Author: Xiyou, ChainCatcher
Editor: Nianqing, ChainCatcher
In 2024, the "Crypto+AI" field achieved unprecedented breakthrough growth. At the beginning of the year, this field was composed of only a handful of projects, but it has now become an undeniable independent track in the crypto market.
According to the latest data compiled by ChainCatcher, on December 7, the total market capitalization of the crypto AI sector had surpassed $70 billion, reaching a maximum proportion of 2% in the entire crypto market, with an annual growth rate of 400%.
At the same time, the number of crypto AI projects has also shown explosive growth, currently exceeding 600, covering various categories of products such as decentralized AI infrastructure and AI Dapps.
Looking back at 2024, the narrative of crypto AI underwent several major changes. At the beginning of the year, the Sora project launched by OpenAI ignited a speculative frenzy around crypto AI infrastructure. Subsequently, the Nvidia AI annual conference further brought decentralized GPUs to the market's attention, and investors began to favor decentralized AI infrastructure. By mid-year, the crypto AI track welcomed an investment boom, with crypto VC institutions announcing their active involvement, and many crypto projects receiving funding support, accelerating technological research and application processes. By the end of the year, the explosion of AI Agent Meme brought the narrative of crypto AI to a new climax.
The total market capitalization of crypto AI assets has surpassed $70 billion, with the number of related projects exceeding 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 surpassing $70 billion on December 7, peaking at $70.42 billion. However, as of December 23, influenced by the overall downward trend in the current crypto market, 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 more than 400%, once again demonstrating the robust growth and immense potential of the crypto AI field.
Daniel Cheung, co-founder of Syncracy Capital, expressed his views on December 12, stating 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 capitalization of this sector is expected to achieve a tenfold increase.
It is worth mentioning that although the overall crypto market has receded, on December 23, the total market capitalization of the entire crypto market reached $3.4 trillion, while the market capitalization of crypto AI assets still accounted for nearly 1.4% of the entire market (with peak market capitalization exceeding 2%), further proving its potential for future market growth.
2024 can be regarded as a key turning point year for the crypto AI field, transitioning from emerging prominence to comprehensive explosion. At the beginning of the year, the crypto AI track was still in its nascent stage, 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 has been divided into multiple sub-tracks, covering decentralized GPUs, AI data platforms, AI infrastructure, and AI Agents, with several hundred projects.
According to the crypto data platform Rootdata, the number of crypto projects containing AI entries has now exceeded 600, and this number continues to increase.
2024 Crypto AI Catalysts: External Forces like OpenAI Narratives, Strong VC Layouts, and AI Agent Meme Explosions.
From the data trends of the total market capitalization of crypto AI assets, the growth in 2024 displayed 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 driven by two significant events in the AI field that provided strong stimulation.
In February, OpenAI shocked the world with the launch of the "text-to-video" large model Sora, which sparked a disruptive transformation in the AI field. At the same time, this event greatly boosted the price of the token WLD for 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 AI model incentive platform Bittensor (TAO) and 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 into this promising emerging field.
Subsequently, the grand opening of Nvidia's annual AI conference GTC in March attracted widespread global attention and propelled its market value to soar, sparking a speculation frenzy around GPU chips. At the conference, key figures in the crypto industry, including Near co-founder Illia Polosukhin and Render Network founder Jules Urbach, re-injected new vitality into the crypto AI field. This series of events led to a surge of concept projects like decentralized GPUs, including the once-popular decentralized io.net, which was founded at this time.
From this point, crypto AI has officially developed into an independent track, with projects such as AI infrastructure, decentralized GPUs, and decentralized AI data emerging in droves, bringing more choices and opportunities to the market.
In October, the growth in the crypto AI field was primarily attributed to the explosive outbreak of AI Agent Meme. The launch of the AI Agent project Truth Terminal's token GOAT triggered a wave of speculation in the issuance of AI Agent Meme tokens, leading to the mass issuance of nearly a hundred AI Agent Meme coins. This trend has allowed AI Agents to rapidly rise, 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 found in the article (Systematic Analysis of the AI Agent Track: AI Meme, Issuance Platforms, and Infrastructure). According to Coingecko data, 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 track ($47 billion), and the speculation heat is still ongoing.
If the launch of OpenAI's text-to-video tool Sora, the rise in Nvidia's market value, and the AI summit it hosted constitute a strong external driving force for the development of the crypto AI sector, 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 dual catalytic effect of both internal and external factors, the crypto AI track has quickly become a key area in the crypto world that cannot be ignored, its importance increasingly significant.
Additionally, in 2024, the crypto AI market has ushered in an unprecedented investment boom, with major investment institutions rushing in and investment amounts sharply rising. In this field, top venture capital firms in the crypto industry, such as Grayscale, Delphi Venture, Coinbase Ventures, Binance Labs, and a16z, have all actively laid out investments in "Crypto+AI" projects.
Among them, Delphi Ventures expressed strong optimism about the combination of Crypto and AI at the beginning of the year and invested in several related projects, such as io.net, OG Labs, and Mythos Ventures. a16z raised a new fund of $6 billion, focusing on investing in the AI field, and selected five crypto AI projects in its fall crypto startup accelerator. In the second half of the year, Pantera Capital, Grayscale, Binance Labs, and Coinbase Ventures also 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, a quarter-on-quarter increase of 250% and a year-on-year increase of 340%.
For specific actions and details of various crypto institutions in the crypto AI field, please refer to the article (2024 Crypto Venture Capital AI Layout Analysis: Which Projects Have Top VCs Like a16z, Binance, and Coinbase Invested In? | Annual Review).
"Crypto for AI" has greater market prospects than "AI for Crypto."
Currently, the crypto AI products on the market can mainly be divided into two categories: "AI for Crypto" and "Crypto for AI."
The former "AI for Crypto" means empowering crypto with AI, mainly focusing on applying AI technology to crypto products to enhance user experience or strengthen various product performances 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, identifying potential security vulnerabilities and errors, improving the safety and stability of the projects; participating in on-chain yield strategies: using AI algorithms to analyze market trends and user behavior, formulating more efficient on-chain yield strategies to help crypto users achieve higher returns; integrating AI chatbots to answer user inquiries and enhance user experience; leveraging 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, using the unique advantages of blockchain technology to address or improve certain aspects of the AI industry. For example, the privacy and transparency of blockchain technology can solve 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 token technology, idle computing power resources can be aggregated to form a computing power market, reducing the cost of training AI models and improving the utilization efficiency of computing power resources.
In summary, the essence of Web3 technology lies in its decentralized blockchain infrastructure, which, by relying on the operation of the token economy system, the autonomous execution of smart contracts, and the powerful capabilities of distributed technology, not only ensures precise definition of data ownership but also greatly enhances the transparency and efficiency of business models through the incentive model of tokens. This characteristic serves as a remedy for the prevalent issues of data opacity and ambiguous business models in the AI industry, providing effective solutions. This aligns perfectly with the macro concept that "AI aims to enhance productivity, while Web3 focuses on optimizing production relationships."
Therefore, industry practitioners 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 individuals within the AI industry to actively seek to leverage encryption technology to tackle the various challenges and problems faced by the AI industry.
Building a crypto AI ecosystem around the three elements of "data, computing power, and algorithms."
Based on the three core elements driving the development of large AI models: "data, computing power, and algorithms," we can further subdivide them into data, computing power, and algorithm model products that cover infrastructure and applications. Among them, data is the foundation for training and optimizing AI models; algorithms refer to the mathematical models and program logic that drive AI systems; and computing power refers to the computational resources required to execute these algorithms, which are also necessary for the continuous updating and iteration of the models.
The specific product forms within the crypto AI product ecosystem include the following aspects:
On the data level, crypto AI data projects cover the collection, storage, and processing of data. Firstly, in terms of data acquisition, to ensure the richness and diversity of data, some crypto AI projects use a token economic mechanism to incentivize users to share their private or proprietary data, such as the Grass project, which encourages data providers through a reward mechanism, Sahara AI which has tokenized AI data assets and launched a dedicated data market, and Vana which provides specialized or customized datasets for AI applications through data pools; regarding data processing, decentralized data labeling platforms provide developers with high-quality training datasets to improve the reinforcement learning and fine-tuning mechanisms of AI models, such as Fraction AI (which completed a $6 million financing round on December 18), Alaya AI, and Public AI, thus optimizing the reinforcement learning and fine-tuning processes of AI models. As for data storage, solutions like Filecoin and Arweave ensure the security and permanence of the data.
On the computing power level, the training and inference execution of AI models cannot be supported without powerful GPU computing resources. As the complexity of AI models increases, the demand for GPU computing resources continues to rise. In the face of challenges such as the shortage of high-quality GPU resources in the market, rising costs, and extended wait times, decentralized GPU computing networks have emerged. These networks allow anyone (such as Bitcoin miners) to contribute their idle GPU computing power to perform AI tasks and receive rewards through tokens, with representative projects including Akash, Render, Gensyn, io.net, and Hyperbolic. Additionally, projects like Exabits and GAIB have tokenized physical GPUs, converting them into financial digital assets on-chain, further promoting the decentralization and liquidity of computing power.
On the algorithm model level, the decentralized AI algorithm networks currently available on the market essentially constitute a decentralized AI algorithm service market that connects numerous AI models with different specialties 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 in the form of subnetworks to deliver high-quality content to users; and Pond, which evaluates the best decentralized models through competition points and incentivizes each model contributor by tokenizing AI models, thus promoting innovation and optimization in AI algorithms.
From this perspective, it can be seen that the current crypto market has built a thriving crypto AI ecosystem around the three pillars of "data, computing power, and algorithms."
What positive factors are there 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 a $150 million financing round in November and was specifically designed to create frameworks and infrastructure for AI Agents.
Moreover, the enthusiasm for AI Agent Meme has not only ignited new speculation hotspots in the crypto AI track but has also shifted market attention from the original decentralized data, GPU, and other foundational infrastructure areas of the crypto AI track to the enthusiastic pursuit of AI Agent applications, such as ai16z's market value exceeding $1 billion, and this enthusiasm continues to rise.
In recent projections of trends in the crypto industry for 2025 released by multiple institutions, a16z, VanEck, Bitwise, Hashed, Blockworks, Messari, and Framework have all expressed optimism about the development of the crypto and AI markets, specifically pointing out that AI Agent-related products will experience explosive growth in 2025.
At the same time, the heat in the external AI field is also continuously rising. On December 23, Elon Musk's AI company xAI announced that it had completed a new financing round of $6 billion, with its valuation skyrocketing to $40 billion, further driving the prosperity of the AI market.
In terms of narrative, OpenAI is undergoing a transition from GPT to a general artificial intelligence body, AI Agent. It is reported that OpenAI plans to launch a new AI Agent product called "Operator" in January 2025, which can automatically perform complex operations such as writing code, booking travel, and online shopping, and is expected to ignite the AI market just as Sora did at the beginning of 2024. Moreover, Nvidia's annual AI summit will also be held in March 2025, which will similarly be a focal point of attention for the crypto and AI industries.
Every time companies like Nvidia and OpenAI upgrade their large models, it ignites the hotspots in the AI track, attracting new capital inflows and further igniting the crypto AI track.
On the policy level, the elected president of the United States, Donald Trump, has announced the appointment of former PayPal executive David O. Sacks as the White House's point person for artificial intelligence and cryptocurrency affairs, responsible for guiding the government in formulating policies in the field of artificial intelligence and cryptocurrency. This person has dual investment experience in the crypto and AI industries, having participated in investments in several crypto companies and AI companies such as Multicoin, and is naturally believed to have a positive impact on the integration of crypto and AI policies.
