this post was submitted on 13 Aug 2025
35 points (100.0% liked)

Technology

3964 readers
260 users here now

Which posts fit here?

Anything that is at least tangentially connected to the technology, social media platforms, informational technologies and tech policy.


Post guidelines

[Opinion] prefixOpinion (op-ed) articles must use [Opinion] prefix before the title.


Rules

1. English onlyTitle and associated content has to be in English.
2. Use original linkPost URL should be the original link to the article (even if paywalled) and archived copies left in the body. It allows avoiding duplicate posts when cross-posting.
3. Respectful communicationAll communication has to be respectful of differing opinions, viewpoints, and experiences.
4. InclusivityEveryone is welcome here regardless of age, body size, visible or invisible disability, ethnicity, sex characteristics, gender identity and expression, education, socio-economic status, nationality, personal appearance, race, caste, color, religion, or sexual identity and orientation.
5. Ad hominem attacksAny kind of personal attacks are expressly forbidden. If you can't argue your position without attacking a person's character, you already lost the argument.
6. Off-topic tangentsStay on topic. Keep it relevant.
7. Instance rules may applyIf something is not covered by community rules, but are against lemmy.zip instance rules, they will be enforced.


Companion communities

!globalnews@lemmy.zip
!interestingshare@lemmy.zip


Icon attribution | Banner attribution


If someone is interested in moderating this community, message @brikox@lemmy.zip.

founded 2 years ago
MODERATORS
top 23 comments
sorted by: hot top controversial new old
[–] spankmonkey@lemmy.world 21 points 2 weeks ago* (last edited 2 weeks ago) (1 children)

By design, LLMs can get faster but cannot be more accurate without a massive intentional approach to verifying their datasets, which isn't feasible because that would counter anything not fact based as LLMs don't understand context. Basically, the training approach means that they get filled with whatever the builders can get their hands on and then they fall back to web searches which return all kinds of unreliable stuff because LLMs don't have a way of verifying reliability.

Even if they were perfect, they will not be able to keep up with the content flood of new information that comes out every minute when used as general purpose answer anything tools.

What AI actually excels at is pattern matching in controlled settings.

[–] slate@sh.itjust.works 17 points 2 weeks ago (2 children)

And now, lots of web searches return results of AI SEO slop chock full of incorrect information, which then fules subsequent training sets and LLM web searches and creates a negative feedback loop that could destroy the internet.

[–] spankmonkey@lemmy.world 11 points 2 weeks ago

The AI SEO slop is already destroying the internet, although that negative feedback loop is certainly accelerating it.

[–] Ramblingman@lemmy.world 1 points 1 week ago

Apparently gpt-5 is much worse, or so the subreddit dedicated to it says. I wonder if that loop has already started?

[–] givesomefucks@lemmy.world 9 points 2 weeks ago (1 children)

They're operating under the long outdated assumption that all you need to simulate a brain is match the number of neurons....

That's not how any of this works, but they've been saying "we'll be there soon" for so long now that we're almost able to do it, their gonna lose their main excuse and main reason for fundraising.

They'll have to tell investors the timeline just changed from years to maybe decades if we're lucky

And it's gonna divebomb our whole economy because fucking every fund manager is dumping insane levels of money into it.

[–] Perspectivist@feddit.uk 0 points 2 weeks ago

Which AI company has taken this approach exactly? Whose this "they" you're refering to?

[–] Perspectivist@feddit.uk 7 points 2 weeks ago (3 children)

I think the title should be "What if LLMs doesn't get much better than this?" because that's effectively what the article is talking about. I see no reason to expect that our AI systems wouldn't keep improving even if LLMs don't.

[–] mindbleach@sh.itjust.works 3 points 2 weeks ago

Neural networks becoming practical is world-changing. This lets us do crazy shit we have no idea how to program sensibly. Dead-reckoning with an accelerometer could be accurate to the inch. Chroma-key should rival professional rotoscoping. Any question with a bunch of data and a simple answer can be trained at some expense and then run on an absolute potato.

So it's downright bizarre that every single company is fixated on guessing the next word with transformers. Alternatives like text diffusion and mamba pop up and then disappear, without so much as a 'so that didn't work' blog post.

[–] kkj@lemmy.dbzer0.com 2 points 1 week ago

Yeah, I think LLMs are close to their peak. Any new revolutionary developments in LLMs will probably be in efficiency rather than capability. Something that can actually think in a real sense will probably happen eventually, though, and unless it's even more absurdly resource-intensive it'll probably replace LLMs in everything but autocomplete (since they're legitimately good at that).

[–] theneverfox@pawb.social 0 points 1 week ago

I think that's true, but also missing the point... We've hit the peak of AI until the next transformative breakthrough

They're still fucking magic. They're really cool and useful, when you use them correctly.

But chat gpt 5 isn't much better than 3.5. It's a bit better, it requires less prompt engineering to get good results, it gives more consistent results... But it's still unreliable. And weirdly likes to talk down to you now, as if I don't know more than it...I am still the expert here, it's a light speed intern, it doesn't know what's going on

[–] mindbleach@sh.itjust.works 2 points 2 weeks ago

Some guy blogged that the smart ones move to advertising.

[–] m532@lemmygrad.ml 1 points 1 week ago

That's what they always say, and then... new stuff

Qwen-Image (diffusion with a LLM as text encoder) came out 10 days ago and it understands the prompt like 20x better, than, for example, SDXL Turbo