Coinworld reports:
Source: Pantera Capital October Blockchain Letter; Translated by: 0xjs@
Crypto: The Powerful Tool of AI Gold Rush
Authors: Matt Stephenson, Research Partner at Pantera Capital; Ally Zach, Research Engineer at Pantera Capital
“AI is infinite wealth, while Crypto is absolute scarcity.”
Sam Altman’s observation in 2021 has since become a mantra for enthusiasts of both technologies. At first glance, wealth seems more influential than forced scarcity, suggesting that AI may be a more cautious investment. In fact, the market value of Nvidia is larger than the entire cryptocurrency market.
However, Altman’s statement reminds us of Adam Smith’s “Diamond-Water Paradox.” Smith pointed out that although water is crucial for survival, abundant water resources make water almost worthless. On the other hand, diamonds, although of 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 comparison, the scarcity of cryptocurrencies is more strategically important and valuable than it initially appears.
Large language models (LLMs) have achieved significant accomplishments, including reportedly outperforming humans in standard intelligence tests such as the Turing test. But this raises a question: if humans can’t distinguish between humans and intelligent AI (in the Turing test), can they distinguish between intelligent AIs? If humans cannot differentiate, then the improvement in AI performance in the future may result in diminishing returns in terms of consumer-perceivable benefits.
Just as the leap from 4K to 8K resolution in television has minimal visible improvements for the average viewer, the difference between high-performance AI models and slightly more advanced models may also be difficult for most users to perceive. This could lead to the commodification of the majority of the AI market, where the most advanced models are used only for research, industrial, or governmental applications, while cost-effective “good enough” models become the standard for everyday use. Top 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 perspective: 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 lie in a high-beta bet on the meme value of AI, but in the practical value capture of a distributed AI future.
Once everyone has a 4K television 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 transaction of distributed AI, cryptocurrencies are closer to conservative “shovels and picks” bets on AI. This may surprise investors who primarily view Crypto x AI as a volatility proxy for AI’s potential growth. Interestingly, in the past six months, while Nvidia seemed like a proxy for AI growth sentiment, cryptocurrencies appear more like a hedge against AI growth sentiment rather than high-beta value investments.
We will first evaluate the bright prospects of “AI agents” and how cryptographic technologies will play a role. Then, we will discuss the potential of cryptographic technologies to support the current inputs of AI: data, computation, and models.
AI Agents: Programs Using Programmable Currency
Author: Matt Stephenson, Research Partner at Pantera Capital
Last year, before most people were talking about AI agents on the blockchain, I co-authored a paper that was accepted by the top AI conference NeurIPS in the United States. Since then, I have had the privilege of participating in crypto and AI agent events at universities such as Stanford, Columbia, Cornell, and Berkeley, giving talks, and attending numerous technical and investment conferences. 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 talks are aimed at better understanding, exploring, and communicating what the future of AI as intelligent agents looks like and how it intersects with blockchain. Of course, I am also invested 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 world of crypto, we already have AI agents operating on the blockchain space for trading and exploration. 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 nuanced than it appears. The definition of an agent in the field of artificial intelligence 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 specific decision-making domain.”
If an agent acts on your behalf, then a robot is essentially an agent that is difficult to communicate with. First, you must write code for the robot to execute, which means communicating in a language that most people do not 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 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 them to buy a souvenir for you. If your friend is like a robot, they would ask you to write a program specifying exactly what souvenir they should buy for you. What if your friend were an agent? You could use language to make the request, and you could trust that your friend would buy what you want. Using language without having to specify preferences for gifts you may receive abroad reduces communication costs. Clearly, this is a better agent.
The need to know conditions in advance (because you have to program them) limits the practicality of robots as agents. And the fact that you have to program robots means that they are out of reach for those who do not program. We turn to AI agent modeling as a means to reduce these communication costs and unlock the corresponding economic value.
Although the communication costs of existing robots are high, the monthly trading volume of stablecoins in the cryptocurrency market, which exceeds trillions of dollars, seems to be robot trading. As robots become better agents, they might be able to trade USDC and USDT based on relative risks, just like you. We should expect this number to increase.
AI agents will use cryptographic technologies
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 precise technical operations required on the blockchain. They can guide users through complex transactions, explain risks, and even recommend 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 in traditional financial systems aligns perfectly with the spirit of cryptocurrencies. In the crypto world, agents do not need permission from central authorities 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 operational automated wealth management, round-the-clock trading, and personalized financial services within the crypto ecosystem.
Finally, 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 leverage cryptographic infrastructure to participate in complex multi-party transactions and protocols. They can negotiate terms, execute transactions within the parameters 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 on tasks that are beyond or not directly manageable by humans.
We believe that these activities will add value to the cryptographic infrastructure. But there are also indirect effects that make crypto itself better. For example,Due to attention constraints in cryptography, decentralized autonomous organizations (DAOs) have been inactive. DAOs managed by AI agents, which represent 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 capabilities, while adhering to the core principles and goals set by their human creators.
AI agents and cryptocurrencies are not just a perfect combination; they are two technologies that need each other. AI agents need programmable currencies to operate autonomously in the digital economy. Cryptocurrencies need AI to improve user experience and fulfill their promise of a financial revolution for everyone.
With the development of this synergy, we may see core blockchain infrastructures such as Solana, Ethereum, Near, and Arbitrum become the main beneficiaries of this new agent-driven economy. They are ready to achieve this goal by promoting decentralized applications that facilitate agent transactions, hosting proxies for interaction, and providing a secure and transparent environment for agent coordination. As agent activity increases, these networks may see 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 science fiction-like.
Cryptographic 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 like this—a journey of highs and lows. In the automotive industry, for example, the quest for more efficient engines hit a dead end. Engineers yearned to push the limits, but the materials they needed didn’t exist. Progress stagnated until new alloys and composites reignited the engine of innovation. Similarly, new technologies like cryptography have the potential to unlock untapped AI capabilities.
The development of AI has been incremental over the years, following a sigmoid curve of slow progress followed by rapid advancements. In 2017, we made a critical breakthrough with the emergence of Transformer-based architectures, as outlined in the influential paper “Attention Is All You Need.” These Transformers revolutionized the processing of sequential data in models, enabling efficient training on large datasets. This sparked the rapid development of powerful new language models and generative AI models.
While AI has made progress, overcoming major bottlenecks in data, computation, and model generation is necessary for the next leap.
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 and fuels its accuracy and reliability. High-quality, representative data is crucial for building effective models, but acquiring this data is challenging due to privacy concerns, restricted access, and inherent biases. Additionally, users are increasingly unwilling 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 AI infrastructure, enabling individuals to contribute data and monetize it while retaining control. Additionally, token economies incentivize high-quality contributions by appropriately rewarding users. This approach helps address privacy concerns by allowing users to own and control their own data. It democratizes data access, enabling 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 available pool of data and potentially producing 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 would limit its effectiveness. Large tech companies still have significant advantages over decentralized platforms due to their massive datasets and mature infrastructure.
Therefore, solutions that include 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, promoting innovative and inclusive AI development.
Computation
Rising GPU costs and scarcity pose significant barriers to AI development for small enterprises. Since the outbreak of the pandemic, GPU prices have skyrocketed due to high demand and supply chain issues, with larger enterprises increasingly monopolizing the use of essential hardware. This restricts innovation as many startups and researchers need assistance in affording tools for training advanced models. It diminishes diversity in AI research and slows progress for small institutions.
However, crypto has the potential to create a fair competitive landscape by commoditizing computational power. Platforms like Exo and io.net are democratizing GPU access through decentralized markets, allowing anyone to access or lend computing 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 previously 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 entry barriers and provide 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 concentrated in a small number of organizations like OpenAI, Google, and Facebook. This centralization limits opportunities for global innovators and raises concerns about whether AI can reflect diverse human values. Centralized control may result in models that embody narrow perspectives, overlooking the needs and viewpoints of broader user populations.
Decentralized platforms are driving a shift by distributing the power of AI development. Platforms like Sentient and Near align with our vision that AI will increasingly operate 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, own, and monetize AI products, ushering in a new era of AI entrepreneurship. Co-author of the groundbreaking paper “Attention Is All You Need” and co-founder of Near, Illia Polosukhin, is fostering an open environment for developing General AI (AGI) through crowdsourcing efforts. Such collaborative initiatives aim to combine 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 encourage diverse ideas to flourish, leading to more innovative solutions and potentially reducing biases in AI models.
Crypto x AI presents a unique opportunity to democratize AI development but also brings significant challenges. Balancing large-scale collaboration with high-quality, expert-driven work is crucial to ensuring robust and ethical models. Through decentralized data access, computational power, and model development, crypto breaks down traditional barriers, enabling talent from around the world to participate in AI’s 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.
