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CoreXDataSet/README.md

# CoreXDataSet

## Overview

CoreXDataSet is a comprehensive multi-modal dataset curated specifically for training and evaluating the OmniCoreX AI model β€” the ultimate AI brain designed for integrating infinite knowledge streams with adaptive reasoning and real-time decision-making capabilities.

This dataset includes diverse data modalities such as text, images, sensor readings, audio, and more, enabling OmniCoreX to learn cross-modal representations and perform advanced multi-stream reasoning across varied real-world scenarios.

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## Contents

- **Text**: Rich corpora including encyclopedic knowledge, technical documents, and conversational data.
- **Images**: High-resolution images covering a wide variety of domains such as nature, urban scenes, and technology.
- **Sensor Data**: Time-series sensor recordings from IoT devices, robotics, and mobile platforms.
- **Audio**: Speech and environmental audio clips for audio pattern understanding and integration.
- **Labels/Annotations**: Metadata and annotations required for supervised learning tasks.

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## Dataset Structure

CoreXDataSet/ β”œβ”€β”€ metadata.json # Descriptions and references for dataset samples β”œβ”€β”€ text/ # Directory containing text files or JSON documents β”œβ”€β”€ images/ # Directory containing images in jpeg/png format β”œβ”€β”€ sensors/ # CSV or binary files for sensor data sequences β”œβ”€β”€ audio/ # Audio clips in WAV/MP3 format └── annotations/ # Optional annotations for supervised tasks


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## License

CoreXDataSet is released under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). Please review the LICENSE file for more details.

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## Usage

### Accessing the Data

Download and extract the CoreXDataSet archive. Use the provided metadata file to index and load samples efficiently using the OmniCoreX data loader utilities.

### Integration

CoreXDataSet is designed for seamless integration with the OmniCoreX training pipelines and model architectures. Utilize the dataset modules and data loaders included within the OmniCoreX repository.

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## Citation

If you use CoreXDataSet in your research, please cite it as:

@dataset{corexdataset2024, title={CoreXDataSet: Multi-Modal Dataset for OmniCoreX AI}, author={Kosasih, Team}, year={2024}, publisher={OmniCoreX Initiative}, url={https://github.com/KOSASIH/CoreXDataSet} }


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## Contribution

We welcome contributions to enhance CoreXDataSet with new modalities, expanded annotations, and improved quality. Please see the CONTRIBUTING.md file in the dataset repository for guidelines.

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## Contact

For inquiries, questions, or support related to CoreXDataSet:

- Email: [email protected]
- GitHub: https://github.com/KOSASIH/CoreXDataSet

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Empower your AI research with the rich and diverse CoreXDataSet β€” training the next generation AI brain.
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