I guess because 99% of generated code will likely need significant edits, so you'd never want to commit direct "AI contributions" - you don't commit every time you take something from StackOverflow, likewise I wonder if people might start adding credit comments to LLMs?
> I guess because 99% of generated code will likely need significant edits
What are you guessing / basing this on?
I have many commits with zero human editing. The relative split is def well away from a 99% vs 1% at this point for any edits, most remaining edits for me are only minor, not "significant"
OP here: I had the same thought, but noticed a very similar trend in both [0]; I think this graph is more interesting because you'd expect the number of new users to be growing [1], but this seems to have very little effect on deleted questions or even answers
The second graph here ([1]) is especially interesting because the total montly number of new users seems completely unrelated to number of posts, until you filter for a rep > 1 which has a close to identical trend
It's great for a prototype which doesn't need to store a huge amount of data, you can run it on the same VM as a node server behind Cloudflare and get a fairly reliable setup going
I really like this reactive guide style interface, which maybe could be quite a good project idea like mdBook[1] but also you to insert quizzes/examples alongside static notes
I had the same thought - I guess it's similar to that idea that if you had someone else's eyes, you might not perceive specific colours to be the same?
But actually it sort of makes sense since (from what I understand) is stimulating an external interface (the receptors), so you're mimicing what the effect a smell would have on you rather than the electrical signal created by the response to a stimulus?
It's a measure of time spent working on something, to standardise comparisons of work capacity and acknowledge that it's not always full time, especially when aggregating the time from different people. One full time person = 1 FTE.
For example if you work 20 hours a week on project A and 20 hours on project B, then project A will count your contribution as 0.5 FTE while you're assigned to that project.
If you also have two other people working on it full timee, and a project manager working 1 day a week on it, then project A will count the contribution from all three of you as 2.7 FTE. (2.7 = 0.5 + 2 + 0.2).
This example assumes 1fte=40 hours which is not nexessarily the case in all countries or under all collective agreements. 1fte can be 36, 38, or even 48 hours.
Yes, but that is usually more relating to pay/benefits. At google (from what I heard) contractors are put on the bad projects, maintenance work or support functions. As in there is a big separation between work done by full-time employees and contractors in most teams.
I think FTE is mostly used as a 'unit'. E.g. if two people work on something 50% of the time, you get one "FTE-equivalent", as there is roughly one full-time employee of effort put in.
Though in this context it just seems to be the number of people working on the code on a consistent basis.
* “Full Time Employee” (which can itself mean “not a part-timer” in a place that employs both, or “not a temp/contractor” [in which case the “full-time” really means “regular/permanent”]) or
* “Full Time Equivalent” (a budgeting unit equal to either a full time worker or a combination of part time workers with the same aggregate [usually weekly] hours as constitute the standard for full-time in the system being used.)
The MS Azure deal is of the same nature. MS “invests” into OpenAI who then buys Azure services for the investment. OpenAI evaluation is increased and the musical chairs will continue for another round.
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