As fully homomorphic encryption struggles with frontier-scale implementation timelines, compact AI architectures are positioning themselves as viable alternatives for privacy-preserving computations. The reduced performance requirements create new opportunities for decentralized applications requiring confidential data processing without compromising user privacy.
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