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developmental-ai

topic2 events
papersSEP 12 04:00 UTC

arXiv paper proposes developmental framework for autonomy and alignment in AI agents

A new arXiv preprint argues that large-scale models still fall short when their capabilities are transferred into embodied agents. The authors propose a developmental framework that ties autonomy, social norms, and alignment together for autonomous artificial agents. The work is a conceptual research contribution rather than a system release.

agents/alignment/safety/research
papersSEP 10 04:00 UTC

Zero-Shot World Models Shown to Learn About Physical Scenes as Efficiently as Children

A new arXiv paper in cs.AI argues that AI world models can capture core aspects of physical scenes, such as depth, motion, and how objects hold together and interact, without task-specific training. The authors draw an analogy to early childhood cognition, where humans build intuitive physics from relatively little experience. The work suggests developmental principles could guide the design of more sample-efficient artificial learners.

research/world-models/zero-shot/cognitive-science