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Joined 1 year ago
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Cake day: September 27th, 2023

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  • Re LLM summaries: I’ve noticed that too. For some of my classes shortly after the ChatGPT boom we were allowed to bring along summaries. I tried to feed it input text and told it to break it down into a sentence or two. Often it would just give a short summary about that topic but not actually use the concepts described in the original text.

    Also minor nitpick but be wary of the term “accuracy”. It is a terrible metric for most use cases and when a company advertises their AI having a high accuracy they’re likely hiding something. For example, let’s say we wanted to develop a model that can detect cancer on medical images. If our test set consists of 1% cancer inages and 99% normal tissue the 99% accuracy is achieved trivially easy by a model just predicting “no cancer” every time. A lot of the more interesting problems have class imbalances far worse than this one too.






  • after leaving can’t join another for a year

    Can you fix this? There was enough misinformation floating around about this already when this feature went into beta.

    Adults can leave a family at any time, however, they will need to wait 1 year from when they joined the previous family to create or join a new family.

    it should say something like: “After joining, can’t join another for a year”




  • This exact image (without the caption-header of course) was on one of the slides for one of the machine-learning related courses at my college, so I assume it’s definitely out there somewhere and also was likely part of the training sets used by OpenAI. Also, the image in those slides has a different watermark at the bottom left, so it’s fair to assume it’s made its rounds.

    Contradictory to this post, it was used as an example for a problem that machine learning can solve far better than any algorithms humans would come up with.