Now let's think for a second about why you would ever want to report it that way. There is not one good reason other than hiding your actual measly revenue.
Fraud is problematic because it results in harm. Betting in the way Anthropic/OpenAI/Nvidia are is legal, and still incredibly likely to cause harm. So sure, you're technically correct, but the resulting harm that we will all suffer when it all comes crashing down won't be any easier because it was legal...
No one has rebutted Ed's points. The only rebuttal is "but look how cool AI is!". He mainly sticks to objective facts about their financial situation, and an honest analysis of that situation is dire, regardless of what you think of AI.
So? Tell me his data is wrong, and then I'll care. His primary "prediction" is that it's a bubble and will crash. And he has lots of empirical facts regarding Anthropic, OpenAI, and all the related companies' actual financial situation. Him being wrong on different predictions does not change the fact that Anthropic and OpenAI are in massive debt and do not have the revenue to handle it, and that a huge percentage of the stock market is being propped up by AI. As he himself says, I really hope nothing bad happens, but the financials are to dire to ignore.
>For example, when Timothy B. Lee looked at a spreadsheet that Zitron used to create a projection of Anthropic's revenue, he found
>He doesn't count February 1-10, counts March 1-10 twice, counts August 21-October 21 as one month instead of two, and doesn't count October 21-November 1. [another commenter notes that his spreadsheet also contains February 30] ... Ed claims he tried to compute Anthropic's revenue for 2025 and came up with $3.6 billion, suggesting some funny business [but the numbers work out once you fix the errors]
from the above link. Personally I agree it's a bubble and there will likely be some sort of crash. But Ed is way to pessimistic on the underlying technology.
And bubbles and crashes are kind of inevitable with any hot new tech given human nature trying to pile in and get rich quick. It's a bit like prediting it'll rain one day.
His "facts" are not facts, he makes stuff up, miss-states things constantly, and is financially illiterate. Whenever I read anything he writes I'm constantly face-palming because it's basically all rubbish.
He's anti-tech, anti-AI, incredibly biased, and just honestly full of bile.
And yes, I'm saying his data is wrong, his interpretation of the data is wrong, and his conclusions are wrong.
I don't understand giving the benefit of the doubt to a company that is actively spying on its customers, which in some jurisdictions would be illegal.
All these companies make their money as 'feeders' to the advertising industry, they just sell a different device to consumers in order to achieve it.
Selling devices to consumers is a solved problem. The problem we're currently trying optimise solutions for is selling consumers to the advertising companies.
Maybe they literally just don't care about how much traffic they put on your network. Maybe the thought is "1 tb of traffic internally is very low utilization of the network over the course of a month".
Whatever they're trying to accomplish with these scans would probably be impeded in some way by this much volume. Like it'd compete with the link it's using to phone home or overload whatever on-device processing it does with that data. The man in the article who discovered this called it a bug, I agree with him.
I'm not saying there's no malice, it's just that maliciously spamming the network would get in the way of the malicious spying they actually want to do.
When the cost of the action to you is 0, why not do it as fast and as frequently as possible until you get your intended benefit.
Even the act of engineering rate limiting costs you more than just having this run wild over your customers networks because the vast majority of people buying these machines do not have the inclination or skills to detect this activity.
Do you know who is not surprised by this? Ed Zitron, and anyone who has read his articles or anyone who have looked into these companies at any level deeper than "AI do cool things! AI must be good investment! AI must make much money!"
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