Comment by goatlover
3 days ago
Personal anecdotes on the benefits of using LLMs don't address complaints about tedious articles over-marketing AI tech. That LLMs provide benefits is well known at this point, it doesn't mean we can't recognize the latest hype cycle for what it is. There's a long list of previous technologies that were going to "change everything".
Yes, of course, but they almost always did too. Internet. Mobile Phones.
I think the issue is whether you think that HN posts on AI are basically marketing, or about sharing new advances with a community that needs to be kept on top of new advances. Some posts are from a small startup trying something, or from a person sharing a tool. I think these are generally valuable. I might benefit from a RAG, but won't build one from scratch. In terms of this crowd, I can't think of advances that in other areas that are as impactful as machine learning lately. Its not like crypto. Crypto was an interesting innovation, but one in which mostly sought a market instead of the a market seeking an innovation. There is no solid "just use a database" analogical response here like was the well used refrain to attempt at practical uses of cryptocurrency tech. Sure, AI companies built on selling something silly like "the perfect algorithm to find you a perfect date!" is pure hackery, but even at the current level of llm, I don't think we are any where near understanding its full potential/application. So even if we are on the brink of an AI winter, its in the Bahamas.
Also, looking at the most popular stories with AI in the title over the last month show quite a varied array of topics. https://hn.algolia.com/?dateRange=pastMonth&page=0&prefix=fa...
If HN readers feel that AI-related articles are showing up too much, then I'd say it would be on them to find articles on topics that interest them and post them to HN.
surely it's not hype if it works?
No, hype is an over-presence and/or over-representation of the benefits. Just because there's a hint of truth to the sentiment does not mean there is no hype.
It is hype if it works but doesn't provide nearly enough revenue to cover the costs.