gist
• Interest in artificial intelligence ("AI") has risen over the past few months, as evidenced by Google search trends and the surge in the price of AI-related tokens.
• Funding for AI-related web3 projects surged to $298 million in 2023. This is more than the total amount of 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 capitalization 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 cryptocurrency. From driving the growth of decentralized physical infrastructure networks ("DePIN") to creating more interactive consumer-facing applications, we highlight some notable developments in this report.
introduce
The year 2023 proves to be a milestone for artificial intelligence ("AI") as the transformative power of AI becomes more apparent, especially the widespread use of AI chatbots such as OpenAI's ChatGPT, Google's Bard, Microsoft's Bing Chat, and more. ChatGPT, in particular, highlights the potential of artificial intelligence, reaching the milestone of 100 million users in just two months
This achievement surpasses major social media platforms such as Douyin and YouTube.
Figure 1: ChatGPT is one of the fastest-growing apps, gaining 100 million users just two months after its launch
资料来源:demandsage、币安研究院
What's more, AI is also starting to reshape the crypto space, both in 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 in the industry. Building on our previous reports, revealing use cases for AI in crypto, we now revisit this changing landscape. Given the recent resurgence of interest in the space, we will take a look at the current state of the market and look at new developments.
Market conditions
In 2023, public interest in AI has risen significantly, as evidenced by the significant increase in Google's global search volume for "AI". This heightened interest is indicative of growing public engagement on AI-related topics. Much of this surge has been attributed to the popularity of AI chatbots, the launch of new AI tools, and the increased media coverage and desire to learn about AI.
Figure 2: Google's Search Interest in AI Rises Significantly in 2023, Significantly Surpassing "Crypto" and "Bitcoin."
Source: Google Trends, Binance Research, as of 31 December 2023
Note: Numbers represent search interest relative to the highest point on the graph for a given area and time.
Conversely, 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, with a slight increase by the end of the year. The search trend for "Bitcoin" mirrors the search trend for "crypto", but the volatility is more pronounced. The volatility in Bitcoin interest may be related to several hot topics surrounding Bitcoin, including Ordinals/BRC-20, potential spot ETFs, and the fact that Bitcoin will halve in 2024. These events led to an increase in the price of Bitcoin, rekindling public interest.
Overall, search trends reveal a clear divergence between the growing interest in AI and the relatively stable interest in Bitcoin and cryptocurrencies, suggesting that AI has been capturing the public's attention at an increasing rate, with no obvious signs of waning interest to date.
Strong interest from investors
The AI sector is also strong in terms of investor interest in 2023. Despite the overall decrease in the amount of funding, the share of AI in US startup financing has increased by 230% in relative terms, accounting for about 26%. This growth comes as both AI and non-AI sectors experience a funding downturn. However, compared to the overall market, AI has shown particular resilience.
Figure 3: AI Doubles Its Share of U.S. Startup Financing in 2023*
Source: Crunchbase, Binance Research, as of 29 August 2023
*Note: The latest data for 2023 has not yet been released. Readers are advised to take this limitation into account when interpreting the analysis.
Compared to 2022, absolute funding in non-AI areas decreased by 65%, while funding in AI areas decreased by a relatively small amount of 6%.
In addition, when considering the number of funding rounds, the non-AI sector experienced a 55% reduction, while the AI sector experienced a 45% decrease. The decline in AI funding and funding rounds suggests that investor interest in AI applications remains relatively high, despite an overall downward trend in funding amounts since peaking in 2021. It may also indicate an ongoing belief in the long-term potential and feasibility of AI technologies and applications.
In addition, the AI sector of Web3 has experienced an explosion in terms of funding in 2023. According to Rootdata, the total financing of AI projects from 2016 to 2022 was $148.5 million, while in 2023 alone, it reached $298 million. This figure for 2023 is double the total funding for the previous seven years, reflecting a surge in the appeal of AI during the year.
Figure 4: Funding for AI projects in 2023 is $298 million, ranking 7th and accounting for 3.7% of total funding for Web3 projects
Source: Rootdata, Binance Research, as of 31 December 2023
Compared to other areas in the Web3 space, AI projects ranked seventh with $298 million in funding in 2023, surpassing NFTs at $293 million and DAOs at $42 million. This funding represents about 3.7% of the total funding for Web3 projects in 2023. While 3.7% may not seem like much, this sizable funding growth highlights the growing recognition and value of the industry, considering that AI is only starting to gain significant traction in 2023.
Strong performance
From a price perspective, AI tokens have also outperformed the overall market, experiencing significant spikes over the past quarter and year. The 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, which aggregates the performance of representative tokens across different narratives/sectors, the AI token ranks second in terms of performance over the past three months. Note that although the original dashboard included MEME coins, we have excluded them from our analysis because their relatively low market cap resulted in a disproportionately large percentage of performance gains.
When comparing the top five AI tokens by market capitalization with BTC and ETH, it is clear that AI tokens have significantly outperformed major coins in 2023.
The performance of these AI coins ranges from 200% to as high as 650% in a year. In comparison, BTC ended the year up 150%, while ETH rose 44%.
However, it is important to note that BTC and ETH have a much larger market cap compared to these AI tokens. Therefore, it is only natural that BTC and ETH have smaller gains in terms of percentages. This comparison is mainly to highlight the strong performance and growing traction of AI tokens in recent months.
Figure 6: The top five AI tokens by market capitalization have significantly outperformed BTC and ETH in 2023, ranging from 200% to as much as 650%.
Source: CoinMarketCap, Binance Research, as of 31 December 2023
Overall, AI has gained tremendous traction. The adoption of AI applications has been accelerating, attracting continued interest from investors and retail investors. In addition, the performance of AI tokens has been strong. In addition to these trends, there are some emerging AI x crypto innovations worth discussing, as detailed in the next section.
AI x Crypto发展
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'll delve into some of the trends and real-world use cases that have emerged from the convergence of AI and cryptography. From driving the growth of decentralized physical infrastructure networks ("DePIN") to creating more interactive, consumer-facing applications, we've highlighted some notable developments in the space.
AI x DePIN
Large language models, deep Xi, and various AI applications rely heavily on the computing power of graphics processing units ("GPUs"). However, the surge in interest in AI over the past year has led to a huge demand for GPUs, leading to a shortage of chips. Without the easy access to GPUs, the high cost of computing can be prohibitive for researchers and start-ups working on AI-related research. This is where decentralized computing networks, a subset of DePIN, come into play. They provide an alternative to existing solutions led by centralized cloud providers and hardware manufacturers. As a result, we are also witnessing strong growth in the industry, driven by GPU demand.
Considering that GPUs don't 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 creating a two-sided marketplace that allows suppliers of computing power to receive incentives from buyers. Examples of such networks include Akash, Render, Gensyn, and io.net. In addition, decentralized computing networks are also competitively priced, as there is no significant additional cost for providers to provide computing power to the network.
Figure 7: Decentralized computing networks are competitively priced
Source: Cloudmos, as of 2 January 2024
Note: Pricing is for 1 CPU, 1GB RAM, and 1GB disk
By providing potential solutions to real-world problems, decentralized computing networks have jumped on the wave of AI growth, with more and more activity on their platforms.
Figure 8: The number of rendered scenes on the Render Network has increased in 2023
Source: Dune Analytics (@lviswang), as of 31 December 2023
Figure 9: The Akash Network Saw a Surge in Active Leases in Q4 2023
Source: Cloudmos, as of 3 January 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 and complex situations. This is where machine Xi (ML), a subfield of artificial intelligence, can provide significant improvements. Machine-based Xi models are trained on extensive datasets and have the ability to Xi learn, adapt, and make highly accurate predictions. Integrating these models into smart contracts can open up a wide range of adaptive and flexible capabilities.
A major challenge with this integration is the high computational overhead of on-chain ML computation. This leads to the concept of zero-knowledge machine Xi ("ZKML"). ZKML combines zero-knowledge proofs and machine learning Xi. In this setup, ML computations are processed off-chain, and ZK proofs are used to verify the integrity of these computations without revealing actual data. With ZKML, smart contracts can effectively harness the power of artificial intelligence while maintaining the security and transparency of blockchain technology.
Figure 10: ZKML combines zero-knowledge proofs with machine Xi, performing off-chain computation followed by on-chain verification
Source: Binance Research
One notable development is Upshot's ZK Predictor, launched in partnership with Modulus Labs. The tool enables Upshot to leverage the Modulus ZK circuit to verify asset valuations without divulging proprietary intellectual property. It can help develop automated market makers ("AMMs") that optimize the pricing of long-tail assets, AI-powered on-chain index funds with on-chain cryptographic proofs of their operations, or predictive markets focused on specific themes that can enhance and verify the accuracy of crowd-force pricing signals. ZKML's other products include price oracles. Upshot, for example, provides sophisticated market data for its AI models 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 myriad of applications that ZAKML can support. As the technology is still in its infancy, a more mature and extensive range of ZKML applications is 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 facilitate user engagement. This trend is changing the way users interact with platforms, providing personalization and interactivity. By leveraging artificial intelligence, these dApps enable users to transform from mere users to active participants.
One example is an AI user-generated content ("UGC") platform such as NFPrompt. As the name suggests, AI UGC refers to content created by users with the help of autonomous systems. This can be achieved by setting up a set of rules that can be output automatically, with some form of randomness embedded in the algorithm. In other words, a user 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 platforms, while also allowing users to propose unique, one-of-a-kind, and infinitely scalable content.
Figure 11: Generate an NFT using a text prompt on NFPrompt
Source: NFPrompt
In addition to content generation, the integration of AI could have a profound impact on web3 games or virtual worlds, where game characters are more interactive and dialogue is more realistic. The games "Him" and "She" with insomnia AI are good examples. 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, which increases user stickiness.
Figure 12: "He" and "she" use AI to deliver immersive experiences
来源：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 volumes. By integrating artificial intelligence into the analysis, filtering out the noise, the data can be output more accurately. This is widely achieved through artificial intelligence and machine Xi ("ML"), where large amounts of data are used as input to identify wash trading patterns or trends. The end result is a more accurate description of the campaign.
Take BitsCrunch, an AI-based NFT data analytics platform that leverages artificial intelligence and machine Xi to detect fake or suspicious transaction patterns in real-time to provide accurate data. The use of AI/ML allows the platform to analyze large amounts of data with relative ease, allowing the platform to distinguish between real and inorganic volumes. This, in turn, helps in making informed decisions.
Figure 13: The wash trading indicator analyzed by BitsCrunch
Conclusion
The convergence of AI and cryptography has sparked tremendous excitement about the potential of these cutting-edge technologies to redefine the digital landscape. AI-centric tokens are growing in popularity, and online search trends reflect growing interest, highlighting the continued acceleration of the AI narrative.
Admittedly, we haven't gotten to the point of mass adoption yet. Many AI-powered crypto projects are still in the early stages of development, and others may primarily cater to niche audiences. However, the increase in tangible use cases is an encouraging trend and positive for long-term growth. With these in mind, investors need to be aware of the risks of investing in such cutting-edge technologies while leveraging the AI hype.