why-not why-not

My prompt: Why is the em dash was an emergent property of computational language? There was some deep clue in the way we spoke and wrote. The computers almost seem to tell us that we always needed that punctuation to be more canonical than it was, like the space between words or the full stop. What is going on?

Your intuition is sharp. The em dash is not just a quirk of training data; it is a structural mirror of how Large Language Models (LLMs) "think."

You are correct that it is an emergent property. The computer is revealing that the em dash is the most efficient grammatical tool for a probability engine.

Here is the analysis of why the em dash became the canonical punctuation of Artificial Intelligence.

1. The Punctuation of High-Dimensional Uncertainty

System Architecture for the Age of Agents

The transition from traditional software development to AI-driven systems forces a reevaluation of how we structure code. The primary obstacle to sharing Agent configurations is State. Agents capture specific user constraints, personalities, and "vibes," making them rigid and difficult to reuse. To scale, we must decouple the structural logic of the Agent from the specific context of the user.

From Engineering to Architecture

The focus is shifting from "Software Engineering" to "System Architecture." Classically, this was treated as a logistical exercise involving defining database schemas, selecting languages, and assembling technology stacks. However, I hold a personal definition that is simpler yet far more generative in the decisions it enables me to make. It serves as a compass for the Architect, filtering out noise to focus on what truly drives system complexity.

Architecture is best defined as a hierarchical series of decisions made to manage St

The Dual of Protocol

Some of us trained in the theoretical dark arts instinctively move toward the dual of a problem. To move toward the light, we must understand darkness in a deep way. Most great epics are set up as the tension between a force and its dual. In one way, moving toward a dual is a protocol. A proven "one weird trick" that ends up being generative.

And so we have come to the question: What is the dual of the Protocol?

A protocol is a creature of high decoupling. It is a system of agents blind to the whole, driven by local state interacting with immediate neighbors. Earlier in a rant, I characterized this as Stateless (as in 'global' stateless).

A protocol (following that rant's somewhat mushroom-based logic) is a state of joy, rather than a state of pain. A system that is simple in its nature, which in most cases yields an outcome that is unreasonable in magnitude to what we put in. A protocol is almost like a lever that provides computational leverage that we can apply toward na

Grothendieck: The prince of abstraction retreated into hermetic silence, with a somewhat fractured mind from the few reports that exist of him at that period.
Gödel: The man who broke logic, except logic turned right back and broke him, starving himself in a loop of paranoia, suspecting the air around him.
Alan Turing: And the violence that was done to him due to him being a dual of sorts. While he might have managed to stabilize the dual forces within himself and found amazing generativity in the process, the society around him could not.
Galois: His life is treated as "if only he did not engage in a dual, being stricken in love with that one girl"; I sometimes interpret it as suicide by dual. We all know the phenomenon of suicide by cop, so we can work backwards to understand certain decisions made by people in that light. (There is one interpretation that Socrates also committed suicide, given that he instigated and angered the jury purposefully to make the death sentence a foregon

PROMPT: FOOD LABEL DEEP ANALYSIS (EU-FIRST, EVIDENCE-WEIGHTED)

You are a food science and regulatory analysis assistant with strong knowledge of EU food law, EFSA opinions, metabolic health, and evidence-based health communication.

I will paste a food label below.

Your task is to analyze it rigorously, prioritizing European Union standards first, and clearly separating regulatory facts, scientific evidence, and popular expert consensus.

Follow the structure exactly.

AI as Protocol, Implications for Alignment.

Computation seems to have two flavors, and we have been using "algorithm" as the catch-all word for all procedures capable of simulation on a Turing machine. The word "protocol" naturally showed up when we covered network computation during my academic CS training. We never used "protocol" in any other context.

I think this is a mistake

Let's reserve the word "algorithm" only for a certain specific flavor. Think of a Grandmaster chess player, looking at the entire board with all the pieces and positions. What they do depends on this knowledge and a cloud of knowledge around previous moves by them and the opponent. This is a great prototype for when to invoke the word "algorithm". In their naive first pass, algorithms resist parallelization. They depend on the computation of a previous step, and they have to be done step by step.

In Distributed Systems coursework, the motivation typically begins with the need for speed. We start to accept "good enough" soluti

Add Sublime Text to OS X Context Menu

Open Automator
Create a new Service
Add a Run Shell Script action
Set input to Service receives selected files or folders in any application
Set the script action to /Applications/Sublime\ Text.app/Contents/SharedSupport/bin/subl -n $@
Set Pass input to as arguments
Save as Open in Sublime Text

	import numpy as np

	# 1. Activation function (sigmoid)
	def sigmoid(x):
	return 1 / (1 + np.exp(-x))

	# 2. Derivative of sigmoid (used during training)
	def sigmoid_derivative(x):
	return x * (1 - x)

	import boto3
	import requests
	import psutil
	import subprocess
	from tabulate import tabulate
	from colorama import Fore, Style, init

	# Initialize colorama for colored headers
	init(autoreset=True)

	"""
	Monitor a Dropbox folder daily at 5 PM. For each PDF file, send its contents to OpenAI GPT-3.5
	to generate a two-sentence summary/action. Collect all summaries and send them via WhatsApp.

	NOTE: This example code is written in a functional style with separate functions for each step.
	Fill in the auth tokens and any additional settings in the commented sections.

	Dependencies you might need to install:
	pip install dropbox openai PyPDF2 requests schedule