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Generative AI Is an Engineering Disaster. A shockingly inefficient trillion-dollar project.
(www.theatlantic.com)
this post was submitted on 15 Jul 2026
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We are repeating an old pattern in computing: throw more hardware at the problem until efficiency becomes impossible to ignore. Bigger models have delivered remarkable gains, but they’re increasingly expensive. The next breakthroughs may come less from adding parameters and more from smarter architectures, better algorithms and more efficient inference.
Except there likely won't be a lot of further breakthroughs if we burn down our planet faster than we already do.
This is all an expenditure of vast amounts of energy for literally no gain for anybody except a handful of billionaires and their corporations.
DeepSeek has really led the way here, especially as they are a bit more hardware constrained. Plus they openly publish their findings and release open source models, so high hopes there.
It's probably China's play to pop the AI bubble, but I'm all for it (:
I wonder what all is in the deepseek code that is malicious. I'd like to try it but don't want a million Mb/s of tracker shit across my network and can't run it myself.
AFAIK, their open models are distributed as weights, not executables and are therefore not able to start network connections / run code. There if of course tool-calling functionality but that just works by having the model output a special pattern and having something external run predetermined commands based on that.
They are open source models, nothing malicious about them. I'd be much more careful about where you run your agents on. The wrong prompt can even make a non-malicious model misbehave.