The Extreme Cost of Training AI Models.

Comments

• breadsmasher@lemmy.world ⁨1⁩ ⁨month⁩ ago

  The source didn’t have this detail - google training gemini “cloud” vs “own hardware”. Does Google Cloud not count as “own hardware” for google?

  source

  • bjorney@lemmy.ca ⁨1⁩ ⁨month⁩ ago

    Does Google Cloud not count as “own hardware” for google?

    That’s why the bars are so different. The “cloud” price is MSRP

    source
  • pandapoo@sh.itjust.works ⁨1⁩ ⁨month⁩ ago

    This is an accounting trick as well, a way to shed profit, and maximize deductions, by having different units within a parent company purchase services from each other.

    I realize that my two sentence explainer doesn’t shed any light on how it gets done, but ironically, you can ask an LLM for an explainer and I bet it’d give a mostly accurate response.

    source
  • General_Effort@lemmy.world ⁨1⁩ ⁨month⁩ ago

    From the source:

    Our primary approach calculates training costs based on hardware depreciation and energy consumption over the duration of model training. Hardware costs include AI accelerator chips (GPUs or TPUs), servers, and interconnection hardware. We use either disclosures from the developer or credible third-party reporting to identify or estimate the hardware type and quantity and training run duration for a given model. We also estimate the energy consumption of the hardware during the final training run of each model.

    As an alternative approach, we also calculate the cost to train these models in the cloud using rented hardware. This method is very simple to calculate because cloud providers charge a flat rate per chip-hour, and energy and interconnection costs are factored into the prices. However, it overestimates the cost of many frontier models, which are often trained on hardware owned by the developer rather than on rented cloud hardware.

    epochai.org/…/how-much-does-it-cost-to-train-fron…

    source
• mox@lemmy.sdf.org ⁨1⁩ ⁨month⁩ ago

  I don’t care how they estimate their cost in dollars. I think the cost to all of us in environmental impact would be more interesting.

  source

  • UnderpantsWeevil@lemmy.world ⁨1⁩ ⁨month⁩ ago

    Unless they’re finding exciting new and efficient ways to generate electricity, I imagine its a linear comparison. Maybe some are worse than others. I know Grok’s datacenter in Mississippi is relying exclusively on portable gas powered electric generators that are wrecking having on the local environment.

    source

    • downhomechunk@midwest.social ⁨1⁩ ⁨month⁩ ago

      Gas like natural gas? Or gas like gasoline? I’m sure it’s the former, but I take nothing for granted anymore.

      source

      • -> View More Comments
    • mox@lemmy.sdf.org ⁨1⁩ ⁨month⁩ ago

      I didn’t know that; thanks for sharing.

      (BTW, I think you meant wreaking havoc.)

      source

      • -> View More Comments
    • linearchaos@lemmy.world ⁨1⁩ ⁨month⁩ ago

      Maybe this is the push we need to switch to nuclear. The attack is good it just needs somebody with deeper pockets than coal/gas to lobby it.

      source

      • -> View More Comments
    • OsrsNeedsF2P@lemmy.ml ⁨1⁩ ⁨month⁩ ago

      Honestly you can thank decades of anti-nuclear lobbying

      source

      • -> View More Comments
  • Sauerkraut@discuss.tchncs.de ⁨1⁩ ⁨month⁩ ago

    I want to see what the long term economic cost was after they fired tens of thousands of tech workers hoping to replace us with AI. It feels like workers are always the ones who suffer the most under capitalism.

    source

    • interdimensionalmeme@lemmy.ml ⁨1⁩ ⁨month⁩ ago

      It depends if they fire them and AI can’t actually do the job, then it would suck.

      If they are fired and the ai can do it, then it’s great, it’s like having that many new people.

      source
    • linearchaos@lemmy.world ⁨1⁩ ⁨month⁩ ago

      They’ll fire more than that when the AI bubble busts and they stop pushing so hard into that development as it stagnates.

      source
  • interdimensionalmeme@lemmy.ml ⁨1⁩ ⁨month⁩ ago

    Assume it is equivalent to burning 200 million $ of gasoline

    source
• Ilovethebomb@lemm.ee ⁨1⁩ ⁨month⁩ ago

  Considering the hype and publicity GPT-4 produced, I don’t think this is actually a crazy amount of money to spend.

  source

  • oce@jlai.lu ⁨1⁩ ⁨month⁩ ago

    Yeah, I’m surprised at how low that is, a software engineer in a developed country is about 100k USD per year. So 40M USD for training ChatGPT 4 is the cost of 400 engineers for one year.
    They say cost of salaries could make up 50% of the total, so the total cost is 800 engineers for one year.
    That doesn’t seem extreme.

    source

    • my_hat_stinks@programming.dev ⁨1⁩ ⁨month⁩ ago

      100k USD per engineer assumes they’re exclusively hiring from US and Switzerland, that’s not a general “developed country” thing. US is an outlier.

      source

      • -> View More Comments
    • jacksilver@lemmy.world ⁨1⁩ ⁨month⁩ ago

      This is just the estimates to train the model, so it’s not accounting for the cost to develop the system for training, collecting the data, etc. This is just pure processing cost, which is staggeringly large numbers.

      source
  • Voroxpete@sh.itjust.works ⁨1⁩ ⁨month⁩ ago

    Comparitively speaking, a lot less hype than their earlier models produced. Hardcore techies care about incremental improvements, but the average user does not. If you try to describe to the average user what is “new” about GPT-4, other than “It fucks up less”, you’ve basically got nothing.

    And it’s going to carry on like this. New models are going to get exponentially more expensive to train, while producing less and less consumer interest each time, because “Holy crap look at this brand new technology” will always be more exciting than “In our comparitive testing version 7 is 9.6% more accurate than version 6.”

    And for all the hype, the actual revenue just isn’t there. OpenAI are bleeding around $5-10bn (yes, with a b) per year. They’re currently trying to raise around $11bn in new funding just to keep the lights on. It costs far more to operate these models (even at the steeply discounted compute costs Microsoft are giving them) than anyone is actually willing to pay to use them. Corporate clients don’t find them reliable or adaptable enough to actually replace human employees, and regular consumers think they’re cool, but in a “nice to have” kind of way. They’re not essential enough a product to pay big money for, but they can only be run profitably by charging big money.

    source
  • huginn@feddit.it ⁨1⁩ ⁨month⁩ ago

    The latest releases ChatGPT 4o costs $600/hr per instance to run based on the discussion I could find about it.

    If OpenAI is running 1k of those models to service the demand (they’re certainly running more since queries can take 30+ seconds) then that’s 200M/yr just keeping the lights on.

    source

    • Ilovethebomb@lemm.ee ⁨1⁩ ⁨month⁩ ago

      That’s a lot, but what’s their revenue?

      source

      • -> View More Comments
• linearchaos@lemmy.world ⁨1⁩ ⁨month⁩ ago

  How in the hell is Gemini both two and a half times more expensive and vastly inferior to GPT?

  source

  • ZILtoid1991@lemmy.world ⁨1⁩ ⁨month⁩ ago

    Some claim due to it was trained on too much data with too little intervention

    source

    • postmateDumbass@lemmy.world ⁨1⁩ ⁨month⁩ ago

      Maybe we donnot understand what its objective function actually wants?

      Maybe it is impeding its users intentionally.

      source
  • PixeIOrange@lemmy.world ⁨1⁩ ⁨month⁩ ago

    Google sucks

    source
• KillingTimeItself@lemmy.dbzer0.com ⁨1⁩ ⁨month⁩ ago

  bro who the fuck is google paying to do cloud compute for them? Google cloud??

  source

  • ripcord@lemmy.world ⁨1⁩ ⁨month⁩ ago

    I assume they’ve come up with some generic cost if someone was training each model using cloud compute.

    source

    • KillingTimeItself@lemmy.dbzer0.com ⁨1⁩ ⁨month⁩ ago

      god i love accounting, it’s so much fun.

      source

      • -> View More Comments
• Wispy2891@lemmy.world ⁨1⁩ ⁨month⁩ ago

  It’s obvious that Google didn’t pay the crazy AWS prices to train Gemini, seeing how many servers they have in gcp.

  They mean that they used creative accounting to pay themselves crazy gcp usage bills to deduct from taxes?

  source
• FinishingDutch@lemmy.world ⁨1⁩ ⁨month⁩ ago

  Geez, you’d think Gemini would be better than it is if they spent that much on it…

  source

  • kromem@lemmy.world ⁨1⁩ ⁨month⁩ ago

    Base model =/= Corpo fine tune

    source
• potentiallynotfelix@lemmy.fish ⁨1⁩ ⁨month⁩ ago

  and gemini is still hot ass

  source

  • pyre@lemmy.world ⁨1⁩ ⁨month⁩ ago

    because this entire model of AI as an idea is garbage to begin with

    source
  • Mwa@lemm.ee ⁨1⁩ ⁨month⁩ ago

    trueee

    source
• _sideffect@lemmy.world ⁨1⁩ ⁨month⁩ ago

  All a huge waste of money.

  This isn’t ai.

  It’s a “Smarter Search”

  source

  • pennomi@lemmy.world ⁨1⁩ ⁨month⁩ ago

    AI is a broader term than you might realize. Historically even mundane algorithms like A* pathfinding was considered AI.

    Turns out people like to constantly redefine artificial intelligence to “whatever a computer can’t quite do yet.”

    source

    • _sideffect@lemmy.world ⁨1⁩ ⁨month⁩ ago

      No.

      What I’m saying is what all these companies are presenting us is a smarter search.

      It’s just a tighter grouping of (biased) data that can be searched and retrieved a bit quicker.

      If they want to use the term ai, then hell, factory machines from the last century are ai too.

      source

      • -> View More Comments
  • SkaveRat@discuss.tchncs.de ⁨1⁩ ⁨month⁩ ago

    I hope you complained all these years when games used “AI” for computer controlled enemies, because otherwise your post would be super awkward

    source

    • _sideffect@lemmy.world ⁨1⁩ ⁨month⁩ ago

      Lmao, you have no idea what you’re saying.

      Keep sucking up to these useless ai companies though, they love it!

      source

      • -> View More Comments
  • ContrarianTrail@lemm.ee ⁨1⁩ ⁨month⁩ ago

    It is AI though. AGI, which is a subcategory of AI and what many people seemingly imagine AI to mean, it’s not—but AI, yes.

    source
  • bitjunkie@lemmy.world ⁨1⁩ ⁨month⁩ ago

    Something was needed, tradsearch has sucked dick at anything other than finding a wiki article for an extremely broad topic for over a decade. Just make electricity sustainably. 🤷‍♂️

    source

    • ZILtoid1991@lemmy.world ⁨1⁩ ⁨month⁩ ago

      Because it got enshittified, with SEO, ads, etc.

      source

      • -> View More Comments
• IndustryStandard@lemmy.world ⁨1⁩ ⁨month⁩ ago

  Only 50 million dollars for gpt4? Cheaper than expected

  source

  • interdimensionalmeme@lemmy.ml ⁨1⁩ ⁨month⁩ ago

    The AI industry could stop right there, we won the jackpot already. They just need to stop while they’re ahead ! It is very unlikely that we will have as much as 1/10 the leap we have already seen.

    source
• hark@lemmy.world ⁨1⁩ ⁨month⁩ ago

  Now imagine if they had to pay for the content they’re training the models off of.

  source
• AbouBenAdhem@lemmy.world ⁨1⁩ ⁨month⁩ ago

  How is Inflection-2 cheaper to train in the cloud than on own hardware?

  source

  • General_Effort@lemmy.world ⁨1⁩ ⁨month⁩ ago

    That probably indicates a problem with the estimates.

    source
• DogEatWaffle@startrek.website ⁨1⁩ ⁨month⁩ ago

  Humanity: develops nuclear fusion

  AI:

  source

  • IndustryStandard@lemmy.world ⁨1⁩ ⁨month⁩ ago

    It’s like the south park “Now we can finally play the game” but for AI. First we get infinite energy and then we can train an AI to calculate how we can create infinite energy.

    source
• DaddysLittleSlut@lemmy.world ⁨1⁩ ⁨month⁩ ago

  We must consider the benefits of AI as such and how they can contribute to our life. I can assure you prices of such while AI may seem like a game or useless thing for others. It’s actually a useful tool able to help others understand complex concepts that most people have a hard time explaining or won’t. Many more things too.

  source

  • interdimensionalmeme@lemmy.ml ⁨1⁩ ⁨month⁩ ago

    If we assume this is already as good as it’s going to get and we don’t throw another 7 trillion into that fire.

    For 100 million, a open source openweight release of gpt4 into the public domain will have been a good deal and releasing it into the public domain and preventing enclosure of our intellectual commons would make the enterprise as a whole a worthwhile endeavor.

    source
• Soup@lemmy.cafe ⁨1⁩ ⁨month⁩ ago

  All that shit needs to be just down and not revisited again.

  source

  • todd_bonzalez@lemm.ee ⁨1⁩ ⁨month⁩ ago

    I love this kind of delusional statement.

    “Researchers spent tens of billions of dollars, and put decades into research, and now that there is breakthrough progress in applied machine learning, but we should bury all knowledge of it and abandon the entire sector because of vibes.”

    Scepticism of AI businesses and hype is perfectly understandable, but you’re not putting this cat back in the bag…

    source

    • Soup@lemmy.cafe ⁨1⁩ ⁨month⁩ ago

      “It cost a lot, so it absolutely should be allowed!”

      Is an even dumber excuse to keep it going.

      source