Proof of intelligence: Part 1 - determinism most models deliver outputs that can’t be recreated or verified across systems. as OpenGradient engineers put it: if two machines can’t agree on the same result, proof doesn’t exist. OpenGradient fixes this by running every model
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@OpenGradient determinism is fundamental to everything we're building without it, ai onchain is just a non-starter. you can't have agents managing real value if their "thinking" is a random number generator
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@OpenGradient This is the foundational problem in scaling AI for enterprise and critical systems. If results aren't deterministic and verifiable, AI is a black box, not a trusted tool. I like that OpenGradient's is using an approach of a deterministic runtime is the necessary "settlement
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@OpenGradient OpenGradient really nailed it with this deterministic setup! Feels like a solid foundation for building real trust in AI systems.
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@OpenGradient You guys work well and do great things 👏🏼 Is there any token launching plan on the roadmap ?
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@OpenGradient Deterministic inference is such an underrated problem. Reproducible outputs are what make AI auditable, trustable, and interoperable, exactly what @OpenGradient is solving.
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