> I use their services, but I frankly don't care who provides it. I'll chase the chepest/best and have no issue switching from one to another.

For the hyperscalers, there is an ease of remaining in the Azure/AWS/GCP fabric from a data provenance perspective, particularly for regulated industries or large, risk-averse enterprises. There's also, of course, a certain network egress tax in most cases.

Amazon Bedrock is probably middlemanning an insane amount of token consumption these days for the same reasons.

Nvidia has a moat. Hardware is hard. No one really competes with them for general compute

I've been thinking for a while, there's not real winners here except the incumbent technology providers. Hear me out: all models are converging towards the same level, gains are getting smaller and harder to come by. The models are commodities nothing more.

This is the leap, nobody really wants to front a model for someone else. If i build an agent, or a service that requires a model, I'd prefer to push the model onto someone else, preferably at no cost. This is a leap as I'm sure right now, most people / businesses are thinking actually i do want to own / front the model.

However, if you accept the leap the easiest way to do this is to make the model the users problem.

From a business point of view that makes things really easy, from a customer point of view, they simply have to accept whatever their vendor of choice is pushing down their throats.

So as a business I build for whatever model Google makes available to android, and whatever model windows bundles, and whatever model Apple bundles, and, excluding the long tail of Chinese vendors and Linux (sorry, its always left out) and that's it, problem solved, and the customer picks up the tab for the tokens

The adoption of standards like skills and agent setup helps a ton. Nobody wants to be locked into an AI vendor like with cloud systems in general. And companies can't hold on to the #1 spot across multiple areas for very long, so users are even more motivated to move their process and stack between coding tools and AI companies behind them like Claude code.

Vendor lock in cannot happen, or you're bankrupt.

The moat is shifting from technology to access to proprietary training data. It doesn't matter how good your LLM platform is if you don't have good data to feed the training run. Public Internet data and published media is already mined out. Now the frontier LLM vendors have shifted to licensing proprietary data that's locked up behind corporate firewalls, and even hiring human domain experts specifically to create new training content in target verticals. You'll see the effects of this next year, although it might not be obvious to those who mostly only use LLMs for coding tasks in popular programming languages for which there was already a lot of training data.

I think anthropic with its enterprise strategy and google with its integration in everything have a bit of a moat.

But I switched from ChatGPT to Claude 3 months ago because my account was down for like 6 hours. I haven’t used it since. It’s too easy to switch away from chatbots on a whim. There is no moat for that.

AWS and Google at least own their own hardware (Trainium and TPUs, respectively). It's a moat in the sense that designing, building, and deploying your own chips at scale is quite a feat and not easily replicated. The vertical integration will allow them to continue to be profitable once the models get good enough and competitors' prices race to the bottom. Google has Gemini; AWS may not deploy its own models (yet?), but that's not necessarily a losing position, as long as the market is able to run models sourced elsewhere on Trainium and the price is right.

Well there is clearly also a lot of non-GAAP style “trust us bro” things going on too which generally boil down to “if you ignore all the reasons why we’re not profitable then we’re profitable.” It’s WeWork’s “community adjusted EBITDA” messaging repackaged.

If the company who holds the mortgage wanted to own the building, they would have just bought it themselves. They don't, for whatever reason, so to some extent they have an incentive to help their customer succeed.

That's why it's so hard to get a residential mortgage, for example. It's more of a partnership, with more mutual vulnerability, than most people think. Same thing seems to be true here.

I think those are just the loud minority. I wouldn't be surprised if they're like 20-30% if a poll were made here

Good question.

Given what happened with xAI’s excess capacity lease to Anthropic, and Meta’s noises about doing the same, seems likely that the demand for inference will continue to slope upwards for a while. If I’m Oracle, I’m not worried about being able to utilize the data centers I’ve built for some price, almost certainly a profitable one.

I’m guessing, though, that Oracle made their capital investments on assumptions of a higher price & return. Possibly because it wasn’t clear when these decisions were made how much competition OpenAI would have at the frontier.

I don’t think this math is all that hard. Capital markets have everything they need to start to figure it out, most especially a year or two of history to project forward.

> They aren't finding AI to be have less ROI than before - they are requiring higher ROI than before, because there is less money remaining.

What ROI? There was no return, and there currently isn't any return on investment, because those companies did not exit yet!

The exit plan is to offload overpriced shares, that they paid billions for, onto the public market. If they don't IPO, those investors get nothing.

> there is less money remaining.

In what sense?

This may be related to the commonly-held fallacy of "cash on the sidelines". Cash is always on the sidelines. Cash is not created or destroyed by buying and selling stocks or bonds. Cash is simply handed from one party to another, but the cash has to be held by somebody.

> is supposed to be the central bank's job.

What? No it's not, and never has been.

Without even getting into the practical vs. theoretical of Fed dual mandate (funding deficits), even the most uncharitable take on modern CBs wouldn't suggest this.

I was at the ophthalmologist for the second time in two weeks - my new prescription wasn't quite right, new lenses should be here this week.

All that to say: I had to move my focus around a bit and re-read "...pumped into AI buildout." several times, because I thought I was reading Ed Zitron :D

Hi there, how do you know Amazon's bond offering was "challenging"? Curious to learn more. Thank you.

> Market signals on an impending AI bust are broader than just Oracle’s woes.

It's worse than that - I believe that Oracle is one of the (many) companies right now that, if their AI experimentation fails, will stop the music, and everyone will be running for a chair.

Oracle is one of a few foundational components in the circular-investing group of AI companies. If they fail to make their commitments they're the first domino to fall.

And none of the major model makers (not counting SpaceX) have IPO'd yet