Highlights

• In this blog series, we summarize our research team's findings and invite you to dig deeper into the original reports.

• This article provides a preview of Binance Research's latest report that discusses the intersection between artificial intelligence (AI) and crypto.

• Currently, there are some use cases for AI in the crypto ecosystem, but we are still in the early stages of development and more potential remains to be unlocked.

Thanks to Binance Research, you can leverage industry-level analysis on the processes shaping the Web3 world. By sharing these reports, we hope to empower our community with the latest knowledge from the field of crypto research. If you want to dig deeper, the full reports are available on the Binance Research website.

AI, blockchain technology, and cryptocurrencies are all examples of disruptive technologies. As such, each of them innovated traditional systems and gave rise to new worlds of possibilities that we have yet to explore.

Currently, there are several areas where AI is being integrated with crypto, improving existing processes and bringing numerous added benefits. AI often plays an auxiliary role in improving the overall user experience. However, as with any emerging technology, there are both benefits and risks to consider.

Today we will explore the intersection between artificial intelligence (AI) and digital assets by examining their benefits, challenges, and key use cases by sector.

Ecosystem Overview

While AI has recently gained widespread popularity with large language models (LLMs) such as OpenAI's ChatGPT, developers have been working on the underlying technology for decades. Despite this, we are still in the early stages, so there is a lot of work to do to reach mass adoption and unlock the full potential of AI. Specifically, the intersection of AI and blockchain technology can unlock several new possibilities.

The use of AI in the crypto space is growing rapidly. Today, technology is used in various aspects of the crypto ecosystem and often plays an auxiliary role in improving the overall user experience.

Ecosystem Overview

Fuente: Binance Research

Broadly speaking, the AI ​​ecosystem in the crypto space can be divided into two parts: smart ledgers and AI-powered services. In this context, smart ledgers are networks that use AI to automate tasks and track them on the blockchain. Along with these, we find AI-powered services, products that use AI in their backend in order to offer various utilities for users.

Benefits and challenges of AI

These are some of the benefits that AI in its current state brings to the crypto sector:

• Improved efficiency: AI can help automate tasks and decision-making processes, thereby improving efficiency and productivity.

• Better analytics and reporting: AI can help with big data analytics by acting as an additional check to improve accuracy. Analyzing huge amounts of data is often time-consuming; AI also helps optimize the process.

• Improved risk management processes: From supplementing smart contract audits to automating risk monitoring processes, AI can help identify red flags and improve risk management.

Of course, any new technology presents new challenges as it is implemented. Key challenges facing today's AI ecosystem as it is applied in the digital assets space include:

• Limited adoption: AI-focused crypto dApps gained some traction, but only among a small group of savvy users. This is understandable in a relatively young space like this, but driving more real-world use cases will be essential to achieving greater adoption.

• Utility vs. proof of concept: While several projects are actively developing in this area and seeking to integrate AI, many are still in the proof of concept stage. Usable products are key to driving adoption and growth in this space.

• Focus on data privacy: Given AI's reliance on large amounts of data, privacy is critical, especially in how data is used and protected. Data protection, its use and its security policies are of utmost importance.

• Technical challenges: Integrating AI and blockchain technology can be technically challenging, requiring project teams to have expertise in both areas. The development of common standards and continued research in these fields will help drive innovation.

Use cases in DeFi

Within decentralized finance (DeFi), we have seen AI complement the smart contract audit process, facilitate trade automation, and pair with predictive analytics to offer more accurate forecasts, among other innovations. Let's explore the first 2 innovations further.

Smart contract audits

Smart contract audits involve inspecting and analyzing smart contract code to identify potential security or technical issues. Audits are a standard protection measure for projects in all sectors of the crypto ecosystem. They are especially important in DeFi, given the amount of funds that smart contracts safeguard.

AI can complement the smart contract audit process. For example, AI tools identify potential red flags during initial security reviews. Experts can then review these potential vulnerabilities, provide solutions, and conduct additional testing as necessary.

AI can basically function as an extra set of eyes in the audit process.

Use case: ChatGPT

ChatGPT is designed to generate human-like responses to natural language input and can help automate tasks. Developers conducted experiments to understand its capabilities, in particular whether it can be used to improve smart contract code.

In one such experiment, CertiK, a blockchain security company, compared audits performed by ChatGPT with those performed by a human auditor. Thus, he found that ChatGPT correctly mentioned several common security conflicts, but struggled with more complicated problems.

Security Audit: ChatGPT vs. human analysis

Source: CertiK

These findings show that while AI models like ChatGPT can help pinpoint common issues, they are not enough on their own and work best as a complement. Manual audits by security experts are still essential for thorough and accurate analysis.

Intelligent trade automation

Monitoring trading positions in DeFi can be difficult and time-consuming, especially during periods of market volatility. While trading bots are nothing new, they can be significantly improved through AI. Additional features and more sophisticated tools are becoming possible thanks to the development and integration of AI in DeFi.

Overall, intelligent automation tools have the ability to improve user experience by streamlining complicated processes and making them more intuitive for DeFi users. In doing so, these tools have the potential to advance the adoption of DeFi applications.

Use cases for NFT

In the NFT space, AI has led to the creation of generative art, smart and interactive NFTs, and tools to optimize data analysis processes, among other innovations. Below, we will explore the first two.

Generative art

Generative art is creative work through the use of an autonomous system. Several NFT projects use AI for such purposes. The creator can enter parameters, rules or restrictions, such as patterns, colors, shapes, etc., and the AI ​​will generate artworks based on this framework.

Using AI, generative art allows creators to make one-of-a-kind pieces that are infinitely scalable, but still maintain a consistent style with the collection.

Case study: Bixel

Binance's Bixel is an AI NFT generator that allows users to create unique AI-created images by simply entering text or an image into the system. It uses AI algorithms to create images based on entered patterns and features.

Users can be more specific and include details such as color schemes, composition, or elements they want to see in the artwork. When they are satisfied with the result, they will be able to mint their creations as NFTs on the BNB Chain.

By analyzing multiple data points, an AI image generator can create original and unique images with styles or elements similar to those in the data set. Such technology has the potential to create realistic images for video games and films at scale, and can also be used to generate design prototypes.

AI image generation with Binance Bixel

Fuente: Binance

Some more notable generative art NFT projects were very successful and produced valuable collections selling for six figures.

iNFT

With AI, previously static NFTs are being transformed into intelligent NFTs (iNFTs) that can communicate with you. Basically, an iNFT brings the underlying NFT to life with the use of the generative powers of AI.

iNFTs integrate both AI and NFT technology to offer interactive tokens with intelligent traits and reasoning abilities. Using AI, they can analyze data to learn and evolve their personality based on real-time interactions. Conceptually, AI allows the iNFT to absorb new metadata to shape its future interactions and personality.

This could have profound implications for Web3 video games and the future of the metaverse in general, where in-game characters would be significantly more interactive and conversations would become more real-life-like.

With the look set in the future

The union of such revolutionary technologies as AI and blockchain opens a world of possibilities and possible use cases. It has already made us reconsider the way we interact with technology by tackling old problems in new ways.

However, it is key to note that while the conceptual use cases may seem interesting, crypto AI projects have yet to reach significant adoption. This suggests that such projects may be “nice to have,” but not essential, at least based on the current level of innovation in the space.

However, emerging technologies take time to develop and reach a more definitive state. Looking ahead, the continued advancement of AI and crypto technology may lead to more use cases that prove useful to various stakeholders in the ecosystem. We'll have to wait and see what the intersection of AI and crypto has in store for Web3 users.

Binance Research

Binance Research team members are committed to providing objective, independent and in-depth analysis of the crypto space. They publish informative opinions on topics related to Web3, including but not limited to the crypto ecosystem, blockchain applications, and the latest developments in the market.

This article is an excerpt from the full report, which presents an in-depth analysis of more use cases and real-life examples in the DeFi and NFT sectors, Decentralized Autonomous Organizations (DAOs), and others. It also includes a discussion on the potential of AI in the crypto space, with perspectives from prominent thought leaders in the space. With so much valuable content, you won't want to miss out on this exclusive information.

To read the full version of the report, click here. You can find other in-depth reports on Web3 on the Insights and Analysis page of the Binance Research website. Don't miss the opportunity to empower yourself with the latest information in the field of cryptocurrency research.

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