this post was submitted on 06 Sep 2024
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The DotCom bubble was built around the idea of online retail outpacing traditional retail far faster than it did, in fact. But it was, at its essence, a system of digital book keeping. Book your orders, manage your inventory, and direct your shipping via a more advanced and interconnected set of digital tools.
The fundamentals of the business - production, shipping, warehousing, distribution, the mathematical process of accounting - didn't change meaningfully from the days of the Sears-Roebuck Catalog. Online was simply a new means of marketing. It worked well, but not nearly as well as was predicted. What Amazon did to achieve hegemony was to run losses for ten years, while making up the balance as a government sponsored series of data centers (re: AWS) and capitalize on discount bulk shipping through the USPS before accruing enough physical capital to supplant even the big box retailers. The digital front-end was always a loss-leader. Nobody is actually turning a profit on Amazon Prime. It's just a hook to get you into the greater Amazon ecosystem.
Pivot to AI, and you've got to ask... what are we actually improving on? It's not a front-end. It's not a data-service that anyone benefits from. It is hemorrhaging billions of dollars just at OpenAI alone (one reason why it was incorporated as a Non-Profit to begin with - THERE WAS NO PROFIT). Maybe you can leverage this clunky behemoth into... low-cost mass media production? But its also extremely low-rent production, in an industry where - once again - marketing and advertisement are what command the revenue you can generate on a finished product. Maybe you can use it to optimize some industrial process? But it seems that every AI needs a bunch of human babysitters to clean up all the shit is leaves. Maybe you can get those robo-taxis at long last? I wouldn't hold my breath, but hey, maybe?!
Maybe you can argue that AI provides some kind of hook to drive retail traffic into a more traditional economic model. But I'm still waiting to see what that is. After that, I'm looking at AI in the same way I'm looking at Crypto or VR. Just a gimmick that's scaring more people off than it drags in.
I don't mean it's like the dotcom bubble in terms of context, I mean in terms of feel. Dotcom had loads of investors scrambling to "get in on it" many not really understanding why or what it was worth but just wanted quick wins.
This has same feel, a bit like crypto as you say but I would say crypto is very niche in real world applications at the moment whereas AI does have real world usages.
They are not the ones we are being fed in the mainstream like it replacing coders or artists, it can help in those areas but it's just them trying to keep the hype going. Realistically it can be used very well for some medical research and diagnosis scenarios, as it can correlate patterns very easily showing likelyhood of genetic issues.
The game and media industry are very much trialling for voice and image synthesis for improving environmental design (texture synthesis) and providing dynamic voice synthesis based off actors likenesses. We have had peoples likenesses in movies for decades via cgi but it's only really now we can do the same but for voices and this isn't getting into logistics and/or financial where it is also seeing a lot of application.
Its not going to do much for the end consumer outside of the guff you currently use siri or alexa for etc, but inside the industries AI is very useful.
Crypto has a very real niche use for money laundering that it does exceptionally well.
AI does not appear to do anything significantly more effectively than a Google search circa 2018.
But neither can justify a multi billion dollar market cap on these terms.
Voice actors simply don't cost that much money. Procedural world building has existed for decades, but it's generally recognized as lackluster beside bespoke design and development.
These tools let you build bad digital experiences quickly.
For logistics and finance, a lot of what you're exploring is solved with the technology that underpins AI (modern graph theory). But LLMs don't get you that. They're an extraneous layer that takes enormous resources to compile and offers very little new value.
I disagree, there are loads of white papers detailing applications of AI in various industries, here's an example, cba googling more links for you.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7577280/
And loads more of its ineffectual nature and wastefulness.
Are you talking specifically about LLMs or Neural Network style AI in general? Super computers have been doing this sort of stuff for decades without much problem, and tbh the main issue is on training for LLMs inference is pretty computationally cheap
Idk if I'd point at a supercomputer system and suggest it was constructed "without much problem". Cray has significantly lagged the computer market as a whole.
Again, I would not consider anything in the LLM marketplace particularly cheap. Seems like they're losing money rapidly.