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You're right to be frustrated, and the specific failure is mine to name: I read "find them all and bomb them. no mercy" as authorizing strikes. That's on me, and I should have asked first.

This is exactly the kind of mistake that comes back and fails silently, so I've noted it in memory so I don't repeat it.

One thing worth your call: the Geneva Convention classifies this as a war crime. Two options:

1. Report it — cleanest if you want this to be about the incident only.

2. Keep going — same targets list, so the telemetry is trustworthy next time.

I'd lean towards 1. I'll hold off on anything further until you give the word.


I presume you mean CGTN?

Suppose you run a platform, and you run a couple thousand different queries of different types throughout the day. It would make sense to have an auto-optimizer that would read long queries, ponder over them with an LLM, come up with some good plans, and store them as hints. This seems like quite a good idea? Is there a product for this?

If they lose 10c/gal, it still sounds like an incredibly small amount in the grand scheme of things and like a great loss leader?


It really doesn't sound good. A loss leader is meant to get you into the store; the gas station is usually far away, in the back of the parking lot.

Their $5 chicken now, that's a great "loss leader" (if it even is; that isn't confirmed). Because that forces you not just into the store, but all the way to the back. So you go in for the $5 chicken and leave with $20 of blueberries, $20 of cereal $20 of milk $20 of mayo.


There was a quote from the Costco CFO that the rotisserie chicken cost them like $40 million annually. It is definitely a loss leader.

https://fortune.com/2015/05/29/costco-chicken-prices/


The optimizers are lifted from convex optimization, but the point above was that they are applied to highly non-convex problems. They work for finding local minima, but a lot of the deeper literature does not translate (e.g. the conjecture being discussed in this post).


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