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Hacker News:AI 熱帖·· 15 小時前AI 評分36

我們都應該問 AI 的關鍵問題是甚麼?

The question we should all be asking about AI

AI 導讀

AI 熱潮的關鍵問題是,債券市場還能支撐不斷增加的開支多久。討論指出,雲端收入增長可能來自借貸,而非終端用戶需求;市場仍在爭論,AI 基建投入能否由未來需求支撐。

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The question we should all be asking about AI (cnn.com) 20 points by heresie-dabord12 hours ago | hide | past | favorite | 19 comments help Image 2vannevar10 hours ago | next[–] "Hyperscalers, by contrast, look like winners. Their cloud revenue (a stat Wall Street uses to measure AI demand) grew 50% in the second quarter. They have huge contract backlogs and the capacity to absorb higher borrowing costs." And if that revenue was coming from end users, it would be great. But it isn't---most of it is coming from the very same debt that is the subject of the article. There's a huge difference in my financial outlook if my biggest customer is borrowing all the money they are spending with me vs earning it in the marketplace. In the latter scenario, my business is tied into the success of the my customer in the market (harder to grow), in the former it's just a question of how much money they can borrow (much easier to grow, especially if I'm Nvidia and I can guarantee their debt). I see the business press make this fundamental mistake all the time, starting off by drawing a boundary around the AI industry as a whole and correctly assessing the staggering levels of debt, but then switching perspective to individual sectors and completely forgetting about where the revenue actually originates, and treating it the same as organic growth. reply Image 3cmiles811 hours ago | prev | next[–] The markets are just in the Twilight Zone at the moment. The CDS on some of these bonds are now priced assuming the bonds will fail (or at least more likely than not). Per headlines on Friday, Anthropic would likely be rated as “junk” status from a bond risk standpoint were it to go public. From a financial standpoint this is all looking like early 2008. The risk assessment bits of the market seem to have concluded this is all totally f*ked. But money keeps getting pumped into things that the market has decided will fail because the only thing that stops it from imploding is pumping more money in. Like 2008 once key players get their armor on, expect things to suddenly unleash in a way that gets real ugly real quick. This is essentially what the article is saying. This all only hasn’t collapsed because money lenders haven’t pulled the plug yet. When that happens, and with every day this looks like a question of when not if, it will be a $hitstorm the likes of which we’ve not seen in a while. reply Image 4armchairhacker11 hours ago | prev | next[–] It’s “How much longer will the bond market sustain the nonstop spending spree?” reply Image 5pigpop8 hours ago | prev | next[–] Methinks they're calling it a bit too early. Earnings volatility combined with the upcoming midterms, some profit taking after a substantial rally and possibly investors freeing up capital ahead of some major IPOs could explain a good portion of the drop. There have been some disappointing earnings and forecasts that added fuel to the fire, and the increasing cost of financing AI infrastructure is certainly a legitimate concern, but I don't think we've seen enough evidence of a fundamental deterioration in demand to conclude that the whole thing is coming apart. Unless the bad news continues to stack up, I don't think this is The End. reply Image 6malfist11 hours ago | prev | next[–] As much as it'd thrill me in one of the worst Pyrrhic victories to see the AI bubble burst, I think it is way too early to claim that a single bad day or a single bad week means it's collapsing. reply Image 7dist-epoch11 hours ago | prev[–] The only thing that matters is who has the Compute. I bought a gaming GPU six months ago for running local LLMs, at outrageous price (2x MSRP), and in 6 months it's price doubled again. AWS already sold all the compute it has planned for 2026, 2027 and 2028. reply Image 8kennywinker11 hours ago | parent | next[–] The compute they sold is based on the idea that the amount of money people spend on inference will continue to go up dramatically. If we’re in a gas shortage, all that matters is who has the gas, true. But the issue is that we’re burning 50% of the gas that’s made every day, mean while the other 50% is being stockpiled based on the idea that everyone is going to drive 10x farther next year. reply Image 9solyin9 hours ago | root | parent | next[–] Is that true? Aren't they going to use those datacenters for training and robotics as well? Not just chatbot inference? GPUs aren't Bitcoin miner ASICs, they can do a wider variety of things. Gasoline in a car is one analogy, but another one is data on the Internet. When the Internet first broke out of universities, there was dial-up. In the late 70's the 300 baud modem was being sold to consumers. It would take roughly three hours to download a novel of 350 pages. It would take roughly two hours to download a single poor quality 256 kilobyte raw 8bpp image file. Jpeg hadn't been invented yet. Now, that image file will take less than ten milliseconds. Roughly a million times faster. The things we transferred changed too. Today, we stream multiple 4k video with audio streams up and down, so a regular home connection won't suffice for more than a few users. Wirth's law; what Intel giveth, Microsoft taketh away; also applies. Sometimes digital trends do tend to 10x, or in the case of ISP speeds, we went from 300 baud to gigabit in ~40 years; 3.3 million times faster. I have no idea what the future holds, but analogies only go so far. reply Image 10kennywinker9 hours ago | root | parent | next[–] > Is that true? Aren't they going to use those datacenters for training and robotics as well? Sure, those things too. I was meaning “inference” as a shorthand for any ai workloads. Whatever analogy you want to use: gas, data transfer, it doesn’t matter. My point is that all the capacity is being hoarded for future use making it feel like a scarce resource now. If the demand grows like they say it will, then hoarding was a smart choice and the people who own the GPUs will make lots of money. If the demand doesn’t grow as fast and as much as they say, then hoarding was a bad call and the house of cards collapses and a lot of people will lose a lot of money. To use your data transfer analog - during the dotcom bubble a ton of fiber was built. But after the bubble popped most of it went unused for years. Some of that “dark fiber” is still unused today, 25+ years later. Afaik it would have been a lot cheaper and more stable for the economy to lay that fiber more incrementally. reply Image 11cmiles810 hours ago | parent | prev[–] Except: 1. GPUs are reportedly increasingly just getting put on shelves because there aren’t data centers to host them, which is creating a setup for a financial mess (rapidly depreciating assets purchased, paid for, but not utilized), 2. And massive chunk of the compute “demand” is coming from circular financing (ie AWS is “sold out” in large part because it gave startups like Anthropic money to buy the thing it’s now telling the market is “sold out” so there’s some shenanigans behind those headlines.) I do agree though that compute is really the only place to make money in AI in the long run. Models are an increasingly a commodity with little value above the cost of compute to run them. However selling compute will be with razor thin margins, not the fat AWS margins the market got used to in cloud, so AWS and others will have to deal with that uncomfortable reality. reply Image 12bigbadfeline4 hours ago | root | parent | next[–] > 1. GPUs are reportedly increasingly just getting put on shelves because there aren’t data centers to host them, which is creating a setup for a financial mess (rapidly depreciating assets purchased, paid for, but not utilized), Unfortunately, "paid for, but not utilized" doesn't result in rapid depreciation in the case of coordinated market scalping. In that case, dark (unused) hardware is kept on storage to actually cause higher prices until them chips can be sold for profit, in the form of services, after eventual deployment. I suspect, digging a bit deeper would find some shady financial practices that may lead to a taxpayer funded bailout via the insurance loophole. reply Image 13cousinbryce10 hours ago | root | parent | prev | next[–] I worry they’re going to destroy the chips they can’t afford to deploy to keep them from being used for local inference reply Image 14dpark7 hours ago | root | parent | next[–] How would chips that, say, Amazon paid for end up in local devices? I don’t understand the scenario that destroying the chips would guard against. Amazon could just leave these chips in a warehouse indefinitely. reply Image 15ozlikethewizard5 hours ago | root | parent | next[–] I guess this is functionally destroying them? Doesnt take long for chips to go out of date. If I buy a load of potatoes and let them rot, have I not destroyed them? reply Image 16bigbadfeline4 hours ago | root | parent | next[–] > If I buy a load of potatoes and let them rot, have I not destroyed them? Depends on how they're stored. Computer chips aren't potato chips, they don't rot, properly stored they can last a really long time, a multitude of storage technologies are available for that purpose. > Doesnt take long for chips to go out of date. That used to be the case but it's no longer true. Advanced chips are made by 3 companies total and competition is nowhere to be seen. Then, with every generation of chips, their production costs and prices are rising more than the benefits that generation provides i.e. the benefits curve is flattening faster than cost curve. Theoretically, China can bring the prices down but they are sanctioned, tariffed and have a huge market of their own to satisfy first. reply Image 17dist-epoch10 hours ago | root | parent | prev[–] > rapidly depreciating assets purchased GPU's produced in 2020, with a supposedly "3 year life before depreciating to zero" are now sold at twice their price from 2020. reply Image 18cmiles810 hours ago | root | parent[–] So did houses in 2007. That’s not a good sign at all. reply Image 19lisplist9 hours ago | root | parent[–] I guess GPUs are interesting because unlike houses, we've suddenly found a massive amount of new utility for these things. If my house suddenly started producing its own furniture, it might be a bit more valuable. Which isn't to say people haven't found new things to do with their houses - COVID made having a home office a lot more valuable, for example, but nothing quite as dramatic as GPUs suddenly able to produce their own code. reply Image 20cmiles88 hours ago | root | parent[–] In 2008 we had both a massive under supply of housing in many cities plus crashing prices. These things can very much exist at the same time if, as if happening now with GPUs, the financial engine fueling the ecosystem is out of whack. reply Image 21 Consider applying for YC's Winter 2027 batch! Applications are open till November 2. Guidelines | FAQ | Lists | API | Security | Legal | Apply to YC | Contact Search:

來源:Hacker News:AI 熱帖 · news.ycombinator.com