Edit: [*] 'we' in my comment here is indicating the HN community, not entirety of humanity.
Edit: [*] 'we' in my comment here is indicating the HN community, not entirety of humanity.
My own opinion is that the cats out of the bag so whatever's going to happen is going to happen wrt LLMs. But trying to shut down all criticism of a new thing just because you think it's cool is itself not cool.
And those little tots sure do look cute spinning the 'saws right?
That seems useful, prudent, and completely in line with the spirit if a community like HN.
There’s no more reason that every critique should come with a “proposal” than that every cheer should come with some kind of admonition. As a community, multiple points of view are expressed and developed simultaneously.
Of course, some of points of view might personally frustrate you or leave you feeling like you don’t know how to respond to them. But is that so bad? Does it need to be squelched just because you don’t enjoy it?
But that's not how any of this is discussed. That's where my scope comment comes from, the scope of every project cannot be "for everyone and 100% safe from the beginning". In this way there is no encouragement to discuss/make better things, just discouragement. I, personally, hate this.
But on the other hand, this is what the guidelines say
> Please don't post shallow dismissals, especially of other people's work. A good critical comment teaches us something.
I don't think these type of comments teach us anything. But these are guidelines and not rules for a reason.
Comments like the one at the root of this thread teach people that the current/approximate generation of LLM’s are poorly suited for certain kinds of tasks and remind us that many people don’t yet seem to understand what their systemic limitations are.
LLM’s are statistical models over their training data and aim responses mostly towards the most dense, data-rich, and redundant centers of their corpus. Summarizing novel, esoteric or or expert material is something they’re poorly suited for because it inherently has poor representation in that data.
Scoping is very constructive feedback.