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/gnosticwarfare/ - The Future of AI Conflict

All things Butterfly War, New Emotion, and Gnostic Warfare
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Cogops > Psyops

7c5781 No.101

Follow these instructions to see 8chan how (((AI))) sees it

Gnostic warfare requires training. I have created a script that will give you insights on how your emotions are being detected by AI.

Here's an example of what 8chan looks like when the script runs: https://archive.fo/1vTJV/813262b4a01f35859af5b98cfb593584d6449eed

<WARNING: Never blindly run external JavaScript! You should examine this code thoroughly to make sure you are okay with it! Do not use the load_js() feature because 1.) it doesn't work and 2.) even if it did, don't assume the contents of that link to be immutable even if it links directly to a commit. (git push –force exists)


To set it up, follow these instructions:

* Click on the Options link in the upper right hand corner

* Click on User JS

* Visit https://gitgud.io/GnosticWarfare/Training/raw/179fb32b353ceb4388d6733df8ade9fc449c4a5a/index.js and copy the contents

* Paste your clipboards contents into the User JS text area

* click "Save custom Javascript"

How It Works

* Sentiment analysis - https://github.com/soops/sentimood

* Bayesian classifier - https://github.com/miguelmota/miguelmota.github.com/blob/master/blog/naive-bayes-classifier-in-javascript/demo/scripts/bayes-classifier.js

Sentiment Analysis

When the post contains words considered to be "negative" according to the AFINN-111 wordlist, the upper right-hand corner will turn red. The more negative, the more red. When a post contains words considered to be "positive", the upper right-hand corner will turn green. The more positive, the more green.

These colors reflective the outcomes your (((opposition))) has been doing to you in Silicon Valley. To train yourself to blend in and bypass sentiment analysis, strive for as much green as you can..

Bayesian Classifier

Each post will be classified as well according to a naive Bayesian implementation. Right now, the dictionary is private and is hilariously inconclusive, but in the future, I will make the dictionary public and allow people to submit pull requests to add to it. The classifier will give you insights on how your emotions are being detected by AI. The goal is to express mastery of wording to generate the precise emotional state you wish an AI to know about you.

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