Interpretability
Opening the black box: what a model represents, where it stores it, and how that representation changes under pressure.
Read the programme →Frontier research
We study the fundamental nature of intelligence to build AI that is interpretable, steerable, and aligned with human values. Our work is guided by a single conviction: the most capable systems must also be the most understood.
Read our research →Opening the black box: what a model represents, where it stores it, and how that representation changes under pressure.
Read the programme →Building systems that can be corrected at the level of intent, not just output — and can explain why they changed course.
Read the programme →Measuring whether a system's behaviour remains within human values when the context shifts beyond its training distribution.
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