Not sure the dial-up analogy fits, instead I tend to think we are in the mainframe period of AI, with large centralised computing models that are so big and expensive to host, only a few corporations can afford to do so. We rent a computing timeshare from them (tokens = punch cards).
I look forward to the "personal computing" period, with small models distributed everywhere...
> I look forward to the "personal computing" period, with small models distributed everywhere...
One could argue that this period was just a brief fluke. Personal computers really took off only in the 1990s, web 2.0 happened in the mid-2000s. Now, for the average person, 95%+ of screen time boils down to using the computer as a dumb terminal to access centralized services "in the cloud".
The personal computing era happened partly because, while there were demands for computing, users' connectivity to the internet were poor or limited and so they couldn't just connect to the mainframe. We now have high speed internet access everywhere - I don't know what would drive the equivalent of the era of personal computing this time.
> We now have high speed internet access everywhere
As I travel a ton, I can confidently tell you, that this is still not true at all, and I’m kinda disappointed that the general rule of optimizing for bad reception died.
I work on a local-first app for fun and someone told me I was simply creating problems for myself and I could just be using a server. But I'm in the same boat as you. I regularly don't have good internet and I'm always surprised when people act like an internet connection is a safe assumption. Even every day I go up and down an elevator where I have no internet, I travel regularly, I go to concerts and music festivals, and so on.
I don't even travel that much, and still have trouble. Tethering at the local library or coffee shops is hit or miss, everything slows down during storms, etc.
Centralized only became mainstream when everything started to be offered "for free". When it was buy or pay recurrently more often the choice was to buy.
I don't know, I think you're conflating content streaming with central compute.
Also, is percentage of screentime the relevant metric? We moved TV consumption to the PC, does that take away from PCs?
Many apps moved to the web but that's basically just streamed code to be run in a local VM. Is that a dumb terminal? It's not exactly local compute independent...
It is true that browsers do much more computation than "dumb" terminals, but there are still non-trivial parallels. Terminals do contain a processor and memory in order to handle settings menus, handle keyboard input and convert incoming sequences into a character array that is then displayed on the screen. A terminal is mostly useless without something attached to the other side, but not _completely_ useless. You can browse the menus, enable local echo, and use device as something like a scratchpad. I once drew up a schematic as ascii art this way. The contents are ephemeral and you have to take a photo of the screen or something in order to retain the data.
Web browsers aren't quite that useless with no internet connection, some sites do offer offline capabilities (for example gmail). but even then, the vast majority of offline experiences exist to tide the user over until network can be re-established, instead of truly offering something useful to do locally. Probably the only mainstream counter-examples would be games.
Nearly entirety of the use cases of computers today don't involve running things on a 'personal computer' in any way.
In fact these days, every one kind of agrees as little as hosting a spreadsheet on your computer is a bad idea. Cloud, where everything is backed up is the way to go.
Umm... I had a PC a decade before the web was invented, and I didn't even use the web for like another 5 years after it went public ("it's an interesting bit of tech but it will obviously never replace gopher...")
The killer apps in the 80s were spreadsheets and desktop publishing.
In time Mainframes of this age will make a come back.
This whole idea that you can connect lots of cheap low capacity boxes and drive down compute costs is already going away.
In time people will go back to thinking compute as a variable of time taken to finish processing. That's the paradigm in the cloud compute world- you are billed for the TIME you use the box. Eventually people will just want to use something bigger that gets things done faster, hence you don't have to rent them for long.
Depends on the app, and the personal device. Mobile devices are increasingly thin clients. Of course hardware-wise they are fully capable personal computers, but ridiculous software-imposed limitations make that increasingly difficult.
I mean, Chromebooks really aren't very far at all from thin clients. But even my monster ROG laptop when it's not gaming is mostly displaying the results of computation that happened elsewhere
I'm not questioning whether the Ipad can be used as a client in some capacity, or whether people tend to use it as a client. I question whether the Ipad is a thin client. The answer to that question doesn't lie in how many applications require an internet connection, but in how many applications require local computational resources.
The Ipad is a high performance computer, not just because Apple think that's fun, but out of necessity given its ambition: the applications people use on it require local storage and rather heavy local computation. The web browser standards if nothing else have pretty much guaranteed that the age of thin clients is over: a client needs to supply a significant amount of computational resources and storage to use the web generally. Not even Chromebooks will practically be anything less than rich clients.
Going back to the original topic (and source of the analogy), IOS hosts an on-device large language model.
As with everything, the lines are a bit blurred these days. We may need a new term for these devices. But despite all the compute and storage and on-device models these supercomputers are barely a step above thin clients.
IPads are incredibly advanced. Though I guess you mean they don't use anything that requires more sophistication from the user (or something like that)?
That 'average' is doing a lot of work to obfuscate the landscape. Open source continues to grow (indicating a robust ecosystem of individuals who use their computers for local work) and more importantly, the 'average' looks like it does not necessarily due to a reduction in local use, but to an explosion of users that did not previously exist (mobile first, SAAS customers, etc.)
The thing we do need to be careful about is regulatory capture. We could very well end up with nothing but monolithic centralized systems simply because it's made illegal to distribute, use, and share open models. They hinted quite strongly that they wanted to do this with deepseek.
There may even be a case to be made that at some point in the future, small local models will outperform monoliths - if distributed training becomes cheap enough, or if we find an alternative to backprop that allows models to learn as they infer (like a more developed forward-forward or something like it), we may see models that do better simply because they aren't a large centralized organism behind a walled garden. I'll grant that this is a fairly polyanna take and represents the best possible outcome but it's not outlandishly fantastic - and there is good reason to believe that any system based on a robust decentralized architecture would be more resilient to problems like platform enshittification and overdeveloped censorship.
At the end of the day, it's not important what the 'average' user is doing, so long as there are enough non-average users pushing the ball forward on the important stuff.
The small mind could have an advantage if it is closer or more trustworthy to users.
It only has to be good enough to do what we want. In the extreme, maybe inference becomes cheap enough that we ask “why do I have to wake up the laptop’s antenna?”
Abundant resources could enable bad designs. I could in particular see a lot of commercial drive for huge models that can solve a bazillion different use cases, but aren't efficient for any of them.
There might be also local/global bias strategies. A tiny local model trained on your specific code/document base may be better aligned to match your specific needs than a galaxy scale model. If it only knows about one "User" class, the one in your codebase, it might be less prone to borrowing irrelevant ideas from fifty other systems.
I don't want to send sensitive information to a data center, I don't want it to leave my machine/network/what have you. Local models can help in that department.
You could say the same about all self-hosted software, teams with billions of dollars to produce and host SaaS will always have an advantage over smaller, local operations.
Makes me want to unplug and go back to offline social media. That's a joke. The dominant effect was networked applications getting developed, enabling community, not a shift back to client terminals.
Even the most popular games (with few exceptions) present as relatively dumb terminals that need constant connectivity to sync every activity to a mainframe - not necessarily because it's an MMO or multiplayer game, but because it's the industry standard way to ensure fairness. And by fairness, of course, I mean the optimization of enforcing "grindiness" as a mechanism to sell lootboxes and premium subscriptions.
And AI just further normalizes the need for connectivity; cloud models are likely to improve faster than local models, for both technical and business reasons. They've got the premium-subscriptions model down. I shudder to think what happens when OpenAI begins hiring/subsuming-the-knowledge-of "revenue optimization analysts" from the AAA gaming world as a way to boost revenue.
But hey, at least you still need humans, at some level, if your paperclip optimizer is told to find ways to get humans to spend money on "a sense of pride and accomplishment." [0]
> Why would companies sell you the golden goose when they can instead sell you an egg every day?
Because someone else can sell the goose and take your market.
Apple is best aligned to be the disruptor. But I wouldn’t underestimate the Chinese government dumping top-tier open-source models on the internet to take our tech companies down a notch or ten.
By that logic none of us should be paying monthly subscriptions for anything because obviously someone would disrupt that pricing model and take business away from all the tech companies who are charging it? Especially since personal computers and mobile devices get more and more powerful and capable with every passing year. Yet subscriptions also get more prevalent every year.
If Apple does finally come up with a fully on-device AI model that is actually useful, what makes you think they won't gate it behind a $20/mo subscription like they do for everything else?
> By that logic none of us should be paying monthly subscriptions for anything because obviously someone would disrupt that pricing model and take business away from all the tech companies who are charging it?
Non sequitur.
If a market is being ripped off by subscription, there is opportunity in selling the asset. Vice versa: if the asset sellers are ripping off the market, there is opportunity to turn it into a subscription. Business models tend to oscillate between these two for a variety of reasons. Nothing there suggets one mode is infinitely yielding.
> If Apple does finally come up with a fully on-device AI model that is actually useful, what makes you think they won't gate it behind a $20/mo subscription like they do for everything else?
If they can, someone else can, too. They can make plenty of money selling it straight.
It's also that same Apple that fights tooth and nail every single attempt to let people have the goose or even the promise of a goose. E.g. by saying that it's entitled to a cut even if a transaction didn't happen through Apple.
It's a lot more complicated than that. They need to be able to take the island very quickly with a decapitation strike, while also keeping TSMC from being sabotaged or destroyed, then they need to be able to weather a long western economic embargo until they can "break the siege" with demand for what they control along with minor good faith concessions.
It's very risky play, and if it doesn't work it leaves China in a much worse place than before, so ideally you don't make the play unless you're already facing some big downside, sort of as a "hail Mary" move. At this point I'm sure they're assuming Trump is glad handing them while preparing for military action, they might even view invasion of Taiwan as defensive if they think military action could be imminent anyhow.
> then they need to be able to weather a long western economic embargo until they can "break the siege" with demand for what they control along with minor good faith concessions
And you know we'd be potting their transport ships, et cetera, from a distance the whole time, all to terrific fanfare. The Taiwan Strait would become the new training ground for naval drones, with the targets being almost exclusively Chinese.
You could say the same thing about Computers when they were mostly mainframe. I am sure someone will figure out how to make it commoditized just like personal computers and internet.
And notably, those phones and tablets are intentionally hobbled by the device owners (Apple, Google) who do everything they can to ensure they can't be treated like personal computing devices. Short of regulatory intervention, I don't see this trend changing anytime soon. We're going full on in the direction of more locked down now that Google is tightening the screws on Android.
They didn't create them, but PC startups like Apple and Commodore only made inroads into the home -- a relatively narrow market compared to business. It took IBM to legitimize PCs as business tools.
> I look forward to the "personal computing" period, with small models distributed everywhere...
Like the web, which worked out great?
Our Internet is largely centralized platforms. Built on technology controlled by trillion dollar titans.
Google somehow got the lion share of browser usage and is now dictating the direction of web tech, including the removal of adblock. The URL bar defaults to Google search, where the top results are paid ads.
Your typical everyday person uses their default, locked down iPhone or Android to consume Google or Apple platform products. They then communicate with their friends over Meta platforms, Reddit, or Discord.
The decentralized web could never outrun money. It's difficult to out-engineer hundreds of thousands of the most talented, most highly paid engineers that are working to create these silos.
Ok, so Brave Browser exists - if you download, you will see 0 ads on the internet, I've never really seen ads on the internet - even in the before brave times.
Fr tho, no ads - I'm not making money off them, I've got no invite code for you, I'm a human - I just don't get it. I've probably told 500 people about Brave, I don't know any that ever tried it.
I don't ever know what to say. You're not wrong, as long as you never try to do something else.
Funny you would pick this analogy. I feel like we’re back in the mainframe era. A lot of software can’t operate without an internet connection. Even if in practice they execute some of the code on your device, a lot of the data and the heavyweight processing is already happening on the server. Even basic services designed from the ground up to be distributed and local first - like email (“downloading”) - are used in this fashion - like gmail. Maps apps added offline support years after they launched and still cripple the search. Even git has GitHub sitting in the middle and most people don’t or can’t use git any other way. SaaS, Electron, …etc. have brought us back to the mainframe era.
It's always struck me as living in some sort of bizaro world. We now have these super powerful personal computers, both handheld (phones) and laptops (My M4 Pro smokes even some desktop class processors) and yet I use all this powerful compute hardware to...be a dumb terminal to someone else's computer.
I had always hoped we'd do more locally on-device (and with native apps, not running 100 instances of chromium for various electron apps). But, it's hard to extract rent that way I suppose.
I don't even understand why computer and phone manufacturers even try to make their devices faster anymore, since for most computing tasks, the bottleneck is all the data that needs to be transferred to and from the modern version of the mainframe.
There are often activities that do require compute though. My last phone upgrade was so Pokemon Go would work again, my friend upgrades for the latest 4k video or similar.
We have a ton of good, small models. The issues are:
1. Most people don't have machines that can run even midsized local models well
2. The local models are nearly as good as the frontier models for a lot of use cases
3. There are technical hurdles to running local models that will block 99% of people. Even if the steps are: download LM Studio and download a model
Maybe local models will get so good that they cover 99% of normal user use cases and it'll be like using your phone/computer to edit a photo. But you'll still need something to make it automatic enough that regular people use it by default.
That said, anyone reading this is almost certainly technical enough to run a local model. I would highly recommend trying some. Very neat to know it's entirely run from your machine and seeing what it can do. LM Studio is the most brainless way to dip your toes in.
As the hype is dying down it's becoming a little bit clearer that AI isn't like blockchain and might be actually useful (for non generative purposes at least)
I'm curious what counts as a midsize model; 4B, 8B, or something larger/smaller?
What models would you recommend? I have 12GB of vram so anything larger than 8B might be really slow, but i am not sure
The "enshittification" hasn't happened yet. They'll add ads and other gross stuff to the free or cheap tiers. Some will continue to use it, but there will be an opportunity for self-hosted models to emerge.
> Like 50% of internet users are already interacting with one of these daily. You usually only change your habit when something is substantially better.
No, you usually only change your habit when the tools you are already using are changed without consulting you, and the statistics are then used to lie.
this -- chips are getting fast enough both arm n x86. unified memory architecture means we can get more ram on devices at faster throughput. we're already seeing local models - just that their capability is limited by ram.
I actually don’t look forward to this period. I have always been for open source software and distributism — until AI.
Because if there’s one thing worse than governments having nuclear weapons, it’s everyone having them.
It would be chaos. And with physical drones and robots coming, it woukd be even worse. Think “shitcoins and memecoins” but unlike those, you don’t just lose the money you put in and you can’t opt out. They’d affect everyone, and you can never escape the chaos ever again. They’d be posting around the whole Internet (including here, YouTube deepfakes, extortion, annoyance, constantly trying to rewrite history, get published, reputational destruction at scale etc etc), and constant armies of bots fighting. A dark forest.
And if AI can pay for its own propagation via decentralized hosting and inference, then the chance of a runaway advanced persistent threat compounds. It just takes a few bad apples, or even practical jokers, to unleash crazy stuff. And it will never be shut down, just build and build like some kind of kessler syndrome. And I’m talking about with just CURRENT AI agent and drone technology.
Funny how this guy thinks he knows exactly what's up with AI, and how "others" are "partly right and wrong." Takes a bit of hubris to be so confident. I certainly don't have the hubris to think I know exactly how it's all going to go down.
The problem is that the bubble people are so unimaginative, similar to Krugman, that those who have any inkling of an imagination can literally feel like visionaries compared to them. I know I’m describing Dunning-Krueger, but so be it, the bubble people are very very wrong. It’s like, man, they really are unable to imagine a very real future.
It’s a weird comparison since internet in the dial-up age was a bubble, are you saying the hype machine for AI is in fact smaller than the internet? Are you implying that AI will in fact grow that much more slowly and sustainably than the internet, despite trillions of investment?
Do you think Sam Altman, Jeff Bezos, and Mark Zuckerberg are all wrong saying that we’re in a bubble? Do they “lack imagination?”
Also? What do I need imagination for, isn’t that what AI does now?
I find the argument for the bubble to be extremely straightforward.
Currently, investment into AI exceeds the dot-com bubble by a factor of 17. Even in the dot-com era, the early internet was already changing media and commerce in fundamental ways. November is the three-year anniversary of ChatGPT. How much economic value are they actually creating? How many people are purchasing AI-generated goods? How much are people paying for AI-provided services? The value created here would have to exceed what the internet was generating in 2000 by a factor of 17 (which seems excessive to me) to even reach parity with the dot-com bubble.
"But think where it'll be in 5 years"—sure, and let's extrapolate that based on where it is now compared to where it was 3 years ago. New models present diminishing returns. 3.5 was groudbreaking; 4 was a big step forward; 5 is incremental. I won't deny that LLMs are useful, and they are certainly much more productized now than they were 3 years ago. But the magnitude of our collective investment in AI requires that a huge watershed moment be just around the corner, and that makes no sense. The watershed moment was 3 years ago. The first LLMs created a huge amount of potential. Now we're realizing those gains, and we're seeing some real value, but things are also tapering off.
Surely we will have another big breakthrough some day—a further era of AI which brings us closer to something like AGI—but there's just no reason to assume AGI will crop up in 2027, and nothing less that that can produce the ROI that such enormous valuations will eventually, inexorably, demand.
I don’t get why people find it so hard to understand that a technology can be value-additive and still be in a position of massive overinvestment. Every generation of Californians seeks to relive the 1848 gold rush, spending millions excavating rivulets for mere ounces of (very real!) gold.
> Even in the dot-com era, the early internet was already changing media and commerce in fundamental ways.
I agree that AI is overhyped but so was the early web. It was projected to do a lot of things ”soon”, but was not really doing that much 4 years in. I don’t think the newspapers or commerce were really worried about it. The transformation of the business landscape took hold after the crash.
This is not true. Obviously the underlying effect is real but not nearly to this scale—for instance, neither the CPI nor the S&P500 are even remotely close to 17x higher than they were at the turn of the millennium.
Almost everyone I hear calling our AI hype machine a bubble aren't claiming AI is a short term fluke. They're saying the marketing doesn't match the reality. The companies don't have the revenue they need. The model performance is hitting the top of the S curve. Essentially, this is the first big wave - but it'll be a while before the sea level rises permanently.
It’s not just a marketing stunt, it’s a trillion dollar grift that VCs are going to try to dump off onto the public markets when the reality doesn’t catch up to the hype fast enough
The only problem is, similarity with dotcom might only go thus far. For example, dotcom bubble itself might not have a similar thing in the past at that time. This is because the overall world context is different and interaction of social, political and economic forces is different.
So, when people say something about future, they are looking into the past to draw some projections or similar trends, but they may be missing the change in the full context. The considered factors of demand and automation might be too few to understand the implications. What about political, social and economic landscape? The systems are not so much insulated to study using just a few factors.
> Expensive software engineers and their labor costs limited what companies could afford to build.
This is clearly false, as is obvious to anyone who has done any software engineering. The big corps are in no shortage of capital and could just add more engineers if this were true. But we know what happens when you add more people to a project.
Rather, there are other more fundamental constraints, like the complexity of software and our ability to grasp and manipulate it. I think the argument would have been better if it focused on that. It'd be more based.
Which is a long-winded way of saying that I agree with others here that this article is full of hubris. I hope you got those chicks on Substack clapping for you, at least. Fast lane to getting laid for sure.
I'm getting ai fatigue. It's ok to rewrite quick emails that i'm having brain farts on but anything deep it just sucks. I certainly can't see paying for it.
Weird because AI has been solving hard problems for me. Even finding solutions that I couldn’t find myself. Ie. sometimes my brain cant wrap around a problem, I throw it to AI and it perfectly solves it.
Calculate the return on investment for a solar installation of a specified size on a specified property based on the current dynamic prices of all of the panels, batteries, inverter, and balance of system components, the current zoning and electrical code, the current cost of capital, the average insolation and weather taking into account likely changes in weather in the future as weather instability increases due to more global increase of temperature, the chosen installation method and angle, and the optimal angle of the solar panels if adjusted monthly or quarterly. Now do a Manual J calculation to determine the correct size of heat pump in each section of that property, taking into account number of occupants, insulation level, etc.
ChatGPT is currently the best solar calculator on the publicly accessible internet and it's not even close. It'll give you the internal rate of return, it'll ask all the relevant questions, find you all the discounts you can take in taxes and incentives, determine whether you should pay the additional permitting and inspection cost for net metering or just go local usage with batteries, size the batteries for you, and find some candidate electricians to do the actual installation once you acquire the equipment.
Edit: My guess is that it'd cost several thousand dollars to hire someone to do this for you, and it'll save you probably in the $10k-$30k range on the final outcomes, depending on the size of system.
It is weird that AI is solving hard problems for you. I can't get it to do the most basic things consistently, most of the time it's just pure garbage. I'd never pay for "AI" because it wastes more of my time than it saves. But I've never had a problem wrapping my head around a problem, I solve problems.
I'm curious what kind of problem your "brain cant wrap around", but the AI could.
I'm curious what kind of problem your "brain cant wrap around", but the AI could.
One of the most common use cases is that I can't figure out why my SQL statement is erroring or doesn't work the way it should. I throw it into ChatGPT and it usually solves it instantly.
Yes. To me, it is. Sometimes queries I give it are 100-200 lines long. Sure, I can solve it eventually but getting an "instant" answer that is usually correct? Absolutely priceless.
It's pretty common for me to spend a day being stuck on a gnarly problem in the past. Most developers have. Now I'd say that's extremely rare. Either an LLM will solve it outright quickly or I get enough clues from an LLM to solve it efficiently.
In this case, the original author stated that AI only good for rewriting emails. I showed a much harder problem that AI is able to help me with. So clearly, my problem can be reasonably described as “hard” relative to rewriting emails.
I work with some very complex queries (that I didn't write), and yeah, AI is an absolute lifesaver, especially in troubleshooting situations. What used to take me hours now takes me minutes.
In my case, Learning new stuff is one place I see AI playing major role. Especially the academic research which is hard to start if you are newbie but with AI I can start my research, read more papers with better clarity.
Great analysis but one thing overlooked is that current gen advanced AI could in five or ten years (or less) be run from the smartphone or desktop, which could negate all the capex from the hyperscalers and also Nvidia, which presents a massive target for competitors right now. The self same AI revolution we’re seeing created right now could take itself down if AI tooling becomes widespread.
> If you told someone in 1995 that within 25 years [...] most people would find that hard to believe.
That's not how I remember it (but I was just a kid so I might be misremembering?)
As I remember (and what I gather from media from the era) late 80s/early 90s were hyper optimistic about tech. So much so that I distinctly remember a ¿german? TV show when I was a kid where they had what amounts to modern smartphones, and we all assumed that was right around the corner. If anything, it took too damn long.
Were adults outside my household not as optimistic about tech progress?
To your point, AT&T's "You Will" commercials started airing in 1993 and present both an optimistic and fairly accurate view of what the future would look like.
To be fair, that has been a Sci-Fi trope for at least 130 years and predates the invention of the car itself (e.g. personal wings/flying horse -> flying ship -> personal balloon -> flying automobile). So countless generations have been waiting for that :)
That’s how I remember it too. The video is from 1999, during the height of the dot-com bubble. These experts are predicting that within 10 years the internet will be on your phone, and that people will be using their phones as credit cards and the phone company would manage the transaction, the prediction actually comes pretty close to the prediction made by bitcoin enthusiasts.
> The other claims that AI will create more jobs than it destroys.
Maybe it's my bubble, but so far I didn't hear someone saying that. What kind of jobs should that be, given that both forms, physical and knowledge work, will be automatable sooner or later?
That claim just reads like he's concocted two sides for his position to be the middle ground between. I did that essays in high school but I try to be better than that now.
The article seems well researched, has some good data, and is generally interesting. It's completely irrelevant to the reality of the situation we are currently in with LLMs.
It's falling into the trap of assuming we're going to get to the science fiction abilities of AI with the current software architectures, and within a few years, as long as enough money is thrown at the problem.
All I can say for certain is that all the previous financial instruments that have been jumped on to drive economic growth have eventually crashed. The dot com bubble, credit instruments leading to the global financial crisis, the crypto boom, the current housing markets.
The current investments around AI that we're all agog at are just another large scale instrument for wealth generation. It's not about the technology. Just like VR and BioTech wasn't about the technology.
That isn't to say the technology outcomes aren't useful and amazing, they are just independant of the money. Yes, there are Trillions (a number so large I can't quite comprehend it to be honest) being focused into AI. No, that doesn't mean we will get incomprehensible advancements out the other end.
AGI isn't happening this round folks. Can hallucinations even be solved this round? Trillions of dollars to stop computers lying to us. Most people where I work don't even realise hallucinations are a thing. How about a Trillion dollars so Karen or John stop dismissing different viewpoints because a chat bot says something contradictory, and actually listen? Now that would be worth a Trillion dollars.
Imagine a world where people could listen to others outside of their bubble. Instead they're being given tools that re-inforce the bubble.
While I mostly agree with the article's premise (that AI will cause more software development to happen, not less) I disagree with two parts:
1. the opening premise comparing AI to dial-up internet; basically everyone knew the internet would be revolutionary long before 1995. Being able to talk to people halfway across the world on a BBS? Sending a message to your family on the other side of the country and them receiving it instantly? Yeah, it was pretty obvious this was transformative. The Krugman quote is an extreme, notable outlier, and it gets thrown out around literally every new technology, from blockchain to VR headsets to 3DTVs, so just like, don't use it please.
2. the closing thesis of
> Consider the restaurant owner from earlier who uses AI to create custom inventory software that is useful only for them. They won’t call themselves a software engineer.
The idea that restaurant owners will be writing inventory software might make sense if the only challenge of creating custom inventory software, or any custom software, was writing the code... but it isn't. Software projects don't fail because people didn't write enough code.
Before I got my first full time software engineering gig (I had worked part time briefly years prior) I was working full time as a carpenter. We were paying for an expensive online work order system. Having some previous experience writing software for music in college and a couple /brief/ LAMP stack freelance jobs after college I decided to try to write my own work order system. It took me like a month and it would never have never scaled, was really ugly, and had the absolute minimum number of features. I could never had accepted money from someone to use it but it did what we needed and we ran with it for several years after that.
I was only able to do this because I had some prior programming experience but I would imagine that if AI coding tools get a bit better they would enable a larger cohort of people to build a personal tool like I did.
I don't think his quote is that extreme and it was definitely not obvious to most people. A common thing you heard even around 95 was "I've tried internet but it was nothing special".
> basically everyone knew the internet would be revolutionary long before 1995. Being able to talk to people halfway across the world on a BBS? Sending a message to your family on the other side of the country and them receiving it instantly? Yeah, it was pretty obvious this was transformative.
That sounds pretty similar to long-distance phone calls? (which I'm sure was transformative in its own way, but not on nearly the same scale as the internet)
Do we actually know how transformative the general population of 1995 thought the internet would or wouldn't be?
In 1995 in France we had the minitel already (like really a lot of people had one) and it was pretty incredible, but we were longing for something prettier, cheaper, snappier and more point to point (like the chat apps or emails).
As soon as the internet arrived, a bit late for us (I'd say 1999 maybe) due to the minitel's "good enough" nature, it just became instantly obvious, everyone wanted it. The general population was raving mad to get an email address, I never heard anyone criticize the internet like I criticize the fake "AI" stuff now.
People keep comparing the AI boom to the Dotcom bubble. They’re wrong. Others point to the Railway Mania of the 1840s — closer, but still not quite right.
The real parallel is Canal Mania — Britain’s late-18th-century frenzy to dig waterways everywhere. Investors thought canals were the future of transport. They were, but only briefly.
Today’s AI runs on GPUs — chips built for rendering video games, not thinking machines. Adapting them for AI is about as sensible as adapting a boat to travel across land. Sure, it moves — but not quickly, not cheaply, and certainly not far.
It works for now, but the economics are brutal. Each new model devours exponentially more power, silicon, and capital. It just doesn't scale.
The real revolution will come with new, hardware built for the job (that hasn't been invented yet) — thousands of times faster and more efficient. When that happens, today’s GPU farms will look like quaint relics of an awkward, transitional age: grand, expensive, and obsolete almost overnight.
I think specialized hardware will emerge for specific proven workloads (transformer inference, for example), but GPUs won't become obsolete. They'll remain the experimentation platform for new architectures. You need flexibility to discover what's worth building custom silicon for.
Think 3D printers versus injection molds: you prototype with flexibility, then mass-produce with purpose-built tooling. We've seen this pattern before too. CPUs didn't vanish when GPUs arrived for graphics. The canal analogy assumes wholesale replacement. Reality is likely more boring: specialization emerges and flexibility survives.
I think it'll be a combination of hardware of course, but also better software - surely there is a better way of doing this (like our brains do) which will eventually require less power
I recall the unit economics making sense for all these other industries and bubbles (short of maybe tulips, which you could plant…) . Sure there were over-valuation bubbles because of speculatory demand, but right now the assumption seems to be “first to AGI wins” but that… may not happen.
The key variable for me in this house of cards is how long folks will wait before they need to see their money again, and whether these companies will go in the right direction long enough given these valuations to get to AGI. Not guaranteed and in the meantime society will need to play ball (also not a guarantee)
> Regardless of which specific companies survive, this infrastructure being built now will create the foundation for our AI future - from inference capacity to the power generation needed to support it.
Does that comparison with the fiber infra from the dotcom era really hold up? Even when those companies went broke, the fiber was still perfectly fine a decade later. In contrast, all those datacenters will be useless when the technology has advanced by just a few years.
Nobody is going to be interested in those machines 10 years from now, no matter if the bubble bursts or not. Data centers are like fresh produce. They are only good for a short period of time and useless soon after. They are being constantly replaced.
how much does the correction here hew to making an AI model just look like standardized API calls with predictable responses? If you took away all the costs (data centers, water consumption, money, etc) I still wouldn't use an LLM as a first choice because it's wrong enough of the time to make it useless -- I have to verify everything it says, which is how I would have approached a task in the first place. If we put that analogy into manufacturing, it's "I have to QA everything off of the line _without exception_ and I get frequent material waste"
If you make the context small enough, we're back at /api/create /api/read /api/update /api/delete; or, if you're old-school, a basic function
People tend to equate this to the railroad boom when saying that infrastructure spending will yield durable returns into the future no matter what.
When the railroad bubble popped we had railroads. Metal and sticks, and probably more importantly, rights-of-way.
If this is a bubble, and it pops, basically all the money will have been spent on Nvidia GPUs that depreciate to 0 over 4 years. All this GPU spending will need to be done again, every 4 years.
Hopefully we at least get some nuclear power plants out of this.
Yeah, the short-lived GPU deprecation cycle does feel very relevant here.
I'm still a fan of the railroad comparisons though for a few additional reasons:
1. The environmental impact of the railroad buildout was almost incomprehensibly large (though back in the 1800s people weren't really thinking about that at all.)
2. A lot of people lost their shirts investing in railroads! There were several bubbly crashes. A huge amount of money was thrown away.
3. There was plenty of wasted effort too. It was common for competing railroads to build out rails that served the same route within miles of each other. One of them might go bust and that infrastructure would be wasted.
There's a lot more to infrastructure spending than GPUs. Companies are building data centers, cooling systems, power plants (including nuclear), laying cables under oceans, launching satellites. Bubble or not, all of this will continue to be useful for decades in the future.
Heck if nothing else all the new capacity being created today may translate to ~zero cost storage, CPU/GPU compute and networking available to startups in the future if the bubble bursts, and that itself may lead to a new software revolution. Just think of how many good ideas are held back today because deploying them at scale is too expensive.
A bunch of the money is being spent on data centers and their associated cooling and power systems and on the power plants and infrastructure. Those should have much longer depreciation schedules.
What percentage of data centre build costs are the GPUs vs power stations, water cooling plants, buildings, roads, network, racks, batteries, power systems, etc
>> basically all the money will have been spent on Nvidia GPUs that depreciate to 0 over 4 years
I agree the depreciation schedule always seems like a real risk to the whole financial assumptions these companies/investors make, but a question I've wondered:
- Will there be an unexpected opportunity when all these "useless" GPUs are put out to pasture? It just seems like saying a factory will be useless because nobody wants to buy an IBM mainframe, but an innovative company can repurpose a non-zero part of that infrastructure for another use case.
Railroads need repair too? Not sure if it's every 4 years. Also, the trains I take to/from work are super slow because there is no money to upgrade.
I think we may not upgrade every 4 years, but instead upgrade when the AI models are not meeting our needs AND we have the funding & political will to do the upgrade.
Perhaps the singularity is just a sigmoid with the top of the curve being the level of capex the economy can withstand.
For what it's worth they cost a lot less than highways to maintain. Something like the 101 in the Bay Area costs about $40,000 per lane-mile per year, or about $240,000.
Trains are closer to $50-100,000 per mile per year.
If there's no money for the work it's a prioritization decision.
Imagine the progress we could have made on climate change if this money had been funneled into that, instead of making some GPU manufacturers obscenely wealthy.
I think the hardware infrastructure may be obsolete but at the moment we are still just beginning to figure out how to use AI. So the knowledge will be the important thing that’s left after the bubble. The current infrastructure will probably be as obsolete as dial up infrastructure.
This is precisely why the AI bubble is so much worse than previous bubbles: the main capital asset that the bubble is acquiring is going to depreciate before the bubble's participants can ever turn a profit. Regardless of what AI's future capabilities are going to be, it's physically impossible for any of these companies to become profitable before the GPUs that they have already purchased are either obsolete or burnt out from running under heavy load.
“But the fact that some geniuses were laughed at does not imply that all who are laughed at are geniuses. They laughed at Columbus, they laughed at Fulton, they laughed at the Wright brothers. But they also laughed at Bozo the Clown.”
Because some notable people dismissed things that wound up having profound effect on the world, it does not mean that everything dismissed will have a profound effect.
We could just as easily be "peak Laserdisc" as "dial-up internet".
I was happy to come into this thread and see I was not the first person for whom that quote came to mind. The dial-up Internet comparison implicitly argues for a particular outcome of current AI as a technology, but doesn't actually support that argument.
There's another presumably unintended aspect of the comparison that seems worth considering. The Internet in 2025 is certainly vastly more successful and impactful than the Internet in the mid-90s. But dial-up itself as a technology for accessing the Internet was as much of a dead-end as Laserdisc was for watching movies at home.
Whether or not AI has a similar trajectory as the Internet is separate from the question of whether the current implementation has an actual future. It seems reasonable to me that in the future we're enjoying the benefits of AI while laughing thinking back to the 2025 approach of just throwing more GPUs at the problem in the same way we look back now and get a chuckle out of the idea of "shotgun modems" as the future.
It's more like the Segway era when people with huge stakes in Segway tried to convince the world we were about to rebuild entire cities around the new model.
The vast majority of the dot-com comparison that I personally see are economic, not technological. People (or at least the ones I see) are claiming that the bubble mechanics of e.g. circular trading and over-investments are similar to the dot-com bubble, not that the AI technology is somehow similar the internet (it obviously isn’t). And to that extent we are in the year 1999 not 1995.
When this article are claiming both sides of the debate, I believe only one of them are real (the ones hyping up the technology). While there are people like me who are pessimistic about the technology, we are not in any position of power, and our opinion on the matter is basically a side noise. I think a much more common (among people with any say in the future of this technology) is the believe that this technology is not yet at a point which warrants all this investment. There were people who said that about the internet in 1999, and they were proven 100% correct in the months that followed.
My head canon is that the thing that preemptively pops the bubble is Apple coming out and saying, very publicly, that AI is a dead end, and they are dropping it completely (no more half assed implicit promises).
And not just that, they come out with an iPhone that has _no_ camera as an attempt to really distance themselves from all the negative press tech (software and internet in particular) has at the moment.
Keyboards were replaced with a touch screen alternative that effectively does the same job though. What is the alternative to a camera? Cameras are way too useful on a mobile device for anyone to even consider dropping them IMO.
That would require people that know about AI to actually choose to cancel it - which nobody that actually knows what AI can do, would ever actually do.
The Apple engineers, with their top level unfettered access to the best Apple AI - they'll convince shareholders to fund it forever, even if normal people never catch on.
> 1. Economic strain (investment as a share of GDP)
> 2. Industry strain (capex to revenue ratios)
> 3. Revenue growth trajectories (doubling time)
> 4. Valuation heat (price-to-earnings multiples)
> 5. Funding quality (the resilience of capital sources)
> His analysis shows that AI remains in a demand-led boom rather than a bubble, but if two of the five gauges head into red, we will be in bubble territory.
This seems like a more quantitative approach than most of "the sky is falling", "bubble time!", "circular money!" etc analyses commonly found on HN and in the news. Are there other worthwhile macro-economic indicators to look at?
It's fascinating how challenging it is meaningfully compare current recent events to prior economic cycles such as the y2k tech bubble. It seems like it should be easy but AFAICT it barely even rhymes.
Besides your chart, another point along these lines is that the article cites Azhar claiming multiples are not in bubble territory while also mentioning Murati getting essentially infinite price multiple. Hmmmm...
It's clear that AI is useful. It's not yet clear how useful. Hype has always obscured real value, and nobody knows the real value until the hype cycle completes.
What is clear, is that we have strapped a rocket to our asses, fueled with cash and speculation. The rocket is going so fast we don't know where we're going to land, or if we'll land softly, or in a very large crater. The past few decades have examples of craters. Where there are potential profits, there are people who don't mind crashing the economy to get them.
I don't understand why we're allowing this rocket to begin with. Why do we need to be moving this quickly and dangerously? Why do we need to spend trillions of dollars overnight? Why do we need to invest half the fucking stock market on this brand new technology as fast as we can? Why can't we develop it in a way that isn't insanely fast and dangerous? Or are we incapable of decisions not based on greed and FOMO?
Who is "we" ? I certainly don't spend trillions on frivolities. I think the Saudis via Softbank do, and these people build fake cities in the desert, they are by definition dumb money.
They earn so much from oil and are so keenly aware this will stop, they'd rather spend a trillion on a failure, than keep that cash rotting away with no future investment.
No project, no country, can swallow the Saudi oil money like Sam Altman can. So, they're building enormous data centers with custom nuclear plants and call that Stargate to syphon that dumb money in. It's the whole business model of Softbank: find a founder whose hubris is as big as Saudi stupidity.
It took a long long time going from a walking bike to the one we know now. It's not going to be different from AI. Transformers will only get us so far and for the rest we need another tock. AGI is not going to happen with this generation of hardware. We are hitting spatial scaling limits in video and image generation and we are hitting limits with LLMs.
Mass production of telephone line modems in the United States began as part of the SAGE air-defense system in 1958, connecting terminals at various airbases, radar sites, and command-and-control centers to the SAGE director centers scattered around the United States and Canada.
Shortly afterwards in 1959, the technology in the SAGE modems was made available commercially as the Bell 101, which provided 110 bit/s speeds. Bell called this and several other early modems "datasets".
> Couldn't AI like be their custom inventory software?
Absolutely not. It's inherently a software with a non-zero amount of probability in every operation. You'd have a similar experience asking an intern to remember your inventory.
Like I enjoy Copilot as a research tool right but at the same time, ANYTHING that involves delving into our chat history is often wrong. I own three vehicles, for example, and it cannot for it's very life remember the year, make and model of them. Like they're there, but they're constantly getting switched around in the buffer. And once I started positing questions about friend's vehicles that only got worse.
But you should be able to say "remember this well" and AI would know it needs a reliable database instead of relying on its LLM cache or whatever. Could it not just spin up Postgres in some Codex Cloud like a human developer would? Not today but in a few years?
Nice article, but somewhat overstates how bad 1995 was meant to be.
A single image generally took nothing like a minute. Most people had moved to 28.8K modems that would deliver an acceptable large image in 10-20 seconds. Mind you, the full-screen resolution was typically 800x600 and color was an 8-bit palette… so much less data to move.
Moreover, thanks to “progressive jpeg”, you got to see the full picture in blocky form within a second or two.
And of course, with pages was less busy and tracking cookies still a thing of the future, you could get enough of a news site up to start reading in less time that it can take today.
One final irk is that it’s little overdone to claim that “For the first time in history, you can exchange letters with someone across the world in seconds”. Telex had been around for decades, and faxes, taking 10-20 seconds per page were already commonplace.
I feel like this article is too cute. The internet, and the state of the art of computing in general has been driven by one thing and one thing alone: Moore’s Law. In that very real sense, it means that the semiconductor and perhaps more generally even just TSMC is responsible for the rise of the internet and the success of it.
We’re at the end of Moore’s Law, it’s pretty reasonable to assume. 3nm M5 chips means there are—what—a few hundred silicon atoms per transistor? We’re an order of magnitude away from .2 nm which is the diameter of a single silicon atom.
My point is, 30 years have passed since dial up. That’s a lot of time to have exponentially increasing returns.
There’s a lot of implicit assumption that “it’s just possible” to have a Moore’s Law for the very concept of intelligence. I think that’s kinda silly.
Moore's law has very little to do with the physical size of a single transistor. It postulates that the speed and capability of computers will double every few years. Miniaturization is one way to get that increase, but there are other ways.
>The internet, and the state of the art of computing in general has been driven by one thing and one thing alone: Moore’s Law.
You're wrong here... the one thing driving the internet and start of the art computing is money. Period. It wouldn't matter if Moore never existed, and his law was never a thing, money would still be driving technology to improve.
> The one thing driving the internet and state of the art computing is money
You're kind of separating yin from yang and pretending that one begot the other. The reason so much money flooded into chip fab was because compute is one of the few technologies (the only technology?) with recursive self improvement properties. Smaller chip fab leads to more compute, which enabled smaller chip fabs though research modeling. Sure: and it's all because humans want to do business faster. But TSMC literally made chips the business and proved out the pure play foundry business model.
> Even if Moore's Law was never a thing
Then arguably in that universe, we would have eventually hit a ceiling, which is precisely the point I'm trying to make against the article: it's a little silly to assume there's an infinite frontier of exponential improvement available just because that was the prior trend.
> Moore's Law has very little to do with the physical size of a single transistor
I mean it has everything to do with the physical size of a single transistor, precisely because of that recursive self improvement phenomenon. In a universe where moore's law doesn't exist, in 2025 we wouldn't be on 3nm production dies, and compute scale would have capped off decades ago. Or perhaps even a lot of other weird physical things would probably be different, like maybe macroscopic quantum phenomena or just an entire universe that is one sentient blob made from the chemical composition of cheeto dust.
I would go so far as to say we are still in the computing dial-up era. We're at the tail end, maybe - we don't write machine code any longe, mostly, and we've abstracted up a few levels but we're still writing code. Eventually computing is something that will be everywhere, like air, and natural language interfaces will be nearly exclusively how people interact with computing machines. I don't think the idea of 'writing software' is something that will stick around, I think we're in a very weird and very brief little epoch where that is a thing.
Recently, in my city, the garbage trucks started to come equipped with a device I call "The Claw" (think Toy Story). The truck drives to your curb where your bin is waiting, and then The Claw extends, grasps the bin, lifts it into the air and empties the contents into the truck before setting it down again.
The Claw allows a garbage truck to be crewed by one man where it would have needed two or three before, and to collect garbage much faster than when the bins were emptied by hand. We don't know what the economics of such automation of (physical) garbage collection portend in the long term, but what we do know is that sanitation workers are being put out of work. "Just upskill," you might say, but until Claw-equipped trucks started appearing on the streets there was no need to upskill, and now that they're here the displaced sanitation workers may be in jeopardy of being unable to afford to feed their families, let alone find and train in some new marketable skill.
So no, we're in the The Claw era of AI, when business finds a new way to funge labor with capital, devaluing certain kinds of labor to zero with no way out for those who traded in such labor. The long-term implications of this development are unclear, but the short-term ones are: more money for the owner class, and some people are out on their ass without a safety net because this is Goddamn America and we don't brook that sort of commie nonsense here.
FYI, this kind of garbage truck has been around for >50 years [0], so any wide-scale impact on employment from this technology has likely already settled out.
The waste collection companies in my area don't use them because it's rural and the bins aren't standardized. The side loaders don't work for all use cases of garbage trucks.
>In 1969, the city of Scottsdale, Arizona introduced the world's first automated side loader. The new truck could collect 300 gallon containers in 30 second cycles, without the driver exiting the cab
Really tired of seeing the story about how, “sure Worldcom et al went bankrupt but their investments in fiber optics gave us the physical infrastructure of the Internet today.”
I mean, sort of, but the fiber optics in the ground have been upgraded several by orders of magnitude of its original capacity by replacing the transceivers on either end. And the fiber itself has lasted and will continue to last for decades.
Neither of those properties is true of the current datacenter/GPU boom. The datacenter buildings may last a few decades but the computers and GPUs inside will not and they cannot be easily amplified in their value as the fiber in the ground was.
Most of the big services seem to waste so much time clunking through updating and editing files.
I'm no expert but I can't help feeling there's lots of things they could be doing vastly better in this regard - presumably there is lots to do and they will get around to it.
I look forward to the "personal computing" period, with small models distributed everywhere...
One could argue that this period was just a brief fluke. Personal computers really took off only in the 1990s, web 2.0 happened in the mid-2000s. Now, for the average person, 95%+ of screen time boils down to using the computer as a dumb terminal to access centralized services "in the cloud".
As I travel a ton, I can confidently tell you, that this is still not true at all, and I’m kinda disappointed that the general rule of optimizing for bad reception died.
There are FOSS alternatives for about everything for hobbyist and consumer use.
Also, is percentage of screentime the relevant metric? We moved TV consumption to the PC, does that take away from PCs?
Many apps moved to the web but that's basically just streamed code to be run in a local VM. Is that a dumb terminal? It's not exactly local compute independent...
Would you classify eg gmail as 'content streaming'?
Web browsers aren't quite that useless with no internet connection, some sites do offer offline capabilities (for example gmail). but even then, the vast majority of offline experiences exist to tide the user over until network can be re-established, instead of truly offering something useful to do locally. Probably the only mainstream counter-examples would be games.
But yes I am looking forward to having my own LMS on my PC which only I have access to.
Nearly entirety of the use cases of computers today don't involve running things on a 'personal computer' in any way.
In fact these days, every one kind of agrees as little as hosting a spreadsheet on your computer is a bad idea. Cloud, where everything is backed up is the way to go.
PC was never 'no web'. No one actually 'counted every screw in their garage' as the PC killer app. It was always the web.
The killer apps in the 80s were spreadsheets and desktop publishing.
This whole idea that you can connect lots of cheap low capacity boxes and drive down compute costs is already going away.
In time people will go back to thinking compute as a variable of time taken to finish processing. That's the paradigm in the cloud compute world- you are billed for the TIME you use the box. Eventually people will just want to use something bigger that gets things done faster, hence you don't have to rent them for long.
Our personal devices are far from thin clients.
I think it depends on if you see the browser for content or as a runtime environment.
Maybe it depends on the application architecture...? I.e., a compute-heavy WASM SPA at one end vs a server-rendered website.
Or is it an objective measure?
Turn off internet on they iPad and see how many apps that people use still work.
The Ipad is a high performance computer, not just because Apple think that's fun, but out of necessity given its ambition: the applications people use on it require local storage and rather heavy local computation. The web browser standards if nothing else have pretty much guaranteed that the age of thin clients is over: a client needs to supply a significant amount of computational resources and storage to use the web generally. Not even Chromebooks will practically be anything less than rich clients.
Going back to the original topic (and source of the analogy), IOS hosts an on-device large language model.
The text content of a weather app is trivial compared to the UI.
Same with many web pages.
Desktop apps use local compute, but that's more a limitation of latency and network bandwidth than any fundamental need to keep things local.
Security and privacy also matter to some people. But not to most.
The thing we do need to be careful about is regulatory capture. We could very well end up with nothing but monolithic centralized systems simply because it's made illegal to distribute, use, and share open models. They hinted quite strongly that they wanted to do this with deepseek.
There may even be a case to be made that at some point in the future, small local models will outperform monoliths - if distributed training becomes cheap enough, or if we find an alternative to backprop that allows models to learn as they infer (like a more developed forward-forward or something like it), we may see models that do better simply because they aren't a large centralized organism behind a walled garden. I'll grant that this is a fairly polyanna take and represents the best possible outcome but it's not outlandishly fantastic - and there is good reason to believe that any system based on a robust decentralized architecture would be more resilient to problems like platform enshittification and overdeveloped censorship.
At the end of the day, it's not important what the 'average' user is doing, so long as there are enough non-average users pushing the ball forward on the important stuff.
Most open source development happens on GitHub.
You'd think non-average developers would have noticed their code is now hosted by Microsoft, not the FSF. But perhaps not.
The AI end game is likely some kind of post-Cambrian, post-capitalist soup of evolving distributed compute.
But at the moment there's no conceivable way for local and/or distributed systems to have better performance and more intelligence.
Local computing has latency, bandwidth, and speed/memory limits, and general distributed computing isn't even a thing.
It only has to be good enough to do what we want. In the extreme, maybe inference becomes cheap enough that we ask “why do I have to wake up the laptop’s antenna?”
There might be also local/global bias strategies. A tiny local model trained on your specific code/document base may be better aligned to match your specific needs than a galaxy scale model. If it only knows about one "User" class, the one in your codebase, it might be less prone to borrowing irrelevant ideas from fifty other systems.
You could say the same about all self-hosted software, teams with billions of dollars to produce and host SaaS will always have an advantage over smaller, local operations.
And AI just further normalizes the need for connectivity; cloud models are likely to improve faster than local models, for both technical and business reasons. They've got the premium-subscriptions model down. I shudder to think what happens when OpenAI begins hiring/subsuming-the-knowledge-of "revenue optimization analysts" from the AAA gaming world as a way to boost revenue.
But hey, at least you still need humans, at some level, if your paperclip optimizer is told to find ways to get humans to spend money on "a sense of pride and accomplishment." [0]
We do not live in a utopia.
[0] https://www.guinnessworldrecords.com/world-records/503152-mo... - https://www.reddit.com/r/StarWarsBattlefront/comments/7cff0b...
Because someone else can sell the goose and take your market.
Apple is best aligned to be the disruptor. But I wouldn’t underestimate the Chinese government dumping top-tier open-source models on the internet to take our tech companies down a notch or ten.
If Apple does finally come up with a fully on-device AI model that is actually useful, what makes you think they won't gate it behind a $20/mo subscription like they do for everything else?
Non sequitur.
If a market is being ripped off by subscription, there is opportunity in selling the asset. Vice versa: if the asset sellers are ripping off the market, there is opportunity to turn it into a subscription. Business models tend to oscillate between these two for a variety of reasons. Nothing there suggets one mode is infinitely yielding.
> If Apple does finally come up with a fully on-device AI model that is actually useful, what makes you think they won't gate it behind a $20/mo subscription like they do for everything else?
If they can, someone else can, too. They can make plenty of money selling it straight.
It's this disruptor Apple in the room with us now?
Apple's second biggest money source is services. You know, subscriptions. And that source keeps growing: https://sixcolors.com/post/2025/10/charts-apple-caps-off-bes...
It's also that same Apple that fights tooth and nail every single attempt to let people have the goose or even the promise of a goose. E.g. by saying that it's entitled to a cut even if a transaction didn't happen through Apple.
It's very risky play, and if it doesn't work it leaves China in a much worse place than before, so ideally you don't make the play unless you're already facing some big downside, sort of as a "hail Mary" move. At this point I'm sure they're assuming Trump is glad handing them while preparing for military action, they might even view invasion of Taiwan as defensive if they think military action could be imminent anyhow.
And you know we'd be potting their transport ships, et cetera, from a distance the whole time, all to terrific fanfare. The Taiwan Strait would become the new training ground for naval drones, with the targets being almost exclusively Chinese.
Data General and Unisys did not create PCs - small disrupters did that. These startups were happy to sell eggs.
Assuming consumers even bother to set up a coop in their living room...
Selling eggs is better how?
Like the web, which worked out great?
Our Internet is largely centralized platforms. Built on technology controlled by trillion dollar titans.
Google somehow got the lion share of browser usage and is now dictating the direction of web tech, including the removal of adblock. The URL bar defaults to Google search, where the top results are paid ads.
Your typical everyday person uses their default, locked down iPhone or Android to consume Google or Apple platform products. They then communicate with their friends over Meta platforms, Reddit, or Discord.
The decentralized web could never outrun money. It's difficult to out-engineer hundreds of thousands of the most talented, most highly paid engineers that are working to create these silos.
Fr tho, no ads - I'm not making money off them, I've got no invite code for you, I'm a human - I just don't get it. I've probably told 500 people about Brave, I don't know any that ever tried it.
I don't ever know what to say. You're not wrong, as long as you never try to do something else.
Or rather, they'd block Brave.
I had always hoped we'd do more locally on-device (and with native apps, not running 100 instances of chromium for various electron apps). But, it's hard to extract rent that way I suppose.
I access websites on a 64gb, 16 core device. I deploy them to a 16gb, 4 core server.
Or even physical things like mattresses, according to discussions around the recent AWS issues.
1. Most people don't have machines that can run even midsized local models well
2. The local models are nearly as good as the frontier models for a lot of use cases
3. There are technical hurdles to running local models that will block 99% of people. Even if the steps are: download LM Studio and download a model
Maybe local models will get so good that they cover 99% of normal user use cases and it'll be like using your phone/computer to edit a photo. But you'll still need something to make it automatic enough that regular people use it by default.
That said, anyone reading this is almost certainly technical enough to run a local model. I would highly recommend trying some. Very neat to know it's entirely run from your machine and seeing what it can do. LM Studio is the most brainless way to dip your toes in.
I'm curious what counts as a midsize model; 4B, 8B, or something larger/smaller?
What models would you recommend? I have 12GB of vram so anything larger than 8B might be really slow, but i am not sure
Like 50% of internet users are already interacting with one of these daily.
You usually only change your habit when something is substantially better.
I don't know how free versions are going to be smaller, run on commodity hardware, take up trivial space and ram etc, AND be substantially better
If you are using an Apple product chances are you are already using self-hosted models for things like writing tools and don't even know it.
No, you usually only change your habit when the tools you are already using are changed without consulting you, and the statistics are then used to lie.
The period when you couldn't use Linux as your main OS because your organization asked for .doc files?
No thanks.
Just a bunch of billionaires jockeying for not being poor.
Because if there’s one thing worse than governments having nuclear weapons, it’s everyone having them.
It would be chaos. And with physical drones and robots coming, it woukd be even worse. Think “shitcoins and memecoins” but unlike those, you don’t just lose the money you put in and you can’t opt out. They’d affect everyone, and you can never escape the chaos ever again. They’d be posting around the whole Internet (including here, YouTube deepfakes, extortion, annoyance, constantly trying to rewrite history, get published, reputational destruction at scale etc etc), and constant armies of bots fighting. A dark forest.
And if AI can pay for its own propagation via decentralized hosting and inference, then the chance of a runaway advanced persistent threat compounds. It just takes a few bad apples, or even practical jokers, to unleash crazy stuff. And it will never be shut down, just build and build like some kind of kessler syndrome. And I’m talking about with just CURRENT AI agent and drone technology.
Do you think Sam Altman, Jeff Bezos, and Mark Zuckerberg are all wrong saying that we’re in a bubble? Do they “lack imagination?”
Also? What do I need imagination for, isn’t that what AI does now?
Currently, investment into AI exceeds the dot-com bubble by a factor of 17. Even in the dot-com era, the early internet was already changing media and commerce in fundamental ways. November is the three-year anniversary of ChatGPT. How much economic value are they actually creating? How many people are purchasing AI-generated goods? How much are people paying for AI-provided services? The value created here would have to exceed what the internet was generating in 2000 by a factor of 17 (which seems excessive to me) to even reach parity with the dot-com bubble.
"But think where it'll be in 5 years"—sure, and let's extrapolate that based on where it is now compared to where it was 3 years ago. New models present diminishing returns. 3.5 was groudbreaking; 4 was a big step forward; 5 is incremental. I won't deny that LLMs are useful, and they are certainly much more productized now than they were 3 years ago. But the magnitude of our collective investment in AI requires that a huge watershed moment be just around the corner, and that makes no sense. The watershed moment was 3 years ago. The first LLMs created a huge amount of potential. Now we're realizing those gains, and we're seeing some real value, but things are also tapering off.
Surely we will have another big breakthrough some day—a further era of AI which brings us closer to something like AGI—but there's just no reason to assume AGI will crop up in 2027, and nothing less that that can produce the ROI that such enormous valuations will eventually, inexorably, demand.
I agree that AI is overhyped but so was the early web. It was projected to do a lot of things ”soon”, but was not really doing that much 4 years in. I don’t think the newspapers or commerce were really worried about it. The transformation of the business landscape took hold after the crash.
Its precisely why these companies are investing so much, robots combined with AI will be creating that value.
true for every marketing ever
So, when people say something about future, they are looking into the past to draw some projections or similar trends, but they may be missing the change in the full context. The considered factors of demand and automation might be too few to understand the implications. What about political, social and economic landscape? The systems are not so much insulated to study using just a few factors.
This is clearly false, as is obvious to anyone who has done any software engineering. The big corps are in no shortage of capital and could just add more engineers if this were true. But we know what happens when you add more people to a project.
Rather, there are other more fundamental constraints, like the complexity of software and our ability to grasp and manipulate it. I think the argument would have been better if it focused on that. It'd be more based.
Which is a long-winded way of saying that I agree with others here that this article is full of hubris. I hope you got those chicks on Substack clapping for you, at least. Fast lane to getting laid for sure.
I pay for chatgpt plus and github copilot.
ChatGPT is currently the best solar calculator on the publicly accessible internet and it's not even close. It'll give you the internal rate of return, it'll ask all the relevant questions, find you all the discounts you can take in taxes and incentives, determine whether you should pay the additional permitting and inspection cost for net metering or just go local usage with batteries, size the batteries for you, and find some candidate electricians to do the actual installation once you acquire the equipment.
Edit: My guess is that it'd cost several thousand dollars to hire someone to do this for you, and it'll save you probably in the $10k-$30k range on the final outcomes, depending on the size of system.
I'm curious what kind of problem your "brain cant wrap around", but the AI could.
It's pretty common for me to spend a day being stuck on a gnarly problem in the past. Most developers have. Now I'd say that's extremely rare. Either an LLM will solve it outright quickly or I get enough clues from an LLM to solve it efficiently.
In this case, the original author stated that AI only good for rewriting emails. I showed a much harder problem that AI is able to help me with. So clearly, my problem can be reasonably described as “hard” relative to rewriting emails.
Examples or it didn't happen.
That's not how I remember it (but I was just a kid so I might be misremembering?)
As I remember (and what I gather from media from the era) late 80s/early 90s were hyper optimistic about tech. So much so that I distinctly remember a ¿german? TV show when I was a kid where they had what amounts to modern smartphones, and we all assumed that was right around the corner. If anything, it took too damn long.
Were adults outside my household not as optimistic about tech progress?
https://www.youtube.com/watch?v=RvZ-667CEdo
https://bsky.app/profile/ruv.is/post/3liyszqszds22
Note that this is the state TV broadcasting this in their main news program. The most popular daily show in Iceland.
Maybe it's my bubble, but so far I didn't hear someone saying that. What kind of jobs should that be, given that both forms, physical and knowledge work, will be automatable sooner or later?
That claim just reads like he's concocted two sides for his position to be the middle ground between. I did that essays in high school but I try to be better than that now.
It's falling into the trap of assuming we're going to get to the science fiction abilities of AI with the current software architectures, and within a few years, as long as enough money is thrown at the problem.
All I can say for certain is that all the previous financial instruments that have been jumped on to drive economic growth have eventually crashed. The dot com bubble, credit instruments leading to the global financial crisis, the crypto boom, the current housing markets.
The current investments around AI that we're all agog at are just another large scale instrument for wealth generation. It's not about the technology. Just like VR and BioTech wasn't about the technology.
That isn't to say the technology outcomes aren't useful and amazing, they are just independant of the money. Yes, there are Trillions (a number so large I can't quite comprehend it to be honest) being focused into AI. No, that doesn't mean we will get incomprehensible advancements out the other end.
AGI isn't happening this round folks. Can hallucinations even be solved this round? Trillions of dollars to stop computers lying to us. Most people where I work don't even realise hallucinations are a thing. How about a Trillion dollars so Karen or John stop dismissing different viewpoints because a chat bot says something contradictory, and actually listen? Now that would be worth a Trillion dollars.
Imagine a world where people could listen to others outside of their bubble. Instead they're being given tools that re-inforce the bubble.
1. the opening premise comparing AI to dial-up internet; basically everyone knew the internet would be revolutionary long before 1995. Being able to talk to people halfway across the world on a BBS? Sending a message to your family on the other side of the country and them receiving it instantly? Yeah, it was pretty obvious this was transformative. The Krugman quote is an extreme, notable outlier, and it gets thrown out around literally every new technology, from blockchain to VR headsets to 3DTVs, so just like, don't use it please.
2. the closing thesis of
> Consider the restaurant owner from earlier who uses AI to create custom inventory software that is useful only for them. They won’t call themselves a software engineer.
The idea that restaurant owners will be writing inventory software might make sense if the only challenge of creating custom inventory software, or any custom software, was writing the code... but it isn't. Software projects don't fail because people didn't write enough code.
I was only able to do this because I had some prior programming experience but I would imagine that if AI coding tools get a bit better they would enable a larger cohort of people to build a personal tool like I did.
That sounds pretty similar to long-distance phone calls? (which I'm sure was transformative in its own way, but not on nearly the same scale as the internet)
Do we actually know how transformative the general population of 1995 thought the internet would or wouldn't be?
As soon as the internet arrived, a bit late for us (I'd say 1999 maybe) due to the minitel's "good enough" nature, it just became instantly obvious, everyone wanted it. The general population was raving mad to get an email address, I never heard anyone criticize the internet like I criticize the fake "AI" stuff now.
The real parallel is Canal Mania — Britain’s late-18th-century frenzy to dig waterways everywhere. Investors thought canals were the future of transport. They were, but only briefly.
Today’s AI runs on GPUs — chips built for rendering video games, not thinking machines. Adapting them for AI is about as sensible as adapting a boat to travel across land. Sure, it moves — but not quickly, not cheaply, and certainly not far.
It works for now, but the economics are brutal. Each new model devours exponentially more power, silicon, and capital. It just doesn't scale.
The real revolution will come with new, hardware built for the job (that hasn't been invented yet) — thousands of times faster and more efficient. When that happens, today’s GPU farms will look like quaint relics of an awkward, transitional age: grand, expensive, and obsolete almost overnight.
Think 3D printers versus injection molds: you prototype with flexibility, then mass-produce with purpose-built tooling. We've seen this pattern before too. CPUs didn't vanish when GPUs arrived for graphics. The canal analogy assumes wholesale replacement. Reality is likely more boring: specialization emerges and flexibility survives.
The key variable for me in this house of cards is how long folks will wait before they need to see their money again, and whether these companies will go in the right direction long enough given these valuations to get to AGI. Not guaranteed and in the meantime society will need to play ball (also not a guarantee)
Does that comparison with the fiber infra from the dotcom era really hold up? Even when those companies went broke, the fiber was still perfectly fine a decade later. In contrast, all those datacenters will be useless when the technology has advanced by just a few years.
Nobody is going to be interested in those machines 10 years from now, no matter if the bubble bursts or not. Data centers are like fresh produce. They are only good for a short period of time and useless soon after. They are being constantly replaced.
If you make the context small enough, we're back at /api/create /api/read /api/update /api/delete; or, if you're old-school, a basic function
I don't expect that to cease in my lifetime.
When the railroad bubble popped we had railroads. Metal and sticks, and probably more importantly, rights-of-way.
If this is a bubble, and it pops, basically all the money will have been spent on Nvidia GPUs that depreciate to 0 over 4 years. All this GPU spending will need to be done again, every 4 years.
Hopefully we at least get some nuclear power plants out of this.
I'm still a fan of the railroad comparisons though for a few additional reasons:
1. The environmental impact of the railroad buildout was almost incomprehensibly large (though back in the 1800s people weren't really thinking about that at all.)
2. A lot of people lost their shirts investing in railroads! There were several bubbly crashes. A huge amount of money was thrown away.
3. There was plenty of wasted effort too. It was common for competing railroads to build out rails that served the same route within miles of each other. One of them might go bust and that infrastructure would be wasted.
Heck if nothing else all the new capacity being created today may translate to ~zero cost storage, CPU/GPU compute and networking available to startups in the future if the bubble bursts, and that itself may lead to a new software revolution. Just think of how many good ideas are held back today because deploying them at scale is too expensive.
Note that these are just power purchase agreements. It's not nothing, but it's a long ways away from building nuclear.
I agree the depreciation schedule always seems like a real risk to the whole financial assumptions these companies/investors make, but a question I've wondered: - Will there be an unexpected opportunity when all these "useless" GPUs are put out to pasture? It just seems like saying a factory will be useless because nobody wants to buy an IBM mainframe, but an innovative company can repurpose a non-zero part of that infrastructure for another use case.
I think we may not upgrade every 4 years, but instead upgrade when the AI models are not meeting our needs AND we have the funding & political will to do the upgrade.
Perhaps the singularity is just a sigmoid with the top of the curve being the level of capex the economy can withstand.
Trains are closer to $50-100,000 per mile per year.
If there's no money for the work it's a prioritization decision.
It takes China 5 years now, but they've been ramping up for more than 20 years.
I’m not sure that’s a certainty.
Because some notable people dismissed things that wound up having profound effect on the world, it does not mean that everything dismissed will have a profound effect.
We could just as easily be "peak Laserdisc" as "dial-up internet".
There's another presumably unintended aspect of the comparison that seems worth considering. The Internet in 2025 is certainly vastly more successful and impactful than the Internet in the mid-90s. But dial-up itself as a technology for accessing the Internet was as much of a dead-end as Laserdisc was for watching movies at home.
Whether or not AI has a similar trajectory as the Internet is separate from the question of whether the current implementation has an actual future. It seems reasonable to me that in the future we're enjoying the benefits of AI while laughing thinking back to the 2025 approach of just throwing more GPUs at the problem in the same way we look back now and get a chuckle out of the idea of "shotgun modems" as the future.
When this article are claiming both sides of the debate, I believe only one of them are real (the ones hyping up the technology). While there are people like me who are pessimistic about the technology, we are not in any position of power, and our opinion on the matter is basically a side noise. I think a much more common (among people with any say in the future of this technology) is the believe that this technology is not yet at a point which warrants all this investment. There were people who said that about the internet in 1999, and they were proven 100% correct in the months that followed.
words to live by...
And not just that, they come out with an iPhone that has _no_ camera as an attempt to really distance themselves from all the negative press tech (software and internet in particular) has at the moment.
The Apple engineers, with their top level unfettered access to the best Apple AI - they'll convince shareholders to fund it forever, even if normal people never catch on.
> 1. Economic strain (investment as a share of GDP)
> 2. Industry strain (capex to revenue ratios)
> 3. Revenue growth trajectories (doubling time)
> 4. Valuation heat (price-to-earnings multiples)
> 5. Funding quality (the resilience of capital sources)
> His analysis shows that AI remains in a demand-led boom rather than a bubble, but if two of the five gauges head into red, we will be in bubble territory.
This seems like a more quantitative approach than most of "the sky is falling", "bubble time!", "circular money!" etc analyses commonly found on HN and in the news. Are there other worthwhile macro-economic indicators to look at?
It's fascinating how challenging it is meaningfully compare current recent events to prior economic cycles such as the y2k tech bubble. It seems like it should be easy but AFAICT it barely even rhymes.
Stockmarket capitalisation as a percentage of GDP AKA the Buffett indicator.
https://www.longtermtrends.net/market-cap-to-gdp-the-buffett...
Good luck, folks.
I'm sure there are other factors that make this metric not great for comparisons with other time periods, e.g.:
- rates
- accounting differences
If that bothers you, just multiply valuations by .75
Doesn’t make much difference even without doing the same adjust for previous eras.
Buffett indicator survives this argument. He’s a smart guy.
What is clear, is that we have strapped a rocket to our asses, fueled with cash and speculation. The rocket is going so fast we don't know where we're going to land, or if we'll land softly, or in a very large crater. The past few decades have examples of craters. Where there are potential profits, there are people who don't mind crashing the economy to get them.
I don't understand why we're allowing this rocket to begin with. Why do we need to be moving this quickly and dangerously? Why do we need to spend trillions of dollars overnight? Why do we need to invest half the fucking stock market on this brand new technology as fast as we can? Why can't we develop it in a way that isn't insanely fast and dangerous? Or are we incapable of decisions not based on greed and FOMO?
They earn so much from oil and are so keenly aware this will stop, they'd rather spend a trillion on a failure, than keep that cash rotting away with no future investment.
No project, no country, can swallow the Saudi oil money like Sam Altman can. So, they're building enormous data centers with custom nuclear plants and call that Stargate to syphon that dumb money in. It's the whole business model of Softbank: find a founder whose hubris is as big as Saudi stupidity.
>We’re in the 1950s equivalent of the internet boom — dial-up modems exist, but YouTube doesn’t.
Mass production of telephone line modems in the United States began as part of the SAGE air-defense system in 1958, connecting terminals at various airbases, radar sites, and command-and-control centers to the SAGE director centers scattered around the United States and Canada.
Shortly afterwards in 1959, the technology in the SAGE modems was made available commercially as the Bell 101, which provided 110 bit/s speeds. Bell called this and several other early modems "datasets".
That is the real dial-up thinking.
Couldn't AI like be their custom inventory software?
Codex and Claud Code should not even exist.
Absolutely not. It's inherently a software with a non-zero amount of probability in every operation. You'd have a similar experience asking an intern to remember your inventory.
Like I enjoy Copilot as a research tool right but at the same time, ANYTHING that involves delving into our chat history is often wrong. I own three vehicles, for example, and it cannot for it's very life remember the year, make and model of them. Like they're there, but they're constantly getting switched around in the buffer. And once I started positing questions about friend's vehicles that only got worse.
Really. Tool use is a big deal for humans, and it's just as big a deal for machines.
A single image generally took nothing like a minute. Most people had moved to 28.8K modems that would deliver an acceptable large image in 10-20 seconds. Mind you, the full-screen resolution was typically 800x600 and color was an 8-bit palette… so much less data to move.
Moreover, thanks to “progressive jpeg”, you got to see the full picture in blocky form within a second or two.
And of course, with pages was less busy and tracking cookies still a thing of the future, you could get enough of a news site up to start reading in less time that it can take today.
One final irk is that it’s little overdone to claim that “For the first time in history, you can exchange letters with someone across the world in seconds”. Telex had been around for decades, and faxes, taking 10-20 seconds per page were already commonplace.
Because we all know how essential the internet is nowadays.
We’re at the end of Moore’s Law, it’s pretty reasonable to assume. 3nm M5 chips means there are—what—a few hundred silicon atoms per transistor? We’re an order of magnitude away from .2 nm which is the diameter of a single silicon atom.
My point is, 30 years have passed since dial up. That’s a lot of time to have exponentially increasing returns.
There’s a lot of implicit assumption that “it’s just possible” to have a Moore’s Law for the very concept of intelligence. I think that’s kinda silly.
>The internet, and the state of the art of computing in general has been driven by one thing and one thing alone: Moore’s Law.
You're wrong here... the one thing driving the internet and start of the art computing is money. Period. It wouldn't matter if Moore never existed, and his law was never a thing, money would still be driving technology to improve.
You're kind of separating yin from yang and pretending that one begot the other. The reason so much money flooded into chip fab was because compute is one of the few technologies (the only technology?) with recursive self improvement properties. Smaller chip fab leads to more compute, which enabled smaller chip fabs though research modeling. Sure: and it's all because humans want to do business faster. But TSMC literally made chips the business and proved out the pure play foundry business model.
> Even if Moore's Law was never a thing
Then arguably in that universe, we would have eventually hit a ceiling, which is precisely the point I'm trying to make against the article: it's a little silly to assume there's an infinite frontier of exponential improvement available just because that was the prior trend.
> Moore's Law has very little to do with the physical size of a single transistor
I mean it has everything to do with the physical size of a single transistor, precisely because of that recursive self improvement phenomenon. In a universe where moore's law doesn't exist, in 2025 we wouldn't be on 3nm production dies, and compute scale would have capped off decades ago. Or perhaps even a lot of other weird physical things would probably be different, like maybe macroscopic quantum phenomena or just an entire universe that is one sentient blob made from the chemical composition of cheeto dust.
The Claw allows a garbage truck to be crewed by one man where it would have needed two or three before, and to collect garbage much faster than when the bins were emptied by hand. We don't know what the economics of such automation of (physical) garbage collection portend in the long term, but what we do know is that sanitation workers are being put out of work. "Just upskill," you might say, but until Claw-equipped trucks started appearing on the streets there was no need to upskill, and now that they're here the displaced sanitation workers may be in jeopardy of being unable to afford to feed their families, let alone find and train in some new marketable skill.
So no, we're in the The Claw era of AI, when business finds a new way to funge labor with capital, devaluing certain kinds of labor to zero with no way out for those who traded in such labor. The long-term implications of this development are unclear, but the short-term ones are: more money for the owner class, and some people are out on their ass without a safety net because this is Goddamn America and we don't brook that sort of commie nonsense here.
The waste collection companies in my area don't use them because it's rural and the bins aren't standardized. The side loaders don't work for all use cases of garbage trucks.
[0] https://en.wikipedia.org/wiki/Garbage_truck
>In 1969, the city of Scottsdale, Arizona introduced the world's first automated side loader. The new truck could collect 300 gallon containers in 30 second cycles, without the driver exiting the cab
I mean, sort of, but the fiber optics in the ground have been upgraded several by orders of magnitude of its original capacity by replacing the transceivers on either end. And the fiber itself has lasted and will continue to last for decades.
Neither of those properties is true of the current datacenter/GPU boom. The datacenter buildings may last a few decades but the computers and GPUs inside will not and they cannot be easily amplified in their value as the fiber in the ground was.
I'm no expert but I can't help feeling there's lots of things they could be doing vastly better in this regard - presumably there is lots to do and they will get around to it.