The AI doom and gloom is so weird, and it's just turning into a bizarre echo chamber. AI is orders of magnitude more useful and transformative than Facebook was in 2005, and Meta is now one of the most valuable companies on the planet. Even if OpenAI has a down round or defaults on some loans, the technology has already proven to have dozens upon dozens of practical applications.
Disagree, no one's going to invite me to their kids birthday party via ChatGPT. It's innovation was in ads knowing so much about the people it targeted, and putting tracking pixels on every webpage with a Like button. Facebook was transformative for online surveillance
IMO LLMs will be equally transformative for online influence campaigns (aka ads + Cambridge analytica on steroids)
People are definitely going to be sending you AI generated birthday invite posters soon.
Oh and yeah, AI has already been shown to be more persuasive than the average human. It's only a matter of time before someone's paying to decide what it persuades you of
If only there were some way to avoid this persuasion by, I don't know, not using or relying on such controlled technology, or by not buying in to the hype of all the companies with vested interests in selling it
| AI is orders of magnitude more useful and transformative than Facebook was in 2005
It better be, it's taken over 40000x the funding.
The question is not whether AI is useful, the question is whether it's useful enough relative to the capital expectations surrounding it. And those expectations are higher than anything the world has ever seen.
"Useful and transformative" doesn't mean "financially successful".
A single LLM provider might have been able to get great margins and capture a significant fraction of the total economic output of (currently e.g. junior grade software engineering), but collectively they're in an all-pay auction for the hardware to train models worth paying for, and at the same on questionable margins because they need to compete with each other on cost.
They can all go bankrupt, and leave behind only trained models that normal people won't be able to run for 5 years while consumer-grade stuff catches up. Or any single one of them might win, which may not be OpenAI. Any or all may get state subsidies (US, Chinese, European, whatever).
Paid/API LLM inference is profitable, though. For example, DeepSeek R1 had "a cost profit margin of 545%" [1] (ignoring free users and using a placeholder $2/hour figure H800 GPU, which seems ballpark of real to me due to Chinese electricity subsidies). Dario has said each Anthropic model is profitable over its lifetime. (And looking at ccusage stats and thinking Anthropic is losing thousands per Claude Code user is nonsense, API prices aren't their real costs. That's why opencode gives free access to GLM 4.7 and other models: it was far cheaper than they expected due to the excellent cache hit rates.) If anyone ran out of money they would stop spending on experiments/research and training runs and be profitable... until their models were obsolete. But it's impossible for everyone to go bankrupt.
That's more of "cloud compute makes money" than "AI makes money".
If the models stop being updated, consumer hardware catches up and we can all just run them locally in about 5 years (for PCs, 7-10 for phones), at which point who bothers paying for a hosted model?
They're not arguing that AI sucks. Only that OpenAI has no hope of meeting it's financial obligations which seems pretty reasonable. And very on brand for Sam Altman. It seems pretty obvious at this point that model training is extremely expensive and affords very little moat. LLMs will continue to improve and gain adoption, but one or more companies will fall by the wayside regardless of their userbase. Google seems pretty clearly to be in pole position at this point as they have massive revenue, data, expertise and their own chips.
AI is orders of magnitude more useful and transformative than Facebook was in 2005
This makes sense because Facebook was one year old in 2005 and OpenAI is 11 years old now. Eleven is just two ones so it’s basically the same thing as one so it is sensible to make that comparison
Comments
The AI doom and gloom is so weird, and it's just turning into a bizarre echo chamber. AI is orders of magnitude more useful and transformative than Facebook was in 2005, and Meta is now one of the most valuable companies on the planet. Even if OpenAI has a down round or defaults on some loans, the technology has already proven to have dozens upon dozens of practical applications.
Disagree, no one's going to invite me to their kids birthday party via ChatGPT. It's innovation was in ads knowing so much about the people it targeted, and putting tracking pixels on every webpage with a Like button. Facebook was transformative for online surveillance
IMO LLMs will be equally transformative for online influence campaigns (aka ads + Cambridge analytica on steroids)
People are definitely going to be sending you AI generated birthday invite posters soon.
Oh and yeah, AI has already been shown to be more persuasive than the average human. It's only a matter of time before someone's paying to decide what it persuades you of
If only there were some way to avoid this persuasion by, I don't know, not using or relying on such controlled technology, or by not buying in to the hype of all the companies with vested interests in selling it
Agreed, just because something is useful for helpful doesn’t mean it’s easy to monetize.
| AI is orders of magnitude more useful and transformative than Facebook was in 2005
It better be, it's taken over 40000x the funding.
The question is not whether AI is useful, the question is whether it's useful enough relative to the capital expectations surrounding it. And those expectations are higher than anything the world has ever seen.
"Useful and transformative" doesn't mean "financially successful".
A single LLM provider might have been able to get great margins and capture a significant fraction of the total economic output of (currently e.g. junior grade software engineering), but collectively they're in an all-pay auction for the hardware to train models worth paying for, and at the same on questionable margins because they need to compete with each other on cost.
They can all go bankrupt, and leave behind only trained models that normal people won't be able to run for 5 years while consumer-grade stuff catches up. Or any single one of them might win, which may not be OpenAI. Any or all may get state subsidies (US, Chinese, European, whatever).
All kinds of outcomes are possible.
Paid/API LLM inference is profitable, though. For example, DeepSeek R1 had "a cost profit margin of 545%" [1] (ignoring free users and using a placeholder $2/hour figure H800 GPU, which seems ballpark of real to me due to Chinese electricity subsidies). Dario has said each Anthropic model is profitable over its lifetime. (And looking at ccusage stats and thinking Anthropic is losing thousands per Claude Code user is nonsense, API prices aren't their real costs. That's why opencode gives free access to GLM 4.7 and other models: it was far cheaper than they expected due to the excellent cache hit rates.) If anyone ran out of money they would stop spending on experiments/research and training runs and be profitable... until their models were obsolete. But it's impossible for everyone to go bankrupt.
[1] https://github.com/deepseek-ai/open-infra-index/blob/main/20...
I don’t think the current industry can survive without both frontier training and inference.
Getting rid of frontier training will mean open source models will very quickly catch up. The great houses of AI need to continue training or die.
In any case, best of luck (not) to the first house to do so!
That's more of "cloud compute makes money" than "AI makes money".
If the models stop being updated, consumer hardware catches up and we can all just run them locally in about 5 years (for PCs, 7-10 for phones), at which point who bothers paying for a hosted model?
They're not arguing that AI sucks. Only that OpenAI has no hope of meeting it's financial obligations which seems pretty reasonable. And very on brand for Sam Altman. It seems pretty obvious at this point that model training is extremely expensive and affords very little moat. LLMs will continue to improve and gain adoption, but one or more companies will fall by the wayside regardless of their userbase. Google seems pretty clearly to be in pole position at this point as they have massive revenue, data, expertise and their own chips.
This makes sense because Facebook was one year old in 2005 and OpenAI is 11 years old now. Eleven is just two ones so it’s basically the same thing as one so it is sensible to make that comparison
Facebook hooked me up with 4 beautiful girlfriends. I don't think Chatgpt is going to do that any time soon.