Simulated Horizons is a series of AI-generated landscapes focused on atmosphere, scale, and detail. The images feel loosely connected to real environments but are not tied to specific locations. Each scene is built from features that show up across different kinds of natural spaces, including plains, forests, wetlands, cliffs, underwater areas, and open sky.

The work reflects a long history of landscape art without trying to imitate any one style. Classic painting, digital imagery from the early 2000s, and modern machine learning all sit in the background of how these scenes form. The images feel straightforward at first, yet they carry a quiet sense of tension because they come from a process that does not rely on direct observation. They present nature as something assembled rather than witnessed.

Simulated Horizons looks at how AI treats the idea of a landscape. The series focuses on the shapes, colors, and moods that continue to appear when nature is rebuilt through data. It shows familiar terrain produced through unfamiliar means, which gives the work a clear but slightly altered presence.