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[-] CerealKiller01@lemmy.world 31 points 1 day ago

Huh?

The smartphone improvements hit a rubber wall a few years ago (disregarding folding screens, that compose a small market share, improvement rate slowed down drastically), and the industry is doing fine. It's not growing like it use to, but that just means people are keeping their smartphones for longer periods of time, not that people stopped using them.

Even if AI were to completely freeze right now, people will continue using it.

Why are people reacting like AI is going to get dropped?

[-] Ultraviolet@lemmy.world 3 points 1 day ago

Because novelty is all it has. As soon as it stops improving in a way that makes people say "oh that's neat", it has to stand on the practical merits of its capabilities, which is, well, not much.

[-] theherk@lemmy.world 7 points 1 day ago

I’m so baffled by this take. “Create a terraform module that implements two S3 buckets with cross-region bidirectional replication. Include standard module files like linting rules and enable precommit.” Could I write that? Yes. But does this provide an outstanding stub to start from? Also yes.

And beyond programming, it is otherwise having positive impact on science and medicine too. I mean, anybody who doesn’t see any merit has their head in the sand. That of course must be balanced with not falling for the hype, but the merits are very real.

[-] Eccitaze@yiffit.net 5 points 1 day ago

There's a pretty big difference between chatGPT and the science/medicine AIs.

And keep in mind that for LLMs and other chatbots, it's not that they aren't useful at all but that they aren't useful enough to justify their costs. Microsoft is struggling to get significant uptake for Copilot addons in Microsoft 365, and this is when AI companies are still in their "sell below cost and light VC money on fire to survive long enough to gain market share" phase. What happens when the VC money dries up and AI companies have to double their prices (or more) in order to make enough revenue to cover their costs?

[-] obbeel@lemmy.eco.br 1 points 6 hours ago

I understand that it makes less sense to spend in model size if it isn't giving back performance, but why would so much money be spent on larger LLMs then?

[-] theherk@lemmy.world 2 points 23 hours ago

Nothing to argue with there. I agree. Many companies will go out of business. Fortunately we’ll still have the llama3’s and mistral’s laying around that I can run locally. On the other hand cost justification is a difficult equation with many variables, so maybe it is or will be in some cases worth the cost. I’m just saying there is some merit.

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this post was submitted on 13 Nov 2024
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