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Generative AI and Semantic Grounding
Finanzierung:
Haushalt;
The project aims to explore how core features of modern Generative AI systems pave the way to the semantic grounding of such systems. It centers around the following working hypotheses:
  1. Generative AI, including LLMs, is based on generative models.
  2. Generative models are probabilistic structural representations that act as world models.
  3. Generative models are key for self-supervised learning.
  4. Semantic grounding is a gradual affair that unfolds along the three dimensions of functional, social and causal grounding.
  5. Causal grounding scales with the development of world models.
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