A lot of non-native English speakers use online communication to practice and most want to be corrected so they can improve.
A lot of native English speakers make mistakes accidentally, or speak with a dialect and some of them get really angry when people try to correct them.
It’s sometimes tricky to know which is which. The best solution is for everyone to just be kind to each other but…
Since when is India not a major player? Last I checked they were the world’s 4th biggest economy, have almost 20% of the population of the planet (more than four USes combined), 4th largest military spend and have nearly 200 nukes.
Not to say that it would be part of a world war but it sounds weird to say that they’re not a heavyweight but Russia is, despite having double Russia’s economic output.
Venom is a type of poison. Poison doesn’t have to be eaten. (Eg. Contact poisons exist).
Venom is just a poison that is delivered through a bite or a sting.
I think the idea is that there are potentially alignment issues in LLMs because it’s not clear what concepts map to what activations. That makes it difficult to see what they’re really “thinking” about when they generate text. Eg. if they’re being misleading or are incorrectly associating concepts that shouldn’t be connected etc.
The idea here is to use some mechanistic interpretability stuff to see what text activates what neurons in an LLM and then crowd source the meanings behind that and see if that’s something you could use to look up some context from an ai. Sort of trying to make a “Wikipedia of AI mind reading”
Dunno how practical it is or how effective that approach is but it’s an interesting idea.
If a worker co-op based society erased it’s competition and formed a monopoly co-op run for the benefit of workers, is that not just a communist managed economy at that point with the monopoly playing the role of the state before erasing itself?