My mental model is that a scaled up GPT becomes as dangerous as many agents precisely because it gets extremely good at producing text that would be an apt continuation of the preceding text.
Note that I do not say “predicting” text, since the system is not “trying” to predict anything. It’s just shaped in initial training by a process that involves treating its outputs as predictions. In fine-tuning it’s very likely that the outputs will not be treated as predictions, and the process may shape the system’s behaviour so that the outputs are more agent-like. It seems likely that this will be more common as the technology matures.
In many ways GPT is already capable of manifesting agents (plural) depending upon its prompts. They’re just not very capable—yet.
My mental model is that a scaled up GPT becomes as dangerous as many agents precisely because it gets extremely good at producing text that would be an apt continuation of the preceding text.
Note that I do not say “predicting” text, since the system is not “trying” to predict anything. It’s just shaped in initial training by a process that involves treating its outputs as predictions. In fine-tuning it’s very likely that the outputs will not be treated as predictions, and the process may shape the system’s behaviour so that the outputs are more agent-like. It seems likely that this will be more common as the technology matures.
In many ways GPT is already capable of manifesting agents (plural) depending upon its prompts. They’re just not very capable—yet.