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AI's Affordability Crisis

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Re: AI's Affordability Crisis

#431

Post by zhivota »

Gigachad wrote: post #336
zhivota wrote: post #330

Earlier quoted context omitted.

I don't see why 3 years is the right number there. I'm using a 10 year old model GPU to generate tokens locally, and given the bottlenecks, a commercial model focused on RAM and transfer speeds should have a longer depreciation curve than 3 years.

Because these GPUs in data centers chew power and take up space. If in 3 years there is a new model that processes far more tokens with the same power and time the economics quickly say the hardware is cheaper to replace than to continue running. As a hobbiest at home the numbers are different and you can afford to do something inefficient.

I still challenge it. After 3 years an H100 has not depreciated to zero, not even close. Even if you want to replace it, it has considerable residual value.

Re: AI's Affordability Crisis

#432

Post by dango369 »

a34729t wrote: post #168

Deepseek is 90% cheaper, and nearly as good for coding tasks as claude/codex, and as good given the right plan. The only moat OpenAI and Anthropic have is regulation. If the Chinese really eant to hammer us, they could realse the full training data and pipeline.

nearly as good but not nearly enough

Re: AI's Affordability Crisis

#433

Post by netdevphoenix »

Insanity wrote: post #20
netdevphoenix wrote: post #3

Earlier quoted context omitted.

It's Proof of (human) Work. Much more useful than having a sticker saying "Done by a Human".

Ask your LLM to 'write like a phishing email' to have it seem more human. I'm actually curious if this works, haven't tried but I assume it would.

I would imagine no mainstream model allows this easily and at scale for obvious reasons.

Re: AI's Affordability Crisis

#434

Post by qnleigh »

whimsicalism wrote: post #294
qnleigh wrote: post #197

The estimate that AI companies need to replace 27% of jobs to service their debt is interesting. But at least Anthropic and Meta seem to have their eyes on replacing software engineers. There are ~1.6M software engineers on the US [0], earning a bit under 150k/year on average [1]. If AI companies captured all of that spend, that amounts to about 250B/year. The article assumed that they need around 300B/year to keep u…

obviating software engineers is effectively AGI-complete and entails obviating most labor in existence .

I think the concept of "AGI-complete" was interesting but had been falsified. LLMs have jagged intelligence, meaning that they are good at some things while being counterintuitively bad at other things that seem much easier. Especially given that a lot of software engineering can be trained via RL, it's entirely plausible that they will get extremely good at that while lagging in other things.

Re: AI's Affordability Crisis

#435

Post by whimsicalism »

qnleigh wrote: post #434
whimsicalism wrote: post #294

Earlier quoted context omitted.

obviating software engineers is effectively AGI-complete and entails obviating most labor in existence .

I think the concept of "AGI-complete" was interesting but had been falsified. LLMs have jagged intelligence, meaning that they are good at some things while being counterintuitively bad at other things that seem much easier. Especially given that a lot of software engineering can be trained via RL, it's entirely plausible that they will get extremely good at that while lagging in other things.

Oh yeah? Who will be working on rounding out the jaggedness of the LLMs and improving the generalizability of their RL environs, etc.?

Re: AI's Affordability Crisis

#436

Post by mikgp »

simianwords wrote: post #429
beepbooptheory wrote: post #415

Earlier quoted context omitted.

No one in FAANG was selling the internet itself.

If we both agree that there will be FAANG type companies out of AI, what would they look like?

We're a few days out here, but I don't agree that a FAANG company will come out of AI, and I think this is a fundamental error to think there will be.

FAANG is rare/hard. It feels like, we've forgotten there's this whole giant middle of like normal companies. Oracle, Cisco, all the consulting companies. Boring companies with "only" a $500B market cap. I don't think any of the AI companies will synergize the like magic set of ingredients you need to be FAANG, and that's the point, they've grown so fast they "have" to to payback investors.

But it's weird that we call them a failure if they don't hit this utopian ideal that only a few companies in history have ever hit.

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