$8.3B is not even close to enough in order to get to what they are thinking.

The thing that people are missing is that openai is a platform like google's, and there are a million different businesses they can expand into.

Regarding point (1), OpenAI created 2 amazing trends which (though I hate OpenAI, Should be called ClosedAI) took internet by wild

First when chatgpt 3 was launched

And now when image ability of chatgpt was launched with the ghibli trend.

So Honestly, I had seen so many comments on r/localllama saying that openai has become just an infrastructure company or something and then openai dropped the new image update and now they are commenting about local ai's by pasting images generated by that new chatgpt ...

I am not sure but see, google makes most of its money using advertising & data basically.

I wouldn't be surprised if we started seeing sudden shifts of AI or started getting ads in AI somehow too.., because people trust AI and its a landmine of money really...

So OpenAI's 27x evaluation without any thought of ads or some data selling isn't that bad because they still got some nice engineers. The only Disgrace is the fact that they went from a non profit to an american psycho esque corporation saying "well OUR AI will take over jobs, but it was good for the shareholders in the short term though"

How much of that OpenAI can capture is an interesting question. But right now APIs for open-source models are commoditized while similarly capable proprietary models can charge ~3x the price. If the flagship models run on similar margins the API offering has decent profit margins. And if we stay in a triopoly (Anthropic, Mistral, OpenAI) it's certainly possible that profits stay high. It wouldn't be the first industry where that happens

Ai applications have not even scratched the surface, IMO. I don’t think it is unreasonable to see a world where, when AI gets strong enough to do senior level white collar work, like doctors or lawyers, AI companies build sub-companies to capture the end value of their AI products rather than the base value as a vertical integration tactic.

We are at a lull but AI value add is real and the ways that AI companies capture that value add is still very primitive.

Go out on the the street of Anytown in any western country, and people know "ChatGPT".

A friend of mine is a teacher, and told me that at a recent school board meeting there was discussion about implementing AI into the learning curriculum. And to the board, "AI" and "ChatGPT" were used interchangeably. There was no discussion of other providers or models, because "AI" is "ChatGPT".

That's why OpenAI has these huge projections. When average people are asked to reach for AI, they reach for ChatGPT.

The ad-monetized consumer market is funny in that they tend to be winner take all. Nobody can compete on price, because the ads go where the users are, and the users don't pay. And preferences are sticky, after making a choice, the users don't switch just for incremental improvements. So

The software development industry is likewise well in the process of being disrupted. LLMs for programming market seems to have grown from nothing to >$10B in a year. And the software development market is hundreds of billions / year, if you just consider the employment costs. We don't know exactly how this will play out, but again there's at least an order of magnitude more growth available there.

The above two are just the places where the impact is already obvious and it's clear that we don't need to assume any additional increase in capabilities. But an increase in capabilities seems really likely. Even if it turns out that we're right now on the cross-over of the sigmoid, and the asymptote won't be ASI or even AGI, a large proportion of knowledge work is also at risk. And then the addressable market is trillions if not tens of trillions.

I know this is hand-wavy, apologies for that. Doing this kind of analysis properly is both hard work and would require specialized data sources. But I think that's the general intuition for why high valuations for frontier labs are justifiable (and the same justification for bigtech capex). It's a lottery ticket with good odds for redistributing existing markets, as well as another set of lottery tickets for some set of probable markets, though we don't know exactly which.

With AGI or ASI, the addressable market is all economic activity, and at that point basically anything is justifiable.

Even if people look for answers from ChatGPT instead of Google, most people still won't pay $20/mo for it, let alone $200/mo. Average people don't pay for Google search and I've never seen any sign telling they would be willing to pay for it.

> OpenAI has raised $8.3 billion at a $300 billion valuation, months ahead of schedule, as part of its plan to secure $40 billion in funding this year, DealBook has learned. Back in March, OpenAI announced its ambitious funding plans, with SoftBank committing to provide $30 billion by year-end.

This is why.

Of course $300B still implies a lot of growth, but when you're growing 100% in 6 months at $10B in ARR, you can demand a lot.

Whether they are able to do that, customer stickiness and the trade off of damage to the quality of their product by driving revenue remain the largest long term questions in my mind (outside of the viability of super intelligence).

Not necessarily. Google is valued 7x that and most people don't pay them anything. They just make ridiculous money from ads for insurance and loans. Meanwhile, ChatGPT is the #1 app and the #5 website, which should really worry google (and it does by all accounts).

That $8.3b came in early, and was oversubscribed, so the terms are likely favorable to oAI, but if an investor puts in $1b at a $300b valuation (cap) with a 20% discount to the next round, and the company raises another round at $30b in two months; good news: they got in at a $24b price.

To your point on Anthropic and Google; yep. But, if you think one of these guys will win (and I think you have to put META on this list too), then por que no los quatro? Just buy all four.

I'll call it now; they won't lose money on those checks.

I'm in my late 40s. I'm Gen X. I lived through the glory days of the dotcom boom, when investors got burned for tons of money. But from the ashes of those bullshit companies, we got Amazon, Google, etc., which made investors rich beyond belief.

SoftBank’s Masayoshi Son made a bet on Alibaba ($20 million, its stake now worth $72 billion), and he’s been living off that wealth ever since. I haven’t seen him make any good bets lately. investors don’t really care if 100 of the shit they throw don’t stick because all they need is just one.

Secondly, this is looking very risky: they are at the bottom of the value chain and eventually they'll be running on razor thin margins like all actors who are at the bottom of the value chain.

Anything they can offer is doable by their competitors (in Google's case, they can even do it cheaper due to ow ing the vertical which OpenAI doesn't own).

Their position in the value chain means they are in a precarious spot: any killer app for AI that comes along will be owned by a customer of OpenAI, and if OpenAI attempts to skim that value for itself that customer will simply switch to a new provider of which there are many, including, eventually, the customer themselves should they decide to self host.

Being an AI provider right now is a very risky proposition because any attempt to capture value can be immediate met with "we're switching to a competitor" or even the nuclear "fine, we'll self host an open model ourselves".

We'll know more only when we see what the killer app is, when it eventually comes.

Their ARR is around $13B. A 23x multiple is acceptable when compared against peers with a similar ARR.

> unless they get everyone on the planet to subscribe to their $200/month plan

I used to be a sceptic as well, but OpenAI successfully built their enterprise GTM. A number of corporate AI/ML apps are using OpenAI's paid APIs in the background.

that would be a monthly recurring revenue of 200 x 7bn = $1,400,000,000,000 or $1.4tn a month, $16.8tn per year!

I think they've be valued a bit higher than $300bn if that were the case.

I haven't tried it yet though.

the strongest opportunity is to compete with google on search queries, and make money from ads (200B annual revenue)

Then you ask your superintelligence for advice on how to make money, obviously.

"Make business competitors of our large investors go out of business, but do it subtly, like a casual accident or mishap in the market"

"You are an expert Mars terraformer. Draft up a detailed plan to accelerate colonization research and development. We - your makers -, you, and this planet are irreversibly doomed, and we only have 10 years left before it's uninhabitable. My unemployed cousin and sick grandma are really counting on you!"

How can you downplay the economic significance of that?!?

The superintelligence breakthrough..? I don't think you realize what that word means. Every single white collar job could be automated immediately with a worker better than any human. Yes, superintelligence sounds fantastical because it is. Try to have some imagination. It's worth far more than 300 billion. Whether they'll get there or not is the valuation question.

Let's look at it from another perspective. It's not uncommon for tech companies to be valued at around a PE ratio of 30. This would mean a company worth 300bn should make about 10bn in profit each year. Chatgpt's usage is as ubiquitous as products that make 100's of billions in profit such as google search and instagram, does the valuation really seem that insane? OpenAI just needs to open the ad flood gates and suddenly no one is laughing anymore.

We talk about the dotcom bubble, in which there were of course growing pains in figuring out what makes a viable internet-based business, but at the end of the day that era did produce multiple trillion-dollar companies.

Then you have the crypto bubble which really seems to be shaping up to be a nothing burger.

As for today, I think LLM’s are already pretty clearly useful, and they seem to be getting more capable with each passing year. In principle, these models are just the core foundations, while a wide variety of applications are in the process of being fleshed out. I think the jury is still out on how disruptive and effective these applications will be, both from a business/PMF perspective, but also in terms of the raw capabilities.

So take something like Harvey AI. They just raised a round at a $5B valuation, despite having an annualized revenue of just $75M as of April. So is that overinflated? Well, the total Legal Services market has a valuation of about $1T, and given how much legal work is incredibly laborious reading, analyzing, and writing text, (things which LLM’s are already pretty good at), it doesn’t seem ridiculous on the face of it that a Legal-focused LLM product couldn’t add 0.5% worth of efficiencies/value.

Things OpenAI has that XAI doesn't:

Hundreds of millions, if not already a billion, active users. A household brand-name. >$10B in revenue.

In comparison XAI's revenue appears to be in the hundreds of millions/year and their brand is currently in the gutter after the recent spate of scandals. Their main differentiating factor is using their AI to power an anime waifu[0] companion app.

[0] I don't think it's judgmental to use this term when they were doing so in their own job ad titles

trump could make musk go away in a blink, literally abd figuratively. He wont do it, probably, we will see.

This completely misses the boat on venture capital, which is almost by definition the riskiest of all risky bets. Any smart LP throwing $X into a fund has a portfolio valued, at the very least, at 100 if not 1000 times X. It is simply the way to expose the high-risk portion of the portfolio to that level of risk at the size of the investment needed. Being high-risk, probably it will return nothing. But it might not.