Those same things were said about hundreds of other technologies that no longer exist in any meaningful sense. Current usage of a technology, which in this specific case I would argue is largely frivolous anyway, is not an accurate indicator of future usage.
rigatti@lemmy.world 1 day ago
Can you give some examples of those technologies? I’d be interested in how many weren’t replaced with something more efficient or convenient.
kautau@lemmy.world 1 day ago
en.wikipedia.org/wiki/Dot-com_bubble
There were certainly companies that survived, because yes, the idea of websites being interactive rather than informational was huge, but everyone jumped on that bandwagon to build useless shit.
As an example, this is today’s ProductHunt
Image
And yesterday’s was AI, and the day before that it was AI, but most of them are demonstrating little value with high valuations.
LLMs will survive, likely improve into coordinator models that request data from SLMs and connect through MCP, but the investment bubble can’t sustain
themurphy@lemmy.ml 1 day ago
Technologies come and go, but often when a worldwide popular one vanishes, it’s because it got replaced with something else.
So lets say we need LLM’s to go away. What should that be? Impossible to answer, I know, but that’s what it would take.
We cant even get rid of Facebook and Twitter.
BUT that being said. LLMs will be 100x more efficient at some point - also like any other new technology. We are just not there yet.
glog78@digitalcourage.social 1 day ago
@themurphy @rigatti There is one difference ... LLM's can't be more efficient there is an inherent limitation to the technology.
https://blog.dshr.org/2021/03/internet-archive-storage.html
In 2021 they used 200PB and they for sure didn't make a copy of the complete internet. Now aks yourself if all this information without loosing informations can fit into a 1TB Model ?? ( Sidenote deepseek r1 is 404GB so not even 1TB ) ... local llm's usually < 16GB ...
This technology has been and will be never able to 100% replicate the original informations.
It has a certain use ( Machine Learning has been used much longer already ) but not what people want it to be (imho).