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The Hater's Guide to the AI Bubble

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51–60 of 168 posts

Re: The Hater's Guide to the AI Bubble

#51

I believe this is a "good" bubble in the sense that the 19th century railroad bubble and original dot com bubble both ended up invested in infrastructure that created immense value. That said, all of these LLMs are interchangeable, there are no moats, and the profit will almost entirely be in the "last mile," in local subject matter experts applying this technology to their bespoke business processes.

I keep saying to people - "if you have a good idea that can make use of large amounts of really really cheap GPUs to do something genuinely useful - get ready for a massive glut of spare capacity". I still haven't thought of anything, unfortunately...

Re: The Hater's Guide to the AI Bubble

#52

I think the author's take is overly bleak. Yes, he supports his claim that AI businesses are currently money pits and unsustainable. But I don't think it's reasonable to claim that AI can't be profitable. This whole thing is moving so extremely fast. Models are getting better by the month. Cost is rapidly coming down. We broadly speaking still don't know how to apply AI. I think it's hubris to claim that, in the wake…

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Re: The Hater's Guide to the AI Bubble

#53
post #40

What's clear is that the hype has reach such a critical mass that people are comfortable enough to publicly and shamelessly extrapolate extraordinary claims based purely on gut feeling. Both here on HN and by complete laymen elsewhere. AI-optimist or not, that's just shocking to me.

I don’t doubt this but it might help to include some examples if you have any close at hand.

Re: The Hater's Guide to the AI Bubble

#54

I believe this is a "good" bubble in the sense that the 19th century railroad bubble and original dot com bubble both ended up invested in infrastructure that created immense value. That said, all of these LLMs are interchangeable, there are no moats, and the profit will almost entirely be in the "last mile," in local subject matter experts applying this technology to their bespoke business processes.

> "good" bubble in the sense how can massively buying hardware that will have to be thrown away in a few years be a "good" bubble in the sense of being a lasting infrastructure investment?

Why would that hardware "have to be thrown away"? I've seen quite old GPUs still in use; given the current demand, I expect the vast majority of hardware used in these data centers to see a lot more extended use than most other types of electronics around the world (e.g. phones).

Re: The Hater's Guide to the AI Bubble

#55
post #40

What's clear is that the hype has reach such a critical mass that people are comfortable enough to publicly and shamelessly extrapolate extraordinary claims based purely on gut feeling. Both here on HN and by complete laymen elsewhere. AI-optimist or not, that's just shocking to me.

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Re: The Hater's Guide to the AI Bubble

#56
post #40

What's clear is that the hype has reach such a critical mass that people are comfortable enough to publicly and shamelessly extrapolate extraordinary claims based purely on gut feeling. Both here on HN and by complete laymen elsewhere. AI-optimist or not, that's just shocking to me.

> people are comfortable enough to publicly and shamelessly extrapolate extraordinary claims based purely on gut feeling

What's the problem with that? Why shouldn't people feel comfortable sharing their vision of the future, even if it's just a "gut feeling" vision? We're not going to run out of ink.

Re: The Hater's Guide to the AI Bubble

#57
In July 2023, I wrote this to a friend:

"...being entirely blunt, I am an AI skeptic. I think AI and LLM are somewhat interesting but a bit like self-driving cars 5 years ago - at the peak of a VC-driven hype cycle and heading for a spectacular deflation.

My main interest in technology is making innovation useful to people and as it stands I just can't conceive of a use of this which is beneficial beyond a marginal improvement in content consumption. What it does best is produce plausible content, but everything it produces needs careful checking for errors, mistakes and 'hallucinations' by someone with some level of expertise in a subject. If a factory produced widgets with the same defect rate as ChatGPT has when producing content, it would be closed down tomorrow. We already have a problem with large volumes of bad (and deceptive!) content on the internet, and something that automatically produces more of it sounds like a waking nightmare.

Add to that the (presumed, but reasonably certain) fact that common training datasets being used contain vast quantities of content lifted from original authors without permission, and we have systems producing well-crafted lies derived from the sweat of countless creators without recompense or attribution. Yuck!"

I'll be interested to see how long it takes for this "spectacular deflation" to come to pass, but having lived through 3 or so major technology bubbles in my working life, my antennae tell me that it's not far off now...

Re: The Hater's Guide to the AI Bubble

#58

I believe this is a "good" bubble in the sense that the 19th century railroad bubble and original dot com bubble both ended up invested in infrastructure that created immense value. That said, all of these LLMs are interchangeable, there are no moats, and the profit will almost entirely be in the "last mile," in local subject matter experts applying this technology to their bespoke business processes.

Ok, but what's the infrastructure that will remain after the AI bubble that can be retooled like railroads or dot com?

Re: The Hater's Guide to the AI Bubble

#59

Earlier quoted context omitted.

> "good" bubble in the sense how can massively buying hardware that will have to be thrown away in a few years be a "good" bubble in the sense of being a lasting infrastructure investment?

The models themselves, and methods and knowledge used to build and use them, are part of the "infrastructure" being built.

You're redefining infrastructure. A supply and demand model is not infrastructure. A Taylor expansion method is not infrastructure.

Re: The Hater's Guide to the AI Bubble

#60

Earlier quoted context omitted.

> "good" bubble in the sense how can massively buying hardware that will have to be thrown away in a few years be a "good" bubble in the sense of being a lasting infrastructure investment?

Why would that hardware "have to be thrown away"? I've seen quite old GPUs still in use; given the current demand, I expect the vast majority of hardware used in these data centers to see a lot more extended use than most other types of electronics around the world (e.g. phones).

GPUs in data centers have short lifespans.

https://www.tomshardware.com/pc-components/gpus/datacenter-g...

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