👾 resources for DeSci + AI experiments: notes, ml, agents, llms, energy based models...

Implementation of Quantum Long Short-term Memory (QLSTM)

An advanced AI application integrating quantum computing capabilities with deep learning frameworks to create powerful hybrid classical-quantum AI models. This technology aims to unlock new applications in fields such as chemistry, materials science, drug discovery, finance, and cryptography.

Natural Language Qu Kit (NLQK)

Quantum-ML is a hybrid quantum-classical machine learning project leveraging quantum computing and AI to deliver advanced predictions and solutions through a fast API interface.

🚀 QIP-X Framework – Quantum-Integrated AI & Cryptography A cutting-edge framework integrating quantum-ascendant cryptography, timeline optimization, and hyper-chaotic neural networks for secure, adaptive, and multiversal intelligence systems.

Hybrid Quantum–Classical model for brain tumor classification using Quantum FiLM modulation and ResNet-18. Supports multi-class MRI tumor detection with quantum circuit integration.

This repository features a Quantum Long Short-Term Memory (QLSTM) model for time-series forecasting using quantum circuits. It provides a custom QLSTMCell and supports real-time loss tracking, making it ideal for research and experimentation. 🛠️🌌

A testing ground for training AI models

🌌 The Supreme Agentic Orchestrator - A quantum-enhanced, consciousness-aware multi-agent system that transcends traditional AI boundaries. Built by Rick Jefferson for KaliVibeCoding.

Hybrid quantum-classical machine learning framework that runs on real quantum computers - bridge between quantum computing and AI.

XQELM is a groundbreaking open-source research project that combines quantum computing with large language models to revolutionize legal reasoning and decision-making. This system leverages quantum superposition, entanglement, and interference to process complex legal relationships while maintaining full explainability for legal applications.

🧠 Classify brain tumors using a hybrid QCNN with ResNet for accurate MRI image analysis across multiple categories, including no tumor detection.

🧠 Detect brain tumors using a hybrid Quantum + Classical model with MRI images, enhancing accuracy and efficiency in diagnosis through advanced AI.