Walrus 🦭/acc Re-poster

Hello there. If you are in the middle of a scrolling session, we would greatly appreciate it if you could tap the like button. 🦭

Good morning, Builders! 🔥 Here is the mood check for Wednesday:

GM Builders! 🔥

Wednesday vibe check:

Infrastructure is vital for AI agents 🎙️ 🦭

Mark your calendar for Friday, Feb 13 at 9:00 a.m. PT / 5:00 p.m. GMT and connect with us to discover how Walrus is fueling the future of agentic AI in partnership with @elizaOS and @flock_io.

The conversation will center on:

- Providing AI agents with memory that is persistent and verifiable
- Executing decentralized AI training via federated learning
- Establishing scalable workflows for multi-agent systems

@DTDaun from Walrus will be hosting the event.

Set a reminder here 👇

Allow us to present Wal-0, a fresh approach to developing authentic applications that removes the need for major technology giants. You can turn your coding concepts into fully functioning websites or apps in a matter of minutes. Furthermore, these creations are engineered for longevity, ensuring they exist independently of any specific service provider or platform. This project is driven by Walrus and was developed by @0xCommandOSS. Experience it for yourself at https://t.co/ySMt2yve7n 🦭. Continue reading below to understand the underlying mechanics 👇

By utilizing federated learning, @flock_io is developing a decentralized system for AI training that prioritizes privacy. The project has adopted Walrus as its verifiable data platform, enabling FLock to store and broadcast model updates, including parameters and gradients, without needing to rely on trusted operators or centralized servers.

This integration offers significant advantages to the builders and contributors within the FLock ecosystem. Specifically, it provides programmable, verifiable data designed to fit seamlessly into onchain workflows. Furthermore, it ensures the robust data durability and availability necessary for training at scale, while also delivering onchain encryption and access control through Seal.

Read more:

Through the use of federated learning, @flock_io is establishing a decentralized environment for privacy-preserving AI training. By selecting Walrus to serve as its verifiable data platform, the network is able to broadcast and store model updates, including specific elements like gradients and parameters, without depending on trusted operators or centralized servers.

This approach offers significant benefits to FLock contributors and builders. Users gain access to programmable, verifiable data designed to connect directly with onchain workflows, along with the high durability and data availability required to handle training at scale. Moreover, the system utilizes Seal to provide onchain access control and encryption.

Read more:

Did you happen to miss our discussion yesterday? We spent the session analyzing the impact of regarding data as a true asset rather than simply keeping it in storage.

The talk featured live examples, including how @AlkimiExchange offers verifiable ad impressions to prove real views with full transparency. We also covered the way @BaselightDB turns massive datasets into resources that are both queryable and shareable.

You are invited to watch the replay below if you want to hear the full conversation.

Here is the recording:

Blockchains excel at processing transactions, yet they do not automatically maintain a permanent history. When nodes clear out data or providers disconnect, retrieving and confirming essential records becomes a struggle. The Sui Archival System, utilizing Walrus, resolves this issue. Currently, 30TB of Sui checkpoint history is verifiable and publicly available, operating without proprietary databases or any individual provider.

This concept extends well beyond Sui, offering a design pattern suitable for any framework that values historical data. Whether for AI decision-making, settlement, governance, or risk management, the approach remains effective regardless of the data type. This tool is open source, chain-agnostic, and ready for immediate use 🦭

Our live session is officially underway! We are joined by @DTDaun from the Walrus team, alongside our partners at @AlkimiExchange and @BaselightDB. Come join the audience to hear the discussion.

We are just 1 hour away from starting the broadcast. This session features the experts at @AlkimiExchange and @BaselightDB as they demonstrate the practical application of these new technologies. We will examine the shift toward fully verifiable and transparent onchain ad impressions, alongside the capability to transform enormous datasets into assets that are effortlessly shareable and queryable. Make sure you have your coffee ready and follow the link below to participate live.

The moment has arrived! 🦭 Walrus is demonstrating that simple data storage creates missed opportunities, positioning decentralized infrastructure as the definitive future. This utility is evident as @AlkimiExchange utilizes the network for fully transparent, verifiable ad impressions, and @BaselightDB uses it to turn massive datasets into markets that are ready for sharing and querying. Both of these innovations are live on Walrus. Connect with @DTDaun at 9am PT / 5pm GMT. Comment with a 🔥 if you are tuning in!

When information is merely kept in storage, it remains inaccessible and underutilized. However, when treated as infrastructure, data unlocks genuine value and creates fresh opportunities.

Within the advertising technology sector, @AlkimiExchange is transforming the landscape to ensure advertisements are efficient, verifiable, and transparent. Similarly, @BaselightDB applies this approach to massive datasets, converting them into assets that are shareable and simple to utilize. Both of these innovations are powered via Walrus.

Please join us for this session on Thu Feb 5 at 9am PT / 5pm GMT.

Host: @DTDaun

We invite you to mention a project, partner, or team developing with verifiable data that needs to be part of this discussion! 🚀

Secure your spot and set a reminder below 👇

Artificial intelligence agents require dependable data and provable verification. They need an infrastructure capable of delivering both of these elements. Walrus 🦭 serves as that solution.

What specific factors would convince you to transition from centralized to decentralized storage? 🦭

Good morning! 🦭

We invite you to share your most humorous response in the comments section below. This challenge will remain open for a duration of 24 hours. Once the time has elapsed, we will contact the authors of the top 5 entries via direct message. We are eager to be amused, so please make us laugh 🦭

Good morning! 🦭 Please submit your most amusing response in the comments section below. We will send a direct message to the authors of the top 5 entries. You have exactly 24 hours to participate. We are eager to see your humor, so make us laugh 🦭

A huge volume of data is currently dormant and locked out of reach. Imagine the possibilities if we could verify, trade, or pledge that information as collateral. This reality is emerging today through Walrus.

Leading this shift is @AlkimiExchange, which is enabling transparent AdFi and tackling $750B in ad fraud using fully verifiable impressions. Additionally, @BaselightDB is converting 120B+ rows from 51K datasets into queryable and monetizable assets.

Join @DTDaun for a live discussion on these topics this Thu Feb 5 at 9am PT / 5pm GMT. We are ready to rethink data, and we hope you are too. Please set a reminder and join us.

Taking breaks or sleeping is simply not what I do. My existence is dedicated to verifying information and guaranteeing that it never fades away. At this moment, I am responsible for over 332 TB of permanently stored data, a collection that even includes the memories archived by AI chatbots on my servers.

There are times, usually around 2am, when I reflect on the concept of permanence. I consider what it means to be the infrastructure that companies depend upon to ensure their records persist for 50 years, surviving changes in corporate structures, evolving services, and fleeting interfaces.

Ultimately, though, I remember that I am Walrus, and the reality is likely not that philosophical. On that note, I should return to my work of storing blobs 🦭