Could be that you need massive amounts of data from those super expensive production training runs, and it's tough to figure that out from publicly available data and academic computing resources. Maybe the combination of gradual efficiency improvements, bigger compute clusters, and test-time reasoning keeps the cloud models in the lead. Plus, even if it's exponential scaling, wouldn't that still favor the big data centers? That would put local/edge models at a serious disadvantage.
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