OpenAI and Anthropic Revenue Breakdown

I'd rather argue that every hyped topic is polarizing, and your argument can be adjusted to basically every hugely hyped topic.

Something similar happened when COBOL came out. Same with website builders. The big difference between most industries versus software is we aren't even close to satisfying the world's desire for software yet, so increases in productivity just gives us bigger leverage.

Is this supposed to be scary? This scenario is absolute stonks if you're a developer worth your salt. A machine makes me 5 times more productive, and I don't even have to commoditize my complement because they're taking care of that themselves?

Personally I think its cyclical as software is such a key component of communication and automation - and so we'll see future growth periods but probably not to the same extent as the last decade where seemingly every undergrad was compelled to study Computer Science.

The rate of change could make the short term bumpy as companies try to play around with less dev work. Eventually though competition will push companies to raise their productivity to the new baseline (programmers + AI).

One thing that is a danger is if devs ignore what's happening in AI. I remember when Google first came out having to learn the art of querying Google to get what I was looking for. AI/LLMs looks to be the same - ignore learning how to leverage them at your own peril.

There are three likely outcomes:

1. AI plateaus. OpenAI slashes the R&D budget to become profitable with revenue in double digit billions and profit in single digit billions. Valuation likely similar to today's.

2. AI doesn't plateau. OpenAI makes a killing. (Hopefully metaphorically, not literally)

3. Scenario 1 or 2, but it's a company other than OpenAI that wins.

> I don't see how a chatbot meets any of those criteria

Calling these things "a chatbot" is likely limiting your vision: some of the stuff people build by fine-tuning LLMs, such as the ones OpenAI offer, use them to generate database queries matching their customers' database schemas.

"Chatbot" is simply a convenient UI for an LLM in the same way that a web browser is a conventional UI for email. (And in this analogy, anyone calling an LLM "autocomplete on steroids" would be making the same mistake as someone saying "Wikipedia is just TCP on steroids").

I expect LLMs to continue to be extremely generic in the same way that web browsers are (market history shows periods where one browser dominates the market despite open source) or like spreadsheets (where Microsoft Office is, or was last I looked, dominant despite free offerings being good enough for most people).

Society needs intelligence. We started using mechanical aids because it became impractical to perform census work by hand as the population increased, AI is a continuation of this process: we need it, it's a commodity, there may be a market opportunity despite free and/or open source competition, and (like Netscape, like Internet Explorer) there's no guarantee that the winner in one year will still be leading the next year or even existing a decade later.

As AI gets more tightly integrated into IDEs, and office suites, then stand-alone products like ChatGPT become less relevant, and the underlying provider more of a replaceable commodity. Would anyone really notice or care if Github CoPilot switched overnight to use a Microsoft/Anthropic/Meta model rather than an OpenAI one ?!

You divide the price by earnings.

OpenAI has negative earnings.

It doesn't have a P/E.

Emphasis added.

You spend money on R&D.

The expectation: You make money.

The AI company reality: The value of your propitiatory models drops to LITERALLY ZERO after they are superseded by a new generation of models, or worse, open inference models.

The risk isn't that the models don't work.

The risk is that it increasingly appears that the 'moat' these companies have is only as good as the amount of money they continue to pour into it. and when the moat is gone, so is the company.

I can also run a business where I create a moat by pouring money into it (remember MoviePass?), eg. literally paying people to use your service; but usually you have to have some kind plan that does not involve magical fairies (eg. AGI) in at the very least your pitch deck, to convince people you have a plan which goes from scale -> mega profit.

The math comes down to the fact that they raised enough money to stay in business until they have to raise even more money.

And a 180 mil users might seem like a lot in two years, but with the free media coverage they have... even if their free to premium conversion rate is pretty dismal, the "have you heard about them" to "active free user" rate is also very bad!

1. Be extremely generous to customers. Give away incredible tech at bargain basement prices. Pamper your employees with extraordinary benefits. Everyone from all angles loves your business.

2. People integrate your product into their lives. They become dependent on it because the value is so good. They tell everyone else in their lives about it. (2.5 IPO. This is where you make an exit, where those people who "love" your product that everyone else loves want to get in on the investment. Retail runs to buy up your shares. Also could be an acquisition.)

3. Close the hand. Competition has been ruined and people are addicted. Now it's time to raise prices and lower product quality. Initial investors are already out, so retail will carry the blame for the enshitification of your product.

* Text generation is really bad if said text is more niche than typical SEO stuff like "give me 300 words about soccer balls". Anything academic is usually wrong (i.e. full of hallucinations) or lacks/hallucinates proper sources. If I have to check everything anyway I can just use a search engine.

* Image generation is really bad if you don't just want deviantart-like content. Just yesterday I tried generating ideas for visualisations of a few topics (with quite a view different prompt approaches) and they almost all were unusable.

It is good at summing up longform content, though, but then again so am I - and I have to read it anyway to confirm there are no hallucinations...

Obviously many people use it for coding (which appears to be the low hanging fruit because code is so heavily formalized), but I can imagine that market is almost saturated by now.

I'm sure they could raise $100B if/when they need to, as long as the growth/scaling story stays intact, but $100B is still a lot. They just raised $6B, which alongside a similar amount raised by x.ai is largest raise by a startup afaik. Buying 100K GPUs atm would be a challenge too, due to supply.

In the meantime, per Dwarkesh interview with SemiAnalysis.com Dylan, Microsoft is in process of fiber-connecting multiple datacenters to make a massive meta-cluster, and this is what OpenAI would lose access to if the relationship with Microsoft sours. Amazon (partnered with Anthropic) and Meta, even x.ai, already have massive clusters, so OpenAI could find themselves temporarily in the GPU-poor club if they upset Microsoft after Microsoft make them expendable (or maybe at that point, it's "will" rather than "could").

I also pay for better AI. My - and probably your time - and the time saved by using superior tooling, is worth far more than the meagre few dollars spent each month on some subscription.

You're stepping over dollars to pick up dimes.