Stream implementations can and do ignore backpressure; and some spec-defined features explicitly break backpressure. tee(), for instance, creates two branches from a single stream. If one branch reads faster than the other, data accumulates in an internal buffer with no limit. A fast consumer can cause unbounded memory growth while the slow consumer catches up — and there's no way to configure this or opt out beyond canceling the slower branch.
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The advice says this group should be screened every two years between the ages of 45 and 61.
I have been thinking a lot lately about “diachronic AI” and “vintage LLMs” — language models designed to index a particular slice of historical sources rather than to hoover up all data available. I’ll have more to say about this in a future post, but one thing that came to mind while writing this one is the point made by AI safety researcher Owain Evans about how such models could be trained: