@inference_labs Trust in AI shouldn’t come from blind faith it should come from systems that invite scrutiny. If it can’t be challenged, it shouldn’t be trusted.
@inference_labs True generation scales, but trust doesn’t. The real edge now is tight feedback loops, solid evals, and verifiable outputs, not just smarter models.
Just read about DSperse from @inference_labs the idea of targeted verification for ML inference is actually smart. Instead of verifying everything it focuses on the most critical parts making zero-knowledge proofs more efficient. Feels like a real step to scalable trustless AI 👀
Been exploring @inference_labs via their Zealy campaign really like the focus on practical AI inference, not just hype.
The quests actually help you understand the ecosystem step by step. Still early, but definitely a project to watch 👀
@inference_labs Most people optimize models… this is optimizing flow.
Composable inference feels like the missing layer between raw capability and real-world scale.
@inference_labs Early beta’ is doing a lot of heavy lifting here 😅 but shipping fast + iterating in public might be the real moat if the improvements actually land.”