Jeeya_Awan

@Dusk , wraz z NPEX, współpracuje z Quantoz Payments, aby wprowadzić EURQ na Dusk.
Siedziba Quantoz Payments znajduje się w Holandii; działa w tym samym obszarze co my – wprowadzając zarejestrowane finanse na łańcuchu. Dzięki ich infrastrukturze, płatności Quantoz są krokiem bliżej masowej akceptacji Dusk. Nie mogli znaleźć lepszego partnera! EURQ to ich cyfrowy euro, zaprojektowany w pełni zgodnie z przepisami MiCA i odpowiedni do zarejestrowanych przypadków użycia.
Dusk to jedna z trzech blockchainów, na której możesz uzyskać dostęp do EURQ, oraz jedyna zaprojektowana specjalnie do natywnego wydawania aktywów rzeczywistych świata i zgodności z przepisami od samego początku.

@Dusk jest zachwycona ogłoszeniem kluczowej współpracy z Cordial Systems, która oznacza ważny krok w kierunku zrealizowania w pełni opartego na blockchainie ekosystemu finansowego. Ta współpraca stanowi kluczowy punkt w wizji Dusk dotyczącej przyszłości finansowej opartej na łańcuchu blokowym. Szybki przyjęcie aktywów tokenizowanych przekształca rynki kapitałowe, uwalniając nowe efektywności, płynność i przejrzystość, a w Dusk jesteśmy na czele dostarczania rzeczywistych rozwiązań dla instytucji.
• Cordial Systems: Partnerzy strategiczni

@Dusk ewoluuje się w trzywarstwowy, modułowy stos, który zmniejsza koszty i czas integracji, zachowując przy tym prywatność i korzyści regulacyjne, które wyróżniają sieć. Nowa architektura umieszcza warstwę zgodności/dostępności danych/wyliczania (DuskDS) poniżej warstwy wykonania EVM (DuskEVM) oraz nadchodzącej warstwy prywatności (DuskVM).
• Dlaczego zmiana?
✓ Przyspiesza wdrażanie aplikacji.
✓ Integracje z portfelami, mostami, wymianami i dostawcami usług są szybsze dzięki standardowym narzędziom Ethereum.

Data powers everything; from our fitness trackers to the ads we see online. But have you ever think that who really controls it? Most of us never question where the data behind our newsfeeds, AI responses, and search results comes from. We simply trust it, assuming someone, somewhere is making sure it's accurate and unbiased.
But the reality is this data isn't always trustworthy or validated. Its origin remains hidden, especially in the case of AI training data, and we have no control over how it's used or who profits from it.
Right now, we have no choice but to trust centralized systems and black box processes. If we want to use these services, we must hand over control. There is no alternative - until now.
• Walrus does it differently:
On Walrus, no single entity controls where your data lives or who can access it. Your data is split up and stored across multiple independent nodes, so there’s no single point of failure. And thanks to access control provided by Seal, developers can build apps that integrate programmable data access - so you can make sure some things stay private.
But building a decentralized storage network is one thing. Keeping it decentralized as it grows is another challenge entirely.
• Solving the Paradox of Scalability:
Unfortunately, trying to achieve scalability can quietly centralize a network. Growth means you need more nodes, so nodes scale and accumulate more stake, and suddenly they have more impact on the network’s operations.
Networks don't stay decentralized on their own: it takes intentional design. Walrus was built to resist that natural tug towards centralization as it grows.
Here’s how:

1. Spreading out power:
Token holders delegate to independent storage nodes, which naturally spreads stake across multiple operators instead of concentrating it in a few giant entities. This prevents censorship by ensuring no one party controls what data gets added or removed.
2. Rewarding performance:
Nodes earn $WAL based on verifiable uptime and reliability, not on size or reputation. This means a smaller node that performs well can compete with the giants, which keeps the network decentralized.
3. Holding nodes accountable:
If nodes perform poorly or act dishonestly, they lose stake. This discourages power hoarding and makes it harder for any one node from attempting to centralize control.
4. Preventing power grabs:
Moving stake around quickly comes with penalties, which stops coordinated groups from gaming the system when it matters most; like during votes, attacks, or attempts to censor data.
5. Governing collectively:
Token holders control key parameters, so decision making stays distributed as participation grows.
• Resilience > false promises:
Decentralization is more than an ideology. It’s about building a system that is fundamentally different from what came before it – a truly distributed network that can withstand attacks, outages, and censorship.
This ethos is baked into Walrus from the ground up. By rewarding honest performance, we’ve created a system where staying decentralized makes good, economic sense, for both nodes and customers. As an organization, @Walrus 🦭/acc is committed to a future built on decentralized data - one where you control your data, verify its origins, and ultimately get to decide who profits from it.
In the end, the question isn’t about why decentralization matters, since the answer is clear. It’s about whether the systems you build on today will still be decentralized tomorrow. With #Walrus , that answer will always be yes.

Jako dostawca infrastruktury generacji następnej, Nami Cloud oferuje zgodne z S3 dezentralizowane przechowywanie danych oraz bezproblemowy dostęp do ekosystemu #Walrus e. Misją platformy jest usunięcie złożoności infrastruktury Web3, umożliwiając programistom przeniesienie się z AWS S3 lub innych dostawców chmury w ciągu kilku minut.
Ofertując wydajne przechowywanie danych zoptymalizowane pod dostępność danych w sieciach, niezawodne usługi RPC oraz uproszczone narzędzia, Nami Cloud eliminuje trudności, z jakimi programiści często się spotykają podczas tworzenia aplikacji dezentralizowanych. Programiści mogą korzystać z Nami Cloud w celu uproszczenia integracji z umowami inteligentnymi opartymi na Sui oraz z dezentralizowanym przechowywaniem danych na Walrus, zapewniając płynne działanie swoich aplikacji z zaufaniem, skalowalnością i efektywnością kosztową.

@Walrus 🦭/acc is Mysten Labs’ decentralized storage protocol. Mysten Labs is the same team that’s behind the Sui Network. Walrus’ latest partnership is with io.net (IO). This is a decentralized computing network. Together, they offer an option to save and train AI models.
That’s with IO’s Bring Your Own Model (BYOM) platform that it builds on Walrus Protocol.
• Walrus Protocol and io.net Partnership:
The partnership between Walrus Protocol and io.net offers start-ups a unique option. Besides building AI models, they can also train and run them. That happens on IOs Bring Your Own Model (BYOM) platform. IO uses Walrus Protocol to store these custom AI models. All this is decentralized and not centralized, like traditional cloud models.

This has various advantages:
✓ Start-ups or AI devs don’t have to own their own hardware or set up a data center. That’s all done for them and available to them.
✓ Traditional centralized cloud models are more expensive than this decentralized option. A great example is the pay-per-use option. In other words, you only pay for the computing power and storage you actually use. This makes it more affordable for teams with small budgets.
✓ There’s no need to use pre-approved models. Devs can build their custom models.
✓ This decentralized option has less privacy risks. Data ownership is also much more clearly defined. A decentralized option is also censorship resistant. You control your data and model instead of Google or OpenAI.
Another advantage is when potential outages happen. In mid-June, Google experienced such an outage. AWS, Cloudflare, and Firebase were also down. As a result, big parts of the internet were down. However, Walrus Protocol stayed active and didn’t experience any downtime.
IO supplies the CPUs and GPUs. It offers well over 30k GPU, on demand. On the other hand, a big company like Apple struggles to find enough GPUs to scale its AI efforts effectively. But here is IO, offering their GPU, which is 70% cheaper as well.
• Which Models Will Work Well with This Partnership?
This partnership between Walrus Protocol and io.net works best with good quality models. However, they need to be lightweight enough for a full download. To assist you with this, you can use the IO Intelligence platform. This is a free-inference platform. Inference in AI is where the AI model takes new information and makes predictions or decisions with it. It currently offers access to over 30 free and open-source models. This should get you well on your way. Here are three examples, but there are more out there. So, make sure to DYOR (do your own research).
✓ Deepseek. IO Intelligence offers four different Deepseek versions that you can use. These are reasoning models that come with variations.
✓ Qwen. This also comes in various models. Qwen also offers language models.
✓ Llama. There are also various Llama models available.
IO Intelligence also offers Google products, like Gemma, or Microsoft’s phi models. These are mostly lightweight models, so you can fully download them. Take a look and find the model that suits you best.
What all this means for Walrus is that it is now a serious hub for decentralized AI activity.
• What Else is Up with Walrus Protocol ?
So, this partnership with io.net is exciting, but Walrus Protocol has more brewing. One of its biggest achievements is its actual usage by other protocols. Currently, already 145 projects call Walrus their storage home. New projects are finding their way to Walrus all the time. But this also led to Walrus currently being at 26.7% of capacity. Out of 4.16PB (petabyte), 1.11PB is already in use. The picture below shows this usage:

Seal is another project built by Mysten Labs. It is a decentralized secrets management service. In other words, it offers privacy. You can integrate it into Walrus, but also into other storage protocols. Private data for your storage solutions.

We can also add Nautilus to this equation. This is Sui’s framework to build oracles. So, let me explain. With Seal, you can store your data securely and with privacy on Walrus. Nautilus can fetch this data for you. It utilizes Trusted Execution Environments (TEEs). These perform computations off-chain. However, verification is on-chain.
So, as we can see, Walrus Protocol keeps marching on. The new partnership with io.net opens new ways to save and train your own AI models. However, that’s not all. Walrus sees more and more projects joining. Currently, it hosts 145 projects that use 26.7% of its storage capacity.
To make full use of the Sui stack, we can also integrate Seal and Nautilus to Walrus. Respectively a privacy platform and for oracles.
#Walrus $WAL