Building AI in the Open: A Conversation with Dean Wampler

March 17, 2025

In the 4th Episode of Season 1 of the Attention Needed podcast, we explore the future of AI innovation with Dean Wampler, IBM’s Chief Technical Representative to the AI Alliance — a collaboration led by IBM, Meta, and other key organizations to promote open, safe, and responsible AI development. This conversation dives into the opportunities and challenges of building AI in the open.

Key Topics We Cover:

🔍 What is "open" AI? The role of collaboration in fostering trust and breaking barriers.

🚀 Who drives it? How startups, enterprises, and institutions shape an open ecosystem.

⚠️ Key challenges: Ensuring safety, trust, and risk management in generative AI.

With deep experience in AI research and enterprise solutions, Dean shares insights on how AI Alliance is shaping AI innovation, ensuring both openness and security.

🎧 Listen to the full episode now!

📖 Appendix: Key Questions from the Episode

- What does “open” mean in the context of AI innovation, and why is it important?

- What does the ultimate state of open AI innovation look like?

- What is the AI Alliance, and what role does it play in enabling open AI development?

- The AI Alliance focuses on knowledge sharing, technical initiatives, and increasing access. Why were these pillars chosen, and what barriers stand in the way of truly open AI innovation?

- What roles do startups play in an open AI ecosystem?

- What roles do larger and more mature incumbents play in this ecosystem?

- How can we align incentives across such a diverse range of players to ensure effective collaboration?

- What are the biggest technical challenges in open AI development, especially with Generative AI?

- Which of these challenges are most pressing from a safety and trust perspective?

- What strategies, tools, or resources can help us responsibly address these issues?

- How is IBM supporting its enterprise clients in navigating the complexities of open, trustworthy AI?

- What excites you the most—and what concerns you the most—about the future of Generative AI?