Author: Xiyou, ChainCatcher
Editor: Nianqing, ChainCatcher
In 2024, the field of “Crypto+AI” has achieved unprecedented breakthrough growth. At the beginning of the year, this field was still composed of only a few projects, but it has now become an independent track in the crypto market that cannot be ignored.
According to the latest data compiled by ChainCatcher, as of December 7, the total market capitalization of the crypto AI sector has exceeded $70 billion, accounting for up to 2% of the entire crypto market, with an annual growth rate reaching 400%.
At the same time, the number of crypto AI projects has also shown explosive growth, currently exceeding 600, covering multiple categories of products such as decentralized AI infrastructure and AI Dapp.
Looking back at 2024, the narrative of crypto AI has experienced multiple significant changes. At the beginning of the year, the Sora project launched by OpenAI ignited a speculative frenzy for crypto AI infrastructure. Subsequently, the Nvidia AI annual conference further pushed decentralized GPUs into the spotlight, and investors began to pursue AI decentralized infrastructure. By mid-year, the crypto AI track welcomed an investment boom, with crypto VC institutions announcing their involvement, many crypto projects receiving funding support, accelerating technological research and application processes. By the end of the year, the explosion of AI Agent Meme pushed the narrative of crypto AI to a new climax.
The total market capitalization of crypto AI assets has exceeded $70 billion within the year, with the number of related projects surpassing 600.
According to the latest data from CoinMarketCap, the number of tokens in the crypto artificial intelligence (Crypto*AI) sector has reached 355, with a total market capitalization exceeding $70 billion on December 7, peaking at $70.42 billion. Currently, due to the overall market correction trend in the crypto market, as of December 23, the total market capitalization of the crypto AI sector has fallen back to $47 billion, with a 24-hour trading volume still reaching $5 billion.
Looking back at the beginning of the year, the total market capitalization of the crypto AI sector was only $17 billion. In less than a year, the total market capitalization of this sector has increased by over 400%, once again showcasing the vigorous development and immense potential of the crypto AI field.
Daniel Cheung, co-founder of Syncracy Capital, expressed his views on December 12, indicating that although the current crypto AI sector only accounts for about 1% of the total market capitalization of the crypto market, with the continuous evolution of market cycles and the strong momentum of AI infrastructure and AI Agents, he predicts that the market value of this sector is expected to achieve tenfold growth.
It is worth mentioning that despite the overall decline in the current crypto market, as of December 23, the total market capitalization of the entire crypto market reached $3.4 trillion, while the market capitalization of crypto AI assets accounted for nearly 1.4% of the entire market (with peak market capitalization exceeding 2%), further proving its future market growth potential.
The year 2024 can be said to be a key turning point for the crypto AI field, moving from emerging to full-scale explosion. At the beginning of the year, the crypto AI track was still in its infancy, with only a handful of projects, mainly represented by decentralized GPU projects like Render (RNDR), AI infrastructure Fetch.ai (FET), and WorldCoin. However, in less than a year, the crypto AI field can now be divided into multiple sub-tracks, covering decentralized GPUs, AI data platforms, AI infrastructure, and AI Agents, with projects numbering in the hundreds.
According to the crypto data platform Rootdata, the number of crypto projects containing AI entries has exceeded 600, and this number continues to increase.
2024 Crypto AI Catalysts: OpenAI Narrative and Other External Forces, VC Heavy Investments, AI Agent Meme Explosion
From the data trend of the total market capitalization of crypto AI assets, the growth in 2024 presents two significant peaks: the first peak occurred between February and March, while the second occurred after October, ushering in a stronger wave of growth.
Between February and March, the growth in the crypto AI field was mainly due to the strong stimulation brought about by two significant events in the AI field.
In February, OpenAI made a shocking release of the “video generation” large model Sora, which sparked a disruptive change in the AI field. At the same time, this event also greatly propelled the price surge of the token WLD from the iris authentication crypto project Worldcoin, led by OpenAI founder Sam Altman, further driving the strong growth of the entire crypto AI asset sector. During this period, high-quality projects such as the AI model incentive platform Bittensor (TAO) and the AI data platform Arkham's ARKM began to receive widespread market attention, and the rise of these projects further ignited investment enthusiasm in the crypto AI market, attracting a large number of investors to flood into this promising emerging field.
Immediately afterward, the grand convening of Nvidia's annual AI conference GTC in March attracted wide attention worldwide and drove its market value to soar, triggering a speculative frenzy for GPU chips. During the conference, prominent figures in the crypto industry, such as Near co-founder Illia Polosukhin and Render Network founder Jules Urbach, once again injected new vitality into the crypto AI field. This series of events led to the emergence of decentralized GPU and other conceptual projects like a sudden downpour, among which the once-popular decentralized io.net was founded at this time.
As such, crypto AI has officially developed into an independent track, with projects in AI infrastructure, decentralized GPUs, decentralized AI data, and more emerging rapidly, bringing more choices and opportunities to the market.
In October, the growth in the crypto AI field was mainly attributed to the explosive emergence of AI Agent Meme. The launch of the AI Agent project Truth Terminal's token GOAT triggered a speculative frenzy in AI Agent Meme projects, driving the mass issuance of nearly a hundred AI Agent Meme coins. This trend has caused AI Agents to rise rapidly, becoming an independent sub-track within the crypto AI field, with products covering AI Agent Meme coins, AI Agent issuance platforms (IAO), and AI Agent underlying infrastructure. Specific projects can be referenced in (Systematic Analysis of the AI Agent Track: AI Meme, Issuance Platforms, and Infrastructure). According to Coingecko, as of December 23, the total market capitalization of AI Agent track tokens has reached $9.8 billion, accounting for about 20% of the total market capitalization of the entire crypto AI sector ($47 billion), and the speculation heat is still ongoing.
If the large model upgrades of Web2 companies in the AI field such as OpenAI's video generation tool Sora, the rise in the market value of Nvidia, and the AI summit it held constitute strong external driving forces for the development of the crypto AI field, then the explosive growth of AI Agent Meme is undoubtedly a fire ignited from within the crypto market, accelerating the rise of this field. Under the combined effect of both external and internal catalytic effects, the crypto AI track has rapidly become a key area in the crypto world that cannot be ignored, with its importance becoming increasingly significant.
Additionally, in 2024, the crypto AI market has experienced an unprecedented investment boom, with major investment institutions flocking in, and investment amounts skyrocketing. In this field, top venture capital firms in the crypto industry, such as Grayscale, Delphi Venture, Coinbase Ventures, Binance Labs, and a16z, have actively laid out “Crypto+AI” projects.
Among them, Delphi Ventures expressed strong optimism about the combination of Crypto and AI early in the year and invested in multiple related projects, such as io.net, OG Labs, and Mythos Ventures. a16z raised a new $6 billion fund focusing on investments in the AI field, selecting five crypto AI projects in its fall crypto startup accelerator. As the second half of the year approached, institutions like Pantera Capital, Grayscale, Binance Labs, and Coinbase Ventures announced their entry into the crypto AI field, establishing dedicated funds or increasing investment efforts. According to a report released by Messari, in the third quarter of 2024, crypto venture capital institutions injected over $213 million into AI projects, representing a 250% quarter-on-quarter growth and a year-on-year growth rate of 340%.
For specific actions and details of various crypto institutions in the crypto AI field, please refer to (2024 Crypto Venture Capital AI Layout Analysis: Which Projects Were Funded by Top VCs Like a16z, Binance, Coinbase? | Annual Review)
The market prospects of “Crypto for AI” are greater than those of “AI for Crypto”.
Currently, the crypto AI products in the market can primarily be divided into two major forms: “AI for Crypto” and “Crypto for AI”.
The former “AI for Crypto” refers to empowering crypto with AI, primarily focusing on applying AI technology to crypto products, enhancing user experience or strengthening product performance by integrating AI elements. For example, using AI for code optimization and security audits: AI technology can automatically detect and analyze the code of Web3 projects, uncovering potential security vulnerabilities and errors to improve project safety and stability; participating in on-chain yield strategies: utilizing AI algorithms to analyze market trends and user behavior, developing more efficient on-chain yield strategies to help crypto users achieve higher returns; integrating AI chatbots to answer user queries and enhance user experience; using AI Agents to eliminate barriers in the on-chain user experience, such as automated trading and asset management, allowing users to participate in the crypto market more conveniently.
“Crypto for AI” focuses on leveraging encryption technology to empower the AI industry, utilizing the unique advantages of blockchain technology to solve or improve certain aspects of the AI industry. For example, the privacy and transparency of blockchain technology can address privacy and security issues in the data collection, processing, and storage processes of AI models; by using model assetization, the community can own or use AI models in a decentralized manner; and through blockchain's token technology, idle computing power resources can be aggregated to form a computing power market, reducing the costs of training AI models and improving the efficiency of computing power resource utilization.
In summary, the essence of Web3 technology lies in its decentralized blockchain infrastructure. It relies on the operation of a token economic system, the autonomous execution of smart contracts, and the powerful efficiency of distributed technology, which not only ensures the precise definition of data ownership but also greatly enhances the transparency and efficiency of business models through the incentive model of tokens. This characteristic is like a remedy, effectively addressing the persistent issues of data opacity and vague business models commonly found in the AI industry. This aligns perfectly with the macro concept that “AI aims to enhance production efficiency, while Web3 focuses on optimizing production relationships.”
Therefore, industry insiders generally reach a consensus: “Crypto for AI” shows broader prospects and potential compared to “AI for Crypto” in terms of market application. This trend has also prompted more and more industry insiders in the AI field to actively seek to leverage encryption technology to tackle the various challenges and difficulties faced by the AI industry.
Building a crypto AI ecosystem around the three essential elements of “data, computing power, and algorithms”.
Based on the three core elements driving the development of large AI models, namely “data, computing power, and algorithms”, we can further subdivide them into data, computing power, and algorithm model products covering infrastructure and applications. Among them, data is the foundation for training and optimizing AI models; algorithms refer to the mathematical models and programming logic that drive AI systems; computing power refers to the computational resources required to execute these algorithms, and these three elements are also necessary conditions for the continuous updating and iteration of models.
The specific product forms within the crypto AI product ecosystem include the following aspects:
At the data level, crypto AI data projects cover data collection, storage, and processing. First, in terms of data acquisition, to ensure the richness and diversity of data, some crypto AI projects leverage token economic mechanisms to incentivize users to share their private or proprietary data. For example, the Grass project encourages data providers through a reward mechanism, Sahara AI tokenizes AI data assets and launched a dedicated data market, and Vana provides dedicated or customized datasets for AI applications through data pools, etc.; in terms of data processing, decentralized data labeling platforms contribute high-quality training datasets for developers, improving the reinforcement learning and fine-tuning mechanisms of AI models, such as Fraction AI (which completed $6 million financing on December 18), Alaya AI, and Public AI, providing high-quality training datasets for developers, thereby optimizing the reinforcement learning and fine-tuning processes of AI models. As for data storage, solutions like Filecoin and Arweave ensure the security and durability of data.
At the computing power level, training and inference of AI models cannot do without the support of powerful GPU computing resources. As the complexity of AI models increases, the demand for GPU computing resources is also on the rise. In the face of challenges such as high-quality GPU resources being in short supply, rising costs, and extended waiting times, decentralized GPU computing networks have emerged. These networks create open markets and GPU aggregation platforms, allowing anyone (such as Bitcoin miners) to contribute their idle GPU computing power to execute AI tasks and earn rewards through tokens. Representative projects include Akash, Render, Gensyn, io.net, and Hyperbolic. Additionally, projects like Exabits and GAIB are further tokenizing physical GPUs, transforming them into digital financial assets on the chain, further promoting the decentralization and liquidity of computing power.
At the algorithm model level, the decentralized AI algorithm networks currently available on the market essentially represent a decentralized AI algorithm service market that connects numerous AI models with different expertise and knowledge. When users pose questions, this market can intelligently select the most suitable AI model to provide answers. Representative products include Bittensor, which aggregates various AI models through subnets to deliver high-quality content to users; and Pond, which evaluates the best decentralized models through competition points and incentivizes every model contributor by tokenizing AI models, thereby promoting innovation and optimization of AI algorithms.
From this perspective, the current crypto market has built a thriving crypto AI ecosystem around the three pillars of “data, computing power, and algorithms”.
What are the favorable factors for the crypto AI track in 2025?
However, since the popularity of the AI Agent Meme market in October, AI Agent-related products have become the new favorites in the crypto AI market, such as the Talus Network project, which announced $150 million in financing with a $6 million investment in November, officially creating a framework and infrastructure specifically for AI Agents.
Moreover, the wave of AI Agent Meme has not only ignited a new speculation hotspot in the crypto AI track, but also shifted the market's focus from the original decentralized data, GPU, and other infrastructure fields of the crypto AI track to the enthusiastic pursuit of AI Agent applications. For example, the market value of ai16z has surpassed $1 billion, and this trend is still intensifying.
In the recent trend outlook for the crypto industry in 2025 published by multiple institutions, organizations such as a16z, VanEck, Bitwise, Hashed, Blockworks, Messari, and Framework have expressed optimism about the development of the crypto and AI markets, particularly noting that AI Agent-related products are expected to experience explosive growth in 2025.
At the same time, the heat in the external AI field is also continuing to rise. On December 23, Elon Musk's AI company xAI announced that it completed an additional $6 billion financing, with its valuation soaring to $40 billion, further promoting the prosperity of the AI market.
In terms of narrative, OpenAI is undergoing a transition from GPT to the general artificial intelligence entity AI Agent. It is reported that OpenAI plans to launch a new AI Agent product called “Operator” in January 2025, which can automatically execute complex operations such as coding, travel booking, and e-commerce shopping. It is expected that this will ignite the AI market again, just like Sora did at the beginning of 2024. Additionally, Nvidia's annual AI summit will also be held in March 2025, which will again be the focus of attention in the crypto and AI industries.
Every time the large models of AI field Web2 companies like Nvidia and OpenAI are upgraded, it ignites hotspots in the AI track, attracting new funds to flow in, further igniting the crypto AI track.
At the policy level, the elected President of the United States, Trump, has announced the appointment of former PayPal executive David O. Sacks as the White House head of artificial intelligence and cryptocurrency affairs, responsible for guiding the government in formulating policies in the fields of artificial intelligence and cryptocurrency. This individual has dual investment experience in both the crypto and AI industries, having previously invested in several crypto and AI companies such as Multicoin, and is naturally believed that the policies he formulates will promote the integration of crypto and AI.
