11–19 of 19 posts
Unless I am repeatedly missing it, it’s not mentioned in the article how much money the researchers spent performing the tests. What was the budget for the AI execution? If the researchers only spent $10,000 to “earn” $400,000, that’s amazing, whereas if they spent $500,000 for the same result, that’s obviously less exciting.
There goes all the low-hanging fruit ...
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I haven't really messed with Claude or other programming AIs much, but when using chatgpt for random stuff, it seems like the safety rails end up blocking a lot of stuff and rephrasing to get around them is necessary. I wonder if some of these programming AIs would be more useful if it some of the context that causes them to produce invalid results was more obvious to the users.
> safety rails end up blocking a lot of stuff curious if you had any examples. i'm fairly meh on llm coding myself but have a pet theory on safety rails. i've certainly hit plenty myself but not with coding with llm's.
If you knew what some of those preferences and rails were ahead of time, it'd be easier to design your request and also know why it making some odd or unworkable suggestions.
Unless I am repeatedly missing it, it’s not mentioned in the article how much money the researchers spent performing the tests. What was the budget for the AI execution? If the researchers only spent $10,000 to “earn” $400,000, that’s amazing, whereas if they spent $500,000 for the same result, that’s obviously less exciting.
And did they actually earn anything, or did they just evaluate the performance and linked it to a fee?
Earlier quoted context omitted.
And did they actually earn anything, or did they just evaluate the performance and linked it to a fee?
Totally. Solving the coding task is just half the challenge. You still got to win the job, etc
Earlier quoted context omitted.
Totally. Solving the coding task is just half the challenge. You still got to win the job, etc
Not only win the job. Deal with management, process, meetings...