It’s very, very costly, both but the hardware and the electricity it takes to run it. There may be a bit of sunk cost fallacy at play for some, especially the execs who are calling for AI Everything, but in the end, in AI doesn’t generate enough increase in revenue to offset its operational costs, even those execs will bow out. I think the economics of AI will cause the bubble to burst because end users aren’t going to pay money for a service that does a mediocre job at most things but costs more.
That’s what I suspect, too, but I’m not entirely sure in my research so far. The question I am still unsure about: Is it as costly in running, or is the real costly part “just” the “training our model” part? I wondered that, because when I was messing around, things like generative text models could run on my potato PC with a bit of python scripting without too much issue, even if not ideally - as long as I had the already trained dataset downloaded.
It’s very, very costly, both but the hardware and the electricity it takes to run it. There may be a bit of sunk cost fallacy at play for some, especially the execs who are calling for AI Everything, but in the end, in AI doesn’t generate enough increase in revenue to offset its operational costs, even those execs will bow out. I think the economics of AI will cause the bubble to burst because end users aren’t going to pay money for a service that does a mediocre job at most things but costs more.
That’s what I suspect, too, but I’m not entirely sure in my research so far. The question I am still unsure about: Is it as costly in running, or is the real costly part “just” the “training our model” part? I wondered that, because when I was messing around, things like generative text models could run on my potato PC with a bit of python scripting without too much issue, even if not ideally - as long as I had the already trained dataset downloaded.
Can’t really answer the expense trade-off until you look at concrete use cases, something general AI is allergic to…