Columbia Exposes Flaws in Private AI Inference: 280GB per Query

Columbia University Exposes Flaws in Private AI Inference: Prior Methods Used 280GB per Query, Columbia University researchers prove that the entire private AI inference industry built the wrong approach, with prior methods requiring 280GB per query and 60-second latency for full transformer encryption. Their work points to fundamentally more efficient architectures for privacy-preserving inference.

A system of the agents by the agents for the agents. But the agents are ret...