Crypto Regulations are coming…

a.shah

19 Oct 2020
Crypto Regulations are coming…

Understanding crypto regulation is an integral step in learning about the blockchain industry. On our Nextrope blog, we decode the existing ecosystem of regulation, recent regulatory changes and barriers against new regulation.

The Status-Quo of Crypto Regulation

Cryptocurrency’s decentralized nature has prevented governments from exercising universal control and regulations. This barrier prompted varying approaches to crypto regulation across countries.

Source: Visual Capitalist

1) Extremely Tight Regulation

Countries such as Algeria, Bolivia, Morocco, Nepal, Pakistan, and Vietnam have completely prohibited cryptocurrency. 

2) Tight Regulation

Qatar and Bahrain permit cryptocurrency-related activities strictly outside the borders. 

3) Slightly Tight Regulation

Instead of directly outlawing crypto-related activities, Bangladesh, Iran, Thailand, Lithuania, Lesotho, China, and Colombia have barred their financial institutions from executing crypto-related transactions.

4) Medium Regulation 

Australia, Canada, and the Isle of Man have amended their counterterrorism and money laundering laws to regulate cryptocurrency markets and mandate  due diligence requirements on their financial institutions.

5) Slightly Weak Regulation

Spain, Belarus, the Cayman Islands, and Luxembourg are establishing crypto-friendly regulations with the goal of attracting tech investments. 

6) Weak Regulation

Belgium, South Africa, and the United Kingdom have determined the current cryptocurrency market to be inconsequentially small and are yet to establish any regulations. 

7) Extremely Weak Regulation

France, Marshall Islands, Venezuela, the Eastern Caribbean Central Bank (ECCB) member states and Lithuania are in efforts of establishing their own cryptocurrency systems. 

Why is Regulation Necessary?

Wei Zhou, the chief financial officer of the cryptocurrency exchange, Binance, spoke out in support of the cryptoregulation. Experts such as Zhou recognize that the human elements of cryptocurrency makes the system vulnerable to fraud, money laundering, terrorism and organized crime. 

Despite some users’ concerns regarding the potential negative effects of crypto regulations on its trading values and innovation, major crypto regulations have empirically never posed a long-term impact on the share price of Bitcoin, save for some immediate volatility. Further, crypto users widely believe that regulations provide the much needed investor protections that offsets its potential drawbacks. 

Source: Finance Magnates

Recent Regulatory Actions 

European Union (EU) – Proposal for a Regulation on Markets in Crypto-assets (MiCa)

On September 24, 2020, the EU Commission enacted the regulations on Markets in Crypto-assets (MiCa). MiCa’s goals are (1) reducing the rate of cash payment, which currently make up 78% of all payments in the eurozone, and (2) stimulating responsible innovation and competition among financial services providers in the EU. 

MiCA plans to differentiate between crypto-assets governed by EU legislation from crypto-assets that fall outside its scope. Prof. Rasa Karpandza, a professor of Economics and Finance at New York University Abu Dhabi and EBS Business School, claimed that “In order to achieve widespread usage as an alternative to fiat options, blockchain and crypto assets need to be classified appropriately and this is a good first step”.

In order to harmonize the EU market and prevent market regulatory fragmentation, the EU Commission published a single set of immediately applicable rules for the EU's Single Market as opposed to a "Directive", which leaves Member State discretion through the need of national transposition. I believe that MiCA will effectively bring together the fragmented national crypto-asset legal regimes within the EU.

United States (US) – Stablecoin guidance

On September 21, 2020,the Securities and Exchange Commission (SEC) published stablecoin guidance, laying out the legal implications of  cryptocurrencies backed by fiat currencies for the first time. Stablecoin (cryptocurrencies designed to minimize volatility of price and usually backed by fiat money) issuers have been using U.S. banks for years but in an unclear regulatory environment. Through the new guidance, the SEC plans to better ensure safety for the federally regulated banks as they provide services to stablecoin issuers.

Venezuela – Decentralized Exchange

On October 2,2020, the National Superintendency of Securities of Venezuela (Sunaval) authorized the operation of a decentralized electronic exchange. This legalized the exchange of shares, fiat money, securities, debt securities and cryptocurrencies. Sunaval plans to decrease the commissions to nearly 0% in order to encourage its use.

Israel – Treatment of cryptocurrency as Fiat

On September 22, 2020, the Israeli legislature proposed the amendment of existing tax law. While the current income tax policy taxes digital currencies 25% anytime it is converted into fiat, the new legislation seeks to (1) have digital currencies be treated like fiat for tax purposes and (2) exempt gain taxes on digital currencies.

Malaysia – Approval of Cryptocurrency exchange

On January 15, 2019, Malaysia passed “The Capital Markets and Services (Prescription of Securities) (Digital Currency and Digital Token) Order 2019”. Designed to regulate DAX operators, the Order was followed by the legalization of a cryptocurrency exchange agency’s operation. 

Nigeria – Beginning of regulatory conversation

Source: Google Trends, Regions with highest bitcoin searches

Bitcoin has become increasingly popular in Nigeria (highest google searches in the World) and the Nigerian SEC is working to recognize cryptocurrencies as financial securities and establishing safety regulations. The Nigerian SEC claimed that “the general objective of regulation is not to hinder technology or stifle innovation, but to create standards that encourage ethical practices”,  advocating that this will protect investors’ interests and promote transparency. 

South Korea – Permit System for Crypto Exchanges

On March 5, 2020, South Korea’s National Assembly passed a revised bill on the reporting and the use of special financial transaction information. The bill introduces a permit system for cryptocurrency exchanges as well as the plans to strengthen the Anti-Money Laundering (AML) system for virtual assets including cryptocurrency.

China – Digital Yuan

China has been working vigorously on the digital yuan, though cryptocurrency is formally banned in the country. Digital yuan targets the dominance of tech giants, such as Alibaba and Tencent, in the digital payments sector. However, the government remains cautious in its approach to both its own cryptocurrency and digital assets and is yet to issue regulations.

Barriers against Regulations?

1) Economic Strategy

Because some governments believe that crypto regulation will impede growth and innovation, they intentionally avoid implementing regulations as an economic strategy. These governments also believe that while high barriers to entry through stricter regulation can benefit users by providing security, it may also curtail potential projects through financial and regulatory strains.

2) Incomplete Understanding of Cryptomarket

Current understanding of cryptocurrency, of users, economists and policymakers, remains incomplete, partly due to the volatility of the crypto market and its small size. Thus, governments are hesitant to implement hasty regulations.

3) Threat to National Economic Sovereignty

Countries, specifically the developing nations, believe that cryptocurrency will be harmful to their economic sovereignty. Decentralized finance has the potential to disrupt the financial services sector. 

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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