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I'm really getting over the enshitification of the internet. (lemmy.world)

submitted 10 months ago by Custoslibera to c/[email protected]

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[–] [email protected] 26 points 10 months ago (3 children)

There's certainly a bubble bursting. You only have to look at all the layoffs.fyi since COVID. I'm just hoping it's happening in a slow enough way that it's not going to take more legitimate companies with it.

AI is the next bubble. It will hit a brick wall either legally or just on functionality (maybe both). I can see uses for targeted models, bespoke to a use case, but training those is too expensive right now. General models are just toys IMHO. Unfortunately it's going to get a few years for everyone to realise.

[–] [email protected] 11 points 10 months ago

The brick wall on AI is not functionality. It's cost of running the neural networks. It's simply not financially realistic to integrate ChatGPT into everything.

[–] [email protected] 1 points 10 months ago

Ha, yeah sure, and trains will never go faster than 15mph.

Natural language computing is huge at the moment because it's a huge and significant development in computing - yes there are lots of shitty ai girlfriend apps and the same goes for generative ai there are lots of shitty art apps but human language interfaces aren't going away nor are generative design tools.

Even just the coding tools already available for free are a game changer, every single programmer I know and all the coding communities I'm in are using chatGPT regularly. When generative design gets into other areas such as cad and cam with natural language and problem solving (as in task based algorithms like the Go solver) then you'll start to see the how ubiquitous and significant these technologies are.

I understand why you'd look at the first commercial computers and think that no normal person will ever have a use for them but look at where we are now. The same is true for ai, current stuff is amazing when carefully worked and it takes a lot to get it all wired in but as the ecosystem of code grows and training sets become better established everything becomes much easier which enables more effective use cases.