[–] shevy-java 18 hours ago
[–] Syntaf 17 hours ago
I’m much more inclined to believe they just don’t _care_ about cost, and profit is an ancillary benefit to their functionality above all else.
Just recently they released auto idle-compaction for large sessions about to miss the cache window. If they were so profit driven I can’t imagine they’d have built this to begin with, that’s free tokens from your perspective.
[–] plagiarist 15 hours ago
[–] pessimizer 14 hours ago
Do you really think this is so interesting, or something that people who work jobs have a responsibility to do?
[–] Syntaf 14 hours ago
I don’t think the CC’s teams have hidden motives to optimize for token inefficiency as the OP I replied to implies.
A reality where a secret cabal of CC engineers are trying to find the most token inefficient ways to build the best harness on the market sounds quite interesting to me, but not realistic.
[–] junofan 14 hours ago
[–] pantsforbirds 14 hours ago
Older programs were MUCH more memory and compute conscious because memory and compute were actively limiting factors. Anthropic engineers probably don't feel the token efficiency requirements nearly as much as we do because they are working with the equivalent of a super beefy dev machine.
[–] sirtaj 17 hours ago
[–] gwd 15 hours ago
That only counts if people wouldn't find some other way to spend tokens anyway. I regularly have to pace my usage to avoid hitting the weekly limit on the 20x plan; I have plenty of things I could automate.
Jeavon's Paradox means that until all possible uses are saturated, the cheaper frontier AI becomes, the more of it they can sell.
[–] shafyy 19 hours ago
Hahaha good one. Profit is the whole reason of existence for for-profit companies. Sure, companies might start with some ideologic grain of thought. But as soon as you reach a certain size, all that goes flying out of the window.
I don't understand this "analysis". Why would it not be about profit?
"Features for internal users" makes no sense here, as it does not apply to the case. "Useful features" is also debatable - LLMs providing user data upstream to Anthropic is a use case for Anthropic, but less so for downstream users and token burners.