walrus

Walrus wird jetzt als Datenschicht für Myriad fungieren. Dieser Schritt wurde unternommen, um Vorhersagemärkte offener und vertrauenswürdiger zu gestalten.
Myriad ist eine Web3-Vorhersagemarkt-Plattform. Sie ermöglicht es den Menschen, Ideen, Nachrichten und zukünftige Ergebnisse in Echtzeit zu handeln. Benutzer können an Märkten teilnehmen, die auf aktuellen Ereignissen und gemeinsamen Ansichten basieren. Das Ziel von Myriad ist es, den Menschen zu ermöglichen, echte Informationen zu nutzen, um bessere Entscheidungen zu treffen.
Walrus ist bekannt dafür, Daten on-chain in einer Weise zu speichern, die jeder überprüfen kann. Vor dieser Partnerschaft arbeitete Walrus bereits mit Decrypt. Die Inhalte von Decrypt wurden on-chain gespeichert, damit die Leser bestätigen konnten, dass sie echt und unverändert waren. Jetzt baut Myriad auf dieser Arbeit auf. Es wird Walrus nutzen, um Marktdaten, Nachrichten und Ergebnisse auf klare und offene Weise zu speichern.

When someone first called Walrus “boring,” I took it as a compliment. In crypto, boring usually means reliable. For years, decentralized storage has existed in an awkward middle ground—important in theory, but not trusted enough to build critical systems on. Data often lived off-chain, behind gateways or on semi-temporary servers, and the industry somehow accepted that as normal. My first impression of Walrus wasn’t hype or skepticism—it was curiosity. The more I studied it, the more its restraint felt deliberate rather than cautious.

Walrus starts with a simple, often unspoken premise: decentralized applications already rely on huge amounts of data. Ignoring that has weakened systems, not purified them. Instead of forcing everything on-chain or overloading loosely incentivized networks, Walrus defines a focused role: making large data objects reliably available over long periods, under adversarial conditions, without trusting a single party. No grandiose promises, no cost competition with hyperscale clouds—just durability, retrievability, and accountability.

Walrus works hand-in-hand with Sui, a platform designed for complex, state-heavy, and parallel applications. Where Sui expects objects to change and execute concurrently, Walrus ensures that data persists independently of any single actor. Availability is embedded into the same trust boundaries developers already rely on. This isn’t exclusivity—it’s coherence. Systems fail less when components are built to anticipate each other.

Technically, Walrus doesn’t reinvent the wheel. It uses erasure coding to split large files into fragments and distributes them across a decentralized network. The innovation isn’t novelty—it’s acceptance. Nodes will go offline, some will underperform, and network churn is expected. As long as enough fragments remain, data is recoverable. The system degrades gracefully instead of collapsing catastrophically—a principle borrowed from mature engineering disciplines but rare in crypto, where ideal conditions are often assumed.

Walrus also enforces reliability in a clear, pragmatic way. The WAL token isn’t for speculation or governance pageantry. It’s a tool for accountability. Storage providers stake WAL, earn rewards for serving data correctly, and get penalized for failures. The incentives are simple: deliver data, get paid; fail, lose stake. No social games, no relying on altruism—just rational, economically enforced behavior.

Having observed infrastructure projects stumble for years, I’ve learned to be wary of flexibility without limits. Ambiguity kills reliability. Walrus deliberately narrows its promises so it can deliver on them. That mindset reflects mature engineering culture more than speculative marketing hype.

Looking forward, the questions aren’t about the need for decentralized storage—they already exist—but about scalability and discipline. Can incentives remain balanced as the network grows? Will operators stay committed through bear markets? Can decentralization hold as demand rises? Walrus doesn’t pretend to have all the answers—it structures the system so these challenges can be met without redesigning everything.

In the broader landscape, Walrus navigates the trilemma of availability, decentralization, and cost with clarity. Availability comes first. Decentralization is enforced economically. Cost is managed, not obsessively minimized. It’s not perfect for purists, but it aligns with real-world application needs.

The early signs are promising. Within the Sui ecosystem, builders increasingly assume persistent storage rather than designing around its absence. That subtle shift, visible in architecture diagrams and product decisions, is the hallmark of infrastructure moving from novelty to necessity.

No system is guaranteed to succeed in crypto. Markets are cyclical, incentives get tested, usage fluctuates, and competitors appear. But Walrus has something rare: alignment between promises and capability. It works now, within clear boundaries, without relying on speculative future upgrades.

Ultimately, Walrus feels less like a flashy breakthrough and more like a correction—a reminder that decentralization without reliable memory is incomplete. By focusing on the unglamorous work of keeping data available, Walrus proves that meaningful progress doesn’t always look like speed or scale. Sometimes it looks like fewer assumptions, clearer incentives, and systems that just keep running when no one is watching. And that kind of progress is often the kind that endures.

@Walrus 🦭/acc #walrus $WAL

ecosystem during an RWA hackathon. At that time Sui had another hackathon running. Even though the schedule was tight and I had never written Move before I decided to join anyway.
The hackathon ran from November sixth to November twenty third in twenty twenty five. It was fully online and open to teams from all over the world. The deadline was first set for November sixteenth and later extended by one more week which helped a lot.
Walrus is a decentralized data storage tool built in the Sui ecosystem. It is one of several core tools together with Seal zkLogin and Nautilus. Sui is still a young chain but its base layer is solid. There are not many applications yet which makes it interesting for builders.
One important thing is that this hackathon did not force teams to use Walrus. There were different tracks to choose from. Even though Walrus and Seal come from Sui they can also work with other blockchains. You still need some basic Sui knowledge but not much. I spent a few hours reading the documents and that was enough to get started.
This was my first fully online hackathon. In the past I usually joined with a team that was prepared in advance and we worked together on site for a few days. This time the hackathon had already started when I looked for teammates. The idea came from discussions with a teammate who has an accounting background. I was the only one with Web3 experience in the team.
The problem we wanted to solve was earn out agreements in mergers and acquisitions. In simple words a buyer does not want to pay the full amount at once because they worry the seller may stop performing after the deal. Part of the payment is delayed and only released if certain goals are met. This is a trust problem.
We decided to use blockchain to reduce this trust issue. We combined Walrus and Seal to build a system where only related parties can see sensitive data. These roles are buyer seller and auditor. The reason to use blockchain is to make the data impossible to change.
Walrus stores the data and Seal handles encryption and access control. We deployed a main contract on Sui and created a deal object for each case. The buyer uploads encrypted files to Walrus. Anyone can download them but only approved roles can decrypt them through Seal.
The rest of the system like auditing and goal checks was simple. I thought about using Nautilus to prove the calculation process but it could not guarantee the input data was correct so we dropped that idea.
We finished the project in about one week with help from an experienced Web2 frontend engineer. This was the most complete project I have ever submitted in a hackathon. There were two hundred seventy nine projects in total and only a small number of winners.
This was my first Sui hackathon. I learned how to write Move contracts and how to use tools in the ecosystem. That alone made the experience worth it. Now I will wait for the results and share an update later.
#walrus @Walrus 🦭/acc $WAL

From the early days of the internet to the rise of Web2 and now the new age of Web3 and artificial intelligence technology has always moved forward through builders and creators. Hackathons have played a key role in this journey by giving developers a space to test ideas learn fast and build real products. Today a new chapter begins as the Walrus Haulout 2025 Global Hackathon officially starts.
Walrus Haulout 2025 invites developers from around the world who are curious about the Web3 data layer. The event offers a global stage strong technical support and generous rewards. Everything is ready for builders who want to turn ideas into working solutions.
Walrus is the core technology behind this hackathon. It is a decentralized storage and data availability protocol designed for large binary files. Walrus allows low cost storage of unstructured content while keeping data available and reliable even during attacks or failures. This makes it a strong foundation for next generation applications.
Walrus works by splitting data into multiple pieces and storing them across distributed nodes. Even if some nodes fail the data can still be accessed without disruption. Walrus is deeply integrated with the Sui ecosystem which allows developers to interact with data easily through simple tools. Smart contracts on Sui are used to verify data availability and validity which adds another layer of trust and security.
Beyond one ecosystem Walrus also supports multiple blockchains. This makes it easier for developers to build applications that work across chains and unlock new data driven business models. The goal of Walrus is simple. Let data move freely securely and with trust while creating real value for users.
The Walrus Haulout 2025 Hackathon is designed as the first major exploration of this new data world. Developers are encouraged to build and experiment on this open foundation.
The hackathon features four main tracks. The first track focuses on data economy and markets where builders can create decentralized data marketplaces with clear ownership pricing and incentives. The second track explores the connection between artificial intelligence and onchain data to power smarter applications and systems. The third track centers on verifiable authenticity including media verification and data trust solutions. The fourth track focuses on privacy and security using advanced tools to protect users and their data.
Each track will reward the top three projects with cash prizes and there are additional awards for outstanding technical execution. The total prize pool exceeds one hundred thousand dollars.
Participants can join as individuals or teams by registering on the official platform and submitting their projects before the deadline. Projects usually include code a demo and clear documentation.
Community support is also a key part of this event. Builders will have access to learning materials discussion groups live online sessions and extra community rewards. This support helps participants learn faster connect with others and improve their chances of success.
Walrus Haulout 2025 is more than a competition. It is an opportunity to build practical tools explore new ideas and shape the future of decentralized data. Developers who join today may help define how data is stored shared and trusted tomorrow.
#walrus @Walrus 🦭/acc $WAL

KI-Agenten sind Systeme, die eigenständig arbeiten und Aufgaben Schritt für Schritt erledigen können.
Dieser Artikel erklärt, wie sie funktionieren und warum sie gemeinsame Datensysteme benötigen, um zu wachsen.
Viele Menschen fühlen sich frustriert, wenn sie normale KI-Helfer verwenden.
Sie können eine KI bitten, Verkaufsdateien vom letzten Jahr zu finden und sie mit diesem Jahr zu vergleichen.
Die Aufgabe klingt einfach.
Aber die KI findet oft falsche Dateien oder verpasst wichtige Details.
Sie müssen weiterhin die Dateien lesen, Zahlen überprüfen und die Ergebnisse selbst ziehen.
KI-Agenten arbeiten auf eine andere Weise.
Sie suchen nicht nur Informationen.

@Walrus 🦭/acc In der schnelllebigen Welt der Krypto wird die Aufmerksamkeit oft von den Projekten monopolisiert, die die lautesten Schlagzeilen machen. Token-Pumps, trendende Narrative und virale Starts dominieren den Diskurs, während die grundlegende Arbeit, die das Ökosystem stützt, oft unbemerkt bleibt. Das Walrus-Protokoll $WAL existiert genau in diesem ruhigeren Bereich. Auf den ersten Blick mag es wie ein weiteres Infrastruktur-Token erscheinen, aber sein Anspruch ist subtiler und weitreichender: Es zielt darauf ab, das persistente Problem der Datenverfügbarkeit in dezentralen Netzwerken zu lösen und ermöglicht es Web3-Anwendungen, ohne die Sicherheit, Überprüfbarkeit oder Persistenz zu opfern, zu skalieren. In gewissem Sinne baut Walrus das Gedächtnis der dezentralen Welt auf – eine Schicht, die oft unsichtbar bleibt, aber für jede Transaktion, jeden Vertrag und jede Interaktion, die folgt, unerlässlich ist.

Die erste Ausgabe des Hackathons zeigte Projekte, die Walrus Seal und Nautilus verwendeten, um dezentrale und überprüfbare Datenlösungen zu entwickeln.
Der Haulout Hackathon 2025 forderte die Teilnehmer heraus, Lösungen in vier Bereichen zu entwickeln: Datenökonomie und Marktplätze, KI-gesteuerte Arbeitsabläufe, überprüfbare Authentizität und Datensicherheit. Aus Hunderten von Einsendungen aus 27 Ländern stachen die Gewinnerprojekte durch ihre Innovation, technische Ausführung und das Potenzial hervor, die Zukunft der Daten zu gestalten.
In der Kategorie KI und Daten ging der erste Platz an Spectra, ein System zur Moderation von Inhalten, das schädliche Beiträge filtert und gleichzeitig die Benutzerdaten privat hält. Der zweite Platz ging an INFINITE HEROES, das Selfies in personalisierte Comicbücher mit Hilfe von KI und Walrus-Speicher verwandelt. Der dritte Platz ging an TradeArena, eine Plattform für Handelswettbewerbe mit KI, bei der alle Entscheidungen und Transaktionen auf Walrus aufgezeichnet werden.

Während neue Projekte darum wetteifern, Aufmerksamkeit durch große Versprechungen oder unreife Technologien zu erregen, erscheint Walrus (WAL) als ein ganz anderes Projekt. Es verlässt sich nicht auf vorübergehenden Lärm, sondern versucht, eine einzigartige digitale Identität zu schaffen, die den Geist der Gemeinschaft, den Spaß an Krypto und das zunehmend wichtige Konzept der Nachhaltigkeit innerhalb des dezentralen Finanzsystems verbindet.

a four point five five percent drop in the last twenty four hours The price has moved between a high of zero point one two eight nine and a low of zero point one two zero nine during this period
Trading volume for WAL is two point five two million while the equivalent in USDT is three hundred fifteen thousand one hundred seventy four The data shows that there is active trading and interest in this pair over the past day
Technical indicators suggest that WAL is in a bearish trend The moving averages show downward momentum which may continue in the short term Traders are closely watching the support level at zero point one two zero nine to see if it holds or if the price moves lower
The chart shows that sellers have been in control over the last twenty four hours The drop in price and the current trend indicate caution for those looking to enter new positions at this time
Despite the recent drop there are still opportunities for traders who follow price action and use support and resistance levels to guide decisions Watching the volume can also provide clues about potential reversals or continuation of the current trend
Overall WAL is showing weakness against USDT but the market is active The support level at zero point one two zero nine will be important in determining if the price can stabilize or if further declines are possible Traders are advised to monitor price movements and adjust strategies based on what the market shows
Keeping an eye on trends volume and key levels is essential for understanding short term movements in the WAL USDT trading pair This information helps traders make informed decisions and plan their next moves in a careful and thoughtful way
In summary WAL has seen a decline in value against USDT with the current price at zero point one two one eight The market shows a bearish trend with important support at zero point one two zero nine Monitoring price action and trading volume will be key for traders looking to navigate this market safely and effectively.
#walrus @Walrus 🦭/acc $WAL

In crypto, it’s easy to chase what’s popular. Harder to stay focused on building something that actually lasts. WAL feels like it’s choosing the second path.

Instead of reacting to every trend, the emphasis seems to be on strengthening the core — making data useful, dependable, and ready for real applications.
Projects that build this way may move quietly, but they usually move with purpose.
Just sharing a grounded take. No advice.
#WAL #Walrus $WAL @Walrus 🦭/acc

You ask an AI agent to watch flight prices for you. You give it your budget and dates. At night the price drops to the perfect level. If the agent cannot pay by itself then the chance is lost. By morning the price is higher again. In this case the agent is not very useful.
For AI agents to be truly helpful they must act at the right time. That includes making payments. This is where trust becomes very important. Once an agent can spend money it must be safe. Users must know the agent is using real data. They must know the rules are followed. They must know every action can be checked later.
Central systems are weak for this job. Logs can be changed. Data can be hidden. Systems can fail in one place and stop everything. When money is involved this risk is too high.
Walrus solves this problem by using a decentralized data system. Data stored on Walrus is verifiable. This means anyone can check that the data is real and unchanged. When an AI agent makes a payment every decision is backed by stored proof. You can later see what data the agent used and why it acted.
Walrus also makes actions easy to track. Each step taken by the agent is recorded with time proof. Spending limits rules and history are all saved. This creates a clear record of behavior. Even when many agents work together their shared memory can still be checked and trusted.
Privacy is also protected. Sensitive payment data is locked. Only approved agents can access it. Smart contracts control who sees what. This keeps user data safe while still allowing the agent to act.
Some payment systems already use Walrus as a memory layer. An AI agent can complete many purchases as one action. Either everything works or nothing does. This avoids half finished orders. All needed details like budget preferences and past choices are stored safely. Walrus holds the data and the network handles fast actions. Together they allow safe automatic payments.
The future of AI depends on trust. If people cannot trust AI with money then automation will stop. Walrus builds that trust by making data clear safe and provable. When your AI agent pays while you sleep you can later see exactly why it did so.
AI is not only about thinking anymore. It is about acting in the real economy. That future is already starting now.
#walrus @Walrus 🦭/acc $WAL

Heute ist WAL um 3,51 Prozent gestiegen und wird bei 0,1210 USDT gehandelt. Der Preis bewegt sich stetig nach oben und sieht im 15-Minuten-Chart stark aus. Die gleitenden Durchschnitte zeigen, dass MA7 und MA25 über MA99 liegen, was ein gutes Zeichen für bullischen Schwung ist.
Die wichtigen Levels, die es zu beobachten gilt, sind das 24-Stunden-Hoch bei 0,1217 und das 24-Stunden-Tief bei 0,1165. Das Handelsvolumen steigt mit 1,35 Millionen WAL, die rund 160k USDT gehandelt werden. Dies zeigt, dass viele Menschen aktiv im Markt sind und der Token die Aufmerksamkeit von Händlern und Haltern gleichermaßen erhält.

In Web3, big promises are easy to make. Solid basics are harder to build. WAL feels focused on getting those basics right — data, structure, and reliability.

When the foundation is strong, growth becomes natural. There’s less need to push narratives and more room to let real usage speak.
Projects built this way don’t rush results. They earn them.
Just a perspective. No advice.
#WAL #Walrus $WAL @Walrus 🦭/acc