I’ve been following @inference_labs and what stands out is their strong focus on verifiable inference. They’re not just building AI models, but ensuring outputs can be trusted, which is critical for real-world adoption across finance
Enterprise AI is moving past pilot theater. The harder phase is production, where outputs affect workflows, audits, contracts, and operational decisions.
Sertn is built for that layer: not just running AI, but preserving verifiable records of what happened.
Hey @DavidOscar110 and @LIGHTLIGHT44730 , if you’re interested in the future of AI, especially Verifiable AI and zkML, you should check out the new Inference Labs X Community. Great place to learn, connect, and stay updated.
@inference_labs Instead of verifying a full, huge ML model in zero-knowledge, which is extremely costly. DSperse focuses on selectively checking the most essential parts of the model for a greater layer and detection
Jumping into @inference_labs’ Zealy campaign and I’m genuinely impressed.
Verifiable inference means AI you can actually trust.
JSTprove + the Inference Network is a big step toward real AI security.
Curious to see where this goes anyone else building with @inference_labs
Jumping into @inference_labs’ Zealy campaign and I’m genuinely impressed.
Verifiable inference means AI you can actually trust.
JSTprove + the Inference Network is a big step toward real AI security.
Curious to see where this goes anyone else building with @inference_labs
Jumping into @inference_labs’ Zealy campaign and I’m genuinely impressed.
Verifiable inference means AI you can actually trust.
JSTprove + the Inference Network is a big step toward real AI security.
Curious to see where this goes anyone else building with @inference_labs
Jumping into @inference_labs’ Zealy campaign and I’m genuinely impressed.
Verifiable inference means AI you can actually trust.
JSTprove + the Inference Network is a big step toward real AI security.
Curious to see where this goes anyone else building with @inference_labs
Every new AI system expands the operational surface area around it.
More models, more pipelines, more integrations, more things to trust.
At Inference Labs, we’re focused on reducing that trust gap by making inference outputs independently verifiable.
https://t.co/91z1UYbDP9
@inference_labs That's exactly the direction AI needs to take. As AI systems become more interconnected, verifiable inference becomes essential for building confidence, accountability, and reliable adoption. Great work from @inference_labs