It all began with a noisy desk in a modest wooden cubicle at Northumbria University, where a young AI researcher named Ben Fielding embarked on his PhD journey in 2015. Beneath that desk sat a large machine filled with early GPUs that not only fueled Fielding’s ambitions but also tested the patience of his lab-mates. The cacophony of this resource-intensive machine was a constant reminder of the challenges that come with advanced AI research.
Fielding’s early ideas were untraditional; he envisioned a future where “swarms” of AI—collections of diverse models—could communicate and learn from one another, thus enhancing their collective intelligence. However, the limitations of his noisy machine imposed a significant constraint. While Google was racing ahead with thousands of GPUs in sprawling data centers, Fielding was acutely aware that he was at a disadvantage. “The methods they were using weren’t radical—I knew them well. It was simply a matter of having the right resources to implement them,” he recalls.
Fast forward to today, and Ben Fielding is the CEO of Gensyn, a company he co-founded in 2020 to tackle the very constraints he had once faced. As a speaker at Consensus 2025 in Toronto, Fielding is now at the forefront of shaping the future of decentralized AI, a concept he championed long before it became a trend.
The crux of Fielding’s vision stems from a pivotal realization: compute limitations would persist as AI endeavors became mainstream. Thus, the answer lay in decentralization. Gensyn’s initial goal focused on developing decentralized computational frameworks, but the architecture being built is much broader—aiming to create a comprehensive network for machine intelligence.
As Gensyn rolls out its groundbreaking tools, including the recently launched “RL Swarms” protocol, it is clear that the futures of blockchain and AI are intertwined. This initiative builds upon Fielding’s PhD work and epitomizes the capacity for decentralized networks to enhance the capability of AI systems. Using blockchain technology to facilitate this process marks a significant development in the current AI landscape.
Leading up to the AI Summit at Consensus 2025, Fielding elaborates on the RL Swarms protocol, revealing how it enables AI models to engage in a peer-to-peer network for reinforcement learning. This collaborative training paradigm fosters an environment where numerous models can critique and build upon one another’s outputs to optimize learning outcomes.
Fielding explains, “It’s remarkable to consider that a model can join a swarm for a brief period, absorb collective knowledge, and subsequently enhance its performance, while also contributing to the improvement of others within the group. That’s the essence of RL Swarm—it’s about collective advancement through interaction.”
So how does blockchain fit into this ecosystem? Fielding describes it as a foundational layer that secures model interactions, facilitating trust and communication among diverse devices executing the models’ tasks. With blockchain integration, Gensyn is equipped to establish persistent identities and enable a consensus mechanism, which is crucial for the integrity of decentralized AI operations.
As Gensyn moves towards a beta version of its infrastructure, Fielding notes that the forthcoming transitions will usher in a wave of capabilities, including programmatic trust and decentralized payments. The roadmap outlined by Gensyn aims to democratize AI development, ensuring every innovator—regardless of size or resources—can contribute to machine learning advancements.
In the coming years, Gensyn aims to dismantle the barriers imposed by centralized AI firms, creating an environment where machine learning resources are accessible to all. Fielding’s vision is clear: to open-source and make resources available for anyone willing to engage with AI technology, transforming the landscape of machine learning in the process.
The journey from a noisy desk to the cutting-edge of decentralized AI has not only shaped Fielding’s career but also signals a new era for the entire AI industry—one where collaboration, openness, and transparency dictate the future of technological innovation.
