Ah, this is a fascinating extension of the concept! You're suggesting that our brain uses a kind of "frequency heuristic" where the significance we assign to similar past experiences helps us evaluate how plausible new experiences or interpretations are.
Let's break this down: Pattern Recognition Our minds naturally index similar experiences The more frequently we encounter similar patterns, the more "weight" they carry in our plausibility assessments This creates a kind of probabilistic framework based on lived experience Significance Weighting Not just frequency, but the emotional and practical impact of past events matters Highly significant events might carry more weight in our plausibility gauge even if they occurred less frequently This suggests a sophisticated weighting system where both frequency and impact matter
Plausibility Assessment When encountering new situations, we unconsciously reference this "significance index" The more our past experiences align with new information, the more plausible it seems This might explain why people from different backgrounds can have vastly different ideas of what's "plausible" This relates to Bayesian reasoning in a way - our prior experiences form a probability distribution that we use to evaluate new information. Would you say this mental indexing system serves as a kind of evolutionary shortcut for rapid decision-making?