13 ms·

How Does OpenAI Survive?

151 points by fredski42 2y ago

funfunfunction 2y ago
> generative AI is a product with no mass-market utility. > I am neither an engineer nor an economist. clearly.
- metalliqaz 2y ago
  If I read you correctly, you are implying that the first statement is obviously false. Can you fill me in on the mass-market utility? Because I keep coming to the same conclusion as the author. The "killer app", as far as I can tell, is essentially natural language search. However, the core function (in my opinion) has existed since DuckDuckGo added contextual infoboxes to the right of search results ("knowledge panels"), and the benefit of using natural language has existed since Siri and has never seemed to add much to the experience for me. AI image generators seems to be used mostly by youtube creators and spammers. The main users of AI language generation seem to be spammers and crappy content farms on TikTok. Commercials for AI products ALWAYS lie by speeding up the time it takes for results to arrive, and the most impressive demos always seem to end up as some version of the same useless feature: "what am I looking at right now?" Who needs that? AI-assisted coding also seems to have a similar issue. Demos that supposedly show off the technology never actually use it to create the kind of code that is actually worth money. I'd be happy to be proven wrong here, but I keep looking and I never find that killer app.
  - zebomon 2y ago
    Chatbots in their current form already make excellent tutors and coding partners for many people.
  - Tossrock 2y ago
    The killer app is replacing 80% of white collar employees in 5 to 10 years.
    - moshun 2y ago
      Agreed. Next gen robotics with AI integration will do the same with blue collar workers a few years after that.
      - dgfitz 2y ago
        You’ve clearly never had to troubleshoot wiring issues on a robot.
        fragmede 2y ago
        when the robots can fix themselves, then we're in really in trouble. if humans still have to fix the robots that seems fine, as long as they run for long enough without needing rewiring.
        dgfitz 2y ago
        If I could make a robot that fixes robots I’d have retired years ago. It’s a complicated problem, and apparently very misunderstood.
      - imtringued 2y ago
        Actually, I would expect the robots to get better at blue collar work faster than LLMs at white collar work. The reason is that there are a lot of highly repetitive physical skills for which you can easily build a dataset for and then fine-tune a model. People have built dedicated plastering robots, strawberry picking robots etc. Each robot only really needs to be good at one thing. Almost nobody is making the foolish mistake of building humanoid robots that then tackle the problem exactly the way humans do. The plastering robots spray the plaster, which is much faster.
    - jamilton 2y ago
      Or 5%, right? What's the minimum amount that's "killer", on a societal level and on an industry-specific level? Human transcription might be a good case study.
    - 2y ago
  - muratsu 2y ago
    Agent for X is valuable and lots of startups are trying to build it in some vertical. As these agents evolve, they have the potential threaten incumbents in their own respective vertical. It’s also unclear how we’ll orchestrate all the agents or discover them. None of this is very obvious and it’s very possible to hit a major tech roadblock. But nobody knows.
    - minimaxir 2y ago
      > As these agents evolve That doesn't answer what's happening now. The AI companies can't keep saying "AGI is around the corner!" for much longer.
      - viraptor 2y ago
        No serious company is claiming AGI is around the corner. There's going to be scams like Rabbit, Friend and similar, but there are scams for everything. Agents are evolving though. The coding agents a few months ago were a joke (Devin) and now they're actually usable for basics.
        plasticeagle 2y ago
        Are they? Have you used Devin to do anything though? So far as I understand it, the Devin demo was faked.
        viraptor 2y ago
        That's what I meant - Devin was a joke, I've seen the promo and didn't use it. But I experimented with Plandex recently and it's usable for various small tasks. Not great, but usable if you make the right choices and getting better.
  - meroes 2y ago
    Don’t worry you’re not alone. I’ll believe it when I see it. So far I haven’t seen it. And I work in AI (albeit at a low level). If I can compare it to Google search back in the 90s. There weren’t all these evangelists saying in 5-10 years blah blah blah. We just used it, in our daily lives. I don’t use AI at all except at work. And I couldn’t even tell you what product it’s going toward because I don’t think 99% of employees know. Why we don’t know, who knows!
    - seanhunter 2y ago
      There absolutely were hordes of evangelists touting this or that tech company (including google, redhat, amazon etc as well as pets.com and a bunch of others who didn't survive) saying in 5-10years these were companies would be the biggest thing since sliced bread. In some cases they were right. The VC money is betting on a similar sort of monopolistic dynamic occurring in the AI space. They're not saying that 100s of billions of dollars of value is going to accrue to openAI because of chatGPT they're saying 100s of billions of dollars of value is going to accrue in the space and the most likely outcome is that the vast majority of that is going to be siphoned up by a couple of behemoths. Other than the incumbents (Microsoft, Google) OpenAI seems best positioned at the moment and whoever else creates breakthroughts will probably be acquired anyway just like instagram got bought out by facebook as soon as they got large enough to matter.
      - Dylan16807 2y ago
        > saying in 5-10years these were companies would be the biggest thing since sliced bread It's not about growth, it's that nobody had to make future claims about web search or online ordering being useful to the average person, they already were useful when someone tried them.
        meroes 2y ago
        Yes thank you that's what I was trying to say.
        seanhunter 2y ago
  - devbent 2y ago
    Thousands of call center employees are being replaced right now. You may not even notice the difference, tier 1 support is heavily scripted already. Outbound sales is being automated. Lots of very hum-drum stuff. Ordering room service at a hotel for example. Tons of data entry jobs are now gone. LLMs are already better at humans from a cost perspective for many tasks.
    - tkgally 2y ago
      Translation is another. It's uncertain to what extent experienced professional translators are losing work—I work in the field, and I've heard anecdotal evidence on both sides—but it's clear that LLM-driven machine translation is already producing significant value for millions of people around the world. This might not be apparent to monolingual people in English-speaking countries, but it's a major factor driving the rapid adoption of LLMs here in Japan. If OpenAI's new voice mode turns out to be as versatile and context-aware as promised, it should be equally valuable for interactive spoken interpretation.
    - lmm 2y ago
      There's definitely some value in undercutting minimum-wage outsourced call centres. But enough to justify these valuations? This is stuff that was already being partially automated back in the '80s; I can see the argument that OpenAI is the next Autonomy, but when you're this heavily leveraged an incremental improvement is a failure.
      - devbent 2y ago
        OpenAI is the platform everyone else is building on top of. Think Microsoft in the late 80s through the 90s. If you are charging for the platform, you can let thousands of other businesses try the risky hard to scale stuff and you'll get a cut of everything no matter who wins.
        lmm 2y ago
        Microsoft wasn't taking any risks there though, they were a profitable business selling positive margin projects the whole time - that's more where NVidia is than where OpenAI is.
  - edmundsauto 2y ago
    > what am I looking at right now?" Who needs that? Anyone who is sight impaired, or doesn’t have their glasses on while reading a menu, or looking at a sign in another language. It’s clearly not in final form. In 1978, people couldn’t see the use of home computers. In 1988, most people were saying the same thing about email. In 1998, most people were saying the same thing about the internet. It might not prove out, but evaluating something super early isn’t all that interesting. Let’s see where we are in 2030 at least.
    - XMPPwocky 2y ago
      > It’s clearly not in final form. In 1978, people couldn’t see the use of home computers. In 1988, most people were saying the same thing about email. In 1998, most people were saying the same thing about the internet. Give it a few more years for more people to forget about how hard things like NFTs got pushed with the same sort of arguments- then this'll come off better.
      - plasticeagle 2y ago
        That one technology worked does not automatically mean any other technology will. There is no argument that begins "A worked and so B will too". Also, email is pretty much dead as a technology - it's just spam and password reset emails at this point.
        edmundsauto 2y ago
        I think parent was not saying new tech will succeed, merely there is an extended hangover/negativity due to recent busts. Regarding email - it's probably one of the most used bits of technology in existence, and I bet it has a similar OOM economic impact to something like Excel. Calling it a dead technology is not accurate - so much business is done via email, especially internally at SMB.
    - edzitron 2y ago
      I realize that these are commonly-held tropes, but where is the actual article that says this? There's the famous "the internet isn't a big deal" thing in Newsweek (and funnily enough that piece is extremely prescient in many other ways!), but I don't know if I've seen the kind of hype-busting then. But also...the reason they might have is that email kind of sucked back then. Of course you wouldn't see the promise in something that was clunky and slow and nobody used. This isn't a comparable to LLMs, though, because even someone who found them clunky could see why you'd want to send an email versus sending a letter.
  - hakanderyal 2y ago
    There is a lot of money being poured into figuring this out[0]. My bet is on agents. They work, right now, and it’ll only get better. [0]: https://x.com/omooretweets/status/1760000618557735289 https://x.com/omooretweets/status/1760000618557735289
  - JackYoustra 2y ago
    The killer app is the chatbot itself? Fastest app adoption / scaling ever? Like I think people are looking for an 'and then' to be sold, but it's unclear why that has to be the case.
    - ketzo 2y ago
      Chatbots are, so far, obviously a $1B+/yr business. I think it’s not obvious yet that they go much further beyond that? It’s a lot of money, sure, but it’s not world-transforming stuff.
  - plasticeagle 2y ago
    Ironically enough, if AI powered code generation actually worked, OpenAI would have a business model right there. But it doesn't, and so they don't. What they hope is that other people will somehow make their business model for them - and then they'll sell their technology into that. But AI code generation is garbage, just like AI text generation is. AI generated books, and songs, and poetry etc is just appalling rubbish that nobody wants to read or hear. AI generated art is ugly and generic, and stands out immediately as zero-effort and near-zero cost. Except of course, it cost alot of money to make, but nobody is willing to pay for it and it's so far been bankrolled by VC capital.
    - com2kid 2y ago
      > But AI code generation is garbage, "create an express server that uses CORS to only accept requests from <mydomain> that has 3 async endpoints defined, 2 GET endpoints titled <a, b> and 1 POST enndpoint titled <c>. The POST endpoint should accept JSON, and the GET endpoints will return JSON. Stub out the route handlers, they will be defined in another file. For the POST endpoint parse out the userId from <header field> and also pass it in along with the JSON" "Here is a typescript definition of the JSON being posted to this endpoint, validate all string fields are less than 100 characters long, and that none of the values are null, then write the data to a redis DB at <location> using auth values already loaded up in the environment. Data should be written to <userid/location>" "Now add exception and error handling around this code, cover the following case: Data is invalid - Return an error message to the user with HTTP error code 400, Redis is not accessible - HTTP 500. Also log errors using the <logging library> that has already been imported and initialized up above, and increment an appropriately named counter using the <analytics library> that is also already imported and initialized." If you are getting garbage AI code, you are not using proper tools. If you just go to ChatGPT and ask it for stuff, you won't get very good code (and IMHO GPT4o is much worse at coding). Use a proper editor that prompt engineers code generation (such as Cursor), and LLMs can write some really good code. Can it end to end generate an entire service with just a vague description? No. But it can easily 2x-4x development speed. Heck I've thrown code at GPT4 and asked it to "please look for common concurrency bugs that may have been overlooked in this code" and watched as GPT4 saved me literal hours of debugging. What OpenAI has is a problem monetizing the value their product brings, since the value to each customer is so different. When I'm at home, I'm happy to pay $15 a month in API usage fees to accelerate my coding, but a company should be happy to pay hundreds of dollars per month to accelerate the speed code is written. Figure $100 an hour average cost for a dev on the east or west coast of the USA, if GPT4 saves 10 hours a month (easy!) then OpenAI should be charging at least $200-$500 a seat licenses per month.
- ajkjk 2y ago
  I'm an engineer and I agree, does that help?
- kyledrake 2y ago
  Pontificating on what actual profit will be generated by LLM companies is fair game, but reaching a conclusion that LLMs have no mass market utility is blisteringly insane. I could easily measure the increase in value I alone have had from using them in the tens of thousands of dollars. It's more plausible for me that we will see a notable productivity increase in a lot of sectors of the economy over the next decade. Part of me wonders if this is an additional reason why the Russell 2000 has been spiking lately (investors concluding that there is more money to be made from the general productivity increases in the wider economy than the tech companies providing the LLMs that don't seem to possess any monopolies on the technology), but this is just my speculation.
  - scarface_74 2y ago
    And he admitted he is “neither an engineer nor an economist, nor do I have privileged information”. So why should we listen to him? ChatGPT has saved me a lot of time. Luckily it’s well trained on AWS API’s, tge SDK, CDK, Terraform and Kubernetes. Anything it isn’t trained on, I just give it links to the documentation
  - edzitron 2y ago
    I think you are misunderstanding my point, and perhaps I should've worded it more-precisely" "Mass market utility" here refers to its ability to sell at the scale it would need to substantiate its costs. As it stands, LLMs do not have mass-market utility at the scale that they need to substantiate their costs. It is really that simple. If they did, these companies would be profitable, and they would be having a meaningful effect on productivity, which they are not. See page 4 of this report from Daron Acemoglu of MIT: https://www.goldmansachs.com/images/migrated/insights/pages/gs-research/gen-ai--too-much-spend,-too-little-benefit-/TOM_AI%202.0_ForRedaction.pdf https://www.goldmansachs.com/images/migrated/insights/pages/...
ethbr1 2y ago
> Nobody has ever raised the amount of money it will need, nor has a piece of technology required such an incredible financial and systemic force — such as rebuilding the American power grid — to survive, let alone prove itself as a technology worthy of such investment. AT&T.
- downrightmike 2y ago
  Via pure monopoly power
  - tazu 2y ago
    Isn't that sama's plan with "safety regulation"?
    - downrightmike 2y ago
      No because even Nortel in canada was a required to buy at&t made phones
  - ethbr1 2y ago
    AT&T didn't have a monopoly when it started. It just burned a ridiculous amount of money stringing lines.
    - edzitron 2y ago
      It also got broken up! https://en.wikipedia.org/wiki/Breakup_of_the_Bell_System https://en.wikipedia.org/wiki/Breakup_of_the_Bell_System
- j_timberlake 2y ago
  The space race cost hundreds of billions in today's dollars, and AI could do a lot more for/to humanity than put a flag on the moon. And I'm guessing Uncle Sam will want control of these AI companies anyway if AI starts looking even a little powerful/threatening.
sweettea 2y ago
A well reasoned article that fundamentally downplays both the pace of innovation and the exponential increase in capabilities per dollar happening over time. AI is rapidly accelerating its improvement rate, and I do believe its capabilities will continue growing exponentially. In particular, GPT-2 to GPT-4 spans an increase from 'well read toddler' to 'average high school student' in just a few years, while simultaneously the computational cost of training less capable models goes down similarly. Also worth noting: the article claims Stripe, another huge money raiser, had an obviously useful product. gdb, sometime-CTO of stripe and its fourth employee, is now president of OpenAI. And, most of all, the author doesn't remember how nonobvious Stripe's utility was in its early days, even in the tech scene: there were established ways to take people's money and it wasn't clear why Stripe had an offering worth switching to. For an alternate take, I think https://situational-awareness.ai https://situational-awareness.ai provides a well reasoned argument for the current status of AI innovation and growth rate, and addresses all of the points here on a general (though not OpenAI specific) way.
- ThereIsNoWorry 2y ago
  That's a lot of unproven assumptions based on the fact that LLMs are just correlation printers.
- joshstrange 2y ago
  > And, most of all, the author doesn't remember how nonobvious Stripe's utility was in its early days, even in the tech scene: there were established ways to take people's money and it wasn't clear why Stripe had an offering worth switching to. I think you are misremembering. Stripe was a _big deal_. They had a curl call on their home page for a while for how to take a payment IIRC. It was like how Twilio opened the door for anyone to send SMS, Stripe made it stupid-easy to handle payments online. Nothing else at the time compared in terms of simplicity and clearly defined fees.
- vrighter 2y ago
  ai is very rapidly hitting a plateau, both because they are just glorified markov chains, and them running out of data anyway
- 2y ago
Arainach 2y ago
>Have a significant technological breakthrough such that it reduces the costs of building and operating GPT — or whatever model that succeeds it — by a factor of thousands of percent. What does reducing costs by "a factor of thousands of percent" mean? It starts printing money? It costs 1/10 as much?
cuddlyogre 2y ago
I was assured that being skeptical about offloading the use of my brain to a third party that might not always be there was being a luddite.
xyz-t 2y ago
[redacted]
- simonw 2y ago
  What kind of agents?
  - toomuchtodo 2y ago
    https://www.freethink.com/robots-ai/ai-agents-openai https://www.freethink.com/robots-ai/ai-agents-openai https://www.theinformation.com/articles/openai-shifts-ai-battleground-to-software-that-operates-devices-automates-tasks https://www.theinformation.com/articles/openai-shifts-ai-bat... (paywall) https://www.technologyreview.com/2024/05/01/1091979/sam-altman-says-helpful-agents-are-poised-to-become-ais-killer-function/ https://www.technologyreview.com/2024/05/01/1091979/sam-altm...
  - viraptor 2y ago
    https://aibusiness.com/nlp/openai-is-developing-ai-agents https://aibusiness.com/nlp/openai-is-developing-ai-agents probably. But I'm not sure how much they need to innovate on that front. There's good agents progress happening everywhere around already. OpenAI could provide some options to make it faster/cheaper, and running the workflow internally would make it faster, but... doesn't feel necessary.
    - simonw 2y ago
      > AI agents differ from robotic process automation (RPA), which still needs developers to manually code steps needed to complete a task, Luan said. OK, so it's robotic process automation then (aka screen scraping / UI automation), just without the hand-written automation code. My frustration with the term "agents" is that it can mean a lot of different things - but people always seem to assume that their own personal definition is the same that everyone else is using.
- FridgeSeal 2y ago
  > OpenAI is currently working on the next step: agents and planning. They are close. Other competitors will shortly follow. Their stocks will rise to unprecedented levels. You have been warned. Any day now everyone will adopt bitcoin and the value will skyrocket and we’ll all be exceedingly rich, HODL, gl, wgtm, to the moon. Not saying they’re not working on stuff, but that’s what you sound like. OpenAI is amazing at generating hype, but the competitors are catching up, or outpacing them, and OpenAI source models are never far behind.
JohnMakin 2y ago
Will always give an upvote to ed zitron, who has a very anti tech/anti AI tilt but a pretty reasonable podcast called “better offline” I’ve quite been enjoying.
mxwsn 2y ago
This article is timely and pairs well with Sequoia's $600B question: https://www.sequoiacap.com/article/ais-600b-question/ https://www.sequoiacap.com/article/ais-600b-question/ calculated simply from NVidia run rate revenue, which is the cost that genAI companies are paying. Where's the profit? Meta's open source LLM stance makes things more spicy, making it challenging for anyone generate differentiated and lasting profit in the LLM space. At the current pace, the LLM bubble is poised to pop in a year or two - negative net revenue can't keep growing forever - barring a transformative, next-generation capability from closed-source AI companies that Meta can't replicate. All eyes on GPT-5.
- lostmsu 2y ago
  I just got a bit of data that hints that at least one of the assumptions in this blog post is false. The post says: > The supply shortage has subsided: Late 2023 was the peak of the GPU supply shortage. Startups were calling VCs, calling anyone that would talk to them, asking for help getting access to GPUs. Today, that concern has been almost entirely eliminated. For most people I speak with, it’s relatively easy to get GPUs now with reasonable lead times. But a couple of days ago I heard from a startup founder that the usual cloud credits (~$100k in cloud compute) that AWS provides to vetted startups that passed some milestones are recently barred from being used on GPU-powered instances.
benreesman 2y ago
Maybe GPT-5 or Claude 4 comes out tomorrow and pays down all the IOUs these people are operating on. As of today all of the evidence indicates the LLM paradigm is saturated. Why all the hand-wringing about hypotheticals? As of today this stuff is a failed experiment. Altman or Amodei coming up with the goods is a tail X-risk.
- edzitron 2y ago
  See, that's the thing. This COULD happen. I do not think it will, but the piece is written not to say "this is 100% not gonna happen," but "I am unsure how it's possible, and if it does not happen, the consequences could be dire." Hypotheses and hypotheticals are useful tools when writing about something big and messy. Instead of me saying - as I have before - that I believe generative AI is a complete dead end and thus OpenAI is in a really bad way - I took great pains to explain the terms under which they WOULD succeed - how difficult success might be, how much money it would take and how many factors would have to go their way. If OpenAI pulls it off, it'd be really remarkable. Truly historic! But if they don't, they are in deep, deep doo doo.
why_only_15 2y ago
If you believe this article, I would be happy to bet up to $10,000 that OpenAI will not collapse in the next 24 months. We could operationalize this by saying that OpenAI will employ at least as many people (or pay at least as much in salaries) in 24 months as it does now. The author of the article refused to take this bet when it was offered to him several times https://x.com/JeffLadish/status/1817999232105627722 https://x.com/JeffLadish/status/1817999232105627722.
- asp_hornet 2y ago
  so we should only listen to the hypotheses of gamblers? The author shouldnt even feel the need to acknowledge the bet. So petty
  - why_only_15 2y ago
    If you are making predictions about the world, you should be willing to put money on those predictions so that you are grounded to making predictions that you actually believe in as opposed to just blathering.
    - kjrfghslkdjfl 2y ago
      This is too reductionist. There's a lot of reasons why someone could turn down that bet, other than "he's just blathering". Maybe he's very confidently down on OpenAI but 10k is a lot of money for him, and is being offered a bet by someone who's a noise generator but who's very well off, for whom 10k means nothing. If you think these people don't exist, you should visit WSB. I evaluate arguments on their own merit, not based on extraneous data like appeal to authority or what bets the author makes.
    - sifar 2y ago
      Predictions can go wrong for any number of reasons beyond one's thesis. One can be right about what but wrong about when. To bet money on that just to satisfy ones (and others) ego is foolish. To recognize that is wisdom.
fragmede 2y ago
I think the thing that nobody saw coming was Facebook coming out with their own, that they spent hundreds millions creating, and then releasing the model of it, with a generous license. If someone had come out of a copy of Google in 2000, we'd be looking at a much different picture.
pseudosavant 2y ago
They say no company has ever raised the kind of money OpenAI has, like they are at some kind of ceiling. Microsoft’s market cap, which is only equity, not including bonds (only $42B), is over $3T.
- tptacek 2y ago
  Right, but Microsoft has been profitable for decades.
  - pseudosavant 2y ago
    And Microsoft was once a smaller company. Google was too. Who is to say OpenAI can't become big tech company like them? Also, I'd like to point out that the total investment into AT&T, which they position as untenable, is less than AT&T has spent on their network investments every single year for at least the last 10 years. It isn't like companies don't invest billions of dollars into things.
- edzitron 2y ago
  Sure, but the argument here isn't that it's impossible. Just that to do what they need to do, they need to do something that really hasn't been done before. I do not THINK Microsoft will put that much money into it. They could! It isn't impossible. But it would be totally unprecedented.
undergod 2y ago
No genius employees = mediocre outcome. Ilya left. Andrej left. Much of the talent at the top of the pyramid left. A company is literally its people.
programjames 2y ago
It's not that these AI companies need to raise $100 billion, it's that they can. They could go slower, working on custom hardware or better architectures to get 1000x cheaper training, but their models would only be as good as the ones from 1-2 years ago. Because foundation models are a winner-takes-all game, any individual company needs to spend as much as they can get, even if it means most investors will lose big. There are many companies working on hardware gains (e.g. Lightmatter, Groq), but they're not competing in the foundation model business.
coding123 2y ago
This whole thing reads like: google doesn't have a business model because anyone can do search. Well, how many years later, yeah the writers saying Google was DOA are actually DOA.
- edzitron 2y ago
  I'm afraid this isn't an accurate comparison. 1. I do not know of any article that said that Google was "DOA" or "done" as a result of the choice of a search engine as a business model. In fact, search engines were an already-established industry at the time. If I'm wrong, I'd love to read it, as I imagine it's a fascinating historical document - even if it was horribly wrong! 2. OpenAI's business model and Google Search's business models are totally different. Apples and oranges. The way that OpenAI monetizes, the technology it uses to both deliver a service AND monetize it, the technology stack, the scaling, even the tech they acquire to build it, just totally different. Again, if you can find an article that had someone in the 90s or 2000s saying "Google is DOA! Search is stupid!" then I'd really really love to read it, genuinely.
prng2021 2y ago
This is a nonsensical article to me. "I ultimately believe that OpenAI in its current form is untenable." Followed by a bunch of reasons why. Later they write: "What I am not saying is that OpenAI will for sure collapse, or that generative AI will definitively fail" What? Didn't they just explain 100 different reasons why they think think OpenAI will fail? There was also this: "To be clear, this piece is focused on OpenAI rather than Generative AI as a technology — though I believe OpenAI's continued existence is necessary to keep companies interested/invested in the industry at all." To be clear? So they are trying to separate OpenAI from gen AI. Then they throw in a hyphen and say, oh but without OpenAI, companies would stop spending time and money on gen AI. Ok, thank you for the..clarification. I stopped reading after that.
- deleted 2y ago
  [deleted]
jumploops 2y ago
> generative AI is a product with no mass-market utility Citation? LLMs bring the cost of writing software close to $0. We can finally live in a world of truly bespoke code. I, for one, welcome back the web of the early 2000s.
- edzitron 2y ago
  Hi! I'm afraid you've made an assumption that isn't true. LLMs do not "bring the cost of writing software close to $0" on a number of levels. 1. The code is not 100% reliable, meaning it requires human oversight, and human beings cost money. 2. LLMs themselves are not cheap, nor profitable. I am comfortable humoring the idea that someone could run their own models - something which is beginning to happen - to write code. I think that's really cool, but I am also not sure how good said code will be or how practical doing so will be. Right now, Microsoft is effectively subsidizing the cost of Github Copilot, though they appear to have produced quite a lot of revenue from it. https://www.benzinga.com/news/24/07/40061358/satya-nadella-says-microsofts-copilot-drives-40-of-githubs-revenue-growth-we-are-also-enabling-anyon https://www.benzinga.com/news/24/07/40061358/satya-nadella-s... However, it seems that Github was not profitable before (https://news.ycombinator.com/item?id=17224136 https://news.ycombinator.com/item?id=17224136) and I would argue isn't profitable now. It's hard to tell, because Microsoft blends their costs into other business lines.
  - jumploops 2y ago
    > Hi! I'm afraid you've made an assumption that isn't true. Citation? Your concerns are certainly valid, but the LLMs are getting smaller, faster, and cheaper to run every day. Now, I also agree that you still need someone "programming" -- in the sense that they're telling a computer what to do, but they no longer need to "code" in the traditional sense (curly braces and semicolons). We're actively seeing non-engineers build useful software for themselves, just with a $20/month subscription to ChatGPT/Claude. Times are changing, you no longer need a 6 figure engineer to build your one-off tool.
    - edzitron 2y ago
comp_throw7 2y ago
> Have a significant technological breakthrough such that it reduces the costs of building and operating GPT — or whatever model that succeeds it — by a factor of thousands of percent. Like they already did in the last 2 years? > Have such a significant technological breakthrough that GPT is able to take on entirely unseen new use cases, ones that are not currently possible or hypothesized as possible by any artificial intelligence researchers. Huh, what are these use-cases which no AI researcher thinks AI is capable of solving? Does the author not realize that many employees at the leading AI labs (including OpenAI) are explicitly trying to build ASI? I am so confused???????? > Have these use cases be ones that are capable of both creating new jobs and entirely automating existing ones in such a way that it will validate the massive capital expenditures and infrastructural investment necessary to continue. Why would they have to create new jobs? They just have to be good enough that OpenAI can charge enough money for them to be in the green. OpenAI already has a $3.4 billion ARR! Most of that is _not_ enterprise sales.
- fragmede 2y ago
  "No AI researcher" is an impossible set of people to satisfy, so this doesn't count, but there's the AIMO contest with a $5m prize for creating an AI that can solve its problems. https://aimoprize.com/ https://aimoprize.com/
deleted 2y ago
[deleted]
tedsanders 2y ago
Small correction: "GPT-4o Mini (OpenAI's "cheaper" model) already beaten in price by Anthropic's Claude Haiku model" GPT-4o Mini is presently cheaper than Claude 3 Haiku.
linotype 2y ago
> generative AI is a product with no mass-market utility - at least on the scale of truly revolutionary movements This line is absurd. I use it constantly. 4o reads my code and generates documentation and type annotations. It generates boilerplate code. It generates logos for projects. I review all of its outputs code wise and make the odd correction here or there. I use it to check over documents before I send them. It’s replaced Stack Overflow entirely in my workflow. I’m curious as to what’s above the author’s line for revolutionary.
- plasticeagle 2y ago
  The fascinating thing with arguments like this is how they entirely ignore that OpenAI trained the tool you're using with Stack Overflow. And so if what you're suggesting is that AI tools will replace SO, then as soon as it does the AI is dead in the water. Who will continue to feed it new information? The answer is, nobody will. And instead of having a community driven knowledge base, you'll have a bankrupt corporation and nowhere to turn to when you discover that you can't write code anymore. None of the tools can exist without stealing the net sum of human knowledge - insofar as that is represented by the contents of the internet - for corporate profit. If what the AI proponents claim comes true, that source of knowledge will cease to exist. And what then?
  - linotype 2y ago
    > And instead of having a community driven knowledge base, you'll have a bankrupt corporation and nowhere to turn to when you discover that you can't write code anymore. I still write a lot of code without needing to use an LLM. It’s just a tool that helps me be more productive. I don’t see how what is doing is any different than Google just displaying the answer instead of links to the answer.
  - jononor 2y ago
    The AI does not loose its utility once it has replaced SO. Further improvements would need to come from other sources than more "free" text data though. There are several avenues for this: A) better learning efficiency - it is known that models are not samples efficient now B) pay people to create more data at large scale - already happening at the big LLM companies (though maybe less do for code right now) C) learn from the prompting interactions that customers - extremely desirable, as people would effectively pay you to improve your model. Companies are gonna keep that close to their chest D) multi-modal learning and transfer between modalities E) Self-learning, where ML model iteratively improved itself. Analogous to AlphaGo, GANs etc. This is the holy grail, but also possibly the hardest. Code has the benefit of being formal languages with available verifiers, which should be useful here. F) Specific go code: Using functional feedback, not just textual. For example the large amount of unit tests available on GitHub So I believe there are many avenues for further improvement. I still think it will be very hard though, and until we hit the next breakthrough, will be very resource intensive and possibly quite slow going.
JSDevOps 2y ago
Maybe they pivot to blockchain…. lol
Animats 2y ago
This question can be asked about several "unicorns" that need huge inputs of capital to keep going. Only the era of zero interest rates made them work. WeWork went bankrupt. Uber briefly made money but is losing it again, and is nowhere near paying back its investors. Tesla has become a major luxury car company, and is somewhat profitable, but the stock is way overpriced for a car company. Everybody now makes electric cars, so this is a low-margin business. (Reuters: "Tesla's bleak margins sink shares as Musk hypes everything but cars.") OpenAI, as a business, is assuming both that LLM-type AI will get much better very fast, and that everybody else won't be able to do what they do. It's unlikely that both of those assumptions hold. Look at autonomous vehicles. First tech demos (CMU) in the 1980s. First reasonably decent demos (DARPA Grand Challenge) in the 2000s. First successful deployment in the 2020s (Waymo, maybe Cruise and Zoox). Still not profitable. 40 years from first demos to deployment, probably 50 to profitability. It's entirely possible that OpenAI's business will look like that. Their burn rate is way too high to sustain for that long. Often it takes that long, even when the basics have been figured out. Xerography was first demoed in the late 1930s. The demo machine used to be in the lobby at Xerox PARC. Profitability came in the 1960s. By the late 1970s, everybody had the technology, and it was low-margin. Electronic digital computing goes back to IBM's 1940s pre-WWII electronic multiplier experiments, but didn't come down from insanely expensive price levels until the 1980s. Memory was a million dollars a megabyte as late as the mid-1970s. Color television was first demoed in 1928, and the first color CRT was developed in the 1940s. But mainstream adoption didn't come until 1966-1967.
- FormerBandmate 2y ago
  All of Uber's investors made money, their market cap is $124 billion. Terrible ROI but higher than all of their rounds
jsnell 2y ago
> However, I do have the ability to read publicly-available data, Maybe, but based on the egregious errors the author has made in previous articles, they probably don't have the ability to understand or reason about any of the data they read. Also note that despite what's implied by this statement, most of this article is not sourced, it's just the opinions of the author who admits they have no qualifications. I didn't read the entire gish gallop, but spot-checked a few paragraphs here and there. It's just the kind of innumerate tripe that you should expect from Zitron based on their past performance. > Have a significant technological breakthrough such that it reduces the costs of building and operating GPT — or whatever model that succeeds it — by a factor of thousands of percent. You can't reduce the cost of anything by more than 100%. At that point it's free. But let's consider the author's own numbers: $4B in revenue, $4B in serving costs, $3B in training costs, $1.5B in payroll. To break even at the current revenue, OpenAI need to cut their serving costs and training costs by about 66% ($1.3B+$1B+$1.5B<$4B), not by "thousands of percent". > As a result, OpenAI's revenue might climb, but it's likely going to climb by reducing the cost of its services rather than its own operating costs. ... Sorry, what? Reducing operating costs does not increase revenue. And I don't know how the author thinks that reducing cost of services would not reduce operating costs. > OpenAI's only real options are to reduce costs or the price of its offerings. It has not succeeded in reducing costs so far, and reducing prices would only increase costs. Reducing prices does not increase costs. > I see no signs that the transformer-based architecture can do significantly more than it currently does. So, here's a prime example of the author basing the "analysis" on them personally "seeing no signs" of something they have no expertise to evaluate. There's no source for this claim, and it's pretty crucial for their conclusions that transformers have hit a wall. > While there may be ways to reduce the costs of transformer-based models, the level of cost-reduction would be unprecedented, But for a given quality of model, haven't the inference costs already gone down by like 90% this year? > particularly from companies like Google, which saw its emissions increase by 48% in the last five years thanks to AI. It should be pretty obvious to somebody who can read publicly available data that all of the increase over 5 years can't be attributed to AI.
- edzitron 2y ago
  Hi! :) It appears you have some issues with my article, and I'm happy to provide some help. "Egregious errors in previous articles" is not a valid argument against current arguments, nor do I agree there were those errors. Nevertheless, we're discussing one particular article today! "I didn't read the entire gish gallop, but spot-checked a few paragraphs here and there. It's just the kind of innumerate tripe that you should expect from Zitron based on their past performance." Well that's not very nice! It also means that your argument is made on incomplete data. "... Sorry, what? Reducing operating costs does not increase revenue. And I don't know how the author thinks that reducing cost of services would not reduce operating costs." I'm afraid you misread what I said, likely because you (and I quote) "spot-checked a few paragraphs." One of the problems OpenAI has is that their cost of revenue - and we don't know it to be exact - is extremely high, higher than the revenue they're actually gaining, otherwise known as an "operating loss." As a result, even if they increase revenue, they'll actually lose more money. On top of that, the argument I was making is that if there's a race to the bottom (one that's already started), they will have to cut costs, making them less money even if they get more customers. "Reducing prices does not increase costs." Does reducing prices reduce operating expenses? Because if it doesn't, it actually does increase costs, because you're taking home less cash for the same cost. It could be that 4oMini is somehow more efficient - i can find no evidence that that's the case, and if it exists, I will happily update my article. "So, here's a prime example of the author basing the "analysis" on them personally "seeing no signs" of something they have no expertise to evaluate. There's no source for this claim, and it's pretty crucial for their conclusions that transformers have hit a wall." I can find no examples of radically-different functionality in GPT or other mass-market transformer-based models. In the event I am wrong, I would be fascinated to read about them, but I would need to understand A) how these functionalities are different and B) how they can be productized. After that, I'd need to understand how this would be profitable, and in turn how this would scale into something truly world-changing. "But for a given quality of model, haven't the inference costs already gone down by like 90% this year?" Have they? "It should be pretty obvious to somebody who can read publicly available data that all of the increase over 5 years can't be attributed to AI." I too read publicly-available data, and my source in this case is "Google." Forgive the messy copy-paste. https://www.gstatic.com/gumdrop/sustainability/google-2024-environmental-report.pdf https://www.gstatic.com/gumdrop/sustainability/google-2024-e... In 2023, our total GHG emissions were 14.3 million tCO2e, representing a 13% year-overyear increase and a 48% increase compared to our 2019 target base year. This result was primarily due to increases in data center energy consumption and supply chain emissions. As we further integrate AI into our products, reducing emissions may be challenging due to increasing energy demands from the greater intensity of AI compute, and the emissions associated with the expected increases in our technical infrastructure investment.
jaygray0919 2y ago
Scott Galloway made his bones with similar WeWork analysis. Once Galloway exposed the non-sustainable WeWork economics, others picked up his work and added their own spin. While WeWork would have imploded without the Galloway analysis, Scott's articles were the tipping point.
deepnotderp 2y ago
GPT-4 could’ve written this article better- hey there’s an use case right there!
dekhn 2y ago
OpenAI will survive by being absorbed into Microsoft as a capability- OpenAI employees will be MSFT badged, working under an MSFT SVP, to add functionality to existing products.
tim333 2y ago
To comment a little on the economics: OpenAI has raised $11.3bn (source the article) Since partnering with Microsoft in 2019, Microsoft's valuation has gone from $0.7tn to $3.1bn, or an increase of $2.4tn, a lot of that on AI enthusiasm. Microsoft can sell some shares to fund OpenAI, 2.4tn being about 200x what they've put in. Sure the market bubble will pop at some stage but not by 200x. I'm skeptical of the they can't survive argument. Also I recall in the early days of Facebook, Google and Amazon people saying they lose money each year, the first two didn't have a monetization model, how will they get by? But of course they ended up some of the world's most profitable companies. With AI also you have to think a few years down the road when ASI's output may exceed the current global GDP ($100tn or so).

151 points by fredski42 2y ago

funfunfunction 2y ago

> generative AI is a product with no mass-market utility. > I am neither an engineer nor an economist. clearly.

metalliqaz 2y ago
If I read you correctly, you are implying that the first statement is obviously false. Can you fill me in on the mass-market utility? Because I keep coming to the same conclusion as the author. The "killer app", as far as I can tell, is essentially natural language search. However, the core function (in my opinion) has existed since DuckDuckGo added contextual infoboxes to the right of search results ("knowledge panels"), and the benefit of using natural language has existed since Siri and has never seemed to add much to the experience for me. AI image generators seems to be used mostly by youtube creators and spammers. The main users of AI language generation seem to be spammers and crappy content farms on TikTok. Commercials for AI products ALWAYS lie by speeding up the time it takes for results to arrive, and the most impressive demos always seem to end up as some version of the same useless feature: "what am I looking at right now?" Who needs that? AI-assisted coding also seems to have a similar issue. Demos that supposedly show off the technology never actually use it to create the kind of code that is actually worth money. I'd be happy to be proven wrong here, but I keep looking and I never find that killer app.
- zebomon 2y ago
  Chatbots in their current form already make excellent tutors and coding partners for many people.
- Tossrock 2y ago
  The killer app is replacing 80% of white collar employees in 5 to 10 years.
  - moshun 2y ago
    Agreed. Next gen robotics with AI integration will do the same with blue collar workers a few years after that.
    - dgfitz 2y ago
      You’ve clearly never had to troubleshoot wiring issues on a robot.
      - fragmede 2y ago
        when the robots can fix themselves, then we're in really in trouble. if humans still have to fix the robots that seems fine, as long as they run for long enough without needing rewiring.
        dgfitz 2y ago
        If I could make a robot that fixes robots I’d have retired years ago. It’s a complicated problem, and apparently very misunderstood.
    - imtringued 2y ago
      Actually, I would expect the robots to get better at blue collar work faster than LLMs at white collar work. The reason is that there are a lot of highly repetitive physical skills for which you can easily build a dataset for and then fine-tune a model. People have built dedicated plastering robots, strawberry picking robots etc. Each robot only really needs to be good at one thing. Almost nobody is making the foolish mistake of building humanoid robots that then tackle the problem exactly the way humans do. The plastering robots spray the plaster, which is much faster.
  - jamilton 2y ago
    Or 5%, right? What's the minimum amount that's "killer", on a societal level and on an industry-specific level? Human transcription might be a good case study.
  - 2y ago
- muratsu 2y ago
  Agent for X is valuable and lots of startups are trying to build it in some vertical. As these agents evolve, they have the potential threaten incumbents in their own respective vertical. It’s also unclear how we’ll orchestrate all the agents or discover them. None of this is very obvious and it’s very possible to hit a major tech roadblock. But nobody knows.
  - minimaxir 2y ago
    > As these agents evolve That doesn't answer what's happening now. The AI companies can't keep saying "AGI is around the corner!" for much longer.
    - viraptor 2y ago
      No serious company is claiming AGI is around the corner. There's going to be scams like Rabbit, Friend and similar, but there are scams for everything. Agents are evolving though. The coding agents a few months ago were a joke (Devin) and now they're actually usable for basics.
      - plasticeagle 2y ago
        Are they? Have you used Devin to do anything though? So far as I understand it, the Devin demo was faked.
        viraptor 2y ago
        That's what I meant - Devin was a joke, I've seen the promo and didn't use it. But I experimented with Plandex recently and it's usable for various small tasks. Not great, but usable if you make the right choices and getting better.
- meroes 2y ago
  Don’t worry you’re not alone. I’ll believe it when I see it. So far I haven’t seen it. And I work in AI (albeit at a low level). If I can compare it to Google search back in the 90s. There weren’t all these evangelists saying in 5-10 years blah blah blah. We just used it, in our daily lives. I don’t use AI at all except at work. And I couldn’t even tell you what product it’s going toward because I don’t think 99% of employees know. Why we don’t know, who knows!
  - seanhunter 2y ago
    There absolutely were hordes of evangelists touting this or that tech company (including google, redhat, amazon etc as well as pets.com and a bunch of others who didn't survive) saying in 5-10years these were companies would be the biggest thing since sliced bread. In some cases they were right. The VC money is betting on a similar sort of monopolistic dynamic occurring in the AI space. They're not saying that 100s of billions of dollars of value is going to accrue to openAI because of chatGPT they're saying 100s of billions of dollars of value is going to accrue in the space and the most likely outcome is that the vast majority of that is going to be siphoned up by a couple of behemoths. Other than the incumbents (Microsoft, Google) OpenAI seems best positioned at the moment and whoever else creates breakthroughts will probably be acquired anyway just like instagram got bought out by facebook as soon as they got large enough to matter.
    - Dylan16807 2y ago
      > saying in 5-10years these were companies would be the biggest thing since sliced bread It's not about growth, it's that nobody had to make future claims about web search or online ordering being useful to the average person, they already were useful when someone tried them.
      - meroes 2y ago
        Yes thank you that's what I was trying to say.
      - seanhunter 2y ago
- devbent 2y ago
  Thousands of call center employees are being replaced right now. You may not even notice the difference, tier 1 support is heavily scripted already. Outbound sales is being automated. Lots of very hum-drum stuff. Ordering room service at a hotel for example. Tons of data entry jobs are now gone. LLMs are already better at humans from a cost perspective for many tasks.
  - tkgally 2y ago
    Translation is another. It's uncertain to what extent experienced professional translators are losing work—I work in the field, and I've heard anecdotal evidence on both sides—but it's clear that LLM-driven machine translation is already producing significant value for millions of people around the world. This might not be apparent to monolingual people in English-speaking countries, but it's a major factor driving the rapid adoption of LLMs here in Japan. If OpenAI's new voice mode turns out to be as versatile and context-aware as promised, it should be equally valuable for interactive spoken interpretation.
  - lmm 2y ago
    There's definitely some value in undercutting minimum-wage outsourced call centres. But enough to justify these valuations? This is stuff that was already being partially automated back in the '80s; I can see the argument that OpenAI is the next Autonomy, but when you're this heavily leveraged an incremental improvement is a failure.
    - devbent 2y ago
      OpenAI is the platform everyone else is building on top of. Think Microsoft in the late 80s through the 90s. If you are charging for the platform, you can let thousands of other businesses try the risky hard to scale stuff and you'll get a cut of everything no matter who wins.
      - lmm 2y ago
        Microsoft wasn't taking any risks there though, they were a profitable business selling positive margin projects the whole time - that's more where NVidia is than where OpenAI is.
- edmundsauto 2y ago
  > what am I looking at right now?" Who needs that? Anyone who is sight impaired, or doesn’t have their glasses on while reading a menu, or looking at a sign in another language. It’s clearly not in final form. In 1978, people couldn’t see the use of home computers. In 1988, most people were saying the same thing about email. In 1998, most people were saying the same thing about the internet. It might not prove out, but evaluating something super early isn’t all that interesting. Let’s see where we are in 2030 at least.
  - XMPPwocky 2y ago
    > It’s clearly not in final form. In 1978, people couldn’t see the use of home computers. In 1988, most people were saying the same thing about email. In 1998, most people were saying the same thing about the internet. Give it a few more years for more people to forget about how hard things like NFTs got pushed with the same sort of arguments- then this'll come off better.
    - plasticeagle 2y ago
      That one technology worked does not automatically mean any other technology will. There is no argument that begins "A worked and so B will too". Also, email is pretty much dead as a technology - it's just spam and password reset emails at this point.
      - edmundsauto 2y ago
        I think parent was not saying new tech will succeed, merely there is an extended hangover/negativity due to recent busts. Regarding email - it's probably one of the most used bits of technology in existence, and I bet it has a similar OOM economic impact to something like Excel. Calling it a dead technology is not accurate - so much business is done via email, especially internally at SMB.
  - edzitron 2y ago
    I realize that these are commonly-held tropes, but where is the actual article that says this? There's the famous "the internet isn't a big deal" thing in Newsweek (and funnily enough that piece is extremely prescient in many other ways!), but I don't know if I've seen the kind of hype-busting then. But also...the reason they might have is that email kind of sucked back then. Of course you wouldn't see the promise in something that was clunky and slow and nobody used. This isn't a comparable to LLMs, though, because even someone who found them clunky could see why you'd want to send an email versus sending a letter.
- hakanderyal 2y ago
  There is a lot of money being poured into figuring this out[0]. My bet is on agents. They work, right now, and it’ll only get better. [0]: https://x.com/omooretweets/status/1760000618557735289 https://x.com/omooretweets/status/1760000618557735289
- JackYoustra 2y ago
  The killer app is the chatbot itself? Fastest app adoption / scaling ever? Like I think people are looking for an 'and then' to be sold, but it's unclear why that has to be the case.
  - ketzo 2y ago
    Chatbots are, so far, obviously a $1B+/yr business. I think it’s not obvious yet that they go much further beyond that? It’s a lot of money, sure, but it’s not world-transforming stuff.
- plasticeagle 2y ago
  Ironically enough, if AI powered code generation actually worked, OpenAI would have a business model right there. But it doesn't, and so they don't. What they hope is that other people will somehow make their business model for them - and then they'll sell their technology into that. But AI code generation is garbage, just like AI text generation is. AI generated books, and songs, and poetry etc is just appalling rubbish that nobody wants to read or hear. AI generated art is ugly and generic, and stands out immediately as zero-effort and near-zero cost. Except of course, it cost alot of money to make, but nobody is willing to pay for it and it's so far been bankrolled by VC capital.
  - com2kid 2y ago
    > But AI code generation is garbage, "create an express server that uses CORS to only accept requests from <mydomain> that has 3 async endpoints defined, 2 GET endpoints titled <a, b> and 1 POST enndpoint titled <c>. The POST endpoint should accept JSON, and the GET endpoints will return JSON. Stub out the route handlers, they will be defined in another file. For the POST endpoint parse out the userId from <header field> and also pass it in along with the JSON" "Here is a typescript definition of the JSON being posted to this endpoint, validate all string fields are less than 100 characters long, and that none of the values are null, then write the data to a redis DB at <location> using auth values already loaded up in the environment. Data should be written to <userid/location>" "Now add exception and error handling around this code, cover the following case: Data is invalid - Return an error message to the user with HTTP error code 400, Redis is not accessible - HTTP 500. Also log errors using the <logging library> that has already been imported and initialized up above, and increment an appropriately named counter using the <analytics library> that is also already imported and initialized." If you are getting garbage AI code, you are not using proper tools. If you just go to ChatGPT and ask it for stuff, you won't get very good code (and IMHO GPT4o is much worse at coding). Use a proper editor that prompt engineers code generation (such as Cursor), and LLMs can write some really good code. Can it end to end generate an entire service with just a vague description? No. But it can easily 2x-4x development speed. Heck I've thrown code at GPT4 and asked it to "please look for common concurrency bugs that may have been overlooked in this code" and watched as GPT4 saved me literal hours of debugging. What OpenAI has is a problem monetizing the value their product brings, since the value to each customer is so different. When I'm at home, I'm happy to pay $15 a month in API usage fees to accelerate my coding, but a company should be happy to pay hundreds of dollars per month to accelerate the speed code is written. Figure $100 an hour average cost for a dev on the east or west coast of the USA, if GPT4 saves 10 hours a month (easy!) then OpenAI should be charging at least $200-$500 a seat licenses per month.
ajkjk 2y ago
I'm an engineer and I agree, does that help?
kyledrake 2y ago
Pontificating on what actual profit will be generated by LLM companies is fair game, but reaching a conclusion that LLMs have no mass market utility is blisteringly insane. I could easily measure the increase in value I alone have had from using them in the tens of thousands of dollars. It's more plausible for me that we will see a notable productivity increase in a lot of sectors of the economy over the next decade. Part of me wonders if this is an additional reason why the Russell 2000 has been spiking lately (investors concluding that there is more money to be made from the general productivity increases in the wider economy than the tech companies providing the LLMs that don't seem to possess any monopolies on the technology), but this is just my speculation.
- scarface_74 2y ago
  And he admitted he is “neither an engineer nor an economist, nor do I have privileged information”. So why should we listen to him? ChatGPT has saved me a lot of time. Luckily it’s well trained on AWS API’s, tge SDK, CDK, Terraform and Kubernetes. Anything it isn’t trained on, I just give it links to the documentation
- edzitron 2y ago
  I think you are misunderstanding my point, and perhaps I should've worded it more-precisely" "Mass market utility" here refers to its ability to sell at the scale it would need to substantiate its costs. As it stands, LLMs do not have mass-market utility at the scale that they need to substantiate their costs. It is really that simple. If they did, these companies would be profitable, and they would be having a meaningful effect on productivity, which they are not. See page 4 of this report from Daron Acemoglu of MIT: https://www.goldmansachs.com/images/migrated/insights/pages/gs-research/gen-ai--too-much-spend,-too-little-benefit-/TOM_AI%202.0_ForRedaction.pdf https://www.goldmansachs.com/images/migrated/insights/pages/...

ethbr1 2y ago

> Nobody has ever raised the amount of money it will need, nor has a piece of technology required such an incredible financial and systemic force — such as rebuilding the American power grid — to survive, let alone prove itself as a technology worthy of such investment. AT&T.

downrightmike 2y ago
Via pure monopoly power
- tazu 2y ago
  Isn't that sama's plan with "safety regulation"?
  - downrightmike 2y ago
    No because even Nortel in canada was a required to buy at&t made phones
- ethbr1 2y ago
  AT&T didn't have a monopoly when it started. It just burned a ridiculous amount of money stringing lines.
  - edzitron 2y ago
    It also got broken up! https://en.wikipedia.org/wiki/Breakup_of_the_Bell_System https://en.wikipedia.org/wiki/Breakup_of_the_Bell_System
j_timberlake 2y ago
The space race cost hundreds of billions in today's dollars, and AI could do a lot more for/to humanity than put a flag on the moon. And I'm guessing Uncle Sam will want control of these AI companies anyway if AI starts looking even a little powerful/threatening.

sweettea 2y ago

A well reasoned article that fundamentally downplays both the pace of innovation and the exponential increase in capabilities per dollar happening over time. AI is rapidly accelerating its improvement rate, and I do believe its capabilities will continue growing exponentially. In particular, GPT-2 to GPT-4 spans an increase from 'well read toddler' to 'average high school student' in just a few years, while simultaneously the computational cost of training less capable models goes down similarly. Also worth noting: the article claims Stripe, another huge money raiser, had an obviously useful product. gdb, sometime-CTO of stripe and its fourth employee, is now president of OpenAI. And, most of all, the author doesn't remember how nonobvious Stripe's utility was in its early days, even in the tech scene: there were established ways to take people's money and it wasn't clear why Stripe had an offering worth switching to. For an alternate take, I think https://situational-awareness.ai https://situational-awareness.ai provides a well reasoned argument for the current status of AI innovation and growth rate, and addresses all of the points here on a general (though not OpenAI specific) way.

ThereIsNoWorry 2y ago
That's a lot of unproven assumptions based on the fact that LLMs are just correlation printers.
joshstrange 2y ago
> And, most of all, the author doesn't remember how nonobvious Stripe's utility was in its early days, even in the tech scene: there were established ways to take people's money and it wasn't clear why Stripe had an offering worth switching to. I think you are misremembering. Stripe was a _big deal_. They had a curl call on their home page for a while for how to take a payment IIRC. It was like how Twilio opened the door for anyone to send SMS, Stripe made it stupid-easy to handle payments online. Nothing else at the time compared in terms of simplicity and clearly defined fees.
vrighter 2y ago
ai is very rapidly hitting a plateau, both because they are just glorified markov chains, and them running out of data anyway
2y ago

Arainach 2y ago

cuddlyogre 2y ago

I was assured that being skeptical about offloading the use of my brain to a third party that might not always be there was being a luddite.

xyz-t 2y ago

[redacted]

simonw 2y ago
What kind of agents?
- toomuchtodo 2y ago
  https://www.freethink.com/robots-ai/ai-agents-openai https://www.freethink.com/robots-ai/ai-agents-openai https://www.theinformation.com/articles/openai-shifts-ai-battleground-to-software-that-operates-devices-automates-tasks https://www.theinformation.com/articles/openai-shifts-ai-bat... (paywall) https://www.technologyreview.com/2024/05/01/1091979/sam-altman-says-helpful-agents-are-poised-to-become-ais-killer-function/ https://www.technologyreview.com/2024/05/01/1091979/sam-altm...
- viraptor 2y ago
  https://aibusiness.com/nlp/openai-is-developing-ai-agents https://aibusiness.com/nlp/openai-is-developing-ai-agents probably. But I'm not sure how much they need to innovate on that front. There's good agents progress happening everywhere around already. OpenAI could provide some options to make it faster/cheaper, and running the workflow internally would make it faster, but... doesn't feel necessary.
  - simonw 2y ago
    > AI agents differ from robotic process automation (RPA), which still needs developers to manually code steps needed to complete a task, Luan said. OK, so it's robotic process automation then (aka screen scraping / UI automation), just without the hand-written automation code. My frustration with the term "agents" is that it can mean a lot of different things - but people always seem to assume that their own personal definition is the same that everyone else is using.
FridgeSeal 2y ago
> OpenAI is currently working on the next step: agents and planning. They are close. Other competitors will shortly follow. Their stocks will rise to unprecedented levels. You have been warned. Any day now everyone will adopt bitcoin and the value will skyrocket and we’ll all be exceedingly rich, HODL, gl, wgtm, to the moon. Not saying they’re not working on stuff, but that’s what you sound like. OpenAI is amazing at generating hype, but the competitors are catching up, or outpacing them, and OpenAI source models are never far behind.

JohnMakin 2y ago

Will always give an upvote to ed zitron, who has a very anti tech/anti AI tilt but a pretty reasonable podcast called “better offline” I’ve quite been enjoying.

mxwsn 2y ago

This article is timely and pairs well with Sequoia's $600B question: https://www.sequoiacap.com/article/ais-600b-question/ https://www.sequoiacap.com/article/ais-600b-question/ calculated simply from NVidia run rate revenue, which is the cost that genAI companies are paying. Where's the profit? Meta's open source LLM stance makes things more spicy, making it challenging for anyone generate differentiated and lasting profit in the LLM space. At the current pace, the LLM bubble is poised to pop in a year or two - negative net revenue can't keep growing forever - barring a transformative, next-generation capability from closed-source AI companies that Meta can't replicate. All eyes on GPT-5.

lostmsu 2y ago
I just got a bit of data that hints that at least one of the assumptions in this blog post is false. The post says: > The supply shortage has subsided: Late 2023 was the peak of the GPU supply shortage. Startups were calling VCs, calling anyone that would talk to them, asking for help getting access to GPUs. Today, that concern has been almost entirely eliminated. For most people I speak with, it’s relatively easy to get GPUs now with reasonable lead times. But a couple of days ago I heard from a startup founder that the usual cloud credits (~$100k in cloud compute) that AWS provides to vetted startups that passed some milestones are recently barred from being used on GPU-powered instances.

benreesman 2y ago

Maybe GPT-5 or Claude 4 comes out tomorrow and pays down all the IOUs these people are operating on. As of today all of the evidence indicates the LLM paradigm is saturated. Why all the hand-wringing about hypotheticals? As of today this stuff is a failed experiment. Altman or Amodei coming up with the goods is a tail X-risk.

edzitron 2y ago
See, that's the thing. This COULD happen. I do not think it will, but the piece is written not to say "this is 100% not gonna happen," but "I am unsure how it's possible, and if it does not happen, the consequences could be dire." Hypotheses and hypotheticals are useful tools when writing about something big and messy. Instead of me saying - as I have before - that I believe generative AI is a complete dead end and thus OpenAI is in a really bad way - I took great pains to explain the terms under which they WOULD succeed - how difficult success might be, how much money it would take and how many factors would have to go their way. If OpenAI pulls it off, it'd be really remarkable. Truly historic! But if they don't, they are in deep, deep doo doo.

why_only_15 2y ago

If you believe this article, I would be happy to bet up to $10,000 that OpenAI will not collapse in the next 24 months. We could operationalize this by saying that OpenAI will employ at least as many people (or pay at least as much in salaries) in 24 months as it does now. The author of the article refused to take this bet when it was offered to him several times https://x.com/JeffLadish/status/1817999232105627722 https://x.com/JeffLadish/status/1817999232105627722.

asp_hornet 2y ago
so we should only listen to the hypotheses of gamblers? The author shouldnt even feel the need to acknowledge the bet. So petty
- why_only_15 2y ago
  If you are making predictions about the world, you should be willing to put money on those predictions so that you are grounded to making predictions that you actually believe in as opposed to just blathering.
  - kjrfghslkdjfl 2y ago
    This is too reductionist. There's a lot of reasons why someone could turn down that bet, other than "he's just blathering". Maybe he's very confidently down on OpenAI but 10k is a lot of money for him, and is being offered a bet by someone who's a noise generator but who's very well off, for whom 10k means nothing. If you think these people don't exist, you should visit WSB. I evaluate arguments on their own merit, not based on extraneous data like appeal to authority or what bets the author makes.
  - sifar 2y ago
    Predictions can go wrong for any number of reasons beyond one's thesis. One can be right about what but wrong about when. To bet money on that just to satisfy ones (and others) ego is foolish. To recognize that is wisdom.

fragmede 2y ago

I think the thing that nobody saw coming was Facebook coming out with their own, that they spent hundreds millions creating, and then releasing the model of it, with a generous license. If someone had come out of a copy of Google in 2000, we'd be looking at a much different picture.

pseudosavant 2y ago

They say no company has ever raised the kind of money OpenAI has, like they are at some kind of ceiling. Microsoft’s market cap, which is only equity, not including bonds (only $42B), is over $3T.

tptacek 2y ago
Right, but Microsoft has been profitable for decades.
- pseudosavant 2y ago
  And Microsoft was once a smaller company. Google was too. Who is to say OpenAI can't become big tech company like them? Also, I'd like to point out that the total investment into AT&T, which they position as untenable, is less than AT&T has spent on their network investments every single year for at least the last 10 years. It isn't like companies don't invest billions of dollars into things.
edzitron 2y ago
Sure, but the argument here isn't that it's impossible. Just that to do what they need to do, they need to do something that really hasn't been done before. I do not THINK Microsoft will put that much money into it. They could! It isn't impossible. But it would be totally unprecedented.

undergod 2y ago

No genius employees = mediocre outcome. Ilya left. Andrej left. Much of the talent at the top of the pyramid left. A company is literally its people.

programjames 2y ago

It's not that these AI companies need to raise $100 billion, it's that they can. They could go slower, working on custom hardware or better architectures to get 1000x cheaper training, but their models would only be as good as the ones from 1-2 years ago. Because foundation models are a winner-takes-all game, any individual company needs to spend as much as they can get, even if it means most investors will lose big. There are many companies working on hardware gains (e.g. Lightmatter, Groq), but they're not competing in the foundation model business.

coding123 2y ago

This whole thing reads like: google doesn't have a business model because anyone can do search. Well, how many years later, yeah the writers saying Google was DOA are actually DOA.

edzitron 2y ago
I'm afraid this isn't an accurate comparison. 1. I do not know of any article that said that Google was "DOA" or "done" as a result of the choice of a search engine as a business model. In fact, search engines were an already-established industry at the time. If I'm wrong, I'd love to read it, as I imagine it's a fascinating historical document - even if it was horribly wrong! 2. OpenAI's business model and Google Search's business models are totally different. Apples and oranges. The way that OpenAI monetizes, the technology it uses to both deliver a service AND monetize it, the technology stack, the scaling, even the tech they acquire to build it, just totally different. Again, if you can find an article that had someone in the 90s or 2000s saying "Google is DOA! Search is stupid!" then I'd really really love to read it, genuinely.

prng2021 2y ago

This is a nonsensical article to me. "I ultimately believe that OpenAI in its current form is untenable." Followed by a bunch of reasons why. Later they write: "What I am not saying is that OpenAI will for sure collapse, or that generative AI will definitively fail" What? Didn't they just explain 100 different reasons why they think think OpenAI will fail? There was also this: "To be clear, this piece is focused on OpenAI rather than Generative AI as a technology — though I believe OpenAI's continued existence is necessary to keep companies interested/invested in the industry at all." To be clear? So they are trying to separate OpenAI from gen AI. Then they throw in a hyphen and say, oh but without OpenAI, companies would stop spending time and money on gen AI. Ok, thank you for the..clarification. I stopped reading after that.

deleted 2y ago
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jumploops 2y ago

> generative AI is a product with no mass-market utility Citation? LLMs bring the cost of writing software close to $0. We can finally live in a world of truly bespoke code. I, for one, welcome back the web of the early 2000s.

edzitron 2y ago
Hi! I'm afraid you've made an assumption that isn't true. LLMs do not "bring the cost of writing software close to $0" on a number of levels. 1. The code is not 100% reliable, meaning it requires human oversight, and human beings cost money. 2. LLMs themselves are not cheap, nor profitable. I am comfortable humoring the idea that someone could run their own models - something which is beginning to happen - to write code. I think that's really cool, but I am also not sure how good said code will be or how practical doing so will be. Right now, Microsoft is effectively subsidizing the cost of Github Copilot, though they appear to have produced quite a lot of revenue from it. https://www.benzinga.com/news/24/07/40061358/satya-nadella-says-microsofts-copilot-drives-40-of-githubs-revenue-growth-we-are-also-enabling-anyon https://www.benzinga.com/news/24/07/40061358/satya-nadella-s... However, it seems that Github was not profitable before (https://news.ycombinator.com/item?id=17224136 https://news.ycombinator.com/item?id=17224136) and I would argue isn't profitable now. It's hard to tell, because Microsoft blends their costs into other business lines.
- jumploops 2y ago
  > Hi! I'm afraid you've made an assumption that isn't true. Citation? Your concerns are certainly valid, but the LLMs are getting smaller, faster, and cheaper to run every day. Now, I also agree that you still need someone "programming" -- in the sense that they're telling a computer what to do, but they no longer need to "code" in the traditional sense (curly braces and semicolons). We're actively seeing non-engineers build useful software for themselves, just with a $20/month subscription to ChatGPT/Claude. Times are changing, you no longer need a 6 figure engineer to build your one-off tool.
  - edzitron 2y ago

comp_throw7 2y ago

> Have a significant technological breakthrough such that it reduces the costs of building and operating GPT — or whatever model that succeeds it — by a factor of thousands of percent. Like they already did in the last 2 years? > Have such a significant technological breakthrough that GPT is able to take on entirely unseen new use cases, ones that are not currently possible or hypothesized as possible by any artificial intelligence researchers. Huh, what are these use-cases which no AI researcher thinks AI is capable of solving? Does the author not realize that many employees at the leading AI labs (including OpenAI) are explicitly trying to build ASI? I am so confused???????? > Have these use cases be ones that are capable of both creating new jobs and entirely automating existing ones in such a way that it will validate the massive capital expenditures and infrastructural investment necessary to continue. Why would they have to create new jobs? They just have to be good enough that OpenAI can charge enough money for them to be in the green. OpenAI already has a $3.4 billion ARR! Most of that is _not_ enterprise sales.

fragmede 2y ago
"No AI researcher" is an impossible set of people to satisfy, so this doesn't count, but there's the AIMO contest with a $5m prize for creating an AI that can solve its problems. https://aimoprize.com/ https://aimoprize.com/

deleted 2y ago

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tedsanders 2y ago

Small correction: "GPT-4o Mini (OpenAI's "cheaper" model) already beaten in price by Anthropic's Claude Haiku model" GPT-4o Mini is presently cheaper than Claude 3 Haiku.

linotype 2y ago

> generative AI is a product with no mass-market utility - at least on the scale of truly revolutionary movements This line is absurd. I use it constantly. 4o reads my code and generates documentation and type annotations. It generates boilerplate code. It generates logos for projects. I review all of its outputs code wise and make the odd correction here or there. I use it to check over documents before I send them. It’s replaced Stack Overflow entirely in my workflow. I’m curious as to what’s above the author’s line for revolutionary.

plasticeagle 2y ago
The fascinating thing with arguments like this is how they entirely ignore that OpenAI trained the tool you're using with Stack Overflow. And so if what you're suggesting is that AI tools will replace SO, then as soon as it does the AI is dead in the water. Who will continue to feed it new information? The answer is, nobody will. And instead of having a community driven knowledge base, you'll have a bankrupt corporation and nowhere to turn to when you discover that you can't write code anymore. None of the tools can exist without stealing the net sum of human knowledge - insofar as that is represented by the contents of the internet - for corporate profit. If what the AI proponents claim comes true, that source of knowledge will cease to exist. And what then?
- linotype 2y ago
  > And instead of having a community driven knowledge base, you'll have a bankrupt corporation and nowhere to turn to when you discover that you can't write code anymore. I still write a lot of code without needing to use an LLM. It’s just a tool that helps me be more productive. I don’t see how what is doing is any different than Google just displaying the answer instead of links to the answer.
- jononor 2y ago
  The AI does not loose its utility once it has replaced SO. Further improvements would need to come from other sources than more "free" text data though. There are several avenues for this: A) better learning efficiency - it is known that models are not samples efficient now B) pay people to create more data at large scale - already happening at the big LLM companies (though maybe less do for code right now) C) learn from the prompting interactions that customers - extremely desirable, as people would effectively pay you to improve your model. Companies are gonna keep that close to their chest D) multi-modal learning and transfer between modalities E) Self-learning, where ML model iteratively improved itself. Analogous to AlphaGo, GANs etc. This is the holy grail, but also possibly the hardest. Code has the benefit of being formal languages with available verifiers, which should be useful here. F) Specific go code: Using functional feedback, not just textual. For example the large amount of unit tests available on GitHub So I believe there are many avenues for further improvement. I still think it will be very hard though, and until we hit the next breakthrough, will be very resource intensive and possibly quite slow going.

JSDevOps 2y ago

Maybe they pivot to blockchain…. lol

Animats 2y ago

This question can be asked about several "unicorns" that need huge inputs of capital to keep going. Only the era of zero interest rates made them work. WeWork went bankrupt. Uber briefly made money but is losing it again, and is nowhere near paying back its investors. Tesla has become a major luxury car company, and is somewhat profitable, but the stock is way overpriced for a car company. Everybody now makes electric cars, so this is a low-margin business. (Reuters: "Tesla's bleak margins sink shares as Musk hypes everything but cars.") OpenAI, as a business, is assuming both that LLM-type AI will get much better very fast, and that everybody else won't be able to do what they do. It's unlikely that both of those assumptions hold. Look at autonomous vehicles. First tech demos (CMU) in the 1980s. First reasonably decent demos (DARPA Grand Challenge) in the 2000s. First successful deployment in the 2020s (Waymo, maybe Cruise and Zoox). Still not profitable. 40 years from first demos to deployment, probably 50 to profitability. It's entirely possible that OpenAI's business will look like that. Their burn rate is way too high to sustain for that long. Often it takes that long, even when the basics have been figured out. Xerography was first demoed in the late 1930s. The demo machine used to be in the lobby at Xerox PARC. Profitability came in the 1960s. By the late 1970s, everybody had the technology, and it was low-margin. Electronic digital computing goes back to IBM's 1940s pre-WWII electronic multiplier experiments, but didn't come down from insanely expensive price levels until the 1980s. Memory was a million dollars a megabyte as late as the mid-1970s. Color television was first demoed in 1928, and the first color CRT was developed in the 1940s. But mainstream adoption didn't come until 1966-1967.

FormerBandmate 2y ago
All of Uber's investors made money, their market cap is $124 billion. Terrible ROI but higher than all of their rounds

jsnell 2y ago

> However, I do have the ability to read publicly-available data, Maybe, but based on the egregious errors the author has made in previous articles, they probably don't have the ability to understand or reason about any of the data they read. Also note that despite what's implied by this statement, most of this article is not sourced, it's just the opinions of the author who admits they have no qualifications. I didn't read the entire gish gallop, but spot-checked a few paragraphs here and there. It's just the kind of innumerate tripe that you should expect from Zitron based on their past performance. > Have a significant technological breakthrough such that it reduces the costs of building and operating GPT — or whatever model that succeeds it — by a factor of thousands of percent. You can't reduce the cost of anything by more than 100%. At that point it's free. But let's consider the author's own numbers: $4B in revenue, $4B in serving costs, $3B in training costs, $1.5B in payroll. To break even at the current revenue, OpenAI need to cut their serving costs and training costs by about 66% ($1.3B+$1B+$1.5B<$4B), not by "thousands of percent". > As a result, OpenAI's revenue might climb, but it's likely going to climb by reducing the cost of its services rather than its own operating costs. ... Sorry, what? Reducing operating costs does not increase revenue. And I don't know how the author thinks that reducing cost of services would not reduce operating costs. > OpenAI's only real options are to reduce costs or the price of its offerings. It has not succeeded in reducing costs so far, and reducing prices would only increase costs. Reducing prices does not increase costs. > I see no signs that the transformer-based architecture can do significantly more than it currently does. So, here's a prime example of the author basing the "analysis" on them personally "seeing no signs" of something they have no expertise to evaluate. There's no source for this claim, and it's pretty crucial for their conclusions that transformers have hit a wall. > While there may be ways to reduce the costs of transformer-based models, the level of cost-reduction would be unprecedented, But for a given quality of model, haven't the inference costs already gone down by like 90% this year? > particularly from companies like Google, which saw its emissions increase by 48% in the last five years thanks to AI. It should be pretty obvious to somebody who can read publicly available data that all of the increase over 5 years can't be attributed to AI.

edzitron 2y ago
Hi! :) It appears you have some issues with my article, and I'm happy to provide some help. "Egregious errors in previous articles" is not a valid argument against current arguments, nor do I agree there were those errors. Nevertheless, we're discussing one particular article today! "I didn't read the entire gish gallop, but spot-checked a few paragraphs here and there. It's just the kind of innumerate tripe that you should expect from Zitron based on their past performance." Well that's not very nice! It also means that your argument is made on incomplete data. "... Sorry, what? Reducing operating costs does not increase revenue. And I don't know how the author thinks that reducing cost of services would not reduce operating costs." I'm afraid you misread what I said, likely because you (and I quote) "spot-checked a few paragraphs." One of the problems OpenAI has is that their cost of revenue - and we don't know it to be exact - is extremely high, higher than the revenue they're actually gaining, otherwise known as an "operating loss." As a result, even if they increase revenue, they'll actually lose more money. On top of that, the argument I was making is that if there's a race to the bottom (one that's already started), they will have to cut costs, making them less money even if they get more customers. "Reducing prices does not increase costs." Does reducing prices reduce operating expenses? Because if it doesn't, it actually does increase costs, because you're taking home less cash for the same cost. It could be that 4oMini is somehow more efficient - i can find no evidence that that's the case, and if it exists, I will happily update my article. "So, here's a prime example of the author basing the "analysis" on them personally "seeing no signs" of something they have no expertise to evaluate. There's no source for this claim, and it's pretty crucial for their conclusions that transformers have hit a wall." I can find no examples of radically-different functionality in GPT or other mass-market transformer-based models. In the event I am wrong, I would be fascinated to read about them, but I would need to understand A) how these functionalities are different and B) how they can be productized. After that, I'd need to understand how this would be profitable, and in turn how this would scale into something truly world-changing. "But for a given quality of model, haven't the inference costs already gone down by like 90% this year?" Have they? "It should be pretty obvious to somebody who can read publicly available data that all of the increase over 5 years can't be attributed to AI." I too read publicly-available data, and my source in this case is "Google." Forgive the messy copy-paste. https://www.gstatic.com/gumdrop/sustainability/google-2024-environmental-report.pdf https://www.gstatic.com/gumdrop/sustainability/google-2024-e... In 2023, our total GHG emissions were 14.3 million tCO2e, representing a 13% year-overyear increase and a 48% increase compared to our 2019 target base year. This result was primarily due to increases in data center energy consumption and supply chain emissions. As we further integrate AI into our products, reducing emissions may be challenging due to increasing energy demands from the greater intensity of AI compute, and the emissions associated with the expected increases in our technical infrastructure investment.

jaygray0919 2y ago

Scott Galloway made his bones with similar WeWork analysis. Once Galloway exposed the non-sustainable WeWork economics, others picked up his work and added their own spin. While WeWork would have imploded without the Galloway analysis, Scott's articles were the tipping point.

deepnotderp 2y ago

GPT-4 could’ve written this article better- hey there’s an use case right there!

dekhn 2y ago

OpenAI will survive by being absorbed into Microsoft as a capability- OpenAI employees will be MSFT badged, working under an MSFT SVP, to add functionality to existing products.

tim333 2y ago

To comment a little on the economics: OpenAI has raised $11.3bn (source the article) Since partnering with Microsoft in 2019, Microsoft's valuation has gone from $0.7tn to $3.1bn, or an increase of $2.4tn, a lot of that on AI enthusiasm. Microsoft can sell some shares to fund OpenAI, 2.4tn being about 200x what they've put in. Sure the market bubble will pop at some stage but not by 200x. I'm skeptical of the they can't survive argument. Also I recall in the early days of Facebook, Google and Amazon people saying they lose money each year, the first two didn't have a monetization model, how will they get by? But of course they ended up some of the world's most profitable companies. With AI also you have to think a few years down the road when ASI's output may exceed the current global GDP ($100tn or so).