[kippinitreal]

Totally agree that this is under appreciated.

Between open source modeling tools being incredible, transfer learning allowing dirt cheap fine-tuning and now mega-models being able to instantly give you a "mostly right" data set, the cost of creating ML features has dropped to almost nothing.

Products that took quarters/years and required big budgets for labeling, ML specialist, GPUs etc just a few years ago can now be done in an hour or so for free (if you are scrappy). I imagine this is going to lead to a ton of great ML features that weren't worth funding in the past but are very valuable in aggregate. Similar to the mid-2000s when the cost/ease of web development came down enough that there was a lot more experimentation and fun to be had.