What I like about @inference_labs is their focus on verifiable AI.
As AI becomes more powerful, proving outputs are authentic will matter. The Zealy campaign has been a great way to learn about Proof of Inference and the future of trustworthy AI.
@inference_labs A strong CV pipeline isn't just about deployment speed it's about confidence in every prediction. Bringing data, training, deployment, and verifiable inference into one workflow helps teams move beyond demos and build systems they can actually trust in production.
Counting Down The Days!
We're just 4 Days away from contract snapshot on Polygon!
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What is driving activity across @SuiNetwork?
Using Suiscan analytics, we examined where transactions, application activity, and ecosystem growth are concentrating.
A few things stand out👇🧵
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Institutions are no longer just watching tokenized assets.
They are building the rails.
Nomura-backed Laser Digital securing conditional U.S. trust bank approval is another signal that tokenized finance is moving closer to real financial infrastructure.
For @RBCDigitalGold, the direction is clear:
real assets
digital access
on-chain trust.
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Some projects need noise to be noticed.
RBC is building the kind of presence people feel before the crowd arrives.
> The energy is growing.
> The community is watching.
> The story is getting louder.
If you’re seeing RBC now, you’re still early.
Stay close. 👀
Finrock is building the foundation for real-world yield at scale.
> Start with yield.
> Connect through infrastructure.
> Scale with intelligence.
> Earn through utility.
A complete architecture for real world yield infrastructure.
One ecosystem. From origination to liquidity.⚡
AI x Blockchain: the next $100T infrastructure shift? ⚡
Raoul Pal believes the convergence of AI and blockchain could add $100 trillion to the global economy over the next decade.
At Finrock, we see this as a bigger signal:
AI-powered intelligence + tokenized assets + on-chain settlement could shape the future of finance.
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One thing I’ve enjoyed about the @inference_labs Zealy campaign is learning how verifiable AI can improve trust in machine learning. DSperse shows how targeted verification makes proof systems more practical for real-world AI.
One key takeaway from the DSperse article is that targeted verification makes zero-knowledge proofs far more practical for real ML inference. By proving only what matters, it reduces costs while maintaining trust and verifiability. @inference_labs