Treffer: FPAI v2.3: A Quantum Probability Framework for Advancing Probabilistic Artificial Intelligence ; Force Francesco Probability Artificial Intelligence

Title:
FPAI v2.3: A Quantum Probability Framework for Advancing Probabilistic Artificial Intelligence ; Force Francesco Probability Artificial Intelligence
Authors:
Bulla, Francesco
Contributors:
Ewelu, Stephanie, Yalla, Satya Praveen Kumar Reddy, Van Dommelen, David, Ahmed, Hassaan
Publisher Information:
Zenodo
Publication Year:
2025
Collection:
Zenodo
Subject Terms:
FPAI, quantum probability, artificial intelligence, quantum AI, intellectual property, AI protection, Computer Science – Artificial Intelligence, Mathematics – Probability, Physics – Quantum Physics, Quantum Computing, Cognitive Science, Cybersecurity & Privacy, Computational Models of Cognition, Machine Learning – Theory, Philosophy of AI, Private Software Licensing, Intellectual Property Law (Technology)
Document Type:
Fachzeitschrift text
Language:
English
Relation:
https://zenodo.org/records/15514326; oai:zenodo.org:15514326; https://openai.com/; https://deepmind.google/models/gemini/; https://claude.ai/; https://x.ai/; https://qwen.org/; https://www.patamu.com/; https://github.com/; https://doi.org/10.5281/zenodo.15514326
DOI:
10.5281/zenodo.15514326
Availability:
https://doi.org/10.5281/zenodo.15514326
https://zenodo.org/records/15514326
https://openai.com/
https://deepmind.google/models/gemini/
https://claude.ai/
https://x.ai/
https://qwen.org/
https://www.patamu.com/
https://github.com/
Rights:
FPAI Private Intellectual Property License ; http://rightsstatements.org/vocab/InC/1.0/ ; FPAI-ABSOLUTE-PROTECTION License v1.0 ; Copyright (C) Francesco Bulla
Accession Number:
edsbas.3C38F649
Database:
BASE

Weitere Informationen

FPAI (Force Francesco Probability Artificial Intelligence) v2.3 is a private quantum-inspired probabilistic framework designed to enhance decision-making in AI systems under uncertainty. It integrates classical Bayesian reasoning with quantum principles such as state superposition, wave function collapse, and the uncertainty principle. The current release includes simulation-based testing, a simplified Shor algorithm module, and a Python prototype. This version is privately owned by Dr. Francesco Bulla and the Brainverse administration team. No public use, redistribution, or commercial deployment is allowed. IP Note: This software and theoretical model are protected by absolute intellectual property rights. Any form of reproduction, training, or use without explicit permission is strictly prohibited.