Lots of critiques here! Something missing in this discussion is people asking _why_ it is that they're doing this. The people who work there aren't stupid!
I think this is a disconnect between people who think that large companies are static entities with established products vs. large companies that still operate like a startup and are trying to grow. When you're building your business from $0 in revenue, you don't know what will work! You try different things, you [launch over and over again](https://www.ycombinator.com/library/6i-how-to-launch-again-a...)...all in hopes of something that works, sticks, and starts to grow.
In every example here, I see OpenAI trying something new, hoping it will grow, and shutting it down after it doesn't. Sora is the pre-eminent example of this. They make news, but you don't talk about the things they launch that successfully grow!
OpenAI isn't shutting down Codex or ChatGPT, because those were launches that they did that actually worked! When you go look at the tweets and communication from OpenAI employees when ChatGPT launched, nobody was sure that it would work. But it did. And if they hadn't launched, we would have never known how valuable it was.
All that is to say...you don't know what will work until you launch. Most things fail, and it's correct to shut them down. But focusing on the products that haven't worked instead of the products that have gets you more clicks, but actually depresses innovation by making future launches less likely.
People are much more willing to give the benefit of the doubt on things like that when the flagbearers of your industry aren't running around sucking all of the oxygen out of the system and telling people things are "solved": that your product will obsolete them in the next 6-12 months.
We get it. They say that stuff to raise money, make sales and keep the party going. But don't expect too much sympathy when the strategy falters a bit.
Sora was losing 15M a day and it was running at least 3 months, so that's a total 1.3 Billion. That's a pretty expensive experiment. It sounds like a company with lots of VC to burn and no discipline. Even Jensen Huang accused them of lack of discipline in business approach.
Yeah. $1.3B isn't scrappy startup pivots, it's the sort of money Google/Meta/Microsoft/Yahoo/Salesforce burn on strategic acquisitions. And those entities absolutely get and deserve the sneers when they "sunset" the product 6-18 months later having concluded that it wasn't even showing enough signs of being a market they should bother with keeping the lights on.
At least Sora was novel and technically impressive, I guess.
Ah, but when you're little, if each misstep annoys a few early users who hit a dead-end with your project, the longer-term reputational damage is trivial. You've still got 99.999% of the TAM (total addressable market) that is ready to be charmed by something new, with no negative vibes in their mind.
As you get bigger, serious numbers of people get annoyed at dealing with a company that keeps inviting us into the Roach Motel of doomed products and features. Big case in point was Google's spree, a few years back, in terms of launching big new services/features that soon afterward got shut down. Great training ground for ambitious PMs; miserable user experience.
Somewhere between the death of Google+ and the demise of Google Hangouts, even folks like me began thinking: Why should I engage with new Google stuff if it's likely to be blown up in a few years, leaving me with buried IP from whatever I tried to do?
I'm not sure your criticism is quite fair. I think everyone here is willing to cut more slack to the underdog. But when your company represents an outsized chunk of the digital economy and employs 10k+ people, and only then says "sooo, let's try to build some sort of a profitable product here", I can see why people are rolling their eyes.
OpenAI also burned a lot of goodwill by pretending to be a nonprofit foundation focused on the betterment of mankind and then executing one of the most spectacular rugpulls in modern history. So yeah, people will be giving them a hard time even if it turns out that the valuation is justified.
Companies with non-stupid people can still do stupid things.
I think the issue with the experimentation is that they still don't have an obvious golden goose yet. Google has been able to fuck around with experiments because search/ads are always still there to carry the team and provide an infinite money spigot, even if the experiments mostly fail. But OpenAI doesn't really have an equivalent for that.
Or perhaps they lucked into chatGPT and the true prowess of the product function is being laid bare. They've had many failed projects now: that shopping stuff, a web browser, Sora.. the success they are having from Codex wasn't an original idea but a classic-case of copying. Have they run out of steam?
Very much possible. What has come out of Meta organically besides Facebook? Its valuation comes predominantly from the assets they acquired + investments yet to be made that build on the acquired assets.
Google is similarly iffy with product development. OAI is better still, marginally, in terms of delivering a more polished experience.
Also I do regard them stupid, simply because they are not following wisdom that was shared decades ago by someone with an incredible batting average when it comes to innovation: start with the customer experience and work backwards to the technology.
They very nearly gave Elon Musk a controlling interest in the company. Their justification for not doing so was entirely vibes based. "Stupid" is a broad categorization, someone can be smart in some areas and do dumb things. You shouldn't let your personal appraisal for someones talent color the actual results they produce.
> When you're building your business from $0 in revenue, you don't know what will work!
When you announce a post money valuation of $852 billion, you should probably be a bit better at figuring out what works, though. You're not a scrappy startup any more, even if you like cosplaying as one.
OpenAI is growing fast, pivoting is only to be expected. It would normally be something HN folk would typically value and encourage on startups.
They have clearly been lacking focus and now finally they seem to be working towards a narrower direction, which is usually highly valued by investors.
This article doesn't explore the depth of the decisions and only regurgitate what you may find your neighbor complaining about on X but with a better stylesheet.
In TFA it is put on the list because some of the users of this GPT version were discontent with its cancellation, which caused even OpenAI to oscillate in its decision, so they first cancelled it, then they resurrected it and then they cancelled it permanently, probably because continuing to run it would have cost more than the generated revenue.
Nothing similar happened when the earlier, presumably worse versions were discontinued.
They’ve lost a whole lot of people in prominent roles over the past few years. I wonder how much of the misfires and general thrash in product direction is a result of brain drain and/or so many hands changing. Or maybe I’m confusing cause and effect… hard to tell
That’s pretty crazy, I swear it wasn’t that long ago these companies were about the only people hiring and the comp packages looked absolutely deranged.
For a brief moment I regretted wasting any time of my life on anything but ML research. But I guess the bigger they come…
This is important context in the wake of yesterday’s “raise” announcement. A lot of this stuff seems to just quietly never happen once the ink on the PR puff dries.
The AI industry increasingly looks in scramble mode to keep the hype going as those storm clouds of financial and business reality get darker and darker on the horizon.
For a company bringing a new technology from zero to mainstream, I think it's pretty normal that there will be a lot of failed attempts at productization.
The thing that isn't normal is the degree of experimentation relative to company valuation. Normally once a company reaches $700 B+ valuation, they've figured out their product and monetization strategy. ChatGPT is clearly still iterating heavily on that - not normal for a company that size.
And not normal for a company that has been at it this long.
The Apple II went on sale on June 10th, 1977. Visicalc went on sale October 17th, 1979- 860 days separate the two. ChatGPT was opened to the public on November 30th, 2022, which was 1219 days ago- almost 50% more time has elapsed than between the Apple II and Visicalc.
Visicalc is often described as the killer app of the first generation Personal Computer(1). It was the product that drove them into every small business in the country, that blew up sales of personal computers and brought them out of the realm of hobbyists into enterprise. And, honestly, I think Visicalc and spreadsheets are still a greater benefit than what I've seen out of generative AI today. And that happened a lot faster than where we are today with generative AI. Apple had enormous actual profits by 1980 (Apple IPO'd in 1980 with a 21% operating margin). So I think that a lot of the "just got to give it more time" argument misses that the previous computer based revolutions that we know about productized and threw off gobs of cash a heck of a lot faster than this one has.
If the end result of this is "certain classes of white collar workers are 10-25% more productive" (which is the best results I can extrapolate from what I've seen so far) then it's really hard to imagine how OpenAI can return a profit to their investors.
>If the end result of this is "certain classes of white collar workers are 10-25% more productive" (which is the best results I can extrapolate from what I've seen so far) then it's really hard to imagine how OpenAI can return a profit to their investors.
If we take this as face value, and say that the absolute best case scenario is there are literally no other uses for AI but helping programmers program faster, given 4.4 million software devs, with an average cost to the company of $200,000 (working off the US here, including benefits/levels/whatever should be close), those 4.4 million devs with 20% productivity would save roughly 176 billion dollars a year.
Some companies will cut jobs, some will expand features, but that's the gist. And it's hard not to see the magnitude of improvement that's come in just 3 years, though if that leads to a 'moat' is yet to be seen.
> If we take this as face value, and say that the absolute best case scenario is there are literally no other uses for AI but helping programmers program faster, given 4.4 million software devs, with an average cost to the company of $200,000 (working off the US here, including benefits/levels/whatever should be close), those 4.4 million devs with 20% productivity would save roughly 176 billion dollars a year.
I don't think that's necessarily out of line with struggling to return a profit to investors though: an individual company is only ever going to capture a tiny fraction of the productivity improvements it enables its customer base to make[1], its own cost base is unusually high for tech, and investors are seeking a 10x+ return on an $852B valuation for a company that isn't even the market leader in that segment (which isn't the only segment, but it's the optimum B2B one). You can have a great business with a great value proposition and a sustainable moat and still not generate the desired returns on investment at a $852B valuation.
[1]and that's productivity improvements over the best-known free models, not productivity improvements over reading StackOverflow
Sorry, I forgot that for many engineers this is, in fact, their first time going through a technology cycle like this, and so would need more explanation. I am too young for Visicalc myself, but the cycle that I saw while I was in high school- the dot-com bubble- doesn't have convenient, easy to mark out dates like the PC does.
Thinking... Thinking...
Tim Berners-Lee proposing HTTP in 1989 is kinda like the original Attention is All You Need paper, I guess? Netscape 1.0 release in December 1994 is ChatGPT 1.0? And then Amazon.com opened up to the public in July 1995 and then IPO'd in May 1997 (after raising less than 10 million dollars in two funding rounds). But once again we have the business side of these previous cycles moving much faster than this one.
WOW. That does really drive home the perspective. I was an adolescent during those years and it did seem quick then, but that's an insane pace in retrospect.
Amazon is perhaps a counter-example to your point, though, to be fair. It seems to me they did a lot of spaghetti throwing while making accounting losses for a good number of years. Granted, they did it on OpenAI's dining budget.
I took it the other way, spreadsheets shook up the world way more than AI has (to date) - it's possible that history will look back and count AI as the bigger "thing" but if I had to pick a killer app, VisiCalc and computer spreadsheets in general would beat ChatGPT.
VisiCalc was "the" killer app for early micros, but being able to edit a written text on screen and then print it out with letter-like quality was nothing to sneeze at, either. This was plausibly a key gain in efficiency for the service sector, perhaps comparable to the 10%~25% that's now being talked about re: LLM's (which is huge on a secular basis).
IMO, the AI companies are trying to be both T-Mobile and Google Doc at the same time. Even Apple is struggling with being both the platform and the product. The issue with OpenAI is that the platform has no moat (other than money) and the product can be easily copied. In the game console world, the platforms have patents and trademarks, and games are not easily produced.
I'm a retired engineering manager so judge me appropriately :-) I've had 1000 good chats with ChatGPT on a wide range of topics. I build personal Excel and Access applications but not any real programming. I don't need workflow automation although I will dabble with Codex. I'm curious why I should abandon what works for Claude.
The Apple II was so simple (by today's standards) that it came with a complete printed circuit diagram. Visicalc was so simple it was written by two guys in a year.
AI is so many orders of magnitude more complex that the comparison is not really useful.
This complexity requires a lot of money- from investors- to sustain. If those investors don't see a return on their investment before they get too anxious, then no more money will be invested and the business is dead. So that would suggest that there will be even less patience from the money than the investors in Apple had. If you are correct that this greater complexity actually makes it harder to productize, then it is hard to see how frontier model generative AI will be viable under a VC funded domain.
It is entirely plausible to me that there are great technologies that are impossible to reach via the normal means of VC/investor financed capitalism. I certainly have encountered market failures requiring extremely patient money (usually in the form of government subsidies) to produce a useful product that eventually does have market value. That has worked many times in the past. But so far generative AI has not had that, and looking at my non-technology friends, I very much doubt that there would be much support among them for government subsidies of AI companies. AI companies have made too many people unhappy, served as too much of a punching bag, to be in a good position politically for that.
For most companies an $850B valuation means you figured out the business model. Here it seems to mean you convinced enough people that figuring it out is inevitable. Those are very different bets.
Which is a good thing. Elon has showed the world, the only thing that limits the upper bound is bureaucracy, extreme risk-averse and no culture for experimenting.
More and more companies will start operating on the correct reward/risk curve or else getting crushed by firms who do. OpenAI has forced Google, Apple, Meta out of their comfort zone because they know OpenAI will eat their lunch
Literally every part of this comment is confusing. Elon hasn't shown anyone anything interesting in at least a decade. OpenAI hasn't forced Apple to do anything - LLMs aren't impinging on hardware or bundled services, and this literally seems right up Google's alley (and they're arguably better at it than OpenAI has demonstrated, now that first-mover-ish is long past).
I suppose Meta's recent comfort zone was simply a stupid bet on VR, so sure, maybe one part of the comment isn't confusing.
They nominally come across as a more stable ship with less clouds over its leadership.
However all of the major privately held AI players are struggling to paint a business and financial picture that doesn’t look “terrible” at best and “verge of market moving implosion” at worst.
For now the only thing keeping this all alive is more and more irrational cash being thrown on the pile in the faint hope that something stops the implosion from happening.
Correct. As compared to other AI companies. Tangible product, specific market segment and stable user base.
But whether it is worth a trillion dollars (like some of the peers are pretending to be) is yet to be seen. A lot of companies are using Anthropic products, but whether the spend is worth it, is also yet to be seen. A more realistic end state for Anthropic would be that they’d enterprise customers, with limited but steady spend due to Anthropic finally having to stop subsidizing tokens and a valuation in around $200-350B.
Yeah TCO on AI is the big hazy uncertainty that a lot of large firms are still waiting on firmer numbers on before they really adopt. And in the nature of things we can't get TCO numbers for another year or so.
But between their token curtailment and time of day restrictions, and some of the clues in the code leak (regex for sentiment, telling the public client to be "brief") it seems like they are facing some capacity issues.
Im guessing that the accountants at all the AI incumbents drink heavily.
Anthropic can't prop up Nvidia and the chip industry itself. If AI as an industry can't start turning a dollar into $1.05, a lot of stuff starts falling in value
Nvidia will be fine, same for the chip makers. They're selling shovels during the gold rush and they stand to gain even if local/on prem AI eventually dominates for casual users.
If/when the bubble bursts Anthropic is going down as well. There's nothing unique that sets it apart from OpenAI. Their cash burn is similarly egregious.
The LLM usage will generate hundreds of billions of dollars in ad revenue, which will be wildly lucrative in terms of margins (not as good as Google search used to be). If GPT is a leader in that, they'll take a sizable share of that pot.
There's a lot more money in being Google -> consumer ads, or Amazon -> consumer ads, or Meta -> consumer ads, than there is in being Anthropic -> enterprise.
Just take a look at the enterprise. Amazon's ad business alone is already a better business than Oracle or SAP or Salesforce, with superior margins, and it's growing faster too.
And of course everybody knows the Google & Meta ad monsters.
The only question remaining is who is going to extract all those LLM ad dollars, how will that break out. Right now it's Gemini and GPT in the obvious lead, with Anthropic in third, and Meta & Grok nowhere to be found (permanent situation for those).
>The LLM usage will generate hundreds of billions of dollars in ad revenue, which will be wildly lucrative in terms of margins (not as good as Google search used to be).
This seems like ... not the situation we are in. LLMs are great for coding now but their text generation capabilities aren't exactly capturing the masses or replacing their jobs yet. People are already tired of the deluge of fake content on the internet, it's not going to drive a second revolution in web ads.
The $20-200 LLM plans are all subsidized and aren't paying for themselves. Something has to give here.
> The $20-200 LLM plans are all subsidized and aren't paying for themselves. Something has to give here.
Whats interesting to me as well as much as companies are pushing AI adoption, i have started to hear AI token spend limits enforced across a few companies, so its not entirely clear that b2b can make them profitable yet either.
If all the models reach good enough, then low cost provider would win. Gemini seems like a safer bet since Google controls more of the stack / has more efficiencies / cross selling / etc.
It’s not like “best” has won any other b2b arms race in the past.
>If all the models reach good enough, then low cost provider would win. Gemini seems like a safer bet since Google controls more of the stack / has more efficiencies / cross selling / etc.
Gemini is the best deal too. For $20: you get multiple quotas per day across the products (web, CLI, antigravity, AI Studio) 2tb of cloud storage, and you can family share the plan.
I don't know Gemini's pricing model in detail, but in general pricing doesn't generalize well between personal/hobbyist and enterprise use. Consumer pricing of variable costs is a balancing act, and most Gemini users aren't going to be anywhere near the quota; a company of 1000 can't always buy for $20,000 what 1000 random users with $20 personal plans are theoretically capped at.
Ultimately though in the long run..
They invented the tech, have a large cashflow generating business subsidizing R&D as well as sales, with network effect of existing B2B relationships.
Further they have their own TPUs, datacenters, etc on which to run their models.
Plus existing data they've squirreled away over the preceding 30 years from books, web, etc.
Just seems like a lot of efficiencies if its going to come down to cost.
In large part because most companies have a set budget for IT spend. Thats how “normal” profitable companies operate outside this cash burning bonanza that’s going on.
And in that reality one can’t just magically spend a bunch more on some fancy new thing, especially when said fancy new thing isn’t retuning value. So “token limits” and cost controls on B2B is entirely expected here.
> especially when said fancy new thing isn’t retuning value
I think this is the key element. Either they can't measure the value, or it's far far lower than anyone wants to believe, or both.
I think the problem is less that it makes some coding tasks XX% faster, but that the end to end of a SWEs roles tasks is only improved by some much smaller Y%.
If a CTO sets $10k/year spend limits on $500k SWEs.. they must not believe any of the hype.
The problem is that AGI fantasy aside, CTOs at companies are expected to deliver results today and tomorrow. Better to let somebody else hold the bag and train models, then once it finally works as advertised you can ease on the brakes.
LLM usage will largely replace traditional search, and that's stage one. To be specific, search will be consumed by the LLMs, it'll be merely an aspect of what they do for the user, and that'll include handling the more intricate details of the search, refining the search, understanding the results of search, etc. The age of the typical user handling any of that is about to end. Search will more be a feature of Gemini in the not very distant future, rather than Gemini being bolted onto/into search.
Fuller integration into the user's life will bring ever more ad opportunities (and it doesn't matter if the HN base hates that notion, it's going to happen regardless). That'll happen over the next decade gradually.
Shopping, home management, tasks (taxes, accounting, lifestyle, reminders, homework, work work, 800 other things), travel (obvious), advice & general conversation (already there), search (being consumed now), gaming (next 3-5 years to start), full at-work integration (gradual spread across all industries, with more narrow expertise), digital world building (10-15+ years out for mass user adoption). And on the list goes. It's pretty much anything the user can or does touch in life.
> To be specific, search will be consumed by the LLMs, it'll be merely an aspect of what they do for the user, and that'll include handling the more intricate details of the search, refining the search, understanding the results of search, etc. The age of the typical user handling any of that is about to end.
We already have the tech for that, why hasn't it happened? People are revolted by the AI results in Google. AI isn't going to make people use their computers more. It's not opening up a new consumer market. This is just making each search infinitely more expensive.
Every year I ask the latest version of Chat GPT a basic facts question about rugby results. It almost always gets it wrong - even when it does web search and cites sources. Wrong scores, hallucinated matches, wrong locations - just gob smacking amounts of wrongness.
The latest "Thinking" version gets it reliably right but spent about 3 minutes coming up with the answer that 10 seconds of googling answers.
So I don't believe we are currently in a situation where LLMs are an effective replacement for search engines.
Who is revolted? I use the AI Google results every day when asking for specific questions, I rarely visit the webpages before anymore. Also Google already injects ads into conversations in the form of Google Shopping affiliate links.
I understand the concern but it's frankly not my problem as a user, that is for the authors and corporations to figure out. No one would (or should) blame car buyers for putting horse and buggies out of business, they're merely participating in the market as a consumer not the producer.
More people going into insular communities like discord or creating micro sites. Like I said it's a self correcting problem, either it is fixed or it's not. It's not my problem.
You see it already with how many people use LLMs for everything these days. Google Gemini can also integrate with your other Google apps to personalize further, and Gemini already has product placement ads.
Do you have a concrete example I can reproduce? I searched for things like how to change the filter of X make and model and it seems correct, not sure if that's what you meant.
I'm not the person you replied to but I'm wondering which Google AI product you are referring to that you use for search which is so excellent that you need someone to find for you an example of it failing?
I think Google has several ai products with search features?
Which one in your experience "seems correct"?
I'm fascinated because I've never found any LLM to be particularly error free at search.
Google.com with the AI overview or whatever they call it now. It seems to source web page information for grounding so it's reasonably correct and doesn't hallucinate recently at least.
I played around with it and its better than it used to be but if you ask it something like
"Whats the name of the third book in the peripheral trilogy going to be" it just regurgitates some dumb reddit comment by someone who seems to be making things up.
There's no actual title that has been announced and the reddit post was not a reasonable bit of speculation.
The problem with these LLMs is they rarely say "the search results were not credible no response can be provided."
Google launched in 1998 and were running ads by 2000. Considering how much more access to adtech product talent there is for OAI a quarter of a century on, what explains their hesitation to pick that route and make billions? After all they had billions avaiable to acquire designer bauble maker Jony Ive's company.
The first AI company to cram their product full of ads will get roasted over the coals for it. My guess is they're all playing chicken and waiting to be the second to do it. I'd also guess that they're all already thinking about ways to introduce it that will generate the least backlash.
Google could do it in 2000 because their search was legitimately so much better, and also because their ads were comparatively more relevant and unobtrusive than modern ads. In comparison, LLMs are relatively similar in performance unless you're picky enough that you're probably already paying and thus wouldn't be in the ad-supported tier.
That said, I wonder if ads are even lucrative enough to move the needle relative to how much training costs are increasing with each generation.
Yep. Finally someone who knows how to think straight.
Google built up immense surplus and ate into it slowly.
OAI can't suddenly start cramming Ads as it fights to survive. Im sure they are employing questionable tactics to keep users hooked. Won't really work on a large enough user base to make the economics viable given the competition they face.
These exact words were said tens of thousands of times about Facebook (am old enough to remember those discussions :) ), “no way they can monetize on mobile” (this was the most fun).
rules are simple, if you have Xbn or XXXm users on your system, you will make big bank in ads eventually
It's tempting to look at trends and assume there must be a rule behind them, but it's also intellectually lazy. Please do the hard work of justifying your stance like GGP did.
it is a simple stance - if you have a product that is used by hundreds of millions of people ad monetization strategy will be found cause there are people a lot smarter than you and me that will get it done. here’s intellectual challenge - find a business with comparable number of users to openai which is not swimming in ad revenue - one will do
A counterpoint is that there are many products with significant usage that fail or never attempt advertising monetization. They just increase the cost of the product.
At that time, Facebook provided a free service without any real competitors. The masses will switch to Meta AI or Gemini or Claude at the drop of an ad that annoys them enough.
Gemini, GPT and Claude will all have ads on the consumer side. They will go together in quasi lock-step into the ad future, because that money is gigantic and they're going to need it.
The masses will have no say in the matter. Just as they had no say in the matter with Google's ads getting ever more intrusive, or cable prices previously, or streaming prices going perpetually higher in the present, or YouTube ads, or anything else. Consumers will have no say in the matter, they'll take it and that's that.
With only three relevant competitors (maybe Mistral in Europe), there will be nowhere to flee the deployment of ads.
amazing this is even a debate, we have now decades of this across everything that reaches enough users, it is a certainty as much that the Sun will rise tomorrow morning. as probably many people here on HN I am designated computer-fixer for all my family so any family gathering I have to look at someone's computer about something. years ago I started checking whether browser(s) anything ad-blocking in place and I am 0 for million by now. while HN crowd might be theoretically pushing back on ads (even with like "I won't use this if there are ads" nonsense) general public is so used to ads that I sometimes feel it is welcomed change when some new service etc gets ads. I remember the first time I saw an ad on Amazon Prime Video and my daughter and I were like "no f'ing way!!!" and my wife was like "oh, ____ is on sale this weekend, cool!" :)
> Just take a look at the enterprise. Amazon's ad business alone is already a better business than Oracle or SAP or Salesforce, with superior margins, and it's growing faster too.
You can say the same about AWS and then prove the b2b case instead of ad case as well
AWS is legitimately a giant and it should be considered in enterprise broadly. It's infrastructure more than enterprise software of course, which is where Anthropic is at. Anthropic is not trying to host the world's databases and services (at present anyway). Anthropic will however help you write software to compete with Salesforce, Oracle, SAP, et al.
Google's ad business remains far larger and more profitable than AWS. And the advertising segment is drastically larger than the segment AWS is in. Just Google + Meta = nearing $600 billion in ad sales. Amazon will soon have their own $100 billion in ad sales.
I guess the question is how many more $100B of ad sales slots are available, aside from just stealing share from incumbents (who already took it from traditional media channels over last 20 years).
At some point someone needs to add value to the real economy, not just take an ad tax off the top.
I don't think advertising is entirely a zero-sum game (there is real value to everyone for steveBK123 to learn of a product that actually solves a real need or saves money, etc) - but it has to be something akin to it - the economy can't support five hundred trillion dollars in advertising spend.
absolutely not the case. there isn’t a single nerve in human brains that goes “oh imma tolerate ads cause this shit’s free but if I pay a few bucks no way” - if the product you use has utility to you, you will tolerate ads provided no other acceptable alternative. not to tell you something you don’t already know but anthropic is getting ads, eventually, it is a given. so while today you may have an alternative (arguably better even if no ads in the equation) at some point you won’t have an alternative (other than running local) and you’ll tolerate ads. the thing with LLM ads is that companies can make $$$$ from “ads” you don’t see, i.e. I can (not now but in the future) companies to push my product, e.g. claude is setting up architecture and proposes upstash (which I own and am paying anthropic a lot of money) instead of any competitor. or even more silently adding dependencies on my NPM library which has free and commercial offering…
Holy f'n Hell, there's such a blatant bias on HackerNews in favor of Anthropic and against OpenAI.
I'm just a user, and in my experience Claude has been consistently crap compared to ChatGPT/Codex.
I use both side-by-side, and have paid for a ChatGPT subscription every month for around 1 year, but only 2 months for Claude; once last year, and again since last month.
Everything from the sign up, the sign in, the payment, the UI, the UX, gosh, just sucks on Claude.
And the AI itself: SO. MUCH. "OoPs you're right! I was mistaken" BACKTRACKING! It's downright DANGEROUS to listen to it! God I can post screenshots of working on the same project and the same prompts with both agents and prove how worse Claude is.
Of course this comment will be downvoted by Anthropic's paid PR machine, because there's no way actual users who have tried both products would be so in favor of Claude.
I’ve been a paid subscriber for all three players since day 1. CC (Opus) has been a clear winner for agentic coding starting about 6 months ago. GPT5.4 reduced the gap somewhat but the gap is still there.
> Of course this comment will be downvoted by Anthropic's paid PR machine, because there's no way actual users who have tried both products would be so in favor of Claude.
Sure, it couldn't possibly be that others have had a different experience. It couldn't even be that some people think OpenAI is nearly as gross as Palantir. It's that they're shills.
OpenAI has stagnated technologically, and is a financial zombie, but that's not true for every part of the industry. Once these early movers flame out, there will be more stability with Google, Microsoft, and AWS.
Because to watch usage go to zero while charging what it actually costs to successfully run the service would immediately liquify the slow moving quicksand investors are currently standing in.
That plus the legal risk is too high, which gets added to the math of making copyright deals + computing, and they decided it didn't make sense at the moment. Even Grok is clamping down on the video side. Can't beat bad economics and lawyers/politicians coming down your throat no matter how good the product is.
What they really should focus on is making those models more efficient. With them most likely losing money on inference (+model training + salaries + building data centers), I can't see why they would want more compute and more products, since more tokens spent is actually bad for them.
Did you really mean to say 4.5? Gpt 4.5 used to cost $75/$150 per million tokens input/output. And it did not even seem to be that good to justify that. I would not expect many people were using it, and I doubt that "expanding to india" was what killed it (if it was that useful/popular they would have kept the api, or keep it for higher end subscriptions).
If anything it should have been no1 in the "openAI graveyard" website.
India in this context is a synecdoche for scaling consumer vs Anthropic's more enterprise-y route, but yes that's pretty much why we didn't get 4.5 with reasoning. Without reasoning, 4.5 had no future.
From Sam Altman himself:
> We had this big GPU crunch. We could go make another giant model. We could go make that, and a lot of people would want to use it, and we would disappoint them. And so we said, let’s make a really smart, really useful model, but also let’s try to optimize for inference cost. And I think we did a great job with that.
4.5 scaled into a unified reasoning model would have been an incredible model. It beat GPT-5 on accuracy and hallucinations without reasoning (!)
It just wouldn't have worked for powering things like ChatGPT Go's rollout and loginless chatgpt.com, so they dropped it.
(And if you want, you could argue it's the compute crunch that didn't let them do both... but Anthropic had to make the same choices at the time and went in the other direction.)
The stargate, nvidia and amd deals are all linked together and the fallout is not public. Nvidia and amd stock seems to not care about it at all. Oracle fired 30000 employees, not sure if it’s to fund that initiative or a fall out of that
Interesting. I never had much of an opinionon Forbes till a few years ago I noticed them posting nearly exclusively NYPost style clickbait. I didn’t think it was that bad of a publication.
My guess is Sam Altman is a better VC than CEO. Better at hype, networking, fund raising, and back room political hijinks than shipping a focused product
He seems to be trying to take almost a "venture studio" approach by throwing shit at the wall, but the problem with these things is always that the "internal startups" are "founded" by people who don't have enough incentive or control over their product to perform as well as an actual startup, and are distracted by internal politics. And frankly, it may also be that the really good founders will just do their own startup vs working on a quasi-startup inside a large org so there's some selection bias as well.
I'm not an OAI fanboy by a longshot - but I'd view lots of experiments that didn't work out as a healthy thing, especially for a company trying to find footing in a new industry.
I think the VC/investor community needs to take A LOT of blame here. They've created an insane rush to financialize everything to moon at the drop of a hat.
I asked an LLM today to take a word document and a PowerPoint template to “convert” the docx to a ppt. It asked some good questions like “it looks like this template is a title slide and content slide only, would you like all the content on the content slide?”
“Yes” I said, slightly impressed. It then asked me to clarify the subheadings, which were correct.
“Cool, this seems neat” I mused.
It generated the PowerPoint. There was not a single word on it from the docx, the header slide was devoid of words, and the 6 following content sliders were identical, and empty of words.
I suppose it’s cool that it used the correct template.
I did the work manually in 10 minutes after waiting around and responding to an LLM for 15.
What a fucking joke. “AI” is a term that we really need to stop fucking using.
Has there ever been a period o time where people saw a bubble coming and that we were in one, but it just inexorably refused to pop/drug out this long? This isn’t a rhetorical question, I’m wondering how this period compares to other irrational periods of the economy like railroad fever etc.
Not at all, there is a famous saying (often attributed to Keynes but as far as I can tell he never said) “Markets can remain irrational longer than you can remain solvent.”
> Has there ever been a period o time where people saw a bubble coming and that we were in one, but it just inexorably refused to pop/drug out this long?
The housing bubble that peaked in 2006 was raised as an issue at least as early as 2000 and became a big topic of conversation in mid-to-late 2002, which is comparable to if we had started talking about an AI bubble roughly simultaneously with the release of GPT-3 and it had become a topic of wide concern shortly after the release of GPT-3.5.
So, in short, not only “this long”, but much longer.
It’s not been that long really. The dot com bubble was called a bubble for a while before it finally imploded. And just like now folks were in massive denial that it was a bubble.
One of the challenges here is that a lot of folks simply weren’t around then and haven’t seen what happens when everything implodes overnight. Those that have experienced it know what that looks like and know it will happen again.
What makes this time weird though is back then (and in most bubbles) the bubble was creating jobs - supposedly (I'm too young) anyone who could write a bit of HTML could get hired in the dot com boom.
Whereas this is a very weird bubble where it creates big pumps in some equity prices but apart from a tiny number of people who are directly involved in AI research etc. it's not created any jobs, in fact by creating uncertainty it's probably caused fewer jobs to be created.
What that means for labour market dynamics when it pops I really don't know
Bubbles don't pop overnight. In the aftermath of any collapse, you can generally see a pretty clear pattern of red flags (and attempts to minimize them or cover them up). Some parties notice earlier than others, but the realization is generally a much more gradual process than the collapse.
Its obvious its coming soon simply because the mismatch between hype and expectations is far too large now. Hype is necessary to lure in investment but now its reached its peak imo.
The question is, is it a big bang or a slow release?
LLMs can be a massively transformative and valuable technology, and this would still be a bubble, there's no reason those two things can't be true at once.
In fact "pure" bubbles where the focus item is of literally no value (tulips, NFTs) are quite rare. Much more common are the bubbles based on an actual real transformative innovation (canals, railways, radio, internet, LLMs).
Railways did absolutely transform how travel worked in the UK, while simultaneously almost everyone who invested in them lost their shirts
"Disney’s then-CEO Bob Iger... was sold on Sora, too. He lauded Altman’s ability to “look around corners”..."
WTF is that supposed to mean? I'm sorry, maybe I'm being dense. I can't figure out what "look around corners" is supposed to mean. "Think outside the box," I guess? Why "look around corners?"
I mean, maybe I do get it. Altman has a weird face that looks like you can't predict where his eyes are based on where his head is. "Shifty," one might say. But I doubt that's what Iger meant.
It's dumb. It's dumb corporate speak. I'm so sick of this kind of stuff getting a pass. We used to bully people over using the word "synergy." Let's make america anti-corporate-weasel again.
I read it as being able to see the future, which is still bullshit par excellence. The future is just around the corner as it were, but us normal people cannot see it, on account of both it being the future, and around a corner.
Before he left I use to enjoy enraging a manager several layers above me. In one instance I explained that asking us to cut a few corners to get things done was fine, usually we can figure out acceptable ways of doing it. But then, it is your job to take those fake numbers and figure out how we are doing. No matter how much effort you make if bullshit goes in you know what will come out.
Now imagine an entire economy working like that. Like say, LLM's are good enough to run entire companies but you don't get to run a company because you are good at it. LLM's can perfectly manage employee schedules but the real job is more like marriage counseling or group therapy. Somewhere along the road we forgot which jobs make the economy go. They are probably the ones with the lowest salaries as those lack the effort of conjuring the job into existence.
Humanity needs obvious things cloths, food, housing, transportation etc but that isn't where the money is. The people cooking the books have the money and they are looking for something like a book cooking book. The market for openAI will be in lying convincingly for the benefit of the investor. Reality must be auctioned off like domain names or search engine placements. Altman is really the perfect guy for the job no one wants. ha-ha
Alternatively we could humble ourselves, ask the Chinese how reality works and attempt to steal their fu. It's just a thought.
Lots of critiques here! Something missing in this discussion is people asking _why_ it is that they're doing this. The people who work there aren't stupid!
I think this is a disconnect between people who think that large companies are static entities with established products vs. large companies that still operate like a startup and are trying to grow. When you're building your business from $0 in revenue, you don't know what will work! You try different things, you [launch over and over again](https://www.ycombinator.com/library/6i-how-to-launch-again-a...)...all in hopes of something that works, sticks, and starts to grow.
In every example here, I see OpenAI trying something new, hoping it will grow, and shutting it down after it doesn't. Sora is the pre-eminent example of this. They make news, but you don't talk about the things they launch that successfully grow!
OpenAI isn't shutting down Codex or ChatGPT, because those were launches that they did that actually worked! When you go look at the tweets and communication from OpenAI employees when ChatGPT launched, nobody was sure that it would work. But it did. And if they hadn't launched, we would have never known how valuable it was.
All that is to say...you don't know what will work until you launch. Most things fail, and it's correct to shut them down. But focusing on the products that haven't worked instead of the products that have gets you more clicks, but actually depresses innovation by making future launches less likely.
People are much more willing to give the benefit of the doubt on things like that when the flagbearers of your industry aren't running around sucking all of the oxygen out of the system and telling people things are "solved": that your product will obsolete them in the next 6-12 months.
We get it. They say that stuff to raise money, make sales and keep the party going. But don't expect too much sympathy when the strategy falters a bit.
Sora was losing 15M a day and it was running at least 3 months, so that's a total 1.3 Billion. That's a pretty expensive experiment. It sounds like a company with lots of VC to burn and no discipline. Even Jensen Huang accused them of lack of discipline in business approach.
Yeah. $1.3B isn't scrappy startup pivots, it's the sort of money Google/Meta/Microsoft/Yahoo/Salesforce burn on strategic acquisitions. And those entities absolutely get and deserve the sneers when they "sunset" the product 6-18 months later having concluded that it wasn't even showing enough signs of being a market they should bother with keeping the lights on. At least Sora was novel and technically impressive, I guess.
Ah, but when you're little, if each misstep annoys a few early users who hit a dead-end with your project, the longer-term reputational damage is trivial. You've still got 99.999% of the TAM (total addressable market) that is ready to be charmed by something new, with no negative vibes in their mind.
As you get bigger, serious numbers of people get annoyed at dealing with a company that keeps inviting us into the Roach Motel of doomed products and features. Big case in point was Google's spree, a few years back, in terms of launching big new services/features that soon afterward got shut down. Great training ground for ambitious PMs; miserable user experience.
Somewhere between the death of Google+ and the demise of Google Hangouts, even folks like me began thinking: Why should I engage with new Google stuff if it's likely to be blown up in a few years, leaving me with buried IP from whatever I tried to do?
I bought a cheap Samsung phone. And it sucked. So I bought the new Pixel and it's so much better. I'll probably never buy a Samsung phone again.
I was disappointed Google killed Reader but I pivoted. Otherwise, Google's reputation for me is fine-ish.
Enron employed a lot of smart people too. So did Bear Stearns. Smart people given bad incentives can create huge messes.
Dumb people given bad incentives can be even worse. No politicians come to mind...
I'm not sure your criticism is quite fair. I think everyone here is willing to cut more slack to the underdog. But when your company represents an outsized chunk of the digital economy and employs 10k+ people, and only then says "sooo, let's try to build some sort of a profitable product here", I can see why people are rolling their eyes.
OpenAI also burned a lot of goodwill by pretending to be a nonprofit foundation focused on the betterment of mankind and then executing one of the most spectacular rugpulls in modern history. So yeah, people will be giving them a hard time even if it turns out that the valuation is justified.
And literally boasted how it was going to obsolete white collar workers. Like of course most people are cheering for its failure.
Companies with non-stupid people can still do stupid things.
I think the issue with the experimentation is that they still don't have an obvious golden goose yet. Google has been able to fuck around with experiments because search/ads are always still there to carry the team and provide an infinite money spigot, even if the experiments mostly fail. But OpenAI doesn't really have an equivalent for that.
Or perhaps they lucked into chatGPT and the true prowess of the product function is being laid bare. They've had many failed projects now: that shopping stuff, a web browser, Sora.. the success they are having from Codex wasn't an original idea but a classic-case of copying. Have they run out of steam?
Very much possible. What has come out of Meta organically besides Facebook? Its valuation comes predominantly from the assets they acquired + investments yet to be made that build on the acquired assets.
Google is similarly iffy with product development. OAI is better still, marginally, in terms of delivering a more polished experience.
Also I do regard them stupid, simply because they are not following wisdom that was shared decades ago by someone with an incredible batting average when it comes to innovation: start with the customer experience and work backwards to the technology.
You can also get the reputation as an unreliable vendor. I would put Google in this category.
>The people who work there aren't stupid!
They very nearly gave Elon Musk a controlling interest in the company. Their justification for not doing so was entirely vibes based. "Stupid" is a broad categorization, someone can be smart in some areas and do dumb things. You shouldn't let your personal appraisal for someones talent color the actual results they produce.
> When you're building your business from $0 in revenue, you don't know what will work!
When you announce a post money valuation of $852 billion, you should probably be a bit better at figuring out what works, though. You're not a scrappy startup any more, even if you like cosplaying as one.
OpenAI is growing fast, pivoting is only to be expected. It would normally be something HN folk would typically value and encourage on startups.
They have clearly been lacking focus and now finally they seem to be working towards a narrower direction, which is usually highly valued by investors.
This article doesn't explore the depth of the decisions and only regurgitate what you may find your neighbor complaining about on X but with a better stylesheet.
> GPT-4o
Why is this on the list? Like... what? How about including GPT 3.5 and GPT 2 here too?
In TFA it is put on the list because some of the users of this GPT version were discontent with its cancellation, which caused even OpenAI to oscillate in its decision, so they first cancelled it, then they resurrected it and then they cancelled it permanently, probably because continuing to run it would have cost more than the generated revenue.
Nothing similar happened when the earlier, presumably worse versions were discontinued.
Gemini models even in last month add this 4o to any text I can bet that that is added by Gemini :D
It's Forbes, lads.
They’ve lost a whole lot of people in prominent roles over the past few years. I wonder how much of the misfires and general thrash in product direction is a result of brain drain and/or so many hands changing. Or maybe I’m confusing cause and effect… hard to tell
That’s pretty crazy, I swear it wasn’t that long ago these companies were about the only people hiring and the comp packages looked absolutely deranged.
For a brief moment I regretted wasting any time of my life on anything but ML research. But I guess the bigger they come…
This is important context in the wake of yesterday’s “raise” announcement. A lot of this stuff seems to just quietly never happen once the ink on the PR puff dries.
The AI industry increasingly looks in scramble mode to keep the hype going as those storm clouds of financial and business reality get darker and darker on the horizon.
For a company bringing a new technology from zero to mainstream, I think it's pretty normal that there will be a lot of failed attempts at productization.
The thing that isn't normal is the degree of experimentation relative to company valuation. Normally once a company reaches $700 B+ valuation, they've figured out their product and monetization strategy. ChatGPT is clearly still iterating heavily on that - not normal for a company that size.
And not normal for a company that has been at it this long.
The Apple II went on sale on June 10th, 1977. Visicalc went on sale October 17th, 1979- 860 days separate the two. ChatGPT was opened to the public on November 30th, 2022, which was 1219 days ago- almost 50% more time has elapsed than between the Apple II and Visicalc.
Without me trying to be snarky why do you feel spreadsheet software launching is comparable to this scenario?
Visicalc is often described as the killer app of the first generation Personal Computer(1). It was the product that drove them into every small business in the country, that blew up sales of personal computers and brought them out of the realm of hobbyists into enterprise. And, honestly, I think Visicalc and spreadsheets are still a greater benefit than what I've seen out of generative AI today. And that happened a lot faster than where we are today with generative AI. Apple had enormous actual profits by 1980 (Apple IPO'd in 1980 with a 21% operating margin). So I think that a lot of the "just got to give it more time" argument misses that the previous computer based revolutions that we know about productized and threw off gobs of cash a heck of a lot faster than this one has.
If the end result of this is "certain classes of white collar workers are 10-25% more productive" (which is the best results I can extrapolate from what I've seen so far) then it's really hard to imagine how OpenAI can return a profit to their investors.
1: https://en.wikipedia.org/wiki/VisiCalc#Killer_app is pretty much the normal narrative on Visicalc and its importance to the Personal Computer.
>If the end result of this is "certain classes of white collar workers are 10-25% more productive" (which is the best results I can extrapolate from what I've seen so far) then it's really hard to imagine how OpenAI can return a profit to their investors.
If we take this as face value, and say that the absolute best case scenario is there are literally no other uses for AI but helping programmers program faster, given 4.4 million software devs, with an average cost to the company of $200,000 (working off the US here, including benefits/levels/whatever should be close), those 4.4 million devs with 20% productivity would save roughly 176 billion dollars a year.
Some companies will cut jobs, some will expand features, but that's the gist. And it's hard not to see the magnitude of improvement that's come in just 3 years, though if that leads to a 'moat' is yet to be seen.
> If we take this as face value, and say that the absolute best case scenario is there are literally no other uses for AI but helping programmers program faster, given 4.4 million software devs, with an average cost to the company of $200,000 (working off the US here, including benefits/levels/whatever should be close), those 4.4 million devs with 20% productivity would save roughly 176 billion dollars a year.
I don't think that's necessarily out of line with struggling to return a profit to investors though: an individual company is only ever going to capture a tiny fraction of the productivity improvements it enables its customer base to make[1], its own cost base is unusually high for tech, and investors are seeking a 10x+ return on an $852B valuation for a company that isn't even the market leader in that segment (which isn't the only segment, but it's the optimum B2B one). You can have a great business with a great value proposition and a sustainable moat and still not generate the desired returns on investment at a $852B valuation.
[1]and that's productivity improvements over the best-known free models, not productivity improvements over reading StackOverflow
Thanks for the in depth explanation. I was definitely not up on my tech history here. :)
Sorry, I forgot that for many engineers this is, in fact, their first time going through a technology cycle like this, and so would need more explanation. I am too young for Visicalc myself, but the cycle that I saw while I was in high school- the dot-com bubble- doesn't have convenient, easy to mark out dates like the PC does.
Thinking... Thinking... Tim Berners-Lee proposing HTTP in 1989 is kinda like the original Attention is All You Need paper, I guess? Netscape 1.0 release in December 1994 is ChatGPT 1.0? And then Amazon.com opened up to the public in July 1995 and then IPO'd in May 1997 (after raising less than 10 million dollars in two funding rounds). But once again we have the business side of these previous cycles moving much faster than this one.
Yeah I started programming in 2006 as a kid and then entered professional work in 2016 I guess as still a kid depending on your perspective :P
This is really the first meteoric rise in tech I've seen / am experiencing first hand.
All I will say is make sure to enjoy your knees while they don't hurt, whippersnapper.
WOW. That does really drive home the perspective. I was an adolescent during those years and it did seem quick then, but that's an insane pace in retrospect.
Amazon is perhaps a counter-example to your point, though, to be fair. It seems to me they did a lot of spaghetti throwing while making accounting losses for a good number of years. Granted, they did it on OpenAI's dining budget.
"It seems to me they did a lot of spaghetti throwing while making accounting losses for a good number of years."
They actually didn't. They knew what they were doing. Bezos had a proper background in Finance, unlike Altman.
I took it the other way, spreadsheets shook up the world way more than AI has (to date) - it's possible that history will look back and count AI as the bigger "thing" but if I had to pick a killer app, VisiCalc and computer spreadsheets in general would beat ChatGPT.
Good link from the other day about spreadsheet impact on business https://davidoks.blog/p/how-the-spreadsheet-reshaped-america
Visicalc is widely regarded to be the first "killer app" for the Apple computer. Perhaps even the first "killer app" period.
VisiCalc was the killer app.
VisiCalc was "the" killer app for early micros, but being able to edit a written text on screen and then print it out with letter-like quality was nothing to sneeze at, either. This was plausibly a key gain in efficiency for the service sector, perhaps comparable to the 10%~25% that's now being talked about re: LLM's (which is huge on a secular basis).
Ah got it. I wasn’t drawing that connection. Thanks
IMO, the AI companies are trying to be both T-Mobile and Google Doc at the same time. Even Apple is struggling with being both the platform and the product. The issue with OpenAI is that the platform has no moat (other than money) and the product can be easily copied. In the game console world, the platforms have patents and trademarks, and games are not easily produced.
I'm a retired engineering manager so judge me appropriately :-) I've had 1000 good chats with ChatGPT on a wide range of topics. I build personal Excel and Access applications but not any real programming. I don't need workflow automation although I will dabble with Codex. I'm curious why I should abandon what works for Claude.
The Apple II was so simple (by today's standards) that it came with a complete printed circuit diagram. Visicalc was so simple it was written by two guys in a year.
AI is so many orders of magnitude more complex that the comparison is not really useful.
This complexity requires a lot of money- from investors- to sustain. If those investors don't see a return on their investment before they get too anxious, then no more money will be invested and the business is dead. So that would suggest that there will be even less patience from the money than the investors in Apple had. If you are correct that this greater complexity actually makes it harder to productize, then it is hard to see how frontier model generative AI will be viable under a VC funded domain.
It is entirely plausible to me that there are great technologies that are impossible to reach via the normal means of VC/investor financed capitalism. I certainly have encountered market failures requiring extremely patient money (usually in the form of government subsidies) to produce a useful product that eventually does have market value. That has worked many times in the past. But so far generative AI has not had that, and looking at my non-technology friends, I very much doubt that there would be much support among them for government subsidies of AI companies. AI companies have made too many people unhappy, served as too much of a punching bag, to be in a good position politically for that.
I'm curious how long it took Google to reach that valuation.
For most companies an $850B valuation means you figured out the business model. Here it seems to mean you convinced enough people that figuring it out is inevitable. Those are very different bets.
Which is a good thing. Elon has showed the world, the only thing that limits the upper bound is bureaucracy, extreme risk-averse and no culture for experimenting.
More and more companies will start operating on the correct reward/risk curve or else getting crushed by firms who do. OpenAI has forced Google, Apple, Meta out of their comfort zone because they know OpenAI will eat their lunch
Literally every part of this comment is confusing. Elon hasn't shown anyone anything interesting in at least a decade. OpenAI hasn't forced Apple to do anything - LLMs aren't impinging on hardware or bundled services, and this literally seems right up Google's alley (and they're arguably better at it than OpenAI has demonstrated, now that first-mover-ish is long past).
I suppose Meta's recent comfort zone was simply a stupid bet on VR, so sure, maybe one part of the comment isn't confusing.
I don't understand what you think you're seeing.
True, Elon has really been achieving win after win with Tesla and Twitter.
Anthropic does look healthier, with their enterprise focus. Or am I missing something?
They nominally come across as a more stable ship with less clouds over its leadership.
However all of the major privately held AI players are struggling to paint a business and financial picture that doesn’t look “terrible” at best and “verge of market moving implosion” at worst.
For now the only thing keeping this all alive is more and more irrational cash being thrown on the pile in the faint hope that something stops the implosion from happening.
> healthier
Correct. As compared to other AI companies. Tangible product, specific market segment and stable user base.
But whether it is worth a trillion dollars (like some of the peers are pretending to be) is yet to be seen. A lot of companies are using Anthropic products, but whether the spend is worth it, is also yet to be seen. A more realistic end state for Anthropic would be that they’d enterprise customers, with limited but steady spend due to Anthropic finally having to stop subsidizing tokens and a valuation in around $200-350B.
Yeah TCO on AI is the big hazy uncertainty that a lot of large firms are still waiting on firmer numbers on before they really adopt. And in the nature of things we can't get TCO numbers for another year or so.
Outwardly it looks much better.
But between their token curtailment and time of day restrictions, and some of the clues in the code leak (regex for sentiment, telling the public client to be "brief") it seems like they are facing some capacity issues.
Im guessing that the accountants at all the AI incumbents drink heavily.
Anthropic can't prop up Nvidia and the chip industry itself. If AI as an industry can't start turning a dollar into $1.05, a lot of stuff starts falling in value
Nvidia will be fine, same for the chip makers. They're selling shovels during the gold rush and they stand to gain even if local/on prem AI eventually dominates for casual users.
Relative to OAI they are healthier.
That isn’t saying much.
If/when the bubble bursts Anthropic is going down as well. There's nothing unique that sets it apart from OpenAI. Their cash burn is similarly egregious.
The LLM usage will generate hundreds of billions of dollars in ad revenue, which will be wildly lucrative in terms of margins (not as good as Google search used to be). If GPT is a leader in that, they'll take a sizable share of that pot.
There's a lot more money in being Google -> consumer ads, or Amazon -> consumer ads, or Meta -> consumer ads, than there is in being Anthropic -> enterprise.
Just take a look at the enterprise. Amazon's ad business alone is already a better business than Oracle or SAP or Salesforce, with superior margins, and it's growing faster too.
And of course everybody knows the Google & Meta ad monsters.
The only question remaining is who is going to extract all those LLM ad dollars, how will that break out. Right now it's Gemini and GPT in the obvious lead, with Anthropic in third, and Meta & Grok nowhere to be found (permanent situation for those).
>The LLM usage will generate hundreds of billions of dollars in ad revenue, which will be wildly lucrative in terms of margins (not as good as Google search used to be).
This seems like ... not the situation we are in. LLMs are great for coding now but their text generation capabilities aren't exactly capturing the masses or replacing their jobs yet. People are already tired of the deluge of fake content on the internet, it's not going to drive a second revolution in web ads.
The $20-200 LLM plans are all subsidized and aren't paying for themselves. Something has to give here.
> The $20-200 LLM plans are all subsidized and aren't paying for themselves. Something has to give here.
Whats interesting to me as well as much as companies are pushing AI adoption, i have started to hear AI token spend limits enforced across a few companies, so its not entirely clear that b2b can make them profitable yet either.
If all the models reach good enough, then low cost provider would win. Gemini seems like a safer bet since Google controls more of the stack / has more efficiencies / cross selling / etc.
It’s not like “best” has won any other b2b arms race in the past.
>If all the models reach good enough, then low cost provider would win. Gemini seems like a safer bet since Google controls more of the stack / has more efficiencies / cross selling / etc.
Gemini is the best deal too. For $20: you get multiple quotas per day across the products (web, CLI, antigravity, AI Studio) 2tb of cloud storage, and you can family share the plan.
I don't know Gemini's pricing model in detail, but in general pricing doesn't generalize well between personal/hobbyist and enterprise use. Consumer pricing of variable costs is a balancing act, and most Gemini users aren't going to be anywhere near the quota; a company of 1000 can't always buy for $20,000 what 1000 random users with $20 personal plans are theoretically capped at.
Ultimately though in the long run.. They invented the tech, have a large cashflow generating business subsidizing R&D as well as sales, with network effect of existing B2B relationships.
Further they have their own TPUs, datacenters, etc on which to run their models.
Plus existing data they've squirreled away over the preceding 30 years from books, web, etc.
Just seems like a lot of efficiencies if its going to come down to cost.
In large part because most companies have a set budget for IT spend. Thats how “normal” profitable companies operate outside this cash burning bonanza that’s going on.
And in that reality one can’t just magically spend a bunch more on some fancy new thing, especially when said fancy new thing isn’t retuning value. So “token limits” and cost controls on B2B is entirely expected here.
> especially when said fancy new thing isn’t retuning value
I think this is the key element. Either they can't measure the value, or it's far far lower than anyone wants to believe, or both.
I think the problem is less that it makes some coding tasks XX% faster, but that the end to end of a SWEs roles tasks is only improved by some much smaller Y%.
If a CTO sets $10k/year spend limits on $500k SWEs.. they must not believe any of the hype.
The problem is that AGI fantasy aside, CTOs at companies are expected to deliver results today and tomorrow. Better to let somebody else hold the bag and train models, then once it finally works as advertised you can ease on the brakes.
> The $20-200 LLM plans are all subsidized and aren't paying for themselves. Something has to give here.
Expert systems were amazing. They were not cost effective.
There might be another bitter lesson to be had here, and unless the accountants start talking we're not gonna know any time soon.
LLM usage will largely replace traditional search, and that's stage one. To be specific, search will be consumed by the LLMs, it'll be merely an aspect of what they do for the user, and that'll include handling the more intricate details of the search, refining the search, understanding the results of search, etc. The age of the typical user handling any of that is about to end. Search will more be a feature of Gemini in the not very distant future, rather than Gemini being bolted onto/into search.
Fuller integration into the user's life will bring ever more ad opportunities (and it doesn't matter if the HN base hates that notion, it's going to happen regardless). That'll happen over the next decade gradually.
Shopping, home management, tasks (taxes, accounting, lifestyle, reminders, homework, work work, 800 other things), travel (obvious), advice & general conversation (already there), search (being consumed now), gaming (next 3-5 years to start), full at-work integration (gradual spread across all industries, with more narrow expertise), digital world building (10-15+ years out for mass user adoption). And on the list goes. It's pretty much anything the user can or does touch in life.
> To be specific, search will be consumed by the LLMs, it'll be merely an aspect of what they do for the user, and that'll include handling the more intricate details of the search, refining the search, understanding the results of search, etc. The age of the typical user handling any of that is about to end.
We already have the tech for that, why hasn't it happened? People are revolted by the AI results in Google. AI isn't going to make people use their computers more. It's not opening up a new consumer market. This is just making each search infinitely more expensive.
I find searching chatgpt.com and asking for sources, then visiting them, works much better than Google to find niche topics
Every year I ask the latest version of Chat GPT a basic facts question about rugby results. It almost always gets it wrong - even when it does web search and cites sources. Wrong scores, hallucinated matches, wrong locations - just gob smacking amounts of wrongness.
The latest "Thinking" version gets it reliably right but spent about 3 minutes coming up with the answer that 10 seconds of googling answers.
So I don't believe we are currently in a situation where LLMs are an effective replacement for search engines.
yep google ai results are old too.
Who is revolted? I use the AI Google results every day when asking for specific questions, I rarely visit the webpages before anymore. Also Google already injects ads into conversations in the form of Google Shopping affiliate links.
>I rarely visit the webpages before anymore.
And what do you think this'll do for future LLM models that need to train on new content if web page traffic collapses?
I understand the concern but it's frankly not my problem as a user, that is for the authors and corporations to figure out. No one would (or should) blame car buyers for putting horse and buggies out of business, they're merely participating in the market as a consumer not the producer.
They won't figure it out. It's the tragedy of the commons.
Then that is how it will be, it's a self correcting problem in that if they don't figure it out, their models won't continue improving.
And web sites will collapse along with them. What do you think the 'corrected' state will look like? If you use the web it is your problem.
More people going into insular communities like discord or creating micro sites. Like I said it's a self correcting problem, either it is fixed or it's not. It's not my problem.
You see it already with how many people use LLMs for everything these days. Google Gemini can also integrate with your other Google apps to personalize further, and Gemini already has product placement ads.
Google is already dumping LLMs into search and it works well and is free.
It doesn't work well. The searches are wrong and uninformative much of the time.
Any examples of bad ones? I find them perfectly fine for my queries.
Search for anything mechanically car related and the results are terrible or wrong.
Do you have a concrete example I can reproduce? I searched for things like how to change the filter of X make and model and it seems correct, not sure if that's what you meant.
I'm not the person you replied to but I'm wondering which Google AI product you are referring to that you use for search which is so excellent that you need someone to find for you an example of it failing?
I think Google has several ai products with search features?
Which one in your experience "seems correct"?
I'm fascinated because I've never found any LLM to be particularly error free at search.
Google.com with the AI overview or whatever they call it now. It seems to source web page information for grounding so it's reasonably correct and doesn't hallucinate recently at least.
I played around with it and its better than it used to be but if you ask it something like
"Whats the name of the third book in the peripheral trilogy going to be" it just regurgitates some dumb reddit comment by someone who seems to be making things up.
There's no actual title that has been announced and the reddit post was not a reasonable bit of speculation.
The problem with these LLMs is they rarely say "the search results were not credible no response can be provided."
It works very poorly
It will not be lucrative if the hundreds of billions of dollars in ad revenue cost the providers trillions in compute. That's still the big question.
I think this is the right question. My search/chat is now 50% ChatGPT, 30% Google, and 20% Gemini. I have no idea the business implications of this.
For that matter, I don't know the bandwidth and compute cycle tradeoffs between traditional search and AI.
Google launched in 1998 and were running ads by 2000. Considering how much more access to adtech product talent there is for OAI a quarter of a century on, what explains their hesitation to pick that route and make billions? After all they had billions avaiable to acquire designer bauble maker Jony Ive's company.
The first AI company to cram their product full of ads will get roasted over the coals for it. My guess is they're all playing chicken and waiting to be the second to do it. I'd also guess that they're all already thinking about ways to introduce it that will generate the least backlash.
Google could do it in 2000 because their search was legitimately so much better, and also because their ads were comparatively more relevant and unobtrusive than modern ads. In comparison, LLMs are relatively similar in performance unless you're picky enough that you're probably already paying and thus wouldn't be in the ad-supported tier.
That said, I wonder if ads are even lucrative enough to move the needle relative to how much training costs are increasing with each generation.
People forget it took Google years of frog-boiling to get us to where we are now.
The first AI to insert blatant ads will be dumped for some other model overnight. Look at the Copilot "backlash" over their "product announcements".
Yep. Finally someone who knows how to think straight.
Google built up immense surplus and ate into it slowly.
OAI can't suddenly start cramming Ads as it fights to survive. Im sure they are employing questionable tactics to keep users hooked. Won't really work on a large enough user base to make the economics viable given the competition they face.
“The LLM usage will generate hundreds of billions of dollars in ad revenue”
And yet every attempt to extract even minimal ad revenue has been canned to date as something nobody wants with AI providers retreating in failure.
I don’t doubt that there’s “some” ad revenue to be had but there’s little evidence that ads are going to save the day here.
For several early years search was thought to have no great business model (banner ads and similar). And then it did.
GoTo.com -> Google -> $$$
These exact words were said tens of thousands of times about Facebook (am old enough to remember those discussions :) ), “no way they can monetize on mobile” (this was the most fun).
rules are simple, if you have Xbn or XXXm users on your system, you will make big bank in ads eventually
It's tempting to look at trends and assume there must be a rule behind them, but it's also intellectually lazy. Please do the hard work of justifying your stance like GGP did.
it is a simple stance - if you have a product that is used by hundreds of millions of people ad monetization strategy will be found cause there are people a lot smarter than you and me that will get it done. here’s intellectual challenge - find a business with comparable number of users to openai which is not swimming in ad revenue - one will do
A counterpoint is that there are many products with significant usage that fail or never attempt advertising monetization. They just increase the cost of the product.
Such as?
Snapchat
Total Quarterly Revenue (Q4 2024): $1.55 billion in total revenue, with $1.41 billion coming from advertising
Basically all their revenue is ad revenue and not too bad
At that time, Facebook provided a free service without any real competitors. The masses will switch to Meta AI or Gemini or Claude at the drop of an ad that annoys them enough.
Gemini, GPT and Claude will all have ads on the consumer side. They will go together in quasi lock-step into the ad future, because that money is gigantic and they're going to need it.
The masses will have no say in the matter. Just as they had no say in the matter with Google's ads getting ever more intrusive, or cable prices previously, or streaming prices going perpetually higher in the present, or YouTube ads, or anything else. Consumers will have no say in the matter, they'll take it and that's that.
With only three relevant competitors (maybe Mistral in Europe), there will be nowhere to flee the deployment of ads.
amazing this is even a debate, we have now decades of this across everything that reaches enough users, it is a certainty as much that the Sun will rise tomorrow morning. as probably many people here on HN I am designated computer-fixer for all my family so any family gathering I have to look at someone's computer about something. years ago I started checking whether browser(s) anything ad-blocking in place and I am 0 for million by now. while HN crowd might be theoretically pushing back on ads (even with like "I won't use this if there are ads" nonsense) general public is so used to ads that I sometimes feel it is welcomed change when some new service etc gets ads. I remember the first time I saw an ad on Amazon Prime Video and my daughter and I were like "no f'ing way!!!" and my wife was like "oh, ____ is on sale this weekend, cool!" :)
> Just take a look at the enterprise. Amazon's ad business alone is already a better business than Oracle or SAP or Salesforce, with superior margins, and it's growing faster too.
You can say the same about AWS and then prove the b2b case instead of ad case as well
AWS is legitimately a giant and it should be considered in enterprise broadly. It's infrastructure more than enterprise software of course, which is where Anthropic is at. Anthropic is not trying to host the world's databases and services (at present anyway). Anthropic will however help you write software to compete with Salesforce, Oracle, SAP, et al.
Google's ad business remains far larger and more profitable than AWS. And the advertising segment is drastically larger than the segment AWS is in. Just Google + Meta = nearing $600 billion in ad sales. Amazon will soon have their own $100 billion in ad sales.
I guess the question is how many more $100B of ad sales slots are available, aside from just stealing share from incumbents (who already took it from traditional media channels over last 20 years).
At some point someone needs to add value to the real economy, not just take an ad tax off the top.
I don't think advertising is entirely a zero-sum game (there is real value to everyone for steveBK123 to learn of a product that actually solves a real need or saves money, etc) - but it has to be something akin to it - the economy can't support five hundred trillion dollars in advertising spend.
Not interested in a service with ads throughout my workday, which is why I switched to Anthropic.
Billions in projected revenue is nothing but hype/cope. Google and Meta got their edge because their product was offered for "free" to the masses.
absolutely not the case. there isn’t a single nerve in human brains that goes “oh imma tolerate ads cause this shit’s free but if I pay a few bucks no way” - if the product you use has utility to you, you will tolerate ads provided no other acceptable alternative. not to tell you something you don’t already know but anthropic is getting ads, eventually, it is a given. so while today you may have an alternative (arguably better even if no ads in the equation) at some point you won’t have an alternative (other than running local) and you’ll tolerate ads. the thing with LLM ads is that companies can make $$$$ from “ads” you don’t see, i.e. I can (not now but in the future) companies to push my product, e.g. claude is setting up architecture and proposes upstash (which I own and am paying anthropic a lot of money) instead of any competitor. or even more silently adding dependencies on my NPM library which has free and commercial offering…
Anthropic is already an ad - for Anthropic. The uniquely "friendly" personality of their user-facing AI chatbot is far from accidental.
hm not sure I follow - the anthropic is selling itself to users that are already using it by being friendly to the users?
Yeah sure, but for me the common man OpenAI doesn't add any value that Claude, Gemini or Meta AI doesn't also provide.
If they want to out-ad those companies to the tune of billions, I'll go with the least annoying. OpenAI hasn't earned any loyalty.
to me and you sure, but what do you reckon how many of their MAU are just people for whom “AI” is ChaptGPT? 90+%?
Holy f'n Hell, there's such a blatant bias on HackerNews in favor of Anthropic and against OpenAI.
I'm just a user, and in my experience Claude has been consistently crap compared to ChatGPT/Codex.
I use both side-by-side, and have paid for a ChatGPT subscription every month for around 1 year, but only 2 months for Claude; once last year, and again since last month.
Everything from the sign up, the sign in, the payment, the UI, the UX, gosh, just sucks on Claude.
And the AI itself: SO. MUCH. "OoPs you're right! I was mistaken" BACKTRACKING! It's downright DANGEROUS to listen to it! God I can post screenshots of working on the same project and the same prompts with both agents and prove how worse Claude is.
Of course this comment will be downvoted by Anthropic's paid PR machine, because there's no way actual users who have tried both products would be so in favor of Claude.
I’ve been a paid subscriber for all three players since day 1. CC (Opus) has been a clear winner for agentic coding starting about 6 months ago. GPT5.4 reduced the gap somewhat but the gap is still there.
Yes I dont get it either. probably bots, paid posts.
> Of course this comment will be downvoted by Anthropic's paid PR machine, because there's no way actual users who have tried both products would be so in favor of Claude.
Sure, it couldn't possibly be that others have had a different experience. It couldn't even be that some people think OpenAI is nearly as gross as Palantir. It's that they're shills.
High-end analysis.
OpenAI != The AI industry
OpenAI has stagnated technologically, and is a financial zombie, but that's not true for every part of the industry. Once these early movers flame out, there will be more stability with Google, Microsoft, and AWS.
The circular deals are getting old - it's like rearranging the chairs on the Titanic's deck.
sell the roadmap, deliver a sku, sell/comp consulting services on escalations
the silicon valley shuffle, tried & true
All the “raises” consist of “committed capital” and all of the revenue is annualized.
Welcome to dot com 2.0
Why sunset sora instead of raising the price 100x?
Because to watch usage go to zero while charging what it actually costs to successfully run the service would immediately liquify the slow moving quicksand investors are currently standing in.
That plus the legal risk is too high, which gets added to the math of making copyright deals + computing, and they decided it didn't make sense at the moment. Even Grok is clamping down on the video side. Can't beat bad economics and lawyers/politicians coming down your throat no matter how good the product is.
To focus on other things.
100x of a small number could be less than 1x of a really large number from a product that they are more comfortable monetizing.
What they really should focus on is making those models more efficient. With them most likely losing money on inference (+model training + salaries + building data centers), I can't see why they would want more compute and more products, since more tokens spent is actually bad for them.
Making existing models more efficient won't make them God in a Box.
True but neither will going bankrupt.
They're all in a race to bankrupt the others, and then pivot and raise prices and go efficient fast enough to avoid their own bankruptcy.
We'll see if it works!
Ye of little faith. God in a Box will tell them how to not go bankrupt.
Except they already did this: if they had scaled 4.5 with RL, 5 would probably have been the leap we expected
If anything 4.5 being abandoned so they could sell India a $3 a month subscription was the first crack in The Box
Did you really mean to say 4.5? Gpt 4.5 used to cost $75/$150 per million tokens input/output. And it did not even seem to be that good to justify that. I would not expect many people were using it, and I doubt that "expanding to india" was what killed it (if it was that useful/popular they would have kept the api, or keep it for higher end subscriptions).
If anything it should have been no1 in the "openAI graveyard" website.
India in this context is a synecdoche for scaling consumer vs Anthropic's more enterprise-y route, but yes that's pretty much why we didn't get 4.5 with reasoning. Without reasoning, 4.5 had no future.
From Sam Altman himself:
> We had this big GPU crunch. We could go make another giant model. We could go make that, and a lot of people would want to use it, and we would disappoint them. And so we said, let’s make a really smart, really useful model, but also let’s try to optimize for inference cost. And I think we did a great job with that.
4.5 scaled into a unified reasoning model would have been an incredible model. It beat GPT-5 on accuracy and hallucinations without reasoning (!)
It just wouldn't have worked for powering things like ChatGPT Go's rollout and loginless chatgpt.com, so they dropped it.
(And if you want, you could argue it's the compute crunch that didn't let them do both... but Anthropic had to make the same choices at the time and went in the other direction.)
It's missing the voice mode that never reached the level they demoed, and then gradually went to shit from that.
The stargate, nvidia and amd deals are all linked together and the fallout is not public. Nvidia and amd stock seems to not care about it at all. Oracle fired 30000 employees, not sure if it’s to fund that initiative or a fall out of that
Had to move away from this thing. Claude is so much better. In every respect.
And if Forbes is reporting this, that means the actual movers and shakers were talking about this months ago.
Keep in mind this is a Forbes "Site", so basically a personal blog with some minor vetting.
Interesting. I never had much of an opinionon Forbes till a few years ago I noticed them posting nearly exclusively NYPost style clickbait. I didn’t think it was that bad of a publication.
Forbes "the publication" is still around somewhere and has some standards.
Forbes "sites" are just the bastard love child of LinkedIn, Medium, and Substack, and should be treated with the respect that deserves.
And that people are going to end up in jail - but only if they are under 30.
I’m not a mover and a shaker. I just have critical thinking skills.
My guess is Sam Altman is a better VC than CEO. Better at hype, networking, fund raising, and back room political hijinks than shipping a focused product
He seems to be trying to take almost a "venture studio" approach by throwing shit at the wall, but the problem with these things is always that the "internal startups" are "founded" by people who don't have enough incentive or control over their product to perform as well as an actual startup, and are distracted by internal politics. And frankly, it may also be that the really good founders will just do their own startup vs working on a quasi-startup inside a large org so there's some selection bias as well.
What he would be truly amazing at is shitcoin rug-pulling.
Isn't he already doing that with his Worldcoin thing?
He tried and messed that up too
I'd say he's a better CTO than CEO
He ran a small (30 employee) tech startup for 7 years
He was a partner at YC for 8 years
He has no research/PhD background in AI and is the CEO of an AI company
There is no objective data point in which he's a better CTO than a CEO
I'm not an OAI fanboy by a longshot - but I'd view lots of experiments that didn't work out as a healthy thing, especially for a company trying to find footing in a new industry.
It's not an experiment if you publicly showcase and create tens of millions worth of marketing materials on it.
Usually company "experiments" are typically hush hush, not blasted on every corporate media channel as a means to boost your company holdings.
I think the VC/investor community needs to take A LOT of blame here. They've created an insane rush to financialize everything to moon at the drop of a hat.
I mean, even Andresson-Horowitz was taking NFT's seriously as though they weren't a scam only a few years ago (https://a16z.com/the-nft-starter-pack-tools-for-anyone-to-an...).
These people are also looking (and funding) quantum computing companies as though quantum computing is right around the corner after AGI.
They need to cool their jets. AI is certainly a worthwhile and super important development, but it's still possible to go overboard with it.
Unfortunately I would bet OpenClaw will be on the list soon
Who is the person in the portrait at the top of the page?
The CEO himself.
For some reason, he does not look like a man whom I would trust with my money, but it appears that there are enough rich investors who disagree.
Threw me off because I have no idea what Altman looks like and the article opened with "OpenAI’s CEO of applications Fidji Simo..."
I asked an LLM today to take a word document and a PowerPoint template to “convert” the docx to a ppt. It asked some good questions like “it looks like this template is a title slide and content slide only, would you like all the content on the content slide?”
“Yes” I said, slightly impressed. It then asked me to clarify the subheadings, which were correct.
“Cool, this seems neat” I mused.
It generated the PowerPoint. There was not a single word on it from the docx, the header slide was devoid of words, and the 6 following content sliders were identical, and empty of words.
I suppose it’s cool that it used the correct template.
I did the work manually in 10 minutes after waiting around and responding to an LLM for 15.
What a fucking joke. “AI” is a term that we really need to stop fucking using.
Unfortunately I would bet OpenClaw is going to be on the list soon
The future of ChatGPT maybe well be as a Microsoft product.
So is OpenAI on track to overtake Google for discontinuing projects?
Has there ever been a period o time where people saw a bubble coming and that we were in one, but it just inexorably refused to pop/drug out this long? This isn’t a rhetorical question, I’m wondering how this period compares to other irrational periods of the economy like railroad fever etc.
Not at all, there is a famous saying (often attributed to Keynes but as far as I can tell he never said) “Markets can remain irrational longer than you can remain solvent.”
“But can the markets remain solvent longer than I can remain rational” is the real question.
In my lifetime: S&Ls, .com's, housing, and NFTs.
> Has there ever been a period o time where people saw a bubble coming and that we were in one, but it just inexorably refused to pop/drug out this long?
The housing bubble that peaked in 2006 was raised as an issue at least as early as 2000 and became a big topic of conversation in mid-to-late 2002, which is comparable to if we had started talking about an AI bubble roughly simultaneously with the release of GPT-3 and it had become a topic of wide concern shortly after the release of GPT-3.5.
So, in short, not only “this long”, but much longer.
It’s not been that long really. The dot com bubble was called a bubble for a while before it finally imploded. And just like now folks were in massive denial that it was a bubble.
One of the challenges here is that a lot of folks simply weren’t around then and haven’t seen what happens when everything implodes overnight. Those that have experienced it know what that looks like and know it will happen again.
What makes this time weird though is back then (and in most bubbles) the bubble was creating jobs - supposedly (I'm too young) anyone who could write a bit of HTML could get hired in the dot com boom.
Whereas this is a very weird bubble where it creates big pumps in some equity prices but apart from a tiny number of people who are directly involved in AI research etc. it's not created any jobs, in fact by creating uncertainty it's probably caused fewer jobs to be created.
What that means for labour market dynamics when it pops I really don't know
It's no coincidence that daytrading ascended with the dotcom era.
NFTs lasted a lot longer than they should have.
yes they did, Salesforce even came out with an "NFT Cloud" product.
Bubbles don't pop overnight. In the aftermath of any collapse, you can generally see a pretty clear pattern of red flags (and attempts to minimize them or cover them up). Some parties notice earlier than others, but the realization is generally a much more gradual process than the collapse.
Its obvious its coming soon simply because the mismatch between hype and expectations is far too large now. Hype is necessary to lure in investment but now its reached its peak imo.
The question is, is it a big bang or a slow release?
The bubble bursting has almost become eschatological for deniers. Keep praying that it will happen. It won't.
LLMs can be a massively transformative and valuable technology, and this would still be a bubble, there's no reason those two things can't be true at once.
In fact "pure" bubbles where the focus item is of literally no value (tulips, NFTs) are quite rare. Much more common are the bubbles based on an actual real transformative innovation (canals, railways, radio, internet, LLMs).
Railways did absolutely transform how travel worked in the UK, while simultaneously almost everyone who invested in them lost their shirts
Why the sudden pivot to agents and subagents? One shotting not good enough? Was a tech plateau reached? Or maybe one related to cost?
That's also what NFT hypebros said.
"Disney’s then-CEO Bob Iger... was sold on Sora, too. He lauded Altman’s ability to “look around corners”..."
WTF is that supposed to mean? I'm sorry, maybe I'm being dense. I can't figure out what "look around corners" is supposed to mean. "Think outside the box," I guess? Why "look around corners?"
I mean, maybe I do get it. Altman has a weird face that looks like you can't predict where his eyes are based on where his head is. "Shifty," one might say. But I doubt that's what Iger meant.
It's dumb. It's dumb corporate speak. I'm so sick of this kind of stuff getting a pass. We used to bully people over using the word "synergy." Let's make america anti-corporate-weasel again.
I read it as being able to see the future, which is still bullshit par excellence. The future is just around the corner as it were, but us normal people cannot see it, on account of both it being the future, and around a corner.
To be very clear, I think it's completely stupid.
Before he left I use to enjoy enraging a manager several layers above me. In one instance I explained that asking us to cut a few corners to get things done was fine, usually we can figure out acceptable ways of doing it. But then, it is your job to take those fake numbers and figure out how we are doing. No matter how much effort you make if bullshit goes in you know what will come out.
Now imagine an entire economy working like that. Like say, LLM's are good enough to run entire companies but you don't get to run a company because you are good at it. LLM's can perfectly manage employee schedules but the real job is more like marriage counseling or group therapy. Somewhere along the road we forgot which jobs make the economy go. They are probably the ones with the lowest salaries as those lack the effort of conjuring the job into existence.
Humanity needs obvious things cloths, food, housing, transportation etc but that isn't where the money is. The people cooking the books have the money and they are looking for something like a book cooking book. The market for openAI will be in lying convincingly for the benefit of the investor. Reality must be auctioned off like domain names or search engine placements. Altman is really the perfect guy for the job no one wants. ha-ha
Alternatively we could humble ourselves, ask the Chinese how reality works and attempt to steal their fu. It's just a thought.
Lying is a virtue.