This is ok. 90% of research is creative thinking, dialogue. One idea creates the next, some are a foil, some are dead ends. As long as there are not outrageous claims being made for 'hard evidence' where there is none, it's fine. Maybe the format isn't fully appropriate but the content is. Most good things come about in a non-linear process which involves provocation along the line somewhere.

I expect science to have a hypothesis which can be falsified. Otherwise it’s just opining on a topic. Otherwise we could just call this HN thread “research”.

Position papers are exceedingly common. Common enough that there's a term for them.

Science is 80% discussion, opining, thinking, reading etc.

A lot of areas are made up of those things. Theology, for example. What sets science apart is testable hypotheses.

This is generally my feeling as well with the paper.

You don't come out feeling "Voila! this tiny thing I learnt is something new", which does happen often with many good papers. Most of the paper just felt a bit anecdotal & underwhelming (but I may be too afraid to say the same on Twiiter for good reason)

I don't know, without enumerating risks to check, there's little basis for doing due diligence and quelling investors. This massively-cited paper gave a good point of departure for establishing rigorous use of LLMs in the real world. Without that, they're just an unestablished tech with unknown downsides - that's harder to get into true mass acceptance outside the SFBA/tech bubble.

Why would there be a falsifiable hypothesis in it? Do you think that's a criterion for something being a scientific paper or something? If it ain't Popper, it ain't proper?

LLMs dramatically lower the bar for generating semi-plausible bullshit and it's highly likely that this will cause problems in the not-so-distant future. This is already happening. Ask any teacher anywhere. Students are cheating like crazy, letting chatGPT write their essays and answer their assignments without actually engaging with the material they're supposed to grok. News sites are pumping out LLM-generated articles and the ease of doing so means they have an edge over those who demand scrutiny and expertise in their reporting—it's not unlikely that we're going to be drowning in this type of content.

LLMs aren't perfect. RLHF is far from perfect. Language models will keep making subtle and not-so-subtle mistakes and dealing with this aspect of them is going to be a real challenge.

Personally, I think everyone should learn how to use this new technology. Adapting to it is the only thing that makes sense. The paper in question raised valid concerns about the nature of (current) LLMs and I see no reason why it should age poorly.