Boyngyn246 (✱,✱) | (❖,❖)

Good evening, Ritual 🌙 Happy to be part of this amazing community and ready to give my full dedication to the project. Excited for everything we’ll build together along the journey. @ericgudboy @ritualfnd @joshsimenhoff @Jez_Cryptoz @SaintLee04

Gritual! Finding my flow with Ritual and Siggy by my side. Today is all about focus and progress. Work hard, chill harder. 🍹🐈‍⬛ @ritualfnd

gRitual ❖❖ This is my daily Ritual routine: Explore search mode on X: "@ritualnet -filter:replies " Best way to discover builders, apps, memes, and active community members early. Try this and send me tks later!

RITUAL CHAIN -TECHNOLOGY OVERVIEW (PART 4) 1. MODULAR COMPUTATIONAL INTEGRITY The core challenge when bringing AI onchain is ensuring that the model ran correctly, was not tampered with, and was not swapped for a different model. ✅And that is the inspiration behind @ritualnet 's support for multiple distinct verification methods simultaneously: ❖ Zero-Knowledge Machine Learning (zkML): Provides mathematical proofs of the computation. ❖ TEE Attestations: Delivers hardware-level trust. ❖ Optimistic ML: Follows a model similar to optimistic rollups (like Ethereum L2s — Arbitrum, Optimism). ❖ Probabilistic Proof Machine Learning: For cases where a full proof is not needed. All methods are supported natively and agnostically, meaning developers can choose the approach that best fits their specific use case. ✅Real-world analogies: ❖ TEE → Trusted employee working inside a secure company office. ❖ ZK → Notarized document with an official government seal. ❖ Optimistic → Unsecured loan (based on trust, with challenge period). ❖ Probabilistic → No need for full proof; accept a certain probability, even “blind bag” / lottery-style verification. => Covers all scenarios, ranging from guaranteed items to "blind bag" secrets. 2. VERIFIABLE PROVENANCE & vTUNE One of the biggest problems in AI today is that no one can be sure whether the running model is the original one, and model creators have no reliable way to prove ownership or collect fees when others use their models. Ritual solves this with Verifiable Provenance: a set of primitives that allow model creators to cryptographically prove ownership of their models even in a fully open, “wild” environment. The first mechanism built on top of these primitives is vTune. It enables precise attribution tracking for both model creators and data providers. This unlocks the creation of a true onchain model marketplace where models can be bought, sold, and borrowed with verifiable proof of origin and usage. In simple terms “Whose model is this, and who should get paid?” For buyers -buy directly from the rightful owner For creators-receive fair compensation for their work and intellectual property. Most importantly It eliminates the need for trusted third parties. @dunken9718 @Jez_Cryptoz @0xMadScientist @SaintLee04 @ericgudboy

gRitual 💚 Good Morning Ritual Family 💚 Happy Sunday and Happy Mother’s Day! Thank you to all the amazing mothers who fill our lives with love and strength. May your day be filled with joy and beautiful Ritual. @ritualnet @joshsimenhoff @Jez_Cryptoz

Just built a free community tool for Axis Hub contributors. AxisScan 🔍 axisscan.vercel.app No wallet connection required. Paste your Base wallet and instantly see: 1⃣Total trajectories, 2⃣How many are signed on-chain vs 3⃣Pending task 4⃣Average score 5⃣Quality breakdown (Perfect / Excellent / Good) It also tracks your activity streak 🔥every day you submit a trajectory counts, not just signed ones. You get your current streak, longest streak ever, and a full 6-month heatmap of your activity (think GitHub contribution graph but for Axis). There's also a shareable card one click copies a clean 1200×630 PNG with all your stats, rank, streak and heatmap. Perfect for flexing 😏 Indonesian Community check this directly on Telegram using /address The tool reads public blockchain data only no wallet connection, no private key, zero risk. @0xsexybanana @plpiaoliang @Rainhoole @irisle_growth @chris_anm01 @0xzagen @LihThooi @mintt_34