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Are we repeating the telecoms crash with AI datacenters?
- gizajob 10mo agoYes
- MarkusQ 10mo agoHolly cow, we've found an exception to Betteridge's Law of Headlines! Talk about burying the lede!
- fnord77 10mo ago> This is the opposite of what happened in telecoms. We're not seeing exponential efficiency gains that make existing infrastructure obsolete. Instead, we're seeing semiconductor physics hitting fundamental limits. What about the possibility of improvements in training and inference algorithms? Or do we know we won't get any better than grad descent/hessians/etc ?
- kragen 10mo agoThis seems to be either LLM AI slop or a person working very hard to imitate LLM writing style: The key dynamic: X were Y while A was merely B. While C needed to be built, there was enormous overbuilding that D ... Why Forecasting Is Nearly Impossible Here's where I think the comparison to telecoms becomes both interesting and concerning. [lists exactly three difficulties with forecasting, the first two of which consist of exactly three bullet points] ... What About a Short-Term Correction? Could there still be a short-term crash? Absolutely. Scenarios that could trigger a correction: 1. Agent adoption hits a wall ... [continues to list exactly three "scenarios"] The Key Difference From S: Even if there's a correction, the underlying dynamics are different. E did F, then watched G. The result: H. If we do I and only get J, that's not K - that's just L. A correction might mean M, N, and O as P. But that's fundamentally different from Q while R. ... The key insight people miss ... If it's not AI slop, it's a human who doesn't know what they're talking about: "enormous strides were made on the optical transceivers, allowing the same fibre to carry 100,000x more traffic over the following decade. Just one example is WDM multiplexing..." when in fact wavelength division multiplexing multiplexing is the entirety of those enormous strides. Although it constantly uses the "rule of three" and the "negative parallelisms" I've quoted above, it completely avoids most of the overused AI words (other than "key", which occurs six times in only 2257 words, all six times as adjectival puffery), and it substitutes single hyphens for em dashes even when em dashes were obviously meant (in 20 separate places—more often than even I use em dashes), so I think it's been run through a simple filter to conceal its origin.
- ashtakeaway 10mo agoRemember we have about 20 years of poorly written articles along with a few well written ones for the LLM to be trained on. I'm confident that attempting to tell LLM from human writing is a waste of time now that the year is almost over. Other than that I'd rather choose a comprehensive article than a summary.
- kragen 10mo agoAttempting to tell LLM writing from human writing is usually a waste of time, but apparently not in this case.
- alienbaby 10mo agoDid you see the reply from the author to similar statements?
- kragen 10mo agoYou mean https://news.ycombinator.com/item?id=46138663 https://news.ycombinator.com/item?id=46138663? He said that he mixed up British and American English all the time, but didn't try to deny that the article was AI slop.
- myrmidon 10mo agoI agree, and it feels like an allergy by now to that style specifically. This is doubly annoying because it ruins the reading experience and just makes me question myself constantly because you often can't be quite certain especially for shorter posts/comments. On topic: It is always quite easy to be the cynical skeptic, but a better question in my view: Is the current AI boom closer to telecoms in 2000 or to video hosting in 2005? Because parallels are strong to both, and the outcomes vastly different (Cisco barely recovered by now compared to 1999 while youtube is printing money).
- alienbaby 10mo agoYou guys make me laugh.
- Havoc 10mo agoDon’t think looking at power consumption of b200s is a good measure of anything. Could well be an indication of higher density rather than hitting limits and cranking voltage to compensate
- _ea1k 10mo agoYes, one of NVidia's selling points for the b200 is that performance per watt is better than before. High power consumption without controlling for performance means nothing.
- asplake 10mo agoYes or no conclusions aside (and despite its title, the article deserves better than that), the key point is I think this one: “But unlike telecoms, that overcapacity would likely get absorbed.”
- lazide 10mo agoTelecom (dark fiber) capacity got absorbed too. Eventually. After a ton of bankruptcies.
- gmm1990 10mo agoSome of the utilization comparisons are interesting, but the article says 2 trillion was spent on laying fiber but that seems suspicious.
- observationist 10mo agoThere's an enormous amount of unused, abandoned fiber. All sorts of fiber was run to last mile locations, across most cities in the US, and a shocking amount effectively got abandoned in the frenzy of mergers and acquisitions. 2 trillion seems like a reasonable estimate. Giant telecoms bought big regional telecoms which came about from local telecoms merging and acquiring other local telecoms. A whole bunch of them were construction companies that rode the wave, put in resources to run dark fiber all over the place. Local energy companies and the like sometimes participated. There were no standard ways of documenting runs, and it was beneficial to keep things relatively secret, since if you could provide fiber capabilities in a key region, but your competition was rolling out DSL and investing lots of money, you could pounce and make them waste resources, and so on. This led to enormous waste and fraud, and we're now on the outer edge of usability for most of the fiber that was laid - 29-30 years after it was run, most of it will never be used, or ever have been used. The 90s and early 2000's were nuts.
- sosodev 10mo agoI so desperately wish it weren't abandoned. I hate that it's almost 2026 and I still can't get a fiber connection to my apartment in a dense part of San Diego. I've moved several times throughout the years and it has never been an option despite the fact that it always seems to be "in the neighborhood".
- Spooky23 10mo agoThat has nothing to do with fiber, it’s all about politics and a regulatory environment where nobody is incented to act. Basically, the states can’t fully regulate internet and the Federal government only wants to fund buildouts on a pork barrel basis. Most recently rural. At the local level, there is generally a cable provider with existing rights of way. To get a fiber provider, there’s 4 possible outcomes: universal service with subsidy (funded by direct subsidy), cherry-picked service (they install where convenient), universal service (capitalized by the telco) and “fuck you”, where they refuse to operate. (ie. Verizon in urban areas) The private capitalized card was played out by cable operators in the 80s (they were innovators then, and AT&T was just broken up and in chaos). They have franchise agreements whose exclusivity was used as loan collateral. Forget about San Diego, there are neighborhoods in Manhattan with the highest population density in the country where Verizon claims it’s unprofitable to operate. I served on a city commission where the mayor and county were very interested in getting our city wired, especially as legacy telco services are on the way out and cable costs are escalating and will accelerate as the merger agreement that formed Spectrum expires. The idea was to capitalize last mile with public funds and create an authority that operated both the urban network and the rural broadband in the county funded by the Federal legislation. With the capital raised with grants and low cost bonding (public authority bonds are cheap and backed by revenue and other assets), it would raise a moderate amount of income in <10 years. We had the ability to get the financing in place, but we would have needed legislation passed to get access to rights of way. Utilities have lots of ancient rights and laws that make disruption difficult. The politicians behind it turned over before that could be changed.
- nuc1e0n 10mo agoThe article claims that AI services are currently over-utilised. Well isn't that because customers are being undercharged for services? A car when in neutral will rev up easily if the accelerator pedal is pushed even very slightly, because there's no load on the engine. But in gear the same engine will rev up much less when the accelerator is pushed the same amount. Will there be the same overutilisation occurring if users have to financially support the infrastructure, either through subscriptions or intrusive advertising? I doubt it. And what if the technology to locally run these systems without reliance on the cloud becomes commonplace, as it now is with open source models? The expensive part is in the training of these models more than the inference.
- aitchnyu 10mo agoWill the OpenRouter marketplace of M clouds X N models die if the investor money stops? I believe its a free and profitable service, offered completely pay as you go.
- an0malous 10mo ago> The article claims that AI services are currently over-utilised. Well isn't that because customers are being undercharged for services? Absolutely, not only are most AI services free but even the paid portion is coming from executives mandating that their employees use AI services. It's a heavily distorted market.
- keeda 10mo agoOn the flip side, there are many indications that a huge part of corporate AI usage is "Shadow AI", i.e. where workers use GenAI without their employer's blessing or knowledge. E.g. https://cacm.acm.org/news/the-real-significant-threat-of-shadow-ai/ https://cacm.acm.org/news/the-real-significant-threat-of-sha... And a majority of those workers do not reveal their AI usage, so they either take credit for the faster work or use the extra time for other activities, which further confounds the impact of AI. This is also distorting the market, but in other ways.
- treis 10mo agoWe're talking miraculous level of improvement for a SOA LLM to run on a phone without crushing battery life this decade. People are missing the forest for the trees here. Being the go to consumer Gen AI is a trillion+ dollar business. How many 10s of billions you waste on building unnecessary data centers is a rounding error. The important number is your odds of becoming that default provider in the minds of consumers.
- kqr 10mo agoIs there a way in which this is good for a segment of consumers? When the current gen of GPUs are too old, will the market be flooded with cheap GPUs that benefit researchers and hobbyists who therwis would not afford them?
- wmf 10mo agoMany researchers and hobbyists cannot even plug in a 10 KW 8 GPU DGX server.
- CamperBob2 10mo agoThat doesn't exactly bode well for the EV revolution, then, does it?
- tekno45 10mo agowut?
- deleted 10mo ago[deleted]
- LogicFailsMe 10mo agoThe average commute in the United States is about 24 miles a day round trip. That's about 10 kWH. That's enough to charge overnight on a 15A circuit.
- CamperBob2 10mo agoYou can drive around with 24 miles of charge, but ... I'll pass, thanks. In reality, if you have a dryer outlet, you have a good fraction of 10 kW available.
- LogicFailsMe 10mo agoI just put in a dedicated 50 amp circuit myself and my car charges from ~25% to full in about 6-7 hours. But I wanted to present the lazy worst case scenario. The warrior's FUD here is that there isn't enough easily available lithium for everyone in just California alone to have one.
- recursive4 10mo agoStylistically, this smells like it was copy and pasted from straight out Deep Research. Substantively, I could use additional emphasis on the mismatch between expectations and reality with regards to telco debt-repayment schedule.
- positron26 10mo agoHardware growth is slow and predictable, but one breakthrough algorithm completely undercuts any finance hypothesis premised on compute not flowing out of the cloud and back to the edges and into the phones. This is a kind of risk that finance people are completely blind to. Open AI won't tell them because it keeps capital cheap. Startups that must take a chance on hardware capability remaining centralized won't even bother analyzing the possibility. With so many actors incentivized to not know or not bother asking the question, there's the biggest systematic risk. The real whiplash will come from extrapolation. If an algorithm advance shows up promising to halve hardware requirements, finance heads will reason that we haven't hit the floor yet. A lot of capital will eventually re-deploy, but in the meantime, a great deal of it will slow down, stop, or reverse gears and get un-deployed.
- sdenton4 10mo agoAI had a kind of Jevons paradox approach to efficiency improvements, unfortunately - if you halve the compute requirements with an algorithmic advance, you can run a model twice as big.
- layer8 10mo agoThe large SOTA models have hit very diminishing returns on further scaling, I think. So you’d rather double the number of models you can run in parallel.
- _f9cu 10mo agoNo. AI data center, or any data center is designed with incorrect data structure resulting in over utilisation of computing resource.
- iambateman 10mo agoThe thing that makes AI investment hard to reason about for individuals is that our expectations are mostly driven by a single person’s usage, just like many of the numbers reported in the article. But the AI providers are betting, correctly in my opinion, that many companies will find uses for LLM’s which are in the trillions of tokens per day. Think less of “a bunch of people want to get recipe ideas.” Think more of “a pharma lab wants to explore all possible interactions for a particular drug” or “an airline wants its front-line customer service fully managed by LLM.” It’s unusual that individuals and industry get access to basically similar tools at the same time, but we should think of tools like ChatGPT and similar as “foot in the door” products which create appetite and room to explore exponentially larger token use in industry.
- gradus_ad 10mo agoWhen I'm building out a new feature, I can churn through millions of tokens in Claude code. And that's just me... Now think about Claude code but integrated with Excel or datadog, or whatever app could be improved through LLM integration. Think about the millions of office workers, beyond just software engineers, who will be running hundreds of thousands or millions of tokens per day through these tools. Let's estimate 200 million office workers globally as TAM running an average of 250k tokens. That's 50 trillion tokens DAILY. Not sure what model provider profit per token is, but let's say it's .001 cents. Thats $500M per day in profit.
- not_the_fda 10mo agoCurrently there is no profit per token, quite a bit of loss per token, that's the problem. Your not going to make it up in volume.
- danielbln 10mo agoDo you have a source for that? I'm especially interested in a source for Anthropic.
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- mNovak 10mo agoNice article; far from bullet-proof, but it brings up some interesting points. HN comments are vicious on the topic of AI non-bubbles.
- dust42 10mo agoOpenAI has 800,000,000 weekly users but only 20,000,000 are paying while 780,000,000 are free riding. Should they by accident under provision then they could simply remove the freebee and raise the prices for the paying clients. But that is not what they want. IMHO the investors are betting on a winner-takes-it-all market and that some magic AGI will be coming out of OpenAI or Anthropic. The questions are: How much money can they make by integrating advertising and/or selling user profiles? What is the model competition going to be? What is the future AI hardware going to be - TPUs, ASICs? Will more people have powerful laptops/desktops to run a mid-sized models locally and be happy with it? The internet didn't stop after the dotcom crash and the AI wont stop either should there be a market correction.
- deleted 10mo ago[deleted]
- alex_c 10mo ago>OpenAI has 800,000,000 weekly users but only 20,000,000 are paying while 780,000,000 are free riding. By itself, this doesn't tell us much. The more interesting metric would be token use comparison across free users, paid users, API use, and Azure/Bedrock. I'm not sure if these numbers are available anywhere. It's very possible B2B use could be a much bigger market than direct B2C (and the free users are currently providing value in terms of training data).
- greekrich92 10mo ago800M people are not using chatGPT every week. Be a little less credulous.
- tokioyoyo 10mo agoI just thought about it, and honestly, from my surroundings of people aged 12-70s, across multiple continents, I can’t think of anyone who isn’t using some sort of LLM once a week.
- cjameskeller 10mo ago
- paulorlando 10mo agoThe 2001 telecoms crash drove benefits for companies that came later in the availability of inexpensive dark fiber after the bubble popped. WorldCom, ICG, Williams sold off to Verizon, Level 3, Teleglobe, and others. That in turn helped future Internet companies gain access to plentiful and inexpensive bandwidth. Cable telephony companies such as Cablevision Systems, Comcast, Cox Communications, and Time Warner, used the existing coaxial connections into the home to launch voice services.
- epistasis 10mo agoThis is indeed true, but doesn't fiber have a far longer lifetime than GPU heavy data centers? The major cost center is the hardware, which has a fairly short shelf life.
- gretch 10mo agoWell you still get the establishment of 1) large industrial buildings 2) water/electricity distribution 3) trained employees who know how to manage a data center Even if all of the GPUs inside burn out and you want to put something else entirely inside of the building, that's all still ready to go. Although there is the possibility they all become dilapidated buildings, like abandoned factories
- epistasis 10mo agoThe building and electrical infrastructure are far cheaper than the hardware. So much so that the electricity is a small cost of the data center build out, but a major cost for the grid. Of the most valuable part is quickly depreciating and goes unused within the first few years, it won't have a chance for long term value like fiber. If data centers become, I don't know, battery grid storage, it will be very very expensive grid storage. Which is to say that while there was an early salivation for fiber that was eventually useful, overallocation of capital to GPUs goes to pure waste.
- gretch 10mo ago
- rhetocj23 10mo ago[dead]
- avazhi 10mo agoNo, because the datacenters will get used. The demand side exists, whether it’s LLM AIs or something completely different that isn’t AI related. That’s very different from a crash where there is absolutely nothing valuable/useable/demanded underneath the bubble.
- turtlesdown11 10mo ago> The demand side exists, whether it’s LLM AIs or something completely different that isn’t AI related. What do you think LLM tuned GPUs or TPUs are going to be used for that is completely different and not AI related?
- avazhi 10mo ago‘LLM tuned GPUs’ are just GPUs. The tuning refers to the models and how they use something like CUDA or whatever. There was a GPU shortage even before LLMs properly burst onto the scene, back with crypto mining. Now, it’s possible TPUs might add a wrinkle to later demand side issues when there is a crash but that will depend on how useful TPUs actually end up being to those outside Google. But GPUs will remain useful, whether it’s for gaming, machine learning (not the AI slop variety of this, but more categorising like for self-driving cars or medical imaging etc), or for the next crypto scam. Surely you agree that powerful computing capacity, independent of AI scams, is here to stay, right? My main point in arguing that now isn’t like 2000 is that unlike in 2000 we have actual hardware and physical assets underpinning this bubble. In 2000 the assets were literally just imaginary. Yes there is speculation now but it is underpinned by silicon that will still be worth decent money even after LLMs are exposed as a hallucinatory mirage.
- turtlesdown11 10mo agoAmazing article, I found it fascinating. > You can already use Claude Code for non engineering tasks in professional services and get very impressive results without any industry specific modifications After clicking on the link, and finding that Claude Code failed to accurately answer the single example tax question given, very impressive results! After all, why pay a professional to get something right when you can use Claude Code to get it wrong?
- venturecruelty 10mo agoNo, because at least dark fiber is useful. AI GPUs will be shipped off to developing nations to be dissolved for rare earth metals once the third act of this clown show is over.
- mwkaufma 10mo agoSimultaneous claims that 'agentic' models are dramatically less efficient, but also forecasts efficiency improvements? We're in full-on tea-leaves-reading mode.
- jfalcon 10mo agoAfter reading the article and the comments, here are a few points people are missing from their analysis: - OverUtilized/UnderCharged: doesn't matter because... - Lead Time vs. TCO vs. IRS Asset Deprecation: The moment you get it fully built, it's already obsolete. Thus from a CapEx point of view, if you can lease your compute (including GPU) and optimize the rest of the inputs for similar then your CapEx overall is much lower and tied to the real estate - not the technology. The rest is cost of doing business and deductible in and of itself. - The "X" factor: Someone mentioned TPU/ASIC but then there is the DeepSeek factor - what if we figure out a better way of doing the work that can shortcut the workflow? - AGI partnerships: Right now, you see a lot of Mega X giving billions to Mega Y because all of them are trying to get their version of Linux or Apache or whatever at parity with the rest. Once AGI is settled and confirmed, then most all of these partnerships will be severed because it then becomes which company is going to get their AI model into that high prestige Montessori school and into the right ivy league schools - like any other rich parent would for their "bot" offspring. So what will it look like when it crashes? A bunch of bland empty "warehouses" with mobile PDU's once filling all their parking lot space gone. Whatever "paradise" that was there may come back... once you bulldoze all that concrete and steel. The money will do something else like a Don McLean song.
- nuc1e0n 10mo ago>once you bulldoze all that concrete and steel You're not quite thinking things through there man. Once the elites who built these follies have gone, the mob will go shopping for building materials. I wouldn't be surprised even if people end up living in these datacentres once they become derelict. They have AC after all.
- bluefirebrand 10mo ago> Once AGI is settled and confirmed This is still pretty far from a guarantee
- kd913 10mo agoI am still a little skeptical about utilisation rates. If demand is so extreme, wouldn't we see rental prices for H100/A100 prices go up or maintain? Wouldn't the cost for such a gpu still be high (you can get em 3k used).
- michaelt 10mo agoOn "runpod community cloud" renting a 5090 costs $0.69/hour [1] and it consumes about $0.10/hour electricity, if running at full power and paying $0.20/kWh. On Amazon, buying a 5090 costs $3000 [2] That's a payback time of 212 days. And Runpod is one of the cheaper cloud providers; for the GPUs I compared, EC2 was twice the price for an on-demand instance. Rental prices for GPUs are pretty darn high. [1] https://www.runpod.io/pricing https://www.runpod.io/pricing [2] https://www.amazon.com/GIGABYTE-Graphics-WINDFORCE-GV-N5090GAMING-OC-32GD/dp/B0DT7GBNWQ https://www.amazon.com/GIGABYTE-Graphics-WINDFORCE-GV-N5090G...
- kd913 10mo agoA 5090 gaming card is a different beast to the 80gb ai cards. That one was 40k usd so for renting that to hit 1.50 dollar per hour is interesting.
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- ruralfam 10mo agoWelp Gemini got me. Using G3 to improve what I write, generate specific images, and use NotebookLM to dive into some research materials. Tried to do a bit each day with my free credits, but hit the limit too often. G2.5 was not nearly as useful. So I upgraded my baselevel Google workspace plan. Recently spoke to someone who is also using G3 a lot with good results. YMMV re: G3, but Google hooked me, and now I pay more. However I think it is worth it for what I do. G3 is my helpful, nerdy work mate. I never plan to use agenic AI. Not using ChatGPT much if any at all anymore. Sorry Sam.
- lordnacho 10mo agoI'm curious about the telecom collapse. How was it not in the pipeline that much better use of the fibres was around the corner? Surely they would have known that people were looking into it with some promise?
- IshKebab 10mo agoIt's human nature not to admit the obvious until it is way way way too late.
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- xorcist 10mo agoTelco capex was $100 billion at the peak of the IT bubble, give or take. There's going to be $400 billion investments in AI in 2025. Just saying.
- zeckalpha 10mo ago> Model efficiency could improve faster than expected. There are compounding incentives for this. I see this as the most likely outcome, though it will likely be stepwise rather than gradual.
- tickerticker 10mo agoOpenAI has first mover advantage with respect to raising money but not wrt tech dominance. Consensus theory: If AGI then superintelligence. AI CapEx plans are not ROI based. Rather, they are the cost of "how do I remain competitive in the race to attain AGI" coupled with conveniently deep pockets. The money is being spent because the spenders can afford it and they see it as an existential risk as much as a profit opportunity. Maybe OP's conclusion about the headline question blunts some political opposition to data centers, but that's not the salient issue. The issue is this: America is betting a meaningful chunk of GDP that AGI is possible. This is The Manhattan Project 2.0.
- iamflimflam1 10mo agoFor those who can’t/won’t read the article - the author argues that the answer is “no - it’s not a repeat”.
- arisAlexis 10mo agoConfusing telephones with AGI is some cope from humans.
- PeterStuer 10mo agoIn the telecoms case, just trowing in extra dark fiber just in case was an almost negligeable cost in light of digging new connections. So who cares if in year 1 you have just 4 fibers lit of the 244 you trew into the trench? This is not the case for AI data centers at all. The compute is a major cost in the whole build budget. Having that installed and not used is financial ruin.
- zombot 10mo ago> Having that installed and not used is financial ruin. And having it used consumes so much energy that it's everyone else's ruin.
- fyrn_ 10mo agoThis piece kind of ignores the "there is no feasible way to get enough electricity" argument. I think that's especially true if we have decided not to do solar or wind for some reason