What happens when AI runs out of energy? As models grow exponentially, the world’s compute and energy needs are skyrocketing—and our current infrastructure may not keep up.

On today's episode of THE PEOPLE'S AI, presented by Gensyn, we speak with Greg Osuri, founder and CEO of Akash Network, to dive into the future of decentralized AI and why distributed compute could be the key to solving AI’s looming energy crisis. Greg explains the real-world constraints facing AI data centers, why GPU shortages are only the beginning, and how asynchronous AI training and swarm learning could fundamentally change how models are trained.

We explore:

• [2:39] The core problem decentralized compute is solving
• [7:17] AI’s insatiable energy demand and the role of hyperscalers
• [9:33] Why energy supply is the real AI bottleneck
• [12:29] Asynchronous and distributed AI training explained
• [20:44] How mainstream AI is beginning to embrace decentralized models
• [24:57] Moving AI compute to the power source: solar, wind, and home devices
• [41:38] The White House AI plan and the future of open-source AI

This episode connects AI infrastructure, energy sustainability, and decentralization, offering a first-principles look at how we can build a more resilient, sovereign future for machine intelligence.

If you’re curious about AI compute, open-source AI, and the intersection of energy and technology, this conversation will expand the way you think about the future of AI.

Akash Network:

https://akash.network/

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.

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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.

Botto

Meet Eva Here

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.

Gensyn - LinkedIn - Twitter - Discord

How will AI Agents transform the world? And why do they need to be Decentralized?

This episode explores the frontier of AI agents—their power, their risks, and their role in shaping our future, on THE PEOPLE'S AI, presented by Gensyn. Host Jeff Wilser talks with Shaw Walters (founder of Eliza Labs) and Harry Grieve (co-founder of Gensyn) about what happens when AI agents become autonomous, self-coding, and capable of running their own workflows or even companies.

Shaw explains how Eliza Labs is building an operating system for AI agents that can write plugins, make decisions, and operate independently. Harry walks through how Gensyn is creating a decentralized infrastructure for machine learning verification, allowing trust to be cryptographically enforced.

Together, they discuss:

• Why “agent swarms” may soon outnumber human teams
• How cryptographic trust can secure AI systems
• Whether AI agents will replace white-collar jobs
• What a decentralized, AI-native internet might look like

We also dig into philosophical questions: Who governs these agents? What does it mean to build trust in autonomous systems? And what happens to society when the agents are working… for themselves?

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.

Gensyn - LinkedIn - Twitter - Discord

Eliza Labs:

https://www.elizaos.ai/