Digital knowledge graphs are easy to centralize because their inputs are cheap, copyable, and globally accessible from a screen. Real-world knowledge graphs behave differently. Their raw inputs require presence: being somewhere, observing change, capturing context, and validating

Торговля акциями через DeFi: знакомьтесь с xStocks Грань между фондовым рынком и криптой стирается. xStocks на STON.fi; владение мировыми активами без посредников и разрешений. Подробности в этом треде 🧵👇🏼 #xStock #TON #STONfi

Every day Yellow keeps showing what real progress in Web3 looks like. Connecting exchanges, improving speed, and building a fairer system for everyone. Decentralization is not a dream, it’s happening right now with Yellow 🟡 #YellowNetwork #Web3

ADIChain Gm ADI Chain is building regulation-ready blockchain infrastructure. By combining ZK compliance, modular architecture, and privacy-preserving payment rails, ADIChain is totally enabling institutional deployment of blockchain for real-world assets and financial

Like Inference Labs used to say Autonomy without auditability is chaos Today autonomous systems lack fragmented and Inference Labs is solving that with Proof of Inference and with Autonometrics and biometric-grade inference verification to every autonomous agent and workflow

DGrid AI redefines intelligence as shared infrastructure, decentralizing inference across a community network instead of corporate silos. Removing centralized control makes AI resilient, transparent, permissionless, and governed by the open network it serves, not closed platforms

GM CT Don’t know why my Xyber Xeet still on zero after over two weeks. Nevertheless, I will keep preaching Xyber Ownable AI isn’t a narrative it’s the future they're building. Verifiable agents via PROOF. Fair launches via 0–100 Engine. Real robots like Xybot earning onchain.

𝐘𝐎𝐔 𝐊𝐍𝐎𝐖 𝐖𝐇𝐀𝐓 𝐀𝐍𝐍𝐎𝐘𝐒 𝐌𝐄 𝐓𝐇𝐄 𝐌𝐎𝐒𝐓 𝐀𝐁𝐎𝐔𝐓 𝐂𝐑𝐘𝐏𝐓𝐎 𝐏𝐀𝐘𝐌𝐄𝐍𝐓𝐒? It’s not that I don’t have the money, the balance is right there. But the moment I’m ready to pay, I start thinking about chains, switching wallets, gas fees, and whether the

DaGama World advances recommendation systems by training privacy-first machine learning models on location signals. Instead of harvesting exhaustive behavioral data, personalization is derived from verified check ins with differential privacy techniques obscuring individual

I didn’t enter this Roast Market bullish or bearish. I entered confused. Builders kept shipping, users kept showing up, infra kept improving and price still acted like nothing changed. That confusion is the contradiction worth roasting.

I’ve been seeing this project appear frequently on my timeline, so I took some time to look into it. After reviewing it more closely, it stands out as a well-thought-out and meaningful effort. Inference Labs is addressing a critical issue in modern AI systems: the lack of

Good Morning, Pipo. I’ve been digging into what the XYO team is doing with their new Layer One blockchain, and honestly,it’s one of the clearest, most coherent designs I’ve seen in web3. Most chains ignore a critical problem until it’s a total mess. what happens when the ledger

DGrid AI is emerging as a key player in decentralized intelligence, building a verifiable AI inference network that prioritizes scalability, trust, and efficiency. By offering unified APIs, intelligent routing, and a strong Proof of Quality system, DGrid AI allows Web3 developers

Gmgm to my Chad and creators mos especially the daGama chads that have been showing up consistently since day 1 The season two is coming to an end soon and I believe y’all can feel the thrill and how real the buzz is Lock in now or lock up later Check-in on the app and

People want AI they can trust, not something that just sounds confident. Inference Labs is building systems that prove what they do using math, not promises. No guessing, no hidden tricks. Just facts you can verify.

Human Presence as the System Clock daGama For too long, time in digital systems was abstract. Updates, visibility, and relevance were dictated by schedules, algorithms, or arbitrary refresh cycles. Human activity happened continuously, but systems observed only snapshots.