

Jeffrey Quesnelle
Co-founder and CEO of Nous Research, an open-source/decentralized AI research organization focused on building permissionless training and inference infrastructure and frontier open-source models.
Top 3 podcasts with Jeffrey Quesnelle
Ranked by the Snipd community

15 snips
Jan 8, 2026 • 59min
URGENT: AI Is Inevitable. But Can It Be Better?
Jeffrey Quesnelle, co-founder and CEO of Nous Research, dives into the urgent need for decentralized, open-source AI. He fears that allowing a few powerful companies to control AI could stifle innovation. The conversation highlights how his organization utilizes crypto for capital formation and coordinates training across multiple data centers. They also delve into the philosophical implications of open-source, comparing it to the historical impact of the printing press. Jeffrey shares insights on AI research trends and the importance of retaining human context in an increasingly intelligent world.

5 snips
Mar 18, 2025 • 2h 6min
#51 – Jeffrey Quesnelle on Nous Research, large language models, and the human mind
In this engaging conversation, Jeffrey Quesnelle, cofounder of Nous Research and an expert on large language models, shares insights into the intersection of AI and human cognition. He discusses the historical evolution of neural networks and how they parallel human reasoning. The dialogue explores the philosophical implications of AI consciousness and the importance of decentralized systems in technology. Quesnelle also emphasizes the balance between computational advancements and human creativity, revealing how meditation and artistic expression relate to AI's development.

Sep 27, 2024 • 1h 13min
DisTrO and the Quest for Community-Trained AI Models
Bowen Peng and Jeffrey Quesnelle from Nous Research discuss their mission to revive open-source AI, emphasizing the DisTrO project, which enables rapid training of AI models over the internet. They explore the challenges faced by independent builders in AI and the critical role of community collaboration. The conversation dives into impressive innovations like the Hermes models, designed for neutral interactions and enhanced with synthetic data. They reflect on the tension between decentralization and centralization in AI protocols and advocate for community-driven solutions.


