“Nothing is in the intellect that was not first in the senses” is a principle associated with Thomas Aquinas and the tradition of empiricism: the idea that knowledge emerges through observation and interaction with the world. This principle ultimately gave rise to the scientific method, where hypotheses are validated through experimentation and grounded in evidence from the natural world. For centuries, this process has driven human scientific and technological progress.

It remains an open question where the next major step-change in computational intelligence will come from. One view is that increasingly capable AI systems will recursively improve themselves and contribute to their own research and development. We agree, and are excited by where this could lead. However, we also believe greater intelligence will come from exploring and learning directly from the world itself. This belief motivates our research on world models.

Starchild-1 is an early step beyond world models that learn only from visual observation, toward systems that learn from richer multimodal interaction with the world. We believe multimodal world models will ultimately enable more natural and capable forms of computational intelligence grounded in how the real world actually evolves and behaves, unlocking new forms of education, gaming, companionship, robotics, and entirely new types of computing devices that have yet to be invented.

In our accompanying technical report, we share the architecture, training pipeline, and systems innovations behind Starchild-1, including our work on causal multimodal rollout, synchronized audio-video generation, and long-horizon real-time interaction. We’re excited to hear your feedback.