> There is no technical moat in this field, and so OpenAI is the epicenter of an investment bubble. Thus, effectively, OpenAI is to this decade’s generative-AI revolution what Netscape was to the 1990s’ internet revolution. The revolution is real, but it’s ultimately going to be a commodity technology layer, not the foundation of a defensible proprietary moat. In 1995 investors mistakenly thought investing in Netscape was a way to bet on the future of the open internet and the World Wide Web in particular.
OpenAI has a short-ish window of opportunity to figure out how to build a moat.
"Trying to spend more" is not a moat, because the largest US and Chinese tech companies can always outspend OpenAI.
There is no technical moat, but that doesn't mean there isn't a moat.
Amazon might be a good analogy here. I'm old enough to remember when Amazon absorbed billions of VC money, making losses year over year. Every day there was some new article about how insane it was.
There's no technical moat around online sales. And lots of companies sell online. But Amazon is still the biggest (by a long long way) (at least in the US). Their "moat" is in public minds here.
Google is a similar story. As is Facebook. Yes the details change, but rhe basic path is well trodden. Uber? Well the juries still out there.
Will OpenAI be the next Amazon? Will it be the next IBM? We don't know, but people are pouring billions in to find out.
Genuinely curious if anyone has ideas how an LLM provider could moat AI. They feel interchangeable like bandwidth providers and seem like it will be a never ending game of leapfrog. I thought perhaps we’d end up with a small set of few top players just based on the scale of investment but now I’ve also seen impressive gains from much smaller companies & models, too.
I believe that, their brand “ChatGPT” is the moat. Here in EU, every news media and random strangers on the streets who don’t understand anything beyond TikTok also knows that AI=ChatGPT. The term is so ubiquitous with AI that, I am willing to bet when someone tells someone else about AI, they tell ChatGPT and the new person will search and use ChatGPT without any knowledge of Claude/Gemini/LLama et. al. This is the same phenomenon as web search is now = Google, despite other prominent ones existing.
The competitions are mostly too narrow(programming/workflow/translation etc) and not interesting.
Why is everyone so sure that technology can’t be the moat? Why are you convinced that all AI systems will be very similar in performance and cost, hence be interchangeable?
Isn’t Google the perfect example that you can create a moat by technological leadership in a nascent space? When Google came along it was 10X better than any alternative and they grabbed the whole market. Now their brand and market position make it almost impossible to compete.
I guess the bet is that one of the AI companies achieves a huge breakthrough and a 10X value creation compared to its competitors…
> In 1995 investors mistakenly thought investing in Netscape was a way to bet on the future
Maybe they were just too early, later on it turned out that the browser is indeed a very valuable and financially sound investment. For Google at least.
So having a dominant market share can indeed be even if the underlying tech is not exactly unobtainable by others.
Adding to this, inference is getting cheaper and more efficient all the time. The investment bubble is probably the biggest reason why inference hardware is so expensive at the moment and why startups in this sector are only targeting large scale applications.
Once this bubble bursts, local inference will become even more affordable than it already is. There is no way that there will be a moat around running models as a service.
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Similarly, there probably won't be a "data moat". The whole point of large foundation models is that they are great priors. You need relatively few examples to fine tune an LLM or diffusion model to get it to do what you want. So long as someone releases up to date foundation models there is no moat here either.
> OpenAI has a short-ish window of opportunity to figure out how to build a moat.
See the scramble to make themselves arbiters of "good AI" with regulators around the world. It's their only real hope but I think the cat's already out of the bag.
This is what I have been asking people in the know too. It seems like developing this is straight forward. So not sure why OpenAI has a lead. That too with how fast things are, the gap should be instantly closed.
Honestly the more I use ChatGPT, the more I see of their "moat-ish" opportunities. While the LLM itself may be ultimately reproducible, the user experience needs a UI/UX wrapper for most users. The future is not user exposure to "raw" LLM interactions but rather a complex workflow whereby a question goes through several iterations of agents, deterministic computation using "traditional" processing, and figuring out when to use what and have it all be seamless. ChatGPT is already doing this but it's still far from where it needs to be. It's totally possible for a company to dominate the market if they're able to orchestrate a streamlined user experience. Whether that will ultimately be OpenAI is an open question.
OpenAI's C-suite: Well, they earned the C, but it was a letter grade.
What a profoundly unimaginative strategy. No matter the industry, a large-scale diversion of resources towards a moonshot goal will likely get you to that goal. They haven't made an argument as to why we should do that just for them, especially with all of the other alternatives.
And no, advertising your previously secret testing models (e.g. o3) as if they were market competitors is not how to prove they should have our money.
”They haven’t made an argument as to why we should do that just for them…”
What “we”? They’ve already raised billions, and I suspect they’re about to succeed at raising tens of billions more, despite the skepticism of random HN users.
In all fairness regarding his comment about Netscape - anyone who invested in Netscape at the IPO (and certainly before the IPO) at $2.9B - made a ton of money on the Internet. On the last day of trading, after the AOL exit 4 years it was worth (cash, stock, etc...) around $10B. Thank Mike Homer for pushing that one through, and Jim Barksdale for being savvy enough to recognize it as the right play.
Also, they started from scratch, they didn't take NCSA's Mosaic public, they left the university, brought in some established players, created a new company, and re-wrote the entire browser from scratch. SamA wants to take everything the non-profit created and just make it for profit. If he want's to do that he can create a new company, lure away the talent, start from scratch, and run from there. This "it's just like Mosaic -> Netscape" line is total bullshit and either Gruber doesn't remember like I do or he's intentionally misleading for some other goal.
This is why I don't think LLMs will lead anywhere other than the present: they are very expensive. If top LLM company in the world can't bring those costs down in a sensible amount of time, it tells you everything you need to know about the future of LLMs. Rest assured, once OpenAI goes down and it really sounds like they are way past the peak, valuations for other LLMs companies will follow. And once they can't raise funding, all of them aside from those backed by big conglomerates (see Google's Gemini and Facebook's Llama) will survive.
The long term future of LLMs sure looks like the LLMs themselves will be commodities and the real value will lie in the use of those LLMs to deliver value
People keep saying stuff like this, but I don't believe it: "There is no technical moat in this field, and so OpenAI is the epicenter of an investment bubble."
AI progress is driven by strong valuable data. Detailed important conversation with a chatbot are much more valuable that quick search queries. As LLMs extend past web UIs, there is even more interaction data to capture and learn from.
The company that captures the most human-AI interaction data will have a TREMENDOUS moat.
If I have the LLM translate a text from French to English... what is there to learn from that? Maybe the translation is great maybe it's awful, but there's no "correct" translation to evaluate the LLM against to improve it.
If I ask the chatbot for working code and it can't provide it, again, there's no "correct" code to train it against found in the conversation.
If I ask an LLM to interpret a bible passage, whether it does a good job or a terrible job there's no "correct" answer that the provider has to use as the gold standard, just the noise of people chatting with arbitrary answers.
When will this come to pass? OpenAI has many orders of magnitude more conversational data and Anthropic just keeps catching up. Until there is some evidence (OpenAI winning, or Google winning rather than Open Source catching up), I don't belive this is true.
What do you think they've been building these multimodal models with? If I had Google application logs from the past few decades I would absolutely be transforming it and loading into my training dataset. I would not be surprised if Google/Meta/Msft are not doing this already
When the big companies say they're running out of data, I think they mean it literally. They have hoovered up everything external and internal and are now facing the overwhelming mediocrity that synthetic data provides.
Yup. We have seen time and again that companies don't need a "technical moat" to stay in the lead. First mover advantage and a 1-2 year head start is always enough. Of course they also need to keep their foot on the gas and not let their product get overtaken. With all the talent OpenAI has I'm pretty sure they will manage.
Investors observed the pattern that the largest platform eats the market and bet on openAI moving along the same paths.
I disagree, that phenomenon is tied to the social network like phenomena we saw with WhatsApp and Facebook and to the aggregator business model of Amazon and Google.
Mathematically we can describe the process by which these monopolies form as nodes joining graphs:
Each node selects graphs to connect to in such a way that the probability is proportional to the number of nodes in the graph.
Sure Amazon and google feature two types of nodes, but the observation still fits:
Selling on Amazon makes sense if there are many customers, buying on Amazon makes sense if there are many offers.
OpenAIs business does not have this feature, it does not get intrinsically get more attractive by having more users.
I use Claude because the model is indeed better, but having listened to John's podcast I know that he means that the experience of using OpenAI overall is better.
Unimaginable sums of money can only come from oil rich countries. They are probably just mentally trying to accept that they are going to take the money from these nations.
The word "open" is still under threat in this scenario too.
I think their vision is as it should be ambitious, but I don't believe they can gain any real technical moat.
Models are commodities, even in the case Open ai goes through another major breakthrough nothing can stop some of their employees to run to other companies or founding their own and replicating or bettering the OpenAI results.
In fairness I realize that I don't use any of OpenAI's models. There are better alternatives for coding, translating or alternatives that are simply faster or cheaper (Gemini) or more open.
This is getting so repetitive now that it is stated as a truism.
Isn't it the same bet yahoo was betting on in 2000 that it would win because their product branding is better? And now, Yahoo's and Microsoft's search engine is worse than Google from 2 decades ago.
Frankly, OpenAI efforts seem quite funny for me personally as for most tasks I do Claude is far superior and yet OpenAI behaves as if they were the only game in town.
The so-called open source models are getting better and better and even if OpenAI suddenly discovered some new tech that would allow for another breakthrough, it will be immediately picked up by others.
[+] [-] cs702|1 year ago|reply
> There is no technical moat in this field, and so OpenAI is the epicenter of an investment bubble. Thus, effectively, OpenAI is to this decade’s generative-AI revolution what Netscape was to the 1990s’ internet revolution. The revolution is real, but it’s ultimately going to be a commodity technology layer, not the foundation of a defensible proprietary moat. In 1995 investors mistakenly thought investing in Netscape was a way to bet on the future of the open internet and the World Wide Web in particular.
OpenAI has a short-ish window of opportunity to figure out how to build a moat.
"Trying to spend more" is not a moat, because the largest US and Chinese tech companies can always outspend OpenAI.
The clock is ticking.
[+] [-] bruce511|1 year ago|reply
Amazon might be a good analogy here. I'm old enough to remember when Amazon absorbed billions of VC money, making losses year over year. Every day there was some new article about how insane it was.
There's no technical moat around online sales. And lots of companies sell online. But Amazon is still the biggest (by a long long way) (at least in the US). Their "moat" is in public minds here.
Google is a similar story. As is Facebook. Yes the details change, but rhe basic path is well trodden. Uber? Well the juries still out there.
Will OpenAI be the next Amazon? Will it be the next IBM? We don't know, but people are pouring billions in to find out.
[+] [-] toddmorey|1 year ago|reply
[+] [-] n_ary|1 year ago|reply
The competitions are mostly too narrow(programming/workflow/translation etc) and not interesting.
[+] [-] florakel|1 year ago|reply
[+] [-] neals|1 year ago|reply
[+] [-] mrtksn|1 year ago|reply
Maybe they were just too early, later on it turned out that the browser is indeed a very valuable and financially sound investment. For Google at least.
So having a dominant market share can indeed be even if the underlying tech is not exactly unobtainable by others.
[+] [-] fmap|1 year ago|reply
Once this bubble bursts, local inference will become even more affordable than it already is. There is no way that there will be a moat around running models as a service.
---
Similarly, there probably won't be a "data moat". The whole point of large foundation models is that they are great priors. You need relatively few examples to fine tune an LLM or diffusion model to get it to do what you want. So long as someone releases up to date foundation models there is no moat here either.
[+] [-] chii|1 year ago|reply
and they are probably going to go with regulatory moat over technical moat.
[+] [-] BeefWellington|1 year ago|reply
See the scramble to make themselves arbiters of "good AI" with regulators around the world. It's their only real hope but I think the cat's already out of the bag.
[+] [-] yalogin|1 year ago|reply
[+] [-] boh|1 year ago|reply
[+] [-] Nasrudith|1 year ago|reply
[+] [-] cyanydeez|1 year ago|reply
But greeed isgood!
[+] [-] numpy-thagoras|1 year ago|reply
OpenAI's C-suite: Well, they earned the C, but it was a letter grade.
What a profoundly unimaginative strategy. No matter the industry, a large-scale diversion of resources towards a moonshot goal will likely get you to that goal. They haven't made an argument as to why we should do that just for them, especially with all of the other alternatives.
And no, advertising your previously secret testing models (e.g. o3) as if they were market competitors is not how to prove they should have our money.
[+] [-] abc-1|1 year ago|reply
Then why do they look about average to Anthropic, Mistral, DeepSeek, and many others of that cohort despite having x100 the amount of resources?
[+] [-] ryanwaggoner|1 year ago|reply
What “we”? They’ve already raised billions, and I suspect they’re about to succeed at raising tens of billions more, despite the skepticism of random HN users.
[+] [-] myhf|1 year ago|reply
The Unreasonable Effectiveness of Huge Sums of Money in the Natural Sciences
Unimaginable Sums of Money Considered Harmful
[+] [-] theideaofcoffee|1 year ago|reply
[+] [-] seydor|1 year ago|reply
[+] [-] SignalsDoctor|1 year ago|reply
[+] [-] yobbo|1 year ago|reply
[+] [-] ghshephard|1 year ago|reply
[+] [-] asadotzler|1 year ago|reply
[+] [-] netdevphoenix|1 year ago|reply
The long term future of LLMs sure looks like the LLMs themselves will be commodities and the real value will lie in the use of those LLMs to deliver value
[+] [-] bravura|1 year ago|reply
AI progress is driven by strong valuable data. Detailed important conversation with a chatbot are much more valuable that quick search queries. As LLMs extend past web UIs, there is even more interaction data to capture and learn from.
The company that captures the most human-AI interaction data will have a TREMENDOUS moat.
[+] [-] staticman2|1 year ago|reply
If I have the LLM translate a text from French to English... what is there to learn from that? Maybe the translation is great maybe it's awful, but there's no "correct" translation to evaluate the LLM against to improve it.
If I ask the chatbot for working code and it can't provide it, again, there's no "correct" code to train it against found in the conversation.
If I ask an LLM to interpret a bible passage, whether it does a good job or a terrible job there's no "correct" answer that the provider has to use as the gold standard, just the noise of people chatting with arbitrary answers.
[+] [-] motoxpro|1 year ago|reply
[+] [-] ijustlovemath|1 year ago|reply
When the big companies say they're running out of data, I think they mean it literally. They have hoovered up everything external and internal and are now facing the overwhelming mediocrity that synthetic data provides.
[+] [-] mrbungie|1 year ago|reply
[+] [-] paxys|1 year ago|reply
[+] [-] niemandhier|1 year ago|reply
I disagree, that phenomenon is tied to the social network like phenomena we saw with WhatsApp and Facebook and to the aggregator business model of Amazon and Google.
Mathematically we can describe the process by which these monopolies form as nodes joining graphs:
Each node selects graphs to connect to in such a way that the probability is proportional to the number of nodes in the graph.
Sure Amazon and google feature two types of nodes, but the observation still fits: Selling on Amazon makes sense if there are many customers, buying on Amazon makes sense if there are many offers.
OpenAIs business does not have this feature, it does not get intrinsically get more attractive by having more users.
[+] [-] andrewstuart|1 year ago|reply
Claude is noticeably better
[+] [-] dmazin|1 year ago|reply
[+] [-] hebrox|1 year ago|reply
[+] [-] ryao|1 year ago|reply
[+] [-] sumedh|1 year ago|reply
[+] [-] bloomingkales|1 year ago|reply
The word "open" is still under threat in this scenario too.
[+] [-] rsync|1 year ago|reply
The world‘s largest oil producer?
[+] [-] Gys|1 year ago|reply
[+] [-] epolanski|1 year ago|reply
Models are commodities, even in the case Open ai goes through another major breakthrough nothing can stop some of their employees to run to other companies or founding their own and replicating or bettering the OpenAI results.
In fairness I realize that I don't use any of OpenAI's models. There are better alternatives for coding, translating or alternatives that are simply faster or cheaper (Gemini) or more open.
[+] [-] janice1999|1 year ago|reply
[+] [-] tiffanyh|1 year ago|reply
Yet Chrome for Google did help create a moat.
A moat that’s is so strong the DoJ is investigating if Chrome should be a forced divesture from Google/Aplhabet.
Note: I do generally agree with the article, but this also shows why you shouldn’t use analogies to reason.
[+] [-] dheera|1 year ago|reply
[+] [-] YetAnotherNick|1 year ago|reply
This is getting so repetitive now that it is stated as a truism.
Isn't it the same bet yahoo was betting on in 2000 that it would win because their product branding is better? And now, Yahoo's and Microsoft's search engine is worse than Google from 2 decades ago.
[+] [-] yodsanklai|1 year ago|reply
[+] [-] benterix|1 year ago|reply
The so-called open source models are getting better and better and even if OpenAI suddenly discovered some new tech that would allow for another breakthrough, it will be immediately picked up by others.
[+] [-] sumedh|1 year ago|reply
The data backs it up, Anthropic make most of their revenue from API while ChatGpt makes most of its revenue from the plus plan.
[+] [-] unknown|1 year ago|reply
[deleted]
[+] [-] robertlagrant|1 year ago|reply