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What do we think of this custom Seiko?

6, 8, or 9

Anyone else riding the $HIVE wave?
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Thought this was interesting. Across 160 teams of researchers, just about all failed to make good life outcome predictions on things like GPA, evictions, layoffs, and others. Data followed 4.5k families across 15 years, with 13k features (varied over time). Haven't looked at it directly yet, but will be turning the docs and data inside out... In the meantime, authors claim this as showing the limits of ML. Oh, and it's published in PNAS, so you know there's some big publication energy there.
https://www.pnas.org/content/117/15/8398
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1. Without IT background expect to get into data linage/management/mapping/etc topics, which require some learning but are straightforward. Thus not hard. Depending on setup you might need to learn sql or whatever the query language the data backend will use.
2. It's a cash cow that's not going away ever with a huge shift towards cloud data management.
3. Bonus info: it is boring as fk. If you truly enjoy it, your superiors will love you and you will get easy staffing anywhere.