Author: Xiyou, ChainCatcher
Editor: Nianqing, ChainCatcher
In 2024, the "Crypto+AI" (Crypto AI) field achieved unprecedented breakthrough growth. At the beginning of the year, the field was only composed of a few projects, but now it has become an independent track that cannot be ignored in the crypto market.
According to the latest data compiled by ChainCatcher, the total market capitalization of the Crypto AI sector has exceeded $70 billion as of December 7th, accounting for the highest proportion of 2% in the entire crypto market, with a year-on-year growth rate of 400%.
At the same time, the number of Crypto AI projects has also experienced explosive growth, currently exceeding 600, covering various categories such as decentralized AI infrastructure and AI Dapps.
The total market capitalization of Crypto AI assets exceeded $70 billion during the year, and the number of related projects exceeded 600
According to the latest data from CoinMarketCap, the Crypto*AI sector has recorded 355 Tokens, and its total market capitalization has exceeded $70 billion as of December 7th, with a peak value reaching $70.42 billion. Currently, affected by the overall downward trend in the crypto market, as of December 23rd, the total market value of the Crypto AI sector has fallen to $47 billion, but the 24-hour trading volume is still as high as $5 billion.
2024 Crypto AI Catalysts: OpenAI narratives, VC heavy layout, and the outbreak of AI Agent Meme
From the data trend of the total market capitalization of Crypto AI assets, the growth in 2024 showed two significant peaks: the first peak occurred between February and March, while the second occurred after October, ushering in a stronger growth wave.
In the period from February to March, the growth of the Crypto AI field was mainly driven by two landmark events in the AI field.
In February, OpenAI released the groundbreaking "text-to-video" large model Sora, which triggered a disruptive revolution in the AI field. At the same time, this event also greatly boosted the token price of Worldcoin, the iris recognition crypto project led by OpenAI founder Sam Altman, and in turn drove the strong growth of the entire Crypto AI asset sector.
Immediately afterwards, the grand opening of NVIDIA's annual AI conference GTC in March once again attracted widespread global attention and led to a surge in its market value, triggering a GPU chip speculation frenzy. At the conference, the appearance of crypto industry leaders such as Near co-founder Illia Polosukhin and Render Network founder Jules Urbach injected new vitality into the Crypto AI field.
In October, the growth of the Crypto AI field was mainly attributed to the outbreak of the AI Agent Meme. The emergence of the GOAT token of the AI Agent project Truth Terminal triggered a wave of AI Agent Meme project token issuance and speculation, driving the rapid rise of the AI Agent as an independent sub-track within the Crypto AI field.
In addition, 2024 witnessed an unprecedented investment boom in the Crypto AI market, with various major investment institutions rushing in. Top crypto venture capital firms such as Grayscale, Delphi Venture, Coinbase Ventures, Binance Labs, and a16z have all actively deployed "Crypto+AI" projects.
"Crypto for AI" has greater market prospects than "AI for Crypto"
Currently, the crypto AI products on the market can be mainly divided into two forms: "AI for Crypto" and "Crypto for AI".
The former, "AI for Crypto", refers to using AI to empower Crypto, focusing mainly on applying AI technology to crypto products, enhancing user experience or strengthening the performance of products by integrating AI elements. For example, using AI for code optimization and security auditing: AI technology can automatically detect and analyze the code of Web3 projects, find potential security vulnerabilities and errors, and improve the security and stability of the projects; participating in on-chain yield strategies: using AI algorithms to analyze market trends and user behavior, formulate more efficient on-chain yield strategies, and help crypto users achieve higher returns; integrating AI chatbots to answer user questions and enhance user experience; using AI agents to eliminate barriers in the on-chain user experience, such as automatic trading and asset management, so that users can participate in the crypto market more conveniently.
"Crypto for AI" focuses on using crypto technology to empower the AI industry, leveraging 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 solve the privacy and security issues in the process of AI model data collection, processing and storage; through the use of model asset tokenization, the community can own or use AI models in a decentralized way; through the Token technology of blockchain, 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, relying on the operation of the Token economic system, the autonomous execution of smart contracts, and the powerful efficiency of distributed technology, not only ensures the precise definition of data ownership, but also greatly improves the transparency and efficiency of business models through the incentive model of Tokens. This feature is just like a panacea, providing an effective solution to the common problems in the AI industry, such as data opacity and unclear business models, which is in line with the macro concept that "AI aims to improve production efficiency, while Web3 focuses on optimizing production relations".
Therefore, industry insiders generally agree that: "Crypto for AI" has a broader prospect and potential in market application than "AI for Crypto". This trend has also prompted more and more AI industry insiders to actively seek to use crypto technology to overcome the various challenges and difficulties facing the AI industry.
Building a crypto AI ecosystem around the three key elements of "data, computing power and algorithms" for AI
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 covering 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 computing resources required to execute these algorithms, and these three elements are also necessary conditions for the continuous updating and iteration of the models.
The specific product forms in the crypto AI product ecosystem include the following aspects:
At the data level, crypto AI data projects cover the collection, storage and processing of data. First, in terms of data acquisition, in order to ensure the richness and diversity of data, some crypto AI projects leverage the Token economic mechanism to incentivize users to share their personal or proprietary data, such as the Grass project using a reward mechanism to encourage data providers, Sahara AI tokenizing AI data assets and launching a dedicated data market, and Vana providing specialized or customized data sets for AI applications through data pools; in terms of data processing, decentralized data annotation platforms have contributed high-quality training data sets to developers, improving the reinforcement learning and fine-tuning mechanisms of AI models, such as Fraction AI (completed $6 million in financing on December 18), Alaya AI and Public AI, providing developers with high-quality training data sets to optimize the reinforcement learning and fine-tuning of AI models. As for data storage, solutions like Filecoin and Arweave ensure the security and persistence of data.
At the computing power level, the training and inference execution of AI models requires the support of powerful GPU computing resources. As the complexity of AI models continues to increase, the demand for GPU computing resources is also constantly rising. Faced with the challenges of high-quality GPU resources being in short supply, rising costs and longer waiting times in the market, 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 receive Token rewards as compensation, with representative projects including Akash, Render, Gensyn, io.net and Hyperbolic. Furthermore, projects like Exabits and GAIB have even tokenized physical GPUs, converting them into on-chain financial digital assets, further promoting the decentralization and liquidity of computing power.
At the algorithm model level, the current decentralized AI algorithm networks on the market are essentially a decentralized AI algorithm service market, connecting numerous AI models with different expertise and knowledge. When a user raises a question, the market can intelligently select the most suitable AI model to provide the answer. Representative products include Bittensor, which aggregates various AI models through sub-networks to output high-quality content for users; and Pond, which selects the best decentralized models through competition scoring, and incentivizes each model contributor through the tokenization of AI models, thereby promoting the innovation and optimization of AI algorithms.
From this, we can see that the crypto market has already built a thriving crypto AI ecosystem around the three pillars of "data, computing power and algorithms" for AI.
What are the positive factors for the crypto AI track in 2025?
However, since the AI Agent Meme market became popular in October, AI Agent-related products have become the new darling of the crypto AI market, such as the Talus Network project, which announced the completion of $15 million in financing in November, specifically building a framework and infrastructure for AI Agents.
Furthermore, the AI Agent Meme craze has not only ignited a new speculative hotspot in the crypto AI track, but also gradually shifted the market's focus from the original decentralized data, GPU and other crypto AI infrastructure areas to the enthusiastic pursuit of AI Agent applications, with the market value of a16z already exceeding $1 billion, and this trend is still continuing to heat up.
In the recent 2025 crypto industry trend outlooks released by multiple institutions, a16z, VanEck, Bitwise, Hashed, Blockworks, Messari, Framework and other institutions have all expressed optimism about the development of the crypto and AI markets, and have specifically pointed out that AI Agent-related products will see explosive growth in 2025.
At the same time, the external AI field is also experiencing continued heat. On December 23, Elon Musk's AI company xAI announced another $6 billion in new financing, with its valuation directly soaring to $40 billion, further boosting the prosperity of the AI market.
At the narrative level, OpenAI is experiencing a transformation from GPT to the general artificial intelligence agent AI Agent. It is reported that OpenAI plans to launch a new AI Agent product "Operator" in January 2025, which will be able to automatically execute tasks such as writing code, booking travel, and e-commerce shopping, and is expected to ignite the AI market again like Sora did in early 2024. In addition, Nvidia's annual AI summit will also be held in March 2025, which is also a focus of attention for the crypto and AI industries.
Each time the large models of Web2 companies like Nvidia and OpenAI are upgraded, it will ignite the hotspots in the AI track, attracting new capital inflows and further igniting the crypto AI track.
At the policy level, the newly elected US President Trump has announced the appointment of former PayPal executive David O. Sacks as the White House's AI and cryptocurrency affairs officer, responsible for guiding the government in formulating policies in the fields of artificial intelligence and cryptocurrencies. As a person with investment experience in both the crypto and AI industries, having participated in investing in companies like Multicoin, he is naturally seen as someone who will promote policies that will drive the integration of crypto and AI.
