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.
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!
>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).
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.
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.
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.
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.
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.
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.
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.
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.
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.
> 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?
>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.
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.
> 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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
People have a hard time detaching the tech from the business. That a successful and revolutionary tech paradigm isn't necessarily very profitable. I think these LLMs are fantastic but they're race to the bottom commodities that are terrible from a profit standpoint and they're expensive to run with high capex requirements.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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
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
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.
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.
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.
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.
People keep mouthing this same wish. But cancer is so many different cancers. And "the cure(s)" aren't just 1000 different drugs, but maybe 1000 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.
Nobody has proposed yet how LLMs can be a magic bullet here. At best they'll give you those 1000 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.
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.
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.
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.
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.
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.
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.
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.
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.
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 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.
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.
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.)
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.
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.
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.
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
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.
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.
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.
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.
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 .
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.
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.
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.
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.
"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"
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.
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.
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.
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.
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.
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.
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.
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)!!
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.
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.
"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.
> 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.
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.
> 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.
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
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.
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.
> 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.
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.
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.
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.
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.
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.
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.
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.
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.
> 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.
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?
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.
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).
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.
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.
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.
In 1999. To ship a book using media mail cost of $1.13 for the first pound and $0.45 for each pound up to 7lbs. It got cheaper per pound above that.
This meant even heavy books were relatively cheap to ship. Way cheaper than random goods.
It doesn't need to be the best. It just needs to be good enough. I'm not smart enough, but if I was I'd be working on a locally ran interface engine. That's where you charge say 100$ 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.
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.
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.
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.
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.
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.
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!
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.
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.
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.
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...
Point is, the number of tokens is a silly metric to proxy these companies' growth.
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…
People keep mouthing this same wish. But cancer is so many different cancers. And "the cure(s)" aren't just 1000 different drugs, but maybe 1000 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.
Nobody has proposed yet how LLMs can be a magic bullet here. At best they'll give you those 1000 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.
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.
These are averages, but still!
https://x.com/AndrewBenson/status/2115458726396310008
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.
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.
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?
If you can think a thing, you should be able to prompt a thing.
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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.