Isn’t your comment more of a perspective on the public perception of AI, the missteps surrounding its implementation, and its current role - rather than an examination of the potential role (practically speaking) of generative AI in a more general AI model? As is the thrust of the post, generative AI will necessarily be part of a larger AI, in part to make up for its weaknesses, in part to utilize its strengths.
That said, generative AI isn’t nearly as endangered by generated training data as is commonly understood. Even if it were that bad, embodiment is rapidly changing the landscape. There are a ton of papers about how to use larger models to make smaller models more effective, using generative AI to improve generative AI along with efficiencies. Heck, novel efficiencies get developed almost as regularly as novel use cases. We’re always learning how to do more with less.