1. Depending on the data source you look at, about 50 - 60% of people use AI at work but only for 5 - 15% of work hours. That leaves about 2x (from users) times 7 - 20x (from work hours) for growth. Furthermore agentic usage is much more token-intensive than regular prompts, that's another unknown multiple that will get applied.
Small models will make a dent for sure, but even they need to run on hardware. It's not clear how much their lower resource requirements will cancel out the scope for growth, but I think it will take time for that dynamic to play out; people are only just starting to ease up on tokenmaxxing. Anthropic revenues would be the canary in the coalmine, and thankfully they'll be IPO'ing soon.
2. All the relevant fabs (mainly, TSMC) are extremely capacity-constrained, so who actually gets the chips depends on who has the best vendor relationships... and who can pay the most for them. Even Apple, famed for its supply chain mastery, is having trouble these days.
I would assume TSMC will try to keep all its customers happy but will prioritize supplying the customer that will pay it the most money, and these days that's Nvidia. Simply because that's where ~all the AI boom money is flowing. Heck, you could even imagine some form of revenue share to keep the spice errr chips flowing...
3. Memory constraints affect all vendors, they will just pass those costs on to customers, like Nvidia with its recent 15% price bump. Notably the bump was announced BEFORE the earnings; I wonder if the effects of that was reflected in these projections.
Nvidia is in the same position with acquiring chip supply that Google is with acquiring search traffic: monopoly profits shared with suppliers make it very hard for other companies to compete.
Comments
Counterpoints:
1. Depending on the data source you look at, about 50 - 60% of people use AI at work but only for 5 - 15% of work hours. That leaves about 2x (from users) times 7 - 20x (from work hours) for growth. Furthermore agentic usage is much more token-intensive than regular prompts, that's another unknown multiple that will get applied.
Small models will make a dent for sure, but even they need to run on hardware. It's not clear how much their lower resource requirements will cancel out the scope for growth, but I think it will take time for that dynamic to play out; people are only just starting to ease up on tokenmaxxing. Anthropic revenues would be the canary in the coalmine, and thankfully they'll be IPO'ing soon.
2. All the relevant fabs (mainly, TSMC) are extremely capacity-constrained, so who actually gets the chips depends on who has the best vendor relationships... and who can pay the most for them. Even Apple, famed for its supply chain mastery, is having trouble these days.
I would assume TSMC will try to keep all its customers happy but will prioritize supplying the customer that will pay it the most money, and these days that's Nvidia. Simply because that's where ~all the AI boom money is flowing. Heck, you could even imagine some form of revenue share to keep the spice errr chips flowing...
3. Memory constraints affect all vendors, they will just pass those costs on to customers, like Nvidia with its recent 15% price bump. Notably the bump was announced BEFORE the earnings; I wonder if the effects of that was reflected in these projections.
Nvidia is in the same position with acquiring chip supply that Google is with acquiring search traffic: monopoly profits shared with suppliers make it very hard for other companies to compete.