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The Generative AI Con

• rsynnott 2y ago
  > So yeah, OpenAI “burned only $340 million last year” as long as you don’t consider billions of other costs for some reason. Ah, yes, the WeWork 'community EBITDA' model.
  • tyzoid 2y ago
    Cue Charlie Munger's "Just replace EBITDA with 'Bullshit Earnings'" https://youtu.be/7B_6AFG0lUU https://youtu.be/7B_6AFG0lUU
• zombiwoof 2y ago
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• deleted 2y ago
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• anothermathbozo 2y ago
  This is one of the most tilted pieces I’ve ever read. For months Ed has predicted The AI Bubble will burst “any day now” frequently citing ai company’s revenue as a sign the product is not viable and the valuations are too high. The valuations seem to be primarily based on the R&D progress instead of on a theory that widespread adoption of the existing product will experience an uptick. The current landscape imho should be viewed as an R&D race amongst private actors.
  • bccdee 2y ago
    > The valuations seem to be primarily based on the R&D progress There hasn't been much R&D progress, though. Sure, as another commenter pointed out, context lengths have gotten longer and chat models can interpret images now, but the industry figureheads have been pushing agents, and we're not much closer to those than we were two years ago when GPT-4 came out. Current models simply are not consistent enough to do the kind of agentic stuff that AI valuations are predicated upon, nor is there any sign that a significantly smarter GPT-5 is just around the corner. Multi-modal chat is cute, but OpenAI is burning money. They're all burning money, and they don't have a product. They imply and imply that there's something big on the horizon, but it's been years, and there just isn't a killer app yet. Their platform isn't good enough, and it's not improving in the ways it would need to in order for Godot to arrive and for agents to be feasible.
    • anothermathbozo 2y ago
      By this I mean it’s a bet on what R&D might yield, current progress being some kind of signal. No one has certainty here. It’s an emergent technology and no one knows for certain how far it can be pushed.
    • x0x0 2y ago
      I think you can simultaneously think that there is some real value being made with LLMs and also look at OpenAI losing $5B a year or thereabouts and really wonder how they're not going to run out of money. That said, I'm learning a new sdk and I've moved 500-1k searches a month from kagi and google to llms.
    • twobitshifter 2y ago
      Recent results are showing exponential improvement in reasoning and dramatic decreases in the time and cost to train models. O3 now ranks 50th on code forces according to openai staff. Are you aware of all of this and still say R&D hasn’t progressed?
      • skydhash 2y ago
        You can invest in building bigger and more complicated pipe structures, but until you show the field that is supposed to be irrigated, you can't say you're disrupting farming business.
      • staticman2 2y ago
        In the context of Moore's law exponential growth was measured in the number of transistors per integrated circuit. This seems vigorous and straightforward. With AI the improvements have certainly been impressive but it isn't straightforward how you can define "reasoning" to measure whether or not the reasoning is exponentially "improving".
      • bccdee 2y ago
        Again: Those are incremental improvements. The valuations are based on the promise that agents are just around the corner, and we just haven't seen the kind of categorical shift in intelligence that agents would require.
  • ksynwa 2y ago
    He hasn't said anything about when the bubble will burst. Just says that it is a bubble and it will inevitably burst.
    • alvah 2y ago
      Spotting bubbles and predicting they will burst at some point is not a particularly useful skill. Housing in Amsterdam was in a bubble for 37 years in the 1700s; identifying the bubble early on would have been completely pointless.
      • ksynwa 2y ago
        So what should one do when one notices a bubble?
        • alvah 2y ago
          If I had a reliable / repeatable answer to that question, my net worth would be a very large multiple of what it currently is!
          • automatic6131 2y ago
            And a Nobel prize in economics to your name!
        • rcxdude 2y ago
          Try not to be caught up in it, even if you feel a lot of FOMO as it lasts longer than you expect.
      • rsynnott 2y ago
        Sure, but predicting when an economic bubble will burst with any accuracy is virtually impossible.
  • JimDabell 2y ago
    > This is one of the most tilted pieces I’ve ever read. He comes across as just a ludicrously unpleasant, spite-filled person. > I'm fucking tired of having to write this sentence. > I am so very bored of having this conversation > I don't care about this number! > Shut the fuck up! > This isn't the early days of shit. > Didn't we just talk about this? Fine, fine. > $3.25 billion a quarter is absolutely pathetic. > This isn’t real business! Sorry! > He said in one of his stupid and boring blogs that > This man is full of shit! Hey, tech media people reading this — your readers hate this shit! Stop printing it! Stop it! > It's here where I'm going to choose to scream. > Dario Amodei — much like Sam Altman — is a liar, a crook, a carnival barker and a charlatan, and the things he promises are equal parts ridiculous and offensive. > Why are we humoring these oafs? > Despite Newton's fawning praise > Nobody talks like this! This isn’t how human beings sound! I don’t like reading it! > Ewww. > I'm sorry, I know I sound like a hater, and perhaps I am, but this shit doesn't impress me even a little. > I know, I know, I'm a hater, I'm a pessimist, a cynic, but I need you to fucking listen to me: everything I am describing is unfathomably dangerous > expensive, stupid, irksome, quasi-useless new product > I know this has been a rant-filled newsletter, but I'm so tired of being told to be excited about this warmed-up dogshit. > I refuse to sit here and pretend that any of this matters. > I'm tired of the delusion. I'm tired of being forced to take these men seriously. When I read this kind of thing, it’s very apparent that this is being driven entirely by spite not insight. He’s just so angry about everything. There are 57 exclamation marks in this article!
    • hudon 2y ago
      There’s substance under the brashness, though. He’s just upset that his reason is contradicting what everyone around him is saying, struggling to cope with the dissonance. Like being gaslighted. It’s a natural reaction, but I agree, annoying to read.
    • ablation 2y ago
      Indignation and fulmination is his shtick and gets him shared across social and the like.
    • wut-wut 2y ago
      I know! I Loved it!
  • suraci 2y ago
    > a theory that widespread adoption of the existing product will experience an uptick because profit of this can not cover the investment in this industry adoption of iphone/smartphone/internet brought new products, including those for reproduction and those for consumption but generative AI is totally different with iPhone, consumers maybe willing to buy a new ai-powered iphone __just like how they bought new iPhones for every 2years before__ > The current landscape imho should be viewed as an R&D race amongst private actors in fact, it's a CapEx race, you don't need to R&D anything (ofc you must pretent you do) that's why it's a con > The AI Bubble will burst “any day now” "The canary in the coal mine to look at is when Satya Nadella or Sundar or Zuckerberg say, ‘You know that $80bn of capex I said I was going to do? I think I’m going to cut that by two-thirds.’ That’s what you need to look for." that's the day
  • krainboltgreene 2y ago
    I can’t help but be reminded of Greenspan’s remarks on the housing market in 2006 while reading this comment: While he was chairman of the central bank through January 2006, Greenspan always denied there was a bubble in the nationwide U.S. real estate market, saying only that a certain number of metropolitan real estate markets could see declines in home values because of a localized run-up in prices. That view of any real estate bubble as a merely a local phenomenon is a condition he termed as "froth" in congressional testimony in 2005, as well as in subsequent comments.
    • wut-wut 2y ago
      A failure of imagination I suppose.
  • silverlake 2y ago
    The writer is a journalist, runs a media firm and podcasts. His job is to get attention. You get attention by being outrageous. The “AI will kill us all” take is covered by too many people, so he’s taking the “AI is doomed” path. No one is going to engage with a reasonable middle-of-the-road article. He’s got no credibility on this subject, but he knows how to turn attention into dollars. Everyone here keeps falling for it.
    • RationPhantoms 2y ago
      He's a good writer. Even if I don't agree with this opinion on it, I still enjoy reading it. Color me "fell" then?
  • smeeger 2y ago
    hes missing a critical insight which is that this is being treated as an arms race now. the money will keep coming for a lot longer than it should.
• locusofself 2y ago
  As a 40yo software engineer (at Microsoft) with no specific domain expertise other than using genAI for fun and some code completion, this essay/blog post articulates my gut feelings about where we are at, very well.
  • golol 2y ago
    I am a math PhD student and I already draw some value from recent reasoning models. I strongky believe than in 1-2 years LLMs will become established tool for scientists to help with coding and math. I really don't think you can call this a con...
  • Ancapistani 2y ago
    41 here, working in healthtech… and Devin has committed more code and closed more tickets on my behalf in the past week at my behest than I’ve done on my own in a month. It’s basically functioning as a team of entry-level junior engineers at this point. Previously I was having to spend a fair amount of time writing tickets and providing context, but lately I’ve fed all my meeting transcripts and such into an LLM and it interactively creates Jira tickets for me. Each one takes me maybe 30s to read before I confirm them and the assistant creates the actual tickets.
    • cmdtab 2y ago
      What kind of tickets are these? Even at non-complex tasks, I find agents struggle a lot. Can you give some examples?
      • Ancapistani 2y ago
        Sure. One task I gave it a couple of days ago was to upgrade the version of Python used in a project. In this case, that was a task suited for a junior engineer - it was simple enough to be described fully, but complex enough to require effort. Devin was able to recognize that the project used Poetry, was Dockerized, and that the Python version was specific in multiple places (.python-version, pyproject.toml, Dockerfile). It saw that a couple of minor dependencies didn’t support the new version of Python, so it went back and upgraded those to the most recent matching version first. Devin had never touched the repository in question before getting this task. I’ve given it more and less complex tasks, and yeah, it struggles with some things. I’d estimate that it consumes about 5-10% of my time but multiples my overall output by ~3x.
• simonw 2y ago
  > When you put aside the hype and anecdotes, generative AI has languished in the same place, even in my kindest estimations, for several months, though it's really been years. The one "big thing" that they've been able to do is to use "reasoning" to make the Large Language Models "think" [...] This is missing the most interesting changes in generative AI space over the last 18 months: - Multi-modal: LLMs can consume images, audio and (to an extent) video now. This is a huge improvement on the text-only models of 2023 - it opens up so many new applications for this tech. I use both image and audio models (ChatGPT Advanced Voice) on a daily basis. - Context lengths. GPT-4 could handle 8,000 tokens. Today's leading models are almost all 100,000+ and the largest handle 1 or 2 million tokens. Again, this makes them far more useful. - Cost. The good models today are 100x cheaper than the GPT-3 era models and massively more capable.
  • adpirz 2y ago
    The "iPhone moment" gets used a lot, but maybe it's more analogous to the early internet: we have the basics, but we're still learning what we can do with this new protocol and building the infrastructure around it to be truly useful. And as you've pointed out, our "bandwidth" is increasing exponentially at the same time. If nothing else, my workflows as a software developer have changed significantly in these past two years with just what's available today, and there is so much work going into making that workflow far more productive.
    • audunw 2y ago
      But if this is like the internet, it’s not refuting the idea that this is a huge bubble. The internet did have a massive investment bubble. And I’d argue it took decades to actually achieve some of the things we were promised in the early days of the internet. Some have still not come to fruition (the tech behind end to end encrypted emails was developed decades ago, yet email as most people use it is still ridiculously primitive and janky)
      • newAccount2025 2y ago
        Can it be an investment bubble but also a hugely promising technology? The FOMO-frothing herd will over-invest in whatever is new and shiny, regardless of its merits?
• ergonaught 2y ago
  Well, he isn't wrong.
  • anothermathbozo 2y ago
    He might be. It’s an emergent technology and no one knows for certain how far it can be pushed.
    • andsoitis 2y ago
      Technology is largely a function of human imagination, tempered by constraints imposed by time on the one hand and amplified by new discoveries unfolding on the other. Imagination being a fuel, what does the imagination project is possible in 100 years?
• lukevp 2y ago
  Why in the world would you want a car?? They are horrible to maintain, difficult to operate, expensive, smell bad, and are slower than horses! -somebody salty about automobiles, circa 1900.
  • bccdee 2y ago
    Tbh they'd have been right. Cars are expensive to buy and to maintain. They are difficult to operate—people die every day. They do smell bad, and the particulate matter they emit is extremely bad for you. And they are slow: Traffic is an unsolvable problem in urban centres. Redesigning our cities around cars was one of the big mistakes of the 20th century.
    • CamperBob2 2y ago
      It's our loss that you weren't around to set everyone straight, I'm sure.
      • bccdee 2y ago
        Definitely. Me or anyone else from the future with a century's worth of hindsight.
    • Ancapistani 2y ago
      And yet, they’re better than what they replaced. Horses weren’t cheap when they were a primary mode of transportation. Lots of people have died riding, driving, and breaking horses. They definitely smell bad, and their “particulate matter” was so bad that houses had to be set back and elevated from the street. Cities designed around cars are far superior to cities designed around horses.
      • muddi900 2y ago
        But cities designed around trains are superior and it was a contemporary technology that was ignored.
• jarsin 2y ago
  > How does this industry actually continue? Do OpenAI and Anthropic continue to raise tens of billions of dollars every six months until they work this out? It's been made fairly clear that the insiders are setting the stage for governments to back them (bail them out).
• paulgb 2y ago
  > And even then, we still don't have a killer app! There is no product that everybody loves, and there is no iPhone moment! I would strongly argue that coding assistants are AI’s first killer app. Copilot, Cursor, Windsurf etc.
  • cmdtab 2y ago
    Are they? I find Agentic mode on most editors barely useful. Autocomplete and inline editing is great though. To use these tools properly, you need to know how to build the same thing precisely.
    • ramraj07 2y ago
      But that still doesn't exclude copilot, which is the most intuitive and genuinely useful version of ai after chatgpt itself.
      • cmdtab 2y ago
        I don’t deny it. I used claude + gemini to whip out a rewrite of a show HN project in less than half an hour to deployment yesterday. https://news.ycombinator.com/item?id=43071381 https://news.ycombinator.com/item?id=43071381 But this sort of work is fairly low value and boilerplate-y.
    • jack_pp 2y ago
      Nah you don't to know to build the same thing precisely. Just the other day I wanted to write a vanilla JS component that could let you select a picture from something like a carousel and be able to blow up the selected picture when clicked. I know JS / HTML but am not used to working with vanilla JS. Copilot didn't write it all by itself but it did teach me things I didn't know like making a custom tag in vanilla JS by extending an HTMLElement. The code isn't the most readable because I don't need it to be however if you make me write it from scratch in an interview style setting I'd have trouble doing it. If I read the code I can follow it and it makes sense + it's an easy component to manually test. So.. no, I don't need to know how to precisely build the same thing. And before you worry that I'm committing code I can't build from scratch.. This is a simple component for a 5 page landing page build with astro where I'm the "main" dev ( wrote like 80% of the code). The web-page won't even need maintainance once it's deployed
• lukevp 2y ago
  I’m a little shocked at how much negativity there is around LLMs among developers. It’s a new tool that requires some learning, and it’s sometimes not so great, but if you’ve used an IDE with real coding assistance built in (eg. VS Code in Edit with Copilot mode - NOT Chat mode, using Claude 3.5), it’s honestly not much worse than a junior dev and 100x faster. And if the code is bad you throw it away and try again 10 seconds later. The amount of speed up I see as a very experienced dev is astronomical. And just like 6 months ago it was awful. How great is it gonna be in a year or two? It doesn’t even have access to running unit tests or reading console errors or IDE hints, and it still generates mostly correct code. Once it gets more deeply embedded it’s just going to improve more and more.
  • stuckkeys 2y ago
    Honestyl. It has its drawbacks but I am usually at 50x with few different agents running side by side. What we need is better GPU competition with tons of ram.
    • notpachet 2y ago
      Doesn't that just scream "bad design" at you? Shouldn't we be aiming for agents that require less GPU? And agents that are good enough that we don't have to shop around for "competing prices" on answers?
  • mlboss 2y ago
    It is difficult to get a man to understand something, when his salary depends on his not understanding it.
    • jayd16 2y ago
      On this site, the adage cuts both ways.
  • jayd16 2y ago
    Unreliable tools are utterly exhausting. > not much worse than a junior dev and 100x faster. Is there a greater hell than this!?
• alvah 2y ago
  Ed occasionally makes good points, but he's very very angry at Big Tech, and his anger often gets in the way of his message. Reading his latest rant reminds me of Karl Denninger railing against Google around the time of their IPO, claiming they would never make enough money to justify an $85 share price (a $1000 investment then would be worth around $375,000 today).
  • danroblew 2y ago
    Maybe OpenAI can become an advertising company?
    • alvah 2y ago
      Maybe. Did you foresee Google becoming a massively profitable advertising company with a search engine attached in 2004? I certainly didn't.
      • jcgrillo 2y ago
        Google solved a real problem. They indexed the web and made search work, and they did it very cheaply. So cheaply, in fact, that they could give their service away to users and monetize it with ads. LLMs are not like this. They're both extremely expensive to run and they don't do anything truly valuable--there's no killer app. So how exactly is OpenAI or their ilk (or for that matter the rest of us) supposed to use these things to make money? This is the only question, and the fact it's still an open question just screams "hype bubble". My bet is this AI stuff goes the way of the NFT.
        • deleted 2y ago
          [deleted]
        • fragmede 2y ago
          I'd take that bet. Google offers a very expensive service for free, but is able to monetize it with ads. Sometimes connecting users to companies is what users actually want. But Google has this problem that since the service is free, its users feel entitled to everything for free. They can't just go and charge people what it costs to run a Google search. OpenAI doesn't have this problem. ChatGPT has a free level to get you hooked, but it's restricted. So a lot of users pay them $20 or $200 or some other amount per month to use their service. So how OpenAI makes money is by selling access to their service. What you do with it is up to you, but their value proposition is simple. Pay us to get more/better access to our service. How much it costs them to operate the service is a secret known only to them. There are a lot of very very educated guesses, but they're just guesses. After the VC money runs out they'll have to charge more than it costs to provide the service to stay afloat, and then we'll see. $20/month for ChatGPT plus is the $1 Uber that got people hooked. There's already a $200/month tier. Whether OpenAI, specifically, will be standing in 20 years, only time will tell. But by this point it should be obvious that there's something to this LLM thing. Even if the product doesn't get any better than it is today, it'll still take 5-10 years for its effects to reverberate through society. The killer app is LLM-accelerated programming. Sure, it doesn't work for all domains and it can't do everything, but even if the only thing it's good for is creating JavaScript react CRUD apps, well, there are a lot of those out there, and they're not actually limited to that. And since tool use means they can generate code and compile it and test that it works, it's possible to generate datasets for other languages and libraries, the only question is which ones is it worth it for. It might not help at all in your line of work, but a friend who does contracting is able to use LLMs to cut the time it takes him to do a specific kind of job in half, if not more, enabling him to take on twice as many clients and make more money. For him it would still worth it even at 100x the current price. thankfully competition means it'll take a while before it's that expensive.
• deleted 2y ago
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• wendyshu 2y ago
  Just because you want something to be true doesn't make it true
• NewUser76312 2y ago
  Hey I have my gripes with the landscape, certainly, but this is just too much. > It sure is! But it doesn't really prove anything other than that people are using the single-most-talked about product in the world. By comparison, billions of people use Facebook and Google. I don't care about this number! > User numbers alone tell you nothing about the sustainability or profitability of a business, or how those people use the product. It doesn’t delineate between daily users, and those who occasionally (and shallowly) flirt with an app or a website. It doesn’t say how essential a product is for that person. Both of these "arguments" could be applied to any of the big tech giants of the last 25 years - Google, Amazon, Facebook, Uber, whatever (and there'd be other incumbents used by billions of people before them). I don't believe these arguments discount ChatGPT from having the potential to continue growing like a Facebook. And who cares how many journalists Altman knows, you don't get a product written about that much unless it's truly a groundbreaking product. > And even then, we still don't have a killer app! There is no product that everybody loves, and there is no iPhone moment! There sure is, it's called programming. He called out quality earlier on, but the quantity and speed and direction the AI can take (as well as its rate of improvement) is breathtaking. My own output has 10x'd easily since GPT-4 came out (although some of that means I'm needing far less hours in certain places). And guess what? The code quality is generally fine. > Where are the products? No, really, where are they? What's the product you use every day, or week, that uses generative AI, that truly changes your life? If generative AI disappeared tomorrow — assuming you are not somebody who actively builds using it — would your life materially change? Ok, the product is called ChatGPT, or Claude, or DeepSeek or whatever, and if it disappeared overnight, my programming productivity would drop dramatically. I would not seek to take on as ambitious projects in as short of a time frame as I am doing now. I don't know, as a user and developer both of AI/LLMs, this article isn't hitting the mark for me. There are legitimate criticisms of the field, but I'm not seeing them thus far. Edit - I'll say I agree with the Deep Research criticisms. These products are very underwhelming. They're literally to help people do a research report which needs to be done, but won't be used or read critically by anyone report.
  • alvah 2y ago
    "I'll say I agree with the Deep Research criticisms. These products are very underwhelming." I haven't shelled out the $200/month for OpenAI's Deep Research offering, but similar products from Google and Perplexity are extremely useful (at least for my use case). I would never present the results unchecked / unedited, but the Deep Research products will dig much deeper for information than Perplexity could be persuaded to previously. The results can then be fed into another part of the process.
• xnx 2y ago
  Plenty of AI companies that are cons or extremely overvalued, but the technology is the real deal and delivering huge improvements over previous techniques in all kinds of domains: language translation, weather prediction, code completion, self driving, etc.
  • advael 2y ago
    I swear no matter how many times people say it people will still conflate all ML with LLMs. No, chatGPT is not driving advances in self-driving or weather prediction
    • xnx 2y ago
      For better or worse, "LLM" or "generative ai" has become roughly synonymous with the current wave of ML. I know very little about ChatGPT, but Waymo is using an LLM: "Powered by Gemini, a multimodal large language model developed by Google, EMMA employs a unified, end-to-end trained model to generate future trajectories for autonomous vehicles directly from sensor data." (https://waymo.com/blog/2024/10/introducing-emma https://waymo.com/blog/2024/10/introducing-emma)
      • advael 2y ago
        Huh. I mean it makes sense to train end-to-end on all the interrelated tasks involved in driving but putting a whole-ass language model in the middle of that seems like a stunt. I wonder if it does better than like, any random transformer not trained on language first? Still, I hadn't heard that so I guess I was wrong about that one
        • magicalist 2y ago
          No, you were right, this appears to be just research on how applicable LLMs could be to the space. They talk about the improvements their LLM makes, especially in being multimodal vs training multiple independent models, but also the limitations that appear to prevent it from being useable as it is. Maybe some form if it will be used some day (it does seem like it would be useful to have semantic understanding of the world integrated into the system), but at least as of when this was published, it's not actually used.
• int_19h 2y ago
  This reads like a straightforward rant to me, not something informative. Which then invites the question: why is this person's opinion on the subject relevant? Do they have some credentials that make it more valuable than a random comment with a similar rant (of which there are plenty) on Reddit or HN?
  • simonw 2y ago
    They have 55,000 newsletter subscribers. https://www.wheresyoured.at/about/ https://www.wheresyoured.at/about/
  • rainonmoon 2y ago
    I mean we insist on enduring Paul Graham's every brainfart on this website so why not other bloggers?
• andsoitis 2y ago
  > I am so very bored of having this conversation, so I am now going to write out some counterpoints so that I don't have to say them again. It is not clear to me why the author feels the need to have the conversation. Human consciousness gives us the ability imagine future states in the universe and make them come true. The results will speak for itself.
  • tim333 2y ago
    He seems to think the hype will do great damage to society "I need you to fucking listen to me: everything I am describing is unfathomably dangerous, even if you put aside the environmental and financial costs." Personally I think he's lost it a bit. I mean say he's right in that LLMs plateau and investors lose some money. Life will go on.
• famouswaffles 2y ago
  >So...yeah, of course ChatGPT has that many users. When you have hundreds of different reporters constantly spitting out stories Oh sure, because you can just have hundreds of reporters constantly write about your product. It's so simple. Why aren't more people thinking of that ? >The weekly users number is really weird. Did it really go from 200 million to 300 million users in the space of three months? According to similarweb, monthly visits grew over 1B in that timeframe so yeah sure it sounds possible. >300 million monthly active users would mean a conversion rate of less than 4%, which is pretty piss-poor A B2C Saas whose lowest price point is $20 will be lucky to get anywhere near 4% conversation. >And even then, we still don't have a killer app! The 6th (and climbing) most visited site in January is not a killer app ? Okay
• tiborsaas 2y ago
  > And when this all falls apart — and I believe it will — there will be a very public reckoning for the tech industry. I shocked he really believes it in his closing thought. Maybe his rant would be bit more digestible if it contained sections with: "here's what I tried and it did not work". But that would make it not a rant but actual research with value.
  • CamperBob2 2y ago
    I'll save him the trouble of writing it: "I asked ChatGPT 3.5 to write a large, underspecified chunk of code a couple of years ago, and it didn't work the first time, unlike the code that I write. This whole 'AI' business is an elaborate scam."
    • parodysbird 2y ago
      He's not a developer. He's really talking about consumer tech.
      • CamperBob2 2y ago
        OK, let's try, "I have no idea how any of this works. However, I have come to the conclusion that it doesn't, and can't." Closer? I'm just going by the headline here.
  • fullshark 2y ago
    He's wrong, there's no other sector of the economy with growth potential and there's so much capital desperately seeking returns. Also anxious capital terrified of being disrupted. The tech industry will just move on to the next hype cycle when this one burns out.
• sambapa 2y ago
  I always wonder how LLMs will achieve superintelligence when they are, by definition, average.
  • drpossum 2y ago
    Where is this defined? I'll wait for your reponse.
    • sambapa 2y ago
      In some math books about markov chains
  • porridgeraisin 2y ago
    To this pedantic point, If the average written intelligence of all humans alive and dead is > the max intelligence of all live humans who are also willing/positioned to do the same task at the same time and at the same place. But yeah, I don't think LLMs (the current core architecture) can provide super intelligence. I think it needs a bit more than next token prediction architecturally speaking.
  • sebastiennight 2y ago
    This is incorrect. If you take the most basic interpretation of an LLM at temperature 0 as predicting the most likely token, and you run it on, say, 1,000 runs of "complete this Spanish sentence with the word for 'X'", then: - maybe ALL humans would fail the test in some way, eg. let's say everybody gets at least 10 of those wrong, and the average person gets 100 of those wrong. - still, as long as most people correctly get each word right, your LLM would get every single response correct (because for each item in the test, 900+ people out of a thousand gave the same correct answer in the training set). In that sense, it's totally possible for a system trained on a vast vat of average-human input to generate super-human outputs.
    • sambapa 2y ago
      But still, the questions in that test are "solved" in the sense of "I can take a dictionary and answers these questions with full certainty". Beyond established knowledge LLMs are monkeys with typewriters, at best.
• dzonga 2y ago
  for people using these AI products for coding what exactly are you doing ? general API plumbing ? call this api, combine the json results & spit it out. Then slap a React / Next.js frontend ? lately, I have been doing your classical business apps - due to the domain rules - ai is pretty useless - but I have found perplexity and deep mind to be smarter stack overflows. that's it.
  • cookiemonsieur 2y ago
    personally I use it as a glorified stack overflow. It really just saves me a few clicks on my browser. For anything even remotely complex or involved, it's just not that useful. Interestingly, It seems to shine the most when doing boilerplate stuff in widely used languages such as python or javascript, but it's extremely bad with terraform.
    • sandos 2y ago
      Its very smart templates imo. Its basically more time-consuming for me to get it to where I want the code than finish it myself. For some scaffolding in python green-field development, sure I save a few minutes.
  • tasuki 2y ago
    I tell it the function name, input, output, and an LLM writes the function for me. I prefer to keep an eye on the architectural decisions myself.
• BrenBarn 2y ago
  A huge part of our problems stems from the fact that it's possible to make "companies" whose business model is built on losing money hand over fist until they've brainwashed everyone into thinking their "product" is good. In a sane world these companies would fail and AI would continue develop through small failures and small successes over a period of years or decades. Instead we get a firehose of nonsense just because a small number of wealthy people are willing to gamble.
  • danroblew 2y ago
    On the plus side, if all the AI companies collapse there will be a lot of spare hardware. Open source projects would have a lot more compute to work with.
    • parodysbird 2y ago
      This is a great point. Now I have extra reason to cheer on the bubble bursting.
    • spacemanspiff01 2y ago
      This is my thought, sure a lot of VCs will lose a lot of money as they write things off. But it's not like people are going to throw out all the Nvidia hardware they bought. And there are ai applications that I can think of that would be viable at 100x cheaper price.
    • BrenBarn 2y ago
      That would be nice, but I'm more worried they won't collapse because they'll succeed at shoving their snake oil down the throats of enough big players to ensure their survival.
• suraci 2y ago
  this can be both true: 1. The Generative AI is very very useful 2. The Generative AI is a epic bubble and it will kill us all (financially) one day It's entirely appropriate to describe it as a 'con', as long as you look deep enough into OpenAI, SoftBank, MSFT, NVDA, SMCI, etc. it's a con, but it's useful, and it will kill us all
  • sebastiennight 2y ago
    Sadly, this comment still works without the word "(financially)"
• Aeolun 2y ago
  [flagged]
• mylastattempt 2y ago
  On LLM/ML itself: it seems a lot of cynical people start with some unreasonable idea that "AI" should be able to do what it will perhaps be able to in 10 or 100 years, and are subsequently upset that it is not capable of that yet. It may get there, it may not. But that's on you for starting with a wrong assumption. Is the AI "business" or "market" overvalued for it's current capabilities? Yeah, I do believe so. Welcome to the financial world, which is completely separated from reality. It's like that in all sectors where something new and exciting is happening, not just IT or AI. People poor money in hoping to be early enough to make a profit. Nothing more, nothing less. The rest is marketing. Some Sam Altman guy promoting the hell out of his own product? That is literally his job, regardless of wether or not he believes it all. But articles like these are so bizarre to me. The author acts like he has millions at stake and his money manager just won't listen and pull all investments out of AI. Hurry up, the bubble is about to burst, I will lose all my money! Except that... they don't. They are just "old man yelling at cloud". If you believe AI is the next Metaverse or WeWork, then it will just die off by itself once the bubble pops. Why are you having so many conversations about it, where you seem to be desperately trying to convince people of the bubble/con that is AI. To the point that you're so sick of it, that you write down your arguments so you can point the blinded there instead of having those tiresome arguments. Genuinely baffled. Spend your energy on something productive rather than destructive, perhaps?
  • danroblew 2y ago
    Trillions of dollars, dude. They need to make trillions of dollars to satisfy their investors.
    • mylastattempt 2y ago
      If you are correcting my use of millions to trillions: I was refering to the author himself, who writes like this giant AI bubble is pushing him forward to the edge of the cliff as people keep believing in it, and he is desperately trying to get the bubble to shrink or he'll fall off and die. Methaphorically. But why does he act or feel that way? Let the trillions be lost, it's just how hypes, bubbles and the stock market in general work.
• yapyap 2y ago
  Love Ed!
• levkk 2y ago
  If my Android (or IPhone) disappeared tomorrow, I would feel like I time traveled back a century. If Google search was gone, I wouldn't be able to do my job anymore. If the cloud disappeared, I wouldn't be able to build apps anymore. There are no workarounds, unless you feel like going to a library...? If ChatGPT disappeared tomorrow (or derivatives like Copilot, etc.), I would be mildly inconvenienced. Then I'd go back to reading docs, writing code slightly slower and carry on. In fact, I did this already, several times (Copilot with GPT-3.5, Cursor, Copilot with GPT-4, Zed with Claude, etc.)
  • n2d4 2y ago
    I think that's an unfair comparison. If the IBM Simon disappeared in 1994, I'm pretty sure you wouldn't have cared. If search engines disappeared in 1992, you'd have felt the same. Also, (what later became) AWS probably didn't interface much with you in 2003. It takes some time for technology to mature, usually at least a decade or two. Even once the iPhone was released it took a few years until it became indispensable.
    • spamizbad 2y ago
      But the AI-public Internet timeline is more like 1995. if all web search disappeared in 1995 it would've been a massive loss, despite how primitive search engines were back then.
      • kevindamm 2y ago
        reminding me that ~1995 for a couple of years it was practical to print listings of web sites: https://www.goodreads.com/book/show/2868341-the-internet-yellow-pages https://www.goodreads.com/book/show/2868341-the-internet-yel...
    • krainboltgreene 2y ago
      I remember when people commented here that the blockchain was the same as early google search or early aws or early iPhone. Everyone thinks their new thing is the T-1.
• peteforde 2y ago
  I would be highly amused if the OP revealed that the essay/rant had been written by o3-mini tomorrow. While I don't really understand what fuels this person's Substack Forensic Journalist energy, I can only say that I am thrilled to pay $20 to OpenAI because it delivers outrageous value to me as a solo, self-taught "engineer"* designing reasonably complex physical devices intended for sale. Air quotes because here in Ontario, if you don't got the ring, you don't got no business using the title. So my first hand gut reaction is that people who cannot fathom meaningful use of modern LLMs are by definition people who are not trying to solve complex problems in domains they aren't yet super confident in. No judgement, and this is intentionally reductive; an LLM skeptic is lots of other things, too. Just saying that if you want to build hard things, reasoning models are dramatic force multipliers.
  • thefz 2y ago
    > So my first hand gut reaction is that people who cannot fathom meaningful use of modern LLMs are by definition people who are not trying to solve complex problems in domains they aren't yet super confident in. OTOH I would never trust anything built by someone not super confident while heavily relying on a LLM.
    • chaos_emergent 2y ago
      Then you should probably stop using most applications today, specifically those that have been iterated upon in the past two years.
      • thefz 2y ago
        There's a reason why most modern software is disappointing
    • peteforde 2y ago
      Nobody starts off super confident! I'm proud to be a life-long learner. I've just learned more, about more things, in the last three years than I did in the previous few decades of coding every day. One person's imposter syndrome is often superior to another's blustery confidence.
• rambambram 2y ago
  Nice write up, but if you'd ask me the author did fall for another con: calling webhosting that fancy C-word.
• DebtDeflation 2y ago
  >People like Marc Benioff claiming that "today's CEOs are the last to manage all-human workforces" This is the real problem. Companies have ALREADY starting laying off significant percentages of their workforce because they're buying into the AI "digital worker" hype without any idea of how exactly AI is going to do the jobs of 80% of THEIR employees across all departments in the next year or so.
  • drpossum 2y ago
    No, they're using that and RTO as an excuse for layoffs. They layoffs were coming inevitably from ZIRP going away. If you were a CEO and looking at that balance sheet would you tell investors "we need to shed workforce because we can't be profitable" or "we can shed workforce because we're cutting edge". Stop listening to CEOs whose literal job it is to make their company look good under any and all circumstances and start looking at SEC filing numbers.
    • cootsnuck 2y ago
      This part. Companies love a smokescreen when they need to tighten their belts.
• ChrisRob 2y ago
  [flagged]
• petesergeant 2y ago
  Article is a motte-and-bailey[0] argument. Bailey (the clickbait): “Generative AI is a con!!” Motte (narrow defendable argument): OpenAI and Anthropic have not shown that building a proprietary model and selling inference is a sustainable business. 0: https://en.m.wikipedia.org/wiki/Motte-and-bailey_fallacy https://en.m.wikipedia.org/wiki/Motte-and-bailey_fallacy
  • card_zero 2y ago
    I see, so whenever anybody states their position tersely, I can accuse them of using a motte-and-bailey argument, and force them to be so pedantic and long winded that their point get lost in the weeds. Unless I like what they're saying, of course. I'll keep it in mind!
    • lblume 2y ago
      These two are completely different statements, though.
      • card_zero 2y ago
        I thought they were fairly similar. I suppose there's the question whether it's a sincere misdirection.
    • petesergeant 2y ago
      …what? The author has a narrow defensible point (OpenAI and Anthropic have questionable business models) and rather than stating it tersely, he’s instead tried to use that to write an unfocused article dismissing all of Generative AI as a con. It feels like you neither read the original article very carefully, nor took the time to understand what a motte-and-bailey argument is before writing this.
• somewhereoutth 2y ago
  > And when this all falls apart — and I believe it will — there will be a very public reckoning for the tech industry. and will trigger the collapse of the wider asset price bubble, with consequent economic turmoil - an unfortunately necessary reset, in my opinion. I suppose the good news is that likely the current US administration will wear this one, though not completely being their fault (much like Covid), and a political reset will also ensue.
  • jcgrillo 2y ago
    I'm worried with a slowing housing market (demand is at a 5yr low) there could be a perfect storm of major market crash coupled with plummeting home values.
    • adamc 2y ago
      That might be a good thing. Current housing prices are insane.
• sakex 2y ago
  The point you're missing is that people were making the same kind of comments about Amazon and Uber not too long ago
  • JTyQZSnP3cQGa8B 2y ago
    Don't rewrite history. Amazon had a million times more books than my shitty local library. ChatGPT is at best the equivalent of a junior that you have to supervise all the time and replaces all your thoughts. It's a very different scenario unless those LLMs can improve very fast which I doubt. And when they reach a senior level, the damage will already be done.
• ForHackernews 2y ago
  The killer app for AI is going to replacing frontline support staff. When you call, email or chat with support for companies that are screwing up, you won't be able to reach a human without going through several layers of "helpful" AI agents first. To succeed here, AI doesn't have to be cheap or good, it only has to be cheaper than human staff.
• stevage 2y ago
  Where's the product that everyone is using and loves? Um, Chatgpt. And Copilot. I use them both. A lot. I'd hate to me without them.
• Kye 2y ago
  I could only skim to verify an automated summary, but if the takeaway is "these AI giants are doomed" then he's right. The future, probably within 10 years, is most tasks being handled by small on-portable-device models (7B parameters or so; see Apple's Intelligence thing), a middle ground of workhorse models (pushing closer to 30s and 70s) running on more capable ML-focused chips in laptops and workstations, and home and office servers for the biggest professional users running on dedicated servers. And then there's the apps. Whoever makes the "Stripe for generative AI" with multiple models with different levels of data provenance, security, SLA, etc for different use cases tied together with support for custom fine tuning stands a good chance of sweeping the market post-collapse.
  • sebastiennight 2y ago
    I'm not on iOS these days, can you elaborate how "Apple's Intelligence thing" has solved the 7B-sized on-portable-device model for everyday users? My understanding of the zeitgest on HN about Apple Intelligence was definitely not leaning towards "they nailed it". Not even in the ballpark of "promising", I'd say.
    • deleted 2y ago
      [deleted]
    • Kye 2y ago
      I didn't say they nailed it. I don't know since I can't run it, but ten years is a long time for any technology. I toyed with the 7B Mistral through MLC Chat and, while slow, the responses were good. The Llama-3.2-3B-Instruct it comes with is fast but sometimes takes questioning to get accurate answers. The older Phi variant it has was thorough and accurate, Phi's selling point, but made my phone run hot being too thorough. I don't know much about Apple's model.
• Cemlolo 2y ago
  It's not a con. It's the frontier. The only new really big one we know. It already solved real issues, see alphafold and it will continue until we hit a ceiling. The money throwing thing is a zeitgeist issue: we have this money and people don't know what to do with it. But yes ml is now the thing. And no it was very very far away speaking to a machine and the machine feeling smart. If you can't see this breakthrough as what it is, you will never be excited for any new invention. Until perhaps aliens are arriving on our door steps.
• stpedgwdgfhgdd 2y ago
  Software development to me has always been about the 80-20 rule. You build 80% of the functionality in 20% of the time. Next you spent 80% of your time to build the remaining 20%. With LLMs it feels we are getting near to 90-10. Finding the bug in those good-looking pieces of generated code is pretty hard. (After all, you did not pay a lot of attention to the generated code, it looked pretty solid) Some will argue that the LLM should spot the bug, Indeed, it should ask clarifications about the requirements. One day… but you need an expert to understand and answer the questions for that last 10%.
  • linuxftw 2y ago
    I feel like finding bugs in golang is a non issue. The language is typed, so obvious problems are caught early in the editor. Unit tests mop up the rest (unit tests which are also written by copilot in my case). How I write unit tests: Open the chat menu, paste in function signature, describe the tests I want. Out pop the tests. Run, fix code as needed. Add more tests, etc. Super easy.
    • skydhash 2y ago
      Or way easier, build an harness, then just copy-paste the few tests you created at the beginning, because test codes is the most repetitive code I've seen. No need to rely on external services and much more simpler to maintain and reason about.
• simne 2y ago
  I wonder, when people will begin read books (or at least learn documentation). > OpenAI burned more than $5 billion last year. Well, this is semi-true. When speaking about LLM technology, must be honest, and make difference of base (or foundation) model training, vs fine-tune it for purpose. Sure, if you just use base model, you also could gain some profit, but real value of LLM achievable if you got already done base model and fine-tune it on your target task. What this mean - base LLM are just learn language structure from really huge dataset (for example, entire Wikipedia), and this is really expensive, but when you fine-tune LLM from for example, your corporation product documentation, it will become AI-consultant about your corporation. Or you could fine-tune LLM from children story book, and it could indefinitely generate texts similar to that story. BTW, rumors said, some orgs fine-tuned GPT-3 on their company codebase and have very interesting results on code generation (much better than with base model). Fact, base model training really cost millions (Llama-2 official cost $5 millions, and I believe it much more than claims of Chinese about deepseek R1 cost also $5 millions). But fine-tune GPT-4o now cost about 20 bucks for 1 million tokens, and inference is $3.75 per million input tokens and $15 per million output tokens. For GPT-4o mini, training cost is $3 per million tokens, and inference is $0.30 per million input tokens and $1.20 per million output tokens (from official announce on OpenAI developer community). If you consider fine-tuning of GPT-3 class model (or for example, similar open source model), official prices are just few bucks for million tokens (run it on your own infrastructure will be slightly more expensive), which I think very tolerable and already affordable for small companies. And I admit, just few Billions of market is not scale of big thing, but I think, it is just because conservative corporate tops, and because security problems of current implementations, and will change nearest years.
• nbuujocjut 2y ago
  GitHub Copilot and similar tools make good developers more productive. This alone is a genuine use case with some associated value. Is it enough to justify the valuations of OpenAI etc? Probably not by itself. But I expect other industries have similar productivity boosts where people learn to use the tools appropriately. What’s the total business opportunity of making all knowledge workers 10% more productive (to pick a more modest goal than outright replacement)?
  • Retr0id 2y ago
    > GitHub Copilot and similar tools make good developers more productive. Do we have any empirical evidence of this? It seems like it'd be an easy experiment to run - task a number of teams with building a particular product, some with Copilot and some without, and see what happens. I've tried copilot myself, and at times it makes me feel more productive, but I can't tell if it's truly helping me overall.
  • sandos 2y ago
    Generative AI only really helps (a meaningful amount) developers where writing code is actually the bottleneck. I have not been in a such a position for years and years.
    • JTyQZSnP3cQGa8B 2y ago
      Same experience here. Today I spent 5 hours debugging code, and wondering how I could put 3 contradicting specifications inside while negotiating some weird stuff that does not concerns me, and then I spent 3 hours deleting 100 lines of code and writing 100 lines of code to please everyone. I fail to see how a LLM could have helped me, and I've been doing this for more than 10 years.
• baggachipz 2y ago
  I had to write a similar post[1] a few months ago because I was so tired of everybody I know telling me we're all gonna be without jobs and we're about to enter a new epoch. I'm so sick of the hype and that will be the real thing that dooms us all. [1] https://blog.curtii.com/blog/posts/the-laypersons-guide-to-ai-hype/ https://blog.curtii.com/blog/posts/the-laypersons-guide-to-a...
• Red_Comet_88 2y ago
  "We are in the midst of a group delusion — a consequence of an economy ruled by people that do not participate in labor of any kind outside of sending and receiving emails and going to lunches that last several hours — where the people with the money do not understand or care about human beings." Regardless of the hostile tone of the article, this stuck out to me as an incredibly poignant description of the current tech/finance elites' mindset. As most of us who have tried LLMs can attest, they are indeed stochastic parrots with no capacity for knowledge or understanding. This is best exemplified by their non-deterministic outputs, wherein they give different answers to the same question if asked enough times. This is not how a human brain works. Perhaps it is a small building block, but the systemic architecture required to reach brain level is currently not in sight based on what I'm seeing.
  • tim333 2y ago
    >non-deterministic outputs, wherein they give different answers to the same question if asked enough times I think you may find some humans do that too.
    • colonial 2y ago
      Only because they're tired of you asking them the same thing over and over, or because they've picked up new knowledge/opinions since you last asked. "How many r's in strawberry?" "3." "How many r's in strawberry?" "...3?" "How many r's in strawberry?" "Piss off!"
• pnathan 2y ago
  Directionally correct. GenAI is - imo - an assistant. Copilot does effectively templating. I can have ChatGPT read an email and check it for tone. Claude can comment on camera kit. Claude does a very nice image recognition for obscure things. What I have become persuaded of is that the /completions API is simply not much more than +10% or a low key helper. I do not need a dumber-than-intern agent going ape on my codebase at speed, which is, approximately, what the codegen tools seem to do. I saw a self driving car startup using a GPT neural network to recognize images during driving. I would assess that class of use as plausibly very promising. I would also hazard that Shirkys BS jobs thesis is being proved true, because if a hallucinating ai can do it... Anyway. I don't think the fundamentals justify the spend. I think there's too much vitriol, but there's also too much hype & by a country mile too.
  • swyx 2y ago
    > the /completions API > I do not need a dumber-than-intern agent two tells that you have not updated since 2023
  • HDThoreaun 2y ago
    > I can have ChatGPT read an email and check it for tone. Maybe Im crazy but this alone is a trillion dollar market cap industry imo. msft is worth 3 trillion off the back of similar products. If LLMs are seen as indispensable by every office worker in the country, as I think they are, and every employee has a subscription for $20 a month we're looking at many billions in revenue.
    • fragmede 2y ago
      20-60 million office workers in the US * $20/month = $5-15 billion, but for a specialist AI, companies can charge more. $200/month * 10 million people = 24 billion.
• Aunche 2y ago
  Protein folding is a an application of generative AI that will probably produce trillions of dollars of value in the long term. It was probably impossible for Google to squeeze that sort of money from researchers who use it, but it proves that the technology definitely useful. Another application that is highly underrated is with robots completing complicated tasks.
  • player1234 2y ago
    Can you lend me 100 billion? I can pay you in a year or two or maybe 10 but I will probably have trillions by then.
  • fullshark 2y ago
    How is predicting protein folding GenAI? Seems like traditional machine learning?
    • Aunche 2y ago
      I suppose I'm thinking about transformer architecture rather than strictly GenAI, but the computer science aspects of protein folding and GenAI seem like they overlap significantly.
      • webmaven 2y ago
        People are using these models to generate candidate molecules for specific purposes. According to some estimates I've seen, their hit rate is about 50% instead of 25-33%, and doesn't take two years.
  • throw234234234 2y ago
    This is a case for example I wish AI was targeting. However its more likely they will build more benchmarks and target dev's/SWE's quickly and hard because that's probably what their VC's want them to do. The domains that will generally benefit society - that's more of a maybe they might do later. They just released a benchmark today to try to attempt it (OpenAI).
• rsynnott 2y ago
  I think at this point it's an open question which comes first; the LLM bubble popping, or Ed Zitron exploding from pure indignation.
  • spondylosaurus 2y ago
    I largely agree with Zitron but I think the angry-newsletter bubble he's milking is also going to pop sooner or later, lol. And I can't say I'll be sad when it happens.
• bentt 2y ago
  Look... I am cheap. I get rid of streaming services when my family isn't paying attention to see if they complain. I keep paying $20/mo to OpenAI even though I think Altman is a frightening snake man. The utility that ChatGPT and other LLMs provide is undeniable. Their revenue will tell us how much value people get because nobody's going to spend $20/mo (much less $200/mo) without getting something for it.
• scotty79 2y ago
  I think ChatGPT is rather iPod moment not iPhone moment and development of AI should be benchmarked against hardware companies not software companies. It's early day of AI, in the way, that at some point, it was early day for smartphones when some computing capacity in phones was prevalent and cheap, but better capabilities were super expensive and still not very good.
• tasuki 2y ago
  > If generative AI disappeared tomorrow — assuming you are not somebody who actively builds using it — would your life materially change? Yes. My coding sessions would surely be different. I now have a very fast junior developer who has excellent knowledge of various libraries, though I have to check their code. Write me a function that accepts X and outputs Y. It works great! Yes, the business model of OpenAI et al is probably unsustainable. I couldn't care less. > I Feel Like I'm Going Insane > Everywhere you look, the media is telling you that OpenAI and their ilk are the future, that they're building "advanced artificial intelligence" that can take "human-like actions," but when you look at any of this shit for more than two seconds it's abundantly clear that it absolutely isn't and absolutely can't. Either I'm the dumb one or Ed Zitron is...
• fullshark 2y ago
  A refreshing read, the take down of OpenAI's 300m users is very weak though and the hand waving "I know GenAI has use cases" could be fleshed out. It's a bubble obviously and some useful software will get written, which has happened in every other bubble and will continue to happen. It's just this bubble is so public, rapidly moving, and capital intensive.
  • gmays 2y ago
    The hard thing is that it's both a bubble and not. It's a bubble in the respect that the hype around integrating into existing companies/software is likely often falling flat. It may not be a bubble in that all of the best/useful/valuable use cases of AI are in new software, which have yet to prove themselves in the enterprise. This makes sense because you can't just bolt it onto existing software/organizations and expect it to work because they're built around the way things used to be, similar how when factories first tried to integrate electricity. For example, I'm sure Palantir is doing some good stuff, but I just have doubts about how useful AI can be in the context of existing companies. And their valuation seems insane, which screams bubble, especially since they're an older companies and less 'AI-native' than the newer ones, like the clunky ways Salesforce and Microsoft implement AI. But do I expect startups to continue to emerge that approach problems in AI-native ways that help companies reorganize? Yes, it's just a question about how long it takes these companies to work their way into the enterprise and earn enough credibility to drive organizational change and restructuring. The 'bubble' question is really about whether this latent/potential productivity will be enough to inflate the bubble before it bursts. My money is on yes, but rather than picking a winner at the app layer and trying to win the lottery I'm heavily invested in the boring stuff like chips (NVDA) and those building data centers with low P/Es (back when I bought them), thus a lot of room to grow even conservatively.
• 65 2y ago
  I suppose we're now entering the trough of disillusionment.
• zyngaro 2y ago
  This is bullshit. Gen AI and related technologies are disruptive and will impact and/or create billion dollars industries one way or another.
• ANarrativeApe 2y ago
  "To say an LLM is intelligent is like saying a scanner has an eye for detail"* paulacannon I have a 6 million+ word archive with ChatGPT. It truly is like having an army of interns, each a confident undergrad in a different subject, who have paid attention to every lecture they ever went to, event the one they'd popped acid just before going in. It's right more often than it is wrong, but some of its clangers are almost unbelievable. Yet, having never written a line of code, to build a python application that analyzed election data and applied the results to an interactive map, that gave constituency specific data on hover. It invariable uses the word clarify instead of correct when challenged. Yet it knows that a clarification is refining an answer within the set of the previously proffered answer, and a correction is a revision on an answer outside of the set previously provided. It believes that this is so consistent that, on the balance of probabilities this is coded and not purely as a result of training data. When asked to write an article on this, and include the instances from that conversation where it had incorrectly used the word clarify, it edited the quotes to remove the evidence (probably the most egregious act I've witnessed it perform). I still use ChatGPT, even more so now since DeepSeek got slow, but I watch it like a hawk. I still call it out every time it prevaricates or flat out lies, it still promises to do better, it still, on being challenged, acknowledges that these assurances are dangerous lies to anyone who doesn't know it's lying. But, for me, it is still a highly useful tool. It frequently makes assumptions that would be made by those in a field I am unfamiliar with in a way that allows me to refine arguments. Sharing ChatGPT chats can be a very helpful means of sharing one's thought process. I have it on strict instructions not to create unless specifically told to, to not regurgitate what it already has, to focus on critiquing instead of echoing or praising. Yet it still reckons 70% of its output violates these instructions. But the remaining 30% justifies the time I spend using this remarkable, next generation, automation machine. Because that is what it is. *To say it is intelligent is like saying a scanner has an eye for detail. Yes, a scanner identifies every pixel but and LLM is no more a brain that a scanner is an eye. (And, yes, I know, but this is a line for people who don't know the neurological processing behind sight, which to be fair, is frequently not very logical.) So it is a threat to people who earn money on fiverr writing bits of code or designing logos - hell yes. It is a threat to those who code complex systems or who's designs can add actual digits to market share? hell no. Or at least not for the foreseeable future. Just as the dotcom bubble funded the internet infrastructure that we still use today (just very inefficiently), it is unlikely these trillions will be completely wasted
• AlienRobot 2y ago
  >iPhone fundamentally redefined what a cellphone and a portable computer could be, as did the iPad, creating entirely new consumer and business use cases almost immediately. >So, what exactly has generative AI actually done? Where are the products? No, really, where are they? What's the product you use every day, or week, that uses generative AI, that truly changes your life? If generative AI disappeared tomorrow — assuming you are not somebody who actively builds using it — would your life materially change? I think ChatGPT and similar generative AI did fundamentally redefine what software could be. Everyone rushed to implement generative AI into every software. Even MS Paint has AI now. Before this, the idea that you would have it was unthinkable. If it doesn't make any money, that's a separate issue. >If generative AI disappeared tomorrow — assuming you are not somebody who actively builds using it — would your life materially change? To put it in another way, you could live without the ability to drag and drop, but that doesn't mean it hasn't redefined user interfaces.
  • wut-wut 2y ago
    My concern is when you've implemented it and rely on it and then the company providing the service pulls a "Google" and deprecates the project. I haven't seen that mentioned in any of the comments.
    • AlienRobot 2y ago
      This is the same issue that would happen with any closed source software, and why the push for fully open source or at least "semi" open source models (which provide the weights but not the training data). If you are critically dependent on software that can just disappear for reasons out of your control, you're beholden to its developers. On the flip side I feel that this is the big problem with monetizing AI. AI is already bad enough in that its output is practically always untrusted output, so any customer-facing application of AI requires a second AI to make sure the first AI didn't output anything improper to consumers or even children (because parents are okay with an app that just tells their children randomly generated text, apparently). It would be a little better if you had control over the model. But without a intellectual property rights over the model, what is the AI company even selling? A GUI? So anyone can just copy and paste the model, skip all the training costs, and just sell a react frontend for the model trained for billions of dollars? It feels like you can't make money from training the AI in a way that makes sense for customers, but you can make money from selling the AI that someone else trained by selling access to it for non-technical users.
• highfrequency 2y ago
  Article seems to have 3 main complaints: 1. LLMs are not very useful 2. Companies like OpenAI and Anthropic are losing tons of money 3. There is a lot of hype around them The first seems objectively untrue - lots of people find them useful especially for coding. Not to mention the fact that they get significantly better every year. The second is completely true but it's not clear how much that matters. Our products are being subsidized by VC firms while costs are falling by 3x-10x every year. Seems great to me. There is a lot of hype because hype helps capitalists get rich faster. Annoying, but a small price to pay for useful technology.
• smeeger 2y ago
  heres a quote from the article Altman uses his digital baba yaga as a means to stoke the hearts of weak-handed and weak-hearted narcissists that would sooner shoot a man dead than lose a dollar, even if it means making their product that much worse. the only correction i would offer for the entire article is that instead of saying “shoot a man dead,” it would be more accurate to say “smother a baby with a pillow.”
• kurige 2y ago
  ChatGPT and LLMs have had a significant impact on my wife's life. She's a second language speaker, and having ChatGPT available to draft and proofread professional sounding emails and text messages has drastically increased her self-confidence and ability to communicate with colleagues. I think that's amazing. That's also the only use of LLMs we've found.
  • throwaway_ocr 2y ago
    The downside to doing this is that you'll sound like an LLM. LLM-generated text is very obvious to anyone with basic reading comprehension and once detected will cause some people to summarily dismiss the sender as a bot.
    • trey-jones 2y ago
      I think this can be mitigated by proofreading and changing up a few things.
    • kurige 2y ago
      This is more than acceptable if it allows you to confidently send of an email in less than a minute that would otherwise take you 30 minutes of agony to write and still not be confident about. Also, these aren't cold calls. The recipients aren't critical about how "botty" the email sounds.
  • trey-jones 2y ago
    Two uses for me (as a native English speaker who writes pretty well on my own): 1. Reformatting notes or bits of information into something more formal (something I consider actually counterproductive in a way, since formal is often more verbose, but that's expected in certain contexts...) 2. Sifting through the crap of the internet to answer obscure questions. The Google replacement that has been needed.
  • ktzar 2y ago
    It's helped me incredibly to proof-read a novel I wrote in Spanish and translated myself into English to make it sound more native. I review ever single suggestion an LLM provides (as I would do with a native proof-reader!). I think this type of job suits LLMs perfectly... At the end of the day it's just a statistical NLP tool.
• phlipski 2y ago
  The capex build-out for the gpu's reminds me of the telecom build-out in the late 90's. So many of those companies went bust but they laid a lot of high-speed fiber before they did which we all are enjoying now. I suspect most of these gen-ai companies will go bust in the next couple of years but all that compute power will be repurposed and used in the decade to come...
• light_triad 2y ago
  If you've been in SV long enough, you've seen multiple hype cycles. AI is the latest one. It doesn't mean AI is a con, there's just a tendency to exaggerate and make hyperbolic claims to sell. AI is primarily used to write text and code. Actually integrating it into workflows across markets will take time. A great article that is neither overly pessimistic or optimistic is Benedict Evan's The AI Summer [1]. He argues that there's a lot of excitement with big corporates but their actual adoption is low so far. "an LLM by itself is not a product - it’s a technology that can enable a tool or a feature, and it needs to be unbundled or rebundled into new framings, UX and tools to be become useful. That takes even more time" [1] https://www.ben-evans.com/benedictevans/2024/7/9/the-ai-summer https://www.ben-evans.com/benedictevans/2024/7/9/the-ai-summ...
  • 34679 2y ago
    >It doesn't mean AI is a con, there's just a tendency to exaggerate and make hyperbolic claims to sell. "Con", in this context, is short for confidence. A con-man is a confidence man. "a swindler who exploits the confidence of his victim" It's a con.
    • tim333 2y ago
      You've got to distinguish the tech from the companies and salesmen. Like in the dot com bubble the internet was real and important but a lot of the companies were cons. Likewise here AI is real and important but a lot of the companies are cons.
    • light_triad 2y ago
      Sure you'll find folks that perhaps literally believe that AI is bigger than fire and the wheel, or whatever. Or business leaders that more cynically try to ride the hype wave with their own customers. I think the key here is actual usage and adoption. If early adopters (marketers and coders) keep using the new tools for real work over the long term then it's a positive signal.
  • outworlder 2y ago
    > you've seen multiple hype cycles. AI is the latest one. It doesn't mean AI is a con, there's just a tendency to exaggerate and make hyperbolic claims to sell. The term "AI Winter" dates back from the 80s, and that should tell us something. At every cycle, we have insane hype (remember when "expert systems" would replace doctors?), a lot of investment. Hype fails to catch up to reality, investors get spooked. Nobody talks about that flavor of "AI" for a few years, even though we usually get new and useful tools.
• vergessenmir 2y ago
  I'm not sure what the rush is. Do we have to make it profitable now? 2 years is not a long time. The point has been made elsewhere by other commentators about the dot-com bubble and how long that took for trillion dollar industries to form. It sounds like his gripe with Altman's hype narrative has soley informed his somewhat negative view on LLMs as a whole. I find it interesting that he almost equates OpenAI === LLMs and misses the fact that the hype is not purely industry driven. For instance, the number of machine learning papers in the last year has quite literally doubled. This is also typical of an Americentric view on innovation that we don't report on the quiet revolution happening in education in underdeveloped countries that are a direct result of the accessibility of this unprofitable technology. I don't think we need killer application right now We also forget the internet bubble happend first I think the author is looking at LLMs through the lens of Sam Altman's hype narrative and I wonder why we care so much that
• incorrecthorse 2y ago
  > So, what exactly has generative AI actually done? Where are the products? The product is ChatGPT, actually. If LLMs are a bubble, then you should expect most of OpenAI's revenue to come from its API (which is used by startups which have raised money to do "magic AI stuff", and the bubble would pop when investors would stop giving the money). But according to https://futuresearch.ai/openai-revenue-report https://futuresearch.ai/openai-revenue-report, revenue from the API accounts only for 15%, the other 85% being the different subscriptions offers, including 55% of ChatGTP Plus subscriptions -- that is, _direct consumers_. This doesn't prove that it isn't a bubble (the consumers could realize it's useless and then leave some time later), but it makes it less likely IMO.
  • mvdtnz 2y ago
    What a clown analysis. Sorry, that is not worth the bits it is written in. OpenAI is a privately owned company and does not publish its financials. The sources your link brags about are pathetic beyond belief, > This report draws on a variety of sources, including those not easily found by search engines, e.g.: > * Personal anecdotes of pricing info from sales calls > * A blog that used DNS records to infer which Fortune 500 companies pay for ChatGPT Enterprise > * Transcripts of OpenAI exec interviews > Just as important are the data points FutureSearch rejected when they didn’t corroborate more trustworthy sources. The core assumption made here is the $3.4 billion in ARR that Bloomberg and TheInformation reported Sam Altman said in a staff meeting.
• karaterobot 2y ago
  It's very rare that I can't get through a blog post because I find the argument too disingenuous to tolerate, but that was the case here. There are usually some nuggets of insight even in a tirade, and that may very well be the case here too, but the bad faith arguments came so fast and furious that I couldn't keep going.
• senordevnyc 2y ago
  It's not even worth responding to these "AI is a useless toy!" screeds anymore. Let 'em rant. I'll just keep using that useless toy to build cooler and cooler stuff faster and faster.
• highfrequency 2y ago
  LLMs write code. Quickly. That is a killer app. Performance improves every year, and costs become 3x-10x lower every year for the same level of performance. The difficulty of the code we want it to write does not increase 3x-10x per year. So there is no cost problem in just a couple years. The level of denial and anger about LLMs on HN is astounding to me. Is this just defensiveness from software engineers worried about losing their jobs? An inability to extrapolate cost or performance trends just a couple years forward? Personal criticism against Altman and Musk? What am I missing?
  • echoangle 2y ago
    Extrapolating trends mostly doesn't work like that, it's very possible that the growth will slow down.
• mvdtnz 2y ago
  > The AI bubble means that effectively every single media outlet has been talking about artificial intelligence in the vaguest way, and there's really only been one "product" that they can try that "is AI" — and that product is ChatGPT. What is this guy even talking about now? Zitron has gone so far off the rails.
• jibolash 2y ago
  The possibility that OpenAI, Anthropic or other companies in the space can lose their investors money does not make the technology a "con". As long as they do not try to pass their losses to the tax payers, how is this a problem? If anything, the history of tech has abundant examples of the first movers in a space not capturing the eventual economic value. It is ridiculous to say that generative AI is a con at this point when it is by far the best way to search the internet (in spite of hallucinations).
• outside415 2y ago
  [flagged]
• 1vuio0pswjnm7 2y ago
  Title could be confused for advertising a conference on generative AI
• idamantium 2y ago
  The mismatch between AI’s actual utility and its hype reminded me of Prediction Machines[1], which frames technological change as progressing from point solutions → platform solutions → system solutions. We’re still in the “what the heck is the point solution here” phase, with a lot of anticipation for platform and system-level shifts. There are some point solutions—like coding assistants—that make existing workflows more efficient and higher quality, but they haven’t translated easily to other domains. Platform solutions require completely rethinking workflows holistically, and system solutions demand restructuring everything that depends on those workflows. That’s going to be slow and messy. Including financially messy. The book likens this to the introduction of electricity. Initially, electrification meant new individual machines in factories organized around steam power. Steam power was hard to turn on and off and not at all portable. Actually getting the full benefit of electricity meant redesigning factories around electricity use as-needed (not just when the steam engine was running) and spatially organize around task efficiency (not proximity to the steam energy production). All that was not a quick shift. I very much sympathize with the author's frustration over hype that fails to understand the underlying technology and puts unwarranted faith in a small collection of corporate leaders. But I do think that this technology does have a high degree systems change potential and possibly the momentum to see it through this time. Not that we know how that will play out of which actors or forces will bring it to fruition. It really doesn't feel the same as the other tech crazes of the last two decades. [1] https://www.predictionmachines.ai/ https://www.predictionmachines.ai/
• ianmcnaney 2y ago
  It's not totally useless. I have more productive conversations about my aquarium with copilot than I do with aquarium related subreddits, and the results are about as useful. I treat them as interesting anecdotes worthy of further research.