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[D] Does Neural Program Synthesis be improved with x100 scaling of samples/compute/labels/curriculum ?!

Looking at some recent papers on program synthesis

Neural (Meta) Program Synthesis, Singh {GB}

AlphaNPI twitted that acceptance to NIPS2019 with spotlight

I am wondering if field is still working out good architectures, representations, etc

OR

existing SOTA techniques can be applied if we have x100 more compute, or a massive dataset of input-output pairs, or maybe a long detailed curated curriculum of specs and solutions, etc

submitted by /u/so_tiredso_tired
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