A user-centric, open-source AI model for Earth
Overview
In collaboration with our partner Clay, we have built a unique user-centric foundation model of Earth. This model makes it faster and cheaper to develop AI-centered applications that are customizable to your data and needs. Clay can be used over a wide range of data sources and spatial resolutions—no matter the platform. Whether you have imagery from drones, airplanes, or satellites, Clay can help.
Challenge
Earth observation foundation models are hard to build but also hard to use. They are hard to build because of the complexity of model architectures and the sheer scale of data required to train them. They are hard to use because they tend to require machine learning expertise and have rigid specifications for input data sources and formats. Our challenge was building a model that is flexible, globally applicable, and easy to use all at once. For this to be possible we had to innovate on the model architecture as well as the data pipelines.
Outcome
We have produced Clay v1, a uniquely versatile foundation model. Clay can accept images from a wide range of sources, different image sizes, pixel resolutions, and spectral band combinations. All of these aspects are input parameters and can be varied freely. This makes Clay usable across a wide range of applications and simplifies usage for use cases with specific data needs.
Clay architecture
Similarity search results. The reference image is the first one on the left, the others are selected by similarity score. This is useful to find features such as pools or solar panels in no-code applications.
Examples of some of the applications Clay is exploring with this open-source AI model for earth.
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