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The Hater's Guide to the AI Bubble
- camillomiller 1y agoThanks, Ed Zitron. This article is to me like a glass of ice water to somebody in hell.
- bibelo 1y agoThe irony is that I asked ChatGPT to make a summary in french. However, i'm tired of the AI bubble and seeing half of my twitter feed filled w AI announcements and threads
- CharlesXY 1y agoReddit and LinkedIn especially has become a cesspool of generated content, thankfully its pretty easy to spot and block
- UltraLutra 1y agoIt’s not bad for summarizing or translating. I like categorize AI outputs by prompt + context input information size vs output information size. Summaries: output < input. It’s pretty good at this for most low-to-medium stakes tasks. Translate: output ≈ input but in different format/language. It’s decent at this, but requires more checking. Generative expansion: output > input. This is where the danger is. Like asking for a cheeseburger and it infers a sesame seed bun because that matches its model of a cheeseburger. Generally that’s fine. Unless you’re deathly allergic to sesame seeds. Then it’s a big problem. So you have to be careful in these cases. And, at best, the anything inferred beyond the input is average by definition. Hence AI slop.
- CharlesXY 1y agoThis is quite refreshing to read, while I would classify myself more in the group of “optimists”, I do believe there is a severe lack of skepticism, and those that share negative or more conservative views are indeed held to different standard to those who paint themselves as "optimists". Unlike other trends before, the wave of grifters in the AI space is atounding, anything can be “AI-powered” as long as its a wrapper/ chatbot
- usrnm 1y agoAre we in a bubble that's going to pop and take a large part of the economy with it? Almost certainly. Does it mean that the AI is a scam? Not really. After all, the Internet did not disappear after the dotcom burst, and, actually, almost everything we were promised by the dotcoms became reality at some point.
- Palomides 1y ago"doing everything on the internet" definitely worked out, but I don't see why that implies "GPU accelerated LLMs will replace large swathes of human labor" will also be true
- usrnm 1y agoThat's not what I'm saying. What dotcoms prove is that some technology can be a bubble and a real technological revolution at the same time, there is no contradiction here. "AI is a bubble and I probably shouldn't invest all my savings in NVDA" is a valid point, "AI is a bubble and therefore stupid and will never work" is not
- cmrdporcupine 1y agoIf there's anything that can be reliably predicated to be true over multiple decades it's that capitalism will continually seek to reduce labour costs and automate everything. You can bet that even if the specific forms attempted in this interval don't take hold, they will eventually. You and I are too expensive, and have had too much power.
- andsoitis 1y ago> If there's anything that can be reliably predicated to be true over multiple decades it's that capitalism will continually seek to reduce labour costs and automate everything. what about improved life quality? what about an explosion of types of jobs? > You and I are too expensive, and have had too much power. do you think the average citizen (or the collective) have MORE power or LESS power than 100 years ago, than 200 years ago?
- jakobnissen 1y agoI think the author's take is overly bleak. Yes, he supports his claim that AI businesses are currently money pits and unsustainable. But I don't think it's reasonable to claim that AI can't be profitable. This whole thing is moving so extremely fast. Models are getting better by the month. Cost is rapidly coming down. We broadly speaking still don't know how to apply AI. I think it's hubris to claim that, in the wake of this whole bubble noone will figure out how to use AI to provide value and noone will be profitable.
- BoredPositron 1y agoWe are pretty much plateauing in base model performance since gpt4. It's mostly tooling and integration now. The target is also AGI so no matter your product you will get measured on your progress towards it. With new "sota" models popping up left and right you also have no good way of user retention because the user is mostly interested in the models performance not the funny meme generator you added. looking at you openai... "They called me bubble boy..." - some dude at Deutsche.
- GaggiX 1y ago>We are pretty much plateauing in base model performance since gpt4. Reasoning models didn't even exist at the time, LLMs were struggling a lot with math at the time, now it's completely different with SOTA models, there have been massive improvements since gpt4.
- impossiblefork 1y agoSo, how do you feel about the recent IMO stuff? Don't they cause a consistency problem for your view that we've plateaued-- to me at least, I felt we were something like two years away from this kind of thing. Probably very expensive to run of course, probably ridiculously so, but they were able to solve really difficult maths problems.
- narrator 1y agoThe biological brain of the top human IMO guy runs on 20 watts. I wonder how much electricity Google used to match that performance.
- thoroughburro 1y agoThe bubble will pop, just like the web bubble popped; and that’s going to suck. AI technologies will remain and be genuinely transformative, just like the web remained and was transformative (for good and ill).
- troupo 1y agoIt's a source of constant amusement to me that "arguments" used for AI are indistinguishable from "arguments" used for crypto. (With a caveat that LLMs actually do have their uses)
- tim333 1y agoI think they are somewhat distinguishable. Going by the HN consensus most people thought cryptocurrency was not much use beyond crime and gambling. On the other hand I think most people see that if AI achieves human level thinking it'll be able to do human like jobs which would be a big deal economically.
- troupo 1y agoThat's a huge if that you can only accept if you buy into "AGI has been achieved internally" marketing.
- tim333 1y agoI'm thinking more that AGI will happen within a few years. It's one of the reasons for the present financial weirdness. Throwing so much money into current AI would make no sense if it stays as it is. It only makes sense if you think the tech will improve.
- troupo 1y agoYou say that arguments for AI and crypto are somewhat distinguishable while presenting arguments indistinguishable from crypto. Billions of dollars were spent on crypto as well.
- louwrentius 1y agoAI is a temporary buoy for FAANG and the tech industry to keep the financial markets happy while they switch to their next source of growth: Military contracts. I hope people understand the irony, but to spell it out: they need to live on government money to sustain growth. Corporate welfare while 60% of the USA population doesn't have the money to cover a 1000$ emergency.
- andsoitis 1y ago> Military contracts. They need to live on government money to sustain growth. Meta makes 99% of its revenue from advertising (according to the article). Google, similarly, makes most of its money from advertising. Tesla makes money by selling cars (there's no indication the government is going to transform their fleets to Tesla vehicles; in fact, they're openly hostile to EVs). Apply needs to rely on US government military contracts for continued growth? What? Amazon, the company that sells toothpaste and cloud services needs to rely on US government military contracts? Consider me not convinced by the story you tell.
- louwrentius 1y agohttps://nymag.com/intelligencer/article/mark-zuckerbergs-meta-is-pivoting-to-defense-contracting.html https://nymag.com/intelligencer/article/mark-zuckerbergs-met...
- bgwalter 1y agoMicrosoft's $22 billion (wasted) IVAS was a fiasco, now they are doubling down: https://breakingdefense.com/2025/01/army-kickstarts-possible-recompete-of-microsofts-22-billion-ivas-production-deal/ https://breakingdefense.com/2025/01/army-kickstarts-possible... Of course it won't work. These tech companies have no clue about the real world and humans.
- bgwalter 1y agoOP is speaking about the next source of growth, not existing revenue streams.
- bgwalter 1y agoSoftBank is also more cautious and the "$500 billion" Stargate project that was hyped in the White House will just build a single data center by the end of 2025: https://www.wsj.com/tech/ai/softbank-openai-a3dc57b4 https://www.wsj.com/tech/ai/softbank-openai-a3dc57b4
- andrewstuart 1y agoThese sound very much in tone like the criticisms of Web 1.0 AI/LLMs are an infant technology, it’s at the beginning. It took many many years until people figured out how to use the internet for more than just copying corporate brochures into HTML. I put it to you that the truly valuable applications of AI/LLMs are yet to be invented and will be truly surprising when they come (which they must of course otherwise we’d invent them now). Amdahl says we tend to overestimate the value of a new technology in the short term and underestimate it in the long term. We’re in the overestimate phase right now. So I’d say ignore the noise about AI/LLMs now - the deep innovations are coming.
- andrewstuart 1y agoActually Amara, not Amdahl I think.
- miltonlost 1y agoAI is not infant. LLMs? yes. But not AI as a whole. Conflating the two is part of the problem when deciding what is useful and profitable.
- andrewstuart 1y agoAI is to LLM what The Internet is to the World Wide Web
- FranzFerdiNaN 1y ago> It took many many years until people figured out how to use the internet for more than just copying corporate brochures into HTML. It was immediately clear for many people how it could be used to express themselves. It took a lot of years to figure out how to kill most of those parts and turn the remainder into a corporate hellscape thats barely more than corporate brochures.
- adverbly 1y ago.
- jcgrillo 1y ago> it's easily possible that these companies are integrating AI into existing lines of business to make them more profitable Has this effect been demonstrated by any company yet? AFAIK it has not, but I could be wrong. This seems like a rather large "what if"
- jjjggggggg 1y agoKeep up the good work, but this could be said with more strength and in far fewer words by removing the indulgent rambling.
- pestatije 1y agodamn he doesn't say when the shorts should start
- louwrentius 1y agoMarkets can stay irrational longer than you can stay solvent
- tim333 1y agoShorting markets is kind of a specialised skill. Judging from the dot com crash you want to wait till there's a substantial drop and people start talking about a crash, then it'll bounce back about half the way and that's when.
- frithsun 1y agoI believe this is a "good" bubble in the sense that the 19th century railroad bubble and original dot com bubble both ended up invested in infrastructure that created immense value. That said, all of these LLMs are interchangeable, there are no moats, and the profit will almost entirely be in the "last mile," in local subject matter experts applying this technology to their bespoke business processes.
- dinkblam 1y ago> "good" bubble in the sense how can massively buying hardware that will have to be thrown away in a few years be a "good" bubble in the sense of being a lasting infrastructure investment?
- entropi 1y agoI am pretty optimistic that as long as hardware capacity exists, people will find ways of using it. Whether it will be profitable or not is another story of course.
- kevindamm 1y agoRivers overflowing with legacy hardware and villages incinerating boards for their metals, and the caustic effects on people & their environment that causes, are already happening. The hardware capacity exists only as long as it is operational and within a few generations. Perhaps we should be careful before building Manhattan-sized data centers. Up to a point it is better than having additional compute sitting idle at the edge, economies of scale and all that, but after some point it becomes excess and wasteful, even if people figure out ways to entertain themselves with it. And if people don't want to pay what it costs to improve and maintain these city-sized electronic brains? Then it all becomes waste, or the majority transformed into office or warehouse space or something else. Proceeding with combined 1% (US GDP)-sized budgets despite this risk being an elephant in the room is what makes it a bubble.
- entropi 1y ago
- elktown 1y agoWhat's clear is that the hype has reach such a critical mass that people are comfortable enough to publicly and shamelessly extrapolate extraordinary claims based purely on gut feeling. Both here on HN and by complete laymen elsewhere. AI-optimist or not, that's just shocking to me.
- 29ebJCyy 1y agoI don’t doubt this but it might help to include some examples if you have any close at hand.
- elktown 1y agoFrom my perspective it's basically in every other comments section of AI related articles. Here's a particularly spicy one from today: https://news.ycombinator.com/item?id=44646797 https://news.ycombinator.com/item?id=44646797
- ddddang 1y ago[dead]
- falcor84 1y ago> people are comfortable enough to publicly and shamelessly extrapolate extraordinary claims based purely on gut feeling What's the problem with that? Why shouldn't people feel comfortable sharing their vision of the future, even if it's just a "gut feeling" vision? We're not going to run out of ink.
- elktown 1y agoI guess I expect higher standards than the kind of confident extrapolation you find in pseudo-science. And "vision of the future" is your euphemistic rewrite. If that's clearly stated I obviously have no problem with people's fanciful speculation. But these are claims in the format: "X will be replaced in a couple of years, how should we adapt as a society?" etc etc.
- xela79 1y agomake a technology very affordable, get people hooked. Then when LLM have basically destroyed the open web, charge more for accessing and searching that wealth of human created knowledge. Profit $$$ Ethical approach? hell no. What do you expect from an unregulated capitalistic system.
- zild3d 1y ago> What do you expect from an unregulated capitalistic system. Competition, fortunately
- xela79 1y ago> Competition, fortunately so there's no competition when there are no rules and regulations... ? interesting. all those sports without rules or regulations, like american football where anything goes.
- zild3d 1y agohuh? I'm saying adding rules and regulations reduces competition yes, by definition it adds barriers to entry. We can argue how high those barriers ought to be. Highly regulated industries: healthcare, banking, aviation Less regulated industries: web software, e-commerce, entertainment It is easier for startups to get started in the latter, harder in the former.
- billy99k 1y agoWith current LLMs, my productivity is increased by at least 50%. This will only get better over time as efficiency is gained and hardware gets cheaper.
- nerevarthelame 1y agoHow are you measuring your productivity? There are studies [0][1] that indicate it's common for people to self-assess that their productivity using LLMs increased by 20-40%, when in fact it decreased based on objective, controlled measures. [0] https://storage.googleapis.com/gweb-research2023-media/pubtools/7713.pdf https://storage.googleapis.com/gweb-research2023-media/pubto... [1] https://metr.org/blog/2025-07-10-early-2025-ai-experienced-os-dev-study/ https://metr.org/blog/2025-07-10-early-2025-ai-experienced-o...
- snapcaster 1y agowho you going to believe? random studies or your own lying eyes?
- urbandw311er 1y agoYou say “random studies” like you’re trying to discredit them in some way. But they’re not “random”, they’re controlled, documented, objective and published for you to go and read the results.
- snapcaster 1y agopersonal experience > some p-hacking academic
- urbandw311er 1y ago1 < 100
- wulfstan 1y agoIn July 2023, I wrote this to a friend: "...being entirely blunt, I am an AI skeptic. I think AI and LLM are somewhat interesting but a bit like self-driving cars 5 years ago - at the peak of a VC-driven hype cycle and heading for a spectacular deflation. My main interest in technology is making innovation useful to people and as it stands I just can't conceive of a use of this which is beneficial beyond a marginal improvement in content consumption. What it does best is produce plausible content, but everything it produces needs careful checking for errors, mistakes and 'hallucinations' by someone with some level of expertise in a subject. If a factory produced widgets with the same defect rate as ChatGPT has when producing content, it would be closed down tomorrow. We already have a problem with large volumes of bad (and deceptive!) content on the internet, and something that automatically produces more of it sounds like a waking nightmare. Add to that the (presumed, but reasonably certain) fact that common training datasets being used contain vast quantities of content lifted from original authors without permission, and we have systems producing well-crafted lies derived from the sweat of countless creators without recompense or attribution. Yuck!" I'll be interested to see how long it takes for this "spectacular deflation" to come to pass, but having lived through 3 or so major technology bubbles in my working life, my antennae tell me that it's not far off now...
- whywhywhywhy 1y ago> but everything it produces needs careful checking for errors, mistakes and 'hallucinations' by someone with some level of expertise in a subject Nah you just post it, if people point out the mistakes the comment is treated as a positive engagement by the algorithm anyway, unfortunately for anyone that cares.
- tim333 1y ago>can't conceive of a use of this which is beneficial beyond a marginal improvement in content consumption AlphaFold is having a big influence in medical research. There's more to AI than chatbots. It's quite interesting the work they are doing there now - article on it https://www.labiotech.eu/in-depth/alpha-fold-3-drug-discovery/ https://www.labiotech.eu/in-depth/alpha-fold-3-drug-discover... I've got a personal interest because my sister has ALS and I think an in silico breakthrough is the only thing that could fix that before her dying.
- frozenseven 1y agoHey, it's the guy who has been predicting the imminent collapse of AI for three years now! As I understand, he's a former video game journalist and being anti-AI is now his full-time thing. Saying it's all useless, fake, evil, etc. A poor man's Gary Marcus, basically.
- alkyon 1y agoSo being a former video game journalist, makes all his arguments void. Thank you for your imput!
- frozenseven 1y agoPretty much. What else would you expect from a non-technical activist who's railing against science/tech? What you see is what you get.
- ch_fr 1y agoI hope Ed Zitron will keep saying that the biggest AI companies in the world are not making any profit for as long as the biggest AI companies in the world are not making any profit. I find that fact alone a bit alarming. You don't need to be a technical expert to understand that it's worrying how the entire media industry is pushing for everyone, everywhere, all of the time, to lean on a tech where the biggest providers are not profitable. You also don't need to be a technical expert to see how much of a failure it is for the entire media industry to interview Sam Altman, let him spew out utter gibberish, and not even question him on it.
- frozenseven 1y ago>biggest AI companies in the world are not making any profit Companies that are exploding in popularity and expanding as fast as possible are not expected to make a profit. This is not unusual in the slightest. >the entire media industry is pushing for everyone, everywhere, all of the time No, people use AI because they want to use AI. New users arrive on their own. If you take a closer look at what the legacy media is actually saying, they tend to have a negative slant against AI. Yet people still show up. And will continue to show up. >Sam Altman, let him spew out utter gibberish, and not even question him on it If Altman is pissing you and Ed off, he's doing at least something right. That said, I follow AI news every single day and I barely even glance at what Altman is saying. Here lies one of the biggest follies of the anti-AI crowd. Zitron et al. think that they can make AI go away by canceling Altman.
- hotpotat 1y agoLots of in-depth analysis, but I think the author is very clearly emotionally invested to the point that they are only drawing conclusions that justify and support their emotions. I agree that we’re in a bubble in the sense that a lot of these companies will go bankrupt, but it won’t be Google or Anthropic (unless Google makes a model that’s an order of magnitude better or order of magnitude cheaper with capability parity). Claude is simply too good at coding in well-represented languages like Python and Typescript to not pay hundreds of dollars a month for (if not thousands, subsidized by employers). These companies are racing to have the most effective agents and models right now. Once the bottleneck is clearly humans’ ability the specify the requirements and context, reducing the cost of the models will be the main competitive edge, and we’re not there yet (although even now the better you are at providing requirements and context, the more effective you are with the models). I think that once cost reduction is the target, Google will win because they have the hardware capabilities to do so.
- danenania 1y agoOpenAI was arguably an oom ahead at one point, and competitors caught up in about a year. So I’m not sure even an advantage like that is insurmountable. Like we saw with Anthropic, you just need a group of key researchers to leave the incumbent and start their own thing—they’ll then have a pretty good shot at catching up.
- cwmma 1y agoIt is not clear at all if Claude will actually be profitable, are there enough people who will actually pay the subsidized costs especially if they end up being a significant fraction of an additional dev's salary.
- 827a 1y agoI think there's enough people willing to pay Claude's token rates today, either via subscription or via proxy through e.g. Cursor, that they can effectively turn the "new model R&D cost" knob to whatever their financials can support, and they'll survive for as long as their models can remain competitive. The challenge all these frontier labs have is: Their existing models can have high token profitability, but they have to invest everything they've got (and everything they're given) into new model R&D, because if they don't xAI will beat them, or Anthropic will beat them, or Google will. That's the nature of frontier spaces like this. But the flipside is, model capability will plateau, they probably are already, and as that happens it becomes safer to aim for profitability. And I have zero doubt that OpenAI and Anthropic can find profitability. xAI, Perplexity, Mistral, and the other labs, I'm less sure about.
- K0balt 1y agoI too am deeply skeptical of the current economic allocation, but it’s typical of frontier expansions in general. Somehow, in AI, people lost sight of the fact that transformer architecture AI is a fundamentally extractive process for identifying and mining the semantic relationships in large data sets. Because human cultural data contains a huge amount of inferred information not overtly apparent in the data set, many smart people confused the results with a generative rather than an extractive mechanism. ….To such a point that the entire field is known as “generative” AI, when fundamentally it is not in any way generative. It merely extracts often unseen or uncharacterized semantics, and uses them to extrapolate from a seed. There are, however, many uses for such a mechanism. There are many, many examples of labor where there is no need to generate any new meaning or “story”. All of this labor can be automated through the application of existing semantic patterns to the data being presented, and to do so we suddenly do not need to fully characterize or elaborate the required algorithm to achieve that goal. We have a universal algorithm, a sonic screwdriver if you will, with which we can solve any fully solved problem set by merely presenting the problems and enough known solutions so that the hidden algorithms can be teased out into the model parameters. But it only works on the class of fully solved problems. Insofar as unsolved problems can be characterized as a solved system of generating and testing hypothesis to solve the unsolved, we may potentially also assail unsolved problems with this tool.
- tim333 1y agoDifferent algorithms do different things but “generative” AI can certainly come up with new stories and images and with different algorithms AI can work with not fully solved problems like protein folding.
- K0balt 1y agoComing up with new arrangements of bits is not a particularly hard problem on its own, but the current crop of ai is certainly able to do that in the extractive process, in fact randomness is a key part of training and inference. But making new things from old parts does not constitute innovation, insofar as the arrangements follow known paths. That doesn’t make it non useful. It just makes it non innovative. Trial and error within a defined problem space is an area where automation can definitely be useful. Once again though, the result is not innovation but rather automation of labor. There is a -lot- of labor requiring mind numbing repetition or iteration. The vast majority of labor falls into this category, and exists in fundamentally solved problem spaces, but still is complex enough that the algorithms involved are opaque. This is where the current type of AI can work miracles when trained with enough oblique data.
- tomjuggler 1y agoBest rant I have read in such a long time. Subscribed despite the fact that I am all-in on AI for coding (plus much more) and disagree completely with the author's point of view.
- jsnell 1y agoThe analysis is just bogus. He is basically comparing two years of inflated AI capex estimates to a low-ball estimate of one year of trailing revenue. Let's unpack that a bit. Capex is spending on capital goods, with the spending being depreciated over the expected lifetime of the good. You can't compare a year of capex to a year of revenue: a truck doesn't need to pay for itself in year 1, it needs to pay for itself over 10 or 20 years. The projected lifetime of datacenter hardware bought today is probably something like 5-7 years (changes to the depreciation schedule are often flagged in earnings releases, so that's a good source for hard data). The projected lifetime of a new datacenter building is substantially longer than that. Somehow Zitron manages to not make a comparison that's even more invalid than comparing one year of Capex to one year of revenue: he basically ends up comparing a year of revenue to two years of Capex. So now the truck needs to pay for itself in six months. They way you'd need to think about this is to for example consider what the return on the capital goods bought in 2024 was in 2025. But that's not what's happening here. Instead the article is basically expecting a GPU that's to be paid for and installed in late 2025 to produce revenue in early 2025. That's not going to happen. In a stable state, this would not matter so much. But this is not a stable state. Both capex and revenue are growing rapidly, and revenue will lag behind. What about the capex being inflated and the revenue being low-balled? None of us really know for sure how much of the capex spending is on things one might call AI. But the pre-AI capex baseline of these companies was tens of billions each. Probably some non-AI projects no longer happen so that the companies can plow more money into AI capex, but it absolutely won't be all of it like the article assumes. As another example, why in the world is Tesla being included in the capex numbers? It's just blatant and desperate padding of the numbers. As for the revenue, this is mostly analyst estimates rather than hard data (with the exception of Microsoft, though Zitron is misrepresenting the meaning of run rate). Given what he has to say about analysts elsewhere, seems odd to trust them here. But more importantly, they are analyst estimates of a subset of the revenue that GPUs/TPUs would produce. What happens when Amazon buys a GPU? Some of those GPUs will be used internally. Some of them will be used to provide genai API services. Some might be used to provide end-user AI proucts. And some of them will be rented out as GPUs. Only the two middle ones would be considered AI revenue. I don't know what the fair and comparable numbers would be, am not aware of a trustworthy public source, and won't even try to guess at them. But when we don't know what the real numbers are, the one thing we should not do is use obviously invalid ones and present them as facts. > I am only writing with this aggressive tone because, for the best part of two years, Zitron's entire griftluencer schtick has always been writing aggressive and often obscenity-laden diatribes. Anyway, please don't forget to subscribe for just $7/month, and remember that he just loves to write and has no motive for clickbait or stirring up some outrage.
- tim333 1y ago>I have written hundreds of thousands of words with hundreds of citations, and still, to this day, there are people who claim I am somehow flawed in my analysis... Says the PR guy who discovered AI a couple of years ago and now knows it all and that all the AI experts are wrong. I mean it's a good rant but I don't think he gets the bigger picture.
- ch_fr 1y agoWhat a nasty dismissal, "he's not a tech guy anyways, he could never understand anything surrounding AI". Quoting the end of the article ad verbatim: > And remember that you, as a regular person, can understand all of this. These people want you to believe this is black magic, that you are wrong to worry about the billions wasted or question the usefulness of these tools. You are currently being "these people". You don't need a huge technical baggage to understand that OpenAI still operates at a loss, and that there are at the very least some risks to consider before trying to rebuild all of society on it. I've seen many people on HN (or maybe it was also you the other times) give this same reply again and again, "what do you know? You've not made your research, and if you made research, you don't have reliable sources, and if you have reliable sources, you're not seeing the bigger picture, and if you are seeing the bigger picture, you're not a tech guy, so what do you know?" This essentially comes back to what the article also says, you are somehow held to crazy fucking standards if you ever say anything remotely critical, and then people will come up in HN threads and say "the human brain is basically also autocomplete, so genAI will be as good as the human brain soon™" (hey, according to your reply, shouldn't people be experts in the human brain to be able to post stuff like this?)
- micahel00 1y ago[dead]
- 827a 1y ago> Outside of OpenAI, Anthropic and Anysphere (which makes AI coding app Cursor), there are no Large Language Model companies — either building models or services on top of others' models — that make more than $500 million in annualized revenue (meaning month x 12), and outside of Midjourney ($200m ARR) and Ironclad ($150m ARR), according to The Information's Generative AI database, and Perplexity (which just announced it’s at $150m ARR), there are only twelve generative AI-powered companies making $100 million annualized (or $8.3 million a month) in revenue. Though the database doesn't have Replit (which recently announced it hit $100 million in annualized revenue), I've included it in my calculations for the sake of fairness. I think this is among the most unhinged paragraphs I've ever read in my entire life. It deeply, metaphysically, struggles to frame what its presenting in a bad light, but the data is so overwhelmingly positive that it just can't do it. "Ugh, there's only twelve companies basically none of which existed two years ago making over a hundred million dollars in revenue. What a failure of an industry. And only three of them are making a half a billion? What utter failures. See, no one is using any of this stuff!!"
- Corrado 1y agoHis comments about Apple ring true to my ears. Apple is definitely lagging behind in the "AI" world, but that is really what they tend to do. They aren't the first company but they are usually the best. Historically, they wait until everyone else makes the mistakes and then introduce something better. I guess they felt like they couldn't wait for the "AI" trend to blow over; probably because Siri is just not very good. I think that Apple will hold on to their "AI" stuff for a while longer and wait until it really dies down. Then they will introduce a much better Siri and get rid of the "summarize your email" and "re-write this sentence" bullshit.