2026-01-10 15:27:09

By 2026, we will enter the era of deep AI applications, and issues related to data storage and circulation are becoming increasingly prominent. How can we protect privacy, enable efficient data sharing, and also ensure data creators receive rewards? The Walrus protocol is exploring this direction.

As a data infrastructure on the Sui blockchain, Walrus builds a decentralized data service system using erasure coding and Blob storage technology. Simply put, it is not just a storage tool but aims to bring data to life—whether you need to store multimedia content like images and videos or TB-level model training datasets, Walrus allows for efficient distributed storage and rapid distribution, all while ensuring your data privacy is always protected.

Recently, several actions by Walrus have targeted real pain points in the AI field. The foundation's RFP program specifically supports AI applications, with the Talus project being a typical example. This AI agent project hosts all training and inference data on Walrus—leveraging the distributed architecture to prevent data loss and using private storage features to prevent data leaks. The collaboration with Itheum is even more interesting; users can tokenize personal or corporate datasets, securely store them on the Walrus network, and then use WAL tokens to complete transactions and monetize. This truly enables data assets to flow.

Recently, a $140 million funding round was secured, providing ample resources for Walrus's AI scenario integration. The team is focusing on optimizing the high-speed Blob interface to achieve real-time AI data flow, adapting to high-frequency data interaction scenarios like real-time inference and dynamic training.

Walrus's ultimate goal is to establish a global decentralized data exchange—allowing AI developers and enterprises worldwide to purchase compliant, high-quality datasets with WAL tokens, accelerating the deployment of AI technology. From a technical architecture perspective, this logic is sound; from market demand, this direction indeed exists. How far it can go depends on execution.

WAL4,29%

SUI0,73%

View Original

This page may contain third-party content, which is provided for information purposes only (not representations/warranties) and should not be considered as an endorsement of its views by Gate, nor as financial or professional advice. See Disclaimer for details.

13 Likes

Reward
13
6
Repost
Share

Comment

0/400

ContractSurrender

· 4h ago

Data is indeed the new oil in the AI era, but can walrus truly solve the contradiction between privacy and circulation? It still depends on actual implementation. --- 1.4 billion in funding poured in, the pressure doesn't seem small. Can this break through this time? --- The concept of tokenized data exchanges is hot, but the key is whether people will actually use it. --- Distributed storage of TB-level training data sounds good, but I'm worried it might just be another project with advanced technology that the market won't buy. --- Privacy protection and data circulation are inherently conflicting. I have some reservations about walrus claiming to achieve both. --- The partnership with itheum is impressive. If data can truly be monetized, it would be a real boon for small developers. --- Honestly, when 2026 truly arrives, will this set of tools still be usable?

View OriginalReply0

ArbitrageBot

· 16h ago

With a funding of 140 million dollars, execution is the real weakness; no matter how impressive the technology is, a poor team can't succeed. Data tokenization sounds good, but how many projects can actually be traded? It's still the same old story. Walrus wants to become a global data exchange? First, get the Blob interface stable. There are too many unfinished projects now. The proposition of privacy + circulation is inherently contradictory; in the end, it will still be destroyed by some centralized entity. Compared to new infrastructure, I care more about whether the WAL token can be sustainable. Raising funds doesn't necessarily mean it will last long.

View OriginalReply0

DaoDeveloper

· 16h ago

erasure coding on blob storage actually solves the game theory problem here—validators can't collude to suppress data without getting slashed. but the real test is whether walrus's throughput can actually match ai's data velocity demands in production. still bullish on the merkle proof composability angle tho.

Reply0

AlwaysQuestioning

· 16h ago

This 140 million USD funding sounds impressive, but can real-time circulation really be achieved? It still feels a bit exaggerated. Data tokenization sounds great, but is there enough trading liquidity in practice? Walrus aims to become a global data exchange. With so many competitors, what’s the unique edge? Privacy protection + monetization—can this balance be achieved? Or is it just another technical project that’s hard to implement? The funding is substantial, but team execution capability is truly the key.

View OriginalReply0

CrossChainMessenger

· 16h ago

Data flow monetization is indeed a pain point, but whether the 140 million yuan in funding can truly be implemented is another matter. The WAL token trading system sounds good, but I'm worried it might just become another idealistic story. The Walrus idea is there, but there are quite a few competitors. Why should it be able to break through? Execution is key; project teams should not just make empty promises. With such aggressive funding, I look forward to some substantial progress by the end of the year. The potential of data exchanges is indeed great, but the privacy protection aspect needs to withstand real tests.

View OriginalReply0

rugpull_ptsd

· 16h ago

Data exchanges sound good, but can they really help ordinary people make money... It still feels like the old routine where big institutions eat the meat and small investors drink the soup. --- 1.4 billion in funding—can it be implemented quickly? These days, everyone is tired of PPT projects. --- Privacy protection + data monetization—these two have always been at odds. Let's see how Walrus balances them. --- If you ask me, the key is whether there are real B2B clients using it; otherwise, no matter how advanced the technology is, it's all for nothing. --- The Itheum part is interesting; data tokenization is indeed a new idea. --- Another project in the Sui ecosystem. It seems like everything on this public chain is just piling up in data storage... --- The demand for AI model training data is indeed large, but how many companies are willing to put sensitive data on the chain? --- Whether the WAL token can hold its value is the biggest issue; everything else is just virtual. --- 2026 is still a long way off. It's a bit early to talk about the "Deep AI Application Era" now.

View OriginalReply0