A non-anthropomorphized view of LLMs

I have the technical knowledge to know how LLMs work, but I still find it pointless to not anthropomorphize, at least to an extent.

The language of "generator that stochastically produces the next word" is just not very useful when you're talking about, e.g., an LLM that is answering complex world modeling questions or generating a creative story. It's at the wrong level of abstraction, just as if you were discussing an UI events API and you were talking about zeros and ones, or voltages in transistors. Technically fine but totally useless to reach any conclusion about the high-level system.

We need a higher abstraction level to talk about higher level phenomena in LLMs as well, and the problem is that we have no idea what happens internally at those higher abstraction levels. So, considering that LLMs somehow imitate humans (at least in terms of output), anthropomorphization is the best abstraction we have, hence people naturally resort to it when discussing what LLMs can do.

On the contrary, anthropomorphism IMO is the main problem with narratives around LLMs - people are genuinely talking about them thinking and reasoning when they are doing nothing of that sort (actively encouraged by the companies selling them) and it is completely distorting discussions on their use and perceptions of their utility.

When I see these debates it's always the other way around - one person speaks colloquially about an LLM's behavior, and then somebody else jumps on them for supposedly believing the model is conscious, just because the speaker said "the model thinks.." or "the model knows.." or whatever.

To be honest the impression I've gotten is that some people are just very interested in talking about not anthropomorphizing AI, and less interested in talking about AI behaviors, so they see conversations about the latter as a chance to talk about the former.

Wait until a conversation about “serverless” comes up and someone says there is no such thing because there are servers somewhere as if everyone - especially on HN -doesn’t already know that.

Why would everyone know that? Not everyone has experience in sysops, especially not beginners.

E.g. when I first started learning webdev, I didn’t think about ‘servers’. I just knew that if I uploaded my HTML/PHP files to my shared web host, then they appeared online.

It was only much later that I realized that shared webhosting is ‘just’ an abstraction over Linux/Apache (after all, I first had to learn about those topics).

I am saying that most people who come on HN and say “there is no such thing as serverless and there are servers somewhere” think they are sounding smart when they are adding nothing to the conversation.

I’m sure you knew that your code was running on computers somewhere even when you first started and wasn’t running in a literal “cloud”.

It’s about as tiring as people on HN who know just a little about LLMs thinking they are sounding smart when they say they are just advanced autocomplete. Both responses are just as unproductive

> I’m sure you knew that your code was running on computers somewhere even when you first started and wasn’t running in a literal “cloud”.

Meh, I just knew that the browser would display HTML if I wrote it, and that uploading the HTML files made them available on my domain. I didn’t really think about where the files went, specifically.

Try asking an average high school kid how cloud storage works. I doubt you’ll get any further than ‘I make files on my Google Docs and then they are saved there’. This is one step short of ‘well, the files must be on some system in some data center’.

I really disagree that “people who come on HN and say “there is no such thing as serverless and there are servers somewhere” think they are sounding smart when they are adding nothing to the conversation.” On the contrary, it’s an invitation to beginning coders to think about what the ‘serverless’ abstraction actually means.