The People's AI: The Decentralized AI Podcast
Who will own the future of AI? The giants of Big Tech? Maybe. But what if the people could own AI, not the Big Tech oligarchs? This is the promise of Decentralized AI. And this is the podcast for in-depth conversations on topics like decentralized data markets, on-chain AI agents, decentralized AI compute (DePIN), AI DAOs, and crypto + AI. From host Jeff Wilser, veteran tech journalist (from WIRED to TIME to CoinDesk), host of the "AI-Curious" podcast, and lead producer of Consensus' "AI Summit." Season 2, presented by Gensyn.
The People's AI: The Decentralized AI Podcast
Can AI Be Creative? With AI Artists Mario Klingemann & Shavonne Wong
What does it mean for AI to be creative? Can a machine surprise us—or even move us?
This week, we explore the frontier of AI-generated art, emotional AI, and decentralized creativity through two very different lenses. In this episode of The People’s AI, presented by Gensyn, we speak with Mario Klingemann, creator of the autonomous artist Botto, and Shavonne Wong, the mind behind the interactive AI companion Eva.
We look at how Botto uses generative AI to create tens of thousands of artworks per week, then lets a DAO community vote on which get minted as NFTs—some of which have sold at Sotheby’s. Shavonne walks us through Eva, a “listening machine” designed to be emotionally available, raising questions about grief tech, AI intimacy, and what it means to be heard.
Topics include:
- (03:48) How Botto works: generation, voting, and DAO-based curation
- (09:15) The role of taste modeling and semantic drift in AI art
- (16:02) AI companions, grief tech, and emotional projection
- (24:30) Will AI cause cultural atrophy—or unlock new creative paradigms?
- (28:44) The tension between AI as tool vs. AI as collaborator
We close with a reflection on how human meaning gets projected onto machines—and what that might mean for the future of art, identity, and emotional connection in an AI-shaped world.
About Gensyn:
Gensyn is a protocol for machine learning computation. It provides a standardised way to execute machine learning tasks over any device in the world. This aggregates the world's computing supply into a single network, which can support AI systems at far greater scale than is possible today. It is fully open source and permissionless, meaning anyone can contribute to the network or use it.