Don't forget it was written in Nov 2017, AlphaGo Zero was just released at this point. Seeing how the field evolved in a 5-year span, I can understand the desir

Don't forget it was written in Nov 2017, AlphaGo Zero was just released at this point. Seeing how the field evolved in a 5-year span, I can understand the desire to be at the forefront. Personally, I want to keep working on things that I can get to the bottom of. In the same way proprietary software is a nightmare to debug, having an AI blackbox in the middle of my stack could wreck all traceability. However, I can see myself using an AI blackbox when its output is consumed/checked by a human or when "best-effort" is good enough (but treat output as dirty). Example: sorting documents by relevance (human consumes), code assistant (human checks), transcription of my audio notes (wouldn't do it myself or pay anyone for that, so any output is good enough), Counter-examples (too dangerous!): AI personal assistant that accept/reject meetings, a ChatGPT text box as an interface for settings, auto-generated tests, Infrastructure-as-a-Desire: input your software and get a new K8S cluster provisioned for it.