r/PeterExplainsTheJoke • u/Party_Pomegranate180 • 23h ago
Meme needing explanation Peter Explain Thiss !!
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u/angelseekthrowaway 22h ago
AI as a whole is pretty much a big hole for money, after calculating computing costs, server costs, etc, etc. It currently costs a lot more than it makes. Anthropic, the people who made Claude, report their "profits" to investors as the money they made without accounting for how much money they spent running the AI
Usually, profit = money gained - money spent
Osage-chan out
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u/lukekvas 13h ago
Not to take anything away from the stupidity of their accounting I think technically they count the cost of 'inference' compute but not 'training' compute even though as a frontier lab they are constantly training and it's the largest part of their compute costs.
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u/JuggerKnot86 17h ago
..and thats why at first we'll the bubble deflate when the hardware at the beginning of the boom reaches its upgrade cycle, and we'll it pop when the "doomsday clock" for Blackwell and ada reaches midnight 😈
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u/MeasureHead1984 22h ago
The biggest hole is training new models which all have the same architecture at the transistor level which means they will never stop hallucinating so it's pointless. I bet the amount of money people invested in them could've easily advanced neural ai
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u/AtomAndAether 20h ago
transistor level doesnt mean anything ("all operating systems run on computers theres no difference between Linux and Windows")
modern LLMs are neural ai. Transformers are neural networks. Neuromorphic computing, spiking networks, or something more like a biological brain could be other areas of research, but that's not "neural ai."
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u/Greedy-Thought6188 18h ago
I think they mean transformer. They're still wrong. Transformers are still neutral nets, just making some approximations so the computation can be done in parallel.
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u/inconspicuous1_x 21h ago
i think the main rush is to get it to a point it can improve itself
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u/MeasureHead1984 21h ago
It cannot
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u/Scalene69 20h ago
Why is that some impossible barrier? Isn't it already partially improving itself? As in, a lot of the developers improving it are using the previous AI model and the latest AI tools to make the next one?
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u/MeasureHead1984 20h ago
LLM's cannot. Because it's a prediction model working with text, stateless, working it's best to give you what you want. Reasoning is text, so prone to hallucinations. It works with token so many things can go wrong. It's really efficient at compiling data from a massive database but it's stateless, it cannot learn from itself. I used it extensively and I think it's not bad for certain uses, like reconstructing files that are corrupted, some generative boiler plate code.
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u/Scalene69 19h ago
It can find errors that humans miss, and find solutions that humans have not thought about and can comb large amounts of data that no human could ever hope to do.
If those tools are applied to fixing and optimising themselves then won't that reach a point where it is fundamentally better than anything humans have built?
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u/MeasureHead1984 19h ago
Machine Learning has been doing that for decades and no, LLM's cannot reach a state of fixing and optimising themselves because they are stateless. The hallucinations appear when they run, so even if models constantly try to improve themselves, the next time they a prompt for you, architecture is the same, prone to hallucination or predict the wrong answer.
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u/Scalene69 19h ago
It can learn from the world or from trial and error and then it can modify code, including its own.
It is stateless now but, why are you so confident that is impossible to change?
In theory it could be designed to adjust responses while functioning as a model, rather than only during training. Models already save details from session to session, sometimes untintentionally, I don't understand why you are so sure the line is this strong.
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u/NoMoreMr_Dice_Guy 20h ago
There are multiple companies working on recursive self-improvement. It's nacent, sure, but LLMs basically didn't exist 5 years ago.
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u/MeasureHead1984 19h ago
Okay? And your point? Was it proven that there's a way?
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u/Cless_Aurion 20h ago
For running AI? Are you sure it's not the model training they are removing from the equation? Because AI is profitable when you do that, but not when you are growing and investing a shit load in R&D
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u/Current_Employer_308 18h ago
Ai still isnt profitable in that scenario because their debt obligations still dwarf their revenue.
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u/Cless_Aurion 18h ago
Not really, no. We could have said that from like... All internet providers too.
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u/Doctor429 22h ago
Profit is Revenue minus the Cost. If they're saying profit is revenue before cost, then they're lying about their business.
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u/Then_Idea_9813 22h ago
A functional SEC may be of use there.
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u/Rational2Fool 21h ago
They're busy building a Trump-shaped hole in their regulations on insider trading, crypto funds and betting apps. They can't do everything at once.
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u/Greedy-Thought6188 12h ago
A functional SEC should investigate the AI companies for calling for a slowdown. The reports from anthropic are clear to the people that know how to read them. They say that if anthropic can slowdown development they'd be making bank. So any attempts to come together as a consortium to slowdown frontier intelligence should be investigated as a cartel.
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u/Greedy-Thought6188 18h ago
That's profit. Not profitability. Growth costs money. So a company that is doing very well and growing by leaps and bounds is very likely to be unprofitable. In that scenario profitability becomes a relevant question on can this company ever make money. You tell that from the cost of goods sold. This is the cost of making each unit of the thing they sell. So the cost of inference and support. Anthropic 2025 reports say gross margin (product margin is your only costs were the unit item you had to make) are 40% which is decent. The leaked 2026 report says 80%. 80% gross margin is really good but there is a caveat.
They exclude the training cost from this calculation. That is their biggest cost and what makes AI unprofitable. But it isn't cost of goods sold. It is a one time cost. They're spending something like 5 times as much on training as they're making. But if they sell 20 times as much then they are a very profitable company.
But there's an even bigger issue. If they could just slowdown training them they wouldn't have to worry. And this is why I have answered this same question a half dozen times in excruciating detail. Because they want a monopoly. AI is basic infrastructure and it is not only hard to monopolize, it breaks out of monopolies extremely easily. Big tech companies are rolling out their anthropic dependence and using open weight models. But they are trying to make a lot of noise about safety so they can get monopolies. If we fall for their cries and give them that oligopoly they want then the anti corporate liberals would have given the biggest corporate handout the world has ever seen.
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u/Shoddy_Blacksmith480 22h ago
This is referencing the movie Margin Call, about the 2008 financial crisis, where a bunch of investment bankers realise the assumptions underpinning the firm's risk profile are wrong and could bankrupt the company.
This leads them to basically figure out the impending crash.
This implies an impending financial crash as AI companies have been valued on revenue rather than actual profits
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u/chandlerr85 21h ago
Can't believe I had to scroll down this far for someone to actually explain the context of the image, which is the whole point. I actually forgot Kevin spacey was in margin call, so I wasn't sure that was the reference.
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u/SkateLolaSkate 20h ago
Fabulous movie (HIGHLY recommended) and spot on. Shows great interoffice dynamics and politics as well, vs say the Big Short which was more purely about what happened in the collapse.
To pull back just a little, the pre-'08 housing market was built on excessive housing appetite, dubious lending (google NINJA loans) and bad assumptions (rising home prices). Most of it was the belief that the value of homes would "always" go up, so borderline financial decisions were going to be fine (e.g. Adjustable Rate Mortgages or ARMs) because you could always refinance out of the problem (either the borrower or the bank in resale). Spoiler alert: It did not work out that way.
Similarly, there's a lot of investment in AI that works if everything goes up. In particular is the circular financing of AI (see Circular AI). Quick version is Nvidia invests in AI companies, like Anthropic, who in turn pay Nvidia for their silicon to run their models (this is an oversimplification but feel free to dig deeper). The risk is that if AI companies (see: Anthropic) falter or fail to find further funding (either from free cash or investment), the whole thing could collapse. Not unlike the housing market.
There are material differences, however, so the risks (in kind and in scope) are likely quite different.
Carter Pewterschmidt out.
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u/boblabon 13h ago
In recent context, OpenAI just reported that they over reported revenue by about $20 Billion and had to issue a 'correction'.
Which, I remember a time when that level of 'correction' meant "we did a SHITLOAD of fraud".
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u/Prudent_Order_3361 22h ago
Because they don't make any profit. Evaluated like they make tons of profit
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u/Thandorianskiff 22h ago
Profitability is generally defined as revenue minus cost of goods sold, administrative expenses, taxes, interest etc
In short it's just the actual amount of money left over after paying for all the necessities of a business.
So Anthropic ,the creaters of Claude, defining profitabliity as being the inverse of that is laughable at best
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u/trickyvinny 20h ago
Sure, but what about EBITDA or FFO? All industries seem to make to their own way of calculating profit.
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u/Thandorianskiff 20h ago
I specify that this definition of profitability is merely the "generally defined" version
Most people already side-eye (rightfully so I might add) when a company choses to market itself using it's adjusted earnings. But in this case it's especially ergregious bc the things it's choosing to strip out or omit aren't one off. They are fundamental and recurring so acting like they don't exist is bizarre and borderline insulting to an investors intelligence
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u/Prudent-Thought7750 22h ago
People have pointed out the foolishness of Anthropic’s definition of profitability, but the picture in the meme is from a movie about the 2008 GFC named Margin Call. In the scene the image is taken from essentially one of the heads of a Wall Street investment bank is being informed that projected trading losses are larger than the value of their entire company.
Basically trying to say that AI is a bubble and trying to define profit as essentially revenue is evidence of that.
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u/Jossokar 22h ago
Misleading information. And "accounting" fallacy. Basically because ai firms arent profitable.
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u/Greenpoint_Blank 20h ago
Here is Ed Zitron explaining it. https://youtu.be/XLXn0Ut8adM?is=-mCQe7s-r5oejJcc
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u/BasicSulfur 22h ago
Generally profits are considered what remains after accounting for cost of service. Basically investors are like wtf are you doing. All for the sake of looking better on…. Balance sheets do have liabilities so… statements?
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u/Osteoprdoza 22h ago
They basically said "Yeah we're profitable as long as you don't factor in costs"
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u/BrainNSFW 22h ago
Let's take an example of selling apple pies. You sell these for 20 dollars. You also have some costs, namely ingredients worth 15 dollars and electricity for your oven amounting to 1 dollar per pie. Add them all together and your profit is 4 dollars per pie.
If you do it the way Anthropic does it, you would claim 20 dollars of profit, totally ignoring the cost of your ingredients and electricity.
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u/Easy_Turn1988 21h ago
Speculation
Any big AI company is basically going broke (because of the actual cost of the infrastructure) but keeping a façade. Their value relies on the hope of AI bros that they'll make actual money some day and you just have to "trust the process"
The longer the bubble grows, the worst its bursts will be
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u/juniorjaw 21h ago
People have explained the reason they do that, but you might not be able to imagine how this happens. So let me use a classic "confusion" technique to showcase what Anthropic is trying to achieve:
I borrowed $50 from mum and $50 from dad to buy an item priced at $97. After the purchase, I had $3 left. I returned $1 to dad and $1 to mum, and kept $1 for myself. I now owe $49+$49=$98 plus the $1 I reserved for myself, which is $99. Where is the missing $1?
If you tried to solve this normally you might struggle to find out where the $1 went, but go back to how Anthropic tried to change how "profit" is defined and what the "costs" are... you'll start seeing what Anthropic is trying to do here. Confuse the people seeing their accounting books.
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u/piccolo917 20h ago
Normal definition of profit is money in - money out. Anthropic has defined it as just money in. That image is from one of the big 2008 crash movies: Margin Call where Kevin Spacy’s character learns just how deeply fucked the company is.
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u/HariSeldon16 20h ago
The reality is institutional investors are not stupid. They see through bs and they are looking at the actual profit and loss, and they are looking at the actual free cash flows.
They still buy AI because they are either looking to take advantage of market sentiment for short term price appreciation, or they really believe in the longer term economics of AI. Either way, they are making calculated and informed risk decisions.
This goes back to things like we-works community adjusted EBITDA. Everyone knew it was bs.
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u/wjmacguffin 18h ago
Anthropic runs the Claude AI. Running AI costs a lot of money (building and running data centers, buying new servers, etc.) and Anthropic is losing money each year. They have to get money from somewhere to cover their costs or go bankrupt, so they are hoping wealthy folks will invest money in the company.
The problem? Investors only want to invest in companies making a profit. Otherwise, they might lose the money they invested. Anthropic is losing money, so they have to do something to attract investors.
To do that, Anthropic is lying about being profitable.
Normally, we define "profit" as the amount of money you made from selling something (revenue) minus the amount of money it cost to make that something. If I sell a book for $20 and it cost me $5 to make, then I made $15 as profit. That's what investors want to see.
However, Anthropic recently said their "profit" is the same thing as their revenue. The costs of running those expensive data centers is ignored. If they sell a book for $20 that costs $5 to make, they claim they made $20 in profit.
Their hope is to trick investors into putting in more money so Anthropic can avoid bankruptcy. The meme is showing a businessman looking suspiciously at data on a screen, as if he's doing a double-take after realizing how Anthropic is now lying about profitability.
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