Binance Research: AI in Crypto – Exploring Use Cases and Possibilities
In this blog series, we summarize our research team’s findings, inviting you to dive deeper into the original reports.
This article previews the recent Binance Research report discussing the intersection between artificial intelligence (AI) and crypto.
Currently, a handful of AI use cases in crypto exist, but we are still in the early stages of development, and more potential is yet to be unlocked.
Thanks to Binance Research, you can take advantage of industry-grade analysis on the processes that shape Web3. By sharing these insights, we hope to empower our community with the latest knowledge from the field of crypto research. For a deeper dive, the full reports are available on the Binance Research website.
AI, blockchain, and cryptocurrency are all examples of disruptive technologies. As such, they have each revolutionized traditional systems and opened new worlds of possibility we are yet to explore.
Currently, there are several areas where AI is being integrated with crypto, enhancing existing processes and bringing numerous added benefits. AI generally plays a supporting role in improving the overall user experience. However, as is the case with any emerging technology, there are both benefits and risks to be mindful of.
Today, we will explore the intersection of artificial intelligence (AI) and digital assets by examining its benefits, challenges, and key use cases by sector.
While AI has recently gained widespread popularity with large language models (LLMs) like OpenAI’s ChatGPT, developers have been working on the underlying technology for decades. Despite this, we are still in the early stages, and more work needs to be done for achieving widespread adoption and unlocking AI’s full potential. Specifically, the intersection of AI and blockchain can unlock numerous new possibilities.
The use of AI in crypto is growing rapidly. Today, the technology is employed in many aspects of crypto and generally plays a supporting role in improving the overall user experience.
Source: Binance Research
Broadly speaking, the ecosystem of AI in crypto 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. Alongside these are AI-powered services – products that use AI on their backend to provide various utilities to users.
Benefits and challenges of AI
The main benefits of AI in crypto at its current stage include the following:
Improved efficiency – AI can help automate tasks and decision-making processes, improving efficiency and productivity.
Better analytics and insights – AI can help big data analytics by acting as an additional check to improve accuracy. Analyzing vast amounts of data is often time-consuming; AI also helps streamline the process.
Enhanced risk management processes – From complementing smart contract audits to automating risk monitoring processes, AI can help identify red flags and enhance risk management.
Of course, any new technology introduces novel challenges as it is implemented. The main challenges faced by the current AI ecosystem as applied in the digital assets space include:
Limited adoption – AI-focused crypto DApps have gained some traction but only among a small group of savvy users. Understandably, this is a relatively young space, but driving more real use cases will be vital for increased adoption.
Utility vs. proof of concept – While numerous projects are actively developing in this field and looking to integrate AI, many are still in the proof of concept stage. Usable products are key in driving adoption and growth in this space.
Focus on data privacy – Given the reliance of AI on large amounts of data, privacy is critical, especially when it comes to how data is used and secured. The importance of data protection, usage, and security policies cannot be overstated.
Technical challenges – Integrating AI and blockchain technology can be technically challenging, requiring project teams to possess expertise in both areas. Developing common standards and continued research in these fields will help drive innovation.
DeFi Use Cases
Within decentralized finance (DeFi), we have seen AI augmenting the smart contract audit process, facilitating trade automation, and being paired with predictive analytics for more accurate forecasts, among other innovations. Let’s explore the first two more deeply.
Smart contract audits
Smart contract audits involve inspecting and analyzing smart contract code to identify potential security or technical issues. Audits are a standard protective measure for projects across all sectors of the crypto ecosystem. They are especially important for DeFi, given the amount of funds secured by smart contracts.
AI can augment the smart contract audit process. For example, AI tools identify potential red flags during initial security screenings. Experts could then review these potential vulnerabilities, provide solutions, and conduct additional tests as required.
Essentially, AI can serve as an additional pair of eyes in the auditing process.
Case study: ChatGPT
ChatGPT is designed to generate human-like responses to natural language inputs and can help automate tasks. Developers have run experiments to understand its capabilities, particularly whether it can be used to improve smart contract code.
In one such experiment, CertiK – a blockchain security company – compared audits by ChatGPT to those conducted by a human auditor. They found that ChatGPT correctly cited several common security concerns but faced trouble with more complicated issues.
Security Audit: ChatGPT vs. Human
These findings show that while AI models like ChatGPT can help point out common issues, they cannot stand alone and are best used in a complementary role. Manual audits by security experts are still essential for a comprehensive and accurate analysis.
Intelligent trade automation
Monitoring DeFi trading positions can be difficult and time-consuming, especially during periods of market volatility. While trading bots are nothing new, they can be significantly improved by AI. Additional features and more sophisticated tools are becoming possible with AI’s development and integration with DeFi.
Overall, intelligent automation tools have the ability to improve user experience by streamlining complicated processes and making them more intuitive for users of DeFi. By doing so, these tools have the potential to advance the adoption of DeFi applications.
NFT Use Cases
In the NFT space, AI has enabled generative art creation, allowed for intelligent and interactive NFTs, and provided tools to streamline the data analytics process, among other innovations. We will explore the first two here.
Generative art is creative work produced by using an autonomous system. Several NFT projects have utilized AI for such purposes. The creator can input parameters, rules, or constraints – such as patterns, colors, shapes, etc. – and the AI will generate artwork based on this framework.
Through the use of AI, generative art enables creators to make unique pieces that are infinitely scalable yet still maintain a consistent style of the collection.
Case Study: Bicasso
Binance’s Bicasso is an AI NFT generator that allows users to create unique images generated by AI simply by inputting text or an image into the system. It uses AI algorithms to create images based on patterns and features of the input.
Users can be more specific by including details such as color schemes, composition, or elements that they want to see in the artwork. When satisfied with the result, they can mint their creations as NFTs on the BNB Chain.
By analyzing many data points, an AI image generator such as Bicasso can create original and unique images with similar styles or elements to those in the dataset. Such a technology has the potential to create realistic images for games and movies at scale and can be used to generate design prototypes.
Generating an AI image with Binance Bicasso
Some of the most notable generative art NFT projects have been very successful and produced prized collections sold for six-digit figures.
With AI, previously static NFTs are being transformed into intelligent NFTs (iNFTs) that can communicate with you. In essence, an iNFT brings the underlying NFT to life by using the generative powers of AI.
iNFTs integrate both AI and NFT technology to offer interactive tokens with intelligent traits and reasoning abilities. By using AI, they can analyze data to learn and evolve their personality based on real-time interactions. Conceptually, AI enables the iNFT to absorb new metadata to shape its future interactions and personality.
This could have profound implications for Web3 gaming and the future of the wider metaverse, where in-game characters are significantly more interactive and conversations become more life-like.
The marriage of such groundbreaking technologies as AI and blockchain opens up a realm of possibilities and potential use cases. It has already made us reconsider the way we interact with technology, approaching old problems in novel ways.
However, it is crucial to note that while the conceptual use cases may seem interesting, AI crypto projects are yet to achieve significant adoption. This suggests that such projects may be “nice-to-have” but are not absolutely necessary – based on the current level of innovation in the space, at least.
Nonetheless, emerging technologies take time to develop and reach a more definitive state. Looking ahead, the continued advancement of AI technology and crypto may usher in more use cases that prove helpful for different stakeholders in the ecosystem. We will have to wait and see what the intersection of AI and crypto has in store for Web3 users.
The Binance Research team is committed to delivering objective, independent, and comprehensive analyses of the crypto space. They publish insightful takes on Web3 topics, including but not limited to the crypto ecosystem, blockchain applications, and the latest market developments.
This article is a snapshot of the full report, which features a comprehensive analysis of further use cases and real-life examples in DeFi and NFT sectors, decentralized autonomous organizations (DAOs), and others. It also includes a discussion of the potential of AI in crypto, complete with perspectives of prominent thought leaders in the space. With so much rich content, you won’t want to miss these exclusive insights.
To read the full version of the report, click here. You can find other in-depth Web3 reports on the Insights & Analysis page of the Binance Research website. Don’t miss the opportunity to empower yourself with the latest insights from the field of crypto research!
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