By the Deep Funding Marketing Team
The Part of the Deep Funding Townhall Spotlight Series

A Glimpse Into the Future of Machine Reasoning

The Deep Funding Townhall isn’t just another community call; it’s where the next generation of decentralized AI takes shape.

In this session, we heard from Nils, a researcher supported by the Deep Funding program, who introduced one of the most intriguing projects in our ecosystem: the Ternary Sheaf Network (TSN).

While Nils modestly called his presentation “improvised,”

What followed captured the attention of everyone in the room. A bold rethinking of how machines can learn, reason, and verify information.

What Problem Is TSN Trying to Solve?

AI models like GPT have changed how we interact with technology, but they have a deep limitation: they’re great at guessing patterns, not understanding structure. They can write paragraphs, generate code, even solve problems, but they don’t actually know how the pieces connect.

This is why developers often end up with AI-generated code that looks plausible but fails to run, or systems that sound smart but reason poorly.

TSN approaches this issue differently. Instead of improving today’s models by adding more data, Nils asked a more fundamental question:

“What mathematical structure would intelligence need to truly understand how systems fit together?”

The Mathematical Backbone of TSN

At its core, the Ternary Sheaf Network is a neural learning architecture grounded in category theory, a branch of mathematics that studies relationships between systems rather than their isolated parts.

This is where the name comes from:

• Sheaf: This concept models how local pieces of information (like individual functions or code files) connect into a global structure (the logic of an entire software repository). It’s a way of “gluing together” small, local insights to form a coherent, system-wide whole.
• Ternary: Refers to the three states of information, enabling the system to not just check if a relationship exists (binary), but also to quantify the consistency of that relationship.

In simple terms:
TSN teaches machines to see context, not just content.

A Smarter Way to Build Software

Nils pointed out a frustration that many developers share; modern AI tools often generate code that looks functional but is riddled with hidden inconsistencies.

“They can flood you with code, but without a real sense of structure,” Nils explained.
“You end up with a pile of text that works sometimes but has no reusable architecture.”

The Ternary Sheaf Network aims to fix that by enabling neural representations of entire repositories, learning the architecture, dependencies, and logic that connect files and modules.

Imagine uploading your project and receiving a mathematically encoded blueprint of your system:

• No exposed source code.
  
• A complete map of how your software fits together.
  
• The ability to share and reuse verified structures safely through a decentralized network.

That’s the long-term goal of TSN: to make AI-assisted development both secure and structurally sound.

Formal Verification: Where Mathematics Meets Trust

One of the most promising applications for TSN is in smart contract development.
Blockchain developers know how one overlooked bug can cost millions. Formal verification — the process of mathematically proving that code behaves as intended — is the gold standard, but it’s slow and highly technical.

By integrating with the Lean Proof Assistant, TSN can automatically check if generated code matches its logical specification, closing the gap between AI generation and formal assurance.

“You wouldn’t want to just vibe-code a smart contract,” Nils joked.
“But with formal guarantees, you can democratize secure development.”

This could make verified smart contract creation faster, more accessible, and safer, a crucial step for both Cardano and SingularityNET ecosystems.

Next Steps for TSN and Deep Funding

The project is currently in its active development phase, funded by Deep Funding, and already undergoing component-level testing.

Nils shared that the team is preparing to release an open-source implementation later this year, alongside a demo at an upcoming Deep Funding Townhall.

“Component-wise, it works,” he confirmed. “The next challenge is scaling it into a distributed learning system, something that can reason and verify across connected datasets.”

Projects like the Ternary Sheaf Network embody the spirit of Deep Funding, supporting researchers who dare to tackle foundational questions in AI. By backing work that combines deep mathematics, open-source collaboration, and verifiable trust, the community isn’t just shaping better models—it’s shaping the science behind intelligence itself.

Join the Next Deep Funding Townhall

The Deep Funding Townhall is a biweekly community event hosted by Deep Funding Events Circle. It’s where funded teams, researchers, and community members come together to share progress, showcase demos, and explore new directions in decentralized AI.

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