[Mizza]

What's the path to recouping that money?

Even if every major company in the US spends $100,000 a year on subscriptions and every household spends $20/month, it still doesn't seem like enough return on investment when you factor in inference costs and all the other overhead.

New medical discoveries, maybe? I saw OpenAI's announcement about gpt-bio and iPSCs which was pretty amazing, but there's a very long gap between that and commercialization.

I'm just wondering what the plan is.

[frfl]

Wasn't the plan AGI, not ROI on offering services based on current gen AI models. AGI was the winner takes all holy grail, so all this money was just buying lottery tickets in hopes of striking AGI first. At least that how I remember it, but AGI dreams may have been hampered by lack of exponential improvement in last year.

[brookst]

I’m sure somebody believed that? But I never met them.

[latexr]

> I’m sure somebody believed that?

“Somebody” like… Sam Altman? Because he said that’s what he actually believes.

https://www.startupbell.net/post/sam-altman-told-investors-b...

[frfl]

As sibling commentor mentions, Zuckerberg is dropping billions on AGI currently (or "super human intelligence", whatever the difference is). And, I don't have time to find it, but maybe Sam Altman might've said AGI is the ultimate goal at somepoint - idk, I don't pay too much attention to this stuff tbh, you'll have to look it up if you're interested.

Oh and John Carmack, of Doom fame, went off to do AGI research and raised a modest 20(?) million last I heard.

[nwsm]

I want to say Mark Zuckerberg but I think Meta's investment is also targeted at creating their own social media content

[ACCount37]

The "game plan" is, and always was, to target human labor. Some human labor is straight up replaceable by AI already, other jobs get major productivity boosts. The economic value of that is immense.

We're not even at AGI, and AI-driven automation is already rampaging through the pool of "the cheapest and the most replaceable" human labor. Things that were previously outsourced to Indian call centers are now increasingly outsourced to the datacenters instead.

Most major AI companies also believe that they can indeed hit AGI if they sustain the compute and the R&D spending.

[elzbardico]

If AI Doesn’t Fire You, It Can’t Pay For Itself https://esborogardius.substack.com/p/if-ai-doesnt-fire-you-i...

[HWR_14]

If LLMs could double the efficiency of white collar workers, major companies would be asked for far more than $100,000 a year. If could cut their expensive workforce in half and then paid even 25% of their savings it could easily generate enough revenue to make that valuation look cheap.

[mathw]

Unfortunately for the LLM vendors, that's not what we're seeing. I guess that used to be the plan, and now they're just scrambling around for whatever they can manage before it all falls apart.

[Gigachad]

Ok but then another AI company would just offer the same thing at a lower cost.

[EGreg]

How much lower though?

[Gigachad]

It'll keep going down until it's hardly over cost price.

[brookst]

$100k/year is literally nothing.

Think of it as maybe $10k/employee, figuring a conservative 10% boost in productivity against a lowball $100k/year fully burdened salary+benefits. For a company with 10,000 employees that’s $100m/year.

[34679]

That's literally not how the word "literally" works.

[jcranmer]

It literally is: https://www.merriam-webster.com/dictionary/literally

[superblas]

That’s literally how the English language works. It literally evolves

[card_zero]

It doesn't proliferate new forms without selection, that's not how evolution works.

(Heh, I see "proliferate" itself is a back-formation.)

[Mizza]

Even at $10k/yr/employee, you'd need 30 million people on the 10k/yr plan to hit 300B ARR. I think that's a hell of a big swing. 3 million, recoup over ten years? Maybe, but I still don't think so. And then competition between 4 or 5 vendors, larger customers figuring out it's cheaper to train their own models for one thing that gives them 90% of the productivity gains, etc.

But rather than speculating, I'm generally curious what the companies are saying to their investors about the matter.

[simianwords]

I don’t get why you need 300B arr?

[techpineapple]

But we won’t get there unless the company integration failure rate falls below 95%

[reb]

Eh, seems likely to me existing companies are structured for human labor in a way that's hard to really hard to untangle — smart individuals can level up with this stuff, but remaking an entire company demands human-level AI (not there yet) or a mostly AI-fluent team (working with/through AI is a new skill and few workers have developed it).

New co's built by individuals who get AI are best positioned to unlock the dramatic effects of the technology, and it's going to take time for them to eclipse encumbent players and then seed the labor market with AI-fluent talent

[simianwords]

They just have to be positive revenue on inference and run it for a long time. Why do you think they can’t recoup it?

[CyanLite2]

Major companies will spend 10-100x that if it resulted in real tangible productivity gains for their businesses.

[mathw]

I think it's "scam everyone into giving us lots of money, then run before the bills come".