According to Bankless, the challenge of private AI may be addressed sooner than expected. While fully homomorphic encryption for large-scale applications remains years away, the requirements for achieving "good enough" privacy have decreased. The development suggests that smaller models could provide more immediate solutions for private AI, potentially impacting various sectors where data privacy is paramount. This could accelerate the adoption of AI in sensitive areas, as per the report.

According to Bankless, the challenge of private AI may be addressed sooner than expected. While fully homomorphic encryption for large-scale applications remains years away, the requirements for achieving "good enough" privacy have decreased. The development suggests that smaller models could provide more immediate solutions for private AI, potentially impacting various sectors where data privacy is paramount. This could accelerate the adoption of AI in sensitive areas, as per the report.