Introducing Seton Labs

Most AI systems perform remarkably well on data that looks similar to what they have seen before. Yet they often struggle when tasks, domains, or distributions change.

At Seton Labs, we're interested in one question:

How do we measure and improve true generalization?

Our initial focus is on building benchmarks and datasets that better capture transfer, abstraction, and out-of-distribution reasoning.

We believe progress comes from rigorous evaluation, reproducible research, and open collaboration.

What We're Building

Over time we hope to publish benchmark proposals, experimental results, datasets, and research notes.

Some projects may fail. Others may evolve into larger community efforts. Either way, everything starts with careful thinking and honest evaluation.

Join Us

If you're interested in AI generalization, benchmark design, evaluation, or research infrastructure, we'd love to have you.

The best way to get involved is through the community Discord.