Ben Fielding: Gensyn’s Polar Opposite Architecture vs AI Data Centers, Fueling an AI-Native Internet, Open vs. Closed Source AI and RL Swarm

MAR 31, 2025

Disclosures: This podcast is strictly informational and educational and is not investment advice or

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Join Tom Shaughnessy as he hosts Ben Fielding, co-founder of Gensyn Network, for an in-depth exploration of decentralized AI infrastructure and the future of machine learning. From Gensyn’s evolution as a low-level infrastructure platform to its revolutionary approach with RL Swarm, the conversation covers transformative developments in distributed computing, model training, and the philosophical implications of AI development.

🎯 Key Highlights

▸ Gensyn’s approach to agnostic, low-level AI infrastructure designed to transcend trends

▸ Transition from vertical to horizontal scaling in AI computing systems

▸ The limitations of centralized hyperscaler data centers and how Gensyn provides an alternative

▸ Deep dive into RL Swarm: enabling peer-to-peer reinforcement learning at scale

▸ The philosophical importance of open, personalized AI models vs centralized systems

▸ Exploration of AI’s future: parameter space, model communication, and verification

▸ Vision for how decentralized AI can democratize machine learning technology

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🧠 Follow the Alpha

▸ Tom’s Twitter: @shaughnessy119

▸ Ben’s Twitter: @fenbielding

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🌐 Portal: https://delphidigital.io/

🐦 Twitter: https://twitter.com/delphi_digital

💼 LinkedIn: https://www.linkedin.com/company/delphi-digital

🎧 Listen on

Spotify: https://open.spotify.com/show/62PR1RigLG2YN5Pelq6UY9?si=18ac7ccf36ab4753

Apple Podcasts: https://podcasts.apple.com/us/podcast/the-delphi-podcast/id1438148082

Youtube: https://www.youtube.com/channel/UC9Yy99ZlQIX9-PdG_xHj43Q

Timestamps

00:00 – Introduction to Gensyn Network

01:29 – Building AI-Agnostic Infrastructure

05:00 – Vertical vs Horizontal Scaling in AI

10:50 – Limitations of Centralized Data Centers

17:42 – Gensyn’s Core Components and Vision

20:45 – The Internet as Parameter Space

28:00 – Execution, Communication, and Verification

34:42 – RL Swarm: Decentralized Reinforcement Learning

41:30 – Model Communication and Improvement

48:46 – Testnet and Persistent Identity

53:56 – Preserving Model Personalization

59:42 – Open vs Closed Source Models

01:05:30 – The Future of AI Development

01:11:20 – Value Capture in AI and Final Thoughts

Disclaimer

This podcast is strictly informational and educational and is not investment advice or a solicitation to buy or sell any tokens or securities or to make any financial decisions. Do not trade or invest in any project, tokens, or securities based upon this podcast episode. The host and members at Delphi Ventures may personally own tokens or art that are mentioned on the podcast. Our current show features paid sponsorships which may be featured at the start, middle, and/or the end of the episode. These sponsorships are for informational purposes only and are not a solicitation to use any product, service or token.

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