An AI lab out of China has ignited panic throughout Silicon Valley after releasing AI models that can outperform America's best despite being built more cheaply and with less-powerful chips. DeepSeek unveiled a free, open-source large-language model in late December that it says took only two months and less than $6 million to build. CNBC's Deirdre Bosa interviews Perplexity CEO Aravind Srinivas and explains why the DeepSeek has raised alarms on whether America's global lead in AI is shrinking.
AI, as in machine learning, has always had uses. Like, real useful additions to human capability. It’s very useful in pattern recognition and statistical analysis of various things.
Our more modern shit connotation comes from capitalists trying replace labor with generative AI, which is a small subset of potential machine learning uses, but by its nature sends massive amounts of shlock at us.
Having dealt with ML engineers in depth before, American tech companies tend to throw blank checks their way which, combined with them not tending to have backgrounds in optimization or infrastructure, means they spin up 8 billion GPU instances in the cloud and use 10% of them ever because engineers are lazy.
They could, without any exaggeration, reduce their energy consumption by a factor of ten with about two weeks of honest engineering work. Yes this bothers the fuck out of me.
That’s my biggest gripe with mainstream closed source AI, they can optimize some of their most powerful MLAs to run on a potato but… they don’t. And they’ll never open source becaue it’d be forked by people who are genuinely passionate about improvement.
So AI could be more sustainable this whole time? Interesting…
Yeah a lot of the breakthrough research has happened via cheaper / resource limited methods now that the cat is out of the bag. We live in interesting times.
source: ML guy i know so this could be entirely unsubstantiated but apparently the main environmental burden of LLM infrastructure comes from training new models not serving inference from already deployed models.
That might change now that companies are creating “reasoning” models like DeepSeek R1. They aren’t really all that different architecturally but they produce longer outputs which just requires more compute.
So AI could be more sustainable this whole time? Interesting…
Who wants to bet their AI will be used for more useful things too?
AI, as in machine learning, has always had uses. Like, real useful additions to human capability. It’s very useful in pattern recognition and statistical analysis of various things.
Our more modern shit connotation comes from capitalists trying replace labor with generative AI, which is a small subset of potential machine learning uses, but by its nature sends massive amounts of shlock at us.
ML has made our xsh translations coherent.
Having dealt with ML engineers in depth before, American tech companies tend to throw blank checks their way which, combined with them not tending to have backgrounds in optimization or infrastructure, means they spin up 8 billion GPU instances in the cloud and use 10% of them ever because engineers are lazy.
They could, without any exaggeration, reduce their energy consumption by a factor of ten with about two weeks of honest engineering work. Yes this bothers the fuck out of me.
That’s my biggest gripe with mainstream closed source AI, they can optimize some of their most powerful MLAs to run on a potato but… they don’t. And they’ll never open source becaue it’d be forked by people who are genuinely passionate about improvement.
AKA they’d be run outta business in no time.
Is it actually “sustainable” though? I’d like to see some wattage numbers.
I said this in the other thread but I’ll say it again: our sophisticated artificial intelligence, their planet burning chatbot.
Unlike in the West where if Nvidia tanks then the entire US economy goes down with it.
Idk about sustainability. It still requires massive computing infrastructure, which for now requires unsustainable ways of sourcing metals
What unsustainable ways of sourcing metals are you thinking about here?
rare earth mining
I think, unfortunately, REE mining is pretty far down the list of environmentally polluting extractive industries.
Not even using kids in the Congo to mine them.
Yeah a lot of the breakthrough research has happened via cheaper / resource limited methods now that the cat is out of the bag. We live in interesting times.
It’s not that unsustainable unless you believe the predicts that your microwave will be building it’s own LLM model every month by 2030
The electricity and water usage isn’t very high in general or compared to data centre usage more broadly (and is basically nothing compared to crypto)
source: ML guy i know so this could be entirely unsubstantiated but apparently the main environmental burden of LLM infrastructure comes from training new models not serving inference from already deployed models.
That might change now that companies are creating “reasoning” models like DeepSeek R1. They aren’t really all that different architecturally but they produce longer outputs which just requires more compute.