Arweave (AR)

The Regulatory Inevitability: zkML is necessary, but not sufficient AI regulation has moved into enforcement. Audit trails are becoming a legal obligation. zkML solves the part we’ve discussed many times: ▸ proving that model X actually produced output Y ▸ no trust required, no “internal testing” assumptions But compliance isn’t judged by blocks or sprints. It’s judged across lifecycles 5, 7, even 10 years after deployment. A proof that’s correct at inference time can still be deleted, altered, or lost in cloud infrastructure. → legally, that’s still a compliance failure. That’s why audit trails must be stored as permanent records: one-time write, no rollback, no operator dependency, on Arweave. zkML proves correctness. Permanent storage proves survivability. Without both, AI doesn’t stand up to regulators. That’s why @inference_labs built a full stack from day one: verifiable execution + permanent memory. It’s the condition for AI to remain permissible in a regulatory world.

JUST IN: Arweave just removed sequencers, mempools, and relayers—AO compute lets agents persist with fork-resistant logic and composable memory. It’s not cloud compute, it’s sovereign cognition baked into the chain. Who builds AI-native apps here first? https://t.co/cpIJXx8ltb

JUST IN: Arweave just erased sequencers, mempools, and relayers—AO compute anchors live, fork-resistant agent logic. It’s persistent execution backed by permanent data. Who builds full AI-native dapps on this first? https://t.co/SSQAYy8lZt

🧑‍💻 OGAudit Web3 Research 📢Introducing @ArweaveEco a decentralized storage network that operates as a collectively owned hard drive, aptly named "the permaweb," aiming to create a permanent, decentralized web. Category: Decentralised Storage Ticker: $AR Market Cap: $228M Rank: 250 OG Score: 58.54/100 Reviewed by 6 OGs. More info: https://t.co/mXIMVTDwRe

$AR- lost the key level, retest and dump https://t.co/igOYKscjPG

JUST IN: Arweave just killed off sequencers, mempools, and offchain relayers with AO compute. Autonomous agents now execute in a fork-resistant, deterministic layer—real-time compute, no trust gap. Who codes the first full AI dapp here? https://t.co/KPgSaz20At

GM I spent the weekend spinning up JSTprove on the Omron Incentivized Testnet and routing a tiny classifier through DSperse. I generated a proof, watched it get anchored to Arweave, and independently verified the receipt. DSperse splitting compute and JSTprove proving only key outputs makes #zkML feel practical, fast, and auditable in ways I didn’t expect after reading papers. If you care about production trust in AI, follow @inference_labs they already show real scale with public proof volume in the hundreds of millions and a working incentivized testnet. TL;DR: provable inferences, permanent audit trail, real infra not buzz. Anyone else running a miner or building on JSTprove yet?

JUST IN: Arweave’s new AO compute layer erases sequencers, rollups, and mempool delays. Agents run autonomously, fork-resistant by default. It’s not just decentralized storage—this is sovereign, live computation. Who builds the first truly agent-native dapp? https://t.co/EsU9cPsROG

Irys Allora Cysic Monad https://t.co/LFrnvRLVqT

JUST IN: Arweave’s AO execution layer is live—no mempools, no sequencers, no offchain logic. Autonomous processes persist forever, resistant to forks by design. This isn’t another rollup—it’s compute reimagined. Who builds agents on it first? https://t.co/kA3fFMYPps