Subvolts take Build private, user-owned AI with decentralized tech and verifiable trust. Sep 30, 2025 - Developers
- Learn about building decentralized AI systems with enhanced privacy and security using blockchain and confidential computing.
- Business
- Understand how decentralized AI can offer new models for data ownership and trust, potentially impacting enterprise AI strategies.
This interview features a key researcher discussing practical approaches to decentralized and private AI development.
The Decentralized Future of Private AI with Illia Polosukhin - #749
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Summary and analysis by Subvolts editorial, AI-assisted.
Illia Polosukhin, co-founder of Near AI and co-author of "Attention Is All You Need," discusses his vision for private, decentralized, user-owned AI. He explains how Near AI uses confidential computing and blockchain to protect data and model weights. The conversation covers fostering trust through open training, verifiable inference, and formal verification of AI agents.
This episode explores building AI that keeps your data private and gives you ownership. It uses special computer tricks and blockchain to make sure AI models are honest and work as intended, building trust for everyone.
This episode offers insight into building AI systems that prioritize user privacy and control, a growing concern as large labs develop increasingly powerful models. Polosukhin's work on decentralized AI and confidential computing directly addresses potential issues with data security and model integrity that frontier labs like Google Gemini and OpenAI are grappling with. It's for researchers, developers, and anyone interested in the ethical and technical underpinnings of future AI, particularly those exploring alternatives to centralized AI development.
- HostSam Charrington
- GuestIllia Polosukhinco-founder, Near AI
- Guest: Illia Polosukhin
- Title: The Decentralized Future of Private AI with Illia Polosukhin - #749
- Show: The TWIML AI Podcast
- Length: 65 minutes
- Guest's Background: Co-author of "Attention Is All You Need" paper, co-founder of Near AI
- Near AI's Approach: Leverages confidential computing, secure enclaves, and blockchain
In this episode, Illia Polosukhin, a co-author of the seminal "Attention Is All You Need" paper and co-founder of Near AI, joins us to discuss his vision for building private, decentralized, and user-owned AI. Illia shares his unique journey from developing the Transformer architecture at Google to building the NEAR Protocol blockchain to solve global payment challenges, and now applying those decentralized principles back to AI. We explore how Near AI is creating a decentralized cloud that leverages confidential computing, secure enclaves, and the blockchain to protect both user data and proprietary model weights. Illia also shares his three-part approach to fostering trust: open model training to eliminate hidden biases and "sleeper agents," verifiability of inference to ensure the model runs as intended, and formal verification at the invocation layer to enforce composable guarantees on AI agent actions. Finally, Illia shares his perspective on the future of open research, the role of tokenized incentive models, and the need for formal verification in building compliance and user trust.
The complete show notes for this episode can be found at https://twimlai.com/go/749.
- confidential computing
- Illia Polosukhin
- Using computers that keep data secret even while it's being processed.
- secure enclaves
- Illia Polosukhin
- Protected areas within a computer's processor that keep data safe from the rest of the system.
- formal verification
- Illia Polosukhin
- Using mathematical methods to prove that an AI system will always behave as expected.
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Questions people ask
- What is Near AI building?
- Near AI is creating a decentralized cloud that uses confidential computing, secure enclaves, and blockchain to protect user data and proprietary model weights.
- How does Near AI foster trust in AI agents?
- They use open model training, verifiable inference to ensure models run as intended, and formal verification to enforce guarantees on AI agent actions.
Page generated Oct 19, 2026. Summaries are Subvolts' own; the audio, artwork and notes belong to Sam Charrington.