If you believe this then you don't understand AI or natural intelligence well enough to refute my statements either.

Perhaps you're trying to refer to something specific by "cross-domain" competence, but firstly, humans vastly overestimate the extent to which experts in one domain can be trusted to speak accurately on topics in other domains (this is a form of authority bias), and secondly, real cross-domain expertise is a result of pre-existing metacognitive ability such as keen reasoning ability, intense focus, and learning-how-to-learn. In other words, Leonardo da Vinci was not a genius because he was a polymath; he was a polymath because he was a genius.

Likewise, I see no evidence that "generalist models" have proven anything about their ability over domain-specific ones other than that the big AI firms seem to believe that "generalist models" are their golden ticket to AGI and therefore a quintillion-dollar valuation. It's obvious in the long run that tools built for specialized tasks will outperform generalist tools for specific tasks, in the same way that a multi-axis CNC mill does not outperform your bog-standard lathe for shaping objects with rotational symmetry, or perhaps more pertinently to this conversation, how no LLM will ever outperform Stockfish at chess.