41–50 of 425 posts
They know it is a scam, but it doesn’t matter as it is now too late. That ship has sailed long ago into the IPO sunset.
That’s absurd. Why couldn’t it still fail, especially when their last raise was at 20x revenue or more? These numbers are horrendous.
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The vast, vast amounts of money they spent on driver incentives city by city would seem to support the OPs claim (source: I was familiar with their spend on ads in the US approximately 10 years ago).
There is no evidence that Uber was systemically losing money per ride instead of at edge cases. Share your evidence please.
This is an impossible ask unless one works at Uber. I can tell you that i saw how much they were spending on ads back in 2016, and how long it continued and can assure you that they were 100% losing money back then.
Like, even now their margin is around 10% (they made 5bn on 50bn of revenue). Other software companies make a much, much, much better margin because Uber is basically not a real software business, it's an app attached to a low-margin delivery business.
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> The reality is that it's not his predictions that matter, but his data, which is almost always correct as of time of writing. If you ignore his opinions, the data presented on liabilities, spend, revenue, loans, commitments, etc across Coreweave, Stargate, Oracle and all of the usual AI companies is, as far as I can tell, correct. Yeah, I think that he does well with sources and data. I also think that his editoria…
> Yeah, I think that he does well with sources and data He's not even good at that, here's him not understanding what ARR means and fumbling a simple calculation and refusing to fix it. https://x.com/binarybits/status/2031392856401666362 Not only not understanding ARR, he simply doesn't do data analysis properly - he misses some few months and days in his calculation to prop up his point. This is a mistake chatgpt wo…
Can you share me the official meaning of ARR? Preferably on a GAAP basis. Should be no problem, right?
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Oh! What’s his reputation?
> Oh! What’s his reputation? The people who are completely sold on the belief that AI providers are running at a profit believe him to be utterly, totally and completely wrong in every one of his predictions. The people who are completely sold on the belief that AI providers are running at a loss they can never recover from believe him to be utterly, totally and completely correct in every one of his predictions. The…
I think the question is more about whether people believe this is a sound business in the long term, which imo isn't possible to tell based on these numbers yet.
So everything else is kind of academic. Of course they were losing money in 2025, they had a technology that was kind of cool - clearly eventually going to deliver something great, but they didn't actually have anything somebody should pay for. Now they have a thing that people will pay for. So who cares what they lost in 2025?
So what's important today is - how competitive are they with Anthropic in delivering that product. How do the economics of companies using AI agents for coding work. That's all. I don't think there's really an argument about them losing money on inference any more.
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> The reality is that it's not his predictions that matter, but his data, which is almost always correct as of time of writing. If you ignore his opinions, the data presented on liabilities, spend, revenue, loans, commitments, etc across Coreweave, Stargate, Oracle and all of the usual AI companies is, as far as I can tell, correct. Yeah, I think that he does well with sources and data. I also think that his editoria…
> Yeah, I think that he does well with sources and data He's not even good at that, here's him not understanding what ARR means and fumbling a simple calculation and refusing to fix it. https://x.com/binarybits/status/2031392856401666362 Not only not understanding ARR, he simply doesn't do data analysis properly - he misses some few months and days in his calculation to prop up his point. This is a mistake chatgpt wo…
Do you have a link to his blog where he gets the ARR wrong?
True, I haven't much of his posts, but the one or two I recall reading with ARR in it didn't seem to have fumbled the calculations.
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> Yeah, I think that he does well with sources and data He's not even good at that, here's him not understanding what ARR means and fumbling a simple calculation and refusing to fix it. https://x.com/binarybits/status/2031392856401666362 Not only not understanding ARR, he simply doesn't do data analysis properly - he misses some few months and days in his calculation to prop up his point. This is a mistake chatgpt wo…
> understanding what ARR means Can you share me the official meaning of ARR? Preferably on a GAAP basis. Should be no problem, right?
This is something Ed clearly doesn't understand https://x.com/edzitron/status/2031124650474852382
And you haven't addressed the fact that he doesn't do simple data calculations - see his blog https://www.wheresyoured.at/the-beginning-of-history
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> Doesn't seem like a domesday scenario Ceteris paribus , those figures imply a $45bn loss this year, $90bn loss next year and $110bn loss in 2028 before breakeven in 2029. That's $250bn of losses to be financed from 2026 onwards. (They raised ~$120bn, $25bn up front and the rest based on milestones. So Another ~$125bn uncovered.) That only works if OpenAI stays a fundraising darling. So not a doomsday sceanario. But…
You're adding absolute dollars rather than using percentages - that usually isn't how that works.
Of course you don’t use percentages when the magnitude of the numbers are so high.
I'm a little confused here. Cost of revenue is lower than revenue. That's good. R&D is the main contributor to losses here and this seems normal in an industry like this. For OpenAI specifically, I think this is problematic. They were the first movers but despite the large R&D they've lost so much ground to Anthropic despite Anthropic seemingly gifting them with weird PR self owns. But if we were to extrapolate this…
The Uber comparison makes no sense. This is the opposite situation. Uber lost money on rides, OpenAI is (possibly) making money on inference. Uber used an R+D moonshot to autonomous driving to justify capturing an established industry without reducing costs meaningfully. OpenAI has a core product that risks becoming a commodity with open source models only 6 months behind.
I'm a little confused here. Cost of revenue is lower than revenue. That's good. R&D is the main contributor to losses here and this seems normal in an industry like this. For OpenAI specifically, I think this is problematic. They were the first movers but despite the large R&D they've lost so much ground to Anthropic despite Anthropic seemingly gifting them with weird PR self owns. But if we were to extrapolate this…
HSBC say they need to turn a 13b revenue to 200b by 2030 AND also find another 204b, in order to become profitable.