Forward the Original Title: 2024 Evolution of the Crypto AI Narrative: From Decentralized GPUs, Data Infrastructure, to AI Agents | Annual Review

Crypto AI market hits $70 billion in total market cap, with over 600 projects.

In 2024, the “Crypto + AI” sector achieved unprecedented growth. At the start of the year, the space was still comprised of just a few projects. Now, it has become a vital independent sector within the crypto market.

According to the latest data from ChainCatcher, by December 7, the total market capitalization of the crypto AI sector had surpassed $70 billion, representing up to 2% of the entire crypto market, with a staggering 400% year-over-year growth.

At the same time, the number of crypto AI projects has skyrocketed, exceeding 600 and covering various categories, including decentralized AI infrastructure and AI DApps.

Looking back at 2024, the crypto AI narrative has evolved through several key shifts. OpenAI’s Sora project ignited hype around crypto AI infrastructure early in the year. The following NVIDIA AI conference brought decentralized GPUs into the spotlight, attracting investor attention to decentralized AI infrastructure. By mid-year, the crypto AI sector experienced an investment surge, with crypto VC firms ramping up their involvement and funding projects to accelerate tech development and application. By the end of the year, the AI Agent meme exploded, propelling crypto AI into a new narrative phase.

The total market capitalization of the crypto AI sector broke $70 billion, with over 600 projects now in play.

As of December 7, according to CoinMarketCap, the crypto AI sector had 355 tokens, with its total market capitalization peaking at $70.42 billion. However, in line with the broader crypto market’s downturn, by December 23, the sector’s total market cap dropped to $47 billion, though its 24-hour trading volume remained strong at $5 billion.

Looking back at the beginning of the year, the total market capitalization of the crypto AI sector was just $17 billion. In less than a year, the sector’s market cap has surged by over 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, noting that although the crypto AI sector currently accounts for just about 1% of the total crypto market cap, with the continuous evolution of the market cycle and the strong momentum of AI infrastructure and AI Agents, he predicts that the sector’s market cap could grow tenfold.

Notably, despite the overall downturn in the crypto market, as of December 23, the total market cap of the crypto market had reached $3.4 trillion, with the market cap of crypto AI assets still accounting for nearly 1.4% of the total market (its peak share exceeded 2%). This further validates the sector’s future growth potential.

2024 has proven to be a key turning point for the crypto AI sector, marking its transition from emerging to explosive growth. At the start of the year, the crypto AI track was still in its infancy, with only a handful of projects such as decentralized GPU project Render (RNDR), AI infrastructure project Fetch.ai (FET), and WorldCoin leading the charge. However, in less than a year, the crypto AI space has expanded into multiple sub-sectors, covering decentralized GPUs, AI data platforms, AI infrastructure, and AI Agents, with hundreds of projects now in existence.

According to the crypto data platform Rootdata, the number of crypto projects related to AI has now exceeded 600 and is still growing.

Crypto AI Catalysts in 2024: OpenAI Narrative, VC Investments, and the Explosion of AI Agent Memes

Looking at the market trends of crypto AI assets, 2024 witnessed two significant growth waves: the first in February to March and the second after October, which saw even stronger growth.

From February to March, the growth of the crypto AI sector was primarily driven by two major events in the AI field.

In February, OpenAI’s groundbreaking release of the “Sora” model, a generative video model, triggered a disruptive transformation in the AI space. At the same time, this event significantly boosted the price of the WLD token from Worldcoin, a crypto project led by OpenAI’s Sam Altman, propelling the entire crypto AI sector to strong growth. During this period, high-quality projects like the AI model incentive platform Bittensor (TAO) and the AI data platform Arkham (ARKM) began to gain widespread market attention, further igniting investment enthusiasm for the crypto AI market and attracting a wave of investors into this emerging, high-potential field.

Then, in March, the grand event of NVIDIA’s annual AI conference, GTC, once again captured global attention and pushed its market value to new heights, sparking a GPU chip frenzy. At the conference, crypto industry leaders such as Illia Polosukhin, co-founder of Near, and Jules Urbach, founder of decentralized GPU rendering network Render Network, brought fresh energy to the crypto AI sector. This series of events led to a surge in decentralized GPU projects, with the once-popular decentralized project io.net being established during this period.

As a result, crypto AI officially developed into an independent track, with a wave of decentralized GPU, AI infrastructure, decentralized AI data, and other related projects emerging, offering the market more choices and opportunities.

In October, the growth of the crypto AI sector was primarily driven by the explosion of AI Agent memes. The launch of the Truth Terminal project’s GOAT token marked the beginning of a meme-driven AI Agent token craze, leading to the mass issuance of nearly 100 AI Agent meme tokens. This trend quickly propelled AI Agents to become an independent sub-sector within crypto AI, with products spanning AI Agent meme coins, AI Agent launch platforms (IAOs), and AI Agent underlying infrastructure. For a detailed analysis of the sector, see ChainCatcher’s November report, Systematic Review of the AI Agent Track: AI Memes, Launch Platforms, and Infrastructure. According to Coingecko data, by December 23, the total market cap of AI Agent tokens had reached $9.8 billion, accounting for about 20% of the total market cap of the crypto AI sector ($47 billion), with the hype continuing.

OpenAI’s launch of the Sora generative video tool, NVIDIA’s rising market cap, and its AI summit have undoubtedly acted as powerful external drivers for the growth of the crypto AI sector. Meanwhile, the explosive growth of AI Agent memes has undoubtedly sparked an internal fire within the crypto market, accelerating the rise of this field. With the combined effect of both external and internal catalysts, the crypto AI sector has rapidly emerged as a critical and inescapable force in the crypto world, its importance growing increasingly evident.

In addition, 2024 saw an unprecedented investment boom in the crypto AI market, with top investment institutions rushing in and funding amounts soaring. Leading venture capital firms in the crypto space, such as Grayscale, Delphi Ventures, Coinbase Ventures, Binance Labs, and a16z, have all actively invested in “Crypto+AI” projects.

At the beginning of the year, Delphi Ventures expressed its strong optimism about the combination of Crypto and AI, investing in several related projects, including io.net, OG Labs, and Mythos Ventures. a16z, on the other hand, raised a $6 billion new fund focused on investing in the AI sector and included five crypto AI projects in its fall crypto startup accelerator. Entering the second half of the year, institutions like Pantera Capital, Grayscale, Binance Labs, and Coinbase Ventures also announced their entry into the crypto AI space, setting up dedicated funds or increasing their investment in the sector. According to a report by Messari, in the third quarter of 2024, crypto venture capital firms injected more than $213 million into AI projects, marking a 250% quarter-over-quarter increase and a staggering 340% year-over-year growth.

For a more detailed breakdown of the specific moves and actions taken by crypto institutions in the crypto AI sector, check out ChainCatcher’s 2024 Crypto VC AI Investment Analysis: What Projects Have a16z, Binance, Coinbase, and Other Top VCs Invested In? | Year-End Review.

“Crypto for AI” Has Greater Market Potential Than “AI for Crypto”

Currently, crypto AI products can primarily be divided into two forms: “AI for Crypto” and “Crypto for AI.”

The former, “AI for Crypto,” refers to using AI to empower crypto, mainly focusing on applying AI technology to crypto products to enhance user experience or improve product performance. Examples include:

• AI for Code Optimization and Security Audits: AI can automatically detect and analyze Web3 project code to identify potential security vulnerabilities and errors, improving project security and stability.
• Participating in On-chain Yield Strategies: AI algorithms analyze market trends and user behaviors to create more efficient on-chain yield strategies, helping crypto users achieve higher returns.
• Integrating AI Chatbots: AI-driven chatbots can answer user queries, improving the overall user experience.
• Leveraging AI Agents to Eliminate On-chain User Experience Barriers: Using AI Agents for tasks like automated trading and asset management, which allows users to participate in the crypto market more easily.

“Crypto for AI,” on the other hand, focuses on using crypto technology to empower the AI industry, leveraging blockchain’s unique advantages to solve or improve certain aspects of the AI industry. For example: For example, the privacy and transparency of blockchain technology can address the privacy and security issues that AI models face during data collection, processing, and storage. By tokenizing AI models, blockchain allows the community to own or access these models in a decentralized manner. Additionally, blockchain’s token system can aggregate idle computational resources, creating a computing power market that reduces the cost of AI model training and improves the efficiency of resource utilization.

In summary, the essence of Web3 technology lies in its decentralized blockchain infrastructure. With the operation of the token economy, the autonomous execution of smart contracts, and the powerful capabilities of distributed technologies, Web3 ensures precise data ownership and greatly enhances the transparency and efficiency of business models through token incentives. This characteristic acts as a remedy for the common issues in the AI industry, such as opaque data and unclear business models, providing an effective solution. This aligns perfectly with the broader vision that “AI aims to improve productivity, while Web3 focuses on optimizing production relations.”

As a result, industry professionals largely agree that the market application of “Crypto for AI” shows greater potential and prospects than “AI for Crypto.” This trend has also prompted more AI industry insiders to actively seek ways to leverage crypto technologies to tackle the various challenges and problems faced by the AI industry.

Building the Crypto AI Ecosystem Around the Three Core Elements of AI: Data, Computing Power, and Algorithms

Based on the three core elements—data, computing power, and algorithms—that drive the development of large AI models, we can further break down the ecosystem into products related to infrastructure and applications in these areas.

• Data: The foundation for training and optimizing AI models.
• Algorithms: The mathematical models and program logic that drive AI systems.
• Computing Power: The computational resources required to execute these algorithms. These three elements are also essential for the continuous updating and iteration of AI models.

The specific product forms within the crypto AI product ecosystem include the following aspects:

Data Layer: Crypto AI data projects encompass data collection, storage, and processing.

• Data Acquisition: To ensure data richness and diversity, some crypto AI projects leverage token-based incentive mechanisms to encourage users to share their private or proprietary data. For example, the Grass project incentivizes data providers through rewards, Sahara AI tokenizes AI data assets and launches a dedicated data marketplace, and Vana offers customized or specialized datasets for AI applications through data pools.
• Data Processing: Decentralized data labeling platforms contribute high-quality training datasets for developers, enhancing the reinforcement learning and fine-tuning mechanisms of AI models. Projects like Fraction AI (which completed a $6 million fundraising round on December 18), Alaya AI, and Public AI provide high-quality training datasets, optimizing the reinforcement learning and fine-tuning processes of AI models.
• Data Storage: Solutions like Filecoin and Arweave ensure the security and permanence of data storage.

Computing Power Layer: The training and inference execution of AI models require robust GPU computing resources. As AI model complexity increases, so does the demand for GPU computing power. To address the challenges of insufficient high-quality GPU resources, rising costs, and longer wait times, decentralized GPU computing networks have emerged. These networks create open markets and GPU aggregation platforms that allow anyone (e.g., Bitcoin miners) to contribute their idle GPU computing power to perform AI tasks and earn tokens as rewards. Representative projects include Akash, Render, Gensyn, io.net, and Hyperbolic. Additionally, projects like Exabits and GAIB have tokenized physical GPUs, turning them into on-chain financial digital assets, further advancing the decentralization and liquidity of computing power.

Algorithm Model Layer: The decentralized AI algorithm networks available on the market are essentially decentralized AI algorithm service markets that connect numerous AI models with different expertise and knowledge. When a user poses a query, the market intelligently selects the most suitable AI model to provide an answer. Representative products include Bittensor, which aggregates various AI models via subnets to output high-quality content for users, and Pond, which ranks the best-decentralized models based on competition scores and incentivizes every model contributor by tokenizing AI models, thereby driving innovation and optimization of AI algorithms.

In summary, the crypto market has built a thriving crypto AI ecosystem around the three core pillars of “data, computing power, and algorithms,” fostering the rapid development of this sector.

What are the Positive Drivers for the Crypto AI Sector in 2025?

Since the rise of the AI Agent Meme market in October, AI Agent-related products have become the new favourite within the crypto AI sector. Projects like Talus Network, which announced a $1.5 billion valuation after securing $6 million in funding in November, are creating dedicated frameworks and infrastructure specifically for AI Agents.

This AI Agent Meme trend has sparked a new wave of speculation within the crypto AI space and shifted the market’s attention. Initially focused on decentralized data, GPUs, and other foundational infrastructure in the crypto AI sector, the focus is now on the fervent enthusiasm for AI Agent applications. For example, ai16z’s market value has surpassed $1 billion, and the trend is continuing to gain momentum.

In recent reports on 2025 trends in the crypto industry from institutions such as a16z, VanEck, Bitwise, Hashed, Blockworks, Messari, and Framework, there is widespread optimism about the growth of the crypto and AI markets. These institutions particularly highlight that AI Agent-related products are poised for explosive growth in 2025.

Meanwhile, external interest in the AI sector is also continuing to rise. On December 23, Elon Musk’s AI company xAI announced it had secured another $6 billion in funding, bringing its valuation to $40 billion, which further fuels the AI market’s boom.

On the narrative front, OpenAI is undergoing a transformation from GPT to general artificial intelligence with its AI Agent. OpenAI is reportedly planning to launch its new AI Agent product, “Operator”, in January 2025. This product will be capable of executing complex tasks such as writing code, booking travel, and shopping online. It is expected to generate the same kind of buzz in the AI market as the launch of Sora in early 2024. Additionally, NVIDIA’s annual AI summit will take place in March 2025, remaining a key focus for both the crypto and AI industries.

Every time major Web2 companies like OpenAI and NVIDIA upgrade their large models, it sparks interest in the AI space, drawing in new capital and further igniting the crypto AI sector.

In terms of policy, US President-elect Donald Trump has announced the appointment of David O. Sacks, former PayPal executive, as the White House’s head of AI and cryptocurrency affairs. Sacks, who has dual investment experience in both the crypto and AI industries, has previously invested in companies like Multicoin and others in the AI and crypto spaces. His appointment is expected to drive policies that accelerate the convergence of AI and crypto.

Disclaimer:

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