Pantera: The Role of Crypto in the AI Revolution

Source: Pantera Capital October Blockchain Letter; Translated by 0xjs@Jinse Finance

Crypto: The Tool for the AI Gold Rush

Author: Matt Stephenson, Research Partner at Pantera Capital; Ally Zach, Research Engineer at Pantera Capital

"AI is infinitely abundant, while Crypto is absolutely scarce."

Sam Altman's observation in 2021 has since become a mantra for lovers of both technologies. At first glance, abundance seems to be more impactful than forced scarcity, suggesting that AI may be a more prudent investment. In fact, Nvidia's market cap is larger than the entire cryptocurrency.

But Altman's remarks remind one of Adam Smith's "paradox of diamonds and water." Smith pointed out that while water is essential for survival, its abundance makes it virtually worthless.

In contrast, diamonds, although not very practical, are valuable due to their scarcity. This paradox suggests that even if AI becomes as important as water, its market value may still be limited. In comparison, the scarcity of cryptocurrencies is strategically more important and valuable than it initially appears.

The large language model (LLM) has made notable achievements, including passing the Turing test, and is reported to outperform humans on standard IQ tests. But this raises the question: if humans can't distinguish between humans and intelligent AI (in the Turing test), can they distinguish between intelligent AIs? If humans can't discern, future improvements in AI performance could yield diminishing returns in terms of perceived benefits to consumers.

Just as the jump in TV resolution from 4K to 8K is a negligible improvement for the average viewer, the difference between a high-performance AI model and a slightly more advanced model may be imperceptible to most users. This could lead to much of the AI market being commoditized, with state-of-the-art models being used only for specialized applications in research, industry, or government, and more cost-effective "good enough" models becoming the standard for everyday use. Top-of-the-line AI models could become "expensive boutiques that mainstream consumers would never consider upgrading."

So, even if we speculate on the potential growth of AI, we should consider another option: the power that AI is known to have already existed and will increasingly commoditize. This is where the intersection of crypto and artificial intelligence ("Crypto x AI") really comes into focus. The potential of Crypto may not be a high beta bet on the value of AI memes, but a practical value acquisition mechanism for the distributed future of AI. Once everyone has a 4K TV in their home, the value lies in what we do with them.

By acting as an important and reliable input to AI and a track for distributed AI coordination and transactions, cryptocurrencies are closer to the conservative "shovel and pick" bet on AI. This may come as a surprise to investors who see Crypto x AI primarily as a proxy for volatility for the potential growth of AI. But interestingly, over the past six months, Nvidia has been seen as a proxy for AI growth sentiment, with cryptocurrencies looking more like a hedge against AI growth sentiment than a high-beta investment.

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We will first assess the bright prospects of "AI agents" and how blockchain technology will play a role. Then, we will discuss the potential of blockchain technology to support the current inputs of AI: data, computation, and models.

AI Agent: Programs Using Programmable Currency

Author: Matt Stephenson, Partner at Pantera Capital

Last year, before most people talk about AI agents on the blockchain, I co-authored a paper that was accepted by NeurIPS, the top AI conference in the United States. Since then, I have had the privilege of attending and speaking at crypto and agent AI events at universities such as Stanford, Columbia, Cornell, and Berkeley, in addition to attending many technology and investment conferences. Next week, I'll be giving talks on AI with professors from the University of Oxford, IEEE Chair, and GBBC members, all to better understand, explore, and communicate what the future of agent AI is and how it intersects with blockchain. Of course, I'm also investing in this future, including investing in agent infrastructure like Sentient and other undisclosed positions.

The future has arrived. Although OpenAI states that AI agents will not be ready until 2025, in the cryptocurrency space, we already have AI agents capable of trading and exploring on the blockchain. An AI agent that has promoted its own token (Note: Truth Terminal) currently has about $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 "robots" we are more familiar with?

Agent is more than just a robot

Defining "agent" is more subtle than it appears. The definition of an agent in the field of artificial intelligence is not very practical: "anything that perceives the environment through sensors and acts on the environment through actuators." Economists' view of agents is closer to what we want: "an agent is someone who acts on your behalf in a specific decision-making domain."

If the agent is acting on your behalf, then the bot is inherently a difficult agent to communicate. First, you have to write code for the bot to execute, which means communicating in a (programming) language that most people don't understand. And for those who understand the language, they still have to program what the robot should do under a variety of different conditions, which means specifying these conditions in advance. Both of these are communication costs.

For example, let's say you have a friend who is going abroad and you ask him to buy you a souvenir. If your friend is like a robot, he will ask you to write a program specifying what souvenirs they should buy you. What if your friend was like an agent? Then you can make requests in words, and you can trust your friends to buy you what you want. Use language without the need to state preferences for gifts you may receive abroad, which can reduce communication costs. Obviously, this is a better agent.

It is essential to understand the conditions in advance (because you have to program them), which limits the practicality of robots as agents. Then, simply the fact that robots must be programmed means that they are out of reach for those who do not program. We will turn to modeling AI agents as a reduction in these communication costs and the corresponding release of economic value.

Despite the high communication costs of existing robots, it seems that over $20 trillion in cryptocurrency stablecoin transactions each month are executed by bots. As robots become better agents, perhaps they will be able to trade USDC and USDT based on relative risk like you do, and we should expect this number to increase.

AI agents will use encryption technology.

One reason why AI agents are beneficial to cryptocurrencies is that they help alleviate cryptocurrency's notorious user experience issues. The complexity of blockchain interactions, wallet management, and decentralized finance protocols has long been a barrier to widespread adoption. AI agents can act as an intuitive interface that translates user intent into precise technical operations required on the blockchain. They can guide users through complex trades, explain risks, and even suggest the best strategy based on market conditions and user preferences.

Another reason is that agents cannot have a bank account, but they can trade with a wallet. This limitation of the traditional financial system is fully in line with the spirit of cryptocurrency. In the crypto world, agents do not need to be licensed by a central authority to operate. They can interact directly with smart contracts and decentralized protocols to hold and manage digital assets on behalf of users. This opens up new possibilities for automated wealth management, round-the-clock trading, and personalized financial services that operate entirely within the crypto ecosystem.

Finally, a mature ecosystem of agents means that agents need to transact and coordinate with each other. Modern smart contracts, as programmable, always-on international legal systems, are ideally suited for this task. AI agents can leverage cryptographic infrastructure to participate in complex multi-party transactions and protocols. They can negotiate terms, execute transactions, and even resolve disputes within parameters set by human principals. This creates a new paradigm of autonomous economic activity, where agents can form temporary alliances, pool resources, and collaborate to accomplish tasks that humans cannot or cannot directly manage.

We believe that all of these activities add value to the crypto infrastructure. But there are also indirect effects that make crypto itself better. For example, the decentralized autonomous organization (DAO) has been inactive due to attention constraints in crypto. DAOs actively managed by a network of AI agents, each representing the interests of DAO voters, will be a game-changer. These agents can analyze proposals, allocate resources, and execute strategies at a speed and scale beyond human capabilities, while adhering to the core principles and goals of their human creators.

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AI agents and cryptocurrencies are not just a perfect combination, they are two technologies that need each other. Agents need programmable money to function autonomously in the digital economy. Cryptocurrencies need AI to improve the user experience and deliver on its promise of bringing about a financial revolution for everyone. As this synergy develops, we may see core blockchain infrastructures such as Solana, Ethereum, Near, and Arbitrum emerge as major beneficiaries of this new agent-driven economy. They are poised to achieve this by facilitating agent transactions, hosting decentralized applications that agents interact with, and providing the secure, transparent environment needed for inter-agent coordination. As agent activity increases, these networks are likely to see increased transaction volumes, increased demand for their native tokens, and enhanced network effects. It's not just about technology compatibility – it's also about creating a new economic paradigm in which AI and cryptocurrencies work together to make finance more efficient, more accessible, and perhaps even a little sci-fi.

Cryptography Technology Empowers Current AI

Author: Ally Zach, Research Engineer at Pantera Capital

Imagine you're about to make a big breakthrough, only to find that the tools you need are out of reach. Innovation often feels like this – a journey full of highs and lows. In the automotive industry, for example, the search for more efficient engines has reached a dead end. Engineers are eager to push the envelope, but the materials needed don't exist yet. Progress stalled until new alloys and composites reinvigorated the innovation engine. Similarly, new technologies such as encryption may unlock the untapped potential of AI.

Over the years, the development of AI has been gradual, first slowly, then rapidly, similar to the S-curve. In 2017, we made a key breakthrough with Transformer-based architectures, as outlined in the influential paper "Attention is All You Need." These transformers revolutionize sequential data processing in models, enabling efficient training on large datasets. This has sparked the rapid development of powerful new LLMs and generative AI models.

Despite the progress made in the development of AI, significant bottlenecks in data, computation, and model generation must be overcome to achieve the next leap. Combining AI with blockchain technology can help decentralize resources and democratize access, opening up innovation to contributors worldwide.

data

Data is the lifeblood of AI and the fuel that drives its accuracy and reliability. High-quality, representative data is essential for building effective models, but access to this data is challenging due to privacy concerns, limited access, and inherent bias. In addition, users are increasingly reluctant to share personal information, which makes data collection resource-intensive and often hampered by trust issues.

Blockchain technology offers a promising solution by introducing a decentralized, secure, and transparent approach to data aggregation. Platforms like Sahara align with our long-term strategy to advance AI decentralized infrastructure, which enables individuals to contribute and monetize data while retaining control. In addition, the token economy incentivizes high-quality contributions by rewarding users accordingly. This approach helps address privacy concerns by giving users ownership and control over their own data. It democratizes data access, enabling small businesses that previously lacked the resources to compete with big tech companies. By incentivizing data sharing in a secure way, blockchain-based platforms turn data into commodities, enriching the available data pool and potentially producing more robust and unbiased AI models.

However, despite being highly innovative, blockchain-based data aggregation is not a standalone solution for AI development. When used in isolation, practical challenges such as scalability, data quality assurance, and integration complexity can limit its effectiveness. With vast datasets and mature infrastructure, large tech companies still have significant advantages that decentralized platforms find hard to compete with.

As a result, solutions, including blockchain-based solutions, introduce new avenues for data collection and collaboration that complement rather than replace traditional approaches. The synergy between decentralization efforts and established technology leaders can lead to partnerships that leverage the strengths of both parties to promote innovation and inclusivity in AI development.

calculation

The rising cost and scarcity of GPUs presents significant hurdles for small businesses in AI development. Due to strong demand and supply chain issues, GPU prices have continued to rise since the start of the pandemic, and large enterprises have increasingly monopolized the use of essential hardware. This limits innovation, as many startups and researchers need help to afford tools for advanced model training. This reduces the diversity of AI research and slows down the progress of small institutions.

However, Crypto has the potential to level the playing field by commoditizing computing power. Platforms like Exo and io.net are democratizing GPU access through decentralized marketplaces where anyone can access or lend computing resources. Individuals with idle computing power can make it available on the network and thus be rewarded. The commoditization of high-performance computing has enabled a wider range of innovators to participate in AI development, breaking down barriers that once limited access to advanced tools.

In the future, as the supply of GPUs increases, the decentralized computing market may compete directly with traditional cloud services. These platforms lower the barrier to entry and provide a cost-effective alternative that enables people to participate more broadly in the AI ecosystem. However, ensuring that users have access to reliable computing power remains a challenge. Verifying GPU standards and maintaining consistent, secure resources is critical to building trust and preventing fraud. While decentralized solutions may not be able to replace traditional services, they can offer competitive alternatives because flexibility and cost are more important than guaranteed performance.

model

Today, AI development is often concentrated in a small group of organizations such as OpenAI, Google, and Facebook. This concentration limits opportunities for global innovators and raises concerns about whether AI can reflect diverse human values. Centralized control can lead to a model that embodies a narrow view and ignores the needs and perspectives of a broader user base.

A shift is taking place to distribute the power of AI development through decentralized platforms. Platforms like Sentient and Near align with our vision that AI will increasingly run on crypto tracks, and they are democratizing development by creating open-source, community-driven ecosystems. Leveraging blockchain technology, they transparently manage contributions, ensuring that developers are recognized and compensated through token rewards. This makes it possible for anyone to build, collaborate, own, and monetize AI products, ushering in a new era of AI startups. Illia Polosukhin, co-author of the seminal paper "Attention is All You Need" and co-founder of Near, is crowdsourcing in an effort to create an open environment for developing artificial general intelligence (AGI). Collaborative initiatives like this aim to align AI development with broad human values.

These platforms act as catalysts for change, driving an AI economy that is both competitive and collaborative. By expanding engagement, they encourage a variety of ideas to flourish, leading to more innovative solutions and potentially reducing bias in AI models.

Crypto x AI presents a unique opportunity to democratize AI development, but it also presents significant challenges. Balancing large-scale collaboration with the need for high-quality, expert-driven work is critical to ensuring that the model is robust and ethical. By decentralizing data access, computing power, and model development, encryption breaks down traditional barriers and enables talent from all over the world to participate in the development of AI. This influx of diverse perspectives fosters collaboration and builds a more inclusive ecosystem. Embracing this collaborative model not only accelerates innovation, but also ensures that a global community shapes the future of AI.