Modern AI data centers consume enormous amounts of power, and it looks like they will get even more power-hungry in the coming years as companies like Google, Microsoft, Meta, and OpenAI strive towards artificial general intelligence (AGI). Oracle has already outlined plans to use nuclear power plants for its 1-gigawatt datacenters. It looks like Microsoft plans to do the same as it just inked a deal to restart a nuclear power plant to feed its data centers, reports Bloomberg.
Bruh you have no idea about the costs. Doubt you have even tried running AI models on your own hardware. There are literally some models that will run on a decent smartphone. Not every LLM is ChatGPT that’s enormous in size and resource consumption, and hidden behind a vail of closed source technology.
Also that trick isn’t going to work just looking at a comment. Lemmy compresses whitespace because it uses Markdown. It only shows the extra lines when replying.
Can I ask you something? What did Machine Learning do to you? Did a robot kill your wife?
Earlier this year, the International Energy Agency released its energy usage and forecast and has predicted that the total global electricity consumption of data centers is set to top 1 PWh (petawatt-hour) in 2026. This more than doubles its 2022 value and (as the report states) “is equivalent to the electricity consumption of Japan.” SOURCE
It does fuck all for me except make art and customer service worse on average, but yes it certainly will result in countless avoidable deaths if we don’t heavily curb its usage soon as it is projected to Quintuple its power draw by 2029.
I am not talking about things like ChatGPT that rely more on raw compute and scaling than some other approaches and are hosted at massive data centers. I actually find their approach wasteful as well. I am talking about some of the open weights models that use a fraction of the resources for similar quality of output. According to some industry experts that will be the way forward anyway as purely making models bigger has limits and is hella expensive.
Another thing to bear in mind is that training a model is more resource intensive than using it, though that’s also been worked on.
You put power in and you get worthless garbage out. Do the world a favor and just mine crypto, try FoldingCoin out.
