When the AI gold rush meets Crypto, AI agents make crypto products easier to "fly into the homes of ordinary people."

Original Title: "AI, Crypto, and America"

Author: Derek Edws, Managing Partner at Collab+Currency

Compiled by: Zen, PANews

I am no longer convinced that our traditional strategic frameworks can cope with the new realities of the future—especially given the astonishing acceleration of artificial intelligence technologies and their disruptive potential for the American workforce.

The United States must begin to move toward a new framework to adapt to the new labor realities. This starts with understanding the two most disruptive technological innovations of the past two decades: AI and Crypto.

Artificial Intelligence

Thirty years ago, internet search engines first emerged. Their value seemed simple: retrieving data from around the world. Twenty-five years later, OpenAI's ChatGPT became the fastest-growing consumer application in history. The product boasts 300 million weekly active users and over 10 million monthly paid subscribers. In less than two years, the product's annual revenue is approximately $3 billion.

What is the value of these AI systems? It combines "retrieval" with "completion." Simply put:

1. Request any task in natural language;

2. Leave the completion of the task to computer intelligence.

In the past three months, we have clearly seen these products rapidly improve in their ability to fulfill work requests, with the areas involved continually expanding—text, mathematics, audio, video, geometry, programming, etc.

So far, the scaling assumptions of AI systems remain valid: more data, more computing power, and better models. Additionally, new dimensions of scaling are being explored, with innovations like test-time compute emerging. Last month, OpenAI's latest reasoning model achieved a 25% score on cutting-edge mathematical benchmarks, problems that only deeply specialized mathematicians could solve.

These next-generation reasoning models are adapting to new tasks, producing observable results. Meanwhile, advancements in robotics are making machines increasingly capable of performing complex physical tasks. Intelligent, humanoid hardware will operate tirelessly, never take vacations, and never go on strike.

The release of this technological productivity is not unprecedented—the industrial revolution of the 18th century and the digital revolution of the 20th century significantly lowered costs, improved efficiency, and transformed various forms of labor markets and economic structures.

But AI seems to represent a different kind of technological revolution. These systems can create value in unprecedented ways, transcending traditional cost structures. Dario Amodei, CEO of Anthropic, believes that AI could bring us nearly 50 to 100 years of biological progress in the next 5 to 10 years, simply by transferring most of our human labor structure to AI systems.

As the infrastructure supporting these systems continues to develop, I believe that humanity will see two trend lines gradually emerge:

• The cost of all cognitive labor will trend toward the cost of running AI systems;

• The cost of all physical labor will trend toward the cost of robotic mechanical parts.

The promise of this technology is very clear:

• Unlimited results;

• Dramatically lower prices;

• Crossing every value category.

For the purpose of this article, we assume that the above trends hold true. As someone who firmly believes that the next generation of Americans should have the same opportunities as their predecessors, I have two questions that linger: First, how can America leverage its advantages to win the AI revolution? Second, how can individual Americans participate in the benefits of future AI systems, realizing their disruptive potential for human labor?

Cryptocurrency

In 2008, Satoshi Nakamoto released the Bitcoin white paper. The paper proposed a new, gamified accounting system in which distributed computers around the world could work together to achieve a shared digital consensus on the Bitcoin ledger.

Today, Bitcoin has become the world's most powerful supercomputer. The scale of this network far exceeds the combined scale of networks from companies like Amazon, Google, and Microsoft. However, after fifteen years of development, blockchain still appears cumbersome:

• Poorly written code can have vulnerabilities, leading to theft or zero account balances;

• User errors in managing private keys are the leading cause of cryptocurrency theft last year;

• Compared to traditional web applications, decentralized applications are more difficult to use, with a high user attrition rate.

Despite these limitations, interaction with cryptocurrency has reached historic highs. One study estimates that 40% of the U.S. population now owns cryptocurrency, up from 30% in 2023. Approximately 24,000 developers globally are actively involved in blockchain and blockchain application development each month, far exceeding the mere 1,000 developers per month a decade ago.

Despite all these limitations, why is cryptocurrency still growing? I believe it is precisely because cryptocurrency possesses five unique characteristics—working together, they cannot be replicated by any other database architecture:

1. Digital ownership. Blockchain databases are global, fully auditable, community-owned, tamper-proof, and operate around the clock. Through blockchain, individuals can own any digital object on the internet, establishing a global digital property rights system for the first time.

2. Coordinated incentives. By automatically executing contracts, blockchain-based protocols can utilize programmable incentive mechanisms to coordinate new forms of digital work on the network. These incentives can be directed toward those who use products or services, provide economic security, contribute core code, supply or demand in the market, or recommend others to use the products.

3. Frictionless micropayments. Today, due to high transaction costs, most internet companies must adopt subscription, bundling, and ad-supported business models. This limitation stifles innovation in internet business models and hinders the emergence of consumer-friendly alternatives. Blockchain databases can facilitate digital payments globally in a frictionless, low-cost manner—bypassing the inefficiencies of traditional payment systems and eliminating concerns about chargeback risks. Additionally, any crypto asset can be divided into arbitrarily small units.

4. Shared standards. By utilizing shared settlement standards on the blockchain, various protocol tokens, stablecoins, applications, games, and financial services can seamlessly integrate, just like Lego blocks can connect in any way.

5. Distributed security. Blockchain networks are typically distributed across multiple nodes globally, eliminating single points of failure. This decentralized architecture makes it more difficult for malicious actors to attack these network systems, as they need to control the majority of nodes simultaneously.

Today, the market capitalization of the cryptocurrency economy is approximately $3.6 trillion, covering multiple emerging fields.

In the next decade, I believe the cryptocurrency economy will be repriced significantly upward—primarily driven by two intersecting trends of AI and cryptocurrency: (1) AI and crypto infrastructure; (2) AI and crypto applications.

AI and Crypto Infrastructure

To understand the current landscape of AI infrastructure, it is helpful to look for parallels in historical events.

In 1849, the California Gold Rush quickly attracted massive investment. Hundreds of new roads were built for rapid transportation. The port of San Francisco became one of the busiest ports in the world, shipping gold seekers, goods, and tools worldwide. A powerful banking and financial system emerged to support the needs of new global enterprises. The infrastructure investments of that time laid the foundation for the region to become an economic powerhouse.

175 years later, the world is witnessing a similar gold rush, this time aimed at creating Artificial General Intelligence (AGI). However, the infrastructure supporting AI is not limited to any specific region; networks of data, computing power, and electricity are being constructed globally by competitors.

Unsurprisingly, the capital and computing power required to train, optimize, and deploy AI infrastructure is extremely expensive, and only a few companies can afford it. It is conservatively estimated that training GPT-3 costs over $4 million, while training GPT-4 exceeds $60 million.

More capital, more computing power, better performance.

While I am very proud of and support the contributions of the United States to AI under traditional corporate forms, I also believe it is necessary to acknowledge its structural limitations:

• Value capture. While centralized companies can leverage venture capital to drive significant AI innovations, the economic benefits of these products are limited to a small number of shareholders, restricting broader societal impact.

• Proprietary knowledge. Progress in technological frameworks is often concentrated within centralized companies, limiting others' opportunities to access key breakthroughs—while information flows at internet speed around the clock.

• Opaque systems. Centralizing AI in opaque, closed centralized systems makes it difficult for independent verifiers to audit companies' practices in data collection, security, and accountability.

• Closed competition. The enormous computational resources required to develop advanced AI pose a significant barrier to new products entering the market, allowing only a few well-funded companies to continually break through technological bottlenecks.

By combining the AI infrastructure of the United States with the five unique characteristics of cryptocurrency—digital ownership, coordinated incentives, frictionless micropayments, shared standards, and distributed security—I believe we can mitigate the negative impacts of centralized AI and restore the competitive spirit of American capital markets that has long been absent. Furthermore, by integrating the AI infrastructure of the United States with cryptocurrency, I believe this will lead to better-performing AI systems: (a) greater transparency, (b) and fairer ownership among millions of American participants in the future.

(a) Better Performance

To understand the breakthroughs AI can achieve without substantial funding, we can look at the DeepSeek team. Two weeks ago, this research group based in China released DeepSeek-V3, a 670B parameter model that performs comparably to many closed-source SOTA models, including GPT-4o and Claude-Sonnet-3.5. DeepSeek has not accepted any venture capital to date.

As demonstrated by open-source projects like Bitcoin and Ethereum, by distributing programmable incentives to a global pool of contributors, it is possible to significantly enhance the qualified labor and computing networks, creating a force more powerful than a single lab or centralized system. From this perspective, creating a system that rewards AI labor and computing networks is not much different from creating a system that rewards Bitcoin labor and computing networks.

A few examples:

• For improved training data, crypto networks can reward humans for contributing high-quality labeled datasets—including private data, proprietary intelligence, or information not captured in traditional web scraping.

• For a more powerful computing network, crypto networks can incentivize individuals and organizations to contribute computing power through decentralized markets—rapidly building a global machine network without upfront capital investment.

• For more efficient model training, open-source developers can provide customized contributions, improvements, and optimizations for existing models in exchange for corresponding rewards. Additionally, when code and model weights are made public, hundreds of researchers and developers can simultaneously release improvements, debug issues, fine-tune custom models and agents, and create new applications based on this—coordinated through the network's incentive mechanisms.

Over time, I believe this broad collaborative approach pioneered by decentralized projects (such as Nous Research, Prime Intellect, and Bittensor) will surpass what resource-rich private companies can achieve internally.

(b) Greater Transparency

Open-source AI models allow the research community to thoroughly examine their training processes, architectures, and behaviors, and to make improvements. This transparency helps identify potential risks or biases early on, leading to the development of more reliable systems that people can trust. By utilizing blockchain in this process, the entire workflow of creating, rewarding, and improving AI protocols can remain transparent and auditable.

(c) Fairer Ownership

Crypto networks designed for various verticals within the AI technology stack will establish a fairer ownership structure than existing centralized models. Through programmatic incentives, all contributors and participants in crypto protocols can transparently receive rewards.

Moreover, the complete market formed around the various tasks and roles within the AI infrastructure stack will encourage more refined competition across different categories of AI design. Categories and subcategories such as data, computing, training, and deployment can compete and accumulate value in mutually independent environments.

However, the ultimate beneficiaries will not just be the AI infrastructure. I believe AI agents will fundamentally reorganize the current trajectory of global cryptocurrency adoption—covering all application verticals.

AI and Cryptocurrency Applications

For a long time, the complexity of cryptocurrency applications has been seen as a significant barrier to widespread adoption. Over the past fifteen years, blockchain has required users to engage in complex approval processes, manage private keys, and understand intricate UI patterns, which are beyond the grasp of most internet users.

However, with the emergence of agent technology, these user patterns are rapidly changing. If you view AI models as responsive infrastructures that react based on previous training data, then you can see AI agents as proactive applications that integrate models into new architectures to achieve narrow objectives.

Simply put, AI agents utilize foundational models to think, plan, and execute actions automatically. It is important to understand that agents differ from what we previously knew as "robots." Unlike robots, AI agents can reason on demand. They can analyze their performance, adjust strategies, and tackle complex tasks that sometimes require hundreds or even thousands of unique steps in the future.

In September 2024, I met with one of my portfolio founders who is building an AI agent protocol for blockchain navigation. This protocol is called Wayfinder. Using his phone and a few simple natural language prompts, I deployed a front end and token contract that replicated Bitcoin's monetary policy onto the BASE blockchain, using ETH cross-chain from the Ethereum mainnet. The entire process took less than four prompts and was completed in a total of five minutes.

Startups like Wayfinder showcase an important trend: AI agents will mediate the long-standing technical friction of cryptocurrency. In the next 12 months, agents will transform the complex structure of blockchain into seamless natural language interactions, increasing the accessibility of protocols, protecting users from their own mistakes, helping developers deploy safer code, and significantly reducing consumer attrition in complex decentralized products and services.

More importantly, key management networks will expand all these agent capabilities, allowing agents to execute tasks seamlessly across blockchains without human involvement. A global naming space network will enable the actions of each agent to span all blockchains and connect with a human identity.

Simply put:

Crypto agents make it easier to build or use any crypto product, regardless of which blockchain it is on.

• In decentralized finance, agents will compress the financial friction of cryptocurrencies into each user's risk appetite by simplifying natural language instructions.

• In the crypto gaming sector, agent workflows will support personalized and ownable generative assets, more complex non-player characters, and on-chain experiences tailored for players.

• In decentralized organizations, humans will agree on overall policy goals and constraints, allowing agents to execute across various dimensions of business, protocols, or administrative functions.

These guiding roles and advantages bring a revolutionary breakthrough from zero to one for all crypto applications. Millions of new users will join in this way, with no field being left untouched.

AI, Cryptocurrency, and Ownership

When understanding the grand trends before us, it is important to reflect on and remember the lessons from our history. For most of human history, the ability to secure and defend resources meant survival itself. Modern property rights systems are a product of millions of years of this evolutionary pressure. The concept of property rights is so crucial to human experience that it is enshrined in the U.S. Constitution (Fifth Amendment). The Founding Fathers of the United States viewed property rights as the cornerstone of our governance system and way of life.

Economists have long argued that strong property rights are the foundation of economic growth. They are essential for individuals to safely generate income, store wealth, and leverage these assets for credit and investment over time.

Multiple studies support this view. Research from 1990 to 2002 across over 100 countries showed that countries with stronger property rights grew faster than those with weaker property rights, partly because they could better promote technological growth and improve resource allocation.

From the perspective of property rights, blockchain is a core competitive technology. They are the most powerful technological foundation for global digital information, capable of providing immutable record-keeping, encrypted ownership, distributed security, and programmatically executing rights through smart contracts.

As the United States enters the digital intelligence era, blockchain can also serve as the standard environment for all AI infrastructure and applications, ensuring that America's AI systems can benefit from the structural support of the five unique characteristics of cryptocurrency. Historically, the United States has created unprecedented opportunities for both individuals and the nation—from breaking free from colonial rule to constitutional commitments to individual freedom, to fighting against racial segregation, and fostering fierce market competition and entrepreneurial spirit.

Today, standing on the threshold of AGI, I believe the United States has a significant opportunity to further solidify its leadership in these same dimensions. Aligning America's AI policy goals with cryptocurrency will inspire unprecedented individual participation in open-source networks, driving incentive contributions across all layers of the AI stack. Broad participation in our AI market will stimulate competition, encourage new forms of grassroots mobilization, and bring about broader social impacts.