0G to Exhibit at ETHDenver Conference from February 17 to 21

The varieties of #RDNT #ORDI tracks are worth paying attention to: 1. MEME board: DOGE, SHIB, PEPE, FLOKI, BONK 2. AI sector: AGIX, WLD, FET, AI, NMR 3. Public chain plates: ETH, SOL, MATIC, FTM, ADA, Avax, DOT, Atom 4. Layer 2: OP, ARB, METIS, IMX, MANTA, EGLD, MNT 5. 2024 halving plates: BCH, BSV, ZEC, ZEN, BTG 6. GAMEFI PLATE: SAND, MANA, GALA, ENJ, RON, PIXEL, ACE, ILV, MAGIC 7. Oracle section: TRB, LINK, API3, BAND 8. Payment concept section: MOB, ACH, XLM, CELO0 9. Inscription plates: ORDI, SATS, RATS BTCS 10. Storage plate: AR, FIL, STORJ, BLZ 11. DEFI sector: Aave, COMP, RDNT, CRV, MKR, Avax, DYDX 12. NFT sector: BLUR, DYDX, L0OKS, DEGO 13. Modular plates: TIA, MANTA, DYM, ALT 14. Sports section: CHZ, SANT0S, POR, CITY, 0G# Bitcoin digital currency

Software Engineer: Anchoring AI on Public Blockchains Aids in Establishing a ‘Permanent Provenance Trail' With artificial intelligence (AI) seemingly destined to become central to everyday digital applications and services, anchoring AI models on public blockchains potentially helps to “establish a permanent provenance trail,” asserted Michael Heinrich, CEO of 0G Labs. According to Heinrich, such a provenance trail enables “ex-post or real-time monitoring analysis” to detect any tampering, injection of bias, or use of problematic data during AI model training.#BTC #ContentStar #比特币 #ETH

GM CT Real progress is often quiet at the start. @0G_labs is focusing on the core parts that matter ,building the base layer for decentralized AI without all the noise. Laying strong infrastructure is not the loudest job, but it is what makes everything else possible later. When the foundation is right, builders can create with more freedom and less friction. The results may take time, but strong systems always speak for themselves.

pov: you bought the dip in zero gravity. 🐸

For many people, blockchain and AI still seem like two concepts hanging in the air, far from reality. It wasn't until I started paying close attention to the progress of 0G Labs, especially as I saw it gradually advancing the mainnet process and attracting infrastructure providers like QuickNode and Thirdweb to participate in ecosystem development, that I realized this is not just a narrative at the vision level, but a serious technical foundation being built. @0G_labs impresses me the most because from the very beginning, it did not position itself as a traditional public chain, but designed its structure around the real needs of AI. It breaks down storage, computation, and data availability into independent modules, like building blocks, allowing developers to freely combine them based on application requirements. The significance of this design will be continuously amplified in practice. In the past, developers often had to passively accept the rules and cost structures set by cloud service providers. Now, they are beginning to gain more initiative, able to deploy and run AI applications on an open network. This change brings not only efficiency improvements but also a shift in power dynamics. My personal biggest feeling is that AI is gradually transforming from products owned by a few companies into infrastructure that anyone can access and use. Perhaps we are still in the early stages, but as more developers enter this ecosystem, true innovation often occurs naturally in such an open environment. That’s also why I continue to follow 0G, because it’s not just building a chain, but trying to redefine what kind of network AI should run on. @Galxe @GalxeQuest @easydotfunX @wallchain