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Mizza | 5 months ago

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.

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frfl|5 months ago

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|5 months ago

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

ACCount37|5 months ago

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.

HWR_14|5 months ago

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|5 months ago

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|5 months ago

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

brookst|5 months ago

$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|5 months ago

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

Mizza|5 months ago

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.

techpineapple|5 months ago

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

simianwords|5 months ago

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|5 months ago

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

mathw|5 months ago

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