There is a key difference, that makes the genie impossible to bottle: People can run local AI on their own machines. Fans of nuclear power can’t easily build nuclear plants in their backyard. A pity, the world could use more nuclear energy. 😔
Anyhow, I am looking forward to someday using frontier-grade AI on my PC. Just need the AI bubble to pop, so that I can afford the terrabytes of memory that would be needed to comfortably run it.
Wait… how do you imagine a world where there’s demand for frontier grade AI but also that the bubble has popped such that there’s not demand for the chips to run frontier grade AI?
The internet survived the Dotcom bubble. Many businesses died, but some survived. The glut of hardware from the dead will end up in the hands of individuals, upstart companies, and the corporations that outlived their peers.
In any case, I believe the definition of frontier AI will change, as would the hardware. My build is based on what local AI is available today, with some wiggle room left over. I believe that it is around 2030, when DDR6 and other major shifts are likely to happen, that we will see the definitions change.
In any case, a Q4 of GLM 5.2 is about 460ish gigs of VRAM+RAM. While expensive, that ain’t out of reach for an AI hobbyist.
Right, but what % of people are currently using/demanding inference right now?
Do you expect that % to change between now and 2030?
Unless you expect demand to decrease, I don’t really see how the pricing of the hardware will decrease.
Let’s say the Pets.com of the AI world ends up going bankrupt and their RAM hits the market. Do you expect that the demand for that RAM will be negligible such that pricing returns to earlier levels?
Your predictive model relies on companies that have hardware going out of business and then other people buying up that hardware, but isn’t accounting for the levels of demand that the market will have for that secondhand hardware even if it ends up existing from failed firms.
Unless the demand shifts, the more likely scenario is that companies going out of business will be able to sell off their RAM at higher prices than they bought it at.
There’d need to be a significant inference memory reduction advance (possible) coupled with stagnating or reduced inference demand (unlikely) to see prices come back down.
Unless the demand shifts, the more likely scenario is that companies going out of business will be able to sell off their RAM at higher prices than they bought it at.
Oh lordy, after the bankruptcies there are going to be creditors fighting each other in court to be paid back in ram.
There is a key difference, that makes the genie impossible to bottle: People can run local AI on their own machines. Fans of nuclear power can’t easily build nuclear plants in their backyard. A pity, the world could use more nuclear energy. 😔
Anyhow, I am looking forward to someday using frontier-grade AI on my PC. Just need the AI bubble to pop, so that I can afford the terrabytes of memory that would be needed to comfortably run it.
Hello enemy of all life on earth, how are you today?
Good. If people had nuclear in their backyard, we’d be a “junkyard nightmare” and a “dirty bomb hellscape.”
Wait… how do you imagine a world where there’s demand for frontier grade AI but also that the bubble has popped such that there’s not demand for the chips to run frontier grade AI?
I’m really confused.
The internet survived the Dotcom bubble. Many businesses died, but some survived. The glut of hardware from the dead will end up in the hands of individuals, upstart companies, and the corporations that outlived their peers.
In any case, I believe the definition of frontier AI will change, as would the hardware. My build is based on what local AI is available today, with some wiggle room left over. I believe that it is around 2030, when DDR6 and other major shifts are likely to happen, that we will see the definitions change.
In any case, a Q4 of GLM 5.2 is about 460ish gigs of VRAM+RAM. While expensive, that ain’t out of reach for an AI hobbyist.
Right, but what % of people are currently using/demanding inference right now?
Do you expect that % to change between now and 2030?
Unless you expect demand to decrease, I don’t really see how the pricing of the hardware will decrease.
Let’s say the Pets.com of the AI world ends up going bankrupt and their RAM hits the market. Do you expect that the demand for that RAM will be negligible such that pricing returns to earlier levels?
Your predictive model relies on companies that have hardware going out of business and then other people buying up that hardware, but isn’t accounting for the levels of demand that the market will have for that secondhand hardware even if it ends up existing from failed firms.
Unless the demand shifts, the more likely scenario is that companies going out of business will be able to sell off their RAM at higher prices than they bought it at.
There’d need to be a significant inference memory reduction advance (possible) coupled with stagnating or reduced inference demand (unlikely) to see prices come back down.
Oh lordy, after the bankruptcies there are going to be creditors fighting each other in court to be paid back in ram.
Speak for yourself, casual