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I think OpenAI and Anthropic will go bust, or at least be scrapped for parts in the next 5 years or so. It's clear that the extreme cost used up for training is

by dvt 13d ago

I think OpenAI and Anthropic will go bust, or at least be scrapped for parts in the next 5 years or so. It's clear that the extreme cost used up for training is impossible to recoup, as inference is already being subsidized. It's also clear that, as Tan indicates, open-weight models will be (and basically already are) just as good as frontier models. It's all about the harness, baby. We will have two main forks in the road, and two new industries created: - AI hardware (NVidia/Cerebras/etc.), the equivalent of Intel/AMD - AI software (harnesses, assistants, etc.) the equivalent of Microsoft/Apple We already saw a glimmer of this with popularity of OpenClaw—the problem is that it's janky, hard to set up, inconsistent, and very hacker-esque. Imo "AI labs" will be a dying breed because there's no real money in the actual models if they get commoditized, which they already kind of are.

FanaHOVA 13d ago
If harness is all that matters, a co-developed harness + model stack + large compute availability advantage + massive distribution advantage with data for post training will win the market.
- willy_k 13d ago
  Inb4 Apple buys OAI in 10 years and gets 75% of the consumer market.
Legend2440 13d ago
>inference is already being subsidized. Inference is not being subsidized and in fact has pretty high margins. Similar-sized open weight models on openrouter are 15x cheaper per token than the big labs. This should reflect the isolated cost of inference, since 3rd party hosts have no reason to subsidize and no training costs to amortize. Only datacenter buildout costs are being subsidized.
- dvt 13d ago
  > Inference is not being subsidized and in fact has pretty high margins. I was referring to the "AI labs" here. Sam Altman himself conceded that OpenAI is losing money on the $200 subscription. Using open-weight/open-source models is indeed cheaper (and no reason for inference to be subsidized).
  - Legend2440 13d ago
    That's not what I mean. If competitors can offer tokens 15x cheaper, the big labs must have high margins per token. (which they can use to amortize training costs) >Sam Altman himself conceded that OpenAI is losing money on the $200 subscription. They have since stopped offering the $200 subscription, probably for this reason. Subscription margins are harder to judge because it depends on usage; token costs are a better comparison.
- reticulates 13d ago
  The majority of revenue comes from API usage. The majority of usage comes from subscriptions. For any of the numbers to make any sense, subscriptions must be subsidized ergo the majority of usage is subsidized. A single $200 subscription can incur upwards of $10,000 in API equivalent usage (and even more when there are frequent resets). If it were true that Anthropic and OpenAI were profitable on all inference they wouldn’t need to constantly raise so much money. Anthropic regularly announce huge investments in infrastructure but it is all smoke and mirrors, data center build out costs aren’t being paid by OpenAI and Anthropic, they’re financed externally. Google, for example, are backstopping tens of billions of datacenter build outs that are being financed based on commitments but not investment from Anthropic. You are underestimating the insanity of subscription subsidization. Being profitable on API inference is meaningless when it is such a small proportion of usage and is only going to fall off a cliff as cheap open weight models become more capable. https://hraness.com/writing/my-girlfriend-asked-me-why-i-have https://hraness.com/writing/my-girlfriend-asked-me-why-i-hav... The absolute majority of tokens are being subsidized and as soon as the subsidies end usage will fall off a cliff, rendering all the data center buildout a terrible waste of money.
  - delecti 13d ago
    > The majority of usage comes from subscriptions Do we know that? As I understand it, enterprise customers pay more. Do we know the usage breakdown between monthly subscribers vs enterprise accounts? I agree that it's inevitable that subsidized subscriptions are unlikely to last forever, but that's not the only assumption in your argument. Edit: I think "enterprise customers pay more" was poorly phrased. I mean that enterprise customers are charged per token, presumably with a profit margin, and thus are not subsidized. While personal accounts are (thought to be) highly subsidized if you consistently max out the quotas. We also don't know what proportion of personal accounts do that though, which is another big question mark.
  - rovr138 13d ago
    I think you're also missing a quirk and that is, is everyone on a $200 plan using $10,000 worth of equivalent API spend? I know people that have the most expensive plan on all the platforms... because The other side to that is, what is 'cost'? Is cost just inference or are expenses also being taken into account? Because the expenses of these companies are huge to build the models.
- denverllc 13d ago
  > Inference is not being subsidized and in fact has pretty high margins. 1. Companies are trying to decrease costs, not increase it, and are looking at alternatives 2. Competitors are catching up, and even if the frontier labs are "better" at some things (like writing plans or complicated analysis), the competitors can take a lot of the inference on routine tasks like implementing a well-defined plan 3. The frontier labs don't just need to have high margins right now. They have to pay back their massive liabilities.
kilroy123 13d ago
I think this is very possible. Plus, something I don't see talked about enough here. The VERY fragile supply chain that keeps it all going. Look at what is happening in the Middle East. The US can no longer keep global trade secure on the high seas. What if the supply chains for GPUs get disrupted for months, a year? Then what? I fear Google will win in the longer run.
hn993302 13d ago
If inference needs to be subsidized to be economical (idk if true), open models have the same problem.
- galleywest200 13d ago
  I agree with this statement in general, but it “hurts less” to spend money when you are running things yourself. Hard for me to give a specific definition as to why, but it may be more palatable to companies to burn their own cash on their own hardware. Maybe it is “sunked cost” or maybe it is “I will do it myself dammit”.
  - hn993302 13d ago
    Wouldn't it be the other way around? They're all using cloud services already for things that they could run themselves.
teravor 12d ago
> inference is already being subsidized idk where this comes from but it's laughably false. the only place where actual subsidization (below cost) might be happening are the subscriptions. even that is unlikely because to be truly below cost you either need to offer below cost of electricity which isn't happening, have potential API users using multiple subscriptions or have opportunity cost loss due to saturation.
nullbio 12d ago
It would probably be for the best if they did, and training became something that humans did collaboratively.

by dvt 13d ago

FanaHOVA 13d ago

If harness is all that matters, a co-developed harness + model stack + large compute availability advantage + massive distribution advantage with data for post training will win the market.

willy_k 13d ago
Inb4 Apple buys OAI in 10 years and gets 75% of the consumer market.

Legend2440 13d ago

>inference is already being subsidized. Inference is not being subsidized and in fact has pretty high margins. Similar-sized open weight models on openrouter are 15x cheaper per token than the big labs. This should reflect the isolated cost of inference, since 3rd party hosts have no reason to subsidize and no training costs to amortize. Only datacenter buildout costs are being subsidized.

dvt 13d ago
> Inference is not being subsidized and in fact has pretty high margins. I was referring to the "AI labs" here. Sam Altman himself conceded that OpenAI is losing money on the $200 subscription. Using open-weight/open-source models is indeed cheaper (and no reason for inference to be subsidized).
- Legend2440 13d ago
  That's not what I mean. If competitors can offer tokens 15x cheaper, the big labs must have high margins per token. (which they can use to amortize training costs) >Sam Altman himself conceded that OpenAI is losing money on the $200 subscription. They have since stopped offering the $200 subscription, probably for this reason. Subscription margins are harder to judge because it depends on usage; token costs are a better comparison.
reticulates 13d ago
The majority of revenue comes from API usage. The majority of usage comes from subscriptions. For any of the numbers to make any sense, subscriptions must be subsidized ergo the majority of usage is subsidized. A single $200 subscription can incur upwards of $10,000 in API equivalent usage (and even more when there are frequent resets). If it were true that Anthropic and OpenAI were profitable on all inference they wouldn’t need to constantly raise so much money. Anthropic regularly announce huge investments in infrastructure but it is all smoke and mirrors, data center build out costs aren’t being paid by OpenAI and Anthropic, they’re financed externally. Google, for example, are backstopping tens of billions of datacenter build outs that are being financed based on commitments but not investment from Anthropic. You are underestimating the insanity of subscription subsidization. Being profitable on API inference is meaningless when it is such a small proportion of usage and is only going to fall off a cliff as cheap open weight models become more capable. https://hraness.com/writing/my-girlfriend-asked-me-why-i-have https://hraness.com/writing/my-girlfriend-asked-me-why-i-hav... The absolute majority of tokens are being subsidized and as soon as the subsidies end usage will fall off a cliff, rendering all the data center buildout a terrible waste of money.
- delecti 13d ago
  > The majority of usage comes from subscriptions Do we know that? As I understand it, enterprise customers pay more. Do we know the usage breakdown between monthly subscribers vs enterprise accounts? I agree that it's inevitable that subsidized subscriptions are unlikely to last forever, but that's not the only assumption in your argument. Edit: I think "enterprise customers pay more" was poorly phrased. I mean that enterprise customers are charged per token, presumably with a profit margin, and thus are not subsidized. While personal accounts are (thought to be) highly subsidized if you consistently max out the quotas. We also don't know what proportion of personal accounts do that though, which is another big question mark.
- rovr138 13d ago
  I think you're also missing a quirk and that is, is everyone on a $200 plan using $10,000 worth of equivalent API spend? I know people that have the most expensive plan on all the platforms... because The other side to that is, what is 'cost'? Is cost just inference or are expenses also being taken into account? Because the expenses of these companies are huge to build the models.
denverllc 13d ago
> Inference is not being subsidized and in fact has pretty high margins. 1. Companies are trying to decrease costs, not increase it, and are looking at alternatives 2. Competitors are catching up, and even if the frontier labs are "better" at some things (like writing plans or complicated analysis), the competitors can take a lot of the inference on routine tasks like implementing a well-defined plan 3. The frontier labs don't just need to have high margins right now. They have to pay back their massive liabilities.

kilroy123 13d ago

I think this is very possible. Plus, something I don't see talked about enough here. The VERY fragile supply chain that keeps it all going. Look at what is happening in the Middle East. The US can no longer keep global trade secure on the high seas. What if the supply chains for GPUs get disrupted for months, a year? Then what? I fear Google will win in the longer run.

hn993302 13d ago

If inference needs to be subsidized to be economical (idk if true), open models have the same problem.

galleywest200 13d ago
I agree with this statement in general, but it “hurts less” to spend money when you are running things yourself. Hard for me to give a specific definition as to why, but it may be more palatable to companies to burn their own cash on their own hardware. Maybe it is “sunked cost” or maybe it is “I will do it myself dammit”.
- hn993302 13d ago
  Wouldn't it be the other way around? They're all using cloud services already for things that they could run themselves.

teravor 12d ago

> inference is already being subsidized idk where this comes from but it's laughably false. the only place where actual subsidization (below cost) might be happening are the subscriptions. even that is unlikely because to be truly below cost you either need to offer below cost of electricity which isn't happening, have potential API users using multiple subscriptions or have opportunity cost loss due to saturation.

nullbio 12d ago

It would probably be for the best if they did, and training became something that humans did collaboratively.