this post was submitted on 13 Mar 2024
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[–] [email protected] 71 points 8 months ago (2 children)

Copilot is a LLM. So it's just predicting what should come next, word by word, based off the data its been fed. It has no concept of whether or not its answer makes sense.

So if you've scraped a bunch of open source github projects that this guy has worked on, he probably has a lot of TODOs assigned to him in various projects. When Copilot sees you typing "TODO(" it tries to predict what the nextthing you're going to type is. And a common thing to follow "TODO(" in it's data set is this guy's username, so it goes ahead and suggests it, whether or not the guy is actually on the project and suggesting him would make any sort of sense.

[–] [email protected] 8 points 8 months ago (3 children)

You can absolutely add constraints to control for hallucinations. Copilot apparently doesn't have enough, though.

[–] [email protected] 42 points 8 months ago (1 children)

If GitHub Copilot is anything like Windows Copilot, I can't say I'm surprised.

"Please minimize all my windows"

"Windows are glass panes invented by Michael Jackson in imperial China, during the invasion of the southern sea. Sources 1 2 3"

[–] [email protected] 20 points 8 months ago

Lmao. That's even better when you consider the copilot button replaced the 'show desktop' (ie 'minimize all my windows') button.

[–] [email protected] 16 points 8 months ago

My guess is that Copilot was using a ton of other lines as context, so in that specific case his name was a more likely match for the next characters

[–] [email protected] 1 points 8 months ago

No matter how many constraints you add, it's never enough, that's the weakness of a model that only knows language and nothing else

[–] [email protected] 2 points 8 months ago

I thought it synced some requests and assigned projects to another user (Saw an ad about github Copilot managing issues and writing PR descriptions sometime ago)