New token types – everything you need to know about them

Maciej Zieliński

02 Feb 2021
New token types – everything you need to know about them

Which tokens are the most popular? What new token types are worth watching in 2021? 

Although cryptographic tokens are created from just a few lines of code, the potential they hold is gigantic. We are already using them today to create digital equivalents of real assets such as shares and real estate or to create innovative product tracking systems in the supply chain. And as digitisation continues, the list of their applications continues to grow.

Currently, the most popular type of token is created in Ethereum ERC-20. However, the continuous development of Blockchain technology in recent years has resulted in the creation of numerous alternatives. New types of tokens are characterised by innovative technological solutions and adaptation to specific business needs. Which of them are particularly worth taking interest in?

Types of tokens 

To better understand the possibilities of this technology, it is worth taking a closer look at its types. Among the many ways to distinguish tokens, the most basic is the division into fungible tokens and non-fungible tokens.):

Fungible tokens 

They make up the vast majority of all tokens. The term fungible means that a single token is indistinguishable from other tokens in the same blockchain ecosystem. This allows it to find uses as a cryptocurrency, credit or exchange of value. A great example of such a token is the well-known Bitcoin: no Bitcoin is more valuable or scarcer than another. If it were otherwise, their free exchange would not be possible, which would disrupt the entire system. 

Convertible tokens are analogous to conventional currencies in this respect: all euros, zlotys, or dollars have exactly the same value. It is precisely the fungibility that makes them useful. Thanks to it we do not have to individually estimate the value of each zloty during a transaction. 

There are 3 categories of fungible tokens:

Payment:

Bitcoin, Litcoin or Dash - this is what they are. Convertible payment tokens were created to be used for transactions between parties instead of or alongside fiat currencies. Their value is determined by the number of people who wish to use them and the number of merchants.

Utility Tokens:

These tokens work in exactly the same way as tokens in an arcade. You exchange tokens for the entertainment available there, but you can use tokens to access services, products or other value on the platform they power.  

The most common example of such a token is Ether. ETH is used to pay for the execution of smart contracts on the Ethereum network. Of course, Ether can be used to make other payments as well, but powering contracts, dapps and DAOs is its primary purpose. 

It is Utility tokens that are used during ICOs, where they serve as a tool to raise funds for the creation of a project in which they can later be used. 

Security tokens

Security tokens are primarily distinguished from Utility tokens by securing the value of the former in real assets. By buying Utility tokens we can of course earn from the increase in their value, but in reality we own nothing - they are worth what the market pays for them and can always fall to zero.

Such tokens are the digital equivalent of real assets. Primarily stocks, bonds and real estate. It is these that are issued during STO and it is these that allow for the tokenisation of precious metalsor luxury cars

New token types

Non-fungible tokens

In opposition to fungible tokens are non-fungible tokens. Non-exchangeability in their case means that each token in a given system is unique. Such tokens have no standard value and often do not allow equivalent exchange of one for another. Each token represents different, unique ownership or identity information. The primary uses of non-fungible tokens are:

Certification 

This is potentially the most important application of this type of token. A token can be used to prove the origin of a document, a piece of data or any physical object in the real world. And because such tokens cannot be duplicated and the information they contain cannot be manipulated, we can be sure that such a token - a certificate of authenticity - will never be counterfeited. 

Securing the authenticity of works of art, luxury fashion or exotic cars - the possibilities of such tokens go much further. If land records were transferred to the blockchain, ownership would just be a matter of having a token corresponding to the property. The same goes for resource extraction rights, or water rights. Non-fungeable tokens have countless potential applications wherever certification of ownership is important. 

 Identity of the things

Like people, products, machines and raw materials can also have a digital identity.  IDoT is a key component of blockchain-based supply chains and IoT applications. 

For example, by assigning unique tokens to products, it becomes possible to trace their entire journey in the supply chain - from raw material extraction to production to sale to retail customers. This not only makes it possible to secure their origin, but also to control transport conditions, especially important in industries such as food. If a spoiled chicken ends up in a supermarket, tokens make it easy to determine at which point in the chain the problem occurred and which party is responsible..  

New token types

What new types of tokens can be used in your project?

  • ERC-721
  • ERC-223
  • ERC- 777
  • ERC-1155 
  • FabToken

ERC-721

The most important advantage of the ERC-721 standard is the ease of creating unalterable tokens. Introduced in 2018, it finds its use wherever distinguishable assets need to be tracked. 

This type of token has gained buzz with the rise in popularity of Ethereum-based collectible game CryptoKitties.

New token types
Source: CoinMetrics Blog

ERC-223

This token is intended to solve the UX shortcomings of other ERC tokens. Occasionally a user will send the token to the wrong wallet address or worse, a smart contract, thus losing it forever. This feature of other standards can effectively deter less familiar users and limit the widespread adoption of a solution. 

ERC-223 solves this problem by alerting users who accidentally send tokens to a smart contract address and cancelling the transaction. 

ERC- 777

The aim of implementing ERC-777 was to improve on the basic ERC-20 standard. What makes it unique is that it introduces a wide range of transaction handling mechanisms while being backwards compatible with ERC-20. 

Among other things, the standard allows for the definition of operators to send tokens on behalf of a given user and gives holders far greater control over their tokens. One of its most innovative features is the option to mint or burn tokens. It also has the potential to significantly simplify token transfers compared to other standards. 

ERC-1155 

ERC-1155 is a multi token standard. This means that it allows any combination of fungible and non-exchangeable tokens to be managed under a single contract, including the transfer of multiple token types simultaneously.

FabToken

Unlike ERC standard tokens, which are created using the Ethereum protocol, FabToken runs on the Hyperledger Fabric Blockchain. 

This system provides a simple interface to tokenise resources on the Fabric protocol, using the security and validation mechanisms that the Fabric protocol provides. Importantly, users do not need to use smart contracts to create or manage tokens. Tokens can establish immutability and ownership of a resource without requiring the user to write and validate complex business logic. Owners can use trusted partners to execute and validate transactions, without having to rely on partners from other organisations. 

Want to know which token will best suit your project needs? Our experts will be happy to answer all your tokenization questions!

Most viewed


Never miss a story

Stay updated about Nextrope news as it happens.

You are subscribed

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?

Follow us to stay updated!

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
Nextrope Logo

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