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0 pointssublinear26d ago0 comments

Already covered in the post.

> So this is inherent to the technology. No amount of tokenmaxxing is going to change it. LLM development even breaks common and well accepted quality norms in software development - like backwards compatibility. You literally can’t (and wouldn’t want!) an LLM to do the same thing in the same way twice. But this means, LLMs - on their own - are not a solid foundation to build a revolution on. They never can be.

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5 comments · 2 top-level

northstar70226d ago· 2 in thread

Fair. I suppose, the question behind my question is -- what else do we need. Thanks.

sublinearOP25d ago

Yeah I have a different take. We will end up scaling human output by hiring more devs as wages for entry to mid level continue to stagnate.

I think LLMs make finding information and learning way more accessible. Even with realistic expectations it already is a revolution for literacy, education, and search. LLMs are a massive achievement that would be celebrated appropriately if only the public wasn't introduced to them during global political/economic crises encouraging grifters and authoritarians muddying the waters.

To be clear, hiring at scale is a sorely needed step. Software is just like any other form of writing. It carries weight and needs cultural and community context to work. We have needed way more technical literacy for decades to make this digital always-on world work. I think most would at least agree that LLMs bridge knowledge gaps. They're a net good thing despite the current abuse by bad actors.

northstar70225d ago

Looking forward to that hiring. So far, just layoffs. That said, there reports that consulting firms are hiring to fuel the demand around AI adoption itself. LLMs are a breakthrough like machines were. We will create new business models around them, and perhaps drives more humans. Wrt software, LLMs can make learning very easy. But with all the AI generated code, who is the "architect"?

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piotrkaminski25d ago· 1 in thread

I thought this was the weakest argument in the article. Yes, non-determinism is inherent to LLMs. It's also inherent to human brains, yet somehow we still manage to call (some) people reliable.

The bit about backwards compatibility doesn't make sense either. LLMs, just like humans, can take backwards compatibility into consideration — or not. Sometimes they'll forget, and sometimes they'll fixate on it even in a system that hasn't been deployed yet. It has nothing to do with LLMs never doing "the same thing the same way twice".

LLMs may or may not become as reliable as other productivity-improving infrastructure, but it's not the nature of their technology that will decide this.

oudlys18d ago

Human brains can explain themselves. What's a black box about LLMs is that they can't. They don't know how they arrived. They didn't arrive at anything. They don't have access to their internal representations. They don't think.

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