NFT tokens- 7 of the biggest projects.

Maciej Zieliński

28 Apr 2021
NFT tokens- 7 of the biggest projects.

NFT tokens are conquering the collectible items markets. During the last months there has been increased interest in NFTs. Therefore we prepared for you the list of the most interesting examples of their possible uses. 

NFT tokens use a special technology called a blockchain that certifies a digital asset to be unique and therefore not interchangeable. Tokens have been recently increasingly used in such key areas as IoT or supply chains. The NFT market value tripled in 2020, reaching more than $315 million.

NFT tokens are non-fungible, which means that each token in a given system is unique. Tokens like that do not have a standard value and often do not allow for the equivalent exchange of one for another. Each token has distinct, unique ownership or identity information. 

NFT tokens basic assets are: 

  • they are impossible to counterfeit
  • they can be moved
  • they retain ownership rights

NFT tokens - the biggest projects

NBA Top shot

The outcome of the cooperation between NBA and Dapper Labs company, in the simplest terms, is an internet platform for exchanging virtual trading cards. At NBA Top shot, basketball fans can buy and sell "moments" video clips from the last seasons of the competition that exist as NFT tokens on the Blockchain.

This is not the first time when NFT tokens have been used by a professional sports League, however, it is without a doubt the biggest one. CryptoSlam estimates that up until to now, the total value of all transactions between users has already reached $ 370 million. 

Axie Infinity

Axie Infinity is a gaming platform that, similarly to Decentraland, allows you to purchase a virtual ground in the form of an NFT token. In February this year an anonymous user with a nickname Flying Falcon bought 8 land grounds in the world of Axie for 1,5 million dollars.

"This largest digital ground sale in history represents a significant development in the short historyof NFT," said the seller in an interview for CoinDesk. "It is virtual economies that will be the new frontier for an increasingly digital world."

The demand for virtual grounds is steadily growing. This year, the average price paid for a plot in Decentraland was $ 2,703 - over three times more than in 2020. However, on another platform of this type - Cryptovoxels, the average value of the land has quadrupled during this time. 

Companies that operate on a traditional real estate market are slowly becoming interested in NFT virtual tokens. A good example is the enterprise called Republic Real Estate which operates in the housing market and opened for investors who are willing to buy a virtual ground. The enterprise is planning to buy a ground in several internet platforms and then reshape them for virtual hotels and shops in order to increase their value among enthusiasts.

“Real estates in the current world are very uncertain’’- said Janine Yorio, head of Republic Real Estate. “Residential prices are extremely high. However, offices and hotels are empty. It seems that virtual grounds are isolated from many real-life dangers’’.

King of Leons - music album released as NFT

Their eighth studio album, When You See Yourself, was released in March this year in the form of a NFT token. This is the first time that NFT tokens have been used by artists with such high visibility. The sale of tokens, in which the company  Yellow Heart was represented, ended on March the 19th, generating over $ 2 million in revenue. 

The NFT tokens released by the band in many ways resemble the typical merche of artists: they guarantee access to future concerts, covers or a limited vinyl edition. The applied technology makes NFT tokens unique. Because of the fact that NFT tokens use smart contracts, a set of rules may be taken into account by their creator to determine what should happen when an NFT is used or changes hands. It is precisely this aspect of NFT tokens that is the most valuable for the music industry.

Owing to NFT tokens , musicians can retain direct ownership of the rights to the song and collect royalties for playback and sales without the intervention of intermediaries.

Nike CryptoKick

NFT tokens are taking the collectibles market by storm. Their using owing to a footwear industry should be no reason to wonder, especially as in the 21st century, shoe collecting permanently entered the mainstream.

The industry giant- Nike joined in the trend registering the patent as a solution named CryptoKick in 2019. It is a system which enable to create and exchange cryptographically secured digital assets in the form of virtual shoes that can be linked to their physical counterpart in the real world.

 In the meantime, the whole project is shrouded in mystery, but it is already known today that is supposed to allow for simultaneous receipt of both versions of shoes; digital and physical at the time of purchasing the actual pair. 

Gucci AR sneakers 

In the fashion industry, where uniqueness and originality have always been of fundamental importance, it seems to be the perfect environment for NFT tokens. Therefore nowadays the biggest brands are investing in the development of the technology. 

Among them was the Gucci fashion house, which launched a series of augmented reality (AR) shoes in the form of NFT. The pair costs less than $ 12, and to make it possible to sell it, the company hired the Belarusian company Wanna, which has also collaborated with brands such as Puma and Reebok. 

"In five, maybe 10 years, a relatively large proportion of fashion brands' revenues will come from digital products," said Wanna CEO Sergey Arkhangelskiy, The Business of Fashion magazine.

,,Our aim as a company is to replace photos of products with something which is much more engaging and much more like shopping offline’’.

Beeple and Christie’s auction

Mike Winkelmann, known professionally as Beeple, is an American digital artist, graphic designer who began to explore and use the benefits of blockchain technology. The artist has been selling his works in the form of NFT tokens for years. However, it was the auction of his work at the Christies auction house that allowed him to become the author of the third most expensive cannon which was sold during the artist's lifetime in history.

The winner of the auction acquired ‘’EVERYDAYS: THE FIRST 5000 DAYS”  as a NFT token for nearly 70 million dollars. Thus, Christies became the first auction house to put a NFT token up for auction. In addition, the payment was made in Ethereum which is totally new for such an institution. 

The first tweet of Twitter's CEO is sold 

Last month, Twitter's CEO and founder sold his first tweet as NFT for 2.9 million dollars. Soon, the entrepreneur was joined by other personalities from the world of business and entertainment, even Elon Musk was close to sell his entry.

"This is not just a tweet!" - the action winner Hakan Estavi, CEO of Bridge Oracle said, "I think that ,after many years, people will realize the true value of this tweet, equal to the portrait of the Mona Lisa."    

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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