I think the article makes decent points but I don't agree with the general conclusion here, which is that all of this investment is wasted unless it "reaches AGI." Maybe it isn't necessary for every single dollar we spend on AI/LLM products and services to go exclusively toward the goal of "reaching AGI?" Perhaps it's alright if these dollars instead go to building out useful services and applications based on the LLM technologies we already have.

The author, for whatever reason, views it as a foregone conclusion that every dollar spent in this way is a waste of time and resources, but I wouldn't view any of that as wasted investment at all. It isn't any different from any other trend - by this logic, we may as well view the cloud/SaaS craze of the last decade as a waste of time. After all, the last decade was also fueled by lots of unprofitable companies, speculative investment and so on, and failed to reach any pie-in-the-sky Renaissance-level civilization-altering outcome. Was it all a waste of time?

It's ultimately just another thing industry is doing as demand keeps evolving. There is demand for building the current AI stack out, and demand for improving it. None of it seems wasted.

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an0malous 2 hours ago | parent | next [-]

That’s not what he’s saying, the investors are the ones who have put trillions of dollars into this technology on the premise that it will achieve AGI. People like Sam Altman and Marc Andreesen have been going into podcasts saying AGI is imminent and they’re going to automate every job.

The author did not say every dollar was wasted, he said that LLMs will never meet the current investment returns.

It’s very frustrating to see comments like this attacking strawmans and setting up Motte and Bailey arguments every time there’s AI criticism. “Oh but LLMs are still useful” and “Even if LLMs can’t achieve AGI we’ll figure out something that will eventually.” Yes but that isn’t what Sam and Andreesen and all these VCs have been saying, and now the entire US economy is a big gamble on a technology that doesn’t deliver what they said it would and because the admin is so cozy with VCs we’re probably all going to suffer for the mistakes of a handful of investors who got blinded by dollar signs in their eyes.

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ComplexSystems an hour ago | parent | next [-]

The author quite literally says that the last few years were a "detour" that has wasted a trillion dollars. He explicitly lists building new LLMs, building larger LLMs and scaling LLMs as the problem and source of the waste. So I don't think I am strawmanning his position at all.

It is one thing to say that OpenAI has overpromised on revenues in the short term and another to say that the entire experiment was a waste of time because it hasn't led to AGI, which is quite literally the stance that Marcus has taken in this article.

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an0malous an hour ago | parent [-]

> The author, for whatever reason, views it as a foregone conclusion that every dollar spent in this way is a waste of time and resources

This is a strawman, the author at no point says that “every dollar is a waste.”

	▲	ComplexSystems 26 minutes ago \| parent [-]
		He quite literally says that the dollars spent on scaling LLMs in the past few years are a waste.

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dist-epoch an hour ago | parent | prev [-]

You are making the same strawman attack you are criticising.

The dollars invested are not justified considering TODAYs revenues.

Just like 2 years ago people said NVIDIA stock prices was not justified and a massive bubble considering the revenue from those days. But NVIDIA revenues 10xed, and now the stock price from 2 years ago looks seriously underpriced and a bargain.

You are assuming LLM revenues will remain flat or increase moderately and not explode.

	▲	an0malous an hour ago \| parent [-]
		You seem like someone who might be interested in my nuclear fusion startup. Right now all we have is a bucket of water but in five years that bucket is going to power the state of California.

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robot-wrangler 2 hours ago | parent | prev [-]

It's not about "every dollar spent" being a waste of time, it's about acknowledging the reality of opportunity cost. Of course, no one in any movement is likely to listen to their detractors, but in this case the pioneers seem to agree.

https://www.youtube.com/watch?v=DtePicx_kFY https://www.bbc.com/news/articles/cy7e7mj0jmro

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ComplexSystems 2 hours ago | parent [-]

I think there is broad agreement that new models and architectures are needed, but I don't see it as a waste to also scale the stack that we currently have. That's what Silicon Valley has been doing for the past 50 years - scaling things out while inventing the next set of things - and I don't see this as any different. Maybe current architectures will go the way of the floppy disk, but it wasn't a waste to scale up production of floppy disk drives while they were relevant. And ChatGPT was still released only 3 years ago!

	▲	vidarh an hour ago \| parent [-]
		And notably, Marcus has been banging this drum for years. Even this article points back to articles he wrote years ago suggesting deep learning was hitting the wall... With GPT 3.... It's sour grapes because the methods he prefers have not gotten the same attention (hah...) or funding. He's continuing to push the ludicrous Apple "reasoning paper" that he described as a "knockout blow for LLMs" even though it was nothing of the sort. With each of his articles, I usually lose more respect for him.