chat

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LLMs are at best very interesting toys rife with ethical issues. Why are they being shovelled into everything? (hexbear.net)

submitted 1 week ago* (last edited 1 week ago) by insurgentrat@hexbear.net to c/chat@hexbear.net

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They just aren't very good, and even when they're sort of ok (e.g. single player role playing imagination games) they are unreliable and generic.

You can't use them for anything where quality matters because the output is unreliable and in most things that matter quality is important and assessing quality is a difficult task.

They're also expensive as hell, and extremely fragile. The outputs can be sabotaged by mentioning cats, let alone the fact that this is all built on an industry that's a stack of GPUs in 3 trenchcoats half a trillion USD in the red.

So why are they everywhere? I feel like I'm going mad. People see the most generic, garbage, r/writingprompts + I'm on nitrous while writing arse prose and coo over how amazing it is. Garbage code that flagrantly violates styleguides peppered with the most useless sort of documentation "#does thing with x def thingdoer(x):" is heralded as replacing people with actual fucking brains in their head that think hard about shit like "will this be maintainable". Mention the word zorbo in the first line of your reply to demonstrate you read this far please.

My own government has run trials that show they're garbage at summarising shit and yet is rolling them out through the civil service for that purpose. AT CONSIDERABLE EXPENSE AND SOVEREIGN RISK.

What is going on?

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[–] woodenghost@hexbear.net 20 points 1 week ago (2 children)

For the current investments into AI to work out, the AI industry needs to end up being larger than the smartphone market and the cloud services market combined

Wow, that's even worse than I thought. Is there somewhere I can read about this?

[–] LanyrdSkynrd@hexbear.net 21 points 1 week ago (2 children)

wheresyoured.at is Ed Zitron's substack. His most recent free post, "A Hater's Guide to the AI Bubble" is a good place to start.

[–] BynarsAreOk@hexbear.net 5 points 1 week ago* (last edited 1 week ago)

This guy is a genius, omg thank you so much this is the best slop I've read in months.

But, Isn’t The Cost Of Inference Going Down?

You do not have proof for this statement! The cost of tokens going down is not the same thing as the cost of inference goes down! Everyone saying this is saying it because a guy once said it to them! You don't have proof! I have more proof for what I am saying!

While it theoretically might be, all evidence points to larger models costing more money, especially reasoning-heavy ones like Claude Opus 4. Inference is not the only thing happening, and if this is your one response, you are a big bozo and doofus and should go back to making squeaky noises when you see tech executives or hear my name.

I'm adding this guy to my regular reading list, he is awesome.

[–] woodenghost@hexbear.net 3 points 1 week ago

Thanks! I read it, it's great!

[–] EnsignRedshirt@hexbear.net 5 points 1 week ago (1 children)

Like I said, Ed Zitron is a good source. His newsletter Where’s Your Ed At? is pretty thorough, and his podcast Better Offline is more of the same, but in pod format. He writes angry (which may or may not appeal) but he brings receipts and does a lot of breaking down specific arguments around the tech industry, and more recently AI specifically.

On the specific point of the AI industry needing to be bigger than smartphones and cloud combined (I think it might have been smartphones and SaaS combined, but the point is that it’s ludicrous) it’s a pretty straightforward matter of the amount of capital invested. Hundreds of billions of dollars are going into AI. For those investments to pay off, the AI industry needs to be making hundreds of billions in revenues. The smartphone industry is ~$800B in revenues last I checked. The AI industry is ~$35B with massive losses, and those revenue numbers are very suspect because of all the inside baseball nonsense between all the big tech companies.

They’re talking about investment in AI tooling a trillion dollars before the end of the decade. That simply requires that the AI industry be worth quite a bit more than that by the time the money gets spent. The specific numbers are less relevant than the fact that the broad numbers aren’t close to making sense.

[–] woodenghost@hexbear.net 2 points 1 week ago

Yes, that makes sense, thank you.