Is Decentralized Finance just another trend?

a.shah

13 Oct 2020
Is Decentralized Finance just another trend?

Have you been hearing about Decentralized Finance and wondered what it really is? Why has it become so popular? On our Nextrope blog, we break down the technology to decipher its constituents and understand what makes it tick. We compare it to Centralized Finance (the current status quo) and see how it holds up.

Why fix something not broken – Centralized Finance vs Decentralized Finance?

Humans have always had a centralized authority directing and regulating the way they earn and spend money. The norm is that a central mint prints and distributes money, the central bank lends to other banks who then lend to their customers, and these customers deposit their savings back into the banks. It has worked for hundreds of years. Why then do we feel like we need an alternative? Why is Decentralized Finance (DeFi) trending? The simple answer is that Centralized Finance (CeFi) has always had glaring problems, but most chose to ignore it since there was no other alternative at hand. With the introduction of distributed ledger technology (blockchain), this is no longer the case. Decentralized Finance has finally become a reality, albeit with drawbacks of its own.

Whenever power, especially financial power, is centralized, most people get locked out of the decision-making process. Consequently, only a small portion of the population reap the benefits of the financial system while the rest are charged exorbitant fees, high interest rates and low returns. Even in the US, only 7% of the bottom 80% of society own shares in companies, whereas in other nations, most do not even have access to stock markets. Currently, transferring money outside of the country involves countless middlemen and substantial fees, obtaining a loan is met with walls of red tape and bureaucracy and the interest rates on deposits is often abysmal.

Even the safety factor that was attributed to banks eroded after the 2008 housing bubble. 2008 showed us that when few control all the money, risk accumulates at the center and endangers the entire system. In addition, banks use money in ways that most people don’t understand. In times of emergency, bank runs (many clients withdrawing their money from a bank) can quickly lead to zero cash balances, as seen in places like Argentina, Venezuela and Zimbabwe.

Is it surprising then that Bitcoin was first launched in 2009, a year after the financial crisis? There was a dire need for the first-ever solution to have global peer-to-peer settlements with no intermediaries required so that individuals could keep control over their assets. However, Bitcoin and early cryptocurrencies only decentralized the issuance and storage of money, not access to a broader set of financial instruments.

The infographic below describes a simplistic example of how the ideal decentralized exchange would occur compared to the status quo.

Source: Defi Pubs

Decentralized Finance (DeFi) – the unlikely hero?

On paper, Decentralized Finance (DeFi) is disruption defined, allowing individuals full control and access over their assets. DeFi is an umbrella term referring to all the financial applications, such as lending, borrowing, exchanging, and investing which occur through decentralized channels and exchanges. The idea is to create an open-source, permissionless, and transparent financial service ecosystem available to everyone via peer-to-peer (P2P) capability, operating without any central authority. DeFi is distinct because it expands the use of blockchain from simple value transfer to more complex financial use cases such as borrowing, insurance etc. The activity in DeFi has increased exponentially in 2020 with total value locked in increasing from $1 Billion to $10 Billion in a span of 4 months.

Source: Defi Pulse

As mentioned previously, DeFi is primarily being used for loans, trading and payments but there are additional use cases such as insurance and investing being developed. The Ethereum blockchain eco-system is the most popular for the development of these applications since it provides increased security, transparency, and growth opportunities. The Ethereum platform functions through ‘smart contracts’ which automatically executes transactions if certain conditions are met, removing the human element from all transactions.

Source: Block Crypto

While more and more people are being drawn to these DeFi applications, it’s hard to say where they’ll go. Much of that depends on who finds them useful and why. Many believe various DeFi projects have the potential to become the next Robinhood (popular online brokerage that enables stock trading at very low fees), drawing in hordes of new users by making financial applications more inclusive and open to those who don’t traditionally have access to such platforms.

DeFi’s not so shining armor

As with any new technology, there are growing pains. Some of the ones hurting DeFi particularly have been highlighted below:

1. Incomplete decentralization - Although protocols are decentralized and based on consensus algorithms, many access points to the system, like exchanges, are still centralized. In addition, many crypto projects are managed through centralized organizations or companies that too often lack transparency or accountability, and do not openly show the development of new parts of the ecosystem.

2. Volatility - Many DeFi applications, such as meme coin YAM, have crashed and burned, sending the market capitalization from $60 million to $0 in 35 minutes. Other DeFi projects, including Hotdog and Pizza, faced the same fate, and many investors lost a lot of money.

3. Security – While there are no humans involved in the smart contract process, humans do create the contracts and that is a major source of errors. Smart contracts are powerful, but they can’t be changed once the rules are baked into the protocol, which often makes bugs permanent and increases risk.

4. Rising Network fees – Network usage is directly correlated with fees and due to the recent popularity of DeFi, the Ethereum fees have sky-rocketed. This has led to a decrease in profitability for DeFi users and is hindering user experience.

Source: Coindesk

5. Risk of Fraud – While smart contracts have no human involvement in its execution, there are humans involved in its coding. This vulnerability leaves the door open for errors and subsequent attacks on the network.

Conclusion

Decentralized Finance is still at its nascent stage and is still trying to find solid ground beneath its legs. Blockchain and cryptocurrency enthusiasts seem to think there is enormous potential and have therefore poured significant sums of money into various DeFi platforms. Given the multiple challenges DeFi currently faces, worse comes to worst, it will at least force the centralized system to become more competitive by introducing changes to their structure.

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Master UI Component Creation with AI: The Ultimate Guide for Developers

Gracjan Prusik

24 Mar 2025
Master UI Component Creation with AI: The Ultimate Guide for Developers

Introduction

Modern frontend development is evolving rapidly, and creating UI components with AI tools is helping developers save time while enhancing interface quality. With AI, we can not only speed up the creation of UI components but also improve their quality, optimize styles, and ensure better accessibility.

This article explores how creating UI components with AI is transforming frontend development by saving time and improving workflows. Specifically, we will discuss:

  • Generating components from images,
  • AI for style analysis and optimization,
  • Automatic style conversion and code migration,
  • AI in generating UI animations.

Creating UI Components with AI from Images

One of the interesting applications of AI in frontend development is the ability to generate components from an image. AI can recognize the structure of the interface and generate HTML/CSS or JSX code that matches the provided image. One of the most popular tools for UI creation is Lovable.

For testing, let's see how the tool performs in creating a simple contact form from the page you are currently on, which is Nextrope.

Query:

"Recreate the image I've sent you in Next.js using CSS."

Sample image used in the query:

The result received:

Tworzenie komponentów UI - Wygenerowany widok

Lovable did an excellent job transforming the image into code. The view is fully responsive. It’s important to remember that the more precise the request, the better the AI will replicate the expected view. However, even with a simple command, the tool performed surprisingly well.

Of course, AI has its limitations. It still makes quite a few mistakes. The generated code still requires review and fixes from the developer, but in some cases, the entire process is significantly sped up—correcting the code often takes less time than creating the component from scratch.

Optimizing UI Components with AI Tools for Style Improvements

This problem of inaccurate code reproduction by AI can be partially addressed by using it to analyze and improve styles. Tools like ChatGPT, DeepSeek and Claude are capable of not only generating code but also diagnosing CSS errors and suggesting why a particular style might not be working as expected.

Simple example: Why is the div not centered?

Query: "Why is this div not centered?"

AI analyzes the code and provides the following response:

Problem: The parent container does not have a defined width or display: flex.
Solution: Add the appropriate styles to the parent container.

.parent {
  display: flex;
  justify-content: center;
  align-items: center;
  width: 100vw;
  height: 100vh;
}

AI for Automatic Style Conversion and Code Migration in UI Components

AI can assist with style conversion between different technologies, such as transferring code from traditional CSS to Styled Components or Tailwind CSS.

Let's assume we have a style written in traditional CSS:

.button {
  background-color: blue;
  color: white;
  padding: 10px 20px;
  border-radius: 5px;
  transition: background-color 0.3s ease;
}

.button:hover {
  background-color: darkblue;
}

We can use AI for automatic conversion to Styled Components:

import styled from "styled-components";

const Button = styled.button`
  background-color: blue;
  color: white;
  padding: 10px 20px;
  border-radius: 5px;
  transition: background-color 0.3s ease;

  &:hover {
    background-color: darkblue;
  }
`;

export default Button;

AI can also assist in migrating code between frameworks, such as from React to Vue or from CSS to Tailwind.

This makes style migration easier and faster.

How AI Enhances UI Animation Creation

Animations are crucial for enhancing user experience in interfaces, but they are not always provided in the project specification. In such cases, developers have to come up with how the animations should look, which can be time-consuming and require significant creativity. AI, in this context, becomes helpful because it can automatically generate CSS animations or animations using libraries like Framer Motion, saving both time and effort.

Example: Automatically Generated Button Animation

Suppose we need to add a subtle scaling animation to a button but don't have a ready-made animation design. Instead of creating it from scratch, AI can generate the code that meets our needs.

Code generated by AI:

import { motion } from "framer-motion";

const AnimatedButton = () => (
  <motion.button
    whileHover={{ scale: 1.1 }}
    whileTap={{ scale: 0.9 }}
    className="bg-blue-500 text-white px-4 py-2 rounded-lg"
  >
    Press me
  </motion.button>
);

In this way, AI accelerates the animation creation process, providing developers with a simple and quick option to achieve the desired effect without the need to manually design animations from scratch.

Summary

AI significantly accelerates the creation of UI components. We can generate ready-made components from images, optimize styles, transform code between technologies, and create animations in just a few seconds. Tools like ChatGPT, DeepSeek, Claude and Lovable are a huge help for frontend developers, enabling faster and more efficient work.

In the next part of the series, we will take a look at:

If you want to learn more about how AI is impacting the entire automation of frontend processes and changing the role of developers, check out our blog article: AI in Frontend Automation – How It's Changing the Developer's Job?

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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