What is staking and how does it work?

Maciej Zieliński

23 Mar 2022
What is staking and how does it work?

Many people see staking as an alternative to mining which requires technical knowledge. It is an activity where you don't have to own and look after complex equipment, but only store funds in a specific cryptocurrency wallet. This ensures the safety and smooth operation of a given blockchain network. Staking crypto is to put it simply, blocking cryptocurrencies, in order to receive awards and many benefits in the form of units of a given cryptocurrency. Most projects allow for staking of digital assets directly from a cryptocurrency portfolio. There are also exchanges that provide a staking service to users as part of their business offer. One such exchange is, for example, Binance. In order to fully understand staking wee need to understand how Proof of Stake (PoS) and Delegated Proof of Stake (DPoS) work.

What is Proof of Stake system (PoS)?

The Proof of Stake systemand staking crypto is a consensus mechanism which allows blockchains to save energy while maintaining proper decentralization. This consensus mechanism is designed to address the vulnerabilities and problems that exist in the Bitcoin network algorithm.

In the Bitcoin network, miners compete for who will be the fastest to solve a mathematical puzzle. The entity that is able to do so in the shortest time adds the block and receives remuneration in the form of BTC. The problem itself is related to the multiplicity of arbitrary calculations and the electricity required to do this, which is considered to be a major cost-negative.

It is worth stressing that there is a way to maintain network decentralization without incurring the high computing costs connected with solving puzzles. The solution is the Proof Stake, whose primary purpose is to validate blocks and use an "internal" investment (own cryptocurrency) instead of "external" investments (energy, crypto mining machines). Network users may “block” their coins. Afterwards, at different intervals, the protocol randomly assigns the right to approve the block to one of the users. The chance to be chosen doesn't depend on who creates a block or how quickly puzzles are solved. However, it depends on how many coins we are blocking. That is, the more wecapital we devote to this, the higher the chance we will be chosen. Another benefit of POS is that attacking a blockchain network is much more expensive because an effective attack would require owning at least 51% of all existing cryptocurrencies of a given blockchain. Of course, the cheaper and more accessible a given cryptocurrency is, the easier such an attack becomes. Hacking also has a greater impact on PoS management models than on PoW (proof of work). When a given network is hacked, miners lose more than just their cryptocurrency; they lose their place on the platform. This is a major problem that has led to the creation of the Delegated Proof of Stake (DPoS).

What is Delegated Proof of Stake (DPoS)?

Proof of Stake model also has an alternative option that was created in 2014 by Daniel Larimer. The method is referred to as Delegated Proof of Stake (DPoS). It was first tested as part of the BitShares blockchain, but shortly thereafter other networks started using this model as well.

DPoS

The DPoS activity can be compared to shares held in a company. This method allows users to treat their cryptocurrency as votes whose force is proportional to their number. These votes are used to select delegates whose jobis to manage a blockchain on behalf of their constituents, which ensures consensus and security.

The strength of each stakeholder (cryptocurrency owner) is determined by the amount of cryptocurrency held. The advantage of the DPoS is, for example, that consensus can be reached with a small number of validation nodes. This improves overall network performance.

How does crypto staking work?

How does crypto staking works? Remember that the Proof of Stake model (PoS) and Delegated Proof of Stake (DPoS) algorithms require staking to function properly. Participants who block larger amounts increase the likelihood that they will be selected as the next validator in the block. This behavior allows blocks to be produced without the need for complex and expensive mining equipment, such as the ASIC system.

It should be noted that mining cryptocurrencies by means of ASIC systems requires large investments in equipment and that staking has only one requirement, which is investing in a given cryptocurrency and freezing one’s capital. Staking may at first glance remind you of depositing money in a bank, but in this case, frozen assets ensure that the blockchain network functions properly and interest is calculated in cryptocurrencies.

In addition, you should be aware that every PoS blockchain has a specific staking currency. There are networks that use a two-token system where prizes are paid out using a separate token (for example, you are freezing cryptocurrency "x", receiving the cryptocurrency "y" as a prize).

Staking rewards

How are rewards for cryptocurrency staking calculated? Several elements need to be analyzed in order to answer this question. Remember that a blockchain network is not uniform and therefore each part of it can use different methods for calculating rewards. Individual projects offer a variety of rewards. The factors that influence the rewards for staking are:

  • Time of active staking by validator
  • Amount of „frozen” coins
  • Inflation rate of assets
  • Total number of coins staked in the network

Interestingly, some networks reward staking using percentages. Such awards are given to validators as a form of compensation for inflation, which in turn encourages network users to spend coins rather than to store them. How much can You earn from this?

For example, staking of LUNA cryptocurrency offered users only 1,5% per year, and the pledged assets are subject to a 21-day unlock period. Another project that has generated greater interest was Cosmos (ATOM), which offered an annual return on investment of around 8%.

What is a staking pool?

The staking pool is a place where a group of individuals who possess given cryptocurrencies combine them with others to maximize the odds of being selected to review blocks and receive rewards funds (crypto holdings). Simply put, the staking pools are a place where group staking takes place. By combining stakes, users of a staking pool share rewards in proportion to their contribution.

Staking Pool

Both knowledge and time are necessary to create and maintain a staking pool. Such mining pools are most effective in networks where the entry threshold is sufficiently high. With this in mind, many pool suppliers charge fees on the prizes that the participants receive. Let us remember that there is a safeguard – a minimum balance is always required and is set up to deter malicious stakers.

A significant part of the staking pool requires a low, minimum balance, but this often does not go hand in hand with the extra time in which we could cash out. As a result, joining a pool rather than ‘playing solo’ can be an very attractive solution for those who are just starting to become involved in this form of making money.

What is cold staking?

Cold staking is a process in a wallet that runs without Internet access, just like the ‘cold wallet’. When you stake crypto coins, they are frozen in your wallet. If your wallet is connected to a blockchain network, it is called a hot wallet because it is connected to the internet and becomes vulnerable to attacks. The cold staking process can be done by, i.e using a hardware wallet. It is interesting to note that you can get this effect when when using an air gap wallet. The average reward you can expect with this method is around 2%.

Networks that support "cold staking" provide the opportunity to stake crypto while ensuring that your funds are safely stored offline, howerver it should be noted that this pertains only to users working in cold staking mode. If the stakeholder transfers their assets from their wallet, the reward will automatically be waived. Cold staking is a beneficial method for big players who not only wish to focus on protecting their assets as much as possible, but also want to support the network.

Which cryptocurrencies can be staked?

At present, half of the thousands of cryptocurrencies are based on the Proof of stake algorithm. The most popular of these are listed below:

  • XLM
  • DASH
  • NOW
  • NEO
  • BNB
  • ADA
  • ALGO
  • DOT
  • XLM
  • CELO
  • BTS
  • TRON
  • PIVX
  • NEBL

The DPoS consensus algorithm was developed by Daniel Larimer and the main cryptocurrencies that are based on this technology are:

  • TRX,
  • LUNA
  • EOS,
  • XTZ
  • ICX
  • LISK
  • BAND

Given that blockchain and cryptocurrencies are an extremely original and diverse ecosystem, it should be noted that cryptocurrencies have a high potential to become a stable source of income. Staking is a cheaper and simpler method than mining and the staking pool makes the investment process even easier. For this reason, it is useful to know the above-mentioned terms.

Why is crypto staking worthwhile? Because thanks to it crypto investors can obtain particular digital asset. Moreover, crypto staking is also worth looking into, as it builds passive income. It is also worth noting that anyone can stake cryptocurrency and thus acquire potentially more lucrative staking rewards than any bank deposit can offer – and all that at a low minimum amount. Crypto staking is currently one of the most interesting financial solutions in the new technologies sector.

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AI in Real Estate: How Does It Support the Housing Market?

Miłosz Mach

18 Mar 2025
AI in Real Estate: How Does It Support the Housing Market?

The digital transformation is reshaping numerous sectors of the economy, and real estate is no exception. By 2025, AI will no longer be a mere gadget but a powerful tool that facilitates customer interactions, streamlines decision-making processes, and optimizes sales operations. Simultaneously, blockchain technology ensures security, transparency, and scalability in transactions. With this article, we launch a series of publications exploring AI in business, focusing today on the application of artificial intelligence within the real estate industry.

AI vs. Tradition: Key Implementations of AI in Real Estate

Designing, selling, and managing properties—traditional methods are increasingly giving way to data-driven decision-making.

Breakthroughs in Customer Service

AI-powered chatbots and virtual assistants are revolutionizing how companies interact with their customers. These tools handle hundreds of inquiries simultaneously, personalize offers, and guide clients through the purchasing process. Implementing AI agents can lead to higher-quality leads for developers and automate responses to most standard customer queries. However, technical challenges in deploying such systems include:

  • Integration with existing real estate databases: Chatbots must have access to up-to-date listings, prices, and availability.
  • Personalization of communication: Systems must adapt their interactions to individual customer needs.
  • Management of industry-specific knowledge: Chatbots require specialized expertise about local real estate markets.

Advanced Data Analysis

Cognitive AI systems utilize deep learning to analyze complex relationships within the real estate market, such as macroeconomic trends, local zoning plans, and user behavior on social media platforms. Deploying such solutions necessitates:

  • Collecting high-quality historical data.
  • Building infrastructure for real-time data processing.
  • Developing appropriate machine learning models.
  • Continuously monitoring and updating models based on new data.

Intelligent Design

Generative artificial intelligence is revolutionizing architectural design. These advanced algorithms can produce dozens of building design variants that account for site constraints, legal requirements, energy efficiency considerations, and aesthetic preferences.

Optimizing Building Energy Efficiency

Smart building management systems (BMS) leverage AI to optimize energy consumption while maintaining resident comfort. Reinforcement learning algorithms analyze data from temperature, humidity, and air quality sensors to adjust heating, cooling, and ventilation parameters effectively.

Integration of AI with Blockchain in Real Estate

The convergence of AI with blockchain technology opens up new possibilities for the real estate sector. Blockchain is a distributed database where information is stored in immutable "blocks." It ensures transaction security and data transparency while AI analyzes these data points to derive actionable insights. In practice, this means that ownership histories, all transactions, and property modifications are recorded in an unalterable format, with AI aiding in interpreting these records and informing decision-making processes.

AI has the potential to bring significant value to the real estate sector—estimated between $110 billion and $180 billion by experts at McKinsey & Company.

Key development directions over the coming years include:

  • Autonomous negotiation systems: AI agents equipped with game theory strategies capable of conducting complex negotiations.
  • AI in urban planning: Algorithms designed to plan city development and optimize spatial allocation.
  • Property tokenization: Leveraging blockchain technology to divide properties into digital tokens that enable fractional investment opportunities.

Conclusion

For companies today, the question is no longer "if" but "how" to implement AI to maximize benefits and enhance competitiveness. A strategic approach begins with identifying specific business challenges followed by selecting appropriate technologies.

What values could AI potentially bring to your organization?
  • Reduction of operational costs through automation
  • Enhanced customer experience and shorter transaction times
  • Increased accuracy in forecasts and valuations, minimizing business risks
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Want to implement AI in your real estate business?

Nextrope specializes in implementing AI and blockchain solutions tailored to specific business needs. Our expertise allows us to:

  • Create intelligent chatbots that serve customers 24/7
  • Implement analytical systems for property valuation
  • Build secure blockchain solutions for real estate transactions
Schedule a free consultation

Or check out other articles from the "AI in Business" series

AI-Driven Frontend Automation: Elevating Developer Productivity to New Heights

Gracjan Prusik

11 Mar 2025
AI-Driven Frontend Automation: Elevating Developer Productivity to New Heights

AI Revolution in the Frontend Developer's Workshop

In today's world, programming without AI support means giving up a powerful tool that radically increases a developer's productivity and efficiency. For the modern developer, AI in frontend automation is not just a curiosity, but a key tool that enhances productivity. From automatically generating components, to refactoring, and testing – AI tools are fundamentally changing our daily work, allowing us to focus on the creative aspects of programming instead of the tedious task of writing repetitive code. In this article, I will show how these tools are most commonly used to work faster, smarter, and with greater satisfaction.

This post kicks off a series dedicated to the use of AI in frontend automation, where we will analyze and discuss specific tools, techniques, and practical use cases of AI that help developers in their everyday tasks.

AI in Frontend Automation – How It Helps with Code Refactoring

One of the most common uses of AI is improving code quality and finding errors. These tools can analyze code and suggest optimizations. As a result, we will be able to write code much faster and significantly reduce the risk of human error.

How AI Saves Us from Frustrating Bugs

Imagine this situation: you spend hours debugging an application, not understanding why data isn't being fetched. Everything seems correct, the syntax is fine, yet something isn't working. Often, the problem lies in small details that are hard to catch when reviewing the code.

Let’s take a look at an example:

function fetchData() {
    fetch("htts://jsonplaceholder.typicode.com/posts")
      .then((response) => response.json())
      .then((data) => console.log(data))
      .catch((error) => console.error(error));
}

At first glance, the code looks correct. However, upon running it, no data is retrieved. Why? There’s a typo in the URL – "htts" instead of "https." This is a classic example of an error that could cost a developer hours of frustrating debugging.

When we ask AI to refactor this code, not only will we receive a more readable version using newer patterns (async/await), but also – and most importantly – AI will automatically detect and fix the typo in the URL:

async function fetchPosts() {
    try {
      const response = await fetch(
        "https://jsonplaceholder.typicode.com/posts"
      );
      const data = await response.json();
      console.log(data);
    } catch (error) {
      console.error(error);
    }
}

How AI in Frontend Automation Speeds Up UI Creation

One of the most obvious applications of AI in frontend development is generating UI components. Tools like GitHub Copilot, ChatGPT, or Claude can generate component code based on a short description or an image provided to them.

With these tools, we can create complex user interfaces in just a few seconds. Generating a complete, functional UI component often takes less than a minute. Furthermore, the generated code is typically error-free, includes appropriate animations, and is fully responsive, adapting to different screen sizes. It is important to describe exactly what we expect.

Here’s a view generated by Claude after entering the request: “Based on the loaded data, display posts. The page should be responsive. The main colors are: #CCFF89, #151515, and #E4E4E4.”

Generated posts view

AI in Code Analysis and Understanding

AI can analyze existing code and help understand it, which is particularly useful in large, complex projects or code written by someone else.

Example: Generating a summary of a function's behavior

Let’s assume we have a function for processing user data, the workings of which we don’t understand at first glance. AI can analyze the code and generate a readable explanation:

function processUserData(users) {
  return users
    .filter(user => user.isActive) // Checks the `isActive` value for each user and keeps only the objects where `isActive` is true
    .map(user => ({ 
      id: user.id, // Retrieves the `id` value from each user object
      name: `${user.firstName} ${user.lastName}`, // Creates a new string by combining `firstName` and `lastName`
      email: user.email.toLowerCase(), // Converts the email address to lowercase
    }));
}

In this case, AI not only summarizes the code's functionality but also breaks down individual operations into easier-to-understand segments.

AI in Frontend Automation – Translations and Error Detection

Every frontend developer knows that programming isn’t just about creatively building interfaces—it also involves many repetitive, tedious tasks. One of these is implementing translations for multilingual applications (i18n). Adding translations for each key in JSON files and then verifying them can be time-consuming and error-prone.

However, AI can significantly speed up this process. Using ChatGPT, DeepSeek, or Claude allows for automatic generation of translations for the user interface, as well as detecting linguistic and stylistic errors.

Example:

We have a translation file in JSON format:

{
  "welcome_message": "Welcome to our application!",
  "logout_button": "Log out",
  "error_message": "Something went wrong. Please try again later."
}

AI can automatically generate its Polish version:

{
  "welcome_message": "Witaj w naszej aplikacji!",
  "logout_button": "Wyloguj się",
  "error_message": "Coś poszło nie tak. Spróbuj ponownie później."
}

Moreover, AI can detect spelling errors or inconsistencies in translations. For example, if one part of the application uses "Log out" and another says "Exit," AI can suggest unifying the terminology.

This type of automation not only saves time but also minimizes the risk of human errors. And this is just one example – AI also assists in generating documentation, writing tests, and optimizing performance, which we will discuss in upcoming articles.

Summary

Artificial intelligence is transforming the way frontend developers work daily. From generating components and refactoring code to detecting errors, automating testing, and documentation—AI significantly accelerates and streamlines the development process. Without these tools, we would lose a lot of valuable time, which we certainly want to avoid.

In the next parts of this series, we will cover topics such as:

Stay tuned to keep up with the latest insights!