autonull

🧠 FluQNet Brain - PoC Prototype Specification

"Quantum-Biased Neurofluid Brain" – A Minimal, Runnable Proof-of-Concept
Inspired directly by Ben Goertzel’s Rethinking the Classical/Quantum Brain framework: https://bengoertzel.substack.com/p/rethinking-classical-quantum-brain

🎯 Overview & Objectives

Build a tiny but complete hybrid simulator that demonstrates the three core layers:

Classical fluid routing (Navier-Stokes / HJB dynamics)
Local quantum micro-bias at nodes (density-matrix evolution + QLN channels)

S list questions that one might be afraid to learn the answer.

Here are some examples of questions that one might be afraid to learn the answers to:

Do I have a terminal illness or serious medical condition? Has my partner been unfaithful? Will I lose my job or get fired soon? Am I going to go bankrupt or face financial ruin? Did a loved one die in an accident or tragedy?

https://www.dhs.gov/medialibrary/assets/videos/23065 AUDREY - Public Safety Agencies Pilot Artificial Intelligence to Aid in First Response | Homeland Security Skip to main content Official websites use .gov A .gov website belongs to an official government organization in the United States. Secure .gov websites use HTTPS

https://dataverse.jpl.nasa.gov/dataset.xhtml?persistentId=hdl:2014/53408 Trusted and exPlainable Artificial Intelligence for Saving Lives (TruePAL) Technology for First Responder Safety Project Introduction - Root No abstract provided but the video is more like advertisement to push the project :)

https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12101/121010G/Neurosymbolic-hybrid-approach-to-driver-collision-warning/10.1117/12.2620209.pdf Neurosymbolic hybrid approach to driver collision warning - SPIE Digital Library

	/*
	Comparative Synthesizer

	To use this script, follow the prompts:
	- Enter your initial prompt
	- For each variation:
	- Copy the prompt
	- Paste into browser
	- Paste result back into terminal
	- Answer y/n for more variations

	import com.fasterxml.jackson.databind.ObjectMapper;
	import jdk.jshell.JShell;
	import jdk.jshell.SnippetEvent;
	import jdk.jshell.VarSnippet;

	import java.net.URI;
	import java.net.http.HttpClient;
	import java.net.http.HttpRequest;
	import java.net.http.HttpResponse;
	import java.util.*;

	saveModel: False
	system:
	seed: 0
	data:
	block_size: 1024
	model:
	model_type: gopher-44m
	activation: LeakyReLU(negative_slope=0.01)
	n_layer: None
	n_head: None

	saveModel: False
	system:
	seed: 0
	work_dir: ./out/chargpt
	data:
	block_size: 1024
	model:
	model_type: gopher-44m
	activation: LeakyReLU(negative_slope=0.01)
	n_layer: None



	saveModel: False
	system:
	seed: 0
	work_dir: ./out/chargpt
	data:
	block_size: 1024
	model:
	model_type: gpt-mini