ChatGPT became publicly available in November 2022, and Claude followed in March 2023. It's year 4. It's foolish to think we know who the big names will be 20 years down the line, which is the kind of timeline bond investors are thinking about. A lot of people probably wish they could have invested (or invested more) in Google or Facebook in 2006, but they are probably very glad they did not invest in Yahoo or MySpace (or Friendster or Tumblr .. you get the idea) at the time, despite looking very promising (MySpace was beating Google on pageviews on some days in '06 and '07). Instagram and Snapchat and TikTok and WeChat didn't even exist yet.
legulere 13 hours ago [-]
My favourite example is amazon.com and pets.com. In hindsight amazon looks like an obviously good investment and pets.com doesn't, however amazon was heavily invested in pets.com itself.
lanthissa 12 hours ago [-]
I don't see anything obvious about that at all for amazon in the book selling days.
dog food is heavy, and a repeat purchase that often requires its own store and brings no joy. Its the ideal thing to get delivered to your house on a schedule.
books are something you choose differently everytime, and the people that like them read recreationally.
Bezos was on another level, launching a successful company(online books) that was effectively just a way to boot strap into an everything store.
XenophileJKO 12 hours ago [-]
It was actually even smarter than that. People also forget about "media postage" rates that existed at the time. (They still exist, just fyi)
In 1999. To ship a book using media mail cost of $1.13 for the first pound and $0.45 for each pound up to 7lbs. It got cheaper per pound above that.
This meant even heavy books were relatively cheap to ship. Way cheaper than random goods.
Zanfa 4 hours ago [-]
Wasn’t one of Amazon’s biggest advantages over brick and mortar stores the fact that you could effectively avoid sales tax for a lot of the purchases?
dannyincolor 11 hours ago [-]
I believe ChatGPT or Anthropic are both trying to be the "everything store" - whatever that may look like - of this brave new world. Call it a "business OS" and/or "life OS", they're clearly aware that research alone won't win dominance, and signs have been cropping up for the last year: Cowork, Research to Artifact pipelines, Dots/Instinct/Muse-esque personal assistant alternatives.
But the counterpoint still translates here: Amazon did not start with 1000 warehouses (i.e. Anthropic's debt obligations) and _then_ race to build a marketplace that would fill them with everything under the sun. It started lean and mean, and I suspect the Anthropic-killer will do the same.
kube-system 13 hours ago [-]
And despite all of that ... Chewy is successful.
hn_throwaway_99 13 hours ago [-]
My favorite example is WebVan vs. Instacart. What a difference a decade makes.
crostlybostly 12 hours ago [-]
Uber / gig economy seems to be the biggest difference
steveBK123 9 hours ago [-]
In some ways, the biggest "new form of business/commerce" that ubiquitous smartphones lead to was the entire gig economy.
lotsofpulp 13 hours ago [-]
CHWY is -7% per year since Sep 2019, while SP500 is +16% per year, and CHWY has 2% profit margins, give or take. I don’t know what success means, but I would not have wanted to buy CHWY stock anytime after IPO.
keeganpoppen 13 hours ago [-]
your point is well-taken enough, but the idea that a sharp investor was investing in Yahoo or Myspace in 2006 is a bit silly. Myspace was bought out in 2005, and it had been dead for years before that. and I don't think I had gone to yahoo.com for any reason other than testing my internet connection anytime in the prior 10 years before that. also, investing in Google or Facebook back then would be enough to retire on, much less had you invested in a basket of tech-but-not-obviously-dead-tech stocks. from what I recall from that era, the one things I knew for sure at the time were (1) Google is gonna be around in 20 years, bigly and (2) Facebook might be DoA in terms of social media endgame, but operationally they are very strong and executing.
what I really push back on is the idea that there are magically going to be all sorts of entrants into the space that meaningfully compete with Anthropic or OpenAI in the near or even medium term. for as much as the reddit set continues to put their collective heads in the sand while screaming "there's no moat"... there is a moat, and one so prominent as to be self-evident. not once has an open-source model come even close to genuinely reaching frontier performance for anything other than cost, and cost is by definition the easiest thing to improve on-- just distill bigger model into smaller model: boom, cheaper!
deepwoods 12 hours ago [-]
>Myspace was bought out in 2005, and it had been dead for years before that.
Myspace's peak popularity (in terms of monthly unique pageviews) came in 2007. Yahoo was ahead of Google for several years, though I am struggling to find good data on the specifics there. Your understanding seems to be based in your own personal experience of those sites, which is fine, but I don't think it quite matches the big picture.
Your proposal that there won't be any new entrants is puzzling to me because, in the grand scheme of things, OpenAI and Anthropic ARE new entrants. The entire space is new. It feels like ChatGPT became public eons ago, but it hasn't even been 4 years. Imagine saying in 2008 that no photo-sharing site would ever surpass Flickr - it's been dominant for 4 years! Why would you go to something new when everyone's photos are already on there?
One absolutely enormous advantage new entrants have in the AI space is that they can start on third base. Anthropic had to spend billions and billions of dollars to get to Opus 4.6. A new entrant could distill its way into a model roughly on par with that far more cheaply, and spend its VC cash on things like marketing and price cutting rather than burning it on actually creating a good model. The existing players need to service mountains of debt and are locked into deals for compute based on outdated assumptions about efficiency. I'm not saying it would be EASY for a new entrant to waltz in, especially to the enterprise market. But it's not impossible especially on the consumer side: Meta was essentially a non-factor until Muse came out, and now most people think of Muse when they think of an AI agent (as opposed to Claude, which is just a chatbot in the public imagination, because that's what it was when it became popular).
steveBK123 9 hours ago [-]
It's not even clear that the "frontier AI lab" is going to be the best, most profitable business model to evolve out of this tech. Especially if models are easy to distill, a new lab can start on 3rd base, and China open weights aren't far behind.
The winning business model may be 1 or 2 abstractions removed from "build a really good LLM model", and yet to be revealed in the marketplace.
ipaddr 12 hours ago [-]
Most people do not think of Muse as an the ai agent. Most think OpenAI or Claude. The people using Muse are using it as a facebook chatbot.
panagathon 11 hours ago [-]
> Most people do not think of Muse as an the ai agent. Most think OpenAI or Claude. The people using Muse are using it as a facebook chatbot.
Yeah, I was with the case bring made, until that point. A very bizarre claim, especially given the questions around safety:
I disagree, Yahoo was actually seen as a technological leader and, unlike Google that was purely a search engine in its early years, Yahoo was a full platform that seemed poised for a while to become a landing page for the internet.
When it comes to AI there simply isn't a moat - Anthropic would be my best guess out of the current entrants due to them trying to construct one via value-adding code assistance tools that might create enough friction to prevent customers from jumping ship but the models themselves are a commodity that depreciates extremely quickly. If you want to retain the frontier premium you need to constantly be improving due to the ease of distillation.
edanm 12 hours ago [-]
Your comment makes the timeline seem very different from the way I remember it. Yahoo was dominant much earlier than Google, and was one of a handful of big search engines. Google was a relative newcomer at the time, which had the benefit of being way better at search, which is why it eventually dominated the competition.
BatFastard 7 hours ago [-]
I was sad on the day when my.yahoo.com shut down. It had a bunch of RSS feeds, and news, I have not found a good replacement for it.
hazbot 11 hours ago [-]
If open source models stay consistently <12 months behind the frontier, that shrinks the moat considerably; not for all use cases, but maybe enough to scupper profitability
unrented7977 15 hours ago [-]
That argument swings both ways. There's no real reason to bet on OAI or Anthropic. Not with the rise of local models and the increasingly desperate attempts at regulatory capture.
deepwoods 15 hours ago [-]
That's what I'm saying. Either one could be Facebook. Or it could be Friendster. The rise of local models raises the even more daunting possibility that nobody becomes Facebook, but you have to imagine somebody will win the consumer market for people who just don't want to bother figuring out a local setup. That market is orders of magnitude less lucrative than the enterprise market, but a company that dominated it would still be one of the hundred or so largest in the world.
999900000999 14 hours ago [-]
Someone can always optimize a model down to running on a typical 32 GB M6 or M5 Mac.
It doesn't need to be the best. It just needs to be good enough. I'm not smart enough, but if I was I'd be working on a locally ran interface engine. That's where you charge say 100$ a year. Said engine would allow you to use a large open source model locally to the point where it's good enough to rival Haiku.
If I had to guess someone is working on this
theptip 13 hours ago [-]
> Someone can always optimize a model down to running on a typical 32 GB M6 or M5 Mac. It doesn't need to be the best.
Two observations - one, there is some set of tasks where intelligence is already saturated, and sure, that threshold is rising by the month. So, sure, for some tasks you don’t need the best model. But there are other tasks that need models smarter than what we have now - like “make a cure for <disease>” that will yield billions of dollars of value, but likely require quintillions of tokens and higher IQ/token than anything we have now.
As long as we have non-saturated economically valuable tasks there will be incentive to train new and smarter models, and the frontier will always be on racks of GPUs not local distilled versions.
Two, it’s not clear that you can distill all the way down to 32GB even for the current frontier models. IIRC Karpathy has speculated that you can get an AGI into GPT-3 size, if you drop all the memorized facts and keep the reasoning core. But this is highly speculative! The best 32GB models right now are substantially dumber than even the large open-weight models, let alone the frontier closed models.
Perhaps I am missing something, what are you imagining of “a locally ran inference engine” that doesn’t already exist in a DGX workstation, Framework desktop, MacBook, etc?
999900000999 11 hours ago [-]
>Perhaps I am missing something, what are you imagining of “a locally ran inference engine” that doesn’t already exist in a DGX workstation, Framework desktop, MacBook, etc?
Someone much smarter than me would figure this out.
One option would be an alternative bare metal OS which could allocate ram more carefully.
I'm sure with billions upon billions in VC funding a solution could be found.
senordevnyc 9 hours ago [-]
Someone much smarter than me would figure this out.
Imagine if we had some kind of really intelligent AI model that we could pose problems like this to. It's obviously not the kind of thing an open weight model running on your local machine could do, but if we had some kind of really large, closed source model running in the cloud that could solve really difficult problems like this, I wonder if there'd be a market for it...
ipaddr 12 hours ago [-]
One way would be to generate a new model for every request. Currently we create an entire universe for each step when training if we predetermined what needed to be created it could be much smaller.
matltc 5 hours ago [-]
I stumbled upon this neural net compressor by Bellard that beats gzip on compression benchmarks
> like “make a cure for <disease>” that will yield billions of dollars of value
I think it's important to qualify that while I will very much appreciate such an innovation and I think it'll provide significant value to society... I remain doubtful of the ability for any company to actually capture such an astronomical yield. Either there's enough of an investment required by the company to help get that to market that the yield will be significantly lower or everyone and their brother will just launch competing products two days later. And, as a society, I don't think it's logical for someone writing "Hey Alex, cure cancer" with billions of dollars so I doubt there's going to be much appetite for creating such a moat via legislation.
This gets to the same point of "If ChatGPT can make you a successful million dollar business in a few prompts why is OpenAI sharing it" paradox. It very well may be that AI tools can accomplish the labor that used to be required to create such a business, and I'm sure a few people will land a jackpot and get rich in the transitional phase but if it's so cheap to build it why would someone pay you money for yours instead of just running the same prompting themselves? For most people that's because they lack the knowledge that they can but you'll still have a significant number of instant impersonators.
saucymew 13 hours ago [-]
Great comment, I'm working on my own Hermes/Mac Mini & the amount of sec ops/setting up its arms is a good challenge as a non-technical.
Building the iPhone-platform equivalent of this would be interesting.
999900000999 13 hours ago [-]
The thing is, would the top AI minds rather charge end users 40 to 300$ a month for AI usage of sell a 100$ a year license to run it locally.
I'm far from an expert, but I don't think it's impossible. Future models won't give out vacation ideas, they'll focus on one or two things. This might allow us to get the size down.
theptip 13 hours ago [-]
Would AI companies rather have $100/yr of license revenue or $480/yr of token revenue at 50% margin? Obviously the latter, by more than 2x? And even larger dollar profit from the higher sub levels you mention.
windexh8er 13 hours ago [-]
The constraints will work against them long term. All this is doing is forcing people to look at how to run more with less. These companies are bloated beyond reality and have no incentive to optimize anything. They're starting out with access to everything and still producing very little tangible value comparative to the inputs. OAI and Anthropic represent the pure gluttony of the US tech bro market and it's not going to be the long term winner. It can't be lest the masses are cool at crowning these narcissists as kings.
TomJansen 14 hours ago [-]
I think the hardware makers are going to have the last laugh, but not sure if that would be NVIDIA
iknowstuff 13 hours ago [-]
Rise of local models? what rise? I run qwen3.8 flash next on my 200GB/s 128gb Strix Halo and even that is barely acceptable, big models require so much more. Nobody's running a local model on their power sipping phone. It's just a nerd's wet dream.
nradov 13 hours ago [-]
That's true today, but what will it look like in 20 years? Over time, algorithms and hardware always gets faster and more efficient. Like if I wanted to run a fluid dynamics simulation, what would have required a supercomputer 20 years ago can now run on a single desktop computer.
dannyincolor 11 hours ago [-]
256x speedup on FAT32 just earlier today; I expect we'll have a nice bump in performance from domain cross-pollination for a good while now.
dannyincolor 11 hours ago [-]
barely acceptable for all use cases? like a speed issue?
Regardless, looking back even a year at SOTA local models that fit on a non-absurd system creates a crazy trendline toward the future. And I think model routing is the gap filler that can make/break now vs. Oct 2027
I suspect Anthropic is of this general thinking as well; they've clearly switched from a thoughtful progression toward a natural IPO to "omg sprint for it". Along with the regulatory capture attempts, it's hard to imagine what is breathing down their neck so hard outside of this.
Totally agree local inference of any major scale is a nerd's wet dream short of many stacked improvements in efficiency. But again, auto-routing smooths over the rough edges if you are ok with a little bit of API spend when needed.
14 hours ago [-]
dualvariable 6 hours ago [-]
Better comparison is probably the dotcom bubble, and companies like pets.com, webvan, kozmo, etoys, worldcom, global crossing, etc. It was not entirely clear to most investors in 2001 that google and amazon would make it.
nfw2 6 hours ago [-]
I don't think pets.com, an online retailer, is an apt comparison to Anthropic, an bleeding edge research lab doing things that most people would consider science fiction a few years ago.
lanthissa 12 hours ago [-]
anthropic has come up with a lot of the core successful consumer facing tooling/standards around ai.
they invented mcp, terminal coding agent, context files like claude/agents.md.
I have no real clue whos going to win the model race but they have repeatedly shown that their internal taste is on point, reminds me a lot of early google.
jacquesm 7 hours ago [-]
With one huge difference: you could never run the Google index on your local PC. But you can run a 'good enough' AI on your local PC. Good enough that Sam Altman thinks you shouldn't do it because he has better uses for your RAM than you do (oh, and besides, because it may hurt his IPO chances).
ImHereToVote 14 hours ago [-]
Why would ASI still have companies around? Seems like an inefficient way to turn the planet into computronium.
cmiles8 16 hours ago [-]
Is this a surprise?
By any sane normal sense of business and financials these AI labs look terrible on paper.
Any loan would be speculative at best, and the rating would simply reflect that.
Investing in these companies is like going wild at the casino. Sure you might make a fortune but strong odds are you’re gonna lose your shirt.
ActionHank 16 hours ago [-]
I’ve discussed with many people at work, all engineers, they’re weirdly oblivious. Most are shocked when I say things like OpenAI and Anthropic are gonna crater.
mercanlIl 15 hours ago [-]
There’s a notable difference between saying those companies may crater, and predicting confidently that they will crater. The wording of your comment makes it seem like a foregone conclusion.
ActionHank 14 hours ago [-]
Because it is, there isn’t enough money to be made to cover their valuation and their competition are essentially free by comparison.
jakeydus 10 hours ago [-]
I can’t imagine being so overleveraged that I run into economic thermodynamics. It’s like interstellar travel: there’s not enough energy available to do it quickly and at scale and efficiently. There’s not enough monetary potential energy to satisfy the buildout.
senordevnyc 9 hours ago [-]
We've been hearing this since DeepSeek was released in Jan 2025, and in that time, Anthropic's revenue has grown 100x. And they're still growing like crazy.
So...why hasn't that "essentially free" competition taken them down yet?
preg_match 6 hours ago [-]
Mostly politics combined with nobody actually knowing how to utilize AI yet. We’re just now finding a singular use-case for AI, which is coding. Every other use-case has been a complete dead end. Cool gimmicks for demos, but nothing anyone uses on any regular basis, and definitely not value creating.
Everything is very unstable right now. This is still a very new tool and we’re very much experimenting on a product level.
senordevnyc 4 hours ago [-]
Tell that to the mathematicians, translators, paralegals, financial analysts, customer support reps, etc, etc.
squidmaster 14 hours ago [-]
[dead]
ewild 15 hours ago [-]
for real i hold the opposing view i think openai will be a 5-10T dollar company in the next 5 years, but im speculating just as much as he is.
manquer 15 hours ago [-]
Just a tad bit more ; it like saying either an event will happen or not so probability is 50%.
Your scenario is certainly possible, that doesn’t make both predictions equally (un)likely.
seanw444 12 hours ago [-]
I'm also speculating that they'll kindly donate at least 1 T of that to me out of the kindness of their heart.
BoredomHeights 13 hours ago [-]
At least you admit you're speculating (we all are). They confidently just say its a foregone conclusion.
If they're actually that confident I hope they short the stock long term with basically all their money.
MadnessASAP 13 hours ago [-]
I also speculate that OpenAI and Anthropic will crater, but I also expect that the market will remain irrational much longer then anyone shorting it today will remain solvent.
So yes, I believe it's going to leave a smoking hole in the ground, but I won't be betting money on it.
antasvara 11 hours ago [-]
If you run a traditional short (borrow and sell the shares), you need to be right on the direction and the timing to make any money. One random surge in the price can kill your short even if said surge is short-lived.
threetonesun 15 hours ago [-]
I still think OpenAI holds on as a Google competitor and Anthropic does fine as a business tool. Do they match their outsized spending with future growth? Well, that I'm not very confident about. A lot of this really comes down to what is the business model of integrating AI with 3rd party systems and I don't see that anyone has truly cracked that yet.
Waterluvian 15 hours ago [-]
The complete opposite is the generally held perspective among engineers where I work. It’s the management that think they’re not going to crater.
outside1234 14 hours ago [-]
"It is difficult to get a man to understand something, when his salary depends on his not understanding it."
-Upton Sinclair
senordevnyc 9 hours ago [-]
It's ironic that this describes both the engineers and the management, depending on where you stand.
tomrod 13 hours ago [-]
Not sure about Anthropic, unless they continue to fall over themselves in ego. They have strong GTM in my take.
Google is a bit oblivious (though is probably the smarter money based on diversification alone IMHO). OpenAI has folks wondering just how publicly Mr. Altman can blunder his wording before he gets ousted (today was along the lines of "you will own nothing" with his take that personal RAM ownership being an affront to efficiency).
All three are trying to convince enterprise buyers that central tokenmaxxing is the best thing since sliced bread; many of the circles I run in occasionally have huge (emphasis: huge in the 2010s ZIRP sense) buyers that are begging for more edge AI.
bcvvvy 15 hours ago [-]
I talk to our risk lead and he was also weirdly oblivious as well. The whole company is dependent on them not going down the shitter. Surely that's a tangible risk?
I'm indifferent either way myself. It's just shocking the amount of ignorance.
giancarlostoro 15 hours ago [-]
It's the cryptobro craze but for AI. It's tiresome, I don't have AI fatigue, I love using Claude, I have aibro fatigue. I'll lump in the people all in on AI, and that includes anyone who hates it vehemently because they just have to sour conversations.
Morromist 14 hours ago [-]
Yeah. AIbros and AI companies are SHOCKED that AI and datacenters are unpopular.
But guys, if your companies weren't run by psycopaths and weren't promoted by assholes who appear to be the exact same guys behind the NFT craze, (this is the future of creative expression! Don't like it? Your a luddite. Cope.) and weren't predicting horrible nightmare scenarios based on their tech maaaaaaybe people would like AI and be more interested in using it?
I personally see that generative AI is a very powerful and useful technology but I hate everyone involved in it and do not want to see them succeed because they're icky people.
Its like if the nazis had discovered how to harness atomic energy before anyone else. Fuck that.
giancarlostoro 12 hours ago [-]
I've talked to someone who has worked at those companies, and they drink the koolaid that people like Sam Altman shove down your throat, even when its blatantly bullshit.
Note that both Sam Altman and Dario have conveniently watered down AGI, and moved away from "trying to achieve AGI" essentially.
13 hours ago [-]
Mistletoe 13 hours ago [-]
1929 all over again.
Melatonic 6 hours ago [-]
Robber Barrons are back !
Question is: Who is gonna be the Carnegie that builds libraries vs the assholes who just hoarded
aleqs 15 hours ago [-]
The model employee must live (or pretend to) inside the company's information bubble.
tintor 15 hours ago [-]
Words are cheap. Put your money and short Anthropic (when it IPOs) if you are convinced it will crater.
ActionHank 14 hours ago [-]
Are you one of those people who lost half their money to spacex? You sound like you are.
m101 13 hours ago [-]
I agree with this sentiment entirely. Too much cheap talk. If you want to talk then you should be taking a position.
bluGill 13 hours ago [-]
There is no position to take. The market will remain irrational longer than I remain solvent. But I'm not sure how long that will be
hintymad 8 hours ago [-]
How so? I thought Anthropic was very capital efficient. They still have more than 100B cash, and their inference margin is 80%.
The world is using 300T token a day. Barely anyone is using AI. This number would grow 30x. If there is anything, Google, OpenAI, Anthropic are undervalued by a great deal.
cmiles8 15 hours ago [-]
There’s no business in tokens. Zero. The only business is selling compute and Anthropic rented all its compute.
Structurally they’re in a terrible position on what’s unfolding now with the completely collapse of model valuations. With truly “open” models gaining more and more momentum models are basically worth nothing and “token” prices are collapsing to the cost of compute. That doesn’t leave anything on the table for the Anthropic and Open AI’s of the world.
cdelsolar 15 hours ago [-]
but Opus 5.5 is the best product ever made in the history of the world (yes I'm serious). There's gotta be some consideration for that.
krona 14 hours ago [-]
It has zero network effects and barely any economies of scale. It's a good product without a moat which will get replaced by any company with their own compute and cheaper energy.
I think the only way out for Anthropic is to buy a few neoclouds as they go under, but even then it's a coin flip as to if they survive the next 3 years.
Melatonic 6 hours ago [-]
Or they partially crash and get bought by Oracle. The Sun route
cmiles8 15 hours ago [-]
The market is a cold beast and doesn’t care. If things hit the fan it will happily take ownership Opus 5.5 in bankruptcy court and slit everything else out on the street.
Tanjreeve 13 hours ago [-]
If people paid a profitable price for Opus 5.5 it would not be the best product in the world and would not be slotted into so many things where it's benefiting from ubiquity. That circle needs squaring. There will be an Opus 5.5 that's a 10th of the price in a few months.
A1kmm 12 hours ago [-]
I personally don't really believe the meme that Anthropic and OpenAI are charging less than the marginal cost (cost of inference on requests). Open weight models have surpassed the abilities of their closed weight models when such claims started, and the inference costs on said open weights models are provably not so high.
Where they quite reasonably might be making a loss is their marginal costs + amortised fixed costs (training).
I predict that eventually the training expenditure is going to slow down. At that point, the large commercial providers are likely hoping they can keep inference demand up, and recoup their investment.
The driver for the training is an arms race between providers and open weights labs. But several dynamics could play out:
* Models will be seen as good enough, with only fine-tuning required, for most use cases, and demand for expensive training of foundation models drops off, stopping the arms race.
* Most of the participants cannot raise capital due to lack of market confidence in them, and there is a 'winner takes all' dynamic with the remaining provider, who can then raise costs.
I personally think the first end game is more likely than the second.
ewild 15 hours ago [-]
openai has a billion users. Ads and they know it.
cmiles8 15 hours ago [-]
The math doesn’t math here. There isn’t enough spent on online ads to dig them out of this hole.
Is that potential source of revenue? Maybe but folks are verbally very negative on AI ads.
Is that a viable business plan for Open AI? No.
arealaccount 15 hours ago [-]
Their ads aren’t converting like search ads, more like social
ejjee22s 14 hours ago [-]
Even social is charitable..
ejjee22s 14 hours ago [-]
What’s with the low quality posts?
Google search ads are highly converting because they are camouflaged.
OpenAI ads are nothing of the sort!
hakfoo 8 hours ago [-]
Google search ads used to also convert highly because they were well-targeted and positioned at the point of consumption.
If I'm searching for red widgets, it's a fairly strong indicator I'm way more likely than the average to want to BUY red widgets, so a well-placed ad for redwidgets-cheap.com didn't feel hostile.
Now when it's "I am clearly searching for red widgets but you want to railroad me into blue doohickeys because they're paying more per click", you're one step above a Taboola chumbox.
Marsymars 13 hours ago [-]
The equivalent model for chatgpt would be randomly getting replies that are generated from a prompt injected with advertiser copy and indicated by a small "sponsored reply" in the corner.
Honestly, having written that out... I'm not sure that's an outcome that's generally avoidable.
legulere 13 hours ago [-]
Google search ads are just highly optimised over now 26 years. There's no reason that OpenAI won't do the same. How successful they are going to be is not clear though.
ewild 13 hours ago [-]
No clue how it's low effort to point out ads. It's not my fault you and everyone here lacks the product creativity to see the reality that they WILL be embedded in the answers and you will not be able to tell it's an ad. This will result in a literally the best ad system the world has ever seen. They simply need to wait a few years for the general pop to be reliant on them (which if you work with kids surprise they believe everything it says) and then slowly shift this over. They will be the most valuable company in the world bar none.
Do I think it's dystopian and shitty? Yes. Doesn't mean it ain't gonna happen and doesn't mean it's not the right move for the business.
randomNumber7 1 hours ago [-]
> surprise they believe everything it says
It's not just kids in my observation.
outside1234 14 hours ago [-]
Google, I hear, is very very good at Ads
JeremyNT 15 hours ago [-]
Cost per token is going to tank; it's a race to the bottom. The frontier model providers have no moat between each other and eventually even the open weight models will be "good enough" for almost every purpose.
Right now the market is expecting something a lot more than "sells a lot of tokens" out of these things to justify their valuation.
tintor 15 hours ago [-]
The future is in private data, private models, and private APIs, which can't be distilled as easily as public APIs.
Turneyboy 17 minutes ago [-]
Well openai and anthropic are sitting on absolute treasure troves of private data that is their users' interaction with their models.
mikem170 13 hours ago [-]
Wouldn't that depend on how much data? I assume those who own the data would rather buy the hardware and create models from this data themselves, as opposed to sending their data off to someone else, or allowing it to be pirated.
oblio 14 hours ago [-]
For most of those Google is much better positioned.
DoingIsLearning 13 hours ago [-]
I disagree, the moat will be of those holding rights for valuable problem domain specific training data. Examples I can think of:
Adobe sits on a treasure trove of:
- Copyrighted multimedia
- Years of telemetry on content creation
Zeiss sits on decades of data:
- Medical imaging, and surgical footage.
- Silicon waffer inspection.
These embody a training corpus that is de facto (lawfully) out of reach of the crawler scrapper approaches of Google/Meta/OpenAI/Anthropic (even if they pirate the seas for torrents like before).
Neither Adobe or Zeiss are an AI power house but the barrier to entry has also dropped with all the movement in the field.
KempyKolibri 13 hours ago [-]
Excellent point, and one that’s not raised enough in these conversations.
ewild 15 hours ago [-]
personally thats why i think OAI is in a way better place with them targeting ads.
kube-system 13 hours ago [-]
Yeah, nobody is doubting that people want to consume tokens. We're doubting that that Google, OpenAI, or Anthropic has a significant enough moat to keep people buying their tokens there. Over the past couple years the moat has been the model. As open models are getting better, that moat is drying up. Eventually the market for "tokens" will converge with the market for compute, which is a commodity with little to no moat.
parthdesai 13 hours ago [-]
I think even if the moat dries up, you could think of tokens/inference similar to compute. There's all the open source tooling available in the world for you to rent your own bare metal servers/racks and use a white glove service, yet there is demand for cloud.
At current prices, it makes sense to self host, but if the price goes down and the demand grows across different verticals, there is room for this business.
cmiles8 15 hours ago [-]
CFOs looking at tons of 2026 token spend but with no clear ROI have joined chat.
dyauspitr 15 hours ago [-]
ROI in the space is not complicated, their revenue is already insane. You just drive down costs with fixed capex (GPUs), that will continue to pay out over 5-10 years. These are growing pains, they need to make it past the GPU scarcity/ramp up phase.
manquer 15 hours ago [-]
The CFOs he is talking about are the enterprises who are spending big money on the tokens ; they are not seeing RoI ; not hyperscalers or frontier labs
sensanaty 14 hours ago [-]
Yep, i can't disclose specific numbers but we went from $X/month/person budgets to $X-100/month recently, and this is a pretty big company with ~5000 people. From what I can tell the pursestrings are only tightening further too, too little actual real-world benefit for the obscene spend
oxag3n 8 hours ago [-]
% would be helpful, is it -1% or -100% per month per person?
cmiles8 14 hours ago [-]
Correct. The people that control the pot of money these labs ultimately need to survive seem increasingly unconvinced that giving these labs money is a good idea. At least at the levels the labs need to not go bankrupt.
qw411k 15 hours ago [-]
What GPU scarcity? Unconnected GPUs are being hoarded by the oligarchy:
Reports indicate GPUs are increasingly being put on shelves in warehouses. There’s a scarcity of power and data centers to host them, but data increasingly suggests the world has an over supply of chips at the moment.
Like most “scarcity” scenarios things flip from under supply to massive oversupply real quick. Remember during COVID when lumber got stupidly expensive and then almost overnight folks couldn’t give wood away.
rokhayakebe 15 hours ago [-]
If everyone is using AI the ROI could just keeping up with everyone else. If anything Intelligence is now becoming a tax or the cost to use the toll road.
mbesto 15 hours ago [-]
If models got smarter and an average prompt response used let's say 5k tokens instead of 10k tokens, would that change your prediction?
Point is, the number of tokens is a silly metric to proxy these companies' growth.
chpatrick 13 hours ago [-]
Everyone I know and their mom is using AI, technical or not. The question is, is it profitable to run a frontier AI lab and sell inference while spending billions on R&D.
Anthropic could be super profitable right now if they stopped developing new models. But then they'd quickly fall behind because there's not much of a moat. Maybe the only ones who will survive this are huge companies like Google with separate incomes who can swallow the cost of staying on top.
ytxm 15 hours ago [-]
I saw a (highly reputable of course) tweet a few days back suggesting all of OpenRouter's DS4 traffic would fit on a single rack of modern Nvidia kit.
ch_sm 14 hours ago [-]
Hm, that’s doubtful. I think even one instance of DS 4.1 Flash alone at ~500B parameters needs a full node (8 GPUs).
arlcode 12 hours ago [-]
4xh200 seem to be enough if you cpu offload the engrams (which is pretty typical and even expected).[1]
And these are quite old cards by now. But yeah "all of OpenRouters traffic" is gonna take more than a rack
high token usage but where is the value? How come the other s&p companies aren't killing it?
jraph 14 hours ago [-]
It's like Agile, if it doesn't work, they must be doing it wrong.
Tanjreeve 15 hours ago [-]
Well they just need to use it properly and build a bunch of software systems for them to lever..oh hang on a minute...
rokhayakebe 15 hours ago [-]
And price could drop 100x.
0x4e 14 hours ago [-]
By reading the comments I wonder if perhaps OAI & ANT are not going to be “model” companies and they are going to be the ones innovating in many fronts and cashing in for the benefits of those advancements…
What I’m trying to say here is, what if, they are staying closed strategically so they keep their most advanced models close to their chest until they make an incredible discovery. Say they cure cancer. In this case, they are taking that IP collaborating with big pharma and cashing in on the upside of such discovery.
So, what if on top of being just another enterprise and consumer product that accelerates the way we all work and live, it also becomes this factory of breakthroughs and that’s where open source models can’t compete with them.
Just speculating…
danaris 44 minutes ago [-]
We're already making huge advances toward curing cancer.
They're not coming from LLMs. They're coming from mRNA-based treatments and applying standard science to their basic principles.
And just to reinforce what djierardi said, you can't make successful new drugs and treatments for diseases just by thinking about it really hard. Practical tests are an absolute, unavoidable necessity—and not even just the final clinical tests; you have to be able to see how the molecules you're synthesizing interact with living tissue of various types, among other things, before you can even hope to test on humans.
Delegate that entirely to an LLM, and you'll end up giving clinical test subjects something that will melt their flesh, or coagulate their blood, or give them turbo-cancer. Because there is no comprehensive dataset that they can use to figure that stuff out purely by computation. We, as a civilization, simply do not yet understand biology and chemistry well enough to model it at that level.
So stop trying to figure out just how OpenAI and Anthropic are playing 12D chess and actually this situation is fantastic and will result in them saving the world. They're just greedy, selfish companies trying desperately not to be left standing when the music stops and all the chairs have disappeared.
nadermx 14 hours ago [-]
Sounds about right. About the only way you could justify the projection of making so much hand over fist.
But can they actually pull it off? Since the open models are kind of able to pull off the same things.
Maybe they can brute force faster, but not releasing allows another to scoop it.
0x4e 14 hours ago [-]
Public closed-source models remain superior on paper, to the best of my knowledge.
Now, consider they have one, two or three generations of models being tested and toyed around before being released.
Those would be the ones used for breakthroughs.
djierardi 12 hours ago [-]
> Say they cure cancer.
A pet peeve of mine.
People keep mouthing this same fantasy. But cancer is so many different cancers. And "the cure(s)" aren't just 1000 different drugs, but maybe 10,000 different candidates for each that pass into lab tests, of which maybe 1% make it to phase 1 trials, and of those maybe 10% make it all the way through phase 3, each after 5-10 years of clinical trials and $100s of millions invested each. For the most part, AI-related biotechs are largely focussing on accelerating the discovery of good candidates. But that's a tiny fraction of the pipeline, which includes lots of lab work (which can be automated) and clinical trials (which OTOH require actual human guinea pigs and years of observation and assessment). How do you meaningfully accelerate that? Presumably by improving the odds of success in phase 3 trials from your initial candidates.
But nobody has proposed yet how LLMs can be a magic bullet here. At best they'll give you those 10,000 candidates per cancer type faster. But then you have all that lab work and clinical work to slog through, and all the likely failures you'll see in clinical trials. And there's just not enough data out there to train ML on to meaningfully improve the odds of success in clinical trials, since you'd really have to understand how your drugs work with all proteins and systems in every type of human body, e.g. "in silico" clinical trials. And we're only merely scratching the surface of that with stuff like OpenADMET.
That is, we can't even model well "how a human body works", much less "how those mechanisms go wrong in each type of cancer". But even if you could do all that, for the cures you'd need to figure out what novel, unusual, out-of-distribution thing (relative to your human model) you can throw into the system to avoid the bad behavior, that doesn't kill the person or interfere with other systems or get degraded too quickly or ... tons of other stuff.
Highly non-trivial. Maybe lower-hanging fruit is with a novel peptide or antibody, since those are better modeled with ML. But small drug-like molecules are galactic in number and not well modeled yet. ("Hey, what happens if I introduce this weird platinum-based drug into a body?" Well yeah, cisplatin is used for chemotherapy, but the body of knowledge needed to assess platinum-based drugs in a human body just doesn't exist, and ML isn't gonna intuit it from known data, nor "learn it" since that would require going down to QM, and then integrating that into its model of all human peptides and pathways.)
This is not a side-project for a chatbot company. Its a (multi-)generational project that requires buy-in from labs that can produce the requisite data.
(And okay so maybe I'm fast-and-loose above. Ideally a single "cure" would be to fix the apoptosis pathway, i.e. repair the built-in cell-death path for fast reproducing cells. But cancer cells mutate quickly and evade known avenues. Perhaps there's a generic fix? Plausible but same reasoning applies: ML doesn't have enough data to intuit a solution, if one exists. And there's no reason, a prior, to assume that one does exist. Only hope.)
0x4e 9 hours ago [-]
Great take and useful for the thought experiment.
I just feel like your taking it all as a given/fact. And maybe you’re right, but I’m not that well versed into it to say things for sure.
What I'm trying to get at is that if we’re considering a black swan event, why not consider both the bull and the bear case or even the neutral one and at least accept that we don’t know which one it will be and it may well be a coin toss…
Perhaps using “cancer” deviated things into a specific subject, but it could be anything. A drug discovery, quantum computing, etc.
Again, I’m no quantum physicist or chemist, but as a world citizen, these feel within the realm of possibilities. Just like it destroying humanity or simply just being yet another technological advancement like the computer or the internet was.
—-
I guess the people working on computers could have argued there was a 10% chance it was going to end humanity and so the people working on the internet because AI was going to come about.
—
I’d say that my final conclusion is that we don’t really know and the signals we’re getting from founders, investors, the market, here, and other people we talk to is that NOBODY KNOWS. All we can do is to continue to speculate and make bets based on hunches.
maxglute 13 hours ago [-]
IMO once AI can flywheel discovery, the entire international ip/patent system would simply break down - world is not going to allow US companies to automate innovation pipeline and horde / extract at scale, unless US somehow maintains full leading edge AI monopoly. Closed model discovering something a few months before open model and getting years of exclusivity rights is just not going to happen / last. If anything expect mass invalidation of IP which will disproportionately fuck over US incumbent IP leadership position.
keybored 14 hours ago [-]
What a movie. Act like religious whackjobs (A) who want to consume the world. In secret you have a bag of world-changing causes. The setback in the middle of the plot is the supercomputer answering something mundane to a serious question. Everyone feels defeated. But one underling is chatting with his pal subagent 3495. And he mentions the mundane answer. Then the subagent makes a critical connection; the answer is not mundane, it just needs a proper interpretation. Then they send the answer out (15 minutes later) cancer is cured. They use the patents to pay off the debts and then give them away to the public. The CEO moves to a shed on Más a Tierra with a talking parrot companion.
0x4e 14 hours ago [-]
I don’t think the cure for cancer will be the result of the prompt “tell me the cure for cancer. Make no mistakes.” But instead applying real AI and ML supercharged by recent advancements to identify genetic mutations that could possibly cure cancer or other diseases.
jorblumesea 12 hours ago [-]
if they can actually do it, they're in big trouble because no one is going to let them hoard truly novel discoveries, eg: new physics, curing cancer.
master_crab 11 hours ago [-]
Yes. I doubt they’d be able to patent those discoveries without serious litigation from the healthcare sector. The models are all “polluted” with others’ IP.
hinkley 16 hours ago [-]
An IPO is where the investors cash out to spend money on something else. It’s where the founders and early employees get rich enough to start chasing other interests, or just retire outright.
haliskerbas 16 hours ago [-]
My understanding is that the underwriting bank and early investors and institutional investors win first, then founders, after that early employees. Usually offloaded onto the robinhood crowd who excitedly buys in.
HarHarVeryFunny 15 hours ago [-]
According to this analysis of Anthropic's S-1, the founders own about 10% of the company, which at $2T valuation would mean they each make about $28B. The employees collectively own about 15% which results in some staggering math - thousands of employees making ~$100M each, even those hired as recently as last year.
Jesus. Why doesnt every man, woman, dog, chat and child work at Anthropic right now?
bix6 14 hours ago [-]
I was on my way but the train broke down again!!
danaris 42 minutes ago [-]
Because if we did, we'd each get about 1000 bucks.
You do understand how individual slices decrease in size as you divide the pie more ways, right...?
hinkley 9 hours ago [-]
Don't we, though?
guelo 15 hours ago [-]
Employee shares usually get put in a 3-6 month lockdown so they don't get to participate in the bubbly robinhood excitement.
hinkley 15 hours ago [-]
It's also often also part of the employee retention plan. If you discover your boss has lied to you shortly after an IPO or a merger, then odds are good they were trying to hold onto you by any means necessary until their bonus was paid out.
I've had several people I trusted destroy our relationship this way over the years.
bix6 14 hours ago [-]
The s1 lays out the exact schedule and let me tell you it is not a normal schedule. Is that a surprise anymore though?
guelo 12 hours ago [-]
Oh wow, I looked it up. Employee's get to sell up to 10% on day 1. That's cool for them.
willio58 4 hours ago [-]
In general I’d agree with you but where else would you go to take the money that’s more exciting than the forefront of AI in the world? Retirement makes sense, though if they wanted to retire they all could and own multi-million dollar homes and do so now, pre-IPO. Post ipo I guess you get a few super yachts and some land in Hawaii? Idk at a certain point I think these guys like the chase more than the result.
semitones 15 hours ago [-]
That certainly comes with the territory. However, being a public company offers a lot of opportunity for the company - easier access to capital, to enterprise/government contracts, and attracting talent that want less risky compensation.
Aboutplants 15 hours ago [-]
IPO = exit for a lot of people
hinkley 15 hours ago [-]
There's also a pretty big morale hit for the people who fall below the remuneration cutoff of peers they are almost as good as or feel they are better than. I've seen a few different people lose almost all of their fucks because some dweeb is buying fancy cars and they're still paying their mortgage every month.
That was a different time and that’s a very small sample of survivor bias.
tschellenbach 16 hours ago [-]
That makes sense, anthropic is in a rapidly changing market. Revenue could crater if a better model is released by a competitor. AI demand could fall behind. Doesn't seem like that will happen, but its definitely not investment-grade debt worthy either.
satellites 15 hours ago [-]
Even if Anthropic invents a godlike frontier model that can do anything, it feels like they won't have a moat for very long before competitors like DeepSeek offer something almost as good for a fraction of the price.
Imustaskforhelp 14 hours ago [-]
If AGI is created, then it will be used by someone else to create a cheaper AGI, making the finances of the person who borrowed trillions to create it in question.
An extremely hypothetical experiment but what if this is some sort of MAD (Mutually Assured Destruction) and in our timeline, we have accepted it with AI.
Deepseek can do MAD on Anthropic and release open weights model (which means that they might not earn the most or basically burn millions/billions to then give us all essentially the same thing and we would all be on equal footing, oh they also released their inference engine right now.)
This might explain why the stock market got into an bubble and is fearing itself right now.
Mutually Assured Commoditization. (Credit where it's due I pasted my comment to Chatgpt and it gave me this term ironically and it seems to fit well to the comment that I am writing, I might write a blog about it someday.)
zdragnar 13 hours ago [-]
MAD / MAC assumes everyone has the same leverage on each other- that they are all as heavily invested in capital.
Where it falls apart is when you get companies that take open models, rent compute and sell tokens at a profit, without heavy investment into research or training. They spend way less, and if they can keep distilling the frontier models, they can produce reasonable products without the massive losses of subscription plans. In your example, DeepSeek et al aren't nearly so vulnerable. There's nothing mutually assured.
It is much more of a classic race to the bottom. Every new frontier model shifts the goal posts a bit, but eventually the house of cards will crumble - or at least, that's what the market seems to be thinking will happen.
margalabargala 12 hours ago [-]
Subscription plans are not massive losses. What are you on about?
They are simply less profitable than API pricing. They are on par with what sellers of open model tokens sell for.
stackskipton 10 hours ago [-]
If you price out Subscription limits against API pricing, subscriptions are 20x-100x less depending on model and so forth.
margalabargala 9 hours ago [-]
Yes, that's accurate.
Are you trying to say "the Anthropic API surely cannot be highly marked up! Therefore subscriptions surely are selling at a loss!"? If not, I'm not sure how your comment is particularly relevant to the discussion?
gavxn 13 hours ago [-]
It would explain why Anthropic are anti open-weight too. They need the moat
ghuyyyyy 16 hours ago [-]
Demand is currently not sustainable because they - ant and OAI - refuse to raise prices.
Infact they’re going to end up in price competition unless they field an army of ‘FDE’ who go to every large firm and reorganise the operations around their models and displace labour.
johnny_canuck 15 hours ago [-]
I was under the impression this was only on the consumer side? I have heard of contracts expiring and them wanting a lot more money now (forcing from generously subsidized enterprise seat plans to all API usage). Specifically Anthropic in this case.
bushbaba 12 hours ago [-]
GitHub copilot then comes in and offers multi provider support including open source models, and gets the contract due to Microsoft’s existing establishment and lower price point.
Anthropic can’t raise their prices without loosing market share of Claude code
tptacek 15 hours ago [-]
How unusual is this? Amazon spent over a decade with junk ratings.
rchaud 15 hours ago [-]
Amazon didn’t borrow anywhere near this much. They also had the sales tax loophole that let them outprice the competition and take their market share for over a decade.
tptacek 15 hours ago [-]
Right, OK, but then that's the interesting or newsworthy claim, not the company's ratings status --- junk status for companies that later went on to become among the most successful in the entire marketplace is not unprecedented.
pera 2 hours ago [-]
It is the combination of several facts what makes this unprecedented, junk rating being one of these
enraged_camel 15 hours ago [-]
>> Amazon didn’t borrow anywhere near this much.
Amazon also did not go from ~$1B revenue to $16B in one year.
manquer 15 hours ago [-]
Meh rookie numbers you give me $250B too and keep doing that every year I will generate revenue $125B revenue easy. I only have to sell a dollar for 50 cents .
Same Amazon to develop AWS to profitable business spent only 30B in all capex (including e-commerce) over 12 years between 2003-15 .
xxajsg 15 hours ago [-]
[flagged]
mercanlIl 15 hours ago [-]
As someone who uses Claude Code daily for work, I fail to see how they lack a real product. It provides tangible value on a day-to-day basis, something my workplace is happy to pay for.
The more interesting questions aren’t about whether they have a real product (they do). It’s whether they can defend that product from competitors, such that their future revenues can justify the massive investments made.
tptacek 15 hours ago [-]
Anthropic has one of the most successful consumer products of all time.
Tanjreeve 15 hours ago [-]
The consumer product is losing them money and the possibly profitable enterprise product (API) is a smaller % of revenue and in an increasingly competitive niche. The constant disingenuous baiting and switching between the two whenever convenient is very tiresome.
tptacek 14 hours ago [-]
That is a different argument and not one I'm engaging with. The claim was made that Anthropic has no product, which is just obviously false.
runarberg 15 hours ago [-]
Really? The most successful consumer product? of all time?
tptacek 14 hours ago [-]
Among them, clearly.
runarberg 14 hours ago [-]
Self evidently so, I suppose.
Perhaps I am just blind to consumer markets, but it is not self evident for me, at least. When I think of successful consumer products, I think of stuff like Coca Cola, the light bulb, the CD, acrylic paint. Are you saying that Claude is as successful consumer products as the Ford model T, and Nike sneakers? I am not buying it.
tptacek 13 hours ago [-]
Anthropic, founded just 5 years ago, has revenue comparable to all of Nike.
runarberg 8 hours ago [-]
I think speed to market and revenue of the company are nonsensical measures of successful consumer products. Like did Theranos have a successful consumer product? How about Juul?
tptacek 8 hours ago [-]
No? Theranos generated under $1MM in total revenue. Juul is obviously a highly successful consumer product.
ralphington 15 hours ago [-]
The anti-ai lab crowd is becoming increasingly cult like and putting their blinders up.
dia80 14 hours ago [-]
Anthropic's S-1 (IPO doc) says they will spend >$0.5T. Where is that money going to come from? The gap between the frontier and the open models isn't large enough to generate anything like that in operating profits. Debt markets are getting tapped out with AI debt. We are about to find out how much stomach equity investors have remaining. The fact that they might have trouble servicing their current and expected future debt comes as no surprise.
dgellow 13 hours ago [-]
The S1 actually said it has $855B of commitment. Above $1T of you take in account some that don’t have fixed prices like extra TPUs and the Broadcom agreement. And that they will also build their own infrastructure, on top of that.
isolay 16 hours ago [-]
I’ve already stashed the popcorn.
6thbit 14 hours ago [-]
It would make sense that they'd be considered high risk borrowers.
But that won't stop them from issuing bonds or more convertible notes as they have and the market may or may not bite.
It does add pressure to their IPO proceedings being as high as possible as their funding mechanism tho. But reduces pressure on them if shares crash a bit after that, still high risk borrowers.
doctorpangloss 14 hours ago [-]
"Hey Mr. Inference Provider, you can sell tokens for $0.03 that cost you $0.02, to PRC end users who are too poor to use Claude or don't like that it refuses their use case, which is spam, scams and cheating on homework.
Or, you can trade $0.03 of tokens that cost you $0.02 for $1.00 in ANTHROPIC SHARES, which makes the thing that everyone uses for like, math discoveries and curing cancer."
Average Hacker News commenter (not you): "Nooooooo it's not profitable Anthropic is going to crater nobody will take their convertible notes"
dofm 16 hours ago [-]
That this is only "may not" is the shocker.
luke5441 16 hours ago [-]
Same thing as with SpaceX. If there is that much of an equity buffer, it should be investment grade.
That it isn't means that the bond market doesn't trust the valuations at all.
Varelion 16 hours ago [-]
I'm so excited to see these companies crater.
jjallen 13 hours ago [-]
No offense to them, but in general, investment grade companies should have a stable future and not have easily-switchable, competing products that cost a fraction as much to use come out regularly. This is almost laughable that I have to say this.
16 hours ago [-]
rvz 16 hours ago [-]
Many companies IPO'd in the late 1990s and did not exist 10 years later.
Let's say that the house of cards crashes down and takes the market with it who will shutdown, survive or have no choice but to get acquired for a 90% discount.
Some will be just alive long enough for the early investors to pull out enough before the market crashes.
jonas21 16 hours ago [-]
And who will be the Amazon and grow 2500x over the next 30 years?
Now, I'm not saying that's going to happen -- but if you take analogies from the dot-com era and assume they're going to play out in the same way, you can't just cherry-pick the bad ones.
zirkonit 15 hours ago [-]
Amazon had valuation of $60M at their first venture round, and it took them 19 years to 3500x it to $200B.
Anthropic had valuation of $550M at their first venture round, and assuming it IPOs at roughly $2T, it will take them 5 years to give this 3500x return to their initial investors.
FloorEgg 15 hours ago [-]
Companies IPO much later now because the laws changed. They used to be forced to IPO much earlier because employees shareholders pushed them over the threshold for # or private shareholders.
So you're absolutely correct about the comparison.
That said, I bet whatever happens over the next 20 years goes beyond what any of us can imagine. I wouldn't be surprised if the winners of this paradigm are worth hundreds of trillions. Sounds ridiculous until you look backwards and valuation a and consider this is an exponential curve and time is compressing.
allenrb 15 hours ago [-]
With enough inflation, you and I might be worth hundreds of trillions. See: Zimbabwe.
FloorEgg 11 hours ago [-]
Well sure..., but what might be less obvious is that a can of beans, a tank of gas, a wig and a chair can all inflate at 2% a year while stocks and land inflate much faster.
The way we measure inflation is focused on consumption goods that everyone depends on. It doesn't take into account the stock market.
In other words we could stay around 3% in measured inflation but see ~30% annual equity inflation...
So my point is that the most valuable companies in 20 years could be worth hundreds of trillions while the cost of a can of beans is like $5, not $200.
Zimbabwe type inflation happens when the economy doesn't get more efficient at producing stuff as fast as the government prints money. If the economy increases efficiency very quickly and the government prints money to peg at 2% inflation, the products we consume only increase a little bit while scarce assets increase a lot.
This is why in the time I took a can of beans to increase in price 3x a house increased 20x.
matwood 15 hours ago [-]
> I wouldn't be surprised if the winners of this paradigm are worth hundreds of trillions.
And the winners may be not be the obvious choice.
motionlessveloc 15 hours ago [-]
And, more importantly, the dollar is inflating.
steveBK123 16 hours ago [-]
None of the current vintage of IPOs are going to 2500x in our lifetimes (inflation adjusted at least..). The VC to IPO process is totally different now.
Companies are staying private longer, raising many orders of magnitude more private funding, and IPOing straight into "top 10 biggest companies in history" size.
If you IPO at $1.5T you are already equivalent to ~1.5% of World GDP.
Thus is just for scale, as comparing GDP vs a company market cap doesn't make total sense since GDP is 1 year economic activity and market caps represent discounted future cashflows of future economic activity...
Let's say Anthropic IPOs at $1.5T and grows even 1000x over 20 years, it would be worth $1.5P (petabillion?). If it had a 20x earnings multiple like google this would imply Net Income of $75T. Mag7 total Net Income for 2025 was $500B or $0.5B.
World GDP is $125T, and has grown less than 5%/year before/thru/after DotCom. So lets say in 20 years its $250B and Anthropic is capturing 30% of world GDP in earnings (not revenue, that would be even higher)!!
So the math doesn't math.
SatvikBeri 15 hours ago [-]
For comparison, Amazon had a valuation of $500 million at IPO, roughly 4,000x less than Anthropic.
muvlon 16 hours ago [-]
You can cherry pick the bad ones if the point you want to make is that it's risky. Nobody is saying Anthropic is definitely going to 0, just that there is a risk.
542458 16 hours ago [-]
But from an economics perspective OAI/Antropic are more similar to Amazon than to Pets.com. Pets.com always had a heavily negative COGS - they were in the business of selling $20 bills for $15. On the flip side, Anthropic appears to be positive on COGS, and OAI could get positive by cutting limits on free and $20 plans. OAI/Anthropic are negative on the books mostly because of massive R&D expenses. This compares well to Amazon circa 1999, which was positive on COGS but negative overall due to massive buildout R&D costs.
Note that I'm not saying OAI/Anthropic are destined for success - because the rate of change combined with competition with cheap Chinese models is pretty novel in the business case history. But I am saying that pessimistic dot-com-boom comparisons don't seem to be all that deep.
motionlessveloc 15 hours ago [-]
AI subscription plans are selling $100 bills for $10, they are way more expensive to the company than people buying metered tokens.
542458 13 hours ago [-]
"they are way more expensive to the company than people buying metered tokens" is true, but that doesn't mean they're a massive loss as you imply. It could be that plans are effectively breakeven but tokens are highly profitable.
But this is further to the point that the economics are more Amazon than Pets.com. If the plans are losers, great, when they need to be profitable they kill the plans and focus on metered tokens.
what 14 hours ago [-]
> OAI/Anthropic are negative on the books mostly because of massive R&D expenses. This compares well to Amazon circa 1999, which was positive on COGS but negative overall due to massive buildout R&D costs.
Isn’t the difference that ai labs can’t stop the R&D spend? They have to continue training new models.
542458 14 hours ago [-]
There's a bunch of arguments you could make there, varying from "yes, to stay ahead of the competition" to "yes, but it'll get a lot cheaper" to "no, things will plateau eventually". All those are datapoints that IMO this isn't a great analogue to the dotcom boom.
what 8 hours ago [-]
Except their own filing shows it’s getting more expensive, not cheaper. It’s highly unlikely that they’ll ever be able to stop.
georgemcbay 16 hours ago [-]
> And who will be the Amazon and grow 2500x over the next 30 years?
Almost certainly nobody if you're tracking post-IPO growth.
And not because there won't be survivors/winners when the next crash comes (there probably will be) but because of the market changes (in the wake of legislation like the JOBS act) that result in these companies having their significant growth periods prior to IPO instead of after it.
IPOs used to be a launch pad to growth, now they are just a way for private investors to finally cash out when the company is already close to peak valuation.
yieldcrv 16 hours ago [-]
A) they’re all getting acquired by these IPO seeking ones
B) nobody is IPOing at $400 million like Amazon did except SPAC share dilution scams, that you have to be willing to pick up at $30 million a year later
C) private secondary markets solve that, for some and are pretty great
D) tokenized synthetic and SPV backed private secondary markets in crypto ecosystems like Hyperliquid give you that exposure too, so now everyone can replicate the 90s
steveBK123 16 hours ago [-]
> B) nobody is IPOing at $400 million like Amazon did
Exactly
You can't wait to IPO until you're already one of the 10 biggest companies ever AND also grow 2500x post-IPO.
Retail is now exit liquidity for Big VC.
paxy 15 hours ago [-]
Not really comparable. An IPO in the 90s is equivalent to a Series C or Series D round today.
_HMCB_ 17 hours ago [-]
What could go wrong?
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empath75 16 hours ago [-]
"Risky" doesn't mean "bad investment". All the AI companies are high risk, high reward plays, and their interest rates will reflect that.
15 hours ago [-]
kakacik 15 hours ago [-]
Yes but it removes some groups of otherwise-investors, meaning there is less interest in stocks, which pushes them up less, if not down
paxy 15 hours ago [-]
This is a bond rating. It has no direct bearing on their stock.
Tanjreeve 15 hours ago [-]
If they can't raise capital then yes that will have a huge impact on a company that's a massive tower of financial engineering as coreweave have been learning.
echelon 16 hours ago [-]
Anthropic won't let people make video games. They are on the wrong side of history.
They are so going to get disrupted. Chinese open weights models will have no such limitations, and there's no way we'll let Anthropic outlaw or ban them. (And even if they did, they can't police the whole world.)
There is no moat. Anthropic should be playing nice, not trying to create a god while holding engineers under their thumb. We will route around it.
drivebyhooting 16 hours ago [-]
I hope so. I would never bow down to such a god.
echelon 16 hours ago [-]
We demand a second amendment right to access god in a first class manner.
If the people can't access god, then we are living under a dictatorship with aims to enslave us.
neutronicus 15 hours ago [-]
> Anthropic won't let people make video games.
Wait, what?
Tadpole9181 14 hours ago [-]
People got upset that Anthropic added rejection rules for people saying "Make Pokemon in Elden Ring" . You can still make games, as long as you aren't telling Claude to recreate a specific, IP-protected game.
neutronicus 11 hours ago [-]
Thankfully GPT-Sol is pretty cavalier with academic paper IP.
Sci-hub doesn't work anymore but I can at least ask GPT what a paper says
randomNumber7 45 minutes ago [-]
Check out Annas-archive for papers.
echelon 12 hours ago [-]
And this is why open weights matter.
If you can think a thing, you should be able to prompt a thing.
please comment if you have used it to ensure other people know if it could be read
and its limited - only click if you are interested
enjoy!
neutronicus 17 hours ago [-]
> Wall Street banks earlier this week closed the North Star deal, which provides the financing for Anthropic to lease 1.5 gigawatts of Google’s semiconductors.
This line is certainly eyebrow-raising to the educated layman.
Apparently it means that anthropic is leasing a Google data center whose constituent servers draw 1.5 GW of power running representative workloads.
rubogubo 17 hours ago [-]
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joe_the_user 16 hours ago [-]
It's interesting you imagine nine shares would suffice for a large site like HN. No, the link doesn't work for me. Honestly, this kind of "sharing" seems a bit disingenuous at this point.
hoppp 16 hours ago [-]
Yeah, 9 shares and then 10k people click
bbg2401 15 hours ago [-]
Do you not feel uneasy about demonstrating such entitlement?
direwolf20 15 hours ago [-]
Yeah, if you actually want to share the article, just copy/paste its content, under a throwaway if you have to.
daviTeodoro 17 hours ago [-]
He is the article:
Roula Khalaf, Editor of the FT, selects her favourite stories in this weekly newsletter.
Blackstone told investors Anthropic may not receive an investment-grade rating immediately after going public, a reversal from its previous guidance that would complicate the AI lab’s ability to finance its massive spending.
The private capital giant told investors in Anthropic’s latest $63bn chip financing deal that the start-up is expected to receive a “high” junk rating from major credit rating agencies after its initial public offering, according to people familiar with the matter.
Blackstone is acting as an anchor investor on the deal, known as “Project North Star”, and is working with banks that stumped up financing on selling the debt on to other investors.
Anthropic filed to go public on Monday, setting up what could be the largest listing of all time next month. The AI lab’s prospectus sketched out its “bold but sane” plans to spend more than $800bn on computing infrastructure between now and 2045.
While Blackstone had told its investment partners in recent months that it was expecting an investment-grade rating for Anthropic before year-end, it has recently signalled that a rating in the double B range or above is more likely given the guidance it has received from major credit agencies, the people said.
Such a designation would limit the pool of capital that Anthropic could tap because many insurance and pension funds are restricted from taking large positions in junk-rated borrowers. As a result, the company might need to continue to rely on its suppliers with high credit ratings to support its debt-raising efforts.
US tech stocks slid to session lows on Friday following the FT’s report on Anthropic’s rating, with the Nasdaq 100 down 3.7 per cent in afternoon trading. Markets were sharply lower prior to the report after earnings from Amazon and Intel worsened fears about the sustainability of the AI boom.
“It’s all about access to credit, it really matters . . . if [Anthropic] isn’t investment grade, the cost of credit goes higher, that’s not good for anyone,” said a US tech-focused portfolio manager.
“It’s a bloodbath out there,” they added, referring to the sell-off in stocks.
Wall Street banks earlier this week closed the North Star deal, which provides the financing for Anthropic to lease 1.5 gigawatts of Google’s semiconductors. More than $42bn of the senior loans is guaranteed by Broadcom, which co-develops the chips and has an investment-grade rating, while $18bn of the junior debt is backed by the AI start-up’s lease payments.
Institutional investors covet senior debt because it takes priority over junior loans in the case of a default. Broadcom’s high A-tier credit rating was an important factor in allowing Anthropic to secure the financing.
Blackstone’s funds invested in $9bn of the junior debt at a lucrative yield of more than 10 per cent, the FT previously reported. Bankers for Anthropic and rival OpenAI have also lobbied the largest rating agencies to grant the AI labs investment-grade ratings after their IPOs.
Project North Star’s $18bn junior debt, which exposes lenders more acutely to Anthropic’s credit risk, has been assigned a double B plus rating with positive outlook from Kroll Bond Rating Agency, a slight improvement from stable outlook in a similar deal known as Project “Big Sky” four months ago. It also received a double B rating from Morningstar DBRS, the people added.
The big three credit agencies — Fitch, Moody’s and S&P — which have bigger influence on companies’ borrowing costs, have not officially issued any credit ratings for Anthropic.
Anthropic, Blackstone, KBRA, Morningstar DBRS and S&P declined to comment. Fitch and Moody’s did not respond to requests for comment.
jacquesm 16 hours ago [-]
"bold but sane" -> that sounds as if Claude wrote their prospectus?
josephine_dc 4 hours ago [-]
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mosesman 17 hours ago [-]
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theropost 14 hours ago [-]
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apercu 16 hours ago [-]
Shocking. /s
rzz3 17 hours ago [-]
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youngtaff 17 hours ago [-]
What's wrong with paying for serious news?
furyofantares 17 hours ago [-]
The problem is sharing it to a group of people who mostly aren't paying for it. It's a good way to get a thread that's just people reacting to the title, which drives HN toward just being a discussion board instead of a place to find good content.
sreekanth67 17 hours ago [-]
I would pay if its token based pay per read model. nobody want to subscribe to 10 news websites paying hundreds every month.
wslh 16 hours ago [-]
This, don't get why there was no model like this. Even understanding the complexity to reach consensus (and technology).
radlad 17 hours ago [-]
Nothing wrong with paying for serious news, but when most viewers can't read the article it probably won't get much useful discussion.
csdreamer7 16 hours ago [-]
Most news articles are not worth paying for. From leaving out details to serving an agenda; a lot of news has lost it's credibility. WSJ is a good example. It had really great long articles backed by real research before it was bought by Murdock.
isatty 17 hours ago [-]
1. Can’t be bothered
2. Never going to visit this site again and I am not going to make an account for it
I am however, okay with turning off the ad blocking if they’re running reasonable ads (not every other paragraph).
eqvinox 17 hours ago [-]
Agree with the 2 siblings: the problem is HN readers at large unable to read it, hence no useful discussion.
I'd also add: from paid online news, I also expect a moderated forum/comment section, with a human to escalate to if automatic/AI moderation fails.
paxy 16 hours ago [-]
Should everyone pay for every news source?
heromal 16 hours ago [-]
Only the ones that ask for it, obviously. What kind of stupid question is this?
lurk2 16 hours ago [-]
People who participate in forums share their insights for free and resent the friction that a paywall adds to information being diffused.
heromal 16 hours ago [-]
Nah they're just cheap.
lurk2 12 hours ago [-]
I can see why you would think that based on the low quality commentary you provide here, but you’re wrong.
12 hours ago [-]
petcat 16 hours ago [-]
Anthropic is in the worst position of the AI labs. As far as investors and "the market" are concerned, the only AI that matters is the one built into your phone, car, your TV, your smart home and appliances. Anthropic has none of that share. It's all Google, Apple, and OpenAI powering Siri.
cookingmyserver 16 hours ago [-]
Personally, I don't think that tracks. If you are measuring "share" as share of vibes or "AI adoption" sure, but having AI in a phone, TV, smart home, etc doesn't make anyone any significant money. Hyperscaling isn't happening because there is an insatiable demand for retail AI usage. People are subscription'd out. A significant portion of people don't want AI in a lot of these things, another portion don't think they need it, and the ones that are eager to adopt it can use AI to bootstrap AI tools they use through a token router. You will have some revenue from retail AI but that isn't surprising considering I quite often have to provide tech support to people to help them cancel their subscription to a calculator app they've been paying $20 a month for.
petcat 15 hours ago [-]
> People are subscription'd out
No, they're not. Maybe you are?
> A significant portion of people don't want AI in a lot of these things
Not true. People love AI. Specifically Android and iPhone AI. I doubt they even know or care about Anthropic or OpenAI.
> the ones that are eager to adopt it can use AI to bootstrap AI tools they use through a token router
Absolutely microscopic share of the overall market for "AI" users. We are hobbyists.
paxy 16 hours ago [-]
No, the only AI that matters is one that large corporations are paying for. And that is Claude.
fancyfredbot 15 hours ago [-]
That's very true but unfortunately Anthropic have locked in contracts for so much compute that they absolutely need to expand beyond the corporations currently paying them.
Realistically they need to 3x their revenue to pay for their compute. While that's plausible, I'm not convinced that it can all come from developers. Many many developers are already using Claude. I think they need consumer, or some other market too.
ghuyyyyy 16 hours ago [-]
Don’t agree with this
Personally I view it like this - did ant and OAI push the industry forward yup? Will they fail as businesses though? Yup. Why? Business economics - as long as cost efficient Chinese replica’s exist it’s fine. Unless the us govt artificially makes the frontier market large then I see no chance of a large enough market that sustains current valuations.
More intelligence alone != more progress. And more intelligence in the context of business != more productivity that shows up in financial performance.
Life is more nuanced.
alpha_squared 16 hours ago [-]
Wouldn't OpenAI be in the same boat? As far as I'm aware, they don't control any means of distribution either.
petcat 16 hours ago [-]
OpenAI models power Apple's Siri assistant
paxy 16 hours ago [-]
They powered the initial "Apple Intelligence". The newer version is Gemini.
> These new capabilities are powered by the next generation of Apple Foundation Models, custom-built in collaboration with Google and its Gemini models for deeply integrated Apple Intelligence experiences.
mattbrewsbytes 15 hours ago [-]
There are some similarities between Anthropic (or OpenAI) and WeWork. Obviously the large difference is software but there is a whole lot of leasing hardware going on (neither frontier lab owns any infrastructure as far as I can tell), long term capital commitments, short term monthly subscriptions, no real moat for the frontier labs (or a hip office rental space), etc.
I think 2027 will be when a lot of companies revisit their AI spend and ROI. Have there been measurable business benefits reported by the media outside of programming?
drakythe 15 hours ago [-]
Nothing solid. All the reporting I see is that numbers are measurable but not on the level many people expected, and that these systems are proving incapable of wholesale replacing employees, which clicks with my own knowledge of some large layoffs accompanied by press releases about streamlining corporate structures using AI and the outgoing employees asking “what AI?” Because they didn’t train an offshore team or document their department responsibilities before being let go.
My suspicion (and many others as well) is that AI is used as a way to cover for large corporate restructuring in the face of money no longer being available for “free” due to interest rates.
dog food is heavy, and a repeat purchase that often requires its own store and brings no joy. Its the ideal thing to get delivered to your house on a schedule.
books are something you choose differently everytime, and the people that like them read recreationally.
Bezos was on another level, launching a successful company(online books) that was effectively just a way to boot strap into an everything store.
In 1999. To ship a book using media mail cost of $1.13 for the first pound and $0.45 for each pound up to 7lbs. It got cheaper per pound above that.
This meant even heavy books were relatively cheap to ship. Way cheaper than random goods.
But the counterpoint still translates here: Amazon did not start with 1000 warehouses (i.e. Anthropic's debt obligations) and _then_ race to build a marketplace that would fill them with everything under the sun. It started lean and mean, and I suspect the Anthropic-killer will do the same.
what I really push back on is the idea that there are magically going to be all sorts of entrants into the space that meaningfully compete with Anthropic or OpenAI in the near or even medium term. for as much as the reddit set continues to put their collective heads in the sand while screaming "there's no moat"... there is a moat, and one so prominent as to be self-evident. not once has an open-source model come even close to genuinely reaching frontier performance for anything other than cost, and cost is by definition the easiest thing to improve on-- just distill bigger model into smaller model: boom, cheaper!
Myspace's peak popularity (in terms of monthly unique pageviews) came in 2007. Yahoo was ahead of Google for several years, though I am struggling to find good data on the specifics there. Your understanding seems to be based in your own personal experience of those sites, which is fine, but I don't think it quite matches the big picture.
Your proposal that there won't be any new entrants is puzzling to me because, in the grand scheme of things, OpenAI and Anthropic ARE new entrants. The entire space is new. It feels like ChatGPT became public eons ago, but it hasn't even been 4 years. Imagine saying in 2008 that no photo-sharing site would ever surpass Flickr - it's been dominant for 4 years! Why would you go to something new when everyone's photos are already on there?
One absolutely enormous advantage new entrants have in the AI space is that they can start on third base. Anthropic had to spend billions and billions of dollars to get to Opus 4.6. A new entrant could distill its way into a model roughly on par with that far more cheaply, and spend its VC cash on things like marketing and price cutting rather than burning it on actually creating a good model. The existing players need to service mountains of debt and are locked into deals for compute based on outdated assumptions about efficiency. I'm not saying it would be EASY for a new entrant to waltz in, especially to the enterprise market. But it's not impossible especially on the consumer side: Meta was essentially a non-factor until Muse came out, and now most people think of Muse when they think of an AI agent (as opposed to Claude, which is just a chatbot in the public imagination, because that's what it was when it became popular).
The winning business model may be 1 or 2 abstractions removed from "build a really good LLM model", and yet to be revealed in the marketplace.
Yeah, I was with the case bring made, until that point. A very bizarre claim, especially given the questions around safety:
https://www.malwarebytes.com/blog/privacy/2026/10/metas-muse...
When it comes to AI there simply isn't a moat - Anthropic would be my best guess out of the current entrants due to them trying to construct one via value-adding code assistance tools that might create enough friction to prevent customers from jumping ship but the models themselves are a commodity that depreciates extremely quickly. If you want to retain the frontier premium you need to constantly be improving due to the ease of distillation.
It doesn't need to be the best. It just needs to be good enough. I'm not smart enough, but if I was I'd be working on a locally ran interface engine. That's where you charge say 100$ a year. Said engine would allow you to use a large open source model locally to the point where it's good enough to rival Haiku.
If I had to guess someone is working on this
Two observations - one, there is some set of tasks where intelligence is already saturated, and sure, that threshold is rising by the month. So, sure, for some tasks you don’t need the best model. But there are other tasks that need models smarter than what we have now - like “make a cure for <disease>” that will yield billions of dollars of value, but likely require quintillions of tokens and higher IQ/token than anything we have now.
As long as we have non-saturated economically valuable tasks there will be incentive to train new and smarter models, and the frontier will always be on racks of GPUs not local distilled versions.
Two, it’s not clear that you can distill all the way down to 32GB even for the current frontier models. IIRC Karpathy has speculated that you can get an AGI into GPT-3 size, if you drop all the memorized facts and keep the reasoning core. But this is highly speculative! The best 32GB models right now are substantially dumber than even the large open-weight models, let alone the frontier closed models.
Perhaps I am missing something, what are you imagining of “a locally ran inference engine” that doesn’t already exist in a DGX workstation, Framework desktop, MacBook, etc?
Someone much smarter than me would figure this out.
One option would be an alternative bare metal OS which could allocate ram more carefully.
I'm sure with billions upon billions in VC funding a solution could be found.
Imagine if we had some kind of really intelligent AI model that we could pose problems like this to. It's obviously not the kind of thing an open weight model running on your local machine could do, but if we had some kind of really large, closed source model running in the cloud that could solve really difficult problems like this, I wonder if there'd be a market for it...
https://bellard.org/nncp/
I think it's important to qualify that while I will very much appreciate such an innovation and I think it'll provide significant value to society... I remain doubtful of the ability for any company to actually capture such an astronomical yield. Either there's enough of an investment required by the company to help get that to market that the yield will be significantly lower or everyone and their brother will just launch competing products two days later. And, as a society, I don't think it's logical for someone writing "Hey Alex, cure cancer" with billions of dollars so I doubt there's going to be much appetite for creating such a moat via legislation.
This gets to the same point of "If ChatGPT can make you a successful million dollar business in a few prompts why is OpenAI sharing it" paradox. It very well may be that AI tools can accomplish the labor that used to be required to create such a business, and I'm sure a few people will land a jackpot and get rich in the transitional phase but if it's so cheap to build it why would someone pay you money for yours instead of just running the same prompting themselves? For most people that's because they lack the knowledge that they can but you'll still have a significant number of instant impersonators.
Building the iPhone-platform equivalent of this would be interesting.
I'm far from an expert, but I don't think it's impossible. Future models won't give out vacation ideas, they'll focus on one or two things. This might allow us to get the size down.
Regardless, looking back even a year at SOTA local models that fit on a non-absurd system creates a crazy trendline toward the future. And I think model routing is the gap filler that can make/break now vs. Oct 2027
I suspect Anthropic is of this general thinking as well; they've clearly switched from a thoughtful progression toward a natural IPO to "omg sprint for it". Along with the regulatory capture attempts, it's hard to imagine what is breathing down their neck so hard outside of this.
Totally agree local inference of any major scale is a nerd's wet dream short of many stacked improvements in efficiency. But again, auto-routing smooths over the rough edges if you are ok with a little bit of API spend when needed.
they invented mcp, terminal coding agent, context files like claude/agents.md.
I have no real clue whos going to win the model race but they have repeatedly shown that their internal taste is on point, reminds me a lot of early google.
By any sane normal sense of business and financials these AI labs look terrible on paper.
Any loan would be speculative at best, and the rating would simply reflect that.
Investing in these companies is like going wild at the casino. Sure you might make a fortune but strong odds are you’re gonna lose your shirt.
So...why hasn't that "essentially free" competition taken them down yet?
Everything is very unstable right now. This is still a very new tool and we’re very much experimenting on a product level.
Your scenario is certainly possible, that doesn’t make both predictions equally (un)likely.
If they're actually that confident I hope they short the stock long term with basically all their money.
So yes, I believe it's going to leave a smoking hole in the ground, but I won't be betting money on it.
-Upton Sinclair
Google is a bit oblivious (though is probably the smarter money based on diversification alone IMHO). OpenAI has folks wondering just how publicly Mr. Altman can blunder his wording before he gets ousted (today was along the lines of "you will own nothing" with his take that personal RAM ownership being an affront to efficiency).
All three are trying to convince enterprise buyers that central tokenmaxxing is the best thing since sliced bread; many of the circles I run in occasionally have huge (emphasis: huge in the 2010s ZIRP sense) buyers that are begging for more edge AI.
I'm indifferent either way myself. It's just shocking the amount of ignorance.
But guys, if your companies weren't run by psycopaths and weren't promoted by assholes who appear to be the exact same guys behind the NFT craze, (this is the future of creative expression! Don't like it? Your a luddite. Cope.) and weren't predicting horrible nightmare scenarios based on their tech maaaaaaybe people would like AI and be more interested in using it?
I personally see that generative AI is a very powerful and useful technology but I hate everyone involved in it and do not want to see them succeed because they're icky people.
Its like if the nazis had discovered how to harness atomic energy before anyone else. Fuck that.
Note that both Sam Altman and Dario have conveniently watered down AGI, and moved away from "trying to achieve AGI" essentially.
Question is: Who is gonna be the Carnegie that builds libraries vs the assholes who just hoarded
Structurally they’re in a terrible position on what’s unfolding now with the completely collapse of model valuations. With truly “open” models gaining more and more momentum models are basically worth nothing and “token” prices are collapsing to the cost of compute. That doesn’t leave anything on the table for the Anthropic and Open AI’s of the world.
I think the only way out for Anthropic is to buy a few neoclouds as they go under, but even then it's a coin flip as to if they survive the next 3 years.
Where they quite reasonably might be making a loss is their marginal costs + amortised fixed costs (training).
I predict that eventually the training expenditure is going to slow down. At that point, the large commercial providers are likely hoping they can keep inference demand up, and recoup their investment.
The driver for the training is an arms race between providers and open weights labs. But several dynamics could play out:
* Models will be seen as good enough, with only fine-tuning required, for most use cases, and demand for expensive training of foundation models drops off, stopping the arms race. * Most of the participants cannot raise capital due to lack of market confidence in them, and there is a 'winner takes all' dynamic with the remaining provider, who can then raise costs.
I personally think the first end game is more likely than the second.
Is that potential source of revenue? Maybe but folks are verbally very negative on AI ads.
Is that a viable business plan for Open AI? No.
Google search ads are highly converting because they are camouflaged.
OpenAI ads are nothing of the sort!
If I'm searching for red widgets, it's a fairly strong indicator I'm way more likely than the average to want to BUY red widgets, so a well-placed ad for redwidgets-cheap.com didn't feel hostile.
Now when it's "I am clearly searching for red widgets but you want to railroad me into blue doohickeys because they're paying more per click", you're one step above a Taboola chumbox.
Honestly, having written that out... I'm not sure that's an outcome that's generally avoidable.
Do I think it's dystopian and shitty? Yes. Doesn't mean it ain't gonna happen and doesn't mean it's not the right move for the business.
It's not just kids in my observation.
Right now the market is expecting something a lot more than "sells a lot of tokens" out of these things to justify their valuation.
Adobe sits on a treasure trove of:
- Copyrighted multimedia
- Years of telemetry on content creation
Zeiss sits on decades of data:
- Medical imaging, and surgical footage.
- Silicon waffer inspection.
These embody a training corpus that is de facto (lawfully) out of reach of the crawler scrapper approaches of Google/Meta/OpenAI/Anthropic (even if they pirate the seas for torrents like before).
Neither Adobe or Zeiss are an AI power house but the barrier to entry has also dropped with all the movement in the field.
At current prices, it makes sense to self host, but if the price goes down and the demand grows across different verticals, there is room for this business.
https://www.businessinsider.com/companies-hoarding-unused-ai...
Like most “scarcity” scenarios things flip from under supply to massive oversupply real quick. Remember during COVID when lumber got stupidly expensive and then almost overnight folks couldn’t give wood away.
Point is, the number of tokens is a silly metric to proxy these companies' growth.
Anthropic could be super profitable right now if they stopped developing new models. But then they'd quickly fall behind because there's not much of a moat. Maybe the only ones who will survive this are huge companies like Google with separate incomes who can swallow the cost of staying on top.
And these are quite old cards by now. But yeah "all of OpenRouters traffic" is gonna take more than a rack
https://recipes.vllm.ai/deepseek-ai/DeepSeek-V4.1-Flash?hard...
What I’m trying to say here is, what if, they are staying closed strategically so they keep their most advanced models close to their chest until they make an incredible discovery. Say they cure cancer. In this case, they are taking that IP collaborating with big pharma and cashing in on the upside of such discovery.
So, what if on top of being just another enterprise and consumer product that accelerates the way we all work and live, it also becomes this factory of breakthroughs and that’s where open source models can’t compete with them.
Just speculating…
They're not coming from LLMs. They're coming from mRNA-based treatments and applying standard science to their basic principles.
And just to reinforce what djierardi said, you can't make successful new drugs and treatments for diseases just by thinking about it really hard. Practical tests are an absolute, unavoidable necessity—and not even just the final clinical tests; you have to be able to see how the molecules you're synthesizing interact with living tissue of various types, among other things, before you can even hope to test on humans.
Delegate that entirely to an LLM, and you'll end up giving clinical test subjects something that will melt their flesh, or coagulate their blood, or give them turbo-cancer. Because there is no comprehensive dataset that they can use to figure that stuff out purely by computation. We, as a civilization, simply do not yet understand biology and chemistry well enough to model it at that level.
So stop trying to figure out just how OpenAI and Anthropic are playing 12D chess and actually this situation is fantastic and will result in them saving the world. They're just greedy, selfish companies trying desperately not to be left standing when the music stops and all the chairs have disappeared.
But can they actually pull it off? Since the open models are kind of able to pull off the same things.
Maybe they can brute force faster, but not releasing allows another to scoop it.
Now, consider they have one, two or three generations of models being tested and toyed around before being released.
Those would be the ones used for breakthroughs.
A pet peeve of mine.
People keep mouthing this same fantasy. But cancer is so many different cancers. And "the cure(s)" aren't just 1000 different drugs, but maybe 10,000 different candidates for each that pass into lab tests, of which maybe 1% make it to phase 1 trials, and of those maybe 10% make it all the way through phase 3, each after 5-10 years of clinical trials and $100s of millions invested each. For the most part, AI-related biotechs are largely focussing on accelerating the discovery of good candidates. But that's a tiny fraction of the pipeline, which includes lots of lab work (which can be automated) and clinical trials (which OTOH require actual human guinea pigs and years of observation and assessment). How do you meaningfully accelerate that? Presumably by improving the odds of success in phase 3 trials from your initial candidates.
But nobody has proposed yet how LLMs can be a magic bullet here. At best they'll give you those 10,000 candidates per cancer type faster. But then you have all that lab work and clinical work to slog through, and all the likely failures you'll see in clinical trials. And there's just not enough data out there to train ML on to meaningfully improve the odds of success in clinical trials, since you'd really have to understand how your drugs work with all proteins and systems in every type of human body, e.g. "in silico" clinical trials. And we're only merely scratching the surface of that with stuff like OpenADMET.
That is, we can't even model well "how a human body works", much less "how those mechanisms go wrong in each type of cancer". But even if you could do all that, for the cures you'd need to figure out what novel, unusual, out-of-distribution thing (relative to your human model) you can throw into the system to avoid the bad behavior, that doesn't kill the person or interfere with other systems or get degraded too quickly or ... tons of other stuff.
Highly non-trivial. Maybe lower-hanging fruit is with a novel peptide or antibody, since those are better modeled with ML. But small drug-like molecules are galactic in number and not well modeled yet. ("Hey, what happens if I introduce this weird platinum-based drug into a body?" Well yeah, cisplatin is used for chemotherapy, but the body of knowledge needed to assess platinum-based drugs in a human body just doesn't exist, and ML isn't gonna intuit it from known data, nor "learn it" since that would require going down to QM, and then integrating that into its model of all human peptides and pathways.)
This is not a side-project for a chatbot company. Its a (multi-)generational project that requires buy-in from labs that can produce the requisite data.
(And okay so maybe I'm fast-and-loose above. Ideally a single "cure" would be to fix the apoptosis pathway, i.e. repair the built-in cell-death path for fast reproducing cells. But cancer cells mutate quickly and evade known avenues. Perhaps there's a generic fix? Plausible but same reasoning applies: ML doesn't have enough data to intuit a solution, if one exists. And there's no reason, a prior, to assume that one does exist. Only hope.)
I just feel like your taking it all as a given/fact. And maybe you’re right, but I’m not that well versed into it to say things for sure.
What I'm trying to get at is that if we’re considering a black swan event, why not consider both the bull and the bear case or even the neutral one and at least accept that we don’t know which one it will be and it may well be a coin toss…
Perhaps using “cancer” deviated things into a specific subject, but it could be anything. A drug discovery, quantum computing, etc.
Again, I’m no quantum physicist or chemist, but as a world citizen, these feel within the realm of possibilities. Just like it destroying humanity or simply just being yet another technological advancement like the computer or the internet was.
—-
I guess the people working on computers could have argued there was a 10% chance it was going to end humanity and so the people working on the internet because AI was going to come about.
—
I’d say that my final conclusion is that we don’t really know and the signals we’re getting from founders, investors, the market, here, and other people we talk to is that NOBODY KNOWS. All we can do is to continue to speculate and make bets based on hunches.
These are averages, but still!
https://x.com/AndrewBenson/status/2115458726396310008
You do understand how individual slices decrease in size as you divide the pie more ways, right...?
I've had several people I trusted destroy our relationship this way over the years.
An extremely hypothetical experiment but what if this is some sort of MAD (Mutually Assured Destruction) and in our timeline, we have accepted it with AI.
Deepseek can do MAD on Anthropic and release open weights model (which means that they might not earn the most or basically burn millions/billions to then give us all essentially the same thing and we would all be on equal footing, oh they also released their inference engine right now.)
This might explain why the stock market got into an bubble and is fearing itself right now.
Mutually Assured Commoditization. (Credit where it's due I pasted my comment to Chatgpt and it gave me this term ironically and it seems to fit well to the comment that I am writing, I might write a blog about it someday.)
Where it falls apart is when you get companies that take open models, rent compute and sell tokens at a profit, without heavy investment into research or training. They spend way less, and if they can keep distilling the frontier models, they can produce reasonable products without the massive losses of subscription plans. In your example, DeepSeek et al aren't nearly so vulnerable. There's nothing mutually assured.
It is much more of a classic race to the bottom. Every new frontier model shifts the goal posts a bit, but eventually the house of cards will crumble - or at least, that's what the market seems to be thinking will happen.
They are simply less profitable than API pricing. They are on par with what sellers of open model tokens sell for.
Are you trying to say "the Anthropic API surely cannot be highly marked up! Therefore subscriptions surely are selling at a loss!"? If not, I'm not sure how your comment is particularly relevant to the discussion?
Infact they’re going to end up in price competition unless they field an army of ‘FDE’ who go to every large firm and reorganise the operations around their models and displace labour.
Anthropic can’t raise their prices without loosing market share of Claude code
Amazon also did not go from ~$1B revenue to $16B in one year.
Same Amazon to develop AWS to profitable business spent only 30B in all capex (including e-commerce) over 12 years between 2003-15 .
The more interesting questions aren’t about whether they have a real product (they do). It’s whether they can defend that product from competitors, such that their future revenues can justify the massive investments made.
Perhaps I am just blind to consumer markets, but it is not self evident for me, at least. When I think of successful consumer products, I think of stuff like Coca Cola, the light bulb, the CD, acrylic paint. Are you saying that Claude is as successful consumer products as the Ford model T, and Nike sneakers? I am not buying it.
But that won't stop them from issuing bonds or more convertible notes as they have and the market may or may not bite.
It does add pressure to their IPO proceedings being as high as possible as their funding mechanism tho. But reduces pressure on them if shares crash a bit after that, still high risk borrowers.
Or, you can trade $0.03 of tokens that cost you $0.02 for $1.00 in ANTHROPIC SHARES, which makes the thing that everyone uses for like, math discoveries and curing cancer."
Average Hacker News commenter (not you): "Nooooooo it's not profitable Anthropic is going to crater nobody will take their convertible notes"
Let's say that the house of cards crashes down and takes the market with it who will shutdown, survive or have no choice but to get acquired for a 90% discount.
Some will be just alive long enough for the early investors to pull out enough before the market crashes.
Now, I'm not saying that's going to happen -- but if you take analogies from the dot-com era and assume they're going to play out in the same way, you can't just cherry-pick the bad ones.
Anthropic had valuation of $550M at their first venture round, and assuming it IPOs at roughly $2T, it will take them 5 years to give this 3500x return to their initial investors.
So you're absolutely correct about the comparison.
That said, I bet whatever happens over the next 20 years goes beyond what any of us can imagine. I wouldn't be surprised if the winners of this paradigm are worth hundreds of trillions. Sounds ridiculous until you look backwards and valuation a and consider this is an exponential curve and time is compressing.
The way we measure inflation is focused on consumption goods that everyone depends on. It doesn't take into account the stock market.
In other words we could stay around 3% in measured inflation but see ~30% annual equity inflation...
So my point is that the most valuable companies in 20 years could be worth hundreds of trillions while the cost of a can of beans is like $5, not $200.
Zimbabwe type inflation happens when the economy doesn't get more efficient at producing stuff as fast as the government prints money. If the economy increases efficiency very quickly and the government prints money to peg at 2% inflation, the products we consume only increase a little bit while scarce assets increase a lot.
This is why in the time I took a can of beans to increase in price 3x a house increased 20x.
And the winners may be not be the obvious choice.
Companies are staying private longer, raising many orders of magnitude more private funding, and IPOing straight into "top 10 biggest companies in history" size.
If you IPO at $1.5T you are already equivalent to ~1.5% of World GDP.
Thus is just for scale, as comparing GDP vs a company market cap doesn't make total sense since GDP is 1 year economic activity and market caps represent discounted future cashflows of future economic activity...
Let's say Anthropic IPOs at $1.5T and grows even 1000x over 20 years, it would be worth $1.5P (petabillion?). If it had a 20x earnings multiple like google this would imply Net Income of $75T. Mag7 total Net Income for 2025 was $500B or $0.5B.
World GDP is $125T, and has grown less than 5%/year before/thru/after DotCom. So lets say in 20 years its $250B and Anthropic is capturing 30% of world GDP in earnings (not revenue, that would be even higher)!!
So the math doesn't math.
Note that I'm not saying OAI/Anthropic are destined for success - because the rate of change combined with competition with cheap Chinese models is pretty novel in the business case history. But I am saying that pessimistic dot-com-boom comparisons don't seem to be all that deep.
But this is further to the point that the economics are more Amazon than Pets.com. If the plans are losers, great, when they need to be profitable they kill the plans and focus on metered tokens.
Isn’t the difference that ai labs can’t stop the R&D spend? They have to continue training new models.
Almost certainly nobody if you're tracking post-IPO growth.
And not because there won't be survivors/winners when the next crash comes (there probably will be) but because of the market changes (in the wake of legislation like the JOBS act) that result in these companies having their significant growth periods prior to IPO instead of after it.
IPOs used to be a launch pad to growth, now they are just a way for private investors to finally cash out when the company is already close to peak valuation.
B) nobody is IPOing at $400 million like Amazon did except SPAC share dilution scams, that you have to be willing to pick up at $30 million a year later
C) private secondary markets solve that, for some and are pretty great
D) tokenized synthetic and SPV backed private secondary markets in crypto ecosystems like Hyperliquid give you that exposure too, so now everyone can replicate the 90s
Exactly You can't wait to IPO until you're already one of the 10 biggest companies ever AND also grow 2500x post-IPO.
Retail is now exit liquidity for Big VC.
They are so going to get disrupted. Chinese open weights models will have no such limitations, and there's no way we'll let Anthropic outlaw or ban them. (And even if they did, they can't police the whole world.)
There is no moat. Anthropic should be playing nice, not trying to create a god while holding engineers under their thumb. We will route around it.
If the people can't access god, then we are living under a dictatorship with aims to enslave us.
Wait, what?
Sci-hub doesn't work anymore but I can at least ask GPT what a paper says
If you can think a thing, you should be able to prompt a thing.
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enjoy!
This line is certainly eyebrow-raising to the educated layman.
Apparently it means that anthropic is leasing a Google data center whose constituent servers draw 1.5 GW of power running representative workloads.
Blackstone told investors Anthropic may not receive an investment-grade rating immediately after going public, a reversal from its previous guidance that would complicate the AI lab’s ability to finance its massive spending.
The private capital giant told investors in Anthropic’s latest $63bn chip financing deal that the start-up is expected to receive a “high” junk rating from major credit rating agencies after its initial public offering, according to people familiar with the matter.
Blackstone is acting as an anchor investor on the deal, known as “Project North Star”, and is working with banks that stumped up financing on selling the debt on to other investors.
Anthropic filed to go public on Monday, setting up what could be the largest listing of all time next month. The AI lab’s prospectus sketched out its “bold but sane” plans to spend more than $800bn on computing infrastructure between now and 2045.
An investment-grade credit rating is central to those ambitions, enabling Anthropic to borrow at lower rates to finance its AI infrastructure projects. The group has cash and equivalents of more than $112bn, and investors anticipate it could raise about $100bn more in the IPO. Sign reading "Blackstone" outside the Blackstone headquarters in New York, with pedestrians and city lights reflected in the glass. Blackstone’s funds have invested in $9bn of the junior debt at a lucrative yield of more than 10% © Angus Mordant/Bloomberg
While Blackstone had told its investment partners in recent months that it was expecting an investment-grade rating for Anthropic before year-end, it has recently signalled that a rating in the double B range or above is more likely given the guidance it has received from major credit agencies, the people said.
Such a designation would limit the pool of capital that Anthropic could tap because many insurance and pension funds are restricted from taking large positions in junk-rated borrowers. As a result, the company might need to continue to rely on its suppliers with high credit ratings to support its debt-raising efforts.
US tech stocks slid to session lows on Friday following the FT’s report on Anthropic’s rating, with the Nasdaq 100 down 3.7 per cent in afternoon trading. Markets were sharply lower prior to the report after earnings from Amazon and Intel worsened fears about the sustainability of the AI boom.
“It’s all about access to credit, it really matters . . . if [Anthropic] isn’t investment grade, the cost of credit goes higher, that’s not good for anyone,” said a US tech-focused portfolio manager.
“It’s a bloodbath out there,” they added, referring to the sell-off in stocks.
Wall Street banks earlier this week closed the North Star deal, which provides the financing for Anthropic to lease 1.5 gigawatts of Google’s semiconductors. More than $42bn of the senior loans is guaranteed by Broadcom, which co-develops the chips and has an investment-grade rating, while $18bn of the junior debt is backed by the AI start-up’s lease payments.
Institutional investors covet senior debt because it takes priority over junior loans in the case of a default. Broadcom’s high A-tier credit rating was an important factor in allowing Anthropic to secure the financing.
Blackstone’s funds invested in $9bn of the junior debt at a lucrative yield of more than 10 per cent, the FT previously reported. Bankers for Anthropic and rival OpenAI have also lobbied the largest rating agencies to grant the AI labs investment-grade ratings after their IPOs.
Project North Star’s $18bn junior debt, which exposes lenders more acutely to Anthropic’s credit risk, has been assigned a double B plus rating with positive outlook from Kroll Bond Rating Agency, a slight improvement from stable outlook in a similar deal known as Project “Big Sky” four months ago. It also received a double B rating from Morningstar DBRS, the people added.
The big three credit agencies — Fitch, Moody’s and S&P — which have bigger influence on companies’ borrowing costs, have not officially issued any credit ratings for Anthropic.
Anthropic, Blackstone, KBRA, Morningstar DBRS and S&P declined to comment. Fitch and Moody’s did not respond to requests for comment.
2. Never going to visit this site again and I am not going to make an account for it
I am however, okay with turning off the ad blocking if they’re running reasonable ads (not every other paragraph).
I'd also add: from paid online news, I also expect a moderated forum/comment section, with a human to escalate to if automatic/AI moderation fails.
No, they're not. Maybe you are?
> A significant portion of people don't want AI in a lot of these things
Not true. People love AI. Specifically Android and iPhone AI. I doubt they even know or care about Anthropic or OpenAI.
> the ones that are eager to adopt it can use AI to bootstrap AI tools they use through a token router
Absolutely microscopic share of the overall market for "AI" users. We are hobbyists.
Realistically they need to 3x their revenue to pay for their compute. While that's plausible, I'm not convinced that it can all come from developers. Many many developers are already using Claude. I think they need consumer, or some other market too.
Personally I view it like this - did ant and OAI push the industry forward yup? Will they fail as businesses though? Yup. Why? Business economics - as long as cost efficient Chinese replica’s exist it’s fine. Unless the us govt artificially makes the frontier market large then I see no chance of a large enough market that sustains current valuations.
More intelligence alone != more progress. And more intelligence in the context of business != more productivity that shows up in financial performance.
Life is more nuanced.
https://www.apple.com/newsroom/2026/09/siri-ai-a-profoundly-...
> These new capabilities are powered by the next generation of Apple Foundation Models, custom-built in collaboration with Google and its Gemini models for deeply integrated Apple Intelligence experiences.
I think 2027 will be when a lot of companies revisit their AI spend and ROI. Have there been measurable business benefits reported by the media outside of programming?
My suspicion (and many others as well) is that AI is used as a way to cover for large corporate restructuring in the face of money no longer being available for “free” due to interest rates.