Arweave (AR)

#AR $AR Stop loss in red with exit on 4-hour candle close https://t.co/P2SV4izK7r

@Laxmanfi sniped long in #ARUSDT Thank you Sir for your valuable Live sessions❤️ https://t.co/bf8wnFArEh

$AR | #AR Support with a stable upward trend line above it is positive 📈 https://t.co/krZ931r1Nu

I posted about @WalrusProtocol 2 weeks back. While drafting that, I came across a research paper they dropped in April. Finally sat down with it. TL;DR ↓ • Every decentralized storage network has the same problem: How do you keep data safe without making 25 copies of everything? • Arweave: Just make 25 copies. Safe, expensive. • Storj/Sia: chop files into pieces, 3 copies worth. Cheap, but if a node dies you have to download the whole file to rebuild its piece. Brutal at scale. • Walrus: 4.5 copies worth, but when a node dies, the replacement only downloads a tiny fraction of the file to rebuild what was lost. • Imagine the file as a grid instead of a list. Each node holds one row and one column. Lose a node and the new node grabs one cell from each surviving node, enough to mathematically reconstruct the missing row and column. When storage nodes swap in or out, most protocols pause writes during the handoff. Walrus doesn't. New writes go to the new nodes, old reads stay with the old. Every file is

Imagine an AI agent kept a diary: Monday: "Started new project with user. Seems cool." Tuesday: "Started new project with user. Seems cool." Wednesday: "Started new project with user. Seems cool." This is how most production AI agents work today: no real memory between sessions, no awareness that you’ve talked before. @WalrusProtocol spent its first year on mainnet fixing this. Here's a quick TL;DR of their progress ↓ 1. What got built in 12 months → 510+ TB stored (passed Arweave's 385 TB inside a year) → 200+ projects building on it → 2nd-largest decentralized storage protocol by volume → Core research paper accepted at ACM CCS 2026, a rare academic stamp for any blockchain project → Zero downtime since day one The interesting stuff is what they built on top of it. Seal → Lets you encrypt data and control who can read it, enforced onchain. Made Walrus usable for healthcare records, financial data, and private AI datasets that can't sit on a public network. Quilt → Bundles small files together to ma

$AR If it holds support, there is a path to the upper resistance; it should be monitored. https://t.co/2jYRNiIBJ8

Some smart ppl on my tl been bullish on #DeSci and PoUW narratives recently. Spent some time digging deeper and I think DeSci x Proof of Useful Work (PoUW) might be one of the few setups where crypto actually pays for real output instead of just incentives. Why? PoUW is trying to turn energy + GPUs into useful output like AI training, molecular simulation, protein folding, ZK optimization, or biomedical research. Right now, AI infra is eating capex. Big tech is racing for the best models, locking up GPU supply. AI compute is scarce, expensive, and very real. But most workloads aren’t training frontier models. They’re inference, fine-tuning, simulations, scientific compute… stuff that doesn’t need perfect clusters. That kind of compute can run on fragmented, idle, or lower-tier GPUs. So why is crypto still mostly paying people to farm points instead of paying networks to run useful workloads? DeSci might be the first crypto-native buyer class that makes PoUW make sense. Because DeSci needs compute, d