The AI Frontier: From Open Weights to Open Research

Why it matters

In this episode, Eiso Kant, co-founder of Poolside AI, discusses the evolution from open weights to open research in AI. Drawing on his deep experience in developer tools and AI infrastructure, he unpacks the tensions between open-source models, research transparency, and industry deployment, offering a forward-looking perspective on the AI research ecosystem—valuable for anyone following open-source AI and commercial innovation.

Key takeaways

• Open weights are not the same as open research; true openness requires transparency in data, methods, and process.
• Engineering capability in AI infrastructure is the critical bridge between research and production.
• The open-source model ecosystem will accelerate AI democratization, but safety and accountability must be built in.
• The future competitiveness of AI research depends on balancing open collaboration and commercial sustainability.