4 ms·

AI is going to be what fiber was to the dotcom bubble. Someone spend a lot of money on a lot of infrastructure, some of which is going to be incredibly useful,

AI is going to be what fiber was to the dotcom bubble. Someone spend a lot of money on a lot of infrastructure, some of which is going to be incredibly useful, but sold for much less than it cost to build. Hardware just depreciates much much faster than fiber networks.

baq 8mo ago
current shortages are exactly the result of fabs not wanting to commit extra capex due to overbuild risk and inference demand seems to be growing 10x yoy; you've famously got 8 year old TPUs at google at 100% load.
hmmmmmmmmmmmmmm 8mo ago
This goes beyond profits. It will be important for national security.
ido 8mo ago
Hardware just depreciates much much faster than fiber The manfucaturing capacity expanded to meet the demand for new hardware doesn't (as much)
- danaris 8mo ago
  But if the demand drops for six months, the manufacturers are going to scale back production. If it drops for a year, they're likely to start shedding capacity, one way or another. This is not an equivalent situation. The vast, vast majority of what's being produced for this bubble is going to be waste once it pops.
  - m4rtink 8mo ago
    I guess you could at least mine the boards from defunct AI companies for memory chips ? Latest videos from Gamers Nexus showed it is apparently not that hard to transfer memory chips from board to board. Then you can leach precious metals from the PCB itself.
    - danaris 8mo ago
      Yes, but if they weren't overproduced and then either run into the ground or left waiting for demand that would never come, then wouldn't those memory chips and precious metals all still be more available than otherwise...? I mean, sure, yes, we can try to recycle waste products—but it's still less wasteful not to produce them unnecessarily in the first place.
      - m4rtink 8mo ago
        Agreed, but basic things like sanity seem to have left this hype cycle long ago. Thankfully real world and physics has the final word, so we can at least plan what to do once the whole thing runs into a wall of reality & make the best of the wreckage.
aurareturn 8mo ago
I'm not saying that data center buildouts can't overshoot demand but AI and compute is different than fiber buildout. The more compute you have, the smarter the AI. You can use the compute to let the AI think longer (maybe hours/days/weeks) on a solution. You can run multiple AI agents simultaneously and have them work together or check each other's work. You can train and inference better models with more compute. So there is always use for more compute to solve problems. Fiber installations can overshoot relatively easily. No matter how much fiber you have installed, that 4k movie isn't going to change. The 3 hours of watch time for consumers isn't going to change.
- zozbot234 8mo ago
  You can't really use compute more because power is already the bottleneck. Datacenter buildouts are now being measured in GW which tells you everything you need to know. Newer hardware will be a lot more power-efficient but also highly scarce for that reason.
  - aurareturn 8mo ago
    Energy is also being scaled up. But the fundamental difference between compute and fiber buildup is different in my opinion.
- BearOso 8mo ago
  Did you pay attention in computer science classes? There are problems you can't simply brute-force. You can throw all the computing power you want at them, but they won't terminate before the heat-death of the universe. An LLM can only output a convolution of its data set. That's its plateau. It can't solve problems, it can only output an existing solution. Compute power can make it faster to narrow down to that existing solution, but it can't make the LLM smarter.
  - aurareturn 8mo ago
    Maybe LLMs can solve novel problems, maybe not. We don't know for sure. It's trending like it can. There are still plenty of problems that having more tokens would allow them to be solved, and solved faster, better. There is no absolutely no way we've already met AI compute demands for the problems that LLMs can solve today.

baq 8mo ago

current shortages are exactly the result of fabs not wanting to commit extra capex due to overbuild risk and inference demand seems to be growing 10x yoy; you've famously got 8 year old TPUs at google at 100% load.

hmmmmmmmmmmmmmm 8mo ago

This goes beyond profits. It will be important for national security.

ido 8mo ago

Hardware just depreciates much much faster than fiber The manfucaturing capacity expanded to meet the demand for new hardware doesn't (as much)

danaris 8mo ago
But if the demand drops for six months, the manufacturers are going to scale back production. If it drops for a year, they're likely to start shedding capacity, one way or another. This is not an equivalent situation. The vast, vast majority of what's being produced for this bubble is going to be waste once it pops.
- m4rtink 8mo ago
  I guess you could at least mine the boards from defunct AI companies for memory chips ? Latest videos from Gamers Nexus showed it is apparently not that hard to transfer memory chips from board to board. Then you can leach precious metals from the PCB itself.
  - danaris 8mo ago
    Yes, but if they weren't overproduced and then either run into the ground or left waiting for demand that would never come, then wouldn't those memory chips and precious metals all still be more available than otherwise...? I mean, sure, yes, we can try to recycle waste products—but it's still less wasteful not to produce them unnecessarily in the first place.
    - m4rtink 8mo ago
      Agreed, but basic things like sanity seem to have left this hype cycle long ago. Thankfully real world and physics has the final word, so we can at least plan what to do once the whole thing runs into a wall of reality & make the best of the wreckage.

aurareturn 8mo ago

I'm not saying that data center buildouts can't overshoot demand but AI and compute is different than fiber buildout. The more compute you have, the smarter the AI. You can use the compute to let the AI think longer (maybe hours/days/weeks) on a solution. You can run multiple AI agents simultaneously and have them work together or check each other's work. You can train and inference better models with more compute. So there is always use for more compute to solve problems. Fiber installations can overshoot relatively easily. No matter how much fiber you have installed, that 4k movie isn't going to change. The 3 hours of watch time for consumers isn't going to change.

zozbot234 8mo ago
You can't really use compute more because power is already the bottleneck. Datacenter buildouts are now being measured in GW which tells you everything you need to know. Newer hardware will be a lot more power-efficient but also highly scarce for that reason.
- aurareturn 8mo ago
  Energy is also being scaled up. But the fundamental difference between compute and fiber buildup is different in my opinion.
BearOso 8mo ago
Did you pay attention in computer science classes? There are problems you can't simply brute-force. You can throw all the computing power you want at them, but they won't terminate before the heat-death of the universe. An LLM can only output a convolution of its data set. That's its plateau. It can't solve problems, it can only output an existing solution. Compute power can make it faster to narrow down to that existing solution, but it can't make the LLM smarter.
- aurareturn 8mo ago
  Maybe LLMs can solve novel problems, maybe not. We don't know for sure. It's trending like it can. There are still plenty of problems that having more tokens would allow them to be solved, and solved faster, better. There is no absolutely no way we've already met AI compute demands for the problems that LLMs can solve today.