MOAI speeds non-interactive homomorphic transformer inference
It cuts BERT-base evaluation time 52.8% versus THOR and reports 2.36 minutes amortized per input on one GPU.
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It cuts BERT-base evaluation time 52.8% versus THOR and reports 2.36 minutes amortized per input on one GPU.
It is pretrained on more than 800,000 unlabeled MIMIC-IV ECGs and fine-tuned on three labeled datasets.
Governing parties grow more alike in speech, opposition diverges, and switchers adapt only after changing party.
QCATS slices transformer FFNs using query predicates, cutting in-database inference latency up to 4.42x.
OPFL verifies federated learning inside MPC with an empirical gradient boundary, stopping model poisoning at much lower cost.

Microsoft says affiliate Storm-2570 reused one playbook across Qilin, DragonForce, Anubis, and BERT.
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