Written by: Grapefruit, ChainCatcher
Editor: Nianqing, ChainCatcher
In 2024, the field of "Crypto+AI" achieved unprecedented breakthrough growth. At the beginning of the year, this field consisted of only a handful of projects, but now it has become an independent track in the crypto market that cannot be ignored.
According to the latest data compiled by ChainCatcher, the total market value of assets in the crypto AI sector exceeded the US$70 billion mark on December 7, accounting for 2% of the entire crypto market, with an annual growth rate of 400%.
At the same time, the number of crypto AI projects has also exploded, 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 undergone several significant changes. At the beginning of the year, OpenAI launched the Sora project, igniting a hype for crypto AI infrastructure. Subsequently, the annual AI conference held by NVIDIA brought decentralized GPUs into the spotlight, with investors beginning to flock to decentralized AI infrastructure. By mid-year, the crypto AI track experienced an investment boom, with various crypto VC institutions announcing their involvement, many crypto projects receiving funding support, accelerating the R&D and application processes of technology. By the end of the year, the explosion of the AI Agent Meme pushed the narrative of crypto AI to a new climax.
The total market value of crypto AI assets exceeded $70 billion this year, with the number of related projects exceeding 600.
According to the latest data from CoinMarketCap, the number of tokens included in the crypto artificial intelligence (Crypto*AI) sector has reached 355, and its total market value exceeded $70 billion on December 7, with a peak value reaching $70.42 billion. Currently, affected by the overall downtrend in the crypto market, as of December 23, the total market value of the crypto AI sector has fallen back to $47 billion, with a 24-hour trading volume still as high as $5 billion.
Looking back at the beginning of the year, the total market value of the crypto AI sector was only 17 billion dollars. In less than a year, the total market value of this sector has increased by over 400%, once again demonstrating the vigorous development and enormous 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 crypto market value, 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 a tenfold increase.
It is worth mentioning that although the current crypto market overall has receded, the total market value of the entire crypto market reached $3.4 trillion on December 23, while the market value of crypto AI assets still accounted for nearly 1.4% of the entire market (with a peak period share exceeding 2%), further proving its potential for future market growth.
The year 2024 can be regarded as a key turning point for the crypto AI field, transitioning from initial visibility to full-blown 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 has been divided into multiple segmented tracks, covering decentralized GPUs, AI data platforms, AI infrastructure, and AI Agents, with hundreds of projects.
According to the crypto data platform Rootdata, there are currently over 600 crypto projects that contain AI-related entries, and this number continues to increase.
2024 Crypto AI Catalysts: External forces like OpenAI narrative, heavy investment from VCs, and the explosion of AI Agent Meme.
From the data trends of the total market value of crypto AI assets, the growth in 2024 shows two significant peaks: the first peak occurred between February and March, while the second occurred after October, ushering in a stronger growth wave.
Between February and March, the growth of the crypto AI field was mainly driven by two landmark events in the AI field.
In February, OpenAI shockingly released the 'text-to-video' large model Sora, a groundbreaking achievement that sparked a revolutionary change in the AI field. At the same time, this event also significantly 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 the AI model incentive platform Bittensor (TAO) and the AI data platform Arkham's ARKM began to receive widespread attention from the market, and the rise of these projects further ignited investment enthusiasm in the crypto AI market, attracting a large number of investors to this promising emerging field.
Immediately following that, in March, the grand opening of NVIDIA's annual AI conference GTC once again attracted widespread attention globally and pushed its market value to soar, triggering a GPU chip hype. At the conference, the appearance of key figures in the crypto industry such as Near co-founder Illia Polosukhin and Render Network founder Jules Urbach injected new vitality into the crypto AI field. This series of events led to a surge of conceptual projects such as decentralized GPUs emerging like mushrooms after the rain, among which the once-popular decentralized io.net was founded at this time.
Since then, crypto AI has officially developed into an independent track, with projects such as AI infrastructure, decentralized GPUs, and decentralized AI data emerging like mushrooms after rain, providing the market with more choices and opportunities.
In October, the growth in the crypto AI field was mainly attributed to the explosive emergence of the AI Agent Meme. The launch of the AI Agent project Truth Terminal's token GOAT triggered a market frenzy for AI Agent Meme projects, 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 segment within the crypto AI field, with products covering AI Agent Meme coins, AI Agent issuance platforms (IAO), and foundational infrastructure for AI Agents. For specific projects, please refer to ChainCatcher's November release (Systematic Overview of the AI Agent Track: AI Meme, Issuance Platforms, and Infrastructure). According to Coingecko data, as of December 23, the total market value of AI Agent track tokens reached $9.8 billion, accounting for about 20% of the total market value of the entire crypto AI sector ($47 billion), and the hype continues.
If the external strong driving forces for the development of the crypto AI field include the launch of OpenAI's video generation tool Sora, the rise in NVIDIA's market value, and its hosting of AI summits, then the explosive growth of the AI Agent Meme is undoubtedly a fire ignited internally within the crypto market, accelerating the rise of this field. Under the combined catalytic effect of both internal and external forces, the crypto AI track has rapidly become a critical area in the crypto world that cannot be ignored, and its importance is increasingly significant.
In addition, in 2024, the crypto AI market has experienced an unprecedented investment boom, with major investment institutions rushing in and investment amounts soaring. In this field, top venture capital institutions in the crypto industry, such as Grayscale, Delphi Venture, Coinbase Ventures, Binance Labs, and a16z, have all actively laid out '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 5 crypto AI projects in its fall crypto startup accelerator. Entering the second half of the year, institutions such as Pantera Capital, Grayscale, Binance Labs, and Coinbase Ventures have also announced their entry into the crypto AI field, establishing dedicated funds or increasing their investment intensity. 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 detailed actions and specifics of various crypto institutions in the crypto AI field, you can refer to the ChainCatcher report published (2024 Analysis of Crypto Venture Capital AI Layout: Which Projects Did Top VCs Like a16z, Binance, and Coinbase Invest In? | Annual Review).
'Crypto for AI' has a greater market prospect than 'AI for Crypto'.
Currently, crypto AI products in the market can mainly be divided into two forms: '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, identify potential security vulnerabilities and errors, improving project security and stability; participating in on-chain yield strategies: using AI algorithms to analyze market trends and user behavior to develop more efficient on-chain yield strategies, helping crypto users achieve higher returns; integrating AI chatbots to answer user questions and enhance user experience; leveraging AI Agents to eliminate obstacles in on-chain user experiences, such as automated trading and asset management, allowing users to participate in the crypto market more conveniently.
'Crypto for AI' focuses on empowering the AI industry through crypto technology, using 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; allowing communities to own or use AI models in a decentralized manner through the tokenization of model assets; and aggregating idle computing resources through blockchain's Token technology to form a computing power market, reducing the cost of AI model training and improving the utilization efficiency of computing resources.
In summary, the essence of Web3 technology lies in its decentralized blockchain infrastructure, which operates on the Token economic system, the autonomous execution of smart contracts, and the powerful efficacy of distributed technology. It 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 is like a remedy, addressing the common issues of data opacity and vague business models in the AI industry and providing effective solutions. This aligns perfectly with the macro concept that 'AI aims to enhance production efficiency, while Web3 focuses on optimizing production relations.'
Therefore, industry professionals generally agree that 'Crypto for AI' shows broader prospects and potential compared to 'AI for Crypto' in terms of market application. This trend has prompted more and more people within the AI industry to actively seek to leverage crypto technology to tackle the various challenges and difficulties faced by the AI industry.
Build a crypto AI ecosystem around the three essential elements of AI: data, computing power, and algorithms.
Based on the core three elements 'data, computing power, and algorithms' driving the development of AI large models, we can further classify 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 driving AI systems; computing power refers to the computational resources needed 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 within the crypto AI product ecosystem include the following aspects:
From the data aspect, crypto AI data projects encompass data collection, storage, and processing. Firstly, 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, such as the Grass project encouraging data providers through a reward mechanism, Sahara AI tokenizing AI data assets and launching a dedicated data market, and Vana providing specialized or customized datasets for AI applications through data pools, etc.; in terms of data processing, decentralized data annotation platforms contribute high-quality training datasets to developers, thereby improving the reinforcement learning and fine-tuning mechanisms of AI models, such as Fraction AI (which completed $6 million in funding on December 18), Alaya AI, and Public AI, among others, providing high-quality training datasets that optimize 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 data.
In terms of computing power, the training and inference execution of AI models cannot be separated from strong GPU computing resources support. As the complexity of AI models increases, the demand for GPU computing resources continues to rise. In the face of challenges such as high-quality GPU resources being in short supply, rising costs, and extended wait 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 receive rewards through Tokens. Representative projects include Akash, Render, Gensyn, io.net, and Hyperbolic. Additionally, projects like Exabits and GAIB have also tokenized physical GPUs, transforming them into financial digital assets on the chain, further promoting the decentralization and liquidity of computing power.
In terms of algorithm models, the current decentralized AI algorithm networks on the market are essentially decentralized AI algorithm service markets that connect numerous AI models with varying 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 in the form of a subnet to deliver high-quality content to users; while Pond evaluates the best decentralized models through competition points and incentivizes every model contributor by tokenizing the AI models, thereby promoting innovation and optimization in AI algorithms.
From this perspective, the current crypto market has built a thriving crypto AI ecosystem centered around the three pillars of 'data, computing power, and algorithms'.
What favorable factors are there for the crypto AI track in 2025?
However, since the rise of the AI Agent Meme market in October, products related to AI Agents have become the new favorites in the crypto AI market, such as Talus Network, which announced the completion of $6 million in financing with a valuation of $150 million in November, officially creating a framework and infrastructure specifically for AI Agents.
Moreover, the wave of AI Agent Meme not only ignited a new hype hotspot in the crypto AI track but also shifted the market's focus from the original decentralized data, GPU, and other foundational areas of crypto AI to enthusiastic support for AI Agent applications, such as ai16z, which has surpassed a market value of $1 billion, and this trend is still continuing.
In recent trend outlooks for the crypto industry for 2025 released by multiple institutions, organizations like a16z, VanEck, Bitwise, Hashed, Blockworks, Messari, and Framework have all expressed optimism about the development of the crypto and AI markets, particularly noting that AI Agent-related products will experience explosive growth in 2025.
At the same time, the heat in the external AI field continues to rise. On December 23, Elon Musk's AI company xAI announced that it had completed another $6 billion in new financing, with its valuation skyrocketing to $40 billion, further boosting the prosperity of the AI market.
On the narrative level, OpenAI is undergoing a transformation 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 will be able to automatically perform complex operations such as writing code, booking travel, and shopping, and is expected to ignite the AI market again, just as Sora did at the beginning of 2024. Additionally, NVIDIA's annual AI summit will also be held in March 2025, which remains a focal point of attention for the crypto and AI industries.
Every time companies like NVIDIA and OpenAI upgrade their large models, it ignites hotspots in the AI track, attracting new funds and further igniting the crypto AI track.
On the policy level, the elected U.S. President Trump has appointed 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 possesses dual investment experience in both the crypto and AI industries, having previously invested in several crypto companies and AI companies such as Multicoin, and is naturally expected to play a role in promoting the policies he formulates in the field of the integration of crypto and AI.
