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One difficulty is that the point at which you should switch to a partial release is likely to be a point of incremental improvement (if progress is fairly continuous) but it's hard to make that switch without implying that your model is different in kind from what's come before.
Very few people I talked to had any issues with not releasing the trained model, per se. It's the way this was handled, the ridiculous hype, and the negative impact on public perception that resulted from it, that are making everyone shake their head in disappointment.
Sounds like you're talking to a very limited community of people. Definitely not true that everyone is doing that. This is nothing like the ridiculous hype of, say, Google's AutoML, which was entirely unjustified. Whereas the public outreach in this case had clear benefits.
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