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Comment by infecto | Hacker News Reader

Dismissing an entire technology because you personally haven’t figured out how to make it useful is a cope, not an argument.

Am I rich? What are you even on about.

I can now spend a few dollars and classify a large dataset that would have taken me real time before. I can again spend a few dollars and turn unstructured data into structure. There absolutely is value to be found in the current gen of tech. Comparing it to crypto is a weak argument. Just because you don’t find value does not mean other organizations and people are not.

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>Am I rich? What are you even on about.

The only people I find harping on about some amorphous "value" floating around in the air are typically people with portfolios.

>I can again spend a few dollars and turn unstructured data into structure.

Saving 5 seconds on a 10 second task using an infinite amount more energy is not "value", it's garbage propped up by VC money and regular people are going to be paying for it when it inevitably goes tits up. Like we've paid for everything. There's your "value".

You’re confusing your frustration with some half-baked React scaffolding with the entire field. “Saving 5 seconds on a 10 second task” is just a strawman, there are workloads where it saves weeks, even months. If you can’t see that, fine, but don’t pretend your blind spot is universal truth.

And spare me the VC boogeyman. The fact that capital flows into bad bets doesn’t erase the actual wins. We’ve had garbage propped up before, railroads, dot-coms, mobile apps but guess what? Railroads exist, the internet exists, mobile exists. Same pattern here.

I would pay good money to be this green again. I talk about regular people, and you revert back to spreadsheet efficiency. Classic tech guy response, just cannot see a bigger picture.

“I’d pay good money to be this green again” just reads as bitterness dressed up as wisdom. You’ve offered zero substance beyond sneering at anyone who finds use in the tools. If your whole argument is “I don’t like it so it’s worthless,” that’s not insight, it’s just cope.

To save months the output would have to be reliable, but it isn't. It saves very little, especially at data input and coding.

It does save time for tasks where the output is easily checked, such as image generation and translations. But the quality is often mediocre.

I cannot say for your work but for classification steps and data structuring it’s quite accurate and this is with regular testing. I cannot speak for your work but for mine and folks in adjacent industries, LLM are fantastic and adding a lot of value to our workflows. You’re honestly holding on to this dead idea that LLM outputs are full of hallucinations. Throwaway account with throwaway comment.

It's "quite accurate" which is not acceptable for almost all relevant tasks is a business context. Somebody needs to manually check everything. Almost no time is saved.

Talking as someone who has built many small OpenAI integrations aka wrappers in business apps.

So I know you are trolling but let’s be real. Why would I share my business measurements with you on here? Of course my experience is an an anecdote and of course the measurements I use to determine accuracy are more in depth than “quite accurate”. What I can say is for structure we beat humans on accuracy and do it extremely quick. That LLM system runs at a lower cost than some of our more traditional system.

If all you have done is built wrappers I see you have bare scratches the engineering surface so that explains it.

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