[dvt]

I wish this kind of low-effort lazy AI "content" would stop making it to the top of HN day after day. In any case, the piece is clearly an ad for Apricot. The examples cited in the article are so pedestrian, it's hardly even worth discussing.

How can you even seriously think that asking GPT for a function that parses OPML is a "realistic" task. I can just Google it and get like 100 pages of Python functions that do exactly that.

[OkGoDoIt]

Personally I found the comparison useful and relatable. I could imagine wanting to accomplish these exact same tasks and wanting to know which language model would be best. And in general I like this qualitative analysis rather than the metrics we get in official releases and research papers which often don’t capture real world use very well. I can’t exactly begrudge the author for killing two birds with one stone here, it’s better than some completely made up use case that’s completely theoretical.

[mkrishnan]

I think this comparisons cover use cases of 99.9999999% of people. As you said, if you are using bard, you will be forced to Google it anyway. Bard is just designed to be not helpful.