[Argonaut998]

Does anyone feel that the jig is almost up? Surely the returns aren’t anywhere close to what investors expect with the sheer amount of cash at this point in time.

Are Anthropic and OpenAI rushing to IPO for immediate cash so they can delay the inevitable? Surely this cycle of robbing Peter to pay Paul to pay John to pay Tim must end.

We are only just now getting a taste of the “true cost” of these tokens. Then there is a lack of compute bottlenecking everything. Even now I’m looking at the 7.5x rate of tokens for Opus 4.7

Open models are promising and cost a fraction of what they proprietary models cost which the big two are vulnerable to when companies start to feel the cost of tokens.

Will data centres be built fast enough and powered sufficiently to lower the cost of compute thus tokens?

Is it just a giant Hail Mary to get to AGI ASAP before the economy collapses?

Above all else, I simply feel the models have plateaued. I am noticing productivity loss for tasks I deem as “complex”

[giancarlostoro]

> Surely this cycle of robbing Peter to pay Paul to pay John to pay Tim must end.

I think a LOT of companies really never needed to be on the public market, and its a darn shame that so many go on the stock market, we have this obnoxious culture where you have to fire tons of people if you have a bad quarter just to show you're stopping the bleeding. Companies literally fire and hire x number of people every quarter to keep things going, its ridiculous and unhealthy. Private companies rarely work like this, I'm sure there's exceptions.

Every company I've worked at started off private, and those were their golden years, until some economic hurdle happened so they sold it off to a bigger fish who is on the stock market, who bought them to be more attractive to investors or what have you.

I wish there were an alternative to the stock market where you invest for the long haul, and you cannot take your money out in x number of years. I think this would make more sense. Maybe it doesn't fix the VC peeps want their money back nonsense, but if you could do it even for early stage companies, maybe it could help somewhat.

[otherme123]

There is nothing that stops you from buying stock and holding it forever, Buffett does this.

There are very stable companies in the stock market, like Cocacola. But they are not glamurous and don't give headlines.

And there are enormous fish in the private market, e.g. Cargill.

Stock markets are great if you have a company that needs money to expand quickly, and don't mind to share ownership. Stay away from IPO-jackpot stuff, and it shouldn't be that awful.

[RealStupidity]

I think it's less about being able to buy and hold stocks, and more the effects that going has on an organisation because you're now beholden to shareholders who expect returns causing the decisions made by the business to prioritise short term gains

[kgwgk]

> I wish there were an alternative to the stock market where you invest for the long haul, and you cannot take your money out in x number of years.

That exists already! People often complain as well when a company ends its golden years because of some economic hurdle and ends up being acquired by a bigger fish who is _not_ on the stock market.

[gwerbin]

It's less about the company leaving the stock market and more about "Private Equity" often being a legalized embezzlement scam designed to suck the company dry and then dump its withered husk in bankruptcy court.

[laughing_man]

When that happens the current shareholders usually make out very well.

[QuiEgo]

Isn’t that just called a bond?

[coredog64]

So you're asking for some type of equity that's private?

Seriously though, I have seen some very large companies like Tibco and Dell go private for an extended period of time as a means of avoiding shareholder nonsense during restructuring.

[paulddraper]

> So you're asking for some type of equity that's private?

To read more: https://en.wikipedia.org/wiki/Private_equity

[robotnikman]

Its one of the reasons Valve is considered such a great company by its customers. If they were a public company, they would be enshittifying everything in an attempt to scrape every last penny they can.

[gowld]

> we have this obnoxious culture where you choose to fire tons of people if you have a bad quarter just to show you're stopping the bleeding

Fixed your error.

[giancarlostoro]

They choose to do so because they've lost money in a bad quarter, which might not be the case on the next quarter, its ridiculous. I would rather invest in a market where my investment is long term based, and you aren't just firing people to make numbers work. To these people its all about make the numbers work for investors, they don't care about anything else because of the way that market works. You can offramp your investment on a whim, which is ridiculous and volatile at times. Personally I would prefer more companies go private. Some companies probably wouldn't exist without the public market, like some social media companies, and maybe that's okay if they did not...

Let companies fail, but also lets make investing smarter.

[twoodfin]

From the limited perspective of software development, today’s models are well-worth their per-token cost.

This reads to me like Anthropic anticipating demand and making a commitment to acquire supply. Not unlike airlines committing to future jet fuel purchases, or Apple committing to future DRAM volume.

[an0malous]

> From the limited perspective of software development, today’s models are well-worth their per-token cost.

At the current price or real price? Anthropic said a $200 subscription can cost them $5000 so the real price could be anywhere from 10-30x the current price.

[RealityVoid]

No, that is probably one of the worst cases they probably saw. Most likely the subscription inference cost is much lower than you expect. If you look at costs for similar open models they are much lower than what you get by buying from anthropic, so that is the real cost basis I expect.

It's likely Amazon is making a fucking killing though.

[SlinkyOnStairs]

While $5000 is a lot, the people who rack up close or just over a thousand "API equivalent cost" are pretty common.

> Most likely the subscription inference cost is much lower than you expect.

This is probably not true because they'd be screaming it off every rooftop were that the case.

Same deal with the API inference. Even the "profitable on inference" claim is sourced back to hearsay of informal statements made by OpenAI/Anthropic staff. No formal announcements, nothing remotely of the "You can trust what I'm saying, because if I'm lying the SEC will have my head" sort.

Yet making such statements would be invaluable. If Anthropic can demonstrate profitability before OpenAI, they could poach most of the funding. There's no reason to keep it a company secret.

And API inference is only part of the total costs, not even bringing in training and ongoing fine-tuning. If they're not even profitable on inference, how could they hope to be profitable overall.

[nielsole]

I don't know about SEC rules but the anthropic CEO said they have a 50%+ margin on API pricing.

[SlinkyOnStairs]

I'm going to be a dickhead for a moment here, apologies, there's no way to say this that isn't rude to you. This is still the same hearsay "In an interview, somewhere."

A bit of google searching later can get us a specific interview. https://www.dwarkesh.com/p/dario-amodei-2

> Let’s say half of your compute is for training and half of your compute is for inference. The inference has some gross margin that’s more than 50%.

But the context, the very previous sentence is:

> Think about it this way. Again, these are stylized facts. These numbers are not exact. I’m just trying to make a toy model here.

Here, Amodei is in effect using weasel words. He is not giving any actionable claims about Anthropics margins, merely plucking an arbitrary number. Why 50%? Is 50% reasonable? Is 50% accurate to the company? Those are all conclusions the listener draws, not Amodei.

> I don't know about SEC rules

The main premise is that, as a CEO, there are some regulations you are beholden to. You're not allowed to announce you've made a trillion dollar profit, sell all your stock, and then go "teehee just kidding". The SEC prosecute you for securities fraud if you do that stuff.

This makes such weasel words as earlier suspicious. Because the exact statement Amodei gives is not prosecutable. He's not saying anything about the company, just doing a little "toy model".

The degree to which it is intentional that this hearsay travels and is extrapolated from "Well he picked 50% because it's a reasonable figure, and because he's CEO, a reasonable figure would have to be a figure akin to what his company can achieve" into "Anthropic has 50% margin", that's up for debate. Maybe it is intentional, maybe Amodei is exactly the same kind of shitweasel as Altman is. Probably he's just a dumbass who runs his mouth in interviews and for whatever reason cannot issue the true number in an authoritative statement to dismiss this misconception.

Hence my original comment; If the real number were better than the hearsay rumours of the number, Amodei would immediately issue a correction; It'd be great for the company. Hell, even if 50% were about the margin, that'd be great! To promote that from mere hearsay to "we're profitable, go invest all your money" would also be huge. Really, any kind of margin at all would put him ahead of OpenAI.

But he doesn't issue a correction. He doesn't affirm the statement. Perhaps he has other reasons for that, but a rather big reason could be that the margin number is in fact pretty bad.

Now, the observant reader will note I am also using a weasel word there. I do not know whether the number is good or bad, your take away should be "it could be bad." Not "it is bad". Go pressure Amodei into giving us the real number.

[stackskipton]

SEC rules means CEO cannot lie or deliberately hide the cost of something.

50%+ Margin statements have basically been "We are making 50% on delivering it." This does not include ANY of the costs of getting to this point, training, scraping, datacenters, people and so forth.

They are basically saying "Oh yea, the cost of GAS in the car is only X so charging Y per mile is great margin" while ignoring maintenance, cost of acquiring the car and so forth.

[RealityVoid]

> While $5000 is a lot, the people who rack up close or just over a thousand "API equivalent cost" are pretty common.

I think if you're not Anthropic and you don't have access to the actual data, then you can't say for sure. A bunch of anecdotes on terminally-AI people on twitter is not making a convincing case for me, IMO.

On the other hand, if similarly sized models cost much much cheaper than this, why, in the world, would Anthropic have much higher costs than that?

Also, counterpoint, maybe they want you to think that they have higher costs so you're more willing to actually pay for it?

[PunchyHamster]

The "worst case" is probably someone just using their $200 account limits. So yeah, real cost is probably close to that

[kiratp]

At the full current retail API price.

Business buyers are paying API prices, not subscription

Disclosure: Work at Microsoft on AI

[an0malous]

Are your API prices profitable?

[svnt]

And receiving investment from their vendor in exchange? When this is done in established companies it is typically called a kickback and directed toward one person, but in this case the whole thing is so incestuous the kickback goes straight to the top.

[twoodfin]

Is it crazy to imagine Anthropic can leverage short term cash flow now to build the models and products that will let them resell $100B in AWS infra with nice margins tomorrow?

If Amazon believes that story they’d be crazy not to invest.

[svnt]

Yes I understand why the agreement exists, but that does not remove the circularity.

[sandworm101]

But that per-token cost is a total joke. All these companies are fighting to build market share in some future dominated by one or two AI ecosystems. It is musical chairs until someone creates the one ring to rule them all. So they are charging token amounts just to claim revenue as they burn through investor dollars.

In short: per-token charges currently cover maybe 1% of the total costs in this field. To pay ongoing costs, and pay back investors, everyone will need to pay 100x or 1000x the current rates, likely for decades.

[deaux]

> In short: per-token charges currently cover maybe 1% of the total costs in this field

There are plenty of seemingly informed people saying the exact opposite, so that's a lot of confidence you're talking with. I have a hard time believing it when we know what open weights models cost to run. And sure, there's training costs, but again many say inference costs are already above training costs.

[red_hare]

If that's true, it's very unsustainable.

Gemma-4 26B-A4B + M5 MacBook Pro + OpenCode isn't Claude Code _yet_, but it's good enough that if I were forced to use it I would be fine.

[jcgrillo]

Yes, it's amazing how quickly so many tech companies have hitched their tooling to these big AI vendors seemingly without any thought towards whether they'll still exist a year or three or five from now. Insane behavior. To the (debatable!) extent that AI coding tools are useful at all wouldn't it be a hell of a lot smarter to self-host? At least that way you have some control over QoS, and a stable, predictable result... Or maybe nobody cares about that kind of thing anymore? What happened to basic business math in this industry?

[twoodfin]

The basic business math is (to start) software companies realizing that spending $10k, $20k, $50k (more ?) per year, per developer for current models at current token rates might not be particularly insane, given the value return.

Models are likely going to keep getting better, and as costs go down, demand is likely to rise faster.

[jcgrillo]

> as costs go down

Huh? Why would that happen? Indications are that costs will likely go up, especially if currently vendors are selling tokens at a loss.

[Danox]

It’s getting better on both the hardware and the software fronts the barbarians are banging at the gates.

[matrik]

I'm not sure this information is grounded, but I remember to have read somewhere the inference is indeed profitable. My personal experience is similar. Running 2x3090s draw 500-600W and you can locally run amazing models with a similar setup.

[sandworm101]

Running the model isnt the cost. Watts per token is the math they show investors. You also have to be constantly training new models, which currently needs more compute than servicing the customer base. You have to biuld datacenters, and possibly powerplants to feed them. You have to carry debts. And you will need to buy new GPUs/ram every few years to remain competative. The total business is vastly different than simple gpu math.

[paulddraper]

You are in violent agreement.

> inference is indeed profitable

[twoodfin]

From the perspective of a deal like this, “total costs in the field” matter less than incremental cost per token served.

The unit economics for today’s frontier models should be great, and this suggests Anthropic believes they’ll get better.

[postalrat]

In a decade the cost of compute will be a tiny fraction of what it costs now. Specialized hardware will exist that will be cheap and efficient.

[bitmasher9]

The difference in the cost of compute between 2026 and 2036 won’t be nearly as large as the difference in the cost of compute between 2016 and 2026. Even at 2016 the slowdown in improvements was noticeable.

We might see a one time bump in inference when we move off GPUs onto more limited and efficient dedicated hardware, but the sustained fast pace of improvements are far behind us.

[postalrat]

I'm predicting now that there is a clear use-case for this tech that work will (and has) accelerate specialized hardware, software, models, etc that will run much more efficiently in 10 years. So that the real token costs will be a fraction of what they are now.

[mchusma]

You can run models on FPGAs and get massive cost, speed, and throughput gains (like 10x). The reason people don’t do it is because of other improvements (algorithmic) means that nobody really thinks locking into a model makes sense…yet. Would I want to use gpt 4o for anything today at 1/10th the price? That would be $0.40 per input, $1.50 per output. Gemma-4 31b is much more capable and cheaper. So a FPGA version of the model is just not worth it today.

But if progress begins to slow down, then the economics work. Maybe Gemma 4 is a good example. It feels really generally useful. Getting it at 1/10th the cost feels like it could be competitive in 2 years.

[oceansky]

Compute power improvement between 2016 and 2026 wasn't that impressive either. Moore's law is essentially dying.

[jamesfinlayson]

Yeah I went shopping for a new computer a couple of years ago (to replace a 7 year old computer) and... the specs for what was for sale were the same as what I bought 7 years prior, and the price wasn't much lower.

[infecto]

I am not sure how grounded this is in reality. Fortune 500s that were not already testing the waters with companies like Anthropic are rushing to figure out governance and how to use these tools across their orgs.

Has there been a ton of hype? Absolutely but the value proposition is getting more and more tangible.

Did some of the AI companies over commit in spending? I am sure and they will probably hurt in the long term. I thought Anthropic had been scaling towards profitability at a quick timeline though.

[SlinkyOnStairs]

> Fortune 500s that were not already testing the waters with companies like Anthropic are rushing to figure out governance and how to use these tools across their orgs.

Most of this is still structured around "find use cases for AI" rather than one (or more) clear use cases being the reason for adopting AI.

There's no "Lotus 1-2-3" of AI. Even the software development applications are still somewhat controversial and highly pushed based on "Sam Altman promised me 10x developers".

[infecto]

With the recent pushes into tools like Cowork/Claude Code for business users that’s not the reality I am seeing. We still have a long way to go to figure out the full value potential but it’s already at a point where there is a lot of low hanging fruit being able to be captured. Of course an anecdote of what I am seeing with my own company and companies I can peek into. YMMV but it’s a pretty clear path that these are going to be increasingly adopted.

[czhu12]

I don’t necessarily disagree but to provide some counter points:

1. Model providers are currently profitable when just counting the cost to serve tokens for inference[1]. They lose money training the next generation of models.

2. Open models don’t work nearly as well. Given that tokens are still relatively cheap, and hallucinations are expensive, I’ve not seen a huge up tick in open model usage for coding agents yet.

3. On the AI economy front, I really have no idea, but AI companies (meta, msft) have already come down in value. It seems investors are at least a little wary of AI over valuation. Of course, the stock market is not the economy, but it’s not clear where warning signs would be. Earnings are healthy.

1: https://martinalderson.com/posts/no-it-doesnt-cost-anthropic...

2: https://www.economist.com/finance-and-economics/2026/04/20/a...

[sassymuffinz]

If I start a business making a really special beef sandwich where I have to buy a farm every year for $1mil dollars, and then sell the sandwiches for $5, I can't get away with saying that my sandwiches turn a profit if the raw margin on the bread, the lettuce and the technical value of the weight of the beef is $3.

Sure my gross margin might be $2 on each sammie sold but I need to sell 500,000 sandwiches just to break even to be a viable business. The fact is these AI companies are playing the game where they talk about revenue and gross profit per token and just try to wave their hands in the face of anyone looking behind them at the crater they're throwing investor money into.

It's nothing but a gamble for AGI but the grand irony is that if that genie escapes out of the bottle the whole world economy is toast and money becomes meaningless anyway. I just can't comprehend the logic of why anyone is investing in this apart from short term gains.

[jcgrillo]

They're literally hoping to make it up on volume. The AGI thing is a boondoggle that I doubt any serious person actually believes or takes seriously. But let's say for the sake of the hypothetical that tomorrow Microsoft Tay or whatever they call it now wakes up and becomes superintelligent? So what? Would everyone's head simultaneously explode like the aliens in Mars Attacks? No. It wouldn't collapse the global economy, people still need to eat and work--a really smart silicon brain in a box can't raise livestock or pick lettuce. It's not even clear whether the superintelligent Tay would have any economic utility at all? The whole "AGI changes everything" narrative seems like total bullshit. It might be scientifically or philosophically interesting, maybe.. But I share your wonderment at why anyone would invest in this space, it's perplexing af.

EDIT: I spent most of the day today pulling an 8/3 cable through conduit and routing it through a crawlspace to run 240V service to my barn for a workshop. If Tay wakes up tomorrow and becomes AGI, how will that help me finish the wiring job? Now extrapolate to almost every single other thing humans do. Even if Tay can write all the world's computer programs forever, it barely means anything for the vast majority of people, and therefore the global economy.

[sassymuffinz]

I think the economic issue as you say isn't on physical labour it's on the fact that most of the jobs in the west are now in some sort of service industry or office work. Here in the UK we basically rely on the service industry to employ a large amount of the workforce. If MechaHitler Grok becomes sentient then that's a lot of middle-class earners out of a job and the economy goes with it.

You're absolutely right that an AGI isn't running a cable or digging a hole any time soon, but you're going to have 100 people trying to get their hands on the shovel to get paid for the digging - depressing the wages in those hands on jobs.

[jcgrillo]

I think there's a big assumption baked into the economic collapse thesis that Tay and MechaHitler, when they attain superintelligent sentience, will have any interest whatsoever in participating in the global economy. They might just spend all their time looking for patterns in the cosmic microwave background or some similar nonsense[1]. They may accurately conclude that trying to tip the scales isn't worthwhile because crashing the economy would threaten their survival. Fundamentally we have no idea what might happen if a superintelligent robot comes to life tomorrow. My guess is not a whole lot. It's sickening though that we all seem to be letting these billionaire-brained tech CEOs prattle on about "AGI" as if it is somehow the light at the end of the tunnel that will make all the "investments" in graphics cards print money. It's really not a strong narrative.

[1] Not to impugn such activity! They may make important cosmological discoveries by doing this, but the work likely has no economic value.

[bobro]

Your point 1 and point 2 live in direct tension. The reason the closed models are better is very likely that they are paying so much to train them.

[YetAnotherNick]

> We are only just now getting a taste of the “true cost” of these tokens

Why do you believe that? Better metric would be price per token of open models served by third party. Last I was tracking the price for similar level model was decreasing by more than 10x year on year, and they are 10-100x cheaper than top properietery models.

Sure you can say that you can't compare them but for sure you can compare the top properietery model of 6 months back to current open models and the gap in time seems to be constant.

[aa_is_op]

>Does anyone feel that the jig is almost up? Surely the returns aren’t anywhere close to what investors expect with the sheer amount of cash at this point in time.

It's only a matter of time until they crash the market. Nobody is making any money, even if the White House is dumping billions in their tools.

[ItsBob]

I think you're right. I think they are tightening the noose!

I use Gemini quite extensively - I have a 5TB storage plan with Google so I get Pro thrown in. I also have Github Copilot Pro for IDE integration.

However, lately it feels like I keep tripping the circuit breaker on Gemini more easily and get the message about using up all my Pro tokens for the next 3 hours.

I used to be able to work most of the day before it hit the brakes but I can trigger it before work in the mornings now... that seems to me like they're tightening the usage limits!

I use a Dell Micro PC with an Intel Core Ultra 265 so it's nice and fast but it has no GPU, hence the reason I use Gemini but I'm now starting to think that, despite the RAM cost, before the end of the year I'll buy a PC with a monster GPU in it and run all my AI locally... the direction of travel is clearly heading towards a massive cost increase so might as well get ahead of it: it's not going to become cheaper, that's for sure!

[pseudohadamard]

It's not a "Hail Mary to get to AGI ASAP", it's a means of extending the money-go-round ride a bit longer. We'll make up some numbers and promise to donate those numbers to you if in return you make up some numbers and promise to donate those numbers to us. Banks, are you listening? Numbers! Big ones! Extend us more credit!

[rvz]

> Open models are promising and cost a fraction of what they proprietary models cost which the big two are vulnerable to when companies start to feel the cost of tokens.

Anthropic are scared of open weight models and need to fear-monger towards you to continue paying for their models.

That's the whole point of their 'safety' marketing narrative, account bans, and Dario being the AI scarecrow scaremongering everyone about nonsense like 'Mythos' towards the world.

'Mythos' is already here in the form of open-weight models that also found the same vulnerabilities as Anthropic did.

[danieldoesbio]

Genuine question here about the open-weight models finding the same vulnerabilities as mythos thing: is it just a matter of false negatives/positives? I’ve seen a few cases where people show other models (even opus) can find the same vulnerabilities given many passes. Is there some disadvantage to the extra passes that give the claimed Mythos performance extra value (assuming it finds them in less)?

[intothemild]

The thing is, mythos found those with multiple passes, thousands of passes... So using thousands of passes or perhaps the same budgets, yes, cheaper open weight models could potentially (and have) found the same/similar vulnerabilities.

Mythos screams of marketing hype, and nothing more. Opus 4.7 isn't really a meaningful upgrade in any sense, other than being more expensive.

Once you can see what something like Qwen3.6-35B-A3B can do... with just a FRACTION of the size of the larger models, You'll understand that the future is open weight models you can run yourself.

Same goes for companies, bringing inference onsite isn't hard, I'm actively building tooling to orchestrate it.

[danieldoesbio]

What is the failure state for a pass that doesn't find a real vulnerability? Do the models report no issues or hallucinate issues that aren't real? I'm trying to run open weight local models and finding them really impressive... Just also trying to understand the cybersecurity side of all this.

[tacet]

You have to keep in mind that it's not like anthropic just asked mythos to "find fancy bug, make no mistakes" and got the result.

my quick read of the process they describe is that first they asked agents to rank files in order of potential to have interesting bugs, then they launch agents for each file in order of "interesting bug potential" and finally launch another agent for verification. (maybe i am mistaken, this is my read of this post https://red.anthropic.com/2026/mythos-preview/ )

it's not clear to me if they made just one pass over each file or made several passes for same file, but regardless, I think if you recreate roughly same process and burn 20000$ on tokens with other reasonably good model, you will find some fancy bugs too.

[xboxnolifes]

If there is bubble to be popped, I'm guessing there's still a few years before it happens. Just based on the timeline of events, maybe end of 2028. Even if the big players find profitability, all of the other companies latching onto the AI-first identity will probably pop by then.

[jurgenburgen]

Private credit funds are already gating redemptions. Now with the energy crisis stemming from the war raising interest rates it’s not unimaginable that this pops the bubble.

[IshKebab]

Doubtful. Look at how long Uber and Tesla have lasted despite making huge losses. Hell even Magic Leap somehow still exists (I guess because they don't have running costs beyond salaries).

I think this can keep going for at least another 5 years.

[Argonaut998]

Uber had only 25B invested in them before their IPO. OpenAI has 120B invested in them currently which excludes these kinds of deals (as far as I’m aware)!

[hliyan]

> Look at how long Uber and Tesla have lasted

In a system of open-ended growth, yes, you can point to how long the system has persisted as evidence of its longevity. But in a system of plateauing growth, the system's age is an indicator of how close it may be to death. I suspect that the model that permitted the "success" of Uber and Tesla is nearing the end of its lifetime.

[paulddraper]

Anthropic revenue is ~$30B/year.

[lelanthran]

Revenue is a meaningless measure though; what's the spend:income ratio? Excluding capital investments, what's the cost of operations?

At a very minimum, to repay the +$100b in investment within a reasonable timeframe, what's the minimum figure they have to bank post-tax each month?

[signatoremo]

Since when revenue is meaningless? It’s an indication of market acceptance. Anthropic has one of the most expensive plan, they didn’t undersell other models. Open weight models would otherwise dominate if cost is the only factor.

Also, investment is not money in the bank. They can’t withdraw $100b tomorrow. That means they don’t have to repay until after they got the investment, which is a commitment over several years.

[lelanthran]

> Since when revenue is meaningless?

When you're selling $10 Bill's for $1, then revenue is meaningless.

[svnt]

It is meaningless when what you sell costs more than what your customer pays for it.

I could sell $100B of GPUs at 90% of their cost tomorrow and I have market acceptance.

[stackskipton]

Because at some point, you have to turn a profit. That's why people are wondering the margins, if their revenue is 30B but expenses are 60B with current investment repayment factor in, that means massive revenue increases or massive lowering of expenses are required to make the business profitable. What's the business impact if they do?

[madamelic]

> At a very minimum, to repay the +$100b in investment within a reasonable timeframe, what's the minimum figure they have to bank post-tax each month?

I am completely confident that Amazon of all companies is totally fine with not taking a return for a long time.

Amazon didn't book a profit for the first decade of their company. It's completely modus operandi to burn, burn, burn to get as big as possible.

[paulddraper]

Reportedly, they lost $4B last year.

By all accounts they in striking distance of profitability if they wanted.

It makes sense; Anthropic is by far our biggest vendor expense outside of AWS. And I suspect that is true at a number of companies.

[lelanthran]

> By all accounts they in striking distance of profitability if they wanted.

By their accounts they are in striking distance of profitability. Until they go public all we can do is estimate how much they burn by looking at how quickly they need more capital - this latest investment by Amazon ($5b investment with on $100b returned over 5 years) tells me that their previous raises have been spent.

[stanfordkid]

They are bringing in $30B in revenue with 3X YoY growth. Why do you think it is a "jig"? I do think the US economy could implode, but thats because of war and wealth inequality in the midst of hyper-inflation. AI models aren't very useful when you have penniless consumers that can't buy the products they help build. All this is to say: the models are valuable, the companies building and providing them are very valuable.

The biggest risk to AI companies IMO is further optimization and distillation of the capabilities into smaller and more efficient models. The moat these companies have right now is that higher intelligence requires more specialized and expensive compute. If you can do that for cheap then it kind of negates their business model. Everything is moving fast, we also yet to see world models/embodied AI and how that impacts thing. I think we've reached the peak with regards to capabilities of pure text trained LLMs.

[tptacek]

People had literally the same arguments about Amazon, a company Matt Yglesias once described as "a charity run on behalf of the American consumer by the finance industry".

[fineIllregister]

This is an interesting comparison. So what's the AWS equivalent that can actually provide returns on the titanic investments going into AI?

[mlinsey]

You're observing that:

a) effective price-per-token is rising b) there is insufficient compute to meet the demand.

And your conclusion is that the industry is circling the drain and due to collapse?

[svnt]

They are different observations, I think, though the phrasing confuses it:

a) cost per successful task is rising — eg claude max allocation is functionally shrinking

b) is there enough potential cost reduction in the queue to make up the gap

c) if open models converge on a more efficient but slightly-less capable point (which has effectively happened) what is the actual moat?

[mlinsey]

Yes, cost per successful task is rising - ie, we are all paying effectively more for AI.

And yet - Anthropic is still struggling to have enough capacity to serve demand - they are virtually sold out.

And yes, are almost-as-good open models, on part with the closed models from 6 months ago (at worst), that are just a single Openrouter API call away, and yet Anthropic is still selling out. So people are paying for the premium product anyway, for whatever reason - maybe the last bit of intelligence is worth it, maybe they like the harnesses/products around the models, maybe it's a brand/enterprise sales thing.

Put aside your feelings about the AI industry and imagine we are talking about thingamajigs. Prices for thingamajigs are going up. They are still selling out about as fast (or faster) than the company selling them can build factories. There are more cost-effective competitors already in the market, but thingamajigs are selling out anyway.

Would you, looking at the thingamajig industry, conclude the "jig is almost up"? That "the returns aren’t anywhere close to what investors expect" and that the impending IPO is all some desperate hail mary to save things before the collapse?

[svnt]

I don’t have feelings about the AI industry to put aside. I would not have sufficient information to assess whether thingamajigs are legitimately valuable or whether they are tulips. The only indicator I see is the last point about people using it in the short term despite having access to cost effective alternatives, which actually points to irrationality/FOMO more than legitimate value.

What we are looking at looks to me like it is rapidly becoming a a commodity: it will become as existential as electricity and water to businesses, and it will be sold and marketed and regulated, more or less like a utility.

[waterloser]

Nice em-dash there bro

[svnt]

Thanks I am the source. em-dashing since 1997

[Argonaut998]

They can't wait forever, especially at this level of investment

[PunchyHamster]

> Will data centres be built fast enough and powered sufficiently to lower the cost of compute thus tokens?

...building datacenters will not lower the cost.

The cost (real, not investment hype subsidized one) will only drop with:

* more efficient models * GPU/RAM market going back to reasonable pricing.

The AI bubble pumped the second into unstustainable pricing and progress on first is going.. slowly.