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NeuroNexus is a cutting-edge, theoretical implementation of an advanced artificial intelligence system. It combines concepts from quantum computing, neuroscience, and state-of-the-art machine learning to create a highly sophisticated language model and potential AGI (Artificial General Intelligence) framework.

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NeuroNexus

Overview

NeuroNexus is a cutting-edge, theoretical implementation of an advanced artificial intelligence system. It combines concepts from quantum computing, neuroscience, and state-of-the-art machine learning to create a highly sophisticated language model and potential AGI (Artificial General Intelligence) framework.

Features

  • Quantum-inspired tensor networks
  • Neuroplastic architecture
  • Fractal attention mechanisms
  • Adaptive compression and expansion
  • Neuro-symbolic reasoning
  • Ethical AI framework
  • Multimodal fusion (text, image, audio)
  • Temporal recursion processing
  • Multiversal inference engine
  • Meta-learning capabilities
  • Self-supervised pretraining
  • Quantum-classical hybrid optimization

Requirements

  • Python 3.8+
  • PyTorch 1.9+
  • Qiskit
  • NumPy
  • SymPy
  • Z3-Solver
  • NetworkX
  • PyViz
  • Matplotlib

Installation

pip install -r requirements.txt

Usage

Here's a basic example of how to use NeuroNexus Omega:

from neuronexus_omega import NeuroNexusOmega

# Initialize the model
model = NeuroNexusOmega(vocab_size=50000, dim=1024, n_qubits=100, n_layers=12, n_heads=16, max_seq_len=512)

# Prepare input data
x = torch.randint(0, vocab_size, (1, 100))
image = torch.randn(1, 100, 1024)
audio = torch.randn(1, 100, 1024)

# Forward pass
output = model(x, image, audio)

# Access different outputs
logits = output['output']
ethical_scores = output['ethical_scores']
temporal_output = output['temporal_output']
multiversal_output = output['multiversal_output']

For more detailed usage instructions, including training and meta-learning, please refer to the documentation.

Training

To train the model:

from neuronexus_omega import train_neuronexus_omega

train_neuronexus_omega(model, train_loader, num_epochs=10, device=torch.device("cuda"))

For meta-learning:

from neuronexus_omega import meta_train_neuronexus_omega

meta_train_neuronexus_omega(model, task_loader, num_epochs=5, device=torch.device("cuda"))

Contributing

Contributions to NeuroNexus Omega are welcome! Please read our contributing guidelines before submitting pull requests.

License

This project is licensed under a custom license that requires attribution. See the LICENSE file for details.

Disclaimer

NeuroNexus Omega is a theoretical implementation and includes speculative concepts. It is intended for research and exploration purposes only.

Contact

For questions or feedback, please contact [sanowl] at [sanowl98@gmail.com].

About

NeuroNexus is a cutting-edge, theoretical implementation of an advanced artificial intelligence system. It combines concepts from quantum computing, neuroscience, and state-of-the-art machine learning to create a highly sophisticated language model and potential AGI (Artificial General Intelligence) framework.

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