Illia Polosukhin: Traditional AI services expose sensitive data, crypto simplifies global payments, and AI will redefine computing interfaces | Bankless

AI's transformation of computing interfaces may soon render traditional operating systems obsolete, with blockchain ensuring secure integration.

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Add us on Google by Editorial Team Apr. 10, 2026

Key Takeaways

• Using traditional AI services can risk exposing sensitive information.
• Crypto offers a streamlined solution for global payments, bypassing traditional banking hurdles.
• The anticipated scaling of AI models faced delays due to insufficient computing power.
• AI is predicted to transform computing interfaces, potentially replacing traditional operating systems.
• Current operating system architectures are not fully compatible with AI, requiring infrastructure upgrades.
• AI is expected to become the main interface for consumer technology, replacing traditional systems.
• Blockchain technology provides a foundational trust layer for AI infrastructure.
• Decentralized blockchain systems offer a method for system upgrades, contrasting centralized control.
• The increasing importance of money is linked to AI’s acceleration of resource demands.
• AI will automate the composition of software and services, enhancing user interactions.
• Blockchain enables secure identity management and protocol upgrades in AI systems.
• The evolution of AI technology will integrate it into consumer devices more seamlessly.
• AI’s role in software development may lead to a shift in how applications are created and managed.
• The relationship between blockchain and AI is critical for future technological advancements.
• AI’s integration into everyday technology will simplify user experiences and interactions.

Guest intro

Illia Polosukhin is the Co-Founder and CEO of the NEAR Foundation. He co-authored the landmark 2017 paper “Attention Is All You Need,” which introduced the Transformer architecture foundational to modern generative AI. His work bridges AI and blockchain to enable scalable, user-friendly decentralized applications.

Risks of using traditional AI services

• Using traditional AI services can expose sensitive information, including access keys and tokens.

• One thing that people don’t realize when they use entropic openai or even worse you use something else for inference opencloud actually sends all your secrets to those services as well.

  — Illia Polosukhin

• Understanding the risks associated with AI services is crucial for data security.
• The need for secure alternatives to traditional AI services is emphasized.
• AI services pose a critical security concern due to potential data exposure.
• The implications for data security are significant when using AI for inference.
• Awareness of these risks can drive the development of more secure AI solutions.
• The conversation highlights the importance of privacy and security in AI applications.

Crypto’s role in global payments

• Crypto provides a natural solution for global payments without traditional banking complexities.

• Crypto was a pretty natural actually like solution we needed for our own problems like hey how do we actually pay people globally without like setting up ton of entities.

  — Illia Polosukhin

• The practical utility of crypto in solving global payment issues is evident.
• Cryptocurrency offers advantages for transactions in a global context.
• The challenges in global payments are addressed by the decentralized nature of crypto.
• Using crypto simplifies the process of paying people worldwide.
• The conversation underscores the importance of crypto in modern financial systems.
• Crypto’s role in global payments highlights its potential for broader financial inclusion.

Delays in AI model scaling

• The scaling of AI models was anticipated to happen sooner than it did due to computing power limitations.

• We thought we were on like kind of the curve we’re seeing right now… we were wrong… the main part was the compute wasn’t there.

  — Illia Polosukhin

• Technological limitations impacted AI development timelines in the late 2010s.
• The misjudgment in AI advancement timelines is significant for understanding the field’s evolution.
• The conversation sheds light on the challenges faced by AI researchers.
• Computing power is a critical factor in the pace of AI advancements.
• The insights reveal the complexities involved in scaling AI technologies.
• The discussion emphasizes the need for continued innovation in AI infrastructure.

AI’s impact on computing interfaces

• AI will fundamentally change how we interface with computing, potentially replacing traditional operating systems.

• My main thesis is ai will be the way we interface computing… computers will write all the code which means the operating system and apps are gonna be just replaced by this ai that’s yours that is just writing all the code.

  — Illia Polosukhin

• The implications of AI advancements on software development are profound.
• AI’s role in computing may lead to a shift in infrastructure and user interaction.
• The prediction highlights a transformative future for technology driven by AI.
• The conversation explores the potential for AI to automate code writing and application development.
• The insights suggest a future where AI personalizes and enhances computing experiences.
• The discussion underscores AI’s potential to redefine traditional computing paradigms.

Challenges of integrating AI into existing systems

• The current service architecture of operating systems is incompatible with AI, necessitating upgrades.

• A lot of it breaks with ai and so you kinda need to fix it and block changes have all the pieces figured out or at least has tools to figure out how to solve that.

  — Illia Polosukhin

• Existing operating systems face limitations in integrating AI technologies.
• The need for innovation in infrastructure is highlighted by AI’s technical challenges.
• The conversation addresses the incompatibility of current systems with AI advancements.
• The insights emphasize the importance of adapting infrastructure to support AI.
• The discussion explores how blockchain can aid in overcoming these challenges.
• The future of technology requires systems that can accommodate AI’s capabilities.

AI’s role in consumer technology

• AI will eventually serve as the primary interface for consumer technology, replacing traditional systems.

• I think it will start small… where the final will be like your phone just comes in with AI right and like it boots into the AI operating system.

  — Illia Polosukhin

• The evolution of AI technology will lead to its seamless integration into consumer devices.
• AI’s transformative role in consumer tech is emphasized in the conversation.
• The insights predict a future where AI simplifies and enhances user interactions.
• The discussion highlights the potential for AI to become the default interface for devices.
• The conversation explores how AI will streamline consumer technology experiences.
• The future of consumer tech is likely to be driven by AI’s capabilities and innovations.

Blockchain’s foundational role in AI infrastructure

• Blockchain serves as a root of trust for AI infrastructure, enabling secure identity management and protocol upgrades.

• Blockchain is really that root of trust right… you can have upgradability which is kind of governed by the whole protocol.

  — Illia Polosukhin

• The relationship between blockchain and AI is critical for technological advancements.
• Blockchain provides a secure foundation for AI systems, emphasizing trust and governance.
• The conversation highlights the importance of blockchain in the broader tech ecosystem.
• The insights explore how blockchain can enhance the capabilities of AI agents.
• The discussion underscores the role of blockchain in ensuring secure and private AI interactions.
• The future of AI infrastructure is likely to be supported by blockchain technology.

Decentralized upgrades through blockchain

• Blockchain provides a decentralized method for upgrading systems, contrasting with centralized control.

• What blockchain allows us to actually have this kind of a broader agreement to upgrade to something… we’re fixing that problem at the core like I mean we’re talking about new internet here.

  — Illia Polosukhin

• The limitations of centralized systems are addressed by blockchain’s decentralized governance.
• Blockchain technology offers a solution for trust and control issues in system upgrades.
• The conversation explores the potential for blockchain to transform internet infrastructure.
• The insights highlight the benefits of decentralized systems for technological innovation.
• The discussion emphasizes the importance of blockchain in enabling secure upgrades.
• The future of technology may rely on decentralized methods for system improvements.

Economic implications of AI advancements

• Money is becoming increasingly important as AI accelerates the demand for resources.

• Money is extremely important component right at the end we have limited amount of resources and unlimited desire and ai is just gonna accelerate that.

  — Illia Polosukhin

• The relationship between AI advancements and economic resource allocation is explored.
• The conversation highlights the critical role of money in a future shaped by AI.
• The insights emphasize the need for a marketplace for resources in an AI-driven world.
• The discussion explores how AI’s demand for resources impacts economic systems.
• The future of economics may be influenced by AI’s acceleration of resource needs.
• The conversation underscores the importance of financial systems in supporting AI advancements.

Disclosure: This article was edited by Editorial Team. For more information on how we create and review content, see our Editorial Policy.