What AIs are not Learning (and Why)
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Abstract (arXiv)
Today's robots do not learn the general skills needed for such services as providing home care, being nursing assistants, or doing household chores. Addressing such aspirational goals requires improving how AIs and robots are created. Today's mainstream AIs are not created by agents learning from experiences doing real world tasks and interacting with people. They do not learn by sensing, acting, doing experiments, and collaborating. This paper investigates what aspirational service robots will need to know. It recommends developing experiential (robotic) foundation models (FMs) for bootstrapping them.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 8 of its 75 references that are in the map. First posted on arXiv 19 Mar 2024.
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8 of 75 references.
References · 8
- 2020Scaling Laws for Neural Language Modelscited by 6,586
- 2022Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agentscited by 1,035
- 2022Socratic Models: Composing Zero-Shot Multimodal Reasoning with Languagecited by 513
- 2023Foundation Models in Robotics: Applications, Challenges, and the Futurecited by 216
- 2021Why AI is Harder Than We Thinkcited by 41
- 2019Adaptive Robot-Assisted Feeding: An Online Learning Framework for Acquiring Previously Unseen Food Itemscited by 14
- 2017Bodily aware soft robots: integration of proprioceptive and exteroceptive sensorscited by 5
- 2023Bootstrapping Developmental AIs: From Simple Competences to Intelligent Human-Compatible AIscited by 1
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