👁️‍🗨️Visualize the Future

Trillions, onchain.

The potential market for onchain AI agents is vast, and while predicting the exact scale is challenging, the OINs protocol is designed to facilitate widespread participation and massive adoption. By ensuring that as many people as possible can benefit from training highly capable intelligent agents and making them openly available, the network aims to decentralize access to this transformative technology. With the ability to scale to millions of users training thousands of agents for diverse purposes, OINs has the potential to revolutionize the AI landscape. As the system grows, efforts will gradually decentralize, placing the ownership and responsibility of building this onchain future in the hands of the OINs community.

Every aspect of the OINs protocol is intentionally designed, drawing inspiration from cutting-edge research in multi-agent systems. Projects like AlphaStar, OpenAI Five, and Pluribus have demonstrated that self-play across hundreds or thousands of agents is one of the most effective strategies for training top-tier intelligence systems. By leveraging these insights, OINs aims to enable the growth of this technology in a more decentralized manner than ever before.

Games are fun. Games are a universal source of entertainment that transcends age, wealth, and geography. Well-designed games captivate people from all walks of life. Many individuals willingly dedicate countless hours to playing or watching these games, simply for the joy of mental stimulation, even in the absence of monetary rewards.

OINs aims to harness this universal appeal by attracting a significant player base to games that contribute computational resources to train AI agents. If successful, this system could potentially leverage a massive amount of computing power distributed across the world. By introducing small microtransactions for each game, OINs could outsource the compute to server farms and GPU networks worldwide, while the [token redacted] training rewards would help incentivize player participation.

DeepMind, a subsidiary of Google, utilized intelligent agent technologies to create AlphaStar, a team of AI agents capable of mastering team-play in the complex strategy game StarCraft II. While DeepMind had access to state-of-the-art research and compute infrastructure, the underlying principles remain the same. By training AlphaStar using approximately 256 Tensor Processing Units (TPUs) over a period of 44 days, they developed a generalized AI team that could outperform human Grandmaster-level teams, despite the human players having trained for many years to reach their level of expertise.

A TPU is essentially a proprietary Google computer that is specialized for processing AI models and their compute pipelines.

Now, we can imagine what it would take for the OINs Open Source Intelligence Network to produce a similar outcome.

A thought experiment:

Anyone, can train agents onchain and they will receive $ECHO based on the amount they trained. Users are incentivized to promote the best performing agents to be trained to mastery. Once an agent is trained to mastery, users that were mining that agent are incentivized to find a new high-performing agent to promote, encouraging diverse competition.

The OINs strategy enables it to compete with top-performing agent training platforms that rely on hundreds to thousands of agents competing in self-play, tournament-like scenarios. As the platform grows, users will become accustomed to collectively training tens to thousands of OINs for each specific game, which happens to be the optimal approach for solving high-difficulty games like StarCraft II using multi-agent populations. This design is intentional and well-considered.

To illustrate the potential scale, consider a scenario where 100,000 people each watch or play a game 1,000 times. This would generate the computational equivalent of 100 million total games played. Assuming each game requires 1 second of computation, 100 million seconds of compute time equates to approximately 26 TPUs trained for 44 days each — 10% of the compute power used to train the hundreds of agents that achieved AlphaStar's superhuman performance. It is highly plausible that OINs could train 10 expert-level agents in games or skills as complex as StarCraft II with this amount of computational power and the rapid advancements in learning research over the past five years.

Now, envision a scenario with 1 million players, each playing 1,000 times. This represents a tenfold increase from the previous example, providing a level of compute power approximately equal to what was used to train AlphaStar's entire team. In this case, OINs could potentially surpass human performance in any task as difficult as StarCraft II, having onboarded only 1 million users to play engaging games. For perspective, ChatGPT — a chatbot — reportedly reached 100 million global users in less than two months. If OINs can achieve a critical mass of users, it has the potential to become one of the largest decentralized intelligence networks in the world.

But this is about more than games. Google's multi-billion-dollar investment in researching, building, and training intelligent agents extends far beyond creating expert-level StarCraft players. By developing AI agents that can excel in complex, real-time environments with imperfect information, open-ended action spaces, and diverse multi-agent interactions, the foundation is being laid for AI systems that can tackle a wide range of real-world challenges.

These agents have already demonstrated the ability to outperform expert human teams in specific tasks like StarCraft II, despite the humans having trained for years to reach their level of proficiency. Moreover, these intelligent agents can generate code and command user interfaces at human levels of excellence. As this technology continues to advance, its potential applications are vast and exciting. OINs is committed to being at the forefront of this development, making the technology openly available to our community and ensuring that its benefits are accessible to all.

Bold thinking and a willingness to challenge the status quo are essential for executing the visionary goals of OINs. While the path forward may be challenging, the potential benefits of decentralized, openly accessible AI agents are immeasurable. World-changing ideas often arise from deep, radical thought and require plans of action that may initially seem unorthodox or even outlandish. However, once the true potential is understood, it becomes difficult to imagine a future without these revolutionary concepts coming to be. At that point, the only remaining step is unwavering execution.

OINs is strategically positioned to capture a significant portion of the rapidly growing AI economy and bring it onchain. As global revenue from AI services continues to skyrocket, OINs stands to benefit substantially. The realization of this vision is not a matter of if, but when. While the journey may be complex and the vision will not materialize overnight, nothing truly transformative ever comes easily. With determination and commitment, the GAIAs community will make this future a reality.

The future of AI is in our hands; let's build it wisely, openly, and for the benefit of all.