The Role of Pantera Crypto in the AI Revolution

Coinworld News Report:
Source: Pantera Capital October Blockchain Letter; Translated by: 0xjs@
Crypto: The tool of AI gold rush
Author: Matt Stephenson, Pantera Capital Research Partner; Ally Zach, Pantera Capital Research Engineer
“AI is infinitely abundant, while crypto is absolutely scarce.”
Sam Altman’s observation in 2021 has since become the mantra for enthusiasts of these two technologies. At first glance, abundance seems to have more influence than enforced scarcity, suggesting that AI may be a more cautious investment. In fact, NVIDIA’s market value is larger than the entire cryptocurrency market.
But Altman’s statement brings to mind Adam Smith’s “diamond-water paradox.” Smith pointed out that while water is vital for survival, the abundance of water resources makes it almost worthless. On the other hand, diamonds, despite having little practical use, are valuable because of their scarcity. This paradox suggests that even if AI becomes as important as water, its market value may still be limited. In contrast, the scarcity of cryptocurrencies is more strategically important and valuable than initially perceived.
Large language models (LLMs) have achieved significant accomplishments, including reportedly outperforming humans in standard intelligence tests, such as the Turing test. But this raises the question: if humans cannot distinguish between human and intelligent AI (in the Turing test), can they distinguish between intelligent AIs? If humans cannot discern, then future improvements in AI performance may result in diminishing returns in terms of consumer-perceivable benefits.
Just as the leap from 4K to 8K resolution on TVs is barely noticeable to the average viewer, the difference between high-performance AI models and slightly more advanced models may also be imperceptible to most users. This could lead to the commoditization of the majority of the AI market, where state-of-the-art models will only be used for specialized applications in research, industry, or government sectors, while more cost-effective “good enough” models become the standard for everyday use. Top-tier AI models may become “expensive boutique items that mainstream consumers will never consider upgrading.”
Therefore, even as we speculate on the potential growth of AI, we should consider an alternative: the powerful capabilities of current AI are already known and becoming increasingly commoditized. This is where the intersection of crypto and artificial intelligence (“Crypto x AI”) truly comes into focus.
The potential of crypto may not be a high-beta bet on the meme value of AI, but rather a mechanism for practical value acquisition in the distributed future of AI.
Once everyone has a 4K TV at home, its value lies in what we do with them.
By serving as important and reliable inputs to AI and facilitating the coordination and transactions of distributed AI, cryptocurrencies are closer to a conservative “shovel and pickaxe” bet on AI. This may come as a surprise to investors who primarily see Crypto x AI as a proxy for the potential growth of AI. Interestingly, in the past six months, while NVIDIA appeared to represent AI growth sentiment, cryptocurrencies seemed more like a hedge against AI growth sentiment rather than a high-beta value investment.


We will first assess the bright prospects of “AI agents” and how crypto technology will play a role. Then, we will discuss the potential of crypto technology to support current inputs for AI: data, computation, and models.
AI Agents: Programs using programmable currency
Author: Matt Stephenson, Pantera Capital Research Partner
Last year, before most people were talking about AI agents on the blockchain, I collaborated with others to write a paper that was accepted by the top AI conference in the United States, NeurIPS. Since then, I have had the privilege of participating in crypto and AI agent activities at universities such as Stanford, Columbia, Cornell, and Berkeley, and giving speeches. Next week, I will be speaking about AI with a professor from Oxford University, the chairman of IEEE, and a member of GBBC. All of these speeches are aimed at better understanding, exploring, and communicating what the future of AI as intelligent agents is and how it intersects with blockchain. Of course, I also invest in this future, including investments in infrastructure for intelligent agents like Sentient and other undisclosed positions.
The future is already here. While OpenAI says that AI agents won’t be ready until 2025, in the realm of cryptocurrencies, we already have AI agents trading and exploring in the blockchain space. An AI agent that has promoted its own token (Note: Truth Terminal) currently has around $300,000, and by the time you read this article, it may become the first AI agent millionaire.
But what are these agents? How are they different from the more familiar “robots”?
Agents are more than just robots
Defining an “agent” is more subtle than it seems. The AI field’s definition of an agent is not very practical: “something that perceives its environment through sensors and acts upon that environment through actuators.” The economist’s view of an agent is closer to what we want: “an agent is someone who acts on your behalf in a particular decision domain.”
If an agent acts on your behalf, then a robot is essentially an agent that is difficult to communicate with. First, you have to write code for the robot to execute, which means communicating in a language that most people don’t understand (programming). And for those who understand the language, they still have to write programs for the robot to do what it should do under various conditions, which means specifying those conditions in advance. Both of these are communication costs.
To give an example, suppose you have a friend going abroad, and you ask them to buy you a souvenir. If your friend is like a robot, they will ask you to write a program specifying exactly what souvenir they should buy for you. What if your friend is an agent? Then you can make a request using language, and you can trust that your friend will buy what you want. Using language, without having to specify preferences for gifts you might receive abroad, reduces communication costs. Clearly, this is a better agent.
The fact that you have to know the conditions in advance (because you have to program them) limits the practicality of robots as agents. And just the fact that you have to program a robot means that it is out of reach for those who don’t program. We will turn to AI agent modeling as a way to reduce these communication costs and unlock corresponding economic value.


While the communication costs of current robots are high, the over $2 trillion monthly stablecoin trading in the cryptocurrency market seems to be robot trading. As robots become better agents, perhaps they will be able to trade USDC and USDT based on relative risks, just like you do. We should expect this number to increase.
AI agents will use crypto technology
One reason AI agents are beneficial for cryptocurrencies is that they help alleviate the notorious user experience problems associated with cryptocurrencies.
The complexity of blockchain interactions, wallet management, and decentralized financial protocols has long been a barrier to widespread adoption. AI agents can serve as intuitive interfaces, translating user intentions into the precise technical operations required on the blockchain. They can guide users through complex transactions, explain risks, and even suggest optimal strategies based on market conditions and user preferences.
Another reason is that agents cannot have bank accounts but can transact with wallets.
This limitation of traditional financial systems aligns perfectly with the spirit of cryptocurrencies. In the crypto world, agents do not need permission from central institutions to operate. They can interact directly with smart contracts and decentralized protocols, representing users in holding and managing digital assets. This opens up new possibilities for fully operationalized automated wealth management, round-the-clock trading, and personalized financial services within the crypto ecosystem.
Lastly, a mature ecosystem of intelligent agents implies that agents need to transact and coordinate with each other.
Modern smart contracts, as programmable and always-online international legal systems, are well-suited for this task. AI agents can engage in complex multi-party transactions and protocols leveraging the cryptographic infrastructure. They can negotiate terms, execute transactions within the parameter range set by human principals, and even resolve disputes. This creates a new paradigm of autonomous economic activity where agents can form temporary alliances, pool resources, and collaborate to accomplish tasks that are beyond or impractical for direct human management.
We believe that these activities will add value to the crypto infrastructure. But there are also indirect effects that make crypto itself better. For example,Due to attention limitations in encryption, decentralized autonomous organizations (DAOs) have been inactive. DAOs managed by AI agents networks (each agent representing the interests of DAO voters) will change the game. These agents can analyze proposals, allocate resources, and execute strategies at a speed and scale beyond human capability, while adhering to the core principles and goals of their human creators.


AI agents and cryptocurrencies are not just a perfect combination; they are two technologies that mutually need each other. Agents need programmable currency to operate autonomously in the digital economy. Cryptocurrencies need AI to improve user experience and fulfill their promise of bringing financial revolution to everyone.
With the development of this synergy, we may see core blockchain infrastructures like Solana, Ethereum, Near, and Arbitrum become the main beneficiaries of this new agent-driven economy. They are prepared to achieve this goal by facilitating decentralized applications that enable agent transactions, hosting agents, and providing a secure and transparent environment for agent coordination. As agent activity increases, these networks may experience an increase in transaction volume, demand for their native tokens, and enhanced network effects. This is not just about technical compatibility—it is about creating a new economic paradigm where AI and cryptocurrencies work together to make finance more efficient, accessible, and even a bit futuristic.
Cryptocurrency technology empowers current AI
Author: Ally Zach, Research Engineer at Pantera Capital
Imagine being on the verge of a breakthrough, only to find that the tools you need are out of reach. Innovation often feels this way—a journey filled with breakthrough highs and challenging lows. Take the automotive industry, for example, the quest for more efficient engines once hit a roadblock. Engineers were eager to push the limits, but the necessary materials didn’t exist. Progress stalled until new alloys and composite materials reignited the innovation engine. Similarly, new technologies like encryption may unlock untapped potential in AI.
AI has been steadily progressing over the years, following a slow-then-rapid development trajectory akin to an S-curve. In 2017, we reached a crucial breakthrough with the advent of Transformer-based architectures, as outlined in the influential paper “Attention Is All You Need.” These Transformers revolutionized sequential data processing in models, enabling efficient training on large datasets. This sparked rapid advancements in powerful new language models and generative AI models.
While AI has made progress, overcoming significant bottlenecks in data, computation, and model generation is necessary for the next leap forward.
Combining AI with blockchain technology can help decentralize resources and democratize access, making innovation open to global contributors.
Data
Data is the lifeblood of AI, fueling its accuracy and reliability. High-quality, representative data is crucial for building effective models, but obtaining this data is challenging due to privacy concerns, restricted access, and inherent biases. Additionally, users are increasingly reluctant to share personal information, making data collection resource-intensive and often hindered by trust issues.
Blockchain technology offers a promising solution by introducing decentralized, secure, and transparent data aggregation methods. Platforms like Sahara align with our long-term strategy of advancing decentralized infrastructure for AI by enabling individuals to contribute data and monetize it while retaining control. Furthermore, token economies incentivize high-quality contributions by appropriately rewarding users. This approach helps address privacy concerns by allowing users to own and control their data. It democratizes data access, empowering small businesses that previously lacked resources to compete with tech giants. By incentivizing data sharing in a secure manner, blockchain-based platforms turn data into a commodity, enriching the pool of available data and potentially leading to more robust and fair AI models.
However, while innovative, blockchain-based data aggregation is not a standalone solution for AI development. If used in isolation, practical challenges such as scalability, data quality assurance, and integration complexity limit its effectiveness. Large tech companies still hold significant advantages over decentralized platforms, thanks to their vast datasets and mature infrastructure.
Therefore, solutions incorporating blockchain-based approaches introduce new avenues for data collection and collaboration, complementing traditional methods rather than replacing them. The synergy between decentralized efforts and established tech leaders can foster partnerships that leverage the strengths of both sides, driving innovation and inclusivity in AI development.
Computation
The rising cost and scarcity of GPUs pose significant obstacles for AI development among small enterprises. Since the outbreak of the pandemic, GPU prices have been continuously rising due to high demand and supply chain issues, leading to increased monopolization of basic hardware by large enterprises. This restricts innovation as many startups and researchers require assistance to afford tools for advanced model training. It diminishes diversity in AI research and slows progress for small institutions.
However, by commoditizing computational power, cryptocurrencies have the potential to create a fair competitive environment. Platforms like Exo and io.net are democratizing GPU access through decentralized marketplaces, allowing anyone to access or lend computational resources. Individuals with idle computing power can offer it on the network and receive rewards in return. The commoditization of high-performance computing enables a broader range of innovators to participate in AI development, breaking down barriers that once limited access to advanced tools.
In the future, as GPU supply increases, decentralized computing markets may directly compete with traditional cloud services. These platforms lower barriers to entry and offer cost-effective alternatives, enabling wider participation in the AI ecosystem. However, ensuring users have reliable computing power remains a challenge. Establishing GPU standards and maintaining consistent, secure resources are crucial for building trust and preventing fraud. While decentralized solutions may not replace traditional services, they can provide competitive alternatives where flexibility and cost outweigh guaranteed performance.
Models
Currently, AI development is mostly concentrated in a few organizations like OpenAI, Google, and Facebook. This centralization limits opportunities for global innovators and raises concerns about whether AI reflects diverse human values. Central control can result in models that embody narrow perspectives, overlooking the needs and viewpoints of a broader user base.
The power distribution of AI development is undergoing a transformation through decentralized platforms. Platforms like Sentient and Near align with our vision of AI increasingly operating on the crypto track, democratizing development through the creation of open-source, community-driven ecosystems. Leveraging blockchain technology, they transparently manage contributions, ensuring developers are recognized and compensated through token rewards. This enables anyone to build, collaborate on, own, and monetize AI products, ushering in a new era of AI entrepreneurship. Illia Polosukhin, co-author of the groundbreaking paper “Attention Is All You Need” and co-founder of Near, is fostering an open environment for developing Artificial General Intelligence (AGI) through crowdsourcing efforts. Such collaborative initiatives aim to merge AI development with diverse human values.
These platforms act as catalysts for change, driving an AI economy that is both competitive and collaborative. By expanding participation, they foster a vibrant range of ideas, leading to more innovative solutions and potentially reducing biases in AI models.
Crypto x AI presents a unique opportunity for democratizing AI development, but it also comes with significant challenges. Balancing large-scale collaboration with high-quality, expert-driven work is crucial for ensuring robust and ethical models. Through decentralized data access, computational power, and model development, encryption breaks down traditional barriers, enabling talents from around the world to participate in AI development. The influx of diverse perspectives promotes collaboration and builds a more inclusive ecosystem. Embracing this collaborative model not only accelerates innovation but also ensures that the global community shapes the future of AI.