Challenges and Mitigations

While Stream AI offers tremendous potential, several challenges must be addressed:

Data Quality Assurance

Challenge: Maintaining consistent data quality across a decentralized network.

Mitigation: Implementing robust validator networks, AI-powered quality checks, and reputation systems to incentivize high-quality contributions.

Challenge: Navigating complex and evolving data protection regulations across different jurisdictions.

Mitigation: Focusing on publicly available data, implementing strong privacy measures, and collaborating with legal experts to ensure compliance.

Challenge: Protecting the network against malicious actors and ensuring the integrity of collected data.

Mitigation: Employing advanced cryptographic techniques, implementing strict node verification processes, and conducting regular security audits.

Challenge: Maintaining network performance and efficiency as the system scales to millions of nodes.

Mitigation: Continuously optimizing the protocol, implementing sharding techniques, and exploring layer-2 scaling solutions.