Learning Objectives
Apply CL's embodied grounding thesis to evaluate contemporary multimodal AI architectures
Analyze Vision-Language Models through the theoretical lens of conceptual integration theory
Evaluate GPT-4V and Gemini against rigorous CL-derived grounding criteria
Identify specific research gaps in multimodal cognitive-linguistic grounding and propose directions
How language, vision, and embodiment converge in multimodal AI systems — analyzed through a CL lens.
This lesson builds on the theoretical foundations established earlier in the module and extends your understanding of how cognitive-linguistic principles apply directly to modern AI systems.
Learning Objectives
Apply CL's embodied grounding thesis to evaluate contemporary multimodal AI architectures
Analyze Vision-Language Models through the theoretical lens of conceptual integration theory
Evaluate GPT-4V and Gemini against rigorous CL-derived grounding criteria
Identify specific research gaps in multimodal cognitive-linguistic grounding and propose directions
Key Concepts
Apply CL's embodied grounding thesis to evaluate contemporary multimodal AI architectures
Analyze Vision-Language Models through the theoretical lens of conceptual integration theory
Evaluate GPT-4V and Gemini against rigorous CL-derived grounding criteria
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