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AI is too expensive

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Re: AI is too expensive

#71

Post by WarmWash »

Aurornis wrote: post #37
bensyverson wrote: post #13

If you're older than 30, you've seen this play out before… This is just how the VC game works. Cross-town Uber rides don't stay $5 forever. The bright side is: this is a golden era of subsidized tokens. It will not always be like this, so now is the time to churn out your passion projects.

Uber is a good comparison because everyone was predicting the demise of ride sharing as soon as they tried to become profitable. The subsidies went away gradually and the prices leveled out in a spot where the services are heavily used. Uber became profitable. Ride sharing is affordable. I think our $20/month plans might become a little less generous and the $200/month plan won’t always allow non-stop vibe coding, bu…

AI will likely cost $60-$80 per user per month.

Akin to an average cellphone bill. The infrastructure costs are comparable and the ROI would be 5-10 years for the current insane build out.

Yes, chinese and local models exist. But so do $20 cell phone plans. People go with what is convenient, works, and is readily available.

Re: AI is too expensive

#72

Post by WarmWash »

add-sub-mul-div wrote: post #27
hypnodrones wrote: post #10

The rug pull on users is bound to happen and it will involve advertising.

Algorithmically and seamlessly weaving undisclosed advertising (or other editorial content) into conversational output is their holy grail. It's the endgame. There's a reason they're pushing so hard.

I mean, we could just avoid this if people realize it's not morally wrong to pay for a service.

Re: AI is too expensive

#74

Post by not_the_fda »

Havoc wrote: post #11

It’s a similar bet as Uber. They also started out with numbers that make no sense - overpaying drivers and undercharging users The math may look questionable but there are also senior people talking of automating all white color work in the next couple years. Even if that estimate is miles off on both time and % it’s still trillions. So crazy as the numbers seem it could still work out

Automating white color work in the next couple years will cause the greatest demand destruction humans have ever seen.

Re: AI is too expensive

#75

Post by wagwang »

You have to look at use cases and there are a bunch of slam dunk use cases that are wildly profitable at todays token prices, whether we keep finding use cases as intelligence goes up is another story.

Re: AI is too expensive

#76

Post by chipotle_coyote »

slackfan wrote: post #61

> If you liked this piece, you should subscribe to my premium newsletter. It’s $70 a year, or $7 a month... This blog is too expensive too.

It seems to me (entirely anecdotal, YMMV, etc. etc.) that Ed Zitron’s blog posts started getting both longer and considerably more histrionic when he started moving most of them behind a paywall. I’m definitely in the “AI skeptic” camp and think Zitron has good points to make about both the shaky business models around AI and the unrelenting hype train, but it’s hard not to get the impression that he’s found a niche of preaching to the rabid AI haters willing to give him money to keep spouting increasingly repetitive vitriol toward Sam Altman and Dario Amodei.

Re: AI is too expensive

#77

Post by voxl »

czhu12 wrote: post #36

I really respected Ed Zitron, but I feel like he's very much lost the plot on AI. Scroll back not too far and he was publishing criticisms that no one wants to spend actual money AI. Anthropic has shattered all notions of that since then. Then there was the idea that even if people want it, we have way too much GPU capacity to ever be saturated. Now almost all providers are hitting limits. Now, its the next iteration…

[flagged]

Re: AI is too expensive

#78

Post by bauldursdev »

czhu12 wrote: post #36

I really respected Ed Zitron, but I feel like he's very much lost the plot on AI. Scroll back not too far and he was publishing criticisms that no one wants to spend actual money AI. Anthropic has shattered all notions of that since then. Then there was the idea that even if people want it, we have way too much GPU capacity to ever be saturated. Now almost all providers are hitting limits. Now, its the next iteration…

I'm not really an AI-futurist or anything, I think the truth is between the extremes, but it seems like a lot of people who are ideologically against AI just move the goal posts whenever a new development is made. They also seem to operate under the assumption that whatever the current state of the technology is is as good as it will ever be. "it can't even do x today, so it'll never be good".

Re: AI is too expensive

#79

Post by mstank »

jayd16 wrote: post #24
changoplatanero wrote: post #16

Imagine you were looking at Google, a sustainable and profitable business, and you thought you saw a once in a lifetime opportunity to compete with them and take their position as a leading tech company. How much money would you need to spend to make a credible attempt? Google has had decades to accumulate intellectual and physical capital. Catching up quickly means spending >500 billion. If you can actually dethrone…

What a strange train of thought. Why would you need that amount in this hypothetical? Why would dethroning them alone be worth it? It would literally only be worth it if you could do so profitably. More realistically, it seems like someone calculated that it could still be profitable up to several hundreds of billions of dollars which explains the initial investment. And continued investment can be explained by tryin…

I think the opposite is true. To dethrone the top tech company, you need to be able to spend much less than them, at higher efficiency and faster growth. Google didn’t catch up to Microsoft and Apple by spending more, they caught up by developing business lines and flywheels that were much more capital efficient.

If it’s a spending game, the incumbent has a huge advantage.

Re: AI is too expensive

#80

Post by luk212 »

A lot of the current AI economics seems to depend on three assumptions being true at once: 1. inference costs fall fast enough 2. usage grows into very large recurring revenue 3. customers don't cut once handed the bill

We should draw a distinction between "AI is valuable" and "AI justifies its current investment levels." There's real productivity value in AI, especially for things like search, boilerplate, tests, refactoring, etc...BUT that doesn't mean every enterprise should let token spend grow without strict telemetry, cost-attribution and outcome-based measurements.

The teams that win here will not be the ones using the Most AI, but the ones that treat it like any other expensive production dependency, which means measuring unit economics, cap runway usage, properly align models with tasks(not just Opus everything), and scale workflows with ROI in mind.

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