Decentralizing AI with Minima—Hugo Feiler on Privacy, Security, and the Future of Peer-to-Peer Intelligence

The rapid evolution of artificial intelligence (AI) presents both opportunities and risks, with centralization emerging as a major concern. Many argue that large language models (LLMs) are controlled by a few powerful entities, raising concerns about data privacy, censorship, manipulation, and monopolization of intelligence.

Hugo Feiler, CEO and co-founder of Minima—described as “the most decentralized and resilient blockchain network on the planet”—highlights the issue: “These systems require massive amounts of data, much of which is collected and processed without users having control over their own information.”

Minima applies blockchain’s decentralization principles to AI governance, offering a censorship-resistant Layer 1 network where data remains locally stored. Feiler explains, “AI systems deployed on Minima benefit from enhanced security against manipulation and verified trust in data integrity on the network.”

In this interview with Lorena Nessi, Feiler shares his views on decentralization, AI governance, and Minima’s approach to security, transparency, and industry applications.

Decentralization for Blockchain and AI

Hugo Feiler states that Minima recognized that “the same principles of decentralization that empower blockchain networks can be applied to the core issues in AI governance.”

He emphasizes that Minima’s approach ensures that AI remains a tool for the many, not a commodity controlled by a few. Here’s what makes it different:

• True decentralization: Unlike blockchains that rely on miners or validators, Minima ensures every participant runs a full node, preventing centralized control.
• Data privacy and sovereignty: AI computations happen without users surrendering their data, ensuring control over personal information.
• Censorship resistance: Minima’s peer-to-peer framework ensures AI services operate without interference from corporations or regulators. Feiler states that users can contribute human-verified data without divulging their personal information.
• Efficiency and scalability: Minima’s lightweight protocol enables AI processing on mobile and edge devices, reducing reliance on centralized computing.
• Trust and transparency: AI models on Minima’s network remain verifiable and auditable, avoiding opaque, black-box decision-making.

Feiler underscores the importance of transparency, stating, “AI decisions must be explainable and verifiable.” He highlights that trust in AI cannot be taken for granted, allowing users to understand and validate how decisions are made. Minima’s decentralized structure ensures that AI systems remain accountable, fostering confidence in their outputs.

The ‘Ultra-Compact’ Design with Creator’s Incentives

A very strong feature of Minima is that it ensures fair rewards in AI by removing centralized control over data, algorithms, or profits.

Unlike traditional blockchains requiring powerful hardware and large storage, Minima operates efficiently on smartphones, IoT devices, and embedded systems. Feiler highlights, “Rather than every node storing the entire blockchain ledger, Minima ensures each node stores only the data relevant to itself, with proofs that all other nodes can verify.”

By eliminating the need for miners or validators, Minima removes reliance on incentives, allowing billions of devices to connect without compromising decentralization.

He explains that Minima “Removes the need for intermediaries by using smart contracts and tokenized incentives, allowing AI creators, data providers, and users to set clear rules for ownership, usage, and revenue sharing.”

This approach guarantees that every contribution is transparently tracked and fairly compensated, creating a more inclusive and open AI economy.

Accessibility Without Barriers

Minima makes AI more accessible based on the fact that users do not need expensive hardware or centralized platforms to participate. As a result, developers can create lightweight applications that work efficiently on any device.

Feiler provides an example: “A peer-to-peer AI training model on Minima enables users to contribute their device’s processing power to train AI models collaboratively. Smart contracts automate fair reward distribution, eliminating intermediaries and reducing reliance on centralized cloud providers.”

He continues, “By enabling AI training to take place directly on users’ devices, Minima fosters a more inclusive, community-driven model where anyone can participate in AI development while maintaining full control over their data and contributions.”

Quantum-Secure Cryptography

Quantum computing threatens traditional encryption, but Minima uses quantum-resistant cryptographic techniques. Feiler provided some details:

• SHA3-256: “Since quantum computers struggle with breaking strong hash functions due to Grover’s algorithm only providing a quadratic speedup, SHA3-256 remains highly secure,” Feiler states.
• Winternitz One-Time Signatures (WOTS): Used instead of ECDSA, with WOTS “signatures are used only once, eliminating the risk of key reuse and significantly improving resistance against quantum attacks.”
• Merkle tree structures: These allow efficient transaction verification, reducing the risk of compromise.

AI in Healthcare, Finance, and Intellectual Property

Minima strengthens AI security in healthcare and finance while protecting creators’ work.

Feiler explains, “Federated learning can be implemented across multiple hospitals or research institutions without sharing raw patient data, ensuring privacy.” AI models train directly on patient devices, reducing data exposure. In finance, Minima’s blockchain creates tamper-proof audit trails for “loan approvals, automated trading, and fraud prevention,” ensuring trust in AI-driven decisions.

AI creators also keep control of their work. Feiler states, “AI developers can register their models, datasets, or innovations on Minima’s blockchain, creating an immutable record of authorship that proves originality and protects against theft or plagiarism.” 

The system secures AI-generated outputs, ensuring “transparency and verifiability, preventing unauthorized modifications or deepfake manipulation.” Feiler adds that this approach enables fair compensation through micropayments, fostering an ecosystem of collaboration rather than competition.

Collaboration and Industry Partnerships

Minima actively collaborates with blockchain and AI communities, working with organizations like:

• Influx technology & McLaren GT4 supercar: Minima secured real-time race data for McLaren’s DePIN Data Logger, ensuring accurate telemetry tracking. Feiler describes, “Data points on over twenty parameters, including ignition timing, braking, oil pressure, engine temperature, and gear switching, were collected and stored immutably on Minima’s blockchain.”
• Arm’s flexible access program: Minima is developing the Minima Chip, embedding blockchain services directly into IoT microchips. Feiler states, “By integrating blockchain capabilities into hardware, we enable secure, autonomous operations in industries ranging from automotive and healthcare to manufacturing and smart cities.”

Future Milestones

Minima aims to transform AI and blockchain by enabling full blockchain nodes on edge devices that interact purely peer-to-peer. Feiler sees this as a foundation for Agentic AI, where AI can operate independently while respecting data security, censorship resistance, and self-sovereign economic control.

As Feiler concludes, “The combination of enhanced data security, censorship resistance, and the ability for self-sovereign economic control will pave the way for the development of Agentic AI interacting and thriving alongside humans.”