What if we could trust AI results the way we trust cryptographic signatures? That’s the radical promise behind Gensyn’s work—building verifiable, decentralized AI infrastructure from the ground up.

We kick off Season 2 of The People’s AI with Ben Fielding and Harry Grieve, the co-founders of Gensyn. We hear how their origin story began in a London warehouse—right before COVID lockdown—and how their mission has evolved from federated learning for tier-one banks to a sweeping new protocol for decentralized machine learning computation.

In this episode, we dig deep into:

• Why decentralized AI is technically hard to pull off — and why Gensyn is focused on solving it
• The limitations of vertical scaling, and how “horizontal scaling” might change everything
• What determinism really means in ML, and why it’s essential for verification and trust
• The nuance behind hallucinations in GenAI — and why they’re not always a bug
• How agentic systems and a “machine economy” might transform our future interactions

We also explore how their work connects to AI arbitration, smart contracts, and the growing demand for trustless execution across compute environments.

This is one of those conversations where infrastructure, philosophy, and future vision converge. We’re excited to share it with you.

About Gensyn, presenting partner of The People's AI Season 2:

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

Why can ChatGPT write your emails, but robots still can’t fold your laundry? The answer isn’t hardware—it’s data.

On today's episode of THE PEOPLE'S AI, presented by Vana, we speak with Bayley Wang, co-founder of PrismaX, a startup building the “base layer” for real-world robotics.

PrismaX connects user-generated video data—like clips of people folding sheets or restocking shelves—with robotics companies that are desperate for this kind of input. Think of it as the data DAO for training robots.

We explore the real reasons robotics has lagged behind generative AI, why teleoperation is suddenly a $50/hour job, and how decentralization could be the missing ingredient in bringing useful robots into everyday life.

Topics include:

– Why software, not hardware, is holding robotics back (0:45)

– The failure of rule-based systems in real-world AI (3:56)

– How videos of everyday tasks are used to train robots (19:15)

– Incentive models: from passive video uploads to paid robot control (17:18–27:06)

– Web3 infrastructure: tokens, DAOs, and decentralized data marketplaces (28:52)

– The robot-in-every-home future (36:23)

PrismaX recently came out of stealth at the A16Z Demo Day, and in this conversation, we unpack what that launch means and what’s next for robotics powered by real-world data and open protocols.

Want to get involved? Learn more at PrismaX.ai

And a big thanks to our partner, Vana, whose mission is to enable user-owned AI through user-owned data -- starting with an ecosystem of Data DAOs and decentralized data marketplaces.

About Vana:

https://linktr.ee/vanahq

Vana on Twitter/X:

https://x.com/vana

Vana ecosystem: vana.com

Subscribe to The People's AI on YouTube:

https://www.youtube.com/channel/UCnLiYlJulQIcmvCjnVRYotw

Jeff Wilser on Twitter/X:

https://x.com/jeffwilser

What if your personal data wasn’t being harvested — but instead valued, tokenized, and returned to you?

That’s the radical shift proposed by Vana, a platform building decentralized data marketplaces that aim to give users economic power over their own data.

In this episode of "The People's AI," we speak with Art Abal, Vana’s co-founder, to unpack how today’s data economy works behind the scenes — and why it’s fundamentally broken. In this episode, we explore how data is currently bought and sold by tech giants, what it would take to redesign that infrastructure around user ownership, and how Vana’s VRC-20 token could be the first step in treating data as a liquid, tradable asset.

We go deep on:

• Why centralized data brokers still dominate AI training pipelines
• How “data market makers” could unlock liquidity in user-owned datasets
• The mechanics and philosophy behind the VRC-20 token
• Real-world case studies, like data DAOs for Reddit and electric vehicle telemetry
• The path toward Universal Data Income (UDI) — and how it might reshape AI’s future

Whether you’re a builder, investor, or simply data-curious, this episode offers a look into a future where AI and Web3 integration doesn’t just protect your privacy — it pays you back.

Please subscribe, share, and join the conversation.

About Vana:

Vana's mission is to enable user-owned AI through user-owned data. Vana recently announced a collaboration with Flower Labs to build the world’s first user-owned foundation model.

About Vana's collaboration with Flower:

https://www.vana.org/posts/vana-flower-labs-partnership

More on Vana:

https://linktr.ee/vanahq

Vana on Twitter/X:

https://x.com/vana

Subscribe to The People's AI on YouTube:

https://www.youtube.com/channel/UCnLiYlJulQIcmvCjnVRYotw

Jeff Wilser on Twitter/X:

https://x.com/jeffwilser