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Comment by etempleton | Hacker News Reader

I think for many, if LLMs and AI only improves marginally in the next 5-10 years it is effectively a dead end. The capital expenditure necessitates AI does something exponentially more valuable than what it does now.

I think we are saying the same thing.i just think the pull back on AI will be dramatic unless something amazing happens very soon.

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I just don’t see it. Both professionally and personally I’m producing so much more now. Back burner projects that weren’t worth months of my time are easily worth a few hours and $20 or whatever.

Why would I pull back?

You're forgetting that the 20$ are not a sustainable price point. Would your backburner personal app thingy be worth 200$?

I’ve wondered about this too.

Perhaps if we used something exotic like solid gold cookware, there might be some amazing benefits that people would love.

But it would be far from practical without being wildly subsidized…

With AI, it feels too much like the “grownups” are acting worse than the kids…

Yes, I have often paid more than that to have someone else develop a personal side project.

Compute capacity for the same workload always gets cheaper over time.

No piece of compute capacity (in the form of equipment) I have bought this year has been in any way cheaper than last year.

So what. Fluctuations over a year or two are meaningless. Do you really believe that the constant-dollar price of an LLM token will be higher in 20 years?

I can see a world where energy costs rise at a rate faster than overall inflation, or are a leading indicator. In that scenario then yes I could see LLM token costs going up.

This is thoroughly debunked at this point. The frontier labs are profitable on the tokens they serve. They are negative when you bake in the training costs for the next generation.

Lol are people like you going to be enough to support the large revenues? Nope.

A firm that see's rising operating expenses but no not enough increase in revenue will start to cut back on spending on LLMs and become very frugal (e.g. rationing).

Before they cut back on human programmers?

You’re probably already experienced at your job and using AI to enhance that, or at least using that experience to keep the AI results clean. That’s something you or a company would want to pay for but it has to be a lot more than today’s prices to make it profitable. Companies want to get more out of you, or get a better price/performance ratio (an AI that delivers cheaper than the equivalent human).

But current gen AIs are like eternal juniors, never quite ready to operate independently, never learning to become the expert that you are, they are practically frozen in time to the capabilities gained during training. Yet these LLMs replaced the first few rungs of the ladder so human juniors have a canyon to jump if they want the same progression you had. I’m seeing inexperienced people just using AI like a magic 8 ball. “The AI said whatever”. [0] LLMs are smart and cheap enough to undercut human juniors, especially in the hands of a senior. But they’re too dumb to ever become a senior. Where’s the big money in that? What company wants to pay for the “eternal juniors” workforce and whatever they save on payroll goes to procuring external seniors which they’re no longer producing internally?

So I’m not too sure a generation of people who have to compete against the LLMs from day 1 will really be producing “so much more” of value later on. Maybe a select few will. Without a big jump in model quality we might see “always junior” LLMs without seniors to enhance. This is not sustainable.

And you enhancing your carpentry skills for your free time isn’t what pays for the datacenters and some CEO’s fat paycheck.

[0] I hire trainees/interns every year, and pore through hundreds of CVs and interviews for this. The quality of a significant portion of them has gone way down in the past years, coinciding with LLMs gaining popularity.

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