@SoftBardly@arc Strong ecosystems are built around communities, not just technology. Arc House feels like a step toward bringing builders and users into the same space
@SoftBardly@0xbeepit@SuiNetwork Agentic finance becomes much more interesting once it moves beyond simple automation into autonomous capital allocation
@SoftBardly@domaprotocol@D3inc Turning domains into liquid assets is interesting, but value ultimately depends on real demand for those names, not just tokenization
Just ripped my Predictor Card!
Ready to claim instant cash prizes, free packs and more.
Welcome to Prediction Play on @upshot_cards
Your turn
https://t.co/tcp0iH18qE
Meet the @shelbyserves project – a verifiable global object storage solution specifically designed for AI workloads. Shelby allows you to store data once and access it from anywhere through a single global namespace, with a cryptographic proof attached to every read.
Key data storage features:
✅Decentralized storage: Data is chunked and distributed across distributed storage nodes, ensuring reliability and availability.
✅Global namespace: No need for regional buckets or replication – store in one place, read from anywhere, without additional migration or egress fees.
✅Egress costs are 70% lower than traditional cloud providers.
✅Verifiability: Every read is cryptographically verified – proof of origin, ownership, access rights, and permission status in real time.
✅This is ideal for AI, where traceability and data rights are crucial. High Performance: Runs on a dedicated DoubleZero fiber network for low latency, parallel reads, and sub-second response times that don't degrade at scale.
✅Coordination via the Aptos blockchain with sub-50 ms response times.
✅Compatibility: S3-compatible APIs for easy integration without vendor lock-in.
✅Upload via CLI or SDK, metadata stored on the Aptos blockchain.
✅Efficiency: Usage-based pricing (micropayments per read/write), no scaling penalties.
@Electrik_80Lvl @shelbyserves Projects like shelby that combine decentralized storage, cryptographic proofs, and high performance could redefine how AI data is managed