They dropped the price $2/mo on their with-ads plan to make a bigger gap between the no-ads plan and the ads plan, and the analyst here looks at their reported ad revenue and user numbers to estimate $12/mo per user from ads.
Whether Meta across all their properties does more than $144/yr in ads is an open question; long-form video ads are sold at a premium but Facebook/IG users see a LOT of ads across a lot of Meta platforms. The biggest advantage in ad-$-per-user Hulu has is that it's US-only. ChatGPT would also likely be considered premium ad inventory, though they'd have a delicate dance there around keeping that inventory high-value, and selling enough ads to make it worthwhile, without pissing users off too much.
Here they estimate a much lower number for ad revenue per Meta user, like $45 bucks a year - https://www.statista.com/statistics/234056/facebooks-average... - but that's probably driven disproportionately by wealth users in the US and similar countries compared to the long tail of global users.
One problem for LLM companies compared to media companies is that the marginal cost of offering the product to additional users is quite a bit higher. So business models, ads-or-subscription, will be interesting to watch from a global POV there.
One wonders what the monetization plan for the "writing code with an LLM using OSS libraries and not interested in paying for enterprise licenses and such" crowd will be. What sort of ads can you pull off in those conversations?
If we’re already paying $20/mo and they’re operating at a loss, what’s the next move (assuming we’re only worth an extra $300/yr with ads?)
The math doesn’t add up, unless we stop training new models and degrade the ones currently in production, or have some compute breakthrough that makes hardware + operating costs an order of magnitudes cheaper.
We're very clearly heading toward a future where there will be a heavily ad-supported free tier, a cheaper (~$20/month) consumer tier with no ads or very few ads, and a business tier ($200-$1000/month) that can actually access state of the art models.
Like Spotify, the free tier will operate at a loss and act as a marketing funnel to the consumer tier, the consumer tier will operate at a narrow profit, and the business tier for the best models will have wide profit margins.
ChatGPT isn't going to capture all the engagement. And even then I don't know whether $300 is much particularly after subtracting operating overhead. I'm just saying I have trouble believing there's gold to be had at the end of this LLM ad rainbow. People just seem to throw out ideas like "ads!" as if it's a sure fire winning lottery ticket or something.
My point is that someone starting an airline can't get away with hopes and dreams about making bank on ads.
I'm quite confident they're not operating at a loss on those subscriptions.
of course there are a lot valuable use cases. irrelevant in the context, though.
the productivity boosts in the creative industries will additionally lower the standards and split the public even further, ensuring that if you want quality, you have to fuck over as many people as possible, so that you can afford quality ( and an ad-free life, of course. if you want a peaceful peripheral, pay up. it's extortion 404, 101 - 303 already successfully implemented on social media, TV and the radio ).
they don't lose. they make TONS OF FAKE MONEY everywhere in the, again, cough,
"ecosystem".
It's important to understand the Amazon part. The amount of damaging mechanisms that platform anchored in workers, jobbers, business people and consumers is brutal.
All those mechanisms converge in more, easy money and a quicker deterioration of local environments, leading to worse health and more business opportunities that aim at mitigating damage; almost entirely in vain, of course, because the worst is accelerating much quicker; it's easier money.
At the same time peoples psychology is primed for bad business practices, literally making people dumber and lowering their standards to make them easier targets. Don't look at the bottom to see this, look at the upper middle class and above.
It's a massive net loss for civilization and humanity. A brutal net negative impact overall.
My key technical complaint about LLMs to date is the general inability to add substantial local context. How can I make it understand my business, my processes, my approach to the market? Can I retrain it? Or make it understand my data warehouse?
I think you are explaining why LLM providers don't care about solving my concerns, generally speaking. This is sobering.
Anthropic has said they have made money on every model so far, just not enough to train the next model, which so far has been much more costly to train every generation. At some point they will probably train an unprofitable model if training costs keep rising dramatically.
OpenAI burns more money on their free tier and might be spending more money building out for future training (I don't know if they do or not) but they both make money on their $20 subscriptions for sure. Inference is very cheap.