do you really think that an architecture that struggles to count r in strawberry is a good choice for proofreading? It perceives words very differently from us.
Counting letters in words and identifying when words are misspelled are two different tasks - it can be good at one and bad at the other.
Interestingly, spell checking is something models have been surprisingly bad at in the past - I remember being shocked at how bad Claude 3 was at spotting typos.
This has changed with Claude 4 and o3 from what I've seen - another example of incremental model improvements swinging over a line in terms of things they can now be useful for.
Wasn't expecting a "you're a shill" accusation to show up on a comment where I say that LLMs used to suck at spell check but now they can just about do it.
So 2 trillion dollars to do what Word could do in 1995... and trying to promote that as an advancement is not propaganda? Sure let's double the amount of resources a couple more times who knows what it will be able to take on after mastering spelling.
Yes, actually I think it works really well for me considering that I’m not a native speaker and one thing I’m after is correcting technical correct but non-idiomatic wording.
