As an AI tech enthusiast, what interests me about @inference_labs is its mission to make AI inference more verifiable, accountable, and practical for real-world use.
The problem with full-model zkML is clear:
β’ It can be expensive
β’ It requires high memory and has proof latency
β’ Retraining makes re-circuitization costly
This is why targeted verification is useful.
Instead of proving the entire model, DSperse focuses on proving only the critical slices of an ML pipeline: the parts where trust matters most.
That approach can reduce proving cost, improve efficiency, and still keep important AI decisions auditable
Really impressed with @inference_labs and their Proof of Inference approach. Verifiable AI for agents and robotics is exactly what this space needs β real accountability instead of blind trust. Their Zealy campaign is fun and educational @inference_labs#ProofOfInference
Really impressed with @inference_labs and their Proof of Inference approach. Verifiable AI for agents and robotics is exactly what this space needs β real accountability instead of blind trust. Their Zealy campaign is fun and educational @inference_labs#ProofOfInference
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