NFT and Gaming: Chainlink Use Cases

Karolina

09 Feb 2024
NFT and Gaming: Chainlink Use Cases

Enter Chainlink, a decentralized oracle network that plays a pivotal role in bridging the gap between blockchain smart contracts and real-world data. Its relevance to gaming and NFTs is profound, particularly through its Verifiable Randomness Function (VRF). Chainlink's VRF brings a new level of integrity and fairness to the process of generating in-game items and NFTs, ensuring that the rarity and uniqueness of these assets are genuinely random and tamper-proof.

MUST READ: "What is Chainlink"

Understanding NFTs in Gaming

NFT Chainlink

Explanation of NFTs and Their Unique Properties

NFTs, or Non-Fungible Tokens, represent uniquely identifiable assets that are verified on a blockchain. NFTs are distinct, with each token having a unique set of attributes and value. This uniqueness and the ability to prove ownership securely make NFTs particularly appealing for the gaming industry, where they can represent anything from in-game items and collectibles to characters and virtual land.

The Significance of NFTs in Gaming for Creating Rare and Unique In-Game Items

In gaming, NFTs bring fresh opportunities for both players and developers. Players gain genuine ownership of in-game assets, enabling trade, sale, or use across various games and platforms. Developers find new paths in game design, engagement, and monetization. Crafting rare and unique NFT items boosts the gaming experience, fosters community, and allows players to gain real-world value from gameplay.

Chainlink's Role in Enhancing NFT Rarity and Value

Overview of Chainlink Verifiable Randomness Function (VRF) and Its Importance

Chainlink VRF revolutionizes blockchain with secure, verifiable randomness, crucial for gaming and NFT minting. Its generated randomness is blockchain-verifiable, allowing independent audits to confirm its fairness and lack of external influence.

How Chainlink VRF Ensures the Fair Minting of Rare NFTs

For the gaming industry, Chainlink VRF ensures fair and transparent NFT minting. It helps determine the attributes and rarity of new NFTs, like character skins or weapons, guaranteeing equal chances for players to get rare items. This builds trust in the gaming community and boosts NFT value, as players trust the fairness of item acquisition.

Chainlink VRF: Revolutionizing Gaming Randomness

Chainlink VRF Applications in Gaming

Chainlink's Verifiable Random Function (VRF) has emerged as a cornerstone technology for blockchain-based applications, particularly in the gaming sector, where randomness plays a critical role in various aspects ranging from character creation to in-game dynamics and rewards distribution.

Detailed Explanation of What Chainlink VRF Is and How It Works

Chainlink VRF combines block data that is still unknown when the request is made with the oracle node’s pre-committed private key to generate both a random number and a cryptographic proof. The VRF's smart contract will only accept the random number input if it has valid cryptographic proof, and the cryptographic proof can only be generated if the VRF process is tamper-proof. This ensures the randomness is provable and not manipulated, bringing fairness and transparency to the forefront of digital randomness applications.

Examples of Gaming Applications Utilizing Chainlink VRF for Randomness

Case Studies:

  • Aavegotchi. This blockchain game integrates Chainlink VRF to mint rare NFTs called "Aavegotchis," each with randomly selected attributes when a player opens a Portal. This process ensures the rarity and uniqueness of each Aavegotchi, making the game more engaging and the assets more valuable.
  • Ether Legends. This digital collectible card game leverages Chainlink VRF to distribute rare crypto-backed NFT prizes to players. The randomness ensures fairness in awarding these prizes, making competitions more exciting and rewarding.
  • Axie Infinity. Known for its vibrant digital pet universe, Axie Infinity uses Chainlink VRF to generate random traits for Origin Axies. This randomness adds a layer of unpredictability and fairness to the breeding and battling mechanics within the game.

The Advent of Dynamic NFTs

Dynamic NFTs represent a groundbreaking shift in the NFT landscape, offering assets that can evolve over time based on real-world events, player achievements, or other criteria.

MUST READ: "What is Dynamic NFT"

Introduction to Dynamic NFTs and Their Evolving Nature

Unlike traditional NFTs, which are static and unchanging, dynamic NFTs can alter in rarity, appearance, or utility. This is made possible by smart contracts that can update the NFT's attributes in response to external data inputs or on-chain events, facilitated by oracles like Chainlink.

Examples of Dynamic NFTs in Sports:

  • MLB star Trey Mancini and NBA Rookie LaMelo Ball have both launched dynamic NFTs that change based on real-life performances and achievements. These NFTs not only serve as digital collectibles but also as living records of the athletes' careers, engaging fans in a novel and interactive manner.

GameFi and Chainlink

Chainlink in Gaming

The fusion of decentralized finance (DeFi) and gaming, known as GameFi, creates a new realm where players can earn real economic rewards through gameplay.

Exploring the Intersection of Gaming and DeFi (GameFi)

Chainlink supports the growing gaming ecosystem in several ways. It provides reliable data feeds for managing in-game economies. It also offers secure random number generation to ensure fair gameplay. Additionally, Chainlink automates smart contract executions, streamlining decentralized gaming operations.

No-Loss Savings Games

A notable DeFi innovation in gaming is no-loss savings games. These games blend entertainment with financial growth opportunities.

PoolTogether as an Example

PoolTogether is a platform that illustrates this concept. It uses Chainlink VRF to randomly select winners in its no-loss savings game. In this game, users pool their funds to collectively earn interest. One lucky participant wins the accumulated interest. Meanwhile, all other players receive their initial deposits back. Chainlink's secure randomness drives this model, promoting transparency and fairness. This encourages broader participation.

Chainlink in Sports and Esports Betting

Blockchain technology enhances sports and esports betting with transparency and fairness, thanks to decentralized oracles like Chainlink. These oracles securely bring real-world data to the blockchain, essential for settling bets on actual game outcomes.

Key Takeaways

Chainlink Gaming NFTs
  • Chainlink's Impact on Gaming and NFTs: Chainlink's technology, especially its Verifiable Randomness Function (VRF) and oracle services, has significantly impacted the gaming and NFT sectors by ensuring fairness, transparency, and trust in digital randomness and real-world data integration.
  • Future Potential of Chainlink in the Gaming Industry: The potential for Chainlink to revolutionize the gaming industry extends into areas like dynamic NFTs, GameFi, and decentralized finance applications within gaming ecosystems.

Conclusion

The transformative potential of Chainlink's technology in gaming and related sectors like NFTs and betting is profound. By enabling fair and transparent randomness, verifiable real-world data integration, and dynamic asset capabilities, Chainlink is not just enhancing existing gaming and betting ecosystems but also paving the way for entirely new gaming paradigms. As the landscape of blockchain gaming and NFTs continues to evolve, Chainlink's contributions are foundational to its growth and sustainability.

FAQ

How does Chainlink's Verifiable Randomness Function (VRF) enhance the gaming and NFT sectors?

  • Chainlink's VRF ensures fairness and transparency in generating in-game items and NFTs by providing genuinely random and tamper-proof rarity and uniqueness.

What are dynamic NFTs and how do they differ from traditional NFTs?

  • Dynamic NFTs can evolve over time based on real-world events or player achievements, offering a more interactive and engaging experience compared to static traditional NFTs.

What integration challenges exist with Chainlink?

  • Issues like scalability and adoption with traditional platforms.

How does Chainlink protect NFT transactions?

  • Through secure data handling and fraud prevention mechanisms.

More about this Topic on Nextrope Blog

  1. What is Chainlink?
  2. Chainlink vs Polkadot
  3. Chainlink in DeFi: Use Cases
  4. Chainlink vs. Avalanche: Exploring the Blockchain Frontier
  5. Authorization and Identity: Chainlink Use Cases
  6. Chainlink and On-Chain Finance Use Cases

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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