[wruza]

I’m conflicted about your comment. On one hand, I agree, useless reductions are boring. But on the other, we are living in the “overselling all up in your ears” epoch, which is known to sell pffts as badabooms. So it isn’t baffling to me that a new tech gets old quickly, because it’s not really what was advertised. Our decades-old ideas of AI weren’t feasible a decade ago, but neither are these now. Those who believe in that too much become hu.ma.ne founders and similar self-bullshitters.

[TeMPOraL]

You're right about "living in the “overselling all up in your ears” epoch", but a good first defense against "being sold pffts as badabooms" is to blanket distrust all the marketing copy and whatever the salespeople say, and rely on your own understanding or experience. You may lose out on becoming an early adopter of some good things, but you'll also be spared wasting money on most garbage.

With that in mind, I still don't get the dismissal. LLMs are broadly accessible - ever since the first ChatGPT, anyone could easily get access to a SOTA LLM and evaluate it for free; even the limited number of requests on free tiers were then, and now are, sufficient to throw your own personal and professional problems at models and see how they do. Everyone can see for themselves this is not hot air - this is an unexpected technological breakthrough that's already overturning way people approach work, research and living, and it's not slowing down.

I'd say: ignore what the companies are selling you - especially those who are just building products on top of LLMs and promising pie in the sky. At this point in time, they aren't doing anything you couldn't do for yourself with ChatGPT or Claude access[0]. We are also beginning to map out the possibilities - two years since the field exploded is very little time. So in short, anything a business does, you could hack yourself - and any speculative idea for AI applications you can imagine, there's likely some research team working on it too. The field is moving both absurdly fast and absurdly slow[1]. So your own personal experience over applying LLMs to your own problems, and watching people around you do the same, is really all you need to tell whether LLMs are hot air or not.

My own perspective from doing that: it's not hot air. The layer of hype is thin, and in some areas the hype is downplaying the impact.

--

[0] - Yes, obviously a bunch of full-time professionals are doing much more work than you or me over couple evenings of playing with ChatGPT. But they're building a marketable product, and 99% of work that goes into that is something you do not need to do, if you just want to replicate the core functionality for yourself.

[1] - I mean, Anthropic just published a report on how exposing "thinking" capability to the model in form of a tool call leads to improvement of performance. On the one hand, kudos to them for testing this properly and publishing. On the other hand, that this was something to do was stupidly obvious ever since 1) OpenAI introduced function calling and 2) people figured out "Let's think step by step" improves model performance - which was back in 2022[2]. It's as clear example as ever that both hype and productization lag behind what anyone paying attention can do themselves at home.

[2] - https://arxiv.org/abs/2205.11916

[wruza]

Idk, I find their output mediocre and sometimes misleading. But that’s not the worst part and is often cheaper than doing things yourself.

The worst part is https://news.ycombinator.com/item?id=43314958 . We may be still blind to this, but new generations may find themselves on the other side of the fence, so to say.

[TeMPOraL]

IDK, I think the linked comment is right. LLMs drop some of the barriers to experimentation so much, that previously rejected project ideas may just become worth trying out (especially when we're talking about hobby or research ideas, not full products). It also has the same effect on ideas you may have now, that before you'd reject as "too much work".

Case in point: my wife needed a QR code generator so she could stop asking me every time she needs to make some codes. There are tons of such generators out there - webapps, mobile apps, downloadable programs, plugins to graphics software, etc. But the software world is such a pile of shit that I don't trust any single one of them - experience shows that most random utility software like this is ad-ridden garbage or malware.

Before a year ago, I'd just invest time to try and evaluate some solutions, find one that's least likely to record inputs, or show ads, or inject redirects into generated code, or run excessive surveillance of your phone, etc. But since this need manifested last week, I just asked Claude to make me a client-side generator up to my specific needs, and quickly got a static page with (vendored) JS library, to host from a domain I own.

There's tons of super-specific or one-off utilities a person could use to help them with some task - utilities that make no sense as products, and if they exist, they're just loaded with ads and garbage. LLMs today make it feasible to just get the computer to write you such utilities from scratch, on demand, which guarantees they're garbage-free.