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Are they price-competitive for those applications though? My understanding is that the main focus is Memory/GPU-interconnect for large models.

Are recommendation/ranking models large enough to take advantage of this? I don't think these cards are generally competitive in throughput/$.

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It's not really clear what you mean, maybe there's gaps in my ML knowledge, but generally the answer depends on "what throughput do you need for your use case?"

Generally I agree that if you only need to deliver mail once daily on a mile long route, a car that takes 24 hours to travel a mile is fine.

Lots of ML applications don't generally care about latency, and throughput only matters per dollar (as you can just scale horizontally).

To my knowledge, most inferencing (at least for simpler models) happens on cheaper, slower GPUs that have better throughput/dollar.

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