▲ 108 ▼ AI's Economics Don't Make Sense (www.wheresyoured.at) submitted 6 months ago by Deep@mander.xyz to c/technology@lemmy.world 14 comments fedilink hide all child comments
[+] MangoCats@feddit.it 16 points 6 months ago (2 children) [removed by mod] permalink fedilink source parent hideshow 2 child comments replies: [–] Fizz@lemmy.nz 1 point 6 months ago (1 child) They're kinda past that phase and now need to show that they have sustainable revenue and user growth. From all the numbers I've seen they(open ai, Gemini, anthropic) have crazy numbers. Hundreds of millions of users paying $50 a month. It's not enough to cover training but it covers inference very nicely. Then with agent bullshit they've managed to turn 1 prompt into 12 and bill the user for that extra so it's even more profitable than the monthly subscriptions. permalink fedilink source parent hideshow 1 child comment replies: [–] mlg@lemmy.world 4 points 6 months ago If it weren't for the massive silicon supply lockdown, I feel like we could easily see local models making it into consumer tech in the coming years and effectively replace all those casual users since you no longer have to pay a subscription to do regular/low effort tasks on whatever device you own. A lot of it has gotten really good, especially with lots of quantization techniques getting superseded by new ones each year. Actually I guess it could probably go the same way as cable and streaming. Eventually they'll keep amping up the ante with the billing (because they always do), and people will just get turned off into a bunch of "cheaper" 3rd parties that have lower costs with some niche tricks, which will fragment the userbase too much. Also I haven't looked into it, but do they advertise those $50 users separately from enterprise? I don't really know anyone outside of "power" users that aren't just using the $20 a month basic plans that give you enough tokens to get by (for now). I feel like they're inflating their numbers from enterprise estimates because that's where they can bait with cheap API prices and then hook with vendor lock in. permalink fedilink source parent [–] partofthevoice@lemmy.zip 2 points 6 months ago* If that’s true, you make a good point. Sounds like they could keep the business model around inference. They’d just need to figure out how to make up the budget for training, which I imagine could be done with good marketing on new releases. As well as finding ways to use more tokens, injecting ads, selling data, investors, … did I miss anything? It doesn’t sound impossible if the inference portion is as lucrative as you say. permalink fedilink source parent load more comments (-1 replies)
[–] Fizz@lemmy.nz 1 point 6 months ago (1 child) They're kinda past that phase and now need to show that they have sustainable revenue and user growth. From all the numbers I've seen they(open ai, Gemini, anthropic) have crazy numbers. Hundreds of millions of users paying $50 a month. It's not enough to cover training but it covers inference very nicely. Then with agent bullshit they've managed to turn 1 prompt into 12 and bill the user for that extra so it's even more profitable than the monthly subscriptions. permalink fedilink source parent hideshow 1 child comment replies: [–] mlg@lemmy.world 4 points 6 months ago If it weren't for the massive silicon supply lockdown, I feel like we could easily see local models making it into consumer tech in the coming years and effectively replace all those casual users since you no longer have to pay a subscription to do regular/low effort tasks on whatever device you own. A lot of it has gotten really good, especially with lots of quantization techniques getting superseded by new ones each year. Actually I guess it could probably go the same way as cable and streaming. Eventually they'll keep amping up the ante with the billing (because they always do), and people will just get turned off into a bunch of "cheaper" 3rd parties that have lower costs with some niche tricks, which will fragment the userbase too much. Also I haven't looked into it, but do they advertise those $50 users separately from enterprise? I don't really know anyone outside of "power" users that aren't just using the $20 a month basic plans that give you enough tokens to get by (for now). I feel like they're inflating their numbers from enterprise estimates because that's where they can bait with cheap API prices and then hook with vendor lock in. permalink fedilink source parent [–] partofthevoice@lemmy.zip 2 points 6 months ago* If that’s true, you make a good point. Sounds like they could keep the business model around inference. They’d just need to figure out how to make up the budget for training, which I imagine could be done with good marketing on new releases. As well as finding ways to use more tokens, injecting ads, selling data, investors, … did I miss anything? It doesn’t sound impossible if the inference portion is as lucrative as you say. permalink fedilink source parent load more comments (-1 replies)
[–] mlg@lemmy.world 4 points 6 months ago If it weren't for the massive silicon supply lockdown, I feel like we could easily see local models making it into consumer tech in the coming years and effectively replace all those casual users since you no longer have to pay a subscription to do regular/low effort tasks on whatever device you own. A lot of it has gotten really good, especially with lots of quantization techniques getting superseded by new ones each year. Actually I guess it could probably go the same way as cable and streaming. Eventually they'll keep amping up the ante with the billing (because they always do), and people will just get turned off into a bunch of "cheaper" 3rd parties that have lower costs with some niche tricks, which will fragment the userbase too much. Also I haven't looked into it, but do they advertise those $50 users separately from enterprise? I don't really know anyone outside of "power" users that aren't just using the $20 a month basic plans that give you enough tokens to get by (for now). I feel like they're inflating their numbers from enterprise estimates because that's where they can bait with cheap API prices and then hook with vendor lock in. permalink fedilink source parent
[–] partofthevoice@lemmy.zip 2 points 6 months ago* If that’s true, you make a good point. Sounds like they could keep the business model around inference. They’d just need to figure out how to make up the budget for training, which I imagine could be done with good marketing on new releases. As well as finding ways to use more tokens, injecting ads, selling data, investors, … did I miss anything? It doesn’t sound impossible if the inference portion is as lucrative as you say. permalink fedilink source parent