
TECH006: Open-Source AI That Protects Your Privacy w/ Mark Suman (Tech Podcast)
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Mark Suman, co-founder of Maple AI and OpenSecret, shares his insights on how to build cutting-edge AI without sacrificing user privacy. 
From secure enclaves and attestation to real-world use cases in law and finance, Mark outlines the technical and ethical foundations of private AI, and why efficient inference, not just open models, is the next big frontier.
IN THIS EPISODE YOU’LL LEARN:
00:00:00 - Intro
00:01:57 - How Mark’s Time at Apple Shaped His Vision for Secure, User-First AI  
00:06:06 - Why Verifiable AI Matters for Protecting User Data  
00:07:38 - The Privacy Threats of Centralized AI Models  
00:15:26 - What Maple AI Does That Other AI Tools Don’t—End-to-End Encrypted, Verifiable Privacy  
00:17:30 - The Threat Models Maple Addresses and How Enclaves + Attestation Work  
00:19:51 - Why Inference Speed and Efficiency—Not Open Weights—Are the New AI Battleground  
00:24:05 - Where Decentralized AI Fits Into Today’s Landscape  
00:25:12 - A Step-by-Step Guide to Getting Started with Maple  
00:29:13 - How Users Change Behavior When They Trust the AI System  
00:32:42 - The Risks and Critiques of TEEs—and How Maple Answers Them  
00:37:35 - Which Professions Benefit Most from Private AI  
00:45:27 - Mark’s Vision for Verifiable, Private AI Over the Next Decade  
Disclaimer: Slight discrepancies in the timestamps may occur due to podcast platform differences.
BOOKS AND RESOURCES
  X Account: Mark Suman.
  Website: Maple AI.
  Related books mentioned in the podcast.
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