Original title: "AI × Crypto: Latest Data and Developments"

Original source: JieXuan Chua, CFA, Binance Research

Original translation: Kate, Mars Finance

Key points

• Interest in artificial intelligence ("AI") has risen in the past few months, as evidenced by Google search trends and soaring prices of AI-related tokens.

• Funding for AI-related web3 projects surged to $298 million in 2023. This is more than the total funding for AI projects from 2016 to 2022 ($148.5 million).

• AI-related tokens have generally performed well in 2023, with the top five AI tokens by market cap significantly outperforming BTC and ETH, with gains ranging from 200% to 650% in 2023.

• We have observed several trends and real-world use cases arising from the convergence of AI and cryptocurrencies. From driving the growth of decentralized physical infrastructure networks (“DePINs”) to creating more interactive consumer-facing applications, we highlight some of the notable developments in this report.

Introduction

2023 is proving to be a milestone for artificial intelligence (“AI”) as the transformative power of AI becomes more evident, particularly with the widespread use of AI chatbots such as OpenAI’s ChatGPT, Google’s Bard, Microsoft’s Bing Chat, and others. ChatGPT in particular highlights the potential of AI, reaching the 100 million user milestone in just two months

This achievement surpasses major social media platforms such as TikTok and YouTube.

Figure 1: ChatGPT is one of the fastest growing apps, reaching 100 million users two months after launch

Source: demandsage, Binance Research

What’s more, AI is also beginning to reshape the crypto space, both in terms of real-world use cases and in the strong interest in AI-related tokens. The convergence of these two disruptive technologies has quickly become a prominent topic within the industry. Building on our previous report, which revealed AI use cases in crypto, we now revisit this changing landscape. In light of the recent resurgence of interest in the space, we’ll take a look at the current state of the market and examine new developments.

Market State

Public interest in AI has risen significantly in 2023, as evidenced by a significant increase in Google searches for “artificial intelligence” worldwide. This surge in interest indicates that the public is increasingly engaging with AI-related topics. This surge can be largely attributed to the popularity of AI chatbots, the launch of new AI tools, and increased media coverage and desire to learn about AI.

Figure 2: Google search interest in AI has risen sharply in 2023, significantly surpassing “crypto” and “bitcoin.”

Source: Google Trends, Binance Research, as of Dec 31, 2023

Note: Numbers represent search interest relative to the highest point on the chart for a given region and time.

In contrast, search interest in “crypto” remained relatively stable throughout the year. There was a slight downward trend from January to May, followed by a period of stability and a slight increase towards the end of the year. Search trends for “bitcoin” mirror those for “crypto”, but with more pronounced fluctuations. The fluctuations in Bitcoin interest can be related to several hot topics surrounding Bitcoin, including Ordinals/BRC-20, potential spot ETFs, and the upcoming Bitcoin halving in 2024. These events led to a rise in Bitcoin prices, which reignited public interest.

Overall, search trends reveal a clear divergence between growing interest in AI and relatively stable interest in Bitcoin and cryptocurrencies, suggesting that AI has been capturing the public’s attention at an increasing pace, with no clear signs of interest waning to date.

Strong Investor Interest

The AI industry also saw strong investor interest in 2023. Despite an overall decrease in funding amounts, AI’s share of U.S. startup funding grew by a relative 230% to approximately 26%. This growth occurred against the backdrop of both AI and non-AI sectors experiencing a funding downturn. However, AI has shown particular resilience compared to the overall market.

Figure 3: AI’s share of US startup funding doubled in 2023*

Source: Crunchbase, Binance Research, as of August 29, 2023

*Note: Updated data for 2023 is not yet available. Readers are advised to interpret the analysis with this limitation in mind.

Compared to 2022, absolute funding in non-AI sectors decreased by 65%, while funding in AI sectors decreased by a relatively smaller 6%.

In addition, when considering the number of funding rounds, non-AI sectors experienced a 55% decrease, while AI sectors experienced a 45% decrease. The relatively small decline in AI funding and funding rounds suggests that despite an overall downward trend in funding amounts since the peak in 2021, investor interest in AI applications remains relatively high. This may also indicate a continued belief in the long-term potential and viability of AI technologies and applications.

In addition, the AI sector of Web3 experienced explosive growth in funding in 2023. According to Rootdata, total funding for AI projects from 2016 to 2022 was $148.5 million, while funding in 2023 alone reached $298 million. This 2023 figure is twice the total funding in the previous seven years, reflecting the surge in AI's appeal in that one year.

Figure 4: AI projects rank 7th with $298M in funding in 2023, accounting for 3.7% of total Web3 project funding

Source: Rootdata, Binance Research Institute, as of December 31, 2023

Compared to other areas in the Web3 space, AI projects rank 7th with $298M in funding in 2023, surpassing NFTs at $293M and DAOs at $42M. This funding accounts for approximately 3.7% of total Web3 project funding in 2023. While 3.7% may not seem like much, considering that AI only began to gain significant traction in 2023, this significant funding growth highlights the growing recognition and value of the industry.

Strong Performance

AI tokens have also outperformed the overall market from a price perspective, experiencing a significant surge over the past quarter and year. Increased interest in the sector has contributed to the strong price performance of AI-related tokens.

Figure 5: AI tokens ranked as the second best performing category over the past three months

Source: Dune Analytics (@cryptokoryo_research) as of January 2, 2023 AI tokens include: AGIX, CTXC, FET, OCEAN, ORAI, RNDR

According to the Dune dashboard that aggregates the performance of representative tokens across different narratives/sectors, AI tokens ranked second in performance over the past three months. Please note that although the original dashboard included MEME coins, we have excluded them from our analysis as their relatively low market cap has resulted in disproportionately large percentage performance gains.

When comparing the top five AI tokens by market cap to BTC and ETH, it is clear that AI tokens have significantly outperformed the major tokens in 2023.

The one-year performance of these AI tokens ranges from 200% to as high as 650%. In comparison, BTC ended the year up 150% and ETH up 44%.

However, it is important to note that BTC and ETH have much larger market caps compared to these AI tokens. Therefore, it is only natural that BTC and ETH have smaller gains in terms of percentage. This comparison is primarily intended to highlight the strong performance and growing traction of AI tokens in recent months.

Figure 6: The top five AI tokens by market cap have significantly outperformed BTC and ETH in 2023, ranging from 200% to as high as 650%

Source: CoinMarketCap, Binance Research, as of December 31, 2023

Overall, AI has gained significant traction. Adoption of AI applications has been accelerating, attracting continued interest from both investors and retail investors. Additionally, AI tokens have been performing strongly. In addition to these trends, there are a few emerging AI x crypto innovations worth discussing, as detailed in the next section.

AI x Crypto Developments

The surge in interest in AI has fueled the growth of AI-related crypto applications, paving the way for continued innovation in the field. In this section, we take a deep dive into some of the trends and real-world use cases arising from the convergence of AI and crypto technologies. From driving the growth of decentralized physical infrastructure networks (“DePINs”) to creating more interactive consumer-facing applications, we highlight some of the noteworthy developments in the field.

AI x DePIN

Large language models, deep learning, and various AI applications rely heavily on the computing power of graphics processing units (“GPUs”). However, over the past year, the surge in interest in AI has led to an outsized demand for GPUs, resulting in a shortage of chips. Without convenient access to GPUs, the high cost of computing can be prohibitive for researchers and startups working on AI-related research. This is where decentralized computing networks (a subset of DePINs) come into play. They offer an alternative to existing solutions dominated by centralized cloud providers and hardware manufacturers. As a result, we have also witnessed strong growth in the industry driven by demand for GPUs.

Given that GPUs do not always run at 100% capacity, decentralized computing networks seek to connect those with spare computing power to those who need them. This is achieved by establishing a two-sided marketplace that allows suppliers of computing power to receive rewards from buyers. Examples of such networks include Akash, Render, Gensyn, and io.net, among others. Furthermore, decentralized computing networks are also competitively priced as there is no significant additional cost for suppliers to provide computing power to the network.

Figure 7: Decentralized Compute Networks are competitively priced

Source: Cloudmos, as of January 2, 2024

Note: Pricing is for 1 CPU, 1GB RAM, and 1GB disk

By providing potential solutions to real-world problems, decentralized compute networks are riding the wave of AI growth, with increasing activity on their platforms.

Figure 8: Number of rendered scenes on Render Network rises in 2023

Source: Dune Analytics (@lviswang), as of December 31, 2023

Figure 9: Akash Network’s active leases surged in Q4 2023

Source: Cloudmos, as of January 3, 2024

AI x Zero Knowledge

Smart contracts are known for their efficiency due to their code-based automation capabilities. However, their predefined nature can sometimes lead to a lack of adaptability, especially in unforeseen complex situations. This is where machine learning (ML), a subfield of artificial intelligence, can provide significant improvements. Machine learning models are trained on extensive data sets and have the ability to learn, adapt, and make highly accurate predictions. Integrating these models into smart contracts can open up a wide range of adaptable and flexible capabilities.

A major challenge to such integration is the prohibitively high computational overhead of on-chain ML computations. This leads to the concept of zero-knowledge machine learning (“ZKML”). ZKML combines zero-knowledge proofs and machine learning. In this setting, ML computations are processed off-chain, and ZK proofs are used to verify the integrity of these computations without revealing the actual data. Using ZKML, smart contracts can effectively leverage the power of AI while maintaining the security and transparency of blockchain technology.

Figure 10: ZKML combines zero-knowledge proofs with machine learning, performing computations off-chain before verification on-chain

Source: Binance Research

A notable development is the ZK Predictor launched by Upshot in partnership with Modulus Labs. The tool enables Upshot to leverage Modulus ZK circuits to verify asset valuations without revealing proprietary intellectual property. It can help develop automated market makers (“AMMs”) that optimize pricing for long-tail assets, AI-driven on-chain index funds with on-chain cryptographic proof of their operation, or prediction markets focused on specific themes that can enhance and verify the accuracy of crowd-source pricing signals. Other products of ZKML include price oracles. For example, Upshot feeds its AI models with complex market data to assess the value of long-tail assets such as NFTs. Modulus’ technology then verifies the correctness of these AI calculations, encapsulates them in proofs, and submits them to Ethereum for final verification.

These examples are just the beginning of the countless applications that ZKML can support. As the technology is still in its infancy, more mature and widespread ZKML applications are expected to emerge in the coming years.

AI x Consumer dApps

Over the past year, we have observed an increase in AI integration in consumer-facing decentralized applications (“dApps”) to increase interactivity and promote user engagement. This trend is changing the way users interact with platforms, providing personalization and interactivity. By leveraging AI, these dApps enable users to move from being mere users to active participants.

An example is AI User Generated Content (“UGC”) platforms such as NFPrompt. As the name suggests, AI UGC refers to content created by users with the help of an autonomous system. This can be achieved by setting a set of rules that can be automatically output and embedding some form of randomness in the algorithm. In other words, users can input a set of rules or constraints (e.g., patterns, colors, shapes) and the AI will generate content based on this framework. By involving users in the creative process, AI UGC platforms create a more participatory relationship between users and the platform, while also allowing users to come up with unique, one-of-a-kind, and infinitely scalable content.

Figure 11: Generating NFTs using text prompts on NFPrompt

Source: NFPrompt

Beyond content generation, the integration of AI could have a profound impact on web3 games or virtual worlds, where game characters are more interactive and dialogues are more realistic. Insomnia AI’s game He and She is a good example. Through the use of AI, the gameplay is characterized by a focus on customization and realistic communication. This provides a more personalized experience and fosters a more authentic emotional connection, thereby increasing user stickiness.

Figure 12: “He” and “She” use AI to provide immersive experiences

Source: Sleepless AI

AI x Data Analytics

Accurate market data is key to understanding industry trends and is essential for investors to make informed investment decisions. However, instances of real trading, such as wash trading, can artificially inflate sales and distort true sales volume. By integrating AI into the analysis, filtering out the noise, data can be output more accurately. This is widely achieved through AI and machine learning ("ML"), where large amounts of data are used as input to identify wash trading patterns or trends. The end result is a more accurate depiction of market activity.

Take BitsCrunch as an example, an AI-based NFT data analysis platform that uses AI and machine learning to detect fake or suspicious trading patterns in real time, thereby providing accurate data. The use of AI/ML enables the platform to analyze large amounts of data with relative ease, allowing the platform to distinguish between real and inorganic trading volume. This in turn helps make informed decisions.

Figure 13: Wash Trading Indicator from BitsCrunch Analysis

Concluding Remarks

The convergence of AI and crypto has sparked tremendous excitement about the potential of these cutting-edge technologies to redefine the digital landscape. The growing popularity of AI-centric tokens, as reflected by the growing interest in online search trends, underscores the continued acceleration of the AI narrative.

Admittedly, we are not at the point of mass adoption yet. Many AI-driven crypto projects are still in the early stages of development, and others may cater primarily to niche audiences. However, the increase in tangible use cases is an encouraging trend and positive for long-term growth. With all this in mind, investors need to understand the risks of investing in such cutting-edge technologies while capitalizing on the AI hype.

Original link

欢迎加入律动 BlockBeats 官方社群：

Telegram 订阅群：https://t.me/theblockbeats

Telegram 交流群：https://t.me/BlockBeats_App

Twitter 官方账号：https://twitter.com/BlockBeatsAsia