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.
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/
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.
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.
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.
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.