Jeff Bezos says AI is in a bubble but society will get 'gigantic' benefits
cnbc.com
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The Dotcom boom was probably good for everyone in some way, but it was much, much better for the extremely wealthy people that have gained control of everything.
Even for the average person in America, the ability to do so many activities online that would have taken hours otherwise (eg. shopping, research, DMV/government activities, etc). The fact that we see negative consequences of this like social network polarization or brainrot doesn't negate the positives that have been brought about.
In poor countries, they may not have access to clean running water but it's almost guaranteed they have cell phones. We saw that in a documentary recently. What's good about that? They use cell phones not only to stay in touch but to carry out small business and personal sales. Something that wouldn't have been possible before the Internet age.
You are describing platform capture. Be it Google Search, YouTube, TikTok, Meta, X, App Store, Play Store, Amazon, Uber - they have all made themselves intermediaries between public and services, extracting a huge fee. I see it like rent going up in a region until it reaches maximum bearable level, making it almost not worth it to live and work there. They extract value both directions, up and down, like ISPs without net-neutrality.
But AI has a different dynamic, it is not easy to centrally control ranking, filtering and UI with AI agents. You can download a LLM, can't download a Google or Meta. Now it is AI agents that got the "ear" of the user base.
It's not like before it was good - we had a generation of people writing slop to grab attention on web and social networks, from the lowest porn site to CNN. We all got prompted by the Algorithm. Now that Algorithms is replaced by many AI agents that serve users more directly than before.
I guess another example of the same thing is power generation capacity, although this comes online so much more slowly I'm not sure the dynamics would work in the same way.
- better weather forecasts
- modeling intermittent generation on the grid to get more solar online
- drug discovery
- economic modeling
- low cost streaming games
- simulation of all types
Not to mean that we're still nowhere near close to solving the broadband coverage problem, especially in less developed countries like the US and most of the third world. If anything, it seems like we're moving towards satellite internet and cellular for areas outside of the urban centers, and those are terrible for latency-sensitive applications like game streaming.
There's still depreciation, but it's not the same. Also look at other forms of hardware, like RAM, and the bonus electrical capacity being built.
I have not seen the prices of GPUs, CPU or RAM going down, on the contrary, each day it gets more expensive.
Just as I'm getting to the point where I can see retirement coming from off in the distance. Ugh.
You can see that all across this discussion.
Honestly I think the most surprising thing about this latest investment boom has been how little debt there is. VC spending and big tech's deep pockets keep banks from being too tangled in all of this, so the fallout will be much more gentle imo.
Markets for electronics have momentum, and estimating that momentum is how chip producers plan for investment in manufacturing capacity, and how chip consumers plan for deprecation.
Of course this does make some moderate assumptions that it was a solid build in the first place, not a flimsy laptop, not artificially made obsolete/slow, etc. Even then, "install an SSD" and "install more RAM" is most of everything.
Of course, if you are a developer you should avoid doing these things so you won't get encouraged to write crappy programs.
And there will also be software infrastructure which could be durable. There will be improvements to software tooling and the ecosystem. We will have enormous pre-trained foundation models. These model weight artifacts could be copied for free, distilled, or fine tuned for a fraction of the cost.
That 40% has a very long shelf life.
Unfortunately, the energy component is almost entirely fossil fuels, so the global warming impact is pretty significant.
At this point, geoengineering is the only thing that can earn us a bit of time to figure...idk, something out, and we can only hope the oceans don't acidify too much in the meantime.
I am using x86 chips though.
The current AI bubble is leading to trained models that won't be feasible to retrain for a decade or longer after the bubble bursts.
As tempting as it is, it leads to false outcomes because you are not thinking about how this particular situation is going to impact society and the economy.
Its much harder to reason this way, but isnt that the point? personally I dont want to hear or read analogies based on the past - I want to see and read stuff that comes from original thinking.
This guy gets it - https://www.youtube.com/watch?v=kxLCTA5wQow
Instead of plainly jumping on the bubble bandwagon he actually goes through a thorough analysis.
AI is already making us wildly more productive. I vibe coded 5 deep ML libraries over the last month or so. This would have taken me maybe years before when I was manually coding as an MLE.
We have clearly hit the stage of exponential improvement, and to not invest basically everything we have in it would be crazy. Anyone who doesn’t see that is missing the bigger picture.
Why is it all these kinds of posts never come with any attachments? We are all interested to see it m8.
I had been mostly opposed to vibe coding for a long time, autocomplete was fine but full agentic coding just made a mess.
That’s changed now, this stuff is genuinely working on really hard problems.
Dot com crash followed by the web getting pretty popular and a bit central to business.
To all those betting big on AI before the crash:
Careful, Icarus.
The leap of faith necessary in LLMs to achieve the same feat is so large its very difficult to imagine it happening. Particularly due to the well known constraints on what the technology is capable of.
The whole investment thesis of LLMs is that it will be able to a) be intelligent b) produce new knowledge. If those two things that dont happen, what has been delivered is not commensurate to the risk in regards to the money invested.
Past bubbles leaving behind something of value is indeed no guarantee the current bubble will do so. For as many times as people post "but dotcom produced Amazon" to HN, people had posted that exact argument about the Blockchain, the NFT, or the "Metaverse" bubbles.
This is because many people have mistaken LLMs for AI, when they’re just a small subset of the technology - and this has driven myopic focus in a lot of development, and has lead to naive investors placing bets on golden dog turds.
I disagree on AI as a whole, however - as unlike previous technologies this one can self-ratchet and bootstrap. ML designed chips, ML designed models, and around you go until god pops out the exit chute.
What does that even mean?
pets.com was a fat loser only telling telling people that were going to fly.
Amazon was Icarus, they did something.
Vs weak commentators going on about the wax melting from their parents root cellar while Icarus was soaring.
Most of Y Combinator are not using AI they just say that and you're worried about the people who do things?
Icarus drowned in the sea.
Even if you want to put the world into only two lumps of cellar dwellers and Icaruses it is still a group of living people on one side and a floating/semi-submerged pile of dead bodies that are literally only remembered for how stupid their deaths were on the other.
Perhaps the most famous implosion of all was AOL who merged (sort of) with TimeWarner gaining the lion's share of control through market cap balancing. AOL fell so destructively that it nearly wiped out all the value of the actual hard assets that TW controlled pre-merger.
It’s different enough that it probably isn’t relevant.
It did, but not for the better. Quality of life and standard of living both declined while income inequality skyrocketed and that period of time is now known as The Great Divergence.
> He's (unsurprisingly) making an analogy to the dotcom bubble, which seems to me correct.
He's got no downside if he's wrong or doesn't deliver, he's promising an analogy to selling you a brand new bridge in exchange for taking half of your money... and you're ecstatic about it.
It will become so valuable so fast we struggle to comprehend it.
2022-2023 AI changed enough to be me to convert from skeptic, to a believer. I started working as an AI Engineer and wanted to be on the front lines.
2023-2024 Again, major changes, especially as far as coding goes. I started building very promising prototypes for companies, was able to build a laundry list of projects that were just boring to write.
2024-2025 My day to day usage has decreased. The models seem better at fact finding but worse for code. None of those "cool" prototypes from myself or anyone else I knew seemed to be able to become more than just that. Many of the cool companies I started learning about in 2022 started to reduce staff and are running into financial troubles.
The only area where I've been impressed is the relatively niche improvements in open source text/image to video models. It's wild that you can make sure animated films on a home computer now.
But even there I'm seeing no signs of "exponential improvement".
My experience has been that it was. I was using AI last year to build ML models about as well as I have been this year.
I'm not saying AI isn't useful, just that the progress certainly looks to be sigmoid not exponential in growth. By far the biggest year for improvement was 2022-2023. Early 2022 I didn't think any of the code assistants were useful, by 2023 I was able to use them more reliably. 2024 was another big improvement, but I honestly haven't felt the change (at least not for the better).
Some of the tooling may be better, but that has little do to with exponential progress in AI itself.
Elsewhere in AI however progress has been enormous, and many projects are only now reaching the point where they are starting to have valuable outputs. Take video gen for instance - it simply did not exist outside of research labs a few years ago, and now it’s getting to the point where it’s actually useful - and that’s just a very visible example, never mind the models being applied to everything from plasma physics to kidney disease.
The claim is "exponential" progress, exponential progress never seems "slow" after it has started to become visible.
I've worked in the research part of this space, there's neat stuff happening, but we are very clearly in the diminishing returns phase of development.
First were the models. Then the APIs. Then the cost efficiencies. Right now the tooling and automated workflows. Next will be a frantic effort to "AI-Everything". A lot of things won't make the cut, but absolutely many tasks, whole jobs, and perhaps entire subsets of industries will flip over.
For example you might say no AI can write a completely tested, secure, fully functional mobile app with one prompt (yet). But look at the advancements in Cline, Claude code, MCPs, code execution environments, and other tooling in just the last 6 months.
The whole monkeys typewriters shakespeare thing starts to become viable.
It's certainly possible that AI will improve this way, but I'd wager it's extremely unlikely. My sense is that what people are calling AI will later be recognized as obviously steroidal statistical models that could do little else than remix and regurgitate in convincing ways. I guess time will tell which of us is correct.
If the model is doing meaningful research that moves along the state of the ecosystem, then we are in the outer loop of self improvement. And yes it will progress because thats the nature of it doing meaningful work.
That's a lot of vague language. I don't really see any way to respond. I suppose I can say this much: the usefulness of a tool is not proof of the correctness of the predictions we make about it.
> And yes it will progress because thats the nature of it doing meaningful work.
This is a non sequitur. It makes no sense.
And I never said there's anything bad about or wrong with statistical models.
If anything it seems to me like we've just swapped coding with what is effectively a lot more code review (of whatever the LLM spits out), at the cost of also losing that long term understanding of a block of code that actually comes from writing it yourself (let's not pretend that a reviewer has the same depth of understanding of a piece of code as an author).
There will be point where ai will consistently write better prs - you can already start to see it here and there - finding and fixing bugs in existing code, refactoring, writing tests, writing and updating documentation and prototyping are some examples of areas where it often surpasses human contribution.
In the past the tradeoff has been very straight forward. But this is a unique situation because it involves knowledge and not just the physicality of the human in regards to productivity.
That was literally what everybody said would happen.
So the question, at least to me, is how these AI companies will find a product or service that makes them profitable. Other than becoming actual monopolies in their current domains.
Why three? Will you ever be in a position where one will do it for you?
> and most of my team is also paying money for various AI stuff.
And what are they using it for?
> Sounds like a real industry to me.
Sounds like early adopter syndrome to me. We'd have to know more about your business to take this out of the realm of hazy anecdotes.
I believe LLMs will be niche tools like databases, you pay for the product not 'gpt' vs 'claude'. You choose the right tool for the job.
I have a feeling coding tool with be separate a niche like Cursor, which LLM it uses doesn't matter. It's the integration, guard rails, prompt seeding, and general software stuff like autocomplete and managing long todos.
Then I pay for ChatGPT because that's my "personal" chat LLM that knows me and knows how I like curt short responses for my dumb questions.
Finally I pay for https://www.warp.dev/terminal as a terminal which replaced Kitty terminal on macos (don't use it for coding) which is another niche. Cursor could enter that arena but VSCode terminal is kinda limited for day-to-day stuff given it's hidden in an larger IDE. Maybe a pure CLI tool will do both better.
These companies are burning cash to support the current formulation of AI services.
These services will survive because they are useful but probably not at its current cost
The lie is that LLMs are the product itself rather than the endless integration opportunities via APIs and online services.
For example:
- Dotcom bubble. Of course making website was and is a real industry.
- Japanese real estate bubble. Of course building houses was and still is a real industry. It's so real people call it real estate, right.
Also nit: Typo right in the digest I assume, assuming “suring” is “during”, does cnbc proofread their content?
One smug English faculty said, "well it's not that hard. You just look for dashes in their writing."
I responded with, "you know you can just tell it not to use those, right?"
Blank stares.
I hate it.
Banning advanced graph calculators on undergrad math exams is not because "they don't want to use new tools", either.
That would cause a lot of pain for those shareholders, but would that be somewhat contained given the public "AI" companies for the most part have strong businesses outside of AI? Or are these market caps at this point so large for some of these AI public companies that anything that happens to them will cause some kind of contagion? And then the follow up is if the private AI companies collapse en masse is that market now also so big that it would cause contagion beyond venture capital and their investors (fully aware that pensions and the such are material investors in VC funds, but they're diversified so even though they'd see those losses maybe the broader market would keep them from taking major hits).
Not giving an opinion here, though my knee jerk is to think we're due for a massive drop, but I've literally been saying that for so long that I'm starting to (stupidly) think this time is different (which typically is when all hell breaks loose of course).
Also keep in mind that the biggest companies during that bubble had peak market caps of ~500B and then lost ~90%, so 400-500B in losses each and total internet related losses of a couple trillion. If NVDA lost 90%, it would be down 4 trillion dollars, or twice that total just by itself.
AI company valuations collapsing would have meaningful impacts on the broader market. Big pension/mutual funds are important sources of capital across every sector, and if they're taking big losses on NVDA, GOOG, and a portfolio of privates, it will have a chilling effect on their other activity.
Theres also plenty of money washing around in private markets so no need to go public. Staying private is an advantage.
However, it is different from the internet bubble partially for the reason you describe.
There have been a few IPOs, but they perhaps happened earlier in the cycle, or companies are pivoting into AI. I'm thinking companies like Palantir, which was always AI, or Salesforce which is making a big AI pivot.
Most of the funding is not coming from public sectors. There is so much private capital available that it isn't necessary. I believe the bubble is in VC, which some would think is find because it protects public markets from the crash, but I'm not sure that is correct.
When the VC money stops flowing into AI, I think it will send a shockwave through the public markets. The huge valuations of companies like OpenAI, Anthropic, etc will be repriced, which will probably force a re-pricing of public darlings like Palantir, Microsoft, NVIDIA.
If VC funds aren't buying NVIDIA chips and building data centers, everyone will feel the need to re-price.
It's emotional, not logical.
The big advantage of staying private is controlling the narrative.
Then you have the busts that follow public equity fueled bubbles (Dotcom crash). Nowhere near as bad as the former, but still a moderate impact on the economy due to the widely dispersed nature of the equity holdings and the resulting wealth effect.
What we have now is more of a narrowly held private equity bubble (acknowledging that there's still an impact through the SP500 given widespread index investing). If OpenAI, Anthropic, Perplexity, and a bunch of AI startups go bust, who loses money and what impact does it have on the rest of the economy?
Also, there s no need to invent new tech names anymore. Marketing can add "AI" to the company name, or (as they say), change the wording from "Loading..." to "Thinking.."
Thus when it is realised that this investment cannot produce the necessary returns, there will simply be no next model. People will continue using the old models, but they will become more and more out of date, and less and less useful, until they are not much more than historical artifacts.
My point is that the threshold for continuing this process (new models) is very big (getting bigger each time?), so the 'pop' will be a step function to zero.
If it's just to catch up with newly discovered knowledge or information then that's not the model, they can just train again with an updated dataset and probably not need to train from scratch.
Life. A great example can be seen in the AI-generated baseball-related news articles that involve the Athletics organization. AI articles this year have been generating articles that incorrectly state that the Atlanta Braves played in games that were actually played by the Athletics, and the reason is due to the outdated training model. For the last 60 years before 2025, the Athletics played in Oakland, and during that time their acronym was OAK. In 2025, they left Oakland for Sacramento, and changed their acronym to ATH. The problem is that AI models are trained on 60 years of data where 1. team acronyms are always based on the city, rather than the mascot of the team, and 2. acronyms OAK = Athletics, ATL = Atlanta Braves, and ATH = nothing. As a result, an AI model that doesnt have context "OAK == ATH in the 2025 season" will see ATH in the input data, associates ATH with nothing in it's model, and will then erroneously assume ATH is a typo for ATL.
There is no reality in which LLMs go away (shy of being replaced).
I don't think we can assume that people producing what appear to be addictive services are going to do that, especially when they seem to be addicted themselves.
If it costs $10B to add 1 year of data to an existing model, every year, that doesn’t sound too good.
Yes: you'll be homeless and living under a bridge, but you'll have an LLM therapist on your phone to console you. That's a benefit!
The rich already have a diminishing returns situation with money. Everyone else has much more upswing.
The long tail may be closer to what I want, but the quality is also generally lower. YouTube just doesn’t support a team of talented writers, Amazon is mostly filled with junk, etc.
Social media and gig work is a mixed bag. Junk e-mail etc may not be a big deal, but those kinds of downsides do erode the net benefit.
Just to use your example: YouTube is filled with talented writers and storytellers, who would have never been able to share their content in the past. *And* the traditional media complex is richer than ever.
I don’t think average quality matters. Just what you want to consume.
If anything, I’d be more open to the opposite argument. Media is so much richer and more engaging that it actually makes our lives worse. The quality of the drugs is too high!
I’ll grant that for comparatively wealthy, privileged people who were always going to have an easy time (which frankly include me), the internet has been a mixed bag.
But for the kids growing up in comparatively poor countries, who can now access all of the world’s information, entertainment, and economy.. I think it’s a pretty clear win.
I expect AI will be similar: perhaps not a huge boon to the best off, but a substantial improvement for most people in the world. Even if we can sit back and say “oh, but they also get misinformation and lower quality YouTube content”
Also, knocking that almost decade off my birthday would assure that I spent most of my adult life with the luxury of thinking that energy didn't have negative externalities that were being forced on later generations.
We had Chomsky-esq "any major world power is kind of fascist if you think about it" instead of literal talk by politicians about putting people in camps if they don't like your diet or country of origin.
TV was pretty bad I guess but music was great and I read more back then.
There was a lot of huffing and puffing about gang violence. I grew up on the street the local gang named themselves after and it only marginally touched my life at all.
Housing was dirt cheap, food was dirt cheap, gas was dirt cheap. There was undeveloped land everywhere around the city I live in and it gave a general sense of potential.
What exactly was so bad about the 90's?
AI harder to tell. Will 2026 models kick 2025 ass or just be slightly better. Who knows.
1. Amazon files the most petitions for H1-B work visas after Indian IT shops. 2. Amazon opposed minimum wage increase to $15/hr until 2018! 3. Amazon not only fires union organizers, it's claiming National Labor Relations Board is unconstitutional!
AI increases everyone’s knowledge and ultimately productivity. It’s on every person the learn to leverage it. The dynamics don’t need to change, we just move faster and smarter
This is incomplete in key ways: it only increases knowledge if people practice information literacy and validate AI claims, which we know is an unevenly-distributed skill. Similarly, by making it easier to create disinformation and pollute public sources of information, it can make people less knowledgeable at the same time they believe they are more informed. Neither of those problems are new, of course, but they’re moving from artisanal to industrial scale.
Another area where this is begging questions is around resource allocation. The best AI models and integrations cost money and the ability to leverage them requires you to have an opportunity to acquire skills and use them to make a living. The more successfully businesses are able to remove or deprofessionalize jobs, the smaller the pool will be of people who can afford to build skills, compete with those businesses, or contribute to open source software. Twenty years ago, professional translators made a modest white collar income; when AI ate those jobs, the workers didn’t “learn to leverage” AI, they had to find new jobs in different fields and anyone who didn’t have the financial reserves to do that might’ve ended up in a retail job questioning whether it’s even possible to re-enter the professional class. That’s great for people like Bezos until nobody can afford to buy things, but it’s worse for society since it accelerates the process of centralizing money and power.
Open source in particular seems likely to struggle here: with programmers facing financial downturns, fewer people have time to contribute and if AI is being trained on your code, you’re increasingly going to ask whether it’s in your best interests to literally train your replacement.
Totally agree with this
>The more successfully businesses are able to remove or deprofessionalize jobs, the smaller the pool will be of people who can afford to build skills, compete with those businesses, or contribute to open source software
I'm mixed on this, ultimately its the responsibility of individuals to adapt. AI makes people way more capable than they have ever been. It's on them to make something of it
> but it’s worse for society since it accelerates the process of centralizing money and power.
I'm not sure this is true, it enables individuals like they never have been before. Yes there are the model infrastructure providers, but they are in a race to the bottom
Society with a capital S are the beneficiaries of the bubble.
AWS and Facebook have extremely low running costs per VPS or Ad sold. That IMO is one of the major reasons tech has received its enormously high valuation.
There is nuance to that, but average investors are dumb and don't care.
Add in a relatively high fixed-cost commodity into the accounting, and intuitively the pitch of "global market domination at ever lower costs" will be a much harder sell. Especially if there is a bubble pop that hurts them.
How are you defining rich, Billionaires? It's sad that your comment is the top post.
When I say benefits to humanity, I don't mean the AI slop, deepfakes and laziness enabler that we have today. There are niche applications of AI that already show great potential. Like developing new medicines to devising new treatments for dangerous diseases, solving long standing mathematical problems, creating new physics theories. And who knows? Perhaps even create viable solutions for the climate crisis that we are in. They don't receive as much attention as they deserve, because that's not where the profit lies in AI. Solving real problems require us to forgo profits in the short term. That's why we can't leave this completely up to the billionaires. They will just use it to transfer even more wealth from the poor and middle classes to themselves.
~ 120 to 190 million daily active users
~ 800 million weekly active users
~ 450 million to over 800 million depending on the data source and methodology.
Get a grip. Hundreds of millions of people are using it, most of them for free. I would say "society" has benefited.
This has to be peak HN.
Create the fastest growing consumer product in history.
HN anon: yes, but who will benefit?
The only thing you have to worry about are not non-rich people, but people without any motivation. The difference of course is that the framing you're using makes it easy to blame "The System", while a motivation-based framing at least leaves people somewhat responsible.
Wealth may get you a seat closer to the table, but everyone is already invited into the room.
You’re imagining the world we have today, but with AI.
In reality it’ll be a world that’s completely different, and most likely in a worse way, and AI is the tool used to make it worse.
Now, ask yourself, what happens when workers lose the only leverage they have against the owner class: their labor? A capitalist economy can only function if workers are able to sell their labor for wages to the owner class, creating a sort of equilibrium between capital and work.
Once AI is able to replace a significant part of workers, 99% of humans on Earth become redundant in the eyes of the owner class, and even a threat to their future prosperity. And they own everything, the police and army included.
Take that for what it is.
Don't they think everyone is a pawn in their money moving games?
At the end of the day though it’s how the system is designed. It’s the needed forrest fire that wipes out overgrowth and destroys all but the strongest trees.
The company I reviewed didn't seem like a great investment, but I don't even think that matters right now.
This is the blind spot that will cause many to lose their shirts, and is also why people are wrong about AI being a bubble. LLMs are a bubble within an overall healthy growth market.
You're in the top 10% in the US if you make $170k/yr.
When you're in your 50s or 60s, the mortgage is repaid, and if nothing blew up, you probably also have a million or two in your 401k, so at that point, it's actually not that hard for a person who had a decent career in the SF Bay Area to be worth $4M+. And many FAANG retirees will probably flirt with $10M+ if they don't spend too much.
Remind me again why we need investors to fund bad ideas? The whole premise of western capitalism is that investors can better align with the needs of the society and the current technological reality.
If the investors aren't the gurus we make them to be, we might as well do with a planning committee. We could actually end up with more diversified research.
"Under socialism, a lot of experimental ideas get funded, the good ideas and the bad ideas. And the planning committee have a hard time in the middle of this excitement, distinguishing between the good ideas and the bad ideas. ... But that doesn't mean anything that is happening isn't real."
A lot of good ideas only look bad in hindsight. It costs time and money to determine goodness, and that deserves funding.
Governments can also do that funding. The most pivotal technologies in recent history have been a result of government investment.
Private capital has a role, but it's mostly at the productization phase, not fundamental research.
The whole point of capitalism is that one is entitled to the consequences of their own stupidity or the lack thereof. The investors are more willing to take the risks because their losses are bounded - they are risking only as much as they are willing, rather than their status in an organization. Of course once all investors ends up investing into the same bubble there is no real advantage over a committee.
Early stage investors generally fund a portfolio of multiple ideas, where each idea faces great uncertainty - some investments will do tremendously well, some won't. Invstors don't need every investment to do well due to the assymmetry of outcomes (a bad investment can at worst go down 100%, a good investment can go up 10,000%, paying off many bad investments).
> The whole premise of western capitalism is that investors can better align with the needs of the society and the current technological reality.
This is not the premise of capitalism, it's the justification for it - it's generally believed that capitalism leads to better outcomes over time than communism, but that doesn't mean capitalism has 0 wasteage or results in 0 bad decisions.
Under socialism bureaucrats risk someone else's money.
We are not in a pure capitalistic society, we also have States, central Banks with central planning expending over half the money in Europe and USA and more than half in Asia.
As a European myself that see the public money being wasted by incompetent people and filling the pockets of politicians, specially marxist ones. For example, the money Spain received after COVID filled so many socialist pockets and has not given information back to Europe as of how it was spent(it was spent on their own companies of friend and family).
Except for the "institutional investors".
Also, the cost of most of the stuff I (have to) buy (i.e. rent, groceries, ...) is not dominated by the wage of knowledge workers.
Or to put it differently: If AI makes me lose my job but doesn't decrease my rent, I'm in a really bad position.
Agreed. So I don't think it's a bubble.
Will also be good for consumers in the long-term: much faster pace of drug discovery and new tech generally.
The hard trades and manual labor services we consume for everything that matters daily? That's not going to be made cheaper by AI.
Could some let Bezos know that he doesn’t truly represent society in any way?
(oh, and keep on eye on all those 'internet scanners', 'script kiddies' using AWS for scans/attacks, honey pot time?).
And again I'm baffled on how they would light such good will and functionality on fire.
And that's what causes bubbles but at this point it should be clear that AI will make a substantial impact - at least as great as the internet, likely larger
See how that works? A few nerds think it's great while everyone else gets screwed by it.
I would use AI to create extensions for my use than trust someone else's.
Yes. Cheap, second hand, datacenters.
Would you mind elaborating on that? I’m not quite sure what you mean.
As an owner of a web host that probably sees advantage to increased bot traffic, this statement is just more “just wait AI will be gigantic any minute now, keep investing in it for me so my investments stay valuable”.
But of course, every company needs to slap AI on their product now just to be seen as a viable product.
Personally, I look forward to seeing the bubble burst and being left with a more rational view of AI and what it can (and can not) do.
Every company seems to be putting all their eggs in the AI basket. And that is causing basic usability and feature work to be neglected. Nobody cares because they are betting that AI agents will replace all that. But it won't and meanwhile everything else about these products will stagnate.
It's a disasterous strategy and when it comes crashing down and the layoffs start, every CEO will get a pass on leading this failure because they were just doing what everyone else is doing.
The challenge is the rest of the industry funding dead companies with billions of dollars on the off chance they replicate OpenAI’s success.
Some other company, that doesn't have a giant pile of debt will then pick up the pieces and make some money though. Once we dig out of the resulting market crash.
Uber and Amazon are really bad examples. Who was Amazons competition? Nobody. By the time anyone woke up and took them seriously it was too late.
Uber only had to contend with Lyft and a few other less funded firms. Less funded being a really important thing to consider. Not to mention the easy access to immense amounts of funding Uber had.
it was making money off those idea at the valuations expected that was problem.
the Internet really did revolutionize things, in substantial ways, but not to the tune of millions of dollars for pets.com
And everybody used them.
Nowdays everybody see them as useless.
AI is more useful than social media. This is not financial advice, but I lean more toward not a bubble.
A lot of us clocked the crypto bullshit waaaay before the crash.
I'm sorry what crash are you talking about?
S Jobs called it back in 1995-97 - he referred to it as shopping for information and shopping for good and services.
Nobody has this crystal clear, tangible vision re. LLMs. Nobody at all. That is a big problem.
I found the interview: https://www.youtube.com/watch?v=MqSfFcaluHc&t=1700s
It was more of web 2.0 company.
Ultimately it doesn't matter who survives the AI bubble, because they are all more or less equivalent, proposing the same technical solution.
Sure, many of these "thin prompt wrapper around the OpenAI API" product "businesses" will all be gone within a few years. But AI? That is going to be here indefinitely.
The "it'll make all your devs 6x as productive by the end of the year" types of promises. But those probably explain the valuations
The technology - for what it is being used vs what is invested - does not match up at all. This is what happened to the dot-com bubble. Theres was a whole bunch of innovation that was needed to come to bring a delightful UX to bring swathes of people onto the internet.
So far this is true about LLMs. Could this change? Sure. Will it change meaningful? Personally I dont believe so.
The internet at its core was all about hooking up computers so they they could transform from just computational beasts to communication. There was a tremendous amount of potentitial that was very very real. It just so happens if computers can communicate we can do a whole bunch of stuff - as is going on today.
What are LLMS? Can someone please explain in a succint way...? Im yet to see something super crystal clear.
The dotcom bubble was not about "the internet" itself. The Internet was fine and pretty much already proven as a very useful communication tool. It was about business that made absolutely no sense getting extremely high valuations just because they operated - however vaguely - over the internet.
Generative AI have never reached the level of usability of the Internet itself, and likely never will.
Yeah, sure some side benefits to people. AI is still a nuclear weapon against labor in the capital - labor (haves - haves not), and will start pushing wealth inequality to the Egyptian pharoah.
The only good news for plebians is that virtual reality entertainment means you just need a little closet to live in.
Overall, this just leads up to further demographic decline, which as an environmental malthusian I would welcome in the initial stages to get us down from our current level, but I also suspect it would turn into an economic downward spiral, especially with AI, where the oligarchs have such total authoritarian control and monopoly on resources that humanity basically stops having kids at all.
"AI is in a bubble but billionaires will get 'gigantic' benefits"
I see no benefit to anyone unless you can live off your stock portfolio and can easily ride through periods where your portfolio can suffer a 50% loss.
Everyone not directly involved seems to want AI to pop. I'm not sure if that says anything about its longevity. Not very fun to have a bubble that feels bad on both sides.
(title fixed now)
Title needs to be changed to something like
"Bezos says AI is in industrial bubble yet promises huge benefits"
This is what he acknowledges.