Efficiency

Today’s frontier AI models are extraordinarily capable, but their size and breadth comes at a cost. Many applications do not require their full range of capabilities. The next stage of development should focus not only on what models can do, but on how efficiently and appropriately they do it.

Smaller, specialized models can preserve valuable expertise while reducing computational costs and making advanced AI more accessible. They can be better aligned with the tasks they perform, without retaining unnecessary capabilities that create avoidable risks.

Cereus conducts research to make models smaller, more efficient, and better suited to their intended purposes. Our work explores how to preserve useful capabilities, reduce unnecessary complexity, and support a more deliberate approach to AI safety.

We believe that AI should be developed not simply to maximize capability, but to make that capability useful, accessible, and socially beneficial.