Abstract: An LLM’s invocation is the non-model code around it that determines when and how the model is called. I illustrate that LLMs are already used under widely varying invocations, and that a model’s capabilities depend in part on its invocation. I discuss several implications for AI safety work including (1) a reminder that the AI is more than just the LLM, (2) discussing the possibility and limitations of “safety by invocation”, (3) suggesting safety evaluations use the most powerful invocations, and (4) acknowledging the possibility of an “invocation overhang”, in which an improvement in invocation leads to sudden capability gains on current models and hardware.
Invocations: The Other Capabilities Overhang?
Invocations: The Other Capabilities Overhang?
Invocations: The Other Capabilities Overhang?
Abstract: An LLM’s invocation is the non-model code around it that determines when and how the model is called. I illustrate that LLMs are already used under widely varying invocations, and that a model’s capabilities depend in part on its invocation. I discuss several implications for AI safety work including (1) a reminder that the AI is more than just the LLM, (2) discussing the possibility and limitations of “safety by invocation”, (3) suggesting safety evaluations use the most powerful invocations, and (4) acknowledging the possibility of an “invocation overhang”, in which an improvement in invocation leads to sudden capability gains on current models and hardware.