> We don’t understand AI or natural intelligence well enough to make such statements.

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.