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feat: update export dataset with new user posts and statistics for 143 active users - Refresh export/0_dataset.txt with updated user counts (143 active, 4281 total contributions) and recalculated IHateForALiving stats (387 contributions, 0.58% share) - Append new posts to user files: 12bitfloat (Advent of Code discussion, rayon performance), Chewbanacas (pets plugin, discipline vs talent), Davidson2021 (thank you reply), Demolishun (carry weight, power supply, emotion control), IHateForALiving (cat decoration, Puff tagging), Lensflare (Amazon guess, old people scrolling feature) - Add three new comment period graphs (comments_per_day, comments_per_hour, comments_per_weekday from 2024-11-07 to 2024-12-05) - Update compiled graphs image and binary wheel/source distribution to version 1.3.37
2024-12-05 23:12:12 +01:00
Strawberry1102 said Yes, LLMs can sometimes provide inaccurate or incomplete information, but this isn't unique to them. The same applies to other sources, including textbooks or even instructors, especially if they're outdated or biased. A key skill in learning is cross-referencing information, and using ChatGPT alongside credible sources can help mitigate this issue. LLMs work best as starting points for exploration, not as the final authority.```
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