LLMs Aren't World Models
14 days ago
- #AI Limitations
- #LLMs
- #World Models
- LLMs lack a true world model, demonstrated by their failure in chess and understanding basic concepts like alpha blending.
- Examples show LLMs failing to track chess pieces or understand transparency in image editing, indicating they don't grasp underlying principles.
- LLMs can generate plausible-sounding answers without true comprehension, leading to errors in logic and reasoning.
- The author predicts future breakthroughs in machine learning will focus on developing true world models, unlike current LLMs.
- LLMs will never reliably know what they don't know or stop making things up, as they lack a model of knowledge and truth.
- The author compares LLM thinking to human cognitive flaws, where predicting words doesn't equate to understanding.
- Despite limitations, LLMs can still be useful for tasks where verification is possible, like proofreading or answering known questions.