GEN-1 still works with lights off, and generalizes under harsh lighting conditions.

The model uses raw video pixels to make decisions, so strong lighting changes can drastically alter its input distribution. Yet performance still holds.

Why? GEN-1 was pre-trained on a massive, diverse dataset of different lighting conditions—everywhere from outdoor farms, to warehouses, from grocery stores, to dimly lit homes—it's already seen it all, and transfers this knowledge to new tasks.

This is a glimpse of what we call Mastery, and is part of the reason these models can cross a new performance threshold.

Read more about it in our blog post in the comments below 👇