It was still a wildly wasteful company doing morally ambiguous things prior to that timeframe. I mean, its entire business model is tracking and ads— and it runs massive, high energy datacenters to make that happen.

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cmrdporcupine 9 hours ago | parent [-]

I wouldn't argue with this necessarily except that again the scale is completely different.

"AI" (and don't get me wrong I use these LLM systems constantly) is off the charts compared to normal data centre use for ads serving.

And so it's again, a kind of whataboutism that pushes the scale of the issue out of the way in order to make some sort of moral argument which misses the whole point.

BTW in my first year at Google I worked on a change where we made some optimizations that cut the # of CPUs used for RTB ad serving by half. There were bonuses and/or recognition for doing that kind of thing. Wasteful is a matter of degrees.

	▲	luckylion 6 hours ago \| parent [-]
		> "AI" (and don't get me wrong I use these LLM systems constantly) is off the charts compared to normal data centre use for ads serving. It wasn't only about serving those ads though, traditional machine-learning (just not LLMs) has always been computationally expensive and was and is used extensively to optimize ads for higher margins, not for some greater good. Obviously, back then and still today, nobody is being wasteful because they want to. If you go to OpenAI today and offer them a way to cut their compute usage in half, they'll praise you and give you a very large bonus for the same reason it was recognized & incentivized at Google: it also cuts the costs.