According to a report, fully homomorphic encryption, a method for performing computations on encrypted data, is still years away from being implemented at a frontier scale. However, the requirements for achieving a workable level of privacy in AI applications have been reduced, suggesting that smaller models may offer a more immediate solution to the private AI problem. The development indicates a potential shift towards more practical, near-term approaches to data privacy in artificial intelligence.

According to a report, fully homomorphic encryption, a method for performing computations on encrypted data, is still years away from being implemented at a frontier scale. However, the requirements for achieving a workable level of privacy in AI applications have been reduced, suggesting that smaller models may offer a more immediate solution to the private AI problem. The development indicates a potential shift towards more practical, near-term approaches to data privacy in artificial intelligence.