We Study Billionaires - The Investor’s Podcast Network TECH006: Open-Source AI That Protects Your Privacy w/ Mark Suman (Tech Podcast)
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Oct 29, 2025 
Mark Suman, co-founder of Maple AI, discusses his journey from Apple to building privacy-first AI. He highlights the importance of verifiable AI and the threats of centralized models capturing user thought processes. Mark elaborates on how Maple AI uses secure enclaves and attestation to maintain user privacy while ensuring efficiency. He shares insights on the future of private AI, the potential for decentralized systems, and the challenges ahead, all while emphasizing that inference speed is the new battleground in the AI landscape.
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Verifiable Is The Right Privacy Frame
- Verifiable AI means you can inspect and prove what code and models handle your data.
- Use open source or trusted execution environments to ensure transparency and trust.
Thoughts Given To AI May Become Irretrievable
- Handing your thought process to proprietary AI risks permanent capture and reuse of your ideas.
- That captured thinking could be trained on or manipulated without your consent.
Verify Before You Send Sensitive Data
- Prefer models you can verify: open-source weights or run in attested secure enclaves.
- Demand mathematical attestation that the cloud runs the published code before sending sensitive data.