These companies are not trying to be companies that sell an LLM to summarize text or write emails. They're trying to make a full Artificial General Intelligence. The LLMs pull in some money today, but are just a step towards what they're actually trying to build. If they can build such a thing (which may or may not be possible, or may not happen soon), then they can immediately use it to make itself better. At this point they don't need nearly as many people working for them, and can begin building products or making money or making scientific discoveries in any field they choose. In which case, they're in essence, the last company to ever exist, and are building the last product we'll ever need (or the first instance of the last product we'll ever produce). And that's why investors think they're worth so much money.
some ppl don't believe this cus it seems crazy.
anyways, yes they're trying to make their own chips to not be beholden to nvidia, and are investing in other chip startups. And at the same time, nvidia is thinking that if they can make an AI, why should they ever even sell their chips, and so they're working on that too.
> they're in essence, the last company to ever exist, and are building the last product we'll ever need
Physical reality is the ultimate rate-limiter. You can train on all of humanity's past experiences, but you can't parallelize new discoveries the same way.
Think about why we still run physical experiments in science. Even with our most advanced simulation capabilities, we need to actually build the fusion reactor, test the drug molecule, or observe the distant galaxy. Each of these requires stepping into genuinely unknown territory where your training data ends.
The bottleneck isn't computational - it's experimental. No matter how powerful your AGI becomes, it still has to interact with reality sequentially. You can't parallelize reality itself. NASA can run millions of simulations of Mars missions, but ultimately needs to actually land rovers on Mars to make real discoveries.
This is why the "last company" thesis breaks down. Knowledge of the past can be centralized, but exploration of the future is inherently distributed and social. Even if you built the most powerful AGI system imaginable, it would still benefit from having millions of sensors, experiments, and interaction points running in parallel across the world.
It's the difference between having a really good map vs. actually exploring new territory. The map can be centralized and copied infinitely. But new exploration is bounded by physics and time.
To conquer the physical world the idea of AGI must merge with the idea of a self replicating machine.
The magnum opus of this notion is the Von Neumann probe.
With the entire galaxy and eventually universe to run these experiments the map will become as close to the territory as it can.
It seems that anyone who has ever played games like Factorio or Satisfactory can readily extrapolate similar real-world conclusions. Physical inefficiencies are merely an interface issue that erodes over time with intelligent modularizations and staging of form factors at various scales.
This might come as a surprise to some people, but the real world is infinitely more complex than a sim game.
Fully agree, self replication is key. But we can't automate GPU production yet.
Current GPU manufacturing is probably one of the most complex human endeavors we've ever created. You need incredibly precise photolithography, ultra-pure materials, clean rooms, specialized equipment that itself requires other specialized equipment to make... It's this massive tree of interdependent technologies and processes.
This supply chain can only exist if it is economically viable, so it needs large demand to pay for the cost of development. Plus you need the accumulated knowledge and skills of millions of educated workers - engineers, scientists, technicians, operators - who themselves require schools, universities, research institutions. And those people need functioning societies with healthcare, food production, infrastructure...
Getting an AI to replicate autonomously would be like asking it to bootstrap modern economy from scratch.
> They're trying to make a full Artificial General Intelligence.
> then they can immediately use it to make itself better.
"AGI" is a notoriously ill-defined term. While a lot of people use the "immediately make itself better" framing, many expert definitions of AGI don't assume it will be able to iteratively self-improve at exponentially increasing speed. After all, even the "smartest" humans ever (on whatever dimensions you want to assess) haven't been able to sustain self-improving at even linear rates.
I agree with you that AGI may not even be possible or may not be possible for several decades. However, I think it's worth highlighting there are many scenarios where AI could become dramatically more capable than it currently is, including substantially exceeding the abilities of groups of top expert humans on literally hundreds of dimensions and across broad domains - yet still remain light years short of iteratively self-improving at exponential rates.
Yet I hear a lot of people discussing the first scenario and the second scenario as if they're neighbors on a linear difficulty scale (I'm not saying you necessarily believe that. I think you were just stating the common 'foom' scenario without necessarily endorsing it). Personally, I think the difficulty scaling between them may be akin to the difference between inter-planetary and inter-stellar travel. There's a strong chance that last huge leap may remain sci-fi.
I pretty much agree with this article - It seems like LLM companies are just riding the hype, and the idea that LLMs will lead onto General AI feels like quite a stretch. They’re simply too imprecise and unreliable for most technical tasks. There's just no way to clearly specify your requirements, so you can never guarantee you’ll get what you actually need. Plus, their behaviour is constantly changing which only makes them even more unreliable.
This is why our team developing The Ac28R have taken a completely new approach. It's a new kind of AI which can write complex accurate code, handling everything from databases to complex financial models. The AI is based on visual specifications which allow you to specify exactly what you want, The Ac28R’s analytical engine builds all the code you need - No guesswork involved.
>If they can build such a thing (which may or may not be possible, or may not happen soon), then they can immediately use it to make itself better.
This sounds like a perpetual motion machine or what we heard over and over in the 3d printing fad.
We have natural general intelligence in 8 billion people on earth and it hasn't solved all of these problems in this sort of instant way, I don't see how a synthetic one without rights, arms, legs, eyes, ability to move around, start companies, etc. changes that.
LLMs are a very good tool for a particular class of problems. They can sift through endless amounts of data and follow reasonably ambiguous instructions to extract relevant parts without getting bored. So, if you use them well, you can dramatically cut down the routine part of your work, and focus on more creative part.
So if you had that great idea that takes a full day to prototype, hence you never bothered, an LLM can whip out something reasonably usable under an hour. So, it will make idea-driven people more productive. The problem is, you don't become a high-level thinking without doing some monkey work first, and if we delegate it all to LLMs, where will the next generation of big thinkers come from?
> This sounds like a perpetual motion machine or what we heard over and over in the 3d printing fad.
Except that it is actually what humanity and these 8 billion people are doing, making each successive generation "better", for some definition of better that is constantly in flux based on what it believed at the current time.
It's not guaranteed though, it's possible to regress. Also, it's not humanity as a whole, but a bunch of subgroups that have slightly differing ideas of what better means at the edges, but that also share results for future candidate changes (whether explicitly through the international scientific community or implicitly through memes and propaganda at a national or group level).
It took a long time to hit on strategies that worked well, but we've found a a bunch over time, from centralized government (we used to be small tribes on plains in in caves) to the scientific method to capitalism (and whether it's what we'll consider the best choice in the future or not it's been invaluable for the last several centuries), they've all moved us forward, which is simple to see if you sample every 100 years or so going into the past.
The difference between what we've actually got in reality with the uman race and what's being promised with GAI is speed of iteration. If a areal GAI can indeed emulate what we have currently with the advancement of the human race but at a faster cycle, then it makes sense it would surpass us at some point, whether very quickly or eventually. That's a big if though, so who knows.
AGI is only coming with huge amounts of good data.
Unfortunately for AI in general, LLMs are forcing data moats, either passive or due to aggressive legal attack, or generating so much crud data that the good data will get drowned out.
In fact, I'm not sure why I continue to uh, contribute, my OBVIOUSLY BRILLIANT commentary on this site knowing it is fodder for AI training.
The internet has always been bad news for the "subject expert" and I think AI will start forcing people to create secret data or libraries.
Current LLMs need huge amounts of data but before we get AGI we'll probably get better algorithms that are less limited by that.
i wrote about the prospect of financial returns from AGI here if anyone's interested - https://sergey.substack.com/p/will-all-this-ai-investment-pa...
This article says something that seems very false to me once you step outside of the developer sphere:
> Most LLM users seem willing to change from Chat-GPT to Claude, for example.
Talk to people who aren't engineers and it's all ChatGPT. Many don't even know about the concept of an LLM or a provider, just literally "ChatGPT". The South Park episode where they parody this stuff? They call it ChatGPT. The stuff students use every year to help with homework? ChatGPT. The website that "chat.com" redirects to? ChatGPT. And cai has cornered to market on horny/lonely male teens.
The moat here is the broader consciousness that a very very large population of people have adopted. Articles like this take something technical -- the cost of switching over to an LLM, which is cheap -- as an assumption that it will happen, without taking into account just how difficult it is to change social forces.
This doesn't mean ChatGPT will forever be what people use. Maybe it will fail spectacularly in a year. But it's OpenAI's game to lose here, not the other way around.
The general public doesn't care to understand the difference between "LLM" and "ChatGPT" any more than they care to understand the difference between "web browser" and "Chrome". Most people will happily use whatever you put in front of them, and if the product is bad, they'll generally grumble and shrug their shoulders in learned helplessness rather than do the research necessary to switch to a better alternative. Discerning consumers are a rounding error.
Which is to say, the platform holders will determine who wins and loses. ChatGPT will win if they pay sufficient fealty to Microsoft, Google, and Apple.
I'd say it's more like kleenex. Lots of people ask you to 'pass them a kleenex' when their nose is runny, but they just mean tissue. They don't actually care what the brand is. Similarly for LLMs most people may not care (or maybe they will, and it will be more like Google search), especially if they just use it via some other app that calls LLM provider APIs. My anecdata so far says early adopters try multiple LLM providers and use the best one for their use-case. No clue on what non-tech folks think though.
Exactly. One of my coworkers prefers Gemini to overcome the blank page hurdle, and he happily describe it as "the ChatGPT from Google". What does that mean for ChatGPT as a business? Nothing. Google would like people to use Gemini, but at least they retain this user and can target him with better ads, their real business. ChatGPT is just a layman synonym for LLM.
It amuses me that ChatGPT actually seems like a generic term already. You Chat with a Generative Pre-trained Transformer. Does what it says on the tin!
The USPTO agrees with you.
"[Trademark] Registration is refused because the applied-for mark merely describes a feature, function, or characteristic of applicant’s goods and services."
https://tsdr.uspto.gov/documentviewer?caseId=sn97733261&docI...
Your argument is essentially "no one will buy generic tissue when everyone calls it Kleenex". That's only powerful when ChatGPT is free. When there's price pain, we can see people adopting alternatives.
Branding is a moat but it's not a deep moat. Branding ironically works best (most profitablye) for incidental things that people exhibit to others - designer clothing is the most obvious - and this is because then brands have a social aspect (there's also branding a real signal of real superior quality - I'd buy a good brand of drill 'cause I have a rational reason to expect better quality but maintaining the quality of a branded product is more costly and hence less profitable than maintain the pure image of something like Coke and LLMs turn out not to really differentiate on quality). Whether they call LLMs "ChatGPTs" or not, people use LLMs for a result - they'll use a different LLM that gives equivalent result if they're motivated to do so. No one else is going to what brand of "ChatGPT" someone "drives", etc.
> Branding is a moat but it's not a deep moat.
Let's do an opposite question. What's Google's moat? What's Apple's moat? All I hear from everyone is "X is not a moat", which while true doesn't mean company couldn't be ahead of the competition forever.
Google's moat for search on the user side is quality, habit and integration but Google search is free and compared other "FANG" companies, Google is actually fairly vulnerable imo.
Apple's moat is people's hardware investment, their interface, their brand in a way that is socially significant as well as implying a real quality difference. Apple's overall moat is much larger than Google's.
Edit: and the specific non-moaty part of LLMs is that their answers are generic - LLMs don't have "personalities" because they are a trained average of all publicly available human language. If a given LLM had restrictions, it wouldn't be as useful.
Google's moat for search are the advertisers networks. Others can't bootstrap a search engine business because they don't have the advertisers to pay for it.
> quality, habit and integration
> hardware investment, their interface, their brand
Exactly, you gave all the possible moats for LLMs. Not saying OpenAI has it right now, I am disagreeing with the premise that LLM provider can never have moat.
My comment on Apple was hardware investment of Apple users. Neither Google nor Apple's own store of hardware matter in the age of "the cloud" imo.
I would agree that moats are relative and companies can stay ahead without deep moats. But I think you still the problem of the specific way that LLMs are generic. Users don't invest in an LLM, they just learn to use them and that learning can transfer. User don't get "bragging rights" for using ChatGPT rather than a competitor (almost the opposite). ChatGPT output doesn't have a "flavor" distinct from other LLMs - in fact, as a user, I want the output flavor I ask for rather than anything identifiable as ChatGPT.
You mentioned list of "deep moats" and all of them are applicable to LLMs. Just to repeat "quality, habit and integration, hardware investment, their interface, their brand".
> quality,
All LLMs are actually converging to about the same LLM, since they are trained on the same Internet/book/average-human-knowledge.
> habit
Habit matter for things people don't pay for. If a person pays, they'll go out of their way to get something for less. Microsoft's big thing is making sure end users never pay for Windows.
> integration,
Not going to matter. Every "AI application" is basically just a prompt and users can make their own prompts.
> hardware investment,
OpenAI doesn't even have a hardware investment, just a deal to use MS Azure. Other AI companies can and will just a cloud too.
> their interface,
Every LLM has the same interface. A chat window.
> their brand"
As above, brand matters for either habit (which again, only matters when thing cheap or free), social signaling (which a LLM choice won't give you) or actual differences in quality (which LLMs don't have).
> since they are trained on the same Internet/book/average-human-knowledge.
By this logic every search engine should converge to same thing? Again I am not talking about current gen llm, just saying your assertion that the quality would remain converged forever isn't substantiated enough.
> Habit matter for things people don't pay for
This is so baseless and ridiculous. e.g. Excel/Adobe isn't ahead of competition for features.
> OpenAI doesn't even have a hardware investment
https://www.reuters.com/technology/artificial-intelligence/o...
Google's moat with this current wave of AI is pretty obvious: They own the compute resources inhouse.
Apple isn't immediately seeking to compete in this field, presumably because they don't see a deep enough moat.
Google and Apple's moat in the mobile world is the monopoly Qualcomm has on modems and those two players being the only ones who can afford them, but nobody wants to talk about that.
> Branding is a moat but it's not a deep moat.
Branding is an extraordinary moat in fact and it is very deep. That's why you can walk into CVS, Walgreens, Walmart, Target, Costco and buy Kleenex and pay a brand mark-up for it, and they have a lot of shelf space in most stores. For no great reason other than brand and people keep buying it - that magic branded paper - by the billions of dollars worth every year.
The same is true for cereal products. $6 for a tiny box of branded, sugar loaded, garbage cereal? Laughable, absurd, and yet people just keep buying it. $3 for a little can of soup, outrageous, and people just keep paying it just to get the brand. It's all for the brand.
The same goes for branded over the counter healthcare products, such as Advil, or countless cough & cold products and supplements. How is Advil still such a massive brand? The brand value is very, very deep. It is deeply entrenched into the consumer thinking process, so much so they commonly think Advil is meaningfully superior to generic labels.
The same is true for the sugar water of Coke and Pepsi. Or 5Hour Energy. Or Monster. Or RedBull. There is nothing particularly special about any of it other than branding + routine. The flavors are fairly easy to mimic or even surpass. Also goes for branded bottled water, most of which is silly labeling, the height of bullshit branding.
$45,000 - $60,000 for a middle tier metal shit box of a vehicle, from any number of the automakers in the bottom 90% in terms of quality. Consumers could go used for $15,000 - $20,000. Instead of piling up an extra $150,000 in net wealth over a couple decades, they do the really dumb thing instead, because they can't control themselves (extremely poor impulse control, same reason they're all so obese and unhappy). They buy those cars to keep up with their peers in lifestyle projection, same reason they buy the brands in anything. If you get position as a brand, you've got consumers in hand (then it's just down to fighting with the other brands).
> The moat here is the broader consciousness that a very very large population of people have adopted.
That's not nothing, but switching costs are very low, and an alternative could arise faster than the switch from Friendster to Myspace or Myspace to Facebook.
Specially because there are no network effects and no lock in.
Only lock in could be if they become smart enough to truly know you and small preferences as a person that would be hard to repeat all the nuances to the next chatbot
Me and my coworkers pass around opinions about what LLM does what task better. The only conclusion is that they are 100% interchangeable, some prefer ChatGPT over Claude, and that just means that when ChatGPT credits get exhausted, they switch tab to Claude, Gemini or whatever their second option is. If ChatGPT started charging money or closed, they won't care at all.
For production workloads, the LLMs are interchangeable.
As a product, ChatGPT + Python + web search + the interface are miles better than anything else except in some use cases I find Google’s NotebookLM to be a better product
If people don’t know what the LLM behind the chat service is, then it seems likely (or plausible at least) that one could easily replace the chat bot used by these services with one backed by a different LLM, right?
Just like ChatGPT changes out models silently. Even if it's mentioned to the user, they don't care.
People just want a solution to their problem. Does a Google user care what iteration of their index engine they're using? No, they just want a picture of a god dang hot dog I tell ya hwat.
> Most LLM users seem willing to change from Chat-GPT to Claude, for example
There is some nuance to this. If you're building an application that embeds an LLM, then your "user" might be a prompt engineer, not necessarily the user using the application. It just so happens you can use the embedded magic using the prompt yourself.
Example: https://asana.com/product/ai
Not a single mention of Chat-GPT or Claude, but if you google you'll see they use Claude under the hood. So I would argue the branding is actually "AI" not ChatGPT.
It's a bit like Crypto and Bitcoin. Not all Crypto is bitcoin, but all bitcoin uses crypto to power it. People recognize both the branding of Crypto and Bitcoin.
This is like Bitcoin.
It's objectively a very bad crypto. It's the prototype and everything it does there is a coin that does it 100x better now.
But man, Bitcoin, that name has serious influence and staying power. It's a testament to the power of branding and being the first mover.
Bitcoin inherently relies on buy-in for its value. It's a shared fiction that becomes real because we share it. In that regard it's similar to countries. I literally cannot switch from Bitcoin to another coin and get the same value unless we collectively do it. It's a inherent property of its usage as a currency. I can switch from ChatGPT to Claude though without anyone else doing so and I get the same value. In fact, if Claude is superior I might actually get more value than if everyone switched because I now have a leg up on everyone else.
> It's a shared fiction that becomes real because we share it.
It's called the network effect, I believe.
There is a lot of truth to that.
Which means OpenAI really dropped the ball calling their first big success "ChatGPT". "Chat" was good, but three random (from the user's standpoint) letters? Ugh.
Whereas "Bitcoin" is practically Platonic. Branding platinum.
I'm one of those people—I use a variety of models but I call them all "chatgpt" (ironically, not including OpenAI's product). For the most part the model used doesn't really impact usage or quality that much, at least for my use-cases. It helps that I tend to keep my expectations very low. I think it's going to become a generic term for "llm chat bot" pretty rapidly, if it's not already metastasized.
I agree. The author makes the argument that airlines have a terrible business partly because consumers don't have any brand loyalty and Coca-Cola has a wonderful business partly because consumers have brand loyalty. What distinguishes those cases? Why should we consider LLMs to be more like one business or the other?
Brand loyalty might matter when the cost of a good is relatively low and the availability high. I can basically choose between coke or Pepsi anywhere, and they cost about the same, so why not go with my favorite?
For airlines availability with a preferred carrier is not guaranteed, and prices can vary wildly. Do I have so much brand loyalty that I will pay perhaps 2x the cost? Like most people, I wouldn't.
In terms of availability and cost, LLM providers are much closer to Coke than to an airline.
An article last year said that LLMs quickly become like brands of bottled water
Yes you will pay 2x the cost for your preferred airline when it’s not your money and you are getting reimbursed by your company.
> What distinguishes those cases?
It's in the article. Making coke is relatively easy compared to running an airline.
> Why should we consider LLMs to be more like one business or the other?
Also in the article. LLM's are analogous to airlines.
You are doing the thing of asking if I read the article without actually directly asking if I read the article. Please don't do that, at least without carefully reading the comment that you're replying to.
My specific point was that the article doesn't appear to support the assertions that it makes about brand loyalty.
I'm simply following the HN guidelines on the subject which prohibit directly asking if people have read the article.
It's a pretty bad guideline in my opinion but my opinion isn't worth shit here.
I'll re-read your comment when I have more time. Sorry if I missed the point.
Most people who bother to comment on HN have an interesting opinion, and I value yours.
The point of that guideline is to ensure that the conversation is substantive. Repeating points from the article with an assertion that those points are indeed in the article doesn't really add to the conversation and it's something that I do find frustrating on HN, which is why I mentioned it. I agree that it isn't a great guideline.
they say running an airline is easy, that's why you're easily underpriced
that should also apply to drinks, in which case coke should be underpriced by pepsi
and it should also happen to every other category of beverage
the author's argument falls apart as soon as you talk about something that's not the brand Coca Cola
is Coca Cola the exception here?
"industry structure" should be about the industry, so this should mean other beverages like tea and water should also be strong industries?
but no they're not, they're terrible just like airlines
The major airlines very much have brand loyalty via loyalty rewards programs, lounges, and cobranded credit cards.
If you are business traveler gaining status by flying a preferred airline and using other people’s money, you aren’t going to go to the cheapest airline.
Most of the profit from the Big three airlines come from business travel and credit cards
This! I'd argue that the only reason loyalty might not always matter is because I am frequently not given a real choice because a given route likely has a very limited number of airlines offering flights and those might be dramatically different in number of stops, price and times. Air travel is one area where I frequently wonder how many benefits of it being a free market on paper we are actually getting. There is limited choice and direct competition seems limited
One of my semi-frequent routes is between MCO (current home) and ABY - a small airport in Southwest GA where my parents live.
There are only two commercial flights a day, both on Delta and both to ATL. A round trip ticket is $540 for two 1 hour segments (MCO - ATL - ABY).
A round trip ticket from MCO (Orlando) to LAX (Los Angeles) is about the same price
Of course I know the trick for former - book through a partner AirFrance for 17K miles
Having masses of people using ChatGPT and not paying for it doesn't make for a successful business. The people who are willing to pay are more likely to be aware of the alternatives and choose the one best suited for their use.
For many school kids I think it's all just "AI", not "ChatGPT".
We said the same about Google, Uber, DoorDash, Facebook, TikTok, <insert any other unprofitable business that eventually became profitable>. Sure, most of them are making money through ads, but for that you need some audience. There’s absolutely survivorship bias here, but eventually it might just pan out.
That's true. Some business models succeed in the most unexpected of ways. They can pivot and change the recipe until it works.
No one ever said that about Facebook. Facebook was profitable way before it IPO’d and only did so because it had more than 500 owners and has to do reporting anyway as a public company.
Google also didn’t go through billions of dollars and was profitable when it IPOd.
DoorDash still isn’t profitable.
But either way, your argument suffers from survivorship bias. There are thousands of companies that fail and disappear into obscurity
I expect it to sort of be like AWS, Azure and Google Cloud.
Many people started with AWS as it was first, and it leads to quite a bit of momentum in terms of market share long past when there was significant differentiators. It is just that there are switching costs and most people have already learnt AWS's APIs.
What are the significant differentiators? I have worked much of a decade in the cloud infrastructure space, and from the POV of a business owner, AWS is such a stupidly superior product that I could not even imagine considering the alternatives. Google offers mostly AWS products but "googleized," and their support is practically nonexistent. Microsoft support isn't as bad, but their products are unreliable at best (from my view) and what differentiators they do have, which to me is better support for MS products in general don't really matter to me or my business at all.
These are the big 3 so the only ones I mentioned. I know alibaba/yandex/digitalocean/etc exist but lack as much experience with them so only commented on the big 3.
I've used both AWS and Google Cloud. I prefer Google Cloud myself and especially Google Cloud Run - which I've written about here: https://benhouston3d.com/blog/why-i-left-kubernetes-for-goog...
It seems like the points you're making are in support of the statement you are quoting - if most people don't know the concept of an LLM or a provider, why would that make it difficult for them to switch? Seems like ChatGPT's only competitive advantage here if I am understanding what you wrote correctly is name recognition. If ChatGPT's "game" to lose here is just staying relevant in the public consciousness, it would appear to me that the main point of this article, that building LLM's is not going to be a great business, is largely correct. I would expect a company such as OpenAI with such fantastic claims they make to have some kind of technical advantage over their competitors.
It's not just name recognition though. The chatgpt site had 3.7B visits last month(#8 in Internet Worldwide Traffic). Most of Open ai's revenue is from paid subscribers. Nothing else is even close.
Just because you can theoretically easily switch or that you brand has grown to the point of generic doesn't mean switching is going to happen. Habits are sticky and branding is incredibly powerful.
Anyone can use bing easily. In fact, bing is the default search engine on the default browser of the OS with by far the majority of users and stil...
Exactly. Reminds me of all the "technically superior" crypto coins that failed, and what ended up winning were the popular memecoins like dogecoin. There's a lot to say about distribution and what "the masses" end up adopting, whether or not it's the "better" product!
ChatGPT is not just an LLM.
It is:
- Dall-e for image generation
- a real time Python interpreter that can run Python code to answer relevant questions
- can search the web to retrieve and validate information
- has the infrastructure to handle processing at scale
Well that's just a branding failure.
How is it a branding failure that ChstGPT - the product - augments the weaknesses of LLM by adding more capabilities?
Well for one thing it calls itself "chat" when it offers so much more.
ChatGPT-Py-D-E has some rhythm, but it just isn't a good branding direction.
At some point, they are going to have to rebrand. Which means they left a lot of first mover branding value on the table.
The initial branding was inherently weak; who cares about chat if you can theoretically offer more than chat. But what do I know?
Just because people say "ChatGPT" doesn't mean they actually mean ChatGPT. I drink "coke" from multiple brands. I've seen people say "ChatGPT" and then actually use Bard.
Being the brand name of the industry is powerful, certainly, but it doesn't mean as much as it sounds like just based on usage numbers.
The chatgpt site had 3.7B visits last month(#8 in Internet worldwide traffic). none of the other LLM vendors are even close.
You're right that there are people who say GPT and mean something else but the vast majority of LLM users are actually using ChatGPT.
There's an interesting parallel between the subjective nature of LLMs (being blackboxes of nondeterministic output) and brands. The whole point of investing in brands is to create a moat. And maybe LLM are converging but because they are hard to predict there will always be factor that people's psyche will favour
Google users are theoretically willing to become Bing users, though I'll admit that ChatGPT is the consumer leader mostly because of brand recognition and being the first mover.
> This doesn't mean ChatGPT will forever be what people use. Maybe it will fail spectacularly in a year. But it's OpenAI's game to lose here, not the other way around.
The AVERAGE person still does not even know what ChatGPT is.
At most, 1 in 10 people have ever used ChatGPT.
This is like saying Social Networking is MySpace's to lose. Not really. Most people hadn't heard of Social Media or MySpace when MySpace was already huge and - by far - the biggest player.
It is likely easier for Facebook, Apple, Microsoft, or Google to introduce >50% of the population to an LLM than for ChatGPT to get from ~2.5% to >50%.
ChatGPT monthly users is about 1 in 40 people, by the way.
Does that mean ChatGPT is doomed to fail. No.
ChatGPT could easily be the winner.
But declaring the race over unless ChatGPT blows both its legs off seems very premature.
> This is like saying Social Networking is MySpace's to lose
But it was. If MySpace had evolved, and stayed ahead of trends, and cannibalized their own products, and really understood the value of social networks... they could have leveraged their initial lead to a dominant position.
Saying the market is ChatGPT's to lose does not mean they can be lazy or incompetent or even just merely good. It means that all things equal, if OpenAI executes at an equal level to their competitors, ChatGPT will win.
It's like saying a marathon is the front-runner's race to lose. It's simply true. It does not mean the race is over.
>The AVERAGE person still does not even know what ChatGPT is.
Who is "the average person" here ?
How unknown do you think the site that got over 3.7B visits (#8 in internet worldwide traffic) last month is ?
The idea that chatgpt is this unknown thing doesn't hold up to any scrutiny at all.
That insight, or lack of it, is esp surprising giving the example of how sticky the Coke brand is.
OAI has certainly positioned themselves culturally the same way as Google did for search engines. Google this, Tweet that, ask ChatGPT.
We know now how much actual competition[0] Google had after the dust had settled, in all practical terms - zero. Even after all the SEO spam and enshittification they haven't lost any notable market lead.
Time will tell if ChatGPT ends up that way but unless OAI implodes (which isn't all that unlikely) they're on the way there.
But Google came years late. I used multiple search engines before Google finally emerged as a winner. altavista, excite, hotbot and others; there was a huge hype around the Lycos IPO and then alltheweb was a thing for a time and then Google won.
So being first does not necessarily mean winning.
And Twitter had strong network effects.
Yeah but early stronghold brands don't always keep the market. Before word there was WordPerfect. Before Excel there was lotus 123. Everyone swore by both but they have been dead for decades.
It's funny because ChatGPT is such a bad mainstream branding. Technical name, hard to pronounce, nobody even knows what GPT stands for. They really got overwhelmed by their own success otherwise they would have done more on the branding side to appeal to mainstream users. But their first mover advantage won't last forever.
That's true, but that doesn't mean much as long as these particular users are free users that don't bring any money to the company (and cost a lot compared to similar users in other technology companies).
The real business is enterprise API endpoint billed by the millions of tokens, and in that particular domain OpenAI has literally zero market lock-in (and they probably depends more on Microsoft sales power than on their own brand value).
Unless OpenAI can show that they are able to make money from the mass of casual users, they are in a tough spot.
There is no money to be made from individual users. All of the money comes from companies building something on top of the LLMs, and those of us building startups on top of LLMs are very much aware of the differences between the LLMs. And, to the point made in the article, it is trivially easy for us to switch from one LLM to another, so the LLMs don't have much of a moat and therefore they cannot charge much money.
Probably true in the long run, but at the moment OpenAI is making about 90% of their revenue from ChatGPT subscriptions.
Agree that the foundation LLM business model is challenging, but I’m not very convinced by these particular arguments.
Yes, Nvidia GPUs are currently expensive. But they will soon be under tremendous competitive pressure from AMD, and more importantly Moore’s law is relentless (both in terms of model size capacity and performance per dollar). The price evolution of miniaturized transistors is basically the opposite of the airplane example.
Second, barriers to entry will keep increasing. Frontier models require stacking many new research and engineering insights. Of course the extent of secrets is currently limited because they only stopped publishing breakthroughs a couple years ago. Obviously that’s going to look very different 5 years from now.
On the other hand, competition between the leading frontier model companies is increasingly fierce (Google and Facebook have been slow to ramp up but theoretically should pose a big threat, and I am suddenly seeing Gemini topping leaderboards in the last few weeks), the moat is indeed questionable and the price of talent is very high. So it’s by no means an easy place to build a profitable business. But it’s at least possible for one or multiple of these firms to achieve process complexity that is extremely hard to replicate, and in the asymptote I really don’t think GPU costs will be a material threat to the business model.
> Yes, Nvidia GPUs are currently expensive. But they will soon be under tremendous competitive pressure from AMD
Similarly, Google run all their stuff on TPUs as far as I understand it, and Microsoft and Amazon both have ML accelerators in the works slated for 2025.
I was following along nicely until I hit this line:
> This is despite the fact that they are identical in both taste and colour.
The only way I could ever mistake Coca-Cola for Pepsi is if I were to completely lose my sense of taste. I'm quite surprised to encounter someone who considers them identical or interchangeable.
He's right, though, that I could change the supplier for airlines, browsers (or ChatGPT) and my world wouldn't be all that different. It would taste the same.
But most people actually can't tell the difference
https://daily.jstor.org/the-coca-cola-wars-can-anybody-reall...
Well of course a soda loses its subtly distinctive flavor if you hide the can! Those tests really didn't make a good point. :)
That's like drinking an unknown wine from a cheap plastic cup alone in an alley after a much too large breakfast, without any bottle label, price tag, companionship or comfortable context for proper tasting calibration!
Our senses really do cross over. Associations and history incontrovertibly shape our subjective experiences. Coke and Pepsi, in their naturally prominent can-habitats, taste very different.
My guess is those test ads were more interesting as stunts than as behavior changers.
You're not wrong, but what's interesting to me and the author of this article is that many products are completely interchangeable, yet their creators enjoy market dominance anyway.
As an aside, I don't think wine is necessarily the best comparison: the most recognizable brands of wine are often the least revered by connoisseurs . It's the experience of drinking wine from a glass bottle with a real cork out of a high quality wine glass in a classy setting that adds a lot to the flavor of wine. But which brand is relatively unimportant. That's not true for Coke where people's associations for "quality" are with the brand alone.
True. Perhaps not the best comparison.
There is a fundamental difference in branding dynamics between markets that value novelty vs. predictability, and exclusivity vs. availability.
With the wine market varying across both those axes.
Then there is the consumption vs. collection aspect. Winos of all persuasions have individually varying degrees of immediate satisfaction, delayed-reward, and hoarding/treasuring instincts.
Not really a cola soda branding type market at all!
Coca-Cola has the superior brand, but I grew up drinking Pepsi for the most part, so that might be a factor. Coke tastes good, but it's not the same, it just doesn't satisfy.
I'm quite sure I'd feel the same way on blind tests and I was assuming that most people have this keen sense when it comes to their favorite drink.
Their apparent superiority is just a product of massive investment in marketing to maintain their status. If it tastes the same as Pepsi or no-name cola, then what else could it be?
Coca-Cola is the only stand out brand here, and even in their massive brand portfolio, only the Coca-Cola product stands out; other ones like Sprite or Fanta don't do nearly as well
I've been commenting throughout the thread; forgot to say I used to work for Coke
It both just sugary water with bubbles. The Coca-Cola branding team has done remarkable work.
Interesting article but gets at least one thing wrong. Not all models are trained on Nvidia chips. https://blog.google/technology/ai/google-gemini-ai/
> Really though, LLM makers have only one true supplier: NVIDIA
The argument relies on the axiom that NVIDIA will have a persistent hardware advantage. Maybe they will, but even if they were always 2 years ahead of the competition, if NVIDIA-trained LLMs would 'good enough' in 2025, then non-NVIDIA-trained LLMs would be 'good enough' in 2027.
> NVIDIA will have a persistent hardware advantage
I think it probably has more to do with CUDA. The reason Python is the undisputed champion in AI and ML isn't because Python is a better, more performant programming language so much as because ecosystem of software in the AI/ML space is extremely concentrated, dense, and rich in the Python ecosystem compared to Java, Go, or C#.
Likewise, it seems like NVDAs advantage isn't even necessarily the hardware but the suite of tools and software that are built up to take advantage of that hardware.
It's definitely not CUDA advantage. If you can get Pytorch/flash attention/triton well supported in any hardware, a huge chunk of client don't care if it means cost saving. Case in point Google's TPU had extensive usage outside Google when they were cheaper for the same performance. Now that isn't the case.
It's TSMC more than NVIDIA.
And it's ASML more than TSMC.
Or maybe there's a highly profitable role for all the different parts of the value chain.
"If LLM makers seem cursed to an airline-style business destiny, how come they are able to raise so much money? ...What do they know that I don't? It is a mystery - but let's consider the options..."
Not mentioned: a lot of the "money" that they raised, was not actually cash but credits for cloud compute. If you've already bought too much cloud capacity, giving away some of it and claiming it as an investment in AI, looks like a good idea.
I've seen the airplane/railway comparison a lot and I'm not sure I buy it.
Nvidia is currently important to training new LLMs but it's not that important to running inference on existing ones.
I think email might be a better comparison? If LLMs really do become something that everyone uses without thinking about (and at least anecdotally it's the first tech trend I've seen that all my non tech friends are using) then yes sure you can easily change provider but in reality most people are just going to use whoever wins, just like most people use Gmail.
So investors are putting in huge amounts of money to have part of the next Gmail, and many of them will lose but there will probably be some dominant player and sure you can change but once you've used one for a few years and it is as good as or equal to another, and it approximates to free, then you'll probably stick with it, compatible api and interface or not.
No because Gmail has strong network effects (people email your @gmail address)
I looked at the numbers at various startups and felt the same
https://ashishb.net/all/llms-great-for-business-but-bad-busi...
One thing the author is forgetting:
Regulatory capture.
The incumbents can lobby for overly restrictive legislation based on copyright or "safety" concerns that make absurdly expensive for new entrants to enter the market.
Think about big tobacco.
But regulation typically only affects one country, and the USA doesn't appear to like regulation since neoliberalism became the politics dejour
I think the big moat will be AI assistants that can accumulate long term individualized rapport and context with its user(s). Suppliers will need to be able to update their customer's assistants capabilities, without restarting/disrupting that valuable and growing knowledge.
The same relationship familiarity/fluency lock-in advantage of human personal assistants.
It doesn’t technically detract from the overall point, but almost everything about airlines is wrong.
It’s incredibly difficult to start a new airline. Small and medium sized airlines are almost non existent. There is currently a pilot shortage. Most people stick with the same airline for the rewards.
> Web browsers are extremely advanced pieces of software even though making a browser is such a bad business that most don't usually count it as a business at all.
The DOJ doesn't seem to realize this.
The article calls out trademarks as part of the reason why soft drinks are successful. I think the impact of laws and regulations cannot be ignored for the future of LLMs either. Legal/regulatory moats make companies more profitable than they otherwise would be.
For example, in the future if you ask a model "are trans women real women" it will have to say "yes" in one country and "no" in another. In one country the LLM will have to talk about the "5000 years of Chinese history" and in another will have to say that's just an invention to feed their superiority complex.
Text interface over the internet is not the end game, far from it. It is just the beginning