An architecture for the new era of AI

The future of AI requires more than just scale. It demands a new foundation. Farang's proprietary architecture is built from the ground up for superior reasoning, efficiency, and privacy, tackling the complex problems that are intractable for current systems.

Basic diagram of Farang's FX architecture

The Transformer limitation

While Large Language Models (LLMs) have been revolutionary, their reliance on the transformer architecture presents a ceiling. They struggle with complex, multi-step reasoning, require colossal amounts of data and computation to train, and their centralized nature creates significant privacy concerns. Simply making these models bigger is a path of diminishing returns, not a viable route to true machine intelligence.

Our architectural edge

At Farang, we have moved beyond the transformer. Our architecture is inspired by principles of biological cognition, focusing on how information is processed, stored, and recalled. This allows our models to achieve a deeper contextual understanding and tackle specialized, cognitive tasks that are far beyond the reach of today’s LLMs.

Faster convergence

By learning more efficiently, our architecture reaches higher levels of capability with significantly less training data and compute. This accelerates development and reduces environmental impact.

Privacy by design

Our models are designed for efficiency, enabling powerful on-device performance. This keeps user data private and secure, reducing reliance on the cloud and giving users true autonomy.

Earlier emergence

Complex reasoning and problem-solving abilities emerge much earlier in the training cycle of our models, demonstrating a more robust and genuine path towards advanced intelligence.

Get Early Access

We are granting early access to a select group of developers, researchers, and partners. To be considered, please tell us more about what you hope to build with a next-generation AI.