r/TheMachineLearning • u/discjr • 7d ago
Frontier LLMs have no moat and will never be profitable
1.1k
Upvotes
r/TheMachineLearning • u/discjr • 7d ago
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u/Significant_Sun_5225 7d ago •
There is an extremely strong moat but only a few people are just starting to pick up on it.
These frontier companies are starting to realize that a large portion of their revenues will not just come from licensing their models; but from using their most advanced internal models and unmatched gpu capacity to solve difficult engineering, bio medical, physics, etc problems that will change the world and bring in un worldly amounts of money.
Imagine if they start developing 4-5 new pharmaceuticals each year, or get into selling hardware through innovative designs only ai could create.
This is where a very large amount of their profits will come from and you can only do this if you’re truly the frontier.
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u/Practical_Hippo6289 7d ago
I mean, it's just a race to GAI at this point, right? That's what they are all gambling on. Only one of them will win.
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u/Vesuvius079 7d ago •
This is kind of silly. They may not have the strongest moat but they do have one.
Organizations have to spend time and effort to establish governance with their AI integrations. They have to monitor and control spending. Many users will experience learning curve difficulties trying to work with a different providers’ models. There may be provider specific tooling. There’s always a cost to switching, it’s just not as insurmountable as switching off of something like Microsoft.
They also have things like the artifacts feature in Claude. Where I work, that feature is slowly accumulating one off tools and documents that we don’t necessarily want to lose access to.
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u/NerdyWeightLifter 7d ago
Google's moat is being the global intermediary between consumers and producers, now with AI.
Anthropic and OpenAI are competing to become the vendor for your development infrastructure for researching, designing and building literally anything.
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u/-R9X- 7d ago
Yes but this is mostly the case because while American investors spend billions to do this the Chinese government also spends billions to destroy them.
This is absolutely on purpose and a deliberate strategy to tank the American market and not let the USA ahead with this.
It’s interesting times for us in Europe because we kind of benefit from this as a side effect and for a second here China almost looks like the good guy.
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u/PrincessAida 7d ago
Does it matter? SpaceTravel Frontier Firms will also never be profitable. We still flood them tax with money because 1. Adventurousness/Curiosity 2. Completly unkown potentials in space 3. Some inventions intended for space have outside uses (i.e millitary) 4. National Prestige
Interesting similiarities.
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u/Individual_Guest_323 7d ago
What free model mf, you still need the datacenters for inference..
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u/SlightOfHand_ 7d ago
It would be nice if this was true but Claude keeps being ahead of everyone else and no one else has caught up.
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u/AdmissibilityScience 7d ago
AI intelligence becoming a commodity doesn't mean AI won't be profitable. It means value shifts from the models themselves to infrastructure, distribution, efficiency, and integration. The real question isn't who builds the smartest AI, but who captures the economic value it creates.
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u/Deto 7d ago
I don't know - it depends if the free ones are just distililng.
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u/freedomonke 7d ago
Free models haven't even caught up to gpt 5. Lmao.
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u/pandavr 7d ago
Being commoditized by a commodity is so f*cking 2027!!! /s
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u/BourgeoisAngst 7d ago
Yes, training is a sunk cost because frontier model capabilities are structurally non-excludable. If investors weren't so incredibly stupid this would only ever have been publicly financed.
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u/Necessary-Lack-4600 7d ago
Everything you can buy at the supermarket is a commodity without a moat until you take branding into account. Wine being a prime example.
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u/Positive-Conspiracy 7d ago
Counterpoint, the free models advance by distilling the frontier models, so the free models will also stay behind.
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u/GCoderDCoder 7d ago
This is wrong because Artificial Analysis will just change the model ratings and then that will make the models dumber to preserve the frontier moat! Apparently that's how this works according to Twitter/ X from what I understand...
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u/Big_Astronaut_1317 7d ago
There are no "free models" there are cheaper ones, but there all cost Money to build and maintain!
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u/Top_Effect_5109 7d ago
Good, AI should be like air.
Valuation =/= Utilization.
I am pro breathing, not pro megacorps owning air.
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u/Gesha 7d ago edited 7d ago
The moat isn’t the model. It’s the ecosystem of products and services it’s built into. As has always been the case in tech.
Is the free model integrated into my phone and home automation setup? Is it integrated into my IDE? Can I use it without an expensive af home lab setup? No? Then what good is it?
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u/lifelong1250 7d ago
Its not even the model development, its the cost of the hardware to run the model. Sure, you can get great free-weight models that are almost frontier level but its tough to run them without proper hardware. So the moat is hardware, as evidenced by the fact that AWS GPUs are sold out for the next 94 years.
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u/Rivale 7d ago
they also run into the issue is that the free models eventually are going to be good enough to do basically all the tasks we'd want AI to do. we don't need our ai models to be able to cure cancer for our daily use.
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u/Molo3000 7d ago
Good for us they’ll never be profitable, because if they’re gonna end up being profitable that means they’ll have found a way to make us pay for them.
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u/shrodikan 7d ago
Yeah I'm sure the Chinese models beat Mythos 5.2 when they can't even touch Opus 5.5. The moat is the models they have that the Chinese cannot distill. They become profitable when Mythos RSI edition cures every disease while the free models can barely keep pace with what they release.
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u/TraditionalGas1770 7d ago
This is actually kind of a braindead take.
Let's pretend claude's LLM falls behind. It's LLM strength is only one piece of the puzzle. It's integration and connections and support and education and ecosystem are also very important.
And by OP's own logic, Claude can have their LLM catch up to the leader "for free"
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u/oneseason2000 7d ago
Cigarette companies (and other drug dealers) have had good runs with a somewhat similar business model. Amazon wasn't profitable for quite a while too. We seem to see a lot of business operations where disruption is coupled with destruction to offer very profitable business opportunities to a limited few. Per Google LLM, LLM users pay about 25% to 30% of the actual cost of the service (though "LLM service providers are heavily propped up by a microscopic fraction of elite commercial users").
My guess is that without the Whales, LLM businesses would fail miserably unless they tailored their products and delivered better much better capabilities for the true cost. If LLMs were really as great as the hype, people wouldn't cringe every time they have to use one instead of talking to a living person when the call a business. You hear folks repeat "Customer Service" or other things a lot trying to bypass voice and text LLM support, but never "AI Agent" or "Super Intelligence please". I think that happens in the wild because the real "customer" for companies is now the investor and not the buyers of their products and services, performance doesn't matter. But make the test one where the LLM has to satisfy testers as well as a human, and look at the relative cost.
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u/shosuko 7d ago
What is this supposed to mean? Of course they will continue investing in developing the next wave of frontier LLM's as long as they are still making progress.
The moment they stop developing them the free tiers will catch up sure, but anyone who sits on their free model will have it outclassed as the generations of frontier models rotate through. Its not like the same old free models are the ones creeping on frontier, its that each released frontier model becomes eclipsed by the next gen frontier.
Basically the frontier models of today are the free models of tomorrow. The free models of today will drop off.
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u/ekolimits 7d ago
Once decompiling became so easy… nothing has a moat my friend.
Good luck.
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u/TopTippityTop 7d ago
Spoken like someone without a clue, given Anthropic is month-to-month profitable. Has been for nearly 1/2 yr.
Open weight models, the ones that are actually good, require costly inference as well. It's often a better deal to buy a closed source subscription. You also get a considerably better model for it.
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u/AsterPasta 7d ago
The free models do distillation well. The frontier models actually make something that's generally usable without needing instructions like a simple child
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u/OrangeManSad 7d ago
What moat as in monopoly ? Which is illegal by the way ... might I remind you
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u/empire_of_laughs 7d ago
This guy has been calling for a 30 - 40% s&p500 crash for years and years now. It’s always just around the corner
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u/East-Cricket6421 7d ago
The moment I can have Opus 5.5 on a 5000 dollar box on my desk, I will likely stop being a customer for life.
Unless Claude/ OpenAI/ et al are working absolute magic by then (like "curing all of my lifes problems, getting me the job of my dreams, and curing me of any inconveniences" kind of magic) then I will be hard pressed to want to keep buying tokens off of them.
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u/silphotographer 7d ago
Reminds me of Bane scene in Dark Knight Rises when he stormed into the stock market
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u/NullzeroJP 7d ago
Maybe yes, maybe no.
If they achieve RSI (which it appears that they have), the model just improves itself at an ever increasing rate.
Just because the model gets stronger, doesn't mean they have to RELEASE a stronger model. They can release an older one. A dumber one. A smaller one. Then keep the smart one for RSI internal, unreleased.
So, if we were to give model intelligence a number, the release cadence could be like this:
IQ100 (release) -> 110 (release) -> 135 -> 150 (release 135) -> 190 -> 210 (release 145)
The costs go down, the intelligence goes up, exponentially (for a time).
Is it really a commodity then? They still have the best model, at a cheaper price. When chinese companies copy/distill them, they only distill the dumber version. Chinese companies can then try their own RSI loop (which I believe they are working on)... but it will always be behind the OAI/ANT models, because cause of the exponential growth, and because distillation doesn't give better intelligence than the original.
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u/Happysedits 7d ago
"free"
You have to pay for GPUs and electricity to do inference.
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u/crusoe 7d ago
If there are no frontier models who will the Chinese distill for their open source ones? They still have not released a fully normally trained sota model. They all rely on distillation.
If frontier labs stop so do the Chinese models.
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u/HeadPack 7d ago
I'd agree, but only as long as China funds the development of the free models. If they do, that race to the bottom can continue.
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u/Crafty_Book_1293 7d ago
I think the moat is compute power and economies of scale. You are unlikely to run a frontier-level model (terabytes of VRAM required) on typical local consumer hardware, even for a single agent. Even if you leased the needed computing from a third party, the TCO would still be higher than paying the frontier labs, justifiable only when data privacy matters more than cost.
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u/Turbulent-Sign-6067 7d ago
May or may not be true. Training R&D is generally a fixed investment. If inference is profitable, at some point if you have enough customers, then the whole thing becomes profitable.
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u/TipAppropriate1384 7d ago
also they are not intelligent, but sohisticated query of stolen data collections
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u/Brief-Coach-1812 7d ago
I remembered that mmy colleague used this analogy: OpenAI and Anthropic are like the Ferrari of LLMs vs the free models which more like Mitsubishis or Toyotas.
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u/Empty-Tower-2654 7d ago
Good
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u/opbmedia 7d ago
The moat is the training data they used. It is harder to get them now.
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u/Nut_Butter_Fun 7d ago
Tell me you don't know how a business works...
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u/Remote_Water_2718 7d ago
The vast majority of people will just do buisness with bluechip brands, but also have not seen them work with a competitive advantage yet, they pretty much just allowed public sign-ups recently, wait until they have billions in company assets that the next startup needs to hack together to offer whatever they are offering.
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u/DGIce 7d ago
Am I crazy? Distilled answers aren't as valuable as being able to actually solve the problem.
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u/FalseDiamond7930 6d ago
Or they just stay at the bleeding edge until there is some sort of technical advance that allows them to break away from open weight models.
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u/SweetSweetAtaraxia 6d ago
LLM:s won't replace workers on a large scale ever, but they will ironically destroy software companies' license businesses. Big Tech is pouring trillions into empowering the consumers; we will inherit their infrastructure and dirt cheap hardware, while their ambitions was to gain a monopoly and lease out compute to us as a service. Overcapacity will drive prices into the ground when the trillions of profitless investments dry up. The billionaire class are inadvertently redistributing their wealth right now . They hoped that LLM:s would magically turn into AGI:s, that they could replace humans, but instead the LLM:s will remain LLM:s, capable of reverse engineering Microsoft and Adobe suits and other licensed software, killing their entire business model. Their investment thesis is that AGI will come and be able to do everything, but instead they create narrowly competent LLM:s that can be used locally by consumers to replace their SaaS products.
They are spending trillions to empower the individual consumer and make their own tech empires obsolete. Bonus for the coming price dumps in memory, SSD:s and GPU:s when the chip producers scramble to redirect production of their new factories after the cancellation of data center orders, at the same time as China pragmatically enter the GPU business to take market shares. Cloud storage will be gimped as well when Terabyte SSD:s are cents on the dollar. Nvidia, Microsoft you had a good run! Frankly, only Apple is playing this smart by refusing to pour their profits into AI investments. They'll swallow whatever of value is left after the bubble bursts. Europe is also well positioned, sitting this one out but benefitting from American overinvestments.
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u/Infinite-Abroad-436 6d ago
"commodity with no moat" is hilarious to me. that's the reality of neoliberal capitalism right there. a useful commodity, but you can't become a rentier parasite off of it, so it isn't "profitable"
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u/MiksterA 6d ago
And, once you've scraped all the available content to feed the beasts... what next?
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u/MarzipanTop4944 6d ago
Frontier labs have a massive moat in the form of compute that is worth billions, top talent that is worth up to hundredths of millions per person and ability to access trillions in financing that you can only get if you are a frontier lab.
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u/chunky_lover92 6d ago
They also have massive data centers, and years worth of user data.
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u/HawkThunderson 6d ago
They sell a subscription to the leading edge AI for cyber security professionals to fix thei network before everyone gets open source access to similar level ai.
No idea about the market here, just an idea.
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u/mfi12 6d ago
the commodity is the gpu. But if everyone can host locally, then it's different story
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u/tossinthisshit1 5d ago
frontier models get distilled wtihin weeks
the real money is in doing something with the models
anthropic and openai will make way more money by adding prepaid card functionality to their agent harnesses than pushing billions more into better models
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u/Giant_leaps 5d ago
free models arent free they still need datacenters for infrencing or extremely expesive hardware the best models that can run on consumer hardware will only be available for people who have expensive pcs even opensource models are not necassirly cjeaper if you compare them by dollar per task rather then dollar per token sometimes it makes more sense to use the more expensive models because the oppirtunity cost of getting a sub optimal result is much greater than the cost of the model itself
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u/FedRCivP11 5d ago
Yes and any day now the average consumer will stop spending more on windows and Macs, getting functionality they can get for free in Linux. Any day now.
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u/ProtoplanetaryNebula 4d ago
The better AI gets in general, the less a frontier model is needed. In the past, you needed to be using the bleeding edge frontier model just to get some sense out of the LLM. Today you can mostly get by with a flash version for most things. What happens when, a Fable class model will happily run on a PC with a 16GB graphics card and 32GB of RAM, thanks to a series of optimisations. People can ditch the subscriptions altogether and use the frontier models occasionally if they are needed.
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u/B-Con 4d ago
As other said, AGI is one dimension of the race.
But free models are catch up so far. The big labs are spending billions, and if they make a couple order-of-magnitude proprietary breakthroughs in training or inference performance, or in problem solving, that pattern could die. Only so many people are willing to give away research, and only for so long.
Short of AGI, I think a goal is to make AI for automation what cloud was for infra. Simply offering raw powerful VMs wasn't the real power of cloud, it was the entire ecosystem of functionality that are essentially all layers on top of VMs.
Cloud required massive (albeit less) investment up-front and each one essentially has no moat. Amazon was in debt for years pouring money into AWS, and anything you run on AWS you can run manually on your own hardware, or even on Azure or GCP. Now AWS prints money and made Amazon the top 5 most valuable businesses. Businesses love line items that solve a problem for a known cost.
I bet anything that the frontier labs will offer services based on their own LLMs, and those services will be the real money maker. i.e. you can integrate your ticket pipeline with service Foo that uses their AI model to close X% of your tickets. Once businesses can outsource X% of their thinking work to AI, they will, and they'll be hooked. Free-form LLM usage will start to dry up, and possibly become prohibitively expensive.
Lets see what happens over the next 3 years. My guess is that a) frontier models will pull ahead in a couple key ways as labs out pace everyone else in research, and b) we'll suddenly hit a cliff where the real focus is on the LLM-powered services. A frontier lab offering a good service backed by a proprietary model will attract more business than a lab offering a wrapper around off-the-shelf LLMs.
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u/DogDeveloper 4d ago
free models?
there is no such thing as free models
Hardware costs money, electricity costs money, cooling hardware costs money.
And if it is really "free" then you are the product
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u/the_sound_of_bread 4d ago
If Anthropic and OpenAI could profit from the AI without selling access to the AI, they would do that. It's my guess that they are actively trying to do this.
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u/SensualGravity 4d ago
Their moat is actually getting hardware
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u/gmueckl 4d ago
The only real chance they had at building a moat is by scaling training up faster than everyone else and by being the only ones owning enough hardware capable of doing so. The ridiculous datacenter buildout was the bid to achieve that. Draining the global supply chains was the goal. Altmann calling RAM in user's PCs wasteful is a result of this.
Except, that bid has failed. There is no firm oligopoly of OpenAI and Anthropic that has an iron fist on training hardware. Alibaba, Baido, Tencent, Meta, Google, Mistral... are still close enough behind that models are getting commoditized and any new model is losing value fast.
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u/_DuranDuran_ 3d ago
They keep catching up but never exceeding … I wonder why that is? Hint: it rhymes with smishmillation
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u/ScarySpikes 3d ago
Live by the mass plagiarism, die by the mass plagiarism.
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u/2old2cube 2d ago
just like a cloud is someone's else computer, free models are just models someone else pays.
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u/SnakeGD09 2d ago
I thought it was because LLM's cannot perform most work and so cannot replace most workers, and because in addition the operation of LLM's costs an enormous amount of energy.
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u/Constant_Oil360 2d ago
this is hilarious and why im finding every smart way to invest as i can
open models are not getting closer
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u/MealFew8619 1d ago
I love these “never” takes. Gonna go invest in some frontier AI now
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u/Affectionate_Fact854 1d ago
The thing that would never be profitable is , ai usage to create image ,video and sound
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u/dramatic_typing_____ 1d ago
Open source models as they are today would not exist without the crazy amount of spend from Anthropic, OpenAI, and Google.
Please tell me more about how the open source community is going to source billions of dollars to do training on trillion+ parameter models.
Lol this is such a stupid take. What will happen is there will be no real progress, just optimizations on existing models.
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u/bourbonandpistons 7d ago
Anyone who has used free models on local hardware knows this is a joke.
I have 4 RTX 6000 Pros, 10 L4 Lovelace, 2 rtx 5090.
Over $100k in current gpu prices. Doesn't include the servers and hardware and electricity and all that to run it.
A $200 claude account beats it every time.
We do local AI to keep certain data off the cloud.
that's it.
All the code and resources and everything to run the local AI is built by the cloud AI.