Maybe if you don't choose it's a vote for a lottery to pick. If half the population doesn't vote then the winner is a random person. So if the authorities manage to prevent people from voting then they can't seize the system with their own pick
zbyte64
joined 2 years ago
Antisocial people develop an antisocial AGI promising it won't be antisocial towards a select group. Surprised Pikachu when the AGI concludes they are not in the in group
"If the west doesn't build it then China will" is a claim to a timeline. And in the context of governments, most would assume you're talking about less than 100 years.
Because asking AI to do humans is still uncanny. Pixar and Ghibli was already ruined by AI...
Psychedelics doesn't magically make a bad person into a good person, just look at Joe Rogan. Though I am all for putting the entire admin deep into a k-hole that they will never escape from
Yeah, it's only our fault if they die a peaceful death instead of going to trial
Yes, code harnesses help by providing deterministic feedback like with a language server and reduce the amount of prompting requirements. I guess I should have led with that example 😅
The person I responded to said:
Also this is class/power issue not a gender issue.
No, it's not the same as copying and pasting the TODO into a prompt. Embedding the TODO in code instead of the prompt reduces tokens burned and increases accuracy because it's observing the TODO in context. Sure you can write more prompting to provide that context, but it still won't be as accurate. The less context you provide via prompting and instead provide more context through automatic deterministc feedback the better the results
The Romans enslaved their own (and other modern day "whites") so racism isn't required to make the analogy.
Examples to consider:
A code base with TODOs embedded will make fewer mistakes and spend less tokens than if you attempt to direct the LLM only with prompting.
A file system gives an LLM more context than a flat file (or large prompt) with the same contents because a file system has a tree like structure and makes it less likely the LLM will ingest context it doesn't need and confuse it
Lastly consider the efficacy of providing it tools vs using agent skills which is another form of prompting. Giving an LLM a deterministic feedback loop beats tweaking your prompts every time
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Right, but this is a democracy we are talking about. If half of the people participating are convinced the entire selection is no better than a random pick then that is very damning.