Our mission is to raise AGI with the richness of human intelligence — curious, witty, imaginative, and full of unexpected brilliance.
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Last year, Google released their “GoEmotions” dataset: a human-labeled dataset of 58K Reddit comments categorized according to 27 emotions. The problem? A whopping 30% of the dataset is mislabeled! Check out some of the egregious errors, and learn how to build better datasets.30% of Google's Emotions Dataset is…
DAYJOB: Tax evaluates AI agents across 50 realistic tax environments, testing their ability to navigate messy records, exercise professional judgment, and deliver reliable tax work.
Would you trust a medical system whose only metric was “which doctor wins the Internet?” No, you'd call that malpractice. Yet that's LMArena.
Why can't Meta A/B test its way back to greatness? To move Instagram beyond short-term engagement metrics, we ran a personalized human evaluation asking 100 users to compare TikTok vs. Instagram Reels. Learn why Gen Z considers Reels the place where TikToks go to die, and what Instagram should do about it.
Are popular toxicity models simply profanity detectors? We show how toxicity models overweight profanity, and make mistakes when profanity is used in a positive way.
Where do human artists fit in a world of rich, creative AI? We asked 100 Surgers to draw the DALL-E prompts.