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Talking about Privacy-Preserving in AI, I think the current two biggest tech are #TEE and #ZK, but their approaches are quite different.
1/ #TEE is like a “hardware secure room” (special CPU/GPU): data runs inside, and no one outside can see it. It’s fast, practical, and suitable for all situations.
– Privacy projects on TEE: @iEx_ec, @SecretNetwork, @OasisProtocol, @PhalaNetwork.
2/ #ZK (or ZKML) uses cryptographic technology that allows proving AI results are correct without revealing the data or the model.
– Privacy projects on ZK: @AleoHQ, @Zcash, @RAILGUN_Project, @CantonNetwork
So, which one will win?
Personally, I believe neither will win alone. The real future I’m seeing in 2026 is hybrid: run heavy inference inside TEE for blazing speed, then attach a ZK proof for public verifiability and auditability.
– Hybrid TEE + ZK projects: @PolyhedraZK, Marlin Oyster @MarlinProtocol, @Arcium, @nillion.
But still, I’m breaking down #TEE vs #ZKML in simple terms, so you can see exactly when to pick one, the other, or the powerful combo of both.