Trusted Execution Environment
A trusted execution environment (TEE) is a hardware-backed isolated environment that can protect code and data during execution and produce attestations about what ran.
Category
Verifiable AI Infrastructure
These terms describe approaches for increasing trust in AI systems by adding proofs, attestations, or isolated execution.
How to recognize this theme
Ways to provide evidence about model execution or outputs.
In a daily board, this category groups terms by their shared role. Look for four cards that describe the same mechanism, risk area, or workflow rather than four words that merely sound similar.
Educational context
These entries are vocabulary notes for learning. They are not project endorsements, token recommendations, exchange rankings, or trading signals.
ZKML
ZKML refers to techniques that generate cryptographic proofs about a machine learning model's computation, aiming to verify claims without revealing all inputs or internals.
Model Attestation
Model attestation is producing evidence about the model version and execution environment used for a result, helping downstream systems reason about trust and provenance.
Proof of Inference
A proof of inference is evidence that a particular model inference computation was performed as claimed, which can be used to improve trust in off-chain or distributed AI services.