[general_dat] Recordatorio: Seminario AISAR – AI in a vat: Fundamental limits of efficient world modelling for agent sandboxing and interpretability

[Agustín Martinez Suñé]

Recordatorio de esta charla online de AISAR que sucederá mañana.

Saludos,
Agus.

> Desde el Programa de Becas AISAR en AI Safety tenemos el placer de
> invitarlos a la próxima charla de nuestro seminario online, con la
> participación de investigadores del área.
>
> 📌 Fecha y hora: Miércoles 22 de octubre, 12:00 hs (ARG).
> 🎤 Orador: Fernando Rosas – Lecturer @ University of Sussex
> 📖 Título: AI in a vat: Fundamental limits of efficient world modelling
> for agent sandboxing and interpretability
>
> 🔗 Charla online: Para asistir a la charla, registrate acá:
> https://luma.com/dywugtbl
>
> Abstract: Recent work proposes using world models to generate controlled
> virtual environments in which AI agents can be tested before deployment to
> ensure their reliability and safety. However, accurate world models often
> have high computational demands that can severely restrict the scope and
> depth of such assessments. Inspired by the classic `brain in a vat' thought
> experiment, here we investigate ways of simplifying world models that
> remain agnostic to the AI agent under evaluation. By following principles
> from computational mechanics, our approach reveals a fundamental trade-off
> in world model construction between efficiency and interpretability,
> demonstrating that no single world model can optimise all desirable
> characteristics. Building on this trade-off, we identify procedures to
> build world models that either minimise memory requirements, delineate the
> boundaries of what is learnable, or allow tracking causes of undesirable
> outcomes. In doing so, this work establishes fundamental limits in world
> modelling, leading to actionable guidelines that inform core design choices
> related to effective agent evaluation.
>
> El paper: https://arxiv.org/abs/2504.04608
> Equipo AISAR
> http://scholarship.aisafety.ar/
> <http://scholarship.aisafety.ar/?utm_source=chatgpt.com>
>