Nextrope on Economic Forum 2024: Insights from the Event

Kajetan Olas

14 Sep 2024
Nextrope on Economic Forum 2024: Insights from the Event

The 33rd Economic Forum 2024, held in Karpacz, Poland, gathered leaders from across the globe to discuss the pressing economic and technological challenges. This year, the forum had a special focus on Artificial Intelligence (AI and Cybersecurity, bringing together leading experts and policymakers.

Nextrope was proud to participate in the Forum where we showcased our expertise and networked with leading minds in the AI and blockchain fields.

Economic Forum 2024: A Hub for Innovation and Collaboration

The Economic Forum in Karpacz is an annual event often referred to as the "Polish Davos," attracting over 6,000 participants, including heads of state, business leaders, academics, and experts. This year’s edition was held from September 3rd to 5th, 2024.

Key Highlights of the AI Forum and Cybersecurity Forum

The AI Forum and the VI Cybersecurity Forum were integral parts of the event, organized in collaboration with the Ministry of Digital Affairs and leading Polish universities, including:

  • Cracow University of Technology
  • University of Warsaw
  • Wrocław University of Technology
  • AGH University of Science and Technology
  • Poznań University of Technology

Objectives of the AI Forum

  • Promoting Education and Innovation: The forum aimed to foster education and spread knowledge about AI and solutions to enhance digital transformation in Poland and CEE..
  • Strengthening Digital Administration: The event supported the Ministry of Digital Affairs' mission to build and strengthen the digital administration of the Polish State, encouraging interdisciplinary dialogue on decentralized architecture.
  • High-Level Meetings: The forum featured closed meetings of digital ministers from across Europe, including a confirmed appearance by Volker Wissing, the German Minister for Digital Affairs.

Nextrope's Active Participation in the AI Forum

Nextrope's presence at the AI Forum was marked by our active engagement in various activities in the Cracow University of Technology and University of Warsaw zone. One of the discussion panels we enjoyed the most was "AI in education - threats and opportunities".

Our Key Activities

Networking with Leading AI and Cryptography Researchers.

Nextrope presented its contributions in the field of behavioral profilling in DeFi and established relationships with Cryptography Researchers from Cracow University of Technology and the brightest minds on Polish AI scene, coming from institutions such as Wroclaw University of Technology, but also from startups.

Panel Discussions and Workshops

Our team participated in several panel discussions, covering a variety of topics. Here are some of them

  • Polish Startup Scene.
  • State in the Blockchain Network
  • Artificial Intelligence - Threat or Opportunity for Healthcare?
  • Silicon Valley in Poland – Is it Possible?
  • Quantum Computing - How Is It Changing Our Lives?

Broadening Horizons

Besides tuning in to topics that strictly overlap with our professional expertise we decided to broaden our horizons and participated in panels about national security and cross-border cooperation.

Meeting with clients:

We had a pleasure to deepen relationships with our institutional clients and discuss plans for the future.

Networking with Experts in AI and Blockchain

A major highlight of the Economic Forum in Karpacz was the opportunity to network with experts from academia, industry, and government.

Collaborations with Academia:

We engaged with scholars from leading universities such as the Cracow University of Technology and the University of Warsaw. These interactions laid the groundwork for potential research collaborations and joint projects.

Building Strategic Partnerships:

Our team connected with industry leaders, exploring opportunities for partnerships in regard to building the future of education. We met many extremely smart, yet humble people interested in joining advisory board of one of our projects - HackZ.

Exchanging Knowledge with VCs and Policymakers:

We had fruitful discussions with policymakers and very knowledgable representatives of Venture Capital. The discussions revolved around blockchain and AI regulation, futuristic education methods and dillemas regarding digital transformation in companies. These exchanges provided us with very interesting insights as well as new friendships.

Looking Ahead: Nextrope's Future in AI and Blockchain

Nextrope's participation in the Economic Forum Karpacz 2024 has solidified our position as one of the leading, deep-tech software houses in CEE. By fostering connections with academia, industry experts, and policymakers, we are well-positioned to consult our clients on trends and regulatory needs as well as implementing cutting edge DeFi software.

What's Next for Nextrope?

Continuing Innovation:

We remain committed to developing cutting-edge software solutions and designing token economies that leverage the power of incentives and advanced cryptography.

Deepening Academic Collaborations:

The partnerships formed at the forum will help us stay at the forefront of technological advancements, particularly in AI and blockchain.

Expanding Our Global Reach:

The international connections made at the forum enable us to expand our influence both in CEE and outside of Europe. This reinforces Nextrope's status as a global leader in technology innovation.

If you're looking to create a robust blockchain system and go through institutional-grade testing please reach out to contact@nextrope.com. Our team is ready to help you with the token engineering process and ensure your project’s resilience in the long term.

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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

AI-Driven Frontend Automation: Elevating Developer Productivity to New Heights

Gracjan Prusik

11 Mar 2025
AI-Driven Frontend Automation: Elevating Developer Productivity to New Heights

AI Revolution in the Frontend Developer's Workshop

In today's world, programming without AI support means giving up a powerful tool that radically increases a developer's productivity and efficiency. For the modern developer, AI in frontend automation is not just a curiosity, but a key tool that enhances productivity. From automatically generating components, to refactoring, and testing – AI tools are fundamentally changing our daily work, allowing us to focus on the creative aspects of programming instead of the tedious task of writing repetitive code. In this article, I will show how these tools are most commonly used to work faster, smarter, and with greater satisfaction.

This post kicks off a series dedicated to the use of AI in frontend automation, where we will analyze and discuss specific tools, techniques, and practical use cases of AI that help developers in their everyday tasks.

AI in Frontend Automation – How It Helps with Code Refactoring

One of the most common uses of AI is improving code quality and finding errors. These tools can analyze code and suggest optimizations. As a result, we will be able to write code much faster and significantly reduce the risk of human error.

How AI Saves Us from Frustrating Bugs

Imagine this situation: you spend hours debugging an application, not understanding why data isn't being fetched. Everything seems correct, the syntax is fine, yet something isn't working. Often, the problem lies in small details that are hard to catch when reviewing the code.

Let’s take a look at an example:

function fetchData() {
    fetch("htts://jsonplaceholder.typicode.com/posts")
      .then((response) => response.json())
      .then((data) => console.log(data))
      .catch((error) => console.error(error));
}

At first glance, the code looks correct. However, upon running it, no data is retrieved. Why? There’s a typo in the URL – "htts" instead of "https." This is a classic example of an error that could cost a developer hours of frustrating debugging.

When we ask AI to refactor this code, not only will we receive a more readable version using newer patterns (async/await), but also – and most importantly – AI will automatically detect and fix the typo in the URL:

async function fetchPosts() {
    try {
      const response = await fetch(
        "https://jsonplaceholder.typicode.com/posts"
      );
      const data = await response.json();
      console.log(data);
    } catch (error) {
      console.error(error);
    }
}

How AI in Frontend Automation Speeds Up UI Creation

One of the most obvious applications of AI in frontend development is generating UI components. Tools like GitHub Copilot, ChatGPT, or Claude can generate component code based on a short description or an image provided to them.

With these tools, we can create complex user interfaces in just a few seconds. Generating a complete, functional UI component often takes less than a minute. Furthermore, the generated code is typically error-free, includes appropriate animations, and is fully responsive, adapting to different screen sizes. It is important to describe exactly what we expect.

Here’s a view generated by Claude after entering the request: “Based on the loaded data, display posts. The page should be responsive. The main colors are: #CCFF89, #151515, and #E4E4E4.”

Generated posts view

AI in Code Analysis and Understanding

AI can analyze existing code and help understand it, which is particularly useful in large, complex projects or code written by someone else.

Example: Generating a summary of a function's behavior

Let’s assume we have a function for processing user data, the workings of which we don’t understand at first glance. AI can analyze the code and generate a readable explanation:

function processUserData(users) {
  return users
    .filter(user => user.isActive) // Checks the `isActive` value for each user and keeps only the objects where `isActive` is true
    .map(user => ({ 
      id: user.id, // Retrieves the `id` value from each user object
      name: `${user.firstName} ${user.lastName}`, // Creates a new string by combining `firstName` and `lastName`
      email: user.email.toLowerCase(), // Converts the email address to lowercase
    }));
}

In this case, AI not only summarizes the code's functionality but also breaks down individual operations into easier-to-understand segments.

AI in Frontend Automation – Translations and Error Detection

Every frontend developer knows that programming isn’t just about creatively building interfaces—it also involves many repetitive, tedious tasks. One of these is implementing translations for multilingual applications (i18n). Adding translations for each key in JSON files and then verifying them can be time-consuming and error-prone.

However, AI can significantly speed up this process. Using ChatGPT, DeepSeek, or Claude allows for automatic generation of translations for the user interface, as well as detecting linguistic and stylistic errors.

Example:

We have a translation file in JSON format:

{
  "welcome_message": "Welcome to our application!",
  "logout_button": "Log out",
  "error_message": "Something went wrong. Please try again later."
}

AI can automatically generate its Polish version:

{
  "welcome_message": "Witaj w naszej aplikacji!",
  "logout_button": "Wyloguj się",
  "error_message": "Coś poszło nie tak. Spróbuj ponownie później."
}

Moreover, AI can detect spelling errors or inconsistencies in translations. For example, if one part of the application uses "Log out" and another says "Exit," AI can suggest unifying the terminology.

This type of automation not only saves time but also minimizes the risk of human errors. And this is just one example – AI also assists in generating documentation, writing tests, and optimizing performance, which we will discuss in upcoming articles.

Summary

Artificial intelligence is transforming the way frontend developers work daily. From generating components and refactoring code to detecting errors, automating testing, and documentation—AI significantly accelerates and streamlines the development process. Without these tools, we would lose a lot of valuable time, which we certainly want to avoid.

In the next parts of this series, we will cover topics such as:

Stay tuned to keep up with the latest insights!