The point is that if they’re not profitable they won’t be relevant since they’re so expensive to run.

And there was never any question as to how social media would make money, everyone knew it would be ads. LLMs can’t do ads without compromising the product.

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tsukikage 9 hours ago | parent | next [-]

You’re not thinking evil enough. LLMs have the potential to be much more insidious about whatever it is they are shilling. Our dystopian future will feature plausibly deniable priming.

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kridsdale3 9 hours ago | parent | prev | next [-]

Well, they haven't really tried yet.

The Meta app Threads had no ads for the first year, and it was wonderful. Now it does, and its attractiveness was only reduced by 1% at most. Meta is really good at knowing the balance for how much to degrade UX by having monetization. And the amount they put in is hyper profitable.

So let's see Gemini and GPT with 1% of response content being sponsored. I doubt we'll see a user exodus and if that's enough to sustain the business, we're all good.

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swat535 5 hours ago | parent | prev | next [-]

> LLMs can’t do ads without compromising the product.

It depends on what you mean by "compromise" here but they sure can inject ads.. like make the user wait 5 seconds, show an ad, then reply..

They can delay the response times and promote "premium" plans, etc

Lots of ways to monetize, I suppose the question is: will users tolerate it?

Based on what I've seen, the answer is yes, people will tolerate anything as long as it's "free".

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Centigonal 9 hours ago | parent | prev | next [-]

I can run an LLM on my RTX3090 that is at least as useful to me in my daily life as an AAA game that would otherwise justify the cost of the hardware. This is today, which I suspect is in the upper part of the Kuznets curve for AI inference tech. I don't see a future where LLMs are too expensive to run (at least for some subset of valuable use cases) as likely.

	▲	TeMPOraL 8 hours ago \| parent [-]
		I don't even get where this argument comes from. Pretraining is expensive, yes, but both LoRAs in diffusion models and finetunes of transformers show us that this is not the be-all, end-all; there's plenty of work being done on extensively tuning base models for cheap. But inference? Inference is dirt cheap and keeps getting cheaper. You can run models lagging 6-12 years on consumer hardware, and by this I don't mean absolutely top-shelf specs, but more of "oh cool, turns out the {upper-range gaming GPU/Apple Silicon machine} I bought a year ago is actually great at running local {image generation/LLM inference}!" level. This is not to say you'll be able to run o3 or Opus 4 on a laptop next year - larger and more powerful models obviously require more hardware resources. But this should anchor expectations a bit. We're measuring inference costs in multiples of gaming GPUs, so it's not an impending ecological disaster as some would like the world to believe - especially after accounting for data centers being significantly more efficient at this, with specialized hardware, near-100% utilization, countless of optimization hacks (including some underhanded ones).

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overfeed 8 hours ago | parent | prev | next [-]

> LLMs can’t do ads without compromising the product.

Spoiler: they are still going to do ads, their hand will be forced.

Sooner or later, investors are going to demand returns on the massive investments, and turn off the money faucet. There'll be consolidation, wind-downs and ads everywhere.

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owlninja 9 hours ago | parent | prev | next [-]

I was chatting with Gemini about vacation ideas and could absolutely picture a world where if it lists some hotels I might like, the businesses that bought some LLM ad space could easily show up more often than others.

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9 hours ago | parent | prev | next [-]

[deleted]

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Geezus_42 2 hours ago | parent | prev | next [-]

Social and search both compromised the product for ad revenue.

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lotsoweiners 5 hours ago | parent | prev [-]

To be fair, ads always compromise the product.