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junio 2026

1181 artículos
La jugada maestra de los data centers: ser flexibles para no colapsar la red
Tecnología

La jugada maestra de los data centers: ser flexibles para no colapsar la red

At the end of a tense and scoreless first half of a soccer match between the English men’s team and rival Germany, millions of Brits let out a collective sigh and did what they so often do in moments of stress: They made tea. That wave of electric kettles clicking on, however, caused a different…

16/06/2026
¿Qué coño es una buena explicación? La IA se enfrenta a su propia crisis de identidad
IA

¿Qué coño es una buena explicación? La IA se enfrenta a su propia crisis de identidad

arXiv:2606.14838v1 Announce Type: new Abstract: How to define a good explanation is a long-standing philosophical debate which has found recent renewed interest in the context of AI outputs. Explainability is crucial for AI adoption in many contexts, but in order to produce good explanations of AI systems, we must first have an understanding of what good explanations are. In this paper we propose a definition inspired by the notion of counterfactual explanations, however we argue that one must

16/06/2026
¿Y si los buscadores de documentos dejaran de ser tan tontos? Esto va de darles manos a las máquinas
Videojuegos

¿Y si los buscadores de documentos dejaran de ser tan tontos? Esto va de darles manos a las máquinas

arXiv:2606.14885v1 Announce Type: new Abstract: Agentic search over large corpora relies on retriever-mediated interfaces (e.g., BM25 or ColBERT) for scalable candidate discovery. While effective at ranking relevant documents, these interfaces expose evidence only as ranked results or bounded document views, limiting agents' ability to reorganize material and verify constraints across documents. Direct Corpus Interaction (DCI) addresses this limitation by exposing shell-executable corpus operat

16/06/2026
La IA necesita entender por qué pasan las cosas, no solo ver patrones
IA

La IA necesita entender por qué pasan las cosas, no solo ver patrones

arXiv:2606.14892v1 Announce Type: new Abstract: An artificial intelligence must have a model of its environment that is causal, supporting reasoning about interventions and counterfactuals, and also combinatorial, supporting generalization to unseen combinations of objects. In this work, we formally study when and how such a model can be learned. We develop relational structural causal models, extending structural causal models (Pearl 2009) to settings where objects and their relations vary. Fi

16/06/2026