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In-depth analysis of the Irys project and the revolution in data storage Seeing the Irys project reminds me of the confusion I had when I first entered the industry regarding blockchain storage. At that time, I always thought that storage was just storage, and execution was just execution. Why make it so complicated? It wasn't until I actually started working on projects that I realized how painful data silos can be. When you write smart contracts on Ethereum, but the data has to be stored on IPFS or Arweave, the delays in calls, verification costs, and development complexity can give you a headache. Not to mention those confirmation times that can take dozens of seconds; the user experience is simply a disaster. The emergence of Irys has shown me a whole new possibility. 1. Irys's innovation and technical logic Redefining the rules of the data storage game Irys is not just another storage project; it is the first true "programmable data chain." What does that mean? It means that data is no longer static but can directly trigger the execution of smart contracts as an active component. Imagine this: you upload an AI training dataset to Irys while embedding copyright rules, access controls, and even automatic profit-sharing logic within the data. Every time someone uses this dataset, the relevant smart contracts will automatically execute, and the copyright fees will be automatically distributed to you. This is a revolutionary shift from "static resources" to "programmable assets." The deep logic of technological innovation The core innovation of Irys lies in the Matrix Packing proof system. Simply put, it divides each 16 TB data partition into 256 small blocks, and miners must add a unique "salt" fingerprint for each block. This design is incredibly clever: Preventing data forgery: Miners cannot simply copy others' data to deceive the system. Parallel verification: 256 blocks can be verified simultaneously rather than sequentially. Browser-friendly: Verification can be completed on ordinary devices. Compared to Filecoin's verification time, which can take hours, Irys achieves millisecond-level confirmations. This difference in experience is a qualitative leap. The ambition of a multi-ledger architecture What excites me even more is Irys's multi-ledger design: Submit Ledger (temporary storage) Publish Ledger (permanent storage) Future industry-specific ledgers This means that the healthcare industry can have encrypted storage ledgers that comply with HIPAA, the financial industry can have audit-trail ledgers that meet SEC requirements, and the AI industry can have storage ledgers specifically optimized for large model datasets. Each industry can customize its own data governance rules, and this flexibility is something other storage projects can only dream of. 2. Economic model, pricing strategy, and application scenarios The precise design of the economic model Irys's 50% token burn mechanism is not for speculation but to solve the fundamental problem of storage projects: miner sell-off pressure. Traditional model: Users pay → All goes to miners → Miners sell off → Token devaluation Irys model: Users pay → 50% burn + 50% to miners → Deflationary spiral → Token appreciation This creates a positive feedback loop: More data → More burn → Tokens become scarcer → Miners earn more → Network becomes more secure. The killer pricing strategy for enterprise-level Irys's pricing strategy directly targets enterprise pain points: Permanent storage: $0.05/GB (16 times cheaper than Arweave) Temporary storage: $2.50/TB/month (cheaper than Filecoin but more predictable) Small files free: Uploads under 100 KB are completely free Cost predictability is crucial for enterprise clients. No one wants to use a storage service that costs $1 today and $10 tomorrow. Deep layout in the AI field Irys's ambitions in the AI field go far beyond just storing data. They aim to become the infrastructure of the AI economy: Currently, there are agent economy platforms like GoKiteAI using Irys, allowing AI to read and write data directly. In the future, it may achieve: Automatic allocation of copyright for AI training data Incremental updates for model weights storage Traceability verification for AI-generated content Imagine how many times the operational efficiency of the entire AI economy would increase when AI models can directly purchase training data from Irys and automatically pay copyright fees. 3. Investment logic and practical implementation Reconstructing investment logic Do not view Irys as just a storage project; the correct understanding is that Irys is the infrastructure of the Web3 era, just like AWS is to Web2. If Irys truly becomes the "on-chain AWS," benchmarking AWS's current market value of $1.6 trillion, even capturing 1% of the market share would be a $16 billion project. Moreover, Irys has just completed a $10 million Series A funding round, bringing the total funding to $20 million, with investors including top institutions like CoinFund and Hypersphere. The network has already processed over 600 million data transactions and has 4 million daily active wallets. This data tells us that Irys is not a conceptual project but a mature protocol with real use cases and a user base. When data transforms from static resources to programmable assets, the entire imagination space of Web3 will be completely opened up. This is the "data revolution" that truly deserves attention. @irys_xyz @cn_irys_xyz

Arweave or IPFS? 🤔 Both decentralize storage 🌐 Both reduce reliance on centralized servers 🌐 Both use content addressing But their approaches, and outcomes, are very different 👀

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