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Goldman Sachs put out a 31-page-report titled "Gen AI: Too Much Spend, Too Little Benefit?” (www.goldmansachs.com)

submitted 4 months ago by [email protected] to c/[email protected]

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[–] [email protected] 6 points 4 months ago (3 children)

Man, I'm so curious when and to what extent this whole hype bubble will implode.
Like, we're not talking blockchain, there is some legitimate use-cases for generative AI, which will continue to exist.

However, there's also many legitimate use-cases which will not continue to exist, because Microsoft et al are subsidizing GenAI to an insane degree.
When the hype falls off, investors pull out their money and Microsoft cannot continue subsidizing, which will make prices shoot up for their customers and serve as a rough awakening to all the websites that integrated a crappy chatbot.

And of course, there's also the complete fucking bullshit use-cases, which will be gutted immediately when investors/management stop being hyped.

[–] [email protected] 0 points 4 months ago* (last edited 4 months ago)

It's very strange when people assume there's no use for decentralized currency/finance.

It's even stranger when they assume there is some greater use for "AI" - the grifting heart of legitimate statistics, data analysis, etc.

[–] [email protected] 2 points 4 months ago

Same, I think there are genuinely useful applications for this tech, but it's far more limited than what's being marketed. The sooner we get past the hype phase the better, because then we can start focusing on figuring out what this tech is actually good for.

The aspect that's driving the hype currently is that we don't know what the plateau is. And people are figuring out ways to improve both accuracy and performance of LLMs, so it's difficult to say definitively what will be possible in the near future. For example, using a router with a set of LLMs can drastically reduce energy consumption while maintaining quality of the output https://lmsys.org/blog/2024-07-01-routellm/

Another example, is using a consensus model leads to more consistent outputs https://www.wired.com/story/game-theory-can-make-ai-more-correct-and-efficient/

So, it's possible that some of the more glaring limitations could be addressed, but it's also possible that we'll hit a wall because there are inherent problems with the approach. The context issue is one example where you start getting diminishing returns as the model gets bigger.

It's going to be interesting to watch how this all develops.

[–] [email protected] 3 points 4 months ago* (last edited 4 months ago) (1 children)

I was amazed that we transitioned from one GPU heavy bubble (Crypto) to another (LLM/AI). Whilst the hype for crypto imploded the use for the hardware sort of didn't. I wonder if the next bubble with be the same, or if we get some refreshing variety to our money sinks?

Microsoft et al are subsidizing GenAI to an insane degree. [...] prices shoot up for their customers and serve as a rough awakening to all the websites that integrated a crappy chatbot.

I've run some much simpler chatbots on just my desktop PC, so they will have some fallback (if they really choose to take it). Still it locks up my entire computer for a few second for each reply, so even a few hundred users per second peak would be an expensive service.

(Insert joke here about customers not noticing or caring about the difference between website chatbots built on big company services vs smaller ones, because they have exactly the same problems just in different hues.)

[–] [email protected] 5 points 4 months ago

I was amazed that we transitioned from one GPU heavy bubble (Crypto) to another (LLM/AI).

From what I understand, that's not a coincidence. We've had the technology for LLMs for a long time. We just didn't make them Large, because the training would have taken an eternity.
Then cryptocurrencies caused the GPU market to boom and then implode, which meant lots of cryptominers were selling their GPUs for dirt cheap. Perfect time to buy a bunch of GPUs, stick them in a server and try to do that eternity-long training.

And yeah, as for local chatbots, I do also imagine they will continue to be a thing, even if they won't get any better anymore when the big companies stop doing the training.
But as you kind of also reasoned, I still don't expect most of these companies to host their own chatbot...

[–] [email protected] 5 points 4 months ago (1 children)

Pft. Sounds like someone's just sour because they didn't invest in AI. /s

[–] [email protected] 1 points 4 months ago* (last edited 4 months ago)

I'm confused. Sacholding?