N70Phone

My point is that for these purposes, users are not fungible. You can't just divide the cost-revenue equation by the amount of users N on both sides.

No it's not.

If you add a pile of fictious users to the usercount, the apparent average cost-per-user drops as the fictious users do not use the service and do not add their own costs. This lowers the apparent amount of per-user revenue you need.

However, as fictious users also do not generate revenue, this is all smoke and mirrors.

You can't average out the userbase like that because the individual usage of the service varies wildly, and advertising revenue is directly tied to amount of usage.

Especially because OpenAI highly inflates user figures.

It's not orders of magnitudes more expensive

This too is skewed by averaging with users who barely use the service.

does work for Google and Meta

I will point out that this is contentious, both of these companies are subject to regulatory investigations around their monopolistic practices & the matter that they are pretty much the only companies for which this is profitable.

Their model, today, is far more relevant than calling back to antiquated banner advertising models from 25 years ago

Hardly. It's fundamentally the same model; Content with an advertisement next to it. Whether that is a literal banner ad or a disguised search result, none of the formfactors are new.

For all the advances in ad-tech, CPMs are still the same old dogshit they were shortly after the dotcom bubble, looking better only because of inflation.

you'll have to convince me that Google and Meta's model cannot work for OpenAI, which you have not adequately done.

That's the "orders and orders of magnitude more expensive" part. Neither Google Search nor Facebook are that profitable per single ad, they make it up in volume. LLMs are simply more expensive to operate than a search engine or a glorified web forum. Can OpenAI cut down their opex and amortized-cap costs down to less than the half-penny they'd extract with good CPMs? Probably not.

But there's a deeper layer. The "fund AI with ads" model paints a scenario in which OpenAI would have to overtake Google; They need the ad-tech monopoly to push up CPMs or you can cut that half-penny down an order of magnitude.

This is unlikely. To make ChatGPT work as a search engine requires all the infrastructure of a search engine. Ipso-facto they are always more expensive than a standalone search engine.

Yet at the same time, people only care about ChatGPT as search because Google Search is shit now. Were ChatGPT to ever become a serious threat to Google, Google can simply turn off the search-enshittifier for a bit and wipe out ChatGPT's marketshare, and push them into bankruptcy by drawing down CPMs below OpenAI's sustainability level.

even today, ignoring the reality of untapped revenue streams like ChatGPT's 800M advertising eyeballs.

Respectfully, the idea of sticking ads in LLMs is just copium. It's never going to work.

LLMs' unfixable inclination for hallucinations makes this an infinite lawsuit machine. Either the regulators will tear OpenAI to shreds over it, or the advertisers seeing their trademarks hijacked by scammers will do it in their stead. LLMs just cannot be controlled enough for this idea to make sense, even with RAG.

And if we step away from the idea of putting ads in the LLM response, we're left with "stick a banner ad on chatgpt dot com". The exact same scheme as the Dotcom Bubble. Worked real well that time, I hear. "Stick a banner ad on it" was a shit idea in 2000. It's not going to bail out AI in 2025.

The original content that LLMs paraphrase is itself struggling to support itself on ads. The idea that you can steal all those impressions through a service that is orders and orders of magnitude more expensive and somehow turn a profit on those very same ads is ludicrous.

Previously (or if you simply don't use var), a lot of java code takes the form of

  BeanFactoryBuilder builder = new BeanFactoryBuilder(...);

Looking at where America is right now. It seems to make a downfall.

It's been happening for years now. 'America', the idea, died the moment the 2nd plane hit the towers.

People saw that happen, and were so fearful they immediately opened their hearts to fascism.

2025 is merely the year where all of Bush's fascist policies & Obama/Biden's failure to clean it up metastasized into the overt fascism that hurts everyone in a country & eventually destroys the country itself.

Part of what's concerning here is that the deals are conditional. OpenAI must meet XYZ conditions before cash/stock/etc is transferred, and the conditions are pretty hard to meet.

The money between OpenAI, Nvidia, Oracle, AMD is not circulating. There is no cashflow, only future commitments that may (and quite likely will) collapse. Yet the stock market & media react as if it's a sure thing. Even in the criticisms of these deals, the hype is affirmed.

This is the same problem as Enron's accounting, minus the fraud. (No need for fraudulent accounting when people simply don't read the fine print.)

It seemed quite the opposite. That you knew exactly what you were saying, but using weasel words to imply ICE was acting above board without stating any falsehoods that might be challenged.

The rhetorical trick of my reply being that it forces you to either address to the meat of the subject, or leave the statement uncontested.

But congratulations, conceding the argument rather than ousting yourself as a fascist was the better choice.

as a general rule

To rudely open a dictionary:

"As a general rule" - phrase of general - in most cases.

Agents of the state are supposed to be acting within the law IN ALL CASES.

The SS & SA were operating entirely within the law, if you ignore the times where they weren't.

I find it funny how people say GPT-5 "bombed".

I used scare quotes for a reason. It didn't "bomb" in the sense of failing [insert metric], it bombed in the sense that OpenAI needed it to generate exponentially more hype and it just didn't. (And on a lesser level, GPT-5 was supposed to cut OpenAI's costs but has failed to do so)

I can trust its proofs or code to be about as correct as my own.

I have little to say about this, as I find such claims to be broadly irreplicable. GPT-5 scores better on the metrics, but still has the same "classes" of faults.

And the trick appears to be working since the stock is up 30% today, meaning it has paid for itself and then some.

It's a bubble. The tricks keep working until they suddenly don't, and then all the prior tricks unwind themselves.

Percentage math doesn't quite work that way. (130% * 90% for gaining 30% and then giving away 10% of that, is 117% not 120%)

But yes. That's the intent.

The "problem" is that OpenAI doesn't have any of the shares yet, and it's unclear how much they actually will get. Right now AMD shareholders have the full +30% gain with none of the loss. But will the +30% gain be wiped out on the news OpenAI won't be buying as many AMD GPUs? Only time can tell.

I also don't get why there commiting so much to the future, are they sure of the quality of the products and their demand that much?

It's one big game of musical chairs, and everyone can hear the phonograph slowing down.

OpenAI is making these desperation plays because they've ran out of hype. GPT-5 "bombed", the wider public doesn't believe AI is going to keep getting exponentially better anymore. They're out of options to generate new hype beyond spewing ever larger numbers into the news cycle.

AMD is making this desperation play because soon, once the AI bubble pops, there'll be a flood of cheap unused GPUs & GPU compute. Nobody's going to be buying their new cards when you can get Nvidia's prior gen for pennies on the dollar.

AMD issues new shares and gets a penny (read: effectively zero) back for them.

ALL ELSE BEING EQUAL this means everyone holding AMD has 10% of their equity/value taken away and handed to OpenAI.

But all else is not equal. OpenAI only gets the shares if they buy AMD GPUs. The intent is that this offsets the dilution by making AMD overall more valuable. (This is why the stock price jumped on the announcement) It's a GPU subsidy paid for by AMD's shareholders rather than AMD itself.

The real risk is that this further entangles AMD in the AI bubble. OpenAI already has enormous datacenter construction obligations. The likelihood of them failing to meet these new obligations, and thus this deal falling through or otherwise not materialising, is pretty high. If the AI bubble goes *POP*, AMD will be hurting a lot more than before this deal.

It is folly to take these statements at their words.

Bezos is just saying shit to generate hype. All these executives are just saying shit. There is no plan. You must treat these people as morons who understand nothing.

Anyone who knows even the slightest details about datacenter design knows what moving heat is the biggest problem. This is the exact thing that being in space makes infinitely harder. "Datacenters in space" is an idea you come up with only if you are a moron who knows nothing about either datacenters or space.

If nothing else this is the singular reason you should treat AI as a bubble. All of the people at the helm of it have not a single fucking clue what they're talking about. They all keep running their mouth with utter nonsense like this.

Given they're referencing Icarus, they seem to agree with you.

Past bubbles leaving behind something of value is indeed no guarantee the current bubble will do so. For as many times as people post "but dotcom produced Amazon" to HN, people had posted that exact argument about the Blockchain, the NFT, or the "Metaverse" bubbles.

Now, go away, or I shall taunt you a second time-a!

That is the implication. The point of the first fine isn't to actually hurt Meta. It's to signal that there will be consequences, that the excuse of "but we thought it was legal" is gone now and give them one final chance to get their act together.

It's to pre-emptively clear away any possibility for Meta to appeal to either higher courts or the court of public opinion that they're being treated unfairly. Which they would do if you immediately hit them with a say, €5 billion fine.

An important matter in this particular case: It's about elections as well.

You can opt to not use facebook yourself to protect your own data, that is more or less fine. (Though we can talk about Facebook's collection of non-user data another time)

You can't individually opt out of the election influence.

a year or two ago

3 years ago. September 2022. https://edition.cnn.com/2022/09/23/economy/powell-fed-labor-...

When unemployment rates were back down to the pre-covid 2020 levels, only time they were even lower was before the 1969 recession. When inflation was at the highest it's been since the 80s.

The statement & monetary policy decision was entirely appropriate at the time.

I.e., understanding a code base, the algorithms, etc.?

The big problem is that LLMs do not *understand* the code you tell them to "explain". They just take probabilistic guesses about both function and design.

Even if "that's how humans do it too", this is only the first part of building an understanding of the code. You still need to verify the guess.

There's a few limitations using LLMs for such first-guessing: In humans, the built up understanding feeds back into the guessing, as you understand the codebase more, you can intuit function and design better. You start to know patterns and conventions. The LLM will always guess from zero understanding, relying only on the averaged out training data.

A following effect is that which bunderbunder points out in their reply: while LLMs are good at identifying algorithms, mere pattern recognition, they are exceptionally bad at world-modelling the surrounding environment the program was written in and the high level goals it was meant to accomplish. Especially for any information obtained outside the code. A human can run a git-blame and ask what team the original author was on, an LLM cannot and will not.

This makes them less useful for the task. Especially in any case where you intent to write new code; Sure, it's great that the LLM can give basic explanations about a programming language or framework you don't know, but if you're going to be writing code in it, you'd be better off taking the opportunity to learn it.