> Data centers are NOT real estate. Buildings and power lines usually last 30-50 years. GPUs become obsolete in 5 years. Data centers are real estate. One of the big players in carrier neutral data centers even calls themselves Digitial Realty. The contents of the DC is not real estate. But neither is the an office or a house or a warehouse.
The “contents” represent the majority of the cost and meaningful functionality of what we call a “datacenter”. Those contents will not last for “real estate” debt timelines.
Right but their payback period is insanely short - a $5M GB200 NVL72 cluster is expected to generate $75M in revenue over 3 years for inference providers. That's a 3 month payback period.
AND - they're operating well past their estimated service lifetime.
i dont understand the concern. they are putting up great financials. you have to invest ahead of the outcome. this is just classic quarterly public company earnings BS, where public markets dont reward innovation investment. they just want crank the handle financials. The bigger issue is on the model front, can Google compete; Gemini doesnt seem to be able to compete on the heavy expert end; they are doing well on li…
> GPUs become obsolete in 5 years The GPUs are far from worthless after 5 years. E.g. the A100 80GB PCIe version cost around $15k when it was introduced in 2021 and now sells for $10k used. Things might be slightly worse for the data center servers, but I am sure they will find find buyers.
They only reason that they are retaining value is there was not so much demand for GPUs in 2021 as there is today. Once the demand drops you will find then in dumpsters across our barren, burning dystopia.
i dont understand the concern. they are putting up great financials. you have to invest ahead of the outcome. this is just classic quarterly public company earnings BS, where public markets dont reward innovation investment. they just want crank the handle financials. The bigger issue is on the model front, can Google compete; Gemini doesnt seem to be able to compete on the heavy expert end; they are doing well on li…
I've given up on Gemini. It sounds smart but most of what it tells me ends up being wrong or misleading. I might actually hand $20/mo to OpenAI. It's been far more helpful with the random collection of legal and health problems I've thrown at it. My recent comment history is going to make me come across like a shill for them but, holy crap, GPT has been doing amazing things for me at work as well. I don't get it eith…
Are you using Gemini Flash or Gemini Pro?
Are you about to compare the free tier of Gemini to the paid tier of OpenAI?
I'm thinking Apple has been really smart in their AI strategy here. It seems a mistake to make unprecedentedly large capital expenditures, in a very very crowded space, without much evidence of a moat. Presumably people thought the moat would be singularity-like self-improvement of AI, but the singularity is merely a religious concept, and nobody should take religious myth as fact, it's merely narrative for orientati…
Their strategy to let Siri stagnate for 15 years and let everyone else take that market? Their strategy to put a bunch of not ready for consumer use AI features on their devices and then roll them back? They just have such a strong hardware + os ecosystem that they can sit on the sidelines. They'll be able to negotiate with some LLM provider at a good discount when the time is right and put harnesses around it for ac…
Claude is a far superior _model_ to whatever Siri uses, but in terms of the Claude app correctly transcribing speech, in my experience it's as bad or worse than Siri (which is already bad). Doesn't matter how good the model is if it misinterprets what you say.
The fact that supply constrained GPUs holding value is negative indicator. It's like the tulips mania except bubble enthusiasts are buying wilted/dead tulips because live tulips supply constrained due to irrational demand. Now GPUs has more gross utility than tulips but seems like at current revenue/capex spend, every GPU is still negative net financial yield - they lose money - literally buying tulips and watching i…
You're making a classic philosophical error here by accidentally anthropomorphizing companies :) A company losing out on a risky bet and failing, letting a new upstart rise up is pretty natural. A large fraction of experts from the failed companies continue at the new ones, business as usual. There are engineering teams at $BIGTECH now full of OS, database, or compiler experts from XP, Sun, HP etc. This natural abili…
Companies are run by people, 100 billion dollar companies are ran by people who want to stay billionaires and will street accordingly. But I'm not sure what we're disagreeing on, yes the talent will migrate, AI industry will eventually settle on some none bubble equilibrium, but that doesn't mean current AI economics is sensible, or inflated hardware costs beyond yield is not danger indicator. Like yeah, risky bets are burning, most people are going to move and carry their technical expertise on instead of unalive themselves or flip burgers, but that's independent of whether business models and broader economy is going to explode.
H100 is nearing five years and costs more to buy a used one now than a new one when it was released :) You are completely missing the bet these companies are making. They think can outlast their competitors and capture a larger portion of the pie while the cost of inference keeps going down dramatically. If you haven't been paying attention, the cost is about 1/100th of what it was in 2024. This is the trajectory pre…
Isn’t that the same bet that famously profitable companies like Uber did in the ride share market?
It's not the exact same bet, but it rhymes.
It worked out for Uber, they are wildly profitable now after spending a decade losing money.
Also worked out as Amazon managed to outlast all the dotcom era e-commerce competitors while being unprofitable.
Google does have a positional advantage in Android and Apple picking up Gemini as the baked-in AI assistant. It will be interesting to see what kind of impact that has in their services and profitability for AI.
I've given up on Gemini. It sounds smart but most of what it tells me ends up being wrong or misleading. I might actually hand $20/mo to OpenAI. It's been far more helpful with the random collection of legal and health problems I've thrown at it. My recent comment history is going to make me come across like a shill for them but, holy crap, GPT has been doing amazing things for me at work as well. I don't get it eith…
Are you using Gemini Flash or Gemini Pro? Are you about to compare the free tier of Gemini to the paid tier of OpenAI?
At work it's paid but in my own personal queries it's free vs free and gemini seems to give erroneous answers with confidence frequently and they will completely flip flop in subsequent queries of the same text. It seems very unstable.
I've given up on Gemini. It sounds smart but most of what it tells me ends up being wrong or misleading. I might actually hand $20/mo to OpenAI. It's been far more helpful with the random collection of legal and health problems I've thrown at it. My recent comment history is going to make me come across like a shill for them but, holy crap, GPT has been doing amazing things for me at work as well. I don't get it eith…
> It's been far more helpful with the random collection of legal and health problems I've thrown at it. As in convincing? Or accurate?
Some of both sadly, but where I've checked, accuracy.