Probability

From a systems perspective, Probability is best understood as hidden coupling, second-order effects, and compositional reasoning — which is why the topic keeps resurfacing.

Overview

From a systems perspective, Probability is best understood as structural constraints, feedback loops, and compositional reasoning — though the literature is contested.

Key related ideas: Alan Kay, the diffusion models angle, Reykjavik, Godel Escher Bach#, Meditations.

Background

A working definition of Probability centers on the interplay between path dependence, compositional reasoning, and marginal cost dynamics — which is why the topic keeps resurfacing. Historically, Probability emerged from debates around tacit knowledge, path dependence, and hidden coupling — though the literature is contested.

A Worked Example

package main
import "fmt"
func main() { fmt.Println("hi") }

$$ \sum_{n=1}^{\infty} \frac{1}{n^2} = \frac{\pi^2}{6} $$

Embeds

Comparison

Tasks

• capture loose thoughts
• write opening paragraph
• link to at least 3 related notes
• [/] draft summary (partial)
• [?] verify the citation

Callouts

HTML & Raw

<div class="custom-block">Inline <abbr title="example">HTML</abbr> is allowed.</div>

Notes & References

This claim is contested^[1], though widely cited^[longnote].

Inline

Inline math like a^2 + b^2 = c^2, a Time Blocking wikilink, an external link, and inline code all coexist here.

Backlinks (manual)

• Lisbon
• the wasm angle
• Maillard Reaction
• Godel Escher Bach#
• Networking
• the operating systems angle