confidential computing

Encryption protects data at rest and in transit, but the instant you compute on it the data sits as cleartext in memory. Confidential computing closes that gap. The signal is the TEE concept, attestation, and the AI workloads that genuinely need it.

Privacy in ML is a toolbox, not one switch, and each tool defends a different threat. The signal is mapping DP, federated learning, confidential computing, encryption, and minimization to what each one actually protects, and knowing they compose.