Detect AI-generated images without AI.
- Goals:
- High Accuracy, Low Cost
- Mathematical and Grey-Box Models
- Minimize Carbon Footprint
- Maximize Data Integrity
Future-Proof Image Compression at Scale.
- Goals:
- Improve Image Quality
- Reduce Data Size
- Create Open-Source Standards
- Maintain Long-Term at Scale
Photorealistic, Physically Correct Realtime Rendering.
- Goals:
- Realtime Pathtracing
- Reduce Render Time and Cost
- Work Within Existing Standards
- Lead a new era of Realtime Rendering
Motivation
Understand the Approach
We want our models to be as transparent and understandable as possible. Because of this, we focus on grey-box and mathematical models, allowing us to fully leverage and tweak our detection techniques.
Motivation
Reduce Carbon Footprint
AI puts a huge burden on the power grid and envionment. Our goal is to create models that minimze this burden, allowing us and our clients detect AI-generated content while still reaching their environmental goals.
Motivation
Increase Transparency
Most of the largest AI models are locked behind both purposeful and unavoidable secrecy. Our goal is to make our tools widely available, and open source when possible.
Motivation
Improve Scalability
We want our tools to be a helpful addition — not a burdensome integration. Our tools will be available for a wide range of datastreams, making them easy to implement and scale but still very effective.