In GPT-2, the large achievement was being able to generate coherent text over a long-form while maintaining context. This was very impressive but for GPT-2 to do new language tasks, it had to be explicitly fine-tuned for the new task.
In GPT-3 (From my understanding), this is no longer the case. It can perform a larger array of language tasks from translation, open domain conversation, summarization, etc., with only a few examples. No explicit fine-tuning is needed.
The actual theory behind GPT-3 is fairly simple, which would not suggest any level of ability other than what would be found in common narrow intelligence systems.
However, looking past the media hype and the news coverage, GPT-3 is not explicitly programmed to "know" how to do these wider arrays of tasks. In fact, with limited examples, it can perform many language tasks quite well and "learn on the fly" so to speak. To me, this does seem to align fairly well with what most people would consider strong AI, but in a narrow context, which is language tasks.
Thoughts? Is GPT-3 an early example of strong AI but in a narrower context?