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Ed... I wrote him a long note about how wrong his analysis on oAI was earlier this year. He wrote back and said "LOL, too long." I was like "Sir, have you read
by vessenes 1y ago
Ed... I wrote him a long note about how wrong his analysis on oAI was earlier this year. He wrote back and said "LOL, too long." I was like "Sir, have you read your posts? Here's a short version of why you're wrong." (In brief, if you depreciate models over even say 12 months they are already profitable. Given they still offer 3.5, three years is probably a more fair depreciation schedule. On those terms, they're super profitable)
No answer.
- boringg 1y agoI mean they are clearly trying to get some attention here. I wouldn't bite. OpenAI is many things but I don't think I would call it boring or desperate. The title seems more desperate to me.
- vessenes 1y agoThe lad doth continue to protest as valuations reach $1T. I wonder if he passed on some early stock and just can't get over it
- deleted 1y ago[deleted]
- triceratops 1y ago> He wrote back and said "LOL, too long." Some nerve
- gorjusborg 1y agoSeriously. It took more time to respond with disrespect than to just ignore it.
- triceratops 1y agoI meant more the nerve to say it was "too long". Ed Zitron may be right but he's got no right to accuse anyone else of writing too many words.
- sharkjacobs 1y agoIt's a rude response from someone whose public persona is famously rude and abrasive. It's also worth considering the difference between publishing 10000 words to an audience of subscribers, and sending 10000 words unsolicited to a stranger.
- azemetre 1y agoThere’s no proof that this exchange ever happened. Happy to eat crow if proven wrong. I’ve disagreed and argued with Ed on his subreddit, he never banned me or acted hostile.
- atonse 1y agoEspecially rude given, if he was feeling it was too long, he could've had an AI summarize it. But this shows a certain intellectual laziness/dishonesty and immaturity in the response. Someone's taken the time to write a response to your article, you can choose to learn from it (assuming it's not an angry rant), or you could just ignore it. In fact, that completely dismisses this stupid article for me.
- watwut 1y agoI mean, using ai to summarise someone's arguments and then using ir in any way would be considerably more dishonest, lazy and rude. Like, expectation that he will treat an unsolicited email with all seriousness is absurd in the first place, but ai summarize it would be wtf.
- atonse 1y agoNot responding was a perfectly good neutral action. Instead they chose to respond with a "LOL" and saying it was too long, like they're a pretty unintellectual person. Let's agree to disagree.
- giorgioz 1y agoWhy 3.5 or 3 years for depreciations? Models have been retrained much faster than that. I would guess more in the 3 months range.
- t-writescode 1y agoBecause businesses and people rely on consistentish responses, which you can get on models you’ve already validated your prompts on. Dropping old models means breaking paying customers, which is bad for business.
- bayarearefugee 1y agoIf you spend more money training the model and offering it as a service (with all the costs that that entails) than you earn back directly from that model's usage, it can only be profitable if you use voodoo economics to fudge it. Luckily we live in a time period where voodoo economics is the norm, though eventually it will all come crashing down.
- vpShane 1y ago[dead]
- true_religion 1y agoThat’s true, but OpenAI and its proponents say each model is individually profitable so if R&D ever stops then the company as a whole will be profitable.
- nickff 1y agoThe problem with this argument is that if R&D ever stops, OpenAI will not be differentiated (because everyone else will be able to catch up), so their pricing power will disappear, and they won't be able to charge much more than the inference costs.
- vessenes 1y agoYou’re right, but that’s not what’s happening. Every major model trained at Anthropic and oAI have been profitable. Inference margins are on the order of 80%.
- deleted 1y ago[deleted]
- oblio 1y ago> Inference margins are on the order of 80%. Source, please?
- bdangubic 1y agowhat exactly does “come crashing down” mean? a service with 700 million users will cease to exist? close shop, oooops our bad? same “come crashing down” arguments permiated HN on Uber and Meta monetizing mobile and … nothing is crashing down at this type of “volume”/user base…
- mrandish 1y ago> I wrote him a long note about how wrong his analysis on oAI was earlier this year. Why don't you consider posting it on HN either as a response in this thread or as it's own post. There's clearly interest in teasing out how much of OAI's unprecedented valuation is hype and/or justified.
- singron 1y agoThe depreciation schedule doesn't affect long term profitability. It just shifts the profits/loss in time. It's a tool to make it appear like you paid for something while it's generating revenue. Any company would look really profitable for a while if it chose long enough depreciation schedules (e.g. 1000 years), but that's just deferring losses until later.
- vessenes 1y agoNo it would in fact be appropriate to match the costs of the model training (incurred over a few months) with the lifetime of its revenue. That’s not some weird shifting - it helps you understand where the business is at. In this case on a per model basis, very profitable.
- godelski 1y ago> it would in fact be appropriate to match the costs of the model training with the lifetime of its revenue You're right. But this also doesn't mean singron is wrong. Think about their example. If the deprication is long lived then you are still paying those costs. You can't just ignore them. The problem with your original comment is that it is too simple of a model. You also read singron's comment as a competing model instead of "your model needs to account for X". You're right that it provides clues that the business might be more profitable in the future than current naïve analysis would suggest but you also need to be careful in how you generalize your additional information
- vessenes 1y agoI think we are, like you suggest, just talking past each other. Depreciation is supposed to conceptually be tied to the useful life of an asset; a 1000 year depreciation schedule might be reasonable for say a Roman bridge. When we talk accrual basis profits we are trying as best we can to match the revenues and expenses even if they occur at different points in the useful life of the asset. Almost zero kibitzers or journalists take this accrual mindset into account when they use the word profit - but that’s what profit is, excess revenue applied against a certain period’s fairly allocated expense. What they generally mean is cashflow; oAI has negative cashflow and is likely to for quite a while. No argument there. I think it’s worth disambiguating these for people though because career and investment decisions in our industry depend on understanding the business mechanics as well as the financial ones. Right now financially simplistic hot takes seem to get a lot of upvotes. I worry this is harming younger engineers and founders.
- atonse 1y agoI agree with you. Even Anthropic's CEO said EXACTLY this. He said, if you actually look at the lifecycle of each model as its own business, then they are all very profitable. It's just that while we're making money from Model A, we've started spending 10x on Model B.
- pmdr 1y agoWell have they actually come up with data supporting this?
- vessenes 1y agoYes and it’s furnished to some of the worlds best investors who are happy to pay valuations between 150 and 500b to access it
- louiereederson 1y agothe logic of a happy WeWork investor
- surgical_fire 1y agoAmong those are the guys that gave money to WeWork. Make of that what you will. I am not really betting on it.
- pmdr 1y agoYeah, no investor has ever been conned before /s I do hope Ed's wrong, I actually stand to financially benefit from it.
- jrflowers 1y agoI don’t quite understand your wording here. Do we have to “pay valuations between 150 and 500b” to access the data that supports the justification of the valuation or can you just link to it?
- jfengel 1y agoExponential cost growth with, at best, linear improvement is not a promising business projection. Perhaps at some point we'll say "this model is profitable and we're just gonna stick with that".
- treadump 1y agoOpenAI expects multi-year losses before turning consistently profitable, so saying they are already profitable based solely on an aggressive depreciation assumption overstates the case
- EvgeniyZh 1y ago> Given they still offer 3.5, three years is probably a more fair depreciation schedule. But the usage should drop considerably as soon as next model is released. Many startups down the line are existing in hope of better model. Many others can switch to a better/cheaper model quite easily. I'd be very surprised if the usage of 3.5 is anywhere near what it was before release of the next generation, even given all the growth. New users just use the new models
- vessenes 1y agoProbably true! If revs shift to a new cheaper model that’s not bad though.
- AbstractH24 1y agoI probably agree!
- BoorishBears 1y agoYour brief doesn't make sense, maybe you need to expand? They're only offering 3.5 for legacy reasons: pre-Deepseek, 3.5 did legitimately have some things that open source hadn't caught up on (like world knowledge, even as an old model), but that's done. Now the wins come from relatively cheap post-training, and a random Chinese food delivery companies can spit out 500B parameter LLMs that beats what OpenAI released a year ago for free with an MIT license. Also as you release models you're enabling both distillation of your own models, and more efficent creation of new models (as the capabilities of the LLM themselves are increasingly useful for building, data labeling, etc.) I think the title is inflammatory, but the reality is if AGI is really around the corner, none of OpenAI's actions are consistent with that. Utilizing compute that should be catapulting you towards the imminent AGI to run AI TikTok and extract $20 from people doesn't add up. They're on a treadmill with more competent competitors than anyone probably expected grabbing at their ankles, and I don't think any model that relies on them pausing to cash in on their progress actually works out.
- vessenes 1y ago> expand brief please OK! Longcat-flash-thinking is not super popular right now; it doesn't appear on the top 20 at open router. I haven't used it, but the market seems to like it a lot less than grok, anthropic or even oAI's open model, oss-20b. Like I said I haven't tried it. And to your point, once models are released open, they will be used in DPO post-training / fine-tuning scenarios, guaranteed, so it's hard to tell who's ahead by looking at an older open model vs a newer one. Where are the wins coming from? It seems to me like there's a race to get efficient good-enough stuff in traditional form factors out the door; emphasis on efficiency. For the big companies it's likely maxing inference margins and speeding up response. For last year's Chinese companies it was dealing with being compute poor - similar drivers though. If you look at DeepSeek's released stuff, there were some architectural innovations, thinking mode, and a lottt of engineering improvements, all of which moved the needle. On treadmills: I posit the oAI team is one of the top 4 AI teams in the world, and it has the best fundraiser and lowest cost of capital. My oAI bull story is this: if capital dries up, it will dry up everywhere, or at the least it will dry up last for a great fundraiser. In that world, pausing might make sense, and if so, they will be able to increase their cash from operations faster than any other company. While a productive research race is on, I agree they shouldn't pause. So far they haven't had to make any truly hard decisions though -- each successive model has been profitable and Sam has been successful scaling up their training budget geometrically -- at some point the questions about operating cashflow being deployed back to R&D and at what pace are going to be challenging. But that day is not right now.
- surgical_fire 1y agoThe problem of this "depreciation" rationale is that it presumes that all the cost is in training, ignoring that actually serving the models is also very expensive. I certainly don't believe they would be profitable, and vague gestures at some hypothetical depreciation sounds like accounting shenanigans. Also, the whole LLM industry is mostly trying to generate hype, at a possible future where it is vastly more capable than it currently is. It's unclear if they would still be generating as much revenue without this promise.
- llbbdd 1y agoThat's disappointing to hear. I've generally liked Ed's writing but all his posts on AI / OAI specifically feel like they come from a place of seething animosity more than an interest in being critical or objective. At least one of his posts repeated the claim that essentially all AI breakthroughs in the last few years are completely useless, which is just trainwreck hyperbole no matter where you lie on the spectrum as far as its utility or potential. I regularly use it for things now that feel like genuine magic, in wonder to the point of annoying my non-technical spouse, for whom it's just all stuff computers can do. I don't know if OpenAI is going to be a gazillion dollar business in ten years but they've certainly locked in enough customers - who are getting value out of it - to sustain for a while.
- fragmede 1y agoThat's not remotely surprising though if you've known anyone like how Ed presents himself through his writing and videos. I don't know him personally, so I can't speak to what he's actually like, but there's something about his writing style and how he comes off in his videos as a conviction that he's right and his got the secret truth and why won't everybody believe him. Cassandra's curse, perhaps, but naming it doesn't convince me.
- dom96 1y agoCan you share your note to him and where he responded that way? Is it public?
- nzeid 1y agoThis perspective ignores headwinds from copyright infringement lawsuits and increasingly popular LLM scraping protections.