Executive summary: Large language models (LLMs) are fundamentally different from human conversationalists, with computational processes that make them far more alien and less coherent than their chat interfaces suggest.
Key points:
LLMs are not single, consistent entities but collections of “clones” processed across different servers and hardware.
The models cannot clearly distinguish between text they produce and text they receive, processing all input similarly.
LLM outputs do not necessarily reflect the model’s actual commitments or perspectives, functioning more like probabilistic text prediction.
The sampling mechanisms used to generate text fundamentally alter the model’s apparent “thoughts” and should not be interpreted as direct representations of internal states.
Probability distributions in LLMs do not straightforwardly indicate confidence or belief, but represent complex computational predictions.
Researchers and users should be cautious about anthropomorphizing LLMs and inferring human-like mental states from their outputs.
This comment was auto-generated by the EA Forum Team. Feel free to point out issues with this summary by replying to the comment, andcontact us if you have feedback.
Executive summary: Large language models (LLMs) are fundamentally different from human conversationalists, with computational processes that make them far more alien and less coherent than their chat interfaces suggest.
Key points:
LLMs are not single, consistent entities but collections of “clones” processed across different servers and hardware.
The models cannot clearly distinguish between text they produce and text they receive, processing all input similarly.
LLM outputs do not necessarily reflect the model’s actual commitments or perspectives, functioning more like probabilistic text prediction.
The sampling mechanisms used to generate text fundamentally alter the model’s apparent “thoughts” and should not be interpreted as direct representations of internal states.
Probability distributions in LLMs do not straightforwardly indicate confidence or belief, but represent complex computational predictions.
Researchers and users should be cautious about anthropomorphizing LLMs and inferring human-like mental states from their outputs.
This comment was auto-generated by the EA Forum Team. Feel free to point out issues with this summary by replying to the comment, and contact us if you have feedback.