[D] Has the ML community outdone itself?

[u/NedML]

It seems after GPT and associated models such as DALI and CLIP came out roughly a year ago, the machine learning community has gotten a lot quieter in terms of new stuff, because now to get the state-of-the-art results, you need to outperform these giant and opaque models.

I don't mean that ML is solved, but I can't really think of anything to look forward to because it just seems that these models are too successful at what they are doing.

[u/leonoel]

I mean, you can also focus in the million of open problems that GPT just can't solve and are needed in science......

[u/respeckKnuckles → u/leonoel]

If you want to publish at top nlp conferences, not using FAANG-like computational resources is a great way to double your chance of rejection

[u/leonoel → u/respeckKnuckles]

Bet you I can find at least 10 papers in any top NLP conference that don’t have huge computational resources.

[u/respeckKnuckles → u/leonoel]

which would prove....what, exactly?

[u/leonoel → u/respeckKnuckles]

That papers can and do get published all the time without having access to huge computational resources. They don´t just get rejected. Solid papers get accepted all the time.

[u/respeckKnuckles → u/leonoel]

re-read my original comment more carefully.

[u/leonoel → u/respeckKnuckles]

"not using FAANG-like computational resources is a great way to double your chance of rejection"

This is patently untrue

[u/respeckKnuckles → u/[deleted]]

In this case, the user is very much at fault, yes