The AI Hype Bubble

When the AI hype bubble bursts, a lot of people (myself included via my superannuation fund) are going to get burnt.

I find using an LLM useful at the margins; I’m glad I’m not working in a company or industry that has a belief it is the great messiah - only to find out the costs are blowing out…

I do love how Ed Zitron writes about this stuff in his latest piece, AI Doesn’t Have ROI. I’ve cherrypicked a few good quotes from a great and long article that I encourage you to read.

You spent a trillion dollars to make it somewhat easier to code some things sometimes but not in such a way that it actually results in anything, research reports that nobody will read, shitty powerpoint decks and excel spreadsheets, and art that looks like stock images because that’s exactly what it was trained on. 

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The reason nobody can show you the ROI from AI is that AI does not have a return on investment. Large Language Models can speed up some things in a way that becomes increasingly less-valuable and accurate with the complexity of the task, and more investment in AI data centers does not appear to do anything other than expand the number of tasks that an LLM can attempt. 

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…every single “AI setup” I’ve seen anyone ever use involves a rube goldberg machine of bullshit deterministic scripts to try and bring the hallucination-guaranteed nature of LLMs to heel, usually to the point that you’re doing more work making the LLM work than you did before they existed, and you’re only proud of it because you feel like you’re special.

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AI is more expensive today than it was three years ago, and it is not getting cheaper.

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Four years and a trillion dollars in, AI is more expensive, its companies more cash-intensive, its products just as unreliable, and its boosters more desperate than ever to make you ignore reality as a means of empowering one of a few ultra-rich oafs.

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If you can’t measure how good something is, how much it might cost, or what your return on investment might be, it’s fair to ask why you’re even paying for it in the first place.