Aeris-UK Insights

Plexal profiles SATORI—our way to see how AI behaves in the messy real world — across systems and people, and when things go wrong — before it goes live.

What if neural networks didn’t just learn from the past, but anticipated what’s ahead? We explore a novel training idea, Prospective Configuration, and what it could mean for efficient, future-aware learning.

Picking a simulator shouldn’t slow your research. We explain when to use Unity, when PyBullet is enough, and when a custom FastSim turns days of training into hours.

Even small teams can reduce the environmental impact of model training. We share our experience of making real-world AI development greener, without needing hyperscaler budgets.

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