I would suggest that the Venn diagram for "people building things" and "people who understand LLMs" is worth contemplating here.
ChatGPT is certainly interesting, and some people are paying for it, but I think a) it's not clear how much of that use is also driven by hype, b) of the non-hype use, it's not clear how much will be sustained over the long term, and c) of that long-term use, it's not clear how much is actually of net benefit to society.
Regarding A, an interesting parallel is blockchain hype. There were a zillion blockchain projects, from startups to enterprise efforts. I can't quickly find a reliable number for how much money product vendors, service vendors, and consulting companies took in, but I wouldn't be surprised if that was in the low billions at peak, to say nothing of all the investor and in-house money spent on staff and whatnot. And as far as I know, no non-cryptocurrency success was ever demonstrated. So we can't just suggest that revenue means something will last.
Regarding B, it's a very volatile landscape both in terms of technology and in terms of market. E.g., for a hot minute, everybody loved lively AI generated images as stock photo replacement, but that fad is already past. People are getting a better sense for machine-generated text, too. I know of one company that fired their contract development shop because they kept getting machine-generated communications from the people they were paying to do actual work. Or we could look at Alexa and her kin as an example of something where despite initial excitement, it turns out people just don't care much. Same for VR; since the 1990s the technology keeps getting better and it keeps being a small niche. And we haven't even gotten to how competition and technological improvement will change (or perhaps eliminate) the margins here.
And regarding C, a number of the uses people are paying for are things that are not making the world better. Academic cheating, for example, may be to the advantage of a student who just wants a credential, but it burns a lot of money and makes the world worse. The same applies for people in companies who want to give the appearance of work. Then we have things like spam and influence operations. Over the long term, parasites tend to get squished, however much they can flourish temporarily when they learn a new trick. So that's another slice of AI revenue that can't be counted on.
And I should add that belief among the technically literate has so far been negatively correlated with there not being a winter. In this talk, iRobot founder and noted robot scientist takes a look at that: https://www.youtube.com/watch?v=pgrzEHJTPPM#t=36m55s
In particular, I set the timestamp to his list of AI hype cycles he had seen, 25 of them. Those all had people who understood the technology and believed in it. Maybe it's different this time, but that's what people say in every hype cycle.
Blockchain is a bad analogy to chatgpt. It would have been a good analogy if there were lots of people actually using blockchain as a currency. Suggesting Nvidia revenue is analogous is at least closer to fair because as I understand it a majority of GPU usage for LLMs is still for training. If everyone is sitting around training and no one is doing inference... there's a problem.
I don't believe any image generation service was earnings billions in revenue. Certainly no VR application did. OpenAI is reported to have done over $3 bill in revenue LTM. That's real money, it's all inference money, none of it is hardware. It's all real usage revenue.
The revenue is different. Money talks. And, even though it's anecdata, I personally know dozens of people who use ChatGPT a lot in their job. I used it a lot and get 1000's of dollars a month of value out of it. I worked in VR at peak hype and everyone who worked in it saw the usage numbers - awful, always awful. Not a single person I knew who had a VR headset used it with any frequency. No one.
Regarding blockchain, I was responding to the point that revenue was proof. A shit-ton of money went into blockchain projects. VR has also had significant sales. Both of these are fine analogies to demonstrate that billions of dollars in revenue does not prove a lasting success.
I'm not arguing that nobody uses ChatGPT; I believe they do. My point instead is that it's not clear how sustained the usage will be. E.g., a counter-anecdote: I know of a team who hired a dev who was a big ChatGPT fan. They eventually fired him, because his LLM-generated communication was poor and confusing, and his code was the kind of bad pretty typical of generated code. I'm sure he felt like he was getting thousands of dollars of value out of it up until the point he was shown the door.
One of the things that makes it especially hard to gauge is the extent to which piles of investor money are driving this. During Bubble 1.0, a lot of infrastructure companies had "real revenue" that turned out to be nth-hand investor money. We know ChatGPT has some real users, but how much of that inference traffic is ineffective or unsustainable startups burning up VC cash? That's a question that I expect will take 18 months or so to answer.
The blockchain stuff wasn't usage revenue, it was people trying to make a quick buck revenue. VR didn't have significant sales of applications, all the sales were hardware which was shelfware.
Billions of dollars of real usage revenue is an entirely different thing.
Bubble 1.0 is akin to Nvidia revenue - lots of dollars being spent on training, less on inference. Very unclear how much of it ever sees a return. There is a big difference between Nvidia revenue and ChatGPT revenue as far as the issue you are discussing. Inference revenue = real, training revenue (for infra providers) = very speculative.
Do you have stats on that "real usage revenue"? Because I don't think inference revenue alone qualifies. There are a lot of "AI" applications that are pumping money into the inference providers, but how much is real, sustainable, socially valuable usage is, as I've said a few times not yet determined.
The 3.4 billion of revenue is a stat. And it's the most meaningful. If a human voluntarily pays money for something you should assume they find it useful/valuable. It's not strictly true (various addictions etc), but the burden of proof to show otherwise is on you.
The specific number of $3.4 billion is not a stat. It's what Altmain claims they are "on pace" for.
Even taking it as real, you're the one making claims about how much of it is "real usage revenue". The burden of proof for that is on you. But as is typical for people riding a hype wave, you have not only repeatedly failed to do so, but you also apparently fail to understand countervailing concerns. That you are, in a fashion also typical for the true believer, trying to insist it's my job to prove the hype wrong, marks you as entirely unserious about honest inquiry here. Given that, I'm done.
Again, your failure to even understand my point, or to even ask questions that might lead you to understanding it, makes me think you are not interested in having a serious discussion, but instead are riding the hype train.
"Everyone who believes in LLMs are on the hype train, the usage is fake, and it's just like every other hyped thing that didn't work out, prove to me otherwise" is just a weak argument. People understand it, you are one of a large group of people making a similar point.
It's anecdata, but it seems every time this argument is made, it's from a person arguing by analogy rather than first principles, and the person don't really understand how LLMs work and haven't made any real effort to use them. You might not be in this bucket but making an analogy to the get rich quick but no real underlying use case blockchain community suggests you are.
Again, your failure to even understand my point, or to even ask questions that might lead you to understanding it, makes me think you are not interested in having a serious discussion, but instead are riding the hype train.
Again, your failure to even understand my point, or to even ask questions that might lead you to understanding it, makes me think you are not interested in having a serious discussion, but instead are riding the hype train.
> OpenAI is reported to have done over $3 bill in revenue LTM.
1. revenue doesn't mean much, afaik they still lose money on every query.
2. I think you are using that as a proxy for utility . Companies buying licenses en-masse hoping it will boost productivity is an unproven thesis. Don't see any profit boost in their qtrly reports from chatgpt licenses that they bought.
I use chatgpt and use it daily for coding. it isn't that its completly useless but uses are limited and certainly not worth hundereds of billions of dollars used to literally boil oceans. If someone took away chatgpt from me it not a big deal for me, to be honest. its dumb as rocks for coding, doesn't do even a tiny bit of high level thinking and almost half of it responses are hallucinating garbage.
ChatGPT is certainly interesting, and some people are paying for it, but I think a) it's not clear how much of that use is also driven by hype, b) of the non-hype use, it's not clear how much will be sustained over the long term, and c) of that long-term use, it's not clear how much is actually of net benefit to society.
Regarding A, an interesting parallel is blockchain hype. There were a zillion blockchain projects, from startups to enterprise efforts. I can't quickly find a reliable number for how much money product vendors, service vendors, and consulting companies took in, but I wouldn't be surprised if that was in the low billions at peak, to say nothing of all the investor and in-house money spent on staff and whatnot. And as far as I know, no non-cryptocurrency success was ever demonstrated. So we can't just suggest that revenue means something will last.
Regarding B, it's a very volatile landscape both in terms of technology and in terms of market. E.g., for a hot minute, everybody loved lively AI generated images as stock photo replacement, but that fad is already past. People are getting a better sense for machine-generated text, too. I know of one company that fired their contract development shop because they kept getting machine-generated communications from the people they were paying to do actual work. Or we could look at Alexa and her kin as an example of something where despite initial excitement, it turns out people just don't care much. Same for VR; since the 1990s the technology keeps getting better and it keeps being a small niche. And we haven't even gotten to how competition and technological improvement will change (or perhaps eliminate) the margins here.
And regarding C, a number of the uses people are paying for are things that are not making the world better. Academic cheating, for example, may be to the advantage of a student who just wants a credential, but it burns a lot of money and makes the world worse. The same applies for people in companies who want to give the appearance of work. Then we have things like spam and influence operations. Over the long term, parasites tend to get squished, however much they can flourish temporarily when they learn a new trick. So that's another slice of AI revenue that can't be counted on.
And I should add that belief among the technically literate has so far been negatively correlated with there not being a winter. In this talk, iRobot founder and noted robot scientist takes a look at that: https://www.youtube.com/watch?v=pgrzEHJTPPM#t=36m55s
In particular, I set the timestamp to his list of AI hype cycles he had seen, 25 of them. Those all had people who understood the technology and believed in it. Maybe it's different this time, but that's what people say in every hype cycle.