Emiley jhon

Plasma is a Layer one blockchain built for stablecoin payments. It focuses on speed ease of use and daily value transfer. The network is made to help people send and receive stablecoins without stress or delay. Transactions are confirmed in less than one second which makes payments feel instant. This is important for real life use like shopping sending money and business payments.

Plasma supports common blockchain apps so developers can build without learning new tools. Users can send stablecoins without paying gas fees in many cases. Fees can also be paid using stablecoins which removes the need to hold other tokens. This makes the system friendly for new users and everyday activity.

Security is a core part of Plasma. The network is linked to Bitcoin to help keep it fair open and hard to control. This design helps protect users from censorship and gives more trust to the system. Plasma is built for people in regions where stablecoins are already part of daily life. It is also made for companies banks and payment services that need fast and reliable settlement.

The goal of Plasma is simple. Make stablecoin payments easy safe and open for everyone.

#Plasma @Plasma $XPL

Walrus Protocol is a project made to help people store data in a better way. Today many apps depend on data but that data often lives in places users do not control. This can feel unsafe and fragile. Walrus was built to fix this problem by giving people a decentralized place to store data that is steady and reliable.

Walrus runs on the Sui blockchain. Sui helps the network stay fast and smooth. Walrus does not put large files directly on chain. Instead it keeps important proof and rules on chain while the real data is stored across many nodes. This keeps costs low and performance high while trust stays strong.

A key idea behind Walrus is how it protects data. Files are broken into small parts and spread across many independent nodes. No single node holds everything. Even if many nodes go offline the data can still be rebuilt. This makes the network very strong and hard to break. It also helps data stay available for a long time.

Walrus is designed to heal itself. If some data parts are lost the network recreates them and spreads them again. Users do not need to worry about manual fixes. The system works quietly in the background to keep data safe.

The WAL token powers the network. People use WAL to pay for storage. Node operators stake WAL to show they act honestly. Token holders can also take part in decisions about the future of the protocol. This creates a shared system where everyone has a role and responsibility.

Walrus has already reached an important step with its mainnet launch. This means the network is live and open for real use. Developers can now build apps that depend on stable decentralized storage. This includes apps for finance art games and artificial intelligence.

The future plan for Walrus is clear. The team wants to support more blockchains and more use cases. The goal is to become a common data layer that many networks can use. Walrus also plans to support large data needs such as training data for AI and rich media for apps.

Community matters a lot for Walrus. Builders are encouraged to test create and share ideas. Tools and guides are provided to make building easy. Over time this helps the network grow in a healthy way.

Walrus is not only about technology. It is about trust and ownership. It gives people control over what they store and who can access it. In a digital world where data often feels temporary Walrus offers something lasting.

Walrus Protocol aims to be a calm and strong base for the decentralized internet. A place where data is stored with care and respect. A place people can rely on every day.

#walrus @Walrus 🦭/acc $WAL

Gata and Walrus are working together to build an open execution base for AI that is simple fair and affordable. The main goal of this partnership is to help decentralized AI grow without high data costs. Many AI projects struggle because storing and using large amounts of data is expensive. Gata uses Walrus to solve this problem and make AI easier for everyone to access.

Gata focuses on building tools for decentralized AI including model training inference and data creation. Walrus becomes the core data layer for these tools. The first product using this setup is called DataAgent. DataAgent helps people work together to create useful data for AI training. Anyone can open a browser and share unused computing power. Together users help generate synthetic data that AI systems need to learn and improve.

During data creation large files must be used many times. In most decentralized systems this leads to high storage and access costs. This makes projects hard to scale. Walrus changes this by offering fast and low cost data storage. One key benefit is that there are no download fees. This allows the Gata community to access and share data freely without worrying about sudden or unfair costs.

Walrus provides performance close to traditional cloud services while keeping a decentralized structure. Data is stored across many independent nodes instead of one place. This improves reliability and keeps the system running even if some nodes go offline. It also helps protect data from loss or control by one party.

A leader from the Walrus Foundation shared that decentralized AI has always faced one big issue which is high data cost. Teams should not have to choose between being decentralized and being affordable. With Walrus Gata can have both. This type of work is exactly what Walrus aims to support.

This partnership also marks the next phase of Gata growth. The team plans to move toward fully decentralized AI training and inference. In the future Gata wants to build a clear and open pricing model. By storing proof of computation on Walrus smart contracts can verify work and handle payments fairly. This creates trust and removes unclear pricing that is common in centralized systems.

Gata founders believe that central control over AI infrastructure increases cost and limits access. This slows down progress and keeps AI out of reach for many people. Their mission is to make AI available to all. To do this they need open execution tools and affordable data systems. Walrus helps remove the data barrier and makes this vision possible.

Today the DataAgent app is already live. It uses Walrus to support community driven data creation. This partnership is a strong step toward building a full decentralized AI system that is fair open and sustainable.

Gata and Walrus together are helping shape a future where AI is built by communities and powered by shared resources not locked behind high costs.

#walrus @Walrus 🦭/acc $WAL

When we write code we want it to feel clean and simple. Writing the same thing again and again feels like a small failure. Good code should save time and effort. Python understands this feeling very well. That is why it gives us smart tools to reduce repetition and make daily coding easier.

For a long time many beginners wrote code that worked but felt heavy. They used a long variable name then wrote the same name again on the same line. This habit wastes energy and slows learning. It also makes code longer than it needs to be. Python looked at this pattern and offered a better way.

Python has something called assignment operators. These operators help update a value without repeating the variable name. They are simple and easy to remember. Instead of writing a full sentence again Python lets you shorten it.

For example imagine you are building a small money app. A wallet balance goes up and down every day. The old style looks like this

wallet_balance = wallet_balance + 50000

Python allows a shorter way that feels natural

wallet_balance += 50000

The meaning stays the same but the line is cleaner. This saves time and keeps your focus strong. Python supports this style for adding subtracting multiplying and more. Once you start using it you rarely go back.

Then Python became even more interesting. In version three point eight it introduced something new called the walrus operator. At first many people were confused by it. Some loved it. Some disliked it. But everyone agreed it was powerful.

The walrus operator lets you assign a value and use it in the same expression. Before this you often had to write two lines. One line to store a value and another line to check or use it. This created extra code that felt unnecessary.

With the walrus operator you can do both jobs at once. This is helpful in conditions and loops where you only need a value once. It keeps logic close together and avoids extra lines.

Here is a simple idea. You want to get the length of user input and check if it exists

if length := len(user_text):
print(length)

In this example the value is created and checked in one place. There is no repeat and no extra step. When used carefully this makes code easier to follow.

Some developers worry that this operator can make code harder to read. That can be true if it is overused. Like any tool it works best when used with care. Simple cases benefit the most.

Python is popular because it respects the daily life of developers. It tries to remove small frustrations. Assignment operators and the walrus operator are good examples of this idea. They do not change what your code does. They change how it feels to write it.

In the end good code is not about writing more lines. It is about writing clear lines that do real work. If two characters can remove repetition then Python is happy to offer them. That is why many people enjoy coding in Python every day.
#walrus @Walrus 🦭/acc $WAL

Plasma Finance continues to grow as a simple and powerful DeFi platform and now fully supports Optimism Layer 2. This update brings faster transactions lower costs and a smoother experience for users who want easy access to decentralized finance in one place.

With Optimism support users can swap and trade tokens using HyperDEX which automatically finds the best prices across supported networks. Users can also move assets from existing supported chains to Optimism in one simple step. Portfolio Management allows users to track and manage all their crypto and DeFi assets from a single dashboard without confusion.

One of the most useful features is the Plasma Gas Station. It allows users to pay gas fees using any token instead of holding a specific one. This removes a common problem many users face and makes daily DeFi use much easier especially for new users.

Ethereum remains the center of most DeFi activity but high fees and slow transactions can be a problem. Optimism solves this by working as a Layer 2 network that keeps Ethereum security while making transactions faster and cheaper. By supporting Optimism Plasma Finance gives users a better way to interact with DeFi without stress or high costs.

Cross chain activity is still one of the biggest challenges in DeFi. Moving assets between chains often takes many steps costs more money and increases the chance of mistakes. Plasma Finance focuses on solving this problem through true interoperability. Users can bridge trade and manage assets across multiple networks in a single step directly from the dashboard.

With Optimism added Plasma Finance now supports Ethereum Polygon Binance Smart Chain Avalanche Fantom Celo and Optimism. This wide support helps users avoid switching platforms and tools. Everything works from one place making DeFi more friendly and practical for daily use.

HyperDEX helps users swap tokens easily by searching for the best rates and deepest liquidity available. The process is simple fast and designed for everyday users not just experts. This makes buying storing and managing DeFi tokens much more comfortable.

Plasma Finance believes DeFi should be open simple and easy for everyone. By bringing Optimism support the platform takes another step toward mass adoption. Lower fees faster transactions and one dashboard for everything make DeFi less complicated and more useful in real life.

Unifying DeFi liquidity and making cross chain use simple is the goal. Plasma Finance is building tools that people can actually use every day without fear or confusion.

#Plasma @Plasma $XPL

Gata is working with Walrus to build an open execution system for AI. This partnership focuses on lowering data costs and making decentralized AI possible at large scale. Gata builds tools for AI training inference and data creation. Walrus is now the core data layer that supports this work inside the Sui ecosystem.

Walrus will support Gata main product called DataAgent. DataAgent is a decentralized data factory powered by AI inference. It allows anyone to take part using only a browser. Users can share idle computing power and help generate synthetic data needed to train AI models. This makes AI development open to more people instead of only large companies.

One of the biggest problems in decentralized AI has always been data cost. Accessing large files many times is expensive on most decentralized networks. This makes large scale AI work hard to sustain. Gata chose Walrus to solve this problem directly.

Walrus provides fast data access with low storage cost. It also removes download fees completely. This means the Gata community can read and use large data files many times without worrying about rising costs. Data can be shared freely in a permissionless way. This makes ongoing AI work stable and affordable.

During data creation DataAgent needs to read and process large files again and again. Walrus supports this pattern well. It offers performance similar to cloud services while staying fully decentralized. This balance is key for AI systems that must run continuously.

The Walrus team shared that decentralized AI has always faced an economic challenge. Data access should not force teams to choose between being decentralized or being affordable. With Walrus Gata can build a data layer that offers both. This kind of project is exactly what Walrus aims to support.

This partnership also opens the door for the next stage of Gata development. Gata plans to move toward fully decentralized AI inference and training. Using Walrus programmable data features Gata will build an open pricing model. This model will be easy to audit and fair to all participants.

Gata plans to store verified proof of computation on Walrus. Smart contracts built with Move can then check this work and handle payment on chain. This creates a clear and open pricing system. It is very different from closed pricing used by large cloud AI providers today.

The Gata team shared that current cloud providers control most of the AI market and earn large profits. This raises costs and limits access. Gata mission is to make AI open and reachable for everyone. To do this it needs open execution and low cost data access. Walrus provides the missing piece.

This collaboration is a key step toward a full decentralized AI stack that actually works at scale. Gata DataAgent is already live and supported by Walrus. Together they enable community driven data creation and AI development.

This partnership shows how decentralized storage and open execution can work together. It brings AI closer to everyday users and builders.

About Sui Network

Sui is a layer one blockchain built from first principles. It is designed to support real world apps and large user numbers. It uses the Move language and allows fast and low cost development for builders.

#walrus @Walrus 🦭/acc $WAL

Walrus has officially launched Quilt a new feature designed to change how small files are stored at large scale. Since the Walrus main network went live the community has grown fast. Developers are using Walrus in creative ways and adoption continues to rise. Today Walrus already supports hundreds of projects and stores a huge amount of data for builders across Web3.

Walrus was created as a global data layer for onchain builders. Many projects moved to Walrus because older storage options were slow costly or hard to verify. Teams working on digital media AI tools news platforms and design libraries all chose Walrus because it is fast flexible and easy to trust.

As Walrus grew one clear need appeared. Many builders needed to store very large numbers of small files. Until now users had to bundle files themselves to reduce cost. This added extra work and made systems harder to manage. Walrus built Quilt to remove this problem and make small file storage feel natural and simple.

Quilt is now officially live. It is a batch storage solution with a clear and easy API. It helps developers store large numbers of small files like NFT media documents chat data logs and AI messages in a clean and cost friendly way. With Quilt Walrus now supports all file sizes on one platform.

Quilt works by grouping many small files into a single storage unit. Instead of paying full cost for each small file users can store them together. This greatly reduces overhead and lowers total cost. Small files that once felt expensive to store now become easy to manage at scale.

Quilt also helps reduce gas costs related to storage actions. This makes it a strong choice for apps that need frequent updates or high activity. Even though files are stored together each file can still be accessed on its own. There is no need to download everything just to get one file.

Some early projects are already using Quilt. A privacy focused file platform uses Quilt to handle many small uploads during busy times. This improved performance and reduced costs. An AI data platform uses Quilt to store many small training files while keeping ownership and access rules for each file. Quilt removed the need for manual packing and saved time for developers.

Quilt is especially useful for apps that deal with many small pieces of data. This includes social apps chat systems AI agent messages sensor data NFT media and metadata. These apps need speed low delay and low cost. Quilt supports all of this in one place.

Quilt also supports built in metadata. Developers can tag files and search them easily. This makes it simple to organize content without extra systems. Files stay easy to find even at large scale.

Quilt is now available on the Walrus test network and will go live on the main network with the next release. Walrus invites builders to start testing Quilt and explore new ways to build with data.

With Quilt Walrus takes another step toward its goal. That goal is to help builders fully use their data in a fast flexible and open way.

About Sui Network

Sui is a layer one blockchain built from the ground up. It is designed to support large scale apps and real users. It uses the Move language and allows fast and low cost development.

#walrus
/@Walrus 🦭/acc $WAL

FLock io is working with Walrus to build a safer and more private way to train AI models. This partnership focuses on giving people control over their data while still allowing open and shared AI development. Walrus is now the main data layer for FLock io inside the Sui ecosystem. Together they aim to support community driven AI in a secure and simple way.

FLock io is known as a decentralized AI training platform. It allows people to train and own AI models without giving up private data. Instead of collecting all data in one place it uses a shared training method where users keep data with them. Walrus fits well into this idea by offering decentralized data storage with strong privacy support.

Walrus provides tools for storing data sharing results and managing access. It also uses SEAL encryption to protect sensitive information. This means only approved users can see or use certain data. By adding Walrus to its system FLock io can store training results and model updates in a way that is open but still safe.

One main focus of this partnership is the FL Alliance. This is a group where many training nodes work together. Walrus helps send and store model updates across these nodes. SEAL makes sure that only trusted members can read or add data. This keeps the training process fair and private while still being open to the community.

FLock io also has other parts in its system. AI Arena allows people to join training contests. Moonbase lets users host models in a decentralized way. All these parts work together to create a full AI setup that is owned and guided by the community. Walrus supports this by making data available when needed and protected at all times.

The team at FLock io shared that past data tools were either not fully decentralized or did not protect privacy well. Walrus solves this by offering encrypted and decentralized storage. This helps lower barriers and allows more users to join safe AI training.

Looking ahead this partnership will also support smart AI tools built for Sui. The next step is to fine tune an open model that works well with Sui apps. The long term goal is to create a helper tool for Sui that can understand context help with smart contracts and support Move code writing.

The Walrus team shared that their goal is to give builders full control over data. By working with FLock io they show how decentralized data can support real AI use in a safe way. This partnership highlights how Web3 tools can help shape the future of AI.

By combining shared learning strong privacy and open data tools FLock io and Walrus are helping developers build better AI while keeping control in their own hands.

About Sui Network

Sui is a layer one blockchain built from the ground up. It is made to support large scale apps. It uses the Move language and allows fast and low cost development for builders.

#walrus @Walrus 🦭/acc $WAL