Earlier quoted context omitted.
Not going to leak my tests, but here's how you can create your own. - Think up a topic that's interesting to you, yet maybe controversial. - Look up primary sources and empirical information about it. - Then look at a relevant Wikipedia article about it to see if the way the Wikipedia article frames it is honestly and faithfully justified by the primary sources and empirical data about it. If the article seems to hav…
I don't get it. If I think that Rabbits and Hares are classified by Wikipedia incorrectly and Ideological Wikipedia Editors are hiding the truth with Disinformation, why would I give the model any credit if it tells the correct answer only if I develop a custom 22 point mammalian biology reasoning checklist that leads it to the Real Truth about Rabbits and Hares? It certainly doesn't inspire confidence that any other…
Magistral — the first reasoning model by Mistral AI
441–444 of 444 posts
Re: Magistral — the first reasoning model by Mistral AI
#442Earlier quoted context omitted.
You’re being downvoted but you’re right. The number of people who act like a web cam reproduces the in person experience perfectly, for good and bad, is hilarious to me.
I think the mistake people make is believing that one approach is best for all. Diffferent people work most effectively in different ways.
Re: Magistral — the first reasoning model by Mistral AI
#443Re: Magistral — the first reasoning model by Mistral AI
#444Earlier quoted context omitted.
Mostly "How is $term in English", what is $thing, review this message for clarity, clean up this data, parse this screenshot, and coding.
I see! So for these, you tend to find the accuracy "good enough" on the faster-but-less-accurate models. I generally find the same thing for simple definitions/translations and other "chat" tasks. I'm a little bit surprised that you also find it so for coding, but otherwise I think I get it.