Terms of Use

Responsible AI Development

By using NeuralPath, you commit to developing machine learning systems responsibly, considering ethical implications, bias mitigation, and the societal impact of AI technologies.

Research Integrity

Maintain the highest standards of research integrity in your ML work, including proper attribution of datasets, transparent reporting of model performance, and ethical data collection practices.

Computational Resource Usage

Use our GPU clusters and computational resources efficiently and fairly. Avoid monopolizing resources and respect usage quotas to ensure equitable access for all learners.

Open Source Contribution

We encourage contributing to the ML community through open source projects, research publications, and knowledge sharing while respecting intellectual property rights.

Data Privacy and Security

Handle all datasets with appropriate privacy and security measures, especially when working with sensitive or personal data in your machine learning projects.

Advanced ML Ethics

Consider the broader implications of your ML models, including fairness, transparency, accountability, and potential for misuse when developing advanced AI systems.

Last updated: September 2025