Video Art Tokenization in 2023

Karolina

24 Aug 2023
Video Art Tokenization in 2023

The vast domain of the artistic sphere features video art as a relatively recent addition, yet one that has established its unique place. As 2023 began, video art gained greater attention and proved to be more than a mere fad. Foundational exhibitions and focused critiques merely touched upon the growth of this art form. However, an interesting metamorphosis was unfolding amidst the praise and curiosity, fueled by the digital era's defining feature: blockchain technology. This led to the emergence of 'video art tokenization', an innovative blend of artistry and tech that could transform the principles and value perception of video art, possibly addressing long-standing issues related to its collectability.

Video Art's Development and Importance

Starting as an avant-garde genre, video art was often regarded as the defiant counterpart to traditional artistic forms. It challenged established norms by providing artists with a vibrant platform where motion replaced stillness, and audio-visual stories held sway. By early 2023, organizations like MoMA underscored its international importance through groundbreaking exhibitions such as "Signals: How Video Transformed the World."

Nevertheless, its inherent qualities presented singular problems. Unlike the physical limitations of paintings or sculptures, video art's digital nature enabled infinite replication. Every copy maintained the original's legitimacy, democratizing the art form while simultaneously detracting from its perceived value based on conventional market standards. In a realm where an artwork's rarity frequently dictated its market worth, video art presented a dilemma. Collectors struggled to comprehend notions of originality and valuation. Why acquire an original if indistinguishable duplicates possessed equal artistic merit?

Video art's incompatibility with traditional art market principles – where scarcity is highly valued – poses not only economic but also philosophical challenges. It urges us to reconsider our understanding of worth, authenticity, and the core essence of art in today's digital age. The importance of video art thus goes beyond its visual allure, placing it at the crossroads of artistic expression, technological innovation, and market dynamics.

The Emergence of NFTs and Video Art Tokenization in the Artistic Sphere

Blockchain technology's inception, followed by the art world's introduction to Non-Fungible Tokens (NFTs), has sparked a transformative revolution. Essentially, an NFT is a distinct digital certificate of authenticity, securely stored on a decentralized digital ledger that confirms the originality of a digital asset. As the digital domain increasingly intertwines with our physical existence, NFTs have made their mark, particularly in supporting the value of digital artwork.

NFTs started as quiet murmurs within specialized digital art circles but quickly gained traction, drawing the interest of artists, galleries, and investors. They provided an answer to the longstanding problem of digital reproduction without devaluation, tackling a central issue for the art community – how to authenticate and appraise digital art when duplication is effortless.

Traditionally, artists did not directly profit from secondary sales of their works; however, NFTs offered newfound empowerment. Artists could now secure royalties from resales through "smart contracts" embedded in NFTs, establishing a viable financial framework that had been previously unattainable.

Moreover, video art tokenization through NFTs revitalized the dynamics of the art market. Auction houses initially expressed skepticism but later adopted this trending wave as record-breaking sales of digital artworks converted to NFTs made headlines. Motivated by the integration of technology and artistry, collectors started to view NFTs as more than mere curiosities – they became genuine investment prospects, signifying a shift in how art is evaluated and exchanged.

Nevertheless, NFTs' true brilliance in the artistic world extends beyond economics; it broadens artistic expression's horizons. Digital artists who were once marginalized within the broader artistic journey moved to center stage as leaders in an era where art transcends visual or auditory limitations and becomes a dynamic, interactive experience.

Examining Tokenized Video Art Collections

The fusion of video art and blockchain technology gives rise to an intriguing world of tokenized video art collections, challenging conventional standards and presenting groundbreaking opportunities for both artists and collectors.

Origins and Development

Tokenized video art collections stem from the unique characteristics of video art, which is dynamic, replicable, and inherently digital, as well as the revolutionary potential of NFTs. When artists started tokenizing their video works, a specific genre of collections emerged that pushed the limits of both video art and the NFT domain.

Prominent Collections and Innovators

The Akeroyd Collection, Shane Akeroyd's online media library, serves as a powerful example of what can be accomplished by blending traditional video art with tokenization's avant-garde features. Housing creations from influential artists like Cory Arcangel, Apichatpong Weerasethakul, and Theaster Gates, this collection demonstrates an exceptional fusion of classical video art and cutting-edge tokenization.

Artwrld is another noteworthy platform that showcases tokenized video collections from celebrated artists such as Shirin Neshat and Paul Pfeiffer. This platform has become a guiding light for digital video artists who want to capitalize on blockchain benefits and engage with a broader and more appreciative audience.

Distinctive Characteristics and Advantages

Enhanced transparency and traceability stand out among the most transformative aspects of tokenized video art collections. Unique digital records of provenance accompany each tokenized piece, adding layers of trust and authenticity while empowering potential buyers to examine the artwork's background, ownership changes, and previous valuations. This shift marks a significant departure from traditional art sales plagued with ambiguous provenance.

Furthermore, tokenizing video art addresses its inherent reproducibility by attaching value to once-easily replicated works. Tokenizing a piece includes a unique digital certificate signifying its originality and market worth.

Potential and Obstacles Ahead

Although tokenized video art collections have undoubtedly had a significant impact, they still face challenges, including concerns about copyrights, exhibition rights, and the broader legal framework governing digital ownership. However, as artists and platforms persist in experimenting, innovating, and stretching boundaries, the possibility for video art tokenization to revolutionize the essence of art collecting is tangible.

In conclusion, the melding of video art with NFTs takes us to the verge of a new epoch. A time when the intangible gains value, duplication transforms into uniqueness, and video art earns its place among highly coveted collectibles.

Tackling Obstacles and Envisioning the Future

The combination of video art and NFT ecosystem has created many opportunities for artists, collectors, and platforms; however, it also involves several complexities. This marriage of art and technology is innovative but comes with a series of issues that must be addressed for enduring success.

Legal Uncertainties and Intellectual Property

A major concern with video art tokenization is the unclear legal rights. How do exhibition rights adapt in a decentralized digital realm? What specific rights are granted to collectors when they obtain a tokenized video artwork, particularly regarding public displays or reproductions?

Traditional Market Ideals and Comprehension

The conventional art market, with its roots in physical art appreciation dating back centuries, may require time to grasp and welcome the intricacies of video art tokenization. The notion that a digitally reproducible piece can hold substantial value might defy long-established market perceptions. It becomes essential to educate traditional galleries and collectors about the inherent worth and possibilities offered by tokenized video art.

Looking Forward: A Hopeful Tomorrow

In spite of these challenges, a bright future awaits. Advancements in blockchain technology will likely reduce technical obstacles by becoming more accessible and user-friendly. As legal structures adapt to the rapid advancements of digital innovations, transparent guidelines pertaining to ownership and rights will develop.

Efforts such as educational initiatives, workshops, and partnerships between art institutions and tech professionals can help bridge the gap, expanding the understanding of video art tokenization's potential to broader audiences.

Conclusion

The joining of video art and NFTs represents more than just a momentary craze; it marks an evolutionary leap in the world of art, unifying innovation with tradition. As artists experience newfound liberation and collectors delve into uncharted territories, the challenges that surface are simply growing pains of a sector on the cusp of transformation. Reflecting on the impact of technology and creativity, it's clear that we stand at a critical turning point. A vast landscape of potential lays ahead, ready to be adorned with the vivid hues of innovation, collaboration, and forward-thinking vision.

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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!